(gentle music) >> Okay, welcome back to Supercloud 2, live here in Palo Alto, California for our live stage performance. Supercloud 2 is our second Supercloud event. We're going to get these out as fast as we can every couple months. It's our second one, you'll see two and three this year. I'm John Furrier, my co-host, Dave Vellante. A panel here to break down the Supercloud momentum, the wave, and the developer impact that we bringing back Vittorio Viarengo, who's a VP for Cross-Cloud Services at VMware. Sarbjeet Johal, industry influencer and Analyst at StackPayne, his company, Cube alumni and Influencer. Sarbjeet, great to see you. Vittorio, thanks for coming back. >> Nice to be here. >> My pleasure. >> Vittorio, you just gave a keynote where we unpacked the cross-cloud services, what VMware is doing, how you guys see it, not just from VMware's perspective, but VMware looking out broadly at the industry and developers came up and you were like, "Developers, developer, developers", kind of a goof on the Steve Ballmer famous meme that everyone's seen. This is a huge star, sorry, I mean a big piece of it. The developers are the canary in the coal mines. They're the ones who are being asked to code the digital transformation, which is fully business transformation and with the market the way it is right now in terms of the accelerated technology, every enterprise grade business model's changing. The technology is evolving, the builders are kind of, they want go faster. I'm saying they're stuck in a way, but that's my opinion, but there's a lot of growth. >> Yeah. >> The impact, they got to get released up and let it go. Those developers need to accelerate faster. It's been a big part of productivity, and the conversations we've had. So developer impact is huge in Supercloud. What's your, what do you guys think about this? We'll start with you, Sarbjeet. >> Yeah, actually, developers are the masons of the digital empires I call 'em, right? They lay every brick and build all these big empires. On the left side of the SDLC, or the, you know, when you look at the system operations, developer is number one cost from economic side of things, and from technology side of things, they are tech hungry people. They are developers for that reason because developer nights are long, hours are long, they forget about when to eat, you know, like, I've been a developer, I still code. So you want to keep them happy, you want to hug your developers. We always say that, right? Vittorio said that right earlier. The key is to, in this context, in the Supercloud context, is that developers don't mind mucking around with platforms or APIs or new languages, but they hate the infrastructure part. That's a fact. They don't want to muck around with servers. It's friction for them, it is like they don't want to muck around even with the VMs. So they want the programmability to the nth degree. They want to automate everything, so that's how they think and cloud is the programmable infrastructure, industrialization of infrastructure in many ways. So they are happy with where we are going, and we need more abstraction layers for some developers. By the way, I have this sort of thinking frame for last year or so, not all developers are same, right? So if you are a developer at an ISV, you behave differently. If you are a developer at a typical enterprise, you behave differently or you are forced to behave differently because you're not writing software.- >> Well, developers, developers have changed, I mean, Vittorio, you and I were talking earlier on the keynote, and this is kind of the key point is what is a developer these days? If everything is software enabled, I mean, even hardware interviews we do with Nvidia, and Amazon and other people building silicon, they all say the same thing, "It's software on a chip." So you're seeing the role of software up and down the stack and the role of the stack is changing. The old days of full stack developer, what does that even mean? I mean, the cloud is a half a stack kind of right there. So, you know, developers are certainly more agile, but cloud native, I mean VMware is epitome of operations, IT operations, and the Tan Zoo initiative, you guys started, you went after the developers to look at them, and ask them questions, "What do you need?", "How do you transform the Ops from virtualization?" Again, back to your point, so this hardware abstraction, what is software, what is cloud native? It's kind of messy equation these days. How do you guys grokel with that? >> I would argue that developers don't want the Supercloud. I dropped that up there, so, >> Dave: Why not? >> Because developers, they, once they get comfortable in AWS or Google, because they're doing some AI stuff, which is, you know, very trendy right now, or they are in IBM, any of the IPA scaler, professional developers, system developers, they love that stuff, right? Yeah, they don't, the infrastructure gets in the way, but they're just, the problem is, and I think the Supercloud should be driven by the operators because as we discussed, the operators have been left behind because they're busy with day-to-day jobs, and in most cases IT is centralized, developers are in the business units. >> John: Yeah. >> Right? So they get the mandate from the top, say, "Our bank, they're competing against". They gave teenagers or like young people the ability to do all these new things online, and Venmo and all this integration, where are we? "Oh yeah, we can do it", and then build it, and then deploy it, "Okay, we caught up." but now the operators are back in the private cloud trying to keep the backend system running and so I think the Supercloud is needed for the primarily, initially, for the operators to get in front of the developers, fit in the workflow, but lay the foundation so it is secure.- >> So, so I love this thinking because I love the rift, because the rift points to what is the target audience for the value proposition and if you're a developer, Supercloud enables you so you shouldn't have to deal with Supercloud. >> Exactly. >> What you're saying is get the operating environment or operating system done properly, whether it's architecture, building the platform, this comes back to architecture platform conversations. What is the future platform? Is it a vendor supplied or is it customer created platform? >> Dave: So developers want best to breed, is what you just said. >> Vittorio: Yeah. >> Right and operators, they, 'cause developers don't want to deal with governance, they don't want to deal with security, >> No. >> They don't want to deal with spinning up infrastructure. That's the role of the operator, but that's where Supercloud enables, to John's point, the developer, so to your question, is it a platform where the platform vendor is responsible for the architecture, or there is it an architectural standard that spans multiple clouds that has to emerge? Based on what you just presented earlier, Vittorio, you are the determinant of the architecture. It's got to be open, but you guys determine that, whereas the nirvana is, "Oh no, it's all open, and it just kind of works." >> Yeah, so first of all, let's all level set on one thing. You cannot tell developers what to do. >> Dave: Right, great >> At least great developers, right? Cannot tell them what to do. >> Dave: So that's what, that's the way I want to sort of, >> You can tell 'em what's possible. >> There's a bottle on that >> If you tell 'em what's possible, they'll test it, they'll look at it, but if you try to jam it down their throat, >> Yeah. >> Dave: You can't tell 'em how to do it, just like your point >> Let me answer your answer the question. >> Yeah, yeah. >> So I think we need to build an architect, help them build an architecture, but it cannot be proprietary, has to be built on what works in the cloud and so what works in the cloud today is Kubernetes, is you know, number of different open source project that you need to enable and then provide, use this, but when I first got exposed to Kubernetes, I said, "Hallelujah!" We had a runtime that works the same everywhere only to realize there are 12 different distributions. So that's where we come in, right? And other vendors come in to say, "Hey, no, we can make them all look the same. So you still use Kubernetes, but we give you a place to build, to set those operation policy once so that you don't create friction for the developers because that's the last thing you want to do." >> Yeah, actually, coming back to the same point, not all developers are same, right? So if you're ISV developer, you want to go to the lowest sort of level of the infrastructure and you want to shave off the milliseconds from to get that performance, right? If you're working at AWS, you are doing that. If you're working at scale at Facebook, you're doing that. At Twitter, you're doing that, but when you go to DMV and Kansas City, you're not doing that, right? So your developers are different in nature. They are given certain parameters to work with, certain sort of constraints on the budget side. They are educated at a different level as well. Like they don't go to that end of the degree of sort of automation, if you will. So you cannot have the broad stroking of developers. We are talking about a citizen developer these days. That's a extreme low, >> You mean Low-Code. >> Yeah, Low-Code, No-code, yeah, on the extreme side. On one side, that's citizen developers. On the left side is the professional developers, when you say developers, your mind goes to the professional developers, like the hardcore developers, they love the flexibility, you know, >> John: Well app, developers too, I mean. >> App developers, yeah. >> You're right a lot of, >> Sarbjeet: Infrastructure platform developers, app developers, yes. >> But there are a lot of customers, its a spectrum, you're saying. >> Yes, it's a spectrum >> There's a lot of customers don't want deal with that muck. >> Yeah. >> You know, like you said, AWS, Twitter, the sophisticated developers do, but there's a whole suite of developers out there >> Yeah >> That just want tools that are abstracted. >> Within a company, within a company. Like how I see the Supercloud is there shouldn't be anything which blocks the developers, like their view of the world, of the future. Like if you're blocked as a developer, like something comes in front of you, you are not developer anymore, believe me, (John laughing) so you'll go somewhere else >> John: First of all, I'm, >> You'll leave the company by the way. >> Dave: Yeah, you got to quit >> Yeah, you will quit, you will go where the action is, where there's no sort of blockage there. So like if you put in front of them like a huge amount of a distraction, they don't like it, so they don't, >> Well, the idea of a developer, >> Coming back to that >> Let's get into 'cause you mentioned platform. Get year in the term platform engineering now. >> Yeah. >> Platform developer. You know, I remember back in, and I think there's still a term used today, but when I graduated my computer science degree, we were called "Software engineers," right? Do people use that term "Software engineering", or is it "Software development", or they the same, are they different? >> Well, >> I think there's a, >> So, who's engineering what? Are they engineering or are they developing? Or both? Well, I think it the, you made a great point. There is a factor of, I had the, I was blessed to work with Adam Bosworth, that is the guy that created some of the abstraction layer, like Visual Basic and Microsoft Access and he had so, he made his whole career thinking about this layer, and he always talk about the professional developers, the developers that, you know, give him a user manual, maybe just go at the APIs, he'll build anything, right, from system engine, go down there, and then through obstruction, you get the more the procedural logic type of engineers, the people that used to be able to write procedural logic and visual basic and so on and so forth. I think those developers right now are a little cut out of the picture. There's some No-code, Low-Code environment that are maybe gain some traction, I caught up with Adam Bosworth two weeks ago in New York and I asked him "What's happening to this higher level developers?" and you know what he is told me, and he is always a little bit out there, so I'm going to use his thought process here. He says, "ChapGPT", I mean, they will get to a point where this high level procedural logic will be written by, >> John: Computers. >> Computers, and so we may not need as many at the high level, but we still need the engineers down there. The point is the operation needs to get in front of them >> But, wait, wait, you seen the ChatGPT meme, I dunno if it's a Dilbert thing where it's like, "Time to tic" >> Yeah, yeah, yeah, I did that >> "Time to develop the code >> Five minutes, time to decode", you know, to debug the codes like five hours. So you know, the whole equation >> Well, this ChatGPT is a hot wave, everyone's been talking about it because I think it illustrates something that's NextGen, feels NextGen, and it's just getting started so it's going to get better. I mean people are throwing stones at it, but I think it's amazing. It's the equivalent of me seeing the browser for the first time, you know, like, "Wow, this is really compelling." This is game-changing, it's not just keyword chat bots. It's like this is real, this is next level, and I think the Supercloud wave that people are getting behind points to that and I think the question of Ops and Dev comes up because I think if you limit the infrastructure opportunity for a developer, I think they're going to be handicapped. I mean that's a general, my opinion, the thesis is you give more aperture to developers, more choice, more capabilities, more good things could happen, policy, and that's why you're seeing the convergence of networking people, virtualization talent, operational talent, get into the conversation because I think it's an infrastructure engineering opportunity. I think this is a seminal moment in a new stack that's emerging from an infrastructure, software virtualization, low-code, no-code layer that will be completely programmable by things like the next Chat GPT or something different, but yet still the mechanics and the plumbing will still need engineering. >> Sarbjeet: Oh yeah. >> So there's still going to be more stuff coming on. >> Yeah, we have, with the cloud, we have made the infrastructure programmable and you give the programmability to the programmer, they will be very creative with that and so we are being very creative with our infrastructure now and on top of that, we are being very creative with the silicone now, right? So we talk about that. That's part of it, by the way. So you write the code to the particle's silicone now, and on the flip side, the silicone is built for certain use cases for AI Inference and all that. >> You saw this at CES? >> Yeah, I saw at CES, the scenario is this, the Bosch, I spoke to Bosch, I spoke to John Deere, I spoke to AWS guys, >> Yeah. >> They were showcasing their technology there and I was spoke to Azure guys as well. So the Bosch is a good example. So they are building, they are right now using AWS. I have that interview on camera, I will put it some sometime later on there online. So they're using AWS on the back end now, but Bosch is the number one, number one or number two depending on what day it is of the year, supplier of the componentry to the auto industry, and they are creating a platform for our auto industry, so is Qualcomm actually by the way, with the Snapdragon. So they told me that customers, their customers, BMW, Audi, all the manufacturers, they demand the diversity of the backend. Like they don't want all, they, all of them don't want to go to AWS. So they want the choice on the backend. So whatever they cook in the middle has to work, they have to sprinkle the data for the data sovereign side because they have Chinese car makers as well, and for, you know, for other reasons, competitive reasons and like use. >> People don't go to, aw, people don't go to AWS either for political reasons or like competitive reasons or specific use cases, but for the most part, generally, I haven't met anyone who hasn't gone first choice with either, but that's me personally. >> No, but they're building. >> Point is the developer wants choice at the back end is what I'm hearing, but then finish that thought. >> Their developers want the choice, they want the choice on the back end, number one, because the customers are asking for, in this case, the customers are asking for it, right? But the customers requirements actually drive, their economics drives that decision making, right? So in the middle they have to, they're forced to cook up some solution which is vendor neutral on the backend or multicloud in nature. So >> Yeah, >> Every >> I mean I think that's nirvana. I don't think, I personally don't see that happening right now. I mean, I don't see the parody with clouds. So I think that's a challenge. I mean, >> Yeah, true. >> I mean the fact of the matter is if the development teams get fragmented, we had this chat with Kit Colbert last time, I think he's going to come on and I think he's going to talk about his keynote in a few, in an hour or so, development teams is this, the cloud is heterogenous, which is great. It's complex, which is challenging. You need skilled engineering to manage these clouds. So if you're a CIO and you go all in on AWS, it's hard. Then to then go out and say, "I want to be completely multi-vendor neutral" that's a tall order on many levels and this is the multicloud challenge, right? So, the question is, what's the strategy for me, the CIO or CISO, what do I do? I mean, to me, I would go all in on one and start getting hedges and start playing and then look at some >> Crystal clear. Crystal clear to me. >> Go ahead. >> If you're a CIO today, you have to build a platform engineering team, no question. 'Cause if we agree that we cannot tell the great developers what to do, we have to create a platform engineering team that using pieces of the Supercloud can build, and let's make this very pragmatic and give examples. First you need to be able to lay down the run time, okay? So you need a way to deploy multiple different Kubernetes environment in depending on the cloud. Okay, now we got that. The second part >> That's like table stakes. >> That are table stake, right? But now what is the advantage of having a Supercloud service to do that is that now you can put a policy in one place and it gets distributed everywhere consistently. So for example, you want to say, "If anybody in this organization across all these different buildings, all these developers don't even know, build a PCI compliant microservice, They can only talk to PCI compliant microservice." Now, I sleep tight. The developers still do that. Of course they're going to get their hands slapped if they don't encrypt some messages and say, "Oh, that should have been encrypted." So number one. The second thing I want to be able to say, "This service that this developer built over there better satisfy this SLA." So if the SLA is not satisfied, boom, I automatically spin up multiple instances to certify the SLA. Developers unencumbered, they don't even know. So this for me is like, CIO build a platform engineering team using one of the many Supercloud services that allow you to do that and lay down. >> And part of that is that the vendor behavior is such, 'cause the incentive is that they don't necessarily always work together. (John chuckling) I'll give you an example, we're going to hear today from Western Union. They're AWS shop, but they want to go to Google, they want to use some of Google's AI tools 'cause they're good and maybe they're even arguably better, but they're also a Snowflake customer and what you'll hear from them is Amazon and Snowflake are working together so that SageMaker can be integrated with Snowflake but Google said, "No, you want to use our AI tools, you got to use BigQuery." >> Yeah. >> Okay. So they say, "Ah, forget it." So if you have a platform engineering team, you can maybe solve some of that vendor friction and get competitive advantage. >> I think that the future proximity concept that I talk about is like, when you're doing one thing, you want to do another thing. Where do you go to get that thing, right? So that is very important. Like your question, John, is that your point is that AWS is ahead of the pack, which is true, right? They have the >> breadth of >> Infrastructure by a lot >> infrastructure service, right? They breadth of services, right? So, how do you, When do you bring in other cloud providers, right? So I believe that you should standardize on one cloud provider, like that's your primary, and for others, bring them in on as needed basis, in the subsection or sub portfolio of your applications or your platforms, what ever you can. >> So yeah, the Google AI example >> Yeah, I mean, >> Or the Microsoft collaboration software example. I mean there's always or the M and A. >> Yeah, but- >> You're going to get to run Windows, you can run Windows on Amazon, so. >> By the way, Supercloud doesn't mean that you cannot do that. So the perfect example is say that you're using Azure because you have a SQL server intensive workload. >> Yep >> And you're using Google for ML, great. If you are using some differentiated feature of this cloud, you'll have to go somewhere and configure this widget, but what you can abstract with the Supercloud is the lifecycle manage of the service that runs on top, right? So how does the service get deployed, right? How do you monitor performance? How do you lifecycle it? How you secure it that you can abstract and that's the value and eventually value will win. So the customers will find what is the values, obstructing in making it uniform or going deeper? >> How about identity? Like take identity for instance, you know, that's an opportunity to abstract. Whether I use Microsoft Identity or Okta, and I can abstract that. >> Yeah, and then we have APIs and standards that we can use so eventually I think where there is enough pain, the right open source will emerge to solve that problem. >> Dave: Yeah, I can use abstract things like object store, right? That's pretty simple. >> But back to the engineering question though, is that developers, developers, developers, one thing about developers psychology is if something's not right, they say, "Go get fixing. I'm not touching it until you fix it." They're very sticky about, if something's not working, they're not going to do it again, right? So you got to get it right for developers. I mean, they'll maybe tolerate something new, but is the "juice worth the squeeze" as they say, right? So you can't go to direct say, "Hey, it's, what's a work in progress? We're going to get our infrastructure together and the world's going to be great for you, but just hang tight." They're going to be like, "Get your shit together then talk to me." So I think that to me is the question. It's an Ops question, but where's that value for the developer in Supercloud where the capabilities are there, there's less friction, it's simpler, it solves the complexity problem. I don't need these high skilled labor to manage Amazon. I got services exposed. >> That's what we talked about earlier. It's like the Walmart example. They basically, they took away from the developer the need to spin up infrastructure and worry about all the governance. I mean, it's not completely there yet. So the developer could focus on what he or she wanted to do. >> But there's a big, like in our industry, there's a big sort of flaw or the contention between developers and operators. Developers want to be on the cutting edge, right? And operators want to be on the stability, you know, like we want governance. >> Yeah, totally. >> Right, so they want to control, developers are like these little bratty kids, right? And they want Legos, like they want toys, right? Some of them want toys by way. They want Legos, they want to build there and they want make a mess out of it. So you got to make sure. My number one advice in this context is that do it up your application portfolio and, or your platform portfolio if you are an ISV, right? So if you are ISV you most probably, you're building a platform these days, do it up in a way that you can say this portion of our applications and our platform will adhere to what you are saying, standardization, you know, like Kubernetes, like slam dunk, you know, it works across clouds and in your data center hybrid, you know, whole nine yards, but there is some subset on the next door systems of innovation. Everybody has, it doesn't matter if you're DMV of Kansas or you are, you know, metaverse, right? Or Meta company, right, which is Facebook, they have it, they are building something new. For that, give them some freedom to choose different things like play with non-standard things. So that is the mantra for moving forward, for any enterprise. >> Do you think developers are happy with the infrastructure now or are they wanting people to get their act together? I mean, what's your reaction, or you think. >> Developers are happy as long as they can do their stuff, which is running code. They want to write code and innovate. So to me, when Ballmer said, "Developer, develop, Developer, what he meant was, all you other people get your act together so these developers can do their thing, and to me the Supercloud is the way for IT to get there and let developer be creative and go fast. Why not, without getting in trouble. >> Okay, let's wrap up this segment with a super clip. Okay, we're going to do a sound bite that we're going to make into a short video for each of you >> All right >> On you guys summarizing why Supercloud's important, why this next wave is relevant for the practitioners, for the industry and we'll turn this into an Instagram reel, YouTube short. So we'll call it a "Super clip. >> Alright, >> Sarbjeet, you want, you want some time to think about it? You want to go first? Vittorio, you want. >> I just didn't mind. (all laughing) >> No, okay, okay. >> I'll do it again. >> Go back. No, we got a fresh one. We'll going to already got that one in the can. >> I'll go. >> Sarbjeet, you go first. >> I'll go >> What's your super clip? >> In software systems, abstraction is your friend. I always say that. Abstraction is your friend, even if you're super professional developer, abstraction is your friend. We saw from the MFC library from C++ days till today. Abstract, use abstraction. Do not try to reinvent what's already being invented. Leverage cloud, leverage the platform side of the cloud. Not just infrastructure service, but platform as a service side of the cloud as well, and Supercloud is a meta platform built on top of these infrastructure services from three or four or five cloud providers. So use that and embrace the programmability, embrace the abstraction layer. That's the key actually, and developers who are true developers or professional developers as you said, they know that. >> Awesome. Great super clip. Vittorio, another shot at the plate here for super clip. Go. >> Multicloud is awesome. There's a reason why multicloud happened, is because gave our developers the ability to innovate fast and ever before. So if you are embarking on a digital transformation journey, which I call a survival journey, if you're not innovating and transforming, you're not going to be around in business three, five years from now. You have to adopt the Supercloud so the developer can be developer and keep building great, innovating digital experiences for your customers and IT can get in front of it and not get in trouble together. >> Building those super apps with Supercloud. That was a great super clip. Vittorio, thank you for sharing. >> Thanks guys. >> Sarbjeet, thanks for coming on talking about the developer impact Supercloud 2. On our next segment, coming up right now, we're going to hear from Walmart enterprise architect, how they are building and they are continuing to innovate, to build their own Supercloud. Really informative, instructive from a practitioner doing it in real time. Be right back with Walmart here in Palo Alto. Thanks for watching. (gentle music)

(bright upbeat music) >> Greetings, brilliant community and thank you so much for tuning in to theCUBE here for the last three days where we've been live from Detroit, Michigan. I've had the pleasure of spending this week with Lisa Martin and John Furrier. Thank you both so much for hanging out, for inviting me into the CUBE family. It's our first show together, it's been wonderful. >> Thank you. >> You nailed it. >> Oh thanks, sweetheart. >> Great job. Great job team, well done. Free wall to wall coverage, it's what we do. We stay till everyone else-- >> Savannah: 100 percent. >> Everyone else leaves, till they pull the plug. >> Lisa: Till they turn the lights out. We're still there. >> Literally. >> Literally last night. >> Still broadcasting. >> Whatever takes to get the stories and get 'em out there at scale. >> Yeah. >> Great time. >> 33. 33 different segments too. Very impressive. John, I'm curious, you're a trend watcher and you've been at every single KubeCon. >> Yep. >> What are the trends this year? Give us the breakdown. >> I think CNCF does this, it's a hard job to balance all the stakeholders. So one, congratulations to the CNCF for another great KubeCon and CloudNativeCon. It is really hard to balance bringing in the experts who, as time goes by, seven years we've been all of, as you said, you get experts, you get seniority, and people who can be mentors, 60% new people. You have vendors who are sponsoring and there's always people complaining and bitching and moaning. They want this, they want that. It's always hard and they always do a good job of balancing it. We're lucky that we get to scale the stories with CUBE and that's been great. We had some great stories here, but it's a great community and again, they're inclusive. As I've said before, we've talked about it. This year though is an inflection point in my opinion, because you're seeing the developer ecosystem growing so fast. It's global. You're seeing events pop up, you're seeing derivative events. CNCF is at the center point and they have to maintain the culture of developer experts, maintainers, while balancing the newbies. And that's going to be >> Savannah: Mm-hmm. really hard. And they've done a great job. We had a great conversation with them. So great job. And I think it's going to continue. I think the attendance metric is a little bit of a false positive. There's a lot of online people who didn't come to Detroit this year. And I think maybe the combination of the venue, the city, or just Covid preferences may not look good on paper, on the numbers 'cause it's not a major step up in attendance. It's still bigger, but the community, I think, is going to continue to grow. I'm bullish on it. >> Yeah, I mean at least we did see double the number of people that we had in Los Angeles. Very curious. I think Amsterdam, where we'll be next with CNCF in the spring, in April. I think that's actually going to be a better pulse check. We'll be in Europe, we'll see what's going on. >> John: Totally. >> I mean, who doesn't like Amsterdam in the springtime? Lisa, what have been some of your observations? >> Oh, so many observations. The evolution of the conference, the hallway track conversations really shifting towards adjusting to the enterprise. The enterprise momentum that we saw here as well. We had on the show, Ford. >> Savannah: Yes. We had MassMutual, we had ING, that was today. Home Depot is here. We are seeing all these big companies that we know and love, become software companies right before our eyes. >> Yeah. Well, and I think we forget that software powers our entire world. And so of course they're going to have to be here. So much running on Kubernetes. It's on-prem, it's at the edge, it's everywhere. It's exciting. Woo, I'm excited. John, what do you think is the number one story? This is your question. I love asking you this question. What is the number one story out KubeCon? >> Well, I think the top story is a combination of two things. One is the evolution of Cloud Native. We're starting to see web assembly. That's a big hyped up area. It got a lot of attention. >> Savannah: Yeah. That's kind of teething out the future. >> Savannah: Rightfully so. The future of this kind of lightweight. You got the heavy duty VMs, you got Kubernetes and containers, and now this web assembly, shows a trajectory of apps, server-like environment. And then the big story is security. Software supply chain is, to me, was the number one consistent theme. At almost all the interviews, in the containers, and the workflows, >> Savannah: Very hot. software supply chain is real. The CD Foundation mentioned >> Savannah: Mm-hmm. >> they had 16,000 vulnerabilities identified in their code base. They were going to automate that. So again, >> Savannah: That was wild. >> That's the top story. The growth of open source exposes potential vulnerabilities with security. So software supply chain gets my vote. >> Did you hear anything that surprised you? You guys did this great preview of what you thought we were going to hear and see and feel and touch at KubeCon, CloudNativeCon 2022. You talked about, for example, the, you know, healthcare financial services being early adopters of this. Anything surprise either one of you in terms of what you predicted versus what we saw? Savannah, let's start with you. >> You know what really surprised me, and this is ironic, so I'm a community gal by trade. But I was really just impressed by the energy that everyone brought here and the desire to help. The thing about the open source community that always strikes me is, I mean 187 different countries participating. You've got, I believe it's something like 175,000 people contributing to the 140 projects plus that CNCF is working on. But that culture of collaboration extends far beyond just the CNCF projects. Everyone here is keen to help each other. We had the conversation just before about the teaching and the learnings that are going on here. They brought in Detroit's students to come and learn, which is just the most heartwarming story out of this entire thing. And I think it's just the authenticity of everyone in this community and their passion. Even though I know it's here, it still surprises me to see it in the flesh. Especially in a place like Detroit. >> It's nice. >> Yeah. >> It's so nice to see it. And you bring up a good point. It's very authentic. >> Savannah: It's super authentic. >> I mean, what surprised me is one, the Wasm, or web assembly. I didn't see that coming at the scale of the conversation. It sucked a lot of options out of the room in my opinion, still hyped up. But this looks like it's got a good trajectory. I like that. The other thing that surprised me that was a learning was my interview with Solo.io, Idit, and Brian Gracely, because he's a CUBE alumni and former host of theCUBE, and analyst at Wikibon, was how their go-to-market was an example of a modern company in Covid with a clean sheet of paper and smart people, they're just doing things different. They're in Slack with their customers. And I walked away with, "Wow that's like a playbook that's not, was never, in the go-to-market VC-backed company playbook." I thought that was, for me, a personal walk away saying that's important. I like how they did that. And there's a lot of companies I think could learn from that. Especially as the recession comes where partnering with customers has always been a top priority. And how they did that was very clever, very effective, very efficient. So I walked away with that saying, "I think that's going to be a standard." So that was a pleasant surprise. >> That was a great surprise. Also, that's a female-founded company, which is obviously not super common. And the growth that they've experienced, to your point, really being catalyzed by Covid, is incredibly impressive. I mean they have some massive brand name customers, Amex, BMW for example. >> Savannah: Yeah. >> Great point. >> And I interviewed her years ago and I remember saying to myself, "Wow, she's impressive." I liked her. She's a player. A player for sure. And she's got confidence. Even on the interview she said, "We're just better, we have better product." And I just like the point of view. Very customer-focused but confident. And I just took, that's again, a great company. And again, I'm not surprised that Brian Gracely left Red Hat to go work there. So yeah, great, great call there. And of course other things that weren't surprising that I predicted, Red Hat continued to invest. They continue to bring people on theCUBE, they support theCUBE but more importantly they have a good strategy. They're in that multicloud positioning. They're going to have an opportunity to get a bite at the apple. And I what I call the supercloud. As enterprises try to go and be mainstream, Cloud Native, they're going to need some help. And Red Hat is always has the large enterprise customers. >> Savannah: What surprised you, Lisa? >> Oh my gosh, so many things. I think some of the memorable conversations that we had. I love talking with some of the enterprises that we mentioned, ING Bank for example. You know, or institutions that have been around for 100 plus years. >> Savannah: Oh, yeah. To see not only how much they've innovated and stayed relevant to meet the demands of the consumer, which are only increasing, but they're doing so while fostering a culture of innovation and a culture that allows these technology leaders to really grow within the organization. That was a really refreshing conversation that I think we had. 