>>Well, hello everybody. John Walls here and continuing our coverage here at AWS Reinvent 22 on the queue. We continue our segments here in the Global Startup program, which of course is sponsored by AWS Startup Showcase, and with us to talk about any scale as the co-founder and CEO of the company, Robert and n, you are Robert. Good to see you. Thanks for joining us. >>Yeah, great. And thank you. >>You bet. Yeah. Glad to have you aboard here. So let's talk about Annie Scale, first off, for those at home and might not be familiar with what you do. Yeah. Because you've only been around for a short period of time, you're telling me >>Company's about >>Three years now. Three >>Years old, >>Yeah. Yeah. So tell us all about it. Yeah, >>Absolutely. So one of the biggest things happening in computing right now is the proliferation of ai. AI is just spreading throughout every industry has the potential to transform every industry. But the thing about doing AI is that it's incredibly computationally intensive. So if you wanna do do ai, you're not, you're probably not just doing it on your laptop, you're doing it across many machines, many gpu, many compute resources, and that's incredibly hard to do. It requires a lot of software engineering expertise, a lot of infrastructure expertise, a lot of cloud computing expertise to build the software infrastructure and distributed systems to really scale AI across all of the, across the cloud. And to do it in a way where you're really getting value out of ai. And so that is the, the problem statement that AI has tremendous potential. It's incredibly hard to do because of the, the scale required. >>And what we are building at any scale is really trying to make that easy. So trying to get to the point where, as a developer, if you know how to program on your laptop, then if you know how to program saying Python on your laptop, then that's enough, right? Then you can do ai, you can get value out of it, you can scale it, you can build the kinds of, you know, incredibly powerful applica AI applications that companies like Google and, and Facebook and others can build. But you don't have to learn about all of the distributed systems and infrastructure. It just, you know, we'll handle that for you. So that's, if we're successful, you know, that's what we're trying to achieve here. >>Yeah. What, what makes AI so hard to work with? I mean, you talk about the complexity. Yeah. A lot of moving parts. I mean, literally moving parts, but, but what is it in, in your mind that, that gets people's eyes spinning a little bit when they, they look at great potential. Yeah. But also they look at the downside of maybe having to work your way through Pike mere of sorts. >>So, so the potential is definitely there, but it's important to remember that a lot of AI initiatives fail. Like a lot of initiative AI initiatives, something like 80 or 90% don't make it out of, you know, the research or prototyping phase and inter production. Hmm. So, some of the things that are hard about AI and the reasons that AI initiatives can fail, one is the scale required, you know, moving. It's one thing to develop something on your laptop, it's another thing to run it across thousands of machines. So that's scale, right? Another is the transition from development and prototyping to production. Those are very different, have very different requirements. Absolutely. A lot of times it's different teams within a company. They have different tech stacks, different software they're using. You know, we hear companies say that when they move from develop, you know, once they prototype and develop a model, it could take six to 12 weeks to get that model in production. >>And that often involves rewriting a lot of code and handing it off to another team. So the transition from development to production is, is a big challenge. So the scale, the development to production handoff. And then lastly, a big challenge is around flexibility. So AI's a fast moving field, you see new developments, new algorithms, new models coming out all the time. And a lot of teams we work with, you know, they've, they've built infrastructure. They're using products out there to do ai, but they've found that it's sort of locking them into rigid workflows or specific tools, and they don't have the flexibility to adopt new algorithms or new strategies or approaches as they're being developed as they come out. And so they, but their developers want the flexibility to use the latest tools, the latest strategies. And so those are some of the main problems we see. It's really like, how do you scale scalability? How do you move easily from development and production and back? And how do you remain flexible? How do you adapt and, and use the best tools that are coming out? And so those are, yeah, just those are and often reasons that people start to use Ray, which is our open source project in any scale, which is our, our product. So tell >>Me about Ray, right? Yeah. Opensource project. I think you said you worked on it >>At Berkeley. That's right. Yeah. So before this company, I did a PhD in machine learning at Berkeley. And one of the challenges that we were running into ourselves, we were trying to do machine learning. We actually weren't infrastructure or distributed systems people, but we found ourselves in order to do machine learning, we found ourselves building all sorts of tools, ad hoc tools and systems to scale the machine learning, to be able to run it in a reasonable amount of time and to be able to leverage the compute that we needed. And it wasn't just us people all across, you know, machine learning researchers, machine learning practitioners were building their own tooling and infrastructure. And that was one of the things that we felt was really holding back progress. And so that's how we slowly and kind of gradually got into saying, Hey, we could build better tools here. >>We could build, we could try to make this easier to do so that all of these people don't have to build their own infrastructure. They can focus on the actual machine learning applications that they're trying to build. And so we started, Ray started this open source project for basically scaling Python applications and scaling machine learning applications. And, well, initially we were running around Berkeley trying to get all of our friends to try it out and, and adopt it and, you know, and give us feedback. And if it didn't work, we would debug it right away. And that slow, you know, that gradually turned into more companies starting to adopt it, bigger teams starting to adopt it, external contributors starting to, to contribute back to the open source project and make it better. And, you know, before you know it, we were hosting meetups, giving to talks, running tutorials, and the project was just taking off. And so that's a big part of what we continue to develop today at any scale, is like really fostering this open source community, growing the open source user base, making sure Ray is just the best way to scale Python applications and, and machine learning applications. >>So, so this was a graduate school project That's right. You say on, on your way to getting your doctorate and now you commercializing now, right? Yeah. I mean, so you're being able to offer it, first off, what a journey that was, right? I mean, who would've thought Absolutely. I guess you probably did think that at some point, but >>No, you know, when we started, when we were working on Ray, we actually didn't anticipate becoming a company, or we at least just weren't looking that far ahead. We were really excited about solving this problem of making distributed computing easy, you know, getting to the point where developers just don't have to learn about infrastructure and distributed systems, but get all the benefits. And of course, it wasn't until, you know, later on as we were graduating from Berkeley and we wanted to continue really taking this project further and, and really solving this problem that it, we realized it made sense to start a company. >>So help me out, like, like what, what, and I might have missed this, so I apologize if I did, but in terms of, of Ray's that building block and essential for your, your ML or AI work down the road, you know, what, what is it doing for me or what, what will it allow me to do in either one of those realms that I, I can't do now? >>Yeah. And so, so like why use Ray versus not using Ray? Yeah, I think the, the answer is that you, you know, if you're doing ai, you need to scale. It's becoming, if you don't find that to be the case today, you probably will tomorrow, you know, or the day after that. And so it's really increasingly, it's a requirement. It's not an option. And so if you're scaling, if you're trying to build these scalable applications you are building, you're either going to use Ray or, or something like Ray or you're going to build the infrastructure yourself and building the infrastructure yourself, that's a long journey. >>So why take that on, right? >>And many of the companies we work with don't want to be in the business of building and managing infrastructure. No. Because, you know, if they, they want their their best engineers to build their product, right? To, to get their product to market faster. >>I want, I want you to do that for me. >>Right? Exactly. And so, you know, we can really accelerate what these teams can do and, you know, and if we can make the infrastructure something they just don't have to think about, that's, that's why you would choose to use Ray. >>Okay. You know, between a and I and ml are, are they different animals in terms of what you're trying to get done or what Ray can do? >>Yeah, and actually I should say like, it's not just, you know, teams that are new teams that are starting out, that are using Ray, many companies that have built, already built their own infrastructure will then switch to using Ray. And to give you a few examples, like Uber runs all their deep learning on Ray, okay. And, you know, open ai, which is really at the frontier of training large models and, and you know, pushing the boundaries of, of ai, they train their largest models using Ray. You know, companies like Shopify rebuilt their entire machine learning platform using Ray, >>But they started somewhere else. >>They had, this is all, you know, like, it's not like the v1, you know, of their, of their machine learning infrastructure. This is like, they did it a different way before, this is like the second version or the third iteration of of, of how they're doing it. And they realize often it's because, you know, I mean in the case of, of Uber, just to give you one example, they built a system called hova for scaling deep learning on a bunch of GPUs. Right Now, as you scale deep learning on GPUs for them, the bottleneck shifted away from, you know, as you scale GPU's training, the bottleneck shifted away from training and to the data ingest and pre-processing. And they wanted to scale data ingest and pre-processing on CPUs. So now Hova, it's a deep learning framework. It doesn't do the data ingest and pre-processing on CPUs, but you can, if you run Hova on top of Ray, you can scale training on GPUs. >>And then Ray has another library called Ray Data you can, that lets you scale the ingest and pre-processing on CPUs. You can pipeline them together. And that allowed them to train larger models on more data before, just to take one example, ETA prediction, if you get in an Uber, it tells you what time you're supposed to arrive. Sure. That uses a deep learning model called d eta. And before they were able to train on about two weeks worth of data. Now, you know, using Ray and for scaling the data, ingestive pre-processing and training, they can train on much more data. You know, you can get more accurate ETA predictions. So that's just one example of the kind of benefit they were able to get. Right. Also, because it's running on top of, of Ray and Ray has this ecosystem of libraries, you know, they can also use Ray's hyper parameter tuning library to do hyper parameter tuning for their deep learning models. >>They can also use it for inference and you know, because these are all built on top of Ray, they inherit the like, elasticity and fault tolerance of running on top of Ray. So really it simplifies things on the infrastructure side cuz there's just, if you have Ray as common infrastructure for your machine learning workloads, there's just one system to, to kind of manage and operate. And if you are, it simplifies things for the end users like the developers because from their perspective, they're just writing a Python application. They don't have to learn how to use three different distributed systems and stitch them together and all of this. >>So aws, before I let you go, how do they come into play here for you? I mean, are you part of the showcase, a startup showcase? So obviously a major partner and major figure in the offering that you're presenting >>People? Yeah, well you can run. So any scale is a managed ray service. Like any scale is just the best way to run Ray and deploy Ray. And we run on top of aws. So many of our customers are, you know, using Ray through any scale on aws. And so we work very closely together and, and you know, we have, we have joint customers and basically, and you know, a lot of the value that any scale is adding on top of Ray is around the production story. So basically, you know, things like high availability, things like failure handling, retry alerting, persistence, reproducibility, these are a lot of the value, the values of, you know, the value that our platform adds on top of the open source project. A lot of stuff as well around collaboration, you know, imagine you are, you, something goes wrong with your application, your production job, you want to debug it, you can just share the URL with your, your coworker. They can click a button, reproduce the exact same thing, look at the same logs, you know, and, and, and figure out what's going on. And also a lot around, one thing that's, that's important for a lot of our customers is efficiency around cost. And so we >>Support every customer. >>Exactly. A lot of people are spending a lot of money on, on aws. Yeah. Right? And so any scale supports running out of the box on cheaper like spot instances, these preempt instances, which, you know, just reduce costs by quite a bit. And so things like that. >>Well, the company is any scale and you're on the show floor, right? So if you're having a chance to watch this during reinvent, go down and check 'em out. Robert Ashihara joining us here, the co-founder and ceo and Robert, thanks for being with us. Yeah. Here on the cube. Really enjoyed it. Me too. Thanks so much. Boy, three years graduate program and boom, here you are, you know, with off to the enterprise you go. Very nicely done. All right, we're gonna continue our coverage here on the Cube with more here from Las Vegas. We're the Venetian, we're AWS Reinvent 22 and you're watching the Cube, the leader in high tech coverage.

(upbeat music) >> Welcome back friends. It's theCUBE LIVE in Las Vegas at the Venetian Expo, covering the first full day of AWS re:Invent 2022. I'm Lisa Martin, and I have the privilege of working much of this week with Dave Vellante. >> Hey. Yeah, it's good to be with you Lisa. >> It's always good to be with you. Dave, this show is, I can't say enough about the energy. It just keeps multiplying as I've been out on the show floor for a few minutes here and there. We've been having great conversations about cloud migration, digital transformation, business transformation. You name it, we're talking about it. >> Yeah, and I got to say the soccer Christians are really happy. (Lisa laughing) >> Right? Because the USA made it through. So that's a lot of additional excitement. >> That's true. >> People were crowded around the TVs at lunchtime. >> They were, they were. >> So yeah, but back to data. >> Back to data. We have a couple of guests here. We're going to be talking a lot with customer challenges, how they're helping to overcome them. Please welcome Kevin Zawodzinski, VP of Sales Engineering at COMMVAULT. >> Thank you. >> And Paul Meighan, Director of Product Management at AWS. Guys, it's great to have you on the program. Thank you for joining us. >> Thanks for having us. >> Thanks for having us. >> Isn't it great to be back in person? >> Paul: It really is. >> Kevin: Hell, yeah. >> You cannot replicate this on virtual, you just can't. It's nice to see how excited people are to be back. There's been a ton of buzz on our program today about Adam's keynote this morning. Amazing. A lot of synergies with the direction, Paul, that AWS is going in and where we're seeing its ecosystem as well. Paul, first question for you. Talk about, you know, in the customer environment, we know AWS is very customer obsessed. Some of the main challenges customers are facing today is they really continue this business transformation, this digital transformation, and they move to cloud native apps. What are some of those challenges and how do you help them eradicate those? >> Well, I can tell you that the biggest contribution that we make is really by focusing on the fundamentals when it comes to running storage at scale, right? So Amazon S3 is unique, distributed architecture, you know, it really does deliver on those fundamentals of durability, availability, performance, security and it does it at virtually unlimited scale, right? I mean, you guys have talked to a lot of storage folks in the industry and anyone who's run an estate at scale knows that doing that and executing on those fundamentals day after day is just super hard, right? And so we come to work every day, we focus on the fundamentals, and that focus allows customers to spend their time thinking about innovation instead of on how to keep their data durably stored. >> Well, and you guys both came out of the storage world. >> Right. >> Yeah, yeah. >> It was a box world, (Kevin laughs) and it ain't no more. >> Kevin: That's right, absolutely. >> It's a service and a service of scale. >> Kevin: Yeah. So architecture matters, right? >> Yeah. >> Yeah. >> Paul, talk a little bit about, speaking of innovation, talk about the evolution of S3. It's been around for a while now. Everyone knows it, loves it, but how has AWS architected it to really help meet customers where they are? >> Paul: Right. >> Because we know, again, there's that customer first focus. You write the press release down the road, you then follow that. How is it evolving? >> Well, I can tell you that architecture matters a lot and the architecture of Amazon S3 is pretty unique, right? I think, you know, the most important thing to understand about the architecture of S3 is that it is truly a regional service. So we're laid out across a minimum of 3 Availability Zones, or AZs, which are physically separated and isolated and have a distance of miles between them to protect against local events like floods and fires and power interruption, stuff like that. And so when you give us an object, we distribute that data across that minimum of 3 Availability Zones and then within multiple devices within each AZ, right? And so what that means is that when you store data with us, your data is on storage that's able to tolerate the failure of multiple devices with no impact to the integrity of your data, which is super powerful. And then again, super hard to do when you're trying to roll your own. So that's sort of a, like an overview of the architecture. In terms of how we think about our roadmap, you know, 90% of our roadmap comes directly from what customers tell us matters, and that's a tenant of how we think about customer obsession at AWS and it really is how we drive a roadmap. >> Right, so speaking of customers Kevin, what are customers asking you guys- >> Yeah. >> for, how does it relate to what you're doing with S3? >> Yeah, it's a wonderful question and one that is actually really appropriate for us being at re:Invent, right? So we got, last three years we've had customers here with us on stage talking about it. First of all, 3 years ago we did a virtual session, unfortunately, but glad to be back as you mentioned, with Coca-Cola and theirs was about scale and scope and really about how can we protect hundreds of thousands of objects, petabyte to data, in a simple and secure way, right. Then last year we actually met with a ACT, Inc. as well and co-presented with them and really talked about how we could protect modern workloads and their modern workloads around whether it was Aurora or as well as EKS and how they continue to evolve as well. And, last but not least it's going to be, this year we're talking with Illinois State University as well about how they're going to continue to grow, adapt and really leverage AWS and ourselves to further their support of their teachers and their staff. So that is really helping us quite a bit to continue to move forward. And the things we're doing, again, with our customer base it's really around, focused on what's important to them, right? Customer obsession, how are we working with that? How are we making sure that we're listening to them? Again, working with AWS to understand how can we evolve together and really ultimately their journeys. As you heard, even with those 3 examples they're all very different, right? And that's the point, is that everybody's at a different point in the journey. They're at a different place from a modernization perspective. So we're helping them evolve, as they're helping us evolve as well, and transform with AWS. >> So very mature COMMVAULT stack, the S3 bucket and all the other capabilities. Paul, you just talked about coming together- >> Right. >> Dave: for your customers. >> Yeah, yeah, absolutely. And just, you know, we were talking the other day, Paul and I were talking the other day, it's been, you know, we've worked with AWS, with integration since 2009, right? So a long time, right? I mean, for some that may not seem like a long time ago, but it is, right? It's, you know, over a decade of time and we've really advanced that integration considerably as well. >> What are some of the things that, I don't know if you had a chance to see the keynote this morning? >> Yeah, a little bit. >> What are some of the things that there was, and in fact this is funny, funny data point for you on data. One of my previous guests told me that Adam Selipsky spent exactly 52 minutes talking about data this morning. 