>> And I'm here at Dell's Presence at MWC with vice president of marketing for telecom and Edge Computing, Aaron Chaisson. Aaron, how's it going? >> Doing great. How's it going today, Dave? >> It's going pretty well. Pretty excited about what you've got going here and I'm looking forward to getting the tour. You ready to take a closer look? >> Ready to do it. Let's go take a look! For us in the telecom ecosystem, it's really all about how we bring together the different players that are innovating across the industry to drive value for our CSP customers. So, it starts really, for us, at the ecosystem layer, bringing partners, bringing telecommunication providers, bringing (stutters) a bunch of different technologies together to innovate together to drive new value. So Paul, take us a little bit through what we're doing to- to develop and bring in these partnerships and develop our ecosystem. >> Uh, sure. Thank you Aaron. Uh, you know, one of the things that we've been focusing on, you know, Dell is really working with many players in the open telecom ecosystem. Network equipment providers, independent software vendors, and the communication service providers. And, you know, through our lines of business or open telecom ecosystem labs, what we want to do is bring 'em together into a community with the goal of really being able to accelerate open innovation and, uh, open solutions into the market. And that's what this community is really about, is being able to, you know, have those communications, develop those collaborations whether it's through, you know, sharing information online, having webinars dedicated to sharing Dell information, whether it's our next generation hardware portfolio we announced here at the show, our use case directory, our- how we're dealing with new service opportunities, but as well as the community to share, too, which I think is an exciting way for us to be able to, you know- what is the knowledge thing? As well as activities at other events that we have coming up. So really the key thing I think about, the- the open telecom ecosystem community, it's collaboration and accelerating the open industry forward. >> So- So Aaron, if I'm hearing this correctly you're saying that you can't just say, "Hey, we're open", and throw a bunch of parts in a box and have it work? >> No, we've got to work together to integrate these pieces to be able to deliver value, and, you know, we opened up a- (stutters) in our open ecosystem labs, we started a- a self-certification process a couple of months back. We've already had 13 partners go through that, we've got 16 more in the pipeline. Everything you see in this entire booth has been innovated and worked with partnerships from Intel to Microsoft to, uh, to (stutters) Wind River and Red Hat and others. You go all the way around the booth, everything here has partnerships at its core. And why don't we go to the next section here where we're going to be showing how we're pulling that all together in our open ecosystems labs to drive that innovation? >> So Aaron, you talked about the kinds of validation and testing that goes on, so that you can prove out an open stack to deliver the same kinds of reliability and performance and availability that we expect from a wireless network. But in the opens- in the open world, uh, what are we looking at here? >> Yeah absolutely. So one of the- one of the challenges to a very big, broad open ecosystem is the complexity of integrating, deploying, and managing these, especially at telecom scale. You're not talking about thousands of servers in one site, you're talking about one server in thousands of sites. So how do you deploy that predictable stack and then also manage that at scale? I'm going to show you two places where we're talkin' about that. So, this is actually representing an area that we've been innovating in recently around creating an integrated infrastructure and virtualization stack for the telecom industry. We've been doing this for years in IT with VxBlocks and VxRails and others. Here what you see is we got, uh, Dell hardware infrastructure, we've got, uh, an open platform for virtualization providers, in this case we've created an infrastructure block for Red Hat to be able to supply an infrastructure for core operations and Packet Cores for telecoms. On the other side of this, you can actually see what we're doing with Wind River to drive innovation around RAN and being able to simplify RAN- vRAN and O-RAN deployments. >> What does that virtualization look like? Are we talking about, uh, traditional virtual machines with OSs, or is this containerized cloud native? What does it look like? >> Yeah, it's actually both, so it can support, uh, virtual, uh-uh, software as well as containerized software, so we leverage the (indistinct) distributions for these to be able to deploy, you know, cloud native applications, be able to modernize how they're deploying these applications across the telecom network. So in this case with Red Hat, uh, (stutters) leveraging OpenShift in order to support containerized apps in your Packet Core environments. >> So what are- what are some of the kinds of things that you can do once you have infrastructure like this deployed? >> Yeah, I mean by- by partnering broadly across the ecosystem with VMware, with Red Hat, uh, with- with Wind River and with others, it gives them the ability to be able to deploy the right virtualization software in their network for the types of applications they're deploying. They might want to use Red Hat in their core, they may want to use Wind River in their RAM, they may want to use, uh, Microsoft or VMware for their- for their Edge workloads, and we allow them to be able to deploy all those, but centrally manage those with a common user interface and a common set of APIs. >> Okay, well I'm dying to understand the link between this and the Lego city that the viewers can't see, yet, but it's behind me. Let's take a look. >> So let's take a look at the Lego city that shows how we not deploy just one of these, but dozens or hundreds of these at scale across a cityscape. >> So Aaron, I know we're not in Copenhagen. What's all the Lego about? >> Yeah, so the Lego city here is to show- and, uh, really there's multiple points of Presence across an entire Metro area that we want to be able to manage if we're a telecom provider. We just talked about one infrastructure block. What if I wanted to deploy dozens of these across the city to be able to manage my network, to be able to manage, uh, uh- to be able to deploy private mobility potentially out into a customer enterprise environment, and be able to manage all of these, uh, very simply and easily from a common interface? >> So it's interesting. Now I think I understand why you are VP of marketing for both telecom and Edge. Just heard- just heard a lot about Edge and I can imagine a lot of internet of things, things, hooked up at that Edge. >> Yeah, so why don't we actually go over to another area? We're actually going to show you how one small microbrewery (stutters) in one of our cities nearby, uh, (stutters) my hometown in Massachusetts is actually using this technology to go from more of an analyzed- analog world to digitizing their business to be able to brew better beer. >> So Aaron, you bring me to a brewery. What do we have- what do we have going on here? >> Yeah, so, actually (stutters) about- about a year ago or so, I- I was able to get my team to come together finally after COVID to be able to meet each other and have a nice team event. One of those nights, we went out to dinner at a- at a brewery called "Exhibit 'A'" in Massachusetts, and they actually gave us a tour of their facilities and showed us how they actually go through the process of brewing beer. What we saw as we were going through it, interestingly, was that everything was analog. They literally had people with pen and paper walking around checking time and temperature and the process of brewing the beer, and they weren't asking for help, but we actually saw an opportunity where what we're doing to help businesses digitize what they're doing in their manufacturing floor can actually help them optimize how they build whatever product they're building, in this case it was beer. >> Hey Warren, good to meet you! What do we have goin' on? >> Yeah, it's all right. So yeah, basically what we did is we took some of their assets in the, uh, brewery that were completely manually monitored. People were literally walking around the floor with clipboards, writing down values. And we censorized the asset, in this case fermentation tanks and we measured the, uh, pressure and the temperature, which in fermentation are very key to monitor those, because if they get out of range the entire batch of beer can go bad or you don't get the consistency from batch to batch if you don't tightly monitor those. So we censorized the fermentation tank, brought that into an industrial I/O network, and then brought that into a Dell gateway which is connected 5G up to the cloud, which then that data comes to a tablet or a phone, which they, rather than being out on the floor and monitor it, can look at this data remotely at any time. >> So I'm not sure the exact date, the first time we have evidence of beer being brewed by humanity... >> Yep. >> But I know it's thousands of years ago. So it's taken that long to get to the point where someone had to come along, namely Dell, to actually digitally transform the beer business. Is this sort of proof that if you can digitally transform this, you can digitally transform anything? >> Absolutely. You name it, anything that's being manufactured, sold, uh, uh, taken care of, (stutters) any business out there that's looking to be able to be modernize and deliver better service to their customers can benefit from technologies like this. >> So we've taken a look at the ecosystem, the way that you validate architectures, we've seen an example of that kind of open architecture. Now we've seen a real world use case. Do you want to take a look a little deeper under the covers and see what's powering all of this? >> We just this week announced a new line of servers that power Edge and RAN use cases, and I want to introduce Mike to kind of take us through what we've been working on and really what the power of what this providing. >> Hey Mike, welcome to theCube. >> Oh, glad- glad to be here. So, what I'd really like to talk about are the three new XR series servers that we just announced last week and we're showing here at Mobile World Congress. They are all short depth, ruggedized, uh, very environmentally tolerant, and able to withstand, you know, high temperatures, high humidities, and really be deployed to places where traditional data center servers just can't handle, you know, due to one fact or another, whether it's depth or the temperature. And so, the first one I'd like to show you is the XR7620. This is, uh, 450 millimeters deep, it's designed for, uh, high levels of acceleration so it can support up to 2-300 watt, uh, GPUs. But what I really want to show you over here, especially for Mobile World Congress, is our new XR8000. The XR8000 is based on Intel's latest Sapphire Rapids technology, and this is- happens to be one of the first, uh, EE boost processors that is out, and basically what it is (stutters) an embedded accelerator that makes, uh, the- the processing of vRAN loads very, uh, very efficient. And so they're actually projecting a, uh, 3x improvement, uh, of processing per watt over the previous generation of processors. This particular unit is also sledded. It's very much like, uh, today's traditional baseband unit, so it's something that is designed for low TCO and easy maintenance in the field. This is the frew. When anything fails, you'll pull one out, you pop a new one in, it comes back into service, and the- the, uh, you know, your radio is- is, uh, minimally disrupted. >> Yeah, would you describe this as quantitative and qualitative in terms of the kinds of performance gains that these underlying units are delivering to us? I mean, this really kind of changes the game, doesn't it? It's not just about more, is it about different also in terms of what we can do? >> Well we are (stutters) to his point, we are able to bring in new accelerator technologies. Not only are we doing it with the Intel, uh, uh, uh, of the vRAN boost technologies, but also (stutters) we can bring it, too, but there's another booth here where we're actually working with our own accelerator cards and other accelerator cards from our partners across the industry to be able to deliver the price and performance capabilities required by a vRAN or an O-RAN deployment in the network. So it's not- it's not just the chip technology, it's the integration and the innovation we're doing with others, as well as, of course, the unique power cooling capabilities that Dell provides in our servers that really makes these the most efficient way of being able to power a network. >> Any final thoughts recapping the whole picture here? >> Yeah, I mean I would just say if anybody's, uh, i- is still here in Mobile World Congress, wants to come and learn what we're doing, I only showed you a small section of the demos we've got here. We've got 13 demos across on 8th floor here. Uh, for those of you who want to talk to us (stutters) and have meetings with us, we've got 13 meeting rooms back there, over 500 costumer partner meetings this week, we've got some whisper suites for those of you who want to come and talk to us but we're innovating on going forward. So, you know, there's a lot that we're doing, we're really excited, there's a ton of passion at this event, and, uh, we're really excited about where the industry is going and our role in it. >> 'Preciate the tour, Aaron. Thanks Mike. >> Mike: Thank you! >> Well, for theCube... Again, Dave Nicholson here. Thanks for joining us on this tour of Dell's Presence here at MWC 2023.

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey everyone and welcome back to Barcelona, Spain, it's theCUBE. We are live at MWC 23. This is day two of our coverage, we're giving you four days of coverage, but you already know that because you were here yesterday. Lisa Martin with Dave Nicholson. Dave this show is massive. I was walking in this morning and almost getting claustrophobic with the 80,000 people that are joining us. There is, seems to be at MWC 23 more interest in enterprise-class technology than we've ever seen before. What are some of the things that you've observed with that regard? >> Well I've observed a lot of people racing to the highest level messaging about how wonderful it is to have the kiss of a breeze on your cheek, and to feel the flowing wheat. (laughing) I want to hear about the actual things that make this stuff possible. >> Right. >> So I think we have a couple of guests here who can help us start to go down that path of actually understanding the real cool stuff that's behind the scenes. >> And absolutely we got some cool stuff. We've got two guests from Dell. Dave Lincoln is here, the VP of Networking and Emerging the Server Solutions, and Deania Davidson, Director Edge Server Product Planning and Management at Dell. So great to have you. >> Thank you. >> Two Daves, and a Davidson. >> (indistinct) >> Just me who stands alone here. (laughing) So guys talk about, Dave, we'll start with you the newest generation of PowerEdge servers. What's new? Why is it so exciting? What challenges for telecom operators is it solving? >> Yeah, well so this is actually Dell's largest server launch ever. It's the most expansive, which is notable because of, we have a pretty significant portfolio. We're very proud of our core mainstream portfolio. But really since the Supercompute in Dallas in November, that we started a rolling thunder of launches. MWC being part of that leading up to DTW here in May, where we're actually going to be announcing big investments in those parts of the market that are the growth segments of server. Specifically AIML, where we in, to address that. We're investing heavy in our XE series which we, as I said, we announced at Supercompute in November. And then we have to address the CSP segment, a big investment around the HS series which we just announced, and then lastly, the edge telecom segment which we're, we had the biggest investment, biggest announce in portfolio launch with XR series. >> Deania, lets dig into that. >> Yeah. >> Where we see the growth coming from you mentioned telecom CSPs with the edge. What are some of the growth opportunities there that organizations need Dell's help with to manage, so that they can deliver what they're demanding and user is wanting? >> The biggest areas being obviously, in addition the telecom has been the biggest one, but the other areas too we're seeing is in retail and manufacturing as well. And, so internally, I mean we're going to be focused on hardware, but we also have a solutions team who are working with us to build the solutions focused on retail, and edge and telecom as well on top of the servers that we'll talk about shortly. >> What are some of the biggest challenges that retailers and manufacturers are facing? And during the pandemic retailers, those that were successful pivoted very quickly to curbside delivery. >> Deania: Yeah. >> Those that didn't survive weren't able to do that digitally. >> Deania: Yeah. >> But we're seeing such demand. >> Yeah. >> At the retail edge. On the consumer side we want to get whatever we want right now. >> Yes. >> It has to be delivered, it has to be personalized. Talk a little bit more about some of the challenges there, within those two verticals and how Dell is helping to address those with the new server technologies. >> For retail, I think there's couple of things, the one is like in the fast food area. So obviously through COVID a lot of people got familiar and comfortable with driving through. >> Lisa: Yeah. >> And so there's probably a certain fast food restaurant everyone's pretty familiar with, they're pretty efficient in that, and so there are other customers who are trying to replicate that, and so how do we help them do that all, from a technology perspective. From a retail, it's one of the pickup and the online experience, but when you go into a store, I don't know about you but I go to Target, and I'm looking for something and I have kids who are kind of distracting you. Its like where is this one thing, and so I pull up the Target App for example, and it tells me where its at, right. And then obviously, stores want to make more money, so like hey, since you picked this thing, there are these things around you. So things like that is what we're having conversations with customers about. >> It's so interesting because the demand is there. >> Yeah, it is. >> And its not going to go anywhere. >> No. >> And it's certainly not going to be dialed down. We're not going to want less stuff, less often. >> Yeah (giggles) >> And as typical consumers, we don't necessarily make the association between what we're seeing in the palm of our hand on a mobile device. >> Deania: Right. >> And the infrastructure that's actually supporting all of it. >> Deania: Right. >> People hear the term Cloud and they think cloud-phone mystery. >> Yeah, magic just happens. >> Yeah. >> Yeah. >> But in fact, in order to support the things that we want to be able to do. >> Yeah. >> On the move, you have to optimize the server hardware. >> Deania: Yes. >> In certain ways. What does that mean exactly? When you say that its optimized, what are the sorts of decisions that you make when you're building? I think of this in the terms of Lego bricks. >> Yes, yeah >> Put together. What are some of the decisions that you make? >> So there were few key things that we really had to think about in terms of what was different from the Data center, which obviously supports the cloud environment, but it was all about how do we get closer to the customer right? How do we get things really fast and how do we compute that information really quickly. So for us, it's things like size. All right, so our server is going to weigh one of them is the size of a shoe box and (giggles), we have a picture with Dave. >> Dave: It's true. >> Took off his shoe. >> Its actually, its actually as big as a shoe. (crowd chuckles) >> It is. >> It is. >> To be fair, its a pretty big shoe. >> True, true. >> It is, but its small in relative to the old big servers that you see. >> I see what you're doing, you find a guy with a size 12, (crowd giggles) >> Yeah. >> Its the size of your shoe. >> Yeah. >> Okay. >> Its literally the size of a shoe, and that's our smallest server and its the smallest one in the portfolio, its the XR 4000, and so we've actually crammed a lot of technology in there going with the Intel ZRT processors for example to get into that compute power. The XR 8000 which you'll be hearing a lot more about shortly with our next guest is one I think from a telco perspective is our flagship product, and its size was a big thing there too. Ruggedization so its like (indistinct) certification, so it can actually operate continuously in negative 5 to 55 C, which for customers, or they need that range of temperature operation, flexibility was a big thing too. In meaning that, there are some customers who wanted to have one system in different areas of deployment. So can I take this one system and configure it one way, take that same system, configure another way and have it here. So flexibility was really key for us as well, and so we'll actually be seeing that in the next segment coming. >> I think one of, some of the common things you're hearing from this is our focus on innovation, purpose build servers, so yes our times, you know economic situation like in itself is tough yeah. But far from receding we've doubled down on investment and you've seen that with the products that we are launching here, and we will be launching in the years to come. >> I imagine there's a pretty sizeable day impact to the total adjustable market for PowerEdge based on the launch what you're doing, its going to be a tam, a good size tam expansion. >> Yeah, absolutely. Depending on how you look at it, its roughly we add about $30 Billion of adjustable tam between the three purposeful series that we've launched, XE, HS and XR. >> Can you comment on, I know Dell and customers are like this. Talk about, I'd love to get both of your perspective, I'm sure you have a favorite customer stories. But talk about the involvement of the customer in the generation, and the evolution of PowerEdge. Where are they in that process? What kind of feedback do they deliver? >> Well, I mean, just to start, one thing that is essential Cortana of Dell period, is it all is about the customer. All of it, everything that we do is about the customer, and so there is a big focus at our level, from on high to get out there and talk with customers, and actually we have a pretty good story around XR8000 which is call it our flagship of the XR line that we've just announced, and because of this deep customer intimacy, there was a last minute kind of architectural design change. >> Hm-mm. >> Which actually would have been, come to find out it would have been sort of a fatal flaw for deployment. So we corrected that because of this tight intimacy with our customers. This was in two Thanksgiving ago about and, so anyways it's super cool and the fact that we were able to make a change so late in development cycle, that's a testament to a lot of the speed and, speed of innovation that we're driving, so anyway that was that's one, just case of one example. >> Hm-mm. >> Let talk about AI, we can't go to any trade show without talking about AI, the big thing right now is ChatGPT. >> Yeah. >> I was using it the other day, it's so interesting. But, the growing demand for AI, talk about how its driving the evolution of the server so that more AI use cases can become more (indistinct). >> In the edge space primarily, we actually have another product, so I guess what you'll notice in the XR line itself because there are so many different use cases and technologies that support the different use cases. We actually have a range form factor, so we have really small, I guess I would say 350 ml the size of a shoe box, you know, Dave's shoe box. (crowd chuckles) And then we also have, at the other end a 472, so still small, but a little bit bigger, but we did recognize obviously AI was coming up, and so that is our XR 7620 platform and that does support 2 GPUs right, so, like for Edge infrencing, making sure that we have the capability to support customers in that too, but also in the small one, we do also have a GPU capability there, that also helps in those other use cases as well. So we've built the platforms even though they're small to be able to handle the GPU power for customers. >> So nice tight package, a lot of power there. >> Yes. >> Beside as we've all clearly demonstrated the size of Dave's shoe. (crowd chuckles) Dave, talk about Dell's long standing commitment to really helping to rapidly evolve the server market. >> Dave: Yeah. >> Its a pivotal payer there. >> Well, like I was saying, we see innovation, I mean, this is, to us its a race to the top. You talked about racing and messaging that sort of thing, when you opened up the show here, but we see this as a race to the top, having worked at other server companies where maybe its a little bit different, maybe more of a race to the bottom source of approach. That's what I love about being at Dell. This is very much, we understand that it's innovation is that is what's going to deliver the most value for our customers. So whether its some of the first to market, first of its kind sort of innovation that you find in the XR4000, or XR8000, or any of our XE line, we know that at the end of day, that is what going to propel Dell, do the best for our customers and thereby do the best for us. To be honest, its a little bit surprising walking by some of our competitors booths, there's been like a dearth of zero, like no, like it's almost like you wouldn't even know that there was a big launch here right? >> Yeah. >> Or is it just me? >> No. >> It was a while, we've been walking around and yet we've had, and its sort of maybe I should take this as a flattery, but a lot of our competitors have been coming by to our booth everyday actually. >> Deania: Yeah, everyday. >> They came by multiple times yesterday, they came by multiple times today, they're taking pictures of our stuff I kind of want to just send 'em a sample. >> Lisa: Or your shoe. >> Right? Or just maybe my shoe right? But anyway, so I suppose I should take it as an honor. >> Deania: Yeah. >> And conversely when we've walked over there we actually get in back (indistinct), maybe I need a high Dell (indistinct). (crowd chuckles) >> We just had that experience, yeah. >> Its kind of funny but. >> Its a good position to be in. >> Yeah. >> Yes. >> You talked about the involvement of the customers, talk a bit more about Dell's ecosystem is also massive, its part of what makes Dell, Dell. >> Wait did you say ego-system? (laughing) After David just. >> You caught that? Darn it! The talk about the influence or the part of the ecosystem and also some of the feedback from the partners as you've been rapidly evolving the server market and clearly your competitors are taking notice. >> Yeah, sorry. >> Deania: That's okay. >> Dave: you want to take that? >> I mean I would say generally, one of the things that Dell prides itself on is being able to deliver the worlds best innovation into the hands of our customers, faster and better that any other, the optimal solution. So whether its you know, working with our great partners like Intel, AMD Broadcom, these sorts of folks. That is, at the end of the day that is our core mantra, again its retractor on service, doing the best, you know, what's best for the customers. And we want to bring the world's best innovation from our technology partners, get it into the hands of our partners you know, faster and better than any other option out there. >> Its a satisfying business for all of us to be in, because to your point, I made a joke about the high level messaging. But really, that's what it comes down to. >> Lisa: Yeah. >> We do these things, we feel like sometimes we're toiling in obscurity, working with the hardware. But what it delivers. >> Deania: Hm-mm. >> The experiences. >> Dave: Absolutely. >> Deania: Yes. >> Are truly meaningful. So its a fun. >> Absolutely. >> Its a really fun thing to be a part of. >> It is. >> Absolutely. >> Yeah. Is there a favorite customer story that you have that really articulates the value of what Dell is doing, full PowerEdge, at the Edge? >> Its probably one I can't particularly name obviously but, it was, they have different environments, so, in one case there's like on flights or on sea vessels, and just being able to use the same box in those different environments is really cool. And they really appreciate having the small compact, where they can just take the server with them and go somewhere. That was really cool to me in terms of how they were using the products that we built for them. >> I have one that's kind of funny. It around XR8000. Again a customer I won't name but they're so proud of it, they almost kinds feel like they co defined it with us, they want to be on the patent with us so, anyways that's. >> Deania: (indistinct). >> That's what they went in for, yeah. >> So it shows the strength of the partnership that. >> Yeah, exactly. >> Of course, the ecosystem of partners, customers, CSVs, telecom Edge. Guys thank you so much for joining us today. >> Thank you. >> Thank you. >> Sharing what's new with the PowerEdge. We can't wait to, we're just, we're cracking open the box, we saw the shoe. (laughing) And we're going to be dealing a little bit more later. So thank you. >> We're going to be able to touch something soon? >> Yes, yes. >> Yeah. >> In couple of minutes? >> Next segment I think. >> All right! >> Thanks for setting the table for that guys. We really appreciate your time. >> Thank you for having us. >> Thank you. >> Alright, our pleasure. >> For our guests and for Dave Nicholson, I'm Lisa Martin . You're watching theCUBE. The leader in live tech coverage, LIVE in Barcelona, Spain, MWC 23. Don't go anywhere, we will be right back with our next guests. (gentle music)