'Cause you can kind of >> Savannah: Absolutely. think about these old stodgy companies. Nah, of course they're going to digitize. >> Thinking about working for the bank, I think it's boring. >> Right? >> Yeah. And they were talking about, in fact, those great t-shirts that they had on, >> Yeah, yeah, yeah, yeah. were all about getting more people to understand how fun it is to work in tech for ING Bank in different industries. You don't just have to work for the big tech companies to be doing really cool stuff in technology. >> What I really liked about this show is we had two female hosts. >> Savannah: Yeah. >> How about that? Come on. >> Hey, well done, well done on your recruitment there, champ. >> Yes, thank you boss. (John laughs) >> And not to mention we have a really all-star production team. I do just want to give them a little shout out. To all the wonderful folks behind the lines here. (people clapping) >> John: Brendan. Good job. >> Yeah. Without Brendan, Anderson, Noah, and Andrew, we would be-- >> Of course Frank Faye holding it back there too. >> Yeah, >> Of course, Frank. >> I mean, without the business development wheels on the ship we'd really be in an unfortunate spot. I almost just swore on television. We're not going to do that. >> It's okay. No one's regulating. >> Yeah. (all laugh) >> Elon Musk just took over Twitter. >> It was a close call. >> That's right! >> It's going to be a hellscape. >> Yeah, I mean it's, shit's on fire. So we'll just see what happens next. I do, I really want to talk about this because I think it's really special. It's an ethos and some magic has happened here. Let's talk about Detroit. Let's talk about what it means to be here. We saw so many, and I can't stress this enough, but I think it really matters. There was a commitment to celebrating place here. Lisa, did you notice this too? >> Absolutely. And it surprised me because we just don't see that at conferences. >> Yeah. We're so used to going to the same places. >> Right. >> Vegas. Vegas, Vegas. More Vegas. >> Your tone-- >> San Francisco >> (both laugh) sums up my feelings. Yes. >> Right? >> Yeah. And, well, it's almost robotic but, and the fact that we're like, oh Detroit, really? But there was so much love for this city and recognizing and supporting its residents that we just don't see at conferences. You uncovered a lot of that with your swag-savvy segments, >> Savannah: Yeah. >> And you got more of that to talk about today. >> Don't worry, it's coming. Yeah. (laughs) >> What about you? Have you enjoyed Detroit? I know you hadn't been here in a long time, when we did our intro session. >> I think it's a bold move for the CNCF to come here and celebrate. What they did, from teaching the kids in the city some tech, they had a session. I thought that was good. >> Savannah: Loved that. I think it was a risky move because a lot of people, like, weren't sure if they were going to fly to Detroit. So some say it might impact the attendance. I thought they did a good job. Their theme, Road Ahead. Nice tie in. >> Savannah: Yeah. And so I think I enjoyed Detroit. The weather was great. It didn't rain. Nice breeze outside. >> Yeah. >> The weather was great, the restaurants are phenomenal. So Detroit's a good city. I missed some hockey games. I'd love to see the Red Wings play. Missed that game. But we always come back. >> I think it's really special. I mean, every time I talked to a company about their swag, that had sourced it locally, there was a real reason for this story. I mean even with Kasten in that last segment when I noticed that they had done Carhartt beanies, Carhartt being a Michigan company. They said, "I'm so glad you noticed. That's why we did it." And I think that type of, the community commitment to place, it all comes back to community. One of the bigger themes of the show. But that passion and that support, we need more of that. >> Lisa: Yeah. >> And the thing about the guests we've had this past three days have been phenomenal. We had a diverse set of companies, individuals come on theCUBE, you know, from Scott Johnston at Docker. A really one on one. We had a great intense conversation. >> Savannah: Great way to kick it off. >> We shared a lot of inside baseball, about Docker, super important company. You know, impressed with companies like Platform9 it's been around since the OpenStack days who are now in a relevant position. Rafi Systems, hot startup, they don't have a lot of resources, a lot of guerilla marketing going on. So I love to see the mix of startups really contributing. The big players are here. So it's a real great mix of companies. And I thought the interviews were phenomenal, like you said, Ford. We had, Kubia launched on theCUBE. >> Savannah: Yes. >> That's-- >> We snooped the location for KubeCon North America. >> You did? >> Chicago, everyone. In case you missed it, Bianca was nice enough to share that with us. >> We had Sarbjeet Johal, CUBE analyst came on, Keith Townsend, yesterday with you guys. >> We had like analyst speed dating last night. (all laugh) >> How'd that go? (laughs) >> It was actually great. One of the things that they-- >> Did they hug and kiss at the end? >> Here's the funny thing is that they were debating the size of the CNC app. One thinks it's too big, one thinks it's too small. And I thought, is John Goldilocks? (John laughs) >> Savannah: Yeah. >> What is John going to think about that? >> Well I loved that segment. I thought, 'cause Keith and Sarbjeet argue with each other on Twitter all the time. And I heard Keith say before, he went, "Yeah let's have it out on theCUBE." So that was fun to watch. >> Thank you for creating this forum for us to have that kind of discourse. >> Lisa: Yes, thank you. >> Well, it wouldn't be possible without the sponsors. Want to thank the CNCF. >> Absolutely. >> And all the ecosystem partners and sponsors that make theCUBE possible. We love doing this. We love getting the stories. No story's too small for theCUBE. We'll go with it. Do whatever it takes. And if it wasn't for the sponsors, the community wouldn't get all the great knowledge. So, and thank you guys. >> Hey. Yeah, we're, we're happy to be here. Speaking of sponsors and vendors, should we talk a little swag? >> Yeah. >> What do you guys think? All right. Okay. So now this is becoming a tradition on theCUBE so I'm very delighted, the savvy swag segment. I do think it's interesting though. I mean, it's not, this isn't just me shouting out folks and showing off t-shirts and socks. It's about standing out from the noise. There's a lot of players in this space. We got a lot of CNCF projects and one of the ways to catch the attention of people walking the show floor is to have interesting swag. So we looked for the most unique swag on Wednesday and I hadn't found this yet, but I do just want to bring it up. Oops, I think I might have just dropped it. This is cute. Is, most random swag of the entire show goes to this toothbrush. I don't really have more in terms of the pitch there because this is just random. (Lisa laughs) >> But so, everyone needs that. >> John: So what's their tagline? >> And you forget these. >> Yeah, so the idea was to brush your cloud bills. So I think they're reducing the cost of-- >> Kind of a hygiene angle. >> Yeah, yeah. Very much a hygiene angle, which I found a little ironic in this crowd to be completely honest with you. >> John: Don't leave the lights on theCUBE. That's what they say. >> Yeah. >> I mean we are theCUBE so it would be unjust of me not to show you a Rubik's cube. This is actually one of those speed cubes. I'm not going to be able to solve this for you with one hand on camera, but apparently someone did it in 17 seconds at the booth. Knowing this audience, not surprising to me at all. Today we are, and yesterday, was the t-shirt contest. Best t-shirt contest. Today we really dove into the socks. So this is, I noticed this trend at KubeCon in Los Angeles last year. Lots of different socks, clouds obviously a theme for the cloud. I'm just going to lay these out. Lots of gamers in the house. Not surprising. Here on this one. >> John: Level up. >> Got to level up. I love these 'cause they say, "It's not a bug." And anyone who's coded has obviously had to deal with that. We've got, so Star Wars is a huge theme here. There's Lego sets. >> John: I think it's Star Trek. But. >> That's Star Trek? >> John: That's okay. >> Could be both. (Lisa laughs) >> John: Nevermind, I don't want to. >> You can flex your nerd and geek with us anytime you want, John. I don't mind getting corrected. I'm all about, I'm all about the truth. >> Star Trek. Star Wars. Okay, we're all the same. Okay, go ahead. >> Yeah, no, no, this is great. Slim.ai was nice enough to host us for dinner on Tuesday night. These are their lovely cloud socks. You can see Cloud Native, obviously Cloud Native Foundation, cloud socks, whole theme here. But if we're going to narrow it down to some champions, I love these little bee elephants from Raft. And when I went up to these guys, I actually probably would've called these my personal winner. They said, again, so community focused and humble here at CNCF, they said that Wiz was actually the champion according to the community. These unicorn socks are pretty excellent. And I have to say the branding is flawless. So we'll go ahead and give Wiz the win on the best sock contest. >> John: For the win. >> Yeah, Wiz for the win. However, the thing that I am probably going to use the most is this really dope Detroit snapback from Kasten. So I'm going to be rocking this from now on for the rest of the segment as well. And I feel great about this snapback. >> Looks great. Looks good on you. >> Yeah. >> Thanks John. (John laughs) >> So what are we expecting between now and KubeCon in Amsterdam? >> Well, I think it's going to be great to see how they, the European side, it's a chill show. It's great. Brings in the European audience from the global perspective. I always love the EU shows because one, it's a great destination. Amsterdam's going to be a great location. >> Savannah: I'm pumped. >> The American crowd loves going over there. All the event cities that they choose are always awesome. I missed Valencia cause I got Covid. I'm really bummed about that. But I love the European shows. It's just a little bit, it's high intensity, but it's the European chill. They got a little bit more of that siesta vibe going on. >> Yeah. >> And it's just awesome. >> Yeah, >> And I think that the mojo that carried throughout this week, it's really challenging to not only have a show that's five days, >> but to go through all week, >> Savannah: Seriously. >> to a Friday at 4:00 PM Eastern Time, and still have the people here, the energy and all the collaboration. >> Savannah: Yeah. >> The conversations that are still happening. I think we're going to see a lot more innovation come spring 2023. >> Savannah: Mm-hmm. >> Yeah. >> So should we do a bet, somebody's got to buy dinner? Who, well, I guess the folks who lose this will buy dinner for the other one. How many attendees do you think we'll see in Amsterdam? So we had 4,000, >> Oh, I'm going to lose this one. >> roughly in Los Angeles. Priyanka was nice enough to share with us, there was 8,000 here in Detroit. And I'm talking in person, we're not going to meddle this with the online. >> 6500. >> Lisa: I was going to say six, six K. >> I'm going 12,000. >> Ooh! >> I'm going to go ahead and go big I'm going to go opposite Price Is Right. >> One dollar. >> Yeah. (all laugh) That's exactly where I was driving with it. I'm going, I'm going absolutely all in. I think the momentum here is building. I think if we look at the numbers from-- >> John: You could go Family Feud >> Yeah, yeah, exactly. And they mentioned that they had 11,000 people who have taken their Kubernetes course in that first year. If that's a benchmark and an indicator, we've got the veteran players here. But I do think that, I personally think that the hype of Kubernetes has actually preceded adoption. If you look at the data and now we're finally tipping over. I think the last two years we were on the fringe and right now we're there. It's great. (voice blares loudly on loudspeaker) >> Well, on that note (all laugh) On that note, actually, on that note, as we are talking, so I got to give cred to my cohosts. We deal with a lot of background noise here on theCUBE. It is a live show floor. There's literally someone on an e-scooter behind me. There's been Pong going on in the background. The sound will haunt the three of us for the rest of our lives, as well as the production crew. (Lisa laughs) And, and just as we're sitting here doing this segment last night, they turned the lights off on us, today they're letting everyone know that the event is over. So on that note, I just want to say, Lisa, thank you so much. Such a warm welcome to the team. >> Thank you. >> John, what would we do without you? >> You did an amazing job. First CUBE, three days. It's a big show. You got staying power, I got to say. >> Lisa: Absolutely. >> Look at that. Not bad. >> You said it on camera now. >> Not bad. >> So you all are stuck with me. (all laugh) >> A plus. Great job to the team. Again, we do so much flow here. Brandon, Team, Andrew, Noah, Anderson, Frank. >> They're doing our hair, they're touching up makeup. They're helping me clean my teeth, staying hydrated. >> We look good because of you. >> And the guests. Thanks for coming on and spending time with us. And of course the sponsors, again, we can't do it without the sponsors. If you're watching this and you're a sponsor, support theCUBE, it helps people get what they need. And also we're do a lot more segments around community and a lot more educational stuff. >> Savannah: Yeah. So we're going to do a lot more in the EU and beyond. So thank you. >> Yeah, thank you. And thank you to everyone. Thank you to the community, thank you to theCUBE community and thank you for tuning in, making it possible for us to have somebody to talk to on the other side of the camera. My name is Savannah Peterson for the last time in Detroit, Michigan. Thanks for tuning into theCUBE. >> Okay, we're done. (bright upbeat music)

(bright upbeat music) >> Welcome back to Detroit guys and girls. Lisa Martin here with John Furrier. We've been on the floor at KubeCon + CloudNativeCon North America for about two days now. We've been breaking news, we would have a great conversations, John. We love talking with CUBE alumni whose companies are just taking off. And we get to do that next again. >> Well, this next segment's awesome. We have former CUBE host, Brian Gracely, here who's an executive in this company. And then the entrepreneur who we're going to talk with. She was on theCUBE when it just started now they're extremely successful. It's going to be a great conversation. >> It is, Idit Levine is here, the founder and CEO of solo.io. And as John mentioned, Brian Gracely. You know Brian. He's the VP of Product Marketing and Product Strategy now at solo.io. Guys, welcome to theCUBE, great to have you here. >> Thanks for having us. >> Idit: Thank so much for having us. >> Talk about what's going on. This is a rocket ship that you're riding. I was looking at your webpage, you have some amazing customers. T-Mobile, BMW, Amex, for a marketing guy it must be like, this is just- >> Brian: Yeah, you can't beat it. >> Kid in a candy store. >> Brian: Can't beat it. >> You can't beat it. >> For giant companies like that, giant brands, global, to trust a company of our size it's trust, it's great engineering, it's trust, it's fantastic. >> Idit, talk about the fast trajectory of this company and how you've been able to garner trust with such mass organizations in such a short time period. >> Yes, I think that mainly is just being the best. Honestly, that's the best approach I can say. The team that we build, honestly, and this is a great example of one of them, right? And we're basically getting the best people in the industry. So that's helpful a lot. We are very, very active on the open source community. So basically it building it, anyway, and by doing this they see us everywhere. They see our success. You're starting with a few customers, they're extremely successful and then you're just creating this amazing partnership with them. So we have a very, very unique way we're working with them. >> So hard work, good code. >> Yes. >> Smart people, experience. >> That's all you need. >> It's simple, why doesn't everyone do it? >> It's really easy. (all laughing) >> All good, congratulations. It's been fun to watch you guys grow. Brian, great to see you kicking butt in this great company. I got to ask about the landscape because I love the ServiceMeshCon you guys had on a co-located event on day zero here as part of that program, pretty packed house. >> Brian: Yep. >> A lot of great feedback. This whole ServiceMesh and where it fits in. You got Kubernetes. What's the update? Because everything's kind of coming together- >> Brian: Right. >> It's like jello in the refrigerator it kind of comes together at the same time. Where are we? >> I think the easiest way to think about it is, and it kind of mirrors this event perfectly. So the last four or five years, all about Kubernetes, built Kubernetes. So every one of our customers are the ones who have said, look, for the last two or three years, we've been building Kubernetes, we've had a certain amount of success with it, they're building applications faster, they're deploying and then that success leads to new challenges, right? So we sort of call that first Kubernetes part sort of CloudNative 1.0, this and this show is really CloudNative 2.0. What happens after Kubernetes service mesh? Is that what happens after Kubernetes? And for us, Istio now being part of the CNCF, huge, standardized, people are excited about it. And then we think we are the best at doing Istio from a service mesh perspective. So it's kind of perfect, perfect equation. >> Well, I'll turn it on, listen to your great Cloud cast podcast, plug there for you. You always say what is it and what isn't it? >> Brian: Yeah. >> What is your product and what isn't it? >> Yeah, so our product is, from a purely product perspective it's service mesh and API gateway. We integrate them in a way that nobody else does. So we make it easier to deploy, easier to manage, easier to secure. I mean, those two things ultimately are, if it's an internal API or it's an external API, we secure it, we route it, we can observe it. So if anybody's, you're building modern applications, you need this stuff in order to be able to go to market, deploy at scale all those sort of things. >> Idit, talk about some of your customer conversations. What are the big barriers that they've had, or the challenges, that solo.io comes in and just wipes off the table? >> Yeah, so I think that a lot of them, as Brian described it, very, rarely they had a success with Kubernetes, maybe a few clusters, but then they basically started to on-ramp more application on those clusters. They need more cluster maybe they want multi-class, multi-cloud. And they mainly wanted to enable the team, right? This is why we all here, right? What we wanted to eventually is to take a piece of the infrastructure and delegate it to our customers which is basically the application team. So I think that that's where they started to see the problem because it's one thing to take some open source project and deploy it very little bit but the scale, it's all about the scale. How do you enable all those millions of developers basically working on your platform? How do you scale multi-cloud? What's going on if one of them is down, how do you fill over? So that's exactly the problem that they have >> Lisa: Which is critical for- >> As bad as COVID was as a global thing, it was an amazing enabler for us because so many companies had to say... If you're a retail company, your front door was closed, but you still wanted to do business. So you had to figure out, how do I do mobile? How do I be agile? If you were a company that was dealing with like used cars your number of hits were through the roof because regular cars weren't available. So we have all these examples of companies who literally overnight, COVID was their digital transformation enabler. >> Lisa: Yes. Yes. >> And the scale that they had to deal with, the agility they had to deal with, and we sort of fit perfectly in that. They re-looked at what's our infrastructure look like? What's our security look like? We just happened to be right place in the right time. >> And they had skillset issues- >> Skillsets. >> Yeah. >> And the remote work- >> Right, right. >> Combined with- >> Exactly. >> Modern upgrade gun-to-the-head, almost, kind of mentality. >> And we're really an interesting company. Most of the interactions we do with customers is through Slack, obviously it was remote. We would probably be a great Slack case study in terms of how to do business because our customers engage with us, with engineers all over the world, they look like one team. But we can get them up and running in a POC, in a demo, get them through their things really, really fast. It's almost like going to the public cloud, but at whatever complexity they want. >> John: Nice workflow. >> So a lot of momentum for you guys silver linings during COVID, which is awesome we do hear a lot of those stories of positive things, the acceleration of digital transformation, and how much, as consumers, we've all benefited from that. Do you have one example, Brian, as the VP of product marketing, of a customer that you really think in the last two years just is solo.io's value proposition on a platter? >> I'll give you one that I think everybody can understand. So most people, at least in the United States, you've heard of Chick-fil-A, retail, everybody likes the chicken. 2,600 stores in the US, they all shut down and their business model, it's good food but great personal customer experience. That customer experience went away literally overnight. So they went from barely anybody using the mobile application, and hence APIs in the backend, half their business now goes through that to the point where, A, they shifted their business, they shifted their customer experience, and they physically rebuilt 2,600 stores. They have two drive-throughs now that instead of one, because now they have an entire one dedicated to that mobile experience. So something like that happening overnight, you could never do the ROI for it, but it's changed who they are. >> Lisa: Absolutely transformative. >> So, things like that, that's an example I think everybody can kind of relate to. Stuff like that happened. >> Yeah. >> And I think that's also what's special is, honestly, you're probably using a product every day. You just don't know that, right? When you're swiping your credit card or when you are ordering food, or when you using your phone, honestly the amount of customer they were having, the space, it's like so, every industry- >> John: How many customers do you have? >> I think close to 200 right now. >> Brian: Yeah. >> Yeah. >> How many employees, can you gimme some stats? Funding, employees? What's the latest statistics? >> We recently found a year ago $135 million for a billion dollar valuation. >> Nice. >> So we are a unicorn. I think when you took it we were around like 50 ish people. Right now we probably around 180, and we are growing, we probably be 200 really, really quick. And I think that what's really, really special as I said the interaction that we're doing with our customers, we're basically extending their team. So for each customer is basically a Slack channel. And then there is a lot of people, we are totally global. So we have people in APAC, in Australia, New Zealand, in Singapore we have in AMEA, in UK and in Spain and Paris, and other places, and of course all over US. >> So your use case on how to run a startup, scale up, during the pandemic, complete clean sheet of paper. >> Idit: We had to. >> And what happens, you got Slack channels as your customer service collaboration slash productivity. What else did you guys do differently that you could point to that's, I would call, a modern technique for an entrepreneurial scale? >> So I think that there's a few things that we are doing different. So first of all, in Solo, honestly, there is a few things that differentiated from, in my opinion, most of the companies here. Number one is look, you see this, this is a lot, a lot of new technology and one of the things that the customer is nervous the most is choosing the wrong one because we saw what happened, right? I don't know the orchestration world, right? >> John: So choosing and also integrating multiple things at the same time. >> Idit: Exactly. >> It's hard. >> And this is, I think, where Solo is expeditious coming to place. So I mean we have one team that is dedicated like open source contribution and working with all the open source community and I think we're really good at picking the right product and basically we're usually right, which is great. So if you're looking at Kubernetes, we went there for the beginning. If you're looking at something like service mesh Istio, we were all envoy proxy and out of process. So I think that by choosing these things, and now Cilium is something that we're also focusing on. I think that by using the right technology, first of all you know that it's very expensive to migrate from one to the other if you get it wrong. So I think that's one thing that is always really good at. But then once we actually getting those portal we basically very good at going and leading those community. So we are basically bringing the customers to the community itself. So we are leading this by being in the TOC members, right? The Technical Oversight Committee. And we are leading by actually contributing a lot. So if the customer needs something immediately, we will patch it for him and walk upstream. So that's kind of like the second thing. And the third one is innovation. And that's really important to us. So we pushing the boundaries. Ambient, that we announced a month ago with Google- >> And STO, the book that's out. >> Yes, the Ambient, it's basically a modern STO which is the future of SDL. We worked on it with Google and their NDA and we were listed last month. This is exactly an example of us basically saying we can do it better. We learn from our customers, which is huge. And now we know that we can do better. So this is the third thing, and the last one is the partnership. I mean honestly we are the extension team of the customer. We are there on Slack if they need something. Honestly, there is a reason why our renewal rate is 98.9 and our net extension is 135%. I mean customers are very, very happy. >> You deploy it, you make it right. >> Idit: Exactly, exactly. >> The other thing we did, and again this was during COVID, we didn't want to be a shell-for company. We didn't want to drop stuff off and you didn't know what to do with it. We trained nearly 10,000 people. We have something called Solo Academy, which is free, online workshops, they run all the time, people can come and get hands on training. So we're building an army of people that are those specialists that have that skill set. So we don't have to walk into shops and go like, well okay, I hope six months from now you guys can figure this stuff out. They're like, they've been doing that. >> And if their friends sees their friend, sees their friend. >> The other thing, and I got to figure out as a marketing person how to do this, we have more than a few handfuls of people that they've got promoted, they got promoted, they got promoted. We keep seeing people who deploy our technologies, who, because of this stuff they're doing- >> John: That's a good sign. They're doing it at at scale, >> John: That promoter score. >> They keep getting promoted. >> Yeah, that's amazing. >> That's a powerful sort of side benefit. >> Absolutely, that's a great thing to have for marketing. Last question before we ran out of time. You and I, Idit, were talking before we went live, your sessions here are overflowing. What's your overall sentiment of KubeCon 2022 and what feedback have you gotten from all the customers bursting at the seam to come talk to you guys? >> I think first of all, there was the pre-event which we had and it was a lot of fun. We talked to a lot of customer, most of them is 500, global successful company. So I think that people definitely... I will say that much. We definitely have the market feed, people interested in this. Brian described very well what we see here which is people try to figure out the CloudNative 2.0. So that's number one. The second thing is that there is a consolidation, which I like, I mean STO becoming right now a CNCF project I think it's a huge, huge thing for all the community. I mean, we're talking about all the big tweak cloud, we partner with them. I mean I think this is a big sign of we agree which I think is extremely important in this community. >> Congratulations on all your success. >> Thank you so much. >> And where can customers go to get their hands on this, solo.io? >> Solo.io? Yeah, absolutely. >> Awesome guys, this has been great. Congratulations on the momentum. >> Thank you. >> The rocket ship that you're riding. We know you got to get to the airport we're going to let you go. But we appreciate your insights and your time so much, thank you. >> Thank you so much. >> Thanks guys, we appreciate it. >> A pleasure. >> Thanks. >> For our guests and John Furrier, This is Lisa Martin live in Detroit, had to think about that for a second, at KubeCon 2022 CloudNativeCon. We'll be right back with our final guests of the day and then the show wraps, so stick around. (gentle music)

>>the Cube presents H P E discovered 2022. Brought to you by H P E. >>Hi, buddy Dave Balon and Jon Ferrier Wrapping up the cubes. Coverage of day two, hp Discover 2022. We're live from Las Vegas. Vishal Lall is here. He's the senior vice president and general manager for HP ES Green Lake Cloud Services Solutions. Michelle, good to see you again. >>Likewise. David, good to see you. It was about a year ago that we met here. Or maybe nine months >>ago. That's right. Uh, September of last year. A new role >>for you. Is that right? I was starting that new role when I last met you. Yeah, but it's been nine months. Three quarters? What have you learned so far? I mean, it's been quite a right, right? I mean, when I was starting off, I had, you know, about three priorities we've executed on on all of them. So, I mean, if you remember back then they we talked about, you know, improving a cloud experience. We talked about data and analytics being a focus area and then building on the marketplace. I think you heard a lot of that over the last couple of days here. Right? So we've enhanced our cloud experience. We added a private cloud, which was the big announcement yesterday or day before yesterday that Antonio made so that's been I mean, we've been testing that with customers. Great feedback so far. Right? And we're super excited about that. And, uh, you know, uh, down there, the test drive section people are testing that. So we're getting really, really good feedback. Really good acceptance from customers on the data and Analytics side. We you know, we launched the S three connector. We also had the analytics platform. And then we launched data fabric as a service a couple of days ago, right, which is kind of like back into that hybrid world. And then on the marketplace side, we've added a tonne of partners going deep with them about 80 plus partners now different SVS. So again, I think, uh, great. I think we've accomplished a lot over the last three quarters or so lot more to be done. Though >>the marketplace is really interesting to us because it's a hallmark of cloud. You've got to have a market price. Talk about how that's evolving and what your vision is for market. Yes, >>you're exactly right. I mean, having a broad marketplace provides a full for the platform, right? It's a chicken and egg. You need both. You need a good platform on which a good marketplace can set, but the vice versa as well. And what we're doing two things there, Right? One Is we expanding coverage of the marketplace. So we're adding more SVS into the marketplace. But at the same time, we're adding more capabilities into the marketplace. So, for example, we just demoed earlier today quickly deploy capabilities, right? So we have an I S p in the marketplace, they're tested. They are, uh, the work with the solution. But now you can you can collect to deploy directly on our infrastructure over time, the lad, commerce capabilities, licencing capabilities, etcetera. But again, we are super excited about that capability because I think it's important from a customer perspective. >>I want to ask you about that, because that's again the marketplace will be the ultimate arbiter of value creation, ecosystem and marketplace. Go hand in hand. What's your vision for what a successful ecosystem looks like? What's your expectation now that Green Lake is up and running. I stay up and running, but like we've been following the announcement, it just gets better. It's up to the right. So we're anticipating an ecosystem surge. Yeah. What are you expecting? And what's your vision for? How the ecosystem is going to develop out? Yeah. I >>mean, I've been meeting with a lot of our partners over the last couple of days, and you're right, right? I mean, I think of them in three or four buckets right there. I s V s and the I S P is coming to two forms right there. Bigger solutions, right? I think of being Nutanix, right, Home wall, big, bigger solutions. And then they are smaller software packages. I think Mom would think about open source, right? So again, one of them is targeted to developers, the other to the I t. Tops. But that's kind of one bucket, right? I s P s, uh, the second is around the channel partners who take this to market and they're asking us, Hey, this is fantastic. Help us understand how we can help you take this to market. And I think the other bucket system indicators right. I met with a few today and they're all excited about. They're like, Hey, we have some tooling. We have the manage services capabilities. How can we take your cloud? Because they build great practise around extent around. Sorry. Aws around? Uh, sure. So they're like, how can we build a similar practise around Green Lake? So again, those are the big buckets. I would say. Yeah, >>that's a great answer. Great commentary. I want to just follow up on that real quick. You don't mind? So a couple things we're seeing observing I want to get your reaction to is with a i machine learning. And the promise of that vertical specialisation is creating unique opportunities on with these platforms. And the other one is the rise of the managed service provider because expertise are hard to come by. You want kubernetes? Good luck finding talent. So managed services seem to be exploding. How does that fit into the buckets? Or is it all three buckets or you guys enable that? How do you see that coming? And then the vertical piece? >>A really good question. What we're doing is through our software, we're trying to abstract a lot of the complexity of take communities, right? So we are actually off. We have actually automated a whole bunch of communities functionality in our software, and then we provide managed services around it with very little. I would say human labour associated with it is is software manage? But at the same time we are. What we are trying to do is make sure that we enable that same functionality to our partners. So a lot of it is software automation, but then they can wrap their services around it, and that way we can scale the business right. So again, our first principle is automated as much as we can to software right abstract complexity and then as needed, uh, at the Manus Services. >>So you get some functionality for HP to have it and then encourage the ecosystem to fill it in or replicated >>or replicated, right? I mean, I don't think it's either or it should be both right. We can provide many services or we should have our our partners provide manage services. That's how we scale the business. We are the end of the day. We are product and product company, right, and it can manifest itself and services. That discussion was consumed, but it's still I p based. So >>let's quantify, you know, some of that momentum. I think the last time you call your over $800 million now in a are are you gotta You're growing at triple digits. Uh, you got a big backlog. Forget the exact number. Uh, give us a I >>mean, the momentum is fantastic Day. Right. So we have about $7 billion in total contract value, Right? Significant. We have 1600 customers now. Unique customers are running Green Lake. We have, um, your triple dip growth year over year. So the last quarter, we had 100% growth year over year. So again, fantastic momentum. I mean, the other couple, like one other metric I would like to talk about is the, um the stickiness factor associated tension in our retention, right? As renewal's is running in, like, high nineties, right? So if you think about it, that's a reflection of the value proposition of, like, >>that's that's kind of on a unit basis, if you will. That's the number >>on the revenue basis on >>revenue basis. Okay? >>And the 1600 customers. He's talking about the size and actually big numbers. Must be large companies that are. They're >>both right. So I'll give you some examples, right? So I mean, there are large companies. They come from different industries. Different geography is we're seeing, like, the momentum across every single geo, every single industry. I mean, just to take some examples. BMW, for example. Uh, I mean, they're running the entire electrical electric car fleet data collection on data fabric on Green Lake, right? Texas Children's Health on the on the healthcare side. Right On the public sector side, I was with with Carl Hunt yesterday. He's the CEO of County of Essex, New Jersey. So they are running the entire operations on Green Lake. So just if you look at it, Barclays the financial sector, right? I mean, they're running 100,000 workloads of three legs. So if you just look at the scale large companies, small companies, public sector in India, we have Steel Authority of India, which is the largest steel producer there. So, you know, we're seeing it across multiple industries. Multiple geography is great. Great uptake. >>Yeah. We were talking yesterday on our wrap up kind of dissecting through the news. I want to ask you the question that we were riffing on and see if we can get some clarity on it. If I'm a customer, CI or C so or buyer HP have been working with you or your team for for years. What's the value proposition? Finish this sentence. I work with HPV because blank because green like, brings new value proposition. What is that? Fill in that blank for >>me. So I mean, as we, uh, talked with us speaking with customers, customers are looking at alternatives at all times, right? Sometimes there's other providers on premises, sometimes as public cloud. And, uh, as we look at it, uh, I mean, we have value propositions across both. Right. So from a public cloud perspective, some of the challenges that our customers cr around latency around, uh, post predictability, right? That variability cost is really kind of like a challenge. It's around compliance, right? Uh, things of that nature is not open systems, right? I mean, sometimes, you know, they feel locked into a cloud provider, especially when they're using proprietary services. So those are some of the things that we have solved for them as compared to kind of like, you know, the other on premises vendors. I would say the marketplace that we spoke about earlier is huge differentiator. We have this huge marketplace. Now that's developing. Uh, we have high levels of automation that we have built, right, which is, uh, you know, which tells you about the TCO that we can drive for the customers. What? The other thing that is really cool that be introduced in the public in the private cloud is fungible itty across infrastructure. Right? So basically on the same infrastructure you can run. Um, virtual machines, containers, bare metals, any application he wants, you can decommission and commission the infrastructure on the fly. So what it does, is it no matter where it is? Uh, on premises, right? Yeah, earlier. I mean, if you think about it, the infrastructure was dedicated for a certain application. Now we're basically we have basically made it compose herbal, right? And that way, what? Really? Uh, that doesnt increases utilisation so you can get increased utilisation. High automation. What drives lower tco. So you've got a >>horizontal basically platform now that handle a variety of work and >>and these were close. Can sit anywhere to your point, right? I mean, we could have a four node workload out in a manufacturing setting multiple racks in a data centre, and it's all run by the same cloud prints, same software train. So it's really extensive. >>And you can call on the resources that you need for that particular workload. >>Exactly what you need them exactly. Right. >>Excellent. Give you the last word kind of takeaways from Discover. And where when we talk, when we sit down and talk next year, it's about where do you want to be? >>I mean, you know, I think, as you probably saw from discovered, this is, like, very different. Antonio did a live demo of our product, right? Uh, visual school, right? I mean, we haven't done that in a while, so I mean, you started. It >>didn't die like Bill Gates and demos. No, >>no, no, no. I think, uh, so I think you'll see more of that from us. I mean, I'm focused on three things, right? I'm focused on the cloud experience we spoke about. So what we are doing now is making sure that we increase the time for that, uh, make it very, you know, um, attractive to different industries to certifications like HIPAA, etcetera. So that's kind of one focus. So I just drive harder at that adoption of that of the private out, right across different industries and different customer segments. The second is more on the data and analytics I spoke about. You will have more and more analytic capabilities that you'll see, um, building upon data fabric as a service. And this is a marketplace. So that's like it's very specific is the three focus areas were driving hard. All right, we'll be watching >>number two. Instrumentation is really keen >>in the marketplace to I mean, you mentioned Mongo. Some other data platforms that we're going to see here. That's going to be, I think. Critical for Monetisation on the on on Green Lake. Absolutely. Uh, Michelle, thanks so much for coming back in the Cube. >>Thank you. Thanks for coming. All >>right, keep it right. There will be John, and I'll be back up to wrap up the day with a couple of heavies from I d. C. You're watching the cube. Mhm. Mm mm. Mhm.

