(steady music) >> Oh, welcome back here on theCUBE. I'm John Walls, we're in The Venetian and day one of a jam-packed three days here at AWS re:Invent '22. This is the Executive Summit sponsored by Accenture, and it is Merck time. And I mean, it is loaded with Merck time. We have quite the panel here, in fact. First threesome of the day, by the way. I see you guys have really loaded up nicely. Ron Kim is with us, the SVP and CTO of Merck. Ron, good to see you, sir. >> Thanks, John. >> Also, Fran Gaetens, who's the VP of Technology Infrastructure, Operations, and Experience, which I want to hear more about. Love that job title, Fran. >> Thanks, John. >> And Sean Finnerty, VP of Cloud and Infrastructure Technology. Again, everybody here from Merck. So fellows, thanks for being with us. >> Thanks, John. >> Appreciate the time. >> Yeah. >> So let's just talk about Merck, first off in general in terms of what's happening with the cloud. And Ron, I'll let you jump onto that first. I realize this talk of journey, right? >> Mm-hm. >> It's different for everybody, different slices depending upon where you are, where you start, where you need to finish. Where are you right now in terms of what you're doing with the cloud? >> Yeah, John, we've been on this journey for about two years, have done some great work and achieve some great results in proving we could move to the cloud, moving to the cloud at scale, achieving really measurable financial and operational results. Where we're focusing now going forward is transforming the business. And as you know, our business is saving and improving lives. And so when we talk about moving things to the cloud, it's much more than just moving servers or things like that. It's really contributing towards our business that saves and improves lives. So for our work that we work on together moving into the cloud, the stakes are high, but we think the opportunity's great. And the way to seize that opportunity is what we're doing now, is our BlueSky program and working with AWS and Accenture on it. >> Yeah, so two years, you're two years in. It's like nascent stage still, right? I mean, and it never ends, (laughs) frankly. >> Yeah. >> But talk about that progression and was it, you know, baby steps, was it diving in? I mean, how do you decide, you know, the batting order basically here about how you're going to get things going? >> The early parts of the the two-year journey so far, we're really starting small, primarily driven by a central team. And we did that consciously to get momentum, build the foundation, prove again we could move things to the cloud with success, we could start to scale. And then as that journey went on, now instead of just relying on the central team, we're starting to get the rest of the company involved. So this is not just this team doing the cloud journey. It's the whole company, and that's an ongoing journey, getting all the different stakeholders involved and things like that. But I think that's where we are on the journey now, is look, let's lock arms with everybody in the company. So it's a Merck-wide cloud transformation, not just the BlueSky team. >> Right, and of course, as you know, the C-suite's got to be behind all this. And we hear about how that it's now being driven in some cases, you know, these kind of transformations, whether it's from CEO level down the CTO and CIO and what have you. Fran, the experience part of your job. I just want to get to that real quick. So you know, how do you define that? >> Yeah. First of all, I'm delighted you asked. >> Okay. (laughs) >> And the focus on experience that my team's accountable for transcends, you know, our cloud journey. We have held for the last three years within my organization a priority that's focused on improving the experience that colleagues in our company have with workplace technology and services. And so I'd come into this role at the time and thought carefully, you know, about how to best title our organization in a way that would draw curiosity or inquisition. >> Sure. >> A very creative colleague that we have an opportunity to work with in our company suggested the term, and I loved it and ran with it. And today, it's, you know, still something that we spend a significant portion of cycles focused on. >> Well, it's a very clear signal, right? And a reminder as well that ultimately the experience whether it's your internal stakeholders or external, your customers, right, that you're delivering a very pleasant and efficient, and hopefully you said life-saving >> Yeah. >> experience as well. And I think that'd be a pretty good reminder for your team, isn't it? >> It is. >> "Hey, we're all part of the experience here." >> Yeah. >> Yeah. Right, so Sean, let's talk about some of the things that we've discussed here, branching out within Merck. >> Yep. >> You know, and making it a company effort, not just an IT effort. Right, now all of a sudden, you're into everybody's business and everybody is sharing this. I mean, is there buying that's necessary here? I mean, how do you bring that bunch along? You've all lived it, you know it. They're experiencing it for the first time. >> Yeah, it's a great question and it's one we get quite a bit walking the halls here at re:Invent. We're very lucky in that we do have, you mentioned earlier, top-down support, right? So when we're talking about moving to the cloud, we're not just running around the halls of the technology, you know, cubes of all the people that are sitting there at computers banging away every day. We're meeting with the CEO and a significant portion of the executive team, talking about how does our cloud journey underpin our business transformation aspirations? How do we speed up scientific research? How do we do clinical trials more effectively? How do we manufacture medicine more effectively, more reliably? Those are all underpinned by this technology transformation that we're embarking on sort of from the bottoms up, and meeting in the middle with the top-down strategic imperative to transform the business by leveraging technology. So that clear and unambiguous support coming from the C-suite at our company allows us to prioritize very aggressively and point at that mission to say, "Hey, we're not just here to talk about moving a server or two. We're here to talk about how we transform scientific research and discovery in the interest of our patients and delivering medicine more effectively, more quickly." So it's really, really interesting. >> Yeah, and so being on one side of that, you know, obviously you're dealing with people, whether chemists, scientists, whomever doing computational chemistry whatever it might be. They know their business and you're trying to integrate these new capabilities into their business, right? How do you do that? I mean, how do you know what they need and how do they tell you what they need when they don't know what you have? (laughs) >> That's quite a question. >> Yeah. I got there. >> Yeah, I mean, my initial thought is, you know, there has to be a compelling value to anybody getting impacted by this. And that's what we all work to do. So whether it's faster, less lead time, reducing cycle times, more reliability, innovation, I mean, there has to be something in it for them, and the work we're doing crosses that whole spectrum. So some of the efforts we have, "Hey, this is a cost-savings effort, this is for agility, this is for speed." So you know, it can't be just we're just doing this for the sake of moving of the cloud. There has some business value in it. And you know, Sean and the team have done a great job on kind of putting the rigor behind how do we describe that value so people then say, "Is that value really there or not? And does it really add up?" And I think that's been one of the keys to our success, is the work that Sean and members of his team have been doing is there's a pretty rigorous way we track our progress. And we've involved finance from day one in that. So having their buy in, you know, gives the whole set of results a lot of credibility. >> But tell me about that, Sean, about in terms of identifying value and quantifying it, in terms that a bottom line can orient to that. >> Yeah, absolutely. I mean, I've been at the cloud migration game myself personally for years, right? I got into this game back in 2011. The challenge of those programs has always been articulating the value associated with migrating stuff. It's easy to say, "I'm going to take a server. I'm going to move it from here to here. Then that difference is X, point at that." That's easy, everyone can understand that. But the labor efficiencies and the business value and the business transformation that comes with moving a capability from on-prem or from another hosting service to the cloud and transforming how we deliver, manage, operate, and scale those solutions, that's really where the power of this comes from, is business value tied to discrete actions, moving systems with a plan from one point to another point. And then being able to clearly articulate the value by implementing, as Ron mentioned, models we've created. So we've created actually financial calculation models to put dollars and cents next to labor efficiencies, time liberated, you know, the ability to deliver with higher velocity, higher quality, higher reliability. Those now have dollar values associated with them, which we're able to take, apply to our portfolio, and look for those opportunities that jump out as, "Hey, you know, that one's worth a million bucks. Let's prioritize that one. The ones that maybe have lower value or less business impact, you know, let's put those to the side and get to those later." So we can constantly demonstrate that not only are we raising our ability to deliver for our patients, but we're also delivering value back to the corporation to invest in other things that need focus and attention. >> Yeah, so talk about AWS and Accenture a little bit about, I mean, obviously big players with this. I'm assuming that interaction, maybe Fran, you know, talk about the partnership and again, how they have helped you get to the point that where you currently reside. >> Yeah, our partnership with both firms has been longstanding. That said, you know, what's changed in a market way happened a couple years ago when we originated this cloud acceleration program that we called BlueSky. We worked directly with Accenture to develop a comprehensive business case that, you know, fundamentally lined out the detail of our intention, how we would prosecute this work, and you know, among other things be crystal clear about the value at stake and how we would capture and realize that over time. So you know, through that lens, it's really taken a village with parties from all three firms, you know, to come together, prosecute this important work, but likewise, as I like to say, keep score, you know, in the context of value because ultimately, it's the one thing that we can talk about unambiguously with the program in the context of measurable results. >> Because of the work you do, obviously, you know, invaluable in many respects. But just the thought about cloud, and I know governance, security, compliance, all these things are critical. You know, how do those weigh in, in terms of considerations you have to make? And especially going forward as you develop new ideas, new things, ideas you're trying to bring to market, >> Yeah. >> I mean, how much does that play and the cloud and what exposures there might be? >> Yeah, it plays in quite a bit. And no matter what type of work we do, cloud or on-premise, I mean, security is of utmost importance. That's how we operate. Now what's interesting is when we think about in AWS, you know, AWS has the ability, they have the the scale and the learnings from multiple clients, right? So rather than a single company like us trying to figure out security on our own, we can benefit from what are all the lessons that they've learned that they bake back into their platform. So that's been a great benefit. But regardless of our partner, we'll always be very, a lot of scrutiny about security no matter what. And that's how we should operate. But the benefits of the platform within AWS, I mean, there's a lot of security intelligence built in from their experience, so that's- >> If I can add to that- >> Sure. >> Yeah. To build on prior remarks that Sean had articulated, this migration to the cloud, right, happens to be a catalyst for a broader transformation. One where we're fundamentally changing our ways of working. Ways that consider, you know, topics like security, compliance, documentation, regulatory requirements. And choosing to bake those in to these solutions from the onset rather than consider them as an appendage or an afterthought. So you know, the cloud is a really important part of this. You know, there's no mistake about it, but it's also a powerful catalyst for something that's broader. >> Tremendously more efficient, right? With our thinking and how we're going to plan and how we're going to execute. >> Yeah, and to build on that even more, we view it as an opportunity to raise the bar on our compliance, security, and regulatory readiness game. As we're touching applications across our portfolio, rearchitecting, leaning in on things like the well-architected framework and other things that AWS and Accenture bring to bear. We set the bar higher when we move things from where they are today to a new destination and introduce automation so that that uplift of control does not come at the cost of additional time or labor. It's simply we're raising the bar in ourselves. We're using this transformational opportunity to implement that change. Our customers are along for the ride and reap the benefits of the fact that, you know, we've raised the bar on ourselves, basically. >> Well, you said two years, so the first steps, and I'm sure the next ones are going to be just as successful. I really appreciate the time. Thanks for sharing that and for bringing so much expertise at the table. >> Thanks, John. >> Appreciate that, good to have you guys with us. >> Thanks. >> Talking about Merck and their cloud transformation. Love that word, we've been talking a lot about it this week. You're watching theCUBE, of course, here at the Executive Summit sponsored by Accenture. And theCUBE being, of course, the leader at tech coverage. (calm music)

