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Rhonda Crate, Boeing | WiDS 2023


 

(gentle music) >> Hey! Welcome back to theCUBE's coverage of WiDS 2023, the eighth Annual Women In Data Science Conference. I'm your host, Lisa Martin. We are at Stanford University, as you know we are every year, having some wonderful conversations with some very inspiring women and men in data science and technical roles. I'm very pleased to introduce Tracy Zhang, my co-host, who is in the Data Journalism program at Stanford. And Tracy and I are pleased to welcome our next guest, Rhonda Crate, Principal Data Scientist at Boeing. Great to have you on the program, Rhonda. >> Tracy: Welcome. >> Hey, thanks for having me. >> Were you always interested in data science or STEM from the time you were young? >> No, actually. I was always interested in archeology and anthropology. >> That's right, we were talking about that, anthropology. Interesting. >> We saw the anthropology background, not even a bachelor's degree, but also a master's degree in anthropology. >> So you were committed for a while. >> I was, I was. I actually started college as a fine arts major, but I always wanted to be an archeologist. So at the last minute, 11 credits in, left to switch to anthropology. And then when I did my master's, I focused a little bit more on quantitative research methods and then I got my Stat Degree. >> Interesting. Talk about some of the data science projects that you're working on. When I think of Boeing, I always think of aircraft. But you are doing a lot of really cool things in IT, data analytics. Talk about some of those intriguing data science projects that you're working on. >> Yeah. So when I first started at Boeing, I worked in information technology and data analytics. And Boeing, at the time, had cored up data science in there. And so we worked as a function across the enterprise working on anything from shared services to user experience in IT products, to airplane programs. So, it has a wide range. I worked on environment health and safety projects for a long time as well. So looking at ergonomics and how people actually put parts onto airplanes, along with things like scheduling and production line, part failures, software testing. Yeah, there's a wide spectrum of things. >> But I think that's so fantastic. We've been talking, Tracy, today about just what we often see at WiDS, which is this breadth of diversity in people's background. You talked about anthropology, archeology, you're doing data science. But also all of the different opportunities that you've had at Boeing. To see so many facets of that organization. I always think that breadth of thought diversity can be hugely impactful. >> Yeah. So I will say my anthropology degree has actually worked to my benefit. I'm a huge proponent of integrating liberal arts and sciences together. And it actually helps me. I'm in the Technical Fellowship program at Boeing, so we have different career paths. So you can go into management, you can be a regular employee, or you can go into the Fellowship program. So right now I'm an Associate Technical Fellow. And part of how I got into the Fellowship program was that diversity in my background, what made me different, what made me stand out on projects. Even applying a human aspect to things like ergonomics, as silly as that sounds, but how does a person actually interact in the space along with, here are the actual measurements coming off of whatever system it is that you're working on. So, I think there's a lot of opportunities, especially in safety as well, which is a big initiative for Boeing right now, as you can imagine. >> Tracy: Yeah, definitely. >> I can't go into too specifics. >> No, 'cause we were like, I think a theme for today that kind of we brought up in in all of our talk is how data is about people, how data is about how people understand the world and how these data can make impact on people's lives. So yeah, I think it's great that you brought this up, and I'm very happy that your anthropology background can tap into that and help in your day-to-day data work too. >> Yeah. And currently, right now, I actually switched over to Strategic Workforce Planning. So it's more how we understand our workforce, how we work towards retaining the talent, how do we get the right talent in our space, and making sure overall that we offer a culture and work environment that is great for our employees to come to. >> That culture is so important. You know, I was looking at some anitab.org stats from 2022 and you know, we always talk about the number of women in technical roles. For a long time it's been hovering around that 25% range. The data from anitab.org showed from '22, it's now 27.6%. So, a little increase. But one of the biggest challenges still, and Tracy and I and our other co-host, Hannah, have been talking about this, is attrition. Attrition more than doubled last year. What are some of the things that Boeing is doing on the retention side, because that is so important especially as, you know, there's this pipeline leakage of women leaving technical roles. Tell us about what Boeing's, how they're invested. >> Yeah, sure. We actually have a publicly available Global Diversity Report that anybody can go and look at and see our statistics for our organization. Right now, off the top of my head, I think we're hovering at about 24% in the US for women in our company. It has been a male majority company for many years. We've invested heavily in increasing the number of women in roles. One interesting thing about this year that came out is that even though with the great resignation and those types of things, the attrition level between men and women were actually pretty close to being equal, which is like the first time in our history. Usually it tends on more women leaving. >> Lisa: That's a good sign. >> Right. >> Yes, that's a good sign. >> And we've actually focused on hiring and bringing in more women and diversity in our company. >> Yeah, some of the stats too from anitab.org talked about the increase, and I have to scroll back and find my notes, the increase in 51% more women being hired in 2022 than 2021 for technical roles. So the data, pun intended, is showing us. I mean, the data is there to show the impact that having females in executive leadership positions make from a revenue perspective. >> Tracy: Definitely. >> Companies are more profitable when there's women at the head, or at least in senior leadership roles. But we're seeing some positive trends, especially in terms of representation of women technologists. One of the things though that I found interesting, and I'm curious to get your thoughts on this, Rhonda, is that the representation of women technologists is growing in all areas, except interns. >> Rhonda: Hmm. >> So I think, we've got to go downstream. You teach, I have to go back to my notes on you, did my due diligence, R programming classes through Boeings Ed Wells program, this is for WSU College of Arts and Sciences, talk about what you teach and how do you think that intern kind of glut could be solved? >> Yeah. So, they're actually two separate programs. So I teach a data analytics course at Washington State University as an Adjunct Professor. And then the Ed Wells program is a SPEEA, which is an Aerospace Union, focused on bringing up more technology and skills to the actual workforce itself. So it's kind of a couple different audiences. One is more seasoned employees, right? The other one is our undergraduates. I teach a Capstone class, so it's a great way to introduce students to what it's actually like to work on an industry project. We partner with Google and Microsoft and Boeing on those. The idea is also that maybe those companies have openings for the students when they're done. Since it's Senior Capstone, there's not a lot of opportunities for internships. But the opportunities to actually get hired increase a little bit. In regards to Boeing, we've actually invested a lot in hiring more women interns. I think the number was 40%, but you'd have to double check. >> Lisa: That's great, that's fantastic. >> Tracy: That's way above average, I think. >> That's a good point. Yeah, it is above average. >> Double check on that. That's all from my memory. >> Is this your first WiDS, or have you been before? >> I did virtually last year. >> Okay. One of the things that I love, I love covering this event every year. theCUBE's been covering it since it's inception in 2015. But it's just the inspiration, the vibe here at Stanford is so positive. WiDS is a movement. It's not an initiative, an organization. There are going to be, I think annually this year, there will be 200 different events. Obviously today we're live on International Women's Day. 60 plus countries, 100,000 plus people involved. So, this is such a positive environment for women and men, because we need everybody, underrepresented minorities, to be able to understand the implication that data has across our lives. If we think about stripping away titles in industries, everybody is a consumer, not everybody, most of mobile devices. And we have this expectation, I was in Barcelona last week at a Mobile World Congress, we have this expectation that we're going to be connected 24/7. I can get whatever I want wherever I am in the world, and that's all data driven. And the average person that isn't involved in data science wouldn't understand that. At the same time, they have expectations that depend on organizations like Boeing being data driven so that they can get that experience that they expect in their consumer lives in any aspect of their lives. And that's one of the things I find so interesting and inspiring about data science. What are some of the things that keep you motivated to continue pursuing this? >> Yeah I will say along those lines, I think it's great to invest in K-12 programs for Data Literacy. I know one of my mentors and directors of the Data Analytics program, Dr. Nairanjana Dasgupta, we're really familiar with each other. So, she runs a WSU program for K-12 Data Literacy. It's also something that we strive for at Boeing, and we have an internal Data Literacy program because, believe it or not, most people are in business. And there's a lot of disconnect between interpreting and understanding data. For me, what kind of drives me to continue data science is that connection between people and data and how we use it to improve our world, which is partly why I work at Boeing too 'cause I feel that they produce products that people need like satellites and airplanes, >> Absolutely. >> and everything. >> Well, it's tangible, it's relatable. We can understand it. Can you do me a quick favor and define data literacy for anyone that might not understand what that means? >> Yeah, so it's just being able to understand elements of data, whether that's a bar chart or even in a sentence, like how to read a statistic and interpret a statistic in a sentence, for example. >> Very cool. >> Yeah. And sounds like Boeing's doing a great job in these programs, and also trying to hire more women. So yeah, I wanted to ask, do you think there's something that Boeing needs to work on? Or where do you see yourself working on say the next five years? >> Yeah, I think as a company, we always think that there's always room for improvement. >> It never, never stops. >> Tracy: Definitely. (laughs) >> I know workforce strategy is an area that they're currently really heavily investing in, along with safety. How do we build safer products for people? How do we help inform the public about things like Covid transmission in airports? For example, we had the Confident Traveler Initiative which was a big push that we had, and we had to be able to inform people about data models around Covid, right? So yeah, I would say our future is more about an investment in our people and in our culture from my perspective >> That's so important. One of the hardest things to change especially for a legacy organization like Boeing, is culture. You know, when I talk with CEO's or CIO's or COO's about what's your company's vision, what's your strategy? Especially those companies that are on that digital journey that have no choice these days. Everybody expects to have a digital experience, whether you're transacting an an Uber ride, you're buying groceries, or you're traveling by air. That culture sounds like Boeing is really focused on that. And that's impressive because that's one of the hardest things to morph and mold, but it's so essential. You know, as we look around the room here at WiDS it's obviously mostly females, but we're talking about women, underrepresented minorities. We're talking about men as well who are mentors and sponsors to us. I'd love to get your advice to your younger self. What would you tell yourself in terms of where you are now to become a leader in the technology field? >> Yeah, I mean, it's kind of an interesting question because I always try to think, live with no regrets to an extent. >> Lisa: I like that. >> But, there's lots of failures along the way. (Tracy laughing) I don't know if I would tell myself anything different because honestly, if I did, I wouldn't be where I am. >> Lisa: Good for you. >> I started out in fine arts, and I didn't end up there. >> That's good. >> Such a good point, yeah. >> We've been talking about that and I find that a lot at events like WiDS, is women have these zigzaggy patterns. I studied biology, I have a master's in molecular biology, I'm in media and marketing. We talked about transportable skills. There's a case I made many years ago when I got into tech about, well in science you learn the art of interpreting esoteric data and creating a story from it. And that's a transportable skill. But I always say, you mentioned failure, I always say failure is not a bad F word. It allows us to kind of zig and zag and learn along the way. And I think that really fosters thought diversity. And in data science, that is one of the things we absolutely need to have is that diversity and thought. You know, we talk about AI models being biased, we need the data and we need the diverse brains to help ensure that the biases are identified, extracted, and removed. Speaking of AI, I've been geeking out with ChatGPT. So, I'm on it yesterday and I ask it, "What's hot in data science?" And I was like, is it going to get that? What's hot? And it did it, it came back with trends. I think if I ask anything, "What's hot?", I should be to Paris Hilton, but I didn't. And so I was geeking out. One of the things I learned recently that I thought was so super cool is the CTO of OpenAI is a woman, Mira Murati, which I didn't know until over the weekend. Because I always think if I had to name top females in tech, who would they be? And I always default to Sheryl Sandberg, Carly Fiorina, Susan Wojcicki running YouTube. Who are some of the people in your history, in your current, that are really inspiring to you? Men, women, indifferent. >> Sure. I think Boeing is one of the companies where you actually do see a lot of women in leadership roles. I think we're one of the top companies with a number of women executives, actually. Susan Doniz, who's our Chief Information Officer, I believe she's actually slotted to speak at a WiDS event come fall. >> Lisa: Cool. >> So that will be exciting. Susan's actually relatively newer to Boeing in some ways. A Boeing time skill is like three years is still kind of new. (laughs) But she's been around for a while and she's done a lot of inspiring things, I think, for women in the organization. She does a lot with Latino communities and things like that as well. For me personally, you know, when I started at Boeing Ahmad Yaghoobi was one of my mentors and my Technical Lead. He came from Iran during a lot of hard times in the 1980s. His brother actually wrote a memoir, (laughs) which is just a fun, interesting fact. >> Tracy: Oh my God! >> Lisa: Wow! >> And so, I kind of gravitate to people that I can learn from that's not in my sphere, that might make me uncomfortable. >> And you probably don't even think about how many people you're influencing along the way. >> No. >> We just keep going and learning from our mentors and probably lose sight of, "I wonder how many people actually admire me?" And I'm sure there are many that admire you, Rhonda, for what you've done, going from anthropology to archeology. You mentioned before we went live you were really interested in photography. Keep going and really gathering all that breadth 'cause it's only making you more inspiring to people like us. >> Exactly. >> We thank you so much for joining us on the program and sharing a little bit about you and what brought you to WiDS. Thank you so much, Rhonda. >> Yeah, thank you. >> Tracy: Thank you so much for being here. >> Lisa: Yeah. >> Alright. >> For our guests, and for Tracy Zhang, this is Lisa Martin live at Stanford University covering the eighth Annual Women In Data Science Conference. Stick around. Next guest will be here in just a second. (gentle music)

Published Date : Mar 8 2023

SUMMARY :

Great to have you on the program, Rhonda. I was always interested in That's right, we were talking We saw the anthropology background, So at the last minute, 11 credits in, Talk about some of the And Boeing, at the time, had But also all of the I'm in the Technical that you brought this up, and making sure overall that we offer about the number of women at about 24% in the US more women and diversity in our company. I mean, the data is is that the representation and how do you think for the students when they're done. Lisa: That's great, Tracy: That's That's a good point. That's all from my memory. One of the things that I love, I think it's great to for anyone that might not being able to understand that Boeing needs to work on? we always think that there's Tracy: Definitely. the public about things One of the hardest things to change I always try to think, live along the way. I started out in fine arts, And I always default to Sheryl I believe she's actually slotted to speak So that will be exciting. to people that I can learn And you probably don't even think about from anthropology to archeology. and what brought you to WiDS. Tracy: Thank you so covering the eighth Annual Women

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Wayne Duso, AWS & Iyad Tarazi, Federated Wireless | MWC Barcelona 2023


 

(light music) >> Announcer: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to the Fira in Barcelona. Dave Vellante with Dave Nicholson. Lisa Martin's been here all week. John Furrier is in our Palo Alto studio, banging out all the news. Don't forget to check out siliconangle.com, thecube.net. This is day four, our last segment, winding down. MWC23, super excited to be here. Wayne Duso, friend of theCUBE, VP of engineering from products at AWS is here with Iyad Tarazi, who's the CEO of Federated Wireless. Gents, welcome. >> Good to be here. >> Nice to see you. >> I'm so stoked, Wayne, that we connected before the show. We texted, I'm like, "You're going to be there. I'm going to be there. You got to come on theCUBE." So thank you so much for making time, and thank you for bringing a customer partner, Federated Wireless. Everybody knows AWS. Iyad, tell us about Federated Wireless. >> We're a software and services company out of Arlington, Virginia, right outside of Washington, DC, and we're really focused on this new technology called Shared Spectrum and private wireless for 5G. Think of it as enterprises consuming 5G, the way they used to consume WiFi. >> Is that unrestricted spectrum, or? >> It is managed, organized, interference free, all through cloud platforms. That's how we got to know AWS. We went and got maybe about 300 products from AWS to make it work. Quite sophisticated, highly available, and pristine spectrum worth billions of dollars, but available for people like you and I, that want to build enterprises, that want to make things work. Also carriers, cable companies everybody else that needs it. It's really a new revolution for everyone. >> And that's how you, it got introduced to AWS. Was that through public sector, or just the coincidence that you're in DC >> No, I, well, yes. The center of gravity in the world for spectrum is literally Arlington. You have the DOD spectrum people, you have spectrum people from National Science Foundation, DARPA, and then you have commercial sector, and you have the FCC just an Uber ride away. So we went and found the scientists that are doing all this work, four or five of them, Virginia Tech has an office there too, for spectrum research for the Navy. Come together, let's have a party and make a new model. >> So I asked this, I'm super excited to have you on theCUBE. I sat through the keynotes on Monday. I saw Satya Nadella was in there, Thomas Kurian there was no AWS. I'm like, where's AWS? AWS is everywhere. I mean, you guys are all over the show. I'm like, "Hey, where's the number one cloud?" So you guys have made a bunch of announcements at the show. Everybody's talking about the cloud. What's going on for you guys? >> So we are everywhere, and you know, we've been coming to this show for years. But this is really a year that we can demonstrate that what we've been doing for the IT enterprise, IT people for 17 years, we're now bringing for telcos, you know? For years, we've been, 17 years to be exact, we've been bringing the cloud value proposition, whether it's, you know, cost efficiencies or innovation or scale, reliability, security and so on, to these enterprise IT folks. Now we're doing the same thing for telcos. And so whether they want to build in region, in a local zone, metro area, on-prem with an outpost, at the edge with Snow Family, or with our IoT devices. And no matter where they want to start, if they start in the cloud and they want to move to the edge, or they start in the edge and they want to bring the cloud value proposition, like, we're demonstrating all of that is happening this week. And, and very much so, we're also demonstrating that we're bringing the same type of ecosystem that we've built for enterprise IT. We're bringing that type of ecosystem to the telco companies, with CSPs, with the ISP vendors. We've seen plenty of announcements this week. You know, so on and so forth. >> So what's different, is it, the names are different? Is it really that simple, that you're just basically taking the cloud model into telco, and saying, "Hey, why do all this undifferentiated heavy lifting when we can do it for you? Don't worry about all the plumbing." Is it really that simple? I mean, that straightforward. >> Well, simple is probably not what I'd say, but we can make it straightforward. >> Conceptually. >> Conceptually, yes. Conceptually it is the same. Because if you think about, firstly, we'll just take 5G for a moment, right? The 5G folks, if you look at the architecture for 5G, it was designed to run on a cloud architecture. It was designed to be a set of services that you could partition, and run in different places, whether it's in the region or at the edge. So in many ways it is sort of that simple. And let me give you an example. Two things, the first one is we announced integrated private wireless on AWS, which allows enterprise customers to come to a portal and look at the industry solutions. They're not worried about their network, they're worried about solving a problem, right? And they can come to that portal, they can find a solution, they can find a service provider that will help them with that solution. And what they end up with is a fully validated offering that AWS telco SAS have actually put to its paces to make sure this is a real thing. And whether they get it from a telco, and, and quite frankly in that space, it's SIs such as Federated that actually help our customers deploy those in private environments. So that's an example. And then added to that, we had a second announcement, which was AWS telco network builder, which allows telcos to plan, deploy, and operate at scale telco network capabilities on the cloud, think about it this way- >> As a managed service? >> As a managed service. So think about it this way. And the same way that enterprise IT has been deploying, you know, infrastructure as code for years. Telco network builder allows the telco folks to deploy telco networks and their capabilities as code. So it's not simple, but it is pretty straightforward. We're making it more straightforward as we go. >> Jump in Dave, by the way. He can geek out if you want. >> Yeah, no, no, no, that's good, that's good, that's good. But actually, I'm going to ask an AWS question, but I'm going to ask Iyad the AWS question. So when we, when I hear the word cloud from Wayne, cloud, AWS, typically in people's minds that denotes off-premises. Out there, AWS data center. In the telecom space, yes, of course, in the private 5G space, we're talking about a little bit of a different dynamic than in the public 5G space, in terms of the physical infrastructure. But regardless at the edge, there are things that need to be physically at the edge. Do you feel that AWS is sufficiently, have they removed the H word, hybrid, from the list of bad words you're not allowed to say? 'Cause there was a point in time- >> Yeah, of course. >> Where AWS felt that their growth- >> They'll even say multicloud today, (indistinct). >> No, no, no, no, no. But there was a period of time where, rightfully so, AWS felt that the growth trajectory would be supported solely by net new things off premises. Now though, in this space, it seems like that hybrid model is critical. Do you see AWS being open to the hybrid nature of things? >> Yeah, they're, absolutely. I mean, just to explain from- we're a services company and a solutions company. So we put together solutions at the edge, a smart campus, smart agriculture, a deployment. One of our biggest deployment is a million square feet warehouse automation project with the Marine Corps. >> That's bigger than the Fira. >> Oh yeah, it's bigger, definitely bigger than, you know, a small section of here. It's actually three massive warehouses. So yes, that is the edge. What the cloud is about is that massive amount of efficiency has happened by concentrating applications in data centers. And that is programmability, that is APIs that is solutions, that is applications that can run on it, where people know how to do it. And so all that efficiency now is being ported in a box called the edge. What AWS is doing for us is bringing all the business and technical solutions they had into the edge. Some of the data may send back and forth, but that's actually a smaller piece of the value for us. By being able to bring an AWS package at the edge, we're bringing IoT applications, we're bringing high speed cameras, we're able to integrate with the 5G public network. We're able to bring in identity and devices, we're able to bring in solutions for students, embedded laptops. All of these things that you can do much much faster and cheaper if you are able to tap in the 4,000, 5,000 partners and all the applications and all the development and all the models that AWS team did. By being able to bring that efficiency to the edge why reinvent that? And then along with that, there are partners that you, that help do integration. There are development done to make it hardened, to make the data more secure, more isolated. All of these things will contribute to an edge that truly is a carbon copy of the data center. >> So Wayne, it's AWS, Regardless of where the compute, networking and storage physically live, it's AWS. Do you think that the term cloud will sort of drift away from usage? Because if, look, it's all IT, in this case it's AWS and federated IT working together. How, what's your, it's sort of a obscure question about cloud, because cloud is so integrated. >> You Got this thing about cloud, it's just IT. >> I got thing about cloud too, because- >> You and Larry Ellison. >> Because it's no, no, no, I'm, yeah, well actually there's- >> There's a lot of IT that's not cloud, just say that okay. >> Now, a lot of IT that isn't cloud, but I would say- >> But I'll (indistinct) cloud is an IT tool, and you see AWS obviously with the Snow fill in the blank line of products and outpost type stuff. Fair to say that you're, doesn't matter where it is, it could be AWS if it's on the edge, right? >> Well, you know, everybody wants to define the cloud as what it may have been when it started. But if you look at what it was when it started and what it is today, it is different. But the ability to bring the experience, the AWS experience, the services, the operational experience and all the things that Iyad had been talking about from the region all to all the way to, you know, the IoT device, if you would, that entire continuum. And it doesn't matter where you start. Like if you start in region and you need to bring your value to other places because your customers are asking you to do so, we're enabling that experience where you need to bring it. If you started at the edge, and- but you want to build cloud value, you know, whether it's again, cost efficiency, scalability, AI, ML or analytics into those capabilities, you can start at the edge with the same APIs, with the same service, the same capabilities, and you can build that value in right from the get go. You don't build this bifurcation or many separations and try to figure out how do I glue them together? There is no gluing together. So if you think of cloud as being elastic, scalable flexible, where you can drive innovation, it's the same exact model on the continuum. And you can start at either end, it's up to you as a customer. >> And I think if, the key to me is the ecosystem. I mean, if you can do for this industry what you've done for the technology- enterprise technology business from an ecosystem standpoint, you know everybody talks about flywheel, but that gives you like the massive flywheel. I don't know what the ratio is, but it used to be for every dollar spent on a VMware license, $15 is spent in the ecosystem. I've never heard similar ratios in the AWS ecosystem, but it's, I go to reinvent and I'm like, there's some dollars being- >> That's a massive ecosystem. >> (indistinct). >> And then, and another thing I'll add is Jose Maria Alvarez, who's the chairman of Telefonica, said there's three pillars of the future-ready telco, low latency, programmable networks, and he said cloud and edge. So they recognizing cloud and edge, you know, low latency means you got to put the compute and the data, the programmable infrastructure was invented by Amazon. So what's the strategy around the telco edge? >> So, you know, at the end, so those are all great points. And in fact, the programmability of the network was a big theme in the show. It was a huge theme. And if you think about the cloud, what is the cloud? It's a set of APIs against a set of resources that you use in whatever way is appropriate for what you're trying to accomplish. The network, the telco network becomes a resource. And it could be described as a resource. We, I talked about, you know, network as in code, right? It's same infrastructure in code, it's telco infrastructure as code. And that code, that infrastructure, is programmable. So this is really, really important. And in how you build the ecosystem around that is no different than how we built the ecosystem around traditional IT abstractions. In fact, we feel that really the ecosystem is the killer app for 5G. You know, the killer app for 4G, data of sorts, right? We started using data beyond simple SMS messages. So what's the killer app for 5G? It's building this ecosystem, which includes the CSPs, the ISVs, all of the partners that we bring to the table that can drive greater value. It's not just about cost efficiency. You know, you can't save your way to success, right? At some point you need to generate greater value for your customers, which gives you better business outcomes, 'cause you can monetize them, right? The ecosystem is going to allow everybody to monetize 5G. >> 5G is like the dot connector of all that. And then developers come in on top and create new capabilities >> And how different is that than, you know, the original smartphones? >> Yeah, you're right. So what do you guys think of ChatGPT? (indistinct) to Amazon? Amazon turned the data center into an API. It's like we're visioning this world, and I want to ask that technologist, like, where it's turning resources into human language interfaces. You know, when you see that, you play with ChatGPT at all, or I know you guys got your own. >> So I won't speak directly to ChatGPT. >> No, don't speak from- >> But if you think about- >> Generative AI. >> Yeah generative AI is important. And, and we are, and we have been for years, in this space. Now you've been talking to AWS for a long time, and we often don't talk about things we don't have yet. We don't talk about things that we haven't brought to market yet. And so, you know, you'll often hear us talk about something, you know, a year from now where others may have been talking about it three years earlier, right? We will be talking about this space when we feel it's appropriate for our customers and our partners. >> You have talked about it a little bit, Adam Selipsky went on an interview with myself and John Furrier in October said you watch, you know, large language models are going to be enormous and I know you guys have some stuff that you're working on there. >> It's, I'll say it's exciting. >> Yeah, I mean- >> Well proof point is, Siri is an idiot compared to Alexa. (group laughs) So I trust one entity to come up with something smart. >> I have conversations with Alexa and Siri, and I won't judge either one. >> You don't need, you could be objective on that one. I definitely have a preference. >> Are the problems you guys solving in this space, you know, what's unique about 'em? What are they, can we, sort of, take some examples here (indistinct). >> Sure, the main theme is that the enterprise is taking control. They want to have their own networks. They want to focus on specific applications, and they want to build them with a skeleton crew. The one IT person in a warehouse want to be able to do it all. So what's unique about them is that they're now are a lot of automation on robotics, especially in warehousing environment agriculture. There simply aren't enough people in these industries, and that required precision. And so you need all that integration to make it work. People also want to build these networks as they want to control it. They want to figure out how do we actually pick this team and migrate it. Maybe just do the front of the house first. Maybe it's a security team that monitor the building, maybe later on upgrade things that use to open doors and close doors and collect maintenance data. So that ability to pick what you want to do from a new processors is really important. And then you're also seeing a lot of public-private network interconnection. That's probably the undercurrent of this show that haven't been talked about. When people say private networks, they're also talking about something called neutral host, which means I'm going to build my own network, but I want it to work, my Verizon (indistinct) need to work. There's been so much progress, it's not done yet. So much progress about this bring my own network concept, and then make sure that I'm now interoperating with the public network, but it's my domain. I can create air gaps, I can create whatever security and policy around it. That is probably the power of 5G. Now take all of these tiny networks, big networks, put them all in one ecosystem. Call it the Amazon marketplace, call it the Amazon ecosystem, that's 5G. It's going to be tremendous future. >> What does the future look like? We're going to, we just determined we're going to be orchestrating the network through human language, okay? (group laughs) But seriously, what's your vision for the future here? You know, both connectivity and cloud are on on a continuum. It's, they've been on a continuum forever. They're going to continue to be on a continuum. That being said, those continuums are coming together, right? They're coming together to bring greater value to a greater set of customers, and frankly all of us. So, you know, the future is now like, you know, this conference is the future, and if you look at what's going on, it's about the acceleration of the future, right? What we announced this week is really the acceleration of listening to customers for the last handful of years. And, we're going to continue to do that. We're going to continue to bring greater value in the form of solutions. And that's what I want to pick up on from the prior question. It's not about the network, it's not about the cloud, it's about the solutions that we can provide the customers where they are, right? And if they're on their mobile phone or they're in their factory floor, you know, they're looking to accelerate their business. They're looking to accelerate their value. They're looking to create greater safety for their employees. That's what we can do with these technologies. So in fact, when we came out with, you know, our announcement for integrated private wireless, right? It really was about industry solutions. It really isn't about, you know, the cloud or the network. It's about how you can leverage those technologies, that continuum, to deliver you value. >> You know, it's interesting you say that, 'cause again, when we were interviewing Adam Selipsky, everybody, you know, all journalists analysts want to know, how's Adam Selipsky going to be different from Andy Jassy, what's the, what's he going to do to Amazon to change? And he said, listen, the real answer is Amazon has changed. If Andy Jassy were here, we'd be doing all, you know, pretty much the same things. Your point about 17 years ago, the cloud was S3, right, and EC2. Now it's got to evolve to be solutions. 'Cause if that's all you're selling, is the bespoke services, then you know, the future is not as bright as the past has been. And so I think it's key to look for what are those outcomes or solutions that customers require and how you're going to meet 'em. And there's a lot of challenges. >> You continue to build value on the value that you've brought, and you don't lose sight of why that value is important. You carry that value proposition up the stack, but the- what you're delivering, as you said, becomes maybe a bigger or or different. >> And you are getting more solution oriented. I mean, you're not hardcore solutions yet, but we're seeing more and more of that. And that seems to be a trend. We've even seen in the database world, making things easier, connecting things. Not really an abstraction layer, which is sort of antithetical to your philosophy, but it creates a similar outcome in terms of simplicity. Yeah, you're smiling 'cause you guys always have a different angle, you know? >> Yeah, we've had this conversation. >> It's right, it's, Jassy used to say it's okay to be misunderstood. >> That's Right. For a long time. >> Yeah, right, guys, thanks so much for coming to theCUBE. I'm so glad we could make this happen. >> It's always good. Thank you. >> Thank you so much. >> All right, Dave Nicholson, for Lisa Martin, Dave Vellante, John Furrier in the Palo Alto studio. We're here at the Fira, wrapping out MWC23. Keep it right there, thanks for watching. (upbeat music)

Published Date : Mar 2 2023

SUMMARY :

that drive human progress. banging out all the news. and thank you for bringing the way they used to consume WiFi. but available for people like you and I, or just the coincidence that you're in DC and you have the FCC excited to have you on theCUBE. and you know, we've been the cloud model into telco, and saying, but we can make it straightforward. that you could partition, And the same way that enterprise Jump in Dave, by the way. that need to be physically at the edge. They'll even say multicloud AWS felt that the growth trajectory I mean, just to explain from- and all the models that AWS team did. the compute, networking You Got this thing about cloud, not cloud, just say that okay. on the edge, right? But the ability to bring the experience, but that gives you like of the future-ready telco, And in fact, the programmability 5G is like the dot So what do you guys think of ChatGPT? to ChatGPT. And so, you know, you'll often and I know you guys have some stuff it's exciting. Siri is an idiot compared to Alexa. and I won't judge either one. You don't need, you could Are the problems you that the enterprise is taking control. that continuum, to deliver you value. is the bespoke services, then you know, and you don't lose sight of And that seems to be a trend. it's okay to be misunderstood. For a long time. so much for coming to theCUBE. It's always good. in the Palo Alto studio.

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Warren Jackson, Dell Technologies & Scott Waller, CTO, 5G Open Innovation Lab | MWC Barcelona 2023


 

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with David Nicholson, day four of MWC '23. Show's winding down a little bit, but it's still pretty packed here. Lot of innovation, planes, trains, automobiles, and we're talking 5G all week, private networks, connected breweries. It's super exciting. Really happy to have Warren Jackson here as the Edge Gateway Product Technologist at Dell Technologies, and Scott Waller, the CTO of the 5G Open Innovation Lab. Folks, welcome to theCUBE. >> Good to be here. >> Really interesting stories that we're going to talk about. Let's start, Scott, with you, what is the Open Innovation Lab? >> So it was hatched three years ago. Ideated about a bunch of guys from Microsoft who ran startup ventures program, started the developers program over at Microsoft, if you're familiar with MSDN. And they came three years ago and said, how does CSPs working with someone like T-Mobile who's in our backyard, I'm from Seattle. How do they monetize the edge? You need a developer ecosystem of applications and use cases. That's always been the thing. The carriers are building the networks, but where's the ecosystem of startups? So we built a startup ecosystem that is sponsored by partners, Dell being one sponsor, Intel, Microsoft, VMware, Aspirant, you name it. The enterprise folks who are also in the connectivity business. And with that, we're not like a Y Combinator or a Techstars where it's investment first and it's all about funding. It's all about getting introductions from a startup who might have a VR or AI type of application or observability for 5G slicing, and bring that in front of the Microsoft's of the world, or the Intel's and the Dell's of the world that they might not have the capabilities to do it because they're still a small little startup with an MVP. So we really incubate. We're the connectors and build a network. We've had 101 startups over the last three years. They've raised over a billion dollars. And it's really valuable to our partners like T-Mobile and Dell, et cetera, where we're bringing in folks like Expedo and GenXComm and Firecell. Start up private companies that are around here they were cohorts from our program in the past. >> That's awesome because I've often, I mean, I've seen Dell get into this business and I'm like, wow, they've done a really good job of finding these guys. I wonder what the pipeline is. >> We're trying to create the pipeline for the entire industry, whether it's 5G on the edge for the CSPs, or it's for private enterprise networks. >> Warren, what's this cool little thing you got here? >> Yeah, so this is very unique in the Dell portfolio. So when people think of Dell, they think of servers laptops, et cetera. But what this does is it's designed to be deployed at the edge in harsh environments and it allows customers to do analytics, data collection at the edge. And what's unique about it is it's got an extended temperature range. There's no fan in this and there's lots of ports on it for data ingestion. So this is a smaller box Edge Gateway 3200. This is the product that we're using in the brewery. And then we have a bigger brother of this, the Edge Gateway 5200. So the value of it, you can scale depending on what your edge compute requirements are at the edge. >> So tell us about the brewery story. And you covered it, I know you were in the Dell booth, but it's basically an analog brewery. They're taking measurements and temperatures and then writing it down and then entering it in and somebody from your company saw it and said, "We can help you with this problem." Explain the story. >> Yeah, so Scott and I did a walkthrough of the brewery back in November timeframe. >> It's in Framingham, Mass. >> Framingham, Mass, correct. And basically, we talked to him, and we said, what keeps you guys up at night? What's a problem that we can solve? Very simple, a kind of a lower budget, didn't have a lot money to spend on it, but what problem can we solve that will realize great benefit for you? So we looked at their fermentation process, which was completely analog. Somebody was walking around with a clipboard looking at analog gauges. And what we did is we digitized that process. So what this did for them rather than being completely reactive, and by the time they realized there was something going wrong with the fermentation process, it's too late. A batch of scrap. This allowed them to be proactive. So anytime, anywhere on the tablet or a phone, they can see if that fermentation process is going out of range and do something about it before the batch gets scrapped. >> Okay. Amazing. And Scott, you got a picture of this workflow here? >> Yeah, actually this is the final product. >> Explain that. >> As Warren mentioned, the data is actually residing in the industrial side of the network So we wanted to keep the IT/OT separation, which is critical on the factory floor. And so all the data is brought in from the sensors via digital connection once it's converted and into the edge gateway. Then there's a snapshot of it using Telit deviceWISE, their dashboarding application, that is decoding all the digital readings, putting them in a nice dashboard. And then when we gave them, we realized another problem was they're using cheap little Chromebooks that they spill beer on once a week and throw them out. That's why they bought the cheap ones 'cause they go through them so fast. So we got a Dell Latitude Rugged notebook. This is a brand new tablet, but they have the dashboarding software. So no matter if they're out there on the floor, but because the data resides there on the factory they have access to be able to change the parameters. This one's in the maturation cycle. This one's in the crashing cycle where they're bringing the temperature back down, stopping the fermentation process, getting it ready to go to the canning side of the house. >> And they're doing all that from this dashboard. >> They're doing all from the dashboard. They also have a giant screen that we put up there that in the floor instead of walking a hundred yards back behind a whole bunch of machinery equipment from a safety perspective, now they just look up on the screen and go, "Oh, that's red. That's out of range." They're actually doing a bunch of cleaning and a bunch of other things right now, too. So this is real time from Boston. >> Dave: Oh okay. >> Scott: This is actually real time from Boston. >> I'm no hop master, but I'm looking at these things flashing at me and I'm thinking something's wrong with my beer. >> We literally just lit this up last week. So we're still tweaking a few things, but they're also learning around. This is a new capability they never had. Oh, we have the ability to alert and monitor at different processes with different batches, different brews, different yeast types. Then now they're also training and learning. And we're going to turn that into eventually a product that other breweries might be able to use. >> So back to the kind of nuts and bolts of the system. The device that you have here has essentially wifi antennas on the back. >> Warren: Correct. >> Pull that up again if you would, please. >> Now I've seen this, just so people are clear, there are also paddle 5G antennas that go on the other side. >> Correct. >> That's sort of the connection from the 5G network that then gets transmogrified, technical term guys, into wifi so the devices that are physically connected to the brew vats, don't know what they're called. >> Fermentation tanks. >> Fermentation tanks, thank you. Those are wifi. That's a wifi signal that's going into this. Is that correct? >> Scott: No. >> No, it's not. >> It's a hard wire. >> Okay, okay. >> But, you're right. This particular gateway. >> It could be wifi if it's hard wire. >> It could be, yes. Could be any technology really. >> This particular gateway is not outfitted with 5G, but something that was very important in this application was to isolate the IT network, which is on wifi and physically connected from the OT network, which is the 5G connection. So we're sending the data directly from the gateway up to the cloud. The two partners that we worked with on this project were ifm, big sensor manufacturer that actually did the wired sensors into an industrial network called IO-Link. So they're physically wired into the gateway and then in the gateway we have a solution from our partner Telit that has deviceWISE software that actually takes the data in, runs the analytics on it, the logic, and then visualizes that data locally on those panels and also up to their cloud, which is what we're looking at. So they can look at it locally, they're in the plant and then up in the cloud on a phone or a tablet, whatever, when they're at home. >> We're talking about a small business here. I don't know how many employees they have, but it's not thousands. And I love that you're talking about an IT network and an OT network. And so they wanted, it is very common when we talk about industrial internet of things use cases, but we're talking about a tiny business here. >> Warren: Correct. >> They wanted to separate those networks because of cost, because of contention. Explain why. >> Yeah, just because, I mean, they're running their ERP system, their payroll, all of their kind of the way they run their business on their IT network and you don't want to have the same traffic out on the factory floor on that network, so it was pretty important. And the other thing is we really, one of the things that we didn't want to do in this project is interrupt their production process at all. So we installed this entire system in two days. They didn't have to shut down, they didn't have to stop. We didn't have to interrupt their process at all. It was like we were invisible there and we spun the thing up and within two days, very simple, easy, but tremendous value for their business. >> Talk about new markets here. I mean, it's like any company that's analog that needs to go digital. It's like 99% of the companies on the planet. What are you guys seeing out there in terms of the types of examples beyond breweries? >> Yeah, I could talk to that. So I spent a lot of time over the last couple years running my own little IoT company and a lot of it being in agriculture. So like in Washington state, 70% of the world's hops is actually grown in Washington state. It's my hometown. But in the Ag producing regions, there's lack of connectivity. So there's interest in private networks because the carriers aren't necessarily deploying it. But because we have the vast amount of hops there's a lot of IPAs, a lot of hoppy IPAs that come out of Seattle. And with that, there's a ton of craft breweries that are about the same size, some are a little larger. Anheuser-Busch and InBev and Heineken they've got great IoT platforms. They've done it. They're mass scale, they have to digitize. But the smaller shops, they don't, when we talk about IT/OT separation, they're not aware of that. They think it's just, I get local broadband and I get wifi and one hotspot inside my facility and it works. So a little bit of it was the education. I have got years in IT/OT security in my background so that education and we come forward with a solution that actually does that for them. And now they're aware of it. So now when they're asking questions of other vendors that are trying to sell them some type of solution, they're inherently aware of what should be done so they're not vulnerable to ransomware attacks, et cetera. So it's known as the Purdue Model. >> Well, what should they do? >> We came in and keep it completely separated and educated them because in the end too we'll build a design guide and a starter kit out of this that other brewers can use. Because I've toured dozens of breweries in Washington, the exact same scenario, analog gauges, analog process, very manual. And in the end, when you ask the brewer, what do they want out of this? It keeps them up at night because if the temperature goes out of range, because the chiller fails, >> They ruined. >> That's $30,000 lost in beer. That's a lot to a small business. However, it's also once they start digitizing the data and to Warren's point, it's read-only. We're not changing any of the process. We augmented on top of their existing systems. We didn't change their process. But now they have the ability to look at the data and see batch to batch consistency. Quality doesn't always mean best, it means consistency from batch to batch. Every beer from exhibit A from yesterday to two months from now of the same style of beer should be the same taste, flavor, boldness, et cetera. This is giving them the insights on it. >> It's like St. Louis Buds, when we were kids. We would buy the St. Louis Buds 'cause they tasted better than the Merrimack Buds. And then Budweiser made them all the same. >> Must be an East coast thing. >> It's an old guy thing, Dave. You weren't born yet. >> I was in high school. Yeah, I was in high school. >> We like the hops. >> We weren't 21. Do me a favor, clarify OT versus IT. It's something we talk about all the time, but not everyone's familiar with that separation. Define OT for me. >> It's really the factory floor. You got IT systems that are ERP systems, billing, you're getting your emails, stuff like that. Where the ransomware usually gets infected in. The OT side is the industrial control network. >> David: What's the 'O' stand for? >> Operation. >> David: Operation? >> Yeah, the operations side. >> 'Cause some people will think objects 'cause we think internet of things. >> The industrial operations, think of it that way. >> But in a sense those are things that are connected. >> And you think of that as they are the safety systems as well. So a machine, if someone doesn't push the stop button, you'd think if there's a lot of traffic on that network, it isn't guaranteed that that stop button actually stops that blade from coming down, someone's going to lose their arm. So it's very tied to safety, reliability, low latency. It is crafted in design that it never touches the internet inherently without having to go through a security gateway which is what we did. >> You mentioned the large companies like InBev, et cetera. You're saying they're already there. Are they not part of your target market? Or are there ways that you can help them? Is this really more of a small to mid-size company? >> For this particular solution, I think so, yeah. Because the cost to entry is low. I mean, you talk about InBev, they have millions of dollars of budgets to spend on OT. So they're completely automated from top to bottom. But these little craft brewers, which they're everywhere in the US. Vermont, Washington state, they're completely manual. A lot of these guys just started in their garage. And they just scaled up and they got a cult kind of following around their beers. One thing that we found here this week, when you talk around edge and 5G and beer, those things get people excited. In our booth we're serving beer, and all these kind of topics, it brings people together. >> And it lets the little guy compete more effectively with the big giants. >> Correct. >> And how do you do more with less as the little guy is kind of the big thing and to Warren's point, we have folks come up and say, "Great, this is for beer, but what about wine? What about the fermentation process of wine?" Same materials in the end. A vessel of some sort, maybe it's stainless steel. The clamps are the same, the sensors are the same. The parameters like temperature are key in any type of fermentation. We had someone talking about olive oil and using that. It's the same sanitary beverage style equipment. We grabbed sensors that were off the shelf and then we integrated them in and used the set of platforms that we could. How do we rapidly enable these guys at the lowest possible cost with stuff that's at the shelf. And there's four different companies in the solution. >> We were having a conversation with T-Mobile a little earlier and she mentioned the idea of this sounding scary. And this is a great example of showing that in fact, at a relatively small scale, this technology makes a lot of sense. So from that perspective, of course you can implement private 5G networks at an industrial scale with tens of millions of dollars of investment. But what about all of the other things below? And that seems to be a perfect example. >> Yeah, correct. And it's one of the things with the gateway and having flexibility the way Dell did a great job of putting really good modems in it. It had a wide spectrum range of what bands they support. So being able to say, at a larger facility, I mean, if Heineken wants to deploy something like this, oh, heck yeah, they probably could do it. And they might have a private 5G network, but let's say T-Mobile offers a private offering on their public via a slice. It's easy to connect that radio to it. You just change the sims. >> Is that how the CSPs fit here? How are they monetized? >> Yeah, correct. So one of our partners is T-Mobile and so we're working with them. We've got other telco partners that are coming on board in our lab. And so we'll do the same thing. We're going to take this back and put it in the lab and offer it up as others because the baseline building blocks or Lego blocks per se can be used in a bunch of different industries. It's really that starter point of giving folks the idea of what's possible. >> So small manufacturing, agriculture you mentioned, any other sort of use cases we should tune into? >> I think it's environmental monitoring, all of that stuff, I see it in IoT deployments all over the world. Just the simple starter kits 'cause a farmer doesn't want to get sold a solution, a platform, where he's got to hire a bunch of coders and partner with the big carriers. He just wants something that works. >> Another use case that we see a lot, a high cost in a lot of these places is the cost of energy. And a lot of companies don't know what they're spending on electricity. So a very simple energy monitoring system like that, it's a really good ROI. I'm going to spend five or $10,000 on a system like this, but I'm going to save $20,000 over a year 'cause I'm able to see, have visibility into that data. That's a lot of what this story's about, just giving visibility into the process. >> It's very cool, and like you said, it gets people excited. Is it a big market? How do you size it? Is it a big TAM? >> Yeah, so one thing that Dell brings to the table in this space is people are buying their laptops, their servers and whatnot from Dell and companies are comfortable in doing business with Dell because of our model direct to customer and whatnot. So our ability to bring a device like this to the OT space and have them have that same user experience they have with laptops and our client products in a ruggedized solution like this and bring a lot of partners to the table makes it easy for our customers to implement this across all kinds of industries. >> So we're talking to billions, tens of billions. Do we know how big this market is? What's the TAM? I mean, come on, you work for Dell. You have to do a TAM analysis. >> Yes, no, yeah. I mean, it really is in the billions. The market is huge for this one. I think we just tapped into it. We're kind of focused in on the brewery piece of it and the liquor piece of it, but the possibilities are endless. >> Yeah, that's tip of the spear. Guys, great story. >> It's scalable. I think the biggest thing, just my final feedback is working and partnering with Dell is we got something as small as this edge gateway that I can run a Packet Core on and run a 5G standalone node and then have one of the small little 5G radios out there. And I've got these deployed in a farm. Give the farmer an idea of what's possible, give him a unit on his tractor, and now he can do something that, we're providing connectivity he had never had before. But as we scale up, we've got the big brother to this. When we scale up from that, we got the telco size units that we can put. So it's very scalable. It's just a great suite of offerings. >> Yeah, outstanding. Guys, thanks for sharing the story. Great to have you on theCUBE. >> Good to be with you today. >> Stop by for beer later. >> You know it. All right, Dave Vellante for Dave Nicholson and the entire CUBE team, we're here live at the Fira in Barcelona MWC '23 day four. Keep it right there. (upbeat music)

Published Date : Mar 2 2023

SUMMARY :

that drive human progress. and Scott Waller, the CTO of that we're going to talk about. the capabilities to do it of finding these guys. for the entire industry, So the value of it, Explain the story. of the brewery back in November timeframe. and by the time they realized of this workflow here? is the final product. and into the edge gateway. that from this dashboard. that in the floor instead Scott: This is actually and I'm thinking something's that other breweries might be able to use. nuts and bolts of the system. Pull that up again that go on the other side. so the devices that are Is that correct? This particular gateway. if it's hard wire. It could be, yes. that actually takes the data in, And I love that you're because of cost, because of contention. And the other thing is we really, It's like 99% of the that are about the same size, And in the end, when you ask the brewer, We're not changing any of the process. than the Merrimack Buds. It's an old guy thing, Dave. I was in high school. It's something we talk about all the time, It's really the factory floor. 'cause we think internet of things. The industrial operations, But in a sense those are doesn't push the stop button, You mentioned the large Because the cost to entry is low. And it lets the little is kind of the big thing and she mentioned the idea And it's one of the of giving folks the all over the world. places is the cost of energy. It's very cool, and like you and bring a lot of partners to the table What's the TAM? and the liquor piece of it, Yeah, that's tip of the spear. got the big brother to this. Guys, thanks for sharing the story. and the entire CUBE team,

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Tammy Whyman, Telco & Kurt Schaubach, Federated Wireless | MWC Barcelona 2023


 