(gentle music playing) >> For centuries, we've been captivated by the concept of machines doing the job of humans. And over the past decade or so, we've really focused on AI and the possibility of intelligent machines that can perform cognitive tasks. Now in the past few years, with the popularity of machine learning models ranging from recent ChatGPT to Bert, we're starting to see how AI is changing the way we interact with the world. How is AI transforming the way we do business? And what does the future hold for us there. At theCube, we've covered Oracle's AI and ML strategy for years, which has really been used to drive automation into Oracle's autonomous database. We've talked a lot about MySQL HeatWave in database machine learning, and AI pushed into Oracle's business apps. Oracle, it tends to lead in AI, but not competing as a direct AI player per se, but rather embedding AI and machine learning into its portfolio to enhance its existing products, and bring new services and offerings to the market. Now, last October at Cloud World in Las Vegas, Oracle partnered with Nvidia, which is the go-to AI silicon provider for vendors. And they announced an investment, a pretty significant investment to deploy tens of thousands more Nvidia GPUs to OCI, the Oracle Cloud Infrastructure and build out Oracle's infrastructure for enterprise scale AI. Now, Oracle CEO, Safra Catz said something to the effect of this alliance is going to help customers across industries from healthcare, manufacturing, telecoms, and financial services to overcome the multitude of challenges they face. Presumably she was talking about just driving more automation and more productivity. Now, to learn more about Oracle's plans for AI, we'd like to welcome in Elad Ziklik, who's the vice president of AI services at Oracle. Elad, great to see you. Welcome to the show. >> Thank you. Thanks for having me. >> You're very welcome. So first let's talk about Oracle's path to AI. I mean, it's the hottest topic going for years you've been incorporating machine learning into your products and services, you know, could you tell us what you've been working on, how you got here? >> So great question. So as you mentioned, I think most of the original four-way into AI was on embedding AI and using AI to make our applications, and databases better. So inside mySQL HeatWave, inside our autonomous database in power, we've been driving AI, all of course are SaaS apps. So Fusion, our large enterprise business suite for HR applications and CRM and ELP, and whatnot has built in AI inside it. Most recently, NetSuite, our small medium business SaaS suite started using AI for things like automated invoice processing and whatnot. And most recently, over the last, I would say two years, we've started exposing and bringing these capabilities into the broader OCI Oracle Cloud infrastructure. So the developers, and ISVs and customers can start using our AI capabilities to make their apps better and their experiences and business workflow better, and not just consume these as embedded inside Oracle. And this recent partnership that you mentioned with Nvidia is another step in bringing the best AI infrastructure capabilities into this platform so you can actually build any type of machine learning workflow or AI model that you want on Oracle Cloud. >> So when I look at the market, I see companies out there like DataRobot or C3 AI, there's maybe a half dozen that sort of pop up on my radar anyway. And my premise has always been that most customers, they don't want to become AI experts, they want to buy applications and have AI embedded or they want AI to manage their infrastructure. So my question to you is, how does Oracle help its OCI customers support their business with AI? >> So it's a great question. So I think what most customers want is business AI. They want AI that works for the business. They want AI that works for the enterprise. I call it the last mile of AI. And they want this thing to work. The majority of them don't want to hire a large and expensive data science teams to go and build everything from scratch. They just want the business problem solved by applying AI to it. My best analogy is Lego. So if you think of Lego, Lego has these millions Lego blocks that you can use to build anything that you want. But the majority of people like me or like my kids, they want the Lego death style kit or the Lego Eiffel Tower thing. They want a thing that just works, and it's very easy to use. And still Lego blocks, you still need to build some things together, which just works for the scenario that you're looking for. So that's our focus. Our focus is making it easy for customers to apply AI where they need to, in the right business context. So whether it's embedding it inside the business applications, like adding forecasting capabilities to your supply chain management or financial planning software, whether it's adding chat bots into the line of business applications, integrating these things into your analytics dashboard, even all the way to, we have a new platform piece we call ML applications that allows you to take a machine learning model, and scale it for the thousands of tenants that you would be. 'Cause this is a big problem for most of the ML use cases. It's very easy to build something for a proof of concept or a pilot or a demo. But then if you need to take this and then deploy it across your thousands of customers or your thousands of regions or facilities, then it becomes messy. So this is where we spend our time making it easy to take these things into production in the context of your business application or your business use case that you're interested in right now. >> So you mentioned chat bots, and I want to talk about ChatGPT, but my question here is different, we'll talk about that in a minute. So when you think about these chat bots, the ones that are conversational, my experience anyway is they're just meh, they're not that great. But the ones that actually work pretty well, they have a conditioned response. Now they're limited, but they say, which of the following is your problem? And then if that's one of the following is your problem, you can maybe solve your problem. But this is clearly a trend and it helps the line of business. How does Oracle think about these use cases for your customers? >> Yeah, so I think the key here is exactly what you said. It's about task completion. The general purpose bots are interesting, but as you said, like are still limited. They're getting much better, I'm sure we'll talk about ChatGPT. But I think what most enterprises want is around task completion. I want to automate my expense report processing. So today inside Oracle we have a chat bot where I submit my expenses the bot ask a couple of question, I answer them, and then I'm done. Like I don't need to go to our fancy application, and manually submit an expense report. I do this via Slack. And the key is around managing the right expectations of what this thing is capable of doing. Like, I have a story from I think five, six years ago when technology was much inferior than it is today. Well, one of the telco providers I was working with wanted to roll a chat bot that does realtime translation. So it was for a support center for of the call centers. And what they wanted do is, Hey, we have English speaking employees, whatever, 24/7, if somebody's calling, and the native tongue is different like Hebrew in my case, or Chinese or whatnot, then we'll give them a chat bot that they will interact with and will translate this on the fly and everything would work. And when they rolled it out, the feedback from customers was horrendous. Customers said, the technology sucks. It's not good. I hate it, I hate your company, I hate your support. And what they've done is they've changed the narrative. Instead of, you go to a support center, and you assume you're going to talk to a human, and instead you get a crappy chat bot, they're like, Hey, if you want to talk to a Hebrew speaking person, there's a four hour wait, please leave your phone and we'll call you back. Or you can try a new amazing Hebrew speaking AI powered bot and it may help your use case. Do you want to try it out? And some people said, yeah, let's try it out. Plus one to try it out. And the feedback, even though it was the exact same technology was amazing. People were like, oh my God, this is so innovative, this is great. Even though it was the exact same experience that they hated a few weeks earlier on. So I think the key lesson that I picked from this experience is it's all about setting the right expectations, and working around the right use case. If you are replacing a human, the level is different than if you are just helping or augmenting something that otherwise would take a lot of time. And I think this is the focus that we are doing, picking up the tasks that people want to accomplish or that enterprise want to accomplish for the customers, for the employees. And using chat bots to make those specific ones better rather than, hey, this is going to replace all humans everywhere, and just be better than that. >> Yeah, I mean, to the point you mentioned expense reports. I'm in a Twitter thread and one guy says, my favorite part of business travel is filling out expense reports. It's an hour of excitement to figure out which receipts won't scan. We can all relate to that. It's just the worst. When you think about companies that are building custom AI driven apps, what can they do on OCI? What are the best options for them? Do they need to hire an army of machine intelligence experts and AI specialists? Help us understand your point of view there. >> So over the last, I would say the two or three years we've developed a full suite of machine learning and AI services for, I would say probably much every use case that you would expect right now from applying natural language processing to understanding customer support tickets or social media, or whatnot to computer vision platforms or computer vision services that can understand and detect objects, and count objects on shelves or detect cracks in the pipe or defecting parts, all the way to speech services. It can actually transcribe human speech. And most recently we've launched a new document AI service. That can actually look at unstructured documents like receipts or invoices or government IDs or even proprietary documents, loan application, student application forms, patient ingestion and whatnot and completely automate them using AI. So if you want to do one of the things that are, I would say common bread and butter for any industry, whether it's financial services or healthcare or manufacturing, we have a suite of services that any developer can go, and use easily customized with their own data. You don't need to be an expert in deep learning or large language models. You could just use our automobile capabilities, and build your own version of the models. Just go ahead and use them. And if you do have proprietary complex scenarios that you need customer from scratch, we actually have the most cost effective platform for that. So we have the OCI data science as well as built-in machine learning platform inside the databases inside the Oracle database, and mySQL HeatWave that allow data scientists, python welding people that actually like to build and tweak and control and improve, have everything that they need to go and build the machine learning models from scratch, deploy them, monitor and manage them at scale in production environment. And most of it is brand new. So we did not have these technologies four or five years ago and we've started building them and they're now at enterprise scale over the last couple of years. >> So what are some of the state-of-the-art tools, that AI specialists and data scientists need if they're going to go out and develop these new models? >> So I think it's on three layers. I think there's an infrastructure layer where the Nvidia's of the world come into play. For some of these things, you want massively efficient, massively scaled infrastructure place. So we are the most cost effective and performant large scale GPU training environment today. We're going to be first to onboard the new Nvidia H100s. These are the new super powerful GPU's for large language model training. So we have that covered for you in case you need this 'cause you want to build these ginormous things. You need a data science platform, a platform where you can open a Python notebook, and just use all these fancy open source frameworks and create the models that you want, and then click on a button and deploy it. And it infinitely scales wherever you need it. And in many cases you just need the, what I call the applied AI services. You need the Lego sets, the Lego death style, Lego Eiffel Tower. So we have a suite of these sets for typical scenarios, whether it's cognitive services of like, again, understanding images, or documents all the way to solving particular business problems. So an anomaly detection service, demand focusing service that will be the equivalent of these Lego sets. So if this is the business problem that you're looking to solve, we have services out there where we can bring your data, call an API, train a model, get the model and use it in your production environment. So wherever you want to play, all the way into embedding this thing, inside this applications, obviously, wherever you want to play, we have the tools for you to go and engage from infrastructure to SaaS at the top, and everything in the middle. >> So when you think about the data pipeline, and the data life cycle, and the specialized roles that came out of kind of the (indistinct) era if you will. I want to focus on two developers and data scientists. So the developers, they hate dealing with infrastructure and they got to deal with infrastructure. Now they're being asked to secure the infrastructure, they just want to write code. And a data scientist, they're spending all their time trying to figure out, okay, what's the data quality? And they're wrangling data and they don't spend enough time doing what they want to do. So there's been a lack of collaboration. Have you seen that change, are these approaches allowing collaboration between data scientists and developers on a single platform? Can you talk about that a little bit? >> Yeah, that is a great question. One of the biggest set of scars that I have on my back from for building these platforms in other companies is exactly that. Every persona had a set of tools, and these tools didn't talk to each other and the handoff was painful. And most of the machine learning things evaporate or die on the floor because of this problem. It's very rarely that they are unsuccessful because the algorithm wasn't good enough. In most cases it's somebody builds something, and then you can't take it to production, you can't integrate it into your business application. You can't take the data out, train, create an endpoint and integrate it back like it's too painful. So the way we are approaching this is focused on this problem exactly. We have a single set of tools that if you publish a model as a data scientist and developers, and even business analysts that are seeing a inside of business application could be able to consume it. We have a single model store, a single feature store, a single management experience across the various personas that need to play in this. And we spend a lot of time building, and borrowing a word that cellular folks used, and I really liked it, building inside highways to make it easier to bring these insights into where you need them inside applications, both inside our applications, inside our SaaS applications, but also inside custom third party and even first party applications. And this is where a lot of our focus goes to just because we have dealt with so much pain doing this inside our own SaaS that we now have built the tools, and we're making them available for others to make this process of building a machine learning outcome driven insight in your app easier. And it's not just the model development, and it's not just the deployment, it's the entire journey of taking the data, building the model, training it, deploying it, looking at the real data that comes from the app, and creating this feedback loop in a more efficient way. And that's our focus area. Exactly this problem. >> Well thank you for that. So, last week we had our super cloud two event, and I had Juan Loza on and he spent a lot of time talking about how open Oracle is in its philosophy, and I got a lot of feedback. They were like, Oracle open, I don't really think, but the truth is if you think about database Oracle database, it never met a hardware platform that it didn't like. So in that sense it's open. So, but my point is, a big part of of machine learning and AI is driven by open source tools, frameworks, what's your open source strategy? What do you support from an open source standpoint? >> So I'm a strong believer that you don't actually know, nobody knows where the next slip fog or the next industry shifting innovation in AI is going to come from. If you look six months ago, nobody foreseen Dali, the magical text to image generation and the exploding brought into just art and design type of experiences. If you look six weeks ago, I don't think anybody's seen ChatGPT, and what it can do for a whole bunch of industries. So to me, assuming that a customer or partner or developer would want to lock themselves into only the tools that a specific vendor can produce is ridiculous. 'Cause nobody knows, if anybody claims that they know where the innovation is going to come from in a year or two, let alone in five or 10, they're just wrong or lying. So our strategy for Oracle is to, I call this the Netflix of AI. So if you think about Netflix, they produced a bunch of high quality shows on their own. A few years ago it was House of Cards. Last month my wife and I binge watched Ginny and Georgie, but they also curated a lot of shows that they found around the world and bought them to their customers. So it started with things like Seinfeld or Friends and most recently it was Squid games and those are famous Israeli TV series called Founder that Netflix bought in, and they bought it as is and they gave it the Netflix value. So you have captioning and you have the ability to speed the movie and you have it inside your app, and you can download it and watch it offline and everything, but nobody Netflix was involved in the production of these first seasons. Now if these things hunt and they're great, then the third season or the fourth season will get the full Netflix production value, high value budget, high value location shooting or whatever. But you as a customer, you don't care whether the producer and director, and screenplay writing is a Netflix employee or is somebody else's employee. It is fulfilled by Netflix. I believe that we will become, or we are looking to become the Netflix of AI. We are building a bunch of AI in a bunch of places where we think it's important and we have some competitive advantage like healthcare with Acellular partnership or whatnot. But I want to bring the best AI software and hardware to OCI and do a fulfillment by Oracle on that. So you'll get the Oracle security and identity and single bill and everything you'd expect from a company like Oracle. But we don't have to be building the data science, and the models for everything. So this means both open source recently announced a partnership with Anaconda, the leading provider of Python distribution in the data science ecosystem where we are are doing a joint strategic partnership of bringing all the goodness into Oracle customers as well as in the process of doing the same with Nvidia, and all those software libraries, not just the Hubble, both for other stuff like Triton, but also for healthcare specific stuff as well as other ISVs, other AI leading ISVs that we are in the process of partnering with to get their stuff into OCI and into Oracle so that you can truly consume the best AI hardware, and the best AI software in the world on Oracle. 'Cause that is what I believe our customers would want the ability to choose from any open source engine, and honestly from any ISV type of solution that is AI powered and they want to use it in their experiences. >> So you mentioned ChatGPT, I want to talk about some of the innovations that are coming. As an AI expert, you see ChatGPT on the one hand, I'm sure you weren't surprised. On the other hand, maybe the reaction in the market, and the hype is somewhat surprising. You know, they say that we tend to under or over-hype things in the early stages and under hype them long term, you kind of use the internet as example. What's your take on that premise? >> So. I think that this type of technology is going to be an inflection point in how software is being developed. I truly believe this. I think this is an internet style moment, and the way software interfaces, software applications are being developed will dramatically change over the next year two or three because of this type of technologies. I think there will be industries that will be shifted. I think education is a good example. I saw this thing opened on my son's laptop. So I think education is going to be transformed. Design industry like images or whatever, it's already been transformed. But I think that for mass adoption, like beyond the hype, beyond the peak of inflected expectations, if I'm using Gartner terminology, I think certain things need to go and happen. One is this thing needs to become more reliable. So right now it is a complete black box that sometimes produce magic, and sometimes produce just nonsense. And it needs to have better explainability and better lineage to, how did you get to this answer? 'Cause I think enterprises are going to really care about the things that they surface with the customers or use internally. So I think that is one thing that's going to come out. And the other thing that's going to come out is I think it's going to come industry specific large language models or industry specific ChatGPTs. Something like how OpenAI did co-pilot for writing code. I think we will start seeing this type of apps solving for specific business problems, understanding contracts, understanding healthcare, writing doctor's notes on behalf of doctors so they don't have to spend time manually recording and analyzing conversations. And I think that would become the sweet spot of this thing. There will be companies, whether it's OpenAI or Microsoft or Google or hopefully Oracle that will use this type of technology to solve for specific very high value business needs. And I think this will change how interfaces happen. So going back to your expense report, the world of, I'm going to go into an app, and I'm going to click on seven buttons in order to get some job done like this world is gone. Like I'm going to say, hey, please do this and that. And I expect an answer to come out. I've seen a recent demo about, marketing in sales. So a customer sends an email that is interested in something and then a ChatGPT powered thing just produces the answer. I think this is how the world is going to evolve. Like yes, there's a ton of hype, yes, it looks like magic and right now it is magic, but it's not yet productive for most enterprise scenarios. But in the next 6, 12, 24 months, this will start getting more dependable, and it's going to change how these industries are being managed. Like I think it's an internet level revolution. That's my take. >> It's very interesting. And it's going to change the way in which we have. Instead of accessing the data center through APIs, we're going to access it through natural language processing and that opens up technology to a huge audience. Last question, is a two part question. And the first part is what you guys are working on from the futures, but the second part of the question is, we got data scientists and developers in our audience. They love the new shiny toy. So give us a little glimpse of what you're working on in the future, and what would you say to them to persuade them to check out Oracle's AI services? >> Yep. So I think there's two main things that we're doing, one is around healthcare. With a new recent acquisition, we are spending a significant effort around revolutionizing healthcare with AI. Of course many scenarios from patient care using computer vision and cameras through automating, and making better insurance claims to research and pharma. We are making the best models from leading organizations, and internal available for hospitals and researchers, and insurance providers everywhere. And we truly are looking to become the leader in AI for healthcare. So I think that's a huge focus area. And the second part is, again, going back to the enterprise AI angle. Like we want to, if you have a business problem that you want to apply here to solve, we want to be your platform. Like you could use others if you want to build everything complicated and whatnot. We have a platform for that as well. But like, if you want to apply AI to solve a business problem, we want to be your platform. We want to be the, again, the Netflix of AI kind of a thing where we are the place for the greatest AI innovations accessible to any developer, any business analyst, any user, any data scientist on Oracle Cloud. And we're making a significant effort on these two fronts as well as developing a lot of the missing pieces, and building blocks that we see are needed in this space to make truly like a great experience for developers and data scientists. And what would I recommend? Get started, try it out. We actually have a shameless sales plug here. We have a free deal for all of our AI services. So it typically cost you nothing. I would highly recommend to just go, and try these things out. Go play with it. If you are a python welding developer, and you want to try a little bit of auto mail, go down that path. If you're not even there and you're just like, hey, I have these customer feedback things and I want to try out, if I can understand them and apply AI and visualize, and do some cool stuff, we have services for that. My recommendation is, and I think ChatGPT got us 'cause I see people that have nothing to do with AI, and can't even spell AI going and trying it out. I think this is the time. Go play with these things, go play with these technologies and find what AI can do to you or for you. And I think Oracle is a great place to start playing with these things. >> Elad, thank you. Appreciate you sharing your vision of making Oracle the Netflix of AI. Love that and really appreciate your time. >> Awesome. Thank you. Thank you for having me. >> Okay. Thanks for watching this Cube conversation. This is Dave Vellante. We'll see you next time. (gentle music playing)

(upbeat music) >> Hello, brilliant cloud community, and welcome back to AWS re:Invent. We are here in Las Vegas, Nevada. I'm Savannah Peterson, joined by my co-host Dave Vellante. Dave, how you doing? >> I'm doing well, thanks, yeah. >> Yeah, I feel like... >> I'm hanging in there. >> you've got a lot of pep in your step today for the fourth day. >> I think my voice is coming back, actually. >> (laughs) Look at you, resilient. >> I was almost lost yesterday, yeah. >> Yeah. (laughs) >> So, I actually, at a Hitachi event one time almost completely lost my voice. The production guys pulled me off. They said, "You're done." (Savannah laughing) They gave me the hook. >> You got booted? >> Dave: Yeah, yeah. >> Yeah, yeah, you actually (laughs) got the hook, wow. >> So, I have good memories of Hitachi. >> I was going to say (Dave laughing) interesting that you mentioned Hitachi. Our two guests this morning are from Hitachi. Sid and KP, welcome to the show. >> Thank you. >> Savannah: How you guys doing? Looking great for day four. >> Great. Thank you. >> Great. >> Hanging in there. >> Thank you, Dave and Savannah. (Savannah laughing) >> Dave: Yeah, cool. >> Savannah: Yeah. (laughs) >> Yeah, it was actually a Pentaho thing, right? >> Oh, Pentaho? Yeah. >> Which kind of you guys into that software edge. It was right when you announced the name change to Hitachi Vantara, which is very cool. I had Brian Householder on. You remember Brian? >> Yeah, I know. >> He was explaining the vision, and yeah (indistinct). >> Yeah. Well, look at you a little Hitachi (indistinct). >> Yeah, I've been around a long time, yeah. >> Yeah, all right. (Dave laughing) >> Just a casual flex to start us off there, Dave. I love it. I love it. Sid, we've talked a lot on the show about delivering outcomes. It's a hot theme. Everyone wants to actually have tangible business outcomes from all of this. How are customers realizing value from the cloud? What does that mean? >> See, still 2007, 2008, it was either/or kind of architecture. Either I'm going to execute my use cases on cloud or I'm going to keep my use cases and outcomes through edge. But in the last four or five years and specifically we are in re:Invent, I would talk about AWS. Lot of the power of hyperscalers has been brought to edge. If you talk about the snowball family of AWS, if you talk about monitor on edge devices, if you talk about the entire server list being brought into Lambda coupled inside snowball, now the architecture premise, if I talk about logical shift is end. Now the customers are talking about executing the use cases between edge and cloud. So, there is a continuum rather than a binary bullion decision. So, if you are talking about optimizing a factory, earlier I'll do the analytics at cloud, and I'll do machine on edge. Now it is optimization of a factory outcome at scale across my entire manufacturing where edge, private cloud, AWS, hyperscalers, everything is a continuum. And the customer is not worried about where, which part of my data ops, network ops, server ops storage ops is being executed. >> Savannah: It's like (indistinct). >> The customer is enjoying the use cases. And the orchestration is abstracted through an industrial player like Hitachi working very collaboratively with AWS. So, that is how we are working on industrial use cases right now. >> You brought up manufacturing. I don't think there's been a hotter conversation around supply chain and manufacturing than there has been the last few years. I can imagine taking that guessing game out for customers is a huge deal for you guys. >> Big because if you look at the world today, right from a safety pin, to a cell phone jacket, to a cell phone, the entire supply chain is throttled. The supply chain is throttled because there are various choke points. >> Savannah: Yeah. >> And each choke points is surrounded by different kind of supply and geopolitical issues. >> Savannah: 100%. >> Now, if we talk about the wheat crisis happening because of the Ukraine-Russia war, but the wheat crisis actually creates a multiple string of impacts which impact everything. Silicon, now we talk about silicon, but we then forget about nickel. Nickel is also controlled in one part of that geopolitical conflict. So, everything is getting conflagrated into a very big supply issue. So, if your factories are not performing beyond optimum, if they are not performing at real, I'm, we are talking about factory, hyperscale of the factory. The factory needs to perform at hyperscale to provide what the world needs today. So, we are in a very different kind of a scenario. Some of the economists call it earlier the recession was because of a demand constraint. The demand used to go down. Today's recession is because the supply is going down. The demand is there, but the supply is going down. And there is a different kind of recession in the world. The supply is what is getting throttled. >> And the demand is somewhat unpredictable too. People, you know, retailers, they've... >> Especially right now. >> kind of messed up their inventory. And so, the data is still siloed. And that's where, you know, you get to, okay, can I have the same experience across clouds, on-prem, out to the edge? Kind of bust those silos. >> Yep. >> You know, I dunno if it's, it's certainly not entirely a data problem. There's (laughs), like you say, geopolitical and social issues. >> Savannah: There's so much complexity. >> But there's a data problem too. >> Yes. >> Big. >> So, I wonder if you could talk about your sort of view of, point of view on that cross-cloud, hybrid, out to the edge, what I call super cloud? >> Absolutely. So, today, if you look at how enterprises are adopting cloud or how they're leveraging cloud, it's not just a hosting platform, right? It is the platform from where they can draw business capabilities. You heard in the re:Invent that Amazon is coming up with a supply chain service out of the box in the cloud. That's the kind of capabilities that business wants to draw from cloud today. So, the kind of multicloud or like hybrid cloud, public cloud, private cloud, those are the things which are kind of going to be behind the scenes. At the end of the day, the cloud needs to be able to support businesses by providing their services closer to their consumers. So, the challenges are going to be there in terms of like reliability, resilience, cost, security. Those are the ones that, you know, many of the enterprises are grappling with in terms of the challenges. And the way to solve that, the way how we approach our customers and work with them is to be able to bring resilience into the cloud, into the services which are running in cloud, and by driving automation, making autonomous in everything that you do, how you are monitoring your services, how we are making it available, how we are securing it, how we are making it very cost-effective as well. It cannot be manually executed; it has to be automated. So, automation is the key in terms of making the services leveraged from all of this cloud. >> That's your value add. >> Absolutely. >> And how do I consume that value add? Is it sort of embedded into infrastructure? Is it a service layer on top? >> Yeah, so everything that we do today in terms of like how these services have to be provided, how the services have to be consumed, there has to be a modern operating model, right? I think this is where Hitachi has come up with what we are calling as Hitachi Application Reliability Center and Services. That is focusing on modern operating, modern ways of like, you know, how you support these cloud workloads and driving this automation. So, whether we provide a hyper-converged infrastructure that is going to be at the edge location, or we are going to be able to take a customer through the journey of modernization or migrating onto cloud, the operating model that is going to be able to establish the foundation on cloud and then to be able to operate with the right levels of reliability, security, cost is the key. And that's the value added service that we provide. And then the way we do that is essentially by looking at three principles: one, to look at the service in totality. Gone are the days you look at infrastructure separately, applications separately, data and security separately, right? >> Savannah: No more silos. >> No more silos. You look at it as a workload, and you look at it as a service. And number two is to make sure that the DevOps that you bring and what you do at the table is totally integrated and it's end to end. It's not a product team developing a feature and then ops team trying to keep the lights on. It has to be a common backlog with the error budget that looks at you know, product releases, product functionalities, and even what ops needs to do to evolve the product as well. And then the third is to make sure that reliability and resiliency is inbuilt. Cloud offers native durability, native availability. But if your service doesn't take advantage of that, it's kind of going to still be not available. So, how do you kind of ingrain and embed all of these things as a value add that we provide? >> There's a lot of noise. We've got hybrid cloud. We've got multicloud. We've got a lot going on. It adds to the complexity. How do you help customers solve that complexity as they begin their transformation journey? I mean, I'm sure you're working with the biggest companies, making really massive change. How do you guide them through that process? >> So, it is to look at the outcome working backwards, like what AWS does, right? Like, you know, how do you look at the business outcome? What is the value that you're looking to drive? Again, it's not to be pinned through one particular cloud. I know there is lot of technology choices that you can make and lot of deployment models that you can choose from. But at the end of the day, having a common operating model which is kind of like modern, agile, and it is kind of like keeping the outcomes in the mind, that is what we do with our customers to be able to create that operating model, which completes the transformation, by the way. And cloud is just one part of the LEGO blocks which provides that overall scheme and then the view for driving that overall transformation. >> So, let's paint a picture. Let's say you've got this resilient foundation; you've kind of helped the customers build that out. How do they turn that into value for their customers? Do you have any examples that you can share? That'd be great. >> Yeah, I can start with what we're doing for one of the, you know, world's largest facility, infrastructure, power, cooling, security, monitoring company that has their products deployed in 2,000 locations across the globe. For them, and always on business means you are monitoring the temperature. You are monitoring the safety of people who are within the facility, right? A temperature shift of one to two degree can affect even the sustainability goals of NARC, our customer, but also their end consumers. So, how do you monitor these kind of like critical parameters? How do you have a platform? >> Savannah: Great example, yeah. >> How you have cloud resources that are going to be always on, that are going to be reliable, that are going to be cost-effective as well is what we are doing for one of our customers. Sid can talk about another example as well. >> Great. >> Yeah, go for it, Sid. >> So, there are examples: rail. We are working with a group in England; it's called West Coast Partnership. And they had a edge device which was increasing in size. Now, this edge device was becoming big because the parameters which go into the edge device were increasing because of regulation and because the rail is part of national security infrastructure. We have worked with West Coast Partnership and Hitachi Rail, which is a group company, to create a miniaturization of this edge device, because if the size of the edge device is increasing on the train, then the weight of the train increases, and the speed profile, velocity profile, everything goes down. So, we have miniaturized the edge device. Secondly, all the data profiles, signal control, traction control, traction motors, direction control, timetable compliance, everything has been kept uniform. And we have done analytics on cloud. So, what is the behavior of the driver? What is a big breaking parameter of the driver? If the timetable has being missed, is there an erratic behavior being demonstrated by the driver to just meet the timetable? And the timetable is a pretty important criteria in rail because if you miss one, then... So, what we have done is we have created an edge-to-cloud environment where the entire rail analytics is happening. Similarly, in another group company, Hitachi Energy, they had a problem that arguably one of the largest transformer manufacturer in the world. The transformer is a pretty common name now because you're seeing what is happening in Ukraine. Russia went after the transformers and substations before the start of the winter so that their district heating can be meddled with. Now, the transformer, it had a lead time of 17 weeks before COVID. So, if you put me an order of a three-phase transformer, I can deliver it to you in 17 weeks. After and during COVID, the entire lead time increased to 57 to 58 weeks. In cases of a complex transformer, it even went up to something like two years. >> Savannah: Ooh! >> Now, they wanted to increase the productivity of their existing plant because there is only that much sheet metal, that much copper for solenoid, that much microprocessor and silicon. So, they wanted to increase the output of their factory from 95 to 105, 10 more transformers every day, which is 500 and, which is 3,650 every- >> Savannah: Year. >> Year. Now, to do that, we went to a very complex machine; it's called a guard machine. And we increased the productivity of the guard machine by just analyzing all the throttles and all the wastages which are happening there. There are multiple case studies because, see, Hitachi is an industrial giant with 105 years of body of work. KP and I just represent the tip of the digital tip of the arrow. But what we are trying to do through HARC, through industry cloud, through partnership with AWS is basically containerizing and miniaturizing our entire body of work into a democratized environment, an industrial app store, if I may say, where people can come and take their industrial outcomes at ease without worrying about their computational and network orchestration between edge and cloud. That's what we are trying to do. >> I love that analogy of an industrial app cloud. Makes it feel easier in decreasing the complexity of all the different things that everyone's factoring into making their products, whatever they're making. So, we have a new challenge here on theCUBE at AWS re:Invent, where we are looking for your 30-second hot take, your Instagram reel, sound bite. What's the most important story or theme either for you as a team or coming out of the show? You can ponder it for a second. >> It might be different. See, for me, it is industrial security. Industrial OT security should be the theme of the Western world. Western world is on the crosshairs of multiple bad actors. And the industrial security is in the chemical plants, is in the industrial plants, is in the power grids, is in our postal networks and our rail networks. They need to be secured; otherwise, we are geopolitically very weak. Gone are the days when anyone is going to pick up a battle with America or Western world on a field. The battle is going to be pretty clandestine on an cyber world. And that is why industrial security is very important. >> Critical infrastructure and protecting it. >> Absolutely. >> Well said, Sid. KP, what's your hot take? >> My take is going to be a modern operating model, which is going to complete the transformation and to be able to tap into business services from cloud. So, a modern operating model through HARC, that is going to be my take. >> Fantastic. Well, can't wait to see what comes out of Hitachi next. Sid, KP... >> KP: Thank you. >> thank you so much for being here. >> Sid: Thank you. >> Absolutely. >> Dave: Thanks, guys. >> Savannah: This is I could talk to you all about supply chain all day long. And thank all of you for tuning in to our continuous live coverage here from AWS re:Invent in fantastic Sin City. I'm Savannah. Oh, excuse me. With Dave Vellante, I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (digital xylophone music)