52 minutes. >> Okay. >> That there's a data point. But talk about some of the things that he talked about, the direction AWS is going in, obviously new era in the last year. Talk about what you heard and how you think that will evolve the COMMVAULT-AWS relationship. >> Yeah, I think part of that is about flexibility, as Paul mentioned too, architecture matters, right? So as we evolve and some of the things that we pride ourselves on is that we developed our systems and our software and everything else to not worry about what do I have to build to today but how do I continue to evolve with my customer base? And that's what AWS does, right? And continues to do. So that's really how we would see the data environment. It's really about that integration. As they grow, as they add more features we're going to add more features as well. And we're right there with them, right? So there's a lot of things that we also talk about, Paul and I talk about, around, you know, how do we, like Graviton3 was brought up today around some of the innovations around that. We're supporting that with Auto Scale right now, right? So we're right there releasing, right when AWS releasing, co-developing things when necessary as well. >> So let's talk about security a little bit. First of all, what is COMMVAULT, right? You're not a security company but you're an adjacency to security. It's sort of, we're rethinking security. >> Kevin: Yep. >> including data protection, not a bolt-on anymore. You guys both have a background in that world and I'm sure that resonates. >> Yeah. >> So what is the security play here? What role does COMMVAULT play? I think we know pretty well what role AWS plays, but love to hear, Paul, your thoughts as well on security. >> Yeah, I'll start I guess. >> Go on Paul. >> Okay. Yeah, so on the security side of things, there's a quite a few things. So again, on the development side of things, we do things like file anomaly detection, so seeing patterns in data. We talked a lot about analytics as well in the keynote this morning. We look at what is happening in the customer environment, if there's something odd or out of place that's happening, we can detect that and we'll notify people. And we've seen that, we have case studies about that. Other things we do are simple, simple but elegant. Is with our security dashboard. So we'll use our security dashboard to show best practices. Are they using Multi-Factor Authentication? Are you viewing password complexity? You know, things like that. And allows people to understand from a security landscape perspective, how do we layer in protection with their other systems around security. We don't profess to be the security company, or a security company, but we help, you know, obviously add in those additional layers. >> And obviously you're securing, you know, the S3 piece of it. >> Mmmhmm. >> You know, from your standpoint because building it in. >> That's right. And we can tell you that for us, security is job zero. And anyone at AWS will tell you that, and not only that but it will always be our top priority. Right from the infrastructure on down. We're very focused on our shared responsibility model where we handle security from the hypervisor, or host operating system level, down to the physical security of the facilities in which our services run and then it's our customer's responsibility to build secure applications, right. >> Yeah. And you talk about Graviton earlier, Nitro comes into play and how you're, sort of, fencing off, you know, the various components of the system from the operating system, the VMs, and then that is designed in and that's a new evolution that it comes as part of the package. >> Yeah, absolutely. >> Absolutely. >> Paul, talk a little bit about, you know, security, talking about that we had so many conversations this year alone about the threat landscape and how it's dramatically changing, it's top of mind for everybody. Huge rise in ransomware attacks. Ransomware is now, when are we going to get hit? How often? What's the damage going to be? Rather than, are we going to get hit? It's, unfortunately it's progressed in that direction. How does ensuring data security impact how you're planning the roadmap at AWS and how are partners involved in shaping that? >> Right, so like I said, you know, 90% of our roadmap comes from what customers tell us matters, right? And clearly this is an issue that matters very much to customers right now, right? And so, you know, we're certainly hearing that from customers, and COMMVAULT, and partners like COMMVAULT have a big role to play in helping customers to secure and protect their applications, right? And that's why it's so critical that we come together here at re:Invent and we have a bunch of time here at the show with the COMMVAULT technical folks to talk through what they're hearing from customers and what we're hearing. And we have a number of regular touch points throughout the year as well, right? And so what COMMVAULT gets from the relationship is, sort of, early access and feedback into our features and roadmap. And what we get out of it really is that feedback from that large number of customers who interface with Amazon S3 through COMMVAULT. Who are using S3 as a backup target behind COMMVAULT, right? And so, you know, that partnership really allows us to get close to those customers and understand what really matters to them. >> Are you doing joint engineering, or is it more just, hey here you go COMMVAULT, here's the tools available, go, go build. Can you address that? >> Yeah, no, absolutely. There's definitely joint engineering like even things around, you know, data migration and movement of data, we integrate really well and we talk a lot about, hey, what are you, like as Paul mentioned, what are you seeing out there? We actually, I just left a conversation about an hour ago where we're talking about, you know, where are we seeing placement of data and how does that matter to, do you put it on, you know, instant access, or do you put it on Glacier, you know, what should be the best practices? And we tell them, again, some of the telemetry data that we have around what do we see customers doing, what's the patterns of data? And then we feed that back in and we use that to create joint solutions as well. >> You know, I wonder if we could talk about cloud, you know, optimization of cloud costs for a minute. That's obviously a big discussion point in the hallways with customers. And on your earnings call you guys talked about specifically some customers and they specifically mentioned, for example, pushing storage to lower cost tiers. So you brought up Glacier just then. What are you seeing in the field in that regard? How are customers taking advantage of that? And where does COMMVAULT play in, sort of, helping make that decision? >> You want to take part one or you want me to take it? >> I can take part one. I can tell you that, you know, we're very focused on helping customers optimize costs, however necessary, right? And, you know, we introduced intelligent hearing here at the show in 2019 and since launch it's helped customers to reduce costs by over $750 million, right? So that's a real commitment to optimizing costs on behalf of customers. We also launched, you know, later in 2020, Glacier Deep Archive, which is the lowest cost storage in the cloud. So it's an important piece of the puzzle, is to provide those storage options that can allow customers to match the workloads that are, that need to be on folder storage to the appropriate store. >> Yeah, and so, you know, S3 is not this, you know, backup and recovery system, not an archiving system and, you know, in terms of, but you have that intelligence in your platform. 'Cause when I heard that from the earnings call I was like, okay, how do customers then go about deciding what they can, you know, when it's all good times, like yeah, who cares? You know, just go, go, go. But when you got to tighten the belt, how do you guys? >> Yeah, and that goes back to understanding the data pattern. So some of that is we have intelligence and artificial intelligence and everything else and machine learning within our, so we can detect those patterns, right? We understand the patterns, we learn from that and we help customers right size, right. So ultimately we do see a blend, right? As Paul mentioned, we see, you know, hey I'm not going to put everything on Glacier necessarily upfront. Maybe they are, it all depends on their workloads and patterns. So we use the data that we collect from the different customers that we have to share those best practices out and create, you know, the right templates, so to speak, in ways for people to apply it. >> Guys, great joint, you talked about the joint engineering, joint go to market, obviously a very strong synergistic partnership between the two. A lot of excitement. This is only day one, I can only imagine what's going to be coming the next couple of days. But I have one final question for you, but I have same question for both of you. You had the chance to create your own bumper sticker, so you get a shiny new car and for some reason you want to put a bumper sticker on it. About COMMVAULT, what would it say? >> Yeah, so for me I would say comprehensive, yet simple, right? So ultimately about giving you all the bells and whistles but if you want to be very simple we can help you in every shape and form. >> Paul, what's your bumper sticker say about AWS? >> I would say that AWS starts with the customer and works backwards from there. >> Great one. >> Excellent. Guys- >> Kevin: Well done. >> it's been a pleasure to have you on the program. Thank you- >> Kevin: Thank you. >> for sharing what's going on, the updates on the AWS-COMMVAULT partnership and what's in it for customers. We appreciate it. >> Dave: Thanks you guys. >> Thanks a lot. >> Thank you. >> All right. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

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

(upbeat synth intro music) >> Hey everyone and welcome to Detroit, Michigan. theCUBE is live at KubeCon CloudNativeCon, North America 2022. Lisa Martin here with John Furrier. John, this event, the keynote that we got out of a little while ago was, standing room only. The Solutions hall is packed. There's so much buzz. The community is continuing to mature. They're continuing to contribute. One of the big topics is Cloud Native at Scale. >> Yeah, I mean, this is a revolution happening. The developers are coming on board. They will be running companies. Developers, structurally, will be transforming companies with just, they got to get powered somewhere. And, I think, the Cloud Native at Scale speaks to getting everything under the covers, scaling up to support developers. In this next segment, we have two Kube alumnis. We're going to talk about Cloud Native at Scale. Some of the things that need to be there in a unified architecture, should be great. >> All right, it's going to be fantastic. Let's go under the covers here, as John mentioned, two alumni with us, Madhura Maskasky joins us, co-founder of Platform9. Sirish Raghuram, also co-founder of Platform9 joins us. Welcome back to theCUBE. Great to have you guys here at KubeCon on the floor in Detroit. >> Thank you for having us. >> Thank you for having us. >> Excited to be here >> So, talk to us. You guys have some news, Madhura, give us the sneak peak. What's going on? >> Definitely, we are very excited. So, we have John, not too long ago we spoke about our very new open source project called Arlon. And, we were talking about the launch of Arlon in terms of its first release and etcetera. And, just fresh hot of the press, we, Platform9 had its 5.6 release which is its most recent release of our product. And there's a number of key interesting announcements that we'd like to share as part of that. I think, the prominent one is, Platform9 added support for EKS Kubernetes cluster management. And, so, this is part of our vision of being able to add value, no matter where you run your Kubernetes clusters, because, Kubernetes or cluster management, is increasingly becoming commodity. And, so, I think the companies that succeed are going to add value on top, and are going to add value in a way that helps end users, developers, DevOps solve problems that they encounter as they start running these environments, with a lot of scale and a lot of diversity. So, towards that, key features in the 5.6 six release. First, is the very first package release of the product online, which is the open source project that we've kicked off to do cluster and application, entire cluster management at scale. And, then there's few other very interesting capabilities coming out of that. >> I want to just highlight something and then get your thoughts on this next, this release 5.6. First of all, 5.6, it's been around for a while, five reps, but, now, more than ever, you mentioned the application in Ops. You're seeing WebAssembly trends, you're seeing developers getting more and more advanced capability. It's going to accelerate their ability to write code and compose applications. So, you're seeing a application tsunami coming. So, the pressure is okay, they're going to need infrastructure to run all that stuff. And, so, you're seeing more clusters being spun up, more intelligence trying to automate. So you got the automation, so you got the dynamic, the power dynamic of developers and then under the covers. What does 5.6 do to push the mission forward for developers? How would you guys summarize that for people watching? what's in it for them right now? >> So it's, I think going back to what you just said, right, the breadth of applications that people are developing on top of something like Kubernetes and Cloud Native, is always growing. So, it's not just a number of clusters, but also the fact that different applications and different development groups need these clusters to be composed differently. So, a certain version of the application may require some set of build components, add-ons, and operators, and extensions. Whereas, a different application may require something entirely different. And, now, you take this in an enterprise context, right. Like, we had a major media company that worked with us. They have more than 10,000 pods being used by thousands of developers. And, you now think about the breadth of applications, the hundreds of different applications being built. how do you consistently build, and compose, and manage, a large number of communities clusters with a a large variety of extensions that these companies are trying to manage? That's really what I think 5.6 is bringing to the table. >> Scott Johnston just was on here early as the CEO of Docker. He said there's more applications being pushed now than in the history of application development combined. There's more and more apps coming, more and more pressure on the system. >> And, that's where, if you go, there's this famous landscape chart of the CNCF ecosystem technologies. And, the problem that people here have is, how do they put it all together? How do they make sense of it? And, what 5.6 and Arlon and what Platform9 is doing is, it's helping you declaratively capture blueprints of these clusters, using templates, and be able to manage a small number of blueprints that helps you make order out of the chaos of these hundreds of different projects, that are all very interesting and powerful. >> So Project Arlon really helping developers produce the configuration and the deployment complexities of Kubernetes at scale. >> That's exactly right. >> Talk about the, the impact on the business side. Ease of use, what's the benefits for 5.6? What's does it turn into for a benefit standpoint? >> Yeah, I think the biggest benefit, right, is being able to do Cloud Native at Scale faster, and while still keeping a very lean Ops team that is able to spend, let's say 70 plus percent of their time, caring for your actual business bread and butter applications, and not for the infrastructure that serves it, right. If you take the analogy of a restaurant, you don't want to spend 70% of your time in building the appliances or setting up your stoves etcetera. You want to spend 90 plus percent of your time cooking your own meal, because, that is your core key ingredient. But, what happens today in most enterprises is, because, of the level of automation, the level of hands-on available tooling, being there or not being there, majority of the ops time, I would say 50, 70% plus, gets spent in making that kitchen set up and ready, right. And, that is exactly what we are looking to solve, online. >> What would a customer look like, or prospect environment look like that would be really ready for platform9? What, is it more apps being pushed, big push on application development, or is it the toil of like really inefficient infrastructure, or gaps in skills of people? What does an environment look like? So, someone needs to look at their environment and say, okay, maybe I should call platform9. What's it look like? >> So, we generally see customers fall into two ends of the barbell, I would say. One, is the advanced communities users that are running, I would say, typically, 30 or more clusters already. These are the people that already know containers. They know, they've container wise... >> Savvy teams. >> They're savvy teams, a lot of them are out here. And for them, the problem is, how do I manage the complexity at scale? Because, now, the problem is how do I scale us? So, that's one end of the barbell. The other end of the barbell, is, how do we help make Kubernetes accessible to companies that, as what I would call the mainstream enterprise. We're in Detroit in Motown, right, And, we're outside of the echo chamber of the Silicon Valley. Here's the biggest truth, right. For all the progress that we made as a community, less than 20% of applications in the enterprise today are running on Kubernetes. So, what does it take? I would say it's probably less than 10%, okay. And, what does it take, to grow that in order of magnitude? That's the other kind of customer that we really serve, is, because, we have technologies like Kube Word, which helps them take their existing applications and start adopting Kubernetes as a directional roadmap, but, while using the existing applications that they have, without refactoring it. So, I would say those are the two ends of the barbell. The early adopters that are looking for an easier way to adopt Kubernetes as an architectural pattern. And, the advanced savvy users, for whom the problem is, how do they operationally solve the complexity of managing at scale. >> And, what is your differentiation message to both of those different user groups, as you talked about in terms of the number of users of Kubernetes so far? The community groundswell is tremendous, but, there's a lot of opportunity there. You talked about some of the barriers. What's your differentiation? What do you come in saying, this is why Platform9 is the right one for you, in the both of these groups. >> And it's actually a very simple message. We are the simplest and easiest way for a new user that is adopting Kubernetes as an architectural pattern, to get started with existing applications that they have, on the infrastructure that they have. Number one. And, for the savvy teams, our technology helps you operate with greater scale, with constrained operations teams. Especially, with the economy being the way it is, people are not going to get a lot more budget to go hire a lot more people, right. So, that all of them are being asked to do more with less. And, our team, our technology, and our teams, help you do more with less. >> I was talking with Phil Estes last night from AWS. He's here, he is one of their engineer open source advocates. He's always on the ground pumping up AWS. They've had great success, Amazon Web Services, with their EKS. A lot of people adopting clusters on the cloud and on-premises. But Amazon's doing well. You guys have, I think, a relationship with AWS. What's that, If I'm an Amazon customer, how do I get involved with Platform9? What's the hook? Where's the value? What's the product look like? >> Yeah, so, and it kind of goes back towards the point we spoke about, which is, Kubernetes is going to increasingly get commoditized. So, customers are going to find the right home whether it's hyperscalers, EKS, AKS, GKE, or their own infrastructure, to run Kubernetes. And, so, where we want to be at, is, with a project like Arlon, Sirish spoke about the barbell strategy, on one end there is these advanced Kubernetes users, majority of them are running Kubernetes on AKS, right? Because, that was the easiest platform that they found to get started with. So, now, they have a challenge of running these 50 to 100 clusters across various regions of Amazon, across their DevTest, their staging, their production. And, that results in a level of chaos that these DevOps or platform... >> So you come in and solve that. >> That is where we come in and we solve that. And it, you know, Amazon or EKS, doesn't give you tooling to solve that, right. It makes it very easy for you to create those number of clusters. >> Well, even in one hyperscale, let's say AWS, you got regions and locations... >> Exactly >> ...that's kind of a super cloud problem, we're seeing, opportunity problem, and opportunity is that, on Amazon, availability zones is one thing, but, now, also, you got regions. >> That is absolutely right. You're on point John. And the way we solve it, is by using infrastructure as a code, by using GitOps principles, right? Where you define it once, you define it in a yaml file, you define exactly how for your DevTest environment you want your entire infrastructure to look like, including EKS. And then you stamp it out. >> So let me, here's an analogy, I'll throw out this. You guys are like, someone learns how to drive a car, Kubernetes clusters, that's got a couple clusters. Then once they know how to drive a car, you give 'em the sports car. You allow them to stay on Amazon and all of a sudden go completely distributed, Edge, Global. >> I would say that a lot of people that we meet, we feel like they're