>> Announcer: The cube's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (background indistinct chatter) >> Good morning from Barcelona, everyone. It's theCUBE live at MWC23, day three of our four days of coverage. Lisa Martin here with Dave Nicholson. Dave, we have had some great conversations. Can't believe it's day three already. Anything sticking out at you from a thematic perspective that really caught your eye the last couple days? >> I guess I go back to kind of our experience with sort of the generalized world of information technology and a lot of the parallels between what's been happening in other parts of the economy and what's happening in the telecom space now. So it helps me understand some of the complexity when I tie it back to things that I'm aware of >> A lot of complexity, but a big ecosystem that's growing. We're going to be talking more about the ecosystem next and what they're doing to really enable customers CSPs to deliver services. We've got two guests here, Tammy Wyman joins us the Global head of Partners Telco at AWS. And Kurt Schaubach, CTO of Federated Wireless. Welcome to theCUBE Guys. >> Thank you. >> Thank you. >> Great to have you here, day three. Lots of announcements, lots of news at MWC. But Tammy, there's been a lot of announcements from partners with AWS this week. Talk to us a little bit more about first of all, the partner program and then let's unpack some of those announcements. One of them is with Federated Wireless. >> Sure. Yeah. So AWS created the partner program 10 years ago when they really started to understand the value of bringing together the ecosystem. So, I think we're starting to see how this is becoming a reality. So now we 100,000 partners later, 150 countries, 70% of those partners are outside of the US. So truly the global nature and partners being ISVs, GSIs. And then in the telco space, we're actually looking at how we help CSBs become partners of AWS and bring new revenue streams. So that's how we start having the discussions around Federated Wireless. >> Talk a little bit about Federated Wireless, Kurt, give the audience an overview of what you guys are doing and then maybe give us some commentary on the partnership. >> Sure. So we're a shared spectrum and private wireless company, and we actually started working with AWS about five years ago to take this model that we developed to perfect the use of shared spectrum to enable enterprise communications and bring the power of 5G to the enterprise to bring it to all of the AWS customers and partners. So through that now through we're one of the partner network participants. We're working very closely with the AWS team on bringing this, really unique form of connectivity to all sorts of different enterprise use cases from solving manufacturing and warehouse logistics issues to providing connectivity to mines, enhancing the experience for students on a university campus. So it's a really exciting partnership. Everything that we deliver on an end-to-end basis from design deployment to bringing the infrastructure on-prem, all runs on AWS. (background indistinct chatter) >> So a lot of the conversations that we've had sort of start with this concept of the radio access network and frankly in at least the public domain cellular sites. And so all of a sudden it's sort of grounded in this physical reality of these towers with these boxes of equipment on the tower, at the base of the tower, connected to other things. How does AWS and Federated Wireless, where do you fit in that model in terms of equipment at the base of a tower versus what having that be off-premises in some way or another. Kind of give us more of a flavor for the kind of physical reality of what you guys are doing? >> Yeah, I'll start. >> Yeah, Tammy. >> I'll hand it over to the real expert but from an AWS perspective, what we're finding is really I don't know if it's even a convergence or kind of a delaying of the network. So customers are, they don't care if they're on Wi-Fi if they're on public spectrum, if they're on private spectrum, what they want are networks that are able to talk to each other and to provide the right connectivity at the right time and with the right pricing model. So by moving to the cloud that allows us that flexibility to be able to offer the quality of service and to be able to bring in a larger ecosystem of partners as with the networks are almost disaggregated. >> So does the AWS strategy focus solely on things that are happening in, say, AWS locations or AWS data centers? Or is AWS also getting into the arena of what I would refer to as an Outpost in an AWS parlance where physical equipment that's running a stack might actually also be located physically where the communications towers are? What does that mix look like in terms of your strategy? >> Yeah, certainly as customers are looking at hybrid cloud environments, we started looking at how we can use Outpost as part of the network. So, we've got some great use cases where we're taking Outpost into the edge of operators networks, and really starting to have radio in the cloud. We've launched with Dish earlier, and now we're starting to see some other announcements that we've made with Nokia about having ran in the cloud as well. So using Outpost, that's one of our key strategies. It creates, again, a lot of flexibility for the hybrid cloud environment and brings a lot of that compute power to the edge of the network. >> Let's talk about some of the announcements. Tammy was reading that AWS is expanding, its telecom and 5g, private 5G network support. You've also unveiled the AWS Telco Network Builder service. Talk about that, who that's targeted for. What does an operator do with AWS on this? Or maybe you guys can talk about that together. >> Sure. Would you like to start? I can talk. All right. So from the network builder, it's aimed at the, I would say the persona that it's aimed at would be the network engineer within the CSPs. And there was a bit of a difficulty when you want to design a telco network on AWS versus the way that the network engineers would traditionally design. So I'm going to call them protocols, but you know I can imagine saying, "I really want to build this on the cloud, but they're making me move away from my typical way that I design a network and move it into a cloud world." So what we did was really kind of create this template saying, "You can build the network as you always do and we are going to put the magic behind it to translate it into a cloud world." So just really facilitating and taking some of the friction out of the building of the network. >> What was the catalyst for that? I think Dish and Swisscom you've been working with but talk about the catalyst for doing that and how it's facilitating change because part of that's change management with how network engineers actually function and how they work. >> Absolutely, yeah. And we're looking, we listen to customers and we're trying to understand what are those friction points? What would make it easier? And that was one that we heard consistently. So we wanted to apply a bit of our experience and the way that we're able to use data translate that using code so that you're building a network in your traditional way, and then it kind of spits out what's the formula to build the network in the cloud. >> Got it. Kurt, talk about, yeah, I saw that there was just an announcement that Federated Wireless made JBG Smith. Talk to us more about that. What will federated help them to create and how are you all working together? >> Sure. So JBG Smith is the exclusive redeveloper of an area just on the other side of the Potomac from Washington DC called National Landing. And it's about half the size of Manhattan. So it's an enormous area that's getting redeveloped. It's the home of Amazon's new HQ two location. And JBG Smith is investing in addition to the commercial real estate, digital place making a place where people live, work, play, and connect. And part of that is bringing an enhanced level of connectivity to people's homes, their residents, the enterprise, and private wireless is a key component of that. So when we talk about private wireless, what we're doing with AWS is giving an enterprise the freedom to operate a network independent of a mobile network operator. So that means everything from the ran to the core to the applications that run on this network are sort of within the domain of the enterprise merging 5G and edge compute and driving new business outcomes. That's really the most important thing. We can talk a lot about 5G here at MWC about what the enterprise really cares about are new business outcomes how do they become more efficient? And that's really what private wireless helps enable. >> So help us connect the dots. When we talk about private wireless we've definitely been in learning mode here. Well, I'll speak for myself going around and looking at some of the exhibits and seeing how things work. And I know that I wasn't necessarily a 100% clear on this connection between a 5G private wireless network today and where Wi-Fi still comes into play. So if I am a new resident in this area, happily living near the amazing new presence of AWS on the East coast, and I want to use my mobile device how am I connected into that private wireless network? What does that look like as a practical matter? >> So that example that you've just referred to is really something that we enable through neutral host. So in fact, what we're able to do through this private network is also create carrier connectivity. Basically create a pipe almost for the carriers to be able to reach a consumer device like that. A lot of private wireless is also driving business outcomes with enterprises. So work that we're doing, like for example, with the Cal Poly out in California, for example is to enable a new 5G innovation platform. So this is driving all sorts of new 5G research and innovation with the university, new applications around IoT. And they need the ability to do that indoors, outdoors in a way that's sort of free from the domain of connectivity to a a mobile network operator and having the freedom and flexibility to do that, merging that with edge compute. Those are some really important components. We're also doing a lot of work in things like warehouses. Think of a warehouse as being this very complex RF environment. You want to bring robotics you want to bring better inventory management and Wi-Fi just isn't an effective means of providing really reliable indoor coverage. You need more secure networks you need lower latency and the ability to move more data around again, merging new applications with edge compute and that's where private wireless really shines. >> So this is where we do the shout out to my daughter Rachel Nicholson, who is currently a junior at Cal Poly San Luis Obispo. Rachel, get plenty of sleep and get your homework done. >> Lisa: She better be studying. >> I held up my mobile device and I should have said full disclosure, we have spotty cellular service where I live. So I think of this as a Wi-Fi connected device, in fact. So maybe I confuse the issue at least. >> Tammy, talk to us a little bit about the architecture from an AWS perspective that is enabling JBG Smith, Cal Poly is this, we're talking an edge architecture, but give us a little bit more of an understanding of what that actually technically looks like. >> Alright, I would love to pass this one over to Kurt. >> Okay. >> So I'm sorry, just in terms of? >> Wanting to understand the AWS architecture this is an edge based architecture hosted on what? On AWS snow, application storage. Give us a picture of what that looks like. >> Right. So I mean, the beauty of this is the simplicity in it. So we're able to bring an AWS snowball, snow cone, edge appliance that runs a pack of core. We're able to run workloads on that locally so some applications, but we also obviously have the ability to bring that out to the public cloud. So depending on what the user application is, we look at anything from the AWS snow family to Outpost and sort of develop templates or solutions depending on what the customer workloads demand. But the innovation that's happened, especially around the pack core and how we can make that so compact and able to run on such a capable appliance is really powerful. >> Yeah, and I will add that I think the diversification of the different connectivity modules that we have a lot of them have been developed because of the needs from the telco industry. So the adaptation of Outpost to run into the edge, the snow family. So the telco industry is really leading a lot of the developments that AWS takes to market in the end because of the nature of having to have networks that are able to disconnect, ruggedize environments, the latency, the numerous use cases that our telco customers are facing to take to their end customers. So like it really allows us to adapt and bring the right network to the right place and the right environment. And even for the same customer they may have different satellite offices or remote sites that need different connectivity needs. >> Right. So it sounds like that collaboration between AWS and telco is quite strong and symbiotic, it sounds like. >> Tammy: Absolutely. >> So we talked about a number of the announcements in our final minutes. I want to talk about integrated private wireless that was just announced last week. What is that? Who are the users going to be? And I understand T-Mobile is involved there. >> Yes. Yeah. So this is a program that we launched based on what we're seeing is kind of a convergence of the ecosystem of private wireless. So we wanted to be able to create a program which is offering spectrum that is regulated as well. And we wanted to offer that on in a more of a multi country environment. So we launched with T-Mobile, Telephonica, KDDI and a number of other succeed, as a start to start being able to bring the regulated spectrum into the picture and as well other ISVs who are going to be bringing unique use cases so that when you look at, well we've got the connectivity into this environment, the mine or the port, what are those use cases? You know, so ISVs who are providing maybe asset tracking or some of the health and safety and we bring them in as part of the program. And I think an important piece is the actual discoverability of this, because when you think about that if you're a buyer on the other side, like where do I start? So we created a portal with this group of ISVs and partners so that one could come together and kind of build what are my needs? And then they start picking through and then the ecosystem would be recommended to them. So it's a really a way to discover and to also procure a private wireless network much more easily than could be done in the past. >> That's a great service >> And we're learning a lot from the market. And what we're doing together in our partnership is through a lot of these sort of ruggedized remote location deployments that we're doing, mines, clearing underbrush and forest forest areas to prevent forest fires. There's a tremendous number of applications for private wireless where sort of the conventional carrier networks just aren't prioritized to serve. And you need a different level of connectivity. Privacy is big concern as well. Data security. Keeping data on premise, which is a another big application that we were able to drive through these edge compute platforms. >> Awesome. Guys, thank you so much for joining us on the program talking about what AWS Federated are doing together and how you're really helping to evolve the telco landscape and make life ultimately easier for all the Nicholsons to connect over Wi-Fi, our private 5g. >> Keep us in touch. And from two Californians you had us when you said clear the brush, prevent fires. >> You did. Thanks guys, it was a pleasure having you on the program. >> Thank you. >> Thank you. >> Our pleasure. For our guest and for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE Live from our third day of coverage of MWC23. Stick around Dave and I will be right back with our next guest. (upbeat music)

Published Date : Mar 1 2023

SUMMARY :

that drive human progress. eye the last couple days? and a lot of the parallels the Global head of Partners Telco at AWS. the partner program and then let's unpack So AWS created the partner commentary on the partnership. and bring the power of So a lot of the So by moving to the cloud that allows us and brings a lot of that compute power of the announcements. So from the network but talk about the catalyst for doing that and the way that we're Talk to us more about that. from the ran to the core and looking at some of the exhibits and the ability to move So this is where we do the shout out So maybe I confuse the issue at least. bit about the architecture pass this one over to Kurt. the AWS architecture the beauty of this is a lot of the developments that AWS and telco is quite strong and number of the announcements a convergence of the ecosystem a lot from the market. on the program talking the brush, prevent fires. having you on the program. of coverage of MWC23.

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Luis Ceze, OctoML | Cube Conversation


 

(gentle music) >> Hello, everyone. Welcome to this Cube Conversation. I'm John Furrier, host of theCUBE here, in our Palo Alto Studios. We're featuring OctoML. I'm with the CEO, Luis Ceze. Chief Executive Officer, Co-founder of OctoML. I'm John Furrier of theCUBE. Thanks for joining us today. Luis, great to see you. Last time we spoke was at "re:MARS" Amazon's event. Kind of a joint event between (indistinct) and Amazon, kind of put a lot together. Great to see you. >> Great to see you again, John. I really have good memories of that interview. You know, that was definitely a great time. Great to chat with you again. >> The world of ML and AI, machine learning and AI is really hot. Everyone's talking about it. It's really great to see that advance. So I'm looking forward to this conversation but before we get started, introduce who you are in OctoML. >> Sure. I'm Luis Ceze, Co-founder and CEO at OctoML. I'm also professor of Computer Science at University of Washington. You know, OctoML grew out of our efforts on the Apache CVM project, which is a compiler in runtime system that enables folks to run machine learning models in a broad set of harder in the Edge and in the Cloud very efficiently. You know, we grew that project and grew that community, definitely saw there was something to pain point there. And then we built OctoML, OctoML is about three and a half years old now. And the mission, the company is to enable customers to deploy models very efficiently in the Cloud. And make them, you know, run. Do it quickly, run fast, and run at a low cost, which is something that's especially timely right now. >> I like to point out also for the folks 'casue they should know that you're also a professor in the Computer Science department at University of Washington. A great program there. This is a really an inflection point with AI machine learning. The computer science industry has been waiting for decades to advance AI with all this new cloud computing, all the hardware and silicon advancements, GPUs. This is the perfect storm. And you know, this the computer science now we we're seeing an acceleration. Can you share your view, and you're obviously a professor in that department but also, an entrepreneur. This is a great time for computer science. Explain why. >> Absolutely, yeah, no. Just like the confluence of you know, advances in what, you know, computers can do as devices to computer information. Plus, you know, advances in AI that enable applications that you know, we thought it was highly futuristic and now it's just right there today. You know, AI that can generate photo realistic images from descriptions, you know, can write text that's pretty good. Can help augment, you know, human creativity in a really meaningful way. So you see the confluence of capabilities and the creativity of humankind into new applications is just extremely exciting, both from a researcher point of view as well as an entrepreneur point of view, right. >> What should people know about these large language models we're seeing with ChatGPT and how Google has got a lot of work going on that air. There's been a lot of work recently. What's different now about these models, and why are they so popular and effective now? What's the difference between now, and say five years ago, that makes it more- >> Oh, yeah. It's a huge inflection on their capabilities, I always say like emergent behavior, right? So as these models got more complex and our ability to train and deploy them, you know, got to this point... You know, they really crossed a threshold into doing things that are truly surprising, right? In terms of generating, you know, exhalation for things generating tax, summarizing tax, expending tax. And you know, exhibiting what to some may look like reasoning. They're not quite reasoning fundamentally. They're generating tax that looks like they're reasoning, but they do it so well, that it feels like was done by a human, right. So I would say that the biggest changes that, you know, now, they can actually do things that are extremely useful for business in people's lives today. And that wasn't the case five years ago. So that's in the model capabilities and that is being paired with huge advances in computing that enabled this to be... Enables this to be, you know, actually see line of sites to be deployed at scale, right. And that's where we come in, by the way, but yeah. >> Yeah, I want to get into that. And also, you know, the fusion of data integrating data sets at scales. Another one we're seeing a lot of happening now. It's not just some, you know, siloed, pre-built data modeling. It's a lot of agility and a lot of new integration capabilities of data. How is that impacting the dynamics? >> Yeah, absolutely. So I'll say that the ability to either take the data that has that exists in training a model to do something useful with it, and more interestingly I would say, using baseline foundational models and with a little bit of data, turn them into something that can do a specialized task really, really well. Created this really fast proliferation of really impactful applications, right? >> If every company now is looking at this trend and I'm seeing a lot... And I think every company will rebuild their business with machine learning. If they're not already doing it. And the folks that aren't will probably be dinosaurs will be out of business. This is a real business transformation moment where machine learning and AI, as it goes mainstream. I think it's just the beginning. This is where you guys come in, and you guys are poised for handling this frenzy to change business with machine learning models. How do you guys help customers as they look at this, you know, transition to get, you know, concept to production with machine learning? >> Great. Great questions, yeah, so I would say that it's fair to say there's a bunch of models out there that can do useful things right off the box, right? So and also, the ability to create models improved quite a bit. So the challenge now shifted to customers, you know. Everyone is looking to incorporating AI into their applications. So what we do for them is to, first of all, how do you do that quickly, without needing highly specialized, difficult to find engineering? And very importantly, how do you do that at cost that's accessible, right? So all of these fantastic models that we just talked about, they use an amount of computing that's just astronomical compared to anything else we've done in the past. It means the costs that come with it, are also very, very high. So it's important to enable customers to, you know, incorporate AI into their applications, to their use cases in a way that they can do, with the people that they have, and the costs that they can afford, such that they can have, you know, the maximum impacting possibly have. And finally, you know, helping them deal with hardware availability, as you know, even though we made a lot of progress in making computing cheaper and cheaper. Even to this day, you know, you can never get enough. And getting an allocation, getting the right hardware to run these incredibly hungry models is hard. And we help customers deal with, you know, harder availability as well. >> Yeah, for the folks watching as a... If you search YouTube, there's an interview we did last year at "re:MARS," I mentioned that earlier, just a great interview. You talked about this hardware independence, this traction. I want to get into that, because if you look at all the foundation models that are out there right now, that are getting traction, you're seeing two trends. You're seeing proprietary and open source. And obviously, open source always wins in my opinion, but, you know, there's this iPhone moment and android moment that one of your investors John Torrey from Madrona, talked about was is iPhone versus Android moment, you know, one's proprietary hardware and they're very specialized high performance and then open source. This is an important distinction and you guys are hardware independent. What's the... Explain what all this means. >> Yeah. Great set of questions. First of all, yeah. So, you know, OpenAI, and of course, they create ChatGPT and they offer an API to run these models that does amazing things. But customers have to be able to go and send their data over to OpenAI, right? So, and run the model there and get the outputs. Now, there's open source models that can do amazing things as well, right? So they typically open source models, so they don't lag behind, you know, these proprietary closed models by more than say, you know, six months or so, let's say. And it means that enabling customers to take the models that they want and deploy under their control is something that's very valuable, because one, you don't have to expose your data to externally. Two, you can customize the model even more to the things that you wanted to do. And then three, you can run on an infrastructure that can be much more cost effective than having to, you know, pay somebody else's, you know, cost and markup, right? So, and where we help them is essentially help customers, enable customers to take machine learning models, say an open source model, and automate the process of putting them into production, optimize them to run with the right performance, and more importantly, give them the independence to run where they need to run, where they can run best, right? >> Yeah, and also, you know, I point out all the time that, you know, there's never any stopping the innovation of hardware silicon. You're seeing cloud computing more coming in there. So, you know, being hardware independent has some advantages. And if you look at OpenAI, for instance, you mentioned ChatGPT, I think this is interesting because I think everyone is scratching their head, going, "Okay, I need to move to this new generation." What's your pro tip and advice for folks who want to move to, or businesses that want to say move to machine learning? How do they get started? What are some of the considerations they need to think about to deploy these models into production? >> Yeah, great though. Great set of questions. First of all, I mean, I'm sure they're very aware of the kind of things that you want to do with AI, right? So you could be interacting with customers, you know, automating, interacting with customers. It could be, you know, finding issues in production lines. It could be, you know... Generating, you know, making it easier to produce content and so on. Like, you know, customers, users would have an idea what they want to do. You know, from that it can actually determine, what kind of machine learning models would solve the problem that would, you know, fits that use case. But then, that's when the hard thing begins, right? So when you find a model, identify the model that can do the thing that you wanted to do, you need to turn that into a thing that you can deploy. So how do you go from machine learning model that does a thing that you need to do, to a container with the right executor, the artifact they can actually go and deploy, right? So we've seen customers doing that on their own, right? So, and it's got a bit of work, and that's why we are excited about the automation that we can offer and then turn that into a turnkey problem, right? So a turnkey process. >> Luis, talk about the use cases. If I don't mind going and double down on the previous answer. You got existing services, and then there's new AI applications, AI for applications. What are the use cases with existing stuff, and the new applications that are being built? >> Yeah, I mean, existing itself is, for example, how do you do very smart search and auto completion, you know, when you are editing documents, for example. Very, very smart search of documents, summarization of tax, expanding bullets into pros in a way that, you know, don't have to spend as much human time. Just some of the existing applications, right? So some of the new ones are like truly AI native ways of producing content. Like there's a company that, you know, we share investors and love what they're doing called runwayyML, for example. It's sort of like an AI first way of editing and creating visual content, right? So you could say you have a video, you could say make this video look like, it's night as opposed to dark, or remove that dog in the corner. You can do that in a way that you couldn't do otherwise. So there's like definitely AI native use cases. And yet not only in life sciences, you know, there's quite a bit of advances on AI-based, you know, therapies and diagnostics processes that are designed using automated processes. And this is something that I feel like, we were just scratching the surface there. There's huge opportunities there, right? >> Talk about the inference and AI and production kind of angle here, because cost is a huge concern when you look at... And there's a hardware and that flexibility there. So I can see how that could help, but is there a cost freight train that can get out of control here if you don't deploy properly? Talk about the scale problem around cost in AI. >> Yeah, absolutely. So, you know, very quickly. One thing that people tend to think about is the cost is. You know, training has really high dollar amounts it tends over index on that. But what you have to think about is that for every model that's actually useful, you're going to train it once, and then run it a large number of times in inference. That means that over the lifetime of a model, the vast majority of the compute cycles and the cost are going to go to inference. And that's what we address, right? So, and to give you some idea, if you're talking about using large language model today, you know, you can say it's going to cost a couple of cents per, you know, 2,000 words output. If you have a million users active, you know, a day, you know, if you're lucky and you have that, you can, this cost can actually balloon very quickly to millions of dollars a month, just in inferencing costs. You know, assuming you know, that you actually have access to the infrastructure to run it, right? So means that if you don't pay attention to these inference costs and that's definitely going to be a surprise. And affects the economics of the product where this is embedded in, right? So this is something that, you know, if there's quite a bit of attention being put on right now on how do you do search with large language models and you don't pay attention to the economics, you know, you can have a surprise. You have to change the business model there. >> Yeah. I think that's important to call out, because you don't want it to be a runaway cost structure where you architected it wrong and then next thing you know, you got to unwind that. I mean, it's more than technical debt, it's actually real debt, it's real money. So, talk about some of the dynamics with the customers. How are they architecting this? How do they get ahead of that problem? What do you guys do specifically to solve that? >> Yeah, I mean, well, we help customers. So, it's first of all, be hyper aware, you know, understanding what's going to be the cost for them deploying the models into production and showing them the possibilities of how you can deploy the model with different cost structure, right? So that's where, you know, the ability to have hardware independence is so important because once you have hardware independence, after you optimize models, obviously, you have a new, you know, dimension of freedom to choose, you know, what is the right throughput per dollar for you. And then where, and what are the options? And once you make that decision, you want to automate the process of putting into production. So the way we help customers is showing very clearly in their use case, you know, how they can deploy their models in a much more cost-effective way. You know, when the cases... There's a case study that we put out recently, showing a 4x reduction in deployment costs, right? So this is by doing a mix optimization and choosing the right hardware. >> How do you address the concern that someone might say, Luis said, "Hey, you know, I don't want to degrade performance and latency, and I don't want the user experience to suffer." What's the answer there? >> Two things. So first of all, all of the manipulations that we do in the model is to turn the model to efficient code without changing the behavior of the models. We wouldn't degrade the experience of the user by having the model be wrong more often. And we don't change that at all. The model behaves the way it was validated for. And then the second thing is, you know, user experience with respect to latency, it's all about a maximum... Like, you could say, I want a model to run at 50 milliseconds or less. If it's much faster than 15 seconds, you're not going to notice the difference. But if it's lower, you're going to notice a difference. So the key here is that, how do you find a set of options to deploy, that you are not overshooting performance in a way that's going to lead to costs that has no additional benefits. And this provides a huge, a very significant margin of choices, set of choices that you can optimize for cost without degrading customer experience, right. End user experience. >> Yeah, and I also point out the large language models like the ChatGPTs of the world, they're coming out with Dave Moth and I were talking on this breaking analysis around, this being like, over 10X more computational intensive on capabilities. So this hardware independence is a huge thing. So, and also supply chain, some people can't get servers by the way, so, or hardware these days. >> Or even more interestingly, right? So they do not grow in trees, John. Like GPUs is not kind of stuff that you plant an orchard until you have a bunch and then you can increase it, but no, these things, you know, take a while. So, and you can't increase it overnight. So being able to live with those cycles that are available to you is not just important for all for cost, but also important for people to scale and serve more users at, you know, at whatever pace that they come, right? >> You know, it's really great to talk to you, and congratulations on OctaML. Looking forward to the startup showcase, we'll be featuring you guys there. But I want to get your personal opinion as someone in the industry and also, someone who's been in the computer science area for your career. You know, computer science has always been great, and there's more people enrolling in computer science, more diversity than ever before, but there's also more computer science related fields. How is this opening up computer science and where's AI going with the computers, with the science? Can you share your vision on, you know, the aperture, or the landscape of CompSci, or CS students, and opportunities. >> Yeah, no, absolutely. I think it's fair to say that computer has been embedded in pretty much every aspect of human life these days. Human life these days, right? So for everything. And AI has been a counterpart, it been an integral component of computer science for a while. And this medicines that happened in the last 10, 15 years in AI has shown, you know, new application has I think re-energized how people see what computers can do. And you, you know, there is this picture in our department that shows computer science at the center called the flower picture, and then all the different paddles like life sciences, social sciences, and then, you know, mechanical engineering, all these other things that, and I feel like it can replace that center with computer science. I put AI there as well, you see AI, you know touching all these applications. AI in healthcare, diagnostics. AI in discovery in the sciences, right? So, but then also AI doing things that, you know, the humans wouldn't have to do anymore. They can do better things with their brains, right? So it's permitting every single aspect of human life from intellectual endeavor to day-to-day work, right? >> Yeah. And I think the ChatGPT and OpenAI has really kind of created a mainstream view that everyone sees value in it. Like you could be in the data center, you could be in bio, you could be in healthcare. I mean, every industry sees value. So this brings up what I can call the horizontally scalable use constance. And so this opens up the conversation, what's going to change from this? Because if you go horizontally scalable, which is a cloud concept as you know, that's going to create a lot of opportunities and some shifting of how you think about architecture around data, for instance. What's your opinion on what this will do to change the inflection of the role of architecting platforms and the role of data specifically? >> Yeah, so good question. There is a lot in there, by the way, I should have added the previous question, that you can use AI to do better AI as well, which is what we do, and other folks are doing as well. And so the point I wanted to make here is that it's pretty clear that you have a cloud focus component with a nudge focused counterparts. Like you have AI models, but both in the Cloud and in the Edge, right? So the ability of being able to run your AI model where it runs best also has a data advantage to it from say, from a privacy point of view. That's inherently could say, "Hey, I want to run something, you know, locally, strictly locally, such that I don't expose the data to an infrastructure." And you know that the data never leaves you, right? Never leaves the device. Now you can imagine things that's already starting to happen, like you do some forms of training and model customization in the model architecture itself and the system architecture, such that you do this as close to the user as possible. And there's something called federated learning that has been around for some time now that's finally happening is, how do you get a data from butcher places, you do, you know, some common learning and then you send a model to the Edges, and they get refined for the final use in a way that you get the advantage of aggregating data but you don't get the disadvantage of privacy issues and so on. >> It's super exciting. >> And some of the considerations, yeah. >> It's super exciting area around data infrastructure, data science, computer science. Luis, congratulations on your success at OctaML. You're in the middle of it. And the best thing about its businesses are looking at this and really reinventing themselves and if a business isn't thinking about restructuring their business around AI, they're probably will be out of business. So this is a great time to be in the field. So thank you for sharing your insights here in theCUBE. >> Great. Thank you very much, John. Always a pleasure talking to you. Always have a lot of fun. And we both speak really fast, I can tell, you know, so. (both laughing) >> I know. We'll not the transcript available, we'll integrate it into our CubeGPT model that we have Luis. >> That's right. >> Great. >> Great. >> Great to talk to you, thank you, John. Thanks, man, bye. >> Hey, this is theCUBE. I'm John Furrier, here in Palo Alto, Cube Conversation. Thanks for watching. (gentle music)

Published Date : Feb 21 2023

SUMMARY :

Luis, great to see you. Great to chat with you again. introduce who you are in OctoML. And make them, you know, run. And you know, this the Just like the confluence of you know, What's the difference between now, Enables this to be, you know, And also, you know, the fusion of data So I'll say that the ability and you guys are poised for handling Even to this day, you know, and you guys are hardware independent. so they don't lag behind, you know, I point out all the time that, you know, that would, you know, fits that use case. and the new applications in a way that, you know, if you don't deploy properly? So, and to give you some idea, and then next thing you So that's where, you know, Luis said, "Hey, you know, that you can optimize for cost like the ChatGPTs of the world, that are available to you Can you share your vision on, you know, you know, the humans which is a cloud concept as you know, is that it's pretty clear that you have So thank you for sharing your I can tell, you know, so. We'll not the transcript available, Great to talk to you, I'm John Furrier, here in

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Evan Touger, Prowess | Prowess Benchmark Testing Results for AMD EPYC Genoa on Dell Servers


 

(upbeat music) >> Welcome to theCUBE's continuing coverage of AMD's fourth generation EPYC launch. I've got a special guest with me today from Prowess Consulting. His name is Evan Touger, he's a senior technical writer with Prowess. Evan, welcome. >> Hi, great to be here. Thanks. >> So tell us a little bit about Prowess, what does Prowess do? >> Yeah, we're a consulting firm. We've been around for quite a few years, based in Bellevue, Washington. And we do quite a few projects with folks from Dell to a lot of other companies, and dive in. We have engineers, writers, production folks, so pretty much end-to-end work, doing research testing and writing, and diving into different technical topics. >> So you- in this case what we're going to be talking about is some validation studies that you've done, looking at Dell PowerEdge servers that happened to be integrating in fourth-gen EPYC processors from AMD. What were the specific workloads that you were focused on in this study? >> Yeah, this particular one was honing in on virtualization, right? You know, obviously it's pretty much ubiquitous in the industry, everybody works with virtualization in one way or another. So just getting optimal performance for virtualization was critical, or is critical for most businesses. So we just wanted to look a little deeper into, you know, how do companies evaluate that? What are they going to use to make the determination for virtualization performance as it relates to their workloads? So that led us to this study, where we looked at some benchmarks, and then went a little deeper under the hood to see what led to the results that we saw from those benchmarks. >> So when you say virtualization, does that include virtual desktop infrastructure or are we just talking about virtual machines in general? >> No, it can include both. We looked at VMs, thinking in terms of what about database performance when you're working in VMs, all the way through to VDI and companies like healthcare organizations and so forth, where it's common to roll out lots of virtual desktops, and performance is critical there as well. >> Okay, you alluded to, sort of, looking under the covers to see, you know, where these performance results were coming from. I assume what you're referencing is the idea that it's not just all about the CPU when you talk about a system. Am I correct in that assumption and- >> Yeah, absolutely. >> What can you tell us? >> Well, you know, for companies evaluating, there's quite a bit to consider, obviously. So they're looking at not just raw performance but power performance. So that was part of it, and then what makes up that- those factors, right? So certainly CPU is critical to that, but then other things come into play, like the RAID controllers. So we looked a little bit there. And then networking, of course can be critical for configurations that are relying on good performance on their networks, both in terms of bandwidth and just reducing latency overall. So interconnects as well would be a big part of that. So with, with PCIe gen 5 or 5.0 pick your moniker. You know in this- in the infrastructure game, we're often playing a game of whack-a-mole, looking for the bottlenecks, you know, chasing the bottlenecks. PCIe 5 opens up a lot of bandwidth for memory and things like RAID controllers and NICs. I mean, is the bottleneck now just our imagination, Evan, have we reached a point where there are no bottlenecks? What did you see when you ran these tests? What, you know, what were you able to stress to a point where it was saturated, if anything? >> Yeah. Well, first of all, we didn't- these are particular tests were ones that we looked at industry benchmarks, and we were examining in particular to see where world records were set. And so we uncovered a few specific servers, PowerEdge servers that were pretty key there, or had a lot of- were leading in the category in a lot of areas. So that's what led us to then, okay, well why is that? What's in these servers, and what's responsible for that? So in a lot of cases they, we saw these results even with, you know, gen 4, PCIe gen 4. So there were situations where clearly there was benefit from faster interconnects and, and especially NVMe for RAID, you know, for supporting NVMe and SSDs. But all of that just leads you to the understanding that it means it can only get better, right? So going from gen 4 to- if you're seeing great results on gen 4, then gen 5 is probably going to be, you know, blow that away. >> And in this case, >> It'll be even better. >> In this case, gen 5 you're referencing PCIe >> PCIe right. Yeah, that's right. >> (indistinct) >> And then the same thing with EPYC actually holds true, some of the records, we saw records set for both 3rd and 4th gen, so- with EPYC, so the same thing there. Anywhere there's a record set on the 3rd gen, you know, makes us really- we're really looking forward to going back and seeing over the next few months, which of those records fall and are broken by newer generation versions of these servers, once they actually wrap to the newer generation processors. You know, based on, on what we're seeing for the- for what those processors can do, not only in. >> (indistinct) Go ahead. >> Sorry, just want to say, not only in terms of raw performance, but as I mentioned before, the power performance, 'cause they're very efficient, and that's a really critical consideration, right? I don't think you can overstate that for companies who are looking at, you know, have to consider expenditures and power and cooling and meeting sustainability goals and so forth. So that was really an important category in terms of what we looked at, was that power performance, not just raw performance. >> Yeah, I want to get back to that, that's a really good point. We should probably give credit where credit is due. Which Dell PowerEdge servers are we talking about that were tested and what did those interconnect components look like from a (indistinct) perspective? >> Yeah, so we focused primarily on a couple benchmarks that seemed most important for real world performance results for virtualization. TPCx-V and VMmark 3.x. the TPCx-V, that's where we saw PowerEdge R7525, R7515. They both had top scores in different categories there. That benchmark is great for looking at database workloads in particular, right? Running in virtualization settings. And then the VMmark 3.x was critical. We saw good, good results there for the 7525 and the R 7515 as well as the R 6525, in that one and that included, sorry, just checking notes to see what- >> Yeah, no, no, no, no, (indistinct) >> Included results for power performance, as I mentioned earlier, that's where we could see that. So we kind of, we saw this in a range of servers that included both 3rd gen AMD EPYC and newer 4th gen as well as I mentioned. The RAID controllers were critical in the TPCx-V. I don't think that came into play in the VM mark test, but they were definitely part of the TPCx-V benchmarks. So that's where the RAID controllers would make a difference, right? And in those tests, I think they're using PERC 11. So, you know, the newer PERC 12 controllers there, again we'd expect >> (indistinct) >> To see continued, you know, gains in newer benchmarks. That's what we'll be looking for over the next several months. >> Yeah. So I think if I've got my Dell nomenclature down, performance, no no, PowerEdge RAID Controller, is that right? >> Exactly, yeah, there you go. Right? >> With Broadcom, you know, powered by Broadcom. >> That's right. There you go. Yeah. Isn't the Dell naming scheme there PERC? >> Yeah, exactly, exactly. Back to your comment about power. So you've had a chance to take a pretty deep look at the latest stuff coming out. You're confident that- 'cause some of these servers are going to be more expensive than previous generation. Now a server is not a server is not a server, but some are awakening to the idea that there might be some sticker shock. You're confident that the bang for your buck, the bang for your kilowatt hour is actually going to be beneficial. We're actually making things better, faster, stronger, cheaper, more energy efficient. We're continuing on that curve? >> That's what I would expect to see, right. I mean, of course can't speak to to pricing without knowing, you know, where the dollars are going to land on the servers. But I would expect to see that because you're getting gains in a couple of ways. I mean, one, if the performance increases to the point where you can run more VMs, right? Get more performance out of your VMs and run more total VMs or more BDIs, then there's obviously a good, you know, payback on your investment there. And then as we were discussing earlier, just the power performance ratio, right? So if you're bringing down your power and cooling costs, if these machines are just more efficient overall, then you should see some gains there as well. So, you know, I think the key is looking at what's the total cost of ownership over, you know, a standard like a three-year period or something and what you're going to get out of it for your number of sessions, the performance for the sessions, and the overall efficiency of the machines. >> So just just to be clear with these Dell PowerEdge servers, you were able to validate world record performance. But this isn't, if you, if you look at CPU architecture, PCIe bus architecture, memory, you know, the class of memory, the class of RAID controller, the class of NIC. Those were not all state of the art in terms of at least what has been recently announced. Correct? >> Right. >> Because (indistinct) the PCI 4.0, So to your point- world records with that, you've got next-gen RAID controllers coming out, and NICs coming out. If the motherboard was PCIe 5, with commensurate memory, all of those things are getting better. >> Exactly, right. I mean you're, you're really you're just eliminating bandwidth constraints latency constraints, you know, all of that should be improved. NVMe, you know, just collectively all these things just open the doors, you know, letting more bandwidth through reducing all the latency. Those are, those are all pieces of the puzzle, right? That come together and it's all about finding the weakest link and eliminating it. And I think we're reaching the point where we're removing the biggest constraints from the systems. >> Okay. So I guess is it fair to summarize to say that with this infrastructure that you tested, you were able to set world records. This, during this year, I mean, over the next several months, things are just going to get faster and faster and faster and faster. >> That's what I would anticipate, exactly, right. If they're setting world records with these machines before some of the components are, you know, the absolute latest, it seems to me we're going to just see a continuing trend there, and more and more records should fall. So I'm really looking forward to seeing how that goes, 'cause it's already good and I think the return on investment is pretty good there. So I think it's only going to get better as these roll out. >> So let me ask you a question that's a little bit off topic. >> Okay. >> Kind of, you know, we see these gains, you know, we're all familiar with Moore's Law, we're familiar with, you know, the advancements in memory and bus architecture and everything else. We just covered SuperCompute 2022 in Dallas a couple of weeks ago. And it was fascinating talking to people about advances in AI that will be possible with new architectures. You know, most of these supercomputers that are running right now are n minus 1 or n minus 2 infrastructure, you know, they're, they're, they're PCI 3, right. And maybe two generations of processors old, because you don't just throw out a 100,000 CPU super computing environment every 18 months. It doesn't work that way. >> Exactly. >> Do you have an opinion on this question of the qualitative versus quantitative increase in computing moving forward? And, I mean, do you think that this new stuff that you're starting to do tests on is going to power a fundamental shift in computing? Or is it just going to be more consolidation, better power consumption? Do you think there's an inflection point coming? What do you think? >> That's a great question. That's a hard one to answer. I mean, it's probably a little bit of both, 'cause certainly there will be better consolidation, right? But I think that, you know, the systems, it works both ways. It just allows you to do more with less, right? And you can go either direction, you can do what you're doing now on fewer machines, you know, and get better value for it, or reduce your footprint. Or you can go the other way and say, wow, this lets us add more machines into the mix and take our our level of performance from here to here, right? So it just depends on what your focus is. Certainly with, with areas like, you know, HPC and AI and ML, having the ability to expand what you already are capable of by adding more machines that can do more is going to be your main concern. But if you're more like a small to medium sized business and the opportunity to do what you were doing on, on a much smaller footprint and for lower costs, that's really your goal, right? So I think you can use this in either direction and it should, should pay back in a lot of dividends. >> Yeah. Thanks for your thoughts. It's an interesting subject moving forward. You know, sometimes it's easy to get lost in the minutiae of the bits and bites and bobs of all the components we're studying, but they're powering something that that's going to effect effectively all of humanity as we move forward. So what else do we need to consider when it comes to what you've just validated in the virtualization testing? Anything else, anything we left out? >> I think we hit all the key points, or most of them it's, you know, really, it's just keeping in mind that it's all about the full system, the components not- you know, the processor is a obviously a key, but just removing blockages, right? Freeing up, getting rid of latency, improving bandwidth, all these things come to play. And then the power performance, as I said, I know I keep coming back to that but you know, we just, and a lot of what we work on, we just see that businesses, that's a really big concern for businesses and finding efficiency, right? And especially in an age of constrained budgets, that's a big deal. So, it's really important to have that power performance ratio. And that's one of the key things we saw that stood out to us in, in some of these benchmarks, so. >> Well, it's a big deal for me. >> It's all good. >> Yeah, I live in California and I know exactly how much I pay for a kilowatt hour of electricity. >> I bet, yeah. >> My friends in other places don't even know. So I totally understand the power constraint question. >> Yeah, it's not going to get better, so, anything you can do there, right? >> Yeah. Well Evan, this has been great. Thanks for sharing the results that Prowess has come up with, third party validation that, you know, even without the latest and greatest components in all categories, Dell PowerEdge servers are able to set world records. And I anticipate that those world records will be broken in 2023 and I expect that Prowess will be part of that process, So Thanks for that. For the rest of us- >> (indistinct) >> Here at theCUBE, I want to thank you for joining us. Stay tuned for continuing coverage of AMD's fourth generation EPYC launch, for myself and for Evan Touger. Thanks so much for joining us. (upbeat music)

Published Date : Dec 8 2022

SUMMARY :

Welcome to theCUBE's Hi, great to be here. to a lot of other companies, and dive in. that you were focused on in this study? you know, how do companies evaluate that? all the way through to VDI looking under the covers to see, you know, you know, chasing the bottlenecks. But all of that just leads you Yeah, that's right. you know, makes us really- (indistinct) are looking at, you know, and what did those interconnect and the R 7515 as well as So, you know, the newer To see continued, you know, is that right? Exactly, yeah, there you go. With Broadcom, you There you go. the bang for your buck, to pricing without knowing, you know, PCIe bus architecture, memory, you know, So to your point- world records with that, just open the doors, you know, with this infrastructure that you tested, components are, you know, So let me ask you a question that's we're familiar with, you know, and the opportunity to do in the minutiae of the or most of them it's, you know, really, it's a big deal for me. for a kilowatt hour of electricity. So I totally understand the third party validation that, you know, I want to thank you for joining us.

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Joe Croney, Arc XP | AWS re:Invent 2022


 

(upbeat sparkling music) >> Hello everyone and welcome back to our wall-to-wall coverage of AWS re:Invent. We are live from the show floor here in fabulous Las Vegas, Nevada. My name is Savannah Peterson, here with my cohost John Furrier on theCUBE. John, end of day three. You're smiling. >> Yeah. >> You're still radiating energy. Is it, is it the community that's keeping your, your level up? >> It's just all the action. We've got a great special guest joining us for the first time on theCUBE. It's going to be great and Serverless wave is hitting. More and more Serverless embedded into the like, things like analytics, are going to make things tightly integrated. You can see a lot more kind of tightly coupled but yet still cohesive elements together being kind of end-to-end, and again, the, the zero-ELT vision is soon to be here. That and security, major news here at Amazon. Of course, this next segment is going to be awesome, about the modernization journey. We're going to hear a lot about that. >> Yeah, we are, and our next guest is also an extraordinarily adventurous one. Please welcome Joe from Arc XP. Thank you so much for being here. >> Thanks for having me. >> Savannah: How this show going for you? >> It's been great and you know, it's the end of the day but there's so much great energy at the show this year. >> Savannah: There really is. >> It's great walking the halls, seeing the great engineers, the thought leaders, including this session. So, it's been really a stimulating time. >> What do you do at Arc, what do you, what's your role? >> So, I'm Vice President of Technology and Product Development. I recently joined Arc to lead all the product development teams. We're an experience platform, so, in that platform we have content tools, we have delivery tools, we have subscription tools. It's a really exciting time in all those spaces. >> John: And your customer base is? >> Our customers today started with publishers. So, Arc XP was built for the Washington Post's internal needs many years ago and word got out about how great it was, built on top of the AWS tech stack and other publishers came and started licensing the software. We've moved from there to B2C commerce as well as enterprise scenarios. >> I think that's really interesting and I want to touch on your background a little bit here. You just mentioned the Washington Post. You have a background in broadcast. What was it, since you, since you are fresh, what was it that attracted you to Arc? What made you say yes? >> Yeah, so I spent a little under 10 years building the Associated Press Broadcast Newsroom Tools, some of them that you have used for many years, and you know, one of the things that was really exciting about joining ARC, was they were cloud native and they were cloud native from the start and so that really gave them a leg up with how quickly they could innovate, and now we see developers here at re:Invent be able to do custom Lambdas and new extensibility points in a way that, really, no one else can do in the CMS space >> Which, which is very exciting. Let's talk a little bit about your team and the development cycle. We've touched a lot on the economic uncertainty right now. How are things internally? What's the culture pulse? >> Yeah, so the return to work has been a thing for us, just like- >> Savannah: Are you back in office? >> All of them. We actually have a globally distributed team, and so, if you happen to be lucky enough to be in Washington, DC or Chicago or some of our other centers, there's an opportunity to be in the office, but most of our engineers work remotely. One of the exciting things we did earlier this year was ARC week. We brought everyone to DC to see each other face-to-face, and that same energy you see at re:Invent, was there in person with our engineers. >> I believe that. So, I'm a marketer by trade. I love that you're all about the digital experience. Are you creating digital- I mean everyone needs some sort of digital experience. >> Joe: Yes. >> Every company is a technology company now. Do you work across verticals? You see more niche or industry specific? >> Yeah, so we began with a very large vertical of media and broadcast. >> Savannah: There's a couple companies in that category. >> There's a couple big ones out there. >> Savannah: Yeah, yeah, yeah. >> And actually their challenges are really high volume production of great digital storytelling, and so, solving their problems has enabled us to have a platform that works for anyone that needs to tell a story digitally, whether it's a commerce site, corporate HR department. >> Savannah: Which is everyone, right? >> Virtually everyone needs to get their story out today. >> Yeah. Yeah. >> And so we have gone to a bunch of other verticals and we've seen the benefits of having that strong, cloud-based platform offer the scale that all storytellers need. >> What are some of the challenges today that aren't, that weren't there a decade ago or even five years ago? We see a lot of media companies looking at the business model innovations, changing landscapes omnichannel distribution, different formats. What's some of the challenges that's going on in content? >> So, you know, content challenges include both production of content and delivery of that content through a great experience. So different parts of ARC focus on those problems and you got to monetize it as well, but what I'd say is unique to Arc and the challenge we talk to our customers about a lot is multi-format production. So, it's not just about one channel. >> Savannah: Right. It's about telling a story and having it go across multi-channels, multi-sites, and having the infrastructure both technically and in the workflow tools, is super critical for our customers and it is a challenge that we receive well. >> A lot of AI is coming into the conversation here. Data, AI, publishing, video, user generated content. It's all data. >> Absolutely, yep. >> It's all data. >> Joe: It's an immense amount of data. >> How do you look at the data plane or the data layer, the data aspect of the platform and what are some of the customers leaning into or are kicking the tires around? What are some of the trends, and what are some of the core issues you see? >> Yeah, so I've spent a lot of time in data ML and analytics looking at giant data sets, and you know, when you look at CMS systems and experience platforms, the first class that it's in, is really the, the documents themselves. What is the story you're saying? But where the rich data is that we can analyze is user behaviors, global distribution of content, how we optimize our CDN and really give a personal experience to the reader, but beyond that, we see a lot of advantages in our digital asset management platform, which is for video, audio, photos, all kinds of media formats, and applying AIML to do detection, suggest photos that might be appropriate based on what a journalist or a marketer is writing in their story. So, there's a lot of opportunities around that sort of data. >> What are some of the business model changes that you're seeing? 'Cause remember we're in digital, Page view advertising has gone down, subscription firewalls on blogs. You got things like Substack emerging. Journalists are kind of like changing. I've seen companies go out of business, some of the media companies or change, some of the small ones go out of business, the bigger ones are evolving. What are some of the business model enablements that you guys see coming, that a platform could deliver, so that a company can value their content, and their talent? >> For sure. I mean this is a perennial question in the media space, right? It's been going on for two decades. >> I was going to say we're- >> Right. >> So it's like- >> Joe: Right, and so we've seen that play out- >> John: Little softball for you. >> Really for almost every format. It's a softball, but- >> It's day three. >> How are we addressing that? You know what, first and foremost, you got to do great storytelling, so, we have tools for that, but then presenting that story, and a great experience no matter what device you're on, that's going to be critical no matter how you're monetizing it, and so, you know, we have customers that go very ad heavy. We also have a subscription platform that can do that built into our infrastructure. >> 50 million plus registered users, correct? >> Yeah, it's unbelievable to scale. Really, Arc is a growth story, and so we went from serving the Washington Post needs, to over 2000 sites today, across 25 countries. >> Very- >> How do we get to that? How do we get that audience if we want to? Can we join that network? Is it a network of people? >> I love that question. >> Of people that are using Arc XP? >> Yeah. >> Actually, we recently launched a new effort around our community, so I think they actually had a meeting yesterday, and so that's one way to get involved, but as you said, everyone needs to have a site and tell great stories. >> Yeah. >> So, we see a wide appeal for our platform, and what's unique about ARC, is it's truly a SaaS model. This is delivered via SaaS, where we take care of all of the services, over a hundred Amazon services, behind the scenes- >> Wow. >> Built into Arc. We manage all of that for our customers, including the CDN. So, it's not as though as our customers have to be making sure the site is up, we've got teams to take care of that 24/7 >> Great value proposition and a lot of need for this, people doing their own media systems themselves. What's the secret sauce to your success? If you had to kind of look at the technology? I see serverless is a big part of it on the EDB stack. What's the, what's the secret sauce? >> I think the secret sauce comes from the roots that Arc has in the Washington Post >> You understand it. >> And some of the most challenging content production workflows anywhere in the world, and I've spent a lot of time, in many newsrooms. So, I think that knowledge, the urgency of what it takes to get a story out, the zero tolerance for the site going down. That DNA really enables our engineers to do great solutions. >> Talk about understanding your user. I mean that that's, and drinking the Kool-Aid, but in a totally amazing way. One of the other things that stuck out to me in doing my research is not only are you a service used, now, by 50 million subscribers, but beyond that, you pride yourself on being a turnkey solution. Folks can get Arc up and running quite quickly. Correct? >> For sure. So, one of the things we built into Arc XP is something called Themes, which has a bunch of pre-built blocks, that our customers don't have to end up with a custom codebase when they've developed a new experience platform. That's not a good solution, of every site be a custom codebase. We're a product with extensibility hooks. >> Savannah: Right. >> That really enables someone to get started very quickly, and that also includes bringing in content from other platforms into Arc, itself. So that journey of migrating a site is really smooth with our toolset. >> What's the history of the company? Is it, did it come from the Washington Post or was that it's original customer? What's the DNA of the firm? >> Yeah, so it was originally built by the Washington Post for the Washington Post. So, designed by digital storytellers, for storytelling. >> Savannah: And one of the largest media outlets out there. >> So, that's that "DNA", the "special sauce". >> Yeah, yeah. >> So that's where that connection is. >> That really is where it comes through. >> John: Awesome. Congratulations on- >> Now today, you know, those roots are still apparent, but we've been very responsive to other needs in the markets around commerce. There's a whole other set of DNA we've brought in, experts in understanding different systems for inventory management, so we can do a great experience on top of some of those legacy platforms. >> My final question, before we go to the challenge- >> Savannah: To the challenge. >> Is, what's next? What's on the roadmap as you look at the technology and the teams that you're managing? What's some of the next milestone or priorities for your business? >> So, it is really about growth and that's the story of Arc XP, which has driven our technology decisions. So, our choice to go serverless was driven by growth and need to make sure we had exceptional experience but most importantly that our engineers could be focused on product development and responding to what the market needed. So, that's why I'd say next year is about, it's enabling our engineers to keep up with the scaling business but still provide great value on the roadmap. >> And it's not like there's ever going to be a shortage of content or stories that need to be told. So I suspect there's a lot of resilience in what you're doing. >> And we hope to be inspired with new ways of telling stories. >> Yeah. >> So if you're in the Washington Post or other media outlets. >> John: Or theCUBE. >> Joe: Or theCUBE. >> Savannah: I know, I was just- >> There's just great formats out there. >> Best dev meeting, let's chat after, for sure. >> Exactly, that's what I've been thinking the whole time. I'm sure the wheels are turning over on this side- >> So great to have you on. >> In a lot of different ways. So, we have a new tradition here at re:Invent, where we are providing you with an opportunity for quite a sizzle reel, Instagram video, 30 second, thought leadership soundbite. What is your hot take, key theme or most important thing that you are thinking about since we're here at this year's show? >> I would say it's the energy that's building in the industry, getting back together, the collaboration, and how that's resulting in us using new technologies. You know, the conversation's no longer about shifting to the cloud. We all have huge infrastructure, the conversation's about observability, how do we know what's going in? How do we make sure we're getting the most value for our customers with those, that technology set. So, I think the energy around that is super exciting. I've always loved building products. So, next year think it's going to be a great year with that, putting together these new technologies. >> I think you nailed it. The energy really is the story and the collaboration. Joe, thank you so much for being here and sharing your story. Arc is lucky to have you and we'll close with one personal anecdote. Favorite place to sail? >> Favorite place to sail. So, I lived in the Caribbean for many years, as we were talking about earlier >> None of us are jealous up here at all. >> And so my favorite place to sail would be in the British Virgin Islands, which was closed during Covid but is now back open, so, if any you've had a chance to go to the BVI, make some time, hop on Catamaran, there's some great spots. >> Well, I think you just gave us a catalyst for our next vacation, maybe a team off-site. >> Bucket list item, of course. >> Yeah, yeah. >> Yeah, Let's bring everyone together. >> Here we go. I love it. Well Joe, thanks so much again for being on the show. We hope to have you back on theCUBE again sometime soon, and thank all of you for tuning in to this scintillating coverage that we have here, live from the AWS re:Invent show floor in Las Vegas, Nevada with John Furrier. I'm Savannah Peterson. This is theCUBE, the leader in high tech coverage. (upbeat music)

Published Date : Dec 1 2022

SUMMARY :

We are live from the show floor Is it, is it the community that's for the first time on theCUBE. Yeah, we are, and energy at the show this year. the thought leaders, the product development teams. and started licensing the software. You just mentioned the Washington Post. and the development cycle. One of the exciting things we did the digital experience. Do you work across verticals? Yeah, so we began with companies in that category. and so, solving their to get their story out today. offer the scale that What are some of the and the challenge we talk and having the infrastructure both into the conversation here. What is the story you're saying? What are some of the in the media space, right? It's a softball, but- and so, you know, we have the Washington Post needs, and so that's one way to get involved, services, behind the scenes- customers, including the CDN. What's the secret sauce to your success? And some of the most One of the other things So, one of the things we built into Arc XP and that also includes bringing in content for the Washington Post. Savannah: And one of the the "special sauce". John: Awesome. to other needs in the and that's the story of Arc XP, that need to be told. And we hope to be So if you're in the Washington Post chat after, for sure. I'm sure the wheels are that you are thinking about in the industry, getting back Arc is lucky to have you So, I lived in the in the British Virgin Islands, Well, I think you again for being on the show.

