>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music intro) (logo background tingles) >> Hi everybody, welcome back to day three of MWC23, my name is Dave Vellante and we're here live at the Theater of Barcelona, Lisa Martin, David Nicholson, John Furrier's in our studio in Palo Alto. Lot of buzz at the show, the Mobile World Daily Today, front page, Netflix chief hits back in fair share row, Greg Peters, the co-CEO of Netflix, talking about how, "Hey, you guys want to tax us, the telcos want to tax us, well, maybe you should help us pay for some of the content. Your margins are higher, you have a monopoly, you know, we're delivering all this value, you're bundling Netflix in, from a lot of ISPs so hold on, you know, pump the brakes on that tax," so that's the big news. Lockheed Martin, FOSS issues, AI guidelines, says, "AI's not going to take over your job anytime soon." Although I would say, your job's going to be AI-powered for the next five years. We're going to talk about data, we've been talking about the disaggregation of the telco stack, part of that stack is a data layer. John Kreisa is here, the CMO of Couchbase, John, you know, we've talked about all week, the disaggregation of the telco stacks, they got, you know, Silicon and operating systems that are, you know, real time OS, highly reliable, you know, compute infrastructure all the way up through a telemetry stack, et cetera. And that's a proprietary block that's really exploding, it's like the big bang, like we saw in the enterprise 20 years ago and we haven't had much discussion about that data layer, sort of that horizontal data layer, that's the market you play in. You know, Couchbase obviously has a lot of telco customers- >> John: That's right. >> We've seen, you know, Snowflake and others launch telco businesses. What are you seeing when you talk to customers at the show? What are they doing with that data layer? >> Yeah, so they're building applications to drive and power unique experiences for their users, but of course, it all starts with where the data is. So they're building mobile applications where they're stretching it out to the edge and you have to move the data to the edge, you have to have that capability to deliver that highly interactive experience to their customers or for their own internal use cases out to that edge, so seeing a lot of that with Couchbase and with our customers in telco. >> So what do the telcos want to do with data? I mean, they've got the telemetry data- >> John: Yeah. >> Now they frequently complain about the over-the-top providers that have used that data, again like Netflix, to identify customer demand for content and they're mopping that up in a big way, you know, certainly Amazon and shopping Google and ads, you know, they're all using that network. But what do the telcos do today and what do they want to do in the future? They're all talking about monetization, how do they monetize that data? >> Yeah, well, by taking that data, there's insight to be had, right? So by usage patterns and what's happening, just as you said, so they can deliver a better experience. It's all about getting that edge, if you will, on their competition and so taking that data, using it in a smart way, gives them that edge to deliver a better service and then grow their business. >> We're seeing a lot of action at the edge and, you know, the edge can be a Home Depot or a Lowe's store, but it also could be the far edge, could be a, you know, an oil drilling, an oil rig, it could be a racetrack, you know, certainly hospitals and certain, you know, situations. So let's think about that edge, where there's maybe not a lot of connectivity, there might be private networks going in, in the future- >> John: That's right. >> Private 5G networks. What's the data flow look like there? Do you guys have any customers doing those types of use cases? >> Yeah, absolutely. >> And what are they doing with the data? >> Yeah, absolutely, we've got customers all across, so telco and transportation, all kinds of service delivery and healthcare, for example, we've got customers who are delivering healthcare out at the edge where they have a remote location, they're able to deliver healthcare, but as you said, there's not always connectivity, so they need to have the applications, need to continue to run and then sync back once they have that connectivity. So it's really having the ability to deliver a service, reliably and then know that that will be synced back to some central server when they have connectivity- >> So the processing might occur where the data- >> Compute at the edge. >> How do you sync back? What is that technology? >> Yeah, so there's, so within, so Couchbase and Couchbase's case, we have an autonomous sync capability that brings it back to the cloud once they get back to whether it's a private network that they want to run over, or if they're doing it over a public, you know, wifi network, once it determines that there's connectivity and, it can be peer-to-peer sync, so different edge apps communicating with each other and then ultimately communicating back to a central server. >> I mean, the other theme here, of course, I call it the software-defined telco, right? But you got to have, you got to run on something, got to have hardware. So you see companies like AWS putting Outposts, out to the edge, Outposts, you know, doesn't really run a lot of database to mind, I mean, it runs RDS, you know, maybe they're going to eventually work with companies like... I mean, you're a partner of AWS- >> John: We are. >> Right? So do you see that kind of cloud infrastructure that's moving to the edge? Do you see that as an opportunity for companies like Couchbase? >> Yeah, we do. We see customers wanting to push more and more of that compute out to the edge and so partnering with AWS gives us that opportunity and we are certified on Outpost and- >> Oh, you are? >> We are, yeah. >> Okay. >> Absolutely. >> When did that, go down? >> That was last year, but probably early last year- >> So I can run Couchbase at the edge, on Outpost? >> Yeah, that's right. >> I mean, you know, Outpost adoption has been slow, we've reported on that, but are you seeing any traction there? Are you seeing any nibbles? >> Starting to see some interest, yeah, absolutely. And again, it has to be for the right use case, but again, for service delivery, things like healthcare and in transportation, you know, they're starting to see where they want to have that compute, be very close to where the actions happen. >> And you can run on, in the data center, right? >> That's right. >> You can run in the cloud, you know, you see HPE with GreenLake, you see Dell with Apex, that's essentially their Outposts. >> Yeah. >> They're saying, "Hey, we're going to take our whole infrastructure and make it as a service." >> Yeah, yeah. >> Right? And so you can participate in those environments- >> We do. >> And then so you've got now, you know, we call it supercloud, you've got the on-prem, you've got the, you can run in the public cloud, you can run at the edge and you want that consistent experience- >> That's right. >> You know, from a data layer- >> That's right. >> So is that really the strategy for a data company is taking or should be taking, that horizontal layer across all those use cases? >> You do need to think holistically about it, because you need to be able to deliver as a, you know, as a provider, wherever the customer wants to be able to consume that application. So you do have to think about any of the public clouds or private networks and all the way to the edge. >> What's different John, about the telco business versus the traditional enterprise? >> Well, I mean, there's scale, I mean, one thing they're dealing with, particularly for end user-facing apps, you're dealing at a very very high scale and the expectation that you're going to deliver a very interactive experience. So I'd say one thing in particular that we are focusing on, is making sure we deliver that highly interactive experience but it's the scale of the number of users and customers that they have, and the expectation that your application's always going to work. >> Speaking of applications, I mean, it seems like that's where the innovation is going to come from. We saw yesterday, GSMA announced, I think eight APIs telco APIs, you know, we were talking on theCUBE, one of the analysts was like, "Eight, that's nothing," you know, "What do these guys know about developers?" But you know, as Daniel Royston said, "Eight's better than zero." >> Right? >> So okay, so we're starting there, but the point being, it's all about the apps, that's where the innovation's going to come from- >> That's right. >> So what are you seeing there, in terms of building on top of the data app? >> Right, well you have to provide, I mean, have to provide the APIs and the access because it is really, the rubber meets the road, with the developers and giving them the ability to create those really rich applications where they want and create the experiences and innovate and change the way that they're giving those experiences. >> Yeah, so what's your relationship with developers at Couchbase? >> John: Yeah. >> I mean, talk about that a little bit- >> Yeah, yeah, so we have a great relationship with developers, something we've been investing more and more in, in terms of things like developer relations teams and community, Couchbase started in open source, continue to be based on open source projects and of course, those are very developer centric. So we provide all the consistent APIs for developers to create those applications, whether it's something on Couchbase Lite, which is our kind of edge-based database, or how they can sync that data back and we actually automate a lot of that syncing which is a very difficult developer task which lends them to one of the developer- >> What I'm trying to figure out is, what's the telco developer look like? Is that a developer that comes from the enterprise and somebody comes from the blockchain world, or AI or, you know, there really doesn't seem to be a lot of developer talk here, but there's a huge opportunity. >> Yeah, yeah. >> And, you know, I feel like, the telcos kind of remind me of, you know, a traditional legacy company trying to get into the developer world, you know, even Oracle, okay, they bought Sun, they got Java, so I guess they have developers, but you know, IBM for years tried with Bluemix, they had to end up buying Red Hat, really, and that gave them the developer community. >> Yep. >> EMC used to have a thing called EMC Code, which was a, you know, good effort, but eh. And then, you know, VMware always trying to do that, but, so as you move up the stack obviously, you have greater developer affinity. Where do you think the telco developer's going to come from? How's that going to evolve? >> Yeah, it's interesting, and I think they're... To kind of get to your first question, I think they're fairly traditional enterprise developers and when we break that down, we look at it in terms of what the developer persona is, are they a front-end developer? Like they're writing that front-end app, they don't care so much about the infrastructure behind or are they a full stack developer and they're really involved in the entire application development lifecycle? Or are they living at the backend and they're really wanting to just focus in on that data layer? So we lend towards all of those different personas and we think about them in terms of the APIs that we create, so that's really what the developers are for telcos is, there's a combination of those front-end and full stack developers and so for them to continue to innovate they need to appeal to those developers and that's technology, like Couchbase, is what helps them do that. >> Yeah and you think about the Apples, you know, the app store model or Apple sort of says, "Okay, here's a developer kit, go create." >> John: Yeah. >> "And then if it's successful, you're going to be successful and we're going to take a vig," okay, good model. >> John: Yeah. >> I think I'm hearing, and maybe I misunderstood this, but I think it was the CEO or chairman of Ericsson on the day one keynotes, was saying, "We are going to monetize the, essentially the telemetry data, you know, through APIs, we're going to charge for that," you know, maybe that's not the best approach, I don't know, I think there's got to be some innovation on top. >> John: Yeah. >> Now maybe some of these greenfield telcos are going to do like, you take like a dish networks, what they're doing, they're really trying to drive development layers. So I think it's like this wild west open, you know, community that's got to be formed and right now it's very unclear to me, do you have any insights there? >> I think it is more, like you said, Wild West, I think there's no emerging standard per se for across those different company types and sort of different pieces of the industry. So consequently, it does need to form some more standards in order to really help it grow and I think you're right, you have to have the right APIs and the right access in order to properly monetize, you have to attract those developers or you're not going to be able to monetize properly. >> Do you think that if, in thinking about your business and you know, you've always sold to telcos, but now it's like there's this transformation going on in telcos, will that become an increasingly larger piece of your business or maybe even a more important piece of your business? Or it's kind of be steady state because it's such a slow moving industry? >> No, it is a big and increasing piece of our business, I think telcos like other enterprises, want to continue to innovate and so they look to, you know, technologies like, Couchbase document database that allows them to have more flexibility and deliver the speed that they need to deliver those kinds of applications. So we see a lot of migration off of traditional legacy infrastructure in order to build that new age interface and new age experience that they want to deliver. >> A lot of buzz in Silicon Valley about open AI and Chat GPT- >> Yeah. >> You know, what's your take on all that? >> Yeah, we're looking at it, I think it's exciting technology, I think there's a lot of applications that are kind of, a little, sort of innovate traditional interfaces, so for example, you can train Chat GPT to create code, sample code for Couchbase, right? You can go and get it to give you that sample app which gets you a headstart or you can actually get it to do a better job of, you know, sorting through your documentation, like Chat GPT can do a better job of helping you get access. So it improves the experience overall for developers, so we're excited about, you know, what the prospect of that is. >> So you're playing around with it, like everybody is- >> Yeah. >> And potentially- >> Looking at use cases- >> Ways tO integrate, yeah. >> Hundred percent. >> So are we. John, thanks for coming on theCUBE. Always great to see you, my friend. >> Great, thanks very much. >> All right, you're welcome. All right, keep it right there, theCUBE will be back live from Barcelona at the theater. SiliconANGLE's continuous coverage of MWC23. Go to siliconangle.com for all the news, theCUBE.net is where all the videos are, keep it right there. (cheerful upbeat music outro)

(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

(upbeat music) >> Welcome back to Supercloud 2 this is Dave Vellante. We're here exploring the intersection of data and analytics and the future of cloud. And in this segment, we're going to look at the evolution of cloud, and try to test some of the Supercloud concepts and assumptions with Brian Gracely, is the founder and co-host along with Aaron Delp of the popular Cloudcast program. Amazing series, if you're not already familiar with it. The Cloudcast is one of the best ways to keep up with so many things going on in our industry. Enterprise tech, platform engineering, business models, obviously, cloud developer trends, crypto, Web 3.0. Sorry Brian, I know that's a sore spot, but Brian, thanks for coming >> That's okay. >> on the program, really appreciate it. >> Yeah, great to be with you, Dave. Happy New Year, and great to be back with everybody with SiliconANGLE again this year. >> Yeah, we love having you on. We miss working with you day-to-day, but I want to start with Gracely's theorem, which basically says, I'm going to paraphrase. For the most part, nothing new gets introduced in the enterprise tech business, patterns repeat themselves, maybe get applied in new ways. And you know this industry well, when something comes out that's new, if you take virtualization, for example, been around forever with mainframes, but then VMware applied it, solve a real problem in the client service system. And then it's like, "Okay, this is awesome." We get really excited and then after a while we pushed the architecture, we break things, introduce new things to fix the things that are broken and start adding new features. And oftentimes you do that through acquisitions. So, you know, has the cloud become that sort of thing? And is Supercloud sort of same wine, new bottle, following Gracely's theorem? >> Yeah, I think there's some of both of it. I hate to be the sort of, it depends sort of answer but, I think to a certain extent, you know, obviously Cloud in and of itself was, kind of revolutionary in that, you know, it wasn't that you couldn't rent things in the past, it was just being able to do it at scale, being able to do it with such amazing self-service. And then, you know, kind of proliferation of like, look at how many services I can get from, from one cloud, whether it was Amazon or Azure or Google. And then, you know, we, we slip back into the things that we know, we go, "Oh, well, okay, now I can get computing on demand, but, now it's just computing." Or I can get database on demand and it's, you know, it's got some of the same limitations of, of say, of database, right? It's still, you know, I have to think about IOPS and I have to think about caching, and other stuff. So, I think we do go through that and then we, you know, we have these sort of next paradigms that come along. So, you know, serverless was another one of those where it was like, okay, it seems sort of new. I don't have to, again, it was another level of like, I don't have to think about anything. And I was able to do that because, you know, there was either greater bandwidth available to me, or compute got cheaper. And what's been interesting is not the sort of, that specific thing, serverless in and of itself is just another way of doing compute, but the fact that it now gets applied as, sort of a no-ops model to, you know, again, like how do I provision a database? How do I think about, you know, do I have to think about the location of a service? Does that just get taken care of for me? So I think the Supercloud concept, and I did a thing and, and you and I have talked about it, you know, behind the scenes that maybe the, maybe a better name is Super app for something like Snowflake or other, but I think we're, seeing these these sort of evolutions over and over again of what were the big bottlenecks? How do we, how do we solve those bottlenecks? And I think the big thing here is, it's never, it's very rarely that you can take the old paradigm of what the thing was, the concept was, and apply it to the new model. So, I'll just give you an example. So, you know, something like VMware, which we all know, wildly popular, wildly used, but when we apply like a Supercloud concept of VMware, the concept of VMware has always been around a cluster, right? It's some finite number of servers, you sort of manage it as a cluster. And when you apply that to the cloud and you say, okay, there's, you know, for example, VMware in the cloud, it's still the same concept of a cluster of VMware. But yet when you look at some of these other services that would fit more into the, you know, Supercloud kind of paradigm, whether it's a Snowflake or a MongoDB Atlas or maybe what CloudFlare is doing at the edge, those things get rid of some of those old paradigms. And I think that's where stuff, you start to go, "Oh, okay, this is very different than before." Yes, it's still computing or storage, or data access, but there's a whole nother level of something that we didn't carry forward from the previous days. And that really kind of breaks the paradigm. And so that's the way I think I've started to think about, are these things really brand new? Yes and no, but I think it's when you can see that big, that thing that you didn't leave behind isn't there anymore, you start to get some really interesting new innovation come out of it. >> Yeah. And that's why, you know, lift and shift is okay, when you talk to practitioners, they'll say, "You know, I really didn't change my operating model. And so I just kind of moved it into the cloud. there were some benefits, but it was maybe one zero not three zeros that I was looking for." >> Right. >> You know, we always talk about what's great about cloud, the agility, and all the other wonderful stuff that we know, what's not working in cloud, you know, tie it into multi-cloud, you know, in terms of, you hear people talk about multi-cloud by accident, okay, that's true. >> Yep. >> What's not great about cloud. And then I want to get into, you know, is multi-cloud really a problem or is it just sort of vendor hype? But, but what's not working in cloud? I mean, you mentioned serverless and serverless is kind of narrow, right, for a lot of stateless apps, right? But, what's not great about cloud? >> Well, I think there's a few things that if you ask most people they don't love about cloud. I think, we can argue whether or not sort of this consolidation around a few cloud providers has been a good thing or a bad thing. I think, regardless of that, you know, we are seeing, we are hearing more and more people that say, look, you know, the experience I used to have with cloud when I went to, for example, an Amazon and there was, you know, a dozen services, it was easy to figure out what was going on. It was easy to figure out what my billing looked like. You know, now they've become so widespread, the number of services they have, you know, the number of stories you just hear of people who went, "Oh, I started a service over in US West and I can't find it anymore 'cause it's on a different screen. And I, you know, I just got billed for it." Like, so I think the sprawl of some of the clouds has gotten, has created a user experience that a lot of people are frustrated with. I think that's one thing. And we, you know, we see people like Digital Ocean and we see others who are saying, "Hey, we're going to be that simplified version." So, there's always that yin and yang. I think people are super frustrated at network costs, right? So, you know, and that's kind of at a lot of, at the center of maybe why we do or don't see more of these Supercloud services is just, you know, in the data center as an application owner, I didn't have to think about, well where, where does this go to? Where are my users? Yes, somebody took care of it, but when those things become front and center, that's super frustrating. That's the one area that we've seen absolutely no cost savings, cost reduction. So I think that frustrates people a lot. And then I think the third piece is just, you know, we're, we went from super centralized IT organizations, which, you know, for decades was how it worked. It was part of the reason why the cloud expanded and became a thing, right? Sort of shadow IT and I can't get things done. And then, now what we've seen is sort of this proliferation of little pockets of groups that are your IT, for lack of a better thing, whether they're called platform engineering or SRE or DevOps. But we have this, expansion, explosion if you will, of groups that, if I'm an app dev team, I go, "Hey, you helped me make this stuff run, but then the team next to you has another group and they have another group." And so you see this explosion of, you know, we don't have any standards in the company anymore. And, so sort of self-service has created its own nightmare to a certain extent for a lot of larger companies. >> Yeah. Thank you for that. So, you know, I want, I want to explore this multi-cloud, you know, by accident thing and is a real problem. You hear that a lot from vendors and we've been talking about Supercloud as this unifying layer across cloud. You know, but when you talk to customers, a lot of them are saying, "Yes, we have multiple clouds in our organization, but my group, we have mono cloud, we know the security, edicts, we know how to, you know, deal with the primitives, whether it's, you know, S3 or Azure Blob or whatever it is. And we're very comfortable with this." It's, that's how we're simplifying. So, do you think this is really a problem? Does it have merit that we need that unifying layer across clouds, or is it just too early for that? >> I think, yeah, I think what you, what you've laid out is basically how the world has played out. People have picked a cloud for a specific application or a series of applications. Yeah, and I think if you talk to most companies, they would tell you, you know, holistically, yes, we're multi-cloud, not, maybe not necessarily on, I don't necessarily love the phrase where people say like, well it happened by accident. I think it happened on purpose, but we got to multi-cloud, not in the way that maybe that vendors, you know, perceived, you know, kind of laid out a map for. So it was, it was, well you will lay out this sort of Supercloud framework. We didn't call it that back then, we just called it sort of multi-cloud. Maybe it was Kubernetes or maybe it was whatever. And different groups, because central IT kind of got disbanded or got fragmented. It turned into, go pick the best cloud for your application, for what you need to do for the business. And then, you know, multiple years later it was like, "Oh, hold on, I've got 20% in Google and 50% in AWS and I've got 30% in Azure. And, you know, it's, yeah, it's been evolution. I don't know that it's, I don't know if it's a mistake. I think it's now groups trying to figure out like, should I make sense of it? You know, should I try and standardize and I backwards standardize some stuff? I think that's going to be a hard thing for, for companies to do. 'cause I think they feel okay with where the applications are. They just happen to be in multiple clouds. >> I want to run something by you, and you guys, you and Aaron have talked about this. You know, still depending on who, which keynote you listen to, small percentage of the workloads are actually in cloud. And when you were with us at Wikibon, I think we called it true private cloud, and we looked at things like Nutanix and there were a lot of other examples of companies that were trying to replicate the hyperscale experience on Prem. >> Yeah. >> And, we would evaluate that, you know, beyond virtualization, and so we sort of defined that and, but I think what's, maybe what's more interesting than Supercloud across clouds is if you include that, that on Prem estate, because that's where most of the work is being done, that's where a lot of the proprietary tools have been built, a lot of data, a lot of software. So maybe there's this concept of sending that true private cloud to true hybrid cloud. So I actually think hybrid cloud in some cases is the more interesting use case for so-called Supercloud. What are your thoughts on that? >> Yeah, I think there's a couple aspects too. I think, you know, if we were to go back five or six years even, maybe even a little further and look at like what a data center looked like, even if it was just, "Hey we're a data center that runs primarily on VMware. We use some of their automation". Versus what you can, even what you can do in your data center today. The, you know, the games that people have seen through new types of automation through Kubernetes, through get ops, and a number of these things, like they've gotten significantly further along in terms of I can provision stuff really well, I can do multi-tenancy, I can do self-service. Is it, you know, is it still hard? Yeah. Because those things are hard to do, but there's been significant progress there. I don't, you know, I still look for kind of that, that killer application, that sort of, you know, lighthouse use case of, hybrid applications, you know, between data center and between cloud. I think, you know, we see some stuff where, you know, backup is a part of it. So you use the cloud for storage, maybe you use the cloud for certain kinds of resiliency, especially on maybe front end load balancing and stuff. But I think, you know, I think what we get into is, this being hung up on hybrid cloud or multi-cloud as a term and go like, "Look, what are you trying to measure? Are you trying to measure, you know, efficiency of of of IT usage? Are you trying to measure how quickly can I give these business, you know, these application teams that are part of a line of business resources that they need?" I think if we start measuring that way, we would look at, you know, you'd go, "Wow, it used to be weeks and months. Now we got rid of these boards that have to review everything every time I want to do a change management type of thing." We've seen a lot more self-service. I think those are the things we want to measure on. And then to your point of, you know, where does, where do these Supercloud applications fit in? I think there are a bunch of instances where you go, "Look, I have a, you know, global application, I have a thing that has to span multiple regions." That's where the Supercloud concept really comes into play. We used to do it in the data center, right? We'd had all sorts of technologies to help with that, I think you can now start to do it in the cloud. >> You know, one of the other things, trying to understand, your thoughts on this, do you think that you, you again have talked about this, like I'm with you. It's like, how is it that Google's losing, you know, 3 billion dollars a year, whatever. I mean, because when you go back and look at Amazon, when they were at that level of revenue where Google is today, they were making money, you know, and they were actually growing faster, by the way. So it's kind of interesting what's happened with Google. But, the reason I bring that up is, trying to understand if you think the hyperscalers will ever be motivated to create standards across clouds, and that may be a play for Google. I mean, obviously with Kubernetes it was like a Hail Mary and kind of made them relevant. Where would Google be without Kubernetes? But then did it achieve the objectives? We could have that conversation some other time, but do you think the hyperscalers will actually say, "Okay, we're going to lean in and create these standards across clouds." Because customers would love that, I would think, but it would sub-optimize their competitive advantage. What are your thoughts? >> I think, you know, on the surface, I would say they, they probably aren't. I think if you asked 'em the question, they would say, "Well, you know, first and foremost, you know, we do deliver standards, so we deliver a, you know, standard SQL interface or a SQL you know, or a standard Kubernetes API or whatever. So, in that, from that perspective, you know, we're not locking you into, you know, an Amazon specific database, or a Google specific database." You, you can argue about that, but I think to a certain extent, like they've been very good about, "Hey, we're going to adopt the standards that people want." A lot of times the open source standards. I think the problem is, let's say they did come up with a standard for it. I think you still have the problem of the costs of migration and you know, the longer you've, I think their bet is basically the longer you've been in some cloud. And again, the more data you sort of compile there, the data gravity concept, there's just going to be a natural thing that says, okay, the hurdle to get over to say, "Look, we want to move this to another cloud", becomes so cost prohibitive that they don't really have to worry about, you know, oh, I'm going to get into a war of standards. And so far I think they sort of realize like that's the flywheel that the cloud creates. And you know, unless they want to get into a world where they just cut bandwidth costs, like it just kind of won't happen. You know, I think we've even seen, and you know, the one example I'll use, and I forget the name of it off the top of my head, but there's a, there's a Google service. I think it's like BigQuery external or something along those lines, that allows you to say, "Look, you can use BigQuery against like S3 buckets and against other stuff." And so I think the cloud providers have kind of figured out, I'm never going to get the application out of that other guy's cloud or you know, the other cloud. But maybe I'm going to have to figure out some interesting ways to sort of work with it. And, you know, it's a little bit, it's a little janky, but that might be, you know, a moderate step that sort of gets customers where they want to be. >> Yeah. Or you know, it'd be interesting if you ever see AWS for example, running its database in other clouds, you started, even Oracle is doing that with, with with Azure, which is a form of Supercloud. My last question for you is, I want to get you thinking about sort of how the future plays out. You know, think about some of the companies that we've put forth this Supercloud, and by the way, this has been a criticism of the concept. Charles Fitzer, "Everything is Supercloud!" Which if true would defeat the purpose of course. >> Right. >> And so right with the community effort, we really tried to put some guardrails down on the essential characteristics, the deployment models, you know, so for example, running across multiple clouds with a purpose build pass, creating a common experience, metadata intelligence that solves a specific problem. I mean, the example I often use is Snowflake's governed data sharing. But yeah, Snowflake, Databricks, CloudFlare, Cohesity, you know, I just mentioned Oracle and Azure, these and others, they certainly claim to have that common experience across clouds. But my question is, again, I come back to, do customers need this capability? You know, is Mono Cloud the way to solve that problem? What's your, what are your thoughts on how this plays out in the future of, I guess, PAs, apps and cloud? >> Yeah, I think a couple of things. So, from a technology perspective, I think, you know, the companies you name, the services you've named, have sort of proven that the concept is viable and it's viable at a reasonable size, right? These aren't completely niche businesses, right? They're multi-billion dollar businesses. So, I think there's a subset of applications that, you know, maybe a a bigger than a niche set of applications that are going to use these types of things. A lot of what you talked about is very data centric, and that's, that's fine. That's that layer is, figuring that out. I think we'll see messaging types of services, so like Derek Hallison's, Caya Company runs a, sort of a Supercloud for messaging applications. So I think there'll be places where it makes a ton of sense. I think, the thing that I'm not sure about, and because again, we've been now 10 plus years of sort of super low, you know, interest rates in terms of being able to do things, is a lot of these things come out of research that have been done previously. Then they get turned into maybe somewhat of an open source project, and then they can become something. You know, will we see as much investment into the next Snowflake if, you know, the interest rates are three or four times that they used to be, do we, do we see VCs doing it? So that's the part that worries me a little bit, is I think we've seen what's possible. I think, you know, we've seen companies like what those services are. I think I read yesterday Snowflake was saying like, their biggest customers are growing at 30, like 50 or 60%. Like the, value they get out of it is becoming exponential. And it's just a matter of like, will the economics allow the next big thing to happen? Because some of these things are pretty, pretty costly, you know, expensive to get started. So I'm bullish on the idea. I don't know that it becomes, I think it's okay that it's still sort of, you know, niche plus, plus in terms of the size of it. Because, you know, if we think about all of IT it's still, you know, even microservices is a small part of bigger things. But I'm still really bullish on the idea. I like that it's been proven. I'm a little wary, like a lot of people have the economics of, you know, what might slow things down a little bit. But yeah, I, think the future is going to involve Supercloud somewhere, whatever people end up calling it. And you and I discussed that. (laughs) But I don't, I don't think it goes away. I don't think it's, I don't think it's a fad. I think it is something that people see tremendous value and it's just, it's got to be, you know, for what you're trying to do, your application specific thing. >> You're making a great point on the funding of innovation and we're entering a new era of public policy as well. R and D tax credit is now is shifting. >> Yeah. >> You know, you're going to have to capitalize that over five years now. And that's something that goes back to the 1950s and many people would argue that's at least in part what has helped the United States be so, you know, competitive in tech. But Brian, always great to talk to you. Thanks so much for participating in the program. Great to see you. >> Thanks Dave, appreciate it. Good luck with the rest of the show. >> Thank you. All right, this is Dave Vellante for John Furrier, the entire Cube community. Stay tuned for more content from Supercloud2.