(upbeat music) >> Okay, welcome back to "theCUBE" stage here in cloud city, TelcoDr, Telco digital revolution. We had a chance to talk to Rob Haberman, CTO of Nokia software. Great interview as part of our hybrid program here, but we're still on the floor onsite. Let's go listen to my great interview with Ron and what he had to say about the power of the cloud. (upbeat digital music) And welcome to "theCUBE's" coverage of Mobile World Congress, 2021. It's an in-person and hybrid event and we're here in Palo Alto through remote interview as part of the hybrid, getting as much content as possible, is a great guest Ron Haberman, who is the CTO of Nokia Cloud Network Services known as CNS. Ron's an expert. He's going to come in and share with us his vision and his commentary on openness in the cloud, Telco cloud, the changes at the Edge, of so much going on, so much innovation that's changing the game, that's going to impact lives and society. Ron, thank you for coming on "theCUBE" for this Mobile World Congress special segment. >> Thank you, glad to be here. >> So the transformation in the cloud is so amazing with 5G. You've got cloud native developers, you've got enterprises changing their architectures, and cloud service probably going to the next level. 5G certainly is a great edge, but the strength of the cloud combined with the new modern applications really is going to be the power. And you start to see people starting to think differently around how developers are building apps and how companies are working together. It's not just one company ruling the world anymore, it's a lot of interoperability, interconnections, a lot of API's openness, kind of sounds like a network. It sounds like a network effect. This is a big deal. What's your take on this whole shift as 5G gets enabling a fast edge and cloud native go hand in hand. What's your take? >> I think 5G and the transformation to cloud native, generically speaking, go very nicely hand in hand. It's important to understand that 5G is not just another G, really because it's more intended for consumption by businesses and not just consumer. And what it means is that it would have a vast impact on how development is done, how the deployment is done and the type of features that would be required from the network. So when we went on our path to start developing for cloud native, primarily, for 5G, it went beyond just being cloud ready. And we started looking at how do we expand the operability with the ecosystems? How do we go into topics such as continuous delivery? How do we create collaboration between CSPs and cloud providers, such as we can provide the advancements. Now, there are quite a few subtopics in the transformation. For example, these might be obvious, but without automation there's really no ability to create a cloud native delivery process. If you're on the cloud, you're creating speed and ability to innovate as well as access, but you also are now required to create a better security system in ways to tie things back together. The multi-vendor environment and the path that it would enable to move to as a service model is again, a topic that can really be established as part of this transition to cloud native and has been greatly in focus for us. And finally there is a bit of a balancing act in some of the use cases in how do we use new technologies such as machine learning, in creating new use cases. For Nokia as a supplier of both the network functions, which are now getting distributed into public cloud in the private cloud, and on the Edges, as well as control systems of different types of OSS, BSS, including charging, enablement, IOP, et cetera, et cetera. It's really about how do we bring these things together in a way that creates use cases that the service providers can position, especially in their now quest to go after B2B, in leveraging their network. >> Yeah, and you guys bring huge strength there on the Nokia side. I want to ask you specifically, as CSPs are collaborating with you guys to leverage that strength of cloud native and open, the question comes up is how fast can they get to a modern, agile, open infrastructure and how fast can they enable value? And that's where this whole interoperability thing, or this interplay between cloud native and innovation hub comes together. Can you take us through how you see that? How cloud service providers are approaching cloud native today? Because that's really kind of where the focus is, how do I get the operating value, with the speed and agility of development, and obviously built in all the security and everything else? That seems to be the disruptor and let's face it, it's been a slow world in the telco place. So cloud has been a speed game with value, but it's an operator game too. What's your thoughts? >> That's right. And look, I'll take you maybe just a little bit into the history of this transition because only just a few years ago, most networks were really build purely with what we're now referring to as SPMS, physical network functions, really a equipment that was installed in a certain pop locations and created the network. We started this transition to virtualization in the world of VMS and then cloud ready and now cloud native. And it's been a few years for these things to come together. And maybe the most important thing that we must get right, is that as we dis-aggregate and in a way it complicates the deployment, if you would, by a few factors, we want to give the tools to indeed go fast, because the name of the game in moving to cloud native is to speed up innovation. So what we've been doing and in collaboration now with Google, is on the one hand, we need to make sure that all of the network functions, the operating models work, into this aggregated cloud. They can go all the way from a private data center through the Edge, into the central data center. Then on the Nokia side, we have to bring the capabilities to tie networks together, be able to migrate workloads between the locations. And maybe most importantly, as we release new versions of our software, as we enable new capabilities, we want to put it in the hands of the service providers and in turn the developers right away. So we need to enable true continuous delivery in the sense that is very familiar in the cloud world, but quite new to telco. So we have- >> You know. All right sorry- >> Go ahead. >> I'm sorry to interrupt, continue. >> Maybe just to give a very practical example of a customer that we share in Europe, Telenet we're starting with an on-premise Anthos based type of deployment, but keeping an eye on moving to the Edge and into the broader cloud, really enabling themselves to be in a multi region and with true Northbound open interfaces for new use cases to be implemented. >> Yeah, Ron, I want to get your thoughts on this. Dave Vellante, my cohost and I we're talking just in an earlier segment around how major inflection points have some characteristics. They all have characters in common. Usually it's proprietary to open shifts happen. And one in point we were looking at was like the nineties, the late eighties, early nineties, when you had proprietary networking protocol stacks, and then OSI stack came out. Obviously we know what happened from there TCP/IP created the best biggest wave of innovation in the computer history we've seen. Similar things happened here. And I won't say proprietary per se, but there were 5G and telcos stuff, that's kind of like operator centric legacy. Are you starting to see this openness come back and I'm not going to say a full stack, but new kinds of disruption and 5G is opening up the door because it's not just consumer technology. A lot of people like the CEO of Intel saying this is a business technology, commercial technology, more than consumer because of the characteristics. And you combine that with cloud native and say openness with scale with cloud services, but you mentioned Google, that's a public cloud. And so public cloud is going to be a disruption, 'cause it brings scale. So it reminds me of this inflection point where you have this new shift and you mentioned networks, these networks are connecting. So you've got a public cloud and Google's known for their networks and their cloud is being highly scalable and secure. But they're not the only network in town. You got a 5G and you got Backhaul, you got all kinds of new heterogeneous environments. What's your comment on that? Because this is what people are talking about. Where's the shift going to go? What wave is this? What's this going to look like? Is this a true disruption or is it more of the same? What's your thoughts? >> I think it's a true disruption. One of the biggest parts of 5G that would enable these new use cases is slicing. Now slicing is a big word describing something that most of us in networks know for quite some time, really the ability to create some kind of a piece of the network that is shared between partners for a particular purpose, with a particular SLA that contains bandwidth and licensing or requirements, locations, et cetera, et cetera. Now the ultimate goal is for an enterprise to be able to interface with the public cloud and with their operator and consume resources completely dynamically. Now, you talked about Google and public cloud. And obviously anybody that used GCP knows that at any point in time, you can go into a region, you can reserve what you need, use what you need, create results, and then either keep it move away, open new locations, et cetera, et cetera. One thing is missing, the connectivity over the mobile air interface to your user. And slicing allows us to combine the power of the true cloud with the ability to dynamically and programmatically, create a slice for a particular purpose. And for us, the ultimate goal is that really networks would become programmable and a developer or their user would be able to interface with the system and literally create network in code. Now there's going to be quite a lot of building blocks required to reach that goal, given that today, most of it is static. But it starts with at least being able to orchestrate resources out of the network, tie them into termination point that by themselves are annex, that are cloud native and potentially even running in the true public cloud and then attach them into a use case. Now you also mentioned openness and Nokia had been on this open path for quite some time in creating choice for our customers, but now with Google coming in with GCP for example, the interface that we create with technology such as Apogee enable openness, not just for our customer being the CSP, but also for the developer to come in from the outside and reside within the ecosystem that they chose and still be able to consume and even create services dynamically. And we enable it with products that interface with that on the other side, which we can get in there. >> Yeah, what's interesting. What you're saying is interesting, I would just call it out because I think it's important. We hear this all the time is that with the Edge and the devices, people are managing an end to end workflow from an application standpoint. But that's very difficult when you don't have networks that are being managed as a heterogeneous environment. So that's a key point you made. So the question I have for you is how can operators best manage this wave? Because this is the holy grail you're talking about here. We're talking about end to end visibility into the workflow as a developer, with the shift left security being built in. No one's debating that, everyone knows that. So as an operator, how do I starting today operate and manage through this? 'Cause I got to operate a large network. It's almost like swapping the engine out at 30,000 feet in the airplane. So how should operators think about taking this step? >> So the first thing to do is to really just accept the fact that there is going to be true legacy... And there are plenty of 3G networks today still operating around the world. There's going to be, to what is now starting to look like semi legacy. So VNX that have only been delivered to networks, maybe in the past couple of years and will carry 4G traffic and will stay in production for quite some time and manage this transition between PMS, VMs, running VNX, VMs running containerized workloads, and true cloud native, which may be bare metal. And as we're working with Google on Anthos, it literally enables this transition by creating a position for us to put the workload in each step of the path, as well as in multiple locations around the network. And what Nokia brings into this equation, it's also a unified view for the operator. So if you're an operator that today runs on VMs on prem, you have some workflows defined and you've been running them in a certain way, we want to keep that view as similar as possible with the tooling that you were enabled to use over the past few years, but create extensions that connects us into the containerized workflow and then a true cloudified workflow out of the same environment. And this is actually in part what we've been collaborating both with some CSPs, as well as with Google on enabling. >> Ron Haberman, CTO, Nokia Cloud Network Services Group, thank you so much for that insight, great commentary. Thank you for sharing your perspective on the future of telco, telco cloud, telco Edge, unifying those networks end to end. Great stuff, thank you for coming on "theCube." >> Thank you. >> Okay, this is Cube's coverage of Mobile World Congress 2021. We're in person and we're virtual, it's a hybrid event. Thanks for watching. >> John clearly the power of the public cloud in that interview. Great job, by the way, >> It was great to get Nokia and to hear the operator impact, and that's awesome. More to come. So back to the studio, Adam and the team back at the studio.