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Bich Le, Platform9 Cloud Native at Scale


 

>>Welcome back everyone, to the special presentation of Cloud Native at scale, the Cube and Platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here with Bickley, who's the chief architect and co-founder of Platform nine Pick. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or later, earlier when OpenStack was going. Great to see you and great to see congratulations on the success of Platform nine. Thank >>You very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now has realized, and you've seen what Docker's doing with the new docker, the open source Docker now just a success Exactly. Of containerization. Right? And now the Kubernetes layer that we've been working on for years is coming, Bearing fruit. This is huge. >>Exactly, Yes. >>And so as infrastructure, as code comes in, we talked to Bacar, talking about Super Cloud. I met her about, you know, the new Arlon, our, our lawn you guys just launched, the infrastructure's code is going to another level, and then it's always been DevOps infrastructure is code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon. Connect the dots for us. What is the state of infrastructures code today? >>So I think, I think I'm, I'm glad you mentioned it. Everybody or most people know about infrastructures code, but with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure is configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D. Instead, with Kubernetes, you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specify. So I think it's, it's a even better version of infrastructures code. Yeah, >>Yeah. And, and that really means it's developer just accessing resources. Okay. That declare, Okay, give me some compute, stand me up some, turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean now with open source, so popular, you don't have to have to write a lot of code, this code being developed. And so it's into integrations, configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you've got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these new, new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space. That's, >>I wrote a LinkedIn post today, it was comments about, you know, hey, enterprise is the new breed, the trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your >>View? It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we tried to do with this new project. Arlon. >>Yeah. So, so we're gonna get into our line in a second. I wanna get into the why Arlon. You guys announced that at our GoCon, which was put on here in Silicon Valley at the, at the community invite in two where they had their own little day over there at their headquarters. But before we get there, vascar, your CEO came on and he talked about Super Cloud at our in AAL event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system, so of deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection to the internet at the, the layer too is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, it's gonna continue. >>It's interesting. I just, when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on a rise. We've remember pointing for many years now, that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a serviced layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd want to have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in in this community of, of co con, which we will be covering. So that brings up the whole what's next? You guys just announced Arlon at ar GoCon, which came out of Intuit. We've had Mariana Tessel at our super cloud event. She's the cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why arlon, why this announcement? Yeah, >>So the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and, you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built our lawn and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, >>And what's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, so let's get into what that means for up above and below the, the, this abstraction or thin layer below as the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads. At the end of the day, you, I talk to CXOs and IT folks that, that are now DevOps engineers. They care about the workloads and they want the infrastructure's code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened to need observability and they need to, to know that it's working. That's right. And here's my workloads running effectively. So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, right? >>So workloads, so Kubernetes has defined kind of a standard way to describe workloads and you can, you know, tell Kubernetes, I wanna run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem, like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases it is like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's coming like an EC two instance, spin up a cluster. We very, people used words like that. >>That's right. And before arlon you kind of had to do all of that using a different set of tools as, as I explained. So with Arlon you can kind of express everything together. You can say I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call a profile. And then you can stamp out your app, your applications and your clusters and manage them in a very, >>So essentially standard like creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook, deploy it. Now what there between say a script like I'm, I have scripts, I can just automate scripts >>Or yes, this is where that declarative API and infrastructures configuration comes in, right? Because scripts, yes you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things got controllers which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure has configuration is built kind of on it's super set of infrastructures code because it's >>An evolution. >>You need edge re's code, but then you can configure the code by just saying do it. You basically declaring it's saying Go, go do that. That's right. Okay, so, alright, so cloud native at scale, take me through your vision of what that means. Someone says, Hey, what does cloud native at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years. I mean people are now starting to figure out, okay, it's not as easy as it sounds. Kubernetes has value. We're gonna hear this year coan a lot of this. What does cloud native at scale mean? >>Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users there, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we try to address with Arran. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state, and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, so I'll put you on the spot. Rogue got Coan coming up and obviously this'll be shipping this segment series out before. What do you expect to see at this year? What's the big story this year? What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jogging for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time, there's ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of cub cons and I expect to continue and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, >>Well maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed, but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there are just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. >>Yeah. Vic, you've had an storied career, VMware over decades with them, obviously in 12 years with 14 years or something like that. Big number co-founder here at Platform now you's been around for a while at this game. We, man, we talked about OpenStack, that project you, we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a cloud a Rod team at that time. We would joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform Nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? Open Stack was an example where the Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will, a, platform nine will be there and we will, you know, take the innovations from the, the, the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yes. Yeah. I think the, the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart Yeah. On this segment, what is at scale, how many clusters do you see that would be a, a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you Yeah, I would you describe that when people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. Yeah. >>And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing, doing over $2 billion billions of transactions a year. And, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud Native at scale? >>The the hyper square? >>Yeah. Yeah. Abras, Azure, Google, >>You mean from a business perspective, they're, they have their own interests that, you know, that they're, they will keep catering to, They, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep Well, >>They got great I performance, I mean from a, from a hardware standpoint, yes. That's gonna be key, right? >>Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyperscalers really want to be in the game in terms of, you know, the, the new risk and arm ecosystems and the >>Platforms. Yeah. Not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, I remember our first year doing the cube. Oh, the cloud is one big distributed computer. It's, it's hardware and you got software and you got middleware. And he kinda over, well he kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. Yes, >>Exactly. >>It's, we're back in the same game. Thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super cloud Arlon open source and how to run large scale applications on the cloud, Cloud native develop for developers. And John Feer with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up.

Published Date : Oct 20 2022

SUMMARY :

Great to see you and great to see congratulations on the success And now the Kubernetes layer that we've been working on for years you know, the new Arlon, our, our lawn you guys just launched, So instead of telling the system, here's how I want my infrastructure by telling it, I mean now with open source, so popular, you don't have to have to write a lot of code, you know, the emergence of systems and layers to help you manage that complexity is becoming I wrote a LinkedIn post today, it was comments about, you know, hey, enterprise is the new breed, the trend of SaaS companies So you have this sprawl of tools. how would you look at the super cloud trend that's emerging? the way I interpret that is, you know, clouds and infrastructure, It's IBM's, you know, connection to the internet at the, this layer that has simplified, you know, computing and, the physics and the, the atoms, the pro, you know, this is where the innovation, all the variations around and, you know, compute storage networks the DevOps engineers, they get a a ways to So how do you guys look at the workload I wanna run this container this particular way, or you can It's coming like an EC two instance, spin up a cluster. So with Arlon you can kind of express And it's like a playbook, deploy it. tell the system what you want and then the system kind of figures You need edge re's code, but then you can configure the code by just saying do it. And that is just complexity for the people operating this or configuring this, What do you expect to see at this year? If you look at a stack necessary for hosting What's the, what are you most excited about as the chief architect? So the successor to Kubernetes, you know, I don't I think the, the reigning in the chaos is key, you know, Now we have now visibility into But roughly speaking when we say, you know, What's the role the cloud play in the cloud Native at scale? you know, that they're, they will keep catering to, They, they will continue to find right? terms of, you know, the, the new risk and arm ecosystems It's, it's hardware and you got software and you got middleware. Thank you for coming on the segment.

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>>Everyone, welcome to the cube here in Palo Alto, California for a special presentation on Cloud native at scale, enabling super cloud modern applications with Platform nine. I'm John Furry, your host of The Cube. We've got a great lineup of three interviews we're streaming today. Mattor Makki, who's the co-founder and VP of Product of Platform nine. She's gonna go into detail around Arlon, the open source products, and also the value of what this means for infrastructure as code and for cloud native at scale. Bickley the chief architect of Platform nine Cube alumni. Going back to the OpenStack days. He's gonna go into why Arlon, why this infrastructure as code implication, what it means for customers and the implications in the open source community and where that value is. Really great wide ranging conversation there. And of course, Vascar, Gort, the CEO of Platform nine, is gonna talk with me about his views on Super Cloud and why Platform nine has a scalable solutions to bring cloud native at scale. So enjoy the program, see you soon. Hello and welcome to the cube here in Palo Alto, California for a special program on cloud native at scale, enabling next generation cloud or super cloud for modern application cloud native developers. I'm John Forry, host of the Cube. Pleasure to have here me Makowski, co-founder and VP of product at Platform nine. Thanks for coming in today for this Cloudnative at scale conversation. >>Thank you for having >>Me. So Cloudnative at scale, something that we're talking about because we're seeing the, the next level of mainstream success of containers Kubernetes and cloud native develop, basically DevOps in the C I C D pipeline. It's changing the landscape of infrastructure as code, it's accelerating the value proposition and the super cloud as we call it, has been getting a lot of traction because this next generation cloud is looking a lot different, but kind of the same as the first generation. What's your view on Super cloud as it fits to cloud native as scales up? >>Yeah, you know, I think what's interesting, and I think the reason why Super Cloud is a really good and a really fit term for this, and I think, I know my CEO was chatting with you as well, and he was mentioning this as well, but I think there needs to be a different term than just multi-cloud or cloud. And the reason is because as cloud native and cloud deployments have scaled, I think we've reached a point now where instead of having the traditional data center style model, where you have a few large distributors of infrastructure and workload at a few locations, I think the model is kind of flipped around, right? Where you have a large number of micro sites. These micro sites could be your public cloud deployment, your private on-prem infrastructure deployments, or it could be your edge environment, right? And every single enterprise, every single industry is moving in that direction. And so you gotta rougher that with a terminology that, that, that indicates the scale and complexity of it. And so I think super cloud is a, is an appropriate term for >>That. So you brought a couple things I want to dig into. You mentioned Edge Notes. We're seeing not only edge nodes being the next kind of area of innovation, mainly because it's just popping up everywhere. And that's just the beginning. Wouldn't even know what's around the corner. You got buildings, you got iot, o ot, and it kind of coming together, but you also got this idea of regions, global infrastructures, big part of it. I just saw some news around cloud flare shutting down a site here, there's policies being made at scale. These new challenges there. Can you share because you can have edge. So hybrid cloud is a winning formula. Everybody knows that it's a steady state. Yeah. But across multiple clouds brings in this new un engineered area, yet it hasn't been done yet. Spanning clouds. People say they're doing it, but you start to see the toe in the water, it's happening, it's gonna happen. It's only gonna get accelerated with the edge and beyond globally. So I have to ask you, what is the technical challenges in doing this? Because it's something business consequences as well, but there are technical challenge. Can you share your view on what the technical challenges are for the super cloud across multiple edges and >>Regions? Yeah, absolutely. So I think, you know, in in the context of this, the, this, this term of super cloud, I think it's sometimes easier to visualize things in terms of two access, right? I think on one end you can think of the scale in terms of just pure number of nodes that you have, deploy number of clusters in the Kubernetes space. And then on the other access you would have your distribution factor, right? Which is, do you have these tens of thousands of nodes in one site or do you have them distributed across tens of thousands of sites with one node at each site? Right? And if you have just one flavor of this, there is enough complexity, but potentially manageable. But when you are expanding on both these access, you really get to a point where that skill really needs some well thought out, well-structured solutions to address it, right? A combination of homegrown tooling along with your, you know, favorite distribution of Kubernetes is not a strategy that can help you in this environment. It may help you when you have one of this or when you, when you scale, is not at the level. >>Can you scope the complexity? Because I mean, I hear a lot of moving parts going on there, the technology's also getting better. We we're seeing cloud native become successful. There's a lot to configure, there's a lot to install. Can you scope the scale of the problem? Because we're talking about at scale Yep. Challenges here. >>Yeah, absolutely. And I think, you know, I I like to call it, you know, the, the, the problem that the scale creates, you know, there's various problems, but I think one, one problem, one way to think about it is, is, you know, it works on my cluster problem, right? So, you know, I come from engineering background and there's a, you know, there's a famous saying between engineers and QA and the support folks, right? Which is, it works on my laptop, which is I tested this change, everything was fantastic, it worked flawlessly on my machine, on production, It's not working. The exact same problem now happens and these distributed environments, but at massive scale, right? Which is that, you know, developers test their applications, et cetera within the sanctity of their sandbox environments. But once you expose that change in the wild world of your production deployment, right? >>And the production deployment could be going at the radio cell tower at the edge location where a cluster is running there, or it could be sending, you know, these applications and having them run at my customer's site where they might not have configured that cluster exactly the same way as I configured it, or they configured the cluster, right? But maybe they didn't deploy the security policies or they didn't deploy the other infrastructure plugins that my app relies on all of these various factors at their own layer of complexity. And there really isn't a simple way to solve that today. And that is just, you know, one example of an issue that happens. I think another, you know, whole new ball game of issues come in the context of security, right? Because when you are deploying applications at scale in a distributed manner, you gotta make sure someone's job is on the line to ensure that the right security policies are enforced regardless of that scale factor. So I think that's another example of problems that occur. >>Okay. So I have to ask about scale because there are a lot of multiple steps involved when you see the success cloud native, you know, you see some, you know, some experimentation. They set up a cluster, say it's containers and Kubernetes, and then you say, Okay, we got this, we can configure it. And then they do it again and again, they call it day two. Some people call it day one, day two operation, whatever you call it. Once you get past the first initial thing, then you gotta scale it. Then you're seeing security breaches, you're seeing configuration errors. This seems to be where the hotpot is. And when companies transition from, I got this to, Oh no, it's harder than I thought at scale. Can you share your reaction to that and how you see this playing out? >>Yeah, so, you know, I think it's interesting. There's multiple problems that occur when, you know, the, the two factors of scale is we talked about start expanding. I think one of them is what I like to call the, you know, it, it works fine on my cluster problem, which is back in, when I was a developer, we used to call this, it works on my laptop problem, which is, you know, you have your perfectly written code that is operating just fine on your machine, your sandbox environment. But the moment it runs production, it comes back with p zeros and POS from support teams, et cetera. And those issues can be really difficult to try us, right? And so in the Kubernetes environment, this problem kind of multi folds, it goes, you know, escalates to a higher degree because yeah, you have your sandbox developer environments, they have their clusters and things work perfectly fine in those clusters because these clusters are typically handcrafted or a combination of some scripting and handcrafting. >>And so as you give that change to then run at your production edge location, like say you radio sell tower site, or you hand it over to a customer to run it on their cluster, they might not have not have configured that cluster exactly how you did it, or they might not have configured some of the infrastructure plugins. And so the things don't work. And when things don't work, triaging them becomes like ishly hard, right? It's just one of the examples of the problem. Another whole bucket of issues is security, which is, is you have these distributed clusters at scale, you gotta ensure someone's job is on the line to make sure that these security policies are configured properly. >>So this is a huge problem. I love that comment. That's not not happening on my system. It's the classic, you know, debugging mentality. Yeah. But at scale it's hard to do that with error prone. I can see that being a problem. And you guys have a solution you're launching, Can you share what our lawn is, this new product, What is it all about? Talk about this new introduction. >>Yeah, absolutely. I'm very, very excited. You know, it's one of the projects that we've been working on for some time now because we are very passionate about this problem and just solving problems at scale in on-prem or at in the cloud or at edge environments. And what arwan is, it's an open source project and it is a tool, it's a Kubernetes native tool for complete end to end management of not just your clusters, but your clusters. All of the infrastructure that goes within and along the sites of those clusters, security policies, your middleware plugins, and finally your applications. So what alarm lets you do in a nutshell is in a declarative way, it lets you handle the configuration and management of all of these components in at scale. >>So what's the elevator pitch simply put for what this solves in, in terms of the chaos you guys are reigning in. What's the, what's the bumper sticker? Yeah, >>What would it do? There's a perfect analogy that I love to reference in this context, which is think of your assembly line, you know, in a traditional, let's say, you know, an auto manufacturing factory or et cetera, and the level of efficiency at scale that that assembly line brings, right online. And if you look at the logo we've designed, it's this funny little robot. And it's because when we think of online, we, we think of these enterprise large scale environments, you know, sprawling at scale creating chaos because there isn't necessarily a well thought through, well structured solution that's similar to an assembly line, which is taking each components, you know, addressing them, manufacturing, processing them in a standardized way, then handing to the next stage. But again, it gets, you know, processed in a standardized way. And that's what Arlon really does. That's like the I pitch. If you have problems of scale of managing your infrastructure, you know, that is distributed. Arlon brings the assembly line level of efficiency and consistency >>For those. So keeping it smooth, the assembly on things are flowing. C C I CD pipelining. Exactly. So that's what you're trying to simplify that ops piece for the developer. I mean, it's not really ops, it's their ops, it's coding. >>Yeah. Not just developer, the ops, the operations folks as well, right? Because developers, you know, there is, the developers are responsible for one picture of that layer, which is my apps, and then maybe that middleware of application that they interface with, but then they hand it over to someone else who's then responsible to ensure that these apps are secure properly, that they are logging, logs are being collected properly, monitoring and observability integrated. And so it solves problems for both those >>Teams. Yeah. It's DevOps. So the DevOps is the cloud native developer. The OP teams have to kind of set policies. Is that where the declarative piece comes in? Is that why that's important? >>Absolutely. Yeah. And, and, and, and you know, Kubernetes really in introduced or elevated this declarative management, right? Because, you know, c communities clusters are Yeah. Or your, yeah, you know, specifications of components that go in Kubernetes are defined in a declarative way. And Kubernetes always keeps that state consistent with your defined state. But when you go outside of that world of a single cluster, and when you actually talk about defining the clusters or defining everything that's around it, there really isn't a solution that does that today. And so online addresses that problem at the heart of it, and it does that using existing open source well known solutions. >>Ed, do I wanna get into the benefits? What's in it for me as the customer developer? But I want to finish this out real quick and get your thoughts. You mentioned open source. Why open source? What's the, what's the current state of the product? You run the product group over at platform nine, is it open source? And you guys have a product that's commercial? Can you explain the open source dynamic? And first of all, why open source? Yeah. And what is the consumption? I mean, open source is great, People want open source, they can download it, look up the code, but maybe wanna buy the commercial. So I'm assuming you have that thought through, can you share open source and commercial relationship? >>Yeah, I think, you know, starting with why open source? I think it's, you know, we as a company, we have, you know, one of the things that's absolutely critical to us is that we take mainstream open source technologies components and then we, you know, make them available to our customers at scale through either a SaaS model on from model, right? But, so as we are a company or startup or a company that benefits, you know, in a massive way by this open source economy, it's only right, I think in my mind that we do our part of the duty, right? And contribute back to the community that feeds us. And so, you know, we have always held that strongly as one of our principles. And we have, you know, created and built independent products starting all the way with fi, which was a serverless product, you know, that we had built to various other, you know, examples that I can give. But that's one of the main reasons why opensource and also opensource because we want the community to really firsthand engage with us on this problem, which is very difficult to achieve if your product is behind a wall, you know, behind, behind a block box. >>Well, and that's, that's what the developers want too. I mean, what we're seeing in reporting with Super Cloud is the new model of consumption is I wanna look at the code and see what's in there. That's right. And then also, if I want to use it, I, I'll do it. Great. That's open source, that's the value. But then at the end of the day, if I wanna move fast, that's when people buy in. So it's a new kind of freemium, I guess, business model. I guess that's the way that, Well, but that's, that's the benefit. Open source. This is why standards and open source is growing so fast. You have that confluence of, you know, a way for helpers to try before they buy, but also actually kind of date the application, if you will. We, you know, Adrian Karo uses the dating me metaphor, you know, Hey, you know, I wanna check it out first before I get married. Right? And that's what open source, So this is the new, this is how people are selling. This is not just open source, this is how companies are selling. >>Absolutely. Yeah. Yeah. You know, I think, and you know, two things. I think one is just, you know, this, this, this cloud native space is so vast that if you, if you're building a close flow solution, sometimes there's also a risk that it may not apply to every single enterprises use cases. And so having it open source gives them an opportunity to extend it, expand it, to make it proper to their use case if they choose to do so, right? But at the same time, what's also critical to us is we are able to provide a supported version of it with an SLA that we, you know, that's backed by us, a SAS hosted version of it as well, for those customers who choose to go that route, you know, once they have used the open source version and loved it and want to take it at scale and in production and need, need, need a partner to collaborate with, who can, you know, support them for that production >>Environment. I have to ask you now, let's get into what's in it for the customer. I'm a customer, why should I be enthused about Arlo? What's in it for me? You know? Cause if I'm not enthused about it, I'm not gonna be confident and it's gonna be hard for me to get behind this. Can you share your enthusiastic view of, you know, why I should be enthused about Arlo customer? >>Yeah, absolutely. And so, and there's multiple, you know, enterprises that we talk to, many of them, you know, our customers, where this is a very kind of typical story that you hear, which is we have, you know, a Kubernetes distribution. It could be on premise, it could be public clouds, native es, and then we have our C I CD pipelines that are automating the deployment of applications, et cetera. And then there's this gray zone. And the gray zone is well before you can you, your CS CD pipelines can deploy the apps. Somebody needs to do all of their groundwork of, you know, defining those clusters and yeah. You know, properly configuring them. And as these things, these things start by being done hand grown. And then as the, as you scale, what typically enterprises would do today is they will have their home homegrown DIY solutions for this. >>I mean, the number of folks that I talk to that have built Terra from automation, and then, you know, some of those key developers leave. So it's a typical open source or typical, you know, DIY challenge. And the reason that they're writing it themselves is not because they want to. I mean, of course technology is always interesting to everybody, but it's because they can't find a solution that's out there that perfectly fits the problem. And so that's that pitch. I think Spico would be delighted. The folks that we've talked, you know, spoken with, have been absolutely excited and have, you know, shared that this is a major challenge we have today because we have, you know, few hundreds of clusters on s Amazon and we wanna scale them to few thousands, but we don't think we are ready to do that. And this will give us >>Stability. Yeah, I think people are scared, not sc I won't say scare, that's a bad word. Maybe I should say that they feel nervous because, you know, at scale small mistakes can become large mistakes. This is something that is concerning to enterprises. And, and I think this is gonna come up at co con this year where enterprises are gonna say, Okay, I need to see SLAs. I wanna see track record, I wanna see other companies that have used it. Yeah. How would you answer that question to, or, or challenge, you know, Hey, I love this, but is there any guarantees? Is there any, what's the SLAs? I'm an enterprise, I got tight, you know, I love the open source trying to free fast and loose, but I need hardened code. >>Yeah, absolutely. So, so two parts to that, right? One is Arlan leverages existing open source components, products that are extremely popular. Two specifically. One is Lon uses Argo cd, which is probably one of the highest rated and used CD open source tools that's out there, right? It's created by folks that are as part of Intuit team now, you know, really brilliant team. And it's used at scale across enterprises. That's one. Second is arlon also makes use of cluster api capi, which is a ES sub-component, right? For lifecycle management of clusters. So there is enough of, you know, community users, et cetera, around these two products, right? Or, or, or open source projects that will find Arlan to be right up in their alley because they're already comfortable, familiar with algo cd. Now Arlan just extends the scope of what Algo CD can do. And so that's one. And then the second part is going back to a point of the comfort. And that's where, you know, Platform nine has a role to play, which is when you are ready to deploy Alon at scale, because you've been, you know, playing with it in your DEF test environments, you're happy with what you get with it, then Platform nine will stand behind it and provide that sla. >>And what's been the reaction from customers you've talked to Platform nine customers with, with, that are familiar with, with Argo and then Arlo? What's been some of the feedback? >>Yeah, I, I, I think the feedback's been fantastic. I mean, I can give you examples of customers where, you know, initially, you know, when you are, when you're telling them about your entire portfolio of solutions, it might not strike a card right away. But then we start talking about Arlan and, and we talk about the fact that it uses Argo CD and they start opening up, they say, We have standardized on Argo and we have built these components, homegrown, we would be very interested. Can we co-develop? Does it support these use cases? So we've had that kind of validation. We've had validation all the way at the beginning of our line before we even wrote a single line of code saying this is something we plan on doing. And the customer said, If you had it today, I would've purchased it. So it's been really great validation. >>All right. So next question is, what is the solution to the customer? If I asked you, Look it, I have, I'm so busy, my team's overworked. I got a skills gap. I don't need another project that's, I'm so tied up right now and I'm just chasing my tail. How does Platform nine help me? >>Yeah, absolutely. So I think, you know, one of the core tenets of Platform nine has always been that we try to bring that public cloud like simplicity by hosting, you know, this in a lot of such similar tools in a SaaS hosted manner for our customers, right? So our goal behind doing that is taking away or trying to take away all of that complexity from customer's hands and offloading it to our hands, right? And giving them that full white glove treatment as we call it. And so from a customer's perspective, one, something like arlon will integrate with what they have so they don't have to rip and replace anything. In fact, it will, even in the next versions, it may even discover your clusters that you have today and, you know, give you an inventory and that, >>So customers have clusters that are growing, that's a sign correct call you guys. >>Absolutely. Either they're, they have massive large clusters, right? That they wanna split into smaller clusters, but they're not comfortable doing that today, or they've done that already on say, public cloud or otherwise. And now they have management challenges. So >>Especially operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure Yeah. And or scale out. >>That's right. Exactly. >>And you provide that layer of policy. >>Absolutely. >>Yes. That's the key value >>Here. That's right. >>So policy based configuration for cluster scale up >>Profile and policy based declarative configuration and life cycle management for clusters. >>If I asked you how this enables Super club, what would you say to that? >>I think this is one of the key ingredients to super cloud, right? If you think about a super cloud environment, there's at least few key ingredients that that come to my mind that are really critical. Like they are, you know, life saving ingredients at that scale. One is having a really good strategy for managing that scale, you know, in a, going back to assembly line in a very consistent, predictable way so that our lot solves then you, you need to compliment that with the right kind of observability and monitoring tools at scale, right? Because ultimately issues are gonna happen and you're gonna have to figure out, you know, how to solve them fast. And alon by the way, also helps in that direction, but you also need observability tools. And then especially if you're running it on the public cloud, you need some cost management tools. In my mind, these three things are like the most necessary ingredients to make Super Cloud successful. And, you know, alarm flows >>In one. Okay, so now the next level is, Okay, that makes sense. There's under the covers kind of speak under the hood. Yeah. How does that impact the app developers and the cloud native modern application workflows? Because the impact to me, seems the apps are gonna be impacted. Are they gonna be faster, stronger? I mean, what's the impact if you do all those things, as you mentioned, what's the impact of the apps? >>Yeah, the impact is that your apps are more likely to operate in production the way you expect them to, because the right checks and balances have gone through, and any discrepancies have been identified prior to those apps, prior to your customer running into them, right? Because developers run into this challenge to their, where there's a split responsibility, right? I'm responsible for my code, I'm responsible for some of these other plugins, but I don't own the stack end to end. I have to rely on my ops counterpart to do their part, right? And so this really gives them, you know, the right tooling for >>That. So this is actually a great kind of relevant point, you know, as cloud becomes more scalable, you're starting to see this fragmentation gone of the days of the full stack developer to the more specialized role. But this is a key point, and I have to ask you because if this Arlo solution takes place, as you say, and the apps are gonna be stupid, there's designed to do, the question is, what did, does the current pain look like of the apps breaking? What does the signals to the customer Yeah. That they should be calling you guys up into implementing Arlo, Argo, and, and, and on all the other goodness to automate, What are some of the signals? Is it downtime? Is it, is it failed apps, Is it latency? What are some of the things that Yeah, absolutely would be in indications of things are effed up a little bit. >>Yeah. More frequent down times, down times that are, that take longer to triage. And so you are, you know, the, you know, your mean times on resolution, et cetera, are escalating or growing larger, right? Like we have environments of customers where they, they have a number of folks on in the field that have to take these apps and run them at customer sites. And that's one of our partners. And they're extremely interested in this because the, the rate of failures they're encountering for this, you know, the field when they're running these apps on site, because the field is automating their clusters that are running on sites using their own script. So these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to reduce your, your meantime to resolution, if you're looking to reduce the number of failures that occur on your production site, that's one. And second, if you are looking to manage these at scale environments with a relatively small, focused, nimble ops team, which has an immediate impact on your, So those are, those are the >>Signals. This is the cloud native at scale situation, the innovation going on. Final thought is your reaction to the idea that if the world goes digital, which it is, and the confluence of physical and digital coming together, and cloud continues to do its thing, the company becomes the application, not where it used to be supporting the business, you know, the back office and the IIA terminals and some PCs and handhelds. Now if technology's running, the business is the business. Yeah. The company's the application. Yeah. So it can't be down. So there's a lot of pressure on, on CSOs and CIOs now and see, and boards is saying, how is technology driving the top line revenue? That's the number one conversation. Yeah. Do you see that same thing? >>Yeah. It's interesting. I think there's multiple pressures at the CXO CIO level, right? One is that there needs to be that visibility and clarity and guarantee almost that, you know, that the, the technology that's, you know, that's gonna drive your top line is gonna drive that in a consistent, reliable, predictable manner. And then second, there is the constant pressure to do that while always lowering your costs of doing it, right? Especially when you're talking about, let's say retailers or those kinds of large scale vendors, they many times make money by lowering the amount that they spend on, you know, providing those goods to their end customers. So I think those, both those factors kind of come into play and the solution to all of them is usually in a very structured strategy around automation. >>Final question. What does cloudnative at scale look like to you? If all the things happen the way we want 'em to happen, The magic wand, the magic dust, what does it look like? >>What that looks like to me is a CIO sipping at his desk on coffee production is running absolutely smooth. And his, he's running that at a nimble, nimble team size of at the most, a handful of folks that are just looking after things with things. So just >>Taking care of, and the CIO doesn't exist. There's no CSO there at the beach. >>Yeah. >>Thank you for coming on, sharing the cloud native at scale here on the cube. Thank you for your time. >>Fantastic. Thanks for having >>Me. Okay. I'm John Fur here for special program presentation, special programming cloud native at scale, enabling super cloud modern applications with Platform nine. Thanks for watching. Welcome back everyone to the special presentation of cloud native at scale, the cube and platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here at Bickley, who's the chief architect and co-founder of Platform nine b. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or well later, earlier when opens Stack was going. Great to see you and great to see congratulations on the success of platform nine. >>Thank you very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now was realized, and you've seen what Docker's doing with the new docker, the open source Docker now just a success Exactly. Of containerization, right? And now the Kubernetes layer that we've been working on for years is coming, bearing fruit. This is huge. >>Exactly. Yes. >>And so as infrastructure's code comes in, we talked to Bacar talking about Super Cloud, I met her about, you know, the new Arlon, our R lawn you guys just launched, the infrastructure's code is going to another level. And then it's always been DevOps infrastructure is code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon, connect the dots for us. What is the state of infrastructures code today? >>So I think, I think I'm, I'm glad you mentioned it, everybody or most people know about infrastructures code. But with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure as configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D instead with Kubernetes, you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specify. So I think it's, it's a even better version of infrastructures code. >>Yeah, yeah. And, and that really means it's developer just accessing resources. Okay. Not declaring, Okay, give me some compute, stand me up some, turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean now with open source, so popular, you don't have to have to write a lot of code. It's code being developed. And so it's into integration, it's configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these new, new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space that, >>That's, I wrote a LinkedIn post today was comments about, you know, hey, enterprise is the new breed, the trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your >>View? It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we try to do with this new project. Arlon. >>Yeah. So, so we're gonna get into Arlan in a second. I wanna get into the why Arlon. You guys announced that at our GoCon, which was put on here in Silicon Valley at the, at the by intu. They had their own little day over there at their headquarters. But before we get there, Vascar, your CEO came on and he talked about Super Cloud at our inaugural event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system, so to deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection for the internet at the, the layer too is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, it's gonna continue. >>It's interesting. I just really wrote another post today on LinkedIn called the Silicon Wars AMD Stock is down arm has been on rise, we've remember pointing for many years now, that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a service layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd wanna have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in, in this community of co con, which will be a covering. So that brings up the whole what's next? You guys just announced our lawn at ar GoCon, which came out of Intuit. We've had Maria Teel at our super cloud event, She's a cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why our lawn, why this announcement? Yeah, >>So the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built AR lawn and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, And >>What's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, so let's get into what that means for up above and below the, the, this abstraction or thin layer below the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads at the end of the day, and I talk to CXOs and IT folks that, that are now DevOps engineers. They care about the workloads and they want the infrastructure's code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened. They need observability and they need to, to know that it's working. That's right. And here's my workloads running effectively. So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, right? >>So workloads, so Kubernetes has defined kind of a standard way to describe workloads and you can, you know, tell Kubernetes, I want to run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem, like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases it is like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's coming like an EC two instance, spin up a cluster. We've heard people used words like that. That's >>Right. And before arlon you kind of had to do all of that using a different set of tools as, as I explained. So with AR loan you can kind of express everything together. You can say I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call the profile. And then you can stamp out your app, your applications and your clusters and manage them in a very, So >>It's essentially standard, like creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook, just deploy it. Now what there is between say a script like I'm, I have scripts, I can just automate scripts >>Or yes, this is where that declarative API and infrastructure as configuration comes in, right? Because scripts, yes you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things are controllers which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure as configuration is built kind of on, it's a super set of infrastructures code because it's >>An evolution. >>You need edge's code, but then you can configure the code by just saying do it. You basically declaring saying Go, go do that. That's right. Okay, so, alright, so cloud native at scale, take me through your vision of what that means. Someone says, Hey, what does cloud native at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years. I mean people are now starting to figure out, okay, it's not as easy as it sounds. Kubernetes has value. We're gonna hear this year at CubeCon a lot of this, what does cloud native at scale >>Mean? Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users there, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we try to address with Arran. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state, and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, so I'll put you on the spot rogue, that CubeCon coming up and now this'll be shipping this segment series out before. What do you expect to see at this year? It's the big story this year. What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jockeying for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time and there's ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of coupon and I expect to continue and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, well >>Maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there are just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. >>Yeah. Vic, you've had an storied career VMware over decades with them within 12 years with 14 years or something like that. Big number co-founder here a platform. I you's been around for a while at this game, man. We talked about OpenStack, that project we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a Cloud Aati team at that time. We would joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform Nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? Opens Stack was an example and then Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will a, platform nine will be there and we will, you know, take the innovations from the the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yes. Yeah, I think the, the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart this segment. What is at scale, how many clusters do you see that would be a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you, Yeah, how would you describe that? When people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. >>Yeah. And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing, doing over $2 billion billions of transactions a year and, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud need of its scale? >>The, the hyper squares? >>Yeah, yeah. A's Azure Google, >>You mean from a business perspective, they're, they have their own interests that, you know, that they're, they will keep catering to, they, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep well, >>They got great performance. I mean, from a, from a hardware standpoint, yes. That's gonna be key, >>Right? Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyper skaters really want to be in the game in terms of, you know, the, the new risk and arm ecosystems, the platforms. >>Yeah. Not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, I remember our first year doing the cube. Oh the cloud is one big distributed computer. It's, it's hardware and you got software and you got middleware and he kinda over, well he's kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. Yes, >>Exactly. >>It's, we're back in the same game. Thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super cloud Arlon open source and how to run large scale applications on the cloud, cloud native develop for developers. And John Furrier with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up. Hey, welcome back everyone to Super Cloud 22. I'm John Fur, host of the Cuba here all day talking about the future of cloud. Where's it all going? Making it super multi-cloud is around the corner and public cloud is winning. Got the private cloud on premise and Edge. Got a great guest here, Vascar Gorde, CEO of Platform nine, just on the panel on Kubernetes. An enabler blocker. Welcome back. Great to have you on. >>Good to see you >>Again. So Kubernetes is a blocker enabler by, with a question mark I put on on there. Panel was really to discuss the role of Kubernetes. Now great conversation operations is impacted. What's just thing about what you guys are doing at Platform nine? Is your role there as CEO and the company's position, kind of like the world spun into the direction of Platform nine while you're at the helm, right? >>Absolutely. In fact, things are moving very well and since they came to us, it was an insight to call ourselves the platform company eight years ago, right? So absolutely whether you are doing it in public clouds or private clouds, you know, the application world is moving very fast in trying to become digital and cloud native. There are many options for you to run the infrastructure. The biggest blocking factor now is having a unified platform. And that's what where we come into >>Patrick, we were talking before we came on stage here about your background and we were kind of talking about the glory days in 2000, 2001 when the first ASPs application service providers came out. Kind of a SaaS vibe, but that was kind of all kind of cloud-like >>It wasn't, >>And web services started then too. So you saw that whole growth. Now, fast forward 20 years later, 22 years later, where we are now, when you look back then to here and all the different cycles, >>In fact, you know, as we were talking offline, I was in one of those ASPs in the year 2000 where it was a novel concept of saying we are providing a software and a capability as a service, right? You sign up and start using it. I think a lot has changed since then. The tooling, the tools, the technology has really skyrocketed. The app development environment has really taken off exceptionally well. There are many, many choices of infrastructure now, right? So I think things are in a way the same but also extremely different. But more importantly now for any company, regardless of size, to be a digital native, to become a digital company is extremely mission critical. It's no longer a nice to have everybody's in the journey somewhere. >>Everyone is going digital transformation here. Even on a so-called downturn recession that's upcoming inflations sea year. It's interesting. This is the first downturn, the history of the world where the hyperscale clouds have been pumping on all cylinders as an economic input. And if you look at the tech trends, GDPs down, but not tech. Nope. Cause pandemic showed everyone digital transformation is here and more spend and more growth is coming even in, in tech. So this is a unique factor which proves that that digital transformation's happening and company, every company will need a super cloud. >>Everyone, every company, regardless of size, regardless of location, has to become modernize their infrastructure. And modernizing infrastructure is not just some, you know, new servers and new application tools. It's your approach, how you're serving your customers, how you're bringing agility in your organization. I think that is becoming a necessity for every enterprise to survive. >>I wanna get your thoughts on Super Cloud because one of the things Dave Alon and I want to do with Super Cloud and calling it that was we, I, I personally, and I know Dave as well, he can, I'll speak from, he can speak for himself. We didn't like multi-cloud. I mean not because Amazon said don't call things multi-cloud, it just didn't feel right. I mean everyone has multiple clouds by default. If you're running productivity software, you have Azure and Office 365. But it wasn't truly distributed. It wasn't truly decentralized, it wasn't truly cloud enabled. It didn't, it felt like they're not ready for a market yet. Yet public clouds booming on premise. Private cloud and Edge is much more on, you know, more, More dynamic, more unreal. >>Yeah. I think the reason why we think Super cloud is a better term than multi-cloud. Multi-cloud are more than one cloud, but they're disconnected. Okay, you have a productivity cloud, you have a Salesforce cloud, you may have, everyone has an internal cloud, right? So, but they're not connected. So you can say, okay, it's more than one cloud. So it's, you know, multi-cloud. But super cloud is where you are actually trying to look at this holistically. Whether it is on-prem, whether it is public, whether it's at the edge, it's a store at the branch. You are looking at this as one unit. And that's where we see the term super cloud is more applicable because what are the qualities that you require if you're in a super cloud, right? You need choice of infrastructure, you need, but at the same time you need a single pan or a single platform for you to build your innovations on, regardless of which cloud you're doing it on, right? So I think Super Cloud is actually a more tightly integrated orchestrated management philosophy we think. >>So let's get into some of the super cloud type trends that we've been reporting on. Again, the purpose of this event is as a pilot to get the conversations flowing with, with the influencers like yourselves who are running companies and building products and the builders, Amazon and Azure are doing extremely well. Google's coming up in third Cloudworks in public cloud. We see the use cases on premises use cases. Kubernetes has been an interesting phenomenon because it's become from the developer side a little bit, but a lot of ops people love Kubernetes. It's really more of an ops thing. You mentioned OpenStack earlier. Kubernetes kind of came out of that open stack. We need an orchestration. And then containers had a good shot with, with Docker. They re pivoted the company. Now they're all in an open source. So you got containers booming and Kubernetes as a new layer there. >>What's, >>What's the take on that? What does that really mean? Is that a new defacto enabler? It >>Is here. It's for here for sure. Every enterprise somewhere in the journey is going on. And you know, most companies are, 70 plus percent of them have 1, 2, 3 container based, Kubernetes based applications now being rolled out. So it's very much here. It is in production at scale by many customers. And it, the beauty of it is yes, open source, but the biggest gating factor is the skill set. And that's where we have a phenomenal engineering team, right? So it's, it's one thing to buy a tool and >>Just be clear, you're a managed service for Kubernetes. >>We provide, provide a software platform for cloud acceleration as a service and it can run anywhere. It can run in public private. We have customers who do it in truly multi-cloud environments. It runs on the edge, it runs at this in stores about thousands of stores in a retailer. So we provide that and also for specific segments where data sovereignty and data residency are key regulatory reasons. We also un on-prem as an air gap version. Can >>You give an example on how you guys are deploying your platform to enable a super cloud experience for your customer? Right. >>So I'll give you two different examples. One is a very large networking company, public networking company. They have hundreds of products, hundreds of r and d teams that are building different, different products. And if you look at few years back, each one was doing it on a different platforms, but they really needed to bring the agility. And they worked with us now over three years where we are their build test dev pro platform where all their products are built on, right? And it has dramatically increased their agility to release new products. Number two, it actually is a light out operation. In fact, the customer says like, like the Maytag service person, cuz we provide it as a service and it barely takes one or two people to maintain it for them. >>So it's kinda like an SRE vibe. One person managing a >>Large 4,000 engineers building infrastructure >>On their tools, >>Whatever they want on their tools. They're using whatever app development tools they use, but they use our platform. What >>Benefits are they seeing? Are they seeing speed? >>Speed, definitely. Okay. Definitely they're speeding. Speed uniformity because now they're building able to build, so their customers who are using product A and product B are seeing a similar set of tools that are being used. >>So a big problem that's coming outta this super cloud event that we're, we're seeing and we heard it all here, ops and security teams. Cause they're kind of part of one thing, but option security specifically need to catch up speed wise. Are you delivering that value to ops and security? Right? >>So we, we work with ops and security teams and infrastructure teams and we layer on top of that. We have like a platform team. If you think about it, depending on where you have data centers, where you have infrastructure, you have multiple teams, okay, but you need a unified platform. Who's your buyer? Our buyer is usually, you know, the product divisions of companies that are looking at or the CTO would be a buyer for us functionally cio definitely. So it it's, it's somewhere in the DevOps to infrastructure. But the ideal one we are beginning to see now many large corporations are really looking at it as a platform and saying we have a platform group on which any app can be developed and it is run on any infrastructure. So the platform engineering teams. So >>You working two sides to that coin. You've got the dev side and then >>And then infrastructure >>Side. >>Okay. Another customer that I give an example, which I would say is kind of the edge of the store. So they have thousands of stores. Retail, retail, you know food retailer, right? They have thousands of stores that are on the globe, 50,000, 60,000. And they really want to enhance the customer experience that happens when you either order the product or go into the store and pick up your product or buy or browse or sit there. They have applications that were written in the nineties and then they have very modern AIML applications today. They want something that will not have to send an IT person to install a rack in the store or they can't move everything to the cloud because the store operations has to be local. The menu changes based on it's classic edge. It's classic edge, yeah. Right? They can't send it people to go install rack access servers then they can't sell software people to go install the software and any change you wanna put through that, you know, truck roll. So they've been working with us where all they do is they ship, depending on the size of the store, one or two or three little servers with instructions that >>You, you say little servers like how big one like a box, like a small little box, >>Right? And all the person in the store has to do like what you and I do at home and we get a, you know, a router is connect the power, connect the internet and turn the switch on. And from there we pick it up. >>Yep. >>We provide the operating system, everything and then the applications are put on it. And so that dramatically brings the velocity for them. They manage thousands of >>Them. True plug and play >>Two, plug and play thousands of stores. They manage it centrally. We do it for them, right? So, so that's another example where on the edge then we have some customers who have both a large private presence and one of the public clouds. Okay. But they want to have the same platform layer of orchestration and management that they can use regardless of the locations. >>So you guys got some success. Congratulations. Got some traction there. It's awesome. The question I want to ask you is that's come up is what is truly cloud native? Cuz there's lift and shift of the cloud >>That's not cloud native. >>Then there's cloud native. Cloud native seems to be the driver for the super cloud. How do you talk to customers? How do you explain when someone says what's cloud native, what isn't cloud native? >>Right. Look, I think first of all, the best place to look at what is the definition and what are the attributes and characteristics of what is truly a cloud native, is CNC foundation. And I think it's very well documented, very well. >>Tucan, of course Detroit's >>Coming so, so it's already there, right? So we follow that very closely, right? I think just lifting and shifting your 20 year old application onto a data center somewhere is not cloud native. Okay? You can't put to cloud, not you have to rewrite and redevelop your application in business logic using modern tools. Hopefully more open source and, and I think that's what Cloudnative is and we are seeing a lot of our customers in that journey. Now everybody wants to be cloudnative, but it's not that easy, okay? Because it's, I think it's first of all, skill set is very important. Uniformity of tools that there's so many tools there. Thousands and thousands of tools you could spend your time figuring out which tool to use. Okay? So I think the complexity is there, but the business benefits of agility and uniformity and customer experience are truly being done. >>And I'll give you an example, I don't know how clear native they are, right? And they're not a customer of ours, but you order pizzas, you do, right? If you just watch the pizza industry, how dominoes actually increase their share and mind share and wallet share was not because they were making better pizzas or not, I don't know anything about that, but the whole experience of how you order, how you watch what's happening, how it's delivered. There were a pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow to the application changes what the expectations >>Are >>For the customer. Customer, >>The customer's expectations change, right? Once you get used to a better customer experience, you learn. >>That's to wrap it up. I wanna just get your perspective again. One of the benefits of chatting with you here and having you part of the Super Cloud 22 is you've seen many cycles, you have a lot of insights. I want to ask you, given your career where you've been and what you've done and now let's CEO platform nine, how would you compare what's happening now with other inflection points in the industry? And you've been, again, you've been an entrepreneur, you sold your company to Oracle, you've been seeing the big companies, you've seen the different waves. What's going on right now put into context this moment in time around Super Cloud. >>Sure. I think as you said, a lot of battles. CARSs being been in an asb, being in a real time software company, being in large enterprise software houses and a transformation. I've been on the app side, I did the infrastructure right and then tried to build our own platforms. I've gone through all of this myself with lot of lessons learned in there. I think this is an event which is happening now for companies to go through to become cloud native and digitalize. If I were to look back and look at some parallels of the tsunami that's going on is a couple of paddles come to me. One is, think of it, which was forced to honors like y2k. Everybody around the world had to have a plan, a strategy, and an execution for y2k. I would say the next big thing was e-commerce. I think e-commerce has been pervasive right across all industries. >>And disruptive. >>And disruptive, extremely disruptive. If you did not adapt and adapt and accelerate your e-commerce initiative, you were, it was an existence question. Yeah. I think we are at that pivotal moment now in companies trying to become digital and cloudnative. You know, that is what I see >>Happening there. I think that that e-commerce is interesting and I think just to riff with you on that is that it's disrupting and refactoring the business models. I think that is something that's coming out of this is that it's not just completely changing the gain, it's just changing how you operate, >>How you think and how you operate. See, if you think about the early days of e-commerce, just putting up a shopping cart that made you an e-commerce or e retailer or an e e e customer, right? Or so. I think it's the same thing now is I think this is a fundamental shift on how you're thinking about your business. How are you gonna operate? How are you gonna service your customers? I think it requires that just lift and shift is not gonna work. >>Nascar, thank you for coming on, spending the time to come in and share with our community and being part of Super Cloud 22. We really appreciate, we're gonna keep this open. We're gonna keep this conversation going even after the event, to open up and look at the structural changes happening now and continue to look at it in the open in the community. And we're gonna keep this going for, for a long, long time as we get answers to the problems that customers are looking for with cloud cloud computing. I'm Sean Fur with Super Cloud 22 in the Cube. Thanks for watching. >>Thank you. Thank you. >>Hello and welcome back. This is the end of our program, our special presentation with Platform nine on cloud native at scale, enabling the super cloud. We're continuing the theme here. You heard the interviews Super Cloud and its challenges, new opportunities around solutions around like Platform nine and others with Arlon. This is really about the edge situations on the internet and managing the edge multiple regions, avoiding vendor lock in. This is what this new super cloud is all about. The business consequences we heard and and the wide ranging conversations around what it means for open source and the complexity problem all being solved. I hope you enjoyed this program. There's a lot of moving pieces and things to configure with cloud native install, all making it easier for you here with Super Cloud and of course Platform nine contributing to that. Thank you for watching.