figuring out how to build a car with the kit tools that they have. And we give them a car that's ready to go and doesn't require them to be trying to... ... they can focus on driving the car, rather than trying to build the car. >> You don't want people to stop, once they get the progressions, they hit that level up on Kubernetes, you guys give them the ability to go much bigger and stronger. >> That's right. >> To accelerate that applications. >> Building a car gets old for people at a certain point in time, and they really want to focus on is driving it and enjoying it. >> And we got four right behind us, so, we'll get them involved. So that's... >> But, you're not reinventing the wheel. >> We're not at all, because, what we are building is two very, very differentiated solutions, right. One, is, we're the simplest and easiest way to build and run Cloud Native private clouds. And, this is where the operational complexity of trying to do it yourself. You really have to be a car builder, to be able to do this with our Platform9. This is what we do uniquely that nobody else does well. And, the other end is, we help you operate at scale, in the hyperscalers, right. Those are the two problems that I feel, whether you're on-prem, or in the cloud, these are the two problems people face. How do you run a private cloud more easily, more efficiently? And, how do you govern at scale, especially in the public clouds? >> I want to get to two more points before we run out of time. Arlon and Argo CD as a service. We previously mentioned up coming into KubeCon, but, here, you guys couldn't be more relevant, 'cause Intuit was on stage on the keynote, getting an award for their work. You know, Argo, it comes from Intuit. That ArgoCon was in Mountain View. You guys were involved in that. You guys were at the center of all this super cloud action, if you will, or open source. How does Arlon fit into the Argo extension? What is Argo CD as a service? Who's going to take that one? I want to get that out there, because, Arlon has been talked about a lot. What's the update? >> I can talk about it. So, one of the things that Arlon uses behind the scenes, is it uses Argo CD, open source Argo CD as a service, as its key component to do the continuous deployment portion of its entire, the infrastructure management story, right. So, we have been very strongly partnering with Argo CD. We, really know and respect the Intuit team a lot. We, as part of this effort, in 5.6 release, we've also put out Argo CD as a service, in its GA version, right. Because, the power of running Arlon along with Argo CD as a service, in our mind, is enabling you to run on one end, your infrastructure as a scale, through GitOps, and infrastructure as a code practices. And on the other end, your entire application fleet, at scale, right. And, just marrying the two, really gives you the ability to perform that automation that we spoke about. >> But, and avoid the problem of sprawl when you have distributed teams, you have now things being bolted on, more apps coming out. So, this is really solves that problem, mainly. >> That is exactly right. And if you think of it, the way those problems are solved today, is, kind of in disconnected fashion, which is on one end you have your CI/CD tools, like Argo CD is an excellent one. There's some other choices, which are managed by a separate team to automate your application delivery. But, that team, is disconnected from the team that does the infrastructure management. And the infrastructure management is typically done through a bunch of Terraform scripts, or a bunch of ad hoc homegrown scripts, which are very difficult to manage. >> So, Arlon changes sure, as they change the complexity and also the sprawl. But, that's also how companies can die. They're growing fast, they're adding more capability. That's what trouble starts, right? >> I think in two ways, right. Like one is, as Madhura said, I think one of the common long-standing problems we've had, is, how do infrastructure and application teams communicate and work together, right. And, you've seen Argo's really get adopted by the application teams, but, it's now something that we are making accessible for the infrastructure teams to also bring the best practices of how application teams are managing applications. You can now use that to manage infrastructure, right. And, what that's going to do is, help you ultimately reduce waste, reduce inefficiency, and improve the developer experience. Because, that's what it's all about, ultimately. >> And, I know that you just released 5.6 today, congratulations on that. Any customer feedback yet? Any, any customers that you've been able to talk to, or have early access? >> Yeah, one of our large customers is a large SaaS retail company that is B2C SaaS. And, their feedback has been that this, basically, helps them bring exactly what I said in terms of bring some of the best practices that they wanted to adopt in the application space, down to the infrastructure management teams, right. And, we are also hearing a lot of customers, that I would say, large scale public cloud users, saying, they're really struggling with the complexity of how to tame the complexity of navigating that landscape and making it consumable for organizations that have thousands of developers or more. And that's been the feedback, is that this is the first open source standard mechanism that allows them to kind of reuse something, as opposed to everybody feels like they've had to build ad hoc solutions to solve this problem so far. >> Having a unified infrastructure is great. My final question, for me, before I end up, for Lisa to ask her last question is, if you had to explain Platform9, why you're relevant and cool today, what would you say? >> If I take that? I would say that the reason why Platform9, the reason why we exist, is, putting together a cloud, a hybrid cloud strategy for an enterprise today, historically, has required a lot of DIY, a lot of building your own car. Before you can drive a car, or you can enjoy the car, you really learn to build and operate the car. And that's great for maybe a 100 tech companies of the world, but, for the next 10,000 or 50,000 enterprises, they want to be able to consume a car. And that's why Platform9 exists, is, we are the only company that makes this delightfully simple and easy for companies that have a hybrid cloud strategy. >> Why you cool and relevant? How would you say it? >> Yeah, I think as Kubernetes becomes mainstream, as containers have become mainstream, I think automation at scale with ease, is going to be the key. And that's exactly what we help solve. Automation at scale and with ease. >> With ease and that differentiation. Guys, thank you so much for joining me. Last question, I guess, Madhura, for you, is, where can Devs go to learn more about 5.6 and get their hands on it? >> Absolutely. Go to platform9.com. There is info about 5.6 release, there's a press release, there's a link to it right on the website. And, if they want to learn about Arlon, it's an open source GitHub project. Go to GitHub and find out more about it. >> Excellent guys, thanks again for sharing what you're doing to really deliver Cloud Native at Scale in a differentiated way that adds ostensible value to your customers. John, and I, appreciate your insights and your time. >> Thank you for having us. >> Thanks so much >> Our pleasure. For our guests and John Furrier, I'm Lisa Martin. You're watching theCUBE Live from Detroit, Michigan at KubeCon CloudNativeCon 2022. Stick around, John and I will be back with our next guest. Just a minute. (light synth outro music)

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

>>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 all going? Making it super multi-Cloud is around the corner and public cloud is winning at the private cloud on premise and edge. Got a great guest here, Vascar go, D 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 thing about what you guys are doing a 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 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 asbs 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, have been pumping on all cylinders as an economic input. And if you look at the tech trends, GDPs down, but not tech. Nope. Because 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 >>E 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, Alan and I want to do with Super Cloud and calling at 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 the 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. >>I, 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? But they're not connected. So you can say okay, it's more than one cloud. So it's you know, multi-cloud. But Supercloud 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, 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 pane, 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, 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 skillset. 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. There 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 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. >>And what benefits are they seeing? Are they seeing speed? >>Speed, definitely. Okay. Definitely their 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 two part of one thing, but ops and great specifically need to catch up. Speedwise, 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 were just two sides to that coin. You've got the dev side and then >>And the infrastructure >>Side. Okay, >>Another customer, I 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 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 rack in the store or they can't move everything to the cloud because the store operations have 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 of 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 say little service, 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. Yeah, 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 plugin >>Play two plugin 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 >>Youcar, of course Detroit's >>Coming in, 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 and business logic using modern tools. Hopefully more open source and, and I think that's what Cloudnative is and we are seeing lot of our customers in that journey. Now everybody wants to be cloud native, 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 you use. Okay? So, so I think the complexities 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 Domino's 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, they were the pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow through 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 will not, >>Thats got 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 in 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 of 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, 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, being at an asb, being 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 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, couple of parallels come to me. One is, think of it, which was forced to on us, 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 cloud native. 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 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 then made you an e-commerce or e retailer or 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. Spend 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.

>>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, Bacar, go deep 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 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 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, >>In fact, you know, as we were talking offline, I was in one of those asbs 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 their 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, 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. Because 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 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 at 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, more >>Real. I, 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 to, 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, 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, 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 OpenStack, 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 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 it, the beauty of it is yes, open source, but the biggest gating factor is the skill. 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. There are thousands of stores in a retailer. So we provide that and also for specific segments where data sovereignty and data residency, our key regulatory reasons. We also run 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 their tools, they're using whatever app development tools they use, but they use our platform. >>And 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 two part of one thing, 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, So you were just two sides of that coin. You've got the dev side and then and the infrastructure side. Okay, >>Another customer, like 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 rack in the store or they can't move everything to the cloud because the store operations have to be local. The menu changes based on it's classic edge if >>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 >>Say little shares, 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, 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 >>Tucan of course Detroit's >>Coming here, 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 cloudnative, okay? You can't port to cloud, not 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 lot of our customers in that journey. Now everybody wants to be cloud native, 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 you use. Okay? So, 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 Domino's 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, they were the pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow through the application changes what the expectations of are for the customer. >>Customer, the customer's expectations change, right? Once you get used to a better customer experience, you will not >>Best part. 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 in 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 of 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, the big companies, you've seen the different waves. What's going on right now Put into context this moment in time. Sure. Around Super >>Cloud. Sure. I think as you said, a lot of battles. Cars being, being 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, couple of parallels come to me. One is, think of it, which was forced to on us 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 wasn't existence. Question. Yeah, I think we are at that pivotal moment now in companies trying to become digital and cloud native and 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 then made you an e-commerce or e retailer or 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 for 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 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.

(upbeat music) >> Okay, we're back to wrap up Fal.con 2022 CrowdStrike's customer event. You're watching theCUBE. My name is Dave Vellante. My co-host, Dave Nicholson, is on injured reserve today, so I'm solo. But I wanted to just give the audience a census to some of my quick takeaways. Really haven't given a ton of thought on this. We'll do review after we check out the videos and the transcripts, and do what we do at SiliconANGLE and theCUBE. I'd say the first thing is, look CrowdStrike continues to expand it's footprint. And, it's adding the identity module, through the preempt acquisition. Working very closely with managed service providers, MSPs, managed security service providers. Having an SMB play. So CrowdStrike has 20,000 customers. I think it could, it could 10X that, you know, over some period of time. As I've said earlier, it's on a path by mid-decade to be a 5 billion company, in terms of revenue. At the macro level, security is somewhat, I'd say it's less discretionary than some other investments. You know, you can, you can probably hold off buying a new storage device. You can maybe clean that up. You know, you might be able to hold off on some of your analytics, but at the end of the day, security is not completely non-discretionary. It's competing. The CISO is competing with other budgets. Okay? So it's, while it's less discretionary, it is still, you know, not an open checkbook for the CISO. Now, having said that, from CrowdStrike standpoint it has an excellent opportunity to consolidate tools. It's one of the biggest problems in the security business Go to Optiv and check out their security taxonomy. It'll make your eyes bleed. There's so many tools and companies that are really focused on one specialization. But really, what CrowdStrike can do with its 22 modules, to say, hey, we can give you ROI and consolidate those. And not only is it risk reduction, it's lowering the labor cost and labor intensity, so you can focus on other areas and free up the biggest problem that CISOs have. It's the lack of enough talent. So, really strong business value and value proposition. A lot of that is enabled by the architecture. We've talked about this. You can check out my breaking analysis that I dropped last weekend, on CrowdStrike. And, you know, can it become a generational company. But it's really built on a cloud-native architecture. George Kurtz and company, they shunned having an on-premise architecture. Much like Snowflake Frank Slootman has said, we're not doing a halfway house. We're going to put all our resources on a cloud-native architecture. The lightweight agent that allows them to add new modules and collect more data, and scale out. The purpose-built threat graph and and time series database, and asset graph that they've built. And very strong use of AI, to not only stop known malware, but stop unknown malware. Identify threats. Do that curation. And really, you know, support the SecOp teams. Product wise, I think the big three takeaways, and there were others, but the big three for me is EDR extending into XDR. You know, X is the extending for, in really, the core of endpoint detection and response, extending that further. Well, it seems to be a big buzzword these days. CrowdStrike, I think, is very focused on making a more complete, a holistic offering, beyond endpoint. And I think it's going to do very well in that space. They're not alone. There are others. It's a very competitive space. The second is identity. Through the acquisition of Preempt. CrowdStrike building that identity module. Partnering with leaders like Okta, to really provide that sort of, treating identity, if you will, as an endpoint. And then sort of Humio is now Falcon Log Scale. Bringing together, you know, the data and the observability piece, and the security piece, is kind of the three big product trends that I saw. I think the last point I'll make, before we wrap, is the ecosystem. The ecosystem here is good. It reminds me, I said, a number of times this week, of ServiceNow in 2013 I think the difference is, CrowdStrike has an SMB play it can go after many more customers, and actually have an even broader platform. And I think it can accelerate its ecosystem faster than ServiceNow was able to do that. I mean, it's got to be, sort of, an open and collaborative sort of ecosystem. You know, ServiceNow is kind of, more of, a one-way street. And I think the other piece of that ecosystem, that we see evolving, into IOT, into the operations technology and critical infrastructure. Which is so important, because critical infrastructure of nations is so vulnerable. We're seeing this in the Ukraine. Security is a key component now of any warfare. And going forward, it's always going to be a key component. Nation states are going to go after trust, or secure infrastructure, or critical infrastructure. Try to disable that and disrupt that. So securing those operation assets is going to be very critical. Not just the refrigerator and the coffee maker, but really going after those critical infrastructures. (chuckles) Getting asked to break. And the last thing I'll say, is the developer platform. We heard from ML that, the opportunity that's there, to build out a PaaS layer, super PaaS layer, if you will, so that developers can add value. I think if that happens, this ecosystem, which is breaking down, will explode. This is Dave Vellante, wrapping up at CrowdStrike, Fal.con 2022, Fal.con 2022. Go to SiliconAngle.com, for all the news. Check out theCUBE.net. You'll see these videos on demand and many others. Check out (indistinct).com for all the research. And look for where we'll be next. Of course, re:Invent is the big fall event, but there are many others in between. Thanks for watching. We're out. (music plays out)