(upbeat music) >> Welcome back to Supercloud 2. This is Dave Vellante. We're here exploring the intersection of data and analytics in the future of cloud and data. In this segment, we're going to look deeper into the life sciences business with Jesse Cugliotta, who leads the Healthcare and Life Sciences industry practice at Snowflake. And Nicholas Nick Taylor, who's the executive director of Informatics at Ionis Pharmaceuticals. Gentlemen, thanks for coming in theCUBE and participating in the program. Really appreciate it. >> Thank you for having us- >> Thanks for having me. >> You're very welcome, okay, we're go really try to look at data sharing as a use case and try to understand what's happening in the healthcare industry generally and specifically, how Nick thinks about sharing data in a governed fashion whether tapping the capabilities of multiple clouds is advantageous long term or presents more challenges than the effort is worth. And to start, Jesse, you lead this industry practice for Snowflake and it's a challenging and vibrant area. It's one that's hyper-focused on data privacy. So the first question is, you know there was a time when healthcare and other regulated industries wouldn't go near the cloud. What are you seeing today in the industry around cloud adoption and specifically multi-cloud adoption? >> Yeah, for years I've heard that healthcare and life sciences has been cloud diverse, but in spite of all of that if you look at a lot of aspects of this industry today, they've been running in the cloud for over 10 years now. Particularly when you look at CRM technologies or HR or HCM, even clinical technologies like EDC or ETMF. And it's interesting that you mentioned multi-cloud as well because this has always been an underlying reality especially within life sciences. This industry grows through acquisition where companies are looking to boost their future development pipeline either by buying up smaller biotechs, they may have like a late or a mid-stage promising candidate. And what typically happens is the larger pharma could then use their commercial muscle and their regulatory experience to move it to approvals and into the market. And I think the last few decades of cheap capital certainly accelerated that trend over the last couple of years. But this typically means that these new combined institutions may have technologies that are running on multiple clouds or multiple cloud strategies in various different regions to your point. And what we've often found is that they're not planning to standardize everything onto a single cloud provider. They're often looking for technologies that embrace this multi-cloud approach and work seamlessly across them. And I think this is a big reason why we, here at Snowflake, we've seen such strong momentum and growth across this industry because healthcare and life science has actually been one of our fastest growing sectors over the last couple of years. And a big part of that is in fact that we run on not only all three major cloud providers, but individual accounts within each and any one of them, they had the ability to communicate and interoperate with one another, like a globally interconnected database. >> Great, thank you for that setup. And so Nick, tell us more about your role and Ionis Pharma please. >> Sure. So I've been at Ionis for around five years now. You know, when when I joined it was, the IT department was pretty small. There wasn't a lot of warehousing, there wasn't a lot of kind of big data there. We saw an opportunity with Snowflake pretty early on as a provider that would be a lot of benefit for us, you know, 'cause we're small, wanted something that was fairly hands off. You know, I remember the days where you had to get a lot of DBAs in to fine tune your databases, make sure everything was running really, really well. The notion that there's, you know, no indexes to tune, right? There's very few knobs and dials, you can turn on Snowflake. That was appealing that, you know, it just kind of worked. So we found a use case to bring the platform in. We basically used it as a logging replacement as a Splunk kind of replacement with a platform called Elysium Analytics as a way to just get it in the door and give us the opportunity to solve a real world use case, but also to help us start to experiment using Snowflake as a platform. It took us a while to A, get the funding to bring it in, but B, build the momentum behind it. But, you know, as we experimented we added more data in there, we ran a few more experiments, we piloted in few more applications, we really saw the power of the platform and now, we are becoming a commercial organization. And with that comes a lot of major datasets. And so, you know, we really see Snowflake as being a very important part of our ecology going forward to help us build out our infrastructure. >> Okay, and you are running, your group runs on Azure, it's kind of mono cloud, single cloud, but others within Ionis are using other clouds, but you're not currently, you know, collaborating in terms of data sharing. And I wonder if you could talk about how your data needs have evolved over the past decade. I know you came from another highly regulated industry in financial services. So what's changed? You sort of touched on this before, you had these, you know, very specialized individuals who were, you know, DBAs, and, you know, could tune databases and the like, so that's evolved, but how has generally your needs evolved? Just kind of make an observation over the last, you know, five or seven years. What have you seen? >> Well, we, I wasn't in a group that did a lot of warehousing. It was more like online trade capture, but, you know, it was very much on-prem. You know, being in the cloud is very much a dirty word back then. I know that's changed since I've left. But in, you know, we had major, major teams of everyone who could do everything, right. As I mentioned in the pharma organization, there's a lot fewer of us. So the data needs there are very different, right? It's, we have a lot of SaaS applications. One of the difficulties with bringing a lot of SaaS applications on board is obviously data integration. So making sure the data is the same between them. But one of the big problems is joining the data across those SaaS applications. So one of the benefits, one of the things that we use Snowflake for is to basically take data out of these SaaS applications and load them into a warehouse so we can do those joins. So we use technologies like Boomi, we use technologies like Fivetran, like DBT to bring this data all into one place and start to kind of join that basically, allow us to do, run experiments, do analysis, basically take better, find better use for our data that was siloed in the past. You mentioned- >> Yeah. And just to add on to Nick's point there. >> Go ahead. >> That's actually something very common that we're seeing across the industry is because a lot of these SaaS applications that you mentioned, Nick, they're with from vendors that are trying to build their own ecosystem in walled garden. And by definition, many of them do not want to integrate with one another. So from a, you know, from a data platform vendor's perspective, we see this as a huge opportunity to help organizations like Ionis and others kind of deal with the challenges that Nick is speaking about because if the individual platform vendors are never going to make that part of their strategy, we see it as a great way to add additional value to these customers. >> Well, this data sharing thing is interesting. There's a lot of walled gardens out there. Oracle is a walled garden, AWS in many ways is a walled garden. You know, Microsoft has its walled garden. You could argue Snowflake is a walled garden. But the, what we're seeing and the whole reason behind the notion of super-cloud is we're creating an abstraction layer where you actually, in this case for this use case, can share data in a governed manner. Let's forget about the cross-cloud for a moment. I'll come back to that, but I wonder, Nick, if you could talk about how you are sharing data, again, Snowflake sort of, it's, I look at Snowflake like the app store, Apple, we're going to control everything, we're going to guarantee with data clean rooms and governance and the standards that we've created within that platform, we're going to make sure that it's safe for you to share data in this highly regulated industry. Are you doing that today? And take us through, you know, the considerations that you have in that regard. >> So it's kind of early days for us in Snowflake in general, but certainly in data sharing, we have a couple of examples. So data marketplace, you know, that's a great invention. It's, I've been a small IT shop again, right? The fact that we are able to just bring down terabyte size datasets straight into our Snowflake and run analytics directly on that is huge, right? The fact that we don't have to FTP these massive files around run jobs that may break, being able to just have that on tap is huge for us. We've recently been talking to one of our CRO feeds- CRO organizations about getting their data feeds in. Historically, this clinical trial data that comes in on an FTP file, we have to process it, take it through the platforms, put it into the warehouse. But one of the CROs that we talked to recently when we were reinvestigate in what data opportunities they have, they were a Snowflake customer and we are, I think, the first production customer they have, have taken that feed. So they're basically exposing their tables of data that historically came in these FTP files directly into our Snowflake instance now. We haven't taken advantage of that. It only actually flipped the switch about three or four weeks ago. But that's pretty big for us again, right? We don't have to worry about maintaining those jobs that take those files in. We don't have to worry about the jobs that take those and shove them on the warehouse. We now have a feed that's directly there that we can use a tool like DBT to push through directly into our model. And then the third avenue that's came up, actually fairly recently as well was genetics data. So genetics data that's highly, highly regulated. We had to be very careful with that. And we had a conversation with Snowflake about the data white rooms practice, and we see that as a pretty interesting opportunity. We are having one organization run genetic analysis being able to send us those genetic datasets, but then there's another organization that's actually has the in quotes "metadata" around that, so age, ethnicity, location, et cetera. And being able to join those two datasets through some kind of mechanism would be really beneficial to the organization. Being able to build a data white room so we can put that genetic data in a secure place, anonymize it, and then share the amalgamated data back out in a way that's able to be joined to the anonymized metadata, that could be pretty huge for us as well. >> Okay, so this is interesting. So you talk about FTP, which was the common way to share data. And so you basically, it's so, I got it now you take it and do whatever you want with it. Now we're talking, Jesse, about sharing the same copy of live data. How common is that use case in your industry? >> It's become very common over the last couple of years. And I think a big part of it is having the right technology to do it effectively. You know, as Nick mentioned, historically, this was done by people sending files around. And the challenge with that approach, of course, while there are multiple challenges, one, every time you send a file around your, by definition creating a copy of the data because you have to pull it out of your system of record, put it into a file, put it on some server where somebody else picks it up. And by definition at that point you've lost governance. So this creates challenges in general hesitation to doing so. It's not that it hasn't happened, but the other challenge with it is that the data's no longer real time. You know, you're working with a copy of data that was as fresh as at the time at that when that was actually extracted. And that creates limitations in terms of how effective this can be. What we're starting to see now with some of our customers is live sharing of information. And there's two aspects of that that are important. One is that you're not actually physically creating the copy and sending it to someone else, you're actually exposing it from where it exists and allowing another consumer to interact with it from their own account that could be in another region, some are running in another cloud. So this concept of super-cloud or cross-cloud could becoming realized here. But the other important aspect of it is that when that other- when that other entity is querying your data, they're seeing it in a real time state. And this is particularly important when you think about use cases like supply chain planning, where you're leveraging data across various different enterprises. If I'm a manufacturer or if I'm a contract manufacturer and I can see the actual inventory positions of my clients, of my distributors, of the levels of consumption at the pharmacy or the hospital that gives me a lot of indication as to how my demand profile is changing over time versus working with a static picture that may have been from three weeks ago. And this has become incredibly important as supply chains are becoming more constrained and the ability to plan accurately has never been more important. >> Yeah. So the race is on to solve these problems. So it start, we started with, hey, okay, cloud, Dave, we're going to simplify database, we're going to put it in the cloud, give virtually infinite resources, separate compute from storage. Okay, check, we got that. Now we've moved into sort of data clean rooms and governance and you've got an ecosystem that's forming around this to make it safer to share data. And then, you know, nirvana, at least near term nirvana is we're going to build data applications and we're going to be able to share live data and then you start to get into monetization. Do you see, Nick, in the near future where I know you've got relationships with, for instance, big pharma like AstraZeneca, do you see a situation where you start sharing data with them? Is that in the near term? Is that more long term? What are the considerations in that regard? >> I mean, it's something we've been thinking about. We haven't actually addressed that yet. Yeah, I could see situations where, you know, some of these big relationships where we do need to share a lot of data, it would be very nice to be able to just flick a switch and share our data assets across to those organizations. But, you know, that's a ways off for us now. We're mainly looking at bringing data in at the moment. >> One of the things that we've seen in financial services in particular, and Jesse, I'd love to get your thoughts on this, is companies like Goldman or Capital One or Nasdaq taking their stack, their software, their tooling actually putting it on the cloud and facing it to their customers and selling that as a new monetization vector as part of their digital or business transformation. Are you seeing that Jesse at all in healthcare or is it happening today or do you see a day when that happens or is healthier or just too scary to do that? >> No, we're seeing the early stages of this as well. And I think it's for some of the reasons we talked about earlier. You know, it's a much more secure way to work with a colleague if you don't have to copy your data and potentially expose it. And some of the reasons that people have historically copied that data is that they needed to leverage some sort of algorithm or application that a third party was providing. So maybe someone was predicting the ideal location and run a clinical trial for this particular rare disease category where there are only so many patients around the world that may actually be candidates for this disease. So you have to pick the ideal location. Well, sending the dataset to do so, you know, would involve a fairly complicated process similar to what Nick was mentioning earlier. If the company who was providing the logic or the algorithm to determine that location could bring that algorithm to you and you run it against your own data, that's a much more ideal and a much safer and more secure way for this industry to actually start to work with some of these partners and vendors. And that's one of the things that we're looking to enable going into this year is that, you know, the whole concept should be bring the logic to your data versus your data to the logic and the underlying sharing mechanisms that we've spoken about are actually what are powering that today. >> And so thank you for that, Jesse. >> Yes, Dave. >> And so Nick- Go ahead please. >> Yeah, if I could add, yeah, if I could add to that, that's something certainly we've been thinking about. In fact, we'd started talking to Snowflake about that a couple of years ago. We saw the power there again of the platform to be able to say, well, could we, we were thinking in more of a data share, but could we share our data out to say an AI/ML vendor, have them do the analytics and then share the data, the results back to us. Now, you know, there's more powerful mechanisms to do that within the Snowflake ecosystem now, but you know, we probably wouldn't need to have onsite AI/ML people, right? Some of that stuff's very sophisticated, expensive resources, hard to find, you know, it's much better for us to find a company that would be able to build those analytics, maintain those analytics for us. And you know, we saw an opportunity to do that a couple years ago and we're kind of excited about the opportunity there that we can just basically do it with a no op, right? We share the data route, we have the analytics done, we get the result back and it's just fairly seamless. >> I mean, I could have a whole another Cube session on this, guys, but I mean, I just did a a session with Andy Thurai, a Constellation research about how difficult it's been for organization to get ROI because they don't have the expertise in house so they want to either outsource it or rely on vendor R&D companies to inject that AI and machine intelligence directly into applications. My follow-up question to you Nick is, when you think about, 'cause Jesse was talking about, you know, let the data basically stay where it is and you know bring the compute to that data. If that data lives on different clouds, and maybe it's not your group, but maybe it's other parts of Ionis or maybe it's your partners like AstraZeneca, or you know, the AI/ML partners and they're potentially on other clouds or that data is on other clouds. Do you see that, again, coming back to super-cloud, do you see it as an advantage to be able to have a consistent experience across those clouds? Or is that just kind of get in the way and make things more complex? What's your take on that, Nick? >> Well, from the vendors, so from the client side, it's kind of seamless with Snowflake for us. So we know for a fact that one of the datasets we have at the moment, Compile, which is a, the large multi terabyte dataset I was talking about. They're on AWS on the East Coast and we are on Azure on the West Coast. And they had to do a few tweaks in the background to make sure the data was pushed over from, but from my point of view, the data just exists, right? So for me, I think it's hugely beneficial that Snowflake supports this kind of infrastructure, right? We don't have to jump through hoops to like, okay, well, we'll download it here and then re-upload it here. They already have the mechanism in the background to do these multi-cloud shares. So it's not important for us internally at the moment. I could see potentially at some point where we start linking across different groups in the organization that do have maybe Amazon or Google Cloud, but certainly within our providers. We know for a fact that they're on different services at the moment and it just works. >> Yeah, and we learned from Benoit Dageville, who came into the studio on August 9th with first Supercloud in 2022 that Snowflake uses a single global instance across regions and across clouds, yeah, whether or not you can query across you know, big regions, it just depends, right? It depends on latency. You might have to make a copy or maybe do some tweaks in the background. But guys, we got to jump, I really appreciate your time. Really thoughtful discussion on the future of data and cloud, specifically within healthcare and pharma. Thank you for your time. >> Thanks- >> Thanks for having us. >> All right, this is Dave Vellante for theCUBE team and my co-host, John Furrier. Keep it right there for more action at Supercloud 2. (upbeat music)

(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)

(soft music) >> Welcome back to Sin City, guys and girls we're glad you're with us. You've been watching theCUBE all week, we know that. This is theCUBE's live coverage of AWS re:Invent 22, from the Venetian Expo Center where there are tens of thousands of people, and this event if you know it, covers the entire strip. There are over 55,000 people here, hundreds of thousands online. Dave, this has been a fantastic show. It is clear everyone's back. We're hearing phenomenal stories from AWS and it's ecosystem. We got a great customer story coming up next, featured on the main stage. >> Yeah, I mean, you know, post pandemic, you start to think about, okay, how are things changing? And one of the things that we heard from Adam Selipsky, was, we're going beyond digital transformation into business transformation. Okay. That can mean a lot of things to a lot of people. I have a sense of what it means. And I think this next interview really talks to business transformation beyond digital transformation, beyond the IT. >> Excellent. We've got two guests. One of them is an alumni, Scott Mullins joins us, GM, AWS Worldwide Financial Services, and Brad Peterson is here, the EVP, CIO and CTO of NASDAQ. Welcome guys. Great to have you. >> Hey guys. >> Hey guys. Thanks for having us. >> Yeah >> Brad, talk a little bit, there was an announcement with NASDAQ and AWS last year, a year ago, about how they're partnering to transform capital markets. It was a highlight of last year. Remind us what you talked about and what's gone on since then. >> Yeah, so, we are very excited. I work with Adena Friedman, she's my boss, CEO of NASDAQ, and she was on stage with Adam for his first Keynote as CEO of AWS. And we made the commitment that we were going to move our markets to the Cloud. And we've been a long time customer of AWS and everyone said, you know the last piece, the last frontier to be moved was the actual matching where all the messages, the quotes get matched together to become confirmed orders. So that was what we committed to less than a year ago. And we said we were going to move one of our options markets. In the US, we have six of them. And options markets are the most challenging, they're the most high volume and high performance. So we said, let's start with something really challenging and prove we can do it together with AWS. So we committed to that. >> And? Results so far? >> So, I can sit here and say that November 7th so we are live, we're in production and the MRX Exchange is called Mercury, so we shorten it for MRX, we like acronyms in technology. And so, we started with a phased launch of symbols, so you kind of allow yourself to make sure you have all the functionality working then you add some volume on it, and we are going to complete the conversion on Monday. So we are all good so far. And I have some results I can share, but maybe Scott, if you want to talk about why we did that together. >> Yeah. >> And what we've done together over many years. >> Right. You know, Brian, I think it's a natural extension of our relationship, right? You know, you look at the 12 year relationship that AWS and NASDAQ have had together, it's just the next step, in the way that we're going to help the industry transform itself. And so not just NASDAQ's business transformation for itself, but really a blueprint and a template for the entire capital markets industry. And so many times people will ask me, who's using Cloud well? Who's doing well in the Cloud? And NASDAQ is an easy example to point to, of somebody who's truly taking advantage of these capabilities because the Cloud isn't a place, it's a set of capabilities. And so, this is a shining example of how to use these capabilities to actually deliver real business benefit, not just to to your organization, but I think the really exciting part is the market technology piece of how you're serving other exchanges. >> So last year before re:Invent, we said, and it's obvious within the tech ecosystem, that technology companies are building on top of the Cloud. We said, the big trend that we see in the 2020s is that, you know, consumers of IT, historically, your customers are going to start taking their stacks, their software, their data, their services and sassifying, putting it on the Cloud and delivering new services to customers. So when we saw Adena on stage last year, we called it by the way, we called it Super Cloud. >> Yeah. >> Okay. Some people liked the term but I love it. And so yeah, Super Cloud. So when we saw Adena on stage, we said that's a great example. We've seen Capital One doing some similar things, we've had some conversations with US West, it's happening, right? So talk about how you actually do that. I mean, because you've got a lot, you've got a big on-premises stay, are you connecting to that? Is it all in the Cloud? Paint a picture of what the architecture looks like? >> Yeah. And there's, so you started with the business transformation, so I like that. >> Yeah. >> And the Super Cloud designation, what we are is, we own and operate exchanges in the United States and in Europe and in Canada. So we have our own markets that we're looking at modernizing. So we look at this, as a modernization of the capital market infrastructure, but we happen to be the leading technology provider for other markets around the world. So you either build your own or you source from us. And we're by far the leading provider. So a lot of our customers said, how about if you go first? It's kind of like Mikey, you know, give it to Mikey, let him try it. >> See if Mikey likes it. >> Yeah. >> Penguin off the iceberg thing. >> Yeah. And so what we did is we said, to make this easy for our customers, so you want to ask your customers, you want to figure out how you can do it so that you don't disrupt their business. So we took the Edge Compute that was announced a few years ago, Amazon Outposts, and we were one of their early customers. So we started immediately to innovate with, jointly innovate with Amazon. And we said, this looks interesting for us. So we extended the region into our Carteret data center in Northern New Jersey, which gave us all the services that we know and love from Amazon. So our technical operations team has the same tools and services but then, we're able to connect because in the markets what we're doing is we need to connect fairly. So we need to ensure that you still have that fairness element. So by bringing it into our building and extending the Edge Compute platform, the AWS Outpost into Carteret, that allowed us to also talk very succinctly with our regulators. It's a familiar territory, it's all buttoned up. And that simplified the conversion conversation with the regulators. It simplified it with our customers. And then it was up to us to then deliver time and performance >> Because you had alternatives. You could have taken a more mature kind of on-prem legacy stack, figured out how to bolt that in, you know, less cloudy. So why did you choose Outposts? I am curious. >> Well, Outposts looked like when it was announced, that it was really about extending territory, so we had our customers in mind, our global customers, and they don't always have an AWS region in country. So a lot of you think about a regulator, they're going to say, well where is this region located? So finally we saw this ability to grow the Cloud geographically. And of course we're in Sweden, so we we work with the AWS region in Stockholm, but not every country has a region yet. >> And we're working as fast as we can. - Yes, you are. >> Building in every single location around the planet. >> You're doing a good job. >> So, we saw it as an investment that Amazon had to grow the geographic footprint and we have customers in many smaller countries that don't have a region today. So maybe talk a little bit about what you guys had in mind and it's a multi-industry trend that the Edge Compute has four or five industries that you can say, this really makes a lot of sense to extend the Cloud. >> And David, you said it earlier, there's a trend of ecosystems that are coming onto the Cloud. This is our opportunity to bring the Cloud to an ecosystem, to an existing ecosystem. And if you think about NASDAQ's data center in Carteret, there's an ecosystem of NASDAQ's clients there that are there to be with NASDAQ. And so, it was actually much easier for us as we worked together over a really a four year period, thinking about this and how to make this technological transition, to actually bring the capabilities to that ecosystem, rather than trying to bring the ecosystem to AWS in one of our public regions. And so, that's been our philosophy with Outpost all along. It's actually extending our capabilities that our customers know and love into any environment that they need to be able to use that in. And so to Brad's point about servicing other markets in different countries around the world, it actually gives us that ability to do that very quickly, very nimbly and very succinctly and successfully. >> Did you guys write a working backwards document for this initiative? >> We did. >> Yeah, we actually did. So to be, this is one of the fully exercised. We have a couple of... So by the way, Scott used to work at NASDAQ and we have a number of people who have gone from NASDAQ data to AWS, and from AWS to NASDAQ. So we have adopted, that's one of the things that we think is an effective way to really clarify what you're trying to accomplish with a project. So I know you're a little bit kidding on that, but we did. >> No, I was close. Because I want to go to the like, where are we in the milestone? And take us through kind of what we can expect going forward now that we've worked backwards. >> Yep, we did. >> We did. And look, I think from a milestone perspective, as you heard Brad say, we're very excited that we've stood up MRX in production. Having worked at NASDAQ myself, when you make a change and when you stand up a market that's always a moment where you're working with your community, with your clients and you've got a market-wide call that you're working and you're wanting to make sure that everything goes smoothly. And so, when that call went smoothly and that transition went smoothly I know you were very happy, and in AWS, we were also very happy as well that we hit that milestone within the timeframe that Adena set. And that was very important I know to you. >> Yeah. >> And for us as well. >> Yeah. And our commitment, so the time base of this one was by the end of 2022. So November 7th, checked. We got that one done. >> That's awesome. >> The other one is we said, we wanted the performance to be as good or better than our current platform that we have. And we were putting a new version of our derivative or options software onto this platform. We had confidence because we already rolled it to one market in the US then we rolled it earlier this year and that was last year. And we rolled it to our nordic derivatives market. And we saw really good customer feedback. So we had confidence in our software was going to run. Now we had to marry that up with the Outpost platform and we said we really want to achieve as good or better performance and we achieved better performance, so that's noticeable by our customers. And that one was the biggest question. I think our customers understand when we set a date, we test them with them. We have our national test facility that they can test in. But really the big question was how is it going to perform? And that was, I think one of the biggest proof points that we're really proud about, jointly together. And it took both, it took both of us to really innovate and get the platform right, and we did a number of iterations. We're never done. >> Right. >> But we have a final result that says it is better. >> Well, congratulations. - Thank you. >> It sounds like you guys have done a tremendous job. What can we expect in 2023? From NASDAQ and AWS? Any little nuggets you can share? >> Well, we just came from the partner, the partner Keynote with Adam and Ruba and we had another colleague on stage, so Nick Ciubotariu, so he is actually someone who brought digital assets and cryptocurrencies onto the Venmo, PayPal platform. He joined NASDAQ about a year ago and we announced that in our marketplace, the Amazon marketplace, we are going to offer digital custody, digital assets custody solution. So that is certainly going to be something we're excited about in 2023. >> I know we got to go, but I love this story because it fits so great at the Super cloud but we've learned so much from Amazon over the years. Two pieces of teams, we talked about working backwards, customer obsession, but this is a story of NASDAQ pointing its internal capabilities externally. We're already on that journey and then, bringing that to the Cloud. Very powerful story. I wonder what's next in this, because we learn a lot and we, it's like the NFL, we copy it. I think about product market fit. You think about scientific, you know, go to market and seeing that applied to the financial services industry and obviously other industries, it's really exciting to see. So congratulations. >> No, thank you. And look, I think it's an example of Invent and Simplify, that's another Amazon principle. And this is, I think a great example of inventing on behalf of an industry and then continually working to simplify the way that the industry works with all of us. >> Last question and we've got only 30 seconds left. Brad, I'm going to direct it to you. If you had the opportunity to take over the NASDAQ sign in Times Square and say a phrase that summarizes what NASDAQ and AWS are doing together, what would it say? >> Oh, and I think I'm going to put that up on Monday. So we're going to close the market together and it's going to say, "Modernizing the capital market's infrastructure together." >> Very cool. >> Excellent. Drop the mic. Guys, this was fantastic. Thank you so much for joining us. We appreciate you joining us on the show, sharing your insights and what NASDAQ and AWS are doing. We're going to have to keep watching this. You're going to have to come back next year. >> All right. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (soft music)