(upbeat music) >> From around the globe, it's the CUBE. With digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Hello, and welcome back to the CUBE's coverage. Virtual coverage of AWS reinvent 2020. It's three weeks we're going on, we're on the ground here in Palo Alto. Doing the remote CUBE, CUBE virtual. We are virtual CUBE here. Wall-to-wall coverage over the three weeks. Got a great segment here, Steven Long regional CTO for AppDynamics and Ron Teeter chief architect with Jobvite. Gentlemen, thank you for joining me on the segment. Appreciate it. Thanks for coming on the CUBE Virtual. >> Thanks for having us. >> Great to be here. >> I wish we were in person. Normally we are, but with the pandemic, it's hard. Steven at AppDynamics. I want to ask you, you've got a customer here. We're going to dig into the use cases of the transformation journey, multiple wave transformation which I'm excited to talk about. But talk about AppDynamics. What's the big story for you guys at re:Invent, quickly get 10 seconds to explain. >> Yeah, sure. AppDynamics is the number one world's leading APM vendor and we're there to be the full stack observability platform. And in that we're talking today about our deep code insights, really to gain that visibility into production, securely capture data and really get that context through a dynamic application. So that you can find the problem and fix it right the first time. >> Great. Thanks. Thanks for that insight. Ron, I want to get into you're the chief architect which means you get the keys to the kingdom at Jobvite. You got to look over the landscape. You got to have the 20 mile stare out to the future but you also got to deal with the reality present here. And it's a tough one. When you go back, this is a terrible year a lot of weirdness, a lot of craziness but everyone's hurting, but they're retooling or they have a tailwind behind their back. So they're either accelerating faster or they're retooling. What does transformation mean to you these days? >> Yeah, so for Jobvite we had a distributed workforce prior to the pandemic shutdown. And what it did for us is it actually forced us to go all in on why can't we work remote all the time? Why do we care where we have facilities? And so we've gotten really good at scaling our organization and being productive remote. Now we actually can hire anywhere we want to, right? And that gives us more leverage and opportunities to scale our DMS going into '21. >> Awesome. Now from a technology standpoint, I'm hearing a couple of different stories, there's two extremes is the... I'll say airlines or those kinds of markets where there's not a lot of business happening, but they're retooling. And then you got obviously video or anything virtual modern applications. It's a surge in business so you have to move faster. Speed is critical. How do you retool in an environment where you've got remote which is totally productive, get that. But now I got more teams. I got to coordinate, I got to communicate. I got to make decisions, architectural decisions. They're big ones. And cloud certainly is here. You've got hybrid and you got the edge big themes this week. How do you look at that? >> The way we look at it, Jobvite has the longevity to remember what it was like from 2008 to 2013. we took that economic recession to build two additional products and launch them into the market in 2013 so that we could ride that wave of growth to drive our business objectives. And we're doing the same thing now. Hiring is a fluid market and this year hiring was way down, right? We saw a 60% drop in open requisitions on our platform alone. And you could see it just dive in March but it started coming back in August and September. And so at this point, we're now post pandemic. So the hiring rates right now are higher than they've been all year. They're very close to where they were last year for the same time. And we expect that to continue to climb as businesses continue to evaluate whether or not it's safe to scale. For us, this lull means we've got an opportunity to make changes to our infrastructure, that aren't going to be disruptive to our customers. But also allow us to get out in front of that so that we can go into '21 with a very strong product focus by taking care of some of the technical debt now. That's exactly what we've been doing is investing in ourselves so that we can operate faster with more agility next year. >> That's worth calling out and mentioning. That's great insight. It really is. You got to come out of the pandemic with a growth strategy. I hear all the CXOs and CSOs in particular dealing with all the security uses but they've got to have the growth strategy. Steven, this is where I think the cloud speed scale the operating model of software networks compute. You're seeing that now get back into the swing of things. That's always been the holy trinity, if you will, of technology, network compute, and storage. Now it's got the cloud and you've got an operating model. We're back to kind of a groove swing here. How does AppDynamics and the Amazon all fit together into this kind of journey? >> Yeah, and if we really look at AppDynamics, we focus on that digital experience. And I think when the pandemic hit we saw 95% of customers that we surveyed in our agents of transformation COVID survey that their priorities shifted. And 95% of those said, within that shift the digital experience became front and center. And so when you're operating in the cloud and you want to have that full stack observability not just from the end user and not just from your application perspective but also from your business perspective. And in any given business the application is the north star of the business. So placing the emphasis on that AppDynamics and surfacing what's actually happening at eliminating blind spots during this pandemic where it's more important than ever to have the best digital experience because that's the brand loyalty really, is that digital experience. >> Ron, I want to ask you, you mentioned something earlier you were talking about how you seized on the opportunity to virtual at home and you retool. But also you mentioned some of the macro conditions in the market, jobs are down, the other on the backup on the upswing. But the geographic hiring is a huge deal. I can almost imagine that's kind of an unforeseen use case where, I mean, it's kind of like working at home. Yeah, X percentage of people be working at home. We plan for that in our disaster recovery or disruption management whatever they do, now 100% people work at home. Now, 100% people looking for jobs. You probably need to rethink the use case because when you have a platform, you've got to think, okay how do I serve my customers who might have a need to recruit from more geographical places? That's a coding thing. So how do you do that stuff? Take us through the mindset of what goes on in your world. >> Yeah, so one of the nice things about building Jobvite as a hiring platform and a sourcing engine is, we use it, right? We now need to solve the same kinds of problems internally that our customers are facing, right? And so we control the software, we understand the problem. And so it's just a matter of deciding these are the things that we're going to prioritize next. We saw a very active summer of social justice outrage, and a lot of that stems from the lack of diversity and inclusive in hiring. And we're already responding to that by delivering features into the product line to help our customers address that in their places. And the key to this is speed. I think you mentioned it and Steve's talked about it as well, right? The ability to move quickly, safely it's the grail that everybody's looking for. And you have to have the right partners to make that successful. >> So I got to ask you then, what are the main benefits you see as you've got working at AppDynamics obviously you're a good customer there. As we're talking through it, you've got a great environment. You're a leader, and how to take advantage of these opportunities and code and shift. What's the benefits of AppDynamics in that equation? >> The key there that we see with AppDynamic's Cisco is the scale and the amount of innovation that they can drive through their product line. One of the things that Steve and I were talking about earlier this year during their transform event, was this deep code insights component which is really production runtime debugging. So imagine I can knock out my meantime to repair, my zero trust and my accelerated solutions of early detection in one solution, right? I can take something that would normally take hours, if not days, into minutes to resolve. The impact on an organization of just one simple feature like that is tremendous when people understand what it can do for them. And it's been invaluable for us. >> Well, you got the speed and the scale with the cloud. So take me through that impact. Because one of the things that's being discussed heavily here at re:Invent and in the industry is the new normal and the new realities we're living in, post pandemic as well. What's going to come out of it. And that is the expectations of the users and is going to drive the new experiences. That's kind of the theme. So the question is whether that's developers or end users or consumers or business users. That's huge, for applications to know what the user experience may be because we don't know what they expect and you don't have the right security (laughs). It kind of all crashes. So what's your... I mean you're nodding your head, weigh in, please. >> Yeah, so I heard a comment earlier from one of my peers in the industry, that is basically saying that nine months ago he had 400 facilities and now he has 18,000. Trying to imagine securing that environment For us, the way we think about it is, work is where you're at. And so we solve the access problems and the tooling problems a long time ago for Jobvite. But we'd been doing for our customers is delivering mobile recruiting solutions. So imagine I don't even need my desktop to complete the hiring process. I can work through the negotiations with a recruiter. I can talk to the candidate, I can text them. One of the big things that we released in early access last month was our new intelligent messaging platform. So that recruiters and hiring managers can have a much more rich conversation with candidates on the mobile device where the candidate is, right? And that's how we're trying to bring this new reality to the marketplace and say, "I can't assume that somebody has a browser and an email client anymore," right? Texting-- >> I mean that's a huge point. I mean, the joke Steven is, it's just distributed computing again 'cause there's really no cloud, there's no... If you think about the edge it's everything is the operating environment. Edge is the data center, edge is the cloud, edge is someone else's place. So if you're thinking about what Ron just said, 18,000 facilities, their homes or wherever, everything has to be looked, that's distributed computing we've been there before, right? I mean. >> Yeah and I think the way Ron, I think describes it, is highly accurate in his company, obviously, but in many companies where, if you've got those 18,000 end points in distributed computing you need to be able to gain visibility into production. And production could be a piece of code living anywhere. And if you can gain that and do that in a secure way which what we do AppDynamics, with our deep code insights, then you can look at data on demand and you can begin to understand the context of what's happening for that end user experience. And you can line up a watch point to watch the code that's executing. And then if it's not working you can actually see how it's not working, recreate that and actually fix it right the first time because you can actually see the code and production in the cloud in this distributed environment. And really be it's more powerful way to operate to reduce time when something happens that you need to fix. >> I was talking to a friend yesterday about this. We weren't on camera. I wish the cameras were rolling. But I'd love to get you guys' reaction to this, because we were saying... I remember when I broke into the business as a young CS major in the late '80s. We had to install everything by hand the software, you install stuff on a server. Or had stuff on a machine and then you put it on a server, you put it in a data center, all those things, right? The young kids then come in and saying, "Okay, I just use the cloud." The next generation and they never installed anything. They don't even know what an installation pack is. Now the next generation's not going to have versions. So you start to get into this notion of evolution with software, because if it's software operated you don't know what version you're running. It shouldn't be disruptive. And the point is this is where I think you guys are getting to here is, the holy grail is there's no disruption. You're running your software at home. Your reaction to that kind of evolution. >> Yeah, you want to take that Steve first? >> Yeah, sure. I mean, it's like you said, the way that code has gone to be delivered and executed is it explodes and disappears. And if there is no way to track that and trace that and understand it, the generation we're in of code, that's a femoral. What's it going to be next? And where's it going to go? And will it ever live anywhere that's alive? The technologies are really being pushed and that's the exciting part. And that's why from an AppDynamics perspective, we're investing in open telemetry is distributed tracing. So as you got distributed computing, we do distributed tracing. And we really look at the problem and provide solutions for our customers. >> Awesome. Ron, your time. I mean, observability, if you can't observe it, you can't measure it. You don't understand, it opens up a lot of things. You got to have the observation space and that's everything. It's hard. >> Yeah. Yeah. And especially as we transition from visual physical servers to virtual hosts, to virtual processes, to virtual functions, right? At some point it's the, I don't even know how to measure capacity for a function in the cloud, right? Let alone try to understand well, what's the cost going to be before I actually deploy it and measure what it's going to cost, right? So these are some of the areas where I think a lot of companies are struggling in understanding how do I move something I'm traditionally very comfortable with. This, I know how much a host costs and I can put my software on there and I can run the CPU at 100% and then I know what I'm getting. But as you start moving into virtual processes and virtual functions, it makes it so much more difficult to think about how you do that capacity planning and budgeting exercise in advance. One of the things that we do with observability is we can test it and we can measure it. And then based on that measure we can make predictions about, okay, this is what it looks like in Def, let's extrapolate what that looks like in production, just by scaling the load. And in areas where you've taken IO and network out of the equation that kind of extrapolation works very well. >> That's awesome. Congratulations on a great a use case, Ron. Thanks for sharing your story, Steven. >> Of course. >> Thanks for coming along and highlighting this great use case and congratulations on having a killer product with observability of AppDynamics. We've been following your work as a company and now at Cisco. So yeah, it's killer software. >> Thanks. Modern software is upon us again the next levels here, gentlemen, thank you for your time. Appreciate the insight >> It been a pleasure. >> Welcome. Thank you for the opportunity. >> Okay, This is the CUBE's virtual covers. We are the CUBE virtual. This is what we do now. We're not in person, but we're remote. When we get back to real life, we'll be back on the scene. We're still doing the interviews. Thanks for watching re:Invent coverage 2020 virtual. (soft music)