(light corporate music) >> Welcome back, everyone, to VMware Explore 22. I'm John Furrier, host of theCUBE with Dave Vellante. Our 12th year covering VMware's User Conference, formerly known as VMworld, now rebranded as VMware Explore. Two great cube alumnus coming down the cube. Ricky Cooper, SVP, Worldwide Partner Commercials VMware, great to see you. Thanks for coming on. >> Thank you. >> We just had a great chat- >> Good to see you again. >> With the Discovery and, of course, Joseph George, vice president of Compute Industry Alliances. Great to have you on. Great to see you. >> Great to see you, John. >> So guys this year is very curious in VMware. A lot goin' on, the name change, the event. Big, big move. Bold move. And then they changed the name of the event. Then Broadcom buys them. A lot of speculation, but at the end of the day, this conference kind of, people were wondering what would be the barometer of the event. We're reporting this morning on the keynote analysis. Very good mojo in the keynote. Very transparent about the Broadcom relationship. The expo floor last night was buzzing. >> Mhm. >> I mean, this is not a show that's lookin' like it's going to be, ya' know, going down. >> Yeah. >> This is clearly a wave. We're calling it Super Cloud. Multi-Cloud's their theme. Clearly the cloud's happenin'. We not to date ourselves, but 2013 we were discussing on theCUBE- >> We talked about that. Yeah. Yeah. >> Discover about DevOps infrastructure as code- >> Mhm. >> We're full realization now of that. >> Yep. >> This is where we're at. You guys had a great partnership with VMware and HPE. Talk about where you guys see this coming together because customers are refactoring. They are lookin' at Cloud Native. The whole Broadcom visibility to the VMware customer bases activated them. They're here and they're leaning in. >> Yeah. >> What's going on? >> Yeah. Absolutely. We're seeing a renewed interest now as customers are looking at their entire infrastructure, bottoms up, all the way up the stack, and the notion of a hybrid cloud, where you've got some visibility and control of your data and your infrastructure and your applications, customers want to live in that sort of a cloud environment and so we're seeing a renewed interest. A lot of conversations we're having with customers now, a lot of customers committing to that model where they have applications and workloads running at the Edge, in their data center, and in the public cloud in a lot of cases, but having that mobility, having that control, being able to have security in their own, you know, in their control. There's a lot that you can do there and, obviously, partnering with VMware. We've been partners for so long. >> 20 years about. Yeah. Yeah. >> Yeah. At least 20 years, back when they invented stuff, they were inventing way- >> Yeah. Yeah. Yeah. >> VMware's got a very technical culture, but Ricky, I got to say that, you know, we commented earlier when Raghu was on, the CEO, now CEO, I mean, legendary product. I sent the trajectory to VMware. Everyone knows that. VMware, I can't know whether to tell it was VMware or HP, HP before HPE, coined hybrid- >> Yeah. >> 'Cause you guys were both on. I can't recall, Dave, which company coined it first, but it was either one of you guys. Nobody else was there. >> It was the partnership. >> Yes. I- (cross talking) >> They had a big thing with Pat Gelsinger. Dave, remember when he said, you know, he got in my grill on theCUBE live? But now you see- >> But if you focus on that Multi-Cloud aspect, right? So you've got a situation where our customers are looking at Multi-Cloud and they're looking at it not just as a flash in the pan. This is here for five years, 10 years, 20 years. Okay. So what does that mean then to our partners and to our distributors? You're seeing a whole seed change. You're seeing partners now looking at this. So, look at the OEMs, you know, the ones that have historically been vSphere customers are now saying, they're coming in droves saying, okay, what is the next step? Well, how can I be a Multi-Cloud partner with you? >> Yep. Right. >> How can I look at other aspects that we're driving here together? So, you know, GreenLake is a great example. We keep going back to GreenLake and we are partaking in GreenLake at the moment. The real big thing for us is going to be, right, let's make sure that we've got the agreements in place that support this SaaS and subscription motion going forward and then the sky's the limit for us. >> You're pluggin' that right into GreenLake, right? >> Well, here's why. Here's why. So customers are loving the fact that they can go to a public cloud and they can get an SLA. They come to a, you know, an On-Premise. You've got the hardware, you've got the software, you've got the, you know, the guys on board to maintain this through its life cycle. >> Right. I mean, this is complicated stuff. >> Yeah. >> Now we've got a situation where you can say, hey, we can get an SLA On-Premise. >> Yeah. And I think what you're seeing is it's very analogous to having a financial advisor just manage your portfolio. You're taking care of just submitting money. That's really a lot of what the customers have done with the public cloud, but now, a lot of these customers are getting savvy and they have been working with VMware Technologies and HPE for so long. They've got expertise. They know how they want their workloads architected. Now, we've given them a model where they can leverage the Cloud platform to be able to do this, whether it's On-Premise, The Edge, or in the public cloud, leveraging HPE GreenLake and VMware. >> Is it predominantly or exclusively a managed service or do you find some customers saying, hey, we want to manage ourself? How, what are you seeing is the mix there? >> It is not predominantly managed services right now. We're actually, as we are growing, last time we talked to HPE Discover we talked about a whole bunch of new services that we've added to our catalog. It's growing by leaps and bounds. A lot of folks are definitely interested in the pay as you go, obviously, the financial model, but are now getting exposed to all the other management that can happen. There are managed services capabilities, but actually running it as a service with your systems On-Prem is a phenomenal idea for all these customers and they're opening their eyes to some new ways to service their customers better. >> And another phenomenon we're seeing there is where partners, such as HPA, using other partners for various areas of their services implementation as well. So that's another phenomenon, you know? You're seeing the resale motion now going into a lot more of the services motion. >> It's interesting too, you know, I mean, the digital modernization that's goin' on. The transformation, whatever you want to call it, is complicated. >> Yeah. >> That's clear. One of the things I liked about the keynote today was the concept of cloud chaos. >> Yeah. >> Because we've been saying, you know, quoting Andy Grove at Intel, "Let chaos rain and rain in the chaos." >> Mhm. >> And when you have inflection points, complexity, which is the chaos, needs to be solved and whoever solves it kicks the inflection point, that's up into the right. So- >> Prime idea right here. Yeah. >> So GreenLake is- >> Well, also look at the distribution model and how that's changed. A couple of points on a deal. Now they're saying, "I'll be your aggregator. I'll take the strain and I'll give you scale." You know? "I'll give you VMware Scale for all, you know, for all of the various different partners, et cetera." >> Yeah. So let's break this down because this is, I think, a key point. So complexity is good, but the old model in the Enterprise market was- >> Sure. >> You solve complexity with more complexity. >> Yeah. >> And everybody wins. Oh, yeah! We're locked in! That's not what the market wants. They want some self-service. They want, as a service, they want easy. Developer first security data ops, DevOps, is already in the cycle, so they're going to want simpler. >> Yeah. >> Easier. Faster. >> And this is kind of why I'll say, for the big announcement today here at VMware Explore, around the VMware vSphere Distributed Services Engine, Project Monterey- >> Yeah. >> That we've talked about for so long, HPE and VMware and AMD, with the Pensando DPU, actually work together to engineer a solution for exactly that. The capabilities are fairly straightforward in terms of the technologies, but actually doing the work to do integration, joint engineering, make sure that this is simple and easy and able to be running HPE GreenLake, that's- >> That's invested in Pensando, right? >> We are. >> We're all investors. Yeah. >> What's the benefit of that? What's, that's a great point you made. What's the value to the customer, bottom line? That deep co-engineering, co-partnering, what does it deliver that others don't do? >> Yeah. Well, I think one example would be, you know, a lot of vendors can say we support it. >> Yep. >> That's great. That's actually a really good move, supporting it. It can be resold. That's another great move. I'm not mechanically inclined to where I would go build my own car. I'll go to a dealership and actually buy one that I can press the button and I can start it and I can do what I need to do with my car and that's really what this does is the engineering work that's gone on between our two companies and AMD Pensando, as well as the business work to make that simple and easy, that transaction to work, and then to be able to make it available as a service, is really what made, it's, that's why it's such a winner winner with our- >> But it's also a lower cost out of the box. >> Yep. >> Right. >> So you get in whatever. Let's call it 20%. Okay? But there's, it's nuanced because you're also on a new technology curve- >> Right. >> And you're able to absorb modern apps, like, you know, we use that term as a bromide, but when I say modern apps, I mean data-rich apps, you know, things that are more AI-driven not the conventional, not that people aren't doing, you know, SAP and CRM, they are, but there's a whole slew of new apps that are coming in that, you know, traditional architectures aren't well-suited to handle from a price performance standpoint. This changes that doesn't it? >> Well, you think also of, you know, going to the next stage, which is to go to market between the two organizations that before. At the moment, you know, HPE's running off doing various different things. We were running off to it again, it's that chaos that you're talking about. In cloud chaos, you got to go to market chaos. >> Yeah. >> But by simplifying four or five things, what are we going to do really well together? How do we embed those in GreenLake- >> Mhm. >> And be known in the marketplace for these solutions? Then you get a, you know, an organization that's really behind the go to market. You can help with sales activation the enablement, you know, and then we benefit from the scale of HPE. >> Yeah. >> What are those solutions I mean? Is it just, is it I.S.? Is it, you know, compute storage? >> Yeah. >> Is it, you know, specific, you know, SAP? Is it VDI? What are you seeing out there? >> So right now, for this specific technology, we're educating our customers on what that could be and, at its core, this solution allows customers to take services that normally and traditionally run on the compute system and run on a DPU now with Project Monterey, and this is now allowing customers to think about, okay, where are their use cases. So I'm, rather than going and, say, use it for this, we're allowing our customers to explore and say, okay, here's where it makes sense. Where do I have workloads that are using a lot of compute cycles on services at the compute level that could be somewhere else like networking as a great example, right? And allowing more of those compute cycles to be available. So where there are performance requirements for an application, where there is timely response that's needed for, you know, for results to be able to take action on, to be able to get insight from data really quick, those are places where we're starting to see those services moving onto something like a DPU and that's where this makes a whole lot more sense. >> Okay. So, to get this right, you got the hybrid cloud, right? >> [Ricky And Joseph] Yes. >> You got GreenLake and you got the distributed engine. What's that called the- >> For, it's HPE ProLiant- >> ProLiant with- >> The VMware- >> With vSphere. >> That's the compute- >> Distributed. >> Okay. So does the customer, how do you guys implement that with the customer? All three at the same time or they mix and match? What's that? How does that work? >> All three of those components. Yeah. So the beauty of the HP ProLiant with VMware vSphere-distributed services engine- >> Mhm. >> Also known as Project Monterey for those that are keeping notes at home- >> Mhm. >> It's, again, already pre-engineered. So we've already worked through all the mechanics of how you would have to do this. So it's not something you have to go figure out how you build, get deployment, you know, work through those details. That's already done. It is available through HPE GreenLake. So you can go and actually get it as a service in partnership with our customer, our friends here at VMware, and because, if you're familiar and comfortable with all the things that HP ProLiant has done from a security perspective, from a reliability perspective, trusted supply chain, all those sorts of things, you're getting all of that with this particular (indistinct). >> Sumit Dhawan had a great quote on theCUBE just an hour or so ago. He said you have to be early to be first. >> Yeah. (laughing) >> I love that quote. Okay. So you were- >> I fought the urge. >> You were first. You were probably a little early, but do you have a lead? I know you're going to say yes, okay. Let's just- >> Okay. >> Let's just assume that. >> Okay. Yeah. >> Relative to the competition, how do you know? How do you determine that? >> If we have a lead or not? >> Yeah. If you lead. If you're the best. >> We go to the source of the truth which is our customers. >> And what do they tell you? What do you look at and say, okay, now, I mean, when you have that honest conversation and say, okay, we are, we're first, we're early. We're keeping our lead. What are the things that you- >> I'll say it this way. I'll say it this way. We've been in a lot of businesses where there, where we do compete head-to-head in a lot of places. >> Mhm. >> And we know how that sales process normally works. We're seeing a different motion from our customers. When we talk about HPE GreenLake, there's not a lot of back and forth on, okay, well, let me go shop around. It is HP Green. Let's talk about how we actually build this solution. >> And I can tell you, from a VMware perspective, our customers are asking us for this the other way around. So that's a great sign is that, hey, we need to see this partnership come together in GreenLake. >> Yeah. >> It's the old adage that Amazon used to coin and Andy Jassy, you know, they do the undifferentiated heavy lifting. >> [Ricky And Joseph] Yeah. >> A lot of that's now Cloud operations. >> Mhm. >> Underneath it is infrastructure's code to the developer. >> That's right. >> That's at scale. >> That's right. >> And so you got a lot of heavy lifting being done with GreenLake- >> Right. >> Which is why there's no objections probably. >> Right. >> What's the choice? What are you going to shop? >> Yeah. >> There's nothing to shop around. >> Yeah, exactly. And then we've got, you know, that is really icing on the cake that we've, you know, that we've been building for quite some time and there is an understanding in the market that what we do with our infrastructure is hardened from a reliability and quality perspective. Like, times are tough right now. Supply chain issues, all that stuff. We've talked, all talked about it, but at HPE, we don't skimp on quality. We're going to spend the dollars and time on making sure we got reliability and security built in. It's really important to us. >> We had a great use case. The storage team, they were provisioning with containers. >> Yes. >> Storage is a service instantly we're seeing with you guys with VMware. Your customers' bringing in a lot of that into the mix as well. I got to ask 'cause every event we talk about AI and machine learning- >> Mhm. >> Automation and DevOps are now infiltrating in with the CICD pipeline. Security and data become a big conversation. >> [Ricky And Joseph] Agreed. >> Okay. So how do you guys look at that? Okay. You sold me on Green. Like, I've been a big fan from day one. Now, it's got maturity on it. I know it's going to get a lot more headroom to do. There's still a lot of work to do, but directionally it's pretty accurate, you know? It's going to be a success. There's still concern about security, the data layer. That's agnostic of environment, private cloud, hybrid, public, and Edge. So that's important and security- >> Great. >> Has got a huge service area. >> Yeah. >> These are on working progress. >> Yeah. Yeah. >> How do you guys view those? >> I think you've just hit the net on the head. I mean, I was in the press and journalist meetings yesterday and our answer was exactly the same. There is still so much work that can be done here and, you know, I don't think anybody is really emerging as a true leader. It's just a continuation of, you know, tryin' to get that right because it is what is the most important thing to our customers. >> Right. >> And the industry is really sort of catching up to that. >> And, you know, when you start talking about privacy and when you, it's not just about company information. It's about individuals' information. It's about, you know, information that, if exposed, actually could have real impact on people. >> Mhm. >> So it's more than just an I.T. problem. It is actually, and from HPE's perspective, security starts from when we're picking our suppliers for our components. Like, there are processes that we put into our entire trusted supply chain from the factory on the way up. I liken it to my golf swing. My golf swing. I slice right like you wouldn't believe. (John laughing) But when I go to the golf pros, they start me back at the mechanics, the foundational pieces. Here's where the problems are and start workin' on that. So my view is, our view is, if your infrastructure is not secure, you're goin' to have troubles with security as you go further up. >> Stay in the sandbox. >> Yeah. >> Yeah. So to speak, you know, they're driving range on the golf analogy there. I love that. Talk about supply chain security real quick because you mentioned supply chain on the hardware side. You're seeing a lot of open source and supply chain in software, trusted software. >> Yep. >> How does GreenLake look at that? How do you guys view that piece of it? That's an important part. >> Yeah. Security is one of the key pillars that we're actually driving as a company right now. As I said, it's important to our customers as they're making purchasing decisions and we're looking at it from the infrastructure all the way up to the actual service itself and that's the beauty of having something like HPE GreenLake. We don't have to pick, is the infrastructure or the middle where, or the top of stack application- >> It's (indistinct), right? >> It's all of it. >> Yeah. >> It's all of it. That matters. >> Quick question on the ecosystem posture. So- >> Sure. >> I remember when HP was, you know, one company and then the GSIs were a little weird with HP because of EDS, you know? You had data protector so we weren't really chatting up Veeam at the time, right? And as soon as the split happened, ecosystem exploded. Now you have a situation where you, Broadcom, is acquiring VMware. You guys, big Broadcom customer. Has your attitude changed or has it not because, oh, we meet with the customers already. Well, you've always said that, but have you have leaned in more? I mean, culturally, is HPE now saying, hmm, now we have some real opportunities to partner in new ways that we don't have to sleep with one eye open, maybe. (John laughing) >> So first of all, VMware and HPE, we've got a variety of different partners. We always have. >> Mhm. >> Well before any Broadcom announcement came along. >> Yeah, sure. >> We've been working with a variety of partners. >> And that hasn't changed. >> And that hasn't changed. And, if your question is, has our posture toward VMware changed at all, the answer's absolutely not. We believe in what VMware is doing. We believe in what our customers are doing with VMware and we're going to continue to work with VMware and partner with the (indistinct). >> And of course, you know, we had to spin out ourselves in November of last year, which I worked on, you know, the whole Dell thing. >> Yeah. We still had the same chairman. >> Yeah. There- (Dave chuckling) >> Yeah, but since then, I think what's really become very apparent and not, it's not just with HPE, but with many of our partners, many of the OEM partners, the opportunity in front of us is vast and we need to rely on each other to help us as, you know, solve the customer problems that are out there. So there's a willingness to overlook some things that, in the past, may have been, you know, barriers. >> But it's important to note also that it's not that we have not had history- >> Yeah. >> Right? Over, we've got over 200,000 customers join- >> Hundreds of millions of dollars of business- >> 100,000, over 10,000, or 100,000 channel partners that we all have in common. >> Yeah. Yeah. >> Yep. >> There's numerous- >> And independent of the whole Broadcom overhang there. >> Yeah. >> There's the ecosystem floor. >> Yeah. >> The expo floor. >> Right. >> I mean, it's vibrant. I mean, there's clearly a wave coming, Ricky. We talked about this briefly at HPE Discover. I want to get an update from your perspectives, both of you, if you don't mind weighing in on this. Clearly, the wave, we're calling it the Super Cloud, 'cause it's not just Multi-Cloud. It's completely different looking successes- >> Smart Cloud. >> It's not just vendors. It's also the customers turning into clouds themselves. You look at Goldman Sachs and- >> Yep. >> You know, I think every vertical will have its own power law of Cloud players in the future. We believe that to be true. We're still testing that assumption, but it's trending in when you got OPEX- >> [Ricky And Joseph] Right. >> Has to go to in-fund statement- >> Yeah. >> CapEx goes too. Thanks for the Cloud. All that's good, but there's a wave coming- >> Yeah. >> And we're trying to identify it. What do you guys see as this wave 'cause beyond Multi-Cloud and the obvious nature of that will end up happening as a state and what happens beyond that interoperability piece, that's a whole other story, and that's what everyone's fighting for, but everyone out in that ecosystem, it's a big wave coming. They've got their surfboards. They're ready to go. So what do you guys see? What is the next wave that everyone's jacked up about here? >> Well, I think that the Multi-Cloud is obviously at the epicenter. You know, if you look at the results that are coming in, a lot of our customers, this is what's leading the discussion and now we're in a position where, you know, we've brought many companies over the last few years. They're starting to come to fruition. They're starting to play a role in, you know, how we're moving forward. >> Yeah. >> Some of those are a bit more