(lively music) >> Good morning. Welcome back to theCUBE's coverage at Supercomputing Conference 2022, live here in Dallas. I'm Dave Nicholson with my co-host Paul Gillin. So far so good, Paul? It's been a fascinating morning Three days in, and a fascinating guest, Ian from AWS. Welcome. >> Thanks, Dave. >> What are we going to talk about? Batch computing, HPC. >> We've got a lot, let's get started. Let's dive right in. >> Yeah, we've got a lot to talk about. I mean, first thing is we recently announced our batch support for EKS. EKS is our Kubernetes, managed Kubernetes offering at AWS. And so batch computing is still a large portion of HPC workloads. While the interactive component is growing, the vast majority of systems are just kind of fire and forget, and we want to run thousands and thousands of nodes in parallel. We want to scale out those workloads. And what's unique about our AWS batch offering, is that we can dynamically scale, based upon the queue depth. And so customers can go from seemingly nothing up to thousands of nodes, and while they're executing their work they're only paying for the instances while they're working. And then as the queue depth starts to drop and the number of jobs waiting in the queue starts to drop, then we start to dynamically scale down those resources. And so it's extremely powerful. We see lots of distributed machine learning, autonomous vehicle simulation, and traditional HPC workloads taking advantage of AWS Batch. >> So when you have a Kubernetes cluster does it have to be located in the same region as the HPC cluster that's going to be doing the batch processing, or does the nature of batch processing mean, in theory, you can move something from here to somewhere relatively far away to do the batch processing? How does that work? 'Cause look, we're walking around here and people are talking about lengths of cables in order to improve performance. So what does that look like when you peel back the cover and you look at it physically, not just logically, AWS is everywhere, but physically, what does that look like? >> Oh, physically, for us, it depends on what the customer's looking for. We have workflows that are all entirely within a single region. And so where they could have a portion of say the traditional HPC workflow, is within that region as well as the batch, and they're saving off the results, say to a shared storage file system like our Amazon FSx for Lustre, or maybe aging that back to an S3 object storage for a little lower cost storage solution. Or you can have customers that have a kind of a multi-region orchestration layer to where they say, "You know what? "I've got a portion of my workflow that occurs "over on the other side of the country "and I replicate my data between the East Coast "and the West Coast just based upon business needs. "And I want to have that available to customers over there. "And so I'll do a portion of it in the East Coast "a portion of it in the West Coast." Or you can think of that even globally. It really depends upon the customer's architecture. >> So is the intersection of Kubernetes with HPC, is this relatively new? I know you're saying you're, you're announcing it. >> It really is. I think we've seen a growing perspective. I mean, Kubernetes has been a long time kind of eating everything, right, in the enterprise space? And now a lot of CIOs in the industrial space are saying, "Why am I using one orchestration layer "to manage my HPC infrastructure and another one "to manage my enterprise infrastructure?" And so there's a growing appreciation that, you know what, why don't we just consolidate on one? And so that's where we've seen a growth of Kubernetes infrastructure and our own managed Kubernetes EKS on AWS. >> Last month you announced a general availability of Trainium, of a chip that's optimized for AI training. Talk about what's special about that chip or what is is customized to the training workloads. >> Yeah, what's unique about the Trainium, is you'll you'll see 40% price performance over any other GPU available in the AWS cloud. And so we've really geared it to be that most price performance of options for our customers. And that's what we like about the silicon team, that we're part of that Annaperna acquisition, is because it really has enabled us to have this differentiation and to not just be innovating at the software level but the entire stack. That Annaperna Labs team develops our network cards, they develop our ARM cards, they developed this Trainium chip. And so that silicon innovation has become a core part of our differentiator from other vendors. And what Trainium allows you to do is perform similar workloads, just at a lower price performance. >> And you also have a chip several years older, called Inferentia- >> Um-hmm. >> Which is for inferencing. What is the difference between, I mean, when would a customer use one versus the other? How would you move the workload? >> What we've seen is customers traditionally have looked for a certain class of machine, more of a compute type that is not as accelerated or as heavy as you would need for Trainium for their inference portion of their workload. So when they do that training they want the really beefy machines that can grind through a lot of data. But when you're doing the inference, it's a little lighter weight. And so it's a different class of machine. And so that's why we've got those two different product lines with the Inferentia being there to support those inference portions of their workflow and the Trainium to be that kind of heavy duty training work. >> And then you advise them on how to migrate their workloads from one to the other? And once the model is trained would they switch to an Inferentia-based instance? >> Definitely, definitely. We help them work through what does that design of that workflow look like? And some customers are very comfortable doing self-service and just kind of building it on their own. Other customers look for a more professional services engagement to say like, "Hey, can you come in and help me work "through how I might modify my workflow to "take full advantage of these resources?" >> The HPC world has been somewhat slower than commercial computing to migrate to the cloud because- >> You're very polite. (panelists all laughing) >> Latency issues, they want to control the workload, they want to, I mean there are even issues with moving large amounts of data back and forth. What do you say to them? I mean what's the argument for ditching the on-prem supercomputer and going all-in on AWS? >> Well, I mean, to be fair, I started at AWS five years ago. And I can tell you when I showed up at Supercomputing, even though I'd been part of this community for many years, they said, "What is AWS doing at Supercomputing?" I know you care, wait, it's Amazon Web Services. You care about the web, can you actually handle supercomputing workloads? Now the thing that very few people appreciated is that yes, we could. Even at that time in 2017, we had customers that were performing HPC workloads. Now that being said, there were some real limitations on what we could perform. And over those past five years, as we've grown as a company, we've started to really eliminate those frictions for customers to migrate their HPC workloads to the AWS cloud. When I started in 2017, we didn't have our elastic fabric adapter, our low-latency interconnect. So customers were stuck with standard TCP/IP. So for their highly demanding open MPI workloads, we just didn't have the latencies to support them. So the jobs didn't run as efficiently as they could. We didn't have Amazon FSx for Lustre, our managed lustre offering for high performant, POSIX-compliant file system, which is kind of the key to a large portion of HPC workloads is you have to have a high-performance file system. We didn't even, I mean, we had about 25 gigs of networking when I started. Now you look at, with our accelerated instances, we've got 400 gigs of networking. So we've really continued to grow across that spectrum and to eliminate a lot of those really, frictions to adoption. I mean, one of the key ones, we had a open source toolkit that was jointly developed by Intel and AWS called CFN Cluster that customers were using to even instantiate their clusters. So, and now we've migrated that all the way to a fully functional supported service at AWS called AWS Parallel Cluster. And so you've seen over those past five years we have had to develop, we've had to grow, we've had to earn the trust of these customers and say come run your workloads on us and we will demonstrate that we can meet your demanding requirements. And at the same time, there's been, I'd say, more of a cultural acceptance. People have gone away from the, again, five years ago, to what are you doing walking around the show, to say, "Okay, I'm not sure I get it. "I need to look at it. "I, okay, I, now, oh, it needs to be a part "of my architecture but the standard questions, "is it secure? "Is it price performant? "How does it compare to my on-prem?" And really culturally, a lot of it is, just getting IT administrators used to, we're not eliminating a whole field, right? We're just upskilling the people that used to rack and stack actual hardware, to now you're learning AWS services and how to operate within that environment. And it's still key to have those people that are really supporting these infrastructures. And so I'd say it's a little bit of a combination of cultural shift over the past five years, to see that cloud is a super important part of HPC workloads, and part of it's been us meeting the the market segment of where we needed to with innovating both at the hardware level and at the software level, which we're going to continue to do. >> You do have an on-prem story though. I mean, you have outposts. We don't hear a lot of talk about outposts lately, but these innovations, like Inferentia, like Trainium, like the networking innovation you're talking about, are these going to make their way into outposts as well? Will that essentially become this supercomputing solution for customers who want to stay on-prem? >> Well, we'll see what the future lies, but we believe that we've got the, as you noted, we've got the hardware, we've got the network, we've got the storage. All those put together gives you a a high-performance computer, right? And whether you want it to be redundant in your local data center or you want it to be accessible via APIs from the AWS cloud, we want to provide that service to you. >> So to be clear, that's not that's not available now, but that is something that could be made available? >> Outposts are available right now, that have this the services that you need. >> All these capabilities? >> Often a move to cloud, an impetus behind it comes from the highest levels in an organization. They're looking at the difference between OpEx versus CapEx. CapEx for a large HPC environment, can be very, very, very high. Are these HPC clusters consumed as an operational expense? Are you essentially renting time, and then a fundamental question, are these multi-tenant environments? Or when you're referring to batches being run in HPC, are these dedicated HPC environments for customers who are running batches against them? When you think about batches, you think of, there are times when batches are being run and there are times when they're not being run. So that would sort of conjure, in the imagination, multi-tenancy, what does that look like? >> Definitely, and that's been, let me start with your second part first is- >> Yeah. That's been a a core area within AWS is we do not see as, okay we're going to, we're going to carve out this super computer and then we're going to allocate that to you. We are going to dynamically allocate multi-tenant resources to you to perform the workloads you need. And especially with the batch environment, we're going to spin up containers on those, and then as the workloads complete we're going to turn those resources over to where they can be utilized by other customers. And so that's where the batch computing component really is powerful, because as you say, you're releasing resources from workloads that you're done with. I can use those for another portion of the workflow for other work. >> Okay, so it makes a huge difference, yeah. >> You mentioned, that five years ago, people couldn't quite believe that AWS was at this conference. Now you've got a booth right out in the center of the action. What kind of questions are you getting? What are people telling you? >> Well, I love being on the show floor. This is like my favorite part is talking to customers and hearing one, what do they love, what do they want more of? Two, what do they wish we were doing that we're not currently doing? And three, what are the friction points that are still exist that, like, how can I make their lives easier? And what we're hearing is, "Can you help me migrate my workloads to the cloud? "Can you give me the information that I need, "both from a price for performance, "for an operational support model, "and really help me be an internal advocate "within my environment to explain "how my resources can be operated proficiently "within the AWS cloud." And a lot of times it's, let's just take your application a subset of your applications and let's benchmark 'em. And really that, AWS, one of the key things is we are a data-driven environment. And so when you take that data and you can help a customer say like, "Let's just not look at hypothetical, "at synthetic benchmarks, let's take "actually the LS-DYNA code that you're running, perhaps. "Let's take the OpenFOAM code that you're running, "that you're running currently "in your on-premises workloads, "and let's run it on AWS cloud "and let's see how it performs." And then we can take that back to your to the decision makers and say, okay, here's the price for performance on AWS, here's what we're currently doing on-premises, how do we think about that? And then that also ties into your earlier question about CapEx versus OpEx. We have models where actual, you can capitalize a longer-term purchase at AWS. So it doesn't have to be, I mean, depending upon the accounting models you want to use, we do have a majority of customers that will stay with that OpEx model, and they like that flexibility of saying, "Okay, spend as you go." We need to have true ups, and make sure that they have insight into what they're doing. I think one of the boogeyman is that, oh, I'm going to spend all my money and I'm not going to know what's available. And so we want to provide the, the cost visibility, the cost controls, to where you feel like, as an HPC administrator you have insight into what your customers are doing and that you have control over that. And so once you kind of take away some of those fears and and give them the information that they need, what you start to see too is, you know what, we really didn't have a lot of those cost visibility and controls with our on-premises hardware. And we've had some customers tell us we had one portion of the workload where this work center was spending thousands of dollars a day. And we went back to them and said, "Hey, we started to show this, "what you were spending on-premises." They went, "Oh, I didn't realize that." And so I think that's part of a cultural thing that, at an HPC, the question was, well on-premises is free. How do you compete with free? And so we need to really change that culturally, to where people see there is no free lunch. You're paying for the resources whether it's on-premises or in the cloud. >> Data scientists don't worry about budgets. >> Wait, on-premises is free? Paul mentioned something that reminded me, you said you were here in 2017, people said AWS, web, what are you even doing here? Now in 2022, you're talking in terms of migrating to cloud. Paul mentioned outposts, let's say that a customer says, "Hey, I'd like you to put "in a thousand-node cluster in this data center "that I happen to own, but from my perspective, "I want to interact with it just like it's "in your data center." In other words, the location doesn't matter. My experience is identical to interacting with AWS in an AWS data center, in a CoLo that works with AWS, but instead it's my physical data center. When we're tracking the percentage of IT that's that is on-prem versus off-prem. What is that? Is that, what I just described, is that cloud? And in five years are you no longer going to be talking about migrating to cloud because people go, "What do you mean migrating to cloud? "What do you even talking about? "What difference does it make?" It's either something that AWS is offering or it's something that someone else is offering. Do you think we'll be at that point in five years, where in this world of virtualization and abstraction, you talked about Kubernetes, we should be there already, thinking in terms of it doesn't matter as long as it meets latency and sovereignty requirements. So that, your prediction, we're all about insights and supercomputing- >> My prediction- >> In five years, will you still be talking about migrating to cloud or will that be something from the past? >> In five years, I still think there will be a component. I think the majority of the assumption will be that things are cloud-native and you start in the cloud and that there are perhaps, an aspect of that, that will be interacting with some sort of an edge device or some sort of an on-premises device. And we hear more and more customers that are saying, "Okay, I can see the future, "I can see that I'm shrinking my footprint." And, you can see them still saying, "I'm not sure how small that beachhead will be, "but right now I want to at least say "that I'm going to operate in that hybrid environment." And so I'd say, again, the pace of this community, I'd say five years we're still going to be talking about migrations, but I'd say the vast majority will be a cloud-native, cloud-first environment. And how do you classify that? That outpost sitting in someone's data center? I'd say we'd still, at least I'll leave that up to the analysts, but I think it would probably come down as cloud spend. >> Great place to end. Ian, you and I now officially have a bet. In five years we're going to come back. My contention is, no we're not going to be talking about it anymore. >> Okay. >> And kids in college are going to be like, "What do you mean cloud, it's all IT, it's all IT." And they won't remember this whole phase of moving to cloud and back and forth. With that, join us in five years to see the result of this mega-bet between Ian and Dave. I'm Dave Nicholson with theCUBE, here at Supercomputing Conference 2022, day three of our coverage with my co-host Paul Gillin. Thanks again for joining us. Stay tuned, after this short break, we'll be back with more action. (lively music)

>> From the CUBE Studios in Palo Alto in Boston, bringing you data driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)

(upbeat techno music) >> Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions, and they were largely confined to regulated industries that had to comply with public policy mandates. But as the cloud went mainstream the tech giants showed us how valuable data could become, and the value proposition for data quality and trust, it evolved from primarily a compliance driven issue, to becoming a linchpin of competitive advantage. But, data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper-specialized skills, to develop data architectures and processes, to serve the myriad data needs of organizations. And it resulted in a lot of frustration, with data initiatives for most organizations, that didn't have the resources of the cloud guys and the social media giants, to really attack their data problems and turn data into gold. This is why today, for example, there's quite a bit of momentum to re-thinking monolithic data architectures. You see, you hear about initiatives like Data Mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business users. You hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver, like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that but also, how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. In other words, while it's enticing to experiment, and run fast and loose with data initiatives, kind of like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated and intelligent. Governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is going to use data that is entrusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. Hello and welcome to theCUBE's coverage of Data Citizens made possible by Collibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Vellante and I'm one of the hosts of our program which is running in parallel to Data Citizens. Now at theCUBE we like to say we extract the signal from the noise, and over the next couple of days we're going to feature some of the themes from the keynote speakers at Data Citizens, and we'll hear from several of the executives. Felix Van de Maele, who is the co-founder and CEO of Collibra, will join us. Along with one of the other founders of Collibra, Stan Christiaens, who's going to join my colleague Lisa Martin. I'm going to also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Haslbeck. He's the Vice President of Data Quality at Collibra. He's an amazingly smart dude who founded Owl DQ, a company that he sold to Collibra last year. Now, many companies they didn't make it through the Hadoop era, you know they missed the industry waves and they became driftwood. Collibra, on the other hand, has evolved its business, they've leveraged the cloud, expanded its product portfolio and leaned in heavily to some major partnerships with cloud providers as well as receiving a strategic investment from Snowflake, earlier this year. So, it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. (upbeat rock music) Last year theCUBE covered Data Citizens, Collibra's customer event, and the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know starting with the Hadoop movement, we had Data lakes, we had Spark, the ascendancy of programming languages like Python, the introduction of frameworks like Tensorflow, the rise of AI, Low Code, No Code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives, and we said at the time, you know maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation. Meaning, making it easier for domain experts to both gain insights from data, trust the data, and begin to use that data in new ways, fueling data products, monetization, and insights. Data Citizens 2022 is back and we're pleased to have Felix Van de Maele who is the founder and CEO of Collibra. He's on theCUBE. We're excited to have you Felix. Good to see you again. >> Likewise Dave. Thanks for having me again. >> You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it why data intelligence is more important now than ever, and get current on what Collibra has been up to over the past year, and what's changed since Data citizens 2021, and we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends and we're not just snapping back to the 2010s, that's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s, from the previous decade, and what challenges does that bring for your customers? >> Yeah, absolutely, and and I think you said it well, Dave and the intro that, that rising complexity and fragmentation, in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use, has only gotten more more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under, respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity, and fragmentation. So, it's become much more acute. And to your earlier point, we do live in a different world and and the past couple of years we could probably just kind of brute force it, right? We could focus on, on the top line, there was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, how do we truly get the value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale with data, not just from a a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? You said at the, the people and process, how do we do that at scale? And that's only, only, only becoming much more important, and we do believe that the, the economic environment that we find ourselves in today is going to be catalyst for organizations to really take that more seriously if, if, if you will, than they maybe have in the have in the past. >> You know, I don't know when you guys founded Collibra, if you had a sense as to how complicated it was going to get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >> Yeah, absolutely. We, we started Collibra in 2008. So, in some sense and the, the last kind of financial crisis and that was really the, the start of Collibra, where we found product market fit, working with large financial institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis. And kind of here we are again, in a very different environment of course 15 years, almost 15 years later, but data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So, what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it Data Citizens, we truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we still relatively early in that, in that journey. >> Well that's interesting, because you know, in my observation it takes 7 to 10 years to actually build a company, and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your current momentum? >> Yeah, absolutely. Again, there's a lot of tailwind organizations that are only maturing their data practices and we've seen that kind of transform or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world with its Adobe, Heineken, Bank of America and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in the, in the market with some of the cloud partners like Google, Amazon, Snowflake, Data Breaks, and and others, right? As those kind of new modern data infrastructures, modern data architectures, are definitely all moving to the cloud. A great opportunity for us, our partners, and of course our customers, to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course data quality isn't new but I think there's a lot of reasons why we're so excited about quality and observability now. One, is around leveraging AI machine learning again to drive more automation. And a second is that those data pipelines, that are now being created in the cloud, in these modern data architecture, architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously, has become absolutely critical so that they're really excited about, about that as well. And on the organizational side, I'm sure you've heard the term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believed in. Federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations, and so that aligns really well with our vision and from a product perspective, we've seen a lot of momentum with our customers there as well. >> Yeah, you know, a couple things there. I mean, the acquisition of OwlDQ, you know Kirk Haslbeck and, and their team. It's interesting, you know the whole data quality used to be this back office function and and really confined to highly regulated industries. It's come to the front office, it's top of mind for Chief Data Officers. Data mesh, you mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So, let's chat a little bit about the, the products. We're going to go deeper into products later on, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes, as you talked about earlier. Tell us a little bit about what you're introducing. >> Yeah, absolutely. We we're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission. Either customers are still start, are just starting on that, on that journey. We want to make it as easy as possible for the, for organization to actually get started, because we know that's important that they do. And for our organization and customers, that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again to make it easier for, really to, to accomplish that mission and vision around that Data Citizen, that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then, how do we make sure that, as clear becomes this kind of mission critical enterprise platform, from a security performance, architecture scale supportability, that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme. From an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One, is around data marketplace. Again, a lot of our customers have plans in that direction, How to make it easy? How do we make How do we make available to true kind of shopping experience? So that anybody in the organization can, in a very easy search first way, find the right data product, find the right dataset, that they can then consume. Usage analytics, how do you, how do we help organizations drive adoption? Tell them where they're working really well and where they have opportunities. Homepages again to, to make things easy for, for people, for anyone in your organization, to kind of get started with Collibra. You mentioned Workflow Designer, again, we have a very powerful enterprise platform, one of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a, a new Low-Code, No-Code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around Collibra protect, which in partnership with Snowflake, which has been a strategic investor in Collibra, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PIA data, is managed as a much more effective, effective rate. Really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily, and quickly, and widely as we can? Moving that to the cloud has been a big part of our strategy. So, we launch our data quality cloud product, as well as making use of those, those native compute capabilities and platforms, like Snowflake, Databricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down, so we're actually pushing down the computer and data quality, to monitoring into the underlying platform, which again from a scale performance and ease of use perspective, is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical, and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So that's a lot coming out, the team has been work, at work really hard, and we are really really excited about what we are coming, what we're bringing to market. >> Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you you talked about, you know, the marketplace, you know you think about Data Mesh, you think of data as product, one of the key principles, you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been, been so hard. So, how do you see sort of the future and, you know give us the, your closing thoughts please? >> Yeah, absolutely. And, and I think we we're really at a pivotal moment and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not going to fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to, deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can, as kind of our, as our mission. And so I'm really, really excited to see what we, what we are going to, how the marks are going to evolve over the next, next few quarters and years. I think the trend is clearly there. We talked about Data Mesh, this kind of federated approach focus on data products, is just another signal that we believe, that a lot of our organization are now at the time, they're understanding need to go beyond just the technology. I really, really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now is the time, given the economic environment that we are in, much more focus on control, much more focus on productivity, efficiency, and now is the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >> Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much. Good luck in, in San Diego. I know you're going to crush it out there. >> Thank you Dave. >> Yeah, it's a great spot for an in-person event and and of course the content post-event is going to be available at collibra.com and you can of course catch theCUBE coverage at theCUBE.net and all the news at siliconangle.com. This is Dave Vellante for theCUBE, your leader in enterprise and emerging tech coverage. (upbeat techno music)