>> Narrator: The cube presents, the Kubecon and Cloudnativecon Europe, 2022 brought to you by Red Hat, the cloud native computing foundation and its ecosystem partners. >> Welcome to Valencia, Spain in Kubecon and Cloudnativecon Europe, 2022. I'm your host Keith Townsend. It's been a amazing day, three days of coverage 7,500 people, 170 sponsors, a good mix of end user organizations, vendors, just people with open source at large. I've loved the conversations. We're not going to stop that coverage just because this is the last session of the conference. Colin Murphy, senior software engineer, Adobe, >> Adobe. >> Oh, wow. This is going to be fun. And then Liam Randall, the chair of CNCF Cloud Native WebAssembly Day. >> That's correct. >> And CNCF & CEO of Cosmonic. >> That's right. >> All right. First off, let's talk about the show. How has this been different than other, if at all of other Kubecons? >> Well, first I think we all have to do a tremendous round of applause, not only for the vendors, but the CNC staff and all the attendees for coming out. And you have to say, Kubecon is back. The online experiences have been awesome but this was the first one, where Hallwaycon was in full effect. And you had the opportunity to sit down and meet with so many intelligent and inspiring peers and really have a chance to learn about all the exciting innovations that have happened over the last year. >> Colin. >> Yeah, it's been my most enjoyable Kubecon I've ever been to. And I've been to a bunch of them over the last few years. Just the quality of people. The problems that we're solving right now, everywhere from this newer stuff that we're talking about today with WebAssembly but then all these big enterprises trying to getting involved in Kubernetes >> Colin, to your point about the problems that we're solving, in many ways the pandemic has dramatically accelerated the pace of innovation, especially inside the CNCF, which is by far the most critical repository of open source projects that enterprises, governments and individuals rely on around the world, in order to deliver new experiences and to have coped and scaled out within the pandemic over the last few years. >> Yeah, I'm getting this feel, this vibe of the overall show that feels like we're on the cuff for something. There's other shows throughout the year, that's more vendor focused that talk about cloud native. But I think this is going to be the industry conference where we're just getting together and talking about it and it's going to probably be, in the next couple of years, the biggest conference of the year, that's just my personal opinion. >> I actually really strongly agree with you. And I think that the reason for that is the diversity that we get from the open source focus of Kubecon Kubecon has started where the industry really started which was in shared community projects. And I was the executive at Capital One that led the donation of cloud custodian into the CNCF. And I've started and put many projects here. And one of the reasons that you do that is so that you can build real scalable communities, Vendors that oftentimes even have competing interest but it gives us a place where we can truly collaborate where we can set aside our personal agendas and our company's agendas. And we can focus on the problems at hand. And how do we really raise the bar for technology for everybody. >> Now you two are representing a project that, you know as we look at kind of, how the web has evolved the past few decades, there's standards, there's things that we know that work, there's things that we know that don't work and we're beyond cloud native, we're kind of resistant to change. Funny enough. >> That's right. >> So WebAssembly, talk to me about what problem is WebAssembly solving that need solving? >> I think it's fitting that here on the last day of Kubecon, we're starting with the newest standard for the web and for background, there's only four languages that make up what we think of as the modern web. There's JavaScript, there's HTML, there's CSS, and now there's a new idea that's WebAssembly. And it's maybe not a new idea but it's certainly a new standard, that's got massive adoption and acceleration. WebAssembly is best thought of as almost like a portable little virtual machine. And like a lot of great ideas like JavaScript, it was originally designed to bring new experiences to browsers everywhere. And as organizations looked at the portability and security value props that come from this tiny little virtual machine, it's made a wonderful addition to backend servers and as a platform for portability to bring solutions all the way out to the edge. >> So what are some of the business cases for WebAssembly? Like what problem, what business problem are we solving? >> So it, you know, we would not have been able to bring Photoshop to the web without WASM. >> Wow. >> And just to be clear, I had nothing to do with that effort. So I want to make sure everybody understands, but if you have a lot of C++ or C code and you want to bring that experience to the web browser which is a great cost savings, cause it's running on the client's machines, really low latency, high performance experiences in the browser, WASM, really the only way to go. >> So I'm getting hints of fruit berry, Java. >> Liam: Yeah, absolutely. >> Colin: Definitely. >> You know, the look, WebAssembly sounds similar to promises you've heard before, right ones, run anywhere. The difference is, is that WebAssembly is not driven by any one particular vendor. So there's no one vendor that's trying to bring a plug in to every single device. WebAssembly was a recognition, much like Kubecon, the point that we started with around the diversity of thought ideas and representation of shared interest, of how do we have a platform that's polyglot? Many people can bring languages to it, and solutions that we can share and then build from there. And it is unlocking some of the most amazing and innovative experiences, both on the web backend servers and all the way to the edge. Because WebAssembly is a tiny little virtual machine that runs everywhere. Adobe's leadership is absolutely incredible with the things that they're doing with WebAssembly. They did this awesome blog post with the Google Chrome team that talked about other performance improvements that were brought into Chrome and other browsers, in order to enable that kind of experience. >> So I get the general concept of WebAssembly and it's one of those things that I have to ask the question, and I appreciate that Adobe uses it but without the community, I mean, I've dedicated some of my team's resources over the years to some really cool projects and products that just died on the buying cause there was no community around. >> Yeah. >> Who else uses WebAssembly? >> Yeah, I think so. We actually, inside the CNCF now, have an entire day devoted just to WebAssembly and as the co-chair of the CNCF Cloud Native WebAssembly Day, we really focus on bringing those case studies to the forefront. So some of the more interesting talks that we had here and at some of the precursor weekend conferences were from BMW, for example, they talked about how they were excited about not only WebAssembly, but a framework that they use on WebAssembly called WASM cloud, that lets them a flexibly scale machine learning models from their own edge, in their own vehicles through to their developer's workstations and even take that data onto their regular cloud Kubernetes and scale analysis and analytics. They invested and they just released a machine learning framework for one of the many great WebAssembly projects called WASM cloud, which is a CNCF project, a member project here in the CNCF. >> So how does that fit in overall landscape? >> So think of WebAssembly, like you think of HTML. It's a technology that gives you a lot of concept and to accelerate your journey on those technologies, people create frameworks. For example, if you were going to write a UI, you would not very likely start with an empty document you'd start with a react or view. And in a similar vein, if you were going to start a new microservice or backend application, project for WebAssembly, you might use WASM cloud or you might use ATMO or you might use a Spin. Those are three different types of projects. They all have their own different value props and their own different opinions that they bring to them. But the point is is that this is a quickly evolving space and it's going to dramatically change the type of experiences that we bring, not only to web browsers but to servers and edges everywhere. >> So Colin, you mentioned C+ >> Colin: Yeah. >> And other coding. Well , talk to me about the ramp up. >> Oh, well, so, yeah, so, C++ there was a lot of work done in scripting, at Adobe. Taking our C++ code and bringing it into the browser. A lot of new instructions, Cimdi, that were brought to make a really powerful experience, but what's new now is the server side aspect of things. So, just what kind of, what Liam was talking about. Now we can run this stuff in the data center. It's not just for people's browsers anymore. And then we can also bring it out to the edge too, which is a new space that we can take advantage of really almost only through WebAssembly and some JavaScript. >> So wait, let me get this kind of under hook. Before, if I wanted a rich experience, I have to run a heavy VDI instance on the back end so that I'm basically getting remote desktop calls from a light thin client back to my backend server, that's heavy. >> That is heavy. >> WebAssembly is alternative to that? >> Yes, absolutely. Think of WebAssembly as a tiny little CPU that is a shim, that we can take the places that don't even traditionally have a concept of a processor. So inside the browser, for example, traditionally cloud native development on the backend has been dominated by things like Docker and Docker is a wonderful technology and Container is a wonderful technology that really drove the last 10 years of cloud native with the great lift and shift, if you will. Take our existing applications, package them up in this virtual desktop and then deliver them. But to deliver the next 10 years of experiences, we need solutions that let us have portability first and a security model that's portable across the entire landscape. So this isn't just browsers and servers on the back end, WebAssembly creates an a layer of equality from truly edge to edge. It's can transcend different CPUs, different operating systems. So where containers have this lower bound off you need to be running Linux and you need to be in a place where you're going to bring Kubernetes. WebAssembly is so small and portable, it transcends that lower bound. It can go to places like iOS. It can go to places like web browsers. It can even go to teeny tiny CPUs that don't even traditionally have a full on operating systems inside them. >> Colin: Right, places where you can't run Docker. >> So as I think about that, and I'm a developer and I'm running my back end and I'm running whatever web stack that I want, how does this work? Like, how do I get started with it? >> Well, there's some great stuff Liam already mentioned with WASM cloud and Frmion Spin. Microsoft is heavily involved now on providing cloud products that can take advantage of WebAssembly. So we've got a lot of languages, new languages coming in.net and Ruby, Rust is a big one, TinyGo, really just a lot of places to get involved. A lot of places to get started. >> At the highest level Finton Ryan, when he was at Gartner, he's a really well known analyst. He wrote something profound a few years ago. He said, WebAssembly is the one technology, You don't need a strategy to adopt. >> Mm. >> Because frankly you're already using it because there's so many wonderful experiences and products that are out there, like what Adobe's doing. This virtual CPU is not just a platform to run on cloud native and to build applications towards the edge. You can embed this virtual CPU inside of applications. So cases where you would want to allow your users to customize an application or to extend functionality. Give you an example, Shopify is a big believer in WebAssembly because while their platform covers, two standard deviations or 80% of the use cases, they have a wonderful marketplace of extensions that folks can use in order to customize the checkout process or apply specialized discounts or integrate into a partner ecosystem. So when you think about the requirements for those scenarios, they line up to the same requirements that we have in browsers and servers. I want real security. I want portability. I want reuseability. And ultimately I want to save money and go faster. So organizations everywhere should take a few minutes and do a heads up and think about one, where WebAssembly is already in their environment, inside of places like Envoy and Istio, some of the most popular projects in the cloud native ecosystem, outside of Kubernetes. And they should perhaps consider studying, how WebAssembly can help them to transform the experiences that they're delivering for their customers. This may be the last day of Kubecon, but this is certainly not the last time we're going to be talking about WebAssembly, I'll tell you that. >> So, last question, we've talked a lot about how to get started. How about day two, when I'm thinking about performance troubleshooting and ensuring clients have a great experience what's day two operation like? >> That's a really good question. So there's, I know that each language kind of brings their own tool chain and their, and you know we saw some great stuff on, on WASM day. You can look it up around the .net experience for debugging, They really tried to make it as seamless and the same as it was for native code. So, yeah, I think that's a great question. I mean, right now it's still trying to figure out server side, It's still, as Liam said, a shifting landscape. But we've got some great stuff out here already >> You know, I'd make an even bigger call than that. When I think about the last 20 years as computing has evolved, we've continued to move through these epics of tech that were dominated by a key abstraction. Think about the rise of virtualization with VMware and the transition to the cloud. The rise of containerization, we virtualized to OS. The rise of Kubernetes and CNCF itself, where we virtualize cloud APIs. I firmly believe that WebAssembly represents the next epic of tech. So I think that day two WebAssembly continues to become one of the dominant themes, not only across cloud native but across the entire technical computing landscape. And it represents a fundamentally gigantic opportunity for organizations such as Adobe, that are always market leading and at the cutting edge of tech, to bring new experiences to their customers and for vendors to bring new platforms and tools to companies that want to execute on that opportunity. >> Colin Murphy, Liam Randall, I want to thank you for joining the Cube at Kubecon Cloudnativecon 2022. I'm now having a JavaScript based app that I want to re-look at, and maybe re-platforming that to WebAssembly. It's some lot of good stuff there. We want to thank you for tuning in to our coverage of Kubecon Cloudnativecon. And we want to thank the organization for hosting us, here from Valencia, Spain. I'm Keith Townsend, and you're watching the Cube, the leader in high tech coverage. (bright music)

>>Welcome back to the cubes cover dot com. Splunk annual conference >>Virtual this year. I'm john for >>your host of the cube as always we're being the best stories. The best guest to you and the best guest today is the ceo Doug merit of course, Top Dog. It's great to see you. Thanks for coming on to be seen. >>So nice. I can't believe it. We had a whole year without seeing each other. >>I love this conference because it's kind of like a studio taking over a full virtual studio multiple sets, cubes here. You have the main stage, you've got rooms upstairs, tons of virtual interactions. Great numbers. Congratulations. >>Thank you. Thank you. We were, we wanted this to be primarily live where we are live, primarily on site. Um, and we pivoted some private marketing team. How quickly they pivoted and I love the environment they've created as I know next year we will be always have virtual now we've all learned but will be on site, which is great. >>It's good to see kind of you guys telling the story a lot, a lot more stories happening and You know, we've been covering splint since 2012 on the Cube. I think longer than aws there was 2013 our first cube seeing Splunk emerge is the trend has been, it's new, it's got value and you operationalize it for customers. Something new happens. You operationalized for customers and it just keeps on the Splunk way, the culture of innovation. It just seems now more than ever. You guys were involved in security early 2015 I think that was the year we started kind of talking about it your first year and now it just feels like something bigger is right here in front of us. It's and people are trying to figure out multi cloud observe ability. We see that what that's a big growth wave coming. What's the wave that's happening? >>So uh the beauty of Splunk and the kind of culture and how we were born was we have this non structured backbone um what I would call the investigative lake where you just dump garbage into it and then get value out of it through the question asking which means you can traverse anywhere because you're not taking a point of view on the data it's usable all over the place. And that's how we went up in security. As we had the I. T. Systems administrators pinging that thing with with questions. And at that point in time the separate teams were almost always part of the I. T. Teams like hey can we ask questions that thing. It's like yeah go ahead. And also they got value. And then the product managers and the app dev guys started asking questions. And so a lot of our proliferation has been because of the underlying back bonus blank the ability for new people to come to the data and find value in the data. Um as you know and as our users know we have tried to stay very focused on the go to market basis on serving the technical triumphant the cyber teams, the infrastructure management, 90 ops teams and the abdomen devoPS teams and on the go to market basis and the solutions we package that is, we're trying to stay super pure to that. That's $90 billion of total addressable market. We're super excited will be well over three billion an error this year, which is amazing is 300 million when I started seven years ago so that 10 x and seven years is great. But three billion and 90 billion like we're all just getting going right now with those Corbyn centers. The were on top of what sean bison as we tell you about, hey, we've got to continue to focus on multi cloud and edge is really important. Machine learning is important. That the lever that we've been focused on for a long time that we'll continue to gain better traction on is making sure that we've got the right data plane and application platform layer so that the rest of the world can participate in building high quality reusable and recyclable applications so that operate operationalization that we have done officially around cyber it and devops and unofficially on a one off basis for marketing and supply chain and logistics and manufacturing that those other use cases can be packaged repeated, sold and supported by the people that really know those domains because we're not manufacturing experts. It's we're honored that portion BMW are using us to get operational insight into the manufacturing floor. But they lead that we just were there is the technical Splunk people to help bring that to life. But there are lots of firms out there, no manufacturing cold process versus the screed and they can create with these packages. They're appropriate for automotive, automotive versus paint versus wineries versus having that. I think the big Accelerant over the next 10 years response, we gotta keep penetrating our core use cases but it would be allowing our ecosystem and so happy Teresa Karlsson's here is just pounding the table and partners to take the other probably 90% of the market that is not covered by by our core market. >>Yeah, I think that's awesome. And the first time we get to the partner 1st and 2nd the rebranding of the ecosystem as it's growing. But you mentioned you didn't know manufacturing as an example where the value is being created. That's interesting because you guys are enabling that value, their adding that because they know their apps then they're experts. That's where the ecosystem is really gonna shine because if you can provide that enablement this control plane as you mentioned, that's going to feed the ecosystem. So the question I have for you is as you guys have become essentially the de facto control playing for most companies because they were using spring for a lot of other great reasons now you have set them up that way is the pattern to just keep building machine learning apps on top of it or more querying what's the what's the customer next level trends that you're seeing. >>So the two core focus areas that we will stay on top of is enriching that data platform and ensure that we continue to provide better at peace and better interfaces so that when people want to build a really interesting automotive parts, supply chain optimization app that they're able to do that, we've got the right A. P. S. We've got the right services, we've got the right separation between the application of platforms so they can get that done, we'll continue to advance that platform so that there's modernization capabilities and there's advertising capabilities and other pieces that they can make their business. The other piece that will stay very focused on is within the cyber realm within I. T. Ops within devops, ensuring that we're leveraging that platform, but baking ml and baking all the advanced edge and other capabilities into those solutions because the cyber teams as where you started with a You know, we really started reporting on cyber 2015, those guys have got such a hard job and while there's lots of people pretending like they're going to come in and serve them, it's the difficulty is there are hundreds of tools and technologies that the average C so deals with and the rate of innovation is not slowing down and those vendors that have a vested interest and I want to maintain my footprint and firewalls, I want to maintain an implant, I want to maintain. It's really hard for them to say, you know what? There are 25 other categories of tools and there's 500 vendors. You gotta play nicely with your competitors and know all those folks if you really want to provide the ml the detection, the remediation, The investigation capabilities. And that's where I'm really excited about the competition. The fake competition in many cases because like, yeah, bring it on. Like I've got 2000 engineers, all they do all day long is focused on the data layer and making sure that we're effective there and I'm not diverting my engineers with any other tasks that I've got a it's hard enough to do what we do in the day layers. Well, >>it's interesting. I just had some notes here, I had one data driven innovation you've been talking about since you've been here. We've been talking about data driven innovation, cybersecurity mentioned for many years, it's almost like the balance of you gotta have tools, but you gotta have the platform. If you have too many tools and no platform, then there's a mix match here and you get hung up with tools and these blind spots. You can't have blind spots, you can't have silos. This is what kind of everyone's pretty much agreeing on right now. It's not a debate. It's more like, okay, I got silos and I got blind spots. Well how do I solve >>the difficulty? And I touched a little bit of the sun my keynote of There are well over 60 and I was using 16 because DB engines categorizes 16 different database tools. But there's actually more if you go deeper. So there's different 16 different categories of database tools. Think relational database, data warehouse, ledger databases, graph database, et cetera over 16 categories those 350 vendors. That's not because we're all stupid in tech like a graph DB is different than a relational database, which is different than what we do with our stimulus index. So there's those categories that many vendors because they're trying to solve different problems within the swim lane that you are in which for us is this non structured, high volume difficult data to manage Now. The problem is how do you create that non broken that end to end view. So you can handle your use cases effectively. Um and then the customer is still going to do with the fact that we're not a relational database engine company. We're not a data warehousing company where we were beginning to use graph DB capabilities within our our solution sets. We're gonna lean on open source other vendors use the tool for the job >>you need. But I think that what you're thinking hitting on my like is this control plane idea. I want to get back to that because if you think about what the modern application developers want is they want devops and deVOps kind of one infrastructures codes there. But if I'm a modern developer, I just want to code, >>I don't want to configure >>the data or the infrastructure. So the data value now is so much more important for the developer, whether that's policy based innovation, get options, some people call it A I ops, these are big trends. This is fairly new in the sense of being mainstream. It's been around for a couple of years, but this time, how do you see the data being much more of a developer input. >>People talk about deVOps is a new thing when I was running on the HR products at Peoplesoft in 2000 and four, we had a deVOPS teams. So that is, you know, there's always been a group of people whether Disney or not that are kind of managing the manufacturing floor for your developers, making sure they got the right tools and databases and what's new is because the ephemeral nature of cloud, that app dev work and devops and everyone that surrounds those or is now 100% data driven because you have ephemeral services, they're popping up and popping down. And if you're not able to trap the data that are each one of those services are admitting and do it on a real time basis and a thorough, complete basis, you can't sample then you are flying blind and that's not gonna work when you've got a critical code push for a feature your customers demanding and if you don't get it out, your competitors are, you need to have assurance that you've done the right things and that the quality and and the actual deployment actually works And that's where what lettuce tubes or ability Three years ago as we roughly started doing our string of acquisitions is we saw that transition from a state full world where it was all transaction engine driven. I've got to insert transaction and engines in a code. Very different engineering problem to I've got to grab data and it's convoluted data. It's chaotic data. It's changing all the time. Well, jeez that sounds and latency >>issues to they're gonna be doing fast. >>I've got to do it. You literally millisecond by millisecond. You've got are are bigger customers were honored because of how we operate. Splunk to serve some of the biggest web properties in the in the globe and they're dealing with hundreds of terabytes to petabytes of data per day that are traversing these pipes and you've got to be able to extract metrics that entire multi petabyte or traces that entire multi pedal extreme and you can't hope you're guessing right by only extracting from portions of it because again, if you missed that data you've missed it forever. So for us that was a data problem, which is why we stepped in and >>other things That data problem these days, it's almost it's the most fun to talk about if you love the problem statement that we're trying to solve. I want to get your reaction something if you don't mind. I was talking to a C. So in the C. I. O. We have a conversation kind of off camera at an event recently and I said what's the biggest challenge that you have? Just curious? I asked him, it's actually it's personnel people are mad at each other. Developers want to go faster because there are ci cd pipeline is devops their coding. They're having to wait for the security groups in some cases weeks and days when they could do it in minutes they want to do it on the in the pipelines, shifting left as some call it and it's kind of getting in the way. So it's kind of like it's not they're not getting along very well uh meaning they're slowing things down. I can say something what they really said, but they weren't getting along. What's your reaction? Because that seems to be a speed scale problem. That's developer centric, not organizational, you've got organizational challenges and being slowed down. >>So uh while we all talk about this converted landscape and how exciting is going to be. You do have diametrically opposed metrics and you're never going to have, it's very difficult to get a single person to have the same allegiance to those diametrically a virgin metrics as you want. So you've got checks and balances and the reality of what the cyber teams need to be doing to ensure that you aren't just coding effective functions with the right delivery timeframe. But that's also secure is I think going to make the security team is important forever and the same thing. You can't just write sloppy code that consumes, that blows your AWS budget or G. C. P budget within the first week of deploying it because you've still got to run a responsible business. So there are different dimensions that we all have to deal with quality time and feature functionality that different groups represent. So we, I believe a converged landscape is important. It's not that we're gonna blow it up and one person is going to do it all if you've got to get those groups talking better and you've got to reduce cycle times now we believe it's plunk is with a common data plane, which is the backbone and then solutions built from that common data plane to serve those groups. You're lessening the lack of understanding and you're reducing the cycle time. So now I can look when I'm publishing the code. If it's done properly, is it also secure And the cyber teams can kind of be flying in saying, hey, wait, wait, wait, we just saw something in the data says we're not quite ready. I'm sorry. I know you want to push, you can't push now, but there'll be a data driven conversation and not this, you shouldn't be waiting a week or two weeks, like we can't operate that scale and you've got to address people with facts and data and logic and that's what we're trying to get done. And you >>guys have a good policy engine, you can put up that up into the pipeline. So awesome. That's great, great insight there. Thanks for sharing. Final question. Um looking back in your time since you've been Ceo the culture kind of hasn't changed at Splunk, it's still they have fun, hard charging laid back a little bit and public company now, he's still got to meet the numbers, but your growing business is good, but there's a lot more coming as a big wave coming talk about the Splunk culture. >>So the core elements of culture that I love that. I think all of us agree you don't want to change one where curiosity driven culture, our tool is an investigative tool, so I never want to lose. I think that threat of grit, determination, tenacity and curiosity is paramount in life and I think literally what we push out represents that and I want our people represent that and I think the fun element is really the quirkiness of the fund, like that is one of the things I love about Splunk but we are a serious company, we are in the data plane of tens of thousands of organizations globally and what we do literally makes a difference on whether they're successful or not. As organizations, we're talking about walmart is example And how one second latency can have a, have a 10% drop off in fulfillment of transaction for wal mart that's like a billion dollars a week if you cannot get their system to perform at the level it needs to so what we do matters and the change that we've been driving that I think is a great enhancement to the culture is as we are now tip into the 50% cloud company, you have the opportunity to measure millisecond by millisecond, second by second, minute by minute, hour by hour and that's a different level of help that you get. You can literally see patterns happening over the course of minutes within customers and that's not something we were born with. We were an on premise solution, we had beautiful tools and it was the C E O. S problem, the CSS problem um and their opportunity to get that feedback. Now we get that feedback so we're trying to measure that crunchiness, the fun, the cool part about Splunk with. We also have got to be very operationally disciplined because we carry a heavy responsibility set from our customers and we're in the middle of that as well as the world knows, we're halfway through our transition to be a cloud first company but I'm excited with the results I'm seeing, so I think curiosity and tenacity go with that operational rigor. Like we should all be growth mindset oriented and very excited about, Hey, can I improve? I guess there's some information that I need that I'm not getting that will make me serve my customers better and that is the tone and tenor. I want to cross all the Splunk of whether in HR legal or engineering or sales or we serve customers and we've got to be so excited every day about getting better feedback and how to serve them better. >>Doug. Thanks for coming on the Cuban, sharing that inside. I know you had to cancel your physical event, pulled off an exceptionally strong virtual event here in person. Thanks for having the Cuban. Thanks for coming on. >>Thank you for being here and I can't wait to do this in person. Next >>to mary the ceo of Splunk here inside the cube cube coverage continues stay with us for more. We've got more interviews all the rest of the day, Stay with us. I'm john for your host. Thanks for watching. Mm >>mm mhm >>mhm >>Yeah