>> David: It's the cube covering the virtual Vertica Big Data conference 2020 brought to you by Vertica. Hello, buddy, welcome to this special digital presentation of the cube. We're tracking the Vertica virtual Big Data conferences, the cubes. I think fifth year doing the BDC. We've been to every big data conference that they've held and really excited to be helping with the digital component here in these interesting times. Ron Cormier is here, Principal database engineer at the Trade Desk. Ron, great to see you. Thanks for coming on. >> Hi, David, my pleasure, good to see you as well. >> So we're talking a little bit about your background you got, you're basically a Vertica and database guru, but tell us about your role at Trade Desk and then I want to get into a little bit about what Trade Desk does. >> Sure, so I'm a principal database engineer at the Trade Desk. The Trade Desk was one of my customers when I was working with Hp, at HP, as a member of the Vertica team, and I joined the Trade Desk in early 2016. And since then, I've been working on building out their Vertica capabilities and expanding the data warehouse footprint and as ever growing database technology, data volume environment. >> And the Trade Desk is an ad tech firm and you are specializing in real time ad serving and pricing. And I guess real time you know, people talk about real time a lot we define real time as before you lose the customer. Maybe you can talk a little bit about you know, the Trade Desk in the business and maybe how you define real time. >> Totally, so to give everybody kind of a frame of reference. Anytime you pull up your phone or your laptop and you go to a website or you use some app and you see an ad what's happening behind the scenes is an auction is taking place. And people are bidding on the privilege to show you an ad. And across the open Internet, this happens seven to 13 million times per second. And so the ads, the whole auction dynamic and the display of the ad needs to happen really fast. So that's about as real time as it gets outside of high frequency trading, as far as I'm aware. So we put the Trade Desk participates in those auctions, we bid on behalf of our customers, which are ad agencies, and the agencies represent brands so the agencies are the madman companies of the world and they have brands that under their guidance, and so they give us budget to spend, to place the ads and to display them and once the ads get displayed, so we bid on the hundreds of thousands of auctions per second. Once we make those bids, anytime we do make a bid some data flows into our data platform, which is powered by Vertica. And, so we're getting hundreds of thousands of events per second. We have other events that flow into Vertica as well. And we clean them up, we aggregate them, and then we run reports on the data. And we run about 40,000 reports per day on behalf of our customers. The reports aren't as real time as I was talking about earlier, they're more batch oriented. Our customers like to see big chunks of time, like a whole day or a whole week or a whole month on a single report. So we wait for that time period to complete and then we run the reports on the results. >> So you you have one of the largest commercial infrastructures, in the Big Data sphere. Paint a picture for us. I understand you got a couple of like 320 node clusters we're talking about petabytes of data. But describe what your environment looks like. >> Sure, so like I said, we've been very good customers for a while. And we started out with with a bunch of enterprise clusters. So the Enterprise Mode is the traditional Vertica deployment where the compute and the storage is tightly coupled all raid arrays on the servers. And we had four of those and we're doing okay, but our volumes are ever increasing, we wanted to store more data. And we wanted to run more reports in a shorter period of time, was to keep pushing. And so we had these four clusters and then we started talking with Vertica about Eon mode, and that's Vertica separation of compute and storage where you get the compute and the storage can be scaled independently, we can add storage without adding compute or vice versa or we can add both, like. So that was something that we were very interested in for a couple reasons. One, our enterprise clusters, we're running out of disk, like when adding disk is expensive. In Enterprise Mode, it's kind of a pain, you got to add, compute at the same time, so you kind of end up in an unbalanced place. So beyond mode that problem gets a lot better. We can add disk, infinite disk because it's backed by S3. And we can add compute really easy to scale, the number of things that we run in parallel concurrency, just add a sub cluster. So they are two US East and US west of Amazon, so reasonably diverse. And and the real benefit is that they can, we can stop nodes when we don't need them. Our workload is fairly lumpy, I call it. Like we, after the day completes, we do the ingest, we do the aggregation for ingesting and aggregating all day, but the final hour, so it needs to be completed. And then once that's done, then the number of reports that we need to run spikes up, it goes really high. And we run those reports, we spin up a bunch of extra compute on the fly, run those reports and then spin them down. And we don't have to pay for that, for the rest of the day. So Eon has been a nice Boone for us for both those reasons. >> I'd love to explore you on little bit more. I mean, it's relatively new, I think 2018 Vertica announced Eon mode, so it's only been out there a couple years. So I'm curious for the folks that haven't moved the Eon mode, can you which presumably they want to for the same reasons that you mentioned why by the stories and chunks when you're on Storage if you don't have to, what were some of the challenges that you had to, that you faced in going to Eon mode? What kind of things did you have to prepare for? Were there any out of scope expectations? Can you share that experience with us? >> Sure, so we were an early adopter. We participated in the beta program. I mean, we, I think it's fair to say we actually drove the requirements and a lot of ways because we approached Vertica early on. So the challenges were what you'd expect any early adopter to be going through. The sort of getting things working as expected. I mean, there's a number of cases, which I could touch upon, like, we found an efficiency in the way that it accesses the data on S3 and it was accessing the data too frequently, which ended up was just expensive. So our S3 bill went up pretty significantly for a couple of months. So that was a challenge, but we worked through that another was that we recently made huge strides in with Vertica was the ability to stop and start nodes and not have to start them very quickly. And when they start to not interfere with any running queries, so when we create, when we want to spin up a bunch to compute, there was a point in time when it would break certain queries that were already running. So that that was a challenge. But again, the very good team has been quite responsive to solving these issues and now that's behind us. In terms of those who need to get started, there's or looking to get started. there's a number of things to think about. Off the top of my head there's sort of new configuration items that you'll want to think about, like how instance type. So certainly the Amazon has a variety of instances and its important to consider one of Vertica's architectural advantages in these areas Vertica has this caching layer on the instances themselves. And what that does is if we can keep the data in cache, what we've found is that the performance is basically the same performance of Enterprise Mode. So having a good size cast when needed, can be a little worrying. So we went with the I three instance types, which have a lot of local NVME storage that we can, so we can cache data and get good performance. That's one thing to think about. The number of nodes, the instance type, certainly the number of shards is a sort of technical item that needs to be considered. It's how the data gets, its distributed. It's sort of a layer on top of the segmentation that some Vertica engineers will be familiar with. And probably I mean, the, one of the big things that one needs to consider is how to get data in the database. So if you have an existing database, there's no sort of nice tool yet to suck all the data into an Eon database. And so I think they're working on that. But we're at the point we got there. We had to, we exported all our data out of enterprise cluster as cache dumped it out to S3 and then we had the Eon cluster to suck that data. >> So awesome advice. Thank you for sharing that with the community. So but at the end of the day, so it sounds like you had some learning to do some tweaking to do and obviously how to get the data in. At the end of the day, was it worth it? What was the business impact? >> Yeah, it definitely was worth it for us. I mean, so right now, we have four times the data in our Eon cluster that we have in our enterprise clusters. We still run some enterprise clusters. We started with four at the peak. Now we're down to two. So we have the two young clusters. So it's been, I think our business would say it's been a huge win, like we're doing things that we really never could have done before, like for accessing the data on enterprise would have been really difficult. It would have required non trivial engineering to do things like daisy chaining clusters together, and then how to aggregate data across clusters, which would, again, non trivial. So we have all the data we want, we can continue to grow data, where running reports on seasonality. So our customers can compare their campaigns last year versus this year, which is something we just haven't been able to do in the past. We've expanded that. So we grew the data vertically, we've expanded the data horizontally as well. So we were adding columns to our aggregates. We are, in reaching the data much more than we have in the past. So while we still have enterprise kicking around, I'd say our clusters are doing the majority of the heavy lifting. >> And the cloud was part of the enablement, here, particularly with scale, is that right? And are you running certain... >> Definitely. >> And you are running on prem as well, or are you in a hybrid mode? Or is it all AWS? >> Great question, so yeah. When I've been speaking about enterprise, I've been referring to on prem. So we have a physical machines in data centers. So yeah, we are running a hybrid now and I mean, and so it's really hard to get like an apples to apples direct comparison of enterprise on prem versus Eon in the cloud. One thing that I touched upon in my presentation is it would require, if I try to get apples to apples, And I think about how I would run the entire workload on enterprise or on Eon, I had to run the entire thing, we want both, I tried to think about how many cores, we would need CPU cores to do that. And basically, it would be about the same number of cores, I think, for enterprise on prime versus Eon in the cloud. However, Eon nodes only need to be running half the course only need to be running about six hours out of the day. So the other the other 18 hours I can shut them down and not be paying for them, mostly. >> Interesting, okay, and so, I got to ask you, I mean, notwithstanding the fact that you've got a lot invested in Vertica, and get a lot of experience there. A lot of you know, emerging cloud databases. Did you look, I mean, you know, a lot about database, not just Vertica, your database guru in many areas, you know, traditional RDBMS, as well as MPP new cloud databases. What is it about Vertica that works for you in this specific sweet spot that you've chosen? What's really the difference there? >> Yeah, so I think the key differences is the maturity. There are a number, I am familiar with another, a number of other database platforms in the cloud and otherwise, column stores specifically, that don't have the maturity that we're used to and we need at our scale. So being able to specify alternate projections, so different sort orders on my data is huge. And, there's other platforms where we don't have that capability. And so the, Vertica is, of course, the original column store and they've had time to build up a lead in terms of their maturity and features and I think that other other column stores cloud, otherwise are playing a little bit of catch up in that regard. Of course, Vertica is playing catch up on the cloud side. But if I had to pick whether I wanted to write a column store, first graph from scratch, or use a defined file system, like a cloud file system from scratch, I'd probably think it would be easier to write the cloud file system. The column store is where the real smarts are. >> Interesting, let's talk a little bit about some of the challenges you have in reporting. You have a very dynamic nature of reporting, like I said, your clients want to they want to a time series, they just don't want to snap snapshot of a slice. But at the same time, your reporting is probably pretty lumpy, a very dynamic, you know, demand curve. So first of all, is that accurate? Can you describe that sort of dynamic, dynamism and how are you handling that? >> Yep, that's exactly right. It is lumpy. And that's the exact word that I use. So like, at the end of the UTC day, when UTC midnight rolls around, that's we do the final ingest the final aggregate and then the queue for the number of reports that need to run spikes. So the majority of those 40,000 reports that we run per day are run in the four to six hours after that spikes up. And so that's when we need to have all the compute come online. And that's what helps us answer all those queries as fast as possible. And that's a big reason why Eon is advantage for us because the rest of the day we kind of don't necessarily need all that compute and we can shut it down and not pay for it. >> So Ron, I wonder if you could share with us just sort of the wrap here, where you want to take this you're obviously very close to Vertica. Are you driving them in a heart and Eon mode, you mentioned before you'd like, you'd have the ability to load data into Eon mode would have been nice for you, I guess that you're kind of over that hump. But what are the kinds of things, If Column Mahoney is here in the room, what are you telling him that you want the team, the engineering team at Vertica to work on that would make your life better? >> I think the things that need the most attention sort of near term is just the smoothing out some of the edges in terms of making it a little bit more seamless in terms of the cloud aspects to it. So our goal is to be able to start instances and have them join the cluster in less than five minutes. We're not quite there yet. If you look at some of the other cloud database platforms, they're beating that handle it so I know the team is working on that. Some of the other things are the control. Like I mentioned, while we like control in the column store, we also want control on the cloud side of things in terms of being able to dedicate cluster, some clusters specific. We can pin workloads against a specific sub cluster and take advantage of the cast that's over there. We can say, okay, this resource pool. I mean, the sub cluster is a new concept, relatively new concept for Vertica. So being able to have control of many things at sub cluster level, resource pools, configuration parameters, and so on. >> Yeah, so I mean, I personally have always been impressed with Vertica. And their ability to sort of ride the wave adopt new trends. I mean, they do have a robust stack. It's been, you know, been 10 plus years around. They certainly embraced to do, the embracing machine learning, we've been talking about the cloud. So I actually have a lot of confidence to them, especially when you compare it to other sort of mid last decade MPP column stores that came out, you know, Vertica is one of the few remaining certainly as an independent brand. So I think that speaks the team there and the engineering culture. But give your final word. Just final thoughts on your role the company Vertica wherever you want to take it. >> Yeah, no, I mean, we're really appreciative and we value the partners that we have and so I think it's been a win win, like our volumes are, like I know that we have some data that got pulled into their test suite. So I think it's been a win win for both sides and it'll be a win for other Vertica customers and prospects, knowing that they're working with some of the highest volume, velocity variety data that (mumbles) >> Well, Ron, thanks for coming on. I wish we could have met face to face at the the Encore in Boston. I think next year we'll be able to do that. But I appreciate that technology allows us to have these remote conversations. Stay safe, all the best to you and your family. And thanks again. >> My pleasure, David, good speaking with you. >> And thank you for watching everybody, we're covering this is the Cubes coverage of the Vertica virtual Big Data conference. I'm Dave volante. We'll be right back right after this short break. (soft music)