>>Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions and they were largely confined to regulatory regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become and the value proposition for data quality and trust. It evolved from primarily a compliance driven issue to becoming a lynchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. >>And it resulted in a lot of frustration with data initiatives for most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today for example, this quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like data mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business Uni users, you hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that, but also how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. >>In other words, while it's enticing to experiment and run fast and loose with data initiatives kinda like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated. And intelligence governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is gonna use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. >>Hello and welcome to the Cube's coverage of Data Citizens made possible by Calibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Ante and I'm one of the hosts of our program, which is running in parallel to data citizens. Now at the Cube we like to say we extract the signal from the noise, and over the, the next couple of days, we're gonna feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives. Felix Von Dala, who is the co-founder and CEO of Collibra, will join us along with one of the other founders of Collibra, Stan Christians, who's gonna join my colleague Lisa Martin. I'm gonna also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the, the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Hasselbeck. >>He's the vice president of Data quality at Collibra. He's an amazingly smart dude who founded Owl dq, a company that he sold to Col to Collibra last year. Now many companies, they didn't make it through the Hado era, you know, they missed the industry waves and they became Driftwood. Collibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio, and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. >>Last year, the Cube Covered Data Citizens Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hado movement, we had data lakes, we'd spark the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of ai, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights for data, trust the data, and begin to use that data in new ways, fueling data, products, monetization and insights data citizens 2022 is back and we're pleased to have Felix Van Dema, who is the founder and CEO of Collibra. He's on the cube or excited to have you, Felix. Good to see you again. >>Likewise Dave. Thanks for having me again. >>You bet. All right, we're gonna get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Collibra has been up to over the past year and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >>Yeah, absolutely. And, and I think you said it well, Dave, and and the intro that that rising complexity and fragmentation in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kinda more, more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well, which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. >>So it's become much more acute. And, and to your earlier point, we do live in a different world and and the the past couple of years we could probably just kind of brute for it, right? We could focus on, on the top line. There was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are, are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, How do we truly get value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale it data, not just from a a technology and infrastructure perspective, but how do you actually scale data from an organizational perspective, right? You said at the the people and process, how do we do that at scale? And that's only, only only becoming much more important. And we do believe that the, the economic environment that we find ourselves in today is gonna be catalyst for organizations to really dig out more seriously if, if, if, if you will, than they maybe have in the have in the best. >>You know, I don't know when you guys founded Collibra, if, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >>Yeah, absolutely. We, we started Colli in 2008. So in some sense and the, the last kind of financial crisis, and that was really the, the start of Colli where we found product market fit, working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis and kind of here we are again in a very different environment, of course 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we are still relatively early in that, in that journey. >>Well, that's interesting because, you know, in my observation it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your, your current momentum? >>Yeah, absolutely. Again, there's, there's a lot of tail organizations that are only maturing the data practices and we've seen it kind of transform or, or, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in, in the, in the markets with some of the cloud partners like Google, Amazon, Snowflake, data bricks and, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners and of course our customers to help them kind of transition to the cloud even faster. >>And so we see a lot of excitement and momentum there within an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging ai, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architecture arch architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical so that they're really excited about about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believe. Then federated focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations. And so that aligns really well with our vision and, and from a product perspective, we've seen a lot of momentum with our customers there as well. >>Yeah, you know, a couple things there. I mean, the acquisition of i l dq, you know, Kirk Hasselbeck and, and their team, it's interesting, you know, the whole data quality used to be this back office function and, and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh. You mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the, the products. We're gonna go deeper in into products later on at, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the, the the under the covers in security, sort of making data more accessible for people just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >>Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission, either customers are still start, are just starting on that, on that journey. We wanna make it as easy as possible for the, for our organization to actually get started because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to, to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving. >>A lot of kind of ease of adoption, ease of use, but also then how do we make sure that lio becomes this kind of mission critical enterprise platform from a security performance architecture scale supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme from an innovation perspective, From a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction, how to make it easy. How do we make, how do we make available to true kind of shopping experience that anybody in your organization can, in a very easy search first way, find the right data product, find the right dataset, that data can then consume usage analytics. How do you, how do we help organizations drive adoption, tell them where they're working really well and where they have opportunities homepages again to, to make things easy for, for people, for anyone in your organization to kind of get started with ppia, you mentioned workflow designer, again, we have a very powerful enterprise platform. >>One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around K Bear Protect, which in partnership with Snowflake, which has been a strategic investor in kib, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as much more effective, effective rate, really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. >>So we launch more data quality cloud product as well as making use of those, those native compute capabilities in platforms like Snowflake, Data, Bricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down. So actually pushing down the computer and data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is gonna make a massive difference. And then more broadly, we, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So there's a lot coming out. The, the team has been work at work really hard and we are really, really excited about what we are coming, what we're bringing to markets. >>Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard. So how do you see sort of the future and, you know, give us the, your closing thoughts please? >>Yeah, absolutely. And I, and I think we we're really at this pivotal moment, and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can. It's kind of, of our, it's our mission. And so I'm really, really excited to see what we, what we are gonna, how the marks gonna evolve over the next, next few quarters and years. I think the trend is clearly there when we talk about data mesh, this kind of federated approach folks on data products is just another signal that we believe that a lot of our organization are now at the time. >>The understanding need to go beyond just the technology. I really, really think about how do we actually scale data as a business function, just like we've done with it, with, with hr, with, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in much more focus on control, much more focused on productivity efficiency and now's the time. We need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >>Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much and good luck in, in San Diego. I know you're gonna crush it out there. >>Thank you Dave. >>Yeah, it's a great spot for an in-person event and, and of course the content post event is gonna be available@collibra.com and you can of course catch the cube coverage@thecube.net and all the news@siliconangle.com. This is Dave Valante for the cube, your leader in enterprise and emerging tech coverage. >>Hi, I'm Jay from Collibra's Data Office. Today I want to talk to you about Collibra's data intelligence cloud. We often say Collibra is a single system of engagement for all of your data. Now, when I say data, I mean data in the broadest sense of the word, including reference and metadata. Think of metrics, reports, APIs, systems, policies, and even business processes that produce or consume data. Now, the beauty of this platform is that it ensures all of your users have an easy way to find, understand, trust, and access data. But how do you get started? Well, here are seven steps to help you get going. One, start with the data. What's data intelligence? Without data leverage the Collibra data catalog to automatically profile and classify your enterprise data wherever that data lives, databases, data lakes or data warehouses, whether on the cloud or on premise. >>Two, you'll then wanna organize the data and you'll do that with data communities. This can be by department, find a business or functional team, however your organization organizes work and accountability. And for that you'll establish community owners, communities, make it easy for people to navigate through the platform, find the data and will help create a sense of belonging for users. An important and related side note here, we find it's typical in many organizations that data is thought of is just an asset and IT and data offices are viewed as the owners of it and who are really the central teams performing analytics as a service provider to the enterprise. We believe data is more than an asset, it's a true product that can be converted to value. And that also means establishing business ownership of data where that strategy and ROI come together with subject matter expertise. >>Okay, three. Next, back to those communities there, the data owners should explain and define their data, not just the tables and columns, but also the related business terms, metrics and KPIs. These objects we call these assets are typically organized into business glossaries and data dictionaries. I definitely recommend starting with the topics that are most important to the business. Four, those steps that enable you and your users to have some fun with it. Linking everything together builds your knowledge graph and also known as a metadata graph by linking or relating these assets together. For example, a data set to a KPI to a report now enables your users to see what we call the lineage diagram that visualizes where the data in your dashboards actually came from and what the data means and who's responsible for it. Speaking of which, here's five. Leverage the calibra trusted business reporting solution on the marketplace, which comes with workflows for those owners to certify their reports, KPIs, and data sets. >>This helps them force their trust in their data. Six, easy to navigate dashboards or landing pages right in your platform for your company's business processes are the most effective way for everyone to better understand and take action on data. Here's a pro tip, use the dashboard design kit on the marketplace to help you build compelling dashboards. Finally, seven, promote the value of this to your users and be sure to schedule enablement office hours and new employee onboarding sessions to get folks excited about what you've built and implemented. Better yet, invite all of those community and data owners to these sessions so that they can show off the value that they've created. Those are my seven tips to get going with Collibra. I hope these have been useful. For more information, be sure to visit collibra.com. >>Welcome to the Cube's coverage of Data Citizens 2022 Collibra's customer event. My name is Dave Valante. With us is Kirk Hasselbeck, who's the vice president of Data Quality of Collibra Kirk, good to see you. Welcome. >>Thanks for having me, Dave. Excited to be here. >>You bet. Okay, we're gonna discuss data quality observability. It's a hot trend right now. You founded a data quality company, OWL dq, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >>Yeah, absolutely. It's, it's definitely exciting times for data quality, which you're right, has been around for a long time. So why now and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And, and while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as, as to why this is becoming so important now. And, and I guess you could kind of break this down simply and think about if Dave, you and I were gonna build, you know, a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, you know, what the ramifications could be, what, what those incidents would look like, or maybe better yet, we try to build a, a new trading algorithm with a crossover strategy where the 50 day crosses the, the 10 day average. >>And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, you know, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. You know, I, I bought a car not too long ago and my dad called and said, How many cylinders does it have? And I realized in that moment, you know, I might have failed him because, cause I didn't know. And, and I used to ask those types of questions about any lock brakes and cylinders and, and you know, if it's manual or, or automatic and, and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips, I, I really don't know that much about it. >>And, and that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the, the individuals loading and consuming all of this data for the company actually may not know that much about the data itself, and that's not even their job anymore. So we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >>You know, the other thing too about data quality, and for years we did the MIT CDO IQ event, we didn't do it last year, Covid messed everything up. But the observation I would make there thoughts is, is it data quality? Used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a, a risk to data as a, as an asset. And now as we say, we're gonna talk about observability. And so it's really become front and center just the whole quality issue because data's so fundamental, hasn't it? >>Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my, my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And, and that's kind of what's going on. There's, there's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before calibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is, is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, you know, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's, it's not ever going to be based on one or two domain experts anymore. >>So, So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they, are they cousins? What's your perspective on that? >>Yeah, it's, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the, the lingo is constantly moving is, you know, as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens, it's wrong and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. You know, everybody's talking about fresh data and stale data and, and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good in the bads. That was kind of your, your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data, but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >>So what's the Collibra angle on all this stuff made the acquisition, you got data quality observability coming together, you guys have a lot of expertise in, in this area, but you hear providence of data, you just talked about, you know, stale data, you know, the, the whole trend toward real time. How is Calibra approaching the problem and what's unique about your approach? >>Well, I think where we're fortunate is with our background, myself and team, we sort of lived this problem for a long time, you know, in, in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the, the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution, it's more advanced than some of the observation techniques that that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights, and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong, just show me the big picture, help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows, you can actually achieve total data governance at this point with the acquisition of what was a Lineage company years ago, and then my company Ldq now Collibra, Data quality Collibra may be the best positioned for total data governance and intelligence in the space. >>Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, you know, they just said, Oh, it's a glitch, you know, so they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you gotta announce new products, right? You're yearly event what's, what's new. Give us a sense as to what products are coming out, but specifically around data quality and observability. >>Absolutely. There's this, you know, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks is Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook in to these databases. And while we've always worked with the the same databases in the past, they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did your, my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? >>And with these native integrations that we're building and about to unveil, here's kind of a sneak peek for, for next week at Data Citizens. We're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration, you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress, cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >>So this is interesting because what you just described, you know, you mentioned Snowflake, you mentioned Google, Oh actually you mentioned yeah, data bricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool, but then Google's got the open data cloud. If you heard, you know, Google next and now data bricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm, I'm hearing to, to really understand the relationships between all those and have confidence across, you know, it's like Jak Dani, you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And, and, and that's what you're bringing to the table, Is that right? Did I get that right? >>Yeah, that's right. And it's, for us, it's, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now, we can send them the, the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network costs, zero egress cost, zero latency of time. And so when you were to log into Big Query tomorrow using our tool or like, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there, just like all of the major brands that you mentioned, but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And, and we think that this positions us to be the leader there. >>I love this example because, you know, Barry talks about, wow, the cloud guys are gonna own the world and, and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. All right, Kirk, give us your, your final thoughts and on on the trends that we've talked about and Data Citizens 22. >>Absolutely. Well, I think, you know, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there, they wanna know where everything is, where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're gonna see more one click solutions, more SAS based solutions and solutions that hopefully prove faster time to value on, on all of these modern cloud platforms. >>Excellent. All right, Kurt Hasselbeck, thanks so much for coming on the Cube and previewing Data Citizens 22. Appreciate it. >>Thanks for having me, Dave. >>You're welcome. Right, and thank you for watching. Keep it right there for more coverage from the Cube. Welcome to the Cube's virtual Coverage of Data Citizens 2022. My name is Dave Valante and I'm here with Laura Sellers, who's the Chief Product Officer at Collibra, the host of Data Citizens. Laura, welcome. Good to see you. >>Thank you. Nice to be here. >>Yeah, your keynote at Data Citizens this year focused on, you know, your mission to drive ease of use and scale. Now when I think about historically fast access to the right data at the right time in a form that's really easily consumable, it's been kind of challenging, especially for business users. Can can you explain to our audience why this matters so much and what's actually different today in the data ecosystem to make this a reality? >>Yeah, definitely. So I think what we really need and what I hear from customers every single day is that we need a new approach to data management and our product teams. What inspired me to come to Calibra a little bit a over a year ago was really the fact that they're very focused on bringing trusted data to more users across more sources for more use cases. And so as we look at what we're announcing with these innovations of ease of use and scale, it's really about making teams more productive in getting started with and the ability to manage data across the entire organization. So we've been very focused on richer experiences, a broader ecosystem of partners, as well as a platform that delivers performance, scale and security that our users and teams need and demand. So as we look at, Oh, go ahead. >>I was gonna say, you know, when I look back at like the last 10 years, it was all about getting the technology to work and it was just so complicated. But, but please carry on. I'd love to hear more about this. >>Yeah, I, I really, you know, Collibra is a system of engagement for data and we really are working on bringing that entire system of engagement to life for everyone to leverage here and now. So what we're announcing from our ease of use side of the world is first our data marketplace. This is the ability for all users to discover and access data quickly and easily shop for it, if you will. The next thing that we're also introducing is the new homepage. It's really about the ability to drive adoption and have users find data more quickly. And then the two more areas of the ease of use side of the world is our world of usage analytics. And one of the big pushes and passions we have at Collibra is to help with this data driven culture that all companies are trying to create. And also helping with data literacy, with something like usage analytics, it's really about driving adoption of the CLE platform, understanding what's working, who's accessing it, what's not. And then finally we're also introducing what's called workflow designer. And we love our workflows at Libra, it's a big differentiator to be able to automate business processes. The designer is really about a way for more people to be able to create those workflows, collaborate on those workflow flows, as well as people to be able to easily interact with them. So a lot of exciting things when it comes to ease of use to make it easier for all users to find data. >>Y yes, there's definitely a lot to unpack there. I I, you know, you mentioned this idea of, of of, of shopping for the data. That's interesting to me. Why this analogy, metaphor or analogy, I always get those confused. I let's go with analogy. Why is it so important to data consumers? >>I think when you look at the world of data, and I talked about this system of engagement, it's really about making it more accessible to the masses. And what users are used to is a shopping experience like your Amazon, if you will. And so having a consumer grade experience where users can quickly go in and find the data, trust that data, understand where the data's coming from, and then be able to quickly access it, is the idea of being able to shop for it, just making it as simple as possible and really speeding the time to value for any of the business analysts, data analysts out there. >>Yeah, I think when you, you, you see a lot of discussion about rethinking data architectures, putting data in the hands of the users and business people, decentralized data and of course that's awesome. I love that. But of course then you have to have self-service infrastructure and you have to have governance. And those are really challenging. And I think so many organizations, they're facing adoption challenges, you know, when it comes to enabling teams generally, especially domain experts to adopt new data technologies, you know, like the, the tech comes fast and furious. You got all these open source projects and get really confusing. Of course it risks security, governance and all that good stuff. You got all this jargon. So where do you see, you know, the friction in adopting new data technologies? What's your point of view and how can organizations overcome these challenges? >>You're, you're dead on. There's so much technology and there's so much to stay on top of, which is part of the friction, right? It's just being able to stay ahead of, of and understand all the technologies that are coming. You also look at as there's so many more sources of data and people are migrating data to the cloud and they're migrating to new sources. Where the friction comes is really that ability to understand where the data came from, where it's moving to, and then also to be able to put the access controls on top of it. So people are only getting access to the data that they should be getting access to. So one of the other things we're announcing with, with all of the innovations that are coming is what we're doing around performance and scale. So with all of the data movement, with all of the data that's out there, the first thing we're launching in the world of performance and scale is our world of data quality. >>It's something that Collibra has been working on for the past year and a half, but we're launching the ability to have data quality in the cloud. So it's currently an on-premise offering, but we'll now be able to carry that over into the cloud for us to manage that way. We're also introducing the ability to push down data quality into Snowflake. So this is, again, one of those challenges is making sure that that data that you have is d is is high quality as you move forward. And so really another, we're just reducing friction. You already have Snowflake stood up. It's not another machine for you to manage, it's just push down capabilities into Snowflake to be able to track that quality. Another thing that we're launching with that is what we call Collibra Protect. And this is that ability for users to be able to ingest metadata, understand where the PII data is, and then set policies up on top of it. So very quickly be able to set policies and have them enforced at the data level. So anybody in the organization is only getting access to the data they should have access to. >>Here's Topica data quality is interesting. It's something that I've followed for a number of years. It used to be a back office function, you know, and really confined only to highly regulated industries like financial services and healthcare and government. You know, you look back over a decade ago, you didn't have this worry about personal information, g gdpr, and, you know, California Consumer Privacy Act all becomes, becomes so much important. The cloud is really changed things in terms of performance and scale and of course partnering for, for, with Snowflake it's all about sharing data and monetization, anything but a back office function. So it was kind of smart that you guys were early on and of course attracting them and as a, as an investor as well was very strong validation. What can you tell us about the nature of the relationship with Snowflake and specifically inter interested in sort of joint engineering or, and product innovation efforts, you know, beyond the standard go to market stuff? >>Definitely. So you mentioned there were a strategic investor in Calibra about a year ago. A little less than that I guess. We've been working with them though for over a year really tightly with their product and engineering teams to make sure that Collibra is adding real value. Our unified platform is touching pieces of our unified platform or touching all pieces of Snowflake. And when I say that, what I mean is we're first, you know, able to ingest data with Snowflake, which, which has always existed. We're able to profile and classify that data we're announcing with Calibra Protect this week that you're now able to create those policies on top of Snowflake and have them enforce. So again, people can get more value out of their snowflake more quickly as far as time to value with, with our policies for all business users to be able to create. >>We're also announcing Snowflake Lineage 2.0. So this is the ability to take stored procedures in Snowflake and understand the lineage of where did the data come from, how was it transformed with within Snowflake as well as the data quality. Pushdown, as I mentioned, data quality, you brought it up. It is a new, it is a, a big industry push and you know, one of the things I think Gartner mentioned is people are losing up to $15 million without having great data quality. So this push down