Published Date : Oct 19 2022

SUMMARY :

So enjoy the program, see you soon. a lot different, but kind of the same as the first generation. And so you gotta rougher and it kind of coming together, but you also got this idea of regions, So I think, you know, in in the context of this, the, Can you scope the scale of the problem? And I think, you know, I I like to call it, you know, And that is just, you know, one example of an issue that happens. you know, you see some, you know, some experimentation. which is, you know, you have your perfectly written code that is operating just fine on your And so as you give that change to then run at your production edge location, And you guys have a solution you're launching, Can you share what So what alarm lets you do in a in terms of the chaos you guys are reigning in. And if you look at the logo we've designed, So keeping it smooth, the assembly on things are flowing. Because developers, you know, there is, the developers are responsible for one picture of So the DevOps is the cloud native developer. And so online addresses that problem at the heart of it, and it does that using So I'm assuming you have that thought through, can you share open source and commercial relationship? products starting all the way with fi, which was a serverless product, you know, that we had built to buy, but also actually kind of date the application, if you will. I think one is just, you know, this, this, this cloud native space is so vast I have to ask you now, let's get into what's in it for the customer. And so, and there's multiple, you know, enterprises that we talk to, shared that this is a major challenge we have today because we have, you know, I'm an enterprise, I got tight, you know, I love the open source trying to It's created by folks that are as part of Intuit team now, you know, And the customer said, If you had it today, I would've purchased it. So next question is, what is the solution to the customer? So I think, you know, one of the core tenets of Platform nine has always been that And now they have management challenges. Especially operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure That's right. And alon by the way, also helps in that direction, but you also need I mean, what's the impact if you do all those things, as you mentioned, what's the impact of the apps? And so this really gives them, you know, the right tooling for But this is a key point, and I have to ask you because if this Arlo solution of challenges, and those are the pain points, which is, you know, if you're looking to reduce your, not where it used to be supporting the business, you know, that, you know, that the, the technology that's, you know, that's gonna drive your top line is If all the things happen the way we want 'em to happen, The magic wand, the magic dust, he's running that at a nimble, nimble team size of at the most, Taking care of, and the CIO doesn't exist. Thank you for your time. Thanks for having of Platform nine b. Great to see you Cube alumni. And now the Kubernetes layer that we've been working on for years is Exactly. you know, the new Arlon, our R lawn you guys just launched, you know, do step A, B, C, and D instead with Kubernetes, I mean now with open source, so popular, you don't have to have to write a lot of code. you know, the emergence of systems and layers to help you manage that complexity is becoming That's, I wrote a LinkedIn post today was comments about, you know, hey, enterprise is the new breed, the trend of SaaS you know, you think you have things under control, but some people from various teams will make changes here in the industry technical, how would you look at the super cloud trend that's emerging? the way I interpret that is, you know, clouds and infrastructure, It's IBM's, you know, connection for the internet at the, this layer that has simplified, you know, computing and, the physics and the, the atoms, the pro, you know, this is where the innovation, all the variations around and you know, compute storage networks the DevOps engineers, they get a a ways to So how do you guys look at the workload side of it? like K native, where you can express your application in more at a higher level, It's coming like an EC two instance, spin up a cluster. And then you can stamp out your app, your applications and your clusters and manage them And it's like a playbook, just deploy it. You just tell the system what you want and then You need edge's code, but then you can configure the code by just saying do it. And that is just complexity for the people operating this or configuring this, What do you expect to see at this year? If you look at a stack necessary for hosting We would joke we, you know, about, about the dream. So the successor to Kubernetes, you know, I don't Yeah, I think the, the reigning in the chaos is key, you know, Now we have now visibility into But roughly speaking when we say, you know, They have some SaaS apps, but mostly it's the ecosystem. you know, that they're, they will keep catering to, they, they will continue to find I mean, from a, from a hardware standpoint, yes. terms of, you know, the, the new risk and arm ecosystems, It's, it's hardware and you got software and you got middleware and he kinda over, Great to have you on. What's just thing about what you guys are doing at Platform nine? clouds, you know, the application world is moving very fast in trying to Patrick, we were talking before we came on stage here about your background and we were kind of talking about the glory days So you saw that whole growth. In fact, you know, as we were talking offline, I was in one of those And if you look at the tech trends, GDPs down, but not tech. some, you know, new servers and new application tools. you know, more, More dynamic, more unreal. So it's, you know, multi-cloud. the purpose of this event is as a pilot to get the conversations flowing with, with the influencers like yourselves And you know, most companies are, 70 plus percent of them have 1, 2, 3 container It runs on the edge, You give an example on how you guys are deploying your platform to enable a super And if you look at few years back, each one was doing So it's kinda like an SRE vibe. Whatever they want on their tools. to build, so their customers who are using product A and product B are seeing a similar set Are you delivering that value to ops and security? Our buyer is usually, you know, the product divisions of companies You've got the dev side and then enhance the customer experience that happens when you either order the product or go into And all the person in the store has to do like And so that dramatically brings the velocity for them. of the public clouds. So you guys got some success. How do you explain when someone says what's cloud native, what isn't cloud native? is the definition and what are the attributes and characteristics of what is truly a cloud native, Thousands and thousands of tools you could spend your time figuring I don't know anything about that, but the whole experience of how you order, For the customer. Once you get used to a better customer experience, One of the benefits of chatting with you here and been on the app side, I did the infrastructure right and then tried to build our If you did not adapt and adapt and accelerate I think that that e-commerce is interesting and I think just to riff with you on that is that it's disrupting How are you gonna service your Nascar, thank you for coming on, spending the time to come in and share with our community and being part of Thank you. I hope you enjoyed this program.

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Bich Le, Platform9 Cloud Native at Scale


 

>>Welcome back everyone, to the special presentation of Cloud Native at scale, the Cube and Platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here with Bickley, who's the chief architect and co-founder of Platform nine Pick. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or well later, earlier when OpenStack was going. Great to see you and great to see congratulations on the success of Platform nine. Thank >>You very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now has realized, and you've seen what Docker's doing with the new docker, the open source, Docker now just the success of containerization, right? And now the Kubernetes layer that we've been working on for years is coming, Bearing fruit. This is huge. >>Exactly. Yes. >>And so as infrastructures code comes in, we talked to Basco talking about Super Cloud. I met her about, you know, the new Arlon, our R lawn, and you guys just launched the infrastructures code is going to another level, and then it's always been DevOps infrastructures code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon. Connect the dots for us. What is the state of infrastructures code today? >>So I think, I think I'm, I'm glad you mentioned it. Everybody or most people know about infrastructures code, but with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure is configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D. Instead, with Kubernetes you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specified. So I think it's, it's a even better version of infrastructures code. Yeah, >>Yeah. And that really means it developer just accessing resources. Okay, not clearing, Okay, give me some compute. Stand me up some, Turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean, now with open source, so popular, you don't have to have to write a lot of code, this code being developed. And so it's integration, it's configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you've got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these, these new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space. The that's, >>I wrote a LinkedIn post today was comments about, you know, hey, enterprise is a new breed. The trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your view? >>It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we try to do with this new project. Arlon. >>Yeah. So, so we're gonna get into Arlan in a second. I wanna get into the why Arlon. You guys announced that at our GoCon, which was put on here in Silicon Valley at the computer by, in two, where they had their own little day over there at their headquarters. But before we get there, Bacar, your CEO came on and he talked about Super Cloud at our in aural event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system. So the deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection for the internet at the, the layer two is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, >>It's >>Gonna >>Continue. It's interesting. I just, when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on a rise. We've remember pointing for many years now, that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a service layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd wanna have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in in this community of, of co con, which will be a covering. So that brings up the whole what's next? You guys just announced our lawn at ar GoCon, which came out of Intuit. We've had Mariana Tessel at our super cloud event. She's the cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why our lawn, why this announcement? >>Yeah, so the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and, you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built Arlan and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, >>And what's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, So let's get into what that means for up above and below the, the, this abstraction or thin layer below as the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads. At the end of the day, you know, I talk to CXOs and IT folks that, that are now DevOps engineers. They care about the workloads and they want the infrastructure's code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened. They need observability and they need to, to know that it's working. That's right. And here's my workloads running effectively. So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, right? >>So workloads, so Kubernetes has defined kind of a standard way to describe workloads. And you can, you know, tell Kubernetes, I want to run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem, like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases, it's like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's coming like an EC two instance, spin up a cluster. We've heard people used words like that. That's >>Right. And before arlon, you kind of had to do all of that using a different set of tools as, as I explained. So with Arlon you can kind of express everything together. You can say, I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call a profile. And then you can stamp out your app, your applications, and your clusters and manage them in a very, So >>It's essentially standard, like creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook, deploy it. Now what's there is between say a script like I have scripts, I can just automate scripts >>Or yes, this is where that declarative API and infrastructures configuration comes in, right? Because scripts, yes, you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things about controllers, which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure has configuration is built kind of on its super set of infrastructures code because it's an evolution. You need edge retro's code, but then you can configure the code by just saying do it. You basically declaring it saying Go, go do that. That's right. Okay, So, all right, so Cloudnative at scale, take me through your vision of what that means. Someone says, Hey, what does cloudnative at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years? I mean, people are now starting to figure out, okay, it's not as easy as it sounds. Kubernetes has value. We're gonna hear this year at co con a lot of this, what does cloud native at scale >>Mean? Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users. There, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we, we try to address with Arlan. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state, and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, So I'll put you on the spot road that Coan coming up, and obviously this will be shipping this segment series out before. What do you expect to see at Coan this year? What's the big story this year? What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jocking for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time and there's their ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of cub cons and I expect to continue, and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, well >>Maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed, but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there're just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. Yeah. >>B, you've had a storied career VMware over decades with them, obviously with 12 years, with 14 years or something like that. Big number. Co-founder here, a platform. Now you guys been around for a while at this game. We, man, we talked about OpenStack, that project you, we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. And I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a cloud a Rod team at that time. We to joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? OpenStack was an example where the Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will a, platform nine will be there and we will, you know, take the innovations from the, the, the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yeah, I think the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart this segment. What is at scale, how many clusters do you see that would be a, a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you Yeah, how would you describe that? When people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. >>Yeah. And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing over $2 billion tran billions of transactions a year and, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud need of its scale? >>The, the hyperscalers? >>Yeah. A's Azure, Google >>You mean from a business perspective, technical, they're, they have their own interests that, you know, that they're, they will keep catering to, they, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep >>Well, they got great I performance, I mean from a, from a hardware standpoint, yes. That's gonna be key, right? >>Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyperscalers really want to be in the game in terms of, you know, the, the new risk and arm ecosystems and, and platforms. >>Yeah. Not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, and I remember our first year doing the cube, Oh, the cloud is one big distributed computer. It's, it's hardware and you got software and you got middleware and he kind of over, well he's kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. >>Yes, >>Exactly. It's, we're back in the same game. Vic, thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super Cloud Arlon open source and how to run large scale applications on the cloud. Cloud Native Phil for developers and John Furrier with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up.

Published Date : Oct 18 2022

SUMMARY :

Great to see you and great to see congratulations on the success And now the Kubernetes layer that we've been working on for years is Exactly. you know, the new Arlon, our R lawn, and you guys just launched the So I think, I think I'm, I'm glad you mentioned it. I mean, now with open source, so popular, you don't have to have to write a lot of code, you know, the emergence of systems and layers to help you manage that complexity is becoming I wrote a LinkedIn post today was comments about, you know, hey, enterprise is a new breed. So you have this sprawl of tools. in the industry technical, how would you look at the super cloud trend that's emerging? the way I interpret that is, you know, clouds and infrastructure, It's IBM's, you know, connection for the internet at the, this layer that has simplified, you know, computing and, the physics and the, the atoms, the pro, you know, this is where the innovation, the state that you want and more consistency. the DevOps engineers, they get a a ways to At the end of the day, you know, And you can, you know, tell Kubernetes, It's coming like an EC two instance, spin up a cluster. So with Arlon you can kind of express everything And it's like a playbook, deploy it. tell the system what you want and then the system kind of figures You need edge retro's code, but then you can configure the code by just saying do it. And that is just complexity for the people operating this or configuring this, What do you expect to see at Coan this year? If you look at a stack necessary for hosting We to joke we, you know, about, about the dream. So the successor to Kubernetes, you know, I don't Yeah, I think the reigning in the chaos is key, you know, Now we have now visibility into But roughly speaking when we say, you know, What's the role the you know, that they're, they will keep catering to, they, they will continue to find right? terms of, you know, the, the new risk and arm ecosystems It's, it's hardware and you got software and you got middleware and he kind of over, Vic, thank you for coming on the segment.

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Platform9, Cloud Native at Scale


 

>>Hello, welcome to the Cube here in Palo Alto, California for a special presentation on Cloud native at scale, enabling super cloud modern applications with Platform nine. I'm John Furr, your host of The Cube. We had a great lineup of three interviews we're streaming today. Meor Ma Makowski, who's the co-founder and VP of Product of Platform nine. She's gonna go into detail around Arlon, the open source products, and also the value of what this means for infrastructure as code and for cloud native at scale. Bickley the chief architect of Platform nine Cube alumni. Going back to the OpenStack days. He's gonna go into why Arlon, why this infrastructure as code implication, what it means for customers and the implications in the open source community and where that value is. Really great wide ranging conversation there. And of course, Vascar, Gort, the CEO of Platform nine, is gonna talk with me about his views on Super Cloud and why Platform nine has a scalable solutions to bring cloudnative at scale. So enjoy the program. See you soon. Hello everyone. Welcome to the cube here in Palo Alto, California for special program on cloud native at scale, enabling next generation cloud or super cloud for modern application cloud native developers. I'm John Furry, host of the Cube. A pleasure to have here, me Makoski, co-founder and VP of product at Platform nine. Thanks for coming in today for this Cloudnative at scale conversation. Thank >>You for having me. >>So Cloudnative at scale, something that we're talking about because we're seeing the, the next level of mainstream success of containers Kubernetes and cloud native develop, basically DevOps in the C I C D pipeline. It's changing the landscape of infrastructure as code, it's accelerating the value proposition and the super cloud as we call it, has been getting a lot of traction because this next generation cloud is looking a lot different, but kind of the same as the first generation. What's your view on super cloud as it fits to cloud native as scales up? >>Yeah, you know, I think what's interesting, and I think the reason why Super Cloud is a really good, in a really fit term for this, and I think, I know my CEO was chatting with you as well, and he was mentioning this as well, but I think there needs to be a different term than just multi-cloud or cloud. And the reason is because as cloud native and cloud deployments have scaled, I think we've reached a point now where instead of having the traditional data center style model where you have a few large distributions of infrastructure and workload at a few locations, I think the model is kind of flipped around, right? Where you have a large number of microsites, these microsites could be your public cloud deployment, your private on-prem infrastructure deployments, or it could be your edge environment, right? And every single enterprise, every single industry is moving in that direction. And so you gotta rougher that with a terminology that, that, that indicates the scale and complexity of it. And so I think supercloud is a, is an appropriate term for that. >>So you brought a couple of things I want to dig into. You mentioned edge nodes. We're seeing not only edge nodes being the next kind of area of innovation, mainly because it's just popping up everywhere. And that's just the beginning. Wouldn't even know what's around the corner. You got buildings, you got iot, ot, and IT kind of coming together, but you also got this idea of regions, global infras infrastructures, big part of it. I just saw some news around CloudFlare shutting down a site here. There's policies being made at scale, These new challenges there. Can you share because you can have edge. So hybrid cloud is a winning formula. Everybody knows that it's a steady state. Yeah. But across multiple clouds brings in this new un engineered area, yet it hasn't been done yet. Spanning clouds. People say they're doing it, but you start to see the toe in the water, it's happening, it's gonna happen. It's only gonna get accelerated with the edge and beyond globally. So I have to ask you, what is the technical challenges in doing this? Because there's something business consequences as well, but there are technical challenges. Can you share your view on what the technical challenges are for the super cloud or across multiple edges and regions? >>Yeah, absolutely. So I think, you know, in in the context of this, the, this, this term of super cloud, I think it's sometimes easier to visualize things in terms of two access, right? I think on one end you can think of the scale in terms of just pure number of nodes that you have deploy a number of clusters in the Kubernetes space. And then on the other axis you would have your distribution factor, right? Which is, do you have these tens of thousands of nodes in one site or do you have them distributed across tens of thousands of sites with one node at each site? Right? And if you have just one flavor of this, there is enough complexity, but potentially manageable. But when you are expanding on both these access, you really get to a point where that scale really needs some well thought out, well structured solutions to address it, right? A combination of homegrown tooling along with your, you know, favorite distribution of Kubernetes is not a strategy that can help you in this environment. It may help you when you have one of this or when you, when you scale, is not at the level. >>Can you scope the complexity? Because I mean, I hear a lot of moving parts going on there, the technology's also getting better. We we're seeing cloud native become successful. There's a lot to configure, there's a lot to install. Can you scope the scale of the problem? Because we're talking about at scale Yep. Challenges here. Yeah, >>Absolutely. And I think, you know, I I like to call it, you know, the, the, the problem that the scale creates, you know, there's various problems, but I think one, one problem, one way to think about it is, is, you know, it works on my cluster problem, right? So I, you know, I come from engineering background and there's a, you know, there's a famous saying between engineers and QA and the support folks, right? Which is, it works on my laptop, which is I tested this chain, everything was fantastic, it worked flawlessly on my machine, on production, It's not working. The exact same problem now happens and these distributed environments, but at massive scale, right? Which is that, you know, developers test their applications, et cetera within the sanctity of their sandbox environments. But once you expose that change in the wild world of your production deployment, right? >>And the production deployment could be going at the radio cell tower at the edge location where a cluster is running there, or it could be sending, you know, these applications and having them run at my customer site where they might not have configured that cluster exactly the same way as I configured it, or they configured the cluster, right? But maybe they didn't deploy the security policies, or they didn't deploy the other infrastructure plugins that my app relies on. All of these various factors are their own layer of complexity. And there really isn't a simple way to solve that today. And that is just, you know, one example of an issue that happens. I think another, you know, whole new ball game of issues come in the context of security, right? Because when you are deploying applications at scale in a distributed manner, you gotta make sure someone's job is on the line to ensure that the right security policies are enforced regardless of that scale factor. So I think that's another example of problems that occur. >>Okay. So I have to ask about scale, because there are a lot of multiple steps involved when you see the success of cloud native. You know, you see some, you know, some experimentation. They set up a cluster, say it's containers and Kubernetes, and then you say, Okay, we got this, we can figure it. And then they do it again and again, they call it day two. Some people call it day one, day two operation, whatever you call it. Once you get past the first initial thing, then you gotta scale it. Then you're seeing security breaches, you're seeing configuration errors. This seems to be where the hotspot is in when companies transition from, I got this to, Oh no, it's harder than I thought at scale. Can you share your reaction to that and how you see this playing out? >>Yeah, so, you know, I think it's interesting. There's multiple problems that occur when, you know, the two factors of scale, as we talked about, start expanding. I think one of them is what I like to call the, you know, it, it works fine on my cluster problem, which is back in, when I was a developer, we used to call this, it works on my laptop problem, which is, you know, you have your perfectly written code that is operating just fine on your machine, your sandbox environment. But the moment it runs production, it comes back with p zeros and pos from support teams, et cetera. And those issues can be really difficult to triage us, right? And so in the Kubernetes environment, this problem kind of multi folds, it goes, you know, escalates to a higher degree because you have your sandbox developer environments, they have their clusters and things work perfectly fine in those clusters because these clusters are typically handcrafted or a combination of some scripting and handcrafting. >>And so as you give that change to then run at your production edge location, like say your radio cell tower site, or you hand it over to a customer to run it on their cluster, they might not have not have configured that cluster exactly how you did, or they might not have configured some of the infrastructure plugins. And so the things don't work. And when things don't work, triaging them becomes nightmarishly hard, right? It's just one of the examples of the problem, another whole bucket of issues is security, which is, is you have these distributed clusters at scale, you gotta ensure someone's job is on the line to make sure that these security policies are configured properly. >>So this is a huge problem. I love that comment. That's not not happening on my system. It's the classic, you know, debugging mentality. Yeah. But at scale it's hard to do that with error prone. I can see that being a problem. And you guys have a solution you're launching. Can you share what Arlon is this new product? What is it all about? Talk about this new introduction. >>Yeah, absolutely. Very, very excited. You know, it's one of the projects that we've been working on for some time now because we are very passionate about this problem and just solving problems at scale in on-prem or at in the cloud or at edge environments. And what arlon is, it's an open source project, and it is a tool, it's a Kubernetes native tool for complete end to end management of not just your clusters, but your clusters. All of the infrastructure that goes within and along the site of those clusters, security policies, your middleware, plug-ins, and finally your applications. So what our LA you do in a nutshell is in a declarative way, it lets you handle the configuration and management of all of these components in at scale. >>So what's the elevator pitch simply put for what dissolves in, in terms of the chaos you guys are reigning in, what's the, what's the bumper sticker? Yeah, what >>Would it do? There's a perfect analogy that I love to reference in this context, which is think of your assembly line, you know, in a traditional, let's say, you know, an auto manufacturing factory or et cetera, and the level of efficiency at scale that that assembly line brings, right? Our line, and if you look at the logo we've designed, it's this funny little robot. And it's because when we think of online, we think of these enterprise large scale environments, you know, sprawling at scale, creating chaos because there isn't necessarily a well thought through, well structured solution that's similar to an assembly line, which is taking each component, you know, addressing them, manufacturing, processing them in a standardized way, then handing to the next stage. But again, it gets, you know, processed in a standardized way. And that's what arlon really does. That's like the deliver pitch. If you have problems of scale of managing your infrastructure, you know, that is distributed. Arlon brings the assembly line level of efficiency and consistency for >>Those. So keeping it smooth, the assembly on things are flowing. See c i CD pipe pipelining. Exactly. So that's what you're trying to simplify that ops piece for the developer. I mean, it's not really ops, it's their ops, it's coding. >>Yeah. Not just developer, the ops, the operations folks as well, right? Because developers, you know, there is, developers are responsible for one picture of that layer, which is my apps, and then maybe that middleware of applications that they interface with, but then they hand it over to someone else who's then responsible to ensure that these apps are secure properly, that they are logging, logs are being collected properly, monitoring and observability integrated. And so it solves problems for both >>Those teams. Yeah. It's DevOps. So the DevOps is the cloud needed developer's. That's right. The option teams have to kind of set policies. Is that where the declarative piece comes in? Is that why that's important? >>Absolutely. Yeah. And, and, and, and you know, ES really in introduced or elevated this declarative management, right? Because, you know, s clusters are Yeah. Or your, yeah, you know, specifications of components that go in Kubernetes are defined a declarative way, and Kubernetes always keeps that state consistent with your defined state. But when you go outside of that world of a single cluster, and when you actually talk about defining the clusters or defining everything that's around it, there really isn't a solution that does that today. And so Arlon addresses that problem at the heart of it, and it does that using existing open source well known solutions. >>And do I want to get into the benefits? What's in it for me as the customer developer? But I want to finish this out real quick and get your thoughts. You mentioned open source. Why open source? What's the, what's the current state of the product? You run the product group over at Platform nine, is it open source? And you guys have a product that's commercial? Can you explain the open source dynamic? And first of all, why open source? Yeah. And what is the consumption? I mean, open source is great, People want open source, they can download it, look up the code, but maybe wanna buy the commercial. So I'm assuming you have that thought through, can you share open source and commercial relationship? >>Yeah, I think, you know, starting with why open source? I think it's, you know, we as a company, we have, you know, one of the things that's absolutely critical to us is that we take mainstream open source technologies components and then we, you know, make them available to our customers at scale through either a SaaS model or on-prem model, right? But, so as we are a company or startup or a company that benefits, you know, in a massive way by this open source economy, it's only right, I think in my mind that we do our part of the duty, right? And contribute back to the community that feeds us. And so, you know, we have always held that strongly as one of our principles. And we have, you know, created and built independent products starting all the way with fision, which was a serverless product, you know, that we had built to various other, you know, examples that I can give. But that's one of the main reasons why opensource and also open source, because we want the community to really firsthand engage with us on this problem, which is very difficult to achieve if your product is behind a wall, you know, behind, behind a block box. >>Well, and that's, that's what the developers want too. And what we're seeing in reporting with Super Cloud is the new model of consumption is I wanna look at the code and see what's in there. That's right. And then also, if I want to use it, I'll do it. Great. That's open source, that's the value. But then at the end of the day, if I wanna move fast, that's when people buy in. So it's a new kind of freemium, I guess, business model. I guess that's the way that long. But that's, that's the benefit. Open source. This is why standards and open source is growing so fast. You have that confluence of, you know, a way for developers to try before they buy, but also actually kind of date the application, if you will. We, you know, Adrian Karo uses the dating met metaphor, you know, Hey, you know, I wanna check it out first before I get married. Right? And that's what open source, So this is the new, this is how people are selling. This is not just open source, this is how companies are selling. >>Absolutely. Yeah. Yeah. You know, I think, and you know, two things. I think one is just, you know, this, this, this cloud native space is so vast that if you, if you're building a close flow solution, sometimes there's also a risk that it may not apply to every single enterprises use cases. And so having it open source gives them an opportunity to extend it, expand it, to make it proper to their use case if they choose to do so, right? But at the same time, what's also critical to us is we are able to provide a supported version of it with an SLA that we, you know, that's backed by us, a SAS hosted version of it as well, for those customers who choose to go that route, you know, once they have used the open source version and loved it and want to take it at scale and in production and need, need, need a partner to collaborate with, who can, you know, support them for that production >>Environment. I have to ask you now, let's get into what's in it for the customer. I'm a customer. Yep. Why should I be enthused about Arla? What's in it for me? You know? Cause if I'm not enthused about it, I'm not gonna be confident and it's gonna be hard for me to get behind this. Can you share your enthusiastic view of, you know, why I should be enthused about Arlo? I'm a >>Customer. Yeah, absolutely. And so, and there's multiple, you know, enterprises that we talk to, many of them, you know, our customers, where this is a very kind of typical story that you hear, which is we have, you know, a Kubernetes distribution. It could be on premise, it could be public clouds, native Kubernetes, and then we have our C I C D pipelines that are automating the deployment of applications, et cetera. And then there's this gray zone. And the gray zone is well before you can you, your CS c D pipelines can deploy the apps. Somebody needs to do all of that groundwork of, you know, defining those clusters and yeah. You know, properly configuring them. And as these things, these things start by being done hand grown. And then as the, as you scale, what typically enterprises would do today is they will have their home homegrown DIY solutions for this. >>I mean, the number of folks that I talk to that have built Terra from automation, and then, you know, some of those key developers leave. So it's a typical open source or typical, you know, DIY challenge. And the reason that they're writing it themselves is not because they want to. I mean, of course technology is always interesting to everybody, but it's because they can't find a solution that's out there that perfectly fits the problem. And so that's that pitch. I think Ops FICO would be delighted. The folks that we've talk, you know, spoken with, have been absolutely excited and have, you know, shared that this is a major challenge we have today because we have, you know, few hundreds of clusters on ecos Amazon, and we wanna scale them to few thousands, but we don't think we are ready to do that. And this will give us the >>Ability to, Yeah, I think people are scared. Not sc I won't say scare, that's a bad word. Maybe I should say that they feel nervous because, you know, at scale small mistakes can become large mistakes. This is something that is concerning to enterprises. And, and I think this is gonna come up at co con this year where enterprises are gonna say, Okay, I need to see SLAs. I wanna see track record, I wanna see other companies that have used it. Yeah. How would you answer that question to, or, or challenge, you know, Hey, I love this, but is there any guarantees? Is there any, what's the SLAs? I'm an enterprise, I got tight, you know, I love the open source trying to free fast and loose, but I need hardened code. >>Yeah, absolutely. So, so two parts to that, right? One is Arlan leverages existing open source components, products that are extremely popular. Two specifically. One is Arlan uses Argo cd, which is probably one of the highest and used CD open source tools that's out there. Right's created by folks that are as part of into team now, you know, really brilliant team. And it's used at scale across enterprises. That's one. Second is Alon also makes use of Cluster api cappi, which is a Kubernetes sub-component, right? For lifecycle management of clusters. So there is enough of, you know, community users, et cetera, around these two products, right? Or, or, or open source projects that will find Arlan to be right up in their alley because they're already comfortable, familiar with Argo cd. Now Arlan just extends the scope of what City can do. And so that's one. And then the second part is going back to a point of the comfort. And that's where, you know, platform line has a role to play, which is when you are ready to deploy online at scale, because you've been, you know, playing with it in your DEF test environments, you're happy with what you get with it, then Platform nine will stand behind it and provide that >>Sla. And what's been the reaction from customers you've talked to Platform nine customers with, with that are familiar with, with Argo and then rlo? What's been some of the feedback? >>Yeah, I, I think the feedback's been fantastic. I mean, I can give you examples of customers where, you know, initially, you know, when you are, when you're telling them about your entire portfolio of solutions, it might not strike a card right away. But then we start talking about Arlan and, and we talk about the fact that it uses Argo adn, they start opening up, they say, We have standardized on Argo and we have built these components, homegrown, we would be very interested. Can we co-develop? Does it support these use cases? So we've had that kind of validation. We've had validation all the way at the beginning of our land before we even wrote a single line of code saying this is something we plan on doing. And the customer said, If you had it today, I would've purchased it. So it's been really great validation. >>All right. So next question is, what is the solution to the customer? If I asked you, Look it, I have, I'm so busy, my team's overworked. I got a skills gap. I don't need another project that's, I'm so tied up right now and I'm just chasing my tail. How does Platform nine help me? >>Yeah, absolutely. So I think, you know, one of the core tenets of Platform nine has always been been that we try to bring that public cloud like simplicity by hosting, you know, this in a lot of such similar tools in a SaaS hosted manner for our customers, right? So our goal behind doing that is taking away or trying to take away all of that complexity from customers' hands and offloading it to our hands, right? And giving them that full white glove treatment, as we call it. And so from a customer's perspective, one, something like arlon will integrate with what they have so they don't have to rip and replace anything. In fact, it will, even in the next versions, it may even discover your clusters that you have today and you know, give you an inventory. And that will, >>So if customers have clusters that are growing, that's a sign correct call you guys. >>Absolutely. Either they're, they have massive large clusters, right? That they wanna split into smaller clusters, but they're not comfortable doing that today, or they've done that already on say, public cloud or otherwise. And now they have management challenges. So >>Especially operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure Yep. And or scale out. >>That's right. Exactly. And >>You provide that layer of policy. >>Absolutely. >>Yes. That's the key value here. >>That's right. >>So policy based configuration for cluster scale up, >>Well profile and policy based declarative configuration and lifecycle management for clusters. >>If I asked you how this enables supercloud, what would you say to that? >>I think this is one of the key ingredients to super cloud, right? If you think about a super cloud environment, there's at least few key ingredients that that come to my mind that are really critical. Like they are, you know, life saving ingredients at that scale. One is having a really good strategy for managing that scale, you know, in a, going back to assembly line in a very consistent, predictable way so that our lot solves then you, you need to compliment that with the right kind of observability and monitoring tools at scale, right? Because ultimately issues are gonna happen and you're gonna have to figure out, you know, how to solve them fast. And arlon by the way, also helps in that direction, but you also need observability tools. And then especially if you're running it on the public cloud, you need some cost management tools. In my mind, these three things are like the most necessary ingredients to make Super Cloud successful. And you know, our alarm fills in >>One. Okay. So now the next level is, Okay, that makes sense. Is under the covers kind of speak under the hood. Yeah. How does that impact the app developers and the cloud native modern application workflows? Because the impact to me, seems the apps are gonna be impacted. Are they gonna be faster, stronger? I mean, what's the impact if you do all those things, as you mentioned, what's the impact of the apps? >>Yeah, the impact is that your apps are more likely to operate in production the way you expect them to, because the right checks and balances have gone through, and any discrepancies have been identified prior to those apps, prior to your customer running into them, right? Because developers run into this challenge to their, where there's a split responsibility, right? I'm responsible for my code, I'm responsible for some of these other plugins, but I don't own the stack end to end. I have to rely on my ops counterpart to do their part, right? And so this really gives them, you know, the right tooling for that. >>So this is actually a great kind of relevant point, you know, as cloud becomes more scalable, you're starting to see this fragmentation gone of the days of the full stack developer to the more specialized role. But this is a key point, and I have to ask you because if this RLO solution takes place, as you say, and the apps are gonna be stupid, they're designed to do, the question is, what did does the current pain look like of the apps breaking? What does the signals to the customer Yeah. That they should be calling you guys up into implementing Arlo, Argo and, and all the other goodness to automate? What are some of the signals? Is it downtime? Is it, is it failed apps, Is it latency? What are some of the things that Yeah, absolutely would be indications of things are effed up a little bit. Yeah. >>More frequent down times, down times that are, that take longer to triage. And so you are, you know, the, you know, your mean times on resolution, et cetera, are escalating or growing larger, right? Like we have environments of customers where they're, they have a number of folks on in the field that have to take these apps and run them at customer sites. And that's one of our partners. And they're extremely interested in this because they're the, the rate of failures they're encountering for this, you know, the field when they're running these apps on site, because the field is automating their clusters that are running on sites using their own script. So these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to reduce your meantime to resolution, if you're looking to reduce the number of failures that occur on your production site, that's one. And second, if you are looking to manage these at scale environments with a relatively small, focused, nimble ops team, which has an immediate impact on your budget. So those are, those are the signals. >>This is the cloud native at scale situation, the innovation going on. Final thought is your reaction to the idea that if the world goes digital, which it is, and the confluence of physical and digital coming together, and cloud continues to do its thing, the company becomes the application, not where it used to be supporting the business, you know, the back office and the maybe terminals and some PCs and handhelds. Now if technology's running, the business is the business. Yeah. Company's the application. Yeah. So it can't be down. So there's a lot of pressure on, on CSOs and CIOs now and boards is saying, How is technology driving the top line revenue? That's the number one conversation. Yep. Do you see that same thing? >>Yeah. It's interesting. I think there's multiple pressures at the CXO CIO level, right? One is that there needs to be that visibility and clarity and guarantee almost that, you know, that the, the technology that's, you know, that's gonna drive your top line is gonna drive that in a consistent, reliable, predictable manner. And then second, there is the constant pressure to do that while always lowering your costs of doing it, right? Especially when you're talking about, let's say retailers or those kinds of large scale vendors, they many times make money by lowering the amount that they spend on, you know, providing those goods to their end customers. So I think those, both those factors kind of come into play and the solution to all of them is usually in a very structured strategy around automation. >>Final question. What does cloudnative at scale look like to you? If all the things happen the way we want 'em to happen, The magic wand, the magic dust, what does it look like? >>What that looks like to me is a CIO sipping at his desk on coffee production is running absolutely smooth. And his, he's running that at a nimble, nimble team size of at the most, a handful of folks that are just looking after things, but things are >>Just taking care of the CIO doesn't exist. There's no ciso, they're at the beach. >>Yep. >>Thank you for coming on, sharing the cloud native at scale here on the cube. Thank you for your time. >>Fantastic. Thanks for >>Having me. Okay. I'm John Fur here for special program presentation, special programming cloud native at scale, enabling super cloud modern applications with Platform nine. Thanks for watching. Welcome back everyone to the special presentation of cloud native at scale, the cube and platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here with Bickley, who's the chief architect and co-founder of Platform nine Pick. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or later, earlier when OpenStack was going. Great to see you and great to see congratulations on the success of platform nine. >>Thank you very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now has realized, and you've seen what Docker's doing with the new docker, the open source Docker now just the success Exactly. Of containerization, right? And now the Kubernetes layer that we've been working on for years is coming, bearing fruit. This is huge. >>Exactly. Yes. >>And so as infrastructures code comes in, we talked to Bacar talking about Super Cloud, I met her about, you know, the new Arlon, our, our lawn, and you guys just launched the infrastructures code is going to another level, and then it's always been DevOps infrastructures code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon, connect the dots for us. What is the state of infrastructure as code today? >>So I think, I think I'm, I'm glad you mentioned it, everybody or most people know about infrastructures code. But with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure is configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D instead with Kubernetes, you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specified. So I think it's, it's a even better version of infrastructures code. >>Yeah. And that really means it's developer just accessing resources. Okay. That declare, Okay, give me some compute, stand me up some, turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean now with open source so popular, you don't have to have to write a lot of code, this code being developed. And so it's into integration, it's configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space. >>That's, I wrote a LinkedIn post today was comments about, you know, hey, enterprise is a new breed. The trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your view? >>It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we try to do with this new project. Arlon. >>Yeah. So, so we're gonna get into Arlan in a second. I wanna get into the why Arlon. You guys announced that at AR GoCon, which was put on here in Silicon Valley at the, at the community meeting by in two, they had their own little day over there at their headquarters. But before we get there, vascar, your CEO came on and he talked about Super Cloud at our in AAL event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or applications specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system, so of deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection for the internet at the, the layer two is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think that the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, it's gonna >>Continue. It's interesting. I just, when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on a rise. We remember pointing for many years now that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a service layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd wanna have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in in this community of, of co con, which will be a covering. So that brings up the whole what's next? You guys just announced our lawn at Argo Con, which came out of Intuit. We've had Mariana Tessel at our super cloud event. She's the cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why our lawn, why this announcement? >>Yeah, so the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and, you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself. You can, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built our lawn and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, And >>What's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, so let's get into what that means for up above and below the the, this abstraction or thin layer below as the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads. At the end of the day, you know, I talk to CXOs and IT folks that are now DevOps engineers. They care about the workloads and they want the infrastructures code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened. They need observability and they need to, to know that it's working. That's right. And is my workloads running effectively? So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, >>Right? So workloads, so Kubernetes has defined kind of a standard way to describe workloads and you can, you know, tell Kubernetes, I want to run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases it is like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's kinda like an EC two instance, spin up a cluster. We very, people used words like that. That's >>Right. And before arlon you kind of had to do all of that using a different set of tools as, as I explained. So with Armon you can kind of express everything together. You can say I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call a profile. And then you can stamp out your app, your applications and your clusters and manage them in a very, so >>Essentially standard creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook. You deploy it. Now what's there is between say a script like I'm, I have scripts, I could just automate scripts >>Or yes, this is where that declarative API and infrastructures configuration comes in, right? Because scripts, yes you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things about controllers which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure has configuration is built kind of on, it's as super set of infrastructures code because it's >>An evolution. >>You need edge's code, but then you can configure the code by just saying do it. You basically declaring and saying Go, go do that. That's right. Okay, so, alright, so cloud native at scale, take me through your vision of what that means. Someone says, Hey, what does cloud native at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years? I mean people are now starting to figure out, okay, it's not as easy as it sounds. Could be nice, it has value. We're gonna hear this year coan a lot of this. What does cloud native at scale >>Mean? Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users there, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we try to address with Arran. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, so I'll put you on the spot road that CubeCon coming up and obviously this will be shipping this segment series out before. What do you expect to see at Coan this year? What's the big story this year? What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jogging for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time and there's ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of cons and I expect to continue and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, well >>Maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there are just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. >>Yeah. Vic, you've had an storied career, VMware over decades with them obviously in 12 years with 14 years or something like that. Big number co-founder here at Platform. Now you guys have been around for a while at this game. We, man, we talked about OpenStack, that project you, we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. And I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a cloud ERO team at that time. We would to joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys tr pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? OpenStack was an example when the Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will a, platform nine will be there and we will, you know, take the innovations from the the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yes. Yeah, I think the, the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart this segment. What is at scale, how many clusters do you see that would be a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you, Yeah, how would you describe that? When people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. >>Yeah. And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing over $2 billion billions of transactions a year and, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud native of its scale? >>The, the hyperscalers, >>Yeahs Azure, Google. >>You mean from a business perspective? Yeah, they're, they have their own interests that, you know, that they're, they will keep catering to, they, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep, >>Well they got great I performance, I mean from a, from a hardware standpoint, yes, that's gonna be key, right? >>Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyperscalers really want to be in the game in terms of, you know, the the new risk and arm ecosystems and the platforms. >>Yeah, not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, I remember our first year doing the cube. Oh the cloud is one big distributed computer, it's, it's hardware and he got software and you got middleware and he kind over, well he's kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. >>Yes, >>Exactly. It's, we're back on the same game. Vic, thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super cloud Arlon open source and how to run large scale applications on the cloud Cloud Native Phil for developers and John Furrier with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up. Hey, welcome back everyone to Super Cloud 22. I'm John Fur, host of the Cuba here all day talking about the future of cloud. Where's it all going? Making it super multi-cloud clouds around the corner and public cloud is winning. Got the private cloud on premise and edge. Got a great guest here, Vascar Gorde, CEO of Platform nine, just on the panel on Kubernetes. An enabler blocker. Welcome back. Great to have you on. >>Good to see you >>Again. So Kubernetes is a blocker enabler by, with a question mark. I put on on that panel was really to discuss the role of Kubernetes. Now great conversation operations is impacted. What's interest thing about what you guys are doing at Platform nine? Is your role there as CEO and the company's position, kind of like the world spun into the direction of Platform nine while you're at the helm? Yeah, right. >>Absolutely. In fact, things are moving very well and since they came to us, it was an insight to call ourselves the platform company eight years ago, right? So absolutely whether you are doing it in public clouds or private clouds, you know, the application world is moving very fast in trying to become digital and cloud native. There are many options for you do on the infrastructure. The biggest blocking factor now is having a unified platform. And that's what we, we come into, >>Patrick, we were talking before we came on stage here about your background and we were gonna talk about the glory days in 2000, 2001, when the first as piece application service providers came out, kind of a SaaS vibe, but that was kind of all kind of cloudlike. >>It wasn't, >>And and web services started then too. So you saw that whole growth. Now, fast forward 20 years later, 22 years later, where we are now, when you look back then to here and all the different cycles, >>I, in fact you, you know, as we were talking offline, I was in one of those ASPs in the year 2000 where it was a novel concept of saying we are providing a software and a capability as a service, right? You sign up and start using it. I think a lot has changed since then. The tooling, the tools, the technology has really skyrocketed. The app development environment has really taken off exceptionally well. There are many, many choices of infrastructure now, right? So I think things are in a way the same but also extremely different. But more importantly now for any company, regardless of size, to be a digital native, to become a digital company is extremely mission critical. It's no longer a nice to have everybody's in the journey somewhere. >>Everyone is going digital transformation here. Even on a so-called downturn recession that's upcoming inflation's here. It's interesting. This is the first downturn in the history of the world where the hyperscale clouds have been pumping on all cylinders as an economic input. And if you look at the tech trends, GDPs down, but not tech. >>Nope. >>Cuz the pandemic showed everyone digital transformation is here and more spend and more growth is coming even in, in tech. So this is a unique factor which proves that that digital transformation's happening and company, every company will need a super cloud. >>Everyone, every company, regardless of size, regardless of location, has to become modernize their infrastructure. And modernizing Infras infrastructure is not just some new servers and new application tools, It's your approach, how you're serving your customers, how you're bringing agility in your organization. I think that is becoming a necessity for every enterprise to survive. >>I wanna get your thoughts on Super Cloud because one of the things Dave Ante and I want to do with Super Cloud and calling it that was we, I, I personally, and I know Dave as well, he can, I'll speak from, he can speak for himself. We didn't like multi-cloud. I mean not because Amazon said don't call things multi-cloud, it just didn't feel right. I mean everyone has multiple clouds by default. If you're running productivity software, you have Azure and Office 365. But it wasn't truly distributed. It wasn't truly decentralized, it wasn't truly cloud enabled. It didn't, it felt like they're not ready for a market yet. Yet public clouds booming on premise. Private cloud and Edge is much more on, you know, more, more dynamic, more real. >>Yeah. I think the reason why we think super cloud is a better term than multi-cloud. Multi-cloud are more than one cloud, but they're disconnected. Okay, you have a productivity cloud, you have a Salesforce cloud, you may have, everyone has an internal cloud, right? So, but they're not connected. So you can say okay, it's more than one cloud. So it's you know, multi-cloud. But super cloud is where you are actually trying to look at this holistically. Whether it is on-prem, whether it is public, whether it's at the edge, it's a store at the branch. You are looking at this as one unit. And that's where we see the term super cloud is more applicable because what are the qualities that you require if you're in a super cloud, right? You need choice of infrastructure, you need, but at the same time you need a single pain, a single platform for you to build your innovations on regardless of which cloud you're doing it on, right? So I think Super Cloud is actually a more tightly integrated orchestrated management philosophy we think. >>So let's get into some of the super cloud type trends that we've been reporting on. Again, the purpose of this event is to, as a pilots, to get the conversations flowing with with the influencers like yourselves who are running companies and building products and the builders, Amazon and Azure are doing extremely well. Google's coming up in third cloudworks in public cloud. We see the use cases on premises use cases. Kubernetes has been an interesting phenomenon because it's become from the developer side a little bit, but a lot of ops people love Kubernetes. It's really more of an ops thing. You mentioned OpenStack earlier. Kubernetes kind of came out of that open stack. We need an orchestration and then containers had a good shot with, with Docker. They re pivoted the company. Now they're all in an open source. So you got containers booming and Kubernetes as a new layer there. What's the, what's the take on that? What does that really mean? Is that a new defacto enabler? It >>Is here. It's for here for sure. Every enterprise somewhere else in the journey is going on. And you know, most companies are, 70 plus percent of them have won two, three container based, Kubernetes based applications now being rolled out. So it's very much here, it is in production at scale by many customers. And the beauty of it is, yes, open source, but the biggest gating factor is the skill set. And that's where we have a phenomenal engineering team, right? So it's, it's one thing to buy a tool >>And just be clear, you're a managed service for Kubernetes. >>We provide, provide a software platform for cloud acceleration as a service and it can run anywhere. It can run in public private. We have customers who do it in truly multi-cloud environments. It runs on the edge, it runs at this in stores are thousands of stores in a retailer. So we provide that and also for specific segments where data sovereignty and data residency are key regulatory reasons. We also un OnPrem as an air gap version. >>Can you give an example on how you guys are deploying your platform to enable a super cloud experience for your >>Customer? Right. So I'll give you two different examples. One is a very large networking company, public networking company. They have, I dunno, hundreds of products, hundreds of r and d teams that are building different, different products. And if you look at few years back, each one was doing it on a different platforms but they really needed to bring the agility and they worked with us now over three years where we are their build test dev pro platform where all their products are built on, right? And it has dramatically increased their agility to release new products. Number two, it actually is a light out operation. In fact the customer says like, like the Maytag service person cuz we provide it as a service and it barely takes one or two people to maintain it for them. >>So it's kinda like an SRE vibe. One person managing a >>Large 4,000 engineers building infrastructure >>On their tools, >>Whatever they want on their tools. They're using whatever app development tools they use, but they use our platform. >>What benefits are they seeing? Are they seeing speed? >>Speed, definitely. Okay. Definitely they're speeding. Speed uniformity because now they're building able to build, so their customers who are using product A and product B are seeing a similar set of tools that are being used. >>So a big problem that's coming outta this super cloud event that we're, we're seeing and we've heard it all here, ops and security teams cuz they're kind of too part of one theme, but ops and security specifically need to catch up speed wise. Are you delivering that value to ops and security? Right. >>So we, we work with ops and security teams and infrastructure teams and we layer on top of that. We have like a platform team. If you think about it, depending on where you have data centers, where you have infrastructure, you have multiple teams, okay, but you need a unified platform. Who's your buyer? Our buyer is usually, you know, the product divisions of companies that are looking at or the CTO would be a buyer for us functionally cio definitely. So it it's, it's somewhere in the DevOps to infrastructure. But the ideal one we are beginning to see now many large corporations are really looking at it as a platform and saying we have a platform group on which any app can be developed and it is run on any infrastructure. So the platform engineering teams, >>You working two sides of that coin. You've got the dev side and then >>And then infrastructure >>Side side, okay. >>Another customer like give you an example, which I would say is kind of the edge of the store. So they have thousands of stores. Retail, retail, you know food retailer, right? They have thousands of stores that are on the globe, 50,000, 60,000. And they really want to enhance the customer experience that happens when you either order the product or go into the store and pick up your product or buy or browse or sit there. They have applications that were written in the nineties and then they have very modern AIML applications today. They want something that will not have to send an IT person to install a rack in the store or they can't move everything to the cloud because the store operations has to be local. The menu changes based on, It's a classic edge. It's classic edge. Yeah. Right. They can't send it people to go install rack access servers then they can't sell software people to go install the software and any change you wanna put through that, you know, truck roll. So they've been working with us where all they do is they ship, depending on the size of the store, one or two or three little servers with instructions that >>You, you say little servers like how big one like a net box box, like a small little >>Box and all the person in the store has to do like what you and I do at home and we get a, you know, a router is connect the power, connect the internet and turn the switch on. And from there we pick it up. >>Yep. >>We provide the operating system, everything and then the applications are put on it. And so that dramatically brings the velocity for them. They manage >>Thousands of them. True plug and play >>Two, plug and play thousands of stores. They manage it centrally. We do it for them, right? So, so that's another example where on the edge then we have some customers who have both a large private presence and one of the public clouds. Okay. But they want to have the same platform layer of orchestration and management that they can use regardless of the location. So >>You guys got some success. Congratulations. Got some traction there. It's awesome. The question I want to ask you is that's come up is what is truly cloud native? Cuz there's lift and shift of the cloud >>That's not cloud native. >>Then there's cloud native. Cloud native seems to be the driver for the super cloud. How do you talk to customers? How do you explain when someone says what's cloud native, what isn't cloud native? >>Right. Look, I think first of all, the best place to look at what is the definition and what are the attributes and characteristics of what is truly a cloud native, is CNC foundation. And I think it's very well documented where you, well >>Con of course Detroit's >>Coming here, so, so it's already there, right? So, so we follow that very closely, right? I think just lifting and shifting your 20 year old application onto a data center somewhere is not cloud native. Okay? You can't put to cloud native, you have to rewrite and redevelop your application and business logic using modern tools. Hopefully more open source and, and I think that's what Cloudnative is and we are seeing a lot of our customers in that journey. Now everybody wants to be cloudnative, but it's not that easy, okay? Because it's, I think it's first of all, skill set is very important. Uniformity of tools that there's so many tools there. Thousands and thousands of tools you could spend your time figuring out which tool to use. Okay? So I think the complexities there, but the business benefits of agility and uniformity and customer experience are truly them. >>And I'll give you an example. I don't know how clear native they are, right? And they're not a customer of ours, but you order pizzas, you do, right? If you just watch the pizza industry, how dominoes actually increase their share and mind share and wallet share was not because they were making better pizzas or not, I don't know anything about that, but the whole experience of how you order, how you watch what's happening, how it's delivered. There were a pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow to the application changes what the expectations of the, for the customer. >>Customer, the customer's expectations change, right? Once you get used to a better customer experience, you learn >>Best car. To wrap it up, I wanna just get your perspective again. One of the benefits of chatting with you here and having you part of the Super Cloud 22 is you've seen many cycles, you have a lot of insights. I want to ask you, given your career where you've been and what you've done and now the CEO platform nine, how would you compare what's happening now with other inflection points in the industry? And you've been, again, you've been an entrepreneur, you sold your company to Oracle, you've been seeing the big companies, you've seen the different waves. What's going on right now put into context this moment in time around Super >>Cloud. Sure. I think as you said, a lot of battles. Cars being been, been in an asp, been in a realtime software company, being in large enterprise software houses and a transformation. I've been on the app side, I did the infrastructure right and then tried to build our own platforms. I've gone through all of this myself with a lot of lessons learned in there. I think this is an event which is happening now for companies to go through to become cloud native and digitalize. If I were to look back and look at some parallels of the tsunami that's going on is a couple of paddles come to me. One is, think of it, which was forced to honors like y2k. Everybody around the world had to have a plan, a strategy, and an execution for y2k. I would say the next big thing was e-commerce. I think e-commerce has been pervasive right across all industries. >>And disruptive. >>And disruptive, extremely disruptive. If you did not adapt and adapt and accelerate your e-commerce initiative, you were, it was an existence question. Yeah. I think we are at that pivotal moment now in companies trying to become digital and cloudnative that know that is what I see >>Happening there. I think that that e-commerce was interesting and I think just to riff with you on that is that it's disrupting and refactoring the business models. I think that is something that's coming out of this is that it's not just completely changing the game, it's just changing how you operate, >>How you think, and how you operate. See, if you think about the early days of eCommerce, just putting up a shopping cart didn't made you an eCommerce or an E retailer or an e e customer, right? Or so. I think it's the same thing now is I think this is a fundamental shift on how you're thinking about your business. How are you gonna operate? How are you gonna service your customers? I think it requires that just lift and shift is not gonna work. >>Mascar, thank you for coming on, spending the time to come in and share with our community and being part of Super Cloud 22. We really appreciate, we're gonna keep this open. We're gonna keep this conversation going even after the event, to open up and look at the structural changes happening now and continue to look at it in the open in the community. And we're gonna keep this going for, for a long, long time as we get answers to the problems that customers are looking for with cloud cloud computing. I'm Sean Feer with Super Cloud 22 in the Cube. Thanks for watching. >>Thank you. Thank you, John. >>Hello. Welcome back. This is the end of our program, our special presentation with Platform nine on cloud native at scale, enabling the super cloud. We're continuing the theme here. You heard the interviews Super Cloud and its challenges, new opportunities around the solutions around like Platform nine and others with Arlon. This is really about the edge situations on the internet and managing the edge multiple regions, avoiding vendor lock in. This is what this new super cloud is all about. The business consequences we heard and and the wide ranging conversations around what it means for open source and the complexity problem all being solved. I hope you enjoyed this program. There's a lot of moving pieces and things to configure with cloud native install, all making it easier for you here with Super Cloud and of course Platform nine contributing to that. Thank you for watching.