(upbeat music) >> Good morning and welcome back to fabulous Las Vegas, Nevada. We're here at AWS re:Invent with wall-to-wall coverage all day long on theCUBE. My name is Savannah Peterson and I am joined this morning by the beautiful Lisa Martin. Lisa, good morning. >> Good morning. Good. >> How you feeling day three? >> Day three is we are going to be shot out of a cannon today. The amount of content coming at you from theCUBE today- >> Get ready, you all. >> Us two gals, is a lot. We're going to have some great conversations. >> And we're starting with a really great one with a Cube Alumni to the max. You've been on the show multiple times. >> John: Yeah. >> Very excited to welcome John, the CMO of Couchbase. Welcome. How you doing this morning? >> Thanks. I'm doing great. Great to be here with you. >> How do you feel about the show so far? What's your pulse? >> The show has been great. I say the energy is great. The traffic at our booth, the conversations that we're having, both with prospective customers and even just partners, right? They're all here. The ecosystem is here >> And everyone's finally back in person and it feels so good. >> John: It does. >> So, we're going to dig in a little bit but just in case the audience isn't familiar, tell us about Couchbase. >> Sure. Couchbase is a publicly traded database company. We have a cloud database platform called Capella which is hosted on AWS and GCP. It is used for building mission-critical applications. So, we have great customers, we're building apps that really matter and are using to drive their business. So, we're very excited about that. 30% of the Fortune 100 are Couchbase customers. >> Nice. Talk a little bit about the AWS relationship. >> Mm-hm. Yeah, so we have a great AWS relationship. In fact, yesterday we announced a deepening of that relationship, a strategic collaboration agreement. We're very excited. It's a multi-year agreement. It's focused on go-to market, from a sales and marketing standpoint. We're going to target, you know, various verticals and, you know, really generate joint business between the two of us. So, it's a deepening of a already strong relationship and we're really excited about that. >> Savannah: Yeah. Go ahead. >> What are some of the industry verticals that you're going to be tackling together? >> Well, gaming for one, right? Manufacturing, the workloads that Couchbase is good for are these mission-critical workloads are ones that are really suited for us to be used with AWS. So, we've done some work with them already in those areas and I'm sure we'll be digging in even deeper. >> That's exciting. Speaking of digging in deeper, tell us a little bit more about Capella. >> Capella. It's a cloud databases services I mentioned. We launched it last October and we are super excited by the uptake, the interest that we're seeing. We have a free 30 day trial, so, you know, people can come and try it and get their hands dirty just getting experience with the product and then, you know, become a customer after that. And we're seeing very strong interest from our existing customer base as well. So, we're really excited about how things are going. >> Talk about Capella and the latest release and how it's really enabling Couchbase to invest deeper into the developer experience. >> Yeah, so, at the end of October, we announced a revamp of our user interface, our user experience for Capella really focused on developers. And what we've done is make it so that it's familiar to developers, right? It's a GitHub-like experience. So, developer comes in, they're very familiar, of course, with GitHub, they are familiar with how the Couchbase Capella interface will work. And so that's something that, you know, we've really invested, in fact, we've invested in developers quite a bit. We announced a Couchbase community hub and a Couchbase ambassadors program, both focused on developers and getting out there and building our community. >> A community is a big topic that we've been talking about at all the conferences this year. We're all back in person, in community. How often are you communicating with your community to get feedback on what that experience should be like? >> Yeah, I mean, we actually have a Discord server, so we're in constant communication. (Savannah laughing) >> Savannah: Yes. (John laughing) 24/7. (laughing) >> Basically, you know, we have staff who's dedicated to making sure that the users on there are getting their answers and giving us feedback on the experience. The ambassadors are somebody who have a really strong relationship, who get early insight and give us feedback before we even release a product. So, it gives us a chance to really test-drive it with core developers and get the insight we need before we get it in the market. >> Yeah. It matters so much. You can build it, but they won't come if it's not fantastic. >> John: Exactly. >> Lisa: Right. >> Let's shift a little bit and talk about customers. How, and price, how do you guys compare? >> Customers and? >> And price, your price performance? >> Price, oh. So, customers, we also announced this week a joint customer Arthrex with AWS. Arthrex is a orthopedics medical devices company and they use our Edge capabilities along with running Couchbase on AWS. So, you think of the kinds of surgeries that orthopedic surgeons do, it's scopes and they are often inside. So, what it does is it collects the data, the video data and all of that on a medical devices and then brings it back to a centralized app for the doctors to use sort of in post when they're actually doing further medical recommendations. >> Savannah: It's so cool. >> So, it's cool, the thing about it is it can work whether it's online or offline, it's one of the reasons that Arthrex selected us because the fact that it can, you know, often sometimes there's not connectivity in the operating room, I'd say deep inside of a hospital. So, these devices work regardless and then when they get connectivity, it sinks back to that centralized service. So, it's one of the main reasons that they selected us. >> That's outstanding. You know, one of the things that John Furrier, you know, John, well, you guys go way back. >> John: Way back. >> He had a sit down with Adam Selensky, oh, about 10 days or so ago. He gets an exclusive with the CEO of AWS every pre re:Invent. And one of the things that Adam said is that the role or the title, data analyst, is going to go away, in that every role will have responsibilities of analyzing data. And I always think of that in terms of operations, marketing, finance, sales, but you just brought up physicians as data analysts in their jobs, right? Probably not, we're thinking about it in that way. >> Yeah. >> But it's so interesting how data is really being democratized. >> John: Yeah. >> And how Couchbase is an enabler of that in an operating room. >> John: Yeah, yeah, yeah. >> That's amazing. >> It's a great story. There's many others and I think, you know, we have embedded operational analytics in Couchbase Capella, and, you know, in our offerings in general. So, what that does is allows us to do real-time, highly personalized applications based on that analytics that are coming in real-time from the data from the applications. And so that's something that's actually driving a highly interactive user experience, one that's very personalized and customized. And that's one of the things that our customers really like about what we do. >> It's fascinating. I never thought about it from a medical device perspective. >> Lisa: No, no. >> John: No. >> My gosh is if doctors don't have enough cognitive burden load. >> John: I know. >> You know, right? Like, they don't need to be a data analyst. I would much rather they were just good at the surgery part. That's a piece of the puzzle I need them to do. Yeah, for sure. That's a fascinating customer example. Can you share any other joint AWS examples with us? >> Joint AW- I mean, there's many in the gaming area where, because Couchbase is memory-first architecture, we deliver very, very interactive user experiences and we're used a lot for session management, user ID management in the gaming space, specifically with AWS. It's an area we've done some joint work already and had a lot of success, you know, with small and large gaming companies. >> Yeah. It looks like you also, according to my notes here, we've got things in travel and hospitality as well. >> Yes. Also Carnival Cruises is a great example. We enable their on-ship, on-board experience, highly customized, everybody wears a device called a medallion, and as they move around the ship, it knows where they are and it's able to provide customized services. You walk up to a bar, you have your favorite drink, it can be hit the bar when you land there. >> I'll take that. >> How about that? (laugh) >> That's outstanding. >> Isn't that great? >> Can we carry that onto the AWS show floor? >> Exactly. >> Or Starbucks order? >> Yeah, yeah. Yes, please. Yes, please. Well, another thing that's so interesting these days, is that every company has to be a data company. Say they have to be a software company. They have to be a data company. You just gave some great examples. Hospitality, gaming, healthcare, where that data democratization has to happen. >> John: Yeah. >> Businesses has to transform. But one of the things that Adam also told John is that CIOs, CEOs are coming to him not wanting to talk about technology but about transformation. >> Yeah. >> Huge topic. >> And that's a journey where every customer is at different levels. >> Yeah. >> How is Couchbase helping businesses transform and where are your customer conversations these days? >> Yeah, yeah, yeah. So, I mean, the transformation of the business is a major topic of conversation. So, we completely agree with that. How Couchbase helps is, you know, in our database, one of the things we have is the SQL engine. And so as people are looking to move and modernize their infrastructure, if they're moving off of, or from like a technology that's principally based on SQL but doesn't give all the flexibility of a JSON database or document database like we do, we actually enable them to get more easily onto our platform so that they can start that transformation. And then it's a, you know, it's a journey of how they want to transform their business and it's really focused on how do they better serve their customers and clients, whether it's internal or external? >> It really matters. I mean, and that ease of use as well as the transformation journey. It takes a long time for people to adapt. So, every piece of that puzzle, every Lego being quicker or easier, more intuitive, like you said, with the user experience, we can tell you're very thoughtful. How does this improve the total cost of ownership for your customers? >> That's one of the things that we announced along with that developer changes, was a new storage engine underneath Couchbase Capella. And it's 10 X more dense storage. And what that means is fewer servers. So, fewer servers is a much better cost of ownership story. That plus just the performance of the platform itself, we find, you know, against competition, we can do things on say six nodes that take 18 nodes for others. >> Lisa: Oh wow. >> And we have a great consolidation story as well because we have, it's a multi-modal database, meaning that it has SQL engine, document database, full tech search, eventing and analytics, all these pieces on one common data layer. So, you can actually consolidate off of other technologies onto one, onto Couchbase, and that actually saves you money. So, that's a great story for us. >> There's got to be a sustainability element to that as well? >> Yeah, I mean it's, obviously, if you're using less, using fewer servers, there's a kind of power consumption aspect of it as well. Absolutely. >> Are you finding that a lot of customers and companies we talk to these days have in their RFPs, they must only work with vendors who have an actual ESG program? Are you finding more customers coming to you saying, how can you help us dial down our carbon emissions? >> John: Yeah. >> Savannah: Great question. >> We've got a sustainability program that we've got to meet, we've got commitments to our customers. >> John: Yeah. >> Is that something that's really now kind of a hard and fast requirement? >> We're hearing it, we're definitely hearing it. I wouldn't say it's, you know, massively pervasive but I would say it's a growing component of, as you said, RFPs. And it's something that we feel like we have a great story for. And so, you know, it's something that helps when we get into those conversations, we can clearly articulate how we can provide that value and how we meet some of those needs that they have. >> Yeah, that's awesome. So, we have a bit of a challenge, new to the show at re:Invent. >> John: Mm-hm. >> Where we are prompting you to give us your 30 second Instagram Reel sizzle highlight. Don't worry, I'm not actually timing you, but your thought leadership hot-take on the most important theme or takeaway from this year's show. >> From the conference here. I would say that, and I think this was talked about a little bit by AWS as well, but the convergence of analytics and operational data, you know, through the applications is one that we're certainly seeing as well. It's the reason we have analytics in our database. But as I walk around and look at it, I see that very much as a common theme as well, in terms of what other vendors are saying and just the conversations we're having. So for me, that's one of the things I think would be a takeaway from this show. >> Yeah. Embedded analytics, real-time, everybody wants to know what's going on, in context. >> Yeah. That's right. >> Right now, not last week, not what we're processing from last month. >> Exactly. >> I mean, right? (cross-talking) >> So, I can react and take advantage or take an action if I have to. >> Exactly. And then deliver that personalized experience that we all expect these days. >> Oh, yes. >> I'll take that medallion- >> It's about the medallion. I was like, okay. >> You up with that, John? >> We'll get right on it. >> Lisa: All right. (laughs) >> About this. So, what's next for Couchbase? >> John: Well- >> I know you got the partnership, you've got all this exciting momentum. >> So, we're excited heading into next year. We're going to continue to innovate on Capella, right? Continue to deliver more value, lean into our developer community that we have. We're investing heavily, not just from a product standpoint but from a company standpoint in terms of, you know, our community meetups and some of those things. We have a big community-focused event coming up in March called Connect, Couchbase Connect. So, that's something that we'll, you know, continue to drive. That'll be a major theme for us next year. Cloud and developers and, you know, continuing to enable that ecosystem. >> Lisa: Excellent. >> I just had a Microsoft moment where I saw you saying, "Cloud developers," on stage. (Lisa and Savannah laughing) >> I'm not going Steve Ballmer on you. (all laughing) >> Pardon. I was trying to get someone to sing yesterday. I was hoping you were my Ballmer dance. Oh, man. Well, this has been a really great way to start the day. John, thank you so much for being on the show with us, seriously. And it's great that you keep coming back. I'm glad we haven't scared you off. (John laughing) >> Never. >> Savannah: We will have you anytime. >> Thank you. >> And thank you all for tuning in for yet another fantastic day of all day live coverage here from AWS re:Invent. We are in Sin City, having a fabulous time with Lisa Martin. I'm Savannah Peterson. This is theCUBE and we are the leader in high-tech technology coverage. (upbeat music) (upbeat music fades)

>>Hey, welcome back everyone. Day three of eight of us Reinvent 2022. I'm John Farmer with Dave Volante, co-host the q Dave. 10 years for us, the leader in high tech coverage is our slogan. Now 10 years of reinvent day. We've been to every single one except with the original, which we would've come to if Amazon actually marketed the event, but they didn't. It's more of a customer event. This is day three. Is the machine learning ai keynote sws up there. A lot of announcements. We're gonna break this down. We got, we got Andy Thra here, vice President, prince Constellation Research. Andy, great to see you've been on the cube before one of our analysts bringing the, bringing the, the analysis, commentary to the keynote. This is your wheelhouse. Ai. What do you think about Swami up there? I mean, he's awesome. We love him. Big fan Oh yeah. Of of the Cuban we're fans of him, but he got 13 announcements. >>A lot. A lot, >>A lot. >>So, well some of them are, first of all, thanks for having me here and I'm glad to have both of you on the same show attacking me. I'm just kidding. But some of the announcement really sort of like a game changer announcements and some of them are like, meh, you know, just to plug in the holes what they have and a lot of golf claps. Yeah. Meeting today. And you could have also noticed that by, when he was making the announcements, you know, the, the, the clapping volume difference, you could say, which is better, right? But some of the announcements are, are really, really good. You know, particularly we talked about, one of that was Microsoft took that out of, you know, having the open AI in there, doing the large language models. And then they were going after that, you know, having the transformer available to them. And Amazon was a little bit weak in the area, so they couldn't, they don't have a large language model. So, you know, they, they are taking a different route saying that, you know what, I'll help you train the large language model by yourself, customized models. So I can provide the necessary instance. I can provide the instant volume, memory, the whole thing. Yeah. So you can train the model by yourself without depending on them kind >>Of thing. So Dave and Andy, I wanna get your thoughts cuz first of all, we've been following Amazon's deep bench on the, on the infrastructure pass. They've been doing a lot of machine learning and ai, a lot of data. It just seems that the sentiment is that there's other competitors doing a good job too. Like Google, Dave. And I've heard folks in the hallway, even here, ex Amazonians saying, Hey, they're train their models on Google than they bring up the SageMaker cuz it's better interface. So you got, Google's making a play for being that data cloud. Microsoft's obviously putting in a, a great kind of package to kind of make it turnkey. How do they really stand versus the competition guys? >>Good question. So they, you know, each have their own uniqueness and the we variation that take it to the field, right? So for example, if you were to look at it, Microsoft is known for as industry or later things that they are been going after, you know, industry verticals and whatnot. So that's one of the things I looked here, you know, they, they had this omic announcement, particularly towards that healthcare genomics space. That's a huge space for hpz related AIML applications. And they have put a lot of things in together in here in the SageMaker and in the, in their models saying that, you know, how do you, how do you use this transmit to do things like that? Like for example, drug discovery, for genomics analysis, for cancer treatment, the whole, right? That's a few volumes of data do. So they're going in that healthcare area. Google has taken a different route. I mean they want to make everything simple. All I have to do is I gotta call an api, give what I need and then get it done. But Amazon wants to go at a much deeper level saying that, you know what? I wanna provide everything you need. You can customize the whole thing for what you need. >>So to me, the big picture here is, and and Swami references, Hey, we are a data company. We started, he talked about books and how that informed them as to, you know, what books to place front and center. Here's the, here's the big picture. In my view, companies need to put data at the core of their business and they haven't, they've generally put humans at the core of their business and data. And now machine learning are at the, at the outside and the periphery. Amazon, Google, Microsoft, Facebook have put data at their core. So the question is how do incumbent companies, and you mentioned some Toyota Capital One, Bristol Myers Squibb, I don't know, are those data companies, you know, we'll see, but the challenge is most companies don't have the resources as you well know, Andy, to actually implement what Google and Facebook and others have. >>So how are they gonna do that? Well, they're gonna buy it, right? So are they gonna build it with tools that's kind of like you said the Amazon approach or are they gonna buy it from Microsoft and Google, I pulled some ETR data to say, okay, who are the top companies that are showing up in terms of spending? Who's spending with whom? AWS number one, Microsoft number two, Google number three, data bricks. Number four, just in terms of, you know, presence. And then it falls down DataRobot, Anaconda data icu, Oracle popped up actually cuz they're embedding a lot of AI into their products and, and of course IBM and then a lot of smaller companies. But do companies generally customers have the resources to do what it takes to implement AI into applications and into workflows? >>So a couple of things on that. One is when it comes to, I mean it's, it's no surprise that the, the top three or the hyperscalers, because they all want to bring their business to them to run the specific workloads on the next biggest workload. As you was saying, his keynote are two things. One is the A AIML workloads and the other one is the, the heavy unstructured workloads that he was talking about. 80%, 90% of the data that's coming off is unstructured. So how do you analyze that? Such as the geospatial data. He was talking about the volumes of data you need to analyze the, the neural deep neural net drug you ought to use, only hyperscale can do it, right? So that's no wonder all of them on top for the data, one of the things they announced, which not many people paid attention, there was a zero eight L that that they talked about. >>What that does is a little bit of a game changing moment in a sense that you don't have to, for example, if you were to train the data, data, if the data is distributed everywhere, if you have to bring them all together to integrate it, to do that, it's a lot of work to doing the dl. So by taking Amazon, Aurora, and then Rich combine them as zero or no ETL and then have Apaches Apaches Spark applications run on top of analytical applications, ML workloads. That's huge. So you don't have to move around the data, use the data where it is, >>I, I think you said it, they're basically filling holes, right? Yeah. They created this, you know, suite of tools, let's call it. You might say it's a mess. It's not a mess because it's, they're really powerful but they're not well integrated and now they're starting to take the seams as I say. >>Well yeah, it's a great point. And I would double down and say, look it, I think that boring is good. You know, we had that phase in Kubernetes hype cycle where it got boring and that was kind of like, boring is good. Boring means we're getting better, we're invisible. That's infrastructure that's in the weeds, that's in between the toes details. It's the stuff that, you know, people we have to get done. So, you know, you look at their 40 new data sources with data Wrangler 50, new app flow connectors, Redshift Auto Cog, this is boring. Good important shit Dave. The governance, you gotta get it and the governance is gonna be key. So, so to me, this may not jump off the page. Adam's keynote also felt a little bit of, we gotta get these gaps done in a good way. So I think that's a very positive sign. >>Now going back to the bigger picture, I think the real question is can there be another independent cloud data cloud? And that's the, to me, what I try to get at my story and you're breaking analysis kind of hit a home run on this, is there's interesting opportunity for an independent data cloud. Meaning something that isn't aws, that isn't, Google isn't one of the big three that could sit in. And so let me give you an example. I had a conversation last night with a bunch of ex Amazonian engineering teams that left the conversation was interesting, Dave. They were like talking, well data bricks and Snowflake are basically batch, okay, not transactional. And you look at Aerospike, I can see their booth here. Transactional data bases are hot right now. Streaming data is different. Confluence different than data bricks. Is data bricks good at hosting? >>No, Amazon's better. So you start to see these kinds of questions come up where, you know, data bricks is great, but maybe not good for this, that and the other thing. So you start to see the formation of swim lanes or visibility into where people might sit in the ecosystem, but what came out was transactional. Yep. And batch the relationship there and streaming real time and versus you know, the transactional data. So you're starting to see these new things emerge. Andy, what do you, what's your take on this? You're following this closely. This seems to be the alpha nerd conversation and it all points to who's gonna have the best data cloud, say data, super clouds, I call it. What's your take? >>Yes, data cloud is important as well. But also the computational that goes on top of it too, right? Because when, when the data is like unstructured data, it's that much of a huge data, it's going to be hard to do that with a low model, you know, compute power. But going back to your data point, the training of the AIML models required the batch data, right? That's when you need all the, the historical data to train your models. And then after that, when you do inference of it, that's where you need the streaming real time data that's available to you too. You can make an inference. One of the things, what, what they also announced, which is somewhat interesting, is you saw that they have like 700 different instances geared towards every single workload. And there are some of them very specifically run on the Amazon's new chip. The, the inference in two and theran tr one chips that basically not only has a specific instances but also is run on a high powered chip. And then if you have that data to support that, both the training as well as towards the inference, the efficiency, again, those numbers have to be proven. They claim that it could be anywhere between 40 to 60% faster. >>Well, so a couple things. You're definitely right. I mean Snowflake started out as a data warehouse that was simpler and it's not architected, you know, in and it's first wave to do real time inference, which is not now how, how could they, the other second point is snowflake's two or three years ahead when it comes to governance, data sharing. I mean, Amazon's doing what always does. It's copying, you know, it's customer driven. Cuz they probably walk into an account and they say, Hey look, what's Snowflake's doing for us? This stuff's kicking ass. And they go, oh, that's a good idea, let's do that too. You saw that with separating compute from storage, which is their tiering. You saw it today with extending data, sharing Redshift, data sharing. So how does Snowflake and data bricks approach this? They deal with ecosystem. They bring in ecosystem partners, they bring in open source tooling and that's how they compete. I think there's unquestionably an opportunity for a data cloud. >>Yeah, I think, I think the super cloud conversation and then, you know, sky Cloud with Berkeley Paper and other folks talking about this kind of pre, multi-cloud era. I mean that's what I would call us right now. We are, we're kind of in the pre era of multi-cloud, which by the way is not even yet defined. I think people use that term, Dave, to say, you know, some sort of magical thing that's happening. Yeah. People have multiple clouds. They got, they, they end up by default, not by design as Dell likes to say. Right? And they gotta deal with it. So it's more of they're inheriting multiple cloud environments. It's not necessarily what they want in the situation. So to me that is a big, big issue. >>Yeah, I mean, again, going back to your snowflake and data breaks announcements, they're a data company. So they, that's how they made their mark in the market saying that, you know, I do all those things, therefore you have, I had to have your data because it's a seamless data. And, and Amazon is catching up with that with a lot of that announcements they made, how far it's gonna get traction, you know, to change when I to say, >>Yeah, I mean to me, to me there's no doubt about Dave. I think, I think what Swamee is doing, if Amazon can get corner the market on out of the box ML and AI capabilities so that people can make it easier, that's gonna be the end of the day tell sign can they fill in the gaps. Again, boring is good competition. I don't know mean, mean I'm not following the competition. Andy, this is a real question mark for me. I don't know where they stand. Are they more comprehensive? Are they more deeper? Are they have deeper services? I mean, obviously shows to all the, the different, you know, capabilities. Where, where, where does Amazon stand? What's the process? >>So what, particularly when it comes to the models. So they're going at, at a different angle that, you know, I will help you create the models we talked about the zero and the whole data. We'll get the data sources in, we'll create the model. We'll move the, the whole model. We are talking about the ML ops teams here, right? And they have the whole functionality that, that they built ind over the year. So essentially they want to become the platform that I, when you come in, I'm the only platform you would use from the model training to deployment to inference, to model versioning to management, the old s and that's angle they're trying to take. So it's, it's a one source platform. >>What about this idea of technical debt? Adrian Carro was on yesterday. John, I know you talked to him as well. He said, look, Amazon's Legos, you wanna buy a toy for Christmas, you can go out and buy a toy or do you wanna build a, to, if you buy a toy in a couple years, you could break and what are you gonna do? You're gonna throw it out. But if you, if you, if part of your Lego needs to be extended, you extend it. So, you know, George Gilbert was saying, well, there's a lot of technical debt. Adrian was countering that. Does Amazon have technical debt or is that Lego blocks analogy the right one? >>Well, I talked to him about the debt and one of the things we talked about was what do you optimize for E two APIs or Kubernetes APIs? It depends on what team you're on. If you're on the runtime gene, you're gonna optimize for Kubernetes, but E two is the resources you want to use. So I think the idea of the 15 years of technical debt, I, I don't believe that. I think the APIs are still hardened. The issue that he brings up that I think is relevant is it's an end situation, not an or. You can have the bag of Legos, which is the primitives and build a durable application platform, monitor it, customize it, work with it, build it. It's harder, but the outcome is durability and sustainability. Building a toy, having a toy with those Legos glued together for you, you can get the play with, but it'll break over time. Then you gotta replace it. So there's gonna be a toy business and there's gonna be a Legos business. Make your own. >>So who, who are the toys in ai? >>Well, out of >>The box and who's outta Legos? >>The, so you asking about what what toys Amazon building >>Or, yeah, I mean Amazon clearly is Lego blocks. >>If people gonna have out the box, >>What about Google? What about Microsoft? Are they basically more, more building toys, more solutions? >>So Google is more of, you know, building solutions angle like, you know, I give you an API kind of thing. But, but if it comes to vertical industry solutions, Microsoft is, is is ahead, right? Because they have, they have had years of indu industry experience. I mean there are other smaller cloud are trying to do that too. IBM being an example, but you know, the, now they are starting to go after the specific industry use cases. They think that through, for example, you know the medical one we talked about, right? So they want to build the, the health lake, security health lake that they're trying to build, which will HIPPA and it'll provide all the, the European regulations, the whole line yard, and it'll help you, you know, personalize things as you need as well. For example, you know, if you go for a certain treatment, it could analyze you based on your genome profile saying that, you know, the treatment for this particular person has to be individualized this way, but doing that requires a anomalous power, right? So if you do applications like that, you could bring in a lot of the, whether healthcare, finance or what have you, and then easy for them to use. >>What's the biggest mistake customers make when it comes to machine intelligence, ai, machine learning, >>So many things, right? I could start out with even the, the model. Basically when you build a model, you, you should be able to figure out how long that model is effective. Because as good as creating a model and, and going to the business and doing things the right way, there are people that they leave the model much longer than it's needed. It's hurting your business more than it is, you know, it could be things like that. Or you are, you are not building a responsibly or later things. You are, you are having a bias and you model and are so many issues. I, I don't know if I can pinpoint one, but there are many, many issues. Responsible ai, ethical ai. All >>Right, well, we'll leave it there. You're watching the cube, the leader in high tech coverage here at J three at reinvent. I'm Jeff, Dave Ante. Andy joining us here for the critical analysis and breaking down the commentary. We'll be right back with more coverage after this short break.