capability for Snowflake really is again, a big ease of use push for us at Collibra of that ability to, to push it into snowflake, take advantage of the data, the data source, and the engine that already lives there and get the right and make sure you have the right quality. >>I mean, the nice thing about Snowflake, if you play in the Snowflake sandbox, you, you, you, you can get sort of a, you know, high degree of confidence that the data sharing can be done in a safe way. Bringing, you know, Collibra into the, into the story allows me to have that data quality and, and that governance that I, that I need. You know, we've said many times on the cube that one of the notable differences in cloud this decade versus last decade, I mean ob there are obvious differences just in terms of scale and scope, but it's shaping up to be about the strength of the ecosystems. That's really a hallmark of these big cloud players. I mean they're, it's a key factor for innovating, accelerating product delivery, filling gaps in, in the hyperscale offerings cuz you got more stack, you know, mature stack capabilities and you know, it creates this flywheel momentum as we often say. But, so my question is, how do you work with the hyperscalers? Like whether it's AWS or Google, whomever, and what do you see as your role and what's the Collibra sweet spot? >>Yeah, definitely. So, you know, one of the things I mentioned early on is the broader ecosystem of partners is what it's all about. And so we have that strong partnership with Snowflake. We also are doing more with Google around, you know, GCP and kbra protect there, but also tighter data plex integration. So similar to what you've seen with our strategic moves around Snowflake and, and really covering the broad ecosystem of what Collibra can do on top of that data source. We're extending that to the world of Google as well and the world of data plex. We also have great partners in SI's Infosys is somebody we spoke with at the conference who's done a lot of great work with Levi's as they're really important to help people with their whole data strategy and driving that data driven culture and, and Collibra being the core of it. >>Hi Laura, we're gonna, we're gonna end it there, but I wonder if you could kind of put a bow on, you know, this year, the event your, your perspectives. So just give us your closing thoughts. >>Yeah, definitely. So I, I wanna say this is one of the biggest releases Collibra's ever had. Definitely the biggest one since I've been with the company a little over a year. We have all these great new product innovations coming to really drive the ease of use to make data more valuable for users everywhere and, and companies everywhere. And so it's all about everybody being able to easily find, understand, and trust and get access to that data going forward. >>Well congratulations on all the pro progress. It was great to have you on the cube first time I believe, and really appreciate you, you taking the time with us. >>Yes, thank you for your time. >>You're very welcome. Okay, you're watching the coverage of Data Citizens 2022 on the cube, your leader in enterprise and emerging tech coverage. >>So data modernization oftentimes means moving some of your storage and computer to the cloud where you get the benefit of scale and security and so on. But ultimately it doesn't take away the silos that you have. We have more locations, more tools and more processes with which we try to get value from this data. To do that at scale in an organization, people involved in this process, they have to understand each other. So you need to unite those people across those tools, processes, and systems with a shared language. When I say customer, do you understand the same thing as you hearing customer? Are we counting them in the same way so that shared language unites us and that gives the opportunity for the organization as a whole to get the maximum value out of their data assets and then they can democratize data so everyone can properly use that shared language to find, understand, and trust the data asset that's available. >>And that's where Collibra comes in. We provide a centralized system of engagement that works across all of those locations and combines all of those different user types across the whole business. At Collibra, we say United by data and that also means that we're united by data with our customers. So here is some data about some of our customers. There was the case of an online do it yourself platform who grew their revenue almost three times from a marketing campaign that provided the right product in the right hands of the right people. In other case that comes to mind is from a financial services organization who saved over 800 K every year because they were able to reuse the same data in different kinds of reports and before there was spread out over different tools and processes and silos, and now the platform brought them together so they realized, oh, we're actually using the same data, let's find a way to make this more efficient. And the last example that comes to mind is that of a large home loan, home mortgage, mortgage loan provider where they have a very complex landscape, a very complex architecture legacy in the cloud, et cetera. And they're using our software, they're using our platform to unite all the people and those processes and tools to get a common view of data to manage their compliance at scale. >>Hey everyone, I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizens. Stan, it's great to have you back on the cube. >>Hey Lisa, nice to be. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation. It also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow gonna to be a data citizen, right? So you need to make sure that these people are aware of it. You need that. People have skills and competencies to do with data what necessary and that's on, all right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in dashboard to actually make that decision and take that action. Right? >>And once you have that why to the organization, that's when you have a good data culture. Now that's continuous effort for most organizations because they're always moving, somehow they're hiring new people and it has to be continuous effort because we've seen that on the hand. Organizations continue challenged their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefit. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example, and we did an IDC study earlier this year, quite interesting. I can recommend anyone to it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, ok, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this re reasons you're trying to bring both of those together and the ones that get data intelligence right, are successful and competitive. That's, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, the organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, laptops, what have you, you're not using those, right? Or you know, you're delivering them throughout organization, but not enabling your colleagues to actually do something with that asset. Same thing as through with data today, right? If you're not properly using the data asset and competitors are, they're gonna to get more advantage. So as to how you get this done, establish this. There's angles to look at, Lisa. So one angle is obviously the leadership whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? So I'm just gonna summarize it as a data leader for a second. >>So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can leadership in the organization and also the business value. And that's important. Cause those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You, I really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like s then the in place to really start upgrading that culture inch by inch if you'll, >>Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Calibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speaks here, are very excited. You know, we have Barb from m MIT speaking about data monetization. We have Dilla at the last minute. So really exciting agen agenda. Can't wait to get back out there essentially. So over the years at, we've doing this since two and eight, so a good years and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, if you, so everybody's wearing all sorts of hat at time. But over the years I've run, you know, presales that sales partnerships, product cetera. And as our company got a little bit biggish, we're now thousand two. Something like people in the company. >>I believe systems and processes become a lot important. So we said you CBRA isn't the size our customers we're getting there in of organization structure, process systems, et cetera. So we said it's really time for us to put our money where is and to our own data office, which is what we were seeing customers', organizations worldwide. And they organizations have HR units, they have a finance unit and over time they'll all have a department if you'll, that is responsible somehow for the data. So we said, ok, let's try to set an examples that other people can take away with it, right? Can take away from it. So we set up a data strategy, we started building data products, took care of the data infrastructure. That's sort of good stuff. And in doing all of that, ISA exactly as you said, we said, okay, we need to also use our product and our own practices and from that use, learn how we can make the product better, learn how we make, can make the practice better and share that learning with all the, and on, on the Monday mornings, we sometimes refer to eating our dog foods on Friday evenings. >>We referred to that drinking our own champagne. I like it. So we, we had a, we had the driver to do this. You know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should, this is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders, if you'll or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products can run, the data can flow and you know, the quality can be checked. >>And then we have a data intelligence or data governance builders where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the CBRA approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a map and started execution use of the use case. And a important ones are very simple. We them with our, our customers as well, people talking about the cata, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and privacy. So they have their process registry and they can see how the data flows. >>So that's a starting place and that turns into a marketplace so that if new analysts and data citizens join kbra, they immediately have a place to go to, to look at, see, ok, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? So they can immediately get access data. And another one that we is around trusted business. We're seeing that since, you know, self-service BI allowed everyone to make beautiful dashboards, you know, pie, pie charts. I always, my pet pee is the pie chart because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted this reporting. So we know if a, the dashboard, a data product essentially is built, we not that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either, Right. And that silver browser, right? Absolutely >>Decay. >>Exactly. Yes, >>Absolutely. Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with to your organization, but there's a few that we use that might be of interest. Use those pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Are the, is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data sciences and products. Are people using them? Are they getting value from it? >>Can we calculate that value in ay perspective, right? Yeah. So that we can to the rest of the business continue to say we're tracking all those numbers and those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or, or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so and so forth. So these are an set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in thousand 10 there may have been like 10 achieve data officers or something. Gartner has exact numbers on them, but then they grew, you know, industries and the number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data. So you'll see over the years that's gonna evolve more digital and more data products. So for next years, my, my prediction is it's all products because it's an immediate link between data and, and the essentially, right? Right. So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. I think there's gonna be a continued challenge for the chief officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? >>So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful and the ones who get that will the ones that do it on the basis of data monetization, right? Connecting value to the data and making that value clear to all the data citizens in the organization, right? And in that sense, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an asset. >>Absolutely. Because there's so much value that can be extracted. Organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful and being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the cube at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage. >>Okay, this concludes our coverage of Data Citizens 2022, brought to you by Collibra. Remember, all these videos are available on demand@thecube.net. And don't forget to check out silicon angle.com for all the news and wiki bod.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on the Cube, your leader in enterprise and emerging tech coverage. We'll see you soon.

(upbeat music) >> Hey everyone, welcome back to theCUBE live in Miami on the floor of IFS Unleashed. I'm your host, Lisa Martin. Had some great conversations. Have more great conversations coming your way. I have two guests joining me. Please welcome Martin Schirmer, the President of Enterprise Service Management, IFS Assyst. And Parminder Khosa, the Senior IT Manager at Parexel. Guys, it's great to have you on the program. >> Lovely to be here. >> It's good to be here. >> Martin, talk to me a little bit... tell the audience a little bit about Assyst so that that get that context before we start asking questions. >> Yeah. Absolutely. So IFS Assyst is a recent acquisition. It's an acquisition we made about a year ago. And fundamentally, it's a platform that takes care of IT service management, enterprise service management and IT operations management. So think of it, of managing sort of the ERP for IT and then broadening that out into the sort of enterprise where you're driving enterprise use cases for all lines of businesses like HR, finance, facilities, so on and so forth. >> Got it. And then Parminder, give the audience just a little bit of a flavor of Parexel, who you guys are, what you do. >> Sure. >> Maybe the impact that you make. >> Yeah, so Parexel is a clinical research organization. And what that means is that we manage drug trials for big pharmaceutical companies. So we're a big company. We're 25,000 people. We have offices in 150 locations all the way from Japan and the east through to the West Coast of the USA. >> Big company. >> Yeah, we are. We are a lot of people. >> And let's start chatting now Martin with some of the questions that you have so we get the understanding of how IFS and Parexel are working together. >> Yeah. Absolutely. I suppose... I mean the first thing is and thank you for traveling here all the way from the UK. (Lisa chuckles) Appreciate it and great energy and vibe. So just what the first question I had really was, you're customer of ours for the last 15 years plus. Maybe just give the audience a bit of context into your journey and how you've evolved from the sort of early years to where you're going into the future. >> Sure. So our history, I was part of a company that Parexel acquired that was already using Assyst. And as Parexel acquired us, they were in the process of also buying Assyst. So it became a kind of natural fit where I carried on with Assyst. And we started relatively small, sort of just the service desktop. And throughout the ongoing 15 years or so, we've just grown and expanded into kind of being a critical tool for Parexel right now. >> Okay, that's fantastic. I mean part of that journey, I know you started in sort of the more they call a ticketing space or IT service management space. Expand a little bit how you've expanded out of that and really moved into the enterprise. >> Sure. So yeah. So when we first rolled Assyst out, it was as I say, purely IT. And eventually we reached out to other business units to say asking questions like, Are you managing your workload through email? Are you managing your workload through Excel spreadsheets? In which case, if you are, we've got a solution for you that will make it a much better experience for your customers. They're all internal. It'll make it much easier for you because you will have official tracking going on through our system. I'll make it better for your management because we can drive metrics from all of the data that we're getting. So if you imagine finance we're getting, kind of 200 miles a day because of the size of our company. And they were just working through them one by one responding, and they becomes just a mess. So we developed forms for them to say, "Okay, Larry raise all your requests here. We will pick it up. We will manage it. We will communicate with you. And once the piece of work that you've asked for is done, we will let you know." And as we go through that process, we'll make it better for us because as I say we're getting those metrics. And we'll make it better for you because we can spot where our gaps are. If a request is taking three days, and of that three days, two days is waiting for someone on our end to respond to you or is waiting for us waiting for a customer to respond, we can iron those out and make it a much better experience for everyone. >> That's fantastic. It's really music to my ears because we always pushing the industry to say move away from just the IT side and really get into the enterprise. And it sounds like you've really gotten a lot of sort of productivity and efficiency gains out of that. >> Definitely, definitely. And it becomes kind of a happy circle. So the finance guys will work with the procurement guys. And they also look... Well, we're doing all of our work through Assyst now. So procurement's a little turnaround. So, well we're using this big spreadsheet to manage all of ours. Can we do the same? And they'll reach out to us and we'll say, "Of course we can. What is your process?" For example, they will say, okay, if someone asks for a new laptop, we need to get the approval from their line manager, from the supplier. We need to do our own internal work and then we will send it out. So imagine if you're doing that in a an email chain. It just becomes chaos. >> Yeah. >> So we will build all of that out for them. And then procurement will talk to HR and it just becomes a snowball. And before you know it, we are doing about 4,000 tickets per day in our Assyst system. And of those, 50% perhaps maybe more than 50% now will be non IT related. >> Oh, that's fantastic. Really music to my ears. And it really breaking down the boundaries or silos within an organization. It's really good. Let the teams work together. Right? >> Definitely. And that's one of the key things that we've learned is that we have to engage completely with our business partners. And our business partners are becoming more and more IT literate as well. So for example, we had a recent big HR solution provided to us. And as part of that, we know there are going to be questions, and queries and perhaps even issues to do with our HR system. So we have to work with us guys, the Assyst front end, the IT HR guys who look after the databases, all of the technology in the background. Then there'll be IT HR who are Workday experts. And then kind of not necessarily at the bottom of the chain will be the HR people themselves who are in their own way, experts in their area, experts in IT in a certain way. So all of those people have to work together. We become the front end, but we have to work with all of those parts of the business. >> That's really great. It's basically what you just said is taking business, IT processes and underpinning solutions. Effectively digital transformation, right? >> Exactly. Yeah. So HR is a great example. They used to have paper flying around with leave request, with sickness requests, with all of those kind of issues. And you said, well if you have an issue with your HR system, you can't raise a leave request, or you can't raise a sickness request, tell us. We will take care of it. We will fix it for you. We will give you the instructions. And we will get rid of all of that paper. >> That's brilliant. Just sort of turning the attention. And all of that, how do you drive the sort of, we'll talk about the autonomous enterprise. How do you drive automation in that process? >> Yeah. Of course, we have to map all of those processes out. Because we're not the experts in HR or procurement or whatever the business area may be. We have to really dig into their work methods, their working areas. What is necessary for them? What is a must have? What is a like to have? What is we don't really need? So we really drive into that processes. Once we've got those, we will automate them. We will build them out in Assyst with the process designer. It's very intuitive now. The latest version is really good to work with. We will do some pretty clever stuff in there. We'll say, okay the manager approval. If the manager is not there, then escalate it to the next person. Then we go to HR and say, okay HR have taken two days to do this. We're not particularly okay with that. So we will escalate it to the next person. And all of that process is completely automated, completely in Assyst. >> Brilliant. I mean obviously, we have a codeless workflow engine with a designer. And if you look at one of the trends from post covid is a war in talent in particular developers. The IDC says there's going to be around 4 million shortage of developers. What is your view on, how easy... Do I need developers? Is it easy, is it difficult to do these workflow extensions and automations? >> Definitely not, no. So the two key areas that you mentioned that with the customizer to develop the forms to make them available to our end users, drag and drop. Really easy to do. You can put some nice filters in there. You can put some nice variables in there. You can drive intelligent drive the forms from there as well. So if option A is correct, then don't show me option B, show me option C. And all of that is codeless, entirely codeless. I don't need to type any code. And when we move on to a process designer that hooks in nicely with the form customizer because we can say, "Okay, if option B on that form is selected, then runs this process." And all of that process is entirely codeless as well. Drag and drop. Creates some tasks. Create some decisions. >> Fantastic. >> Brilliant. >> Sounds really good. Switching gears a little bit. You spoke about experience, and that's also obviously very topical post, well, Covid becoming a remote workforce. Clearly, we need to be digitally connected to our business and organization because the hybrid workforce, as we all know, is here to stay. And that employee experience is fundamental because it is their sort of channel to the engagement of the organization. Of course, that has retention impacts and productivity impact. So just from your perspective, how was Covid, from your perspective, and how easy or difficult was it to get your employees engaged and productive and working? >> Yeah. And for us, it's a double edged sword Covid was. Because of the nature of our business. We do covid stuff. We do drug stuff. So we may have issues with some trials that are related to that. So we need to escalate those. We need to be aware of them and move them to the top of the chain as soon as possible. And then Assyst becomes a source of truth. Everybody knows that if I've got an issue with the current environment that we're living in, I can raise it in Assyst. And everybody knows that's where that information is. There's no need to have huge conference calls or huge email chains to try and follow those around. So with our Assyst platform, with our employees as well, everybody knew that this is where the source of truth was. We didn't have any dropouts. We didn't have any concerns with our system or performance. We knew it was there. We had to do some work like, as I say, around covid issues just to make sure they get pushed up to the top of the chain. But otherwise, we were fine. And great credit to our IT operations team as well who managed that pretty much seamlessly. >> That's brilliant. That's good news. >> Yeah. >> It really is. Just taking a little bit further and talking a little bit about what next. My team has been, I know, talking to your team about the whole area of asset management. Maybe talk to us a little bit about that journey. >> Sure, sure. So we're an ITOM customer as well. So all of our hardware data is stored within the ITOM platform. So we've pushed out the agents to all of our end user machines, so 25,000 agents. And we're in the process of integrating that into our Assyst platform to make that the single source of truth. And that part of that we're working on the software asset management side as well. So we've got a really good idea of where our software assets are. It comes to all license auditing, we know exactly how much we've got there. And the more complex side of it is of course server. So software management management as well. So we're in the process of getting all of that data as well. So once we've done all that, there is other all as the next step. The next step will be to perhaps do monitoring or pushing out software using the ITOM platform and getting rid of some of the disparate systems that we have right now. >> Well that's good news. And I think I saw a study. I think, every single person as an employee carries around 15 or 20 assets with him at any one time. Be it from a PC, phone, physical software licenses, so on and so forth. In that context, I can imagine the business case around it. >> Definitely. Yeah. And every, again, we map every user to their assets and (indistinct) their assets. And again Assyst as a source of truth for that. So if you want to look at my record, so, all right. Pam's got a laptop. He's got a mobile phone. We're thinking about giving him a tablet, but we'll find out. That he's in the process of getting a tablet as well. So I can have a look at my user record and know exactly what I've got with all of the asset tags and the various links that it has to the software pieces so it becomes a big tree of my assets. >> That's wonderful. Just the question I had was, we spoke about breaking down silos and the enterprise use cases and the effect that has. Do you envisage that Assyst can really get to being enterprisewide as, when I say enterprisewide, everybody in the organization effectively using this tool as their sort of source of experience, and level of automation of process? >> Definitely, definitely. As I say, we're getting... We're really pushing to get to that. As I say, 4,000 tickets a day with a user base of 25,000 kind of means that everybody will interact with the system perhaps every two weeks or so. So we're getting to that point and with the new functionality that's coming out with the Assyst product, with the team's integration, and the bot and everything that will bring to us because we are a big. We use teams. We use bots. We use that kind of technology. It will just fit in seamlessly. And trying to break down the silos, as I say finance, procurement, all of the big beasts within our company already are using the Assyst tool. And we want to bring in more and more of those processes as we mature. >> Brilliant. I think Omnichannel's critical. We want to connect from any device from anywhere. It's just the way we work. So I think that's critical. Teams is of course a a tool that most of us have become too familiar with. >> Yup. (chuckles) >> To be fair. (chuckles) It's better to be here in person finally, right? >> Yeah. >> So I think, that's all exciting news. And it's really fantastic. >> Great. >> So I suppose maybe in the time that we have left, what's next? >> What's next for us is that we're in the process of migrating our solution to the cloud, to the IFS cloud. That will open up a huge new user base for us. If we think all of our customers, all of our people who work on studies will have the ability to connect to Assyst and ask questions. That's a lot of it is just ask a question, or raise an issue or ask for something. So we're talking, it could be expanded by hundreds of thousands of new users that will meet more people on the backend to manage those requests as well. So yeah. It's just going to get bigger and bigger. And as you say, with the CMDB work that we're doing as well, that's another big ongoing stream for us. >> It's great because as you know, with Assyst we have a disruptive licensing model. >> Yeah. >> We have a t-shirt size pricing. All you can need based a number of employees. So there's no barriers to entry for you. >> There really is. And that really helps us because as I said initially, particularly when finance came on board and now they're expanding, there is no cost implication for it. The more that we use it, the better it is for. The more bang for buck that we get. >> Yep. That's our mantra. Enterprise users, right? For the price of a cup of coffee, for the price of a user. That's our mantra. >> I love it. You guys have done such a great job of articulating the synergies in the relationship that IFS Assyst has with Paraxel. You talked about the great outcomes that you're achieving. And it's all about Martin, I know, from IFS Assyst perspective, it's all about helping customers achieve those outcomes and those moments of service that are so critical to your customers on the other end staying with you, doing more business. Whether it's the end user customer, whether it's the actual employee. You talked a lot about the customer experience, the employee experience, and what you guys are doing together to enable that. And I always think that the employee experience and the customer experience are like this. They're inextricably linked. You can't, you shouldn't. Otherwise you're going to have problems. >> Yeah, no, absolutely. And there's actually a study on that saying that, 70% of customers generally don't feel they get what they want from organizations. >> 70. Wow! >> And if you take that one step further to what you said, the interconnectivity between customer employee, employee shops on Amazon, right? It's on those websites. So you can't be rolling out and digitally connect to the employee with something that is clunky and has the wrong experience. Like I said, it really affects that level of engagement the employee has with the company which happens to be largely these days remote. >> It does. Last question Martin, is for you. Talk to us about what's next for IFS Assyst. Obviously, we're back in person. There's a lot of momentum about the company. I was talking with Darren, the growth and first half was great. He kind of gave us some teaser about second half, but what's next from your perspective? >> Yeah. So what's next for us is achieving our goal. We are here to disrupt the industry. It's an industry that's dominated by one player and a fair amount of legacy players. We've disrupted the business model as I've told you. We here to do more because it's a simple thing. And that's the word simple. We want to keep things simple. We're going to keep engineering and driving our product forward, right? We've made sure that our platform is up there with the best. Yeah. We've just been certified by pink. Pink is a verification of ITIL four they call it. So it's a body. And the top level is you can get 20 out of 20. We got 17 out of 20. There's only one other vendor that has more than us and it's only by little. And after it's a big white space, the next one is 14. So we on the right track. We are going to of course drive and capture the market. So watch this space. We here to grow. >> We will watch this space. Congratulations on being that disrupter. >> Thank you. >> Parminder great work with what you guys are doing. You did a great job of articulating, as I said, the customers tour here. We appreciate your insights, your time. >> Thank you very much. >> Pleasure. >> All right, my pleasure. >> Thank you. For my guests, I'm Lisa Martin. You're watching The Cube live from Miami on the show floor of IFS Unleashed. We'll be back after a short break.