Published Date : Oct 18 2022

SUMMARY :

See you soon. but kind of the same as the first generation. And so you gotta rougher and IT kind of coming together, but you also got this idea of regions, So I think, you know, in in the context of this, the, this, Can you scope the scale of the problem? the problem that the scale creates, you know, there's various problems, but I think one, And that is just, you know, one example of an issue that happens. Can you share your reaction to that and how you see this playing out? which is, you know, you have your perfectly written code that is operating just fine on your And so as you give that change to then run at your production edge location, And you guys have a solution you're launching. So what our LA you do in a But again, it gets, you know, processed in a standardized way. So keeping it smooth, the assembly on things are flowing. Because developers, you know, there is, developers are responsible for one picture of So the DevOps is the cloud needed developer's. And so Arlon addresses that problem at the heart of it, and it does that using existing So I'm assuming you have that thought through, can you share open source and commercial relationship? products starting all the way with fision, which was a serverless product, you know, that we had built to buy, but also actually kind of date the application, if you will. I think one is just, you know, this, this, this cloud native space is so vast I have to ask you now, let's get into what's in it for the customer. And so, and there's multiple, you know, enterprises that we talk to, shared that this is a major challenge we have today because we have, you know, I'm an enterprise, I got tight, you know, I love the open source trying And that's where, you know, platform line has a role to play, which is when been some of the feedback? And the customer said, If you had it today, I would've purchased it. So next question is, what is the solution to the customer? So I think, you know, one of the core tenets of Platform nine has always been been that And now they have management challenges. Especially operationalizing the clusters, whether they want to kind of reset everything and remove things around and And And arlon by the way, also helps in that direction, but you also need I mean, what's the impact if you do all those things, as you mentioned, what's the impact of the apps? And so this really gives them, you know, the right tooling for that. So this is actually a great kind of relevant point, you know, as cloud becomes more scalable, So these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to to be supporting the business, you know, the back office and the maybe terminals and that, you know, that the, the technology that's, you know, that's gonna drive your top line is If all the things happen the way we want 'em to happen, The magic wand, the magic dust, he's running that at a nimble, nimble team size of at the most, Just taking care of the CIO doesn't exist. Thank you for your time. Thanks for Great to see you and great to see congratulations on the success And now the Kubernetes layer that we've been working on for years is Exactly. you know, the new Arlon, our, our lawn, and you guys just launched the So I think, I think I'm, I'm glad you mentioned it, everybody or most people know about infrastructures I mean now with open source so popular, you don't have to have to write a lot of code, you know, the emergence of systems and layers to help you manage that complexity is becoming That's, I wrote a LinkedIn post today was comments about, you know, hey, enterprise is a new breed. you know, you think you have things under control, but some people from various teams will make changes here in the industry technical, how would you look at the super cloud trend that's emerging? the way I interpret that is, you know, clouds and infrastructure, It's IBM's, you know, connection for the internet at the, this layer that has simplified, you know, computing and, the physics and the, the atoms, the pro, you know, this is where the innovation, the state that you want and more consistency. the DevOps engineers, they get a a ways to So how do you guys look at the workload native ecosystem like K native, where you can express your application in more at It's kinda like an EC two instance, spin up a cluster. And then you can stamp out your app, your applications and your clusters and manage them And it's like a playbook. You just tell the system what you want and then You need edge's code, but then you can configure the code by just saying do it. And that is just complexity for the people operating this or configuring this, What do you expect to see at Coan this year? If you look at a stack necessary for hosting We would to joke we, you know, about, about the dream. So the successor to Kubernetes, you know, I don't Yeah, I think the, the reigning in the chaos is key, you know, Now we have now visibility into But roughly speaking when we say, you know, They have some SaaS apps, but mostly it's the ecosystem. you know, that they're, they will keep catering to, they, they will continue to find terms of, you know, the the new risk and arm ecosystems it's, it's hardware and he got software and you got middleware and he kind over, Great to have you on. What's interest thing about what you guys are doing at Platform nine? clouds, you know, the application world is moving very fast in trying to Patrick, we were talking before we came on stage here about your background and we were gonna talk about the glory days in So you saw that whole growth. So I think things are in And if you look at the tech trends, GDPs down, but not tech. Cuz the pandemic showed everyone digital transformation is here and more And modernizing Infras infrastructure is not you know, more, more dynamic, more real. So it's you know, multi-cloud. So you got containers And you know, most companies are, 70 plus percent of them have won two, It runs on the edge, And if you look at few years back, each one was doing So it's kinda like an SRE vibe. Whatever they want on their tools. to build, so their customers who are using product A and product B are seeing a similar set Are you delivering that value to ops and security? Our buyer is usually, you know, the product divisions of companies You've got the dev side and then that happens when you either order the product or go into the store and pick up your product or like what you and I do at home and we get a, you know, a router is And so that dramatically brings the velocity for them. Thousands of them. of the public clouds. The question I want to ask you is that's How do you explain when someone says what's cloud native, what isn't cloud native? is the definition and what are the attributes and characteristics of what is truly a cloud native, Thousands and thousands of tools you could spend your time figuring out which I don't know anything about that, but the whole experience of how you order, Being agility and having that flow to the application changes what the expectations of One of the benefits of chatting with you here and been on the app side, I did the infrastructure right and then tried to build our own If you did not adapt and adapt and accelerate I think that that e-commerce was interesting and I think just to riff with you on that is that it's disrupting How are you gonna service your Mascar, thank you for coming on, spending the time to come in and share with our community and being part of Thank you, John. I hope you enjoyed this program.

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Jack Andersen & Joel Minnick, Databricks | AWS Marketplace Seller Conference 2022


 

(upbeat music) >> Welcome back everyone to The Cubes coverage here in Seattle, Washington. For AWS's Marketplace Seller Conference. It's the big news within the Amazon partner network, combining with marketplace, forming the Amazon partner organization. Part of a big reorg as they grow to the next level, NextGen cloud, mid-game on the chessboard. Cube's got it covered. I'm John Furry, your host at Cube. Great guests here from Data bricks. Both cube alumni's. Jack Anderson, GM and VP of the Databricks partnership team for AWS. You handle that relationship and Joel Minick vice president of product and partner marketing. You guys have the keys to the kingdom with Databricks and AWS. Thanks for joining. Good to see you again. >> Thanks for having us back. >> Yeah, John, great to be here. >> So I feel like we're at Reinvent 2013. Small event, no stage, but there's a real shift happening with procurement. Obviously it's a no brainer on the micro, you know, people should be buying online. Self-service, Cloud Scale. But Amazon's got billions being sold through their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website, marketplace. Merge our partner organizations, have more synergy and frictionless experiences so everyone can make more money and customer's are going to be happier. >> Yeah, that's right. >> I mean, you're running relationship. You're in the middle of it. >> Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do, is to work with Amazon on these really, you know, unique use cases. >> You know, I interviewed Ali many times over the years. I remember many years ago, maybe six, seven years ago, we were talking. He's like, "we're all in on AWS." Obviously now the success of Databricks, you've got multiple clouds, see that. Customers have choice. But I remember the strategy early on. It was like, we're going to be deep. So this is, speaks volumes to the relationship you have. Years. Jack, take us through the relationship that Databricks has with AWS from a partner perspective. Joel, and from a product perspective. Because it's not like you guys are Johnny come lately, new to the scene. >> Right. >> You've been there, almost president creation of this wave. What's the relationship and how does it relate to what's going on today? >> So most people may not know that Databricks was born on AWS. We actually did our first $100 million of revenue on Amazon. And today we're obviously available on multiple clouds. But we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon, and marketplace broadens our reach. And so, we think of marketplace in three different aspects. We've got the marketplace private offer business, which we've been doing for a number of years. Matter of fact, we were driving well over a hundred percent year over year growth in private offers. And we have a nine figure business. So it's a very significant business. And when a customer uses a private offer, that private offer counts against their private pricing agreement with AWS. So they get pricing power against their private pricing. So it's really important it goes on their Amazon bill. In may we launched our pay as you go, on demand offering. And in five short months, we have well over a thousand subscribers. And what this does, is it really reduces the barriers to entry. It's low friction. So anybody in an enterprise or startup or public sector company can start to use Databricks on AWS, in a consumption based model, and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation, pilots, POCs. They're really learning the value of that first, use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offer, CPPO. Super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with Databricks on behalf of customers. >> So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data, coming in with the buyers you get. And obviously the integration piece all fitting in there. >> Exactly. >> Okay, so those are the offers, that's current, what's in marketplace today. Is that the products... What are people buying? >> Yeah. >> I mean, I guess what's the... Joel, what are people buying in the marketplace? And what does it mean for them? >> So fundamentally what they're buying is the ability to take silos out of their organization. And that is the problem that Databricks is out there to solve. Which is, when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data. And your teams are trying to use all of this data to solve really complicated problems. And as Databricks, as the Lakehouse Company, what we're helping customers do is, how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find, through the marketplace, those rapid adoption use cases where they can get rid of these data warehousing, data lake silos they've had in the past. Get their unstructured and structured data onto one data platform, an open data platform, that is no longer adherent to any proprietary formats and standards and something they can, very much, very easily, integrate into the rest of their data environment. Apply one common data governance layer on top of that. So that from the time they ingest that data, to the time they use that data, to the time they share that data, inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform, with that common governance solution, they'd being able to bring all of those use cases together. Across their real time streaming, their data engineering, their BI, their AI. All of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges they just couldn't solve before. A good example of this, you know, one of the world's now largest data streaming platforms runs on Databricks with AWS. And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses. That they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data, from what the customers are doing with their platform and the recommendations they want to push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex. But by building it on Databricks, they were able to release it in record time and have grown at a record pace to now be the number one platform. >> And this product, it's impacting product development. >> Absolutely. >> I mean, this is like the difference between lagging months of product development, to like days. >> Yes. >> Pretty much what you're getting at. >> Yes. >> So total agility. >> Mm-hmm. >> I got that. Okay, now, I'm a customer I want to buy in the marketplace, but you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from AWS's leadership, Chris, was up there speaking, and Mona was, "Hey, he's a CRO conference chief revenue officer" conversation. Which means someone's getting compensated. So, if I'm the sales rep at Databricks, what's my motion to the customer? Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Or, how do you handle it? >> Well, I'd add what Joel just talked about with, you know, with the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, it's the entire Data Bricks offering. And- >> The flagship, all the, the top stuff. >> Everything, the flagship, the complete offering. So it's not segmented. It's not a sub segment. >> Okay. >> It's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we view this two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend Databricks for the right situation. Same thing with Databricks, our sales force wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get Databricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars. You have $5 million of spend. You put that spend through the flywheel with AWS marketplace, and then you can use that in your negotiations with AWS to get better pricing overall. So that's how we view it. >> So customers are driving. This sounds like. >> Correct. For sure. >> So they're looking at this as saying, Hey, I'm going to just get purchasing power with all my relationships. Because it's a solution architectural market, right? >> Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider. If they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing power. >> Okay, Joel, we're going to date ourselves. At least I will. So back in the old days, (group laughter) It used to be, do a Barney deal with someone, Hey, let's go to market together. You got to get paper, you do a biz dev deal. And then you got to say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for Databricks, or any company is, to go find those partners and do deals, versus now Amazon is the center point for the customer. So you can still do those joint deals, but this seems to be flipping the script a little bit. >> Well, it is, but we still have vars and consulting partners that are doing implementation work. Very valuable work, advisory work, that can actually work with marketplace through the CPPO offering. So the marketplace allows multiple ways to procure your solution. >> So it doesn't change your business structure. It just makes it more efficient. >> That's correct. >> That's a great way to say it. >> Yeah, that's great. >> Okay. So, that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >> Yes. >> Absolutely. >> Economically. >> Economically, it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon. Especially when it comes back to co-selling, right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution. And our teams are working backwards from those use cases, you know, to collaborate and land them. >> Yeah. I want to get that out there. Go ahead, Joel. >> So one of the other things I might add to that too, you know, and why this is advantageous for companies like Databricks to work through the marketplace. Is it makes it so much easier for customers to deploy a solution. It's very, literally, one click through the marketplace to get Databricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. >> You know, it's interesting. I want to bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself, EDI back in the old days, you know, all that craziness. Now this is all the internet, basically through the console. I get the infrastructure side, you know, spin up and provision some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage. A little nuanced. Most enterprises aren't yet there of integrating tech, on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrators dilemma, not an innovator's dilemma. So like, I want to integrate. So now I have integration points with Databricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you got to build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or am I off because, no one's going to be buying software like they used to. They buy software to integrate it. >> Yeah, no- >> Because everything's integrated. >> I think AWS has done a great job at creating a partner ecosystem, right? To give customers the right tools for the right jobs. And those might be with third parties. Databricks is doing the same thing with our partner connect program, right? We've got customer partners like Five Tran and DBT that, you know, augment and enhance our platform. And so you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >> Yeah. It's almost like, you know, bundling and un bundling. I was talking about this with, with Dave Alante about Supercloud. Which is why wouldn't a customer want the best solution in their architecture? Period. In its class. If someone's got API security or an API gateway. Well, you know, I don't want to be forced to buy something because it's part of a suite. And that's where you see things get sub optimized. Where someone dominates a category and they have, oh, you got to buy my version of this. >> Joel and I were talking, we were actually saying, what's really important about Databricks, is that customers control the data, right? You want to comment on that? >> Yeah. I was going to say, you know, what you're pushing on there, we think is extraordinarily, you know, the way the market is going to go. Is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically, I think, really strong places, Databricks and AWS have lined up, is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the Lakehouse, one thing we've always been extremely committed to, as a company, is building the data platform on an open foundation. And we do that primarily through Delta Lake and making sure that, to Jack's point, with Databricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed Databricks to have the breadth of integrations that it has with all the other data tools out there. Because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >> When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what am I foreclosing if I go with something else that's not as open? What's the customer's downside as you think about what's around the corner in the industry? Because if you believe it's going to be open, open source, which I think open source software is the software industry, and integration is a big deal. Because software's going to be plentiful. >> Sure. >> Let's face it. It's a good time to be in software business. But Cloud's booming. So what's the downside, from your Databricks perspective? You see a buyer clicking on Databricks versus that alternative. What's potentially should they be a nervous about, down the road, if they go with a more proprietary or locked in approach? >> Yeah. >> Well, I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also, then, beholden to the pace at which that provider is able to innovate. >> Mm-hmm. >> And I think we've seen lots of times over history where, you know, a proprietary format may run ahead, for a while, on a lot of innovation. But as that market control begins to solidify, that desire to innovate begins to degrade. Whereas in the open formats- >> So extract rents versus innovation. (John laughs) >> Exactly. Yeah, exactly. >> I'll say it. >> But in the open world, you know, you have to continue to innovate. >> Yeah. >> And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you are always going to be at the forefront of what is the latest. >> You know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked with proprietary. >> Yeah. >> You know, SNA and IBM, deck net was digital. You know the rest. And then TCPIP was part of the open systems interconnect. >> Mm-hmm. >> Revolutionary (indistinct) a big part of that, as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. >> Yeah. >> But that helped inter operate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid-game, then you get the end game. You're not there at the end game yet at Cloud. But Cloud- >> There's, always some form of lock in, right? Andy Jazzy will address it, you know, when making a decision. But if you're going to make a decision you want to reduce- You don't want to be limited, right? So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now, is an AI driven business, right? And so it has to do with, can you get that data out of silos? Can you organize it and secure it? And then can you work with data scientists to feed those models? >> Yeah. >> In a very consistent manner. And so the tools of tomorrow will, to Joel's point, will be open and we want interoperability with those tools. >> And choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds, is that they have to compete directly too. Redshift competes directly with a lot of other stuff. But they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're going to be, they're onto it. This is the- >> To Amazon's credit by having these solutions that may compete with native services in marketplace, they are providing customers with choice, low price- >> And access to the core value. Which is the hardware- >> Exactly. >> Which is their platform. Okay. So I want to get you guys thought on something else I see emerging. This is, again, kind of Cube rumination moment. So on stage, Chris unpacked a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing, compensation, workflows, services behind the curtain. And one of those things he mentioned was, they talk about resellers or channel partners, depending upon what you talk about. We believe, Dave and I believe on the Cube, that the entire indirect sales channel of the industry is going to be disrupted radically. Because those players were selling hardware in the old days and software. That game is going to change. You mentioned you guys have a program, let me get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in. Which means that the old reseller channels are going to be rewritten. They're going to be refactored with this new kinds of access. Because you've got scale, you've got money and you've got product. And you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, a value added reseller or VAB or business. >> You've got to evolve. >> You got to, you got to be here. >> Yes. >> Yeah. >> How are you guys working with those partners? Because you say you have a product in your marketplace there. How do I make money if I'm a reseller with Databricks, with Amazon? Take me through that use case. >> Well I'll let Joel comment, but I think it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations. They need expertise from consulting and SI partners. If those consulting and SI partners happen to resell the solution as well. Well, that's another aspect of their business. But I really think it is the expertise that the partners bring to help customers get outcomes. >> Joel, channel big opportunity for Amazon to reimagine this. >> For sure. Yeah. And I think, you know, to your comment about how do resellers take advantage of that, I think what Jack was pushing on is spot on. Which is, it's becoming more and more about the expertise you bring to the table. And not just transacting the software. But now actually helping customers make the right choices. And we're seeing, you know, both SIs begin to be able to resell solutions and finding a lot of opportunity in that. >> Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's going to be the evolution that this goes. >> At the end of the day, it's about services, right? >> For sure. Yeah. >> I mean... >> You've got a great service. You're going to have high gross profits. >> Yeah >> Managed service provider business is alive and well, right? Because there are a number of customers that want that type of a service. >> I think that's going to be a really hot, hot button for you guys. I think being the way you guys are open, this channel, partner services model coming in, to the fold, really kind of makes for kind of that Supercloud like experience, where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on, within Databricks. >> For sure. >> On top of this ecosystem. How does that work? This is kind of like, hasn't been written up in business school and case studies yet. This is new. What is this? >> I think, you know, what it comes down to is, you're seeing ecosystems begin to evolve around the data platforms. And that's going to be one of the big, kind of, new horizons for us as we think about what drives ecosystems. It's going to be around, well, what's the data platform that I'm using? And then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around Databricks in its Lakehouse platform as well. As customers are looking at well, if I'm standing these Lakehouses up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >> I mean you think about ecosystem theory, we're living a whole nother dream. And I'm not kidding. It hasn't yet been written up and for business school case studies is that, we're now in a whole nother connective tissue, ecology thing happening. Where you have dependencies and value proposition. Economics, connectedness. So you have relationships in these ecosystems. >> And I think one of the great things about the relationships with these ecosystems, is that there's a high degree of overlap. >> Yeah. >> So you're seeing that, you know, the way that the cloud business is evolving, the ecosystem partners of Databricks, are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for you. >> Joel, Jack, I love it because you know what it means? The best ecosystem will win, if you keep it open. >> Sure, sure. >> You can see everything. If you're going to do it in the dark, you know, you don't know the outcome. I mean, this is really kind of what we're talking about. >> And John, can I just add that when I was at Amazon, we had a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? >> Yeah. >> And so there's a platform decision being made and that ecosystem is going to evolve around the platform. >> Yeah, and I totally agree. And the word innovation gets kicked around. That's why, you know, when we had our Supercloud panel, it was called the innovators dilemma, with a slash through it, called the integrater's dilemma. Innovation is the digital transformation. So- >> Absolutely. >> Like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating? If APIs are connective tissue, what's automation, what's the service messages look like? I mean, a whole nother set of, kind of thinking, goes on in these new ecosystems and these new products. >> And that thinking is, has been born in Delta Sharing, right? So the idea that you can have a multi-cloud implementation of Databricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud solution. >> Well, Databricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great growing ecosystem. And again, I think a shining example of what every enterprise is going to do. Build on top of something, operating model, get that operating model, driving revenue. >> Mm-hmm. >> Yeah. >> Whether, you're Goldman Sachs or capital one or XYZ corporation. >> S and P global, NASDAQ. >> Yeah. >> We've got, you know, the biggest verticals in the world are solving tough problems with Databricks. I think we'd be remiss because if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions. Whether it's the relationship we have with our engineering and service teams. Our marketing teams, you know, product development. And we're going to be at Reinvent. A big presence at Reinvent. We're looking forward to seeing you there, again. >> Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening. This NextGen Cloud is here. We're seeing this evolve, kind of new economics, new value propositions kind of scaling up. Producing more. So you guys are doing a great job. Thanks for coming on the Cube and taking the time. Joel, great to see you at the check. >> Thanks for having us, John. >> Okay. Cube coverage here. The world's changing as APN comes together with the marketplace for a new partner organization at Amazon web services. The Cube's got it covered. This should be a very big, growing ecosystem as this continues. Billions of being sold through the marketplace. And of course the buyers are happy as well. So we've got it all covered. I'm John Furry. your host of the cube. Thanks for watching. (upbeat music)

Published Date : Oct 10 2022

SUMMARY :

You guys have the keys to the kingdom on the micro, you know, You're in the middle of it. you know, unique use cases. to the relationship you have. and how does it relate to And so we see customers, you know, And obviously the integration Is that the products... buying in the marketplace? And that is the problem that Databricks And this product, it's the difference between So how do you guys look at So it's not a subset, it's the Everything, the flagship, and then you can use So customers are driving. For sure. Hey, I'm going to just you know, multiple ISV spend here is that the alternative So the marketplace allows multiple ways So it doesn't change So you guys are actually incented It's the right thing to do for out there. the marketplace to get Databricks stood up I get the infrastructure side, you know, Databricks is doing the same thing And that's where you see And that is one of the things that aren't as open as you guys, down the road, if they go that provider is able to innovate. that desire to innovate begins to degrade. So extract rents versus innovation. Yeah, exactly. But in the open world, you know, And the open source the protocol stacked with proprietary. You know the rest. And so like, you know, that was, I call it the chessboard, you know, And if you look at what every customer's And so the tools of tomorrow And I would say that, you know, And access to the core value. to data centers or software, you know, How are you guys working that the partners bring to to reimagine this. And I think, you know, And that's going to be the Yeah. You're going to have high gross profits. that want that type of a service. I think being the way you guys are open, This is kind of like, And so I think there's, you know, So you have relationships And I think one of the great things And so as you build these because you know what it means? in the dark, you know, that want to build things themselves. to evolve around the platform. And the word innovation more of a, are you open? So the idea that you and the CapEx gift from AWS. Whether, you're Goldman for all of the investments across Joel, great to see you at the check. And of course the buyers

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Stelio D'Alo & Raveesh Chugh, Zscaler | AWS Marketplace Seller Conference 2022


 

(upbeat electronic music) >> Welcome back to everyone, to "theCUBE's" coverage here in Seattle, Washington for Amazon Web Services Partner Marketplace Seller Conference, combining their partner network with Marketplace forming a new organization called AWS Partner Organization. This is "theCUBE" coverage. I'm John Furrier, your host. We've got great "Cube" alumni here from Zscaler, a very successful cloud company doing great work. Stelio D'Alo, senior director of cloud business development and Raveesh Chugh, VP of Public Cloud Partnerships at Zscaler. Welcome back to "theCUBE." Good to see you guys. Thanks for coming on. >> Thank you. >> Thanks having us, John. >> So we've been doing a lot of coverage of Zscaler, what a great success story. I mean, the numbers are great. The business performance, it's in the top two, three, one, two, three in all metrics on public companies, SaaS. So you guys, check. Good job. >> Yes, thank you. >> So you guys have done a good job. Now you're here, selling through the Marketplace. You guys are a world class performing company in cloud SaaS, so you're in the front lines doing well. Now, Marketplace is a procurement front end opportunity for people to buy. Hey, self-service, buy and put things together. Sounds novel, what a great concept. Great cloud life. >> Yes. >> You guys are participating and now sellers are coming together. The merger of the public, the partner network with Marketplace. It feels like this is a second act for AWS to go to the next level. They got their training wheels done with partners. Now they're going to the next level. What do you guys think about this? >> Well, I think you're right, John. I think it is very much something that is in keeping with the way AWS does business. Very Amazonian, they're working back from the customer. What we're seeing is, our customers and in general, the market is gravitating towards purchase mechanisms and route to market that just are lower friction. So in the same way that companies are going through their digital transformations now, really modernizing the way they host applications and they reach the internet. They're also modernizing on the purchasing side, which is super exciting, because we're all motivated to help customers with that agility. >> You know, it's fun to watch and again I'm being really candid and props to you guys as a company. Now, everyone else is kind of following that. Okay, lift and shift, check, doing some things. Now they go, whoa, I can really build on this. People are building their own apps for their companies. Going to build their own stuff. They're going to use piece parts. They're going to put it together in a really scalable way. That's the new normal. Okay, so now they go okay, I'm going to just buy through the market, I get purchasing power. So you guys have been a real leader with AWS. Can you share what you guys are doing in the Marketplace? I think you guys are a nice example of how to execute the Marketplace. Take us through. What are you guys offering there? What's the contract look like? Is it multi-pronged? What's the approach? What do customers get if they go to the marketplace for Zscaler? >> Yeah, so it's been a very exciting story and been a very pleasing one for us with AWS marketplace. We see a huge growth potentially. There are more than 350,000 customers that are actively buying through Marketplace today. We expect that number to grow to around a million customers by the next, I would say, five to ten years and we want to be part of this wave. We see AWS Marketplace to be a channel where not only our resalers or our channel partners can come and transact, but also our GSIs like Accenture want to transact through this channel. We are doing a lot, in terms of bringing new customers through Marketplace, who want to not only close their deals, but close it in the next few hours. That's the beauty of Marketplace, the agility, the flexibility in terms of pricing that it provides to ISVs like us. If a customer wants to delay their payments by a couple of quarters, Marketplace supports that. If a customer wants to do monthly payments, Marketplace supports that. We are seeing lot of customers, big customers, that have signed EDPs, enterprise discount plans with AWS. These are multi-year cloud commits coming to us and saying we can retire our EDPs with AWS if we transact your solution through AWS Marketplace. So what we have done, as of today, we have all of our production services enabled through AWS Marketplace. What that means for customers, they can now retire their EDPs by buying Zscaler products through AWS Marketplace and in return get the full benefit of maximizing their EDP commits with AWS. >> So you guys are fully committed, no toe on the water, as we heard. You guys are all in. >> Absolutely, that's exactly the way to put it. We're all in, all of our solutions are available in the marketplace. As you mentioned, we're a SaaS provider. So we're one of the vendors in the Marketplace that have SaaS solutions. So unlike a lot of customers and even the market in general, associate the Marketplace for historical reasons, the way it started with a lot of monthly subscriptions and just dipping your toe in it from a consumer perspective. Whereas we're doing multimillion dollar, multi-year SaaS contracts. So the most complicated kinds of transactions you'd normally associate with enterprise software, we're doing in very low friction ways. >> On the Zscaler side going in low friction. >> Yep, yeah, that's right. >> How about the customer experience? >> So it is primarily the the customer that experiences. >> Driving it? >> Yeah, they're driving it and it's because rather than traditional methods of going through paperwork, purchase orders- >> What are some of the things that customers are saying about this, bcause I see two benefits, I'll say that. The friction, it's a channel, okay, for Zscaler. Let's be clear, but now you have a customer who's got a lot of Amazon. They're a trusted partner too. So why wouldn't they want to have one point of contact to use their purchasing power and you guys are okay with that. >> We're absolutely okay with it. The reason being, we're still doing the transaction and we can do the transaction with our... We're a channel first company, so that's another important distinction of how people tend to think of the Marketplace. We go through channel. A lot of our transactions are with traditional channel partners and you'd be surprised the kinds of, even the Telcos, carrier providers, are starting to embrace Marketplace. So from a customer perspective, it's less paperwork, less legal work. >> Yeah, I'd love to get your reaction to something, because I think this highlights to me what we've been reporting on with "theCUBE" with super cloud and other trends that are different in a good way. Taking it to the next level and that is that if you look at Zscaler, SaaS, SaaS is self-service, the scale, there's efficiencies. Marketplace first started out as a self-service catalog, a website, you know, click and choose, but now it's a different. He calls it a supply chain, like the CICD pipeline of buying software. He mentions that, there's also services. He put the Channel partners can come in. The GSIs, global system integrators can come in. So it's more than just a catalog now. It's kind of self-service procurement more than it is just a catalog of buy stuff. >> Yes, so yeah, I feel CEOs, CSOs of today should understand what Marketplace brings to the bear in terms of different kinds of services or Zscaler solutions that they can acquire through Marketplace and other ISV solutions, for that matter. I feel like we are at a point, after the pandemic, where there'll be a lot of digital exploration and companies can do more in terms of not just Marketplace, but also including the channel partners as part of deals. So you talked about channel conflict. AWS addressed this by bringing a program called CPPO in the picture, Channel Partner Private Offers. What that does is, we are not only bringing all our channel partners into deals. For renewals as well, they're the partner of record and they get paid alongside with the customer. So AWS does all the heavy lifting, in terms of disbursements of payments to us, to the channel partner, so it's a win-win situation for all. >> I mean, private offers and co-sale has been very popular. >> It has been, and that is our bread and butter in the Marketplace. Again, we do primarily three year contracts and so private offers work super well. A nice thing for us as a vendor is it provides a great amount of flexibility. Private Offer gives you a lot of optionality, in terms of how the constructs of the deal and whether or not you're working with a partner, how the partner is utilizing as well to resell to the end user. So, we've always talked about AWS giving IT agility. This gives purchasing and finance business agility. >> Yeah, and I think this comes up a lot. I just noticed this happening a lot more, where you see dedicated sessions, not just on DevOps and all the goodies of the cloud, financial strategy. >> Yeah. >> Seeing a lot more conversation around how to operationalize the business transactions in the cloud. >> Absolutely. >> This is the new, I mean it's not new, it's been thrown around, but not at a tech conference. You don't see that. So I got to ask you guys, what's the message to the CISOs and executives watching the business people about Zscaler in the Marketplace? What should they be looking at? What is the pitch for Zscaler for the Marketplace buyer? >> So I would say that we are a cloud-delivered network security service. We have been in this game for more than a decade. We have years of early head start with lots of features and functionality versus our competitors. If customers were to move into AWS Cloud, they can get rid of their next-gen firewalls and just have all the traffic routed through our Zscaler internet access and use Zscaler private access for accessing their private applications. We feel we have done everything in our capacity, in terms of enabling customers through Marketplace and will continue to participate in more features and functionality that Marketplace has to offer. We would like these customers to take advantage of their EDPs as well as their retirement and spend for the multi-commit through AWS Marketplace. Learn about what we have to offer and how we can really expedite the motion for them, if they want to procure our solutions through Marketplace >> You know, we're seeing an ability for them to get more creative, more progressive in terms of the purchasing. We're also doing, we're really excited about the ability to serve multiple markets. So we've had an immense amount of success in commercial. We also are seeing increasing amount of public sector, US federal government agencies that want to procure this way as well for the same reasons. So there's a lot of innovation going on. >> So you have the FedRAMP going on, you got all those certifications. >> Exactly right. So we are the first cloud-native solution to provide IL5 ATO, as well as FedRAMP pie and we make that all available, GSA schedule pricing through the AWS Marketplace, again through FSIs and other resellers. >> Public private partnerships have been a big factor, having that span of capability. I got to ask you about, this is a cool conversation, because now you're like, okay, I'm selling through the Marketplace. Companies themselves are changing how they operate. They don't just buy software that we used to use. So general purpose, bundled stuff. Oh yeah, I'm buying this product, because this has got a great solution and I have to get forced to use this firewall, because I bought this over here. That's not how companies are architecting and developing their businesses. It's no longer buying IT. They're building their company digitally. They have to be the application. So they're not sitting around, saying hey, can I get a solution? They're building and architecting their solution. This is kind of like the new enterprise that no one's talking about. They kind of, got to do their own work. >> Yes. >> There's no general purpose solution that maps every company. So they got to pick the best piece parts and integrate them. >> Yes and I feel- >> Do you guys agree with that? >> Yeah, I agree with that and customers don't want to go for point solutions anymore. They want to go with a platform approach. They want go with a vendor that can not only cut down their vendors from multi-dozens to maybe a dozen or less and that's where, you know, we kind of have pivoted to the platform-centric approach, where we not only help customers with Cloud Network Security, but we also help customers with Cloud Native Application Protection Platform that we just recently launched. It's going by the name of the different elements, including Cloud Security Posture Management, Cloud Identity Event Management and so we are continuously doing more and more on the configuration and vulnerability side space. So if a customer has an AWS S3 bucket that is opened it can be detected and can be remediated. So all of those proactive steps we are taking, in terms of enhancing our portfolio, but we have come a long way as a company, as a platform that we have evolved in the Marketplace. >> What's the hottest product? >> The hottest product? >> In Marketplace right now. >> Well, the fastest growing products include our digital experience products and we have new Cloud Protection. So we've got Posture and Workload Protection as well and those are the fastest growing. For AWS customers a strong affinity also for ZPA, which provides you zero trust access to your workloads on AWS. So those are all the most popular in Marketplace. >> Yeah. >> So I would like to add that we recently launched and this has been a few years, a couple of years. We launched a product called Zscaler Digital X, the ZDX. >> Mm-hmm. >> What that product does is, let's say you're making a Zoom call and your WiFi network is laggy or it's a Zoom server that's laggy. It kind of detects where is the problem and it further tells the IT department you need to fix either the server on which Zoom is running, or fix your home network. So that is the beauty of the product. So I think we are seeing massive growth with some of our new editions in the portfolio, which is a long time coming. >> Yeah and certainly a lot of growth opportunities for you guys, as you come in. Where do you see Zscaler's big growth coming from product-wise? What's the big push? Actually, this is great upside for you here. >> Yeah. >> On the go to market side. Where's the big growth for Zscaler right now? So I think we are focused as a company on zero trust architecture. We want to securely connect users to apps, apps to apps, workloads to workloads and machines to machines. We want to give customers an experience where they have direct access to the apps that's hidden from the outside world and they can securely connect to the apps in a very succinct fashion. The user experience is second to none. A lot of customers use us on the Microsoft Office 365 side, where they see a lag in connecting to Microsoft Office 365 directly. They use the IE service to securely connect. >> Yeah, latency kills. >> Microsoft Office 365. >> Latency kills, as we always say, you know and security, you got to look at the pattern, you want to see that data. >> Yeah, and emerging use cases, there is an immense amount of white space and upside for us as well in emerging use cases, like OT, 5G, IOT. >> Yeah. >> Federal government, DOD. >> Oh god, tactical edge government. >> Security at the edge, absolutely, yeah. >> Where's the big edge? What's the edge challenge right now, if you have to put your finger on the edge, because right now that's the hot area, we're watching that. It's going to be highly contested. It's not yet clear, I mean certainly hybrid is the operating model, cloud, distributing, computing, but edge has got unique things that you can't really point to on premises that's the same. It's highly dynamic, you need high bandwidth, low latency, compute at the edge. The data has to be processed right there. What's the big thing at the edge right now? >> Well, so that's probably an emerging answer. I mean, we're working with our customers, they're inventing and they're kind of finding the use cases for those edge, but one of the good things about Zscaler is that we are able to, we've got low latency at the edge. We're able to work as a computer at the edge. We work on Outpost, Snowball, Snowcone, the Snow devices. So we can be wherever our customers need us. Mobile devices, there are a lot of applications where we've got to be either on embedded devices, on tractors, providing security for those IOT devices. So we're pretty comfortable with where we are being the- >> So that's why you guys are financially doing so well, performance wise. I got to ask you though, because I think that brings up the great point. If this is why I like the Marketplace, if I'm a customer, the edge is highly dynamic. It's changing all the time. I don't want to wait to buy something. If I got my solution architects on a product, I need to know I'm going to have zero trust built in and I need to push the button on Zscaler. I don't want to wait. So how does the procurement side impact? What have you guys seen? Share your thoughts on how Marketplace is working from the procurement standpoint, because it seems to me to be fast. Is that right, or is it still slow on their side? On the buyer side, because this to me would be a benefit to developers, if we say, hey, the procurement can just go really fast. I don't want to go through a bunch of PO approvals or slow meetings. >> It can be, that manifests itself in several ways, John. It can be, for instance, somebody wants to do a POC and traditionally you could take any amount of time to get budget approval, take it through. What if you had a pre-approved cloud budget and that was spent primarily through AWS Marketplace, because it's consolidated data on your AWS invoice. The ability to purchase a POC on the Marketplace could be done literally within minutes of the decision being made to go forward with it. So that's kind of a front end, you know, early stage use case. We've got examples we didn't talk about on our recent earnings call of how we have helped customers bring in their procurement with large million dollar, multimillion dollar deals. Even when a resaler's been involved, one of our resaler partners. Being able to accelerate deals, because there's so much less legal work and traditional bureaucratic effort. >> Agility. >> That agility purchasing process has allowed our customers to pull into the quarter, or the end of month, or end of quarter for them, deals that would've otherwise not been able to be done. >> So this is a great example of where you can set policy and kind of create some guard rails around innovation and integration deals, knowing if it's something that the edge is happening, say okay, here's some budget. We approved it, or Amazon gives credits and partnership going on. Then I'd say, hey, well green light this, not to exceed a million dollars, or whatever number in their range and then let people have the freedom to execute. >> You're absolutely right, so from the purchasing side, it does give them that agility. It eliminates a lot of the processes that would push out a purchase in actual execution past when the business decision is made and quite frankly, to be honest, AWS has been very accommodative. They're a great partner. They've invested a lot in Marketplace, Marketplace programs, to help customers do the right thing and do it more quickly as well as vendors like us to help our customers make the decisions they need to. >> Rising tide, a rising tide floats all boats and you guys are a great example of an independent company. Highly successful on your own. >> Yep. >> Certainly the numbers are clear. Wall Street loves Zscaler and economics are great. >> Our customer CSAT numbers are off the scale as well. >> Customers are great and now you've got the Marketplace. This is again, a new normal. A new kind of ecosystem is developing where it's not like the old monolithic ecosystems. The value creation and extraction is happening differently now. It's kind of interesting. >> Yes and I feel we have a long way to go, but what I can tell you is that Zscaler is in this for the long run. We are seeing some of the competitors erupt in the space as well, but they have a long way to go. What we have built requires years worth of R&D and features and thousands of customer's use cases which kind of lead to something what Zscaler has come up with today. What we have is very unique and is going to continuously be an innovation in the market in the years to come. In terms of being more cloud-savvy or more cloud-focused or more cloud-native than what the market has seen so far in the form of next-gen firewalls. >> I know you guys have got a lot of AI work. We've had many conversations with Howie over there. Great stuff and really appreciate you guys participating in our super cloud event we had and we'll see more of that where we're talking about the next generation clouds, really enabling that new disruptive, open-spanning capabilities across multiple environments to run cloud-native modern applications at scale and secure. Appreciate your time to come on "theCUBE". >> Thank you. >> Thank you very much. >> Thanks for having us. >> Thanks, I totally appreciate it. Zscaler, leading company here on "theCUBE" talking about their relationship with Marketplace as they continue to grow and succeed as technology goes to the next level in the cloud. Of course "theCUBE's" covering it here in Seattle. I'm John Furrier, your host. Thanks for watching. (peaceful electronic music)

Published Date : Sep 28 2022

SUMMARY :

Good to see you guys. I mean, the numbers are great. So you guys have done a good job. The merger of the public, So in the same way that companies and props to you guys as a company. and in return get the full benefit So you guys are fully committed, and even the market in general, On the Zscaler side So it is primarily the the customer What are some of the things and we can do the transaction with our... and that is that if you So AWS does all the heavy lifting, I mean, private offers and in terms of how the constructs of the deal the goodies of the cloud, in the cloud. So I got to ask you guys, and just have all the traffic routed in terms of the purchasing. So you have the FedRAMP going on, and we make that all available, This is kind of like the new enterprise So they got to pick the best evolved in the Marketplace. Well, the fastest growing products Zscaler Digital X, the ZDX. So that is the beauty of the product. What's the big push? On the go to market side. and security, you got Yeah, and emerging use cases, on premises that's the same. but one of the good things about Zscaler and I need to push the button on Zscaler. of the decision being made or the end of month, or the freedom to execute. It eliminates a lot of the processes and you guys are a great example Certainly the numbers are clear. are off the scale as well. It's kind of interesting. and is going to continuously the next generation clouds, next level in the cloud.