(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)

(bright music) >> Hello, everyone. Welcome back to live coverage day two or day one, day two for theCUBE, day one for the event. I'm John Furrier, host of theCUBE. It's the keynote analysis segment. Adam just finished coming off stage. I'm here with Dave Vellante and Zeus Kerravala, with principal analyst at ZK Research, Zeus, it's great to see you. Dave. Guys, the analysis is clear. AWS is going NextGen. You guys had a multi-day analyst sessions in on the pre-briefs. We heard the keynote, it's out there. Adam's getting his sea legs, so to speak, a lot of metaphors around ocean. >> Yeah. >> Space. He's got these thematic exploration as he chunked his keynote out into sections. Zeus, a lot of networking in there in terms of some of the price performance, specialized instances around compute, this end-to-end data services. Dave, you were all over this data aspect going into the keynote and obviously, we had visibility into this business transformation theme. What's your analysis? Zeus, we'll start with you. What's your take on what Amazon web service is doing this year and the keynote? What's your analysis? >> Well, I think, there was a few key themes here. The first one is I do think we're seeing better integration across the AWS portfolio. Historically, AWS makes a lot of stuff and it's not always been easy to use say, Aurora and Redshift together, although most customers buy them together. So, they announce the integration of that. It's a lot tighter now. It's almost like it could be one product, but I know they like to keep the product development separately. Also, I think, we're seeing a real legitimization of AWS in a bunch of areas where people said it wasn't possible before. Last year, Nasdaq said they're running in the cloud. The Options Exchange today announced that they're going to be moving to the cloud. Contact centers running the cloud for a lot of real time voice. And so, things that we looked at before and said those will never move to the cloud have now moved to the cloud. And I think, my third takeaway is just AWS is changing and they're now getting into areas to allow customers to do things they couldn't do before. So, if you look at what they're doing in the area of AI, a lot of their AI and ML services before were prediction. And I'm not saying you need an AI, ML to do prediction, was certainly a lot more accurate, but now they're getting into generative data. So, being able to create data where data didn't exist before and that's a whole new use case for 'em. So, AWS, I think, is actually for all the might and power they've had, it's actually stepping up and becoming a much different company now. >> Yeah, I had wrote that post. I had a one-on-one day, got used of the transcript with Adam Selipsky. He went down that route of hey, we going to change NextGen. Oh, that's my word. AWS Classic my word. The AWS Classic, the old school cloud, which a bunch of Lego blocks, and you got this new NextGen cloud with the ecosystems emerging. So, clearly, it's Amazon shifting. >> Yeah. >> But Dave, your breaking analysis teed out the keynote. You went into the whole cost recovery. We heard Adam talk about macro at the beginning of his keynote. He talked about economic impact, sustainability, big macro issues. >> Yeah. >> And then, he went into data and spent most of the time on the keynote on data. Tools, integration, governance, insights. You're all over that. You had that, almost your breaking analysis almost matched the keynote, >> Yeah. >> thematically, macro, cost savings right-sizing with the cloud. And last night, I was talking to some of the marketplace people, we think that the marketplace might be the center where people start managing their cost better. This could have an impact on the ecosystem if they're not in in the marketplace. So, again, so much is going on. >> What's your analogy? >> Yeah, there's so much to unpack, a couple things. One is we get so much insight from theCUBE community plus your sit down 101 with Adam Selipsky allowed us to gather some nuggets, and really, I think, predict pretty accurately. But the number one question I get, if I could hit the escape key a bit, is what's going to be different in the Adam Selipsky era that was different from the Jassy era. Jassy was all about the primitives. The best cloud. And Selipsky's got to double down on that. So, he's got to keep that going. Plus, he's got to do that end-to-end integration and he's got to do the deeper business integration, up the stack, if you will. And so, when you're thinking about the keynote and the spirit of keynote analysis, we definitely heard, hey, more primitives, more database features, more Graviton, the network stuff, the HPC, Graviton for HPC. So, okay, check on that. We heard some better end-to-end integration between the elimination of ETL between Aurora and Redshift. Zeus and I were sitting next to each other. Okay, it's about time. >> Yeah. >> Okay, finally we got that. So, that's good. Check. And then, they called it this thing, the Amazon data zones, which was basically extending Redshift data sharing within your organization. So, you can now do that. Now, I don't know if it works across regions. >> Well, they mentioned APIs and they have the data zone. >> Yep. And so, I don't know if it works across regions, but the interesting thing there is he specifically mentioned integration with Snowflake and Tableau. And so, that gets me to your point, at the end of the day, in order for Amazon, and this is why they win, to succeed, they've got to have this ecosystem really cranking. And that's something that is just the secret sauce of the business model. >> Yeah. And it's their integration into that ecosystem. I think, it's an interesting trend that I've seen for customers where everybody wanted best of breed, everybody wanted disaggregated, and their customers are having trouble now putting those building blocks together. And then, nobody created more building blocks than AWS. And so, I think, under Adam, what we're seeing is much more concerted effort to make it easier for customers to consume those building blocks in an easy way. And the AWS execs >> Yeah. >> I talked to yesterday all committed to that. It's easy, easy, easy. And I think that's why. (Dave laughing) Yeah, there's no question they've had a lead in cloud for a long time. But if they're going to keep that, that needs to be upfront. >> Well, you're close to this, how easy is it? >> Yeah. >> But we're going to have Adrian Cockcroft (Dave laughing) on at the end of the day today, go into one analysis. Now, that- >> Well, less difficult. >> How's that? (indistinct) (group laughing) >> There you go. >> Adrian retired from Amazon. He's a CUBE analyst retiree, but he had a good point. You can buy the bag of Lego blocks if you want primitives >> Yeah. >> or you can buy the toy that's glued together. And it works, but it breaks. And you can't really manage it, and you buy a new one. So, his metaphor was, okay, if the primitives allow you to construct a durable solutions, a lot harder relative to rolling your own, not like that, but also the simplest out-of-the box capability is what people want. They want solutions. We call Adam the solutions CEO. So, I think, you're going to start to see this purpose built specialized services allow the ecosystem to build those toys, so that the customers can have an out-of-the box experience while having the option for the AWS Classic, which is if you want durability, you want to tune it, you want to manage it, that's the way to go for the hardcore. Now, can be foundational, but I just see the solutions things being very much like an out-of-the-box. Okay, throw away, >> Yeah. >> buy a new toy. >> More and more, I'm saying less customers want to be that hardcore assembler of building blocks. And obviously, the really big companies do, but that line is moving >> Yeah. >> and more companies, I think, just want to run their business and they want those prebuilt solutions. >> We had to cut out of the keynote early. But I didn't hear a lot about... The example that they often use is Amazon Connect, the call center solution. >> Yeah. >> I didn't hear a lot to that in the keynote. Maybe it's happening right now, but look, at the end of the day, suites always win. The best of breed does well, (John laughing) takes off, generate a couple billion, Snowflake will grow, they'll get to 10 billion. But you look at Oracle, suites work. (laughs) >> Yeah. >> What I found interesting about the keynote is that he had this thematic exploration themes. First one was space that was like connect the dot, the nebula, different (mumbles) lens, >> Ocean. >> ask the right questions. (Dave laughing) >> Ocean was security which bears more, >> Yeah. >> a lot more needed to manage that oxygen going deep. Are you snorkeling? Are you scuba diving? Barely interesting amount of work. >> In Antarctica. >> Antarctica was the performance around how you handle tough conditions and you've got to get that performance. >> Dave: We're laughing, but it was good. >> But the day, the Ocean Day- >> Those are very poetic. >> I tweeted you, Dave, (Dave laughing) because I sit on theCUBE in 2011. I hate hail. (Dave laughing) It's the worst term ever. It's the day the ocean's more dynamic. It's a lot more flowing. Maybe 10 years too soon, Dave. But he announces the ocean theme and then says we have a Security Lake. So, like lake, ocean, little fun on words- >> I actually think the Security Lake is pretty meaningful, because we were listening to talk, coming over here talking about it, where I think, if you look at a lot of the existing solutions, security solutions there, I describe 'em as a collection of data ponds that you can view through one map, but they're not really connected. And the amount of data that AWS holds now, arguably more than any other company, if they're not going to provide the Security Lake, who is? >> Well, but staying >> Yeah. >> on security for a second. To me, the big difference between Azure and Amazon is the ecosystem. So, CrowdStrike, Okta, Zscaler, name it, CyberArk, Rapid7, they're all part of this ecosystem. Whereas Microsoft competes with all of those guys. >> Yes. Yeah. >> So it's a lot more white space than the Amazon ecosystem. >> Well, I want to get you guys to take on, so in your reaction, because I think, my vision of what what's happening here is that I think that whole data portion's going to be data as code. And I think, the ecosystem harvests the data play. If you look at AWS' key announcements here, Security Lake, price performance, they're going to optimize for those kinds of services. Look at security, okay, Security Lake, GuardDuty, EKS, that's a Docker. Docker has security problems. They're going inside the container and looking at threat detection inside containers with Kubernetes as the runtime. That's a little nuance point, but that's pretty significant, Dave. And they're now getting into, we're talking in the weeds on the security piece, adding that to their large scale security footprint. Security is going to be one of those things where if you're not on the inside of their security play, you're probably going to be on the outside. And of course, the price performance is going to be the killer. The networking piece surprise me. Their continuing to innovate on the network. What does that mean for Cisco? So many questions. >> We had Ajay Patel on yesterday for VMware. He's an awesome middleware guy. And I was asking about serverless and architectures. And he said, "Look, basically, serverless' great for stateless, but if you want to run state, you got to have control over the run time." But the point he made was that people used to think of running containers with straight VMs versus Fargate or Knative, if you choose, or serverless. They used to think of those as different architectures. And his point was they're all coming together. And it's now you're architecting and calling, which service you need. And that's how people are thinking about future architectures, which I think, makes a lot of sense. >> If you are running managed Kubernetes, which everyone's doing, 'cause no one's really building it in-house themselves. >> No. >> They're running it as managed service, skills gaps and a variety of other reasons. This EKS protection is very interesting. They're managing inside and outside the container, which means that gives 'em visibility on both sides, under the hood and inside the application layer. So, very nuanced point, Zeus. What's your reaction to this? And obviously, the networking piece, I'd love to get your thought. >> Well, security, obviously, it's becoming a... It's less about signatures and more of an analytics. And so, things happen inside the container and outside the container. And so, their ability to look on both sides of that allows you to happen threats in time, but then also predict threats that could happen when you spin the container up. And the difficulty with the containers is they are ephemeral. It's not like a VM where it's a persistent workload that you can do analysis on. You need to know what's going on with the container almost before it spins up. >> Yeah. >> And that's a much different task. So, I do think the amount of work they're doing with the containers gives them that entry into that and I think, it's a good offering for them. On the network side, they provide a lot of basic connectivity. I do think there's a role still for the Ciscos and the Aristas and companies like that to provide a layer of enhanced network services that connects multicloud. 'Cause AWS is never going to do that. But they've certainly, they're as legitimate network vendor as there is today. >> We had NetApp on yesterday. They were talking about latency in their- >> I'll tell you this, the analyst session, Steven Armstrong said, "You are going to hear us talk about multicloud." Yes. We're not going to necessarily lead with it. >> Without a mention. >> Yeah. >> But you said it before, never say never with Amazon. >> Yeah. >> We talk about supercloud and you're like, Dave, ultimately, the cloud guys are going to get into supercloud. They have to. >> Look, they will do multicloud. I predict that they will do multicloud. I'll tell you why. Just like in networking- >> Well, customers are asking for it. >> Well, one, they have the, not by design, but by defaulter and multiple clouds are in their environment. They got to deal with that. I think, the supercloud and sky cloud visions, there will be common services. Remember networking back in the old days when Cisco broke in as a startup. There was no real shortest path, first thinking. Policy came in after you connected all the routers together. So, right now, it's going to be best of breed, low latency, high performance. But I think, there's going to be a need in the future saying, hey, I want to run my compute on the slower lower cost compute. They already got segmentation by their announcements today. So, I think, you're going to see policy-based AI coming in where developers can look at common services across clouds and saying, I want to lock in an SLA on latency and compute services. It won't be super fast compared to say, on AWS, with the next Graviton 10 or whatever comes out. >> Yeah. >> So, I think, you're going to start to see that come in. >> Actually, I'm glad you brought Graviton up too, because the work they're doing in Silicon, actually I think, is... 'Cause I think, the one thing AWS now understands is some things are best optimized in Silicon, some at software layers, some in cloud. And they're doing work on all those layers. And Graviton to me is- >> John: Is a home run. >> Yeah. >> Well- >> Dave, they've got more instances, it's going to be... They already have Gravitons that's slower than the other versions. So, what they going to do, sunset them? >> They don't deprecate anything ever. So, (John laughing) Amazon paid $350 million. People believe that it's a number for Annapurna, which is like one of the best acquisitions in history. (group laughing) And it's given them, it's put them on an arm curve for Silicon that is blowing away Intel. Intel's finally going to get Sapphire Rapids out in January. Meanwhile, Amazon just keeps spinning out new Gravitons and Trainiums. >> Yeah. >> And so, they are on a price performance curve. And like you say, no developer ever wants to run on slower hardware, ever. >> Today, if there's a common need for multicloud, they might say, hey, I got the trade off latency and performance on common services if that's what gets me there. >> Sure. >> If there's maybe a business case to do that. >> Well, that's what they're- >> Which by the way, I want to.... Selipsky had strong quote I thought was, "If you're looking to tighten your belt, the cloud is the place >> Yeah. >> to do it." I thought >> I tweeted that. >> that was very strong. >> Yeah. >> Yeah. >> And I think, he's right. And then, the other point I want to make on that is, I think, I don't have any data on this, but I believe believe just based on some of the discussions I've had that most of Amazon's revenue is on demand. Paid by the drink. Those on demand customers are at risk, 'cause they can go somewhere else. So, they're trying to get you into optimized pricing, whether it's reserved instances or one year or three-year subscriptions. And so, they're working really hard at doing that. >> My prediction on that is that's a great point you brought up. My prediction is that the cost belt tightening is going to come in the marketplace, is going to be a major factor as companies want to get their belts tighten. How they going to do that, Dave? They're going to go in the marketplace saying, hey, I already overpaid a three-year commitment. Can I get some cohesively in there? Can I get some of this or that and the other thing? >> Yep. >> You're going to start to see the vendors and the ecosystem. If they're not in the marketplace, that's where I think, the customers will go. There are other choices to either cut their supplier base or renegotiate. I think, it's going to happen in the marketplace. Let's watch. I think, we're going to watch that grow. >> I actually think the optimization services that AWS has to help customers lower spend is a secret sauce for them that they... Customers tell me all the time, AWS comes in, they'll bring their costs down and they wind up spending more with them. >> Dave: Yeah. >> And the other cloud providers don't do that. And that has been almost a silver bullet for them to get customers to stay with them. >> Okay. And this is always the way. You drop the price of storage, you drop the price of memory, you drop the price of compute, people buy more. And in the question, long term is okay. And does AWS get commoditized? Is that where they're going? Or do they continue to thrive up the stack? John, you're always asking people about the bumper sticker. >> Hold on. (John drowns out Dave) Before we get the bumper sticker, I want to get into what we missed, what they missed on the keynote. >> Yeah, there are some blind spots. >> I think- >> That's good call. >> Let's go around the horn and think what did they miss? I'll start, I think, they missed the developer productivity angle. Supply chain software was not talked about at all. We see that at all the other conferences. I thought that could have been weaved in. >> Dave: You mean security in the supply chain? >> Just overall developer productivity has been one of the most constant themes I've seen at events. Who are building the apps? Who are the builders? What are they actually doing? Maybe Werner will bring that up on his last day, but I didn't hear Adam talk about it all, developer productivity. What's your take in this? >> Yeah, I think, on the security side, they announced security data lake. I think, the other cloud providers do a better job of providing insights on how they do security. With AWS, it's almost a black hole. And I know there's a careful line they walk between what they do, what their partners do. But I do think they could be a little clearer on how they operate, much like Azure and GCP. They announce a lot of stuff on how their operations works and things like that. >> I think, platform across cloud is definitely a blind spot for these guys. >> Yeah. >> I think, look at- >> But none of the cloud providers have embraced that, right? >> It's true. >> Yeah. >> Maybe Google a little bit >> Yeah. >> and Microsoft a little bit. Certainly, AWS hasn't at this point in time, but I think, they perceive the likes of Mongo and Snowflake and Databricks, and others as ISVs and they're not. They're platform players that are building across clouds. They're leveraging, they're building superclouds. So, I think that's an opportunity for the ecosystem. And very curious to see how Amazon plays there down the stream. So, John, what do you think is the bumper sticker? We're only in day one and a half here. What do you think so far the bumper sticker is for re:Invent 2022? >> Well, to me, the day one is about infrastructure performance with the whole what's in the data center? What's at the chip level? Today was about data, specialized services, and security. I think that was the key theme here. And then, that's going to sequence into how they're going to reorganize their ecosystem. They have a new leader, Ruba Borno, who's going to be leading the charge. They've integrated all their bespoke fragmented partner network pieces into one leadership. That's going to be really important to hear that. And then, finally, Werner for developers and event-based services, micro services. What that world's going on, because that's where the developers are. And ultimately, they build the app. So, you got infrastructure, data, specialized services, and security. Machine learning with Swami is going to be huge. And again, how do developers code it all up is going to be key. And is it the bag of Legos or the glued toy? (Dave chuckles) So, what do you want? Out-of-the-box or you want to build your own? >> And that's the bottom line is connecting those dots. All they got to be is good enough. I think, Zeus, to your point, >> Yep. >> if they're just good enough, less complicated, the will keep people on the base. >> Yeah. I think, the bumper stickers, the more you buy, the more you're saving. (John laughing) Because from an operational perspective, they are trying to bring down the complexity level. And with their optimization services and the way their credit model works, I do think they're trending down that path. >> And my bumper sticker's ecosystem, ecosystem, ecosystem. This company has 100,000 partners and that is a business model secret weapon. >> All right, there it is. The keynote announced. More analysis coming up. We're going to have the leader of (indistinct) coming up next, here on to break down their perspective, you got theCUBE's analyst perspective here. Thanks for watching. Day two, more live coverage for the next two more days, so stay with us. I'm John Furrier with Dave Vellante and Zeus Kerravala here on theCUBE. Be right back. (bright music)

>>Hey everyone. Welcome back to Las Vegas. The cube is live at the Venetian Expo Center for AWS Reinvent 2022. There are thousands and thousands and thousands of people here joining myself, Lisa Martin at Dave Valante. David, it's great to see the energy of day one alone. People are back, they're ready to be back. They're ready to hear from AWS and what it's gonna announce to. >>Yeah, all through the pandemic. Of course, we've talked about digital transformation, but the conversation is evolving beyond that to business transformation now, deeper integration of the cloud to really transform fundamental business operations and And that's a new era. >>It is a new era. It's exciting. We've got a couple of guests that we're gonna unpack that with. Anan. Beji joins us, the President Digital Business Services at HCL Tech and Prar, SVP and Global head of AWS business unit. Also from HCL Tech. Guys, welcome. Thank >>You. Thank you, >>Thank you. >>Let's talk about some of the latest trends anon. We'll start with you. What are some of the latest trends in digitalization, especially as it relates to cloud adoption? What are you hearing out in the marketplace? >>Yeah, I think you said it right. The post pandemic, every industry, every enterprise and every industry realize that for resilience, for their ability to change and adapt change and their ability to increase, you know, velocity of change so that they can move fast and keep up the expectations of their consumers, their partners, their employees, they need to have composability at the core and resilience at the core. And so, digital transformation became all about the ability to change, an ability to pivot faster. Now, it's easier said than done, right? Larger enterprises, especially as you move into complex regulated industries, you know, oil and gas, manufacturing, life sciences, healthcare, utilities, these are industries that are not easy to change. They're not adaptable to change, and yet they had to really become more adaptable. And they saw cloud as an enabler to, to all of that, right? So they started looking at every area of their business, business processes that make up their value chains and really look at how can they increase the adaptability and the ability to change these value chains so that they can engage with their customers better, their partners, better their employees better, and also build some of the composability. >>And what might mean that is that just kind of like Lego blocks, they don't have to make changes that are sweeping and big that are difficult to make, but make them in parts so that they can make them again and again. So velocity of change becomes important. Clouds become an enabler to all of this. And so if I look at the last four years, every industry, whether regulated or not b2c, B2B to C, B2B is adopting cloud for digital acceleration. >>I'm curious to what you're seeing on the front lines, given the macro headwinds. You mentioned business resilience and during the pandemic, it was a lot of CIOs told us, wow, we were, we were kind of focused on disaster recovery, but our business wasn't resilient. We were really optimizing for efficiency. And then they started to okay, build in that business resilience. But now you got the economic headwinds. Yes. People are tapping their brakes a little bit. There's some uncertainty, a longer sales cycle, even the cloud's not immune. Yeah. Even though it's still growing at 30% plus per year. What are you guys seeing in the field with the AWS partnership? How are customers, you know, dealing with some of those more strategic transformation projects? Yeah, >>Yeah. So you know, first off, one thing that's changed and is different is every industry realizes that there is no choice. They don't have a choice to not be resilient. They don't have a choice to not be adaptable. The pandemic has taught them that the markets and the macros are increasingly changing supply chains. It's changing customer behavior for their own industries. It's changing their pricing and their cost models. And for all of that, they need to continue on their digital journeys. Now, what's different though is they wanna prioritize. They wanna prioritize and do more with less. They want to adapt faster, but also make sure that they don't, they don't just try to do everything together. And so there's a lot of focus on what do we prioritize? How do we leverage cloud to move faster, you know, and cheaper in terms of our change. >>And also to decide where do we consume and where do we compose? We'll talk a little bit more about that. There are certain things that you don't want to invent yourself. You can consume from cloud providers, whether it's business features, whether it is cloud capabilities. And so it's, there is a shift from adopting cloud just for cost takeout and just for resilience, but also for composability, which means let's consume what I can consume from the cloud and really build those features faster. So squeeze the go to market time, squeeze the time to market and squeeze the price to market, right? So that's the >>Change and really driving those business outcomes. As we talked about Absolut ard, talk to us about how hcl tech and AWS are working together. How are you enabling customers to achieve what an was talking about? >>Oh, absolutely. I mean, our partnership has started almost 10 years back, but over the last one year, we have created what we call as AWS dedicated business unit to look at end to end stock from an AWS perspective. So what we see in the market as a explained is more drive from clients for optimization, driving, app modernization, driving consolidation, looking at the cost, sustainability angles, looking at the IOT angle, manufacturing platforms, the industry adoption. All this is actually igniting the way the industry would look at AWS and as well as the partnership. So from an HCL tech and AWS partnership, we're actually accelerating most of these conversations by building bespoke accelerated industry solutions. So what I mean is, for example, there is an issue with a manufacturing plant and take Covid situation, people can't get into a a manufacturing plant. So how can AWS help put it in the cloud, accelerate those conversations. So we are building those industry specific solutions so that it can be everybody from a manufacturing sector can adopt and actually go to market. As well as you can access all this applications once it is in the cloud from anywhere, any device with a scalable options. That's where our partnership is actually igniting lot of cloud conversations and playing conversations in the market. So we see a lot of traction there. Lisa, on >>That, incredibly important during the last couple of years alone. >>Absolutely. I mean, last couple of years have been groundbreaking, right? Especially with the covid, for example, Amazon Connect, we use, we used Amazon Connect to roll out, you know, call center at the cloud, right? So you don't have to walk into an office, for example. People are working in the banking sector, especially in the trading platform. They were, they were not able to get there. So, but they need to make calls. How do you do the customer service? So Amazon Connect came right at the junction, so call center in the cloud and you can access, dial the number so the customer don't feel the pain of, you know, somebody not answering. It's accessible. That's where the partnership or the HCL tech partnership and AWS comes into play because we bring the scale, the skill set capability with the services of, you know, aws, Amazon, and that forms a concrete story for the client, right? That's one such example. And you know, many such examples are in the market that we are accelerating in the, in the discussions. >>And connect is a good example. Lisa, we were talking earlier about Amazon doubling down on the primitives, but also moving up up market as well, up chain up the value chain. And it needs partners like HCL to be able to go into various industries and apply that effectively. Absolutely. And that's where business transformation comes >>In. Absolutely. Absolutely. I think some of the aspects that we are looking at is, you know, while we do most of this cloud transformation initiatives from an tech perspective, what we are doing is we are encompassing them into a story, which we call it as cloud smart, right? So we are calling it as cloud smart, which is a go-to market offering from Atcl Tech, where the client doesn't have to look at each of these services from various vendors. So it's a one stop shop, right? From strategy consulting, look, implementation, underpinned by app modernization, consolidation, and the operational. So we do that as end to end service with our offerings, which is why helping us actually accelerate conversations on the crowd. What happen is the clients are also building these capabilities more and more often. You see a lot of new services are being added to aws, so not many clients are aware of it. So it is the responsibility of system integrator like us to make them aware and bring it into a shape where the client can consume in a low cost option, in an optimized way. That's where I think it's, it's, it's working out very well for us. With the partnership of, so >>You curate those services that you know will fit the customer's business. You, you know, the ingredients that you could put together, the, the dinner. >>Absolutely. You're preparing a dish, right? So you're preparing a dish, you know where the ingredients are. So the ingredients are supplied by aws. So you need to prepare a pasta dish, right? So you, you how spicy you want to make it howland, you want to make it, you know what source you want to use. How do you bring all those elements together? That's what, you know, tech has been focusing on. >>And you use the word curation, right? Curation is really industry process down, depending on your industry, every industry, every enterprise, there are things that are differentiating them. There's a business processes that differentiate you and there are business processes that don't necessarily differentiate you but are core to you. For example, if you're a retailer, you know, you're retailing, you're merchandising, how you price your products, how you market your products, your supply chains, those differentiate you. How you run your general ledger, your accounting, your payables. HR is core to your business but doesn't differentiate you. And the choices you make in the cloud for each of these areas are different. What differentiates you? You compose what doesn't differentiate you consume because you don't want to try and compose what >>Telco Exactly. Oh my gosh. >>Our biggest examples are in Telco, right? Right. Their omnichannel marketing, you know, how they connect with their consumers, how they do their billing systems, how they do their pricing systems. Those are their differentiations and things that don't they want to consume. And that's where cloud adoption needs to come with really a curation framework. We call it the Phoenix framework, which defines what differentiates you versus not. And based on that, what are the architectural choices you make at the applications layer, the integration layer, the data layer, and the infrastructure layer all from aws and how do you make those choices? >>Talk about a customer example anon that really articulates that value. >>Yeah, I'll give you an example that sort of, everybody can relate to a very large tools company that manufactures tools that we all use at home for, you know, remodeling our houses, building stuff, building furniture. Their business post pandemic dramatically shifted in every way possible. Nobody was going anymore to Home Depot and Lowe's to buy their tools, their online business surge by 200%. Their supply chains were changing because their manufacturers originally were in China and Malaysia. They were shifting a lot of that base to Taiwan and Germany and Latin America. Their pricing model was changing. Their last mile deliveries were changing cuz they were not used to delivering you and me last mile deliveries. So every aspect of their business was changing. They hadn't thought of their business in the same way, but guess what? That business was growing, but the needs were changing and they needed to rethink every value chain in their business. >>And so they had to adopt cloud. They leverage AWS at their core to rethink every part of their business. Rebuilding their supply chain applications, modernizing their warehouse management systems, modernizing their pricing systems, modernizing their sales and marketing platforms, every aspect you can think of and all of that within 24 months. Cuz otherwise they would lose market share, you know, in any given market. And all of this, while they were, you know, delivering their day to day business, they were manufacturing the goods and they were shipping products. So that was quite a lot to achieve in 24 months. And that's not just one example is across industries, examples like that that we have. That's >>One of the best business transformation examples I think I've heard. >>Absolutely. Absolutely. And so cloud does need to start with a business transformation objective. And that's what's happening to the cloud. It's changing away from an infrastructure consolidation discussion to business task. >>Because I know you guys have a theater session tomorrow on, on continuous modern, it was experiencing cloud transformation and continuous modernization. That's the theme. Pre-cloud. It was just a, you'd, you'd live, you'd rip and replace your infrastructure and it was a big application portfolio assessment and rationalization. It was just, it just became this years long, you know, like an SAP installation. Yes. How has cloud changed that and what's, tell us more about that session and that continuous modernization. Yeah, >>So, so we are doing a John session with a client on how HCL Tech helped the client in terms of transforming the landscape and adopting cloud much faster, you know, into the ecosystem. So what we are currently doing is, so it's a continuous process. So when we talk about cloud adoption transformation, it doesn't stop there. So it, it needs to keep evolving. So what we came up with a framework for the all such clients who are on the cloud transformation part need to look at which we call it a smart waste cloud, cloud smart. Where once it is in the clouds, smart waste to cloud for cloud and in the cloud. So what happens is, when it is to cloud, what do you do? What are the accelerators? What are the frameworks? Smart waste for clouds? How do you look at the governance of it? >>Okay? Consolidation activities of it, once it is in the cloud, how do we optimize, what do you look at? Security aspects, et cetera. So the client doesn't have to go to multiple ecosystem partners to look at it. So he is looking at one such service provider who can actually encompass and give all this onto the plate in a much more granular fashion with accelerated approach. So we build accelerated solutions frameworks, which helps the client to actually pick and choose in a much lower cost, I think. And it has to be a continuous modernization for the client. So why we are calling it as a continuous modernization is we are also also creating what we call cloud foundries and factories. What happens is the client can look at not only in a transformation journey, but also futuristic when there are new services are adapted, how this transformation and factories helping them in a lower cost option and driving that a acceleration story. So we are addressing it in multiple ways. One on the transformation front, one on the TCO front, one on the AX accelerated front, one on the operational front. So all this combined into one single framework, which is what is a continuous modernization of clouded option from xgl tech. >>When you apply this framework with customers, how do you deal with technical debt? Can you avoid technical debt? Can you hide technical debt? Or is it like debt and taxes? We're always gonna have technical debt because Amazon, you know, they'll talk about, they don't ever deprecate anything. Yeah. You know, are they gonna, are we gonna see Amazon take on tech? How do you avoid that? Or at least shield the customer for that technical debt. >>So every cio, right? Key ambitions are digital cloud, TCO optimization, sustainability. So we have a framework for that. So every CIO will look at, okay, I wanna spend, but I want to be optimized. My TCO should not go up. So that's where a system integrator like us comes. We have AOP story where, which does the complete financial analysis of your cloud adoption as to what estate and what technical client already has. How can we optimize that and how can we, how can we overlay on top of that our own services to make it much more optimized solution for the client? And there are several frameworks that we have defined for the CIO organizations where the CIO can actually look at some of these elements and adopt it internally within the system. You wanna pick it from there? >>Yeah, I think, I think it's, it's, it's a great question. First of all, there's a generational shift in the last three years where nobody's doing lift and shift of traditional applications or traditional data systems to the cloud. As you said, nobody's taking their technical debt to the cloud anymore. >>Business value's not there. >>There's no business value, right? The value is really being cloud native, which means you want to continuously modernize your value chains, which means your applications, your integration, your data to leverage the cloud and continuously modernize. Now you will still make priority decisions, right? Things that really differentiate you. You will modernize them through composition things that don't, you'll rather consume them, but in both factors, you're modernizing, I use the word surround and drown enterprises are surrounding their traditional, you know, environments and drowning them over a period of time. So over the next five years, you'll see more and more irrelevant legacy because the relevance is being built in the cloud, cloud for the future. That's the way I see it. >>Speaking of, take us out here, speaking of business value and on, we're almost outta time here. If there's a billboard on 1 0 1 in Palo Alto regarding HCL tech, what's the value prop? What does it say? >>It's a simple billboard. We say we are super charging our customers, our partners, our employees. We are super charging progress. And we believe that the strength that we bring from learnings of over 200,000 professionals that work at hcl working with over half of, you know, 500 of the, the largest Fortune thousands in the world is, is really bringing those learnings that we continuously look at every day that we live with, every day across all kind of regulations, all kind of industries, in adopting new technologies, in modernizing their business strategies and achieving their business transformation goals with the velocity they want. That's kind of the supercharging progress mantra, >>Super charging progress. Love it. Guys, thank you so much for joining. David, me on the program talking about, thank you for having a conversation. Our pleasure. What's going on with HCL Tech, aws, the value that you're delivering for customers. Thank you so much for your time. Thank >>You. Thank you. Thanks. Have a great time. >>Take care for our guests. I'm Lisa Martin, he's Dave Valante. You're watching The Cube, the leader in live enterprise and emerging tech coverage.