(bright music) >> Welcome back everyone. theCube's live coverage here. Day two, of two sets, three days of theCube coverage here at VMware Explore. This is our 12th year covering VMware's annual conference, formerly called VM World. I'm John Furrier, with Dave Vellante. We'd love seeing the progress and we've got great security comes Tom Gill, senior vices, president general manager, networking and advanced security business group at VMware. Great to see you. Thanks for coming on. >> Thanks. for having me. >> Yeah, really happy we could have you on. >> I think this is my sixth edition on the theCube. Do I get frequent flyer points or anything? >> Yeah. >> You first get the VIP badge. We'll make that happen. You can start getting credits. >> Okay, there we go. >> We won't interrupt you. Seriously, you got a great story in security here. The security story is kind of embedded everywhere, so it's not called out and blown up and talked specifically about on stage. It's kind of in all the narratives in the VM World for this year. But you guys have an amazing security story. So let's just step back and to set context. Tell us the security story for what's going on here at VMware and what that means to this supercloud, multi-cloud and ongoing innovation with VMware. >> Yeah, sure thing. So probably the first thing I'll point out is that security's not just built in at VMware. It's built differently. So, we're not just taking existing security controls and cut and pasting them into our software. But we can do things because of our platform, because of the virtualization layer that you really can't do with other security tools. And where we're very, very focused is what we call lateral security or East-West movement of an attacker. 'Cause frankly, that's the name of the game these days. Attackers, you've got to assume that they're already in your network. Already assume that they're there. Then how do we make it hard for them to get to the stuff that you really want? Which is the data that they're going after. And that's where we really should. >> All right. So we've been talking a lot, coming into VMware Explore, and here, the event. About two things. Security, as a state. >> Yeah. >> I'm secure right now. >> Yeah. >> Or I think I'm secure right now, even though someone might be in my network or in my environment. To the notion of being defensible. >> Yeah. >> Meaning I have to defend and be ready at a moment's notice to attack, fight, push back, red team, blue team. Whatever you're going to call it. But something's happening. I got to be able to defend. >> Yeah. So what you're talking about is the principle of Zero Trust. When I first started doing security, the model was we have a perimeter. And everything on one side of the perimeter is dirty, ugly, old internet. And everything on this side, known good, trusted. What could possibly go wrong. And I think we've seen that no matter how good you make that perimeter, bad guys find a way in. So Zero Trust says, you know what? Let's just assume they're already in. Let's assume they're there. How do we make it hard for them to move around within the infrastructure and get to the really valuable assets? 'Cause for example, if they bust into your laptop, you click on a link and they get code running on your machine. They might find some interesting things on your machine. But they're not going to find 250 million credit cards. >> Right. >> Or the script of a new movie or the super secret aircraft plans. That lives in a database somewhere. And so it's that movement from your laptop to that database. That's where the damage is done and that's where VMware shines. >> So if they don't have the right to get to that database, they're not in. >> And it's not even just the right. So they're so clever and so sneaky that they'll steal a credential off your machine, go to another machine, steal a credential off of that. So, it's like they have the key to unlock each one of these doors. And we've gotten good enough where we can look at that lateral movement, even though it has a credential and a key, we're like wait a minute. That's not a real CIS Admin making a change. That's ransomware. And that's where you. >> You have to earn your way in. >> That's right. That's right. Yeah. >> And we're all kinds of configuration errors. But also some user problems. I've heard one story where there's so many passwords and username and passwords and systems that the bad guys scour, the dark web for passwords that have been exposed. >> Correct. >> And go test them against different accounts. Oh one hit over here. >> Correct. >> And people don't change their passwords all the time. >> Correct. >> That's a known vector. >> Just the idea that users are going to be perfect and never make a mistake. How long have we been doing this? Humans are the weakest link. So people are going to make mistakes. Attackers are going to be in. Here's another way of thinking about it. Remember log4j? Remember that whole fiasco? Remember that was at Christmas time. That was nine months ago. And whoever came up with that vulnerability, they basically had a skeleton key that could access every network on the planet. I don't know if a single customer that said, "Oh yeah, I wasn't impacted by log4j." So here's some organized entity had access to every network on the planet. What was the big breach? What was that movie script that got stolen? So there wasn't one, right? We haven't heard anything. So the point is, the goal of attackers is to get in and stay in. Imagine someone breaks into your house, steals your laptop and runs. That's a breach. Imagine someone breaks into your house and stays for nine months. It's untenable, in the real world, right? >> Right. >> We don't know in there, hiding in the closet. >> They're still in. >> They're watching everything. >> Hiding in your closet, exactly. >> Moving around, nibbling on your cookies. >> Drinking your beer. >> Yeah. >> So let's talk about how this translates into the new reality of cloud-native. Because now you hear about automated pentesting is a new hot thing right now. You got antivirus on data is hot within APIs, for instance. >> Yeah. >> API security. So all kinds of new hot areas. Cloud-native is very iterative. You know, you can't do a pentest every week. >> Right. >> You got to do it every second. >> So this is where it's going. It's not so much simulation. It's actually real testing. >> Right. Right. >> How do you view that? How does that fit into this? 'cause that seems like a good direction to me. >> Yeah. If it's right in, and you were talking to my buddy, Ahjay, earlier about what VMware can do to help our customers build cloud native applications with Tanzu. My team is focused on how do we secure those applications? So where VMware wants to be the best in the world is securing these applications from within. Looking at the individual piece parts and how they talk to each other and figuring out, wait a minute, that should never happen. By almost having an x-ray machine on the innards of the application. So we do it for both for VMs and for container based applications. So traditional apps are VM based. Modern apps are container based. And we have a slightly different insertion mechanism. It's the same idea. So for VMs, we do it with a hypervisor with NSX. We see all the inner workings. In a container world we have this thing called a service mesh that lets us look at each little snippet of code and how they talk to each other. And once you can see that stuff, then you can actually apply. It's almost like common sense logic of like, wait a minute. This API is giving back credit card numbers and it gives five an hour. All of a sudden, it's now asking for 20,000 or a million credit cards. That doesn't make any sense. The anomalies stick out like a sore thumb. If you can see them. At VMware, our unique focus in the infrastructure is that we can see each one of these little transactions and understand the conversation. That's what makes us so good at that East-West or lateral security. >> You don't belong in this room, get out or that that's some weird call from an in memory database, something over here. >> Exactly. Where other security solutions won't even see that. It's not like there algorithms aren't as good as ours or better or worse. It's the access to the data. We see the inner plumbing of the app and therefore we can protect the app from. >> And there's another dimension that I want to get in the table here. 'Cause to my knowledge only AWS, Google, I believe Microsoft and Alibaba and VMware have this. >> Correct >> It's Nitro. The equivalent of a Nitro. >> Yes. >> Project Monterey. >> Yeah. >> That's unique. It's the future of computing architectures. Everybody needs a Nitro. I've written about this. >> Yeah. >> Right. So explain your version. >> Yeah. >> It's now real. >> Yeah. >> It's now in the market, right? >> Yeah. >> Or soon will be. >> Here's our mission. >> Salient aspects. >> Yeah. Here's our mission of VMware. Is that we want to make every one of our enterprise customers. We want their private cloud to be as nimble, as agile, as efficient as the public cloud. >> And secure. >> And secure. In fact, I'll argue, we can make it actually more secure because we're thinking about putting security everywhere in this infrastructure. Not just on the edges of it. Okay. How do we go on that journey? As you pointed out, the public cloud providers realized five years ago that the right way to build computers was not just a CPU and a graphics process unit, GPU. But there's this third thing that the industry's calling a DPU, data processing unit. And so there's kind of three pieces of a computer. And the DPU is sometimes called a Smartnic. It's the network interface card. It does all that network handling and analytics and it takes it off the CPU. So they've been building and deploying those systems themselves. That's what Nitro is. And so we have been working with the major Silicon vendors to bring that architecture to everybody. So with vSphere 8, we have the ability to take the network processing, that East-West inspection I talked about, take it off of the CPU and put it into this dedicated processing element called the DPU and free up the CPU to run the applications that Ahjay and team are building. >> So no performance degradation at all? >> Correct. To CPU offload. >> So even the opposite, right? I mean you're running it basically Bare Metal speeds. >> Yes, yes and yes. >> And you're also isolating the storage from the security, the management, and. >> There's an isolation angle to this, which is that firewall, that we're putting everywhere. Not just that the perimeter, but we put it in each little piece of the server is running when it runs on one of these DPUs it's a different memory space. So even if an attacker gets to root in the OS, they it's very, very, never say never, but it's very difficult. >> So who has access to that resource? >> Pretty much just the infrastructure layer, the cloud provider. So it's Amazon, Google, Microsoft, and the enterprise. >> Application can't get in. >> Can't get in there. Cause you would've to literally bridge from one memory space to another. Never say never, but it would be very. >> But it hasn't earned the trust to get. >> It's more than barbwire. It's multiple walls. >> Yes. And it's like an air gap. It puts an air gap in the server itself so that if the server is compromised, it's not going to get into the network. Really powerful. >> What's the big thing that you're seeing with this supercloud transition. We're seeing multi-cloud and this new, not just SaaS hosted on the cloud. >> Yeah. >> You're seeing a much different dynamic of, combination of large scale CapEx, cloud-native, and then now cloud-native drills on premises and edge. Kind of changing what a cloud looks like if the cloud's on a cloud. >> Yeah. >> So we're the customer, I'm building on a cloud and I have on premise stuff. So, I'm getting scale CapEx relief from the hyperscalers. >> I think there's an important nuance on what you're talking about. Which is in the early days of the cloud customers. Remember those first skepticism? Oh, it'll never work. Oh, that's consumer grade. Oh, that's not really going to work. Oh some people realize. >> It's not secure. >> Yeah. It's not secure. >> That one's like, no, no, no it's secure. It works. And it's good. So then there was this sort of over rush. Let's put everything on the cloud. And I had a lot of customers that took VM based applications said, I'm going to move those onto the cloud. You got to take them all apart, put them on the cloud and put them all back together again. And little tiny details like changing an IP address. It's actually much harder than it looks. So my argument is, for existing workloads for VM based workloads, we are VMware. We're so good at running VM based workloads. And now we run them on anybody's cloud. So whether it's your east coast data center, your west coast data center, Amazon, Google, Microsoft, Alibaba, IBM keep going. We pretty much every. >> And the benefit of the customer is what. >> You can literally VMotion and just pick it up and move it from private to public, public to private, private to public, Back and forth. >> Remember when we called Vmotion BS, years ago? >> Yeah. Yeah. >> VMotion is powerful. >> We were very skeptical. We're like, that'll never happen. I mean we were. This supposed to be pat ourselves on the back. >> Well because alchemy. It seems like what you can't possibly do that. And now we do it across clouds. So it's not quite VMotion, but it's the same idea. You can just move these things over. I have one customer that had a production data center in the Ukraine. Things got super tense, super fast and they had to go from their private cloud data center in the Ukraine, to a public cloud data center out of harm's way. They did it over a weekend. 48 hours. If you've ever migrated a data center, that's usually six months. Right. And a lot of heartburn and a lot of angst. Boop. They just drag and dropped and moved it on over. That's the power of what we call the cloud operating model. And you can only do this when all your infrastructures defined in software. If you're relying on hardware, load balancers, hardware, firewalls, you can't move those. They're like a boat anchor. You're stuck with them. And by the way, they're really, really expensive. And by the way, they eat a lot of power. So that was an architecture from the 90's. In the cloud operating model your data center. And this comes back to what you were talking about is just racks and racks of X86 with these magic DPUs, or smart nics, to make any individual node go blisteringly fast and do all the functions that you used to do in network appliances. >> We just had Ahjay taking us to school, and everyone else to school on applications, middleware, abstraction layer. And Kit Culbert was also talking about this across cloud. We're talking supercloud, super pass. If this continues to happen, which we would think it will happen. What does the security posture look like? It feels to me, and again, this is your wheelhouse. If supercloud happens with this kind of past layer where there's vMotioning going on. All kinds of spanning applications and data across environments. >> Yeah. Assume there's an operating system working on behind the scenes. >> Right. >> What's the security posture in all this? >> Yeah. So remember my narrative about the bad guys are getting in and they're moving around and they're so sneaky that they're using legitimate pathways. The only way to stop that stuff, is you've got to understand it at what we call Layer 7. At the application layer. Trying to do security to the infrastructure layer. It was interesting 20 years ago, kind of less interesting 10 years ago. And now it's becoming irrelevant because the infrastructure is oftentimes not even visible. It's buried in some cloud provider. So Layer 7 understanding, application awareness, understanding the APIs and reading the content. That's the name of the game in security. That's what we've been focused on. Nothing to do with the infrastructure. >> And where's the progress bar on that paradigm. One to ten. Ten being everyone's doing it. >> Right now. Well, okay. So we as a vendor can do this today. All the stuff I talked about, reading APIs, understanding the individual services looking at, Hey, wait a minute this credit card anomalies, that's all shipping production code. Where is it in customer adoption life cycle? Early days 10%. So there's a whole lot of headroom for people to understand, Hey, I can put these controls in place. They're software based. They don't require appliances. It's Layer 7, so it has contextual awareness and it's works on every single cloud. >> We talked about the pandemic being an accelerator. It really was a catalyst to really rethink. Remember we used to talk about Pat as a security do over. He's like, yes, if it's the last thing I do, I'm going to fix security. Well, he decided to go try to fix Intel instead. >> He's getting some help from the government. >> But it seems like CISOs have totally rethought their security strategy. And at least in part, as a function of the pandemic. >> When I started at VMware four years ago, Pat sat me down in his office and he said to me what he said to you, which is like, "Tom," he said, "I feel like we have fundamentally changed servers. We fundamentally change storage. We fundamentally change networking. The last piece of the puzzle of security. I want you to go fundamentally change it." And I'll argue that the work that we're doing with this horizontal security, understanding the lateral movement. East- West inspection. It fundamentally changes how security works. It's got nothing to do with firewalls. It's got nothing to do with Endpoint. It's a unique capability that VMware is uniquely suited to deliver on. And so Pat, thanks for the mission. We delivered it and it's available now. >> Those WET web applications firewall for instance are around, I mean. But to your point, the perimeter's gone. >> Exactly. >> And so you got to get, there's no perimeter. so it's a surface area problem. >> Correct. And access. And entry. >> Correct. >> They're entering here easy from some manual error, or misconfiguration or bad password that shouldn't be there. They're in. >> Think about it this way. You put the front door of your house, you put a big strong door and a big lock. That's a firewall. Bad guys come in the window. >> And then the windows open. With a ladder. >> Oh my God. Cause it's hot, bad user behavior trumps good security every time. >> And then they move around room to room. We're the room to room people. We see each little piece of the thing. Wait, that shouldn't happen. Right. >> I want to get you a question that we've been seeing and maybe we're early on this or it might be just a false data point. A lot of CSOs and we're talking to are, and people in industry in the customer environment are looking at CISOs and CSOs, two roles. Chief information security officer, and then chief security officer. Amazon, actually Steven Schmidt is now CSO at Reinforce. They actually called that out. And the interesting point that he made, we had some other situations that verified this, is that physical security is now tied to online, to your point about the service area. If I get a password, I still got the keys to the physical goods too. >> Right. So physical security, whether it's warehouse for them or store or retail. Digital is coming in there. >> Yeah. So is there a CISO anymore? Is it just CSO? What's the role? Or are there two roles you see that evolving? Or is that just circumstance. >> I think it's just one. And I think that the stakes are incredibly high in security. Just look at the impact that these security attacks are having on. Companies get taken down. Equifax market cap was cut 80% with a security breach. So security's gone from being sort of a nuisance to being something that can impact your whole kind of business operation. And then there's a whole nother domain where politics get involved. It determines the fate of nations. I know that sounds grand, but it's true. And so companies care so much about it they're looking for one leader, one throat to choke. One person that's going to lead security in the virtual domain, in the physical domain, in the cyber domain, in the actual. >> I mean, you mention that, but I mean, you look at Ukraine. I mean that cyber is a component of that war. I mean, it's very clear. I mean, that's new. We've never seen. this. >> And in my opinion, the stuff that we see happening in the Ukraine is small potatoes compared to what could happen. >> Yeah. >> So the US, we have a policy of strategic deterrence. Where we develop some of the most sophisticated cyber weapons in the world. We don't use them. And we hope never to use them. Because our adversaries, who could do stuff like, I don't know, wipe out every bank account in North America. Or turn off the lights in New York City. They know that if they were to do something like that, we could do something back. >> This is the red line conversation I want to go there. So, I had this discussion with Robert Gates in 2016 and he said, "We have a lot more to lose." Which is really your point. >> So this brand. >> I agree that there's to have freedom and liberty, you got to strike back with divorce. And that's been our way to balance things out. But with cyber, the red line, people are already in banks. So they're are operating below the red line line. Red line meaning before we know you're in there. So do we move the red line down because, hey, Sony got hacked. The movie. Because they don't have their own militia. >> Yeah. >> If their were physical troops on the shores of LA breaking into the file cabinets. The government would've intervened. >> I agree with you that it creates tension for us in the US because our adversaries don't have the clear delineation between public and private sector. Here you're very, very clear if you're working for the government. Or you work for an private entity. There's no ambiguity on that. >> Collaboration, Tom, and the vendor community. I mean, we've seen efforts to try to. >> That's a good question. >> Monetize private data and private reports. >> So at VMware, I'm very proud of the security capabilities we've built. But we also partner with people that I think of as direct competitors. We've got firewall vendors and Endpoint vendors that we work with and integrate. And so coopetition is something that exists. It's hard. Because when you have these kind of competing. So, could we do more? Of course we probably could. But I do think we've done a fair amount of cooperation, data sharing, product integration, et cetera. And as the threats get worse, you'll probably see us continue to do more. >> And the government is going to trying to force that too. >> And the government also drives standards. So let's talk about crypto. Okay. So there's a new form of encryption coming out called processing quantum. >> Quantum. Quantum computers have the potential to crack any crypto cipher we have today. That's bad. Okay. That's not good at all because our whole system is built around these private communications. So the industry is having conversations about crypto agility. How can we put in place the ability to rapidly iterate the ciphers in encryption. So, when the day quantum becomes available, we can change them and stay ahead of these quantum people. >> Well, didn't NIST just put out a quantum proof algo that's being tested right now by the community? >> There's a lot of work around that. Correct. And NIST is taking the lead on this, but Google's working on it. VMware's working on it. We're very, very active in how do we keep ahead of the attackers and the bad guys? Because this quantum thing is a, it's an x-ray machine. It's like a dilithium crystal that can power a whole ship. It's a really, really, really powerful tool. >> Bad things will happen. >> Bad things could happen. >> Well, Tom, great to have you on the theCube. Thanks for coming on. Take the last minute to just give a plug for what's going on for you here at VMWorld this year, just VMware Explore this year. >> Yeah. We announced a bunch of exciting things. We announced enhancements to our NSX family, with our advanced load balancer. With our edge firewall. And they're all in service of one thing, which is helping our customers make their private cloud like the public cloud. So I like to say 0, 0, 0. If you are in the cloud operating model, you have zero proprietary appliances. You have zero tickets to launch a workload. You have zero network taps and Zero Trust built into everything you do. And that's what we're working on. Pushing that further and further. >> Tom Gill, senior vices president, head of the networking at VMware. Thanks for coming on. We do appreciate it. >> Thanks for having us. >> Always getting the security data. That's killer data and security of the two ops that get the most conversations around DevOps and Cloud Native. This is The theCube bringing you all the action here in San Francisco for VMware Explore 2022. I'm John Furrier with Dave Vellante. Thanks for watching. (bright music)

>>Welcome back everyone Cube's live coverage here. Day two, two sets, three days of cube coverage here at VMware Explorer. This is our 12th year covering VMware's annual conference, formally called world I'm Jean Dave ante. We'd love seeing the progress and we've got great security comes Tom Gill, senior rights, president general manager, networking and advanced security business group at VMware. Great to see you. Thanks for coming on. Thanks >>For having me. Yeah, really happy we could have you on, you know, I think, I think this is my sixth edition on the cube. Like, do I get freaking flyer points or anything? >>Yeah, you get first get the VIP badge. We'll make that happen. You can start getting credits. >>Okay. There we go. >>We won't interrupt you. No, seriously, you got a great story in security here. The security story is kind of embedded everywhere, so it's not like called out and, and blown up and talked specifically about on stage. It's kind of in all the narratives in, in the VM world for this year. Yeah. But you guys have an amazing security story. So let's just step back into set context. Tell us the security story for what's going on here at VMware and what that means to this super cloud multi-cloud and ongoing innovation with VMware. Yeah, >>Sure thing. So, so probably the first thing I'll point out is that, that security's not just built in at VMware it's built differently, right? So we're not just taking existing security controls and cut and pasting them into, into our software. But we can do things because of our platform because of the virtualization layer that you really can't do with other security tools and where we're very, very focused is what we call lateral security or east west movement of an attacker. Cuz frankly, that's the name of the game these days. Right? Attackers, you gotta assume that they're already in your network. Okay. Already assume that they're there, then how do we make it hard for them to get to what the, the stuff that you really want, which is the data that they're, they're going after. Right. And that's where we, >>We really should. All right. So we've been talking a lot coming into world VMware Explorer and here the event about two things security as a state. Yeah. I'm secure right now. Yeah. Or I, I think I'm secure right now, even though someone might be in my network or in my environment to the notion of being defensible. Yeah. Meaning I have to defend and be ready at a moment's notice to attack, fight, push back red team, blue team, whatever you're gonna call it, but something's happening. I gotta be a to defend. Yeah. >>So you, what you're talking about is the principle of zero trust. So the, the, when we, when I first started doing security, the model was we have a perimeter and everything on one side of the perimeter is dirty, ugly, old internet and everything on this side known good, trusted what could possibly go wrong. And I think we've seen that no matter how good you make that perimeter, bad guys find a way in. So zero trust says, you know what? Let's just assume they're already in. Let's assume they're there. How do we make it hard for them to move around within the infrastructure and get to the really valuable assets? Cuz for example, if they bust into your laptop, you click on a link and they get code running on your machine. They might find some interesting things on your machine, but they're not gonna find 250 million credit cards. Right. Or the, the script of a new movie or the super secret aircraft plans, right. That lives in a database somewhere. And so it's that movement from your laptop to that database. That's where the damage is done. Yeah. And that's where VMware shines. If they don't >>Have the right to get to that database, they're >>Not >>In and it's not even just the right, like, so they're so clever. And so sneaky that they'll steal a credential off your machine, go to another machine, steal a credential off of that. So it's like they have the key to unlock each one of these doors and we've gotten good enough where we can look at that lateral movement, even though it has a credential and a key where like, wait a minute, that's not a real CIS admin making a change. That's ransomware. Yeah. Right. And that's, that's where we, you have to earn your way in. That's right. That's >>Right. Yeah. And we're all, there's all kinds of configuration errors. But also some, some I'll just user problems. I've heard one story where there's so many passwords and username and passwords and systems that the bad guy's scour, the dark web for passwords that have been exposed. Correct. And go test them against different accounts. Oh one hit over here. Correct. And people don't change their passwords all the time. Correct? Correct. That's a known, known vector. We, >>We just, the idea that users are gonna be perfect and never make mistake. Like how long have we been doing this? Like humans with the weakest link. Right. So, so, so people are gonna make mistakes. Attackers are gonna be in here's another way of thinking about it. Remember log for J. Remember that whole ago, remember that was a Christmas time. That was nine months ago. And whoever came up with that, that vulnerability, they basically had a skeleton key that could access every network on the planet. I don't know if a single customer that was said, oh yeah, I wasn't impacted by log for J. So seers, some organized entity had access to every network on the planet. What was the big breach? What was that movie script that got stolen? So there wasn't one. Right? We haven't heard anything. So the point is the goal of attackers is to get in and stay in. Imagine someone breaks into your house, steals your laptop and runs. That's a breach. Imagine someone breaks into your house and stays for nine months. Like it's untenable, the real world. Right, right. >>We don't even go in there. They're still in there >>Watching your closet. Exactly. Moving around, nibbling on