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Trish Cagliostro, Wiz | AWS Marketplace Seller Conference 2022


 

>>Okay, welcome back everyone. It's the cubes coverage here in Seattle, Washington for Amazon web services, marketplace seller event. Really the big news here is the combination of the partner network with marketplace to one organization called the Amazon web services partner organization. Again, great news. Things are coming together, getting simplified and I'm John furry host of the cube. You've got a great guest here. Trish TRO head of worldwide Alliance at Wiz the fastest growing software company in history. Congratulations. Welcome to the cube. >>Thank you so much. And thanks for having us. >>So we were talking on camera. You had a little insight to a AWS. You jumped on this company. Oh my God. Amazing team. Take us through the story real quick. It's worth noting Wiz the company fastest growth. We're seeing take us through the quick soundbite. >>Sure. So the quick soundbite. So I was at AWS and my husband shared an article with me on cnbc.com about Wiz. They just done a big funding raise and he's like, you really have to read this. And I read it. And I said, oh my God, every single customer that I've met with the last year and a half has this problem. I have to find a way to be there. I don't care if I have to sweep the floors, lucky enough, they needed someone to run channels and alliances. So I did not have to sweep the floors, but for me, you know, when I think about our success, it's really this convergence of a series of things it's it's right time. Right? COVID forced everybody to the cloud, probably a little faster than they were ready to, you know, right market. And we have this convergence of the incredible product market fit, helping customers accelerate their cloud journey securely. And then I can't say enough about the team. You know, I thought it was fascinating, you know, as great as our product is when I got on board, everyone kept telling me, you know, they bought our product because of the team. And I was like, okay, cool. What about the product? And then I met the team and I understood. So jumped >>On one off one rocket ship. Yeah. To go onto another one. Yeah. You like the rocket, you like to ride those big, fast growth companies. You >>Know, I, I wish I was the kind of person where, you know, I just, I need excitement. Right? I'm I love to build. And I've had really good luck that I've always been able to find myself in a place, whether it's at a massive company or a startup to find myself as a builder, which has always been awesome. >>Well, tr it's great to have you on the cube. And a little fun fact is your sister was interviewed here on the cube in 2019 by myself. And so we have the first sisters, both cube alumni. Congratulations. >>I think that's, you know, honestly of all the accomplishments in my career, that's definitely one. I gotta make sure I get a plaque for that. You >>Will get a VIP sticker too. Yes, we, we all >>Sticker. Let's not get crazy now. >>All right. We'll designate in the front page. We'll have a very big story. L fund all good. We'd love the queue. We'd love to get the insight. So I wanna get your thoughts. Okay. You you've seen the Amazon side. You've been on that side. Now you're another side of the table with a partner growing. We're here to seller our conference. Big mission here is let's make things simpler and easier to procure software since you're already fast growing, what's in it for the customer to work through AWS, to get Wiz. Obviously you guys got a lot of demand. Yeah. A lot of money flowing through. You guys have a direct sales force. Are you going through the marketplace? What's the relationship between Wiz and Aish marketplace. >>So huge, honestly, and it's been a huge contributor to our success. We were lucky because we're, we were born during COVID, we're born in the cloud company. We got to build it from the ground up. This wasn't something that we had to go and figure out how to integrate into our existing ecosystem. Our ecosystem is actually built around the marketplace motion. You know, it's, it's interesting as you know, coming from AWS and now being on the other side, you know, something we really put a focus on is, you know, I see a lot of the companies that I was working with, you know, cloud was very much this thing. That's kind of in a silo and it's its own box and it competes internally. And really when you, you get deeper and deeper into the marketplace, it becomes about how do I use the cloud to really accelerate what I'm doing and to integrate it across my different channels. And for us, you know, AWS is our deepest relationship on the partner side. We invested heavily early and often, and it's been amazing. You >>Know, tr I was talking one of the data brick guys as well, and other companies that are big successes. This is a unique time here at the marketplace. We're on the ground floor. You can see here, we're at the, there's no stage. It's the smaller Q small venue, very intimate event. But it reminds me of 2013 when reinvent was starting to get traction second year, small, intimate, little bit bigger, obviously, but this is gonna feel like it's gonna explode. And you mentioned that you guys are building emotions around the ecosystem of the marketplace because you were born, born in the cloud. And COVID, so it's almost like if you're a startup today, why wouldn't you be in the marketplace first? Why even have that motion? So reminds me of the old days of you're a startup. Why not use the cloud? Why build a data center? >>No, and I think that's a really great analogy, you know, at least from what I've seen, it's, it's super interesting as a startup, because part of when you come out with a new technology in a perfect world, customers would already know what you were gonna make and have funding allocated for it. And we would all have this much easier sales cycle. That's not how it works. The customers, you know, as much as they might wanna get your solution, they have real things like budgets to deal with. And so it's really cool because when you work with the marketplace, it's a pool of funding that the customer has allocated on the customer side. It burns down their commit with the, with their different contracts. So that's usually powerful for them, right? Being able to consolidate your it, spend, reduce your overall total cost of ownership is, is usually powerful to the customer. And it on our side is a startup. So not only are they the financial benefits, it also helps you elevate the conversation. You know, a lot of times in the security industry, it's really all about like speeds and beads. That's how we sell cyber crime is 300% on the rise and stuff like that. Right. But being able to kind of get above that and help the customer, you know, have that financial conversation is, is really helpful too. >>So if I'm a startup, I'm a company, what would be the playbook for me and say, you know what, I'm gonna go all in, in the marketplace, I'm just gonna build the best kick ass product. Okay. I got product market fit. I'm gonna focus all my creative energy on building the best tech with the best, best team. All my friends and colleagues, and none of this non says go to market direct Salesforce, go all in on AWS. I know the product market fits there. What's the playbook. What do I do? Do just list it. >>So list, I think this is one of the mistakes that a lot of companies make when, when they first start out with the marketplace, right? They're like I will get to the marketplace and then AWS will sell my solution. I'm done the marketplace really? >>Where's the money back up the truck, come on. >>Exactly. Right? Like they have all these customers, they should just all come to me. Right. And I think that's one of the mistakes that organizations stumble on initially, cuz they go to the marketplace and then AWS is not selling their solution for them immediately. And they're like, the marketplace is a failure and it's really not. It's just the beginning of that. Being able to go into the marketplace, being able, honestly, to set expectations internally and understanding the journey that really comes into play here. You know, building, you know, one of the things that I talk to a lot about my team with is like building success within the sales reps and helping them be big advocates and champions for the marketplace. And the other thing is like, don't assume people know, I can't tell you. I feel like my, my real job at Wiz is I'm like the marketplace evangelist and cheap cuz that's all I do is talk about why they should use the marketplace and how it can solve all these different problems. Don't assume that people know how to do these things. Like you have to keep reiterating the message. You have to find sellers that are ready for it. And then you have to really, you have to teach them how to do it and then align your sales process accordingly. Like confidentiality come up a whole bunch at this conference today. It's important. You need it. >>It's huge. How big is your sales force right now? >>On >>The direct side. >>On the direct side, I think we're like a hundred or something like >>That. So you have, you have people out there on the streets knocking on doors selling. How's that comp decision go internally as you guys have that, what's the, what's the uptake in the marketplace for you guys right now? Is it high? Is it it's >>Been really high honestly. Yeah. It's and we've been really great. We have some incredible champions internally who are really great about sharing their experience, helping other sellers understand like we've, we've honestly had amazing co-sell stories at AWS where they've been so supportive and helpful. And it's amazing. Like we've had so many sellers that have done their first marketplace transaction ever. And now it's like for some of our sellers, they're at the point where they're like, I don't wanna, I don't wanna not do a marketplace transaction. It's just, it's so much easier. Take us >>For the procurement benefits. Take, walk me through what happens on the procurement side. What's the benefits for using the marketplace as you, as the procurement process goes through? >>Oh, from a, from a procurement side, right? It's like, it's simple, right? Like you, you essentially click a button and it's done like from the seller's side, like imagine not having to like chase down 15 different signatures and make sure nobody's on vacation. Right? So it just takes this really convoluted ti process that they would normally deal with. It makes it a lot simpler on the customer side. Right. Being able to have one consolidated is super powerful, burning down against commit, super powerful. And I think that's something that's really helped. Our sellers too, is being able, like we, we spend a tremendous amount of resources on educating our sellers. Not only about how it's gonna help them, but also how it's gonna help the customer too, >>Too. So good internally for you guys frictionless easier, better, better. Sounds like a better path >>On that. Oh, I won't say frictionless. I mean we're, we're about a year into this, but it wasn't so much frictionless, but it's not a hassle itself. Right. It's not a hassle. And it's all about >>On scale one to 10, 10 being frictionless. Would you get a, an eight or >>I'd say like an eight. Yeah. Okay. Okay. Cool. But it's important for organizations to understand that, right? Like that just because there's a little bit of friction at first. Like the most important thing I told my team is they were like, look like, well, why doesn't everybody wanna do this? This is so easy. And a, a good seller will take the hard time every way when they know what the defined outcome is. Yeah. The marketplace to them feels like a shortcut at first. Yeah. So a very much helps them become like, Hey look, this isn't a shortcut. This is gonna help you. Like, this is a good thing. And once you get that adoption like that, that's where the primary friction is. They almost go, is this, is this too good to be true? This can't be real. >>It, it, it almost sounds too good to be true when you think about, okay, so lemme take, I'm gonna put them a sales rep for a second. Like I'm selling WIS and I go and knock on a door and there's a company and I get an, a champion inside the company and says, oh, I love this product. I wanna buy it. I gotta get my PO approved and I gotta go get, I tell my boss about it. Does it go through that kind of normal kind of normal sales motion where you got buy in and now they gotta commit and close and get contract or they just go to the person who runs the account, click the button, like, like, is there, I mean, I'd like to see that shortcut happen. Like so on the customer side, what, what do you see as the process? Is it just go to the console and hit by and >>You know, depends on the customer honestly, and kind of where they are in their cloud journey. You know, really mature customers tend to have a little bit more of a mature process, you know, earlier customers, it tends to be a little less, let's say structured, but no, it's definitely not. The customer just clicks the button and it's done. That would be quite nice. We're just not there yet, but it's definitely a much simpler process cuz you know, you think about it on the customer side when they decide they wanna buy something, especially something new, they don't have allocated funding for us. They have to go build all this justification for funding. They still have to do that. Right. But then now there's a pot of money that they can go to and be able to retire against. There, there, it does help in that sense. A >>Lot. Chris, Chris grew has talked about on his keynote, the buyer journey survey. That seems to be on the, on the customer side. Yeah. Having those processes where they can forecast against it, they kind of know what they're getting. That's that's that's sounds like a great thing that's happening. I wanna get back to this comp issue again. Cause this came up. I heard that a lot. We talked with Chris about the competing thing. That's not an issue in my mind, but I think the factor to me, if I'm looking at this is that if you get the comp right, they can sell it at Amazon. You get comped, your sales people get comped goes through the marketplace. How do you look at that? How do company her look? How do they look at the comp what's what's the deciding factor or is it a non-issue what's the, what's the core. >>So I'm opportunity. I'm gonna be honest. I think I got a little lucky because I think the getting alignment at the executive level that this was something we should do to be totally honest here. Wasn't wasn't super hard. When we presented a clear plan, how we were gonna do it, what other companies were doing, what it did for their business to our executives. We do, we get some pushback. Sure. Healthy questions. Sure. But like it, it really >>Was it margin related or more like operational costs. >>It wasn't even margin related. It was again, more of like, is this, this feels too good to be true kind of thing. So it was more like proving it to them. Like no, like it really can be that easy. Yeah. And then on the, the comp side, right. For us, we look at it as like cost of sales. So yeah. You know, we, we treat it the same way. We treat all other channels and we wanted to make sure for our reps that, you know, when we think about the channel, whether, you know, from, especially with marketplace, like it can't be harder for them to do a marketplace transaction or less incentive for them to do that than a direct one that doesn't incentivize the right behaviors. >>So it's more of an indirect channel play. >>Yeah. So it's all for us. It was about aligning the right incentives to drive the right behaviors. It wasn't, it actually was a pretty short discussion on the confidentiality. Everyone was like, no, this, this makes sense. We should do that. >>Yeah. I mean, I think it's, I think it's an easy, easy, but you have to be organized for it. Like, like Chris said, don't put the toe in the water. Right. Put your flagship offering in there, make it valuable. And then the flag wheel gets going, the Amazon sales people can sell it. Right. They get calm. That's always a good thing. >>Yeah. And I think that's something that was really interesting. Like when we started on the marketplace journey, like I said, it's not just, you get in a marketplace and you're done, you know, Chris talked a lot about ISV accelerate and you know, how you elevate yourself within that program, doing things with ACE, like putting in different opportunities to, to start to essentially build that groundswell to drive co-sell it's, it's gets that first step into it. But there's so much more that, that we're still discovering and learning today is we're building it >>Out. And you said you had some good co-sell examples. >>Oh yeah. So we've had some great Cosell. >>What's your best one. Best one to >>Share. Oh, so my favorite one, I won't say the customer name, but we were in the final stages and a customer was really like, oh, like this is a lot of money. I'm really nervous. And the, they, I think what's crazy is that at AWS you have a different relationship with customers. Like you are truly a trusted advisor and rightfully so. Yeah. AWS really does a great job with making sure their account teams do what's best for the customer. And so an AWS seller or technical resource on an account says, Hey, no, this is the right thing for your business. That is huge for the customer. So we at Wiz actually spend a lot of time investing in enabling and educating the AWS account teams. So they feel comfortable when they get into that situation where the customers nervous of being saying like, no, this is you need to do this. This is >>Gonna be, you carry a lot of weight with the customers. >>Absolutely. >>And so you almost have to treat them like a lunch and learn, get 'em up, find, share. So it's kind of like an indirect relationship for you, but for them it's a part, you know, this is basically a channel. >>Yeah. And I think that's the thing that, that really is something we we've really heavily invested in is, is building. I like call the ground game within AWS. Right? Yeah. Making sure we spend time with enabling their reps. We enable their technical teams lunch and learns, right? Like there's so much energy at AWS to really invest in technical solutions that help their customers. Awesome. Which you don't always find that a lot of partners honestly. >>Well, Trish, great. Great to have you on sharing the AWS relationship story with WIS, gotta ask you, what's it like to be working for the fastest growing startup? What's it like? It's, it's, it's pretty fun. >>You know, it's, let's say I don't ever wake up on a day and say, man, I just wish I had more things to do. No, it's, it's been an incredible journey. The people, you know, my favorite part of a startup is, you know, getting to do this with a bunch of really incredible, awesome people. It's, it's the most fun thing in the world. We've, I've learned more in the last, you know, we like to joke that we're a five year old company and a one year old company at the exact same time. Yeah. And what's cool is we get to learn and, and I I've learned so much this year. >>When was the company officially >>Formed? It was officially formed before. Like, so it was officially formed in February, 2020. We started officially operating in the January following 21. So 21. Yep. >>Yeah. So one and a half years, >>One and a half years. Isn't that crazy? Great. >>And a hundred million ARR already. Yeah. Hitting that. >>Yep. It's been a, a wild journey. I I'll put it that way >>Is the, what's the success of the businesses? It, the onboarding the, is it the business model of freemium? What's the product market fit dynamic. Why is so fast? I mean, that's the needs there? Pandemic fresh, clean piece, piece of paper doing it, right. What's the, why is it? Why is that going so fast? >>Well, I think about this, I've been in the security industry for too many years. And when you think about normal security products, like there's so much time to value, you have to deploy all this infrastructure and then you gotta wait till something happens that you find that's scary, that will excite the customer. Right? It's, it's, it's a lot of time to show value. What blew my mind is the way that we approach our, the problem that we're solving is essentially immediate time to value. So the customer connects within minutes, they're immediately presented with here's your, your top risks. And then they can take action on them. Right? Like it's not just, here's these big threats and detecting, it's actually giving, empowering the customer to go and, and fix things. That's that's powerful for them. Yeah. Yeah. >>So, and the renewals are there coming in, people like the product, >>I mean, we've only been around for a year and a half, so there aren't that many renewals yet, but let's say we have extremely strong renewal rate from our customer base. >>Yeah. I mean you can have when you have a great product. Yeah. Well, thanks for coming on sharing. What's your assessment so far of the database marketplace kind of reorg with APN partner network to have one organization. What does that mean to the, to the market? What does that what's that tell you? >>So I was really excited. So we're actually built this way. So I run both our channels and alliances organization and it was, it was great because it allows these two things to work together and, and very well. And AWS, I think, is realizing the power of bringing those two groups together. So when I saw that, I was like, that's gonna be great. It's gonna make it simpler, easier. And at least for us, it's been really powerful. >>Awesome. Thanks for coming on the cube. Really appreciate it. We'll get you that plaque shortly. >>I thought I was getting a sticker too. >>Don't forget the sticker. Oh, the sticker definitely guaranteed. And we'll give you a VIP icon on our cube alumni network. All >>Right. I like that. >>Thanks for coming out. Alls great stuff. Thanks. Awesome. Thanks for having all best growing company history here on the cube, bringing all the action again, the new flywheel is gonna be procured through the marketplaces. This is obvious how it all kind of works and forms. It's kind of happening in real time. Cube's got you covered on the ground floor here in Seattle with more coverage after the short break.

Published Date : Sep 21 2022

SUMMARY :

Really the big news here is the combination of the partner network with Thank you so much. You had a little insight to a AWS. You know, I thought it was fascinating, you know, as great as our product is when I got on board, You like the rocket, And I've had really good luck that I've always been able to find myself in a place, Well, tr it's great to have you on the cube. I think that's, you know, honestly of all the accomplishments in my career, that's definitely one. Will get a VIP sticker too. Let's not get crazy now. What's the relationship between Wiz and on the other side, you know, something we really put a focus on is, you know, I see a lot of the companies that I was working with, emotions around the ecosystem of the marketplace because you were born, born in the cloud. So not only are they the financial benefits, it also helps you elevate the conversation. So if I'm a startup, I'm a company, what would be the playbook for me and say, you know what, I'm gonna go all So list, I think this is one of the mistakes that a lot of companies make when, when they first start out with the marketplace, And then you have to really, you have to teach them how to do it and then align your sales process accordingly. How big is your sales force right now? decision go internally as you guys have that, what's the, what's the uptake in the marketplace for And now it's like for some of our sellers, they're at the point where they're like, I don't wanna, I don't wanna not do a marketplace transaction. What's the benefits for using but also how it's gonna help the customer too, Sounds like a better path And it's all about Would you get a, an eight or And once you get that adoption like that, that's where the primary friction is. Like so on the customer side, what, what do you see as the process? know, really mature customers tend to have a little bit more of a mature process, you know, earlier customers, That's not an issue in my mind, but I think the factor to me, if I'm looking at this is that if at the executive level that this was something we should do to be totally honest here. you know, when we think about the channel, whether, you know, from, especially with marketplace, like it can't be harder for them to It was about aligning the right incentives to drive the right behaviors. don't put the toe in the water. it's not just, you get in a marketplace and you're done, you know, Chris talked a lot about ISV accelerate and you So we've had some great Cosell. Best one to they, I think what's crazy is that at AWS you have a different relationship with customers. And so you almost have to treat them like a lunch and learn, get 'em up, find, share. I like call the ground game within AWS. Great to have you on sharing the AWS relationship story with WIS, We've, I've learned more in the last, you know, we like to joke that we're a five year old company and We started officially operating in the January following 21. Isn't that crazy? And a hundred million ARR already. I I'll put it that way What's the product market fit dynamic. think about normal security products, like there's so much time to value, you have to deploy all this infrastructure I mean, we've only been around for a year and a half, so there aren't that many renewals yet, but let's say we have extremely What does that mean to the, And AWS, I think, is realizing the power of bringing those two groups together. Thanks for coming on the cube. And we'll give you a VIP icon on our cube alumni I like that. Cube's got you covered on the ground floor here in Seattle with more coverage after the short break.

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Megan Buntain, Seeq | AWS Marketplace Seller Conference 2022


 

>>Hello everyone. I'm John furry with the cube. We're here, live on the ground in Seattle, Washington at the Bellevue Hilton for thes marketplace seller conference. It's kind of like the one and a half inaugural event. They have their first event in 2019, and now with the pandemic, they're re rebooting it, but it's really all about AWS's marketplace and partner network coming together, creating an experience for how people will be buying software and how people will be selling through with their ecosystem. I'm Jennifer, the cube we're here with Megan. Fontain, who's the VP of cloud seek. Who's a seller and partner of AWS making great to see you. Thanks for coming on the cube. >>Thank you so much. It's, it's nice to be back in person and it's great to be with you. >>So watching the progression of how Amazon web services is evolving the marketplace and the partner network, you're starting to see some patterns. One is, I'll say they have their own stuff, and they're addressing that in the room, but they're really letting the thousand flowers bloom in the ecosystem. You hear that every year reinvent, even when Andy Jesse who's now the CEO of Amazon would say, no, we want the best of breed. Best product wins. Adam. Celeste's the same view, new leadership here, the combination of APN partner network with the marketplace now partner organization, APO is the big news. They're open. They're building an API service layer between their old marketplace to create this new model here. What's your, what's your, what's your take? What's your seller view? >>Yeah, so our marketplace and APN journey started with AWS about three years ago. And I think something that was the most profound to me out of the keynote this morning was that Chris Gus, who runs the API organization for ISVs talked about marketplace as the automation layer for how AWS will partner going forward. So an independent software vendor likes, we see that as opening up the door for two things. One, we get to leverage the great global scale and platform of AWS, but then secondly, it really brings together this idea that we will sell together to the end customer through the marketplace. And we will also sell as partners through co-sell and APM. >>You know, I love these kind of new, new development models around channel partners, ISVs at the end of the day, buyers are buying software. Yes. And they're cloud they're on a cloud journey. You're the VP of cloud at the company, your company seek take a minute to explain what your company's known for, what you guys do, your relationship with the market. You're an ISV. Yeah. Where are you guys? Cuz you guys ha have a good thing going on here. What do you guys do? What are you known for >>Sure. So seek is market leading software for advanced analytics for the manufacturing industry. So we're squarely in that industry. ISV, we sell SAS solutions to business buyers who want two things. One is they want technology that they can deploy quickly in their organizations drive that great business value ROI that drives the next level of investment in technology seeks unique offering in marketplace is that we've solved a lot of the challenges around that operational data in manufacturing. So manufacturing the industry, it's going through massive transformation, supply chain, disruption, or coming out of that, the globalization of manufacturing. And yet they have data that they've stored for 20, 30 years, that they're still in the first generation of trying to gain insights from. So that's why seek exists. It's really to bring the insights outta that data and then help the manufacturing customers we work with. Get to the cloud. >>What's interesting. I like your perspective and I want to follow up on that because data analytics used to be this thing. Well, I got a database. Yeah. You hosted on some storage and you got structured data, unstructured data. Okay. You got scale. But now you've got data platforms. You've got data mesh. I think Gardner actually has a different term, but gets a whole nother conversation. Data platforms are diverse. Yeah. They're pervasive. They're part of core infrastructure in cloud. It's not like a point solution anymore. It's gotta be integrated and customers are trying to work on, this is one of the hardest problems today. Yeah. In cloud transformation is the data layer, the relationship to other services. Yeah. >>So the Dataverse common data models. How APIs will interact with data. The trend there though is something that it is the ecosystem that will bring value to customers because no database is gonna serve every need. Right. And you think about the data layer. It really has to solve the problems whereby any application, any user, any insight can be generated almost seamlessly. And we're really on the first wave of that journey. But I think a, an element for seek that we certainly understand with our customers is that data alone is not an end objective, right? If it doesn't lead to a decision and an action and a workflow that humans can take to go drive and improvement in their business process, then you haven't tapped into the, you know, value of that technology >>When a buyer comes to the marketplace. Yeah. And they see your listing and solutions. Yes. What are they getting? What are they, what, what are they buying? >>So for seek, we've radically simplified that we, we really embrace this idea of simplification. We just sell, seek. So we have one seat listing in the AWS marketplace, all applications of seek they're all available there. We really leaned into the enterprise procurement models. So private offers are how we do the most of our business on marketplace. And it really went from a stage of experimentation where couple of customers, you know, what is this marketplace? Maybe we'll buy a few of our business applications there all the way through to now we're starting to see the demand side come through for customers where it's not just their security software or their DevOps or infrastructure software. They wanna buy solutions like seek including line of business buyers through a common catalog in the marketplace. >>Great. So I wanna ask you, cuz I want to give you the opportunity to give the pitch, the customer watching right now. Yeah. What's the pitch. Why seek, why this listing? Why should they hit the purchase button? I wish it was that easy. Why should they, why should they what's the pitch? Sure. >>So the first thing is seek through marketplace is a five clicks on three screens procurement experience. So compare that to months and months of back and forth with contracts and purchase orders and vendor set up, this is five less than five minutes, few screens, couple of clicks. And you can buy a multi-year subscription of seek to cover your entire enterprise. The second pitch is that it's a SaaS application that now can be deployed within hours. And then your users, your insights, your value is starting within the first couple hours. This is not a heavy lift it project. That's gonna take months. And then lastly seek specifically. So seek, because we're validated in the marketplace has been well architected for AWS cloud. We have that, you know, stamp of credibility. And we are leading in this space for manufacturing organizations who want cloud native secure software for analytics on their operational data. >>That's awesome. And customers have the challenge when they think about data, the use case security, yes governance, there's a variety of different use cases. What are you seeing as the top three use cases for C? >>So on the there's two lines of that question. The first is really the line of business use cases. And those are all about what outcome are we gonna drive? Are we gonna approve efficiency in your factory? Are we gonna reduce greenhouse gas emissions? Those are the kinds of use cases on the business side that that seek works with our customers on, on the it side. They wanna know that we can access data securely, that we can be part of an ecosystem where they can bring in aerations and algorithms and machine learning and new applications. And they also wanna know that we are sustainable. So meaning that we're driving constant innovation that is easy for them to consume and to gain access, to, to drive the next level of >>Improvement. My final AWS marketplace seller question is, yeah. How does the procurement process through marketplace help you and your customers what's in it for them? What value do the, does the customer get going through AWS procuring? >>So there's really really three. The first is you get a validated set of a catalog of solutions, right? That AWS says, you know, we undergo a rigorous process technically and commercially to be in the marketplace. The second thing for procurement effect of for procurement professionals is that they can leverage their cloud committed spend with AWS. So as they commit more expense and spend with AWS, now these marketplace purchases can be credited to that committed expense. We found that brings it and the business together with procurement to really work more collectively on that. And then the third piece is, imagine buying software where you don't need legal, you know, back and forth, back and forth because we're using a standard doula that thousands of other software companies are using in the marketplace today. >>I thought the keynote had a great line. We are not just a website of a catalog. We are a API service layer. Yes. With automation, more like a C I C D pipe lining. Yes. Of software. Yeah. And we are hearing more and more about software supply chain, more about scaling. This is kind of the future of procurement. Why wouldn't you buy direct, pick a few buttons and assemble your solutions at scale. >>There's some amount of tenant consequences that we've really learned as well. It brings it and the business closer together. So the it person wants to know, well, what is this seek, you know, piece of my AWS invoice. And so they get more engaged earlier in the process with procurement, with the business. And we've actually found that it brings internally for our customers, more people to the seat at the table around what are the applications and how will they govern them across the enterprise. >>Megan, I really appreciate you taking the time to speak with me here at the, at the conference, the seller S marketplace. I have to ask you, we were talking before we came on camera, you made a comment. I'd like you to share this comment with some commentary. You said I'm the VP of cloud transformation. And in the future that might title might not exist. Explain what you mean there, cuz I think this is kind of a telling moment about where we are at this point in the industry. >>Sure. So maybe it's, maybe it's funny to sort of envision a future where your role doesn't exist. But I think, you know, it's a to innovators do that, right? And for us we're a software company. That's going through the transition on-prem to SAS, you know, cloud native sets of applications, but in the pretty near term fore, really the next two years, all of our business will be SaaS and cloud. And so we won't need a separate VP or a separate team or separate function. It will just be how the business operates. >>Megan, thanks for running cue, Meghan bine, who is SI, she's a cloud VP of cloud transformation, VP of cloud, and she's successful. The title will go away and she'll move on to some other great valuable things like running the business. Thanks for coming on. Thank you so much. Okay. This is a cube here in Seattle. We're covering the eights marketplace seller conference. Part of APN merging with Amazon marketplace now called the APO Amazon partner organization. I'm John ER, with the cube. Thanks for watching.

Published Date : Sep 21 2022

SUMMARY :

I'm Jennifer, the cube we're here with Megan. It's, it's nice to be back in person and it's great to be with you. new leadership here, the combination of APN partner network with And we will also sell as partners through co-sell You're the VP of cloud at the company, your company seek take a minute to explain what your So manufacturing the industry, it's going through massive transformation, supply chain, is the data layer, the relationship to other services. So the Dataverse common data models. And they see your listing and solutions. the way through to now we're starting to see the demand side come through for customers where it's not just their What's the pitch. So the first thing is seek through marketplace is a five And customers have the challenge when they think about data, the use case security, So on the there's two lines of that question. process through marketplace help you and your customers what's in it for them? We found that brings it and the business together with procurement to really work more This is kind of the future of procurement. So the it person wants to know, well, what is this seek, And in the future that might title might not exist. to SAS, you know, cloud native sets of applications, but in the pretty We're covering the eights marketplace seller conference.

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Kristian Gyorkos, Kong | AWS Marketplace Seller Conference 2022


 

>>Welcome back everyone to the cubes coverage here in Seattle, Washington for the Avis marketplace seller conference, part of the APN partner network merging with the marketplace to form the Amazon partner organization. I'm John furrier, host of the cube Walter Wall coverage today, Christian Gor cash, who is the VP of alliances at Kong Inc. Welcome to the cube. Thanks for coming on. >>Thank you. Thank you, John. Really glad to be here. Corke exactly. Yeah. It's awesome. >>So Kong we've been following you guys for while Docker Kong cube. You've been part of our cube conversation. Also part of our, our startup showcase fast growing startup, you know, working on stuff that everyone loves APIs. I mean, APIs are so popular now that they now a security concern, right? Yeah. So like it gets squat there everywhere. I won't say API sprawl, but APIs are the connections and that are, is the web. That is the cloud. Okay. Now with cloud native developers who are now in the front lines have taken over it, everyone knows DevOps dev SecOps is now the new it and it's the developers security and data they're below they're the new ops, right? So, so this is where microservices come in, open source service MES new automation is coming down the pike. That's super valuable to businesses as they look at cloud native architecture, what are you guys doing in there? Take a minute to explain Kong's value proposition, the hot products, and then why you're here. >>Yeah. So, you know, I joined Kong now or three years ago, you know, we were still just reaching our hundred employees, mark, which is very important, very startup, but even back then, you know, Kong was relatively well known in industry, you know, so we have one of the most, well the most popular open source project in API gateway area. So con API gateway, you know, we cross now 300 million downloads, even more important is just the scale it, which the product's been used. So between our open source community and enterprise customers, we are now crossing like 11 trillion transactions per month. Now just give you comparison. Like this is like 18, 19 times more than Netflix per month. You know? So for any company that has a technology that operates it at scale, you need to hit few things outta the park. You know, as he mentions cloud data developers, they want simplicity. You know, they want automation. They also want performance and scale and security, which are all critical, you know, to how Kong, you know, start as opensource project. Now, of course we have the whole suite of enterprise products. We also have our con service mesh offering as well as our cloud offerings. >>Yeah. And this is how open source is doing it now, obviously, you know, I, I still remember, I still tell the story to the young startups. Hey, I, there was proprietary software when I was in college. Open source is now everything. Now you've got, got cloud scale. So the dynamic between open source, which has become the software industry open source success doesn't mean it's it's game over. It's the beginning. The commercialization that you guys have gone through is super important. Trillions of transactions. Now you have enterprises working with you. What's the big advantage of the seller relationship that you have with Amazon? Why are customers using it? What are they buying it for? Give the pitch of con for the marketplace customer. >>Yeah, it's actually, we are relatively new in AWS marketplace. You know, so our first transaction that we ever done was actually in July and 2021. So we are just over a year, you know, that journey, you know, when I look what Chris gross talked today, he was talking about, you know, Hey, just publishing marketplace, not enough. You know, you need to understand what's your value proposition. You need to make sure your operations already, your sales is ready. Everything is, is set. And we kind of did this for the first year and a half is spend a lot of time improving our integration with AWS overall, all the first party services relevant to con we also understood, well, what does it take to kind of fine tune our value proposition? We have like three specific sales place. And you know, when we launch our flagship product con connect enterprise and got our first transaction, that was great milestone for, for star like Kong. But then what we've seen is just that work that we've done before really paid off. I mean right now, >>Like what we'll give example. >>Yeah. So, you know, we are focusing on as measure three sales place. Money is we are focused, specific on helping customers who are modernizing and, and their application going to the cloud. And you have a lot of these, you know, lifting shift and are rearchitect and modernized, but most of the attentions on the workloads, what about the connections? You know, so a monolith application had to authentic all the users understand wheres the network and so on. When you build those, when you now decouple this built like 1,000 thousand microservices, you don't want to repeat this for every microservice. So that's where K brings the whole suite from, you know, service match to the API gate to help manage the journey and really support this environment. And we spend a lot of time to just fine tune that message. So that customers understood where, you know, how can we help them on their journey beyond what, for instance, cloud native or AWS API gateway offers them. So we can really help them from day one on the journey and accelerate. And >>I think I it's a no, it's a no braining for a customer to buyer or to come into the marketplace and say, click, I'm gonna buy some data analytics services. I'm gonna buy gateway through Kong. But when they start getting into these microservices, this automation opportunity there, there's more behind the curtain for them with Kong. So I have to ask you with the keynote we heard from Chris, the leader of the marketplace. Now he said that he wants the ISVs to be more native in the cloud. That probably resonates with you. You, >>You guys well with con's relatively simple because we were built at cloud native, you know, so very briefly the whole story of Congo. This is before Ajo, our founders were actually running the, the very popular API exchange col mesh shape. And they had to build their own gateway just to handle the scale and was built on cloud native technologies. And then when everybody's calling you, what are you using to running? This are using PGS. And so else, no, we built ourselves, oh, how can we get our hands on? That's how con actually >>Came to. And that's how the big winners usually happen too. They start build their own, solve their own problem because it's a big scale problem. Exactly. No one's had that problem. >>Yeah. And what we have seen, especially what was very, you know, through, through the pandemic, what we have seen. And it's interesting, you know, being in a startup doing pandemic is like, whoa, will the life just shut down or what we're doing? You know? But actually what we have seen customers prioritize the new business capability. For instance, you have a large parental companies that overnight, they have to understand where the assets are. Yeah. Or banks who are like 45 days of, you know, approving process for the loans. They need to reduce it for a day or two. >>Yeah. And they're adding more developers, too, exactly. To build the modern application. So they need to have that infrastructure as code aspect. Correct. >>And they >>Need in place. >>Yeah. I need to like you have, you know, I don't think that many customers still have waterfall cycles, but they have, have pre pretty long developers development cycles. And now you need to, you know, do this multiple times a day. That's >>Interesting. We talked to a lot of cloud architects and C CIO C says, and you know, the executive just hire more developers take that hill, build. It just don't build a new app. It's not that easy boss. When, when the cloud architect says we have to be fully operationally ready with cloud native infrastructure's code. So with that, you're seeing a lot more enterprises come in now that are more savvy. They getting better. We're seeing Kubernetes more and more. You're seeing containerization. You're seeing that cloud native enterprise acceptance. What does that mean for you guys in the marketplace, as you look at the value proposition, how are you guys working with the marketplace today and where do you see customers buying in the future? >>Yeah, so we as mentioned, you know, we, we are now a year into that journey. We already seen tremendous benefits just in terms of reducing the friction. You know, the whole procurement, you know, you come as a startup with some, some of the largest companies in the world, they used to buy five, 10 billion in software and they have all these processes and you're like, well, but we only have like two people in finance. Sorry. How can you, and where marketplace can really, really helps us is, you know, improve this experience, both sides because they understand like we are fast moving company. They, they want us because of our speed and, and innovation that we, the product's strong. Yeah. They don't want us to get bogged down in all these pro procurement processes either. And so, so that's the first benefit. We also are working very hard to make sure that the customers can provision Kong in AWS and automate across the board. So essentially reducing their time to value dramatically. Yeah. And another thing that we found tremendously beneficial for us is a startup is the whole concept of a standard marketplace contract. Yeah. So instead of us coming with our little MSA or come like 50 page MSA from companies, we now have a middle ground. So we can just agree. You know, there's some differences, some specifics to qu software and it's tremendously reduced costs on both sides. >>Great. For you guys great for the buyers. Yeah. You get deployed services. They're not just buying, they're managing and deploying. Yeah, >>Exactly. Great. >>Quick, final question. Put a plugin for the company. What are you working on now? What's the big news. What's the con update? >>Well, that's an interesting part because I can't tell you because next week we have our con summit. Oh right. In San Francisco. The cubes not so 28, 20 ninth. Yeah. We, we we'll, I think we are gonna fix that in the future. But anyway, this is the first time after pandemic to do this in person, we have number of very exciting announcement, our Kong products, as well as you may hear some news about our AWS partnership, >>We like con we believe that DevOps has happened. Dev sec ops, whatever you gonna call it, dev is now the developers they're in the front lines. They're in the C I CD pipeline. They're shifting left. That's the new they took over it. That's what DevOps does. It's not a title. Now you have security and data ops behind the scenes. That's gonna be middleware. That's gonna have tons of microservices. So more, more, more action coming, all API based. >>Exactly. And the more, you know, the more complexity we can take away from that, the better we, you know, the >>Whole community. Thank you. Spending the time to come on the cube here at the, a us marketplace seller conference. What do you think about the APN merging with the marketplace formed the P the Amazon partner organization. Thumbs up, thumbs down. What's your heard? >>It's excellent. We have a great friend in AP, a great friend, us marketplace. Now both of them work together with huge. >>Fantastic. Yes. Thanks for okay. Cube coverage here in Seattle. I'm John furier APN marketplace together. APOs the new organization making it easier. Of course, we got all the coverage here. Thanks for watching.

Published Date : Sep 21 2022

SUMMARY :

conference, part of the APN partner network merging with the marketplace to form Yeah. Also part of our, our startup showcase fast growing startup, you know, So con API gateway, you know, we cross now 300 million downloads, The commercialization that you guys have gone through is super important. So we are just over a year, you know, that journey, you know, the whole suite from, you know, service match to the API gate to help manage the journey So I have to ask you with the keynote You guys well with con's relatively simple because we were built at cloud native, you know, And that's how the big winners usually happen too. And it's interesting, you know, being in a startup doing pandemic So they need to have that infrastructure And now you need to, you know, do this multiple times a day. We talked to a lot of cloud architects and C CIO C says, and you know, the executive just hire more You know, the whole procurement, you know, you come as a startup with some, For you guys great for the buyers. Exactly. What are you working on now? announcement, our Kong products, as well as you may hear some news about our AWS partnership, Now you have security and data ops behind the scenes. And the more, you know, the more complexity we can take away from that, Spending the time to come on the cube here at the, a us marketplace seller conference. We have a great friend in AP, a great friend, us marketplace. APOs the new organization making it easier.

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Jack Andersen & Joel Minnick, Databricks | AWS Marketplace Seller Conference 2022


 

>>Welcome back everyone to the cubes coverage here in Seattle, Washington, AWS's marketplace seller conference. It's the big news within the Amazon partner network, combining with marketplaces, forming the Amazon partner organization, part of a big reorg as they grow the next level NextGen cloud mid-game on the chessboard. Cube's got cover. I'm John fur, host of Cub, a great guests here from data bricks, both cube alumnis, Jack Anderson, GM of the and VP of the data bricks partnership team. For ADOS, you handle that relationship and Joel Minick vice president of product and partner marketing. You guys are the, have the keys to the kingdom with data, bricks, and AWS. Thanks for joining. Thanks for good to see you again. Thanks for >>Having us back. Yeah, John, great to be here. >>So I feel like we're at reinvent 2013 small event, no stage, but there's a real shift happening with procurement. Obviously it makes it's a no brainer on the micro, you know, people should be buying online self-service cloud scale, but Amazon's got billions being sold to their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website marketplace merge our partner to have more synergy and friction, less experiences so everyone can make more money and customer's gonna be happier. >>Yeah, that's right. >>I mean, you're run relationship. You're in the middle of it. >>Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do is to work with Amazon on these really, you know, unique use cases. >>You know, I interviewed Ali many times over the years. I remember many years ago, I think six, maybe six, seven years ago, we were talking. He's like, we're all in ons. Obviously. Now the success of data bricks, you've got multiple clouds. See that customers have choice, but I remember the strategy early on. It was like, we're gonna be deep. So this is speaks volumes to the, the relationship you have years. Jack take us through the relationship that data bricks has with AWS from a, from a partner perspective, Joel, and from a product perspective, because it's not like you got to Johnny come lately new to the new, to the scene, right? We've been there almost president creation of this wave. What's the relationship and has it relate to what's going on today? >>So, so most people may not know that data bricks was born on AWS. We actually did our first 100 million of revenue on Amazon. And today we're obviously available on multiple clouds, but we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon and marketplace broadens our reach. And so we think of marketplace in three different aspects. We've got the marketplace, private offer business, which we've been doing for a number of years. Matter of fact, we we're driving well over a hundred percent year over year growth in private offers and we have a nine figure business. So it's a very significant business. And when a customer uses a private offer that private offer counts against their private pricing agreement with AWS. So they get pricing power against their, their private pricing. >>So it's really important. It goes on their Amazon bill in may. We launched our pay as you go on demand offering. And in five short months, we have well over a thousand subscribers. And what this does is it really reduces the barriers to entry it's low friction. So anybody in an enterprise or startup or public sector company can start to use data bricks on AWS and pay consumption based model and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation pilots, POCs, they're, they're really learning the value of that first use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offers C P O super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with data bricks on behalf of customers. >>So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data coming in with, with the buyers you go. And obviously the integration piece all fitting in there. Exactly. Exactly. Okay. So that's that those are the offers that's current and what's in marketplace today. Is that the products, what are, what are people buying? I mean, I guess what's the Joel, what are, what are people buying in the marketplace and what does it mean for >>Them? So fundamentally what they're buying is the ability to take silos out of their organization. And that's, that is the problem that data bricks is out there to solve, which is when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data, and your teams are trying to use all of this data to solve really complicated problems. And as data bricks as the lake house company, what we're helping customers do is how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find through the marketplace, those rapid adoption use cases where they can get rid of these data, warehousing data lake silos they've had in the past, get their unstructured and structured data onto one data platform and open data platform that is no longer adherent to any proprietary formats and standards and something. >>They can very much, very easily integrate into the rest of their data environment, apply one common data governance layer on top of that. So that from the time they ingest that data to the time they use that data to the time they share that data inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform with that common governance solution, they'd being able to bring all of those use cases together across their real time, streaming their data engineering, their BI, their AI, all of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges. They just couldn't solve before a good example of this, you know, one of the world's now largest data streaming platforms runs on data bricks with AWS. >>And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses, that they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data from what the customers are doing with their platform and the recommendations they wanna push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex, but by building it on data bricks, they were able to release it in record time and have grown at, at record pace >>To not be that's product platform that's impacting product development. Absolutely. I mean, this is like the difference between lagging months of product development to like days. Yes. Pretty much what you're getting at. Yeah. So total agility. I got that. Okay. Now I'm a customer I wanna buy in the marketplace, but I also, you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from a Davis's leadership, Chris was up there speaking and, and, and moment I was, Hey, he's a CRO conference, chief revenue officer conversation, which means someone's getting compensated. So if I'm the sales rep at data bricks, what's my motion to the customer. Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Is there or an audio lift? >>Well, I I'd add what Joel just talked about with, with, you know, what the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, the entire data bricks offering and >>The flagship, all the, the top, >>Everything, the flagship, the complete offering. So it's not, it's not segmented. It's not a sub segment. It's it's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we, we, we view this two, two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend data bricks for the right situation. Same thing with data bricks. Our Salesforce wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get data bricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars, you have $5 million of spend, you put that spend through the flywheel with AWS marketplace. And then you can use that in your negotiations with AWS to get better pricing overall. So that's how we, >>We do it. So customers are driving. This sounds like, correct. For sure. So they're looking at this as saying, Hey, I'm gonna just get purchasing power with all my relationships because it's a solution architectural market, right? >>Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider, if they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing >>Power, okay, Jill, we're gonna date ourselves. At least I will. So back in the old days, it used to be, do a Barney deal with someone, Hey, let's go to market together. You gotta get paper, you do a biz dev deal. And then you gotta say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for data bricks or any company is to go find those partners and do deals versus now Amazon is the center point for the customer so that you can still do those joint deals. But this seems to be flipping the script a little bit. >>Well, it is, but we still have VAs and consulting partners that are doing implementation work very valuable work advisory work that can actually work with marketplace through the C PPO offering. So the marketplace allows multiple ways to procure your >>Solution. So it doesn't change your business structure. It just makes it more efficient. That's >>Correct. >>That's a great way to say it. Yeah, >>That's great. So that's so that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >>Yes, >>Absolutely. Economically. Yeah. >>E economically it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon, especially when it comes back to co-selling right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution and our teams are working backwards from those use cases, you know, to collaborate, land them. >>Yeah. I want, I wanna get that out there. Go ahead, Joel. >>So one of the other things I might add to that too, you know, and why this is advantageous for, for companies like data bricks to, to work through the marketplace, is it makes it so much easier for customers to deploy a solution. It's, it's very, literally one click through the marketplace to get data bricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. You >>Know, it's interesting. I wanna bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself EDI back in the old days, you know, all that craziness. Now this is all the, all the internet, basically through the console, I get the infrastructure side, you know, spin up and provision. Some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage little nuance, most enterprises aren't yet there of integrating tech on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrator's dilemma, not an innovator's dilemma. So like, I want to integrate, so now I have integration points with data bricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you gotta build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or, or am I off because no, one's gonna be buying software. Like they used to, they buy software to integrate it. >>Yeah, >>No, I, cause everything's integrated. >>I think AWS has done a great job at creating a partner ecosystem, right. To give customers the right tools for the right jobs. And those might be with third parties, data bricks is doing the same thing with our partner connect program. Right. We've got customer, customer partners like five tra and D V T that, you know, augment and enhance our platform. And so you, you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >>Yeah. It's almost like, you know, bundling and unbundling. I was talking about this with, with Dave ante about Supercloud, which is why wouldn't a customer want the best solution in their architecture period. And it's class. If someone's got API security or an API gateway. Well, you know, I don't wanna be forced to buy something because it's part of a suite and that's where you see things get suboptimized where someone dominates a category and they have, oh, you gotta buy my version of this. Yeah. >>Joel, Joel. And that's Joel and I were talking, we're actually saying what what's really important about Databricks is that customers control the data. Right? You wanna comment on that? >>Yeah. I was say the, you know what you're pushing on there we think is extraordinarily, you know, the way the market is gonna go is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically I think really strong places, data, bricks, and AWS have lined up is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the lake house, one thing we've always been extremely committed to as a company is building the data platform on an open foundation. And we do that primarily through Delta lake and making sure that to Jack's point with data bricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed data bricks to have the breadth of integrations that it has with all the other data tools out there, because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >>When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what's the, what am I foreclosing? If I go with something else that's not as open what what's the customer's downside as you think about what's around the corner in the industry. Cuz if you believe it's gonna be open, open source, which I think opens our software is the software industry and integration is a big deal, cuz software's gonna be plentiful. Let's face it. It's a good time to be in software business, but cloud's booming. So what's the downside from your data bricks perspective, you see a buyer clicking on data bricks versus that alternative what's potentially is should they be a nervous about down the road if they go with a more proprietary or locked in approach? Well, >>I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also then beholden to the pace at which that provider is able to innovate. And I think we've seen lots of times over history where, you know, a proprietary format may run ahead for a while on a lot of innovation. But as that market control begins to solidify that desire to innovate begins to, to degrade, whereas in the open format. So >>Extract rents versus innovation. Exactly. >>Yeah, exactly. >>But >>I'll say it in the open world, you know, you have to continue to innovate. Yeah. And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you were always going to be at the forefront of what is the >>Latest, you know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked for proprietary. Yeah. You know, SNA at IBM deck net was digital, you know, the rest is, and then TCP, I P was part of the open systems, interconnect, revolutionary Oly, a big part of that as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. Yeah. But that helped interoperate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid game. Then you got the end game and we're not there. The end game yet cloud the cloud. >>There's, there's always some form of lock in, right. Andy jazzy will, will address it, you know, when making a decision. But if you're gonna make a decision you want to reduce as you don't wanna be limited. Right. So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now is an AI driven business. Right? And so it has to do with, can you get that data outta silos? Can you, can you organize it and secure it? And then can you work with data scientists to feed those models? Yeah. In a, in a very consistent manner. And so the tools of tomorrow will to Joel's point will be open and we want interoperability with those >>Tools and, and choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds is that they have to compete directly too. Redshift competes directly with a lot of other stuff, but they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're gonna be they're onto it. This is >>The Amazon's credit by having these, these solutions that may compete with native services in marketplace, they are providing customers with choice, low >>Price and access to the S and access to the core value. Exactly. Which the >>Hardware, which is their platform. Okay. So I wanna get you guys thought on something else. I, I see emerging, this is again kind of cube rumination moment. So on stage Chris unpacked, a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing compensation, workflows services behind the curtain. And one of the things he mentioned was they talk about resellers or channel partners, depending upon what you talk about. We believe Dave and I believe on the cube that the entire indirect sales channel of the industry is gonna be disrupted radically because those players were selling hardware in the old days and software, that game is gonna change. You know, you mentioned you guys have a program, want to get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in which means that the old reseller channels are gonna be rewritten. They're gonna be refactored with this new kinds of access. Cuz you've got scale, you've got money and you've got product and you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, value added reseller or V or business, >>You've gotta evolve. >>You gotta, you gotta be here. Yes. How are you guys working with those partners? Cuz you say you have a part in your marketplace there. How do I make money? If I'm a reseller with data bricks with eight Amazon, take me through that use case. >>Well I'll let Joel comment, but I think it's, it's, it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations, they need expertise from consulting and SI partners. If those consulting SI partners happen to resell the solution as well. Well, that's another aspect of their business, but I really think it is the expertise that the partners bring to help customers get outcomes. >>Joel, channel big opportunity for re re Amazon to reimagine this. >>For sure. Yeah. And I think, you know, to your comment about how to resellers take advantage of that, I think what Jack was pushing on is spot on, which is it's becoming more about more and more about the expertise you bring to the table and not just transacting the software, but now actually helping customers make the right choices. And we're seeing, you know, both SI begin to be able to resell solutions and finding a lot of opportunity in that. Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's gonna be the evolution that >>This gets at the end of the day. It's about services for sure, for sure. You've got a great service. You're gonna have high gross profits. And >>I think that the managed service provider business is alive and well, right? Because there are a number of customers that want that, that type of a service. >>I think that's gonna be a really hot, hot button for you guys. I think being the way you guys are open this channel partner services model coming in to the fold really kind of makes for kind of that super cloudlike experience where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on within data bricks for sure. On top of this ecosystem, how does that work? This is kinda like hasn't been written up in business school and case studies yet this is new. What is this? >>I think, you know, what it comes down to is you're seeing ecosystems begin to evolve around the data platforms and that's gonna be one of the big kind of new horizons for us as we think about what drives ecosystems it's going to be around. Well, what is the, what's the data platform that I'm using and then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around data bricks in its Lakehouse platform, as well as customers are looking at well, if I'm standing these Lakehouse up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >>I mean you think about ecosystem theory, we're living a whole nother dream and I'm, and I'm not kidding. It hasn't yet been written up and for business school case studies is that we're now in a whole nother connective tissue ecology thing happening where you have dependencies and value proposition economics connectedness. So you have relationships in these ecosystems. >>And I think one of the great things about relationships with these ecosystems is that there's a high degree of overlap. Yeah. So you're seeing that, you know, the way that the cloud business is evolving, the, the ecosystem partners of data bricks are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for >>You. Joel, Jack, I love it because you know what it means the best ecosystem will win. If you keep it open. Sure. You can see everything. If you're gonna do it in the dark, you know, you don't know the outcome. I mean, this is really kind we're talking about. >>And John, can I just add that when I was in Amazon, we had a, a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? Yeah. And so there's a platform decision being made and that ecosystem gonna evolve around the >>Platform. Yeah. And I totally agree. And, and, and the word innovation get kicks around. That's why, you know, when we had our super cloud panel was called the innovators dilemma with a slash through it called the integrated dilemma, innovation is the digital transformation. So absolutely like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating if APIs are the connective tissue, what's automation, what's the service message look like. I mean, a whole nother set of kind of thinking goes on and these new ecosystems and these new products >>And that, and that thinking is, has been born in Delta sharing. Right? So the idea that you can have a multi-cloud implementation of data bricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud >>Solution. Well, data bricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great grow ecosystem. And again, I think in a shining example of what every enterprise is going to do, build on top of something operating model, get that operating model, driving revenue. >>Yeah. >>Well we, whether whether you're Goldman Sachs or capital one or XYZ corporation >>S and P global NASDAQ, right. We've got, you know, these, the biggest verticals in the world are solving tough problems with data breaks. I think we'd be remiss cuz if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions, whether it's the relationship we have with our engineering and service teams. Yeah. Our marketing teams, you know, product development and we're gonna be at reinvent the big presence of reinvent. We're looking forward to seeing you there again. >>Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening this next gen cloud is here. We're seeing this evolve kind of new economics, new value propositions kind of scaling up, producing more so you guys are doing a great job. Thanks for coming on the Cuban, taking time. Chill. Great to see you at the check. Thanks for having us. Thanks. Going. Okay. Cube coverage here. The world's changing as APN comes to give the marketplace for a new partner organization at Amazon web services, the Cube's got a covered. This should be a very big growing ecosystem as this continues, billions of being sold through the marketplace. Of course the buyers are happy as well. So we've got it all covered. I'm John furry, your host of the cube. Thanks for watching.