>> Live from Barcelona, Spain, it's theCUBE! Covering Cisco Live! Europe, brought to you by Cisco and its ecosystem partners. >> Hey, welcome back everyone. We're live here in Barcelona, Spain, theCUBE's coverage of Cisco Live! Europe 2019. I'm John Furrier, Stu Miniman, and Dave Vellante all here this week getting all the action. Our next guests is Ron Sterbenz who's the marketing manager of Stealthwatch Cloud. Formerly is part of the acquisition the original team of observable networks. >> Correct, that's a good one. >> A small startup that was bought by Cisco in 2017. Now you're in the big company. Key part of the portfolio and security and cloud. Welcome to the cube again. Good to see you. >> Thank you John. >> So what's going on in Europe? What are the big trends obviously you here in Barcelona its a mirror, Europe, Middle east, Africa, and Russia. >> Yup. A lot of compliance, a lot of regulated industries across the board. >> Yup. >> A lot of security concerns, a lot of privacy concerns. >> That's right. >> Security is at the center of the values in the Cisco network approach. >> Yup. You know as of last year we were down in the front of this of the event. And I would say that traffic was pretty good. Now we're in the back, we're seeing a lot more interest, we're seeing actual customers come up, subscribers to our product, and service say "I've been with you now for a year, what's new?" So its nice to see that, that we didn't have right after the acquisition, which was where we were last year. >> So, in Europe, what are some of the trends, what's resonating? >> Kubernetes You know, you guys were out at KubeCon, for us that was a great show, lot of interesting kubernetes, and we're seeing the same thing here in the base, as well as the Cisco solution for it. >> And the definite zone which we're in has all these classrooms, I got to say, right next to us is Classroom One, the kubernetes session yesterday, >> Mhmm >> Was overflowing into our set. >> Yeah. >> Why don't we explain a little bit, what's exciting people about Kubernetes, do you have any guidance as to, you know, who they're using, cause I think back a year ago, a lot of the customers I talked to, they were like, building their own. Is kubernetes the hard way, as opposed to today, you know, Cisco's got a solution, you've got deep partnership with AWS, with Google and the like, so, yeah. >> We're seeing it all across the board. Lot of folks using Amazon to do it, we would always teach customers... Google was a natural for it, we are actually having customers come up to say, We're using the Cisco platform for it. So, for us it's the whole breath. What's also nice about it is we really simplify the deployment for kubernetes, so it doesn't matter whether any of those environments are going to be used from a security perspective. Real easy to inject it into the kubernetes environments, expand and contract, and feed the security solution that we offer. So, again, what's also really nice is the multi-cloud, so whether it's kubernetes, a little bit of AWS on the web servers, a little bit of the on PREM, any of the other Cisco kind of compute platforms, all of that data is coming in. >> I wonder if, when you look at security, it felt like a few years ago we got over the hump of the public cloud can be secure, but one of the challenges I have is if I'm in a multi-cloud environment, security is different in every one of those, so I've got different skill sets I have to match then, how are you helping customers? How are they sorting through that? >> Yeah, and then the other part of it is, they're used to what they would see on PREM in a physical network. So, by doing what we do into the cloud, allows the customer to have that traditional security perspective across all those environments of things that they're used to. So, if you look at it from the automation and simplicity, that's a great value prop. The other one that's a really interesting value prop is, I don't want to have to normalize for every data feed and element that comes out of those clouds, so, by for us doing it across all of our portfolio, when a feed changes with AWS, we're normalizing it and bringing it in as a security perspective for the customer, so you basically outsource a lot of the easy or hard lift of modifying those particular feeds into our solution or service. >> Talk about the cloud center service that you guys have as a suite now, gives a variety of, mentioned portfolio, certainly securities in there, stealth watch cloud, you mentioned kubernetes, you can't look at without containers being part of that, you've got the Cisco container service, Google and AWS, how do you guys fit into that? What's the key Stealthwatch Cloud value proposition? >> Yeah, so there is a reference architecture that Cisco has put out where we look at ACI anywhere, we look at the container platform, security on the top of it, we're able to integrate in other solutions, we're seeing a lot more interest in SD-WAN part of the house, being able to, again, simplify the security for all of those infrastructures back, so that's a really nice reference for architecture to go into an environment and try to leverage the whole portfolio for simplicity, broader breadth and depth. >> What are some of the conversations you're having with the customers around multi-cloud? Do they come in and say, Okay, give me some of that Stealthwatch Cloud, or, how do I architect it in, how does it fit in, what are some of those customer conversations? What do they look like? >> Well, the first one is simplicity, how difficult is this to do, how broad can I put it in a solution, and will it really do what you're forecasting or saying it will, with this thing called Endpoint Modeling, or Entity Modeling. What we also encourage free trial, so we allow customers to use the full service across all of those platforms, go as broad as they want during that trial period, and we prove out the value prop, in other words, you're able to see these devices in the real time, devices that you're normal and familiar with, the ability to again, to expand and contract in kubernetes, and see those whether you put an Apache server on a node, and that's the way it performs, and you expand out and get six of those, they will perform exactly the same way, and the expectation is that they will. But what we do in the demos in the booth is show the customer how easy it is to do that, and then encourage them to do it with their own environment in a trial, and that's where we solidify the customer into a sale. Into an ongoing subscriber. >> So, Ron, it's been interesting to watch this, we've got a lot of background and history with Cisco. Your solution, you're in the AWS marketplace, they buy you software, in the Google marketplace it's not boxes and that model, talk about how it's been coming into Cisco now, and kind of the go to market, how that, you know, we're watching a lot of Cisco change to go more towards where you were pre acquisition, even, so, how's that dynamic changing? >> We went from a team of 14, I think we're up to 21, 22 now, and then we've got the other partnership, our brothers and sisters of 70 thousand people, so it is one influencing that product, plus all the partners, and then getting them to encourage them to sell, the ability to sell on Cisco GPL, also the ability to transact, and Cisco is really supportive of whatever the customer wants to be, whether that's AWS, Azure, AWS marketplace, very easy to do a transaction there, and at the same time, we don't lose any of the internal compensation for Cisco employees or Cisco salers, so that's really nice, and it's simple for our customer. >> As you move from being a startup, which is nimble, you guys are small, you're in the front lines, you come into Cisco, what was your impression about how Cisco's portfolio was coming together, and where is it now, almost one year later, coming up on your one year anniversary >> Yeah, I think you can see that in the floor space here when you look at cloud. So, the first year that we were here, we were included in that whole piece, probably lighter traffic. This year we're seeing a lot more people with the interest in cloud, I think next year you will see more Cisco sellers, partners, buyers in that space, asking about what's coming next, I mean we're getting MSPs this year to say, Look, we're trying to do a kubernetes practice, is there a way that we can attach a security perspective to that? In a multi-tennancy, servicing our customers, being able to do the mediation, and we are and I don't think that's a conversation we had last year. >> Take a minute to explain, simply, the story for multi-cloud for Cisco from a security perspective. How would you describe to someone the multi-cloud story from Cisco? What is it? Take a minute to explain that. >> The multi-cloud story for Cisco for security is the ability to see and leverage intelligence, actionable insight across any one of those platforms. Normalizing it, bring it in, show me the interaction, whether that customer is sitting on a Cisco network, or this customer's sitting at the end point, outside of a web server on AWS. What can I see across that, what are my expectations of that interaction? >> Susie Wee was on yesterday, she's the champion of DevNet, this whole DevNet zone where we're located, lot of energy, lot of developers, Cisco app dynamics, which brings that app perspective, as the network becomes programmable, and you see the rise of kubernetes, great indicator that you mentioned that earlier, how should customers think about programmability with the security paradigm that's put forth from Cisco today? What's the guiding principals, what are some of the strategies they should take, what's your view on that? >> Intelligence and interoperability. So, whether we're looking at like an ICE integration, or a crypto threat analytics, or any of the other services that Cisco puts together, bringing all that intelligence back in, and putting it into usable fashion. Simplicity of integrating the products and suites services. >> Service providers you mentioned before, they're used to programmability, what I've seen over the last few years is they're embracing the multi-cloud message before. Five years ago it was, Oh my god, that's the enemy, I need to fight against them, now they're direct connecting into a lot of these public clouds, they're figuring out what of their services they keep vs offering services to customer and pass them through, seems like a great opportunity for you to help them expand, especially their security footprint across those environments. >> It definitely is. The ability for a customer to say, Hey, what is my real value at in this vs the pipe and the mechanics from behind the scene, so for us we focus on what we do really well, we allow our partners, look if you're going to do remediation, if you're going to do deployments into the web front end, or new applications, if you're going to look at portability across cube environments, whatever the cost benefit or ratio is, we let them focus on that, and we take the back end processing, which is the back end processing of alerts, back end processing of what we call observations, simplicity of bringing on partners for MSPs, and servicing 'em. >> I want to get your thoughts on a quote we heard on theCUBE yesterday from a practitioner, talking about multi-cloud, and cloud in general, as people move to SAS models and cloud, they don't really own the equipment, the quote was, "IT doesn't own the equipment, but owns the outcome." So the operating models changing a little bit, okay, I buy that, makes sense to me, and the quote was, "It moves from find and fix, to get evidence and escalate." How to handle the data becomes the core issue. Security data's a super important part of it, can you comment on your reaction to that quote, the positioning, cause certainly cloud is a rent vs buy, that's classic, you've still got the on premise, but security's dealing across the holistic environment where data and escalating, sharing data, big part of it, what's your thoughts on the role, how to handle the data? >> Well, if you look at security and look at SAS, what is our role? Our role is to normalize that data and be responsive every time a change is made in a cloud platform. The other thing what's great about a SAS service is upgrading, right, so upgrading is updates and everything else that comes at you from a security perspective, SAS is best to handle that, because we are looking at that, we're providing updates as well as changes to our platform almost daily, we publish that back to the customers, and as a subscriber, you don't renew if you're not happy. So, it continually puts us on the forefront of saying, look, we've got to innovate, we've got to be responsive to the customer, we've got to be able to address any other kind of... And it isn't always just malware or something that goes wrong, it could also be malfunction, it could also be left over assets that are sitting in AWS environment, or LAM defunctions that go awry, so we have multiple ways of providing value to the customer on those infastructures. >> Lot of moving parts, dependencies could be, >> That's right. >> We could move the availability zone, have some dependencies across the network, lot of things (laughs) at play here. >> Right, and what's really good about Stealthwatch Cloud is from the back end of it we're sitting out and addressing that, we're trying to put a human's touch to what we would find in an alert, and what would be important to a customer, and how we drive that value. >> So, Ron, we know that security's always an ongoing journey, so there's no end to where you need to go, you mentioned LAM defunctions, serverless something that your team's involved in, or are there other areas that we should be looking for throughout 2019 for some to maturation. >> I think there is, but I don't... As far as the road map goes, there's always integration, look, integration with Meraki, integration with other Cisco products, and the same thing goes with any other, I had just finished a meeting with Google about, what other data elements can we get to enrich that security perspective from Google, that would be the exact same thing with AWS functions, the team will look at all of those feeds, which ones are relative to things that we can provide from a security perspective, or generate value to the customer and integrate those first. >> This highlights the operating model for Cisco as a company, you mentioned Google, Amazon, these are real integrations, these are real partnerships, deep, meaningful, technical relationships. Share some insight into how that's going. >> There's a lot. There's always a lot from each of those platforms, so you do have to kind of pick and choose as to what you're going to address, I'm sure all of us on the team that are in the forefront of selling are saying, What about this? What about that? Can we incorporate it? >> Worth the backlog >> It's difficult, but, I would also say what's really big here in Europe is Azure. That's a real big potential customer base to address as well. >> We talked to the DNA center platform guys, and they're like, the backlog is huge and we're just going to work the backlog, to your point about SAS, you knock these things down one at a time, you go get you, prioritize, do the classic product management. But Ron, thanks for coming on, really appreciate the insight, final minute, just give a plug for what's going on at Stealthwatch Cloud. What are some of the highlights, what are some of the things you guys are promoting, what's the good news? Share with us. >> I would say probably the best news is adding all the cloud platforms, being able to truly be a multi-cloud story. Integration with other Cisco products that are coming in the forefront that we'll be announcing at other events, throughout I think RSA we've got some other announcements coming out, so if you'll be there, and then the part that we keep hitting home is meeting with the sales teams, starting the trial, and allowing us to kind of prove out the value of the product and service. >> Security portfolios expand, you get Tetracia and SAS coming around the corner, a lot of other interesting things happening in the Cisco world. >> Duo. >> Hey, thanks for coming on, we're here inside theCUBE in Barcelona, Spain for Cisco Live Europe, I'm John Furrier, stay with us for more Day Three coverage, after this short break.