>> Narrator: From around the globe, it's theCUBE. With digital coverage of AWS re:Invent 2020. Sponsored by intel, AWS, and our community partners. >> Welcome back to the CUBE's coverage of the AWS re:Invent 2020. Three weeks we're here, covering re:Invent. It's virtual. We're not in person. Normally we are on the floor. Instructing *signal from the noise, but we're virtual. This is theCUBE Virtual. We are theCUBE Virtual. I'm John Furrier, your host. Got a great interview here today. Sathish Balakrishnan, Vice president of hosted platforms for Red Hat joining us. Sathish, great to see you. Thanks for coming on. >> Thank you, John. Great to see you again. >> I wish we were in person, but we're remote because of the pandemic. But it's going to be a lot of action going on, a lot of content. Red Hat's relationship with AWS, and this is a really big story this year, at many levels. One is your relationship with Red Hat, but also the world's evolved. Clearly hybrid cloud's in play. Now you got multiple environments with the edge and other clouds around the corner. This is a huge deal. Hybrids validated multiple environments, including the edge. This is big. On premise in the cloud. What's your new update for your relationship? >> Absolutely, John, yeah. this is so you know, if anything this year has accelerated digital transformation, right The joke that COVID-19 is the biggest digital accelerator, digital transformation accelerator is no joke. I think going back to our relationship with AWS, as you rightly pointed out, we have a very storied and long relationship with AWS, we've been with AWS partnering with AWS since 2007, when we offered the Red Hat Enterprise Linux on AWS since then, you know, we've made a lot of strides, but not in the middle of our products that are layered on AWS, as well as back in 2015, we offered OpenShift dedicated Red Hat OpenShift dedicated, which is our managed offering on AWS, you know, and since then we made a bunch of announcements right around the service broker, and then you know, the operators operator hub, and the operators that AWS has for services to be accessed from Kubernetes. As well as you know, the new exciting joint service that we announced. So you know, by AWS and Red Hat, increasingly, right, our leaders in public cloud and hybrid cloud and are approached by IT decision makers who are looking for guidance or on changing requirements, and they know how they should be doing application development in a very containerized and hybrid cloud world. So you know, excited to be here. And and this is a great event, you know, three week event, but you know, usually we were in Las Vegas, but you know, this week, this year, we will do it on workshop. But you know, nevertheless, the same excitement. And you know, I'm sure there's going to be same set of announcements that are going to come out of this event as well. >> Yeah, we'll keep track of it. Because it's digital. I think it's going to be a whole another user experience personally on the Discovery sites Learning Conference. But that's great stuff. I want to dig into the news, cause I think the relevant story here that you just talked about, I want to dig into the announcement, the new offering that you have with AWS, it's a joint offering, I believe, can you take a minute to explain what was and what's discussed? Cause you guys announced some stuff in May. Now you have OpenShift services. Is it on AWS? Can you take a minute to explain the news here? >> Absolutely John yeah. So I think we had really big announcement in May, you know, the first joint offering with AWS and it is Red Hat open shift service on AWS, it's a joint service with Red Hat and AWS, we're very excited to partner with them, and you know, be on the AWS console. And you know, it's great to be working with AWS engineering team, we've been making a lot of really good strides, it just amplify, as you know, our managed services story. So we are very excited to have that new offering that's going to be completely integrated with AWS console transacted through you know AWS marketplace, but you know, customers will get all the benefit of AWS service, like you know, how just launch it off the console, basically get, you know there and be part of the enterprise discount program and you we're very really excited and you know, that kind of interest has been really, really amazing. So we just announced that, you know, it's in preview we have a lot of customers already in preview, and we have a long list of customers that are waiting to get on this program. So but this offering, right, we have three ways in which you can consume OpenShift on AWS. One is, as I mentioned previously OpenShift dedicated on AWS, which we've had since 2015. Then we have OpenShift container platform, which is our previous self managed offering. And that's been available on AWS, also since 2015. And then, of course, this new service that are that OpenShift servers on AWS. So there's multiple ways in which customers can consume AWS and leverage the power of both OpenShift and AWS. And what I want to do here as well, right, is to take a moment to explain, you know what Red Hat's been doing in managed services, because then it's not very natural for somebody to say, oh, what's the Red Hat doing in managed services? You know, Red Hat believes in choice, right. We are all about try for that it's infrastructure footprint that's public cloud on-prem. It's managed or self managed, that's also tries to be offered to customers. And we've been doing managed services since 2011. That's kind of like a puzzling statement, people will be like, what? And yeah, it is true that we've been doing this since 2011. And in fact, we are one of the, you know, the earliest providers of managed Kubernetes. Since 2015. Right, I think there's only one other provider other than us, who has been doing managed Kubernetes, since then, which is kind of really a testament to the engineering work that Red Hat's been doing in Kubernetes. And, you know, with all that experience, and all the work that we've done upstream and building Kubernetes and making Kubernetes, really the you know, the hybrid cloud platform for the entire IT industry, we are excited to bring this joint offering. So we can bring all the engineering and the management strengths, as well as combined with the AWS infrastructure, and you know and other AWS teams, to bring this offering, because this is really going to help our customers as they move to the cloud. >> That's great insight, thanks for explaining that managed service, cause I was going to ask that question, but you hit it already. But I want to just follow up on that. Can you just do a deeper dive on the offering specifically, on what the customer benefits are here from having this managed service? Because again, you said, You Red Hats get multiple choice consumption vehicles here? What's the benefits? what's under the what's the deep dive? >> Absolutely, absolutely is a really, really good question. right as I mentioned, first thing is choice. like we start with choice customers, if they want, self managed, and they can always get that anywhere in any infrastructure footprint. If they're going to the cloud, most customers tend to think that you know, I'm going to the cloud because I want to consume everything as a service. And that's when all of these services come into play. But before we even get to the customer benefits, there's a lot of advantages to our software product as well. But as a managed service, we are actually customer zero. So we go through this entire iteration, right. And you probably everybody's familiar with, how we take open source projects, and we pull them into enterprise product. But we take it a second step, after we make it an enterprise product, we actually ship it to our multi tenant software system, which is called OpenShift Online, which is publicly available to millions of customers that manage exports on the public Internet, and then all the security challenges that we have to face through and fix, help solidify the product. And then we moved on to our single tenant OpenShift dedicated or you know soon to be the Red Hat OpenShift service on AWS but, you know, pretty much all of Red Hat's mission critical applications, like quedado is a service that's serving like a billion containers, billion containers a month. So that scale is already been felt by the newly shipped product, so that you know, any challenges we have at scale, any challenges, we have security, any box that we have we fix before we really make the product available to all our customers. So that's kind of a really big benefit to just that software in general, with us being a provider of the software. The second thing is, you know, since we are actually now managing customers clusters, we exactly know, you know, when our customers are getting stock, which parts of the stock need to improve. So there's a really good product gap anticipation. So you know, as much as you know, we want still really engage with customers, and we continue to engage with customers, but we can also see the telemetry and the metrics and figure out, you know, what challenges our customers' facing. And how can we improve. Other thing that, you know, helps us with this whole thing is, since we are operators now, and all our customers are really operators of software, it gives us better insights into what the user experience should be, and in how we can do things better. So there's a whole lot of benefits that Red Hat gets out of just being a managed service provider. Because you know, drinking our own champagne really helps us you know, polish the champagne and make it really better for all our customers that are consuming. >> I always love the champagne better than dog food because champagne more taste better. Great, great, great insight. Final question. We only have a couple minutes left, only two minutes left. So take the time to explain the big customer macro trend, which is the on premise to cloud relationship. We know that's happening. It's an operating model on both sides. That's clear as it is in the industry. Everyone knows that. But the managed services piece. So what drives an organization and transition from an on-prem Red Hat cloud to a managed service at Amazon? >> Is a really good question. It does many things. And it really starts with the IT and technology strategy. The customer has, you know, it could be like a digital transformation push from the CEO. It could be a cloud native development from the CPO or it could just be a containerization or cost optimization. So you have to really figure out you know, which one of this and it could be multiple and many customers, it could be all four of them and many customers that's driving the move to the cloud and driving the move to containerization with OpenShift. And also customers are expanding into new businesses, they got to be more agile, they got to basically protect the stuff. Because you know, there are a lot of competitors, you know, that, and b&b and other analogies, you know, how they take on a big hotel chains, it's kind of, you know, customers have to be agile IT is, you know, very strategic in these days, you know, given how everything is digital, and as I pointed out, it has coverts really like the number one digital transformation(mumbles). So, for example, you know, we have BMW is a great customer of ours that uses OpenShift, for all the connected car infrastructure. So they run it out of, you know, their data centers, and, you know, they suddenly want to go to a new geo syn, in Asia, you know, they may not have the speed to go build a data center and do things, so they'll just move to the cloud very easily. And from all our strategy, you know, I think the world is hybrid, I know there's going to be a that single cloud, multi cloud on-pram, it's going to be multiple things that customers have. So they have to really start thinking about what are the compliance requirements? What is the data regulations that they need to comply to? Is that a lift and shift out(mumbles) gistic things? So they need to do cloud native development, as well as containerization to get the speed out of moving to the cloud. And then how are they measuring availability? You know, are they close to the customer? You know, what is the metrics that they have for, you know, speed to the customer, as well, as you know, what databases are they using? So we have a lot of experience with this. Because, you know, this is something that, you know, we've been advocating, you know, for at least eight years now, the open hybrid cloud, a lot of experience with open innovation labs, which is our way of telling customers, it's not just about the technology, but also about how you change processes and how you change other things with people aspects of it, as well as continued adoption programs and a bunch of other programs that Red Hat has been building to help customers with this transformation. >> Yeah, as a speed game. One of the big themes of all my interviews this week, a couple weeks here at reInvent has been speed. And BMW, what a great client. Yeah, shifting into high gear with BMW with OpenShift, you know, little slogan there, you know, free free attribute. >> Thank you, John, >> Shifting the idea, you know, OpenShift. Congratulations, and great announcement. I love the direction always been a big fan of OpenShift. I think with Kubernetes, a couple years ago, when that kind of came together, you saw everything kind of just snap into place with you guys. So congratulations Sathish. Final question. What is the top story that people should take away from you this year? Here at reInvent? What's the number one message that you'd like to share real quick? >> Yeah, I think number one is, you know, we have a Joint Service coming soon with AWS, it is one of it's kind work for us. And for AWS, it's the first time that we are partnering with them at such a deep level. So this is going to really help accelerate our customers' move to the cloud, right to the AWS cloud, and leverage all of AWS services very natively like they would if they were using another container service that's coming out of AWS and it's like a joint service. I'm really, really excited about the service because, you know, we've just seen that interest has been exploding and, you know, we look forward to continuing our collaboration with AWS and working together and you know, helping our customers, you know, move to the cloud as well as cloud native development, containerization and digital transformation in general. >> Congratulations, OpenShift on AWS. big story here, >> I was on AWS. I want to make sure that you know we comply with the brand >> OpenShifts on open shift service, on AWS >> on AWS is a pretty big thing. >> Yeah, and ecosys everyone knows that's a super high distinction on AWS has a certain the highest form of compliment, they have join engineering everything else going on. Congratulations thanks for coming on. >> Thank you John. Great talking to you. >> It's theCUBE virtual coverage we got theCUBE virtual covering reInvent three weeks we got a lot of content, wall to wall coverage, cube virtualization. We have multiple cubes out there with streaming videos, we're doing a lot of similar live all kinds of action. Thanks for watching theCUBE (upbeat music)

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, >>Hi. We are the Cube live covering AWS reinvent 2020. I'm Lisa Martin, and I've got one of our cube alumni back with me. Mike Miller is here. General manager of A W s AI Devices at AWS. Mike, welcome back to the Cube. >>Hi, Lisa. Thank you so much for having me. It's really great to join you all again at this virtual reinvent. >>Yes, I think last year you were on set. We have always had to. That's at reinvent. And you you had the deep race, your car, and so we're obviously socially distance here. But talk to me about deepracer. What's going on? Some of the things that have gone on the last year that you're excited >>about. Yeah, I'd love to tell. Tell you a little bit about what's been happening. We've had a tremendous year. Obviously, Cove. It has restricted our ability to have our in person races. Eso we've really gone gone gangbusters with our virtual league. So we have monthly races for competitors that culminate in the championship. Um, at reinvent. So this year we've got over 100 competitors who have qualified and who are racing virtually with us this year at reinvent. They're participating in a series of knockout rounds that are being broadcast live on twitch over the next week. That will whittle the group down to AH Group of 32 which will have a Siris of single elimination brackets leading to eight finalists who will race Grand Prix style five laps, eight cars on the track at the same time and will crown the champion at the closing keynote on December 15th this year. >>Exciting? So you're bringing a reinforcement, learning together with with sports that so many of us have been missing during the pandemic. We talked to me a little bit about some of the things that air that you've improved with Deep Racer and some of the things that are coming next year. Yeah, >>absolutely so, First of all, Deep Racer not only has been interesting for individuals to participate in the league, but we continue to see great traction and adoption amongst big customers on dare, using Deep Racer for hands on learning for machine learning, and many of them are turning to Deep Racer to train their workforce in machine learning. So over 150 customers from the likes of Capital One Moody's, Accenture, DBS Bank, JPMorgan Chase, BMW and Toyota have held Deep Racer events for their workforces. And in fact, three of those customers Accenture, DBS Bank and J. P. Morgan Chase have each trained over 1000 employees in their organization because they're just super excited. And they find that deep racers away to drive that excitement and engagement across their customers. We even have Capital one expanded this to their families, so Capital One ran a deep raise. Their Kids Cup, a family friendly virtual competition this past year were over. 250 Children and 200 families got to get hands on with machine learning. >>So I envisioned some. You know, this being a big facilitator during the pandemic when there's been this massive shift to remote work has have you seen an uptick in it for companies that talking about training need to be ableto higher? Many, many more people remotely but also train them? Is deep Racer facilitator of that? Yeah, >>absolutely. Deep Racer has ah core component of the experience, which is all virtualized. So we have, ah, console and integration with other AWS services so that racers can participate using a three d racing simulator. They can actually see their car driving around a track in a three D world simulation. Um, we're also selling the physical devices. So you know, if participants want to get the one of those devices and translate what they've done in the virtual world to the real world, they can start doing that. And in fact, just this past year, we made our deep race or car available for purchase internationally through the Amazon Com website to help facilitate that. >>So how maney deep racers air out there? I'm just curious. >>Oh, thousands. Um, you know, And there what? What we've seen is some companies will purchase you, know them in bulk and use them for their internal leagues. Just like you know, JP Morgan Chase on DBS Bank. These folks have their own kind of tracks and racers that they'll use to facilitate both in person as well as the virtual racing. >>I'm curious with this shift to remote that we mentioned a minute ago. How are you seeing deepracer as a facilitator of engagement. You mentioned engagement. And that's one of the biggest challenges that so Maney teams develops. Processes have without being co located with each other deep Brister help with that. I mean, from an engagement perspective, I think >>so. What we've seen is that Deep Racer is just fun to get your hands on. And we really lower the learning curve for machine learning. And in particular, this branch called reinforcement Learning, which is where you train this agent through trial and error toe, learn how to do a new, complex task. Um, and what we've seen is that customers who have introduced Deep Racer, um, as an event for their employees have seen ah, very wide variety of employees. Skill sets, um, kind of get engaged. So you've got not just the hardcore deep data scientists or the M L engineers. You've got Web front end programmers. You even have some non technical folks who want to get their hands dirty. Onda learn about machine learning and Deep Racer really is a nice, gradual introduction to doing that. You can get engaged with it with very little kind of coding knowledge at all. >>So talk to me about some of the new services. And let's look at some specific use case customer use cases with each service. Yeah, >>absolutely. So just to set the context. You know, Amazon's got hundreds. A ws has hundreds of thousands of customers doing machine learning on AWS. No customers of all sizes are embedding machine learning into their no core business processes. And one of the things that we always do it Amazon is We're listening to customers. You know, 90 to 95% of our road maps are driven by customer feedback. And so, as we've been talking to these industrial manufacturing customers, they've been telling us, Hey, we've got data. We've got these processes that are happening in our industrial sites. Um, and we just need some help connecting the dots like, how do we really most effectively use machine learning to improve our processes in these industrial and manufacturing sites? And so we've come up with these five services. They're focused on industrial manufacturing customers, uh, two of the services air focused around, um, predictive maintenance and, uh, the other three services air focused on computer vision. Um, and so let's start with the predictive maintenance side. So we announced Amazon Monitor On and Amazon look out for equipment. So these services both enable predictive maintenance powered by machine learning in a way that doesn't require the customer to have any machine learning expertise. So Mono Tron is an end to end machine learning system with sensors, gateway and an ML service that can detect anomalies and predict when industrial equipment will require maintenance. I've actually got a couple examples here of the sensors in the gateway, so this is Amazon monitor on these little sensors. This little guy is a vibration and temperature sensor that's battery operated, and wireless connects to the gateway, which then transfers the data up to the M L Service in the cloud. And what happens is, um, the sensors can be connected to any rotating machinery like pump. Pour a fan or a compressor, and they will send data up to the machine learning cloud service, which will detect anomalies or sort of irregular kind of sensor readings and then alert via a mobile app. Just a tech or a maintenance technician at an industrial site to go have a look at their equipment and do some preventative maintenance. So um, it's super extreme line to end to end and easy for, you know, a company that has no machine learning expertise to take advantage of >>really helping them get on board quite quickly. Yeah, >>absolutely. It's simple tea set up. There's really very little configuration. It's just a matter of placing the sensors, pairing them up with the mobile app and you're off and running. >>Excellent. I like easy. So some of the other use cases? Yeah, absolutely. >>So So we've seen. So Amazon fulfillment centers actually have, um, enormous amounts of equipment you can imagine, you know, the size of an Amazon fulfillment center. 28 football fields, long miles of conveyor belts and Amazon fulfillment centers have started to use Amazon monitor on, uh, to monitor some of their conveyor belts. And we've got a filament center in Germany that has started using these 1000 sensors, and they've already been able to, you know, do predictive maintenance and prevent downtime, which is super costly, you know, for businesses, we've also got customers like Fender, you know, who makes guitars and amplifiers and musical equipment. Here in the US, they're adopting Amazon monitor on for their industrial machinery, um, to help prevent downtime, which again can cost them a great deal as they kind of hand manufacture these high end guitars. Then there's Amazon. Look out for equipment, which is one step further from Amazon monitor on Amazon. Look out for equipment. Um provides a way for customers to send their own sensor data to AWS in order to build and train a model that returns predictions for detecting abnormal equipment behavior. So here we have a customer, for example, like GP uh, E P s in South Korea, or I'm sorry, g S E P s in South Korea there in industrial conglomerate, and they've been collecting their own data. So they have their own sensors from industrial equipment for a decade. And they've been using just kind of rule basic rules based systems to try to gain insight into that data. Well, now they're using Amazon, look out for equipment to take all of their existing sensor data, have Amazon for equipment, automatically generate machine learning models on, then process the sensor data to know when they're abnormalities or when some predictive maintenance needs to occur. >>So you've got the capabilities of working with with customers and industry that that don't have any ML training to those that do have been using sensors. So really, everybody has an opportunity here to leverage this new Amazon technology, not only for predicted, but one of the things I'm hearing is contact list, being able to understand what's going on without having to have someone physically there unless there is an issue in contact. This is not one of the words of 2020 but I think it probably should be. >>Yeah, absolutely. And in fact, that that was some of the genesis of some of the next industrial services that we announced that are based on computer vision. What we saw on what we heard when talking to these customers is they have what we call human inspection processes or manual inspection processes that are required today for everything from, you know, monitoring you like workplace safety, too, you know, quality of goods coming off of a machinery line or monitoring their yard and sort of their, you know, truck entry and exit on their looking for computer vision toe automate a lot of these tasks. And so we just announced a couple new services that use computer vision to do that to automate these once previously manual inspection tasks. So let's start with a W A. W s Panorama uses computer vision toe improve those operations and workplace safety. AWS Panorama is, uh, comes in two flavors. There's an appliance, which is, ah, box like this. Um, it basically can go get installed on your network, and it will automatically discover and start processing the video feeds from existing cameras. So there's no additional capital expense to take a W s panorama and have it apply computer vision to the cameras that you've already got deployed, you know, So customers are are seeing that, um, you know, computer vision is valuable, but the reason they want to do this at the edge and put this computer vision on site is because sometimes they need to make very low Leighton see decisions where if you have, like a fast moving industrial process, you can use computer vision. But I don't really want to incur the cost of sending data to the cloud and back. I need to make a split second decision, so we need machine learning that happens on premise. Sometimes they don't want to stream high bandwidth video. Or they just don't have the bandwidth to get this video back to the cloud and sometimes their data governance or privacy restrictions that restrict the company's ability to send images or video from their site, um, off site to the cloud. And so this is why Panorama takes this machine learning and makes it happen right here on the edge for customers. So we've got customers like Cargill who uses or who is going to use Panorama to improve their yard management. They wanna use computer vision to detect the size of trucks that drive into their granaries and then automatically assign them to an appropriately sized loading dock. You've got a customer like Siemens Mobility who you know, works with municipalities on, you know, traffic on by other transport solutions. They're going to use AWS Panorama to take advantage of those existing kind of traffic cameras and build machine learning models that can, you know, improve congestion, allocate curbside space, optimize parking. We've also got retail customers. For instance, Parkland is a Canadian fuel station, um, and retailer, you know, like a little quick stop, and they want to use Panorama to do things like count the people coming in and out of their stores and do heat maps like, Where are people visiting my store so I can optimize retail promotions and product placement? >>That's fantastic. The number of use cases is just, I imagine if we had more time like you could keep going and going. But thank you so much for not only sharing what's going on with Deep Racer and the innovations, but also for show until even though we weren't in person at reinvent this year, Great to have you back on the Cube. Mike. We appreciate your time. Yeah, thanks, Lisa, for having me. I appreciate it for Mike Miller. I'm Lisa Martin. You're watching the cubes Live coverage of aws reinvent 2020.