Published Date : Sep 21 2022

SUMMARY :

Thanks for good to see you again. Yeah, John, great to be here. Obviously it makes it's a no brainer on the micro, you know, You're in the middle of it. you know, unique use cases. So this is speaks volumes to the, the relationship you have years. And when you look at what the APN allows us to do, And so we see customers, you know, doing rapid experimentation pilots, POCs, So you got the big contracts with the private offer. And that's, that is the problem that data bricks is out there to solve, They just couldn't solve before a good example of this, you know, And if you think about what does it take to set that up? So how do you guys look at this? Well, I I'd add what Joel just talked about with, with, you know, what the solution, the value of the solution our entire offering And that really helps customers because if you get data bricks So they're looking at this as saying, you know, multiple ISV spend through that same primary provider, you get pricing And then you gotta say, okay, now let's coordinate our sales teams, a lot of moving parts. So the marketplace allows multiple ways to procure your So it doesn't change your business structure. Yeah, So you guys are actually incented to Yeah. It's the right thing to do for our relationship with Amazon, So one of the other things I might add to that too, you know, and why this is advantageous for, I get the infrastructure side, you know, spin up and provision. you know, augment and enhance our platform. you know, I don't wanna be forced to buy something because it's part of a suite and the data. And that is one of the things that's allowed data bricks to have the breadth of integrations that it has with When you see other solutions out there that aren't as open as you guys, you guys are very open by the I think the challenge with proprietary ecosystems is you become beholden to the Exactly. I'll say it in the open world, you know, you have to continue to innovate. I call it the chessboard, you know, you got opening game and mid game. And so it has to do with, can you get that data outta silos? And I would say that, you know, the argument for why I think Amazon Price and access to the S and access to the core value. So I wanna get you guys thought on something else. You gotta, you gotta be here. If those consulting SI partners happen to resell the solution as well. And we're seeing, you know, both SI begin to be This gets at the end of the day. I think that the managed service provider business is alive and well, right? I think being the way you guys are open this channel I think, you know, what it comes down to is you're seeing ecosystems begin to evolve around So you have relationships in And so as you build these platforms out into the cloud, you're able to really take advantage you don't know the outcome. And John, can I just add that when I was in Amazon, we had a, a theory that there's buyers and builders, That's why, you know, when we had our super cloud panel So the idea that you can have a multi-cloud implementation of data bricks, and actually share data But you guys have done a great job taking that building differentiation into the product. We're looking forward to seeing you there again. Great to see you at the check.

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Lea Purcell, Foursquare | AWS Marketplace Seller Conference 2022


 

>>Welcome back everyone to the cubes coverage here in Seattle, Washington for AWS's marketplace seller conference. The big news here is that the Amazon partner network and marketplace coming together and reorganizing into one organization, the AIST partner organization, APO bringing together the best of the partnership and the marketplace to sell through. It's a sellers company. This is the second year, but technically with COVID, I call it a year and a half. This is the cube. I'm John for your host. Got a great guest, Leah for sale vice president of business development at four square. Leah, thanks for coming on the cube. Look great. Yeah. >>Hey, thanks. Thanks for having me here. >>So four square, everyone, and that has internet history knows you. You check in you'd become the mayor of a place right back in the day, all fun. It was a great app and I think it was competitor go sold the Facebook, but that was the beginning of location data. Now you got Uber apps, you got all apps, location, everywhere. Data is big here in the marketplace. They sell data, they got a data exchange, Chris head of marketplaces. Like we have all these things we're gonna bring 'em together, make it simpler. So you're on the data side. I'm assuming you're selling data and you're participating at the data exchange. What is Foursquare doing right now? Yeah, >>Exactly. So we are part of the data exchange. And you mentioned checking in. So we, we are really proud of our roots, the, the four square app, and that's kind of the basis still of our business. We have a hundred million data points, which are actually places of interest across the world 200 countries. And we are we're in the business of understanding whereplace are and how people move through those places over time. And >>What's the value proposition for that data. You're selling the data. >>We are selling the data and we're selling it. You can think about use cases. Like how can I improve the engagement with my app through location data? So for example, next door, as a customer of ours, everyone knows next door. When a new business comes online, they wanna make sure that business is a real business. So they use our places to ensure that the address of that business is accurate. >>So how did you, how do you guys get your data? Because if you don't have the first party app, you probably had critical mass of data. Yeah. But then do other people use your data and then re contribute back in kinda like, well, Stripe is for financial. You guys are plugging in yeah. To >>Apps. A great question. So we still do have our consumer apps. We're still proud of those. It's still a basis of our company really. Okay. So, but we take that data. So our first party data, we also, for all the web, we have some partners integrate our SDK. And so we're pulling in all that data from various sources and then scrubbing it and making sure we have the most unique. >>So you guys still have a business where the app's working. Yep. Okay. But also let's just say, I wanna have a cube app. Yeah. And I want to do a check in button. Yep. So rather than build checking in, could I OEM you could four square is that you >>Could, and we could help you understand where people are checking in. So we know someone's here at the Hilton and Bellevue, we know exactly where that place is. You building the Cub app. You could say, I'm gonna check in here and we are verified. We know that that's the >>Right place. So that's a good for developer if they're building an app. >>Absolutely. So we have an SDK that any developer can integrate. >>Great. Okay. So what's the relationship with the marketplace? Take us through how Foursquare works with AWS marketplace. >>Sure. So we are primarily integrated with ADX, which is sort of a piece of marketplace it's for data specifically, we have both of our main products, which are places that POI database and visits, which is how people move through those places over time. So we're able to say these are the top chains in the country. Here's how people move throughout those. And both those products are listed on ADX. >>So if I'm in Palo Alto and I go to Joe in the juice yeah. You know that I kind of hang in one spot or is it privacy there? I mean, how do you know like what goes on? Well, >>We know somebody does that. We don't >>Know that you do that. So >>We ensure, you know, we're very privacy centric and privacy focused. We're not gonna, we don't tell anybody at you >>Yourself it's pattern data. It is. >>Okay. So it's normalized data, right? Over time groups of people, >>How they, how are people using the data to improve processes, user experience? What are some of the use cases? >>So that example, nextdoor, that's really a use case that we see a lot and that's improving their application. So that nextdoor app to ensure that the ACC, the data's accurate and that as you, as a user, you know, that that business is real. Cuz it's verified by four wear. Another one is you can use our data to make business decisions around where you're gonna place your next loca. You know, your next QSR. So young brands is a customer of ours. Those are, those guys are pizza hut KFC. They work with us to figure out where they should put their next KFC. Yeah. >>I mean retail location, location, location. Yeah. >>Right. Yeah. People are still, even though e-commerce right. People still go into stores >>And still are. Yeah. There's, there's, there's probably lot, a lot of math involved in knowing demographics patterns. Volume. >>Yeah. Some of our key customers are really data scientists. Like the think about cus with businesses that have true data science companies. They're really looking at that. >>Yeah. I mean in, and out's on the exit for a reason. Right. They want in and out. Yeah. So they wanna put it inland. >>Right. And we can actually tell you where that customer from in and out where they go next. Right. So then, you know, oh, they go to this park or they go somewhere and we can help you place your next in and out based on that visitation. >>Yeah. And so it's real science involved. So take us through the customers. You said data scientists, >>Mostly data scientists is kind of a key customer data science at a large corporation, like a QSR that's >>Somebody. Okay. So how is the procurement process on the marketplace? What does the buyer get? >>So what we see the real value is, is because they're already a customer of Amazon. That procurement is really easy, right? All the fulfillment goes through Amazon, through ADX. And what you're buying is either at API. So you can, that API can make real time calls or you're buying a flat file, like an actual database of those hundred points of interest. >>And then they integrate into their tool set. Right. They can do it. So it's pretty data friendly in terms of format. >>You can kind of do whatever you want with it. We're gonna give you that as long as you're smart enough to figure out what to do. Do we have a >>Lot of, so what's your experience with AWS marketplace? I mean, obviously we, we see a lot of changes. They had a reorg partner network merging with marketplace. You've been more on the data exchange, Chris kind of called that out. It's yeah. It's kind of a new thing. And, and he was hinting at a lot of confusion, but simplifying things. Yeah. What's your take of the current AWS marketplace >>Religions? I actually think ADX because our experience has primarily been ADX. I think they've done a really good job. They've really focused on the data and they understand how CU, how, you know, people like us sell our data. It hasn't been super confusing. We've had a lot of support. I think that's what Amazon gives you. You have to put a lot of effort into it, but they're also, they also give you a lot of support. >>Yeah. And, and I think data exchange is pretty significant to the strategic. It is >>Mission. It is. We feel that. Yeah. You know, we feel like they really value us as a partner. >>What's the big thing you're seeing out there right now in data, because like you're seeing a lot more data exchanges going on. There's always been data exchange, but you're seeing a lot more exchanges between companies. So let's just take partners. You're seeing a lot more people handle front end of a, a supply chain and you got more data exchanges. What's the future of data exchanges. If you had to kind of, you know, guess given your history in, in the industry. Yeah. What's the next around the corner trend? >>I think. Well, I think there's a, has to be consolidation. I know everyone's building one, but there's probably too many. I know from our experience, we can't support all of them. We're not a huge company. We can't support Amazon and X and Y and Z. Like it's just too many. So we kind of put all of our eggs in a couple baskets. So I think there'll be consolidation. I think there has to be just some innovation on what data products are, you know, for us, we have these two, it's an API and a flat file. I think as exchanges think about, you know, expanding what are the other types of data products that can help us build? >>Yeah. I mean, one of the things that's, you know, we see, we cover a lot of on the cube is edge. You know, you got, yeah. Amazon putting out new products in regions, you got new wavelength out there, you got regions, you got city level connectivity, data coming from cars. So a lot more IOT data. How do you guys see that folding into your vision of data acquisition and data usage, leverage, reuse, durability. These >>Are, yeah. I mean, we're, we are keeping an eye on all of that. You know, I think we haven't quite figured out how we wanna allocate resources against it, but you know, it's definitely, it's a really interesting space to be in. Like, I don't think data's going anywhere and I think it's really just gonna grow and how people use it's >>Gonna expand. Okay. So if I'm a customer, I go to the marketplace, I wanna buy four square data. What's the pitch. >>We can help you improve your business decisions or your applications through location data. We know where places are and how people move through the world over time. So we can tell you we're, we're sure that this is the Hilton in Bellevue. We know that, that we know how many people are moving through here and that's really the pitch. >>And they use that for whatever their needs are, business improvement, user experience. Yeah. >>Those are really the primary. I mean, we also have some financial use cases. So hedge funds, maybe they're thinking about yeah. How they wanna invest their money. They're gonna look at visits over time to understand what people are doing. Right. The pandemic made that super important. >>Yeah. That's awesome. Well, this is great. Great success story. Congratulations. And thanks for sharing on the cube. Really appreciate you coming on. Thank you. My final question is more about kind of the future. I wanna get your thoughts because your season pro, when you have the confluence of physical and digital coming together. Yeah. You know, I was just talking with a friend about FedEx's earnings, comparing that to say, AWS has a fleet of delivery too. Right? Amazon, Amazon nots. So, but physical world only products location matters. But then what about the person when they're walking around the real world? What happens when they get to the metaverses or, you know, they get to digital, they tend an event. Yeah. How do you see that crossroad? Cuz you have foot in both camps. We do, you got the app and you got the physical world it's gonna come together. Is there thoughts around, you can take your course care hat off and put your industry hat on. Yeah. You wanna answer that? Not officially on behalf of Foursquare, but I'm just curious, this is a, this is the confluence of like the blending of physical and digital. >>Yeah. I know. Wow. I admittedly haven't thought a whole lot about that. I think it would be really weird if I could track myself over time and the metaverse I mean, I think, yeah, as you said, it's >>It's, by the way, I'm not Bo on the metaverse when it's blocked diagrams, when you have gaming platforms that are like the best visual experience possible, right? >>Yeah. I mean, I think it, I think we'll see, I don't, I don't know that I have a >>Prediction, well hybrid we've seeing a lot of hybrid events. Like this event is still intimate VIP, but next year I guarantee it's gonna be larger, much larger and it's gonna be physical and face to face, but, but digital right as well. Yeah. Not people experiencing the, both that first party, physical, digital hybrid. Yeah. And it's interesting something that we track a lot >>Of. Yeah, for sure. Yeah. I think we'll have a, well, I think we'll, there's something there for us. I think that those there's a play there as we watch kind >>Of things change. All right, Leah, thank you for coming on the Q appreciate so much it all right. With four Graham, John fur a year checking in with four square here on the cube here at the Amazon web services marketplace seller conference. Second year back from the pandemic in person, more coverage after this break.

Published Date : Sep 21 2022

SUMMARY :

and the marketplace to sell through. Thanks for having me here. So four square, everyone, and that has internet history knows you. So we are part of the data exchange. What's the value proposition for that data. I improve the engagement with my app through location data? So how did you, how do you guys get your data? So our first party data, we also, for all the web, So you guys still have a business where the app's working. Could, and we could help you understand where people are checking in. So that's a good for developer if they're building an app. So we have an SDK that any developer can integrate. Take us through how Foursquare works with AWS So we're able to say these are I mean, how do you know like what goes on? We know somebody does that. Know that you do that. we don't tell anybody at you It is. So that example, nextdoor, that's really a use case that we see a lot and that's improving I mean retail location, location, location. People still go into stores And still are. Like the think about cus with businesses that have true So they wanna put it inland. So then, you know, oh, they go to this park or they go somewhere and we can help you place your next in and out based on that visitation. So take us through the customers. What does the buyer get? So you can, that API can make real time calls or you're buying a flat file, So it's pretty data friendly in terms of You can kind of do whatever you want with it. You've been more on the data exchange, Chris kind of called that out. They've really focused on the data and they understand how CU, how, you know, people like us sell It is You know, we feel like they really value us as a partner. If you had to kind of, you know, guess given your history in, I think as exchanges think about, you know, expanding what are the other types of data products You know, you got, yeah. we wanna allocate resources against it, but you know, it's definitely, it's a really interesting space to be in. What's the pitch. So we can tell you we're, And they use that for whatever their needs are, business improvement, user I mean, we also have some financial use cases. We do, you got the app and you got the physical world it's mean, I think, yeah, as you said, it's that we track a lot I think that those there's a play there as All right, Leah, thank you for coming on the Q appreciate so much it all right.

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8 Stelio D'Alo & Raveesh Chugh, Zscaler | AWS Marketplace Seller Conference 2022


 

(upbeat electronic music) >> Welcome back to everyone, to "theCUBE's" coverage here in Seattle, Washington for Amazon Web Services Partner Marketplace Seller Conference, combining their partner network with Marketplace forming a new organization called AWS Partner Organization. This is "theCUBE" coverage. I'm John Furrier, your host. We've got great "Cube" alumni here from Zscaler, a very successful cloud company doing great work. Stelio D'Alo, senior director of cloud business development and Raveesh Chugh, VP of Public Cloud Partnerships at Zscaler. Welcome back to "theCUBE." Good to see you guys. Thanks for coming on. >> Thank you. >> Thanks having us, John. >> So we've been doing a lot of coverage of Zscaler, what a great success story. I mean, the numbers are great. The business performance, it's in the top two, three, one, two, three in all metrics on public companies, SaaS. So you guys, check. Good job. >> Yes, thank you. >> So you guys have done a good job. Now you're here, selling through the Marketplace. You guys are a world class performing company in cloud SaaS, so you're in the front lines doing well. Now, Marketplace is a procurement front end opportunity for people to buy. Hey, self-service, buy and put things together. Sounds novel, what a great concept. Great cloud life. >> Yes. >> You guys are participating and now sellers are coming together. The merger of the public, the partner network with Marketplace. It feels like this is a second act for AWS to go to the next level. They got their training wheels done with partners. Now they're going to the next level. What do you guys think about this? >> Well, I think you're right, John. I think it is very much something that is in keeping with the way AWS does business. Very Amazonian, they're working back from the customer. What we're seeing is, our customers and in general, the market is gravitating towards purchase mechanisms and route to market that just are lower friction. So in the same way that companies are going through their digital transformations now, really modernizing the way they host applications and they reach the internet. They're also modernizing on the purchasing side, which is super exciting, because we're all motivated to help customers with that agility. >> You know, it's fun to watch and again I'm being really candid and props to you guys as a company. Now, everyone else is kind of following that. Okay, lift and shift, check, doing some things. Now they go, whoa, I can really build on this. People are building their own apps for their companies. Going to build their own stuff. They're going to use piece parts. They're going to put it together in a really scalable way. That's the new normal. Okay, so now they go okay, I'm going to just buy through the market, I get purchasing power. So you guys have been a real leader with AWS. Can you share what you guys are doing in the Marketplace? I think you guys are a nice example of how to execute the Marketplace. Take us through. What are you guys offering there? What's the contract look like? Is it multi-pronged? What's the approach? What do customers get if they go to the marketplace for Zscaler? >> Yeah, so it's been a very exciting story and been a very pleasing one for us with AWS marketplace. We see a huge growth potentially. There are more than 350,000 customers that are actively buying through Marketplace today. We expect that number to grow to around a million customers by the next, I would say, five to ten years and we want to be part of this wave. We see AWS Marketplace to be a channel where not only our resalers or our channel partners can come and transact, but also our GSIs like Accenture want to transact through this channel. We are doing a lot, in terms of bringing new customers through Marketplace, who want to not only close their deals, but close it in the next few hours. That's the beauty of Marketplace, the agility, the flexibility in terms of pricing that it provides to ISVs like us. If a customer wants to delay their payments by a couple of quarters, Marketplace supports that. If a customer wants to do monthly payments, Marketplace supports that. We are seeing lot of customers, big customers, that have signed EDPs, enterprise discount plans with AWS. These are multi-year cloud commits coming to us and saying we can retire our EDPs with AWS if we transact your solution through AWS Marketplace. So what we have done, as of today, we have all of our production services enabled through AWS Marketplace. What that means for customers, they can now retire their EDPs by buying Zscaler products through AWS Marketplace and in return get the full benefit of maximizing their EDP commits with AWS. >> So you guys are fully committed, no toe on the water, as we heard. You guys are all in. >> Absolutely, that's exactly the way to put it. We're all in, all of our solutions are available in the marketplace. As you mentioned, we're a SaaS provider. So we're one of the vendors in the Marketplace that have SaaS solutions. So unlike a lot of customers and even the market in general, associate the Marketplace for historical reasons, the way it started with a lot of monthly subscriptions and just dipping your toe in it from a consumer perspective. Whereas we're doing multimillion dollar, multi-year SaaS contracts. So the most complicated kinds of transactions you'd normally associate with enterprise software, we're doing in very low friction ways. >> On the Zscaler side going in low friction. >> Yep, yeah, that's right. >> How about the customer experience? >> So it is primarily the the customer that experiences. >> Driving it? >> Yeah, they're driving it and it's because rather than traditional methods of going through paperwork, purchase orders- >> What are some of the things that customers are saying about this, bcause I see two benefits, I'll say that. The friction, it's a channel, okay, for Zscaler. Let's be clear, but now you have a customer who's got a lot of Amazon. They're a trusted partner too. So why wouldn't they want to have one point of contact to use their purchasing power and you guys are okay with that. >> We're absolutely okay with it. The reason being, we're still doing the transaction and we can do the transaction with our... We're a channel first company, so that's another important distinction of how people tend to think of the Marketplace. We go through channel. A lot of our transactions are with traditional channel partners and you'd be surprised the kinds of, even the Telcos, carrier providers, are starting to embrace Marketplace. So from a customer perspective, it's less paperwork, less legal work. >> Yeah, I'd love to get your reaction to something, because I think this highlights to me what we've been reporting on with "theCUBE" with super cloud and other trends that are different in a good way. Taking it to the next level and that is that if you look at Zscaler, SaaS, SaaS is self-service, the scale, there's efficiencies. Marketplace first started out as a self-service catalog, a website, you know, click and choose, but now it's a different. He calls it a supply chain, like the CICD pipeline of buying software. He mentions that, there's also services. He put the Channel partners can come in. The GSIs, global system integrators can come in. So it's more than just a catalog now. It's kind of self-service procurement more than it is just a catalog of buy stuff. >> Yes, so yeah, I feel CEOs, CSOs of today should understand what Marketplace brings to the bear in terms of different kinds of services or Zscaler solutions that they can acquire through Marketplace and other ISV solutions, for that matter. I feel like we are at a point, after the pandemic, where there'll be a lot of digital exploration and companies can do more in terms of not just Marketplace, but also including the channel partners as part of deals. So you talked about channel conflict. AWS addressed this by bringing a program called CPPO in the picture, Channel Partner Private Offers. What that does is, we are not only bringing all our channel partners into deals. For renewals as well, they're the partner of record and they get paid alongside with the customer. So AWS does all the heavy lifting, in terms of disbursements of payments to us, to the channel partner, so it's a win-win situation for all. >> I mean, private offers and co-sale has been very popular. >> It has been, and that is our bread and butter in the Marketplace. Again, we do primarily three year contracts and so private offers work super well. A nice thing for us as a vendor is it provides a great amount of flexibility. Private Offer gives you a lot of optionality, in terms of how the constructs of the deal and whether or not you're working with a partner, how the partner is utilizing as well to resell to the end user. So, we've always talked about AWS giving IT agility. This gives purchasing and finance business agility. >> Yeah, and I think this comes up a lot. I just noticed this happening a lot more, where you see dedicated sessions, not just on DevOps and all the goodies of the cloud, financial strategy. >> Yeah. >> Seeing a lot more conversation around how to operationalize the business transactions in the cloud. >> Absolutely. >> This is the new, I mean it's not new, it's been thrown around, but not at a tech conference. You don't see that. So I got to ask you guys, what's the message to the CISOs and executives watching the business people about Zscaler in the Marketplace? What should they be looking at? What is the pitch for Zscaler for the Marketplace buyer? >> So I would say that we are a cloud-delivered network security service. We have been in this game for more than a decade. We have years of early head start with lots of features and functionality versus our competitors. If customers were to move into AWS Cloud, they can get rid of their next-gen firewalls and just have all the traffic routed through our Zscaler internet access and use Zscaler private access for accessing their private applications. We feel we have done everything in our capacity, in terms of enabling customers through Marketplace and will continue to participate in more features and functionality that Marketplace has to offer. We would like these customers to take advantage of their EDPs as well as their retirement and spend for the multi-commit through AWS Marketplace. Learn about what we have to offer and how we can really expedite the motion for them, if they want to procure our solutions through Marketplace >> You know, we're seeing an ability for them to get more creative, more progressive in terms of the purchasing. We're also doing, we're really excited about the ability to serve multiple markets. So we've had an immense amount of success in commercial. We also are seeing increasing amount of public sector, US federal government agencies that want to procure this way as well for the same reasons. So there's a lot of innovation going on. >> So you have the FedRAMP going on, you got all those certifications. >> Exactly right. So we are the first cloud-native solution to provide IL5 ATO, as well as FedRAMP pie and we make that all available, GSA schedule pricing through the AWS Marketplace, again through FSIs and other resellers. >> Public private partnerships have been a big factor, having that span of capability. I got to ask you about, this is a cool conversation, because now you're like, okay, I'm selling through the Marketplace. Companies themselves are changing how they operate. They don't just buy software that we used to use. So general purpose, bundled stuff. Oh yeah, I'm buying this product, because this has got a great solution and I have to get forced to use this firewall, because I bought this over here. That's not how companies are architecting and developing their businesses. It's no longer buying IT. They're building their company digitally. They have to be the application. So they're not sitting around, saying hey, can I get a solution? They're building and architecting their solution. This is kind of like the new enterprise that no one's talking about. They kind of, got to do their own work. >> Yes. >> There's no general purpose solution that maps every company. So they got to pick the best piece parts and integrate them. >> Yes and I feel- >> Do you guys agree with that? >> Yeah, I agree with that and customers don't want to go for point solutions anymore. They want to go with a platform approach. They want go with a vendor that can not only cut down their vendors from multi-dozens to maybe a dozen or less and that's where, you know, we kind of have pivoted to the platform-centric approach, where we not only help customers with Cloud Network Security, but we also help customers with Cloud Native Application Protection Platform that we just recently launched. It's going by the name of the different elements, including Cloud Security Posture Management, Cloud Identity Event Management and so we are continuously doing more and more on the configuration and vulnerability side space. So if a customer has an AWS S3 bucket that is opened it can be detected and can be remediated. So all of those proactive steps we are taking, in terms of enhancing our portfolio, but we have come a long way as a company, as a platform that we have evolved in the Marketplace. >> What's the hottest product? >> The hottest product? >> In Marketplace right now. >> Well, the fastest growing products include our digital experience products and we have new Cloud Protection. So we've got Posture and Workload Protection as well and those are the fastest growing. For AWS customers a strong affinity also for ZPA, which provides you zero trust access to your workloads on AWS. So those are all the most popular in Marketplace. >> Yeah. >> So I would like to add that we recently launched and this has been a few years, a couple of years. We launched a product called Zscaler Digital X, the ZDX. >> Mm-hmm. >> What that product does is, let's say you're making a Zoom call and your WiFi network is laggy or it's a Zoom server that's laggy. It kind of detects where is the problem and it further tells the IT department you need to fix either the server on which Zoom is running, or fix your home network. So that is the beauty of the product. So I think we are seeing massive growth with some of our new editions in the portfolio, which is a long time coming. >> Yeah and certainly a lot of growth opportunities for you guys, as you come in. Where do you see Zscaler's big growth coming from product-wise? What's the big push? Actually, this is great upside for you here. >> Yeah. >> On the go to market side. Where's the big growth for Zscaler right now? So I think we are focused as a company on zero trust architecture. We want to securely connect users to apps, apps to apps, workloads to workloads and machines to machines. We want to give customers an experience where they have direct access to the apps that's hidden from the outside world and they can securely connect to the apps in a very succinct fashion. The user experience is second to none. A lot of customers use us on the Microsoft Office 365 side, where they see a lag in connecting to Microsoft Office 365 directly. They use the IE service to securely connect. >> Yeah, latency kills. >> Microsoft Office 365. >> Latency kills, as we always say, you know and security, you got to look at the pattern, you want to see that data. >> Yeah, and emerging use cases, there is an immense amount of white space and upside for us as well in emerging use cases, like OT, 5G, IOT. >> Yeah. >> Federal government, DOD. >> Oh god, tactical edge government. >> Security at the edge, absolutely, yeah. >> Where's the big edge? What's the edge challenge right now, if you have to put your finger on the edge, because right now that's the hot area, we're watching that. It's going to be highly contested. It's not yet clear, I mean certainly hybrid is the operating model, cloud, distributing, computing, but edge has got unique things that you can't really point to on premises that's the same. It's highly dynamic, you need high bandwidth, low latency, compute at the edge. The data has to be processed right there. What's the big thing at the edge right now? >> Well, so that's probably an emerging answer. I mean, we're working with our customers, they're inventing and they're kind of finding the use cases for those edge, but one of the good things about Zscaler is that we are able to, we've got low latency at the edge. We're able to work as a computer at the edge. We work on Outpost, Snowball, Snowcone, the Snow devices. So we can be wherever our customers need us. Mobile devices, there are a lot of applications where we've got to be either on embedded devices, on tractors, providing security for those IOT devices. So we're pretty comfortable with where we are being the- >> So that's why you guys are financially doing so well, performance wise. I got to ask you though, because I think that brings up the great point. If this is why I like the Marketplace, if I'm a customer, the edge is highly dynamic. It's changing all the time. I don't want to wait to buy something. If I got my solution architects on a product, I need to know I'm going to have zero trust built in and I need to push the button on Zscaler. I don't want to wait. So how does the procurement side impact? What have you guys seen? Share your thoughts on how Marketplace is working from the procurement standpoint, because it seems to me to be fast. Is that right, or is it still slow on their side? On the buyer side, because this to me would be a benefit to developers, if we say, hey, the procurement can just go really fast. I don't want to go through a bunch of PO approvals or slow meetings. >> It can be, that manifests itself in several ways, John. It can be, for instance, somebody wants to do a POC and traditionally you could take any amount of time to get budget approval, take it through. What if you had a pre-approved cloud budget and that was spent primarily through AWS Marketplace, because it's consolidated data on your AWS invoice. The ability to purchase a POC on the Marketplace could be done literally within minutes of the decision being made to go forward with it. So that's kind of a front end, you know, early stage use case. We've got examples we didn't talk about on our recent earnings call of how we have helped customers bring in their procurement with large million dollar, multimillion dollar deals. Even when a resaler's been involved, one of our resaler partners. Being able to accelerate deals, because there's so much less legal work and traditional bureaucratic effort. >> Agility. >> That agility purchasing process has allowed our customers to pull into the quarter, or the end of month, or end of quarter for them, deals that would've otherwise not been able to be done. >> So this is a great example of where you can set policy and kind of create some guard rails around innovation and integration deals, knowing if it's something that the edge is happening, say okay, here's some budget. We approved it, or Amazon gives credits and partnership going on. Then I'd say, hey, well green light this, not to exceed a million dollars, or whatever number in their range and then let people have the freedom to execute. >> You're absolutely right, so from the purchasing side, it does give them that agility. It eliminates a lot of the processes that would push out a purchase in actual execution past when the business decision is made and quite frankly, to be honest, AWS has been very accommodative. They're a great partner. They've invested a lot in Marketplace, Marketplace programs, to help customers do the right thing and do it more quickly as well as vendors like us to help our customers make the decisions they need to. >> Rising tide, a rising tide floats all boats and you guys are a great example of an independent company. Highly successful on your own. >> Yep. >> Certainly the numbers are clear. Wall Street loves Zscaler and economics are great. >> Our customer CSAT numbers are off the scale as well. >> Customers are great and now you've got the Marketplace. This is again, a new normal. A new kind of ecosystem is developing where it's not like the old monolithic ecosystems. The value creation and extraction is happening differently now. It's kind of interesting. >> Yes and I feel we have a long way to go, but what I can tell you is that Zscaler is in this for the long run. We are seeing some of the competitors erupt in the space as well, but they have a long way to go. What we have built requires years worth of R&D and features and thousands of customer's use cases which kind of lead to something what Zscaler has come up with today. What we have is very unique and is going to continuously be an innovation in the market in the years to come. In terms of being more cloud-savvy or more cloud-focused or more cloud-native than what the market has seen so far in the form of next-gen firewalls. >> I know you guys have got a lot of AI work. We've had many conversations with Howie over there. Great stuff and really appreciate you guys participating in our super cloud event we had and we'll see more of that where we're talking about the next generation clouds, really enabling that new disruptive, open-spanning capabilities across multiple environments to run cloud-native modern applications at scale and secure. Appreciate your time to come on "theCUBE". >> Thank you. >> Thank you very much. >> Thanks for having us. >> Thanks, I totally appreciate it. Zscaler, leading company here on "theCUBE" talking about their relationship with Marketplace as they continue to grow and succeed as technology goes to the next level in the cloud. Of course "theCUBE's" covering it here in Seattle. I'm John Furrier, your host. Thanks for watching. (peaceful electronic music)

Published Date : Sep 21 2022

SUMMARY :

Good to see you guys. I mean, the numbers are great. So you guys have done a good job. The merger of the public, So in the same way that companies and props to you guys as a company. and in return get the full benefit So you guys are fully committed, and even the market in general, On the Zscaler side So it is primarily the the customer What are some of the things and we can do the transaction with our... and that is that if you So AWS does all the heavy lifting, I mean, private offers and in terms of how the constructs of the deal the goodies of the cloud, in the cloud. So I got to ask you guys, and just have all the traffic routed in terms of the purchasing. So you have the FedRAMP going on, and we make that all available, This is kind of like the new enterprise So they got to pick the best evolved in the Marketplace. Well, the fastest growing products Zscaler Digital X, the ZDX. So that is the beauty of the product. What's the big push? On the go to market side. and security, you got Yeah, and emerging use cases, on premises that's the same. but one of the good things about Zscaler and I need to push the button on Zscaler. of the decision being made or the end of month, or the freedom to execute. It eliminates a lot of the processes and you guys are a great example Certainly the numbers are clear. are off the scale as well. It's kind of interesting. and is going to continuously the next generation clouds, next level in the cloud.

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Ameya Talwalker & Subbu Iyer, Cequence Security | AWS Startup Showcase S2 E4 | Cybersecurity


 

>>Hello, and welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four, the ongoing series covering exciting startups from the AWS ecosystem to talk about cyber security. I'm your host, John feer. And today we're excited to join by a Mediatel Walker, CEO of Quin security and sub IER, vice president of product management of sequence security gentlemen, thanks for joining us today on this showcase. >>Thank you, John PRAs. >>So the title of this session is continuous API protection life cycle to discover, detect, and defend security. APIs are part of it. They're hardened, everyone's using them, but they're they're target for malicious behavior. This is the focus of this segment. You guys are in the leading edge of this. What are the biggest challenges for organizations right now in assessing their security risks? Because you're seeing APIs all over the place in the news, just even this week, Twitter had a whistleblower come out from the security group, talking about their security plans, misleading the FTC on the bots and some of the malicious behavior inside the API interface of Twitter. This is really a mainstream Washington post is reporting on it. New York times, all the global outlets are talking about this story. This is the risk. I mean, yeah, this is what you guys do protect against this. >>Yeah, this is absolutely top of mind for a lot of security folks today. So obviously in the media and the type of attack that that is being discussed with this whistleblower coming out is called reputation bombing. This is not new. This has been going on since I would say at least eight to 10 years where the, the bad actors are using bots or automation and ultimately using APIs on these large social media platforms, whether it's Facebook, whether it's Twitter or some other social media platform and messing with the reputation system of those large platforms. And what I mean by that is they will do fake likes, fake commenting, fake retweeting in the case of Twitter. And what that means is that things that are, should not be very popular, all of a sudden become popular. That that way they're able to influence things like elections, shopping habits, personnel. >>We, we work with similar profile companies and we see this all the time. We, we mostly work on some of the secondary platforms like dating and other sort of social media platforms around music sharing and things like video sharing. And we see this all the time. These, these bots are bad. Actors are using bots, but ultimately it's an API problem. It's not just a bot problem. And that's what we've been trying to sort of preach to the world, which is your bot problem is subset of your API security challenges that you deal as an organization. >>You know, IMIA, we talked about this in the past on a previous conversation, but this really is front and center mainstream for the whole world to see around the challenges. All companies face, every CSO, every CIO, every board member organizations out there looking at this security posture that spans not just information technology, but physical and now social engineering. You have all kinds of new payloads of malicious behavior that are being compromised through, through things like APIs. This is not just about CSO, chief information security officer. This is chief security officer issues. What's your reaction >>Very much so I think the, this is a security problem, but it's also a reputation problem. In some cases, it's a data governance problem. We work with several companies which have very restrictive data governance and data regulations or data residency regulations there to conform to those regulations. And they have to look at that. It's not just a CSO problem anymore. In case of the, the news of the day to day, this is a platform problem. This goes all the way to the, that time CTO of Twitter. And now the CEO of Twitter, who was in charge of dealing with these problems. We see as just to give you an example, we, we work, we work with a similar sort of social media platform that allows Oop based login to their platform that is using tokens. You can sort of sign in with Facebook, sign in with Twitter, sign in with Google. These are API keys that are generated and trusted by these social media platforms. When we saw that Facebook leaked about 50 million of these login credentials or API keys, this was about three, four years ago. I wrote a blog about it. We saw a huge spike in those API keys being used to log to other social media platforms. So although one social platform might be taking care of its, you know, API or what problem, if something else gets reached somewhere else, it has a cascading impact on a variety of platforms. >>You know, that's a really interesting dynamic. And if you think about just the token piece that you mentioned, that's kind of under the coverage, that's a technology challenge, but also you get in the business logic. So let's go back and, and unpack that, okay, they discontinue the tokens. Now they're being reused here. In the case of Twitter, I was talking to an executive here in Silicon valley and they said, yeah, it's a cautionary tale, for sure. Although Twitter's a unique situation, but they abstract out the business value and say, Hey, they had an M and a deal on the table. And so if someone wants to unwind that deal, all I gotta say is, Hey, there's a bot problem. And now you have essentially new kinds of risk in the business have nothing to do with some sign the technology, okay. They got a security breach, but here with Twitter, you have an, an, an M and a deal, an acquisition that's being contested because of the, the APIs. So, so if you're in business, you gotta think to yourself, what am I risking with my API? So every organization should be assessing their security risks, tied to their APIs. This is a huge awakening for them. Where should they start? And that's the, that's the core question. Okay. You got my attention risks with the API. What do I do? >>So when I talked to you in my previous interview, the start is basically knowing what to, in most cases, you see these that are hitting the wire much. Every now there is a major in cases you'll find these APIs are targeted, that are not poorly protected. They're absolutely just not protected at all, which means the security team or any sort of team that is responsible for protecting these APIs are just completely unaware of these APIs being there in the first place. And this is where we talk about the shadow it or shadow API problem. Large enterprises have teams that are geo distributed, and this problem is escalated after the pandemic even more because now you have teams that are completely distributed. They do M and a. So they acquire new companies and have no visibility into their API or security practices. And so there are a lot of driving factors why these APIs are just not protected and, and just unknown even more to the security team. So the first step has to be discover your API attack surface, and then prioritize which APIs you wanna target in terms of runtime protection. >>Yeah. I wanna dig into that API kind of attack surface area management, runtime monitoring capability in a second, but so I wanna get you in here too, because we're talking about APIs, we're talking about attacks. What does an API attack look like? >>Yeah, that's a very good question, John, there are really two different forms of attacks of APIs, one type of attack, exploits, APIs that have known vulnerabilities or some form of vulnerabilities. For instance, APIs that may use a weak form of authentication or are really built with no authentication at all, or have some sort of vulnerability that makes them very good targets for an attacker to target. And the second form of attack is a more subtle one. It's called business logic abuse. It's, it's utilizing APIs in completely legitimate manner manners, but exploiting those APIs to exfiltrate information or key sensitive information that was probably not thought through by the developer or the designers or those APIs. And really when we do API protection, we really need to be able to handle both of those scenarios, protect against abuse of APIs, such as broken authentication, or broken object level authorization APIs with that problem, as well as protecting APIs from business logic abuse. And that's really how we, you know, differentiate against other vendors in this >>Market. So just what are the, those key differentiated ways to identify the, in the malicious intents with APIs? Can you, can you just summarize that real quick, the three ways? >>Sure. Yeah, absolutely. There are three key ways that we differentiate against our competition. One is in the, we have built out a, in the ability to actually detect such traffic. We have built out a very sophisticated threat intelligence network built over the entire lifetime of the company where we have very well curated information about malicious infrastructures, malicious operators around the world, including not just it address ranges, but also which infrastructures do they operate on and stuff like that, which actually helps a lot in, in many environments in especially B2C environments, that alone accounts for a lot of efficacy for us in detecting our weed out bad traffic. The second aspect is in analyzing the request that are coming in the API traffic that is coming in and from the request itself, being able to tell if there is credential abuse going on or credential stuffing going on or known patterns that the traffic is exhibiting, that looks like it is clearly trying to attack the attack, the APM. >>And the third one is, is really more sophisticated as they go farther and farther. It gets more sophisticated where sequence actually has a lot of machine learning models built in which actually profile the traffic that is coming in and separate. So the legitimate or learns the legitimate traffic from the anomalous or suspicious traffic. So as the traffic, as the API requests are coming in, it automatically can tell that this traffic does not look like legitimate traffic does not look like the traffic that this API typically gets and automatically uses that to figure out, okay, where is this traffic coming from? And automatically takes action to prevent that attack? >>You know, it's interesting APIs have been part of the goodness of cloud and cloud scale. And it reminds me of the old Andy Grove quote, founder of, in one of the founders of Intel, you know, let chaos, let, let the chaos happen, then reign it in it's APIs. You know, a lot of people have been creating them and you've got a lot of different stakeholders involved in creating them. And so now securing them and now manage them. So a lot of creation now you're starting to secure them and now you gotta manage 'em. This all is now big focus. As you pointed out, what are some of the dynamics that customers who have to deal with on the product side and, and organization, let, let chaos rain, and then rain in the chaos, as, as the saying goes, what, what do companies do? >>Yeah. Typically companies start off with like, like a mayor talked about earlier. Discovery is really the key thing to start with, like figuring out what your API attack surfaces and really getting your arms around that problem. And typically we are finding customers start that off from the security organization, the CSO organization to really go after that problem. And in some cases, in some customers, we even find like dedicated centers of excellence that are created for API security, which go after that problem to be able to get their arms around the whole API attack surface and the API protection problem statement. So that's where usually that problem starts to get addressed. >>I mean, organizations and your customers have to stop the attacks. A lot of different techniques, you know, run time. You mentioned that earlier, the surface area monitoring, what's the choice. What's the, where are, where are, where is everybody? Is everyone in the, in the boiling water, like the frog and boiling water or they do, they know it's happening? Like what did they do? What's their opportunity to get in >>Position? Yeah. So I, I think let's take a step back a little bit, right? What has happened is if you draw the cloud security market, if you will, right. Which is the journey to the cloud, the security of these applications or APIs at a container level, in terms of vulnerabilities and, and other things that market grew with the journey to the cloud, pretty much locked in lockstep. What has happened in the API side is the API space has kind of lacked behind the growth and explosion in the API space. So what that means is APIs are getting published way faster than the security teams are able to sort of control and secure them. APIs are getting published in environments that the security completely unaware of. We talked about in the past about the parameter, the parameter, as we know, it doesn't exist anymore. It used to be the case that you hit a CDN, you terminate your SSL, you stop your layer three and four DDoS. >>And then you go into the application and do the business logic. That parameter is just gone because it's now could be living in multi-cloud environment. It could be living in the on-prem environment, which is PubNet is friendly. And so security teams that are used to protecting apps, using a perimeter defense plus changes, it's gone. You need to figure out where your perimeter is. And therefore we sort of recommend an approach, which is have a uniform view across all your APIs, wherever they could be distributed and have a single point of control across those with a solution like sequence. And there are others also in this space, which is giving you that uniform view, which is first giving you that, you know, outside and looking view of what APIs to protect. And then let's, you sort of take the journey of securing the API life cycle. >>So I would say that every company now hear me out on this indulges me for a second. Every company in the world will be non perimeter based, except for maybe 5% because of maybe unique reason, proprietary lockdown, information, whatever. But for most, most companies, everyone will be in the cloud or some cloud native, non perimeter based security posture. So the question is, how does your platform fit into that trajectory? And specifically, why are you guys in the position in your mind to help customers solve this API problem? Because again, APIs have been the greatest thing about the cloud, right? Yeah. So the goodness is there because of APS. Now you gotta reign it in reign in the chaos. Yeah. What, what about your platform share? What is it, why is it win? Why should customers care about this? >>Absolutely. So if you think about it, you're right, the parameter doesn't exist. People have APIs deployed in multiple environments, multicloud hybrid, you name it sequence is uniquely positioned in a way that we can work with your environment. No matter what that environment is. We're the only player in this space that can protect your APIs purely as a SA solution or purely as an on-prem deployment. And that could be a SaaS platform. It doesn't need to be RackN, but we also support that and we could be a hybrid deployment. We have some deployments which are on your prem and the rest of this solution is in our SA. If you think about it, customers have secured their APIs with sequence with 15 minutes, you know, going live from zero to life and getting that protection instantaneously. We have customers that are processing a billion API calls per day, across variety of different cloud environments in sort of six different brands. And so that scale, that flexibility of where we can plug into your infrastructure or be completely off of your infrastructure is something unique to sequence that we offer that nobody else is offering >>Today. Okay. So I'll be, I'll be a naysayer. Yeah, look, it, we are perfectly coded APIs. We are the best in the business. We're locked down. Our APIs are as tight as a drum. Why do I need you? >>So that goes back to who's answer. Of course, >>Everyone's say that that's, that's great, but that's my argument. >>There are two types of API attacks. One is a tactic problem, which is exploiting a vulnerability in an API, right? So what you're saying is my APIs are secure. It does not have any vulnerability I've taken care of all vulnerabilities. The second type of attack that targets APIs is the business logic. Use this stuff in the news this week, which is the whistleblower problem, which is, if you think APIs that Twitter is publishing for users are perfectly secure. They are taking care of all the vulnerabilities and patching them when they find new ones. But it's the business logic of, you know, REWE liking or commenting that the bots are targeting, which they have no against. Right. And then none of the other social networks too. Yeah. So there are many examples. Uber wrote a program to impersonate users in different geo locations to find lifts, pricing, and driver information and passenger information, completely legitimate use of APIs for illegitimate, illegitimate purpose using bots. So you don't need bots by the way, don't, don't make this about bot versus not. Yeah. You can use APIs sort of for the, the purpose that they're not designed for sort of exploiting their business logic, either using a human interacting, a human farm, interacting with those APIs or a bot form targeting those APIs, I think. But that's the problem when you have, even when you've secured all your problem, all your APIs, you still have to worry about these of challenges. >>I think that's the big one. I think the business logic one, certainly the Twitter highlights that the Uber example is a good one. That is basically almost the, the backlash of having a simplistic API, which people design to. Right. Yeah. You know, as you point out, Twitter is very simple API, hardened, very strong security, but they're using it to maliciously manipulate what's inside. So in a way that perimeter's dead too. Right. So how do you stop that business logic? What's the, what's the solution what's the customer do about that? Because their goal is to create simple, scalable APIs. >>Yeah. I'll, I'll give you a little bit, and then I think Subaru should maybe go into a little bit of the depth of the problem, but what I think that the answer lies in what Subaru spoke earlier, which is our ML. AI is, is good at profiling plus split between the API users, are these legitimate users, humans versus bots. That's the first split we do. The split second split we do is even when these, these are classified users as bots, we will say there are some good bots that are necessary for the business and bad bots. So we are able to split this across three types of users, legitimate humans, good bots and bad bots. And just to give you an example of good bots is there are in the financial work, there are aggregators that are scraping your data and aggregating for end users to consume, right? Your, your, and other type of financial aggregators FinTech companies like MX. These are good bots and you wanna allow them to, you know, use your APIs, whereas you wanna stop the bad bots from using your APIs super, if you wanna add so, >>So good bots versus bad bots, that's the focus. Go ahead. Weigh in, weigh in on your thought on this >>Really breaks down into three key areas that we talk about here, sequence, right? One is you start by discovering all your APIs. How many APIs do I have in my environment that ly immediately highlight and say, Hey, you have, you know, 10,000 APIs. And that usually is an eye opener to many customers where they go, wow. I thought we had a 10th of that number. That usually is an eyeopener for them to, to at least know where they're at. The second thing is to tell them detection information. So discover, detect, and defend detect will tell them, Hey, your APIs are getting traffic from. So and so it addresses so and so infrastructure. So and so countries and so on that usually is another eye opener for them. They then get to see where their API traffic is coming from. Let's say, if you are a, if you're running a pizza delivery service out of California and your traffic is coming from Eastern Europe to go, wait a minute, nobody's trying, I'm not, I'm not, I don't deliver pizzas in Eastern Europe. Why am I getting traffic from that part of the world? So that sort of traffic immediately comes up and it will tell you that it is hitting your unauthenticated API. It is hitting your API. That has, that is vulnerable to a broken object level, that authorization, vulnerable be and so on. >>Yeah, I think, and >>Then comes the different aspect. Yeah. The different aspect is where you can take action and say, I wanna block certain types of traffic, or I wanna rate limit certain types of traffic. If, if you're seeing spikes there or you could maybe insert header so that it passes on to the end application and the application team can use that bit to essentially take a, a conscious response. And so, so the platform is very flexible in allowing them to take an action that suits their needs. >>Yeah. And I think this is the big trend. This is why I like what you guys are doing. One APIs we're built for the goodness of cloud. They're now the plumbing, you know, anytime you see plumbing involved, connection points, you know, that's pretty important. People are building it out and it has made the cloud what it is. Now, you got a security challenge. You gotta add more intelligence, more smarts to it. This is where I think platform versus tools matter. Can you guys just quickly share your thoughts on that? Cuz a lot of your customers and, and future customers have dealt with the sprawls of all these different tools. Right? I got a tool for this. I got a tool for that, but people are gravitating towards platforms, but how many platforms can a customer have? So again, this brings up the point point around how you guys are engaging with customers. Can you share your thoughts on tooling platforms? Your customers are constantly inundated with the same tsunami. Isn't new thing. Why, what, how should they look at this? >>Yeah, I mean, we don't wanna be, we don't wanna add to that alert fatigue problem that affects much of the cybersecurity industry by generating a whole bunch of alerts and so on. So what we do is we actually integrate very well with S IEM systems or so systems and allow customers to integrate the information that we are detecting or mitigating and feed them onto enterprise systems like a Splunk or a Datadog where they may have sophisticated processes built in to monitor, you know, spikes in anomalous traffic or actions that are taken by sequence. And that can be their dashboard where a whole bunch of alerting and reporting actually happens. So we play in the security ecosystem very well by integrating with other products and integrate very tightly with them, right outta the box. >>Okay. Mia, this is a wrap up now for the showcase. Really appreciate you guys sharing your awesome technology and very relevant product for your customers and where we are right now in this we call Supercloud or now multi-cloud or hybrid world of cloud. Share a, a little bit about the company, how people can get involved in your solution, how they can consume it and things they should know about, about sequence security. >>Yeah, we've been on this journey, an exciting journey it's been for, for about eight years. We have very large fortune 100 global 500 customers that use our platform on a daily basis. We have some amazing logos, both in Europe and, and, and in us customers are, this is basically not the shelf product customers not only use it, but depend on sequence. Several retailers. We are sitting in front of them handling, you know, black Friday, cyber, Monday, Christmas shopping, or any sort of holiday seasonality shopping. And we have handled that the journey starts by, by just simply looking at your API attack surface, just to a discover call with sequence, figure out where your APIs are posted work with you to prioritize how to protect them in a sort of a particular order and take the whole life cycle with sequence. This is, this is an exciting phase exciting sort of stage in the company's life. We just raised a very sort of large CDC round of funding in December from Menlo ventures. And we are excited to see, you know, what's next in, in, in the next, you know, 12 to 18 months. It certainly is the, you know, one of the top two or three items on the CSOs, you know, budget list for next year. So we are extremely busy, but we are looking for, for what the next 12 to 18 months are, are in store for us. >>Well, congratulations to all the success. So will you run the roadmap? You know, APIs are the plumbing. If you will, you know, they connection points, you know, you want to kind of keep 'em simple, as they say, keep the pipes dumb and make the intelligence around it. You seem to see more and more intelligence coming around, not just securing it, but does, where does this go in your mind? Where, where do we go beyond once we secure everything and manage it properly, APRs, aren't going away, they're only gonna get better and smarter. Where's the intelligence coming share a little bit. >>Absolutely. Yeah. I mean, there's not a dull moment in the space. As digital transformation happens to most enterprise systems, many applications are getting transformed. We are seeing an absolute explosion in the volume of APIs and the types of APIs as well. So the applications that were predominantly limited to data centers sort of deployments are now splintered across multiple different cloud environments are completely microservices based APIs, deep inside a Kubernetes cluster, for instance, and so on. So very exciting stuff in terms of proliferation of volume of APIs, as well as types of APIs, there's nature of APIs. And we are building very sophisticated machine learning models that can analyze traffic patterns of such APIs and automatically tell legitimate behavior from anomalous or suspicious behavior and so on. So very exciting sort of breadth of capabilities that we are looking at. >>Okay. I mean, yeah. I'll give you the final words since you're the CEO for the CSOs out there, the chief information security officers and the chief security officers, what do you want to tell them? If you could give them a quick shout out? What would you say to them? >>My shout out is just do an assessment with sequence. I think this is a repeating thing here, but really get to know your APIs first, before you decide what and where to protect them. That's the one simple thing I can mention for thes >>Am. Thank you so much for, for joining me today. Really appreciate it. >>Thank you. >>Thank you. Okay. That is the end of this segment of the eight of his startup showcase. Season two, episode four, I'm John for your host and we're here with sequin security. Thanks for watching.