>> Announcer: Live from San Jose, it's theCUBE. Presenting Big Data, Silicon Valley, brought to you by Silicon Angle Media and its ecosystem partners. >> Welcome back to theCUBE's continuing coverage of our event Big Data SV. I'm Lisa Martin, joined by Dave Vellante and we've been here all day having some great conversations really looking at big data, cloud, AI machine-learning from many different levels. We're happy to welcome back to theCUBE one of our distinguished alumni, Ron Bodkin, who's now the Technical Director of Applied AI at Google. Hey Ron, welcome back. >> It's nice to be back Lisa, thank you. >> Yeah, thanks for coming by. >> Thanks Dave. >> So you have been a friend of theCUBE for a long time, you've been in this industry and this space for a long time. Let's take a little bit of a walk down memory lane, your perspectives on Big Data Hadoop and the evolution that you've seen. >> Sure, you know so I first got involved in big data back in 2007. I was VP in generating a startup called QuantCast in the online advertising space. You know, we were using early versions of Hadoop to crunch through petabytes of data and build data science models and I saw a huge opportunity to bring those kind of capabilities to the enterprise. You know, we were working with early Hadoop vendors. Actually, at the time, there was really only one commercial vendor of Hadoop, it was Cloudera and we were working with them and then you know, others as they came online, right? So back then we had to spend a lot of time explaining to enterprises what was this concept of big data, why it was Hadoop as an open source could get interesting, what did it mean to build a data lake? And you know, we always said look, there's going to be a ton of value around data science, right? Putting your big data together and collecting complete information and then being able to build data science models to act in your business. So you know, the exciting thing for me is you know, now we're at a stage where many companies have put those assets together. You've got access to amazing cloud scale resources like we have at Google to not only work with great information, but to start to really act on it because you know, kind of in parallel with that evolution of big data was the evolution of the algorithms as well as the access to large amounts of digital data that's propelled, you know, a lot of innovation in AI through this new trend of deep learning that we're invested heavily in. >> I mean the epiphany of Hadoop when I first heard about it was bringing, you know, five megabytes of code to a petabyte of data as sort of the bromide. But you know, the narrative in the press has really been well, they haven't really lived up to expectations, the ROI has been largely a reduction on investment and so is that fair? I mean you've worked with practitioners, you know, all your big data career and you've seen a lot of companies transform. Obviously Google as a big data company is probably the best example of one. Do you think that's a fair narrative or did the big data hype fail to live up to expectations? >> I think there's a couple of things going on here. One is, you know, that the capabilities in big data have varied widely, right? So if you look at the way, for example, at Google we operate with big data tools that we have, they're extremely productive, work at massive scale, you know, with large numbers of users being able to slice and dice and get deep analysis of data. It's a great setup for doing machine learning, right? That's why we have things like BigQuery available in the cloud. You know, I'd say that what happened in the open source Hadoop world was it ended up settling in on more of the subset of use cases around how do we make it easy to store large amounts of data inexpensively, how do we offload ETL, how do we make it possible for data scientists to get access to raw data? I don't think that's as functional as what people really had imagined coming out of big data. But it's still served a useful function complementing what companies were already doing at their warehouse, right? So I'd say those efforts to collect big data and to make them available have really been a, they've set the stage for analytic value both through better building of analytic databases but especially through machine learning. >> And there's been some clear successes. I mean, one of them obviously is advertising, Google's had a huge success there. But much more, I mean fraud detection, you're starting to see health care really glom on. Financial services have been big on this, you know, maybe largely for marketing reasons but also risk, You know for sure, so there's been some clear successes. I've likened it to, you know, before you got to paint, you got to scrape and you got to, you put in caulking and so forth. And now we're in a position where you've got a corpus of data in your organization and you can really start to apply things like machine learning and artificial intelligence. Your thoughts on that premise? >> Yeah, I definitely think there's a lot of truth to that. I think some of it was, there was a hope, a lot of people thought that big data would be magic, that you could just dump a bunch of raw data without any effort and out would come all the answers. And that was never a realistic hope. There's always a level of you have to at least have some level of structure in the data, you have to put some effort in curating the data so you have valid results, right? So it's created a set of tools to allow scaling. You know, we now take for granted the ability to have elastic data, to have it scale and have it in the cloud in a way that just wasn't the norm even 10 years ago. It's like people were thinking about very brittle, limited amounts of data in silos was the norm, so the conversation's changed so much, we almost forget how much things have evolved. >> Speaking of evolution, tell us a little bit more about your role with applied AI at Google. What was the genesis of it and how are you working with customers for them to kind of leverage this next phase of big data and applying machine learning so that they really can identify, well monetize content and data and actually identify new revenue streams? >> Absolutely, so you know at Google, we really started the journey to become an AI-first company early this decade, a little over five years ago. We invested in the Google X team, you know, Jeff Dean was one of the leaders there, sort of to invest in, hey, these deep learning algorithms are having a big impact, right? Fei-Fei Li, who's now the Chief Scientist at Google Cloud was at Stanford doing research around how can we teach a computer to see and catalog a lot of digital data for visual purposes? So combining that with advances in computing with first GPUs and then ultimately we invested in specialized hardware that made it work well for us. The massive-scale TPU's, right? That combination really started to unlock all kinds of problems that we could solve with machine learning in a way that we couldn't before. So it's now become central to all kinds of products at Google, whether it be the biggest improvements we've had in search and advertising coming from these deep learning models but also breakthroughs, products like Google Photos where you can now search and find photos based on keywords from intelligence in a machine that looks at what's in the photo, right? So we've invested and made that a central part of the business and so what we're seeing is as we build up the cloud business, there's a tremendous interest in how can we take Google's capabilities, right, our investments in open source deep learning frameworks, TensorFlow, our investments in hardware, TPU, our scalable infrastructure for doing machine learning, right? We're able to serve a billion inferences a second, right? So we've got this massive capability we've built for our own products that we're now making available for customers and the customers are saying, "How do I tap into that? "How can I work with Google, how can I work with "the products, how can I work with the capabilities?" So the applied AI team is really about how do we help customers drive these 10x opportunities with machine learning, partnering with Google? And the reason it's a 10x opportunity is you've had a big set of improvements where models that weren't useful commercially until recently are now useful and can be applied. So you can do things like translating languages automatically, like recognizing speech, like having automated dialog for chat bots or you know, all kinds of visual APIs like our AutoML API where engineers can feed up images and it will train a model specialized to their need to recognize what you're looking for, right? So those types of advances mean that all kinds of business process can be reconceived of, and dramatically improved with automation, taking a lot of human drudgery out. So customers are like "That's really "exciting and at Google you're doing that. "How do we get that, right? "We don't know how to go there." >> Well natural language processing has been amazing in the last couple of years. Not surprising that Google is so successful there. I was kind of blown away that Amazon with Alexa sort of blew past Siri, right? And so thinking about new ways in which we're going to interact with our devices, it's clearly coming, so it leads me into my question on innovation. What's driven in your view, the innovation in the last decade and what's going to drive innovation the next 10 years? >> I think innovation is very much a function of having the right kind of culture and mindset, right? So I mean for us at Google, a big part of it is what we call 10x thinking, which is really focusing on how do you think about the big problem and work on something that could have a big impact? I also think that you can't really predict what's going to work, but there's a lot of interesting ideas and many of them won't pan out, right? But the more you have a culture of failing fast and trying things and at least being open to the data and give it a shot, right, and say "Is this crazy thing going to work?" That's why we have things like Google X where we invest in moonshots but that's where, you know, throughout the business, we say hey, you can have a 20% project, you can go work on something and many of them don't work or have a small impact but then you get things like Gmail getting created out of a 20% project. It's a cultural thing that you foster and encourage people to try things and be open to the possibility that something big is on your hands, right? >> On the cultural front, it sounds like in some cases depending on the enterprise, it's a shift, in some cases it's a cultural journey. The Google on Google story sounds like it could be a blueprint, of course, how do we do this? You've done this but how much is it a blueprint on the technology capitalizing on deep learning capabilities as well as a blueprint for helping organizations on this cultural journey to be actually being able to benefit and profit from this? >> Yeah, I mean that's absolutely right Lisa that these are both really important aspects, that there's a big part of the cultural journey. In order to be an AI-first company, to really reconceive your business around what can happen with machine learning, it's important to be a digital company, right? To have a mindset of making quick decisions and thinking about how data impacts your business and activating in real time. So there's a cultural journey that companies are going through. How do we enable our knowledge workers to do this kind of work, how do we think about our products in a new way, how do we reconceive, think about automation? There's a lot of these aspects that are cultural as well, but I think a big part of it is, you know, it's easy to get overwhelmed for companies but it's like you have pick somewhere, right? What's something you can do, what's a true north, what's an area where you can start to invest and get impact and start the journey, right? Start to do pilots, start to get something going. What we found, something I've found in my career has been when companies get started with the right first project and get some success, they can build on that success and invest more, right? Whereas you know, if you're not experimenting and trying things and moving, you're never going to get there. >> Momentum is key, well Ron, thank you so much for taking some time to stop by theCUBE. I wish we had more time to chat but we appreciate your time. >> No, it's great to be here again. >> See ya. >> We want to thank you for watching theCUBE live from our event, Big Data SV in San Jose. I'm Lisa Martin with Dave Vellante, stick around we'll be back with our wrap shortly. (relaxed electronic jingle)

>> Announcer: Live from San Jose in the heart of Silicon Valley, It's theCUBE covering DataWorks Summit 2017. Brought to you by Hortonworks. >> Welcome back to theCUBE. We are live at the DataWorks Summit on day two. We have had a great day and a half learning a lot about the next generation of big data, machine learning, artificial intelligence, I'm Lisa Martin, and my co-host is George Gilbert. We are next joined by a CUBE alumni, Ron Bodkin, the VP and General Manager of Artificial Intelligence for Teradata. Welcome back to theCUBE! >> Well thank you Lisa, it's nice to be here. >> Yeah, so talk to us about what you're doing right now. Your keynote is tomorrow. >> Ron: Yeah. >> What are you doing, what is Teradata doing in helping customers to be able to leverage artificial intelligence? >> Sure, yeah so as you may know, I ha`ve been involved in this conference and the big data space for a long time as the founding CEO of Think Big Analytics. We were involved in really helping customers in the beginning of big data in the enterprise. And so, we are seeing a very similar trend in the space of artificial intelligence, right? The rapid advances in recent years in deep learning have opened up a lot of opportunity to really create value from all the data the customers have in their data ecosystems, right? So Teradata has a big role to play in having high quality product, Teradata database, analytic ecosystem products such as Hadoop, such as QueryGrid for connecting these systems together, right? So what we're seeing is our customers are very excited by artificial intelligence, but what we're really focused on is how do they get to the value, right? What can they do that's really going to get results, right? And we bring this perspective of having this strong solutions approach inside of Teradata, and so we have Think Big Analytics consulting for data science, we now have been building up experts in deep learning in that organization, working with customers, right? We've brought product functionality so we're innovating around how do we keep pushing the Teradata product family forward with functionality around streaming with listeners. Functionality like the ability to, how do you take GPU and start to think about how can we add that and make that deploy efficiently inside our customer's data center. How can you take advantage of innovation in open source with projects like TensorFlow and Keras becoming important for our customers. So we're seeing is a lot of customers are excited about use cases for artificial intelligence. And tomorrow in the keynote I'm going to touch on a few of them, ranging from applications like preventative maintenance, anti-fraud in banking, to e-commerce recommendations and we're seeing those are some of the examples of use cases where customers are saying hey, there's a lot of value in combining traditional machine learning, wide learning, with deep