applicable to the commercial space. We're finding commercial customers that never bought from us before. Never. Hundreds and hundreds are coming through our partner networks every single quarter, you know? So brand new to VMware. The trick then is how do you nurture them? How do you encourage them? >> So new logos are comin' in. >> New logos are coming in all the time, all the time, from, you know, from across the ecosystem. It's not just the OEMs. It's all the way back- >> So the ecosystem's back of VMware. >> Unbelievably. So what are we doing to help that? There's two big things that we've announced in the recent weeks is that Partner Connect 2.0. When I talked to you about Multi-Cloud and what the (indistinct), you know, the customers are doing, you see that trend. Four, five different separate clouds that we've got here. The next piece is that they're changing their business models with the partners. Their services is becoming more and more apparent, et cetera, you know? And the use of other partners to do other services, deployment, or this stuff is becoming prevalent. Then you've got the distributors that I talked about with their, you know, their, then you route to market, then you route to business. So how do you encapsulate all of that and ensure your rewarding partners on all aspects of that? Whether it's deployment, whether it's test and depth, it's a points-based system we've put in place now- >> It's a big pie that's developing. The market's getting bigger. >> It's getting so much bigger. And then you help- >> I know you agree, obviously, with that. >> Yeah. Absolutely. In fact, I think for a long time we were asking the question of, is it going to be there or is it going to be here? Which was the wrong question. (indistinct cross talking) Now it's everything. >> Yeah. >> And what I think that, what we're seeing in the ecosystem, is that people are finding the spots that, where they're going to play. Am I going to be on the Edge? >> Yeah. >> Am I going to be on Analytics Play? Am I going to be, you know, Cloud Transition Play? There's a lot of players are now emerging and saying, we're- >> Yeah. >> We're, we now have a place, a part to play. And having that industry view not just of, you know, a commercial customer at that level, but the two of us are lookin' at Teleco, are looking at financial services, at healthcare, at manufacturing. How do these new ecosystem players fit into the- >> (indistinct) lifting. Everyone can see their position there. >> Right. >> We're now being asked for simplicity and talk to me about partner profitability. >> Yes. >> How do I know where to focus my efforts? Am I spread too thin? And, you know, that's, and my advice that the partner ecosystem out there is, hey, let's pick out spots together. Let's really go to, and then strategic solutions that we were talking about is a good example of that. >> Yeah. >> Sounds like composability to me, but not to go back- (laughing) Guys, thanks for comin' on. I think there's a big market there. I think the fog is lifted. People seeing their spot. There's value there. Value creation equals reward. >> Yeah. >> Simplicity. Ease of use. This is the new normal. Great job. Thanks for coming on and sharing. (cross talking) Okay. Back to live coverage after this short break with more day one coverage here from the blue set here in Moscone. (light corporate music)

(upbeat music) >> Welcome back to San Francisco, "theCUBE" is live, our day two coverage of VMware Explore 2022 continues. Lisa Martin with Dave Nicholson. Dave and I are pleased to welcome Jason Collier, principal member of technical staff at AMD to the program. Jason, it's great to have you. >> Thank you, it's great to be here. >> So what's going on at AMD? I hear you have some juicy stuff to talk about. >> Oh, we've got a ton of juicy stuff to talk about. Clearly the Project Monterey announcement was big for us, so we've got that to talk about. Another thing that I really wanted to talk about was a tool that we created and we call it, it's the VMware Architecture Migration Tool, call it VAMT for short. It's a tool that we created and we worked together with VMware and some of their professional services crew to actually develop this tool. And it is also an open source based tool. And really the primary purpose is to easily enable you to move from one CPU architecture to another CPU architecture, and do that in a cold migration fashion. >> So we're probably not talking about CPUs from Tandy, Radio Shack systems, likely this would be what we might refer to as other X86 systems. >> Other X86 systems is a good way to refer to it. >> So it's interesting timing for the development and the release of a tool like this, because in this sort of X86 universe, there are players who have been delayed in terms of delivering their next gen stuff. My understanding is AMD has been public with the idea that they're on track for by the end of the year, Genoa, next gen architecture. So can you imagine a situation where someone has an existing set of infrastructure and they're like, hey, you know what I want to get on board, the AMD train, is this something they can use from the VMware environment? >> Absolutely, and when you think about- >> Tell us exactly what that would look like, walk us through 100 servers, VMware, 1000 VMs, just to make the math easy. What do you do? How does it work? >> So one, there's several things that the tool can do, we actually went through, the design process was quite extensive on this. And we went through all of the planning phases that you need to go through to do these VM migrations. Now this has to be a cold migration, it's not a live migration. You can't do that between the CPU architectures. But what we do is you create a list of all of the virtual machines that you want to migrate. So we take this CSV file, we import this CSV file, and we ask for things like, okay, what's the name? Where do you want to migrate it to? So from one cluster to another, what do you want to migrate it to? What are the networks that you want to move it to? And then the storage platform. So we can move storage, it could either be shared storage, or we could move say from VSAN to VSAN, however you want to set it up. So it will do those storage migrations as well. And then what happens is it's actually going to go through, it's going to shut down the VM, it's going to take a snapshot, it is going to then basically move the compute and/or storage resources over. And once it does that, it's going to power 'em back up. And it's going to check, we've got some validation tools, where it's going to make sure VM Tools comes back up where everything is copacetic, it didn't blue screen or anything like that. And once it comes back up, then everything's good, it moves onto the next one. Now a couple of things that we've got feature wise, we built into it. You can parallelize these tasks. So you can say, how many of these machines do you want to do at any given time? So it could be, say 10 machines, 50 machines, 100 machines at a time, that you want to go through and do this move. Now, if it did blue screen, it will actually roll it back to that snapshot on the origin cluster. So that there is some protection on that. A couple other things that are actually in there are things like audit tracking. So we do full audit logging on this stuff, we take a snapshot, there's basically kind of an audit trail of what happens. There's also full logging, SYS logging, and then also we'll do email reporting. So you can say, run this and then shoot me a report when this is over. Now, one other cool thing is you can also actually define a change window. So I don't want to do this in the middle of the afternoon on a Tuesday. So I want to do this later at night, over the weekend, you can actually just queue this up, set it, schedule it, it'll run. You can also define how long you want that change window to be. And what it'll do, it'll do as many as it can, then it'll effectively stop, finish up, clean up the tasks and then send you a report on what all was successfully moved. >> Okay, I'm going to go down the rabbit hole a little bit on this, 'cause I think it's important. And if I say something incorrect, you correct me. >> No problem. >> In terms of my technical understanding. >> I got you. >> So you've got a VM, essentially a virtual machine typically will consist of an entire operating system within that virtual machine. So there's a construct that containerizes, if you will, the operating system, what is the difference, where is the difference in the instruction set? Where does it lie? Is it in the OS' interaction with the CPU or is it between the construct that is the sort of wrapper around the VM that is the difference? >> It's really primarily the OS, right? And we've not really had too many issues doing this and most of the time, what is going to happen, that OS is going to boot up, it's going to recognize the architecture that it's on, it's going to see the underlying architecture, and boot up. All the major operating systems that we test worked fine. I mean, typically they're going to work on all the X86 platforms. But there might be instruction sets that are kind of enabled in one architecture that may not be in another architecture. >> And you're looking for that during this process. >> Well usually the OS itself is going to kind of detect that. So if it pops up, the one thing that is kind of a caution that you need to look for. If you've got an application that's explicitly using an instruction set that's on one CPU vendor and not the other CPU vendor. That's the one thing where you're probably going to see some application differences. That said, it'll probably be compatible, but you may not get that instruction set advantage in it. >> But this tool remediates against that. >> Yeah, and what we do, we're actually using VM Tools itself to go through and validate a lot of those components. So we'll look and make sure VM Tools is enabled in the first place, on the source system. And then when it gets to the destination system, we also look at VM Tools to see what is and what is not enabled. >> Okay, I'm going to put you on the spot here. What's the zinger, where doesn't it work? You already said cold, we understand, you can schedule for cold migrations, that's not a zinger. What's the zinger, where doesn't it work? >> It doesn't work like, live migrations just don't work. >> No live, okay, okay, no live. What about something else? What's the oh, you've got that version, you've got that version of X86 architecture, it-won't work, anything? >> A majority of those cases work, where it would fail, where it's going to kick back and say, hey, VM Tools is not installed. So where you would see this is if you're running a virtual appliance from some vendor, like insert vendor here that say, got a firewall, or got something like that, and they don't have VM Tools enabled. It's going to fail it out of the gate, and say, hey, VM Tools is not on this, you might want to manually do it. >> But you can figure out how to fix that? >> You can figure out how to do that. You can also, and there's a flag in there, so in kind of the options that you give it, you say, ignore VM Tools, don't care, move it anyway. So if you've got less, some VMs that are in there, but they're not a priority VM, then it's going to migrate just fine. >> Got It. >> Can you elaborate a little bit on the joint development work that AMD and VMware are doing together and the value in it for customers? >> Yeah, so it's one of those things we worked with VMware to basically produce this open source tool. So we did a lot of the core component and design and we actually engaged VMware Professional Services. And a big shout out to Austin Browder. He helped us a ton in this project specifically. And we basically worked, we created this, kind of co-designed, what it was going to look like. And then jointly worked together on the coding, of pulling this thing together. And then after that, and this is actually posted up on VMware's public repos now in GitHub. So you can go to GitHub, you can go to the VMware samples code, and you can download this thing that we've created. And it's really built to help ease migrations from one architecture to another. So if you're looking for a big data center move and you got a bunch of VMs to move. I mean, even if it's same architecture to same architecture, it's definitely going to ease the pain of going through and doing a migration of, it's one thing when you're doing 10 machines, but when you're doing 10,000 virtual machines, that's a different story. It gets to be quite operationally inefficient. >> I lose track after three. >> Yeah. >> So I'm good for three, not four. >> I was going to ask you what your target market segment is here. Expand on that a little bit and talk to me about who you're working with and those organizations. >> So really this is targeted toward organizations that have large deployments in enterprise, but also I think this is a big play with channel partners as well. So folks out there in the channel that are doing these migrations and they do a lot of these, when you're thinking about the small and mid-size organizations, it's a great fit for that. Especially if they're kind of doing that upgrade, the lift and shift upgrade, from here's where you've been five to seven years on an architecture and you want to move to a new architecture. This is really going to help. And this is not a point and click GUI kind of thing. It's command line driven, it's using PowerShell, we're using PowerCLI to do the majority of this work. And for channel partners, this is an excellent opportunity to put the value and the value add and VAR, And there's a lot of opportunity for, I think, channel partners to really go and take this. And once again, being open source. We expect this to be extensible, we want the community to contribute and put back into this to basically help grow it and make it a more useful tool for doing these cold migrations between CPU architectures. >> Have you seen any in the last couple of years of dynamics, obviously across the world, any industries in particular that are really leading edge for what you guys are doing? >> Yeah, that's really, really interesting. I mean, we've seen it, it's honestly been a very horizontal problem, pretty much across all vertical markets. I mean, we've seen it in financial services, we've seen it in, honestly, pretty much across the board. Manufacturing, financial services, healthcare, we have seen kind of a strong interest in that. And then also we we've actually taken this and presented this to some of our channel partners as well. And there's been a lot of interest in it. I think we presented it to about 30 different channel partners, a couple of weeks back about this. And I got contact from 30 different channel partners that said they're interested in basically helping us work on it. >> Tagging on to Lisa's question, do you have visibility into the AMD thought process around the timing of your next gen release versus others that are competitors in the marketplace? How you might leverage that in terms of programs where partners are going out and saying, hey, perfect time, you need a refresh, perfect time to look at AMD, if you haven't looked at them recently. Do you have any insight into that in what's going on? I know you're focused on this area. But what are your thoughts on, well, what's the buzz? What's the buzz inside AMD on that? >> Well, when you look overall, if you look at the Gartner Hype Cycle, when VMware was being broadly adopted, when VMware was being broadly adopted, I'm going to be blunt, and I'm going to be honest right here, AMD didn't have a horse in the race. And the majority of those VMware deployments we see are not running on AMD. Now that said, there's an extreme interest in the fact that we've got these very cored in systems that are now coming up on, now you're at that five to seven year refresh window of pulling in new hardware. And we have extremely attractive hardware when it comes to running virtualized workloads. The test cluster that I'm running at home, I've got that five to seven year old gear, and I've got some of the, even just the Milan systems that we've got. And I've got three nodes of another architecture going onto AMD. And when I got these three nodes completely maxed to the number of VMs that I can run on 'em, I'm at a quarter of the capacity of what I'm putting on the new stuff. So what you get is, I mean, we worked the numbers, and it's definitely, it's like a 30% decrease in the amount of resources that you need. >> That's a compelling number. >> It's a compelling number. >> 5%, 10%, nobody's going to do anything for that. You talk 30%. >> 30%. It's meaningful, it's meaningful. Now you you're out of Austin, right? >> Yes. >> So first thing I thought of when you talk about running clusters in your home is the cost of electricity, but you're okay. >> I'm okay. >> You don't live here, you don't live here, you don't need to worry about that. >> I'm okay. >> Do you have a favorite customer example that you think really articulates the value of AMD when you're in customer conversations and they go, why AMD and you hit back with this? >> Yeah. Actually it's funny because I had a conversation like that last night, kind of random person I met later on in the evening. We were going through this discussion and they were facing exactly this problem. They had that five to seven year infrastructure. It's funny, because the guy was a gamer too, and he's like, man, I've always been a big AMD fan, I love the CPUs all the way since back in basically the Opterons and Athlons right. He's like, I've always loved the AMD systems, loved the graphics cards. And now with what we're doing with Ryzen and all that stuff. He's always been a big AMD fan. He's like, and I'm going through doing my infrastructure refresh. And I told him, I'm just like, well, hey, talk to your VAR and have 'em plug some AMD SKUs in there from the Dells, HPs and Lenovos. And then we've got this tool to basically help make that migration easier on you. And so once we had that discussion and it was great, then he swung by the booth today and I was able to just go over, hey, this is the tool, this is how you use it, here's all the info. Call me if you need any help. >> Yeah, when we were talking earlier, we learned that you were at Scale. So what are you liking about AMD? How does that relate? >> The funny thing is this is actually the first time in my career that I've actually had a job where I didn't work for myself. I've been doing venture backed startups the last 25 years and we've raised couple hundred million dollars worth of investment over the years. And so one, I figured, here I am going to AMD, a larger corporation. I'm just like, am I going to be able to make it a year? And I have been here longer than a year and I absolutely love it. The culture at AMD is amazing. We still have that really, I mean, almost it's like that underdog mentality within the organization. And the team that I'm working with is a phenomenal team. And it's actually, our EVP and our Corp VP, were actually my executive sponsors, we were at a prior company. They were one of my executive sponsors when I was at Scale. And so my now VP boss calls me up and says, hey, I'm putting a band together, are you interested? And I was kind of enjoying a semi-retirement lifestyle. And then I'm just like, man, because it's you, yes, I am interested. And the group that we're in, the work that we're doing, the way that we're really focusing on forward looking things that are affecting the data center, what's going to be the data center like three to five years from now. It's exciting, and I am having a blast, I'm having the time of my life. I absolutely love it. >> Well, that relationship and the trust that you will have with each other, that bleeds into the customer conversations, the partner conversations, the employee conversations, it's all inextricably linked. >> Yes it is. >> And we want to know, you said three to five years out, like what? Like what? Just general futurist stuff, where do you think this is going. >> Well, it's interesting. >> So moon collides with the earth in 2025, we already know that. >> So we dialed this back to the Pensando acquisition. When you look at the Pensando acquisition and you look at basically where data centers are today, but then you look at where basically the big hyperscalers are. You look at an AWS, you look at their architecture, you specifically wrap Nitro around that, that's a very different architecture than what's being run in the data center. And when you look at what Pensando does, that's a lot of starting to bring what these real clouds out there, what these big hyperscalers are running into the grasps of the data center. And so I think you're going to see a fundamental shift. The next 10 years are going to be exciting because the way you look at a data center now, when you think of what CPUs do, what shared storage, how the networking is all set up, it ain't going to look the same. >> Okay, so the competing vision with that, to play devil's advocate, would be DPUs are kind of expensive. Why don't we just use NICs, give 'em some more bandwidth, and use the cheapest stuff. That's the competing vision. >> That could be. >> Or the alternative vision, and I imagine everything else we've experienced in our careers, they will run in parallel paths, fit for function. >> Well, parallel paths always exist, right? Otherwise, 'cause you know how many times you've heard mainframe's dead, tape's dead, spinning disk is dead. None of 'em dead, right? The reality is you get to a point within an industry where it basically goes from instead of a growth curve like that, it goes to a growth curve of like that, it's pretty flat. So from a revenue growth perspective, I don't think you're going to see the revenue growth there. I think you're going to see the revenue growth in DPUs. And when you actually take, they may be expensive now, but you look at what Monterey's doing and you look at the way that those DPUs are getting integrated in at the OEM level. It's going to be a part of it. You're going to order your VxRail and VSAN style boxes, they're going to come with them. It's going to be an integrated component. Because when you start to offload things off the CPU, you've driven your overall utilization up. When you don't have to process NSX on basically the X86, you've just freed up cores and a considerable amount of them. And you've also moved that to where there's a more intelligent place for that pack to be processed right, out here on this edge. 'Cause you know what, that might not need to go into the host bus at all. So you have just alleviated any transfers over a PCI bus, over the PCI lanes, into DRAM, all of these components, when you're like, but all to come with, oh, that bit needs to be on this other machine. So now it's coming in and it's making that decision there. And then you take and integrate that into things like the Aruba Smart Switch, that's running the Pensando technology. So now you got top of rack that is already making those intelligent routing decisions on where packets really need to go. >> Jason, thank you so much for joining us. I know you guys could keep talking. >> No, I was going to say, you're going to have to come back. You're going to have to come back. >> We've just started to peel the layers of the onion, but we really appreciate you coming by the show, talking about what AMD and VMware are doing, what you're enabling customers to achieve. Sounds like there's a lot of tailwind behind you. That's awesome. >> Yeah. >> Great stuff, thank you. >> It's a great time to be at AMD, I can tell you that. >> Oh, that's good to hear, we like it. Well, thank you again for joining us, we appreciate it. For our guest and Dave Nicholson, I'm Lisa Martin. You're watching "theCUBE Live" from San Francisco, VMware Explore 2022. We'll be back with our next guest in just a minute. (upbeat music)