>> Narrator: From around the globe, it's theCUBE. With digital coverage of AWS re:Invent 2020. Sponsored by intel, AWS, and our community partners. >> Welcome back to the CUBE's coverage of the AWS re:Invent 2020. Three weeks we're here, covering re:Invent. It's virtual. We're not in person. Normally we are on the floor. Instructing *signal from the noise, but we're virtual. This is theCUBE Virtual. We are theCUBE Virtual. I'm John Furrier, your host. Got a great interview here today. Satish Balakrishnan, Vice president of hosted platforms for Red Hat joining us. Satish, great to see you. Thanks for coming on. >> Thank you, John. Great to see you again. >> I wish we were in person, but we're remote because of the pandemic. But it's going to be a lot of action going on, a lot of content. Red Hat's relationship with AWS, and this is a really big story this year, at many levels. One is your relationship with Red Hat, but also the world's evolved. Clearly hybrid cloud's in play. Now you got multiple environments with the edge and other clouds around the corner. This is a huge deal. Hybrids validated multiple environments, including the edge. This is big. On premise in the cloud. What's your new update for your relationship? >> Absolutely, John, yeah. this is so you know, if anything this year has accelerated digital transformation, right The joke that COVID-19 is the biggest digital accelerator, digital transformation accelerator is no joke. I think going back to our relationship with AWS, as you rightly pointed out, we have a very storied and long relationship with AWS, we've been with AWS partnering with AWS since 2007, when we offered the Red Hat Enterprise Linux on AWS since then, you know, we've made a lot of strides, but not in the middle of our products that are layered on AWS, as well as back in 2015, we offered OpenShift dedicated Red Hat OpenShift dedicated, which is our managed offering on AWS, you know, and since then we made a bunch of announcements right around the service broker, and then you know, the operators operator hub, and the operators that AWS has for services to be accessed from Kubernetes. As well as you know, the new exciting joint service that we announced. So you know, by AWS and Red Hat, increasingly, right, our leaders in public cloud and hybrid cloud and are approached by IT decision makers who are looking for guidance or on changing requirements, and they know how they should be doing application development in a very containerized and hybrid cloud world. So you know, excited to be here. And and this is a great event, you know, three week event, but you know, usually we were in Las Vegas, but you know, this week, this year, we will do it on workshop. But you know, nevertheless, the same excitement. And you know, I'm sure there's going to be same set of announcements that are going to come out of this event as well. >> Yeah, we'll keep track of it. Because it's digital. I think it's going to be a whole another user experience personally on the Discovery sites Learning Conference. But that's great stuff. I want to dig into the news, cause I think the relevant story here that you just talked about, I want to dig into the announcement, the new offering that you have with AWS, it's a joint offering, I believe, can you take a minute to explain what was and what's discussed? Cause you guys announced some stuff in May. Now you have OpenShift services. Is it on AWS? Can you take a minute to explain the news here? >> Absolutely John yeah. So I think we had really big announcement in May, you know, the first joint offering with AWS and it is Red Hat open shift service on AWS, it's a joint service with Red Hat and AWS, we're very excited to partner with them, and you know, be on the AWS console. And you know, it's great to be working with AWS engineering team, we've been making a lot of really good strides, it just amplify, as you know, our managed services story. So we are very excited to have that new offering that's going to be completely integrated with AWS console transacted through you know AWS marketplace, but you know, customers will get all the benefit of AWS service, like you know, how just launch it off the console, basically get, you know there and be part of the enterprise discount program and you we're very really excited and you know, that kind of interest has been really, really amazing. So we just announced that, you know, it's in preview we have a lot of customers already in preview, and we have a long list of customers that are waiting to get on this program. So but this offering, right, we have three ways in which you can consume OpenShift on AWS. One is, as I mentioned previously OpenShift dedicated on AWS, which we've had since 2015. Then we have OpenShift container platform, which is our previous self managed offering. And that's been available on AWS, also since 2015. And then, of course, this new service that are that OpenShift servers on AWS. So there's multiple ways in which customers can consume AWS and leverage the power of both OpenShift and AWS. And what I want to do here as well, right, is to take a moment to explain, you know what Red Hat's been doing in managed services, because then it's not very natural for somebody to say, oh, what's the Red Hat doing in managed services? You know, Red Hat believes in choice, right. We are all about try for that it's infrastructure footprint that's public cloud on-prem. It's managed or self managed, that's also tries to be offered to customers. And we've been doing managed services since 2011. That's kind of like a puzzling statement, people will be like, what? And yeah, it is true that we've been doing this since 2011. And in fact, we are one of the, you know, the earliest providers of managed Kubernetes. Since 2015. Right, I think there's only one other provider other than us, who has been doing managed Kubernetes, since then, which is kind of really a testament to the engineering work that Red Hat's been doing in Kubernetes. And, you know, with all that experience, and all the work that we've done upstream and building Kubernetes and making Kubernetes, really the you know, the hybrid cloud platform for the entire IT industry, we are excited to bring this joint offering. So we can bring all the engineering and the management strengths, as well as combined with the AWS infrastructure, and you know and other AWS teams, to bring this offering, because this is really going to help our customers as they move to the cloud. >> That's great insight, thanks for explaining that managed service, cause I was going to ask that question, but you hit it already. But I want to just follow up on that. Can you just do a deeper dive on the offering specifically, on what the customer benefits are here from having this managed service? Because again, you said, You Red Hats get multiple choice consumption vehicles here? What's the benefits? what's under the what's the deep dive? >> Absolutely, absolutely is a really, really good question. right as I mentioned, first thing is choice. like we start with choice customers, if they want, self managed, and they can always get that anywhere in any infrastructure footprint. If they're going to the cloud, most customers tend to think that you know, I'm going to the cloud because I want to consume everything as a service. And that's when all of these services come into play. But before we even get to the customer benefits, there's a lot of advantages to our software product as well. But as a managed service, we are actually customer zero. So we go through this entire iteration, right. And you probably everybody's familiar with, how we take open source projects, and we pull them into enterprise product. But we take it a second step, after we make it an enterprise product, we actually ship it to our multi tenant software system, which is called OpenShift Online, which is publicly available to millions of customers that manage exports on the public Internet, and then all the security challenges that we have to face through and fix, help solidify the product. And then we moved on to our single tenant OpenShift dedicated or you know soon to be the Red Hat OpenShift service on AWS but, you know, pretty much all of Red Hat's mission critical applications, like quedado is a service that's serving like a billion containers, billion containers a month. So that scale is already been felt by the newly shipped product, so that you know, any challenges we have at scale, any challenges, we have security, any box that we have we fix before we really make the product available to all our customers. So that's kind of a really big benefit to just that software in general, with us being a provider of the software. The second thing is, you know, since we are actually now managing customers clusters, we exactly know, you know, when our customers are getting stock, which parts of the stock need to improve. So there's a really good product gap anticipation. So you know, as much as you know, we want still really engage with customers, and we continue to engage with customers, but we can also see the telemetry and the metrics and figure out, you know, what challenges our customers' facing. And how can we improve. Other thing that, you know, helps us with this whole thing is, since we are operators now, and all our customers are really operators of software, it gives us better insights into what the user experience should be, and in how we can do things better. So there's a whole lot of benefits that Red Hat gets out of just being a managed service provider. Because you know, drinking our own champagne really helps us you know, polish the champagne and make it really better for all our customers that are consuming. >> I always love the champagne better than dog food because champagne more taste better. Great, great, great insight. Final question. We only have a couple minutes left, only two minutes left. So take the time to explain the big customer macro trend, which is the on premise to cloud relationship. We know that's happening. It's an operating model on both sides. That's clear as it is in the industry. Everyone knows that. But the managed services piece. So what drives an organization and transition from an on-prem Red Hat cloud to a managed service at Amazon? >> Is a really good question. It does many things. And it really starts with the IT and technology strategy. The customer has, you know, it could be like a digital transformation push from the CEO. It could be a cloud native development from the CPO or it could just be a containerization or cost optimization. So you have to really figure out you know, which one of this and it could be multiple and many customers, it could be all four of them and many customers that's driving the move to the cloud and driving the move to containerization with OpenShift. And also customers are expanding into new businesses, they got to be more agile, they got to basically protect the stuff. Because you know, there are a lot of competitors, you know, that, and b&b and other analogies, you know, how they take on a big hotel chains, it's kind of, you know, customers have to be agile IT is, you know, very strategic in these days, you know, given how everything is digital, and as I pointed out, it has coverts really like the number one digital transformation(mumbles). So, for example, you know, we have BMW is a great customer of ours that uses OpenShift, for all the connected car infrastructure. So they run it out of, you know, their data centers, and, you know, they suddenly want to go to a new geo syn, in Asia, you know, they may not have the speed to go build a data center and do things, so they'll just move to the cloud very easily. And from all our strategy, you know, I think the world is hybrid, I know there's going to be a that single cloud, multi cloud on-pram, it's going to be multiple things that customers have. So they have to really start thinking about what are the compliance requirements? What is the data regulations that they need to comply to? Is that a lift and shift out(mumbles) gistic things? So they need to do cloud native development, as well as containerization to get the speed out of moving to the cloud. And then how are they measuring availability? You know, are they close to the customer? You know, what is the metrics that they have for, you know, speed to the customer, as well, as you know, what databases are they using? So we have a lot of experience with this. Because, you know, this is something that, you know, we've been advocating, you know, for at least eight years now, the open hybrid cloud, a lot of experience with open innovation labs, which is our way of telling customers, it's not just about the technology, but also about how you change processes and how you change other things with people aspects of it, as well as continued adoption programs and a bunch of other programs that Red Hat has been building to help customers with this transformation. >> Yeah, as a speed game. One of the big themes of all my interviews this week, a couple weeks here at reInvent has been speed. And BMW, what a great client. Yeah, shifting into high gear with BMW with OpenShift, you know, little slogan there, you know, free free attribute. >> Thank you, John, >> Shifting the idea, you know, OpenShift. Congratulations, and great announcement. I love the direction always been a big fan of OpenShift. I think with Kubernetes, a couple years ago, when that kind of came together, you saw everything kind of just snap into place with you guys. So congratulations Satish. Final question. What is the top story that people should take away from you this year? Here at reInvent? What's the number one message that you'd like to share real quick? >> Yeah, I think number one is, you know, we have a Joint Service coming soon with AWS, it is one of it's kind work for us. And for AWS, it's the first time that we are partnering with them at such a deep level. So this is going to really help accelerate our customers' move to the cloud, right to the AWS cloud, and leverage all of AWS services very natively like they would if they were using another container service that's coming out of AWS and it's like a joint service. I'm really, really excited about the service because, you know, we've just seen that interest has been exploding and, you know, we look forward to continuing our collaboration with AWS and working together and you know, helping our customers, you know, move to the cloud as well as cloud native development, containerization and digital transformation in general. >> Congratulations, OpenShift on AWS. big story here, >> I was on AWS. I want to make sure that you know we comply with the brand >> OpenShifts on open shift service, on AWS >> on AWS is a pretty big thing. >> Yeah, and ecosys everyone knows that's a super high distinction on AWS has a certain the highest form of compliment, they have join engineering everything else going on. Congratulations thanks for coming on. >> Thank you John. Great talking to you. >> It's theCUBE virtual coverage we got theCUBE virtual covering reInvent three weeks we got a lot of content, wall to wall coverage, cube virtualization. We have multiple cubes out there with streaming videos, we're doing a lot of similar live all kinds of action. Thanks for watching theCUBE (upbeat music)

from around the globe it's thecube with coverage of kubecon and cloudnativecon north america 2020 virtual brought to you by red hat the cloud native computing foundation and ecosystem partners hello and welcome back to the cube's coverage of kubecon plus cloud nativecon 2020 the virtual edition abinav joshi is here he's the senior product marketing manager for openshift at red hat and tom dean is the senior director of pro product management at cloudera gentlemen thanks for coming on thecube good to see you thank you very much for having us here hey guys i know you would be here it was great to have you and guys i know you're excited about the partnership and i definitely want to get in and talk about that but before we do i wonder if we could just set the tone you know what are you seeing in the market tom let's let's start with you i had a great deep dive a couple of weeks back with anupam singh and he brought me up to speed on what's new with cloudera but but one of the things we discussed was the accelerated importance of data putting data at the core of your digital business tom what are you seeing in the marketplace right now yeah absolutely so um overall we're still seeing a growing demand for uh storing and and processing massive massive amounts of data even in the past few months um where perhaps we see a little bit more variety is on by industry sector is on the propensity to adopt some of the latest and greatest uh technologies that are out there or that we we deliver to the market um so whether perhaps in the retail hospitality sector you may see a little bit more risk aversion around some of the latest tools then you you go to the healthcare industry as an example and you see we see a strong demand for our latest technologies uh with with everything that is that is going on um so overall um still a lot lots of demand around this space so abnormal i mean we just saw in ibm's earnings though the momentum of red hat you know growing in the mid teens and the explosion that we're seeing around containers and and obviously openshift is at the heart of that how the last nine months affected your customers priorities and what are you seeing yeah we've been a lot more busier like in the last few months because there's like a lot of use cases and if you look at the like a lot of the research and so on and we are seeing that from our customers as well that now the customers are actually speeding up the digital transformation right people say that okay kovac 19 has actually uh speeded up the digital transformation for a lot of our customers for the right reasons to be able to help the customers and so on so we are seeing a lot of attraction on like number of verticals and number of use cases beyond the traditional lab dev data analytics aiml messaging streaming edge and so on like lots of use cases in like a lot of different like industry verticals so there's a lot of momentum going on on openshift and the broader that portfolio as well yeah it's ironic the the timing of the pandemic but it sure underscores that this next 10 years is going to be a lot different than the last 10 years okay let's talk about some of the things that are new around data tom cloudera you guys have made a number of moves since acquiring hortonworks a little over two years ago what's new with uh with the cloudera data platform cdp sure so yes our latest therap uh platform is called cbp clara data platform last year we announced the public cloud version of cdp running on aws and then azure and what's new is just two months ago we announced the release of the version of this platform targeted at the data center and that's called cvp private cloud and really the focus of this platform this new version has been around solving some of the pain points that we see around agility or time to value and the ease of use of the platform and to give you some specific examples with our previous technology it could take a customer three months to provision a data warehouse if you include everything from obtaining the infrastructure to provisioning the warehouse loading the data setting security policies uh and fine-tuning the the software now with cbp private cloud we've been able to take those uh three months and turn it into three minutes so significant uh speed up in in that onboarding time and in time to valley and a key piece of this uh that enabled this this speed up was a revamping of the entire stack specifically the infrastructure and service services management layer and this is where the containerization of the platform comes in specifically kubernetes and red hat open shift that is a key piece of the puzzle that enables this uh order of magnitude uh improvement in time right uh now abner you think about uh red hat you think about cloudera of course hortonworks the stalwarts of of of open source you got kind of like birds of a feather how are red hat and cloudera partnering with each other you know what are the critical aspects of that relationship that people should be aware of yeah absolutely that's a very good question yeah so on the openshift side we've had a lot of momentum in the market and we have well over 2000 customers in terms of a lot of different verticals and the use cases that i talked about at the beginning of our conversation in terms of traditional and cloud native app dev databases data analytics like ai messaging and so on right and the value that you have with openshift and the containers kubernetes and devops like part of the solution being able to provide the agility flexibility scalability the cross cloud consistency like so all that that you see in a typical app dev world is directly applicable to fast track the data analytics and the ai projects as well and we've seen like a lot of customers and some of the ones that we can talk about in a public way like iix rbc bank hca healthcare boston children's bmw exxon mobil so all these organizations are being are able to leverage openshift to kind of speed up the ai projects and and help with the needs of the data engineers data scientists and uh and the app dev folks now from our perspective providing the best in class uh you say like experience for the customers at the platform level is key and we have to make sure that the tooling that the customers run on top of it uh gets the best in class the experience in terms of the day zero to day two uh management right and it's uh and and it's an ecosystem play for us and and and that's the way cloudera is the top isv in the space right when it comes to data analytics and ai and that was our key motivation to partner with cloudera in terms of bringing this joint solution to market and making sure that our customers are successful so the partnership is at all the different levels in the organization say both up and down as well as in the the engineering level the product management level the marketing level the sales level and at the support and services level as well so that way if you look at the customer journey in terms of selecting a solution uh putting it in place and then getting the value out of it so the partnership it actually spans across the entire spectrum yeah and tom you know i wonder if you could add anything there i mean it's not just about the public cloud with containers you're seeing obviously the acceleration of of cloud native principles on-prem in a hybrid you know across clouds it's sort of the linchpin containers really and kubernetes specifically linchpin to enable that what would you add to that discussion yeah as part of the partnership when we were looking for a vendor who could provide us that kubernetes layer we looked at our customer base and if you think about who clara is focused on we really go after that global the global 2000 firms out there these customers have very strict uh security requirements and they're often in these highly regulated uh industries and so when we looked at a customer's base uh we saw a lot of overlap and there was a natural good fit for us there but beyond that just our own technical evaluation of the solutions and also talking to uh to our own customers about who they do they see as a trusted platform that can provide enterprise grade uh features on on a kubernetes layer red hat had a clear leadership in in that front and that combined with our own uh long-standing relationship with our parent company ibm uh it made this partnership a natural good thing for us right and cloudera's always had a good relationship with ibm tom i want to stay with you if i can for a minute and talk about the specific joint solutions that you're providing with with red hat what are you guys bringing to customers in in terms of those solutions what's the business impact where's the value absolutely so the solution is called cbd or color data platform private cloud on red hat openshift and i'll describe three uh the three pillars that make up cbp uh first what we have is the five data analytic experiences and that is meant to cover the end to end data lifecycle in the first release we just came out two months ago we announced the availability of two of those five experiences we have data warehousing for bi analytics as well as machine learning and ai where we offer a collaborative data science data science tools for data scientists to come together do exploratory data analytics but also develop predictive models and push them to production going forward we'll be adding the remaining three uh experiences they include data engineering or transformations on uh on your data uh data flow for streaming analytics and ingest uh as well as operational database for uh real-time surveying of both structure and unstructured data so these five experiences have been re-banked right compared to our prior platform to target these specific use cases and simplify uh these data disciplines the second pillar that i'll talk about is the sdx or uh what what we call the shared data experience and what this is is the ability for these five experiences to have one global data set that they can all access with shared metadata security including fine grain permissions and a suite of governance tools that provide lineage provide auditing and business metadata so by having these shared data experiences our developers our users can build these multi-disciplinary workflows in a very straightforward way without having to create all this custom code and i can stitch you can stitch them together and the last pillar that i'll mention uh is the containerization of of the platform and because of containers because of kubernetes we're now able to offer that next level of agility isolation uh and infrastructure efficiency on the platform so give you a little bit more specific examples on the agility i mentioned going from three months to three minutes in terms of the speed up with i uh with uh containers we can now also give our users the ability to bring their own versions of their libraries and engines without colliding with another user who's sharing the platform that has been a big ask from our customers and last i'll mention infrastructure efficiency by re-architecting our services to running a microservices architecture we can now impact those servers in a much more efficient way we can also auto scale auto suspend bring all this as you mentioned bring all these cloud native concepts on premises and the end result of that is better infrastructure efficiency now our customers can do more with the same amount of hard work which overall uh reduces their their total spend on the solution so that's what we call cbp private cloud great thanks for that i mean wow we've seen really the evolution from the the wild west days of you know the early days of so-called big data ungoverned a lot of shadow data science uh maybe maybe not as efficient as as we'd like and but certainly today taking advantage of some of those capabilities dealing with the noisy neighbor problem enough i wonder if you could comment another question that i have is you know one of the things that jim whitehurst talked about when ibm acquired red hat was the scale that ibm could bring and what i always looked at in that context was ibm's deep expertise in vertical industries so i wonder what are some of the key industry verticals that you guys are targeting and succeeding in i mean yes there's the pandemic has some effects we talked about hospitality obviously airlines have to have to be careful and conserving cash but what are some of the interesting uh tailwinds that you're seeing by industry and some of the the more interesting and popular use cases yeah that's a very good question now in terms of the industry vertical so we are seeing the traction in like a number of verticals right and the top ones being the financial services like healthcare telco the automotive industry as well as the federal government are some of the key ones right and at the end of the day what what all the customers are looking at doing is be able to improve the experience of their customers with the digital services that they roll out right as part of the pandemic and so on as well and then being able to gain competitive edge right if you can have the services in your platform and make them kind of fresh and relevant and be able to update them on a regular basis that's kind of that's your differentiator these days right and then the next one is yeah if you do all this so you should be able to increase your revenue be able to save cost as well that's kind of a key one that you mentioned right that that a lot of the industries like the hospitality the airlines and so on are kind of working on saving cash right so if you can help them save the cost that's kind of key and then the last one is is being able to automate the business processes right because there's not like a lot of the manual processes so yeah if you can add in like a lot of automation that's all uh good for your business and then now if you look at the individual use cases in these different industry verticals what we're seeing that the use cases cannot vary from the industry to industry like if you look at the financial services the use cases like fraud detection being able to do the risk analysis and compliance being able to improve the customer support and so on are some of the key use cases the cyber security is coming up a lot as well because uh yeah nobody wants to be hacked and so and and so on yeah especially like in these times right and then moving on to healthcare and the life sciences right what we're seeing the use cases on being able to do the data-driven diagnostics and care and being able to do the discovery of drugs being able to say track kobit 19 and be able to tell that okay uh which of my like hospital is going to be full when and what kind of ppe am i going to need at my uh the the sites and so on so that way i can yeah and mobilize like as needed are some of the key ones that we are seeing on the healthcare side uh and then in terms of the automotive industry right that's where being able to speed up the autonomous driving initiatives uh being able to do uh the auto warranty pricing based on the history of the drivers and so on and then being able to save on the insurance cost is a big one that we are seeing as well for the insurance industries and then but more like manufacturing right being able to do the quality assurance uh at the shop floor being able to do the predictive maintenance on machinery and also be able to do the robotics process automation so like lots of use cases that customers are prioritizing but it's very verticalized it kind of varies from the vertical to a vertical but at the end of the day yeah it's all about like improving the customer experience the revenue saving cost and and being able to automate the business processes yeah that's great thank you for that i mean we we heard a lot about automation we were covering ansible fest i mean just think about fraud how much you know fraud detection has changed in the last 10 years it used to be you know so slow you'd have to go go through your financial statements to find fraud and now it's instantaneous cyber security is critical because the adversaries are very capable healthcare is a space where you know it's ripe for change and now of course with the pandemic things are changing very rapidly automotive another one an industry that really hasn't hadn't seen much disruption and now you're seeing with a number of things autonomous vehicles and you know basically software on wheels and insurance great example even manufacturing you're seeing you know a real sea change there so thank you for that description you know very often in the cube we like to look at joint engineering solutions that's a gauge of the substance of a partnership you know sometimes you see these barney deals you know there's a press release i love you you love me okay see you but but so i wonder if you guys could talk about specific engineering that you're doing tom maybe you could start sure yeah so on the on the engineering and product side um we've um for cbp private cloud we've we've changed our uh internal development and testing to run all on uh openshift uh internally uh and as part of that we we have a direct line to red hat engineering to help us solve any issues that that uh we run into so in the initial release we start with support of openshift43 we're just wrapping up uh testing of and we'll begin with openshift46 very soon on another aspect of their partnership is on being able to update our images to account for any security vulnerabilities that are coming up so with the guidance and help from red hat we've been we've standardized our docker images on ubi or the universal based image and that allows us to automatically get many of these security fixes uh into our into our software um the last point that i mentioned here is that it's not just about providing kubernetes uh red hat helps us with the end to end uh solution so there is also the for example bringing a docker registry into the picture or providing a secure vault for storing uh all the secrets so all these uh all these pieces combined make up the uh a strong complete solution actually the last thing i'll mention is is a support aspect which is critical to our customers in this model our customers can bring support tickets to cluberra but as soon as we determine that it may be an issue that uh related to red hat or openshift where we can use their help we have that direct line of communication uh and automated systems in the back end to resolve those support tickets uh quickly for our customers so those are some of the examples of what we're doing on the technical side great thank you uh enough we're out of time but i wonder if we could just close here i mean when we look at our survey data with our data partner etr we see containers container orchestration container management generally and again kubernetes specifically is the the number one area of investment for companies that has the most momentum in terms of where they're putting their efforts it's it's it's right up there and even ahead of ai and machine learning and even ahead of cloud which is obviously larger maybe more mature but i wonder if you can add anything and bring us home with this segment yeah absolutely and i think uh so uh one thing i want to add is like in terms of the engineering level right we also have like between cloudera and red hat the partnership and the sales and the go to market levels as well because once you build the uh the integration it yeah it has to be built out in the customer environments as well right so that's where we have the alignment um at the marketing level as well as the sales level so that way we can like jointly go in and do the customer workshops and make sure the solutions are getting deployed the right way right uh and also we have a partnership at the professional services level as well right where um the experts from both the orgs are kind of hand in hand to help the customers right and then at the end of the day if you need help with support and that's what tom talked about that we have the experts on the support side as well yeah and then so to wrap things up right uh so all the industry research and the customer conversation that we are having are kind of indicating that the organizations are actually increasing the focus on digital uh transformation with the data and ai being a key part of it and that's where this strategic partnership between cloudera and and red hat is going to play a big role to help our mutual customers uh through that our transition and be able to achieve the key goals that they set for their business great well guys thanks so much for taking us through the partnership and the integration work that you guys are doing with customers a great discussion really appreciate your time yeah thanks a lot dave really appreciate it really enjoyed the conversation all right keep it right there everybody you're watching thecube's coverage of cubecon plus cloud nativecon north america the virtual edition keep it right there we'll be right back