your ni line, your cookies. You know what I mean? Drinking your beer. >>Yeah. So, so let's talk about how this translates into the new reality of cloud native, because now know you hear about, you know, automated pen testing is a, a new hot thing right now you got antivirus on data. Yeah. Is hot is hot within APIs, for instance. Yeah. API security. So all kinds of new hot areas, cloud native is very iterative. You know, you, you can't do a pen test every week. Right. You gotta do it every second. Right. So this is where it's going. It's not so much simulation. It's actually real testing. Right. Right. How do you view that? How does that fit into this? Cuz that seems like a good direction to me. >>Yeah. It, it, it fits right in. And you were talking to my buddy AJ earlier about what VMware can do to help our customers build cloud native applications with, with Zu, my team is focused on how do we secure those applications? So where VMware wants to be the best in the world is securing these applications from within looking at the individual piece parts and how they talk to each other and figuring out, wait a minute. That, that, that, that, that should never happen by like almost having an x-ray machine on the ins of the application. So we do it for both for VMs and for container based applications. So traditional apps are VM based. Modern apps are container based and we, and we have a slightly different insertion mechanism. It's the same idea. So for VMs, we do it with the hypervisor, with NSX, we see all the inner workings in a container world. >>We have this thing called a service me that lets us look at each little snippet of code and how they talk to each other. And once you can see that stuff, then you can actually apply. It's almost like common sense logic of like, wait a minute. You know, this API is giving back credit card numbers and it gives five an hour. All of a sudden, it's now asking for 20,000 or a million credit card that doesn't make any sense. Right? The anomalies stick out like a sore thumb. If you can see them. And VMware, our unique focus in the infrastructure is that we can see each one of these little transactions and understand the conversation. That's what makes us so good at that east west or lateral >>Security. Yeah. You don't belong in this room, get out or that that's right. Some weird call from an in-memory database, something over >>Here. Exactly. Where other, other security solutions won't even see that. Right. It's not like there algorithms aren't as good as ours or, or better or worse. It's that, it's the access to the data. We see the, the, the, the inner plumbing of the app. And therefore we can protect >>The app from, and there's another dimension that I wanna get in the table here, cuz to my knowledge only AWS, Google, I, I believe Microsoft and Alibaba and VMware have this, it nitro the equivalent of a nitro. Yes. Project Monterey. Yeah. That's unique. It's the future of computing architectures. Everybody needs a nitro. I've I've written about this. Yeah. Right. So explain your version. Yeah. Project. It's now real. It's now in the market right. Or soon will be. Yeah. Here. Here's our mission salient aspects. Yeah. >>Here's our mission of VMware is that we wanna make every one of our enterprise customers. We want their private cloud to be as nimble, as agile, as efficient as the public cloud >>And secure >>And secure. In fact, I'll argue, we can make it actually more secure because we're thinking about putting security everywhere in this infrastructure. Right. Not just on the edges of it. So, so, so, okay. How do we go on that journey? As you pointed out, the public cloud providers realized, you know, five years ago that the right way to build computers was not just a CPU and a GPU graphics process, unit GPU, but there's this third thing that the industry's calling a DPU data processing unit. So there's kind of three pieces of a computer. And the DPU is sometimes called a smart Nick it's the network interface card. It does all that network handling and analytics and it takes it off the CPU. So they've been building and deploying those systems themselves. That's what nitro is. And so we have been working with the major Silicon vendors to bring that architecture to everybody. So, so with vSphere eight, we have the ability to take the network processing that east west inspection. I talked about, take it off of the CPU and put it into this dedicated processing element called the DPU and free up the CPU to run the applications that AJ and team are building. >>So no performance degradation at all, correct. >>To CPU >>Offload. So even the opposite, right? I mean you're running it basically bare metal speeds. >>Yes, yes. And yes. >>And, and, and you're also isolating the, the storage right from the, from the, the, the security, the management. And >>There's an isolation angle to this, which is that firewall that we're putting everywhere. Not just that the perimeter, we put it in each little piece of the server is running when it runs on one of these DPU, it's a different memory space. So even if, if an attacker gets to root in the OS, they it's very, very, never say never, but it's very difficult. >>So who has access to that? That, that resource >>Pretty much just the infrastructure layer, the cloud provider. So it's Google Microsoft, you know, and the enterprise, the >>Application can't get in, >>Can't get in there. Cause it, you would've to literally bridge from one memory space to another, never say never, but it would be very, very, >>It hasn't earned the trust >>To get it's more than Bob wire. It's, it's, it's multiple walls and, and >>It's like an air gap. It puts an air gap in the server itself so that if the server's compromised, it's not gonna get into the network really powerful. >>What's the big thing that you're seeing with this super cloud transition we're seeing, we're seeing, you know, multicloud and this new, not just SAS hosted on the cloud. Yeah. You're seeing a much different dynamic of combination of large scale CapEx, cloud native. And then now cloud native develops on premises and edge kind of changing what a cloud looks like if the cloud's on a cloud. So rubber customer, I'm building on a cloud and I have on-prem stuff. So I'm getting scale CapEx relief from the, from the cap, from the hyperscalers. >>I, I think there's an important nuance on what you're talking about, which is, is in the early days of the cloud customers. Remember those first skepticism? Oh, it'll never work. Oh, that's consumer grade. Oh, that's not really gonna work. And some people realize >>It's not secure. Yeah. >>It, it's not secure that one's like, no, no, no, it's secure. It works. And it, and it's good. So then there was this sort of over rush. Like let's put everything on the cloud. And I had a lot of customers that took VM based applications said, I'm gonna move those onto the cloud. You gotta take 'em all apart, put 'em on the cloud and put 'em all back together again. And little tiny details, like changing an IP address. It's actually much harder than it looks. So my argument is for existing workloads for VM based workloads, we are VMware. We're so good at running VM based workloads. And now we run them on anybody's cloud. So whether it's your east coast data center, your west coast data center, Amazon, Google, Microsoft, Alibaba, IBM keep going. Right. We pretty much every, and >>The benefit of the customer is what you >>Can literally vMotion and just pick it up and move it from private to public public, to private, private, to public, public, back and forth. >>Remember when we called VMO BS years ago. Yeah, yeah, yeah. >>We were really, skeptic is >>Powerful. We were very skeptical. We're like, that'll never happen. I mean, we were, I mean, it's supposed to be pat ourselves on the back. We, well, >>Because it's alchemy, it seems like what you can't possibly do that. Right. And so, so, so, and now we do it across clouds, right? So we can, you know, it's not quite VMO, but it's the same idea. You can just move these things over. I have one customer that had a production data center in the Ukraine, things got super tense, super fast, and they had to go from their private cloud data center in the Ukraine to a public cloud data center outta harm's way. They did it over a weekend, 48 hours. If you've ever migrated data, that's usually six months, right? And a lot of heartburn and a lot of angst, boom. They just drag and drop, moved it on over. That's the power of what we call the cloud operating model. And you can only do this when all your infrastructure's defined in software. >>If you're relying on hardware, load, balancers, hardware, firewalls, you can't move those. They're like a boat anchor. You're stuck with them. And by the way, really, really expensive. And by the way, they eat a lot of power, right? So that was an architecture from the nineties in the cloud operating model, your data center. And this goes back to what you were talking about is just racks and racks of X 86 with these magic DPU or smart necks to make any individual node go blisteringly fast and do all the functions that you used to do in network appliances. >>We just said, AJ taking us to school and everyone else to school on applications, middleware abstraction layer. Yeah. And kit Culver was also talking about this across cloud. We're talking super cloud, super pass. If this continues to happen, which we would think it will happen. What does the security posture look like? It has. It feels to me. And again, this is, this is your wheelhouse. If super cloud happens with this kind of past layer where there's B motioning going on, all kinds of yeah. Spanning applications and data. Yeah. Across environments. Yeah. Assume there's an operating system working on behind the scenes. Right. What's the security posture in all this. Yeah. >>So remember my narrative about like VA guys are getting in and they're moving around and they're so sneaky that they're using legitimate pathways. The only way to stop that stuff is you've gotta understand it at what, you know, we call layer seven at the application layer the in, you know, trying to do security, the infrastructure layer. It was interesting 20 years ago, kind of less interesting 10 years ago. And now it's becoming irrelevant because the infrastructure is oftentimes not even visible, right. It's buried in some cloud provider. So layer seven, understanding, application awareness, understanding the APIs and reading the content. That's the name of the game in security. That's what we've been focused on. Right. Nothing to do with >>The infras. And where's the progress bar on that, that paradigm early one at the 10, 10 being everyone's doing it >>Right now. Well, okay. So we, as a vendor can do this today. All the stuff I talked about about reading APIs, understanding the, the individual services looking at, Hey, wait a minute. This credit card anomalies, that's all shipping production code. Where is it in customer adoption life cycle, early days, 10%. So, so there's a whole lot of headroom. We, for people to understand, Hey, I can put these controls in place. There's software based. They don't require appliances. It's layer seven. So it has contextual awareness and it's works on every single cloud. >>You know, we talk about the pandemic. Being an accelerator really was a catalyst to really rethink. Remember we used to talk about pat his security a do over. He's like, yes, if it's the last thing I'm due, I'm gonna fix security. Well, he decided to go try to fix Intel instead, but, >>But, but he's getting some help from the government, >>But it seems like, you know, CISOs have totally rethought, you know, their security strategy. And, and at least in part is a function of the pandemic. >>When I started at VMware four years ago, pat sat me down in his office and he said to me what he said to you, which is like Tom, he said, I feel like we have fundamentally changed servers. We fundamentally changed storage. We fundamentally changed networking. The last piece of the puzzle of security. I want you to go fundamentally change it. And I'll argue that the work that we're doing with this, this horizontal security understanding the lateral movement east west inspection, it fundamentally changes how security works. It's got nothing to do with firewalls. It's got nothing to do with endpoint. It's a unique capability that VMware is uniquely suited to deliver on. And so pat, thanks for the mission. We delivered it and available >>Those, those wet like web applications firewall for instance are, are around. I mean, but to your point, the perimeter's gone. Exactly. And so you gotta get, there's no perimeter. So it's a surface area problem. Correct. And access and entry, correct. They're entering here easy from some manual error or misconfiguration or bad password that shouldn't be there. They're >>In. Think about it this way. You put the front door of your house, you put a big strong door and a big lock. That's a firewall bad guys, come in the window. Right. And >>Then the window's open and the window with a ladder room. Oh my >>God. Cause it's hot, bad user behavior. Trump's good security >>Every time. And then they move around room to room. We're the room to room people. Yeah. We see each little piece of the thing. Wait, that shouldn't happen. Right. >>I wanna get you a question that we've been seeing and maybe we're early on this, or it might be just a, a false data point. A lot of CSOs and we're talking to are, and people in industry in the customer environment are looking at CSOs and CSOs, two roles, chief information security officer, and then chief security officer Amazon, actually, Steven Schmidt is now CSO at reinforced. They actually called that out. Yeah. And the, and the interesting point that he made, we've had some other situations that verified. This is that physical security is now tied to online to your point about the service area. If I get a password, I still at the keys to the physical goods too. Right. Right. So physical security, whether it's warehouse for them is, or store or retail digital is coming in there. Yeah. So is there a CSO anymore? Is it just CSO? What's the role or are there two roles you see that evolving or is that just, >>Well, >>I circumstance, >>I, I think it's just one. And I think that, that, you know, the stakes are incredibly high in security. Just look at the impact that these security attacks are having on it. It, you know, companies get taken down, Equifax market cap was cut, you know, 80% with a security breach. So security's gone from being sort of a nuisance to being something that can impact your whole kind of business operation. And then there's a whole nother domain where politics get involved. Right. It determines the fate of nations. I know that sounds grand, but it's true. Yeah. And so, so, so companies care so much about it. They're looking for one liter, one throat to choke, you know, one person that's gonna lead security in the virtual domain, in the physical domain, in the cyber domain, in, in, you know, in the actual, well, it is, >>I mean, you mentioned that, but I mean, mean you look at Ukraine. I mean the, the, that, that, that cyber is a component of that war. I mean, that's very clear. I mean, that's, that's new, we've never seen >>This. And in my opinion, the stuff that we see happening in the Ukraine is small potatoes compared to what could happen. Yeah, yeah. Right. So the us, we have a policy of, of strategic deterrents where we develop some of the most sophisticated cyber weapons in the world. We don't use them and we hope never to use them because the, the, our adversaries who could do stuff like, oh, I don't know, wipe out every bank account in north America, or turn off the lights in New York city. They know that if they were to do something like that, we could do something back. >>I, this discuss, >>This is the red line conversation I wanna go there. So >>I had this discussion with Robert Gates in 2016 and he said, we have a lot more to lose, which is really >>Your point. So this brand, so I agree that there's the, to have freedom and Liberty, you gotta strike back with divorce and that's been our way to, to balance things out. Yeah. But with cyber, the red line, people are already in banks. So they're addresses are operating below the red line, red line, meaning before we know you're in there. So do we move the red line down because Hey, Sony got hacked the movie because they don't have their own militia. Yeah. If they were physical troops on the shores of LA breaking into the file cabinets. Yeah. The government would've intervened. >>I, I, I agree with you that it creates, it creates tension for us in the us because our, our adversaries don't have the clear delineation between public and private sector here. You're very, very clear if you're working for the government or you work for an private entity, there's no ambiguity on that. And so, so we have different missions in each department. Other countries will use the same cyber capabilities to steal intellectual, you know, a car design as they would to, you know, penetrate a military network. And that creates a huge hazard for us on the us. Cause we don't know how to respond. Yeah. Is that a civil issue? Is that a, a, a military issue? And so, so it creates policy ambiguity. I still love the clarity of separation of, you know, sort of the various branches of government separation of government from, >>But that, but, but bureau on multinational corporation, you then have to, your cyber is a defensible. You have to build the defenses >>A hundred percent. And I will also say that even though there's a clear D mark between government and private sector, there's an awful lot of cooperation. So, so our CSO, Alex toshe is actively involved in the whole intelligence community. He's on boards and standards and we're sharing because we have a common objective, right? We're all working together to fight these bad guys. And that's one of the things I love about cyber is that that even direct competitors, two big banks that are rivals on the street are working together to share security information and, and private, is >>There enough? Is collaboration Tom in the vendor community? I mean, we've seen efforts to try to, that's a good question, monetize private data, you know? Yeah. And private reports and, >>And, you know, like, so at VMware, we, we, I'm very proud of the security capabilities we've built, but we also partner with people that I think of as direct competitors, we've got firewall vendors and endpoint vendors that we work with and integrate. And so cooperation is something that exists. It's hard, you know, because when you have these kind of competing, you know, so could we do more? Of course we probably could, but I do think we've done a fair amount of cooperation, data sharing, product integration, et cetera, you know, and, you know, as the threats get worse, you'll probably see us continue to do more. >>And the governments is gonna trying to force that too. >>And, and the government also drives standards. So let's talk about crypto. Okay. So there's a new form of encryption coming out called quantum processing, calling out. Yeah. Yeah. Quantum, quantum computers have the potential to crack any crypto cipher we have today. That's bad. Okay. Right. That's not good at all because our whole system is built around these private communications. So, so the industry is having conversations about crypto agility. How can we put in place the ability to rapidly iterate the ciphers in encryption? So when the day quantum becomes available, we can change them and stay ahead of these quantum people. Well, >>Didn't this just put out a quantum proof algo that's being tested right now by the, the community. >>There's a lot of work around that. Correct. And, and, and this is taking the lead on this, but you know, Google's working on it, VMware's working on it. We're very, very active in how do we keep ahead of the attackers and the bad guys? Because this quantum thing is like a, it's a, it's a x-ray machine. You know, it's like, it's like a, a, a di lithium crystal that can power a whole ship. Right. It's a really, really, really powerful >>Tool. It's bad. Things will happen. >>Bad things could happen. >>Well, Tom, great to have you on the cube. Thanks for coming. Take the last minute to just give a plug for what's going on for you here at world this year, VMware explore this year. Yeah. >>We announced a bunch of exciting things. We announced enhancements to our, our NSX family, with our advanced load balancer, with our edge firewall. And they're all in service of one thing, which is helping our customers make their private cloud like the public cloud. So I like to say 0, 0, 0. If you are in the cloud operating model, you have zero proprietary appliances. You have zero tickets to launch a workload. You have zero network taps and zero trust built into everything you do. And that's, that's what we're working on and pushing that further and further. >>Tom Gill, senior vices president head of the networking at VMware. Thanks for coming up for you. Appreciate >>It. Yes. Thanks for having guys >>Always getting the security data. That's killer data and security of the two ops that get the most conversations around dev ops and cloud native. This is the queue bringing you all the action here in San Francisco for VMware. Explore 2022. I'm John furrier with Dave, Alan. Thanks for watching.

(upbeat music) >> Welcome back everyone to theCUBEs live coverage in San Francisco for VMware Explorer. I'm John Furrier with my host, Dave Vellante. Two sets, three days of wall to wall coverage. This is day two. We got a great guest, Scott Baker, CMO at IBM, VP of Infrastructure at IBM. Great to see you. Thanks for coming on. >> Hey, good to see you guys as well. It's always a pleasure. >> ()Good time last night at your event? >> Great time last night. >> It was really well-attended. IBM always has the best food so that was good and great props, magicians, and it was really a lot of fun, comedians. Good job. >> Yeah, I'm really glad you came on. One of the things we were chatting, before we came on camera was, how much changed. We've been covering IBM storage days, back on the Edge days, and they had the event. Storage is the center of all the conversations, cyber security- >> ()Right? >> ... But it's not just pure cyber. It's still important there. And just data and the role of multi-cloud and hybrid cloud and data and security are the two hottest areas, that I won't say unresolved, but are resolving themselves. And people are talking. It's the most highly discussed topics. >> Right. >> ()Those two areas. And it's just all on storage. >> Yeah, it sure does. And in fact, what I would even go so far as to say is, people are beginning to realize the importance that storage plays, as the data custodian for the organization. Right? Certainly you have humans that are involved in setting strategies, but ultimately whatever those policies are that get applied, have to be applied to a device that must act as a responsible custodian for the data it holds. >> So what's your role at IBM and the infrastructure team? Storage is one only one of the areas. >> ()Right. >> You're here at VMware Explore. What's going on here with IBM? Take us through what you're doing there at IBM, and then here at VMware. What's the conversations? >> Sure thing. I have the distinct pleasure to run both product marketing and strategy for our storage line. That's my primary focus, but I also have responsibility for the mainframe software, so the Z System line, as well as our Power server line, and our technical support organization, or at least the services side of our technical support organization. >> And one of the things that's going on here, lot of noise going on- >> Is that a bird flying around? >> Yeah >> We got fire trucks. What's changed? 'Cause right now with VMware, you're seeing what they're doing. They got the Platform, Under the Hood, Developer focus. It's still an OPS game. What's the relationship with VMware? What are you guys talking about here? What are some of the conversations you're having here in San Francisco? >> Right. Well, IBM has been a partner with VMware for at least the last 20 years. And VMware does, I think, a really good job about trying to create a working space for everyone to be an equal partner with them. It can be challenging too, if you want to sort of throw out your unique value to a customer. So one of the things that we've really been working on is, how do we partner much stronger? When we look at the customers that we support today, what they're looking for isn't just a solid product. They're looking for a solid ecosystem partnership. So we really lean in on that 20 years of partnership experience that we have with IBM. So one of the things that we announced was actually being one of the first VMware partners to bring both a technical innovation delivery mechanism, as well as technical services, alongside VMware technologies. I would say that was one of the first things that we really leaned in on, as we looked out at what customers are expecting from us. >> So I want to zoom out a little bit and talk about the industry. I've been following IBM since the early 1980s. It's trained in the mainframe market, and so we've seen, a lot of things you see come back to the mainframe, but we won't go there. But prior to Arvind coming on, it seemed like, okay, storage, infrastructure, yeah it's good business, and we'll let it throw off some margin. That's fine. But it's all about services and software. Okay, great. With Arvind, and obviously Red Hat, the whole focus shift to hybrid. We were talking, I think yesterday, about okay, where did we first hear hybrid? Obviously we heard that a lot from VMware. I heard it actually first, early on anyway, from IBM, talking hybrid. Some of the storage guys at the time. Okay, so now all of a sudden there's the realization that to make hybrid work, you need software and hardware working together. >> () Right. So it's now a much more fundamental part of the conversation. So when you look out, Scott, at the trends you're seeing in the market, when you talk to customers, what are you seeing and how is that informing your strategy, and how are you bringing together all the pieces? >> That's a really awesome question because it always depends on who, within the organization, you're speaking to. When you're inside the data center, when you're talking to the architects and the administrators, they understand the value in the necessity for a hybrid-cloud architecture. Something that's consistent. On The Edge, On-Prem, in the cloud. Something that allows them to expand the level of control that they have, without having to specialize on equipment and having to redo things as you move from one medium to the next. As you go upstack in that conversation, what I find really interesting is how leaders are beginning to realize that private cloud or on-prem, multi cloud, super cloud, whatever you call it, whatever's in the middle, those are just deployment mechanisms. What they're coming to understand is it's the applications and the data that's hybrid. And so what they're looking for IBM to deliver, and something that we've really invested in on the infrastructure side is, how do we create bidirectional application mobility? Making it easy for organizations, whether they're using containers, virtual machines, just bare metal, how do they move that data back and forth as they need to, and not just back and forth from on-prem to the cloud, but effectively, how do they go from cloud to cloud? >> Yeah. One of the things I noticed is your pin, says I love AI, with the I next to IBM and get all these (indistinct) in there. AI, remember the quote from IBM is, "You can't have AI without IA." Information architect. >> () Right. >> () Rob Thomas. >> Rob Thomas (indistinct) the sound bites. But that brings up the point about machine learning and some of these things that are coming down the like, how is your area devolving the smarts and the brains around leveraging the AI in the systems itself? We're hearing more and more softwares being coded into the hardware. You see Silicon advances. All this is kind of, not changing it, but bringing back the urgency of, hardware matters. >> That's right. >> () At the same time, it's still software too. >> That's right. So let's connect a couple of dots here. We talked a little bit about the importance of cyber resiliency, and let's talk about a little bit on how we use AI in that matter. So, if you look at the direct flash modules that are in the market today, or the SSDs that are in the market today, just standard-capacity drives. If you look at the flash core modules that IBM produces, we actually treat that as a computational storage offering, where you store the data, but it's got intelligence built into the processor, to offload some of the responsibilities of the controller head. The ability to do compression, single (indistinct), deduplication, you name it. But what if you can apply AI at the controller level, so that signals that are being derived by the flash core module itself, that look anomalous, can be handed up to an intelligence to say, "Hey, I'm all of a sudden getting encrypted rights from a host that I've never gotten encrypted rights for. Maybe this could be a problem." And then imagine if you connect that inferencing engine to the rest of the IBM portfolio, "Hey, Qradar. Hey IBM Guardian. What's going on on the network? Can we see some correlation here?" So what you're going to see IBM infrastructure continue to do is invest heavily into entropy and the ability to measure IO characteristics with respect to anomalous behavior and be able to report against that. And the trick here, because the array technically doesn't know if it's under attack or if the host just decided to turn on encryption, the trick here is using the IBM product relationships, and ecosystem relationships, to do correlation of data to determine what's actually happening, to reduce your false positives. >> And have that pattern of data too. It's all access to data too. Big time. >> That's right. >> And that innovation comes out of IBM R&D? Does it come out of the product group? Is it IBM research that then trickles its way in? Is it the storage innovation? Where's that come from? Where's that bubble up? That partnership? >> Well, I got to tell you, it doesn't take very long in this industry before your counterpart, your competitor, has a similar feature. Right? So we're always looking for, what's the next leg? What's the next advancement that we can make? We knew going into this process, that we had plenty of computational power that was untapped on the FPGA, the processor running on the flash core module. Right? So we thought, okay, well, what should we do next? And we thought, "Hey, why not just set this thing up to start watching IO patterns, do calculations, do trending, and report that back?" And what's great about what you brought up too, John, is that it doesn't stay on the box. We push that upstack through the AIOPS architecture. So