>>Set restaurants. And who says TEUs had got a little ass more skin in the game for us, in charge of his destiny? You guys are excited. Robert Worship is Chief Alumni. >>My name is Dave Ante, and I'm a long time industry analyst. So when you're as old as I am, you've seen a lot of transitions. Everybody talks about industry cycles and waves. I've seen many, many waves. Met a lot of industry executives and of a little bit of a, an industry historian. When you interview many thousands of people, probably five or 6,000 people as I have over the last half of a decade, you get to interact with a lot of people's knowledge and you begin to develop patterns. And so that's sort of what I bring is, is an ability to catalyze the conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody's expert at something. Everybody's passionate about something and has real deep knowledge about that's something well, we wanna focus in on that area and extract that knowledge and share it with our communities. This is Dave Ante. Thanks for watching the Cube. >>Hello everyone and welcome back to the Cube where we are streaming live this week from CubeCon. I am Savannah Peterson and I am joined by an absolutely stellar lineup of cube brilliance this afternoon. To my left, a familiar face, Lisa Martin. Lisa, how you feeling? End of day two. >>Excellent. It was so much fun today. The buzz started yesterday, the momentum, the swell, and we only heard even more greatness today. >>Yeah, yeah, abs, absolutely. You know, I, I sometimes think we've hit an energy cliff, but it feels like the energy is just >>Continuous. Well, I think we're gonna, we're gonna slide right into tomorrow. >>Yeah, me too. I love it. And we've got two fantastic analysts with us today, Sarge and Keith. Thank you both for joining us. We feel so lucky today. >>Great being back on. >>Thanks for having us. Yeah, Yeah. It's nice to have you back on the show. We were, had you yesterday, but I miss hosting with you. It's been a while. >>It has been a while. We haven't done anything in since, Since pre >>Pandemic, right? Yeah, I think you're >>Right. Four times there >>Be four times back in the day. >>We, I always enjoy whole thing, Lisa, cuz she's so well prepared. I don't have to do any research when I come >>Home. >>Lisa will bring up some, Oh, sorry. Jeep, I see that in 2008 you won this award for Yeah. Being just excellent and I, I'm like, Oh >>Yeah. All right Keith. So, >>So did you do his analysis? >>Yeah, it's all done. Yeah. Great. He only part, he's not sitting next to me too. We can't see it, so it's gonna be like a magic crystal bell. Right. So a lot of people here. You got some stats in terms of the attendees compared >>To last year? Yeah, Priyanka told us we were double last year up to 8,000. We also got the scoop earlier that 2023 is gonna be in Chicago, which is very exciting. >>Oh, that is, is nice. Yeah, >>We got to break that here. >>Excellent. Keith, talk to us about what some of the things are that you've seen the last couple of days. The momentum. What's the vibe? I saw your tweet about the top three things you were being asked. Kubernetes was not one of them. >>Kubernetes were, was not one of 'em. This conference is starting to, it, it still feels very different than a vendor conference. The keynote is kind of, you know, kind of all over the place talking about projects, but the hallway track has been, you know, I've, this is maybe my fifth or sixth CU con in person. And the hallway track is different. It's less about projects and more about how, how do we adjust to the enterprise? How do we Yes. Actually do enterprise things. And it has been amazing watching this community grow. I'm gonna say grow up and mature. Yes. You know, you know, they're not wearing ties yet, but they are definitely understanding kind of the, the friction of implementing new technology in, in an enterprise. >>Yeah. So ge what's your, what's been your take, We were with you yesterday. What's been the take today to take aways? >>NOMA has changed since yesterday, but a few things I think I, I missed talking about that yesterday were that, first of all, let's just talk about Amazon. Amazon earnings came out, it spooked the market and I think it's relevant in this context as well, because they're number one cloud provider. Yeah. And all, I mean, almost all of these technologies on the back of us here, they are related to cloud, right? So it will have some impact on these. Like we have to analyze that. Like will it make the open source go faster or slower in, in lieu of the fact that the, the cloud growth is slowing. Right? So that's, that's one thing that's put that's put that aside. I've been thinking about the, the future of Kubernetes. What is the future of Kubernetes? And in that context, I was thinking like, you know, I think in, when I put a pointer there, I think in tangents, like, what else is around this thing? So I think CN CNCF has been writing the success of Kubernetes. They are, that was their number one flagship project, if you will. And it was mature enough to stand on its own. It it was Google, it's Google's Borg dub da Kubernetes. It's a genericized version of that. Right? So folks who do tech deep down, they know that, Right. So I think it's easier to stand with a solid, you know, project. But when the newer projects come in, then your medal will get tested at cncf. Right. >>And cncf, I mean they've got over 140 projects Yeah. Right now. So there's definitely much beyond >>Kubernetes. Yeah. So they, I have numbers there. 18 graduated, right, 37 in incubation and then 81 in Sandbox stage. They have three stages, right. So it's, they have a lot to chew on and the more they take on, the less, you know, quality you get goes into it. Who is, who's putting the money behind it? Which vendors are sponsoring like cncf, like how they're getting funded up. I think it >>Something I pay attention to as well. Yeah. Yeah. Lisa, I know you've got >>Some insight. Those are the things I was thinking about today. >>I gotta ask you, what's your take on what Keith said? Are you also seeing the maturation of the enterprise here at at coupon? >>Yes, I am actually, when you say enterprise versus what's the other side? Startups, right? Yeah. So startups start using open source a lot more earlier or lot more than enterprises. The enterprise is what they need. Number one thing is the, for their production workloads, they want a vendor sporting them. I said that yesterday as well, right? So it depend depending on the size of the enterprise. If you're a big shop, definitely if you have one of the 500 or Fortune five hundreds and your tech savvy shop, then you can absorb the open source directly coming from the open source sort of universe right. Coming to you. But if you are the second tier of enterprise, you want to go to a provider which is managed service provider, or it can be cloud service provider in this case. Yep. Most of the cloud service providers have multiple versions of Kubernetes, for example. >>I'm not talking about Kubernetes only, but like, but that is one example, right? So at Amazon you can get five different flavors of Kubernetes, right? Fully manage, have, manage all kind of stuff. So people don't have bandwidth to manage that stuff locally. You have to patch it, you have to roll in the new, you know, updates and all that stuff. Like, it's a lot of work for many. So CNCF actually is formed for that reason. Like the, the charter is to bring the quality to open source. Like in other companies they have the release process and they, the stringent guidelines and QA and all that stuff. So is is something ready for production? That's the question when it comes to any software, right? So they do that kind of work and, and, and they have these buckets defined at high level, but it needs more >>Work. Yeah. So one of the things that, you know, kind of stood out to me, I have good friend in the community, Alex Ellis, who does open Fast. It's a serverless platform, great platform. Two years ago or in 2019, there was a serverless day date. And in serverless day you had K Native, you had Open Pass, you had Ws, which is supported by IBM completely, not CNCF platforms. K native came into the CNCF full when Google donated the project a few months ago or a couple of years ago, now all of a sudden there's a K native day. Yes. Not a serverless day, it's a K native day. And I asked the, the CNCF event folks like, what happened to Serverless Day? I missed having open at serverless day. And you know, they, they came out and said, you know what, K native got big enough. >>They came in and I think Red Hat and Google wanted to sponsor a K native day. So serverless day went away. So I think what what I'm interested in and over the next couple of years is, is they're gonna be pushback from the C against the cncf. Is the CNCF now too big? Is it now the gatekeeper for do I have to be one of those 147 projects, right? In order enough to get my project noticed the open, fast, great project. I don't think Al Alex has any desire to have his project hosted by cncf, but it probably deserves, you know, shoulder left recognition with that. So I'm pushing to happen to say, okay, if this is open community, this is open source. If CNC is the place to have the cloud native conversation, what about the projects that's not cncf? Like how do we have that conversation when we don't have the power of a Google right. Or a, or a Lenox, et cetera, or a Lenox Foundation. So GE what, >>What are your thoughts on that? Is, is CNC too big? >>I don't think it's too big. I think it's too small to handle the, what we are doing in open source, right? So it's a bottle. It can become a bottleneck. Okay. I think too big in a way that yeah, it has, it has, it has power from that point of view. It has that cloud, if you will. The people listen to it. If it's CNCF project or this must be good, it's like in, in incubators. Like if you are y white Combinator, you know, company, it must be good. You know, I mean, may not be >>True, but, >>Oh, I think there's a bold assumption there though. I mean, I think everyone's just trying to do the best they can. And when we're evaluating projects, a very different origin and background, it's incredibly hard. Very c and staff is a staff of 30 people. They've got 180,000 people that are contributing to these projects and a thousand maintainers that they're trying to uphold. I think the challenge is actually really great. And to me, I actually look at events as an illustration of, you know, what's the culture and the health of an organization. If I were to evaluate CNCF based on that, I'd say we're very healthy right now. I would say that we're in a good spot. There's a lot of momentum. >>Yeah. I, I think CNCF is very healthy. I'm, I'm appreciative for it being here. I love coupon. It's becoming the, the facto conference to have this conversation has >>A totally >>Different vibe to other, It's a totally different vibe. Yeah. There needs to be a conduit and truth be told, enterprise buyers, to subject's point, this is something that we do absolutely agree on, on enterprise buyers. We want someone to pick winners and losers. We do, we, we don't want a box of Lego dumped on our, the middle of our table. We want somebody to have sorted that out. So while there may be five or six different service mesh solutions, at least the cncf, I can go there and say, Oh, I'll pick between the three or four that are most popular. And it, it's a place to curate. But I think with that curation comes the other side of it. Of how do we, how, you know, without the big corporate sponsor, how do I get my project pushed up? Right? Elevated. Elevated, Yep. And, and put onto the show floor. You know, another way that projects get noticed is that startups will adopt them, Push them. They may not even be, I don't, my CNCF project may not, my product may not even be based on the CNCF product. But the new stack has a booth, Ford has a booth. Nothing to do with a individual prod up, but promoting open source. What happens when you're not sponsored? >>I gotta ask you guys, what do you disagree on? >>Oh, so what, what do we disagree on? So I'm of the mindset, I can, I can say this, I I believe hybrid infrastructure is the future of it. Bar none. If I built my infrastructure, if I built my application in the cloud 10 years ago and I'm still building net new applications, I have stuff that I built 10 years ago that looks a lot like on-prem, what do I do with it? I can't modernize it cuz I don't have the developers to do it. I need to stick that somewhere. And where I'm going to stick that at is probably a hybrid infrastructure. So colo, I'm not gonna go back to the data center, but I'm, I'm gonna look, pick up something that looks very much like the data center and I'm saying embrace that it's the future. And if you're Boeing and you have, and Boeing is a member, cncf, that's a whole nother topic. If you have as 400 s, hpu X, et cetera, stick that stuff. Colo, build new stuff, but, and, and continue to support OpenStack, et cetera, et cetera. Because that's the future. Hybrid is the future. >>And sub g agree, disagree. >>I okay. Hybrid. Nobody can deny that the hybrid is the reality, not the future. It's a reality right now. It's, it's a necessity right now you can't do without it. Right. And okay, hybrid is very relative term. You can be like 10% here, 90% still hybrid, right? So the data center is shrinking and it will keep shrinking. Right? And >>So if by whole is the data center shrinking? >>This is where >>Quick one quick getting guys for it. How is growing by a clip? Yeah, but there's no data supporting. David Lym just came out for a report I think last year that showed that the data center is holding steady, holding steady, not growing, but not shrinking. >>Who sponsored that study? Wait, hold on. So the, that's a question, right? So more than 1 million data centers have been closed. I have, I can dig that through number through somebody like some organizations we published that maybe they're cloud, you know, people only. So the, when you get these kind of statements like it, it can be very skewed statements, right. But if you have seen the, the scene out there, which you have, I know, but I have also seen a lot of data centers walk the floor of, you know, a hundred thousand servers in a data center. I cannot imagine us consuming the infrastructure the way we were going into the future of co Okay. With, with one caveat actually. I am not big fan of like broad strokes. Like make a blanket statement. Oh no, data center's dead. Or if you are, >>That's how you get those esty headlines now. Yeah, I know. >>I'm all about to >>Put a stake in the ground. >>Actually. The, I think that you get more intelligence from the new end, right? A small little details if you will. If you're golden gold manak or Bank of America, you have so many data centers and you will still have data centers because performance matters to you, right? Your late latency matters for applications. But if you are even a Fortune 500 company on the lower end and or a healthcare vertical, right? That your situation is different. If you are a high, you know, growth startup, your situation is different, right? You will be a hundred percent cloud. So cloud gives you velocity, the, the, the pace of change, the pace of experimentation that actually you are buying innovation through cloud. It's proxy for innovation. And that's how I see it. But if you have, if you're stuck with older applications, I totally understand. >>Yeah. So the >>We need that OnPrem. Yeah, >>Well I think the, the bring your fuel sober, what we agree is that cloud is the place where innovation happens. Okay? At some point innovation becomes legacy debt and you have thus hybrid, you are not going to keep your old applications up to date forever. The, the, the math just doesn't add up. And where I differ in opinion is that not everyone needs innovation to keep moving. They need innovation for a period of time and then they need steady state. So Sergeant, we >>Argue about this. I have a, I >>Love this debate though. I say it's efficiency and stability also plays an important role. I see exactly what you're talking about. No, it's >>Great. I have a counter to that. Let me tell you >>Why. Let's >>Hear it. Because if you look at the storage only, right? Just storage. Just take storage computer network for, for a minute. There three cost reps in, in infrastructure, right? So storage earlier, early on there was one tier of storage. You say pay the same price, then now there are like five storage tiers, right? What I'm trying to say is the market sets the price, the market will tell you where this whole thing will go, but I know their margins are high in cloud, 20 plus percent and margin will shrink as, as we go forward. That means the, the cloud will become cheaper relative to on-prem. It, it, in some cases it's already cheaper. But even if it's a stable workload, even in that case, we will have a lower tier of service. I mean, you, you can't argue with me that the cloud versus your data center, they are on the same tier of services. Like cloud is a better, you know, product than your data center. Hands off. >>I love it. We, we are gonna relish in the debates between the two of you. Mic drops. The energy is great. I love it. Perspective. It's not like any of us can quite see through the crystal ball that we have very informed opinions, which is super exciting. Yeah. Lisa, any last thoughts today? >>Just love, I love the debate as well. That, and that's, that's part of what being in this community is all about. So sharing about, sharing opinions, expressing opinions. That's how it grows. That's how, that's how we innovate. Yeah. Obviously we need the cloud, but that's how we innovate. That's how we grow. Yeah. And we've seen that demonstrated the last couple days and I and your, your takes here on the Cuban on Twitter. Brilliant. >>Thank you. I absolutely love it. I'm gonna close this out with a really important analysis on the swag of the show. Yes. And if you know, yesterday we were looking at what is the weirdest swag or most unique swag We had that bucket hat that took the grand prize. Today we're gonna focus on something that's actually quite cool. A lot of the vendors here have really dedicated their swag to being local to Detroit. Very specific in their sourcing. Sonotype here has COOs. They're beautiful. You can't quite feel this flannel, but it's very legit hand sound here in Michigan. I can't say that I've been to too many conferences, if any, where there was this kind of commitment to localizing and sourcing swag from around the corner. We also see this with the Intel booth. They've got screen printers out here doing custom hoodies on spot. >>Oh fun. They're even like appropriately sized. They had local artists do these designs and if you're like me and you care about what's on your wrist, you're familiar with Shinola. This is one of my favorite swags that's available. There is a contest. Oh going on. Hello here. Yeah, so if you are Atan, make sure that you go and check this out. The we, I talked about this on the show. We've had the founder on the show or the CEO and yeah, I mean Shine is just full of class as since we are in Detroit as well. One of the fun themes is cars. >>Yes. >>And Storm Forge, who are also on the show, is actually giving away an Aston Martin, which is very exciting. Not exactly manufactured in Detroit. However, still very cool on the car front and >>The double oh seven version named the best I >>Know in the sixties. It's love it. It's very cool. Two quick last things. We talk about it a lot on the show. Every company now wants to be a software company. Yep. On that vein, and keeping up with my hat theme, the Home Depot is here because they want everybody to know that they in fact are a technology company, which is very cool. They have over 500,000 employees. You can imagine there's a lot of technology that has to go into keeping Napa. Absolutely. Yep. Wild to think about. And then last, but not at least very quick, rapid fire, best t-shirt contest. If you've ever ran to one of these events, there are a ton of T-shirts out there. I rate them on two things. Wittiest line and softness. If you combine the two, you'll really be our grand champion for the year. I'm just gonna hold these up and set them down for your laughs. Not afraid to commit, which is pretty great. This is another one designed by locals here. Detroit Code City. Oh, love it. This one made me chuckle the most. Kiss my cash. >>Oh, that's >>Good. These are also really nice and soft, which is fantastic. Also high on the softness category is this Op Sarah one. I also like their bird logo. These guys, there's just, you know, just real nice touch. So unfortunately, if you have the fumble, you're not here with us, live in Detroit. At least you're gonna get taste of the swag. I taste of the stories and some smiles hear from those of us on the cube. Thank you both so much for being here with us. Lisa, thanks for another fabulous day. Got it, girl. My name's Savannah Peterson. Thank you for joining us from Detroit. We're the cube and we can't wait to see you tomorrow.

>>Good morning and welcome back to the Cube where we are excited to be broadcasting live all week from Detroit to Michigan at Cuban slash cloud Native con. Depending on who you're asking, Lisa, it's day two things are buzzing. How are you feeling? >>Good, excited. Ready for day two, ready to have more great conversations to see how this community is expanding, how it's evolving, and how it's really supporting it itself. >>Yeah, Yeah. This is a very supportive community. Something we talked a lot about. And speaking of community, we've got some very bold and brave folks over here. We've got this CTO and the head of product from Storm Forge, and they are on a mission to automate Kubernetes. Now automatic and Kubernetes are not words that go in the same sentence very often, so please welcome Patrick and Yasmin. Thank you both for being here. Hello. How you doing? >>Thanks for having us. >>Thanks for having us. >>Talk about what you guys are doing. Cause as you said, Kubernetes auto spelling is anything but auto. >>Yeah. >>The, what are some of the challenges? How do you help >>Eliminate this? Yeah, so the mission at Storm Forge is primarily automatic resource configuration and optimization essentially. So we started as a machine learning company first. And it's kind of an interesting story cuz we're one of those startups that has pivoted a few times. And so we were running our machine learning workloads. Most >>Have, I think, >>Right? Yeah. Yeah. We were, we started out running our machine learning workloads and moving them into Kubernetes. And then we weren't quite sure how to correctly adjust and size our containers. And so our ML team, we've got three PhDs and applied mathematics. They said, Well, hang on, we could write an algorithm for that. And so they did. And then, Oh, I love this. Yeah. And then we said, Well holy cow, that's actually really useful. I wonder if other people would like that. And that's kind of where we got our start. >>You solved your own problem and then you built a business >>Around it. Yeah, exactly. >>That is fantastic. Is, is that driving product development at Storm Forge still? That kind of attitude? >>I mean that kind of attitude definitely drives product development, but we're, you know, balancing that with what the users are, the challenges that they have, especially at large scale. We deal with a lot of large enterprises and for us as a startup, we can relate to the problems that come with Kubernetes when you're trying to scale it. But when you're talking about the scale of some of these larger enterprises, it's just a different mentality. So we're trying to balance that of how we take that input into how we build our product. Talk >>About that, like the, the end user input and how you're taking that in, because of course it's only going to be a, you know, more of a symbiotic relationship when that customer feedback is taken and >>Acted on. Yeah, totally. And for us, because we use machine learning, it's a lot of building confidence with our users. So making sure that they understand how we look at the data, how we come up with the recommendations, and actually deploy those changes in their environment. There's a lot of trust that needs to be built there. So being able to go back to our users and say, Okay, we're presenting you this type of data, give us your feedback and building it alongside them has helped a lot in these >>Relationships. Absolutely. You said the word trust, and that's something that we talk about at every >>Show. I was gonna jump on that too. It's >>Not, Yeah, it's not a buzzword. It's not, It shouldn't be. Yeah. It really should be, I wanna say lived and breathed, but that's probably grammatically incorrect. >>We're not a gram show. It's okay darling. Yeah, thank >>You. It should be truly embodied. >>Yeah. And I, I think it's, it's not even unique to just what we do, but across tech in general, right? Like when I talk about SRE and building SRE teams, one of the things I mentioned is you have to build that trust first. And with machine learning, I think it can be really difficult too for a couple different reasons. Like one, it tends to be a black box if it's actually true machine learning. Totally. Which ours is. But the other piece that we run into. Yeah. And the other piece we run into though is, is what I was an executive at United Health Group before I joined Storm Forge. And I would get companies that would come to me and try to sell me machine learning and I would kind of look at it and say, Well no, that's just a basic decision tree. Or like, that's a super basic whole winter forecast, right? Like that's not actually machine learning. And that's one of the things that we actually find ourselves kind of battling a little bit when we talk about what we do in building that trust. >>Talk a little bit about the latest release as you guys had a very active September. Here we are. And towards the, I think end of October. Yeah. What are some of the, the new things that have come out? New integrations, new partnerships. Give us a scoop on that. >>Yeah, well I guess I'll start and then I'll probably hand it over to you. But like the, the big thing for us is we talked about automating Kubernetes in the very beginning, right? Like Kubernetes has got a vpa it's >>A wild sentence anyway. Yeah, yeah. >>It it >>Has. We're not gonna get over at the whole show. Yeah. >>It as a VPA built in, it has an HPA built in and, and when you look at the data and even when you read the documentation from Google, it explicitly says never the two should meet. Right. Because you'll end up thrashing and they'll fight each other. Well the big release we just announced is with our machine learning, we can now do both. And so we vertically scale your pods to the correct up. Yeah. >>Follow status. I love that. >>Yeah, we can, we can scale your pods to the correct size and still allow you to enable the HPA and we'll make recommendations for your scaling points and your thresholds on the HPA as well so that they can work together to really truly maximize your efficiency that without sacrificing your performance and your reliability of the applications that you're running. That >>Sounds like a massive differentiator for >>Storm launch, which I would say it is. Yeah. I think as far as I know, we're the first in the industry that can do this. Yeah. >>And >>From very singularity vibes too. You know, the machines are learning, teaching themselves and doing it all automatically. Yep. Gets me very >>Excited. >>Yeah, absolutely. And from a customer demand perspective, what's the feedback been? Yeah, it's been a few >>Weeks. Yeah, it's been really great actually. And a lot of why we went down this path was user driven because they're doing horizontal scale and they want to be able to vertically size as they're scaling. So if you put yourself in the shoes of someone that's configuring Kubernetes, you're usually guessing on what you're setting your CPU requests and limits do. But horizontal scale makes sense. You're either adding more things or removing more things. And so once they actually are scaled out as a large environment and they have to rethink, how am I gonna resize this now? It's just not possible. It's so many thousands of settings across all the different environments and you're only thinking about CPU memory, You're not thinking about a lot of things. It's just, but once you scale that out, it's a big challenge. So they came to us and said, Okay, you're doing, cuz we were doing vertical scaling before and now we enable vertical and horizontal. And so they came to us and said, I love what you're doing about right sizing, but we wanna be able to do this while also horizontally scaling. And so the way that our software works is we give you the recommendations for what the setting should be and then allow Kubernetes to continue to add and remove replicas as needed. So it's not like we're going in and making changes to Kubernetes, but we make changes to the configuration settings so that it's the most optimal from a resource perspective. >>Efficiency has been a real big theme of the show. Yeah. And it's clear that that's a focus for you. Everyone here wants to do more faster Of course. And innovation, that's the thing to do that sometimes we need partners. You just announced an integration with Datadog. Tell us about that. Yeah, >>Absolutely. Yeah. So the way our platform works is we need data of course, right? So they're, they're a great partner for us and we use them both as an input and an output. So we pull in metrics from Datadog to provide recommendations and we'll actually display all those within the Datadog portal. Cause we have a lot of users that are like, Look, Datadog's my single pane of glass and I hate using that word, but they get all their insights there. They can see their recommendations and then actually go deploy those. Whether they wanna automatically have the recommendations deployed or go in and actually push a button. >>So give me an example of a customer that is using the, the new release and some of the business outcomes they're achieving. I imagine one of the things that you're enabling is just closing that ES skills gap. But from a business level perspective, how are they gaining like competitive advantages to be able to get products to market faster, for example? >>Yeah, so one of the customers that was actually part of our press release and launch and spoke about us at a webinar, they are a SaaS product and deal with really bursty workloads. And so their cloud costs have been growing 40% year over year. And their platform engineering team is basically enabled to provide the automation for developers and in their environment, but also to reduce those costs. So they want to, it's that trade off of resiliency and cost performance. And so they came to us and said, Look, we know we're over provisioned, but we don't know how to tackle that problem without throwing tons of humans at the problem. And so we worked with them and just on a single app found 60% savings and we're working now to kind of deploy that across their entire production workload. But that allows them to then go back and get more out of the, the budget that they already have and they can kind of reallocate that in other areas, >>Right? So there can be chop line and bottom >>Line impact. Yeah. And I, I think there's some really direct impact to the carbon emissions of an organization as well. That's a good point. When you can reduce your compute consumption by 60%. >>I love this. We haven't talked about this at all during the show. Yeah. And I'm really glad that you brought this up. All of the things that power this use energy. Yeah. >>What is it like seven to 8% of all electricity in the world is consumed by data centers. Like it's crazy. Yeah. Yeah. And so like that's wild. Yeah. Yeah. So being able to make a reduction in impact there too, especially with organizations that are trying to sign green pledges and everything else. >>It's hard. Yeah. ESG initiatives are huge. >>Absolut, >>It's >>A whole lot. A lot of companies have ESG initiatives where they can't even go out and do an RFP with a business, Right. If they don't have an actual active starting, impactful ESG program. Yes. Yeah. >>And the RFPs that we have to fill out, we have to tell them how they'll help. >>Yeah. Yes. It's so, yeah, I mean I was really struck when I looked on your website and I saw 54% average cost reduction for Yeah. For your cloud operations. I hadn't even thought about it from a power perspective. Yeah. I mean, imagine if we cut that to 3% of the world's power grid. That is just, that is very compelling. Speaking of compelling and exciting future things, talk to us about what's next? What's got you pumped for 2023 and and what lies >>Ahead? Oh man. Well that seems like a product conversation for sure. >>Well, we're super excited about extending what we do to other platforms, other metrics. So we optimize a lot right now around CPU and memory, but we can also give people insights into, you know, limiting kills, limiting CPU throttling, so extending the metrics. And when you look at hba and horizontal scale today, most of it is done with cpu, but there are some organizations out there that are scaling on custom metrics. So being able to take in more data to provide more recommendations and kind of extend what we can do from an optimization standpoint. >>That's, yeah, that's cool. And what house you most excited on the show floor? Anything? Anything that you've seen? Any keynotes? >>There's, Well, I haven't had a lot of time to go to the keynotes unfortunately, but it's, >>Well, I'm shock you've been busy or something, right? Much your time here. >>I can't imagine why. But no, there's, it's really interesting to see all the vendors that are popping up around Kubernetes focus specifically with security is always something that's really interesting to me. And automating CICD and how they continue to dive into that automation devs, SEC ops continues to be a big thing for a lot of organizations. Yeah. Yeah. >>I I do, I think it's interesting when we marry, Were you guys here last year? >>I was not here. >>No. So at, at the smaller version of this in Los Angeles. Yeah. I, I was really struck because there was still a conversation of whether or not we were all in on Kubernetes as, as kind of a community and a society this year. And I'm curious if you feel this way too. Everyone feels committed. Yeah. Yeah. I I I feel like there's no question that Kubernetes is the tool that we are gonna be using. >>Yeah. I I think so. And I think a lot of that is actually being unlocked by some of these vendors that are being partners and helping people get the most outta Kubernetes, you know, especially at the larger enterprise organizations. Like they want to do it, but the skills gap is a very real problem. Right. And so figuring out, like Jasmine talked about figuring out how do we, you know, optimize or set up the correct settings without throwing thousands of humans at it. Never mind the fact you'll never find a thousand people that wanna do that all day every day. >>I was gonna, It's a fold endeavor for those >>People study, right? Yeah. And, and being able to close some of those gaps, whether it's optimization, security, DevOps, C I C D. As we get more of those partners like I just talked about on the floor, then you see more and more enterprises being more open to leaning into Kubernetes a little bit. >>Yeah. Yeah. We've seen, we've had some great conversations the last day and, and today as well with organizations that are history companies like Ford Motor Companies for >>Example. Yeah. Right. >>Just right behind us. One of their EVs and, and it's, they're becoming technology companies that happen to do cars or home >>Here. I had a nice job with 'em this morning. Yes. With that storyline, honestly. >>Yes. That when we now have such a different lens into these organizations, how they're using technologies, advanced technologies, Kubernetes, et cetera, to really become data companies. Yeah. Because they have to be, well the consumers on the other end expect a Home Depot or a Ford or whomever or your bank Yeah. To know who you are. I want the information right here whenever I need it so I can do the transaction I need and I want you to also deliver me information that is relevant to me. Yeah. Because there, there's no patience anymore. Yeah. >>And we partner with a lot of big FinTech companies and it's, it's very much that. It's like how do we continue to optimize? But then as they look at transitioning off of older organizations and capabilities, whether that's, they have a physical data center that's racked to the gills and they can't do anything about that, so they wanna move to cloud or they're just dipping their toe into even private cloud with Kubernetes in their own instances. A lot of it is how do we do this right? Like how do we lean in and, Yeah. >>Yeah. Well I think you said it really well that the debate seems to be over in terms of do we go in on Kubernetes? That that was a theme that I think we felt that yesterday, even on on day one of the keynotes. The community seems to be just craving more. I think that was another thing that we felt yesterday was all of the contributors and the collaborators, people want to be able to help drive this community forward because it's, it's a flywheel of symbiosis for all of the vendors here. The maintainers and, and really businesses in any industry can benefit. >>Yeah. It's super validating. I mean if you just look at the floor, there's like 20 different booths that talk about cost reporting for Kubernetes. So not only have people moved, but now they're dealing with those challenges at scale. And I think for us it's very validating because there's so many vendors that are looking into the reporting of this and showing you the problem that you have. And then where we can help is, okay, now you know, you have a problem, here's how we can fix it for you. >>Yeah. Yeah. That, that sort of dealing with challenges at scale that you set, I think that's also what we're hearing. Yeah. And seeing and feeling on the show floor. >>Yeah, absolutely. >>What can folks see and, and touch and feel in your booth? >>We have some demos there you can play around with the product. We're giving away a Lego set so we've let >>Gotta gets >>Are right now we're gonna have to get some Lego, We do a swag segment at the end of the day every day. Now we've >>Some cool socks. >>Yep. Socks are hot. Let's, let's actually talk about scale internally as our closing question. What's going on at Storm Forge? If someone's watching right now, they're excited. Are you hiring? We are hiring. Yeah. How can they stalk you? What's the >>School? Absolutely. So you can check us out on Storm forge.io. We're certainly hiring across the engineering organization. We're hiring across the UX a product organization. We're dealing, like I said, we've got some really big customers that we're, we're working through with some really fun challenges. And we're looking to continue to build on what we do and do new innovative things like especially cuz like I said, we are a machine learning organization first. And so for me it's like how do I collect all the data that I can and then let's find out what's interesting in there that we can help people with. Whether that's cpu, memory, custom metrics, like as said, preventing kills, driving availability, reliability, What can we do to, to kind of make a little bit more transparent the stuff that's going on underneath the covers in Kubernetes for the decision makers in these organizations. >>Yes. Transparency is a goal of >>Many. >>Yeah, absolutely. Well, and you mentioned fun. If this conversation is any representation, it would be very fun to be working on both of your teams. We, we have a lot of fun Ya. Patrick, thank you so much for joining. Thanks for having us, Lisa, As usual, thanks for being here with me. My pleasure. And thank you to all of you for turning into the Cubes live show from Detroit. My name's Savannah Peterson and we'll be back in a few.