learning using neural nets to generalize. >> Help us understand if there's an arc where there's the mix of what's repeatable and what's packagable, or what's custom, how that changes over time, or whether it's just by solution. >> Yeah, it's a great question. Right, I mean I think there's a lot of infrastructure that any of these systems need to rest on. So having data infrastructure, having quality data that you can rely on is foundational, and so you need to get that installed and working well as a beginning point. Obviously having repeatable products that manage data with high SLAs and supporting not use production use, but also how do you let data scientists analyze data in a lab and make that work well. So there's that foundational data layer. Then there's the whole integration of the data science into applications, which is critical, analytics, ops, agile ways of making it possible to take the data and build repeatable processes, and those are very horizontal, right? There's some variation, but those work the same in a lot of use cases. At this stage, I'd say, in deep learning, just like in machine learning generally, you still have a lot of horizontal infrastructure. You've got Spark, you've got TensorFlow, those are support use case across many industries. But then you get to the next level, you get specific problems, and there's a lot of nuance. What modeling techniques are going to work, what data sets matter? Okay, you've got time series data and a problem like fraud. What techniques are going to make that work well? And recommendations, you may have a long tail of items to think about recommending. How do you generalize across the long tail where you can't learn. People who use some relatively small thing or go to an obscure website, or buy an obscure product, there's not enough data to say are they likely to buy something else or do something else, but how do you categorize them so you get statistical power to make useful recommendations, right? Those are things that are very specific that there's a lot of repeatability and a specific solution area of. >> This is, when you talk about the data assets that might be specific to a customer and then I guess some third party or syndicated sources. If you have an outcome in mind, but not every customer has the same inventory of data, so how do you square that circle? >> That's a great question. And I really think that's a lot of the opportunity in the enterprise of applying analytics, so this whole summit DataWorks is about hey, the power of your data. What you can get by collecting your data in a well-managed ecosystem and creating value. So, there's always a nuance. It's like what's happening in your customers, what's your business process, what's special about how you interact, what's the core of your business? So I guess my view is that the way anybody that wants to be a winner in this new digital era and have processes that take advantage of artificial intelligence is going to have to use data as a competitive advantage and build on their unique data. So because we see a lot of times enterprises struggle with this. There's a tendency to say hey, can we just buy a package off the shelf SaaS solution and do that? And for context, for things that are the same for everybody in an industry, that's a great choice. But if you're doing that for your core differentiation of your business, you're in deep trouble in this digital era. >> And that's a great place, sorry George, really quickly. That this day and age, every company is a technology company. You mentioned a use case in banking, fraud detection, which is huge. There's tremendous value that can be gleaned from artificial intelligence, and there's also tremendous risk to them. I'm curious, maybe just kind of a generalization. Where are your customers on this journey in terms of have they, are you going out to customers that have already embraced Hadoop and have a significant amount of data that they say, all right, we've got a lot of data here, we need to understand the context. Where are customers in that maturity evolution? >> Sure, so I'd say that we're really fast-approaching the slope of enlightenment for Hadoop, which is to say the enthusiasm of three years ago when people thought Hadoop was going to do everything have kind of waned and there's now more of an appreciation, like there's a lot of value in having a data warehouse for high value curated data for large-scale use. There's a lot of value in having a data lake of fairly raw data that can be used for exploration in the data science arena. So there's emerging, like what is the best architecture for streaming and how do you drive realtime decisions, and that's still very much up in the air. So I'd say that most of our customers are somewhere on that journey, I think that a lot of them have backed off from their initial ambitions that they bought a little too much of the hype of all that Hadoop might do and they're realizing what it is good for, and how they really need to build a complementary ecosystem. The other thing I think is exciting though is I see the conversation is moving from the technology to the use cases. People are a lot more excited about how can we drive value and analytics, and let's work backwards from the analytics value to the data that's going to support it. >> Absolutely. >> So building on that, we talk about sort of what's core and if you can't have something completely repeatable that's going to be core to your sustainable advantage, but if everyone is learning from data, how does a customer achieve a competitive advantage or even sustain a competitive advantage? Is it orchestrating learning that feeds, that informs processes all across the business, or is it just sort of a perpetual Red Queen effect? >> Well, that's a great question. I mean, I think there's a few things, right? There's operational excellence in every discipline, so having good data scientists, having the right data, collecting data, thinking about how do you get network effects, those are all elements. So I would say there's a table-stakes aspect that if you're not doing this, you're in trouble, but then if you are it's like how do you optimize and lift your game and get better at it? So that's an important fact that you see companies that say how do we acquire data? Like one of the things that you see digital disruptors, like a Tesla, doing is changing the game by saying we're changing the way we work with our customers to get access to the data. Think of the difference between every time you buy a Tesla you sign over the rights for them to collect and use all your data, when the traditional auto OEMs are struggling to get access to a lot of the data because they have intermediaries that control the relationship and aren't willing to share. And a similar thing in other industries, you see in consumer packaged goods. You see a lot of manufacturers there are saying how do we get partnerships, how do we get more accurate data? The old models of going out to the Nielsens of the world and saying give us aggregates, and we'll pay you a lot to give us a summary report, that's not working. How do we learn directly in a digital world about our consumers so we can be more relevant? So one of the things is definitely that control of data and access to data, as well as we see a lot of companies saying what are the acquisitions we can make? What are start ups and capabilities that we can plug in, and complement to get data, to get analytic capability that we can then tailor for our needs? >> It's funny that you mention Tesla having more cars on the road, collecting more data than pretty much anyone else at this point. But then there's like Stanford's sort of luminary for AI, Fei-Fei Li. She signed on I think with Toyota, because she said they sell 10 million cars a year, I'm going to be swimming in data compared to anyone else, possible exception of GM or maybe some Chinese manufacturer. So where does, how can you get around scale when using data at scale to inform your models? How would someone like a Tesla be able to get an end run around that? So that's the battle, the disruptor comes in, they're not at scale, but they maybe change the game in some way. Like having different terms that give them access to different kinds of data, more complete data. So that's sort of part of the answer, is to disrupt an industry you need a strategy what's different, right, like in Tesla's case an electric vehicle. And they've been investing in autonomous vehicles with AI, of course everybody in the industry is seeing that and is racing. I mean, Google really started that whole wave going a long time ago as another potential disruptor coming in with their own unique data asset. So, I think it's all about the combination of capabilities that you need. Disruptors often bring a commitment to a different business process, and that's a big challenge is a lot of times the hardest things are the business processes that are entrenched in existing organizations and disruptors can say we're rethinking the way this gets done. I mean, the example of that in ride sharing, the Ubers and Lyfts of the world, deities where they are re-conceiving what does it mean to consume automobile services. Maybe you don't want to own a car at all if you're a millennial, maybe you just want to have access to a car when you need to go somewhere. That's a good example of a disruptive business model change. >> What are some things that are on the intermediate-term horizon that might affect how you go about trying to create a sustainable advantage? And here I mean things like where deep learning might help data scientists with feature engineering so there's less need for, you can make data scientists less of a scarce resource. Or where there's new types of training for models where you need less data? Those sorts of things might disrupt the practice of achieving an advantage with current AI technology. >> You know, that's a great question. So near-term, the ability to be more efficient in data science is a big deal. There's no surprise that there's a big talent gap, big shortage of qualified data scientists in the enterprise and one of the things that's exciting is that deep learning lets you get more information out of the data, so it learns more so that you'd have to do less future engineering. It's not like a magic box you just pour in raw data to deep learning and out comes the answers, so you still need qualified data scientists, but it's a force multiplier. There's less work to do in future engineering, and therefore you get better results. So that's a factor, you're starting to see things like a hyperparameter search where people will create neural networks that search for the best machine learning model, and again get another level of leverage. Now, today doing that is very expensive. The amount of hardware to do that, very few organizations are going to spend millions of dollars to sort of automate the discovery of models, but things are moving so fast. I mean, even just in the last six weeks to have Nvidia and Google both announce significant breakthroughs in hardware. And I just had a colleague forward me a paper for recent research that says hey this technique could produce a hundred times faster results in deep learning convergence. So you've got rapid advances in investment in the hardware and the software. Historically software improvements have outstripped hardware improvements throughout the history of computing, so it's quite reasonable to expect you'll have 10 thousand times the price performance for deep learning in five years. So things that today might cost a hundred million dollars and no one would do, could cost 10 thousand dollars in five years, and suddenly it's a no-brainer to apply a technique like that to automate something instead of hiring more scarce data scientists that are hard to find, and make the data scientists more productive so they're spending more time thinking about what's going on and less time trying out different variations of how do I configure this thing, does this work, does this, right? >> Oh gosh, Ron, we could keep chatting away. Thank you so much for stopping by theCUBE again, we wish you the best of luck in your keynote tomorrow. I think people are going to be very inspired by your passion, your energy, and also the tremendous opportunity that is really sitting right in front of us. >> Thank you, Lisa, it's a very exciting time to be in the data industry, and the emergence of AI and the enterprise, I couldn't be more excited by it. >> Oh, excellent, well your excitement is palpable. We want to thank you for watching. We are live on theCUBE at the DataWorks Summit day 2, #dws17. For my cohost George Gilbert, I'm Lisa Martin, stick around. We'll be right back. (upbeat electronic melody)

(lively music) >> Narrator: Live from Las Vegas, it's the CUBE covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Okay, welcome back everyone. We are here live in Las Vegas, the Mandalay Bay for Oracle's Modern CX conference, hashtag Modern CX. This is the CUBE. I'm John Furrier Silicone Angle. My cost, Peter Burch with us for two days. Our next guest is Ron Corbisier. Owner and CEO of Relationship One. Back again, from last year. It was one of my memorable interviews last year. Welcome back-- >> Ron: Thank you for having me. >> to the cube. We went down and dirty last year. I remember we were having a great conversation about ad tech. If you've taken that video, it's on YouTube and look at it, I guarantee you, it's going to play right into what happened this year. Again, we predicted it. We didn't say AI but we did say we're going to see data really driving. That's what Oracle ended up locking in on daily. >> Yeah, absolutely. Data is going to be the underlying conversation for the next few years. We spoke, a lot, last year about martech stack. Actually, martech and ad tech colliding, coming together. All of that is being fueled by the mass quantities of data that we have as sales and marketing folks out there, to leverage and how do you use it. It's never about, do I have enough data? A lot of times you feel you, almost, have too much. But it's, now how can you use it appropriately? >> We were talking, before we came on camera here about that dynamic of ad tech and marteh collision which we talked about last year. It's interesting. If you just say digital, end-to-end, as a fabric, then you can still talk about these pillars of solutions but they're not silos. If you look at the holistic data approach and say, hey, if we're going to have horizontally scalable data which we want, frictionless less than 150 milliseconds responses they want to promote. You can still do your pillars but be open to data sharing versus here's my silent stack. I do this, I do this, that's shifted and that's what Oracle's main news is here. >> Yeah, absolutely. I think what you're seeing, even in, not only Oracle, that organizational level, people are taking a more holistic view of data that they own and data that they can enrich with external information, right? How does that information, then, fuel all of these other areas within customer experience within the CX world? How do you use that to provide better service? How do you use that information to optimize your sales efforts and from a marketing standpoint, obviously, my background, it's how do we leverage that to optimize our spend, optimize our communication, our orchestration, all of those pieces. It all comes down to that common language of data that we have access to. >> Tell me about the real time aspect cause we teased on it last time and we did talk about how to leverage some of the advertising opportunities and