(plane engine roars) (upbeat music) >> They call me Dr. Goh. I'm Senior Vice President and Chief Technology Officer of AI at Hewlett Packard Enterprise. And today I'm in Munich, Germany. Home to one and a half million people. Munich is famous for everything from BMW, to beer, to breathtaking architecture and festive markets. The Bavarian capital is the beating heart of Germany's automobile industry. Over 50,000 of its residents work in automotive engineering, and to date, Munich allocated around 30 million euros to boost electric vehicles and infrastructure for them. (upbeat music) >> Hello, everyone, my name is Dr. Jerome Baudry. I am a professor at the University of Alabama in Huntsville. Our mission is to use a computational resources to accelerate the discovery of drugs that will be useful and efficient against the COVID-19 virus. On the one hand, there is this terrible crisis. And on the other hand, there is this absolutely unique and rare global effort to fight it. And that I think is a is a very positive thing. I am working with the Cray HPE machine called Sentinel. This machine is so amazing that it can actually mimic the screening of hundreds of thousands, almost millions of chemicals a day. What we take weeks, if not months, or years, we can do in a matter of a few days. And it's really the key to accelerating the discovery of new drugs, new pharmaceuticals. We are all in this together, thank you. (upbeat music) >> Hello, everyone. I'm so pleased to be here to interview Dr. Jerome Baudry, of the University of Alabama in Huntsville. >> Hello, Dr. Goh, I'm very happy to be meeting with you here, today. I have a lot of questions for you as well. And I'm looking forward to this conversation between us. >> Yes, yes, and I've got lots of COVID-19 and computational science questions lined up for you too Jerome. Yeah, so let's interview each other, then. >> Absolutely, let's do that, let's interview each other. I've got many questions for you. And , we have a lot in common and yet a lot of things we are addressing from a different point of view. So I'm very much looking forward to your ideas and insights. >> Yeah, especially now, with COVID-19, many of us will have to pivot a lot of our research and development work, to address the most current issues. I watch your video and I've seen that you're very much focused on drug discovery using super computing. The central notebook you did, I'm very excited about that. Can you tell us a bit more about how that works, yeah? >> Yes, I'd be happy to in fact, I watch your video as well manufacturing, and it's actually quite surprisingly close, what we do with drugs, and with what other people do with planes or cars or assembly lanes. we are calculating forces, on molecules, on drug candidates, when they hit parts of the viruses. And we essentially try to identify what small molecules will hit the viruses or its components, the hardest to mess with its function in a way. And that's not very different from what you're doing. What you are describing people in the industry or in the transportation industry are doing. So that's our problem, so to speak, is to deal with a lot of small molecules. Guy creating a lot of forces. That's not a main problem, our main problem is to make intelligent choices about what calculates, what kind of data should we incorporate in our calculations? And what kind of data should we give to the people who are going to do the testing? And that's really something I would like you to do to help us understand better. How do you see artificial intelligence, helping us, putting our hands on the right data to start with, in order to produce the right data and accuracy. >> Yeah, that's that's a great question. And it is a question that we've been pondering in our strategy as a company a lot recently. Because more and more now we realize that the data is being generated at the far out edge. By edge. I mean, something that's outside of the cloud and data center, right? Like, for example, a more recent COVID-19 work, doing a lot of cryo electron microscope work, right? To try and get high resolution pictures of the virus and at different angles, so creating lots of movies under electron microscope to try and create a 3D model of the virus. And we realize that's the edge, right, because that's where the microscope is, away from the data center. And massive amounts of data is generated, terabytes and terabytes of data per day generated. And we had to develop means, a workflow means to get that data off the microscope and provide pre-processing and processing, so that they can achieve results without delay. So we learned quite a few lessons there, right, especially trying to get the edge to be more intelligent, to deal with the onslaught of data coming in, from these devices. >> That's fantastic that you're saying that and that you're using this very example of cryo-EM, because that's the kind of data that feeds our computations. And indeed, we have found that it is very, very difficult to get the right cryo-EM data to us. Now we've been working with HPE supercomputer Sentinel, as you may know, for our COVID-19 work. So we have a lot of computational power. But we will be even faster and better, frankly, if we knew what kind of cryo-EM data to focus on. In fact, most of our discussions are based on not so much how to compute the forces of the molecules, which we do quite well on an HP supercomputer. But again, what cryo-EM 3D dimensional space to look at. And it's becoming almost a bottleneck. >> Have access to that. >> And we spend a lot of time, do you envision a point where AI will be able to help us, to make this kind of code almost live or at least as close to live as possible, as that that comes from the edge? How to pack it and not triage it, but prioritize it for the best possible computations on supercomputers? >> What a visionary question and desire, right? Like exactly the vision we have, right? Of course, the ultimate vision, you aim for the best, and that will be a real time stream of processed data coming off the microscope straight, providing your need, right? We are not there. Before this, we are far from there, right? But that's the aim, the ability to push more and more intelligence forward, so that by the time the data reaches you, it is what you need, right, without any further processing. And a lot of AI is applied there, particularly in cryo-EM where they do particle picking, right, they do a lot of active pictures and movies of the virus. And then what they do is, they rotate the virus a little bit, right? And then to try and figure out in all the different images in the movies, to try and pick the particles in there. And this is very much image processing that AI is very good at. So many different stages, application is made. The key thing, is to deal with the data that is flowing at this at this speed, and to get the data to you in the right form, that in time. So yes, that's the desire, right? >> It will be a game changer, really. You'll be able to get things in a matter of weeks, instead of a matter of years to the colleague who will be doing the best day. If the AI can help me learn from a calculation that didn't exactly turn out the way we want it to be, that will be very, very helpful. I can see, I can envision AI being able to, live AI to be able to really revolutionize all the process, not only from the discovery, but all the way to the clinical, to the patient, to the hospital. >> Well, that's a great point. In fact, I caught on to your term live AI. That's actually what we are trying to achieve. Although I have not used that term before. Perhaps I'll borrow it for next time. >> Oh please, by all means. >> You see, yes, we have done, I've been doing also recent work on gene expression data. So a vaccine, clinical trial, they have the blood, they get the blood from the volunteers after the first day. And then to run very, very fast AI analytics on the gene expression data that the one, the transcription data, before translation to emit amino acid. The transcription data is enormous. We're talking 30,000, 60,000 different items, transcripts, and how to use that high dimensional data to predict on day one, whether this volunteer will get an adverse event or will have a good antibody outcome, right? For efficacy. So yes, how to do it so quickly, right? To get the blood, go through an SA, right, get the transcript, and then run the analytics and AI to produce an outcome. So that's exactly what we're trying to achieve, yeah. Yes, I always emphasize that, ultimately, the doctor makes that decision. Yeah, AI only suggests based on the data, this is the likely outcome based on all the previous data that the machine has learned from, yeah. >> Oh, I agree, we wouldn't want the machine to decide the fate of the patient, but to assist the doctor or nurse making the decision that will be invaluable? And are you aware of any kind of industry that already is using this kind of live AI? And then, is there anything in, I don't know in sport or crowd control? Or is there any kind of industry? I will be curious to see who is ahead of us in terms of making this kind of a minute based decisions using AI? Yes, in fact, this is very pertinent question. We as In fact, COVID-19, lots of effort working on it, right? But now, industries and different countries are starting to work on returning to work, right, returning to their offices, returning to the factories, returning to the manufacturing plants, but yet, the employers need to reassure the employees that things, appropriate measures are taken for safety, but yet maintain privacy, right? So our Aruba organization actually developed a solution called contact location tracing inside buildings, inside factories, right? Why they built this, and needed a lot of machine learning methods in there to do very, very well, as you say, live AI right? To offer a solution? Well, let me describe the problem. The problem is, in certain countries, and certain states, certain cities where regulations require that, if someone is ill, right, you actually have to go in and disinfect the area person has been to, is a requirement. But if you don't know precisely where the ill person has been to, you actually disinfect the whole factory. And if you have that, if you do that, it becomes impractical and cost prohibitive for the company to keep operating profitably. So what they are doing today with Aruba is, that they carry this Bluetooth Low Energy tag, which is a quarter size, right? The reason they do that is, so that they extract the tag from the person, and then the system tracks, everybody, all the employees. We have one company, there's 10,000 employees, right? Tracks everybody with the tag. And if there is a person ill, immediately a floor plan is brought up with hotspots. And then you just targeted the cleaning services there. The same thing, contact tracing is also produced automatically, you could say, anybody that is come in contact with this person within two meters, and more than 15 minutes, right? It comes up the list. And we, privacy is our focused here. There's a separation between the tech and the person, on only restricted people are allowed to see the association. And then things like washrooms and all that are not tracked here. So yes, live AI, trying to make very, very quick decisions, right, because this affects people. >> Another question I have for you, if you have a minute, actually has to be the same thing. Though, it's more a question about hardware, about computer hardware purify may. We're having, we're spending a lot of time computing on number crunching giant machines, like Sentinel, for instance, which is a dream to use, but it's very good at something but when we pulled it off, also spent a lot of time moving back and forth, so data from clouds from storage, from AI processing, to the computing cycles back and forth, back and forth, did you envision an architecture, that will kind of, combine the hardware needed for a massively parallel calculations, kind of we are doing. And also very large storage, fast IO to be more AI friendly, so to speak. You see on the horizon, some kind of, I would say you need some machine, maybe it's to be determined, to be ambitious at times but something that, when the AI ahead plan in terms of passing the vector to the massively parallel side, yeah, that makes sense? >> Makes a lot of sense. And you ask it I know, because it is a tough problem to solve, as we always say, computation, right, is growing capability enormously. But bandwidth, you have to pay for, latency you sweat for, right? >> That's a very good >> So moving data is ultimately going to be the problem. >> It is. >> Yeah, and we've move the data a lot of times, right, >> You move back and forth, so many times >> Back and forth, back and forth, from the edge that's where you try to pre-process it, before you put it in storage, yeah. But then once it arrives in storage, you move it to memory to do some work and bring it back and move it memory again, right, and then that's what HPC, and then you put it back into storage, and then the AI comes in you, you do the learning, the other way around also. So lots of back and forth, right. So tough problem to solve. But more and more, we are looking at a new architecture, right? Currently, this architecture was built for the AI side first, but we're now looking and see how we can expand that. And this is that's the reason why we announced HPE Ezmeral Data Fabric. What it does is that, it takes care of the data, all the way from the edge point of view, the minute it is ingested at the edge, it is incorporated in the global namespace. So that eventually where the data arrives, lands at geographically one, or lands at, temperature, hot data, warm data or cold data, regardless of eventually where it lands at, this Data Fabric checks everything, from in a global namespace, in a unified way. So that's the first step. So that data is not seen as in different places, different pieces, it is a unified view of all the data, the minute that it does, Just start from the edge. >> I think it's important that we communicate that AI is purposed for good, A lot of sci-fi movies, unfortunately, showcase some psychotic computers or teams of evil scientists who want to take over the world. But how can we communicate better that it's a tool for a change, a tool for good? >> So key differences are I always point out is that, at least we have still judgment relative to the machine. And part of the reason we still have judgment is because our brain, logical center is automatically connected to our emotional center. So whatever our logic say is tempered by emotion, and whatever our emotion wants to act, wants to do, right, is tempered by our logic, right? But then AI machine is, many call them, artificial specific intelligence. They are just focused on that decision making and are not connected to other more culturally sensitive or emotionally sensitive type networks. They are focus networks. Although there are people trying to build them, right. That's this power, reason why with judgment, I always use the phrase, right, what's correct, is not always the right thing to do. There is a difference, right? We need to be there to be the last Judge of what's right, right? >> Yeah. >> So that says one of the the big thing, the other one, I bring up is that humans are different from machines, generally, in a sense that, we are highly subtractive. We, filter, right? Well, machine is highly accumulative today. So an AI machine they accumulate to bring in lots of data and tune the network, but our brains a few people realize, we've been working with brain researchers in our work, right? Between three and 30 years old, our brain actually goes through a pruning process of our connections. So for those of us like me after 30 it's done right. (laughs) >> Wait till you reach my age. >> Keep the brain active, because it prunes away connections you don't use, to try and conserve energy, right? I always say, remind our engineers about this point, about prunings because of energy efficiency, right? A slice of pizza drives our brain for three hours. (laughs) That's why, sometimes when I get need to get my engineers to work longer, I just offer them pizza, three more hours, >> Pizza is universal solution to our problems, absolutely. Food Indeed, indeed. There is always a need for a human consciousness. It's not just a logic, it's not like Mr. Spock in "Star Trek," who always speaks about logic but forgets the humanity aspect of it. >> Yes, yes, The connection between the the logic centers and emotional centers, >> You said it very well. Yeah, yeah and the thing is, sleep researchers are saying that when you don't get enough REM sleep, this connection is weakened. Therefore, therefore your decision making gets affected if you don't get enough sleep. So I was thinking, people do alcohol test breathalyzer test before they are allowed to operate sensitive or make sensitive decisions. Perhaps in the future, you have to check whether you have enough REM sleep before, >> It is. This COVID-19 crisis obviously problematic, and I wish it never happened, but there is something that I never experienced before is, how people are talking to each other, people like you and me, we have a lot in common. But I hear more about the industry outside of my field. And I talk a lot to people, like cryo-EM people or gene expression people, I would have gotten the data before and process it. Now, we have a dialogue across the board in all aspects of industry, science, and society. And I think that could be something wonderful that we should keep after we finally fix this bug. >> Yes. yes, yes. >> Right? >> Yes, that's that's a great point. In fact, it's something I've been thinking about, right, for employees, things have changed, because of COVID-19. But very likely, the change will continue, yeah? >> Right. Yes, yes, because there are a few positive outcomes. COVID-19 is a tough outcome. But there positive side of things, like communicating in this way, effectively. So we were part of the consortium that developed a natural language processing system in AI system that would allow you scientists to do, I can say, with the link to that website, allows you to do a query. So say, tell me the latest on the binding energy between the Sasko B2 virus like protein and the AC receptor. And then you will, it will give you a list of 10 answers, yeah? And give you a link to the papers that say, they say those answers. If you key that in today to NLP, you see 315 points -13.7 kcal per mole, which is right, I think the general consensus answer, and see a few that are highly out of out of range, right? And then when you go further, you realize those are the earlier papers. So I think this NLP system will be useful. (both chattering) I'm sorry, I didn't mean to interrupt, but I mentioned yesterday about it, because I have used that, and it's a game changer indeed, it is amazing, indeed. Many times by using this kind of intelligent conceptual, analyzes a very direct use, that indeed you guys are developing, I have found connections between facts, between clinical or pharmaceutical aspects of COVID-19. That I wasn't really aware of. So a it's a tool for creativity as well, I find it, it builds something. It just doesn't analyze what has been done, but it creates the connections, it creates a network of knowledge and intelligence. >> That's why three to 30 years old, when it stops pruning. >> I know, I know. (laughs) But our children are amazing, in that respect, they see things that we don't see anymore. they make connections that we don't necessarily think of, because we're used to seeing a certain way. And the eyes of a child, are bringing always something new, which I think is what AI could potentially bring here. So look, this is fascinating, really. >> Yes, yes, difference between filtering subtractive and the machine being accumulative. That's why I believe, the two working together, can have a stronger outcome if used properly. >> Absolutely. And I think that's how AI will be a force for good indeed. Obviously see, seems that we would have missed that would end up being very important. Well, we are very interested in or in our quest for drug discovery against COVID-19, we have been quite successful so far. We have accelerated the process by an order of magnitude. So we're having molecules that are being tested against the virus, otherwise, it would have taken maybe three or four years to get to that point. So first thing, we have been very fast. But we are very interested in natural products, that chemicals that come from plants, essentially. We found a way to mine, I don't want to say explore it, but leverage, that knowledge of hundreds of years of people documenting in a very historical way of what plants do against what diseases in different parts of the world. So that really has been a, not only very useful in our work, but a fantastic bridge to our common human history, basically. And second, yes, plants have chemicals. And of course we love chemicals. Every living cell has chemicals. The chemicals that are in plants, have been fine tuned by evolution to actually have some biological function. They are not there just to look good. They have a role in the cell. And if we're trying to come up with a new growth from scratch, which is also something we want to do, of course, then we have to engineer a function that evolution hasn't already found a solution to, for in plants, so in a way, it's also artificial intelligence. We have natural solutions to our problems, why don't we try to find them and see their work in ourselves, we're going to, and this is certainly have to reinvent the wheel each time. >> Hundreds of millions of years of evolution, >> Hundreds of millions of years. >> Many iterations, >> Yes, ending millions of different plants with all kinds of chemical diversity. So we have a lot of that, at our disposal here. If only we find the right way to analyze them, and bring them to our supercomputers, then we will, we will really leverage this humongus amount of knowledge. Instead of having to reinvent the wheel each time we want to take a car, we'll find that there are cars whose wheels already that we should be borrowing instead of, building one each time. Most of the keys are out there, if we can find them, They' re at our disposal. >> Yeah, nature has done the work after hundreds of millions of years. >> Yes. (chattering) Is to figure out, which is it, yeah? Exactly, exactly hence the importance of biodiversity. >> Yeah, I think this is related to the Knowledge Graph, right? Where, yes, to objects and the linking parameter, right? And then you have hundreds of millions of these right? A chemical to an outcome and the link to it, right? >> Yes, that's exactly what it is, absolutely the kind of things we're pursuing very much, so absolutely. >> Not only only building the graph, but building the dynamics of the graph, In the future, if you eat too much Creme Brulee, or if you don't run enough, or if you sleep, well, then your cells, will have different connections on this graph of the ages, will interact with that molecule in a different way than if you had more sleep or didn't eat that much Creme Brulee or exercise a bit more, >> So insightful, Dr. Baudry. Your, span of knowledge, right, impressed me. And it's such fascinating talking to you. (chattering) Hopefully next time, when we get together, we'll have a bit of Creme Brulee together. >> Yes, let's find out scientifically what it does, we have to do double blind and try three times to make sure we get the right statistics. >> Three phases, three clinical trial phases, right? >> It's been a pleasure talking to you. I like we agreed, you knows this, for all that COVID-19 problems, the way that people talk to each other is, I think the things that I want to keep in this in our post COVID-19 world. I appreciate very much your insight and it's very encouraging the way you see things. So let's make it happen. >> We will work together Dr.Baudry, hope to see you soon, in person. >> Indeed in person, yes. Thank you. >> Thank you, good talking to you.

>> Narrator: From around the globe, it's theCUBE with digital coverage of AnsibleFest 2020, brought to you by Red Hat. >> The ascendancy of massive clouds underscored the limits of human labor. People, they simply don't scale at the pace of today's technology. And this trend created an automation mandate for IT which has been further accentuated by the pandemic. The world is witnessing the build-out of a massively distributed system that comprises on-prem apps, public clouds and edge computing. The challenge we face is how to go from managing things you can see and touch to cost effectively managing, securing and scaling these vast systems. It requires an automation first mindset. Hello, everyone. This is Dave Vellante and welcome back to AnsibleFest 2020. We have a great panel to wrap up this show. With me are our three excellent guests and CUBE alums. Ashesh Badani is the Senior Vice President of Cloud Platforms at Red Hat. Ashesh, good to see you again. Thanks for coming on. >> Yeah, likewise. Thanks for having me on again, Dave. >> Stefanie Chiras is Vice President and General Manager of the RHEL Business Unit and my sports buddy. Stefanie, glad to see you back in the New England area. I knew you'd be back. >> Yeah, good to see you, Dave. Thanks for having us today. >> You're very welcome. And then finally, Joe Fitzgerald, longtime CUBE alum, Vice President and General Manager of the Management Business Unit at Red Hat. Joe, good to see you. >> Hey, Dave, good to be here with you. >> Ashesh, I'm going to start with you. Lay out the big picture for us. So how do you see this evolution to what we sometimes talk about as hybrid cloud, but really truly a hybrid cloud environment across these three platforms that I just talked about? >> Yeah, let me start off by echoing something that most of your viewers have probably heard in the past. There's always this notion about developers, developers, developers. And you know, that still holds true. We aren't going away from that anymore. Developers are the new kingmakers. But increasingly, as the scope and complexity of applications and services that are deployed in this heterogeneous environment increases, it's more and more about automation, automation, automation. In the times we live in today, even, you know, before dealing with the crises that, you know, we have, just the sheer magnitude of requirements that are being placed on enterprises and expectations from customers require us to be more and more focused on automating tasks which humans just can't keep up with. So you know, as we look forward, this conversation here today, you know, what Ansible's doing, you know, is squarely aimed at dealing with this complexity that we all face. >> So Stefanie, I wonder if you could talk about what it's going to take to implement what I call this true hybrid cloud, this connection and management of this environment. RHEL is obviously a key piece of that. That's going to be your business unit, but take us through your thoughts there. >> Yeah, so I'm kind of building on what Ashesh said. When we look at this hybrid cloud world, right, which now hybrid is much more than it was considered five years ago. It used to be hybrid was on-prem versus off-prem. Now, hybrid translates to many layers in the stack. It can be VMs hybrid with containers. It can be on-prem with off-prem and clearly with edge involved, as well. Whenever you start to require the ability to bridge across these, that's where we focus on having a platform that allows you to access sort of all of those and be able to deploy your applications in a simple way. When I look at what customers require, it's all about speed of deploying applications, right, build, deploy and run your applications. It's about stability, which is clearly where we're focused on RHEL being able to provide that stability across multiple types of hybrid deployment models. And third is all about scale. It is absolutely all about scale and that's across multiple ranges in hybrid, be it on-prem, off-prem, edge and that's where all of this automation comes in, so to me, it's really about where do you make those strategic decisions that allow you to choose, right, for the flexibility that you need and still be able to deploy applications with speed, have that stability, resiliency, and be able to scale. >> So Joe, let's talk about your swim lane and it's weird to even use that term, right? 'Cause as Stefanie just said, we're kind of breaking down all these silos that we talk in terms of platform, but how do you see this evolving, and specifically, what's the contribution from a management perspective? >> Right, so Stefanie and Ashesh talked about sort of speed, scale and complexity. Right, people are trying to deploy things faster or larger scale, and oh, by the way, keep everything highly available and secure. That's a challenge, right? And so, you know, interestingly enough, Red Hat, about five years ago, we recognized that automation was going to be a problem as people were moving into open hybrid clouds, which we've been working with our customers for years on. And so we acquired this small company called Ansible, which had some really early emerging technology, all open source, right, to do automation. And what we've done over the past five years is we've really amplified that automation and amplified the innovation in that community to be able to provide automation across a wide array of domains that you need to automate, right, and to be able to plug that in to all the different processes that people need in order to be able to go faster, but to track, manage, secure and govern these kind of environments. So we made this bet years ago and it's paying off for Red Hat in very big ways. >> I mean, no doubt about it. I mean, when you guys bought Ansible, so it wasn't clear that it was going to be the clear leader. It is now. I mean, it's pulled ahead of Chef, Puppet. You saw, you know, VMware bought Salt, but I mean, Ansible very clearly has, based on our surveys, the greatest market momentum. We're going to talk about that. I know some of the other analysts have chimed in on this, but let me come back to this notion of on-prem and cloud and edge and this is complicated. I mean, the edge, it's kind of its own island, isn't it? I mean, you got the IT and the OT schism, so maybe you could talk a little bit about how you see those worlds coming together, the cloud, the on-prem, the edge. Maybe Stefanie, you can start. >> Yeah, I think the magic, Dave, is going to happen when it's not its own island, right, as we start to see this world driven by data cause the spread of a data center to be really dis-aggregated and allow that compute to move out closer to the data, the magic happens when it doesn't feel like an island, right, that's the beauty and the promise of hybrid. So when you start to look at what can you provide that is consistent that serves as a single language that you can talk to from on-prem, off-prem and edge, you know, it all comes down to, for us, having a platform that you can build once and deploy across all of those, but the real delicacy with edge is there are some different deployment models. I think that comes into deployment space and we're clearly getting feedback from customers. We're working on some capabilities where edge requires some different deployment models in the ways you update, et cetera, and thanks to all of you out there who are working with us upstream in order to deliver that. And I think the second place where it's unique is in this ability to manage and automate out at the edge, but our goal is certainly at our platform levels, whether it be on RHEL, whether it be on OpenShift to provide that consistent platform that allows you that ease of deployment, then you got to manage and automate it and that's where the whole Ansible and the ecosystem really plays in. You need that ecosystem and that's always what I love about AnsibleFest is this community comes together and it's a vibrant community, for sure. >> Well, I mean, Ashesh, you guys are betting big on this and I often think of the cloud is just this one big cloud. You got the on-prem cloud, you got the public clouds. Edge becomes just an extension of that cloud. Is that how you think about it and what is it actually going to take to make that edge not an island? >> Yeah, great point, Dave, and that's exactly how we think about it. We've always thought about our vision of the cloud as being a platform and abstraction that spans all the underlying infrastructure that the user can take advantage of, so if it happens to reside in a data center, some in a private cloud running off a data center, more increasingly in the public cloud setting, and as Stefanie called out, we're also starting to see edge deployments come in. We're seeing, you know, big build-outs in the work we're doing with telecom providers from a 5G perspective that's helping drive that. We're seeing, if you will, IOT-like opportunities with, let's say, the automotive sector or some in the retail sector, as well. And so this fabric, if you will, needs to span this entire set of deployment that a customer will take advantage of. And Joe started touching on this a little bit, right, with this notion of the speed, scale and complexity, so we see this platform needing to expand to all these footprints that customers are using. At the same time, the requirements that they have, even when they're going out the edge, is the same with regard to what they see in the data center and the public cloud, so putting all that together really is our sweet spot. That's our focus. And to the point you're making, Dave, that's where we're making a huge bet across all of Red Hat. >> So I mentioned, you know, some of our research and I do these breaking analysis segments every week and recently I was digging into cloud and specifically was interested in hybrid and multi. And you know, hybrid been I think pretty well understood for awhile. Multi I think was a lot of, you know, a lot of talk, but it's becoming real and the data really shows that. It shows OpenShift and Ansible have momentum. I mentioned that before. Yeah, you know, obviously VMware is there, but clearly Red Hat is well positioned specifically in multicloud and hybrid. And I know some of the other analyst firms have picked up on this. What are you guys seeing in the market? Maybe Joe, you can chime in and Ashesh, you can maybe add some color. >> Yeah, so you know, there's a lot of fashion, right, around hybrid and multicloud today, so every vendor is jumping on with multicloud storing. And you know, a lot of the vendors' strategies are, pick my solution and vertically use my stuff in the public cloud on-premise, maybe even at the edge, right, and you'll be fine. And you know, obviously customers don't like lock-in. They like to be able to take advantage of the best services, availability, security, different things that are available in each of these different clouds, right? So there is a strong preference for hybrid and multicloud. Red Hat is sort of the Switzerland of hybrid and multicloud because we enable you to run your workloads across all these different substrates, whether it's in public clouds, multiple, right, into the data center and physical, virtual, bare metal, out to the edge and edge is not a single homogeneous, you know, set of hardware or even implementation. It varies a lot by vertical, so you have a lot of diversity, right? And so Red Hat is really good at helping provide the platforms like OpenShift and RHEL that are going to provide that consistency across those different environments or also in the case of Ansible to provide automation that's going to match the physics of management and automation that are required across each of those different environments. Trust me, managing or automating something at the edge and with very small footprint of some device across the constraint network is very, very different than managing things in a public cloud or in a data center and that's where I think Red Hat is really focused and that's our sweet spot, helping people manage those environments. >> And Ashesh, you guys have obviously put a lot of effort there. If you could maybe comment. >> Yeah, I was just going to say, Dave, I'll add just really quickly to what Joe said. He said it well. But the thing I will add is the way for us to succeed here is to follow the user, follow the customer. Right, instead of us just coming out with regard to what we believe the path to be, you know, we're really kind of working closely with the actual customers that we have. So for example, recently been working with a large water utility in Italy, but they're thinking about, you know, the world that they live in and how can they go off and, you know, have kiosks that are spread throughout Italy, able to provide reports with regard to the quality of the water that's available, as well as other services to all their citizens. But it's really interesting use case for us to go off and pursue because in some sense, you can ask yourself, well, is that public cloud? Are they going to take advantage of those services? Is that, you know, private cloud? Is that data center, is that IOT, is that edge? At a certain point in time, what you've got to think about is, well, we've got to provide integrated end-to-end solution that spans all of these different worlds, and so as long as I think we keep that focus, as long as we make sure our North Star is really what the user's trying to do, what problem they're trying to solve, I think we'll come out just fine on the other side of this. >> So I'd love to get all your thoughts, all three of you, on just what's going on in containers, generally, Kubernetes, specifically. I mean, everybody knows it's a hot space and the data shows that it is maturing, but it's amazing to me how much momentum it still has. I mean, it's like the new shiny toy, but it's everywhere and so it's able to sort of maintain that velocity and it's really becoming the go-to cloud native development platform, so the question is how is Red Hat, you know, helping your customers connect OpenShift to the rest of their IT infrastructure, platforms, their processes, the tools. I mean, who wants to start? I'd love to hear from all three of you. Ashesh, why don't you kick it off and then we'll just go left to right. >> So Dave, we've spoken to you and to folks the CUBE, as well, other for many years on this. We've made a huge investment in the Kubernetes market and been one of the earliest to do that and we continue to believe in the promise that it delivers to users, this notion of being able to have an environment that customers can use regardless of the underlying choices that they make. Here's an extremely powerful one, it's truly an open source, right? This is key to, you know, what we do. Increasingly, what we're working on is to ensure that one, if you make a commitment to Kubernetes and increasingly we see lots of customers around the world doing that, that we ensure that we're working closely, that our entire portfolio helps support that. So if you're going to make a choice with regard to Kubernetes base deployment, we help support you running it yourself wherever it is that you choose to run it, we help support you whether you choose to have us manage on your behalf and then also make sure we're providing an entire portfolio of services, both within Red Hat as well as from third parties so that you have the most productive, integrated experience possible. >> Okay, and Stefanie, loved your point of view on this, and Joe, I'd love to understand how you're bridging kind of the Ansible and Kubernetes communities, but Stefanie, why don't you chime in first? >> Yeah, I'll quickly add to what Ashesh said and talked about well on really the promise and the value of containers, but particularly from a RHEL perspective, we have taken all our capabilities and knowledge in the Linux space and we have taken that to apply it to OpenShift, right, because Kubernetes and containers is just another way to deploy Linux, so making sure that that underpinning is stable, secure and resilient and tied to an ecosystem, right? An ecosystem of various architectures, an ecosystem of ISVs and tooling, right? We've pulled that together and everything we've done in Linux for, you know, over decades now at Red Hat and we've put that into that customer experience around OpenShift to deploy containers, so we've really built, it has been a portfolio-wide effort, as Ashesh alluded to, and of course, it passes over to Ansible as well with Joe's portfolio. >> Yeah, we talked about this upfront, Joe. The communities are so crucial, so how are you bridging those Ansible and Kubernetes communities? What's your thought on that? >> Well, a quick note about those communities. So you know, OpenShift is built on Kubernetes and a number of other projects. Kubernetes is number seven in the top 10 open source projects based on the number of contributors. Turns out Ansible is number nine, right? So if you think about it, these are two incredibly robust communities, right? On the one hand, building the container platform in Kubernetes and in the other around Ansible and automation. It turns out that as