(upbeat music) >> Hey guys, welcome back to the show floor of KubeCon + CloudNativeCon '22 North America from Detroit, Michigan. Lisa Martin here with John Furrier. This is day one, John at theCUBE's coverage. >> CUBE's coverage. >> theCUBE's coverage of KubeCon. Try saying that five times fast. Day one, we have three wall-to-wall days. We've been talking about Kubernetes, containers, adoption, cloud adoption, app modernization all morning. We can't talk about those things without addressing security. >> Yeah, this segment we're going to hear container and Kubernetes security for modern application 'cause the enterprise are moving there. And this segment with Red Hat's going to be important because they are the leader in the enterprise when it comes to open source in Linux. So this is going to be a very fun segment. >> Very fun segment. Two guests from Red Hat join us. Please welcome Doron Caspin, Senior Principal Product Manager at Red Hat. Michael Foster joins us as well, Principal Product Marketing Manager and StackRox Community Lead at Red Hat. Guys, great to have you on the program. >> Thanks for having us. >> Thank you for having us. >> It's awesome. So Michael StackRox acquisition's been about a year. You got some news? >> Yeah, 18 months. >> Unpack that for us. >> It's been 18 months, yeah. So StackRox in 2017, originally we shifted to be the Kubernetes-native security platform. That was our goal, that was our vision. Red Hat obviously saw a lot of powerful, let's say, mission statement in that, and they bought us in 2021. Pre-acquisition we were looking to create a cloud service. Originally we ran on Kubernetes platforms, we had an operator and things like that. Now we are looking to basically bring customers in into our service preview for ACS as a cloud service. That's very exciting. Security conversation is top notch right now. It's an all time high. You can't go with anywhere without talking about security. And specifically in the code, we were talking before we came on camera, the software supply chain is real. It's not just about verification. Where do you guys see the challenges right now? Containers having, even scanning them is not good enough. First of all, you got to scan them and that may not be good enough. Where's the security challenges and where's the opportunity? >> I think a little bit of it is a new way of thinking. The speed of security is actually does make you secure. We want to keep our images up and fresh and updated and we also want to make sure that we're keeping the open source and the different images that we're bringing in secure. Doron, I know you have some things to say about that too. He's been working tirelessly on the cloud service. >> Yeah, I think that one thing, you need to trust your sources. Even if in the open source world, you don't want to copy paste libraries from the web. And most of our customers using third party vendors and getting images from different location, we need to trust our sources and we have a really good, even if you have really good scanning solution, you not always can trust it. You need to have a good solution for that. >> And you guys are having news, you're announcing the Red Hat Advanced Cluster Security Cloud Service. >> Yes. >> What is that? >> So we took StackRox and we took the opportunity to make it as a cloud services so customer can consume the product as a cloud services as a start offering and customer can buy it through for Amazon Marketplace and in the future Azure Marketplace. So customer can use it for the AKS and EKS and AKS and also of course OpenShift. So we are not specifically for OpenShift. We're not just OpenShift. We also provide support for EKS and AKS. So we provided the capability to secure the whole cloud posture. We know customer are not only OpenShift or not only EKS. We have both. We have free cloud or full cloud. So we have open. >> So it's not just OpenShift, it's Kubernetes, environments, all together. >> Doron: All together, yeah. >> Lisa: Meeting customers where they are. >> Yeah, exactly. And we focus on, we are not trying to boil the ocean or solve the whole cloud security posture. We try to solve the Kubernetes security cluster. It's very unique and very need unique solution for that. It's not just added value in our cloud security solution. We think it's something special for Kubernetes and this is what Red that is aiming to. To solve this issue. >> And the ACS platform really doesn't change at all. It's just how they're consuming it. It's a lot quicker in the cloud. Time to value is right there. As soon as you start up a Kubernetes cluster, you can get started with ACS cloud service and get going really quickly. >> I'm going to ask you guys a very simple question, but I heard it in the bar in the lobby last night. Practitioners talking and they were excited about the Red Hat opportunity. They actually asked a question, where do I go and get some free Red Hat to test some Kubernetes out and run helm or whatever. They want to play around. And do you guys have a program for someone to get start for free? >> Yeah, so the cloud service specifically, we're going to service preview. So if people sign up, they'll be able to test it out and give us feedback. That's what we're looking for. >> John: Is that a Sandbox or is that going to be in the cloud? >> They can run it in their own environment. So they can sign up. >> John: Free. >> Doron: Yeah, free. >> For the service preview. All we're asking for is for customer feedback. And I know it's actually getting busy there. It's starting December. So the quicker people are, the better. >> So my friend at the lobby I was talking to, I told you it was free. I gave you the sandbox, but check out your cloud too. >> And we also have the open source version so you can download it and use it. >> Yeah, people want to know how to get involved. I'm getting a lot more folks coming to Red Hat from the open source side that want to get their feet wet. That's been a lot of people rarely interested. That's a real testament to the product leadership. Congratulations. >> Yeah, thank you. >> So what are the key challenges that you have on your roadmap right now? You got the products out there, what's the current stake? Can you scope the adoption? Can you share where we're at? What people are doing specifically and the real challenges? >> I think one of the biggest challenges is talking with customers with a slightly, I don't want to say outdated, but an older approach to security. You hear things like malware pop up and it's like, well, really what we should be doing is keeping things into low and medium vulnerabilities, looking at the configuration, managing risk accordingly. Having disparate security tools or different teams doing various things, it's really hard to get a security picture of what's going on in the cluster. That's some of the biggest challenges that we talk with customers about. >> And in terms of resolving those challenges, you mentioned malware, we talk about ransomware. It's a household word these days. It's no longer, are we going to get hit? It's when? It's what's the severity? It's how often? How are you guys helping customers to dial down some of the risk that's inherent and only growing these days? >> Yeah, risk, it's a tough word to generalize, but our whole goal is to give you as much security information in a way that's consumable so that you can evaluate your risk, set policies, and then enforce them early on in the cluster or early on in the development pipeline so that your developers get the security information they need, hopefully asynchronously. That's the best way to do it. It's nice and quick, but yeah. I don't know if Doron you want to add to that? >> Yeah, so I think, yeah, we know that ransomware, again, it's a big world for everyone and we understand the area of the boundaries where we want to, what we want to protect. And we think it's about policies and where we enforce it. So, and if you can enforce it on, we know that as we discussed before that you can scan the image, but we never know what is in it until you really run it. So one of the thing that we we provide is runtime scanning. So you can scan and you can have policy in runtime. So enforce things in runtime. But even if one image got in a way and get to your cluster and run on somewhere, we can stop it in runtime. >> Yeah. And even with the runtime enforcement, the biggest thing we have to educate customers on is that's the last-ditch effort. We want to get these security controls as early as possible. That's where the value's going to be. So we don't want to be blocking things from getting to staging six weeks after developers have been working on a project. >> I want to get you guys thoughts on developer productivity. Had Docker CEO on earlier and since then I had a couple people messaging me. Love the vision of Docker, but Docker Hub has some legacy and it might not, has does something kind of adoption that some people think it does. Are people moving 'cause there times they want to have these their own places? No one place or maybe there is, or how do you guys see the movement of say Docker Hub to just using containers? I don't need to be Docker Hub. What's the vis-a-vis competition? >> I mean working with open source with Red Hat, you have to meet the developers where they are. If your tool isn't cutting it for developers, they're going to find a new tool and really they're the engine, the growth engine of a lot of these technologies. So again, if Docker, I don't want to speak about Docker or what they're doing specifically, but I know that they pretty much kicked off the container revolution and got this whole thing started. >> A lot of people are using your environment too. We're hearing a lot of uptake on the Red Hat side too. So, this is open source help, it all sorts stuff out in the end, like you said, but you guys are getting a lot of traction there. Can you share what's happening there? >> I think one of the biggest things from a developer experience that I've seen is the universal base image that people are using. I can speak from a security standpoint, it's awesome that you have a base image where you can make one change or one issue and it can impact a lot of different applications. That's one of the big benefits that I see in adoption. >> What are some of the business, I'm curious what some of the business outcomes are. You talked about faster time to value obviously being able to get security shifted left and from a control perspective. but what are some of the, if I'm a business, if I'm a telco or a healthcare organization or a financial organization, what are some of the top line benefits that this can bubble up to impact? >> I mean for me, with those two providers, compliance is a massive one. And just having an overall look at what's going on in your clusters, in your environments so that when audit time comes, you're prepared. You can get through that extremely quickly. And then as well, when something inevitably does happen, you can get a good image of all of like, let's say a Log4Shell happens, you know exactly what clusters are affected. The triage time is a lot quicker. Developers can get back to developing and then yeah, you can get through it. >> One thing that we see that customers compliance is huge. >> Yes. And we don't want to, the old way was that, okay, I will provision a cluster and I will do scans and find things, but I need to do for PCI DSS for example. Today the customer want to provision in advance a PCI DSS cluster. So you need to do the compliance before you provision the cluster and make all the configuration already baked for PCI DSS or HIPAA compliance or FedRAMP. And this is where we try to use our compliance, we have tools for compliance today on OpenShift and other clusters and other distribution, but you can do this in advance before you even provision the cluster. And we also have tools to enforce it after that, after your provision, but you have to do it again before and after to make it more feasible. >> Advanced cluster management and the compliance operator really help with that. That's why OpenShift Platform Plus as a bundle is so popular. Just being able to know that when a cluster gets provision, it's going to be in compliance with whatever the healthcare provider is using. And then you can automatically have ACS as well pop up so you know exactly what applications are running, you know it's in compliance. I mean that's the speed. >> You mentioned the word operator, I get triggering word now for me because operator role is changing significantly on this next wave coming because of the automation. They're operating, but they're also devs too. They're developing and composing. It's almost like a dashboard, Lego blocks. The operator's not just manually racking and stacking like the old days, I'm oversimplifying it, but the new operators running stuff, they got observability, they got coding, their servicing policy. There's a lot going on. There's a lot of knobs. Is it going to get simpler? How do you guys see the org structures changing to fill the gap on what should be a very simple, turn some knobs, operate at scale? >> Well, when StackRox originally got acquired, one of the first things we did was put ACS into an operator and it actually made the application life cycle so much easier. It was very easy in the console to go and say, Hey yeah, I want ACS my cluster, click it. It would get provisioned. New clusters would get provisioned automatically. So underneath it might get more complicated. But in terms of the application lifecycle, operators make things so much easier. >> And of course I saw, I was lucky enough with Lisa to see Project Wisdom in AnsibleFest. You going to say, Hey, Red Hat, spin up the clusters and just magically will be voice activated. Starting to see AI come in. So again, operations operator is got to dev vibe and an SRE vibe, but it's not that direct. Something's happening there. We're trying to put our finger on. What do you guys think is happening? What's the real? What's the action? What's transforming? >> That's a good question. I think in general, things just move to the developers all the time. I mean, we talk about shift left security, everything's always going that way. Developers how they're handing everything. I'm not sure exactly. Doron, do you have any thoughts on that. >> Doron, what's your reaction? You can just, it's okay, say what you want. >> So I spoke with one of our customers yesterday and they say that in the last years, we developed tons of code just to operate their infrastructure. That if developers, so five or six years ago when a developer wanted VM, it will take him a week to get a VM because they need all their approval and someone need to actually provision this VM on VMware. And today they automate all the way end-to-end and it take two minutes to get a VM for developer. So operators are becoming developers as you said, and they develop code and they make the infrastructure as code and infrastructure as operator to make it more easy for the business to run. >> And then also if you add in DataOps, AIOps, DataOps, Security Ops, that's the new IT. It seems to be the new IT is the stuff that's scaling, a lot of data's coming in, you got security. So all that's got to be brought in. How do you guys view that into the equation? >> Oh, I mean you become big generalists. I think there's a reason why those cloud security or cloud professional certificates are becoming so popular. You have to know a lot about all the different applications, be able to code it, automate it, like you said, hopefully everything as code. And then it also makes it easy for security tools to come in and look and examine where the vulnerabilities are when those things are as code. So because you're going and developing all this automation, you do become, let's say a generalist. >> We've been hearing on theCUBE here and we've been hearing the industry, burnout, associated with security professionals and some DataOps because the tsunami of data, tsunami of breaches, a lot of engineers getting called in the middle of the night. So that's not automated. So this got to get solved quickly, scaled up quickly. >> Yes. There's two part question there. I think in terms of the burnout aspect, you better send some love to your security team because they only get called when things get broken and when they're doing a great job you never hear about them. So I think that's one of the things, it's a thankless profession. From the second part, if you have the right tools in place so that when something does hit the fan and does break, then you can make an automated or a specific decision upstream to change that, then things become easy. It's when the tools aren't in place and you have desperate environments so that when a Log4Shell or something like that comes in, you're scrambling trying to figure out what clusters are where and where you're impacted. >> Point of attack, remediate fast. That seems to be the new move. >> Yeah. And you do need to know exactly what's going on in your clusters and how to remediate it quickly, how to get the most impact with one change. >> And that makes sense. The service area is expanding. More things are being pushed. So things will, whether it's a zero day vulnerability or just attack. >> Just mix, yeah. Customer automate their all of things, but it's good and bad. Some customer told us they, I think Spotify lost the whole a full zone because of one mistake of a customer because they automate everything and you make one mistake. >> It scale the failure really. >> Exactly. Scaled the failure really fast. >> That was actually few contact I think four years ago. They talked about it. It was a great learning experience. >> It worked double edge sword there. >> Yeah. So definitely we need to, again, scale automation, test automation way too, you need to hold the drills around data. >> Yeah, you have to know the impact. There's a lot of talk in the security space about what you can and can't automate. And by default when you install ACS, everything is non-enforced. You have to have an admission control. >> How are you guys seeing your customers? Obviously Red Hat's got a great customer base. How are they adopting to the managed service wave that's coming? People are liking the managed services now because they maybe have skills gap issues. So managed service is becoming a big part of the portfolio. What's your guys' take on the managed services piece? >> It's just time to value. You're developing a new application, you need to get it out there quick. If somebody, your competitor gets out there a month before you do, that's a huge market advantage. >> So you care how you got there. >> Exactly. And so we've had so much Kubernetes expertise over the last 10 or so, 10 plus year or well, Kubernetes for seven plus years at Red Hat, that why wouldn't you leverage that knowledge internally so you can get your application. >> Why change your toolchain and your workflows go faster and take advantage of the managed service because it's just about getting from point A to point B. >> Exactly. >> Well, in time to value is, you mentioned that it's not a trivial term, it's not a marketing term. There's a lot of impact that can be made. Organizations that can move faster, that can iterate faster, develop what their customers are looking for so that they have that competitive advantage. It's definitely not something that's trivial. >> Yeah. And working in marketing, whenever you get that new feature out and I can go and chat about it online, it's always awesome. You always get customers interests. >> Pushing new code, being secure. What's next for you guys? What's on the agenda? What's around the corner? We'll see a lot of Red Hat at re:Invent. Obviously your relationship with AWS as strong as a company. Multi-cloud is here. Supercloud as we've been saying. Supercloud is a thing. What's next for you guys? >> So we launch the cloud services and the idea that we will get feedback from customers. We are not going GA. We're not going to sell it for now. We want to get customers, we want to get feedback to make the product as best what we can sell and best we can give for our customers and get feedback. And when we go GA and we start selling this product, we will get the best product in the market. So this is our goal. We want to get the customer in the loop and get as much as feedback as we can. And also we working very closely with our customers, our existing customers to announce the product to add more and more features what the customer needs. It's all about supply chain. I don't like it, but we have to say, it's all about making things more automated and make things more easy for our customer to use to have security in the Kubernetes environment. >> So where can your customers go? Clearly, you've made a big impact on our viewers with your conversation today. Where are they going to be able to go to get their hands on the release? >> So you can find it on online. We have a website to sign up for this program. It's on my blog. We have a blog out there for ACS cloud services. You can just go there, sign up, and we will contact the customer. >> Yeah. And there's another way, if you ever want to get your hands on it and you can do it for free, Open Source StackRox. The product is open source completely. And I would love feedback in Slack channel. It's one of the, we also get a ton of feedback from people who aren't actually paying customers and they contribute upstream. So that's an awesome way to get started. But like you said, you go to, if you search ACS cloud service and service preview. Don't have to be a Red Hat customer. Just if you're running a CNCF compliant Kubernetes version. we'd love to hear from you. >> All open source, all out in the open. >> Yep. >> Getting it available to the customers, the non-customers, they hopefully pending customers. Guys, thank you so much for joining John and me talking about the new release, the evolution of StackRox in the last season of 18 months. Lot of good stuff here. I think you've done a great job of getting the audience excited about what you're releasing. Thank you for your time. >> Thank you. >> Thank you. >> For our guest and for John Furrier, Lisa Martin here in Detroit, KubeCon + CloudNativeCon North America. Coming to you live, we'll be back with our next guest in just a minute. (gentle music)

>>Welcome back to the cubes coverage here in Seattle for AWS marketplace seller conference, the combination of the Amazon partner network, combined with the marketplace from the AWS partner organization, the APO and John Forer host of the queue, bringing you all the action and what it all means. Our next guest is Trisha kata, Malva, chief strategy officer at DataRobot. Great to have you. Thanks for coming on. >>Thank you, John. Great to be here. >>So DataRobot obviously in the big data business data is the big theme here. A lot of companies are in the marketplace selling data solutions. I just ran into snowflake person. I ran into another data analyst company, lot of, lot of data everywhere. You're seeing security. You're seeing insights a lot more going on with data than ever before. It's one of the most popular categories in the marketplace. Talk about DataRobot what you guys are doing. What's your product in there? Yeah, >>Absolutely. John. So we are an artificial intelligence machine learning platform company. We have been around for 10 years. This is this year marks our 10th anniversary and we provide a platform for data scientists and also citizen data scientists. So essentially wanna be data scientists on the business side to rapidly experiment with data and to get insights and then productionize ML models. So the 100% workflow that goes into identifying the data that you need for machine learning and then building models on top of that and operationalizing a, >>How big is the company, roughly employee count? What's the number in >>General general, about a thousand employees. And we have customers all over the world. Our biggest verticals are financial services, insurance, manufacturing, healthcare pharma, all the highly regulated, as well as our tech presence is also growing. And we have people spread across multiple geographies and I can't disclose a customer number, but needless to say, we have hundreds of customers across the >>World. A lot of customers. Yeah, yeah. You guys are well known in the industry have been following some of the recent news lately as well. Yeah. Obviously data's exploding. What in the marketplace are you guys offering? What's the pitch, someone hits the marketplace that wants to buy DataRobot what's the pitch. >>The pitch is if you're looking to get real value from your data science, personal investments and your data, then you have DataRobot that you can download from your AWS marketplace. You can do a free trial and essentially get from, get value from data in a matter of minutes and not months or quarters, that's generally associated with IML. And after that, if you want to purchase you, it's a private offer on, in the marketplace. So you need to call DataRobot representative, but AWS marketplace offers a fantastic distribution channel for us. >>Yeah. I mean, one of the things I heard Chris say, who's now heading up the marketplace and the partner network was the streamlining, a lot of the benefits for the sellers and for the buyers to have a great experience buyers. Clearly we see this as a macro trend, that's gonna only get stronger in terms of self-service buying bundling, having the console on AWS for low level services like infrastructure. But now you've got other business applications that like analytics applies to. You're seeing that work. Now he said things like than the keynote, I wanna get your reaction to like, we're gonna make this more like a C I C D pipeline. We're gonna have more native services built into AWS. What that means to me is that sounds like, oh, if I have a solution, like DataRobot, that can be more native into AWS level services. How do you see that working out for you guys is that play well for your strategy and your customers? What's the, what's the what's resonating with the >>Customers. It plays extremely well with the strategy. So I call this as a win, win, win strategy, win for DataRobot win for customers and win for AWS, which is our partner. And it's a win for DataRobot because the amount of people, the number of eyeballs that look at AWS marketplace, a significantly higher than, than the doors that we can go knock on. So it's a distribution multiplier for us. And the integration into AWS services that you're talking about. It is very important because in this day and age, we need to be interoperable with cloud player services that they offer, whether it is with SageMaker or Redshift, we support all of those. And it's a win for customers because customers, it is a very important growing buyer persona for DataRobot. Yeah. And they already have pre-committed spend with AWS and they can use the, those spend dollars for DataRobot to procure DataRobot. So it eases their procurement life cycle as >>Well. It's a forced multiplier on, on the revenue side, correct? I mean, as well as, as on the business front cost of sales, go down the cost of order dollar. Correct. This is good. Goodness. >>It's it's definitely sorry, just to finish my thought on the win for the partner for AWS. It's great win for them because they're getting the consumption from the partner side, to your point on the force multiplier. Absolutely. It is a force multiplier on the revenue side, and it's great for customers and us, because for us, we have seen that the deal size increases when there is the cloud commit that we can draw down for, for our customers, the procurement cycle shortens. And also we have multiple constituencies within the customers working together in a very seamless fashion. >>How has the procurement going through AWS helped your customers? What specific things are you seeing that are popping out as benefits to the customer? >>So from a procurement standpoint, we, we are early in our marketplace journey. We got listed about a year ago, but the amount of revenue that has gone through marketplace is pretty significant at DataRobot. We experienced like just in, by, I think this quarter until this quarter, we got like about 20 to 30 transactions that went through AWS marketplace. And that is significant within just a year of us operating on the marketplace. And the procurement becomes easier for our customers. Yeah. Because they trust AWS and we can put our legal paperwork through the AWS machine as well, which we haven't done yet. But if we do that, that'll be a further force multiplier because that's the, the less friction there is. >>I like how you say that it's a machine. Yeah. And if you think about the benefits too, like one of the things that I see happening, and I love to get your thoughts because I think this is what's happening here. Infrastructure services, I get that IAS done hardware I'm oversimplifying, but all the, all the goodness, but as customers have business apps and vertical market solutions, you got more AI involved. You need more data that's specialized for that use case. Or you need a business application. Those, you don't hear words like let's provision that app. I mean, your provision hardware and, and infrastructure, but the, the new net cloud native is that you provision turn on the apps. So you're seeing the wave of building apps are composing Lego blocks, if you will. So it seems like the customers are starting to assemble the solution, almost like deploying a service, correct. And just pressing a button. And it happens. This seems to be where the, the business apps are going. >>Yeah, absolutely. You agree for us? We are, we are a data science platform and for us being very close to the data that the customers have is very important. And where if, if the customer's data is in Redshift, we are close to there. So being very close to the hyperscale or ecosystem in that entire C I C D pipeline, and also the data platform pipeline is very important. >>You know, what's interesting is, is the data is such a big part of, I mean, DevOps infrastructure has code has been the movement for decade. Yeah. So throw security in there. It's dev SecOps. Yeah. That is the developer now. Yeah. They're running essentially what used to be it now the new ops is security and data. Yeah. You see, in those teams really level up to be highly high velocity data meshes, semantic layer. These are words I'm hearing in the industry around the big waves of data, having this mesh. Yeah. Having it connected. So you're starting to see data availability become more pervasive. And, and we see this as a way that's powering this next gen data science revolution where it's like the business person is now the data science person. >>That's exactly. That is, that is what DataRobot does the best. We were founded with the vision that we wanted to democratize the access to AI within enterprises. It shouldn't be restricted to a small group of people don't get me wrong. Data scientists also love DataRobot. They use DataRobot. But the mission is to enhance many, many hundreds of people within an organization to use data science, like how you use Tableau on a regular basis, how you use Microsoft Excel on a regular basis. We want to democratize AI. And when you want to democratize AI, you need to democratize access to data, which is, which could be stored in data marketplaces, which could be stored in data warehouses and push all the intelligence that we grab from that data into the E R P into the apps layer. Because at the end of the day, business users, customers consume predictions through applications layer. >>You know, it's interesting, you mentioned that comment about, you know, trying not to, to offend data scientists, it's actually a rising tide that the tsunami of data is actually making that population bigger too. Right. So correct. You also have data engineering, which has come out of the woodwork. We covered a lot on the cube, which is, you know, we call data as code. So infrastructure as code kind of a spoof on that. But the reality is that there's a lot more data engineering. I call that the smallest population. Those are the, those are the alphas, the alpha geeks. Yeah. Hardcore data operating systems, kind of education, data science, big pool growing. And then the users yeah. Are the new data science practitioners. Correct? Exactly. So kind of a, the landscape is you see that picture too, right? >>For sure. I mean, we, we have presence in all of those, right? Like data engineers are very important. Data scientists. Those are core users of DataRobot like, how can you develop thousands and hundreds of thousands of models without having to hand code? If you have to hand code, it takes months and years to solve one problem for one customer in one location. I mean, see how fast the microeconomic conditions are moving. And data engineers are very important because at the end of the day, yes, you do. You create the model, but you need to operationalize that model. You need to monitor that model for data drift. You need to monitor how the model is performing and you need to productionize the insights that you gain. And for that engineering effort is very important behind the scenes. Yeah. And the users at the end of the day, they are the ones who consume the predictions. >>Yeah. I mean the volume and, and the scale and scope of the data requires a lot of automation as well. Correct. Cause you had that on top of it. You gotta have a platform that's gonna do the heavy lifting. >>Correct. Exactly. The platform is we call it as an augmented platform. It augments data scientists by eliminating the tedious work that they don't want to do in their everyday life, which some of which is like feature engineering, right? It's a very high value add work. However, it takes like multiple iterations to understand which features in your data actually impact the outcome. >>This is where the SAS platform is a service is evolved and we call that super cloud, right. This new model where people can scale it out and up. So horizontally, scalable cloud, but vertically integrated into the applications. It's an integrator dilemma. Not so much correct innovators dilemma, as we say in the queue. Yeah. So I have to ask you, I'm a, I'm a buyer I'm gonna come to the marketplace. I want DataRobot why should they buy DataRobot what's in it for them? What's the key features of DataRobot for a company to hit the subscribe, buy button. >>Absolutely. Do you want to scale your data science to multiple projects? Do you want to be ahead of your competition? Do you want to make AI real? That is our pitch. We are not about doing data science for the sake of data science. We are about generating business value out of data science. And we have done it for hundreds of customers in multiple different verticals across the world, whether it is investment banks or regional banks or insurance companies or healthcare companies, we have provided real value out of data for them. And we have the knowhow in how to solve, whether it is your supply chain, forecasting, problem, demand, forecasting problem, whether it is your foreign exchange training problem, how to solve all these use cases with AI, with DataRobot. So if you want to be in the business of using your data and being ahead of your competitors, DataRobot is your tool log choice. >>Sure. Great to have you on the cube as a strategy officer, you gotta look at the chess board, right. And we're kind of in the mid game, I call it the cloud opening game was, you know, happened. Now we're in the mid game of cloud computing where you're seeing a lot of refactoring of opportunities where technologies and data is the key to success, being things secure and operationally, scalable, etcetera, et cetera. What's the key right now for the ecosystem as a strategy, look at the chessboard for data robots. Obviously marketplace is important strategy. Yeah. And bet for, for DataRobot. What else do you see for your company to be successful? And you could share with, with customers watching. >>Yeah. For us, we are in the intelligence layer, the data, the layer below us is the data layer. The layer about us is the applications and the engagement layer. DataRobot I mean, interoperability and ecosystem is important for every company, but for DataRobot it's extra important because we are in that middle of middle layer of intelligence. And we, we have to integrate with all different data warehouses out there enable our customers to pull the data out in a very, very faster way and then showcase all the predictions into, into their tool of choice. And from a chessboard perspective, I like your phrase of we are in the mid cycle of the cloud revolution. Yeah. And every cloud player has a data science platform, whether it is simple one or more complex one, or whether it has been around for quite some time or it's been latent features. And it is important for us that we have complimentary value proposition with all of them, because at the end of the day, we want to maximize our customer's choice. And DataRobot wants to be a neutral platform in supporting all the different vendors out there from a complementary standpoint, because you don't want to have a vendor lock in for your customers. So you create models in SageMaker. For example, you monitor those in DataRobot or you create models in DataRobot and monitor those in AWS so that you have to provide like a very flexible >>That's a solution architecture. >>Correct? Exactly. You have to provide a very flexible tech stack for your customers. >>Yeah. That's the choice. That's the choice. It's all good. Thank you for coming on the cube, sharing the data robot. So I really appreciate it. Thank >>You for coming. Thank you very much for the opportunity. >>Okay. Breaking it all down with the partners here, the marketplace, it's the future, obviously where people are gonna buy the buyers and sellers coming together, the partner network and marketplace, the big news here at 80 seller conference. I'm John ferry with the cube will be right back with more coverage after this short break.