(upbeat music) >> Good afternoon. theCUBE is live at VMware Explorer. Lisa Martin here in San Francisco with Dave Nicholson. This is our second day of coverage talking all things VMware and it's ecosystem. We're excited to welcome from DXC Technology, James Bion, Hybrid Cloud and Multi Cloud Offering manager to have a conversation next. Welcome to the program. >> Thank you very much. >> Welcome. >> Talk to us a little bit about before we get into the VMware partnership, what's new at DXC? What's going on? >> So DXC is really evolving and revitalizing into more of a cloud orientated company. So we're already driving change in our customers at the moment. We take them on that cloud journey, but we're taking them in the right way, in a structured mannered way. So we are really excited about it, we're kicking off our Cloud First type, Cloud Right sort of story and helping customers on that journey. >> Yesterday in the keynote, VMware was talking about customers are on this Cloud chaos phase, they want to get to Cloud Smart. You're saying they want to get to Cloud Right. Talk to us about what DXC Cloud Right is, what does it mean? What does it enable businesses to achieve? >> That's a very good question. So DXC has come up with this concept of Cloud Right, we looked at it from a services and outcome. So what do customers want to achieve? And how do we get it successfully? This is not a technology conversation, this is about putting the right workloads at the right place, at the right time, at the right cost to get the right value for your business. It's not about just doing it for the sake of doing it, okay. There's a lot of changes it's not technology only you've got to change how people operate. You've got to work through the organizational change. You need to ensure that you have the right security in place to maintain it. And it's about value, really about value proposition. So we don't just focus on cost, we focus on operations of it, we focus on security of it. We focus on ensuring the value proposition of it and putting not just for one Cloud, it's the right place. Big focus on Hybrid and Multi Cloud solutions in particular, we're very excited about what's happening with VMware Cloud on maybe AWS or et cetera because we see there a real dynamic change for our customers where they can transition across to the right Cloud services, at the right time, at the right place, but minimal disruption to the actual operation of their business. Very easy to move a workload into that place using the same skilled resources, the same tools, the same environment that you have had for many years, the same SLAs. Customers don't want a variance in their SLAs, they just want an outcome at a right price and the right time. >> Right, what are some of the things going on with the VMware partnership and anything you know, here we are at this the event called the theme is "The Center of the Multi Cloud Universe", which I keep saying sounds like a Marvel movie, I think there needs to be some superheroes here. But how is DXC working with VMware to help customers that are in Multi Cloud by default, not by design? >> That's a very good one. So DXC works jointly with VMware for more than a thousand clients out there. Wide diversity of different clients. We go to market together, we work collaboratively to put roadmaps in place for our clients, it's a unified team. On top of that, we have an extremely good VMware practice, joint working VMware team working directly with DXC dedicated resources and we deliver real value for clients. For example, we have a customer experience zone, we have a customer innovation zone so we can run proof of concepts on all the different VMware technologies for customers. If they want to try something different, try and push the boundaries a little bit with the VMware products, we can do that for them. But at the end of the day we deliver outcome based services. We are not there to deliver a piece of software, but a technology which show the customer the value of the service that they've been receiving within that. So we bring the VMware fantastic technologies in and then we bring the DXC managed services which we do so well and we look after our customers and do the right thing for our customers. >> So what does the go-to market strategy look like from a DXC perspective? We say that there are a finite number of strategic seats at the customer table. DXC has longstanding deep relationships with customers, so does VMware and probably over a shorter period of time, the Hyper scale Cloud Providers. How are you approaching these relationships with customers? Is it you bringing in your friends from the cloud? Is it the cloud bringing in their friend DXC? What does it look like? >> So we have relationships with all of them, but were agnostic. So we are the people who bring it all together into that unified platform and services that the customers expect. VMware will bring us certainly to the table and we'll bring VMware to the table. Equally, we work very collaboratively with all the cloud providers and we work in deals together. They bring us deals, we bring them deals. So it works extremely well from that perspective, but of course it's a multi-cloud world these days. We don't just deal with one cloud provider, we'll normally have all of the different services to find the right place for our customers. >> Now, one thing that that's been mentioned from DXC is this idea that Cloud First which has been sort of a mantra that scores you points if you're a CIO lately, maybe that's not the best way to wake up in the morning. Why not saying, Cloud First? >> So we have a lot of clients who who've tried that Cloud First journey and they've aggressively taken on migration of workloads. And now that they've settled in a few of those they're discovering maybe the ROI isn't quite what they expected it was going to be. That transformation takes a long time, a very long time. We've seen some of the numbers around averaging a hundred apps can take up to seven years to transition and transform, that's a long time. It makes you almost less agile by doing the transformation quite ironically. So DXC's Cloud Right program really helps you to ensure that you assess those workloads correctly, you target the ones that are going to give you the best business value, possibly the best return on investment using our Cloud and advisory practice to do that. And then obviously off the back of that we've got our migration teams and our run services and our application modernization factories and our application platforms for that. So DXC Cloud Right can certainly help our customers on that journey and get that sort of Hybrid Multi Cloud solution that suits their particular outcomes, not just one Cloud provider. >> So Cloud Right isn't just Cloud migration? >> No. >> People sometimes confuse digital transformation with Cloud migration. >> Correct. >> So to be clear Cloud Right and DXC has the ability to work with customers on not just, oh, here, this is how we box it up and ship it out, but what makes sense to box up and ship out. >> Correct, and it's all about that whole end to end life cycle. Remember, this is not just a technology conversation, this is an end to end business conversation. It's the outcomes are important, not the technology. That's why you have good partners like DXC who will help you on that technology journey. >> Let's talk about in the dynamics of the market the last couple of years, we saw so many customers in every industry race to the Cloud, race to digitally transform. You bring up a good point of people interchangeably talking about digital transformation, Cloud migration, but we saw the massive adoption of SaaS technologies. What are you seeing? Are you seeing customers in that sort of Cloud chaos as VMware calls it? That you're coming in with the Cloud Right approach saying, let's actually figure out, you may have done this because of the pandemic maybe it was accelerated, you needed to facilitate collaboration or whatnot, but actually this is the right approach. Are you seeing a lot of customers in that situation? >> We are certainly seeing some customers going into that chaos world. Some of them are still in the early stages of their journey and are taking a more cautious step towards in particular, the companies that would die on systems to be up available all the time. Others have gone too far, the other are in extreme are in the chaos world. And our Cloud Right program will certainly help them to pull their chaos back in, identify what workloads are potentially running in the wrong place, get the framework in place for ensuring that security and governance is in place. Ensuring that we don't have a cost spend blowout in particular, make sure that security is key to everything that we do and operations is key to everything we do. We have our own intelligent Platform X, it's called, our service management platform which is really the engine that sits behind our delivery mechanism. And that's got a whole lot of AI analytics engines in there to identify things and proactively identify workload placements, workload repairs, scripting, and hyper automation behind that too, to keep available here and there. And that's really some of our Cloud Right story, it's not just sorting out the mess, it's sorting out and then running it for you in the right way. >> So what does a typical, a customer engagement look like for a customer in that situation? >> So we would obviously engage our client right advisory team and they would come in and sit down with your application owners, sit down with the business units, identify what success needs to look like. They do all the discovery, they'll run it through our engines to identify what workloads are in the right place, should go to the right place. Just 'cause you can do something doesn't mean you should do something and that's an important thing. So we will come back with that and say, this is where I think your cloud roadmap journey should be. And obviously that takes an intuitive process, but we then can pick off the key topics early at the right time and that low hanging fruit that's really going to drive that value for the customer. >> And where are your customer conversations these days? I mean from a Cloud perspective, digital transformation, we're seeing everything escalate up the C-suite? Are you engaging the executives in this conversation so that they really want to facilitate, let's do things the right way that's the most efficient that allows us as a business to do what we're best at? >> So where we've seen programs fail is where we don't have executive leadership and brought in from day one. So if you don't have that executive and business driver and business leadership, then you're definitely not going to be successful. So to answer your question, yes, of course we are, but we also working directly with the IT departments as well. >> So you just brought up an insight executive alignment, critically important. Based on what you've experienced in the real world, contrast that with the sort of message to the world that we hear constantly about Cloud and IT, what would be the most shocking thing that you can share with us that people might not be aware of? It's like what shocks you the most about the disconnect between what everybody talks about and the reality on the ground? Don't name any names of anyone, but give us an example of the like, this is what's really going on. >> So, we certainly are seeing that big sort of move into Cloud quickly, okay. And then the big bill shock comes and just moving a workload across doesn't mean you're in Cloud, it's a transition and transformation to the SaaS and power services, it's where you get your true value out of cloud. So the concept that just 'cause it's in Cloud it's cheap is not always the case. Doing it right in Cloud is definitely going to have some cost value, but it's going to bring other additional values to their business. It's going to give them agility, it's going to give them resilience. So if you look at all three of those platforms cost, agility, and resilience and live across all three of those, then you're definitely going to get the best outcomes. And we've certainly seen some of those where they haven't taken all of those into consideration, quite often it's cost is what drives it, not the other two. And if you can't keep operations up working efficiently then you are in a lot of trouble. >> So Cloud wrong comes with sticker shock. >> It certainly does. >> What's on the horizon for DXC? >> We're certainly seeing a big drive towards apps modernization and certainly help our customers on that journey. DXC is definitely a Cloud company, may that be on Hybrid Cloud, Private Cloud, Public Cloud, DXC is certainly leading that edge and pushing it forward. >> Excellent, James, thank you so much for joining us on the program today talking about what Cloud Right is, the right approach, how you're helping customers really get to that right approach with the people, the processes, and the technology. We appreciate your time. >> Thank you very much. >> For our guest and Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live from VMware Explorer, 2022. Our next guest joins us momentarily so don't change the channel. (upbeat music)

(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase. Topic is MarTech: Emerging Cloud-Scale Experience. This is season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. Talk about their value proposition and their company and all the good stuff that's going on. I'm your host, John Furrier. And today we're excited to be joined by Manyam Mallela who's the co-founder and head of AI at Blueshift. Great to have you on here to talk about the Blueshift-Intelligent Customer Engagement, Made Simple. Thanks for joining us today. >> Thank you, John. Thank you for having me. >> So last time we did our intro video. We put it out in the web. Got great feedback. One of the things that we talked about, which is resonating out there in the viral Twitter sphere and in the thought leadership circles is this concept that you mentioned called 10X marketer. That idea that you have a solution that can provide 10X value. Kind of a riff on the 10X engineer in the DevOps cloud world. What does it mean? And how does someone get there? >> Yeah, fantastic. I think that's a great way to start our discussion. I think a lot of organizations, especially as of this current economic environment are looking to say, I have limited resources, limited budgets, how do I actually achieve digital and customer engagement that helps move the needle for my key metrics, whether it's average revenue per user, lifetime value of the user and frequent interactions. Above all, the more frequently a brand is able to interact with their customers, the better they understand them, the better they can actually engage them. And that usually leads to long term good outcomes for both customer and the brand and the organizations. So the way I see 10X marketer is that you need to have tools that give you that speed and agility without hindering your ability to activate any of the campaigns or experience that you want to create. And I see the roadblocks usually for many organizations, is that kind of threefold. One is your data silos. Usually data that is on your sites, does not talk to your app data, does not talk to your social data, does not talk to your CRM data and so forth. So how do I break those silos? The second is channel silos. I actually have customers who are only engaging on email or some are on email and mobile apps. Some are on email and mobile apps and maybe the OTT TV in a Roku or one of the connected TV experiences, or maybe in the future, another Web3 environments. How do I actually break those channel silos so that I get a comprehensive view of the customer and my marketing team can engage with all of them in respect to the channel? So break the channel silos. And the last part, what I call like some of the little talked about is I call the inside silo, which is that, not only do you need to have the data, but you also have to have a common language to share and talk about within your organizations. What are we learning from our customers? What do we translate our learning and insight on this common data platform or fabric into an action? And that requires the shared language of how do I actually know my customers and what do I do with them? Like either the inside silo as well. I think a lot of times organizations do get into this habit like each one speaks their own language, but they don't actually are talking the common language of what did we actually know about the real customer there. >> Yeah, and I think that's a great conversation because there's two, when you hear 10X marketer or 10X conversations, it implies a couple things. One is you're breaking an old way and bringing in something new. And the new is a force multiplier, in this case, 10X marketer. But this is the cloud scale so marketing executives, chiefs, staffs, chiefs of staffs of CMOs and their staffs. They want to get that scale. So marketing at scale is now the table stakes. Now budget constraints are there as well. So you're starting to see, okay, I need to do more with less. Now the big question comes up is ROI. So I want to have AI. I want to have all these force multipliers. What do I got to do with the old? How do I handle that? How do I bring the new in and operationalize it? And if that's the case, I'm making a change. So I have to ask you, what's your view on the ROI of AI marketing, because this is a key component 'cause you've got scale factor here. You've got to force multiplier opportunity. How do you get that ROI on the table? >> I think that as you rightly said, it's table stakes. And I think the ROI of AI marketing starts with one very key simple premise that today some of the tools allow you to do things one at a time. So I can actually say, "can I run this campaign today?" And you can scramble your team, hustle your way, get everybody involved and run that campaign. And then tomorrow I'd say like, Hey, I looked at the results. Can I do this again? And they're like, oh, we just asked for all of us to get that done. How do I do it tomorrow? How do I do it next week? How do I do it for every single week for the rest of the year? That's where I think the AI marketing is essentially taking your insight, taking your creativity, and creating a platform and a tool that allows you to run this every single day. And that's agility at scale. That is not only a scale of the customer base, but scale across time. And that AI-based automation is the key ROI piece for a lot of AI marketing practitioners. So Forrester, for example, did a comprehensive total economic impact study with our customers. And what they found out was actually the 781% ROI that they reported in that particular report is based on three key factors. One is being able to do experiences that are intelligent at scale, day in and day out. So do your targeting, do your recommendations. Not just one day, but do it every single day. And don't hold back yourself on being able to do that. >> I think they got to get the return. They got to get the sales too. This is the numbers. >> That's right. They actually have real dollars, real numbers attached to it. They have a calculator. You can actually go in and plug your own numbers and get what you might expect from your existing customer base. The second is that once you have a unified platform like ours, the 10X marketer that we're talking about is actually able to do more. It's sometimes actually, it's kind of counterintuitive to think that a smaller team does more. But in reality, what we have seen, that is the case. When you actually have the right tools, the smaller teams actually achieve more. And that's the redundant operations, conflicting insights that go away into something more coherent and comprehensive. And that's the second insight that they found. And the third is just having reporting and all of the things in one place means that you can amplify it. You can amplify it across your paid media channels. You can amplify it across your promotions programs and other partnerships that you're running. >> That's the key thing about platforms that people don't understand is that you have a platform and it enables a lot of value. In this case, force multiplier value. It enables more value than you pay for it. But the key is it enables customers to do things without a line of code, meaning it's a platform. They're innovating on top of it. And that's, I think, where the ROI comes in and this leads me where the next question is. I wanted to ask you is, not to throw a wet blanket on the MarTech