the need for this digital acceleration and building these container-based applications comes along, there's a lot of other things that have to be done when you deploy container-based applications, whether it's infrastructure automation, right, to expand and manage and automate the infrastructure that you're running your container-based applications on, creating more clusters, you know, configuring storage, network, you know, counts, things like that, but also connecting to other systems in the environment that need to be integrated with around, you know, ITSM or systems of record, change management, inventory, cost, things like that, so what we've done is we've integrated Ansible, right, in a very powerful way with OpenShift through our advanced cluster management capability, which allows us to provide an easy way to instrument Ansible during critical points, whether it's you're deploying new clusters out there or you're deploying a new version of an application or a new application for the first time, whether you're checking policy, right, to ensure that, you know, the thing is secure and that, you know, you can govern these environments, right, that you're relying on. So we've really now tied together two sort of de facto standards, OpenShift built on Kubernetes and a number of other projects and then Ansible, or Red Hat, has taken this innovation in the community and created these certified content collections, platforms and capabilities that people can actually build and rely on and know that it's going to work. >> Ashesh, I mean, Red Hat has earned the right, really, to play in both the cloud native world and of course the traditional infrastructure world, but I'm interested in what you're seeing there, how you're bringing those two worlds together. Are they still, you know, largely separate? Are you seeing traditional IT? I mean, you're certainly seeing them lean in to more and more cloud native, but what are you guys doing specifically to kind of bring those worlds together? >> Yeah, increasingly it's really hard to be able to separate out those worlds, right? So in the past, we used to call it shadow IT. There really is no shadow IT anymore, right? This is IT. So we've embraced that completely. You know, our take on that is to say there are certain applications that are going to be appropriate for being run in a data center a certain way. There are certain other workloads that'll find their way appropriate for the public cloud. We want to make sure we're meeting them across, but what we want to do is constantly introduce technologies to help support the choices customers make. What do I mean by that? Let me give a couple examples. One is, you know, we can say customers have VMs that are based out in specific environments and they can only run as VMs. That code can't be containerized for a variety of reasons, right? You know, hard to re-architect that, don't have the funds, you know, have certain security compliance reasons. Well, what if we could take those VMs and then have them be run in containers in a native fashion? Wouldn't that be extremely powerful value proposition to run containers and then VMs as containers sort of side by side with Kubernetes orchestrating them all. So that's a capability we call open source virtualization. We've introduced that and made that generally available within our platform. Another one, which I think Joe starting to touch on a little bit here, is both around this notion of Ansible, as well as advanced cluster management. And say, once technologies like Ansible are familiar to our customers, how about if we find ways to introduce things like the operator framework to help support people's use of Ansible and introduce technologies like advanced cluster management, which allows for us to say, well, regardless of where you run your clusters, whether you run your Kubernetes clusters on premise, you run them in the cloud, right, we can imagine a consistent fashion and manage, you know, health and policy and compliance of applications across that entire state. So David, question's extremely good one, right, but what we are trying to do is try to be able to say, you know, we are going to just span those two worlds and provide as many tools as possible to ensure that customers feel like, you know, the shift, if you will, or the move between traditional enterprise software application development and the more modern cloud native can be bridged as seamlessly as possible. >> Yeah, Joe, we heard a lot of this at AnsibleFest, so the ACM as a key component of your innovation, and frankly, your competitive posture. Anything you would add to what Ashesh just shared? >> Well, I think that one of the things that Red Hat is really good at is we take management and automation as sort of an intrinsic part of what needs to go on. It's not an afterthought. You just don't go build something, go, "Oh I need management," go out and, you know, go get something, right, so we've been working on, sort of automation and management for many, many years, right, so we build it in concert with these platforms, right, and we understand the physics of these different environments, so we're very focused on that from inception, as opposed to an afterthought when people sort of paint themselves into a corner or have management challenges they can't deal with. >> There's a lot of analogs in our business, isn't there? Management is a bolt-on and security is a bolt-on. It just doesn't work that well and certainly doesn't scale. Stefanie, I want to come back to you and I want to come back to the edge. We hear a lot of people talking about extending their deployments to the edge in the future. I mean, you look at what IBM's doing. They're essentially betting its business on RHEL and OpenShift and betting that its customers are going to do the same as well are you. Maybe talk about, you know, what you're doing to specifically extend RHEL to the edge. >> Yeah, Dave, so we've been looking at this space consistent with our strategy, as Ashesh talked about, right? Our goal is to make sure that it all looks and feels the same and provides one single Linux experience. We've been building on a number of those aspects for quite some time, things like being able to deal with heterogeneous architectures, as an example, being able to deal with, you know, having Arm components and x86 components and power components and being able to leverage all of that from multiple vendors and being able to deploy. Those are things we've been focused on for a long time and now when you move into the space of the edge, certainly we're seeing, you know, essentially data center level hardware move out to be dis-aggregated and dispersed as they move it closer to the data and where that's coming in and where the analysis needs to be done, but some of those foundational things that we've been working on for years starts to pay off because the edge tends to be more heterogeneous all the way from an architecture level to an application level, so now we're seeing some asks. We've been working upstream in order to pull in some features that drive capabilities around specifically updating, deploying those updates, doing rollbacks and things like that, so we're focused on that. But really, it's about pulling together the capabilities of having multiple architectures, dealing with heterogeneous infrastructure out there at the edge, being able to reliably deploy it even when, for example, we have customers who they deploy their hardware and they can't touch it for years. How do they make sure that that's out there in a stable environment that they can count on? And then, you know, adding in things like containerization. We talked about the magic of that, being able to deploy an application consistently and being able to deploy a single container out there to the edge. We're thinking about it all the way from the architecture up to how the application gets deployed and it's going to take the whole portfolio to do that as you need to manage it, as you need to deploy containers, so it's a focus across the company for how we deal with that. >> And as we were talking about before, you know, it takes a village. You know that bromide, but it does, requires an ecosystem of jobs. I mean, there's some real technical challenges in R&D that has to happen. I mean, you've got to be, you know, you're talking about cloud native in all three different clouds, and you know, and not just the big three, but other clouds and then bringing that to the edge, so there's some clear technical challenges, but there's also some business challenges out there. So you know, what are you seeing in that regard? You know, what are some of those things that you hope to solve by bridging that gap? >> Well, I think one of the things we're trying to do and I'm focused on the management and automation side is to provide a common set of management tooling of automation, right, and I think Ansible fits that quite well. So for the past five years since Ansible's been part of Red Hat, we've expanded from, you know, they started off initially doing configuration management, right? We've expanded to include, you know, network and storage and security, now edge. At AnsibleFest, we demonstrated things like serverless event-driven automation, right, building an OpenShift serverless in Knative. We're trying to expand the use cases for Ansible so that there's a simplicity, there's a tool reduction, right, across all these environments and you don't have to go deal with nine vendors, and you know, 17 different tools to try to manage each element here to be able to provide a common set. It reduces complexity, cost and allows skills to be able to be reused across these different areas. It's going to all be about digital acceleration, right, and reducing that complexity. And one last comment. One of the reasons we bought Ansible years ago is the architecture, it's agent-less. Many of our competitors that you hear, the first thing they want to do is go deploy an agent somewhere and that creates its own ongoing burden of, do I have the latest version of the agent? Is it secure? Does it fit on the device? As Stefanie mentioned, is there a version that fits on the architecture the device is running on? It starts getting really, really complicated. So Ansible is just simple, elegant, agent-less. We've expanded the domains we can automate with it and we've expanded sort of the modality. How can I call it? User, driven by an event, as part of some life cycle management, app deployment, Ansible plugs right in. >> Well, Joe, you can tell you're a management guy, right? Agents, another thing that has to be managed. You just laundry list of stuff. (laughs) I want to come back to this notion Joe just touched on, this digital transformation. They say, "If it ain't broke, don't fix it." Well, COVID broke everything. And I got to say, I mean, all the talk about digital transformation over the last, you know, several years, yes, it was certainly happening, but there was also a lot of lip service going on and now if you're not digital, you're out of business. And so, you know, given everything that we've seen in the last, you know, whatever, 150, 200 days or so, what's the impact that you're seeing on customers' digital transformation initiatives, and you know, what is Red Hat doing to respond? Maybe Ashesh, you could start and we can get feedback from the others. >> Yeah, David, it's an unfortunate thing to say, right, but there's that meme going around with regard to who's responsible for digital transformation and it's a little bit of I guess gallows humor to call it COVID, but we're increasingly seeing that customers and the journey that they're on is one that they haven't really gotten off, even with this, if you will, change of environment that's come about. So projects that we've seen in play, you know, are still underway. We've seen acceleration, actually, in some places with regard to making services more easily accessible. Anyone who's invested in hybrid cloud or public cloud is seeing huge value with regard to being able to consume services remotely, being able to do this on demand and that's a big part of the value proposition, you know, that comes forward. And increasingly what we're trying to do is try to say, how can we engage and assist you in these times, right? So our services team, for example, has transformed to be able to help customers remotely. Our support team has gone off and work more and more with customers. For a company like Red Hat, that hasn't been completely, if you will, difficult thing to do mostly because we've been so used to working in a distributed fashion, working remotely with our customers, so that's not a challenge in itself, but making sure customers understand that this is really a critical journey for them to go on and how we can kind of help them, you know, walk through that has been good and we're finding that that message really resonates. Right, so both Stefanie and Joe talked a little bit about, you know, how essentially our entire portfolio is now built around, you know, ensuring that if you'd like to consume on demand, we can help support you, if you'd like to consume in a traditional fashion, we can help you. That amount of flexibility that we provide to customers is really coming to bear at this point in time. >> So maybe we could wrap with, we haven't really dropped any customer names. Stefanie and Joe and Ashesh, I wonder if you have any stories you can share or, you know, customer examples that we could close on that are exciting to you this year. >> So I can start, if that's okay. >> Please. >> So an area that I find super interesting from a customer perspective that we're increasingly seeing more and more customers go down is sheer interest in, if you will, kind of diversity of use cases that we're seeing, right? So we see this, for example, in automotive, right? So whether it's a BMW or a Volkswagen, we see this now in health care with the ACA, in we'll say a little bit more traditional industries like energy with Exxon or Schlumberger around increasingly embrace of AIML, right? So artificial machine learning, if you will, advanced analytics being much more proactive with regard to how they can take data that's coming in, adjust it, be able to make sense of the patterns and then be able to, you know, have some action that has real business impact. So this whole trend towards, you know, AIML workloads that they can run is extremely powerful. We work very closely with Nvidia, as well, and we're seeing a lot of interest, for example, in being able to run a Kubernetes-based platform, support Nvidia GPUs for specific class workloads. There's a whole bunch of customers, people in financial services that, you know, this is a rich area of interest. You know, we've seen great use cases for example around grid with Deutsche Bank. And so, to me, I'm personally really excited to see kind of that embrace the PC from our customers regard to saying there's a whole lot of data that's out there. You know, how can we essentially use all of these tools that we have in place? You know, we talk about containers, microservices, DevOps, you know, all of this and then put it to bear to really put to work and get business value. >> Great, thank you for that, Ashesh. Stefanie, Joe, Stefanie, anything you want to add or final thoughts? >> Yeah, just one thing to add and I think Ashesh talked to a whole number across industry verticals and customers. But I think the one thing that I've seen through COVID is that if nothing else, it's taught us that change is the only constant and I think, you know, our whole vision of open hybrid cloud is how to enable customers to be flexible and do what they need to do when they need to do it, wherever they want to deploy, however they want to build. We provide them some consistency, right, across that as they make those changes and I think as I've worked with customers here through since the beginning of COVID, it's been amazing to me the diversity of how they've had to respond. Some have doubled down in the data center, some have doubled down on going public cloud and to me, this is the proof of the strategy that we're on, right, that open hybrid cloud is about delivering flexibility, and boy, nothing's taught us the need for flexibility like COVID has recently, so I think there's a lot more to do. I think pulling together the platforms and the automation is what is going to enable the ability to do that in a simple fashion. >> So Joe, you get the final word. I mean, AnsibleFest 2020, I mean, it's weird, right? But that's the way these events are, all virtual. Hopefully, next year we got a shot at being face to face, but bring us home, please. >> Yeah, I got to tell ya, having, you know, 20,000 or so of your closest friends get together to talk about automation for a couple of days is just amazing. That just shows you sort of the power of it. You know, we have a lot of customers this week at AnsibleFest telling you their story, you know, CarMax and ExxonMobil, you know, BlueCross BlueShield. I mean, there's a number across all different verticals, globally, Cepsa from Europe. I mean, just an incredibly, you know, diverse array of customers and use cases. I would encourage people to look at some of the customer presentations that were on at AnsibleFest, listen to the customer telling you what they're doing with Ansible, deploying their networks, deploying their apps, managing their infrastructure, container apps, traditional apps, connecting it, moving faster. They have amazing stories. I encourage people to go look. >> Well, guys, thanks so much for helping us wrap up AnsibleFest 2020. It was really a great discussion. You guys have always been awesome CUBE guests. Really appreciate the partnership and so thank you. >> Thanks a lot, Dave. Appreciate it. >> Yeah, thanks, Dave. >> Thanks for having us. >> All right, and thank you for watching, everybody. This is Dave Vellante for theCUBE and we'll see you next time. (calm music)

>> (upbeat music) >> production: From around the globe, it's the Cube covering Google cloud Next on-Air 20. (Upbeat music) >> Welcome back. I'm Stu Miniman and this is the CUBE coverage of Google cloud Next on Air 20. Of course, the nine week distributed all online program that Google cloud is doing and going to be talking about, of course, multi-cloud, Google of course had a big piece in multi-cloud. When they took what was originally Borg, They built Kubernetes. They made that open source and gave that to the CNCF and one of Google's partners and a leader in that space is of course, Red Hat. Happy to welcome to the program Sathish Balakrishnan, he is the Vice President of hosted platforms at Red Hat. Sathish, thanks so much for joining us. >> Thank you. It's great to be here with you on Google Cloud Native insights. >> Alright. So I, I tied it up, of course, you know, we talk about, you know, the hybrid multicloud and open, you know, two companies. I probably think of the most and that I've probably said the most about the open cloud are Google and Red Hat. So maybe if we could start just, uh, you hosted platforms, help us understand what that is. And, uh, what was the relationship between Red Hat and the Open Shift team and Google cloud? >> Absolutely. Great question. And I think Google has been an amazing partner for us. I think we have a lot of things going on with them upstream in the community. I think, you know, we've been with Google and the Kubernetes project since the beginning and you know, like the second biggest contributor to Kubernetes. So we have great relationships upstream. We also made Red Hat Enterprise Linux as well as Open Shift available on Google. So we have customers using both our offerings as well as our other offerings on Google cloud as well. And more recently with the hosted our offerings. You know, we actually manage Open Shift on multiple clouds. We relaunched our Open Shift dedicated offering on Google cloud back at Red Hat Summit. There's a lot of interest for the offering. We had back offered the offering in 2017 with Open Shift Three and we just relaunched this with Open Shift Four and we received considerable interest for the Google cloud Open Shift dedicated offering. >> Yeah, Sathish maybe it makes sense if we talk about kind of the maturation of open source solutions, managed services has seen really tremendous growth, something we've seen, especially if we were talking about in the cloud space. Maybe if you could just walk us through a little bit out that, you know, what are you hearing from customers? How does Red Hat think about managed solutions? >> Absolutely. Stu, I think it was a good question, right? I think, uh, as we say, the customers are looking at, you know, multiple infrastructure footprints, Be iteither the public cloud or on-prem. They'll start looking at, you know, if I go to the cloud, you know, there's this concept of, I want something to be managed. So what Open Shift is doing is in Open Shift, as you know it's Red Hat's hybrid cloud platform and with Open Shift, all the things that we strive to do is to enable the vision of the Open Hybrid Cloud. Uh, so, but Open Hybrid Cloud, it's all about choice, So we want to make sure the customers have both the managed as well as the self managed option. Uh, so if you really look at it, you know, Red Hat has multiple offerings from a managed standpoint. One as you know, we have Open Shift dedicated, which runs from AWS and Google. And, you know, we just have, as I mentioned earlier. We relaunched our Google service at Red Hat Summit back in May. So that's actually getting a lot of traction. We also have joint offerings with Azure that we announced a couple of years back and, there's a lot of interest for that offering as well as the new offering that we announced post-summit, the Amazon-Red Hat Open Shift, which basically is another native offering that we have on Amazon. If you really look at, having, having spoken about these offerings, if you really look at Red Hat's evolution as a managed service provider in the public cloud, we've been doing this since 2011. You know, that's kind of surprising for a lot of people, but you know, we've been doing Open Shift online, which is kind of a multi-tenant parcel multi-talent CaaS solution 2011. And we are one of the earliest providers of managed kubernetes, you know, along with Google Kubernetes engine GKE, we are our Open Shift dedicated offering back in 2015. So we've been doing Kubernetes managed since, Open Shift 3.1. So that's actually, you know, we have a lot of experience with management of Kubernetes and, you know, the devolution of Open Shift we've now made it available and pretty much all the clouds. So that customers have that exact same experience that they can get any one cloud across all clouds, as well as on-prem. Managed service customers now have a choice of a self managed Open Shift or completely managed Open Shift. >> Yeah. You mentioned the choice and one of the challenges we have right now is there's really the paradox of choice. If you look in the Kubernetes space, you know, there are dozens of offerings. Of course, every cloud provider has their offerings. You know, Google's got GKE, they have Anthos, uh, they, they have management tools around there. You, you talked a bit about the, you know, the experience and all the customers you have, the, you know, there's one of the fighters talks about, there's no compression algorithm for experience. So, you know, what is Red Hat Open Shift? What really differentiates in the market place from, you know, so many of the other offerings, either from the public high providers, some of the new startups, that we should know. >> Yeah. I think that's an interesting question, right? I think all Google traders start with it's complete open source and, you know, we are a complete open source company. So there is no proprietary software that we put into Open Shift. Open Shift, basically, even though it has, you know, OC command, it basically has CPR. So you can actually use native Google networks as you choose on any Google network offering that you have be it GKE, EKS or any of the other things that are out there. So that's why I think there are such things with google networks and providers and Red Hat does not believe in open provider. It completely believes in open source. We have everything that we is open source. From an it standpoint, the value prop for Red Hat has always been the value of the subscription, but we actually make sure that, you know, Google network is taken from an upstream product. It's basically completed productized and available for the enterprise to consume. But that right, when we have the managed offering, we provide a lot more benefits to it, right? The benefits are right. We actually have customer zero for Open Shift. So what does that mean? Right. We will not release Open Shift if we can't run open Shift dedicated or any of their (indistinct) out Open Shift for them is under that Open Shift. Really really well. So you won't get a software version out there. The second thing is we actually run a lot of workloads, but then Red Hat that are dependent on our managed or open shift off. So for example, our billing systems, all of those internal things that are important for Red Hat run on managed Open Shift, for example, managed Open Shift. So those are the important services for Red Hat and we have to make sure that those things are running really, really well. So we provide that second layer of enterprise today. Then having put Open Shift online, out that in public. We have 4 million applications and a million developers that use them. So that means, I've been putting it out there in the internet and, you know, there's security hosts that are constantly being booked that are being plugged in. So that's another benefit that you get from having a product that's a managed service, but it also is something that enterprises can now use it. From an Open Shift standpoint, the real difference is we add a lot of other things on top of google network without compromising the google network safety. That basically helps customers not have to worry about how they're going to get the CIC pipeline or how they have to do a bunch of in Cobra Net as an outside as the inside. Then you have technologies like Store Street Metrics kind of really help customers not to obstruct the way the containerization led from that. So those are some of the benefits that we provide with Open Shift. >> Yeah. So, so, so Sathish, as it's said, there's lots of options when it comes to Kubernetes, even from a Red Hat offering, you've got different competing models there. If I look inside your portfolio, if it's something that I want to put on my infrastructure, if I haven't read the Open Shift container platform, is that significantly different from the managed platform. Maybe give us a little compare contrast, you know. What do I have to do as a customer? Is the code base the same? Can I do, you know, hybrid environments between them and you know, what does that mean? >> It's a smart questions. It's a really, really good question that you asked. So we actually, you know, as I've said, we add a lot of things on top of google network to make it really fast, but do you want to use the cast, you can use the desktop. So one of the things we've found, but you know, what we've done with our managed offering is we actually take Open Shift container platform and we manage that. So we make sure that you get like a completely managed source, you know. They'll be managed, the patching of the worker nodes and other things, which is, again, another difference that we have with the native Cobra Net of services. We actually give plush that admin functionality to customers that basically allows them to choose all the options that they need from an Open Shift container platform. So from a core base, it's exactly the same thing. The only thing is, it's a little bit opinionated. It to start off when we deploy the cluster for the customer and then the customer, if they want, they can choose how to customize it. So what this really does is it takes away any of the challenges the customer may have with like how to install and provision a cluster, which we've already simplified a lot of the open shift, but with the managed the Open Shift, it's actually just a click of it. >> Great. Sathish Well, I've got the trillion dollar question for you. One of the things we've been looking at for years of course, is, you know, what do I keep in my data center? What do I move to the cloud? How do I modernize it? We understand it's a complex and nuanced solution, but you talk to a lot of customers. So I, you know, here in 2020, what's the trends? What are some of the pieces that you're seeing some change and movement that, you know, might not have been the case a year ago? >> I think, you know, this is an interesting question and it's an evolving question, right? And it's something that if you ask like 10 people you'll get real answers, but I'm trying to generalize what I've seen just from all the customer conversations I've been involved. I think one thing is very clear, right? I think that the world is right as much as anybody may want to say that I'm going to go to a single cloud or I'm going to just be on prem. It is inevitable that you're going to basically end up with multiple infrastructure footprint. It's either multicloud or it's on Prem versus a single cloud or on prem versus multiple cloud. So the main thing is that, we've been noticing as, what customers are saying in a whole. How do I make sure that my developers are not confused by all these difference than one? How do I give them a consistent way to develop and build their applications? Not really worry about, what is the infrastructure. What is the footprint that they're actually servicing? So that's kind of really, really important. And in terms of, you know, things that, you know, we've seen customers, you know, I think you always start with compliance requirements and data regulations. Back there you got to figure it out. What compliance do I need? And as the infrastructure or the platform that I'm going to go to meet the compliance requirements that I have, and what are the data regulations? You know, what is the data I'm going to be setting? Is it going to meet the data submitted rules that my country or my geo has? I got to make sure I worry about that. And then I got to figure out if I'm going to basically more to the cloud from the data center or from one cloud to another cloud. I might just be doing a lift or shift. Am I doing a transformation? What is it that I really worry about? In addition to the transformation, they got to figure it out, or I need to do that. Do I not need to do that? And then, you know, we've got to figure out what your data going to set? What your database going to look in? And do you need to connect to some legacy system that you have on prem? Or how do you go? How do you have to figure that out and give them all of these complexities? This is really, really common for any large enterprise that has like an enterprise ID for that multi-cloud. That's basically in multiple geographies, servicing millions of customers. So that has a lot of experience doing all these things. We have open innovation labs, which are really, really awesome experience for customers. Whether they take a small project, they figured out how to change things. Not only learn how to change things from a technology standpoint, but also learn how to culturally change things, because a lot of these things. So it's not just moving from one infrastructure to another, but also learning how to do things differently. Then we have things like the container adoption programmer, which is like, how do you take a big legacy monolith application? How do you containerize it? How do you make it micro services? How do you make sure that you're leveraging the real benefits that you're going to get out of moving to the cloud or moving to a container platform? And then we have a bunch of other things like, how do you get started with Open Shift and all of that? So we've had a lot of experience with like our 2,400 plus customers doing this kind of really heavy workload migration and lifting. So the customers really get the benefits that they see out of Open Shift. >> Yeah. So Sathish, if I think about Google, specifically talking about Google cloud, one of the main reasons we hear customers using Google is to have access to the data services. They have the AI services they have. So how does that tie into what we were just talking about? If I, if I use Open Shift and you know. I'm living in Google cloud, can, can I access all of those cloud native services? Are there any nuances things I need to think about to be able to really unleash that innovation of the platform that I'm tying into? >> Yeah, absolutely not. Right. I think it's a great question. And I think customers are always wondering about. Hey, if I use Open Shift, am I going to be locked out of using the cloud services? And if anything run out as antilock. We want to make sure that you can use the best services that you need for your enterprise, like the strategy as well as for applications. So with that, right. And we've developed the operator framework, which I think Google has been a very early supporter of. They've built a lot of operators around their services. So you can develop those operators to monitor the life cycle of these services, right from Open Shift. So you can actually connect to an AI service if you want. That's absolutely fine. You can connect the database services as well. And you can leverage all of those things while your application runs on Open Shift from Google cloud. Also I think that done us right. We recognize that, when you're talking about the open hybrid cloud, you got to make sure that customers can actually leverage services that are the same across different clouds. So when you can actually leverage the Google services from On Prem as well, if you choose to have localized services. We have a large catalog of operators that we have in our operator hub, as well as in the Red Hat marketplace that you can actually go and leverage from third party, third party ISV, so that you're basically having the same consistent experience if you choose to. But based on the consistent experience, that's not tied to a cloud. You can do that as well. But we would like for customers to use any service that they want, right from Open Shift without any restrictions. >> Yeah. One of the other things we've heard a lot from Google over the last year or so has been, you know, just helping customers, especially for those mission, critical business, critical applications, things like SAP. You talked a bit about databases. What advice would you give customers these days? They're, they're looking at, you know, increasing or moving forward in their cloud journeys. >> I think it sounds as an interesting question because I think customers really have to look at, you know, what is the ID and technology strategy? What are the different initiatives to have? Is it digital transformation? Is it cloud native development? Is it just containerization or they have an overarching theme over? They've got to really figure that out and I'm sure they're looking at it. They know which one is the higher priority when all of them are interrelated and in some ways. They also got to figure out how they going to expand to new business. Because I think as we said, right, ID is basically what is driving personal software is eating the load. Software services are editing them. So you got to figure out, what are your business needs? Do you need to be more agile? Do you need to enter new businesses? You know, those are kind of important things. For example, BMW is a great example, they use Open Shift container platform as well as they use Open Shift dedicated, you know. They are like a hundred hundred plus year old car, guess, you know what they're trying to do. They're actually now becoming connected car infrastructure. That's the main thing that they're trying to build so that they can actually service the cars in any job. So in one shoe, they came from a car manufacturing company to now focus on being a SAS, an Edge and IOT company. If you really look at the cars as like the internet of things on an edge computer and what does that use case require? That use case cannot anymore have just one data center in Munich, they have to basically build a global platform of data centers or they can really easily go to the cloud. And then they need to make sure that that application double close when they're starting to run on multiple clouds, multiple geographies, they have the same abstraction layer so that they can actually apply things fast. Develop fast. They don't have to worry about the infrastructure frequently. And that's basically why they started using Open Shift. And don't know why they're big supporters of Open Shift. And then I think it's the right mission for their use. So I think it really depends on, you know, what the customer is looking for, but irrespective of what they're looking for, I think Open Shift nicely fits in because what it does, is it provides you that commonality across all infrastructure footprints. It gives you all the productivity gains and it allows you to connect to any service that you want anywhere because we are agnostic to that and as well as we bring a whole lot of services from Red Hat marketplace so you can actually leverage your status. >> Well, Sathish Balakrishnan, thank you so much for the updates. Great to hear about the progress you've got with your customers. And thank you for joining us on the Google cloud Next On Air Event. >> Thank you Stu. It's been great talking to you and look forward to seeing you in person one day. >> Alright. I'm Stu Miniman. And thank you as always for watching the Cube. (upbeat music) (upbeat music)