(upbeat music) >> Welcome back to The Cube's coverage of Fal.Con 22. I'm Dave Vellante with Dave Nicholson. This is day one of our coverage. We had the big keynotes this morning. Derek Jeter was one of the keynotes. We have a big Yankee fan here: George Kurtz is the co-founder and CEO of CrowdStrike. George, thanks for coming on The Cube. >> It's great to be here. >> Boston fan, you know, I tweeted out Derek Jeter. He broke my heart many times, but I can't hate on Jeter. You got to have respect for the guy. >> Well, I still remember I was in Japan when Boston was down you know, by three games and came back to win. So I've got my own heartbreak as well. >> It did heal some wounds, but it almost changed the rivalry, you know? I mean, >> Yeah. >> Once, it's kind of neutralized it, you know? It's just not as interesting. I mean, I'm a season ticket holder. I go to all the games and Yankee games are great. A lot of it used to be, you would never walk into Fenway park with, you know pin stripes, when today there's as many Yankee fans as there are... >> I know. >> Boston fans. Anyway, at Fenway, I mean. >> Yeah. >> Why did you start CrowdStrike? >> Biggest thing for me was to really change the game in how people were looking at security. And at my previous company, I think a lot of people were buying security and not getting the outcome that they wanted. Not- I got acquired by a company, not my first company. So, to be clear, and before I started CrowdStrike, I was in the antivirus world, and they were spending a lot of money with antivirus vendors but not getting the outcome I thought they should achieve, which is to stop the breach, not just stop malware. And for me, security should be outcome based not sort of product based. And the biggest thing for us was how could we create the sales force of security that was focused on getting the right outcome: stopping the breach. >> And the premise, I've seen it, the unstoppable breach is a myth. No CSOs don't live by that mantra, but you do. How are you doing on that journey? >> Well I think, look, there's no 100% of anything in security, but what we've done is really created a platform that's focused on identifying and stopping breaches as well as now, extending that out into helping IT identify assets and their hygiene and basically providing more visibility into IT assets. So, we talked about the convergence of that. Maybe we'll get into it, but. >> Dave Vellante: Sure. >> We're doing pretty well. And from our standpoint, we've got a lot of customers, almost 20,000, that rely on us day to day to help stop the breach. >> Well, and when you dig into the CrowdStrike architecture, what's so fascinating is, you know, Dave, we've talked about this: agent bad. Well, not necessarily, if you can have a lightweight agent that can scale and support a number of modules, then you can consolidate all these point tools out there. You talked about in your keynote, your pillars, workloads, which really end points >> Right. >> ID, which we're going to talk about. Identity data and network security. You're not a network security specialist, >> Right. >> But the other three, >> Yes. >> You're knocking down. >> Yeah. >> You guys went deep into that today. Talk about that. >> We did, most folks are going to know us for endpoint and Cloud workload protection and visibility. We did an acquisition almost two years to the day on preempt. And that was our identity play, identity threat protection and detection. And that really turned out to be a smart move, because it's the hottest topic right now. If you look at all the breaches over the last couple years, it's all identity based. Big, big talking points in our keynotes today. >> Dave Vellante: Right. >> And then the third area is on data, and data is really the you know, the new currency that people trade in. So how do you identify and protect endpoints and workloads? How do you tie that together with identity, as well as understanding how you connect the dots and the data and where data flows? And that's really been our focus and we continue to deliver on that for customers. >> And you've had a real dogma, I'll call it, about Cloud Native. I've had this conversation with Frank Slootman, "No we're not going to do a halfway house." You, I think, said it really well today. I think it was you who said it. If you've got On-Prem and Cloud, you got two code bases, >> George Kurtz: Right. >> That you got to maintain. >> That's it, yeah. >> And that means you're taking away resources from one or the other. >> That's exactly right. And what a lot of our competitors have done is they started On-Prem as an AV vendor, and then they took what they had and they basically put it in a Cloud instance called a Cloud, which doesn't really scale. And then, you know, where they need to, they basically still keep their On-Prem, and that just diffuses your engineering team. And most of the On-Prem stuff doesn't even have the features of what they're trying to offer from the Cloud. So either you're Cloud Native or you're not. You can't be halfway. >> But it doesn't mean that you can't include and ingest On-Prem data- >> Well, absolutely. >> into your platform, and that's what I think most people just some reason don't seem to understand. >> Well our agents run wherever. They certainly run On-Prem. >> Dave Vellante: Right. Right. >> And they run in the Cloud, they run wherever. But the crowd in the CrowdStrike is the fact that we can crowdsource this threat information at scale into our threat graph, which gives us unique insight, 7 trillion events per week. And you can't do that if you're not Cloud Native. And that crowd gives the, we call, community immunity. We see all kinds of attacks across 176 different countries. That benefit accrues to all of our customers. >> But how do you envision and maintain and preserve a lightweight agent that can support so many modules? As you do more acquisitions and you knock down new areas and bring in new functionality, go after things like operations technology, how is it that you're able to keep that agent lightweight? >> Well, we started as a platform company, meaning that the whole idea was we're going to build a lightweight agent. First iteration had no security capabilities. It was collect data, get it into a common data architecture or threat graph, in one spot. And then once we had the data then we applied AI to it and we created different workflows. So, the first incarnation was get data into the Cloud at scale. And that still holds true today. So if you think about why we can actually have all these different modules without an impact on the performance, it's we collect data one time. It's a threat data, you know? We're not collecting user data, but threat data collection mechanism. Once we have all that data, then we can slice and dice and create other modules. So the new modules never have to even touch the agent 'cause we've already collected the data. >> I'm going to just keep going, Dave, unless you shove your way in. >> No, no, go ahead. No, no, no. I'm waiting to pounce. >> But okay, so, I think, George, but George, I need to ask you about a comment that you made about we're not just shoving it into a data lake. But you are collecting all the data. Can you explain that nuance? >> Yeah. So there's a difference between a collect and forward agent. It means they just collect a bunch of data. They'll probably store it in a lot of space on the endpoint. It's slow and cumbersome, and then they'll forward it up into another data lake. So you have no context going into no context. Our agent is a smart agent, which actually allows us to always track the context of all these processes in what's happening on the endpoint. And it's a mini graph, meaning we keep track of the relationships. And as we ship that contextual information to the Cloud, we never lose that context. And then it goes into the bigger graph database, always with the same level of context. So, we keep the context of each individual workload or endpoint, and then across the Cloud, we have the context of all of those put together. It's massive. And that allows us to create different insights rather than a data lake, which is, you know, you're looking for, you're creating a bigger needle stack looking for needles. >> And I'm envisioning almost an index that is super, super fast. I mean, you're talking about sub, well second kind of near real time responses, correct? >> Absolutely. So a lot of what we do in terms of protection is already pushed down to the endpoint , 'cause it has intelligence and the AI model. And then again, the Cloud is always looking for different anomalies, not only on each individual endpoint or workload, but across the entire spectrum of our customer base. And that's all real time. It continually self-learns from all the data we collect. >> So when, yeah, when you've made these architectural decisions over time, there was a time when saying that you needed to run an agent could be a deal killer somewhere for people who argued against that. >> George Kurtz: Right. >> You've made the right decision there, clearly. Having everything be crowdsourced into Cloud makes perfect sense. Has that, though, posed a challenge from a sovereignty perspective? If you were deploying stuff On-Prem all over the place, you don't need to worry about that. Everything is here >> George Kurtz: Yeah. >> in a given country. How do you address the challenges of sovereignty when these agents are sending data into some sort of centralized Cloud space that crosses boundaries? >> Well, yeah, I guess what we would, let me go back to the beginning. So I started company in 2011 and I had to convince people that delivering endpoint security from the Cloud was going to be a good thing. >> Dave Vellante: Right. (chuckles) >> You know, you go into a Swiss bank and a bunch of other places and they're like, you're crazy. Right? >> Dave Nicholson: Right. >> They all became customers afterwards, right? And you have to just look at what they're doing. And the question I would have in the early days is, well, let me ask you are you using Dropbox, Box? Are you using a Microsoft? You know, what are you using? Well, they're all sending data to the Cloud. So good news! You already have a model, you've already approved that, right? So let's talk about our benefit. And you know, you can either have an adversary steal your data or you can send threat data to our Cloud, which by the way is in a lot of sovereign Clouds that are out there. And when you actually break it down to what we're sending to the Cloud, it's threat data, right? It isn't user files and documents and stuff. It's threat data. So, we work through all of that. And the Cloud is bigger than CrowdStrike. So you look at Sales Force, Service Now, Workday, et cetera. That's being used all over the place, Box, Dropbox. We just tagged onto it. Like why shouldn't security be the platform of record, and why shouldn't CrowdStrike be the platform of record and be the pillar of Cloud security? >> Explain your observability strategy, 'cause you acquired Humio for, I mean, I think it was $400 million, which is a song. >> Yeah. >> And then Reposify is the latest acquisition. I see that as an extension, 'cause it gives you visibility. Is that part of your security, of your observability play? Explain where you do play and don't play. >> Sure. Well observability is a big, you know, fluffy word. Where we play is in probably the first two areas of observability, right? There's five, kind of, pillars. We're focused on event collection. Let's get events from the endpoints. Let's get events from really anywhere in the network. And we can do that with Humio is now log scale. And then the second piece is with our agents, let's get an understanding of their, the asset itself. What is the asset? What state is it in? Does it have vulnerabilities? Does it have, you know, is it running out of disc space? Is it have, does it have a performance issue? Those are really the first two, kind of, areas of observability. We're not in application performance, we're in let's collect data from the endpoint and other sources, and let's understand if the thing is working, right? And that's a huge value for customers. And we can do that because we already have a privileged spot on the endpoint with our agent. >> Got it. Question on the TAM. Like I look at your TAMs, your charts, I love it. You know, generally do. Were you taking known data from you know, firms like IDC >> George Kurtz: Yeah. >> and saying, okay we're going to play there, now we're made this acquisition. We're new modules, now we're playing there. Awesome. I think you got a big TAM. And I guess that's, that's the point. There's no lack of market for you. >> George Kurtz: Right. >> But I do feel like there's this unknown unquantifiable piece of your TAM. IDC can't see it, 'cause they're kind of looking back >> George Kurtz: Right. >> seein' what the market do last year and we'll forecast it out. It's almost, you got to be a futurist to see it. How do you think about your total available market and the opportunity that's out there? >> Well, it's well in excess of 120 billion and we've actually updated that recently. So it's even beyond that. But if you look at all the modules each module has a discreet TAM and again, for what, you know, what we're focused on is how do you give an outcome to a customer? So a lot of the modules map back into specific TAM and product categories. When you add 'em all up and when you look at, you know, some of the new things that we're coming out with, again, it's well in excess of 120 billion. So that's why we like to say like, you know, we're not an endpoint company. We're really, truly a security platform company that was born in the Cloud. And I think if you see the growth rates, and one of the things that we've talked about, and I think you might have pointed out in prior podcasts, is we're the second fastest company to 2 billion dollars in annual recurring revenue, only behind Zoom. And you know I would argue- great company, by the way, a customer- but that was a black Swan event in a pandemic, right? >> Dave Vellante: I'll say! >> Yeah. >> So we are rarefied air when you think about the capabilities that we have and the performance and the TAM that's available to us. >> The other thing I said in my breaking analysis was 'cause you guys aspire to be a generational company. And I think you got a really good shot at being one, but to be a generational company, you have to have an ecosystem. So I'd love you to talk about the ecosystem, but where you want to see it in five years. >> Well, it really is a good point and we are a partner first company. Ecosystem is really important. Cameras probably can't see all the vendors that are here that are our partners, right? It's a big part of this show that we're at. You see a lot of, well, you see some vendors behind us. >> Yep. >> We have to realize in 2022, and I think this is something that we did well and it's my philosophy, is we are not the only game in town. We like to be, and we are, for many companies the security platform on record, but we don't do everything. We talked about network in other areas. We can't do everything. You can't be good and try to do everything. So, for customers today, what they're looking at is best of platform. And in the early days of security, I've been in it over 30 years, it used to be best of breed products, then it was best of suite, now it's best of platform. So what do I mean by that? It means that customers don't want to engineer their own solution. They, like Lego blocks, they want to pull the platforms, and they want to stitch 'em together via API. And they want to say, okay, CrowdStrike works with Okta, works with Zscaler, works with Proofpoint, et cetera. And that's what customers want. So, ecosystem is incredibly important for us. >> Explain that. You mentioned Okta, I had another question for you. I was at Reinforce, and I saw this better together presentation, CrowdStrike and Okta talking about identity. You've got an identity module. Explain to people how you're not competing with Okta. You guys complement each other, there. >> Well, an identity kind of broker, if you will, is basically what Okta does in others, right? So you log in single sign on and you get access. They broker access to all these other applications. >> Dave Vellante: Right. >> That's not what we do. What we do is we look at those endpoints and workloads and domain controllers and directory services and we figure out, are there vulnerabilities and are there threats associated with them? And we call that out. The second piece, which is critical, is we prevent lateral movement. So if credentials are stolen we can prevent those credentials from being laundered or used and moved laterally, which is a key part of how breaches happen. We then create a trust score on those endpoints and workloads. And we basically say, okay, do we think the trust on the endpoint and workload is high or low? Do we think the identity, you know, is it George on the endpoint, or not? We give that a score. And we pass that along to Okta or Ping or whoever, and they then use that as part of their calculus in how they broker access to other resources. So it really is better together. >> So your execution has been stellar. This is my competition question. You obviously have competition out there. I think architecturally, you've got some advantages. You have a great relationship with AWS. I don't know what's going on with Google, but Kevin's up on stage. >> George Kurtz: Yeah. >> They're now part of Google. >> George Kurtz: We have a great relationship with them. >> Microsoft obviously, a competitor. You obviously do some things in, >> Right. >> in Azure. Are you building the security Cloud? >> We are. We think we are, because when you look at the amount of data that we actually ingest, when you look at companies using us for critical decisions and critical protection, not only on their On-Prem, but also in their Cloud environment, and the knowledge we have, we think it is a security Cloud. You know, you had, you had Salesforce and Workday and ServiceNow and each of them had their respective Clouds. When I started the company, there was no security Cloud. You know, it wasn't any of the companies that you know. It wasn't the firewall companies, wasn't the AV companies. And I think we really defined ourselves as the security Cloud. And the level of knowledge and insights we have in our Cloud, I think, are world class. >> But you know, it's a difference of being those- 'cause you mentioned those other, you know, seminal Clouds. They, like Salesforce, Workday, they're building their own Clouds. Maybe not so much Workday, but certainly Salesforce and ServiceNow built their own >> Yeah. >> Clouds, their own data centers. You're building on top of hyperscalers, correct? >> Well, >> Well you have your own data centers, too. >> We have our own data centers, yeah. So when we first started, we started in AWS as many do, and we have a great relationship there. We continue to build out. We are a huge customer and we also have, you know, with data sovereignty and those sort of things, we've got a lot of our sort of data that sits in our private Cloud. So it's a hybrid approach and we think it's the best of both worlds. >> Okay. And you mean you can manage those costs and it's, how do you make the decision? Is it just sovereignty or is it cost as well? >> Well, there's an operational element. There's cost. There's everything. There's a lot that goes into it. >> Right. >> And at the end of the day we want to make sure that we're using the right technology in the right Clouds to solve the right problem. >> Well, George, congratulations on being back in person. That's got to feel good. >> It feels really good. >> Got a really good audience here. I don't know what the numbers are but there's many thousands here, >> Thousands, yeah. >> at the ARIA. Really appreciate your time. And thanks for having The Cube here. You guys built a great set for us. >> Well, we appreciate all you do. I enjoy your programs. And I think hopefully we've given the audience a good idea of what CrowdStrike's all about, the impact we have and certainly the growth trajectory that we're on. So thank you. >> Fantastic. All right, George Kurtz, Dave Vellante for Dave Nicholson. We're going to wrap up day one. We'll be back tomorrow, first thing in the morning, live from the ARIA. We'll see you then. (calm music)