if you're using Turbonomic, and you want to look applications stack down, to know if you've got threat potential, or your attack surface is open, you can make some changes there. If you want to look at it across your infrastructure landscape with a storage insight, you could do that. But our goal here is to begin to make the machine smarter and aware of impacts on the data, not just on the data they hold onto, but usage, to move it into the appropriate tier, different write activities or read activities or delete activities that could indicate malicious efforts that are underway, and then begin to start making more autonomous, how about managed autonomous responses? I don't want to turn this into a, oh, it's smart, just turn it on and walk away and it's good. I don't know that we'll ever get there just yet, but the important thing here is, what we're looking at is, how do we continually safeguard and protect that data? And how do we drive features in the box that remove more and more of the day to day responsibility from the administrative staff, who are technically hired really, to service and solve for bigger problems in the enterprise, not to be a specialist and have to manage one box at a time. >> Dave mentioned Arvind coming on, the new CEO of IBM, and the Red Hat acquisition and that change, I'd like to get your personal perspective, or industry perspective, so take your IBM-hat off for a second and put the Scott-experience-in-the-industry hat on, the transformation at the customer level right now is more robust, to use that word. I don't want to say chaotic, but it is chaotic. They say chaos in the cloud here at VM, a big part of their messaging, but it's changing the business model, how things are consumed. You're seeing new business models emerge. So IBM has this lot of storage old systems, you're transforming, the company's transforming. Customers are also transforming, so that's going to change how people market products. >> () Right. >> For example, we know that developers and DevOps love self-service. Why? Because they don't want to install it. Let me go faster. And they want to get rid of it, doesn't work. Storage is infrastructure and still software, so how do you see, in your mind's eye, with all your experience, the vision of how to market products that are super important, that are infrastructure products, that have to be put into play, for really new architectures that are going to transform businesses? It's not as easy as saying, "Oh, we're going to go to market and sell something." The old way. >> () Right. >> This shifting happening is, I don't think there's an answer yet, but I want to get your perspective on that. Customers want to hear the storage message, but it might not be speeds and fees. Maybe it is. Maybe it's not. Maybe it's solutions. Maybe it's security. There's multiple touch points now, that you're dealing with at IBM for the customer, without becoming just a storage thing or just- >> () Right. >> ... or just hardware. I mean, hardware does matter, but what's- >> Yeah, no, you're absolutely right, and I think what complicates that too is, if you look at the buying centers around a purchase decision, that's expanded as well, and so as you engage with a customer, you have to be sensitive to the message that you're telling, so that it touches the needs or the desires of the people that are all sitting around the table. Generally what we like to do when we step in and we engage, isn't so much to talk about the product. At some point, maybe later in the engagements, the importance of speeds, feeds, interconnectivity, et cetera, those do come up. Those are a part of the final decision, but early on it's really about outcomes. What outcomes are you delivering? This idea of being able to deliver, if you use the term zero trust or cyber-resilient storage capability as a part of a broader security architecture that you're putting into place, to help that organization, that certainly comes up. We also hear conversations with customers about, or requests from customers about, how do the parts of IBM themselves work together? Right? And I think a lot of that, again, continues to speak to what kind of outcome are you going to give to me? Here's a challenge that I have. How are you helping me overcome it? And that's a combination of IBM hardware, software, and the services side, where we really have an opportunity to stand out. But the thing that I would tell you, that's probably most important is, the engagement that we have up and down the stack in the market perspective, always starts with, what's the outcome that you're going to deliver for me? And then that drags with it the story that would be specific to the gear. >> Okay, so let's say I'm a customer, and I'm buying it to zero trust architecture, but it's going to be somewhat of a long term plan, but I have a tactical need. I'm really nervous about Ransomware, and I don't feel as though I'm prepared, and I want an outcome that protects me. What are you seeing? Are you seeing any patterns? I know it's going to vary, but are you seeing any patterns, in terms of best practice to protect me? >> Man, the first thing that we wanted to do at IBM is divorce ourselves from the company as we thought through this. And what I mean by that is, we wanted to do what's right, on day zero, for the customer. So we set back using the experience that we've been able to amass, going through various recovery operations, and helping customers get through a Ransomware attack. And we realized, "Hey. What we should offer is a free cyber resilience assessment." So we like to, from the storage side, we'd like to look at what we offer to the customer as following the NIST framework. And most vendors will really lean in hard on the response and the recovery side of that, as you should. But that means that there's four other steps that need to be addressed, and that free cyber-resilience assessment, it's a consultative engagement that we offer. What we're really looking at doing is helping you assess how vulnerable you are, how big is that attack surface? And coming out of that, we're going to give you a Vendor Agnostic Report that says here's your situation, here's your grade or your level of risk and vulnerability, and then here's a prioritized roadmap of where we would recommend that you go off and start solving to close up whatever the gaps or the risks are. Now you could say, "Hey, thanks, IBM. I appreciate that. I'm good with my storage vendor today. I'm going to go off and use it." Now, we may not get some kind of commission check. We may not sell the box. But what I do know is that you're going to walk away knowing the risks that you're in, and we're going to give you the recommendations to get started on closing those up. And that helps me sleep at night. >> That's a nice freebie. >> Yeah. >> Yeah, it really is, 'cause you guys got deep expertise in that area. So take advantage of that. >> Scott, great to have you on. Thanks for spending time out of your busy day. Final question, put a plug in for your group. What are you communicating to customers? Share with the audience here. You're here at VMware Explorer, the new rebranded- >> () Right? >> ... multi-cloud, hybrid cloud, steady state. There are three levels of transformation, virtualization, hybrid cloud, DevOps, now- >> Right? >> ... multi-cloud, so they're in chapter three of their journey- >> That's right. >> Really innovative company, like IBM, so put the plugin. What's going on in your world? Take a minute to explain what you want. >> Right on. So here we are at VMware Explorer, really excited to be here. We're showcasing two aspects of the IBM portfolio, all of the releases and announcements that we're making around the IBM cloud. In fact, you should come check out the product demonstration for the IBM Cloud Satellite. And I don't think they've coined it this, but I like to call it the VMware edition, because it has all of the VMware services and tools built into it, to make it easier to move your workloads around. We certainly have the infrastructure side on the storage, talking about how we can help organizations, not only accelerate their deployments in, let's say Tanzu or Containers, but even how we help them transform the application stack that's running on top of their virtualized environment in the most consistent and secure way possible. >> Multiple years of relationships with VMware. IBM, VMware together. Congratulations. >> () That's right. >> () Thanks for coming on. >> Hey, thanks (indistinct). Thank you very much. >> A lot more live coverage here at Moscone west. This is theCUBE. I'm John Furrier with Dave Vellante. Thanks for watching. Two more days of wall-to-wall coverage continuing here. Stay tuned. (soothing music)

(modern music) >> Welcome back, everyone to theCUBE's live coverage here in San Francisco for VMware Explore, formerly VMworld. theCUBE's been here 12 years today, we've been watching the evolution of the user conference. It's been quite a journey to see and, you know, virtualization just explode. We got two great guests here, we're going to break it all down. Ash McCarty, director of Multicloud Product Management Dell Technologies, no stranger to the VMworld, now VMware Explore, and Josh Prewitt, Chief Product Officer at Rackspace Technology. Great to see you guys, thanks for coming on. >> Absolutely. >> Yeah, thanks so much, thanks for having us. >> So, you know, the theme this year is multicloud, but it's really all about vSphere 8's out, you got VxRail, you got containers, you got the magic going on around cloud native, which it really points to the future state of where this is going, which is agile enterprises, infrastructure as code, high performance under the hood, I mean, all the things that you guys have been doing for many, many years and decades and business, but now with VMware putting it all together, it feels like, this year, it's like you got visibility into the value proposition, people have clear line of sight into where the performances are from the hardware software and now Cloud, it's kind of coming together, feels like it's coming together. Let's talk about that and the relationship between you guys, Rackspace and Dell and VMware. >> Perfect. That sounds great. Well, thanks so much for having us. You know, I'll sort of kick that off. We've got a huge lifelong partnership and relationship with Dell and VMware and the technologies that these guys create that we're able to put in front of our customers are really what allows us to go drive those business outcomes. So, yeah, happy to dive into it. >> Yeah, and I think to add to that, we understand that customers have a tremendously complex challenge ahead of them on managing their infrastructure. That's why with VxRail, we have intelligent infrastructure. We want it to simplify the outcomes for customers no matter if they're managing VMware or if they're managing the actual hardware infrastructure underneath it. >> Yeah, one of the things that we always talk about, you know, you read about it on the blogs and the news and the startup world, is "Oh, product-market fit," and, well, it kind of applies here, if you think about what's going on on the product side with the Edge emerging, hybrid cloud on pace with private cloud, and obviously, cloud native is great too if you have native applications in there, but now, putting it all together, you're hearing things like the telco cloud, I hear buzzwords like that, I hear supercloud, which we promoting, which you see in companies becoming cloud themselves, with the CapEx being handled by either public cloud or optimized on premise or hosted hardware. I mean, this is now, this is not all about everything's going to the cloud, this is now cloud operations on premise and in hosting hardware, so I'd love to get your perspective on that because you guys are huge hosting, you've got huge experience there, modernizing all the time. What does the modern era look like for the customer? >> Yeah, yeah, so, I mean, I think it's very clear to everybody that it's a multicloud world, right? I think the main question is, are you multicloud as a strategy, or are you multicloud as a situation? Because everybody's multicloud. That ship has sailed, right? >> Yeah, exactly. >> And so, when I look at the capabilities that we have with the partnership with Dell and the VxRail technologies, you know, life-cycle management that you have to go and perform across your fleet can be extremely difficult, and whenever you take something like the VxRail and you add, you know, you have the hardware and you have the software all fully integrated there, it makes it much easier to do life-cycle management, so for a company like Rackspace, where we have tens of thousands of nodes that we're managing for customers across 29 global data centers, and we're all over the place, the ability to have that strength with Dell's hardware, the VMware platform improve life-cycle management makes it so much easier for us to manage our fleet and be able to deliver those outcomes even faster for customers. >> So assuming that VxRail isn't a virtual railroad that delivers data to Rackspace data centers, if it's not that, what is it, Ash? Give us a little premier on what VxRail is. >> Well, VxRail is the first and only jointly engineered HCI system with VMware, so everything we do with VMware is better. >> So hyperconverged infrastructure. >> Hyperconverged infrastructure. >> What we used to call a server because all the bits are in the box, right? >> All the storage is computed in there. >> Everything's in there. Right. >> Simplifies management. And we built in with the VxRail HCI system software, which is really our secret sauce, we built in to actually add those automation capabilities with VMware, so it allows you to scale out very quickly, scale up very quickly. And one of our big capabilities is our life-cycle management, which is full stack, meaning it life-cycles the entire vSphere stack as well as the hardware infrastructure underneath as one continuously validated state, meaning that customers can focus more on their business outcomes and driving their business forward versus spending time managing their infrastructure. >> And when you talk about customers, it's also the value proposition that's flowing through Rackspace because Rackspace, when you install these systems, how long does it take to spin up to have a VM available for use when you install one of these systems? >> Oh, so you can have the system up and running very quickly. So we automate all the day one deployment, so you can have the system up and running in your labs, in your data centers in 45 minutes, and you can have VMs up in provision very shortly after that. >> So what do you do with that kind of agility? >> Oh my gosh, so we've actually taken that, and we've taken the VxRail platform and we've created what we call Rackspace Services for VMware Cloud, and this is our platform that is based on VxRail, it's based on vCloud Director from VMware, and by having the VxRail is already RackStacked, ready to go for our customers, we're able to sign a customer up today, and then, within a matter of minutes, give them access to a vCloud Director portal where they can go in and spin up a new VM anytime they want, but then, it also integrates into all of those cloud management platforms and tools, right? It integrates into your Terraform, so you've got, you know, your full CI/CD pipeline, and so you have that full end-to-end capability. If you want to go click around on a portal, you can using vCloud Director and using vSphere and all that great stuff. If you want to automate it, you can do that too. And we do it all in the backs of that VxRail hyperconverged infrastructure. >> Talk about the DPU dynamic. We're hearing a lot about DPUs. VxRail, you guys have some HCI-like vibe there with DPUs. How is that impacting performance, can you guys see? 'Cause we're hearing a lot of buzz around the VxRail and the VMware DPUs really making things much faster. >> I mean, it's the thing we talk about most with customers now is their challenges with scaling their infrastructure, and VxRail is going to be the first and only jointly engineered system that will have vSphere 8 with DPUs functionality and will have the full life-cycle management, and what this really empowers customers to do is, as they're growing their environments that they're scaling out their workloads in the data center, they need a way to scale to that next generation of networking and network security, and that's what DPUs allow you to do. They give you that offload and that high performance capability. >> Talk about the... I'd love to get your guys' perspective, while we're just riffing on this real quick sidebar for a second, if VxRail has these capabilities which you guys are promoting it does and some of the things go on in the modern era, the next gen apps are going to look a lot different. We're kind of calling it supercloud, if you will, for lack of a better description. Yeah, multicloud is a state, I agree. It's a situation and a state, but supercloud is really the functionality of what cloud does. So what do you guys see as, maybe it's tea leaves reading now or dots connecting, what are some of those next gen apps? I mean the Edge is there with, "Oh, the Edge is going to explode," and I can see the Edge having new kinds of apps that we've never seen before, whether it's on premise building lights and however they work or IoT changing. What do you guys see as the next gen app/apps coming out that's not looking the same as now, or how are apps today changing for next gen? 'Cause you get more performance at the Edge, you get more action, you get more co-locations in GEOS, so it's clear multicloud multi-presence is happening too, right? So what are you guys seeing? What's this... >> Yeah, I would say two areas that resonate most with customers is customers transitioning to their cloud native journey, so beginning it and using things like Tanzu for Kubernetes Operations, which we fully support and have a white paper out there list for customers, another area is really in the AIML space, so we've been partnering with both VMware and Nvidia to simplify how customers deploy new AIML infrastructure. I mean, it's challenging, complex, a lot of customers are wanting to dive in because it really enables them to better operate and operate on insights and analytics they get from running their business. >> Josh? >> And, you know, I think it really comes down to, whether you want to call it Edge or IoT or, you know, smart things, whatever, right? It all comes down to how we are expected, now, to capture all of the data to create a better user experience, and that's what we're seeing the modern applications being built around, right, is how do you leverage all of the data that's now at your fingertips, whether it's from wearables, machine vision, whatever it may be, and drive that improved user experience. And so that's the apps that we're seeing now, right? You know, of course, you still have all your business apps, all your ERP capabilities that need to exist and all of that great stuff, but at the same time, I also expect that, whenever, you know, now, whenever I'm walking into a store and their machine vision picks me up and they're pinging my phone and pushing me push notifications, I expect to have a better user experience. >> And do a database search on you too, by the way. >> Yeah, exactly, right? >> No search warrants out for 'em, you know, you're good. >> That's exactly it, so, you know, you kind of expect that better user experience and that's where I'm seeing a lot of the new app development. >> Yeah, it's fun, as these cases are intoxicating to think about all the weird coolness around it. The thing that I want to get your thoughts on is, we were just talking on the analyst session earlier in theCUBE, if DevOps is here and won, which we believe it has and infrastructure as code is happening, the cloud native discussion, shifting left CI/CD pipeline, that's DevOps in my mind, that's like cloud native developers, that's like traditional IT in my mind, so that's all part of the coding. DataOps and Security Ops seem to be the most robust areas of conversations where that's the new Ops, right? So, I mean, I made the term up, but new Ops, in terms of the focus, what are you making more efficient? What are you optimizing for? What's your guys reaction to that? Because all the conversations that we talk about is data, security, and then the rest seems to be cool, all good on the developer's side. Yeah, shift left events happening up there, Kubernetes containers, but all the action on the Ops side seems to be data and security. >> Yeah. >> What's your reaction to that? Is that right? >> So personally, I do think that it's right. I think that, you know with great power comes great responsibility, right? And so the clouds have brought that to us, all of your infrastructure as code has brought that to us. We have that great power now, right? But then you start to see, kind of, the pipeline attacks that are starting to become more and more popular. And so how you secure something that is as complex as, you know, a cloud native development pipeline is really hard, it's really challenging, so I do think that it warrants the attention. Then on the data side, I think that that matters because when I talked about those examples of a better user experience, I don't want my better user experience tomorrow, I don't want it 20 minutes from now. I want that real time capability, and so with that comes massive requirements from a compute and hardware perspective, massive requirements from a software perspective, and from, you know, what folks are now calling DataOps perspective >> Data addressability, having the data available to be delivered in real time. >> You know, there there's been a lot of talk, here at the conference, about the disaggregation of, you know, the brainularism, if we're going to make up words, you know, the horsepower that's involved, CPU, DPU, GPU. I'll make up another word. We're familiar with the thermometers used during COVID to measure temperature. Pretend that I've invented a device called a Care-o-meter and I'm pointing at various people's foreheads, who needs to care about DPUs and GPUs and CPUs? You know, John was referencing the idea of security at the Edge, data. Well, wow, we've got GPUs that can do things. Who needs to care about that? Obviously, we care about it. You care about it. You care about it. You're building this stuff, you're deploying this stuff, but at what level in the customer stack do they need to care about it? Are you going in, is RackSpace engaging customers and saying, "Look, here's the value proposition: we understand your mission to be this. We believe we can achieve your mission." How far down in the organization do you go before you get to someone where you have to have the DPU conversation? 'Cause we didn't even define DPU yet here, which is always offensive to me. >> I think I defined it actually. >> Did you define DPU? Good. Thank you John. >> Yeah, yeah. >> But so who should care? Who should really care about that? >> Oh, that's such a complex question, right? Because everybody, Rackspace included >> But a good one. But a good question. >> Oh, it's a great question. >> Thank you. >> Great question. (laughing) >> Everybody, Rackspace included, is talking about selling business outcomes, right? And ultimately, that is what matters. It is what matters, is selling those business outcomes to the customer. And so of course we're dealing with our business buyers who are just looking for, "Hey, improve my KPIs, make this run faster, better, stronger, all of that great stuff," but ultimately you get down to an IT staff, and to the IT staff, these things matter because the IT staff, they all have budgets that they have to hit. The realities start to hit them and they can't just go and spend whatever they want, you know, trying to hit the KPIs of the marketing department or the finance department, right? And so you have your business buyers that do care significantly about buying their outcomes, and so we're having, you know, the business outcomes conversations with them and then, oftentimes, they will come back to us and say, "Okay, but now we need you to talk to this person over in our IT organization. We need you to talk with our CIO, with our VP of infrastructure," whatever that may be, where we really get down to the nuts and bolts and we talk about how, you know, we can stretch the hardware coming from Dell, we can stretch the software coming from VMware, and we can deliver a higher caliber experience, a lower TCO, by taking advantage of some of the new technologies coming out. >> Yeah, so there's a reason why I ask that awesome question, and it's because I can imagine a scenario where, and this speaks to RackSpace's position in the market today and moving forward and what your history has been, people want to know, "Well, why should I work with Rackspace instead of some mega-hyper-monster-cloud?" If part of the answer is: well, it's because, for very specific application environments, like healthcare we talked about earlier, that might be a conversation where you're actually bringing in Dell to have a conversation about how you are specifically optimizing hardware and software to achieve things that otherwise can't be achieved with t-shirt sizes of servers in a hyperscale cloud. I mean, is that part of the Rackspace value proposition moving forward, that you can do things like that with partners like Dell that the other folks aren't going to focus on? >> Absolutely, it is, right? And a lot of the power of Rackspace is that, you know, we're the best-in-class pure play cloud solutions provider, and we can talk to you about your AWS, your Azure, your GCP, all of that great stuff, but we can also talk to you about private cloud solutions that are built on the backs of Dell Technologies, and in this multicloud world, you don't have that one size fits all for every single application. There are some things that run great in a hyperscale provider, and we can help you get there, but just exactly like you said, there are these verticals where you have applications that don't necessarily run all that well or they're not modernized, they haven't been refactored to be able to take advantage of cloud native services. And if all you're going to do is run that on bare metal in VMs, a hosted private cloud is, by far, the best way to do that, right? And Rackspace provides that hosted private cloud on the backs of Dell technology, on the backs of VMware technology, and we can go deliver those custom bespoke solutions to customers. >> So the infrastructure and the hardware still matters, Ash, yes? >> Absolutely, and I think he just highlighted, while what he does with his customers and what's important to his internal organization is being to deliver faster outcomes, better outcomes, give those customers, to meet those KPIs of those customers consuming their infrastructure at Rackspace, so I think, really, what the DPU and the underlying infrastructure enables is all that full stack integration to allow them to quickly scale to the demands of those customers and what they need in their infrastructure. >> Guys, while we got you here, what do you think about this year's VMware Explore, a lot of anticipation around how many people are going to show up and, you know, all kinds of things around the new name and Broadcom. Big attendance here, I mean, I was very surprised about the size of the attendance and the show floor, the ecosystem, this train is not stopping. I mean, this is VMware's third act, no matter what the contextual situation is. What's your observation of the show? Do you agree, or is there anything that you could want to share about for folks who didn't make it, what they missed? >> Yeah, I mean it really highlights, I mean, you've seen the breadth of the show, I know people that aren't here that aren't able to see it are really missing the excitement. So there's a lot of great announcements around multicloud, around all the announcements, around the vSphere 8 with the DPUs, the vSAN Express Storage architecture, ton of new exciting technologies that are really empowering how customers, you know, the future of how customers are going to consume their workloads in their data centers. >> Josh, they're not short on products and stuff. A lot of moving parts. vSphere 8, a bunch of new stuff. And the cloud native stuff's looking pretty good too, off the tee. >> You know, it does feel like a focus on the core, though, in a way. So I don't think there's been a lot of peripheral noise at the show. Sometimes it's, you know, "And we got this, and this, and this, and this." It's vSphere 8, vSAN 8, cloud software, you know, really hammering it home and refining it. >> But you don't think of it as a little bit of a circus act. I mean the general keynote was theatrical, I thought, I mean, I thought they did a good job on that. I think vSphere 8 was buried a little bit, I thought they could have... They checked the box at the beginning. >> That's true, that's true. >> I mean, they mentioned it, but we didn't see the demos. You know? Demos are usually great. But that's my only criticism. >> Well, that's why we supplemented it with the VxRail announcements, right? With our big announcements around vSphere 8 and with the DPUs as well as the vSAN Express Storage architecture being integrated into VxRail, so I think, you know, it's always that ongoing partnership and, you know, doing what's best for our customers, showing them the next generation and how they consume that technology. >> Yeah, you guys got good props on VxRail. We had a great chat about it yesterday. Rackspace, you guys doing good? Quick update on what's happening with you guys. Give a quick plug. What's going on at Rackspace? What's hot? What's going on? Give a quick plug for what the services are and the products you got going on there. >> Yeah, absolutely. So we are that end-to-end cloud provider, right? And so we've got really exciting offers in market, helping customers take advantage of all the hyperscale providers, and then giving them that private cloud experience. We've got everything from single-tenant running in our data centers on the backs of vSphere, vCloud Director, and VxRails, all the way through to, like, multi-tenant burstable capability that runs within our own data centers as well. It's a really exciting time for technology, a really exciting time for Rackspace. >> Congratulations, we've been following your journey for a long time. Dell, you guys do continue to do a great job and end-to-end phenomenal work. The telco thing's a huge opportunity, we didn't even go there. But Ash, thanks. Josh, thanks for coming on. Appreciate it. >> Yeah, thanks so much. Thanks for having us. >> Thank you very much. >> Okay, thanks for watching theCUBE. We're live, day two of three days of wall-to-wall coverage. Two sets here in Moscone West on the ground level, in the lobby, checking out all the action. Stay with us for more coverage after this short break. (modern music)