industry, but I got to think of when I hear marketing automation, I kind of think old. I think old, inadequate antiquated technologies. I think email blasting and just some boring stuff that just gets siloed or it's bespoke from something else. Are marketing automation tools created equal? Does something like, what you guys are doing with SmartHub? Change that, and can you just talk about that 'cause it's not going to go away. It's just another level that's going to be abstracted away under the coverage. >> Yeah, great question. Certainly, email marketing has been practiced for two or three decades now and in some form or another. I think we went from essentially what people call list-based marketing. I have a list, let me keep blasting the same message to everybody and then hopefully something will come out of it. A little bit more of saying, then they can, okay, maybe now I have CRM database and can I do database marketing, which they will call like, "Hey, Hi John. Hi Manyam", which is the first name. And that's all they think will get the customer excited about because you'll call them by name, which is certainly helpful, but not enough. I think now what we call like, the new age that we live in is that we call it graph-based marketing. And the way we materialize that is that every single user is interacting with a brand with their offerings. So that this interaction graph that's happening across millions of customers, across thousands of content articles, videos, shows, products, items, and that graph actually has much richer knowledge of what the customer wants than the first names or list-based ones. So I think the next evolution of marketing automation, even though the industry has been there a while, there is a step change in what can actually be done at scale. And which is taking that interaction graph and making that a part of the experience for the customer, and that's what we enable. That's why we do think of that as a big step change from how people are being practicing list-based marketing. And within that, certainly there is a relation of curve as to how people approach AI marketing and they are in a different spectrum. Some people are still at list-based marketing. Some people are database marketing. And hopefully will move them to this new interaction graph-based marketing. >> Yeah and I think the context is key. I like how you bring up the graph angle on this because the graph databases imply there's a lot of different optionality around what's happened contextually both over time and currently and it adds to it. Makes it smarter. It's not just siloed, just one dimensional. It feels like it's got a lot there. This is clearly I'm a big fan of and I think this is the way to go. As you get more personalization, you get more data. Graphic database makes a lot of sense. So I have to ask you, this is a really cutting edge value proposition, who are the primary buyers and users in an organization that you guys are working with? >> Yeah, great question. So we typically have CMO organizations approaching us with this problem and they usually talk to their CIO organizations, their counterparts, and the chief information officers have been investing in data fabrics, data lakes, data warehouses for the better part of last decade or two, and have some very cutting edge technology that goes into organizing all this data. But that doesn't still solve the problem of how do I take this data and make a meaningful, relevant, authentic experience for the customer. That's the CMO problem. And CMO are now challenge with creating product level experience with every interaction and that's where we coming. So the CMO are the buyers of our SmartHub CDP platform. And we're looking for consolidating hundreds of tools that they had in the past and making that one or two channel marketers. Actually, the 10X marketer that we talk about. And you need the right tool on top of your data lakes and data warehouses to be able to do that. So CMO are also the real drivers of using this technology. >> I think that also place the ROI equation around ROI and having that unified platform. Great call out there. I got to ask you the question here 'cause this comes up a lot and when I hear you talking, I think, okay, all the great stuff you guys have there. But if I'm a company, I want to make my core competencies mine. I don't really want to outsource or buy something that's going to be core to my business. But at the same time as market shifts, the business changes. And sometimes people don't even know what business they're in at the end of the day. And as it gets more complicated too, by the way. So the question comes up with companies and I can see this clearly, do I buy it? Do I build it? When it comes to AI because that's a core competency. Wait a minute, AI. I'm going to maybe buy some chatbot technology. That's not really AI, but it feels like AI, but I'm a company, I want to buy it or build it. That's a choice. What do you see there? 'Cause you guys have a very comprehensive platform. It's hard to replicate, imitates, inimitable. So what's your customers doing with respect buy and build? And where do they get the core competency? What do they get to have as a core competency? >> Fantastic. I think certainly, AI as it applies to at the organization level, I've seen this at my previous organization that I was part of, and there will be product and financial applications that are using AI for the service of that organization. So we do see, depending upon the size of the organization having in-house AI and data science teams. They are focused on these long term problems that they are doing as part of their product itself. Adjacent to that, the CMO organization gets some resources, but not certainly a lot. I think the CMO organization is usually challenged with the task, but not given the hundred people data science and engineering team to be able to go solve that. So what we see among our customer base is that they need agile platform to do most of the things that they need to do on a day to day basis, but augmented with what our in-house data science they have. So we are an extensible platform. What we have seen is that half of our customers use us solely for the AI needs. The other half certainly uses both AI modules that we provide and are actually augmented with things that they've already built. And we do not have a fight in that ring. But we do acknowledge and we do provide the right hooks for getting the data out of our system and bringing their AI back into our system. And we think that at the end of the day, if you want agility for the CMO, there should not be any barriers. >> It's like they're in the data business and that's the focus. So I think with what I hear you saying is that with your technology and platform, you're enabling to get them to be in the data business as fast as possible. >> That's right. >> Versus algorithm business, which they could add to over time. >> Certainly they could add to. But I think the bulk of competencies for the CMO are on the creative side. And certainly wrangling with data pipelines day in and day out and wondering what actually happened to a pipeline in the middle of the night is not probably what they would want to focus on. >> Not their core confidence. Yeah, I got that. >> That's right. >> You can do all the heavy lifting. I love that. I got to ask you on the Blueshift side on customer experience consumption. how can someone experience the product before buying? Is there a trial or POC? What's the scale and scope of operationalizing and getting the Blueshift value proposition in them? >> Yeah, great. So we actually recently released a fantastic way to experience our product. So if you go to our website, there's only one call-to-action saying, explore Blueshift. And if you click on that, without asking, anything other than your business email address, you're shown the full product. You're given a guided tour of all the possibilities. So you can actually experience what your marketing team would be doing in the product. And they call it Project Rover. We launched it very recently and we are seeing fantastic reception to that. I think a lot of times, as you said, there is that question mark of like, I have a marketing team that is already doing X, Y, Z. Now you are asking me to implement Blueshift. How would they actually experience the product? And now they can go in and experience the product. It's a great way to get the gist of the product in 10 clicks. Much more than going through any number of videos or articles. I think people really want to say, let me do those 10 clicks. And I know what impression that I can get from platform. So we do think that's a great way to experience the product and it's easily available from the main website. >> It's in the value proposition. It isn't always a straight line. And you got that technology. And I got to ask from between your experience with the customers that you're talking to, prospects, and customers, where do you see yourself winning deals on Customer Engagement, Made Simple because the word customer engagement's been around for a while, and it's become, I won't say cliche, but there's been different generational evolutions of technology that made that possible. Obviously, we're living in an era of high velocity Omni-Channel, a lot of data, the graph databases you mentioned are in there, big part of it. Where are you winning deals? Where are customers pain points where you are solving that specifically? >> Yeah, great question. So the organizations that come to us usually have one of the dimensions of either they have offering complexity, which is what catalog of content or videos or items do they offer to the customers. And on the data complexity on the other side is to what the scale of customer base that I usually target. And that problem has not gone away. I think the customer engagement, even though has been around for a while, the problem of engaging those customers at scale hasn't gone away and it only is getting harder and harder and organizations that have, especially on what we call the business-to-consumer side where the bulk of what marketing organizations in a B2C segments are doing. I have tens to millions of customers and how do I engage them day in and day out. And I think that all that problem is only getting harder because consumer preferences keeps shifting all the time. >> And where's your sweet spot for your customer? What size? Can you just share the target organization? Is it medium enterprise, large B2C, B2B2C? What's the focus area? >> Yeah, great question. So we have seen like startups that are in Silicon Valley. I have now half a million monthly active users, how do I actually engage them to customers and clients like LendingTree and PayPal and Discovery and BBC who have been in the business for multiple decades, have tens of millions of customers that they're engaging with. So that's kind of our sweet spot. We are certainly not maybe for small shop with maybe a hundred plus customers. But as you reach the scale of tens of thousands of customers, you start seeing this problem. And then you start to look out for solutions that are beyond, especially list-based marketing and email blast. >> So as the scale, you can dial up and down, but you have to have some enough scale to get the data pattern. >> That's right. >> If I can connect the dots there. >> I would probably say, looking at a hundred thousand or more monthly active customer base, and then you're trying to ramp up your own growth based on what you're learning and to engage those customers. >> It's like a bulldozer. You need the heavy equipment. Great conversation. For the last minute we have here Manyam, give you a plug for the company. What's going on? What are you guys doing? What's new? Give some success stories, your latest achievements. Take a minute to give a plug for the company. >> Yeah, great. We have been recognized by Deloitte as the fastest growth startup two years in a row and continuing to be on that streak. We have released currently integrations with AWS partners and Snowflake partners and data lake partners that allow implementing Blueshift a much streamlined experience with bidirectional integrations. We have now hundred plus data connectors and data integrations in our system and that takes care of many of our needs. And now, I think organizations that have been budget constraint and are trying to achieve a lot with a small team are actually going to look at these solutions and say, "Can I get there?" and "Can I become that 10X marketing organization? And as you have said, agility at scale is very, very hard to achieve. Being able to take your marketing team and achieve 10X requires the right platform and the right solution. We are ready for it. >> And every company's in the data business that's the asset. You guys make that sing for them. It's good stuff. Love the 10X. Love the scale. Manyam Mallela, thanks for coming on. Co-founder, Head of AI at Blueshift. This is the AWS Startup Showcase season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. I'm John Furrier, your host. Thanks for watching. >> Thank you, John. (upbeat music)

(introductory riff) >> Hey everyone. Welcome to theCUBE's presentation of the "AWS Startup Showcase." This is Season 2, Episode 3 of our ongoing series that features great partners in the massive AWS partner ecosystem. This series is focused on, "MarTech, Emerging Cloud-Scale Customer Experiences." I'm Lisa Martin, and I've got two guests here with me to talk about this. Please welcome Daisy Urfer, Cloud Alliance Sales Director at Algolia, and Jason Lang, the Head of Product for Apply Digital. These folks are here to talk with us today about how Algolia's Search and Discovery enables customers to create dynamic realtime user experiences for those oh so demanding customers. Daisy and Jason, it's great to have you on the program. >> Great to be here. >> Thanks for having us. >> Daisy, we're going to go ahead and start with you. Give the audience an overview of Algolia, what you guys do, when you were founded, what some of the gaps were in the market that your founders saw and fixed? >> Sure. It's actually a really fun story. We were founded in 2012. We are an API first SaaS solution for Search and Discovery, but our founders actually started off with a search tool for mobile platforms, so just for your phone and it quickly expanded, we recognize the need across the market. It's been a really fun place to grow the business. And we have 11,000 customers today and growing every day, with 30 billion searches a week. So we do a lot of business, it's fun. >> Lisa: 30 billion searches a week and I saw some great customer brands, Locost, NBC Universal, you mentioned over 11,000. Talk to me a little bit about some of the technologies, I see that you have a search product, you have a recommendation product. What are some of those key capabilities that the products deliver? 'Cause as we know, as users, when we're searching for something, we expect it to be incredibly fast. >> Sure. Yeah. What's fun about Algolia is we are actually the second largest search engine on the internet today to Google. So we are right below the guy who's made search of their verb. So we really provide an overall search strategy. We provide a dashboard for our end users so they can provide the best results to their customers and what their customers see. Customers want to see everything from Recommend, which is our recommended engine. So when you search for that dress, it shows you the frequently bought together shoes that match, things like that, to things like promoted items and what's missing in the search results. So we do that with a different algorithm today. Most in the industry rank and they'll stack what you would want to see. We do kind of a pair for pair ranking system. So we really compare what you're looking for and it gives a much better result. >> And that's incredibly critical for users these days who want results in milliseconds. Jason, you, Apply Digital as a partner of Algolia, talk to us about Apply Digital, what it is that you guys do, and then give us a little bit of insight on that partnership. >> Sure. So Apply Digital was originally founded in 2016 in Vancouver, Canada. And we have offices in Vancouver, Toronto, New York, LA, San Francisco, Mexico city, Sao Paulo and Amsterdam. And we are a digital experiences agency. So brands and companies, and startups, and all the way from startups to major global conglomerates who have this desire to truly create these amazing digital experiences, it could be a website, it could be an app, it could be a full blown marketing platform, just whatever it is. And they lack either the experience or the internal resources, or what have you, then they come to us. And and we are end-to-end, we strategy, design, product, development, all the way through the execution side. And to help us out, we partner with organizations like Algolia to offer certain solutions, like an Algolia's case, like search recommendation, things like that, to our various clients and customers who are like, "Hey, I want to create this experience and it's going to require search, or it's going to require some sort of recommendation." And we're like, "Well, we highly recommend that you use Algolia. They're a partner of ours, they've been absolutely amazing over the time that we've had the partnership. And that's what we do." And honestly, for digital experiences, search is the essence of the internet, it just is. So, I cannot think of a single digital experience that doesn't require some sort of search or recommendation engine attached to it. So, and Algolia has just knocked it out of the park with their experience, not only from a customer experience, but also from a development experience. So that's why they're just an amazing, amazing partner to have. >> Sounds like a great partnership. Daisy, let's point it back over to you. Talk about some of those main challenges, Jason alluded to them, that businesses are facing, whether it's e-commerce, SaaS, a startup or whatnot, where search and recommendations are concerned. 'Cause we all, I think I've had that experience, where we're searching for something, and Daisy, you were describing how the recommendation engine works. And when we are searching for something, if I've already bought a tent, don't show me more tent, show me things that would go with it. What are some of those main challenges that Algolia solution just eliminates? >> Sure. So I think, one of the main challenges we have to focus on is, most of our customers are fighting against the big guides out there that have hundreds of engineers on staff, custom building a search solution. And our consumers expect that response. You expect the same search response that you get when you're streaming video content looking for a movie, from your big retailer shopping experiences. So what we want to provide is the ability to deliver that result with much less work and hassle and have it all show up. And we do that by really focusing on the results that the customers need and what that view needs to look like. We see a lot of our customers just experiencing a huge loss in revenue by only providing basic search. And because as Jason put it, search is so fundamental to the internet, we all think it's easy, we all think it's just basic. And when you provide basic, you don't get the shoes with the dress, you get just the text response results back. And so we want to make sure that we're providing that back to our customers. What we see average is even, and everybody's going mobile. A lot of times I know I do all my shopping on my phone a lot of the time, and 40%-50% better relevancy results for our customers for mobile users. That's a huge impact to their use case. >> That is huge. And when we talked about patients wearing quite thin the last couple of years. But we have this expectation in our consumer lives and in our business lives if we're looking for SaaS or software, or whatnot, that we're going to be able to find what we want that's relevant to what we're looking for. And you mentioned revenue impact, customer churn, brand reputation, those are all things that if search isn't done well, to your point, Daisy, if it's done in a basic fashion, those are some of the things that customers are going to experience. Jason, talk to us about why Algolia, what was it specifically about that technology that really led Apply Digital to say, "This is the right partner to help eliminate some of those challenges that our customers could face?" >> Sure. So I'm in the product world. So I have the wonderful advantage of not worrying about how something's built, that is left, unfortunately, to the poor, poor engineers that have to work with us, mad scientist, product people, who are like, "I want, make it do this. I don't know how, but make it do this." And one of the big things is, with Algolia is the lift to implement is really, really light. Working closely with our engineering team, and even with our customers/users and everything like that, you kind of alluded to it a little earlier, it's like, at the end of the day, if it's bad search, it's bad search. It just is. It's terrible. And people's attention span can now be measured in nanoseconds, but they don't care how it works, they just want it to work. I push a button, I want something to happen, period. There's an entire universe that is behind that button, and that's what Algolia has really focused on, that universe behind that button. So there's two ways that we use them, on a web experience, there's the embedded Search widget, which is really, really easy to implement, documentation, and I cannot speak high enough about documentation, is amazing. And then from the web aspect, I'm sorry, from the mobile aspect, it's very API fort. And any type of API implementation where you can customize the UI, which obviously you can imagine our clients are like, "No we want to have our own front end. We want to have our own custom experience." We use Algolia as that engine. Again, the documentation and the light lift of implementation is huge. That is a massive, massive bonus for why we partnered with them. Before product, I was an engineer a very long time ago. I've seen bad documentation. And it's like, (Lisa laughing) "I don't know how to imple-- I don't know what this is. I don't know how to