>> Announcer: From around the globe, it's theCUBE with coverage of KubeCon + CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation and Ecosystem partners. >> Welcome back I'm Stu Miniman, this is theCUBE's coverage of KubeCon + CloudNativeCon Europe 2020, the virtual event. Of course, when we talk about Cloud Native we talk about Kubernetes there's a lot that's happening to modernize the infrastructure but a very important thing that we're going to talk about today is also what's happening up the stack, what sits on top of it and some of the new use cases and applications that are enabled by all of this modern environment and for that we're going to talk about artificial intelligence and machine learning or AI and ML as we tend to talk in the industry, so happy to welcome to the program. We have two first time guests joining us from Red Hat. First of all, we have Abhinav Joshi and Tushar Katarki they are both senior managers, part of the OpenShift group. Abhinav is in the product marketing and Tushar is in product management. Abhinav and Tushar thank you so much for joining us. >> Thanks a lot, Stu, we're glad to be here. >> Thanks Stu and glad to be here at KubeCon. >> All right, so Abhinav I mentioned in the intro here, modernization of the infrastructure is awesome but really it's an enabler. We know... I'm an infrastructure person the whole reason we have infrastructure is to be able to drive those applications, interact with my data and the like and of course, AI and ML are exciting a lot going on there but can also be challenging. So, Abhinav if I could start with you bring us inside your customers that you're talking to, what are the challenges, the opportunities? What are they seeing in this space? Maybe what's been holding them back from really unlocking the value that is expected? >> Yup, that's a very good question to kick off the conversation. So what we are seeing as an organization they typically face a lot of challenges when they're trying to build an AI/ML environment, right? And the first one is like a talent shortage. There is a limited amount of the AI, ML expertise in the market and especially the data scientists that are responsible for building out the machine learning and the deep learning models. So yeah, it's hard to find them and to be able to retain them and also other talents like a data engineer or app DevOps folks as well and the lack of talent can actually stall the project. And the second key challenge that we see is the lack of the readily usable data. So the businesses collect a lot of data but they must find the right data and make it ready for the data scientists to be able to build out, to be able to test and train the machine learning models. If you don't have the right kind of data to the predictions that your model is going to do in the real world is only going to be so good. So that becomes a challenge as well, to be able to find and be able to wrangle the right kind of data. And the third key challenge that we see is the lack of the rapid availability of the compute infrastructure, the data and machine learning, and the app dev tools for the various personas like a data scientist or data engineer, the software developers and so on that can also slow down the project, right? Because if all your teams are waiting on the infrastructure and the tooling of their choice to be provisioned on a recurring basis and they don't get it in a timely manner, it can stall the projects. And then the next one is the lack of collaboration. So you have all these kinds of teams that are involved in the AI project, and they have to collaborate with each other because the work one of the team does has a dependency on a different team like say for example, the data scientists are responsible for building the machine learning models and then what they have to do is they have to work with the app dev teams to make sure the models get integrated as part of the app dev processes and ultimately rolled out into the production. So if all these teams are operating in say silos and there is lack of collaboration between the teams, so this can stall the projects as well. And finally, what we see is the data scientists they typically start the machine learning modeling on their individual PCs or laptops and they don't focus on the operational aspects of the solution. So what this means is when the IT teams have to roll all this out into a production kind of deployment, so they get challenged to take all the work that has been done by the individuals and then be able to make sense out of it, be able to make sure that it can be seamlessly brought up in a production environment in a consistent way, be it on-premises, be it in the cloud or be it say at the edge. So these are some of the key challenges that we see that the organizations are facing, as they say try to take the AI projects from pilot to production. >> Well, some of those things seem like repetition of what we've had in the past. Obviously silos have been the bane of IT moving forward and of course, for many years we've been talking about that gap between developers and what's happening in the operation side. So Tushar, help us connect the dots, containers, Kubernetes, the whole DevOps movement. How is this setting us up to actually be successful for solutions like AI and ML? >> Sure Stu I mean, in fact you said it right like in the world of software, in the world of microservices, in the world of app modernization, in the world of DevOps in the past 10, 15 years, but we have seen this evolution revolution happen with containers and Kubernetes driving more DevOps behavior, driving more agile behavior so this in fact is what we are trying to say here can ease up the cable to EIML also. So the various containers, Kubernetes, DevOps and OpenShift for software development is directly applicable for AI projects to make them move agile, to get them into production, to make them more valuable to organization so that they can realize the full potential of AI. We already touched upon a few personas so it's useful to think about who the users are, who the personas are. Abhinav I talked about data scientists these are the people who obviously do the machine learning itself, do the modeling. Then there are data engineers who do the plumbing who provide the essential data. Data is so essential to machine learning and deep learning and so there are data engineers that are app developers who in some ways will then use the output of what the data scientists have produced in terms of models and then incorporate them into services and of course, none of these things are purely cast in stone there's a lot of overlap you could find that data scientists are app developers as well, you'll see some of app developers being data scientist later data engineer. So it's a continuum rather than strict boundaries, but regardless what all of these personas groups of people need or experts need is self service to that preferred tools and compute and storage resources to be productive and then let's not forget the IT, engineering and operations teams that need to make all this happen in an easy, reliable, available manner and something that is really safe and secure. So containers help you, they help you quickly and easily deploy a broad set of machine learning tools, data tools across the cloud, the hybrid cloud from data center to public cloud to the edge in a very consistent way. Teams can therefore alternatively modify, change a shared container images, machine learning models with (indistinct) and track changes. And this could be applicable to both containers as well as to the data by the way and be transparent and transparency helps in collaboration but also it could help with the regulatory reasons later on in the process. And then with containers because of the inherent processes solution, resource control and protection from threat they can also be very secure. Now, Kubernetes takes it to the next level first of all, it forms a cluster of all your compute and data resources, and it helps you to run your containerized tools and whatever you develop on them in a consistent way with access to these shared compute and centralized compute and storage and networking resources from the data center, the edge or the public cloud. They provide things like resource management, workload scheduling, multi-tendency controls so that you can be a proper neighbors if you will, and quota enforcement right? Now that's Kubernetes now if you want to up level it further if you want to enhance what Kubernetes offers then you go into how do you write applications? How do you actually make those models into services? And that's where... and how do you lifecycle them? And that's sort of the power of Helm and for the more Kubernetes operators really comes into the picture and while Helm helps in installing some of this for a complete life cycle experience. A kubernetes operator is the way to go and they simplify the acceleration and deployment and life cycle management from end-to-end of your entire AI, ML tool chain. So all in all organizations therefore you'll see that they need to dial up and define models rapidly just like applications that's how they get ready out of it quickly. There is a lack of collaboration across teams as Abhinav pointed out earlier, as you noticed that has happened still in the world of software also. So we're talking about how do you bring those best practices here to AI, ML. DevOps approaches for machine learning operations or many analysts and others have started calling as MLOps. So how do you kind of bring DevOps to machine learning, and fosters better collaboration between teams, application developers and IT operations and create this feedback loop so that the time to production and the ability to take more machine learning into production and ML-powered applications into production increase is significant. So that's kind of the, where I wanted shine the light on what you were referring to earlier, Stu. >> All right, Abhinav of course one of the good things about OpenShift is you have quite a lot of customers that have deployed the solution over the years, bring us inside some of your customers what are they doing for AI, ML and help us understand really what differentiates OpenShift in the marketplace for this solution set. >> Yeah, absolutely that's a very good question as well and we're seeing a lot of traction in terms of all kinds of industries, right? Be it the financial services like healthcare, automotive, insurance, oil and gas, manufacturing and so on. For a wide variety of use cases and what we are seeing is at the end of the day like all these deployments are focused on helping improve the customer experience, be able to automate the business processes and then be able to help them increase the revenue, serve their customers better, and also be able to save costs. If you go to openshift.com/ai-ml it's got like a lot of customer stories in there but today I will not touch on three of the customers we have in terms of the different industries. The first one is like Royal Bank of Canada. So they are a top global financial institution based out of Canada and they have more than 17 million clients globally. So they recently announced that they build out an AI-powered private cloud platform that was based on OpenShift as well as the NVIDIA DGX AI compute system and this whole solution is actually helping them to transform the customer banking experience by being able to deliver an AI-powered intelligent apps and also at the same time being able to improve the operational efficiency of their organization. And now with this kind of a solution, what they're able to do is they're able to run thousands of simulations and be able to analyze millions of data points in a fraction of time as compared to the solution that they had before. Yeah, so like a lot of great work going on there but now the next one is the ETCA healthcare. So like ETCA is one of the leading healthcare providers in the country and they're based out of the Nashville, Tennessee. And they have more than 184 hospitals as well as more than 2,000 sites of care in the U.S. as well as in the UK. So what they did was they developed a very innovative machine learning power data platform on top of our OpenShift to help save lives. The first use case was to help with the early detection of sepsis like it's a life-threatening condition and then more recently they've been able to use OpenShift in the same kind of stack to be able to roll out the new applications that are powered by machine learning and deep learning let say to help them fight COVID-19. And recently they did a webinar as well that had all the details on the challenges they had like how did they go about it? Like the people, process and technology and then what the outcomes are. And we are proud to be a partner in the solution to help with such a noble cause. And the third example I want to share here is the BMW group and our partner DXC Technology what they've done is they've actually developed a very high performing data-driven data platform, a development platform based on OpenShift to be able to analyze the massive amount of data from the test fleet, the data and the speed of the say to help speed up the autonomous driving initiatives. And what they've also done is they've redesigned the connected drive capability that they have on top of OpenShift that's actually helping them provide various use cases to help improve the customer experience. With the customers and all of the customers are able to leverage a lot of different value-add services directly from within the car, their own cars. And then like last year at the Red Hat Summit they had a keynote as well and then this year at Summit, they were one of the Innovation Award winners. And we have a lot more stories but these are the three that I thought are actually compelling that I should talk about here on theCUBE. >> Yeah Abhinav just a quick follow up for you. One of the things of course we're looking at in 2020 is how has the COVID-19 pandemic, people working from home how has that impacted projects? I have to think that AI and ML are one of those projects that take a little bit longer to deploy, is it something that you see are they accelerating it? Are they putting on pause or are new project kicking off? Anything you can share from customers you're hearing right now as to the impact that they're seeing this year? >> Yeah what we are seeing is that the customers are now even more keen to be able to roll out the digital (indistinct) but we see a lot of customers are now on the accelerated timeline to be able to say complete the AI, ML project. So yeah, it's picking up a lot of momentum and we talk to a lot of analyst as well and they are reporting the same thing as well. But there is the interest that is actually like ramping up on the AI, ML projects like across their customer base. So yeah it's the right time to be looking at the innovation services that it can help improve the customer experience in the new virtual world that we live in now about COVID-19. >> All right, Tushar you mentioned that there's a few projects involved and of course we know at this conference there's a very large ecosystem. Red Hat is a strong contributor to many, many open source projects. Give us a little bit of a view as to in the AI, ML space who's involved, which pieces are important and how Red Hat looks at this entire ecosystem? >> Thank you, Stu so as you know technology partnerships and the power of open is really what is driving the technology world these days in any ways and particularly in the AI ecosystem. And that is mainly because one of the machine learning is in a bootstrap in the past 10 years or so and a lot of that emerging technology to take advantage of the emerging data as well as compute power has been built on the kind of the Linux ecosystem with openness and languages like popular languages like Python, et cetera. And so what you... and of course tons of technology based in Java but the point really here is that the ecosystem plays a big role and open plays a big role and that's kind of Red Hat's best cup of tea, if you will. And that really has plays a leadership role in the open ecosystem so if we take your question and kind of put it into two parts, what is the... what we are doing in the community and then what we are doing in terms of partnerships themselves, commercial partnerships, technology partnerships we'll take it one step at a time. In terms of the community itself, if you step back to the three years, we worked with other vendors and users, including Google and NVIDIA and H2O and other Seldon, et cetera, and both startups and big companies to develop this Kubeflow ecosystem. The Kubeflow is upstream community that is focused on developing MLOps as we talked about earlier end-to-end machine learning on top of Kubernetes. So Kubeflow right now is in 1.0 it happened a few months ago now it's actually at 1.1 you'll see that coupon here and then so that's the Kubeflow community in addition to that we are augmenting that with the Open Data Hub community which is something that extends the capabilities of the Kubeflow community to also add some of the data pipelining stuff and some of the data stuff that I talked about and forms a reference architecture on how to run some of this on top of OpenShift. So the Open Data Hub community also has a great way of including partners from a technology partnership perspective and then tie that with something that I mentioned earlier, which is the idea of Kubernetes operators. Now, if you take a step back as I mentioned earlier, Kubernetes operators help manage the life cycle of the entire application or containerized application including not only the configuration on day one but also day two activities like update and backups, restore et cetera whatever the application needs. Afford proper functioning that a "operator" needs for it to make sure so anyways, the Kubernetes operators ecosystem is also flourishing and we haven't faced that with the OperatorHub.io which is a community marketplace if you will, I don't call it marketplace a community hub because it's just comprised of community operators. So the Open Data Hub actually can take community operators and can show you how to run that on top of OpenShift and manage the life cycle. Now that's the reference architecture. Now, the other aspect of it really is as I mentioned earlier is the commercial aspect of it. It is from a customer point of view, how do I get certified, supported software? And to that extent, what we have is at the top of the... from a user experience point of view, we have certified operators and certified applications from the AI, ML, ISV community in the Red Hat marketplace. And from the Red Hat marketplace is where it becomes easy for end users to easily deploy these ISVs and manage the complete life cycle as I said. Some of the examples of these kinds of ISVs include startups like H2O although H2O is kind of well known in certain sectors PerceptiLabs, Cnvrg, Seldon, Starburst et cetera and then on the other side, we do have other big giants also in this which includes partnerships with NVIDIA, Cloudera et cetera that we have announced, including our also SaaS I got to mention. So anyways these provide... create that rich ecosystem for data scientists to take advantage of. A TEDx Summit back in April, we along with Cloudera, SaaS Anaconda showcased a live demo that shows all these things to working together on top of OpenShift with this operator kind of idea that I talked about. So I welcome people to go and take a look the openshift.com/ai-ml that Abhinav already referenced should have a link to that it take a simple Google search might download if you need some of that, but anyways and the other part of it is really our work with the hardware OEMs right? And so obviously NVIDIA GPUs is obviously hardware, and that accelerations is really important in this world but we are also working with other OEM partners like HP and Dell to produce this accelerated AI platform that turnkey solutions to run your data-- to create this open AI platform for "private cloud" or the data center. The other thing obviously is IBM, IBM Cloud Pak for Data is based on OpenShift that has been around for some time and is seeing very good traction, if you think about a very turnkey solution, IBM Cloud Pak is definitely kind of well ahead in that and then finally Red Hat is about driving innovation in the open-source community. So, as I said earlier, we are doing the Open Data Hub which that reference architecture that showcases a combination of upstream open source projects and all these ISV ecosystems coming together. So I welcome you to take a look at that at opendatahub.io So I think that would be kind of the some total of how we are not only doing open and community building but also doing certifications and providing to our customers that assurance that they can run these tools in production with the help of a rich certified ecosystem. >> And customer is always key to us so that's the other thing that the goal here is to provide our customers with a choice, right? They can go with open source or they can go with a commercial solution as well. So you want to make sure that they get the best in cloud experience on top of our OpenShift and our broader portfolio as well. >> All right great, great note to end on, Abhinav thank you so much and Tushar great to see the maturation in this space, such an important use case. Really appreciate you sharing this with theCUBE and Kubecon community. >> Thank you, Stu. >> Thank you, Stu. >> Okay thank you and thanks a lot and have a great rest of the show. Thanks everyone, stay safe. >> Thanks you and stay with us for a lot more coverage from KubeCon + CloudNativeCon Europe 2020, the virtual edition I'm Stu Miniman and thank you as always for watching theCUBE. (soft upbeat music plays)

>>From the cube studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a cute conversation. Hi, welcome back. I'm Stu middleman. And this is a cube conversation digging in with, talking about what they're doing to help people. Yeah. Really bringing some of the networking ideals to cloud native environment, both know in the cloud, in the data centers program, Krishna penny. He is the vice president of software. Thanks so much for joining us. Thank you so much for talking to me. Alright, so, so Krishna the pin Sandow team, uh, you know, very well known in the industry three, uh, you innovation. Yeah. Especially in the networking world. Give us a little bit about your background specifically, uh, how long you've been part of this team and, uh, you know, but, uh, you know, you and the team, you know? Yeah. >>And Sando. Yup. Um, so, uh, I'm VP of software in Sandow, um, before Penn Sarno, before founding concern, though, I worked in a few startups in CME networks, uh, newer systems and Greenfield networks, all those three startups have been acquired by Cisco. Um, um, my recent role before this, uh, uh, this, this company was a, it was VP of engineering and Cisco, uh, I was responsible for a product called ACA, which is course flagship SDN tonic. Mmm. So I mean, when, why did we find a phone, uh, Ben Sandoz? So when we were looking at the industry, uh, the last, uh, a few years, right? The few trends that are becoming clear. So obviously we have a lot of enterprise background. We were watching, you know, ECA being deployed in the enterprise data centers. One sore point for customers from operational point of view was installing service devices, network appliances, or storage appliances. >>So not only the operational complexity that this device is bringing, it's also, they don't give you the performance and bandwidth, uh, and PPS that you expect, but traffic, especially from East West. So that was one that was one major issue. And also, if you look at where the intelligence is going, has been, this has been the trend it's been going to the edge. The reason for that is the motors or switches or the devices in the middle. They cannot handle the scale. Yeah. I mean, the bandwidths are growing. The scale is growing. The stateful stuff is going in the network and the switches and the appliances not able to handle it. So you need something at the edge close to the application that can handle, uh, uh, this kind of, uh, services and bandwidth. And the third thing is obviously, you know, x86, okay. Even a few years back, you know, every two years, you know, you're getting more transistors. >>I mean, obviously the most lined it. And, uh, we know we know how that, that part is going. So the it's cycles are more valuable and we don't want to use them for this network services Mmm. Including SDN or firewalls or load balancer. So NBME, mutualization so looking at all these trends in the industry, you know, we thought there is a good, uh, good opportunity to do a domain specific processor for IO and build products around it. I mean, that's how we started Ben signed off. Yeah. So, so Krishna, it's always fascinating to watch. If you look at startups, they are often yeah. Okay. The time that they're in and the technologies that are available, you know, sometimes their ideas that, you know, cakes a few times and, you know, maturation of the technology and other times, you know, I'll hear teams and they're like, Oh, well we did this. >>And then, Oh, wow. There was this new innovation came out that I wish I had add that when I did this last time. So we do, a generation. Oh, wow. Talking about, you know, distributed architectures or, you know, well, over a decade spent a long time now, uh, in many ways I feel edge computing is just, you know, the latest discussion of this, but when it comes to, and you know, you've got software, uh, under, under your purview, um, what are some of the things that are available for that might not have been, you know, in your toolkit, you know, five years ago. Yeah. So the growth of open source software has been very helpful for us because we baked scale-out microservices. This controller, like the last time I don't, when we were building that, you know, we had to build our own consensus algorithm. >>We had to build our own dishwasher database for metrics and humans and logs. So right now, uh, we, I mean, we have, because of open source thing, we leverage CD elastic influx in all this open source technologies that you hear, uh, uh, since we want to leverage the Kubernetes ecosystem. No, that helped us a lot at the same time, if you think about it. Right. But even the software, which is not open source, close source thing, I'm maturing. Um, I mean, if you talk about SDN, you know, seven APS bank, it was like, you know, the end versions of doing off SDN, but now the industry standard is an ADPN, um, which is one of the core pieces of what we do we do as Dean solution with DVA. Um, so, you know, it's more of, you know, the industry's coming to a place where, you know, these are the standards and this is open source software that you could leverage and quickly innovate compared to building all of this from scratch, which will be a big effort for us stocked up, uh, to succeed and build it in time for your customer success. >>Yeah. And Krishna, I, you know, you talk about open forum, not only in the software, the hardware standards. Okay. Think about things, the open compute or the proliferation of, you know, GPS and, uh, everything along that, how was that impact? I did. So, I mean, it's a good thing you're talking about. For example, we were, we are looking in the future and OCP card, but I do know it's a good thing that SEP card goes into a HP server. It goes into a Dell software. Um, so pretty much, you know, we, we want to, I mean, see our goal is to enable this platform, uh, that what we built in, you know, all the use cases that customer could think of. Right. So in that way, hardware, standardization is a good thing for the industry. Um, and then same thing, if you go in how we program the AC, you know, we at about standards of this people, programming, it's an industry consortium led by a few people. >>Um, we want to make sure that, you know, we follow the standards for the customer who's coming in, uh, who wants to program it., it's good to have a standards based thing rather than doing something completely proprietary at the same time you're enabling innovations. And then those innovations here to push it back to the open source. That's what we trying to do with before. Yeah. Excellent. I've had some, some real good conversations about before. Um, and, and the way, uh, and Tondo is, is leveraging that, that may be a little bit differently. You know, you talk about standards and open source, oftentimes it's like, well, is there a differentiator there, there are certain parts of the ecosystem that you say, well, kind of been commodified. Mmm. Obviously you're taking a lot of different technologies, putting them together, uh, help, help share the uniqueness. Okay. And Tondo what differentiates, what you're doing from what was available in the market or that I couldn't just cobbled together, uh, you know, a bunch of open source hardware and software together. >>Yeah. I mean, if you look at a technologist, I think the networking that both of us are very familiar with that. If you want to build an SDN solution, or you can take a, well yes. Or you can use exhibit six and, you know, take some much in Silicon and cobble it together. But the problem is you will not get the performance and bandwidth that you're looking for. Okay. So let's say, you know, uh, if you want a high PPS solution or you want a high CPS solution, because the number of connections are going for your IOT use case or Fiji use case, right. If you, uh, to get that with an open source thing, without any assist, uh, from a domain specific processor, your performance will be low. So that is the, I mean, that's once an enterprise in the cloud use case state, as you know, you're trying to pack as many BMCs containers in one set of word, because, you know, you get charged. >>I mean, the customer, uh, the other customers make money based on that. Right? So you want to offload all of those things into a domain specific processor that what we've built, which we call the TSC, which will, um, which we'll, you know, do all the services at pretty much no cost to accept a six. I mean, it's to six, you'll be using zero cycles, a photo doing, you know, features like security groups or VPCs, or VPN, uh, or encryption or storage virtualization. Right. That's where that value comes in. I mean, if you count the TCO model using bunch of x86 codes or in a bunch of arm or AMD codes compared to what we do. Mmm. A TCO model works out great for our customers. I mean, that's why, you know, there's so much interest in a product. Excellent. I'm proud of you. Glad you brought up customers, Christina. >>One of the challenges I have seen over the years with networking is it tends to be, you know, a completely separate language that we speak there, you know, a lot of acronyms and protocols and, uh, you know, not necessarily passable to people outside of the silo of networking. I think back then, you know, SDN, uh, you know, people on the outside would be like, that stands for still does nothing, right? Like networking, uh, you know, mumbo jumbo there for people outside of networking. You know what I think about, you know, if I was going to the C suite of an enterprise customer, um, they don't necessarily care about those networking protocols. They care about the, you know, the business results and the product Liberty. How, how do you help explain what pen Sandow does to those that aren't, you know, steeped in the network, because the way I look at it, right? >>What is customer looking? But yeah, you're writing who doesn't need, what in cap you use customer is looking for is operational simplicity. And then he wants looking for security. They, it, you know, and if you look at it sometimes, you know, both like in orthogonal, if you make it very highly secure, but you make it like and does an operational procedure before you deploy a workload that doesn't work for the customer because in operational complexity increases tremendously. Right? So it, we are coming in, um, is that we want to simplify this for the customer. You know, this is a very simple way to deploy policies. There's a simple way to deploy your networking infrastructure. And in the way we do it is we don't care what your physical network is, uh, in some sense, right? So because we are close to the server, that's a very good advantage. >>We have, we have played the policies before, even the packet leaves the center, right? So in that way, he knows his fully secure environment and we, and you don't want to manage each one individually, we have this, okay, Rockwell PSM, which manages, you know, all this service from a central place. And it's easy to operationalize a fabric, whether you talk about upgrades or you talk about, you know, uh, deploying new services, it's all driven with rest API, and you can have a GUI, so you can do it a single place. And that's where, you know, a customer's value is rather than talking about, as you're talking about end caps or, you know, exactly the route to port. That is not the main thing that, I mean, they wake up every day, they wake up. Have you been thinking about it or do I have a security risk? >>And then how easy for me is to deploy new, uh, in a new services or bring up new data center. Right. Okay. Krishna, you're also spanning with your product, a few different worlds out. Yeah. You know, traditionally yeah. About, you know, an enterprise data center versus a hyperscale public cloud and ed sites, hi comes to mind very different skillset for management, you know, different types of okay. Appointments there. Mmm. You know, I understand right. You were going to, you know, play in all of those environments. So talk a little bit about that, please. How you do that and, you know, you know, where you sit in, in that overall discussion. Yes. So, I mean, a number one rule inside a company is we are driven by customers and obviously not customer success is our success. So, but given said that, right. What we try to do is that we try to build a platform that is kind of, you know, programmable obviously starting from, you know, before that we talked about earlier, but it's also from a software point of view, it's kind of plugable right. >>So when we build a software, for example, at cloud customers, and they use BSC, they use the same set of age KPI's or GSP CRS, TPS that DSC provides their controller. But when we ship the same, uh, platform, what enterprise customers, we built our own controller and we use the same DC APS. So the way we are trying to do is things is fully leverage yeah. In what we do for enterprise customers and cloud customers. Mmm. We don't try to reinvent the wheel. Uh, obviously at the same time, if you look at the highest level constructs from a network perspective, right. Uh, audience, for his perspective, what are you trying to do? You're trying to provide connectivity, but you're trying to avoid isolation and you're trying to provide security. Uh, so all these constructs we encapsulated in APA is a, which, you know, uh, in some, I, some, some mostly like cloud, like APS and those APIs are, are used, but cloud customers and enterprise customers, and the software is built in a way of it. >>Any layer is, can be removed on any layer. It can be hard, right? Because it's not interested. We don't want to be multiple different offers for different customers. Right. Then we will not scale. So the idea when we started the software architecture, is that how we make it pluggable and how will you make the program will that customer says, I don't want this piece of it. You can put them third party piece on it and still integrate, uh, at a, at a common layer with using. Yeah. Yeah. Well, you know, Krishna, you know, I have a little bit of appreciation where some of the hard work, what your team has been doing, you know, a couple of years in stealth, but, you know, really accelerating from, uh, you know, the announcement coming out of stealth, uh, at the end of 2019. Yeah. Just about half a year, your GA with a major OEM of HPE, definitely a lot of work that needs to be done. >>It brings us to, you know, what, what are you most proud about from the work that your team's doing? Uh, you know, we don't need to hear any, you know, major horror stories, but, you know, there always are some of them, you know, not holes or challenges that, uh, you know, often get hidden yeah. Behind the curtain. Okay. I mean, personally, I'm most proud of the team that we've made. Um, so, uh, you know, obviously, you know, uh, our executors have it good track record of disrupting the market multiple times, but I'm most proud of the team because the team is not just worried about that., uh, that, uh, even delegate is senior technologist and they're great leaders, but they're also worried about the customer problem, right? So it's always about, you know, getting the right mix, awfully not execution combined with technology is when you succeed, that is what I'm most proud of. >>You know, we have a team with, and Cletus running all these projects independently, um, and then releasing almost we have at least every week, if you look at all our customers, right. And then, you know, being a small company doing that is a, Hmm, it's pretty challenging in a way. But we did, we came up with methodologists where we fully believe in automation, everything is automated. And whenever we release software, we run through the full set of automation. So then we are confident that customer is getting good quality code. Uh, it's not like, you know, we cooked up something and that they should be ready and they need to upgrade to the software. That's I think that's the key part. If you want to succeed in this day and age, uh, developing the features at the velocity that you would want to develop and still support all these customers at the same time. >>Okay. Well, congratulations on that, Christian. All right. Final question. I have for you give us a little bit of guidance going forward, you know, often when we see a company out and we, you know, to try to say, Oh, well, this is what company does. You've got a very flexible architecture, lot of different types of solutions, what kind of markets or services might we be looking at a firm, uh, you know, download down the road a little ways. So I think we have a long journey. So we have a platform right now. We already, uh, I mean, we have a very baby, we are shipping. Mmm Mmm. The platforms are really shipping in a storage provider. Uh, we are integrating with the premier clouds, public clouds and, you know, enterprise market, you know, we already deployed a distributed firewall. Some of the customers divert is weird firewall. >>So, you know, uh, so if you take this platform, it can be extendable to add in all the services that you see in data centers on clubs, right. But primarily we are driven from a customer perspective and customer priority point of view. Mmm. So BMW will go is even try to add more ed services. We'll try to add more storage features. Mmm. And then we, we are also this initial interest in service provider market. What we can do for Fiji and IOT, uh, because we have the flexible platform. We have the, see, you know, how to apply this platform, this new application, that's where it probably will go into church. All right. Well, Krishna not a penny vice president of software with Ben Tondo. Thank you so much for joining us. Thank you, sir. It was great talking to you. All right. Be sure to check out the cube.net. You can find lots of interviews from Penn Sundo I'm Stu Miniman and thank you. We're watching the cute.