Published Date : Sep 7 2022

SUMMARY :

This is season two, episode four, the ongoing series covering exciting startups from the AWS ecosystem So the title of this session is continuous API protection life cycle to discover, So obviously in the media and the type of attack that that is being discussed And that's what we've been trying to sort of preach to the world, which is your bot problem is mainstream for the whole world to see around the challenges. the news of the day to day, this is a platform problem. of risk in the business have nothing to do with some sign the technology, okay. So the first step has to be discover your API attack surface, runtime monitoring capability in a second, but so I wanna get you in here too, And that's really how we, you know, differentiate against other So just what are the, those key differentiated ways to identify the, in the malicious in the ability to actually detect such traffic. So the legitimate or learns the legitimate traffic from the anomalous or suspicious traffic. And it reminds me of the old Andy Grove quote, founder of, in one of the founders of Intel, Discovery is really the key thing to start with, You mentioned that earlier, the surface area monitoring, Which is the journey to the cloud, the security of And there are others also in this space, which is giving you that uniform And specifically, why are you guys in the position in your mind to help customers solve And so that scale, that flexibility of where we can plug into your infrastructure or We are the best in the business. So that goes back to who's answer. in the news this week, which is the whistleblower problem, which is, if you think APIs So how do you stop that business logic? And just to give you an example of good bots is there are in the financial work, there are aggregators that So good bots versus bad bots, that's the focus. So that sort of traffic immediately comes up and it will tell you that it is hitting your unauthenticated And so, so the platform is very flexible in They're now the plumbing, you know, anytime you see plumbing involved, connection points, in to monitor, you know, spikes in anomalous traffic or actions that are taken by Really appreciate you guys sharing your awesome And we are excited to see, you know, what's next in, in, in the next, So will you run the roadmap? So the applications that were predominantly limited to data centers sort of I'll give you the final words since you're the CEO for the CSOs out there, but really get to know your APIs first, before you decide what and where Am. Thank you so much for, for joining me today. Season two, episode four, I'm John for your host and we're here with sequin security.

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Luis Ceze, OctoML | Amazon re:MARS 2022


 

(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)

Published Date : Jun 24 2022

SUMMARY :

live on the floor at AWS re:MARS 2022. for having me in the show, John. but machine learning is the And that allows you to get certainly on the silicon side. 'cause I could see the progression. So once upon a time, yeah, no... because if you wake up learning runs in the end, that's going to give you the So that was pre-conventional wisdom. the Hamilton was working on. and to this day, you know, That's the beginning of that was logical when you is that the ecosystem because that's kind of the test First, you know-- and scaling the model the way you want, not having to do that integration work. Scale, and run the models So if you can move data to the edge, So do not have any of the typical And you can use existing-- the Artemis too, in space. If they have the hardware. And that allows you So I have to ask you, So if you believe that to be true, to the chips that you want. about the smart part. And you get good recruiting for PhDs So you have to make money. And also, in the process So depends on the scale of the deployment. So, you have direct sales How many customers do you have? We have a bunch of, you know, And they're both here, right. I won't give it away. One has three, one has four. in Japan, you know, self They're integrating, they see this as it to these customers. Since you can see the booth, others can't. and see how you look like We got a lot of So, you can use that. But I could use it. and then you can request But you can serve anybody, of removing the machine for other features that you normally have It's so obvious now that you say it. So we can help you navigate. in the dealer showroom. you can see the simulation. And it can run on the edge devices-- You're a machine learning as a service. know that you want to do, I get the DevOps agility but all of the convenience it brings the craftsmanship for machine learning to solve that. Cause the lean startup No, that's not it going to work. You know, that was from DevOps. double down, we all know the such that you can integrate, and then, you know, OSI on any deice that you Professor. That's great to have you on. Thank you very much. Uncoupling the machine learning Luis: Thank you.

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Muhammad Faisal, Capgemini | Amazon re:MARS 2022


 

(bright music) >> Hey, welcome back everyone, theCUBE coverage here at AWS re:Mars 2022. I'm John, your host of the theCUBE. re:Mars, part of the three re big events, re:Invent is the big one, re:Inforce the security, re:MARS is the confluence of industrial space, of automation, robotics and machine learning. Got a great guest here, Muhammad Faisal senior consultant solutions architect at Capgemini. Welcome to theCUBE. Thanks for coming on. >> Thank you. >> So we, you just we're hearing the classes we had with the professor from Okta ML from Washington. So he's in the weeds on machine learning. He's down getting dirty with all the hardcore, uncoupling it from hardware. Machine learning has gone really super nova in the past couple years. And this show points to the tipping point where machine learning's driving space, it's driving robotics industrial edge at unprecedented rates. So it's kind of moving from the old I don't want to say old, couple years ago and the legacy AI, I mean, old school AI is kind of the same new school with a twist it's just modernized and has faster, cheaper, smaller chips. >> Yeah. I mean, but there is a change also in the way it's working. So you had the classical AI, where you are detecting something and then you're making an action. You are perceiving something, making an action, you're detecting something, and you're assuming something that has been perceived. But now we are moving towards more deeper learning, deep. So AI, where you have to train your model to do things or to detect things and hope that it will work. And there's like, of course, a lot of research going on into explainable AI to help facilitate that. But that's where the challenges come into play. >> Well, Muhammad , first let's take, what do you do over there? Talk about your role specifically. You're doing a lot of student architecting around AI machine learning. What's your role? What's your focus. >> Yeah. So we basically are working in automotive to help OEMs and tier-one suppliers validate ADAS functions that they're working on. So advanced driving assistance systems, there are many levels that are, are when we talk about it. So it can be something simple, like, you know, a blind spot detection, just a warning function. And it goes all the way. So SAE so- >> So there's like the easy stuff and then the hard stuff. >> Muhammad : Exactly. >> Yeah. >> That's what you're getting at. >> Yeah. Yeah. And, and the easy stuff you can test validate quite easily because if you get it wrong. >> Yeah. >> The impact is not that high. The complicated stuff, if you have it wrong, then that can be very dangerous. (John laughs) >> Well, I got to say the automotive one was one was that are so fascinating because it's been so archaic and just in the past recent years, and Tesla's the poster child for this. You see that you go, oh my God, I love that car. I want to have a software driven car. And it's amazing. And I don't get a Tesla on now because that's, it's more like I should have gotten it earlier. Now I'm going to just hold my ground. >> Everyone has- >> Everyone's got it in Palo Alto. I'm not going to get another car, no way. So, but you're starting to see a lot of the other manufacturers, just in the past five years, they're leveling up. It may not be as cool and sexy as the Tesla, but it's, they're there. And so what are they dealing with when they talk about data and AI? What's the, what's some of the challenges that you're seeing that they're grappling with in terms of getting things integrated, developing pipelines, R and D, they wrangling data. Take us through some of the things. >> Muhammad: I mean, like when I think about the challenges that autonomous or the automakers are facing, I can think of three big ones. So first, is the amount of data they need to do their training. And more importantly, the validation. So we are talking about petabytes or hundred of petabytes of data that has to be analyzed, validated, annotated. So labeling to create gen, ground truth processed, reprocessed many times with every creation of a new software. So that is a lot of data, a lot of computational power. And you need to ensure that all of the processing, all of handling of the data allows you complete transparency of what is happening to the data, as well as complete traceability. So your, for home allocations, so approval process for these functions so that they can be released in cars that can be used on public roads. You need to have traceability. Like you can, you are supposed to be able to reproduce the data to validate your work that was done. So you can, >> John: Yeah >> Like, prove that your function is successful or working as expected. So this, the big data is the first challenge. I see that all the automotive makers are tackling. The second big one I see is understanding how much testing is enough. So with AI or with classical approach, you have certain requirements, how a function is supposed to work. You can test that with some test cases based on your architecture, and you have a successful or failed result. With deep learning, it gets more complicated. >> John: What are they doing with deep learning? Give an example of some of things. >> I mean, so you are, you need to then start thinking about statistics that I will test enough data with like a failure rate of potentially like 0.0, 0.1%. How much data do I need to test to make sure that I am achieving that rate. So then we are talking about, in terms of statistics, which requires a lot of data, because the failure rate that we want to have is so low. And it's not only like, failure in terms of that something is always detected, and if it's there, but it's also having like, a low false positive rate. So you are only detecting objects which are there and not like, phantom objects. >> What's some of the trends you're seeing across the client base, in terms of the patterns that they're all kind of, what, where's the state of their mindset and position with AI and some of the work they're doing, are they feeling, you feel like they're all crossed over across the chasm so to speak, in terms of executing, are they still in experimental mode in driving with the full capabilities is conservative or is it progressive? >> Muhammad: I mean, it's a mixture of both. So I'm in German automotive where I'm from, there is for functions, which are more complicated ones. There's definitely hesitancy to release them too early in the car, unless we are sure that they are safe. But of course, for functions which are assisting the drivers everyday usage they are widely available. Like one of the things like, so when we talk about this complex function. >> John: Highly available or available? >> Muhammad: I would say highly available. >> Higher? Is that higher availability and highly available. >> Okay. Yeah. (both laughing) >> Yeah, so. >> I know there's a distinction. >> Yeah. I mean >> I bring up as a joke cuz of the Jedi contract. (Muhammad laughs) >> I mean, in like, our architecture. So when we are developing our solution, high availability is one of our requirements. It is highly available, but the ADAS functions are now available in more and more cars. >> John: Well, latency, man. I mean, it's kind of a joke of storage, but it's a storage joke, but you know, it's latency, you got it, okay. (Muhammad laughs) But these are decisions that have to be made. >> Muhammad: They... >> I mean. >> Muhammad: I mean, they are still being made. >> So I mean, we are... >> John: Good. >> We haven't reached like, level five, which is the highest level of autonomous driving yet on public roads. >> John: That's hard. That's hard to do. >> Yeah. And I mean, the biggest difference, like, as you go above these levels is in terms of availability. So are they these functions? >> John: Yeah. >> Can they handle all possible scenarios or are they only available in certain scenarios? And of course the responsibility. So, it's, in the end, so with Tesla, you would be like, if you had a one you would be the person who is in control or responsible to monitor it. >> John: Yeah. But as we go >> John: Actually the reason I don't have a Tesla all my family would want one. I don't want to get anyone a Tesla. >> But I mean, but that's the sort the liabilities is currently on you, if like, you're not monitoring. >> Allright, so, talk about AWS, the relationship that Capgemini has with AWS, obviously, the partnerships there, you're here and this show is really a commitment to, this is a future to me, this is the future. >> Muhammad: Yeah. >> This is it. All right here, industrial, innovation's going to come massive. Back-office cloud, done deal. Data centers, hybrid somewhat multi-cloud, I guess. But hybrid is a steady state in the back-office cloud, game over. >> Muhammad: Yeah. >> Amazon, Azure, Google, Alibaba done. So super clouds underneath. Great. This is a digital transformation in the industrial area. >> Muhammad: Yeah. >> This is the big thing. What's your relationship with AWS >> Muhammad: So, as I mentioned, the first challenge, data, like, we have so much data, so much computational power and it's not something that is always needed. You need it like on demand. And this is where like a hyperscale or cloud provider, like AWS, can be the key to achieve, like, the higher, the acceleration that we are providing to our customers using our technology built on top of AWS services. We did a breakout session, this during re:MARS, where we demonstrated a couple of small tools that we have developed out of our offering. One of them was ability to stream data from the vehicle that is collecting data worldwide. So during the day when we did it from Vegas, driving on the strip, as well as from Germany, and while we are while this data is uploaded, it's at the same time real time anonymized to make sure it you're privacy aligned with the, the data privacy >> Of course. Yeah. That's hard to do right there. >> Yeah. And so the faces are blurred. The licenses are blurred. We also, then at the same time can run object detection. So we have real time monitoring of what our feed is doing worldwide. And... >> John: Do you, just curious, do you do that blurring? Is that part of a managed service, you call an API or is that built into the go? >> Muhammad: So from like part of our DSV, we have many different service offerings, so data production, data test strategy orchestration. So part of data production is worldwide data collection. And we can then also offer data management services, which include then anonymization data, quality check. >> John: And that's service you provide. >> Yeah. >> To the customer. Okay. Got it. Okay. >> So of course, like, in collaboration with the customer, so our like, platform is very modular. Microservices based the idea being if the customer already has a good ML model for anonymization, we can plug it into our platform, running on AWS. If they want to use it, we can develop one or we can use one of our existing ones or something off the shelf or like any other supplier can provide one as well. And we all integrate. >> So you are, you're tight with Amazon web services in terms of your cloud, your service. It's a cloud. >> Yeah. >> It's so Capgemini Super Cloud, basically. >> Exactly. >> Okay. So this we call we call it Super Cloud, we made that a thing and re:Invent Charles Fitzgerald would disagree but we will debate him. It's a Super Cloud, but okay. You got your Super Cloud. What's the coolest thing that you think you're doing right now that people should pay attention to. >> I mean, the cool thing that we are currently working on, so from the keynote today, we talked about also synthetic data for validation. >> John: Now That was phenomenal. So that was phenomenal. >> We are working on digital twin creation. So we are capturing data in real world creating a virtual identity of it. And that allows you the freedom to create multiple scenarios out of it. So that's also something where we are using machine learning to determine what are the parameters you need to change between, or so, you have one scenario, such as like, the cut-in scenario and you can change. >> John: So what scenario? >> A cut-in scenario. So someone is cutting in front of you or overtake scenario. And so, I mean, in real world, someone will do it in probably a nicer way, but of course, in, it is possible, at some point. >> Cognition to the cars. >> Yeah. >> It comes up as a vehicle. >> I mean, at some point some might, someone would be very aggressive with it. We might not record it. >> You might be able to predict too. I mean, the predictions, you could say this guy's weaving, he's a potential candidate. >> It it is possible. Yes. But I mean, but to, >> That's a future scenario. >> Ensure that we are testing these scenarios, we can translate a real world scenario into a digital world, change the parameters. So the distance between those two is different and use ML. So machine learning to change these parameters. So this is exciting. And the other thing we are... >> That is pretty cool. I will admit that's very cool. >> Yeah. Yeah. The other thing we like are trying to do is reduce the cost for the customer in the end. So we are collecting petabytes of data. Every time they make updates to the software, they have to re-simulate it or replay this data, so that they can- >> Petabytes? >> Petabytes of data. And, and physically sometimes on a physical hardware in loop device. And then this >> That's called a really heavy edge. You got to move, you don't want to be moving that around the Amazon cloud. >> Yeah. That that's, that's the challenge. And once we have replayed this or re-simulated it. we still have to calculate the KPIs out of it. And what we are trying to do is optimize this test orchestration, so that we are minimizing the REAP simulation. So you don't want the data to be going to the edge, >> Yeah. >> Unnecessarily. And once we get this data back to optimize the way we are doing the calculation, so you're not calculating- >> There's a huge data, integrity management. >> Muhammad: Yeah. >> New kind of thing going on here, it's kind of is it new or is it? >> Muhammad: I mean, it's- >> Sounds new to me. >> The scale is new, so- >> Okay, got it. >> The management of the data, having the whole traceability, that has been in automotive. So also Capgemini involved in aerospace. So in aerospace. >> Yeah. >> Having this kind of high, this validation be very strictly monitored is norm, but now we have to think about how to do it on this large scale. And that's why, like, I think that's the biggest challenge and hopefully what we are trying to, yeah, solve with our DSV offering. >> All right, Muhammad, thanks for coming on theCUBE. I really appreciate it. Great way to close out re:MARS, our last interview our the show. Thanks for coming on. Appreciate your time. >> I mean like just one last comment, like, so I think in automotive, like, so part of the automation the future is quite exciting, and I think that's where like- >> John: Yeah. >> It's, we have to be hopeful that like- >> John: Well, the show is all about hope. I mean, you had, you had space, moon habitat, you had climate change, potential solutions. You have new functionality that we've been waiting for. And, you know, I've watch every episode of Star Trek and SkyNet and kind of SkyNet going on air. >> The robots. >> Robots running cubes, robot cubes host someday. >> Yeah. >> You never know. Yeah. Thanks for coming on. Appreciate it. >> Thank you. Okay. That's theCUBE here. Wrapping up re:MARS. I'm John Furrier You're watching theCUBE, stay with us for the next event. Next time. Thanks for watching. (upbeat music)

Published Date : Jun 24 2022

SUMMARY :

re:Invent is the big one, So it's kind of moving from the old So AI, where you have to what do you do over there? And it goes all the way. So there's like the easy And, and the easy stuff you The impact is not that high. and just in the past recent years, and sexy as the Tesla, So first, is the amount of data they need I see that all the automotive John: What are they I mean, so you are, Like one of the things like, Is that higher availability cuz of the Jedi contract. but the ADAS functions are now available that have to be made. Muhammad: I mean, they of autonomous driving yet on public roads. That's hard to do. the biggest difference, And of course the responsibility. But as we go John: Actually the But I mean, but that's the sort so, talk about AWS, the relationship in the back-office cloud, game over. in the industrial area. This is the big thing. So during the day when hard to do right there. So we have real time monitoring And we can then also offer To the customer. or something off the shelf So you are, you're tight with It's so Capgemini What's the coolest thing that you think so from the keynote today, we talked about So that was phenomenal. And that allows you the freedom of you or overtake scenario. I mean, at some point some might, I mean, the predictions, you could say But I mean, but to, And the other thing we are... I is reduce the cost for And then this You got to move, you don't so that we are minimizing are doing the calculation, There's a huge data, The management of the data, that's the biggest challenge our last interview our the show. John: Well, the show is all about hope. Robots running cubes, Yeah. stay with us for the next event.

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Frank Slootman, Snowflake | Snowflake Summit 2022


 

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

Published Date : Jun 15 2022

SUMMARY :

Good to see you again, Frank. You have AWS, you know, I use that term, AWS. you know, with that data, they don't want to just, you know, run data operations, populate dashboards, One of the analysts asked Mike, you know, do you ever consider going to a subscription model? with people that build on snowflake, um, you know, they have trouble, you know, with their financial model because bad, you know, pay us. you know, so many users from, you know, Salesforce and ServiceNow or whoever you have just purchased the they, they will probably pay for that, you know, on an annual basis, you know, that three year contract. Phase one, better simpler, you know, cloud enterprise data warehouse, You connect to the database, you know, you read or right data, you know, you do data, data manipulations. like, yeah, you know, as an enterprise or an institution, you know, I'm the epicenter of you know, for example, you know, take, you know, uh, an investment bank, you know, in, you know, were you ever, you go on Preem and you said, look, I'll never say never, but it defeats the purpose. just naturally, you know, uh, not an easy thing to conceive of, but, you know, You know, we can virtualize, you know, Dell object storage, you know, I don't know if you ever get to the edge, you know, we'll see, we're not quite quite there yet, So that's why, you know, we're, And you basically get, you just shifted. Oh. They throw it in the container and run it. you know, you said today, well, we're not sure where it's gonna go, but we offering options. you know, on snowflake, without the developer, you know, reading the, the files out of snowflake, And it's actually intolerable the risk that enterprises, you know, take, So there are trade offs of, of going into this snowflake cloud, you get all this great functionality. uh, you know, other, other things in apple cannot, you know, get that these objects. Um, now of course you see that Oh, um, you know, we have a enormous, uh, ISV following and, be built by somebody, you know, I mean, are you really gonna run infrastructure, you know, of software, you know, two men or two women in a dog, and a handful of files can build you know, and I, and I put a big gorilla on the front page and I said, how do you compete with Amazon gorilla? regulatory, you know, clearing houses, investment bankers, uh, retail banks, It's like procurement, do they, do you have an MSA yeah. Data networking is becoming core ecosystem in the world of computing. Again, you know, It's not like I, I sit in this incredible place, you know, and that's, And, you know, the, the, the other issue obviously is that, you know, we were obviously in California, We just did that because we were, uh, required to, you know, you know, I have been watching, you know, we go to a lot of events, you'll see a technology company tell And then C you know, you know, a data strategy, you know, and in our world, that means you have a data cloud and you have all the enablement that thats, you know, and then we, we work, we through training models, you know, you know, pun intended. And thank you for watching.

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Alex Ellis, OpenFaaS | Kubecon + Cloudnativecon Europe 2022


 

(upbeat music) >> Announcer: TheCUBE presents KubeCon and CloudNativeCon Europe, 2022. Brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain, a KubeCon, CloudNativeCon Europe, 2022. I'm your host, Keith Townsend alongside Paul Gillon, Senior Editor, Enterprise Architecture for SiliconANGLE. We are, I think at the half point way point this to be fair we've talked to a lot of folks in open source in general. What's the difference between open source communities and these closed source communities that we attend so so much? >> Well open source is just it's that it's open it's anybody can contribute. There are a set of rules that manage how your contributions are reflected in the code base. What has to be shared, what you can keep to yourself but the it's an entirely different vibe. You know, you go to a conventional conference where there's a lot of proprietary being sold and it's all about cash. It's all about money changing hands. It's all about doing the deal. And open source conferences I think are more, they're more transparent and yeah money changes hands, but it seems like the objective of the interaction is not to consummate a deal to the degree that it is at a more conventional computer conference. >> And I think that can create an uneven side effect. And we're going to talk about that a little bit with, honestly a friend of mine Alex Ellis, founder of OpenFaaS. Alex welcome back to the program. >> Thank you, good to see Keith. >> So how long you've been doing OpenFaaS? >> Well, I first had this idea that serverless and function should be run on your own hardware back in 2016. >> Wow and I remember seeing you at DockerCon EU, was that in 2017? >> Yeah, I think that's when we first met and Simon Foskett took us out to dinner and we got chatting. And I just remember you went back to your hotel room after the presentation. You just had your iPhone out and your headphones you were talking about how you tried to OpenWhisk and really struggled with it and OpenFaaS sort of got you where you needed to be to sort of get some value out of the solution. >> And I think that's the magic of these open source communities in open source conferences that you can try stuff, you can struggle with it, come to a conference either get some advice or go in another direction and try something like a OpenFaaS. But we're going to talk about the business perspective. >> Yeah. >> Give us some, like give us some hero numbers from the project. What types of organizations are using OpenFaaS and what are like the download and stars all those, the ways you guys measure project success. >> So there's a few ways that you hear this talked about at KubeCon specifically. And one of the metrics that you hear the most often is GitHub stars. Now a GitHub star means that somebody with their laptop like yourself has heard of a project or seen it on their phone and clicked a button that's it. There's not really an indication of adoption but of interest. And that might be fleeting and a blog post you might publish you might bump that up by 2000. And so OpenFaaS quite quickly got a lot of stars which encouraged me to go on and do more with it. And it's now just crossed 30,000 across the whole organization of about 40 different open source repositories. >> Wow that is a number. >> Now you are in ecosystem where Knative is also taken off. And can you distinguish your approach to serverless or FaaS to Knatives? >> Yes so, Knative isn't an approach to FaaS. That's simply put and if you listen to Aikas Ville from the Knative project, he was working inside Google and wished that Kubernetes would do a little bit more than what it did. And so he started an initiative with some others to start bringing more abstractions like Auto Scaling, revision management so he can have two versions of code and and shift traffic around. And that's really what they're trying to do is add onto Kubernetes and make it do some of the things that a platform might do. Now OpenFaaS started from a different angle and frankly, two years earlier. >> There was no Kubernetes when you started it. >> It kind of led in the space and and built out that ecosystem. So the idea was, I was working with Lambda and AWS Alexa skills. I wanted to run them on my own hardware and I couldn't. And so OpenFaaS from the beginning started from that developer experience of here's my code, run it for me. Knative is a set of extensions that may be a building block but you're still pretty much working with Kubernetes. We get calls come through. And actually recently I can't tell you who they are but there's a very large telecommunications provider in the US that was using OpenFaaS, like yourself heard of Knative and in the hype they switched. And then they switched back again recently to OpenFaaS and they've come to us for quite a large commercial deal. >> So did they find Knative to be more restrictive? >> No, it's the opposite. It's a lot less opinionated. It's more like building blocks and you are dealing with a lot more detail. It's a much bigger system to manage, but don't get me wrong. I mean the guys are very friendly. They have their sort of use cases that they pursue. Google's now donated the project to CNCF. And so they're running it that way. Now it doesn't mean that there aren't FaaS on top of it. Red Hat have a serverless product VMware have one. But OpenFaaS because it owns the whole stack can get you something that's always been very lean, simple to use to the point that Keith in his hotel room installed it and was product with it in an evening without having to be a Kubernetes expert. >> And that is and if you remember back that was very anti-Kubernetes. >> Yes. >> It was not a platform I thought that was. And for some of the very same reasons, I didn't think it was very user friendly. You know, I tried open with I'm thinking what enterprise is going to try this thing, especially without the handholding and the support needed to do that. And you know, something pretty interesting that happened as I shared this with you on Twitter, I was having a briefing by a big microprocessor company, one of the big two. And they were showing me some of the work they were doing in Cloud-native and the way that they stretch test the system to show me Auto Scaling. Is that they bought up a OpenFaaS what is it? The well text that just does a bunch of, >> The cows maybe. >> Yeah the cows. That does just a bunch of texts. And it just all, and I'm like one I was amazed at is super simple app. And the second one was the reason why they discovered it was because of that simplicity is just a thing that's in your store that you can just download and test. And it was open fast. And it was this big company that you had no idea that was using >> No >> OpenFaaS. >> No. >> How prevalent is that? That you're always running into like these surprises of who's using the solution. >> There are a lot of top tier companies, billion dollar companies that use software that I've worked on. And it's quite common. The main issue you have with open source is you don't have like the commercial software you talked about, the relationships. They don't tell you they're using it until it breaks. And then they may come in incognito with a personal email address asking for things. What they don't want to do often is lend their brands or support you. And so it is a big challenge. However, early on, when I met you, BT, live person the University of Washington, and a bunch of other companies had told us they were using it. We were having discussions with them took them to Kubecon and did talks with them. You can go and look at them in the video player. However, when I left my job in 2019 to work on this full time I went to them and I said, you know, use it in production it's useful for you. We've done a talk, we really understand the business value of how it saves you time. I haven't got a way to fund it and it won't exist unless you help they were like sucks to be you. >> Wow that's brutal. So, okay let me get this right. I remember the story 2019, you leave your job. You say I'm going to do OpenFaaS and support this project 100% of your time. If there's no one contributing to the project from a financial perspective how do you make money? I've always pitched open source because you're the first person that I've met that ran an open source project. And I always pitched them people like you who work on it on their side time. But they're not the Knatives of the world, the SDOs, they have full time developers. Sponsored by Google and Microsoft, etc. If you're not sponsored how do you make money off of open source? >> If this is the million dollar question, really? How do you make money from something that is completely free? Where all of the value has already been captured by a company and they have no incentive to support you build a relationship or send you money in any way. >> And no one has really figured it out. Arguably Red Hat is the only one that's pulled it off. >> Well, people do refer to Red Hat and they say the Red Hat model but I think that was a one off. And we quite, we can kind of agree about that in a business. However, I eventually accepted the fact that companies don't pay for something they can get for free. It took me a very long time to get around that because you know, with open source enthusiast built a huge community around this project, almost 400 people have contributed code to it over the years. And we have had full-time people working on it on and off. And there's some people who really support it in their working hours or at home on the weekends. But no, I had to really think, right, what am I going to offer? And to begin with it would support existing customers weren't interested. They're not really customers because they're consuming it as a project. So I needed to create a product because we understand we buy products. Initially I just couldn't find the right customers. And so many times I thought about giving up, leaving it behind, my family would've supported me with that as well. And they would've known exactly why even you would've done. And so what I started to do was offer my insights as a community leader, as a maintainer to companies like we've got here. So Casting one of my customers, CSIG one of my customers, Rancher R, DigitalOcean, a lot of the vendors you see here. And I was able to get a significant amount of money by lending my expertise and writing content that gave me enough buffer to give the doctors time to realize that maybe they do need support and go a bit further into production. And over the last 12 months, we've been signing six figure deals with existing users and new users alike in enterprise. >> For support >> For support, for licensing of new features that are close source and for consulting. >> So you have proprietary extensions. Also that are sort of enterprise class. Right and then also the consulting business, the support business which is a proven business model that has worked >> Is a proven business model. What it's not a proven business model is if you work hard enough, you deserve to be rewarded. >> Mmh. >> You have to go with the system. Winter comes after autumn. Summer comes after spring and you, it's no point saying why is it like that? That's the way it is. And if you go with it, you can benefit from it. And that's what the realization I had as much as I didn't want to do it. >> So you know this community, well you know there's other project founders out here thinking about making the leap. If you're giving advice to a project founder and they're thinking about making this leap, you know quitting their job and becoming the next Alex. And I think this is the perception that the misperception out there. >> Yes. >> You're, you're well known. There's a difference between being well known and well compensated. >> Yeah. >> What advice would you give those founders >> To be. >> Before they make the leap to say you know what I'm going to do my project full time. I'm going to lean on the generosity of the community. So there are some generous people in the community. You've done some really interesting things for individual like contributions etc but that's not enough. >> So look, I mean really you have to go back to the MBA mindset. What problem are you trying to solve? Who is your target customer? What do they care about? What do they eat and drink? When do they go to sleep? You really need to know who this is for. And then customize a journey for them so that they can come to you. And you need some way initially of funneling those people in qualifying them because not everybody that comes to a student or somebody doing a PhD is not your customer. >> Right, right. >> You need to understand sales. You need to understand a lot about business but you can work it out on your way. You know, I'm testament to that. And once you have people you then need something to sell them that might meet their needs and be prepared to tell them that what you've got isn't right for them. 'cause sometimes that's the one thing that will build integrity. >> That's very hard for community leaders. It's very hard for community leaders to say, no >> Absolutely so how do you help them over that hump? I think of what you've done. >> So you have to set some boundaries because as an open source developer and maintainer you want to help everybody that's there regardless. And I think for me it was taking some of the open source features that companies used not releasing them anymore in the open source edition, putting them into the paid developing new features based on what feedback we'd had, offering support as well but also understanding what is support. What do you need to offer? You may think you need a one hour SLA for a fix probably turns out that you could sell a three day response time or one day response time. And some people would want that and see value in it. But you're not going to know until you talk to your customers. >> I want to ask you, because this has been a particular interest of mine. It seems like managed services have been kind of the lifeline for pure open source companies. Enabling these companies to maintain their open source roots, but still have a revenue stream of delivering as a service. Is that a business model option you've looked at? >> There's three business models perhaps that are prevalent. One is OpenCore, which is roughly what I'm following. >> Right. >> Then there is SaaS, which is what you understand and then there's support on pure open source. So that's more like what Rancher does. Now if you think of a company like Buoyant that produces Linkerd they do a bit of both. So they don't have any close source pieces yet but they can host it for you or you can host it and they'll support you. And so I think if there's a way that you can put your product into a SaaS that makes it easier for them to run then you know go for it. However, we've OpenFaaS, remember what is the core problem we are solving, portability So why lock into my cloud? >> Take that option off the table, go ahead. >> It's been a long journey and I've been a fan since your start. I've seen the bumps and bruises and the scars get made. If you're open source leader and you're thinking about becoming as famous as Alex, hey you can do that, you can put in all the work become famous but if you want to make a living, solve a problem, understand what people are willing to pay for that problem and go out and sell it. Valuable lessons here on theCUBE. From Valencia, Spain I'm Keith Townsend along with Paul Gillon and you're watching theCUBE the leader in high-tech coverage. (Upbeat music)

Published Date : May 19 2022

SUMMARY :

Brought to you by Red Hat, What's the difference between what you can keep to yourself And I think that can create that serverless and function you went back to your hotel room that you can try stuff, the ways you guys measure project success. and a blog post you might publish And can you distinguish your approach and if you listen to Aikas Ville when you started it. and in the hype they switched. and you are dealing And that is and if you remember back and the support needed to do that. that you can just download and test. like these surprises of and it won't exist unless you help you leave your job. to support you build a relationship Arguably Red Hat is the only a lot of the vendors you see here. that are close source and for consulting. So you have proprietary extensions. is if you work hard enough, And if you go with it, that the misperception out there. and well compensated. to say you know what I'm going so that they can come to you. And once you have people community leaders to say, no Absolutely so how do you and maintainer you want to help everybody have been kind of the lifeline perhaps that are prevalent. that you can put your product the table, go ahead. and the scars get made.

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Kawthar Al-Gallaf, E-Jam'ia | Women in Tech: International Women's Day


 

>>mhm. Hello and welcome to the Cubes presentation of Women in text. Global Event Celebrating International Women's Day I'm John for your host of the Cube here in Palo Alto, California and we had a great remote guests coming in from Bahrain in the Middle East. Cather Allegheny, general manager of 9 73 Labs. Uh, thanks for coming in and and being part of the Cube our International Women's Day. You can't get any more international in Bahrain. Thank you for coming on. >>It's my great pleasure and honour to be here. John, thank you so much for this opportunity. >>Well, I'm super excited to chat with you because in our two visits with the Cube in Bahrain covering the summit there the past few years, we notice of surgeon entrepreneurship. Um, it's almost as if the region of AWS has create this revitalization and energy and vitality and and momentum around entrepreneurship. Can you >>share? What's >>the scene down there? What's the What's it like? >>Well, uh, when it comes to my country, we're lucky to have a small population. It's not that large, but we have so many creative people who is eager to try the entrepreneurial journey, and having Amazon as a data centre in Bahrain is a privilege. And they are pushing, uh, to have more entrepreneurial ideas and innovation and solutions within the ecosystem of rain. So definitely with their support, I can I can see that so many youths, they are eager to come in and contribute. >>I noticed that you're also the general manager of, uh, 9 73 labs, but also the founder of a company. So you've got two things going on here. You've got the entrepreneurial thing happening. Um, this seems to be normal. People got entrepreneurial activity and the job doing both. They're both entrepreneurial. Is that normal? >>Yes, Absolutely. Well, I started my entrepreneurial journey back in, uh, four years and I've been appointed as a general manager of 97 3 labs, which is I'm leading on digital innovation. So that compliments my passion of being an entrepreneur. And while we can acquire talented people and support them to create their own solutions the best way they can So basically, uh, following the main pillars of the lab that I'm working on, which is conducting appropriate research and data analytics, innovation and sustainability. So, uh, for my two founded cos it's not only one I've worked in Fintech and also in property as well. >>What inspired you to be an entrepreneur and technology? >>Well, I would say that my inspiration was to think outside the box, and I see problems and gaps as an opportunity. So that helps me to figure out and come up with solutions that can be beneficial for everyone. So analysing detail as well as something that I would really love. And also, um, enhancing my skills and being more creative is my inspiration. >>I know this is a lot of entrepreneur activity in Bahrain. A lot of investors are now coming into the market. Um, what are some of the things that are going on there? Can you share what the entrepreneurial scene is like there what people are working on has cloud computing accelerated that? What's what are some of the things happening there on the ground? >>Um, I would see that there is multiple competitions or hackathons run by multiple financial institutions. Uh, and also, uh, there are so many NGO s as I am a board member and technology and business society and also a member of women empowerment in the field of cheque, we are trying to motivate and accelerate the desire to be within this ecosystem of entrepreneurial journey. So, basically, uh, we have the Supreme Council of Women who is pushing as well women and ladies to be in this, uh, sector, uh, from early age from, uh, university or even high school graduates that they should start on working on their ideas and come up with solutions. So you can see that everyone is up to, uh, being part of the ecosystem by putting in their ideas. >>And the government wants to be digitally completely transformed, and >>by certain >>they're pushing it hard to >>Absolutely. Yes, we have the governmental sector trying to migrate from legacy infrastructure to the cloud. I would say, uh and it's it's more efficient for government and also to the private sector as well. >>You know, one of the things that jumped out at me when I was in my rain visiting was there was a lunch. Uh, I'm sorry. Breakfast for women in tech. And I went there because I always go to those breakfast cause I really want to see and meet people. I had to get kicked out because it wasn't a table space. So I was for all the people that were there, Um, because I was the guy that was spot for women, it was sold out, was lying and lying to get in. So there's a huge interest of women in tech. I saw that firsthand. There are more and more people want to come in. So motivating women to consider Korean tech is really the focus. What steps do you see to make that happen? How do we take that to the next level? What's your view on motivating women to get into tech? How would you talk about that? >>Well, absolutely. I think it's really crucial to have a woman contribution within the field of cheque. But I believe there is some challenges, given our cultural norms of how man perceived woman working in the field of cheque, sometimes society burden woman from, you know, pursuing her passion to be in because it's a demanding field. I would say that it's, uh, equal to the medical field. You have to keep on updating and to be aware about what's going on. Um, so basically, that might create a bit of a burden for specifically married women of looking after her husband or their families. So I think, uh, this is one of the challenges. But the steps to overcome those challenge challenges is why, uh, you know, trying to shift and change the way, uh, society think about where women should position herself and what kind of job should she should be. And, uh, So I think the other thing is by having educational curriculum that we taught in schools, teaching both genders about the importance of, uh, how we are equal and how we can complement each other in that field because the future is in technology. So the young generation should understand this very well. >>How is the women, um, entrepreneurship going? Are they being finance for their ventures out there? What's the what's the What's the momentum and progress on women starting ventures? >>Yes, absolutely. We're lucky to have our first lady, the wife of the king who is heading the Supreme Council of Women who is pushing women to create their own businesses or to come to become an entrepreneur. Also, we have financings becoming through the government with an entity called Temkin will provide different plants and support all through, not financials only, but it covers other areas of businesses as well. So financing is not a problem again for an entrepreneur. Uh, woman. As an entrepreneur, you can always seek multiple options for financing, not necessarily inside. It can be international as well. >>So a lot of good capital there also, this fellowship opportunities. I noticed you were a Halsey in, uh, fellow. The fellowship with the Halsey in organisation. Talk about that. That experience? >>Well, I really loved the experience. We started in fact, last year, and we flew to Washington in July, and we've met with Amazon people who were really supportive. We got solution architects supporting us of how to build the solution that we want to deliver. And I got my CTO to get trained by the Amazon as well. So we found so much value and the courses and the mentorship they provided, uh, and I'm really glad to be part of that family and their CEO. She said, Now, uh, for a lifetime, you are part of our family, and, you know, it's all the support that we needed to get. >>It's a great community. What advice would you give to people who are out there who want to learn and get into cloud computing and take that step towards creating value on whether it's entrepreneurial or within a company. What's the secret formula that you would say our secrets to success? >>Absolutely. I think a cloud is a a massive, and it's a brilliant opportunity for any technology to be built on myself. I believe in the cloud. Most or all of my solutions is built on cloud. And now even me leading the digital lab on building infrastructure on cloud and basically it will give you more room. Uh, identify more gaps. You do assessment. You can utilise the tools that is within cloud, which is artificial intelligence machine learning. Uh, you call it so you can seize the opportunity to the maximum, and you can skill faster. So basically, you're not limited to your, uh, country. You can go across countries as well utilising cloud >>Catherine to talk about what's next for you. What's the next step? >>Well, uh, the next step in my new role or a new job leading on a digital innovation in 973 Labs is to finalise my strategy and also to acquire talented young people And, uh, you know, go through a programme, which is I designed where they get the mentorship, the support till they get a final product that will be invested in. And they can guarantee themselves a carrier, uh, within the digital love that I'm trying to lead on. Uh, and I think the projects that will be covering not specifically only infant IQ, it could be in any other industry. So, uh, we're trying to follow the recent trends, Uh, thanks to Amazon and Google and the other companies that we can extract data and create our own reporting. So to, uh, come up where we should be investing our time. >>That's great. I wanna ask you about the demographics of the folks in Bahrain. I noticed that they're very a lot of young entrepreneurs coming up and learn a lot of them. Um, is that true? >>Yes, Uh, our population, the majority of our youth, uh and I would say, um uh, the average age is in thirties until 35 or 36. So, relatively, we have so many young people or youth who was eager to learn. But again, we need the expertise. We need older people to also mentor and coach the young generation of how they should calculate the risk and come up with a proper business models and brilliant ideas. >>Well, I'm very impressed with the folks down there, I said before the pandemic. Unfortunately, the pandemic it, But we really wanted to have a cube location there, a lot of vitality out of action, a lot of good stuff going on. Certainly with the NWS region in there, it's really create a lot of value. And so we're looking forward to hearing more. And, uh, thanks for coming on and sharing your storey with us and for the folks out there watching. What advice would you give to women who are watching around the world around entrepreneurship? What's going on from your experience? What should we be doing and talking about? What's the Storey? I'll see this theme is bias, uh, inherent bias and in the culture, um, what would you share your thoughts on to the world? >>Well, I think the only advice I can give to all of the women out there just try something new to try to solve a problem. There are so many gaps we have around. Just look around. You just take one step forward and try it. At least once in your life, you can come up with a brilliant, uh, solution that serves all humankind, not only the people of your country. So even if the road is bumpy, just be have the courage, be resilient and go for it. >>And we're all connected on the Internet. So of course, we can communicate with each other and have a good time and and grow the community. Thanks so much for coming on the Cube and celebrating International Women's Day with us as part of our special presentation. Thanks for coming on. I really appreciate it. >>Thank you. It's my pleasure. Thank you so much. >>Okay, this is the cubes presentation of women in text. Global event Celebrating International Women's Day. I'm John for a host of the Cube. Thanks for watching. Yeah,

Published Date : Mar 9 2022

SUMMARY :

thanks for coming in and and being part of the Cube our International Women's Day. It's my great pleasure and honour to be here. Well, I'm super excited to chat with you because in our two visits with the Cube in Bahrain It's not that large, but we have so many Um, this seems to be normal. So basically, uh, following the main pillars of the lab that So that helps me to figure out and come up with solutions that can be beneficial for everyone. A lot of investors are now coming into the market. the desire to be within this ecosystem of entrepreneurial journey. for government and also to the private sector as well. I had to get kicked out because it wasn't a table about the importance of, uh, how we are equal and how we can complement each We're lucky to have our first lady, the wife of the king So a lot of good capital there also, this fellowship opportunities. how to build the solution that we want to deliver. What advice would you give to people who are out there who want to learn and get I believe in the cloud. What's the next step? Google and the other companies that we can extract data and I wanna ask you about the demographics of the folks in Bahrain. Yes, Uh, our population, the majority of our youth, um, what would you share your thoughts on to the world? Well, I think the only advice I can give to all of the women out So of course, we can communicate with each other and have a good time and and grow the community. Thank you so much. I'm John for a host of the Cube.

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