implement this, I don't even know what I'm looking at." But with Algolia and everything, it's so simple. And I know I can just hear the Apply Digital technology team, just grinding sometimes, "Why is a product guy saying that (mumbles)? He should do it." But it is, it just the lift, it's the documentation, it's the support. And it's a full blown partnership. And that's why we went with it, and that's what we tell our clients. It's like, listen, this is why we chose Algolia, because eventually this experience we're creating for them is theirs, ultimately it's theirs. And then they are going to have to pick it up after a certain amount of time once it's theirs. And having that transition of, "Look this is how easy it is to implement, here is all the documentation, here's all the support that you get." It just makes that transition from us to them beautifully seamless. >> And that's huge. We often talk about hard metrics, but ease of use, ease of implementation, the documentation, the support, those are all absolutely business critical for the organization who's implementing the software, the fastest time to value they can get, can be table stakes, and it can be on also a massive competitive differentiator. Daisy, I want to go back to you in terms of hard numbers. Algolia has a recent force or Total Economic Impact, or TEI study that really has some compelling stats. Can you share some of those insights with us? >> Yeah. Absolutely. I think that this is the one of the most fun numbers to share. We have a recent report that came out, it shared that there's a 382% Return on Investment across three years by implementing Algolia. So that's increase to revenue, increased conversion rate, increased time on your site, 382% Return on Investment for the purchase. So we know our pricing's right, we know we're providing for our customers. We know that we're giving them the results that we need. I've been in the search industry for long enough to know that those are some amazing stats, and I'm really proud to work for them and be behind them. >> That can be transformative for a business. I think we've all had that experience of trying to search on a website and not finding anything of relevance. And sometimes I scratch my head, "Why is this experience still like this? If I could churn, I would." So having that ability to easily implement, have the documentation that makes sense, and get such high ROI in a short time period is hugely differentiated for businesses. And I think we all know, as Jason said, we measure response time in nanoseconds, that's how much patience and tolerance we all have on the business side, on the consumer side. So having that, not just this fast search, but the contextual search is table stakes for organizations these days. I'd love for you guys, and on either one of you can take this, to share a customer example or two, that really shows the value of the Algolia product, and then also maybe the partnership. >> So I'll go. We have a couple of partners in two vastly different industries, but both use Algolia as a solution for search. One of them is a, best way to put this, multinational biotech health company that has this-- We built for them this internal portal for all of their healthcare practitioners, their HCPs, so that they could access information, data, reports, wikis, the whole thing. And it's basically, almost their version of Wikipedia, but it's all internal, and you can imagine the level of of data security that it has to be, because this is biotech and healthcare. So we implemented Algolia as an internal search engine for them. And the three main reasons why we recommended Algolia, and we implemented Algolia was one, HIPAA compliance. That's the first one, it's like, if that's a no, we're not playing. So HIPAA compliance, again, the ease of search, the whole contextual search, and then the recommendations and things like that. It was a true, it didn't-- It wasn't just like a a halfhearted implementation of an internal search engine to look for files thing, it is a full blown search engine, specifically for the data that they want. And I think we're averaging, if I remember the numbers correctly, it's north of 200,000 searches a month, just on this internal portal specifically for their employees in their company. And it's amazing, it's absolutely amazing. And then conversely, we work with a pretty high level adventure clothing brand, standard, traditional e-commerce, stable mobile application, Lisa, what you were saying earlier. It's like, "I buy everything on my phone," thing. And so that's what we did. We built and we support their mobile application. And they wanted to use for search, they wanted to do a couple of things which was really interesting. They wanted do traditional search, search catalog, search skews, recommendations, so forth and so on, but they also wanted to do a store finder, which was kind of interesting. So, we'd said, all right, we're going to be implementing Algolia because the lift is going to be so much easier than trying to do everything like that. And we did, and they're using it, and massively successful. They are so happy with it, where it's like, they've got this really contextual experience where it's like, I'm looking for a store near me. "Hey, I've been looking for these items. You know, I've been looking for this puffy vest, and I'm looking for a store near me." It's like, "Well, there's a store near me but it doesn't have it, but there's a store closer to me and it does have it." And all of that wraps around what it is. And all of it was, again, using Algolia, because like I said earlier, it's like, if I'm searching for something, I want it to be correct. And I don't just want it to be correct, I want it to be relevant. >> Lisa: Yes. >> And I want it to feel personalized. >> Yes. >> I'm asking to find something, give me something that I am looking for. So yeah. >> Yeah. That personalization and that relevance is critical. I keep saying that word "critical," I'm overusing it, but it is, we have that expectation that whether it's an internal portal, as you talked about Jason, or it's an adventure clothing brand, or a grocery store, or an e-commerce site, that what they're going to be showing me is exactly what I'm looking for, that magic behind there that's almost border lines on creepy, but we want it. We want it to be able to make our lives easier whether we are on the consumer side, whether we on the business side. And I do wonder what the Go To Market is. Daisy, can you talk a little bit about, where do customers go that are saying, "Oh, I need to Algolia, and I want to be able to do that." Now, what's the GTM between both of these companies? >> So where to find us, you can find us on AWS Marketplace which another favorite place. You can quickly click through and find, but you can connect us through Apply Digital as well. I think, we try to be pretty available and meet our customers where they are. So we're open to any options, and we love exploring with them. I think, what is fun and I'd love to talk about as well, in the customer cases, is not just the e-commerce space, but also the content space. We have a lot of content customers, things about news, organizations, things like that. And since that's a struggle to deliver results on, it's really a challenge. And also you want it to be relevant, so up-to-date content. So it's not just about e-commerce, it's about all of your solution overall, but we hope that you'll find us on AWS Marketplace or anywhere else. >> Got it. And that's a great point, that it's not just e-commerce, it's content. And that's really critical for some industry, businesses across industries. Jason and Daisy, thank you so much for joining me talking about Algolia, Apply Digital, what you guys are doing together, and the huge impact that you're making to the customer user experience that we all appreciate and know, and come to expect these days is going to be awesome. We appreciate your insights. >> Thank you. >> Thank you >> For Daisy and Jason, I'm Lisa Martin. You're watching "theCUBE," our "AWS Startup Showcase, MarTech Emerging Cloud-Scale Customer Experiences." Keep it right here on "theCUBE" for more great content. We're the leader in live tech coverage. (ending riff)

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

>>Everyone welcome back from the cubes coverage here in Las Vegas for Aus re Mars. It's one of the re shows, as we know, reinvent is the big show. Now they have focus, shows reinforces coming up that security Remar is here. Machine learning, automation, robotics, and space. I'm John for your host, Michael Mike Miller here, director of machine learning thought leadership with AWS. Great to see you again. Yeah. Give alumni welcome back here. Back every time we got deep racer, always to talk >>About, Hey John, thanks for having me once again. It's great to be here. I appreciate it. >>So I want to get into the deep racer in context here, but first re Mars is a show. That's getting a lot of buzz, a lot of press. Um, not a lot of news, cuz it's not a newsy show. It's more of a builder kind of a convergence show, but a lot is happening here. It's almost a, a moment in time that I think's gonna be one of those timeless moments where we're gonna look back and saying that year at re Mars was an inflection point. It just seems like everything's pumping machine learning, scaling robotics is hot. It's now transforming fast. Just like the back office data center did years ago. Yeah. And so like a surge is coming. >>Yeah. >>What, what's your take of this show? >>Yeah. And all of these three or four components are all coming together. Right. And they're intersecting rather than just being in silos. Right. So we're seeing machine learning, enabled perception sort of on robots, um, applied to space and sort of these, uh, extra sort of application initiatives. Um, and that's, what's really exciting about this show is seeing all these things come together and all the industry-wide examples, um, of amazing perception and robotics kind of landing together. So, >>So the people out there that aren't yet inside the ropes of the show, what does it mean to them? This show? What, what, what they're gonna be what's in it for me, what's all this show. What does it mean? >>Yeah. It's just a glimpse into where things are headed. Right. And it's sort of the tip of the iceberg. It's sort of the beginning of the wave of, um, you know, these sort of advanced capabilities that we're gonna see imbued in applications, um, across all different industries. >>Awesome. Well, great to have you in the cube. Every time we have an event we wanna bring you on because deep racers become a, the hottest, I won't say cult following because it's no longer cult following. It's become massive following. Um, and which started out as an IOT, I think raspberry pie first time was like a, like >>A, we did a little camera initially camera >>And it was just a kind of a fun, little clever, I won't say hack, but just having a project that just took on a life OFS own, where are we? What's the update with racer you're here with the track. Yeah, >>Possibly >>You got the track and competing with the big dogs, literally dog, you got spot over there. Boston dynamics. >>Well we'll, we'll invite them over to the track later. Yeah. So deep razor, you know, is the fastest way to get hands on with machine learning. You know, we designed it as, uh, a way for developers to have fun while learning about this particular machine learning technique called reinforcement learning, which is all about using, uh, a simulation, uh, to teach the robot how to learn via trial and error. So deep racer includes a 3d racing simulator where you can train your model via trial and error. It includes the physical car. So you can take, uh, the model that you trained in the cloud, download it to this one 18th scale, um, kind of RC car. That's been imbued with an extra sensor. So we have a camera on the front. We've got an extra, uh, Intel, X, 86 processor inside here. Um, and this thing will drive itself, autonomously around the track. And of course what's a track and uh, some cars driving around it without a little competition. So we've got the deep racer league that sort of sits on top of this and adds a little spice to the whole thing. It's >>It's, it's like formula one for nerds. It really is. It's so good because a lot of people will have to readjust their models cuz they go off the track and I see people and it's oh my, then they gotta reset. This has turned into quite the phenomenon and it's fun to watch and every year it gets more competitive. I know you guys have a cut list that reinvent, it's almost like a, a super score gets you up. Yeah. Take, take us through the reinvents coming up. Sure. What's going on with the track there and then we'll get into some of the new adoption in terms of the people. >>Yeah, absolutely. So, uh, you know, we have monthly online races where we have a new track every month that challenges our, our developers to retrain their model or sort of tweak the existing model that they've trained to adapt for those new courses. Then at physical events like here at re Mars and at our AWS summits around the world, we have physical, uh, races. Um, and we crown a champion at each one of those races. You may have heard some cheering a minute ago. Yeah. That was our finals over there. We've got some really fast cars, fast models racing today. Um, so we take the winners from each of those two circuits, the virtual and the physical and they, the top ones of them come together at reinvent every year in November, December. Um, and we have a set of knockout rounds, championship rounds where these guys get the field gets narrowed to 10 racers and then those 10 racers, uh, race to hold up the championship cup and, um, earn, earn, uh, you know, a whole set of prizes, either cash or, or, you know, scholarships or, you know, tuition funds, whatever the, uh, the developer is most interested >>In. You know, I ask you this question every time you come on the cube because I I'm smiling. That's, it's so much fun. I mean, if I had not been with the cube anyway, I'd love to do this. Um, would you ever imagine when you first started this, that it would be such so popular and at the rise of eSports? So, you know, discord is booming. Yeah. The QB has a discord channel now. Sure, sure. Not that good on it yet, but we'll get there, but just the gaming culture, the nerd culture, the robotics clubs, the young people, just nerds who wanna compete. You never thought that would be this big. We, >>We were so surprised by a couple key things after we launched deep racer, you know, we envisioned this as a way for, you know, developers who had already graduated from school. They were in a company they wanted to grow their machine learning skills. Individuals could adopt this. What we saw was individuals were taking these devices and these concepts back to their companies. And they're saying, this is really fun. Like we should do something around this. And we saw companies like JPMC and Accenture and Morningstar into it and national Australia bank all adopting deep racer as a way to engage, excite their employees, but then also create some fun collaboration opportunities. Um, the second thing that was surprising was the interest from students. And it was actually really difficult for students to use deep racer because you needed an AWS account. You had to have a credit card. You might, you might get billed. There was a free tier involved. Um, so what we did this past year was we launched the deep racer student league, um, which caters to students 16 or over in high school or in college, uh, deep Razer student includes 10 hours a month of free training, um, so that they can train their models in the cloud. And of course the same series of virtual monthly events for them to race against each other and win, win prizes. >>So they don't have to go onto the dark web hack someone's credit card, get a proton email account just to get a deep Razer that's right. They can now come in on their own. >>That's right. That's right. They can log into that virtual the virtual environment, um, and get access. And, and one of the other things that we realized, um, and, and that's a common kind of, uh, realization across the industry is both the need for the democratization of machine learning. But also how can we address the skills gap for future ML learners? Um, and this applies to the, the, the world of students kind of engaging. And we said, Hey, you know, um, the world's gonna see the most successful and innovative ideas come from the widest possible range of participants. And so we knew that there were some issues with, um, you know, underserved and underrepresented minorities accessing this technology and getting the ML education to be successful. So we partnered with Intel and Udacity and launched the AI and ML scholarship program this past year. And it's also built on top of deep Bracer student. So now students, um, can register and opt into the scholarship program and we're gonna give out, uh, Udacity scholarships to 2000 students, um, at the end of this year who compete in AWS deep racer student racers, and also go through all of the learning modules online. >>Okay. Hold on, lets back up. Cuz it sounds, this sounds pretty cool. All right. So we kind went fast on that a little bit slow today at the end of the day. So if they sign up for the student account, which is lowered the batteries for, and they Intel and a desk, this is a courseware for the machine learning that's right. So in order to participate, you gotta take some courseware, check the boxes and, and, and Intel is paying for this or you get rewarded with the scholarship after the fact. >>So Intel's a partner of ours in, in putting this on. So it's both, um, helping kind of fund the scholarships for students, but also participating. So for the students who, um, get qualified for the scholarship and, and win one of those 2000 Udacity Nanodegree scholarships, uh, they also will get mentoring opportunities. So AWS and Intel, um, professionals will help mentor these students, uh, give them career advice, give them technical advice. C >>They'll they're getting smarter. Absolutely. So I'm just gonna get to data here. So is it money or credits for the, for the training? >>That's the scholarship or both? Yes. So, so the, the student training is free for students. Yep. They get 10 hours a month, no credits they need to redeem or anything. It's just, you log in and you get your account. Um, then the 2000, uh, Udacity scholarships, those are just scholarships that are awarded to, to the winners of the student, um, scholarship program. It's a four month long, uh, class on Python programming for >>AI so's real education. Yeah. It's like real, real, so ones here's 10 hours. Here's check the box. Here's here's the manual. Yep. >>Everybody gets access to that. That's >>Free. >>Yep. >>To the student over 16. Yes. Free. So that probably gonna increase the numbers. What kind of numbers are you looking at now? Yeah. In terms of scope to scale here for me. Yeah. Scope it >>Out. What's the numbers we've, we've been, uh, pleasantly surprised. We've got over 55,000 students from over 180 countries around the world that have signed up for the deep racer student program and of those over 30,000 have opted into that scholarship program. So we're seeing huge interest, um, from across the globe in, in this virtual students, um, opportunity, you know, and students are taking advantage of those 20 hours of learning. They're taking advantage of the fun, deep racer kind of hands on racing. Um, and obviously a large number of them are also interested in this scholarship opportunity >>Or how many people are in the AWS deep racer, um, group. Now, because now someone's gotta work on this stuff. It's went from a side hustle to like a full initiative. Well, >>You know, we're pretty efficient with what we, you know, we're pretty efficient. You've probably read about the two pizza teams at Amazon. So we keep ourselves pretty streamlined, but we're really proud of, um, what we've been able to bring to the table. And, you know, over those pandemic years, we really focused on that virtual experience in viewing it with those gaming kind of gamification sort of elements. You know, one of the things we did for the students is just like you guys, we have a discord channel, so not only can the students get hands on, but they also have this built in community of other students now to help support them bounce ideas off of and, you know, improve their learning. >>Awesome. So what's next, take us through after this event and what's going on for you more competitions. >>Yeah. So we're gonna be at the remainder of the AWS summits around the world. So places like Mexico city, you know, uh, this week we were in Milan, um, you know, we've got some AWS public sector, um, activities that are happening. Some of those are focused on students. So we've had student events in, um, Ottawa in Canada. We've had a student event in Japan. We've had a student event in, um, Australia, New Zealand. And so we've got events, both for students as well as for the professionals who wanna compete in the league happening around the world. And again, culminating at reinvent. So we'll be back here in Vegas, um, at the beginning of December where our champions will, uh, compete to ho to come. >>So you guys are going to all the summits, absolutely. Most of the summits or >>All of them, anytime there's a physical summit, we'll be there with a track and cars and give developers the opportunity to >>The track is always open. >>Absolutely. All >>Right. Well, thanks for coming on the cube with the update. Appreciate it, >>Mike. Thanks, John. It was great to be >>Here. Pleasure to know you appreciate it. Love that program. All right. Cube coverage here. Deep race are always the hit. It's a fixture at all the events, more exciting than the cube. Some say, but uh, almost great to have you on Mike. Uh, great success. Check it out free to students. The barrier's been lower to get in every robotics club. Every math club, every science club should be signing up for this. Uh, it's a lot of fun and it's cool. And of course you learn machine learning. I mean, come on. There's one to learn that. All right. Cube coverage. Coming back after this short break.