>>Hey guys. Good morning. And welcome back to the cube. Lisa Martin here with John furrier. This is the Cube's third day of Wal Dal coverage of VMware Explorer. We're very pleased to welcome one of our alumni back to the program. Chris Wolf joins us chief research and innovation officer at VMware. Chris, welcome back to the >>Cube. Yeah. Thanks Lisa. It's always a pleasure. >>This has been a great event. We, we, the key note was standing room only on Tuesday morning. We've had great conversations with VMware's ecosystem and VMware of course, what are some of the, the hot things going on from an R and D perspective? >>Yeah, there's, there's a lot. I mean, we're, we have about four or five different priorities. And these look at this is looking at sovereign clouds and multi-cloud edge computing, modern applications and data services. We're doing quite a bit of work in machine learning as well as insecurity. So we're, we're relatively large organization, but at the same time, we really look to pick our bets. So when we're doing something in ML or security, then we wanna make sure that it's high quality and it's differentiated and adds value for VMware, our partners and our customers. >>Where are our customers in the mix in terms of being influential in the roadmap? >>Very, very much in the mix. What we, what we like to do is in early stage R and D, we want to have five to 10 customers as design partners. And that really helps. And in addition to that, as we get closer to go to market, we look to a lineup between one and three of our SI partners as well, to really help us, you know, in a large company, sometimes your organic innovations can get lost in the shuffle. Yeah. And when we have passionate SI that are like, yes, we want to take this forward with you together. That's just awesome. And it also helps us to understand at a very early stage, what are the integration requirements? So we're not just thinking about the, the core product itself, but how would it play in the ecosystem equally important? >>We had hit Culbert on CTO, great work. He's dealing with the white paper and cross cloud, obviously vSphere, big release, lot of this stuff. Dave ante had mentioned that in the analyst session, you had a lot of good stuff you were talking about. That's coming around the corner. That's shipping coming outta the oven and a big theme this year is multi-cloud cloud native. The relationship what's one's ahead. Bleed dog. No one, you kinda get a feel for multi-cloud. It's kind of out front right now, but now cloud native's got the most history what's coming out of the oven right now in terms of hitting the market. That's not yet in this, in the, in the, in the numbers, in terms of sales, like there's, there's some key cloud native stuff coming out. Where's the action. Can you share what you've shared at the analyst meeting? >>Yeah. So at the analyst meeting, what I was going through was a number of our new innovation projects or projects. And, and these are things that are typically close to being product or service at VMware, you know, somewhere in the year out timeframe. Some, some of these are just a few months out. So let me just go through some of them, I'll start with project keek. So keek is super exciting because when you think about edge, what we're hearing from customers is the, the notion of a single platform, a single piece of hardware that can run their cloud services, their containers, their VMs, their network, and security functions. Doing all of this on one platform, gives them the flexibility that as changes happen, it's a software update. They don't have to buy another piece of hardware, but if we step back, what's the management experience you want, right? >>Simple get ops oriented, simple life cycle and configuration management, very low touch. I don't need technical skills to deploy these types of devices. So this is where keek comes in. So what keek is doing is exposing a Kubernetes API above the ESXi hypervisor and taking a complete, get op style of management. So imagine now, when you need to do an update for infrastructure, you're logging into GitHub, you're editing a YAML file and pushing the update. We're doing the same thing for the applications that reside. I can do all of this through GitHub. So this is very, I would say, even internally disruptive to VMware, but super exciting for our customers and partners that we've shared this with. >>What else is happening? What else on the cloud native side Tansu Monterey those lot areas. >>Oh, there's so much. So if we look at project Monterey, I had a presentation within Invidia yesterday. We're really talking through this. And what I'm seeing now is there's a couple of really interesting inflection points with DPU. The first thing is the performance that you're getting and the number of cores that you can save on an X 86 host is actually providing a very strong business case now to bring DPU into the servers, into the data center. So that's one. So now you have a positive ROI. Number two, you start to decouple core services now from the X 86 host itself. So think about a distributed firewall that I can run on a PCI adapter. Now that's DEC coupled, physically from the server, and it really allows me to scale out east west security in a way that I could not do before. So again, I think that's really exciting and that's where we're seeing a lot of buzz from customers. >>So that DPU, which got a lot of buzz, by the way, Lisa, I never, you had trouble interviews on this. I had to the Dell folks too, V X RS taking the advantage of it, the performances, I see the performance angle on that and deep user hot. Can you talk about that security east west thing? Cuz Tom Gillis was on yesterday talking about that's a killer advantage for the security side. Can you touch on that real >>Quick? Yeah. A hundred percent. So what I can now do is take a, a firewall and run it isolated from the X 86 host that it's trying to protect. So it's right next to the host. I can get line rate speeds in terms of analytics and processing of my network and security traffic. So that's also huge. So I'm running line rate on the host and I'm able to run one of these firewall instances on every host in my data center, you cannot do that. You can never afford it with physical appliances. So to me, this is an inflection point because this is the start of network and security functions moving off of hardware appliances and onto DPU. And if you're the ecosystem vendors, this is how they're going to be able to scale some of their services and offerings into the public >>Cloud. So a lot of good stuff happening within the VMware kind of the hardware, low level atoms and the bits as well as the software. The other thing I wanna get your thoughts on relative to the next question is that takes to the next level is the super cloud world we're living in is about cloud native developers, which is DevOps dev security ops and data ops are now big parts of the, the challenges that the people are reigning in the chaos that that's being reigned in. How does VMware look at the relationship to the cloud providers? Cause we heard cloud universal. We had the cloud. If you believe in multi-cloud, which you guys are saying, people are agreeing with, then you gotta have good tight couple coupled relationships with the cloud services, >>A hundred percent. >>We can be decoupled, but highly cohesive, but you gotta connect in via APIs. What's the vision for the VMware customers who want to connect say AWS, for instance, is that seamless? What makes that happen? What's that roadmap look like for taking that VMware on premises hybrid and making it like turbo charging it to be like public cloud hybrid together? >>Yeah, I think there's some lessons that can be learned here. You know, an analogy I've been using lately is look at the early days of virtualization when VMware had vCenter, right? What was happening was you saw the enterprise management vendors try to do this overlay above virtualization management and say, we can manage all hypervisors. And at the end of the day, these multi hypervisor managers, no one bought 'em because they can do 20% of the functionality of a tool from VMware or Microsoft. And that's the lesson that we have to take to multi-cloud. We don't have to overlay every functionality. There's really good capabilities that the cloud providers are offering through their own tooling and APIs. Right? But you, you, if you step back, you say, well, what do I wanna centralize? I wanna have a centralized, secure software supply chain and I can get that through VMware tan zoo and, and where we're going with Kubernetes. When you're going with native cloud services, you might say, you know what, I wanna have a central view of, of visibility for compliance. So that's what we're doing with secure state or a central view of cost management. And we're doing that with cloud health. So you can have some brokering and governance, but then you also have to look from a surgical perspective as to what are the things that I really need to centralize versus what do I not need to centralize? >>One of the themes that we heard on the keynote on Tuesday was the, the different phases and that a lot of customers are still in the cloud chaos phase. We talked a lot about that in the last couple days with VMware, with its partner ecosystem. And, but the goal of getting to cloud smart, how does the R and D organization, how do, how are you helping customers really navigate that journey from the chaos that they're in, maybe they've inherited multi-cloud environment to getting to cloud smart. And what does cloud smart mean from your perspective >>Cloud? Smartt from my perspective means pragmatism. It means really thinking about what should I do here first, right? I don't want to just go somewhere because I can, right. I want to be really mindful of the steps I'm going to take. So one ex one example of this is I've met with a customer this morning and we were talking about using our vRealize network insight tool, because what that allows 'em to do is get a map of all of their application dependencies in their data center. And they can learn like, well, I can move this to the cloud or maybe I can't move this cuz it has all these other dependencies and it would be really difficult. So that's that's one example. It also means really thinking through issues around data sovereignty, you know, what do I wanna hold onto a customer? I just met with yesterday. They were talking about how valuable their data is and their services that they want to use via SA in the cloud. But then there's also services, which is their core research. They wanna make sure that they can maintain that in their data centers and maintain full control because they see researchers will leave. And now all of a sudden, so that intellectual property has actually gone with the person and they need to, they need to have, you know, better accountability there. >>Yeah. One of the things about that we discovered at our super cloud event was is that, you know, we kind didn't really kind of put too much structure on other than our, our vision. It's, it's not just SaaS on cloud and it's not just, multi-cloud, it's a new kind of application end state or reality that if you believe in digital transformation, then technology is everywhere. And like it in the old days, it powered the back office and then terminals and PCs and whatnot, wasn't powering the boardroom obviously or other business. But if, if it happens like that digital transformation, the company is the app, the app is the company. So you're all digital. So that means the operating expenses has to drive an income statement and the CapEx handled by the cloud provides a lot of goodness. So I think everyone's gonna realize that AWS and the hyperscalers are providing great CapEx gifts. They do all the work and you only pay when you've made your success. So that's a great business model. >>Absolutely >>That's and then combine that with open source, which is now growing so fast, going next level, the software industry's open source. That's not even a debate Mo in some circles, maybe like telco, cloud's got the CapEx. The new operating model is this cloud layer. That's going to transform the companies finally in a hundred percent. Okay. That's super cloud. If that's the case, does it really matter who provides the electricity or the power? It's the coders that are in charge. It's the developers that have to make the calls because if the application is the core, the developers are, are not only the front lines, they are the company. This is really kind of where the sea change is. So if, if we believe that, I'm sure you, you agree with that generally? >>Yeah, of >>Course. Okay. So then what's the VMware customer roadmap here. So to me, that's the big story here at the show is that we're at this point in time where the VMware customers are, have to go there >>A hundred percent, >>What's that path. What is the path for the VMware customer to go from here to there? And what's this order of operations or is there a roadmap? Can, can you share your thoughts on >>That? Yeah, I think part of it is, is with these disruptive technologies, you have to start small, you know, whether it's in your data center, into cloud, you have to build the own institutional knowledge of your team members in the organization. It's much easier than trying to attract outside talent, for least for many of our customers. So I think that's important. The other part of this when with the developer and control, like in my organization, I want my innovators to innovate any other noise around them. I don't want them to have to worry about it. And it's the same thing with our customers. So if your developers are building the technologies that is really differentiating your company, then things like security and cryptography shouldn't have to be things they worry about. So we've been doing a lot of work. Like one of the projects we announced this week was around being able to decouple cryptography from the applications themselves. And we can expose that through a proxy through service mesh. And that's really exciting because now it ops can make these changes. Our SecOps teams can make these changes without having to impact the application. So that's really key is focusing the developers on innovation and then really being mindful about how you can build the right automation around everything else. And certainly open source is key to all >>That. So that's so, so then if you, if that's happening, which I'm, I'm not gonna debate that then in essence, what's really going on here is that the companies are decomposing their entire businesses down to levels that are manageable completely different than the way they did them 20, 30 years ago. >>Absolutely. You, you, you could take a modular approach to how you're solving business problems. And we do the same thing with technology, where there might be a ML algorithms that we've developed that we're exposing as SA service, but then all of the interconnects around that service are open source and very flexible so that the businesses and the customers and the VMware partners can decide what's the right way to build a puzzle for a given problem. >>We were talking on day one, I was riffing with an executives. It was Ragu and Victoria. And the concept around cross cloud was if you get to this Nirvana state, which is we, people want to get to this or composability mode, you're not coding, you're composing cuz coding's kinda happening open source and not the old classic, write some code and write that app. It's more orchestrate, compose and orchestrate. Do you, what's your thoughts on >>That? Yeah, yeah. Yeah. I, I agree. And it's it's I would add one more part to it too, which is scope. You know, I think sometimes we see projects fail because the, the initial scope is just too big. You know, what is the problem that you need to solve, scope it properly and then continuously calibrate. So even like our customers have to listen to their customers and we have to be thinking about our customers' customers, right? Because that's really how we innovate because then we can really be mindful of a holistic solution for them. >>You know, Lisa, when we had a super cloud event, you know, one of the panels was called the innovators dilemma with a question mark. And of course everyone kinds of quotes that book innovators dilemma, but one of the panelists, Chris ho beaker on Twitter said, let's change the name from the innovator's dilemma to the integrator's dilemma. And we all kind of got chuckled. We all kind of paused and said, Hey, that's actually a good point. Yeah. If you're now in a cloud and you're seeing some of the ecosystem floor vendors out there talking in this game too, they're all kind of fitting in snapping in almost like modular, like you said, so this is a Lego game. Now it feels like, it feels like, you know, let's compose, let's orchestrate, let's integrate. Now I integrations API driven. Now you're seeing a lot more about API security in the news and we've been covering at least I've probably interviewed six companies in the past, you know, six months that are doing API security, who would've thought API, that's the link, frankly, with the web. Now that's now a target area for hackers. >>Oh. And that's such an innovation area for VMware, John. Okay. >>There it is. So, I mean, this is, again, this means the connected tissue is being attacked yet. We need it to grow. No one's debating that is wrong, but it's under siege. >>Yes. Yes. So something else we introduced this week was a project. We called project Trinidad. And the way, the way you can think about it is a lot of the anomaly detection software today is looking at point based anomalies. Like this API header looks funny where we, where we've gone further is we can look at full sequence based anomalies so we can learn the sequences of transactions at an application takes and really understand what is expected behavior within those API calls within the headers, within the payloads. And we can model legitimate application behavior based on what those expectations are. So like a, like a common sequence might be doing an e-commerce checkout, right? There's lots of operations that happen logging into the site, searching, finding a product, going through the cart. Right. All of those things. Right. So if something's out of sequence, like all of a sudden somebody's just trying to do a checkout, but they haven't actually added to the cart. Right. This just seems odd. Right. So we can start to, and that's a simplistic example, but we're able now to use our algorithms to model legitimate application behavior through the entire sequence of how applications behave and then we can start to trap on anomalies. That's very differentiating IP and, and we think it's gonna be really important for the industry. Yeah. >>Because a lot of the hacks, sometimes on the API side, even as a example, are not necessarily on the API, it's the business logic in them. That's what you're getting at here. Yes. The APIs are hard. Oh our APIs are secure. Right. Well, yeah, but you're not actually securing the business logic internally. That's what you're getting at. If I read >>That right. Or exactly. Exactly. Yeah. Yeah. And it, it's the thing it's right. It's great that you can, you can look at a header, but what's the payload, right? What is what's, what's the actual data flow, right. That's associated with the call and that's what we want to really hone in on. And that's just a, it's, it's a, it's a far different level of sophistication in being able to understand east west vulnerabilities, you know, log for JX voice and these kind of things. So we have some real, it's interesting technology >>There. Security conversations now are not about security there about defense ability because security's a state of time, your secure here, you're not secure or someone might be in the network or in the app, but can you defend yourself from, and in >>That's it, you know, our, our, our malware software, right. That we're building to prevent and respond has to be more dynamic than the threats we face. Right. And this is why machine learning is so essential in, in these types of applications. >>Let me ask you a question. So just now zooming out riffing here since day, three's our conversational day where we debate and just riff more like a podcast style. If you had to do a super cloud or build a NextGen cloud multi-cloud with abstraction layer, that's, you know, all singing and dancing and open everyone's happy hardware below it's working ISAs and then apps are killed. Can ass what's in that. What does it look like to you if you had to architect the, the ultimate super cloud enabler, that something that would disrupt the next 10 years, what would it look like and how does, and assuming, and trying to do where everybody wins go, you have 10 seconds. No, >>Yeah, yeah. So the, you know, first of all, there has to be open source at all of the intersections. I think that's really important. And, and this is, this goes from networking constructs to our database, as a service layers, you know, everything in between, you know, the, the, the participants should be able to win on merit there. The other part of super cloud though, that hasn't happened that I probably is the most important area of innovation is going to be decoupled control planes. We have a number of organizations building sovereign cloud initiatives. They wanna have flexibility in where their services physically run. And you're not going to have that with a limited number of control planes that live in very specific public cloud data centers. So that's an area, give >>An example of what a, a, a, a narrowly defined control plane is. >>Yeah, sure. So my database as a service layer, so the, the, the actual portal that the customer is going into to provision databases, right. Rep managed replication, et cetera. Right. I should be able to run that in a colo. I should be able to run that somewhere in region that is guaranteed, that I'm going to have data stay physically in region. You know, we still have some of these challenges in networking in terms of being able to constrain traffic flows and be able to predict and audit them within a particular region as well. >>It's interesting. You bring up region again, more complexity. You know, you got catalogs here, catalogs different. I mean, this is where the chaos really comes down. I mean, it's, it's advancing, but it's advancing the state of functionality, but making it hella complex, I mean, come on. Don't you think it's like pretty amazingly hard to reign in that? Well, or is it maybe you guys making it easier? I just think I just, my mind just went, oh my God, I gotta, I gotta provision to that region, but then it's gotta be the same over there. And >>When you go back to modular architecture constructs, it gets far easier. This has been really key for how VMware is even building our own clouds internally is so that we have a, a shared services platform for the different apps and services that we're building, so that you do have that modularized approach. Like I said, the, the examples of innovation projects I've shared have been really driven by the fact that, you know, what, I don't know how customers are gonna consume it, and I don't have to know. And if you have the right modular architecture, the right APIs around it, you don't have to limit a particular project or technology's future at the time you build >>It. Okay. So your super would have multiple control planes that you can move, manage with that within one place. I get that. What about the data control plane? That seems to be something that used to be the land grab in, in conversations from vendors. But that seems to be much more of a customer side, cuz if I'm a customer, I want my control plane data plane to be, you know, mine. Like I don't want to have anyone cuz data's gotta move around, gotta be secure. >>Oh exactly. >>And that's gonna be complicated. How does, how do you see the data planes emerging? >>Yeah. Yeah. We, we see an opportunity really around having a, a centralized view that can give me consistent indexing and consistent awareness of data, no matter where it resides. And then being able to have that level of integration now between my data services and my applications, because you're right, you know, right now we have data in different places, but we could have a future where data's more perpetually in motion. You know, we're already looking at time sensitive fabrics where we're expecting microservices to sometimes run in different cell towers depending on the SLA that they need to achieve. So then you have data parts that's going to follow, right? That may not always be in the same cloud data center. So there's, this is enormously complicated, not just in terms of meeting application SLAs, but auditing and security. Right. That makes it even further. So having these types of data layers that can give me a consistent purview of data, regardless of where it is, allow me to manage and life cycle data globally, that's going to be super important, I believe going forward. >>Yeah. Awesome. Well, my one last question, Lisa, gonna get a question in here. It's hard. Went for her. I'm getting all the, all the questions in, sorry, Lisa that's okay. What's your favorite, most exciting thing that you think's going on right now that people should pay attention to of all the things you're looking at, the most important thing that that's happening and maybe something that's super important that people aren't talking about or it could be the same thing. So the, the most important thing that you think that's happening in the industry for cloud next today and, and maybe something that you think people should look at and pay more attention to. >>Okay. Yeah, those are good questions. And that's hard to answer because there's, there's probably so much happening. I I've been on here before I've talked about edge. I still think that's really important. I think the value of edge soft of edge velocity being defined by software updates, I think is quite powerful. And that's, that's what we're building towards. And I would say the industry is as well. If you look at AWS and Azure, when they're packaging a service to go out to the edge it's package as a container. So it's already quite flexible and being able to think about how can I have a single platform that can give me all of this flexibility, I think is really, really essential. We're building these capabilities into cars. We have a version of our Velo cloud edge device. That's able to run on a ruggedized hardware in a police car today. We're piloting that with a customer. So there is a shift happening where you can have a core platform that can now allow you to layer on applications that you're not thinking about in the future. So I think that's probably obvious. A lot of people are like, yeah. Okay. Yes. Let's talk about edge, big deal. >>Oh it's, it's, it's big. Yes. It's >>Exploding, but >>It's complicated too. It's not easy. It's not obvious. Right. And it's merging >>There's new things coming every day. Yeah. Yeah. And related to that though, there is this kind of tension that's existing between machine learning and privacy and that's really important. So an area of investment that I don't think enough people are paying attention to today is federated machine learning. There's really good projects in open source that are having tangible impact on, in a lot of industries in VMware. We are, we're investing in a, in a couple of those projects, namely fate in the Linux foundation and open FFL. And in these use cases like the security product I mentioned to you that is looking at analyzing API sequence API call sequences. We architected that originally so that it can run in public cloud, but we're also leveraging now federated machine learning so that we can ensure that those API calls and metadata associated with that is staying on premises for the customers to ensure privacy. So I think those intersections are really important. Federated learning, I think is a, an area not getting enough attention. All right. All >>Right, Chris, thanks so much for coming on. Unfortunately we are out of time. I know you guys could keep going. Yeah. Good stuff. But thank you for sharing. What's going on in R and D the customer impact the outcomes that you're enabling customers to achieve. We appreciate your >>Insights. We're just getting started >>In, in early innings, right? Yeah. Awesome. Good stuff for guest and John furrier. I'm Lisa Martin. You're watching the cube live from VMware Explorer, 2022. Our next guest joins us momentarily. >>Okay.

(upbeat music) >> Hey everyone. Welcome to theCUBE's coverage of VMware Explore 2022. We are at Moscone West. Lisa Martin and Dave Nicholson here. Excited, really excited, whereas they were saying in the VMware keynote, pumped and jacked and jazzed to be back in-person with a lot of folks here. Keynote with standing room only. We've just come from that. We've got a couple of guests here from Expedient, going to unpack their relationship with VMware. Please welcome Brian Smith, the Senior Vice President and Chief Strategy Officer at Expedient. And Brent Meadows, the Vice President of Advanced Solution Architecture at Expedient. Guys it's great to have you on the program. >> Appreciate it bringing us on. >> Yep, welcome. >> Isn't it great to be back in person? >> It is phenomenal to be back. >> So let's talk about obviously three years since the last, what was called VMworld, so many dynamics in the market. Talk to us about what's going on at Expedient, we want to dig into Cloud Different, but kind of give us a lay of the land of what's going on and then we're going to uncrack the VMware partnership as well. >> Sure, so Expedient we're a full stack cloud service provider. So we have physical data centers that we run and then have VMware-based cloud and we've seen a huge shift from the client perspective during the pandemic in how they've really responded from everything pre-pandemic was very focused with Cloud First and trying to go that route only with hyper scaler. And there's been a big evolution with how people have to change how they think about their transformation to get the end result they're looking for. >> Talk about Cloud Different and what it's helping customers to achieve as everyone's in this accelerated transformation. >> Yeah. So, Cloud Different is something that Expedient branded. It's really about how the transformation works. And traditionally, companies thought about doing their transformation, at first they kept everything in house that they were doing and they started building their new applications out into a hyper scale cloud. And what that really is like is, a good analogy would be, it's like living in a house while you're renovating it. And I know what that's like from my relationship versus if you build a new house, or move to a new property that's completed already. And that's really the difference in that experience from a Cloud Different approach from transformation is you think of all the things that you have internally, and there's a lot of technical debt there, and that's a lot of weight that you're carrying when you're trying to do that transformation. So if you kind of flip that around and instead look to make that transformation and move all that technical debt into a cloud that's already built to run those same types of applications, a VMware-based cloud, now you can remove all of that noise, move into a curated stack of technology and everything just works. It has the security in place, your teams know how to run it, and then you can take that time you really reclaim and apply that towards new applications and new things that are strategic to the business. >> That's really critical, Brent, to get folks in the IT organization across the business, really focused on strategic initiatives rather than a lot of the mundane tasks that they just don't have time for. Brent, what are you hearing in the last couple of years with the dynamics we talked about, what are you hearing from the customer? >> Right. So, one of the big things and the challenges in the current dynamic is kind of that staffing part. So as people have built their infrastructure over the years, there's a lot of tribal knowledge that's been created during that process and every day more and more of that knowledge is walking out the door. So taking some of that technical debt that Brian mentioned and kind of removing that so you don't have to have all that tribal knowledge, really standardizing on the foundational infrastructure pieces, allows them to make that transition and not have to carry that technical debt along with them as they make their digital transformations. >> We heard a lot this morning in the keynote guys about customers going, most of them still being in cloud chaos, but VMware wanting them to get to cloud smart. What does that mean, Brian, from Expedient's perspective? What does cloud smart look like to Expedient and its customers? >> Yeah, we completely agree with that message. And it's something we've been preaching for a couple years in part of that Cloud Different story. And it's really about having a consistent wrapper across all of your environments. It doesn't matter if it's things that you're running on-premises that's legacy to things that are in a VMware-based cloud, like an Expedient cloud or things that are in a hyper scale, but having one consistent security, one consistent automation, one consistent cost management, really gives you the governance so that you can get the value out of cloud that you are hoping for and remove a lot of the noise and think less about the technology and more about what the business is getting out of the technology. >> So what does that look like as a practical matter? I imagine you have customers whose on-premises VMware environments look different than what you've created within Expedient data centers. I'm thinking of things like the level of adoption of NSX, how well a customer may embrace VSAN on-prem as an example. Is part of this transmogrification into your data center, kind of nudging people to adopt frameworks that are really necessary for success in the future? >> It's less of a nudge because a lot of times as a service provider, we don't talk about the technology, we talk more about the outcome. So the nice thing with VMware is we can move that same virtual machine or that container into the platform and the client doesn't always know exactly what's underneath because we have that standardized VMware stack and it just works. And that's part of the beauty of the process. I dunno if you want to talk about a specific client or... >> Yeah, so one of the ones we worked with is Bob Evans Foods. So they were in that transformation stage of refreshing, not only their office space and their data center, but also their VMware environment. So we helped them go through and first thing is looking at their existing environment, figuring out what they currently have, because you can't really make a good decision of what you need to change until you know where you're starting from. So we worked with them through that process, completely evacuated their data center. And from a business perspective, what that allowed them to do as well is have more flexibility in the choice of their next corporate office, because they didn't have to have a data center attached to it. So just from that data center perspective, we gave them some flexibility there. But then from an operations perspective, really standardize that process, offloaded some of those menial tasks that you mentioned earlier, and allow them to really look more towards business-driving projects, instead of just trying to keep those lights on, keeping the backups running, et cetera. >> Brian, question for you, here we are, the theme of the event is "The Center of the Multi-cloud Universe" which seems like a Marvel movie, I haven't seen any new superheroes yet, but I suspect there might be some here. But as customers end up and land in multi-cloud by default not by strategy, how does Expedient and VMware help them actually take the environment that they have and make it strategic so that the business can achieve the outcomes, improving revenue, finding new revenue streams, new products, new routes to market to delight those customers. How do you turn that kind of cloud chaos into a strategy? >> Yeah. I'd say there's a couple different components. One is really time. How can you give them time back for things that are creating noise and aren't really strategic to the business? And so if you can give that time back, that's the first way that you can really impact the business. And the second is through that standardization, but also a lot of times when people think of that new standard, they're only thinking if you're building from scratch. And what VMware has really helped is by taking those existing workloads and giving a standard that works for those applications and what you're building new and brings those together under a common platform and so had a really significant impact to the speed that somebody can get to that cloud operating model, that used to be a multi-year process and most of our clients can go from really everything or almost everything on-prem and a little bit in a cloud to a complete cloud operating model, on average, in four to six months. >> Wow! >> So if I have an on-premises environment and some of my workloads are running in a VMware context, VMware would make the pitch in an agnostic way that, "Well, you can go and deploy that "on top of a stack of infrastructure "and anybody and anywhere now." Why do customers come to you instead of saying, "Oh, we'll go to "pick your flavor of hyper scale cloud provider." What's kind of your superpower? You've mentioned a couple of things, but really hone it in on, why would someone want to go to Expedient? >> Yeah. In a single word, service. I mean, we have a 99% client retention rate and have for well over a decade. So it's really that expertise that wraps around all the different technology so that you're not worried about what's happening and you're not worried about trying to keep the lights on and doing the firefighting. You're really focused on the business. And the other way to, I guess another analogy is, if you think about a lot of the technology and the way people go to cloud, it's like if you got a set of Legos without the box or the instructions. So you can build stuff, it could be cool, but you're not going to get to that end state-- >> Hold on. That's how Legos used to work. Just maybe you're too young to remember a time-- >> You see their sales go up because now you buy a different set for this-- >> I build those sets with my son, but I do it grudgingly. >> Do you ever step on one? >> Of course I do. >> Yeah, there's some pain involved. Same thing happens in the transformation. So when they're buying services from an Expedient, you're buying that box set where you have a picture of what your outcome's going to be, the instructions are there. So you also have confidence that you're going to get to the end outcome much faster than you would if you're trying to assemble everything yourself. (David laughing) >> In my mind, I'm imagining the things that I built with Lego, before there were instructions. >> No death star? >> No. Nothing close with the death star. Definitely something that you would not want your information technology to depend upon. >> Got it. >> Brent, we've seen obviously, it seems like every customer these days, regardless of industry has a cloud first initiative. They have competitors in the rear view mirror who are, if they're able to be more agile and faster to market, are potential huge competitive threat. As we see the rise of multi-cloud in the last 12 months, there's also been a lot of increased analyst coverage for alternate specialty hybrid cloud. Talk to us about, Expedient was in the recent Gartner market guide for specialty cloud. How are these related? What's driving this constant change out in the customer marketplace? >> Sure. So a lot of that agility that clients are getting and trying to do that digital transformation or refactor their applications requires a lot of effort from the developers and the internal IT practitioners. So by moving to a model with an enterprise kind of like Expedient, that allows them to get a consistent foundational level for those technical debt, the 'traditional workloads' where they can start focusing their efforts more on that refactoring of their applications, to get that agility, to get the flexibility, to get the market advantage of time to market with their new refactored applications. That takes them much faster to market, allows them to get ahead of those competitors, if they're not already ahead of them, get further ahead of them or catch up the ones that may have already made that transition. >> And I would add that the analyst coverage you've seen in the last 9 to 12 months, really accelerate for our type of cloud because before everything was hyper scale, everything's going to be hyper scale and they realized that companies have been trying to go to the cloud really for over a decade, really 15 years, that digital transformation, but most companies, when you look at the analysts say they're about 30% there, they've hit a plateau. So they need to look at a different way to approach that. And they're realizing that a VMware-based cloud or the specialty cloud providers give a different mode of cloud. Because you had of a pendulum that everything was on-premises, everything swung to cloud first and then it swung to multi-cloud, which meant multiple hyper scale providers and now it's really landing at that equilibrium where you have different modes of cloud. So it's similar like if you want to travel the world, you don't use one mode of transportation to get from one continent to the other. You have to use different modes. Same thing to get all the way to that cloud transformation, you need to use different modes of cloud, an enterprise cloud, a hyper scale cloud, working them together with that common management plan. >> And with that said Brian, where have customer conversations gone in the last couple of years? Obviously this has got to be an executive level, maybe even a board level conversation. Talk to us about how your customer conversations have changed. Have the stakeholders changed? Has things gone up to stack? >> Yeah. The business is much more involved than what it's been in the past and some of the drivers, even through the pandemic, as people reevaluate office space, a lot of times data centers were part of the same building. Or they were added into a review that nobody ever asked, "Well, why are you only using 20% of your data center?" So now that conversation is very active and they're reevaluating that and then the conversation shifts to "Where's the best place?" And that's a lot of, the conference also talks about the best place for your application for the workload in the right location. >> My role here is to dive down into the weeds constantly to stay away from business outcomes and things like that. But somewhere in the middle there's this question of how what you provide is consumed. So fair to assume that often people are moving from CapEx model to an OPEX model where they're consuming by the glass, by the drink. What does that mean organizationally for your customers? And do you help them work through that journey, reorganizing their internal organization to take advantage of cloud? Is that something that Expedient is a part of, or do you have partners that help them through that? How does that work? >> Yeah. There's some unique things that an enterprise doesn't understand when they think about what they've done on-prem versus a service provider is. There's whole models that they can purchase with us in consumption, not just the physical hardware, but licensing as well. Do you want to talk about how clients actually step in and start to do that evaluation? >> Sure. So it really kind of starts on the front end of evaluating what they have. So going through an assessment process, because traditionally, if you have a big data center full of hardware, you've already paid for it. So as you're deploying new workloads, it's "free to deploy." But when you go to that cloud operating model, you're paying for each drink that you're taking. So we want to make sure that as they're going into that cloud operating model, that they are right sized on the front end. They're not over-provisioned on anything that they're going to just waste money and resources on after they make that transition. So it's really about giving them great data on the front end, doing all that collection from a foundational level, from a infrastructure level, but also from a business and IT operations perspective and figuring out where they're spending, not just their money, but also their time and effort and helping them streamline and simplify those IT operations. >> Let's talk about one of the other elephants in the room and that is the remote hybrid workforce. Obviously it's been two and a half years, which is hard to believe. I think I'm one of the only people that hates working from home. Most people, do you too? Okay, good. Thank you, we're normal. >> Absolutely. (Lisa laughing) But VMware was talking about desktop as a service, there was so much change and quick temporary platform set up to accommodate offsite workers during the pandemic. What are some of the experiences that your clients are having and how is Expedient plus VMware helping businesses adapt and really create them the right hybrid model for them going forward? >> Sure. So as part of being that full sack cloud service provider, desktop in that remote user has to be part of that consideration. And one of the biggest things we saw with the pandemic was people stood up what we call pandemic VDI, very temporary solutions. And you saw the news articles that they said, "We did it in 10 days." And how many big transformational events do people plan and execute in 10 days that transform their workforce? So now they're having to come back and say, "Okay, what's the right way to deploy it?" And do you want to talk about some of the specifics of what we're seeing in the adjustments that they're doing? >> Sure. So it is, when you look at it from the end user perspective, it's how they're operating, how they're getting their tools through their day to day job, but it's also the IT administrators that are having to provide that service to the end users. So it's really kind of across the board, it's affecting everyone. So it's really kind of going through and helping them figure out how they're going to support their users going forward. So we've spun up things like VMware desktop as a service providing that multi-tenant ability to consume on a per desktop basis, but then we've also wrapped around with a lot of security features. So one of the big things is as people are going and distributing where they're working from, that data and access to data is also opened up to those locations. So putting those protections in place to be able to protect the environment and then be able, if something does get in, to be able to detect what's going on. And then of course, with a lot of the other components, being able to recover those environments. So building the desktops, the end user access into the disaster recovery plans. >> And talk more, a little bit Brent, about the security aspect. We've seen the threat landscape change dramatically in the last couple of years, ransomware is a household word. I'm pretty sure even my mom knows what that means, to some degree. Where is that in customer conversations? I can imagine in certain industries like financial services and healthcare with PII, it's absolutely critical to ensure that that data is, they know where it is. It's protected and it's recoverable, 'cause everyone's talking about cyber resilience these days. >> Right. And if it's not conversation 1, it's conversation 1A. So it's really kind of core to everything that we do when we're talking to clients. It's whether it's production DR or the desktops, is building that security in place to help them build their security practice up. So when you think about it, it's doing it at layers. So starting with things like more advanced antivirus to see what's actually going on the desktop and then kind of layering above there. So even up to micro-segmentation, where you can envelop each individual desktop in their own quasi network, so that they're only allowed kind of that zero trust model where, Hey, if you can get to a file share, that's the only place you should be going or do I need web apps to get my day to day job done, but really restricting that access and making sure that everything is more good traffic versus unknown traffic. >> Yeah. >> And also on the, you asked about the clouds smarter earlier. And you can really weave the desktop into that because when you're thinking of your production compute environment and your remote desktop environment, and now you can actually share storage together, you can share security together and you start to get economies of scale across those different environments as well. >> So as we are in August, I think still yeah, 2022, barely for a couple more days, lot of change going on at VMware. Expedient has been VMware America's partner of the year before. Talk to us about some of the things that you think from a strategic perspective are next for the partnership. >> That it's definitely the multi-cloud world is here. And it's how we can go deeper, how we're going to see that really mature. You know, one of the things that we've actually done together this year was we worked on a project and evaluated over 30 different companies of what they spend on IT. Everything from the physical data center to the entire stack, to people and actually build a cloud transformation calculator that allows you to compare strategies, so that if you look at Strategy A over a five year period, doing your current transformation, versus that Cloud Different approach, it can actually help quantify the number of hours difference that you can get, the total cost of ownership and the speed that you can get there. So it's things like that that help people make easier decisions and simplify information are going to be part of it. But without a doubt, it's going to be how you can have that wrapper across all of your different environments that really delivers that cloud-like environment that panacea people have been looking for. >> Yeah. That panacea, that seems like it's critical for every organization to achieve. Last question for you. When customers come to you, when they've hit that plateau. They come to Expedient saying, "Guys, with VMware, help us accelerate past this. "We don't have the time, we need to get this done quickly." How do you advise them to move forward? >> Sure. So it goes back to that, what's causing them to hit that plateau? Is it more on the development side of things? Is it the infrastructure teams, not being able to respond fast enough to the developers? And really putting a plan in place to really get rid of those plateaus. It could be getting rid of the technical debt. It could be changing the IT operations and kind of that, the way that they're looking at a cloud transformation model, to help them kind of get accelerated and get them back on the right path. >> Back on the right path. I think we all want to get back on the right path. Guys, thank you so much for joining David and me on theCUBE today, talking about Expedient Cloud Different, what you're seeing in the marketplace, and how Expedient and VMware are helping customers to succeed. We appreciate your time. >> Yep. >> Thanks for having us. >> For our guests and Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live from VMware Explorer '22, stick around, Dave and I will be back shortly with our next guest. (gentle upbeat music)