the role of data in real time. That's been a message here from batch to real time. The consumer's in motion all the time depending upon their context. How does real time fit into this? >> Yeah, this is the evolution of what we're seeing in the technology, right? Historically, you've built a campaign. You've, maybe, created some type of journey or persona. You're building content around very specific elements within a life cycle structure. Life cycles are not linear any longer. They never really were but they're, definitely, not now and you have to adapt very quickly. Leverage technology, to say, one of my saying, communicating and what channel but in more in a real time thing. You have to look at what was the last thing that individual did, the activity, all of that. Historically, you haven't had that depth or degree of real time lists. It's been more of a structured candance. That doesn't exist, right? That's not going to exist going forward. That's where things like AI which I always hesitate to use that term because it's the buzz word now of today. But tools that are more of that augmentation of how we do things. Leveraging the power of technology. That's going to change how we orchestrate things and how we communicate. >> I'm just looking at your tweet here. I want to bring this up because you mentioned AI and we were talking about it. Thanks to all who stopped by my MME 17 Modern Marketing Experience 17. A little bit of a jab at the messaging that's cool like that. Session on artificial intelligence. Loved all the support from my fellow modern marketers. What do you mean by that? You make a bold statement. Did you have courage? Did you stand tall? Did you call out AI? What was the conversation there? >> Well I called out the silliness of the term AI. I picked on that the marketers but I picked on the term We, as marketers, I call them the squirell moments that, as marketers, we're on to the next thing. I reviewed the past eight some years of these conferences and what were the topics, right? There were some topics that were transformational topics like how does marketing automation or organizational change or those type of things. Those are things that stick with you. There is things that are more timely things. Like predictive scoring and their tactics. There more things that I use as a marketer or sales person. What I was picking on with AI is that it's the buzz word. It gets you funding. It gets you people in a room for a conference, that's great. But it doesn't do anything by itself. It's really an enabler. It's a pervasive thing that combines machine cycle and data but you have to teach it, you have to incorporate it into your applications. As marketers, ultimately, it's going to change our tool set to make it better. It's more poking fun at the term-- >> We always say AI. I've said it on the CUBE, AI's BS. Although, I'm a software guy. I love AI because it really promotes software that has been very nuance. So, IOT, machine learning, this is very geeky computer science stuff that's super cool. Anything that can take that mainstream in the software world, I'm a big fan of. That being said, I think the augmentation is the real message which is, you can use machine learning, you can use software, use some technical things, to make things better. You said it on our earlier segment this morning which is there's a variety of things that you can automate away. >> The thing that's, and you mentioned earlier, it's the ability that we now have the ability to collect an enormous amount of data, that's relevant and important. And we now have the technology to, actually, do something with that data. But we still have to apply it and there's a lot of change that has to happen. The way AI is different from other systems is that, historically, financial systems, software would deliver and answer. It was highly stylized. It was rarely, a clear correspondence with the real world. We closed the books. How much money did we make? There was an answer and it came from some data structures that were defined within the system. Now we're trying to bring in the real world and have these technologies focus on the real world. And they're giving ranges of possible options. That is new. It's good and it's useful but it does not take the requirement for discretion out of the system. That's why it's the augmentation. >> Ron and I were talking last year about this, Peter and I. I think you're getting a trajectory that, I've been saying for a while and this is developing in real time here on the CUBE and also some of our commentary is the role of software development and DevOps that we've seen in Cloud, is moving into the front lines of business. Meaning their techniques. You're seeing Agile, already, being talked about. You're seeing standing up campaigns. Language, you can go to the Cloud stack and say, building blocks, EC2, S3, Cooper Netties, containers, micro services and apply that to marketing because there's a lot of parallels going on to the characteristics of the infrastructure. Certainly critical infrastructure to enabling infrastructure. It's interesting that you're seeing marketers being more savvy and inadative. What's your thoughts on that, a reaction? >> Yeah, it's the evolution though. If you go back to, we as marketers have been using rules engines, we've been using tools like collaborative filtering. You go back to late 90's, early 2000's when we were building recommendation engines in simple. That's algorithmic stuff, right? No different than we're doing today with pricing rules and all that stuff. The difference it that you now have more power to do it. You have the ability to do it more real time and on the fly. You use far more data. More computing power and more data. Not only your data that you own but data that you leverage from third party to really understand people. You have a wider lens. Historically, you're making recommendations based on what you had in a cart or some other things that people have bought that also had that in the cart, that's different now, right? With this type of technology, this enabling kind of world, you an look at a lot more data points to give you that. The problem is that anything around AI requires a couple of things. It is a dumb system so AI. (laughs) >> Still a computer. >> It's still a computer. Everyone forgets that for it to work, it has to learn. I have some friends who have built marketing tools on top of Watson, for example. It takes hundreds and hundreds of hours for it to start doing something. You have to train it. You have to, not only, give it the data, you have to train it. >> Even the word learning and training is misleading in may respects. At the end of the day it's software but what is new is it's being applied in richer, more complex domains. The recommendation engine used to be just for recommendation. Now we're using those same models and we're combining them and applying them to richer more complex domains. Yet, ideally, the software's not getting more difficult to use. And I think what really makes this compelling, as a software engineer, is that we're doing all this more complexity but we're packing it and making it simpler. >> I think that's the point of where Oracle's going and why they don't call it AI. They're using it more the adaptive. Because they're thinking of it at the micro service level. They're thinking of how can they make these widgets of functionality to better the tools we have. To incorporate it into not make it so a jump forward in our tool set. It's just now, an augmented component of what we do today. >> It's, almost, a stack approach. You got foundational building blocks and at the top is high velocity, highly dynamic apps and you could argue, we were talking that the CMO's going to be an app shop, some day. This banks the question and I'd like to get both of you guys to weigh in on this. Because this is a question that I'd like to get on the record. What is modern marketing these days? Define modern marketing because what we're getting at here is, to your point of the evolution is we've seen this movie before. Is it a replatforming? Is it a building block approach? What is a modern marketer? What is a modern marketer mean? How do you execute that? >> I think it's quick and nimble and adaptive. The whole point of modern marketing is that you're always looking at how you can rethink, how you can optimize, how you can leverage technology to do things. It's not about replacing head count with a machine or a tool or a tech. It's really about how do you leverage that head count more effectively? How can you focus on optimization using those technologies. Modern marketing is, again, probably another buzz word but just like modern sales, modern commerce, all of that. It's really about how do you enable it with that stack do better. >> So, is it fashion or is it like hey, there's a modern marketer over there, look at what he or she is wearing. Or is it more technology based that's got some fundamental foundational shifts that are being worked on or both? >> It's leveraging technology and it's leveraging data more effectively and creatively. It's not being stuck with a prescriptive approach on campaign and orchestration and building. It still requires strategy and all of that but it's really how you approach it. >> So, how you think of it. What's your angle on this? >> That's a great question. And that's why I giggled about it. I think you gave a great answer. The three key precepts of Agile are, iterative, opportunistic and empirical and it's nimble quick and you change. But to me, I'll answer the question this way. Modern marketing focuses on delivering value to the customer not back into the business. It used to be that you would deliver into the business. He'd say, oh, we give you a whole bunch of new leads. We give you a whole bunch of this. If along the way, it created value for the customer, that's okay. But more often that not, it was annoying. As customer's can share their experience and share information about how (mumbles) engaged them, that's amplified. Annoying gets amplified. I think if you focus on are you creating value for the customer, you also end up with the derivative element that you're accelerating leads, they are in the process and where they are in the journey. The way I'd answer it. It's not distinct from yours but the idea of modern marketing focuses on creating value for the customer. The only way you, consisting do that is by being nimble and blah-blah-blah-blah-blah. >> I agree, in the same thing though. A core tenant, if you will, of modern marketing is absolutely. It is the value proposition. It's also making sure you understand the impact of the value of proposition The velocity of the pipeline, the impact on revenue, all of those things right? Because it's all about that value which it has to be, from a customers perspective but you're not doing all of the other pieces. You're not going to justify the spend. You're not going to get all of those together. >> Let me see if I can thread the two points together. Cause what I'm seeing, by listening is, you mentioned, the main thing in my mind was the data. That's different right? You're saying okay, thing differently, talk to the customer and the value to the enterprise value is being created through a different mechanism versus just serving it. >> Not really, not really. The fundamental focus, historically, of marketing has been what are we doing for the business? What are we doing for sales? Now, if we focus on, now you say well no. We have to created value for the customer in every thing we do, then we get permission to do things differently. We get more data out of the customer because the trust is there. We're allowed to bias the customer to the next, best option. >> I'm trying to answer my questions. I can see your point. My point is this, the modern marketer is defined by doing it. The business practices it a little bit differently to achieve the same thing. >> By focusing or creating value they have to do things differently and now they can because technology allows them to do it. >> We saw Time Warner, they weren't using data prior. That's a little different. If you go outward to go in, it's a great value while doing the table stake stuff. >> It's changing strategically thinking different of how you do it. Creating that value proposition's very different and also being able to measure and optimize are you doing it correctly? Is it having impact on the business? Most of my customers are not for profits They, actually, have to show, bottom line an impact. All of that requires data and speed and velocity in which we have to run requires tech. >> They got gestures in the market with customers. They have that touch point. They can leverage that. >> Here's (mumbles) modern marketing is not speeding up and increasing the rate and lowering the cost of doing bad marketing. >> No, no, I mean that's exactly. >> It was marketers point. >> That's right. (laughing) You can spend a lot of money to do bad marketing. >> Let's double down on our bad marketing. Ron, thanks so much for coming on the CUBE again. Thanks for sharing the insights. It's always a pleasure to get down and dirty and peel back the onion on some of these things. Final question for you. What do you expect for the evolution for this next year. >> I think AI's going to be with us for awhile just because it's the new buzz word. We've got a couple cycles on that. >> John: It reminds me of Web 2.0, what is it? >> And that lasted for a few years as well. I think over the next year or so, we're going to see the benefits of that augmentation. We're going to, actually, see some of these micro services as people start fueling some of the tools that we already have. You're also going to see some of that further collision of ad tech and mertech. Cause everything's digital and the impact of what that means for us as marketers. >> I can't wait of the hashtag, marketing native. Cause Cloud Native is coming. Someone's going to make it up, I hope not. >> Peter: You did. >> Ron: You just did. >> Okay, Marketing Native. What does that mean? We'll do a whole segment on that. We'll get Ron to come in. Hey, thanks for coming on the CUBE. >> Thanks for having me. >> Great to see you. I'm John Furrier. Peter Burris here inside the CUBE getting all the action. Straight from the data and sharing it with you. Thank you Ron, for coming on again twice in a row, two years in a row. This is the CUBE. We'll be back with more after this short break. (lively music) >> Narrator: Robert Herjavec. >> People, obviously, know you from Shark Tank. But the Herjavec group has been, really, laser folks in cyber security. >> Cause I, actually, helped bring a product called Check Point to Canada, firewalls, URI filtering, that kind of stuff. >> But you're also an entrepreneur? And you know the business. You've been in software, in the tech business. (mumbles) you get a lot of pitches as entertainment meets business. >> On our show, we're a bubble. We don't get to do a lot of tech.

>> Is about what our youth is, and who we are today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (gentle music) Live from Silicon Valley it's The Cube covering Google Cloud Next '17. (upbeat music) >> Hi, welcome back to The Cube's coverage of Google Next 2017 happening in San Francisco. We're shooting live from our 4,500 square foot here in Palo Alto in the heart of SiliconANGLE. Happy to welcome back to the program, I guess we haven't had him for a little while, but one that we know quite well, Ron Bianchini who's the CEO of Avere. Thanks for joining us. >> Thanks for having me. >> All right, so Ron, for our audience, why don't you give us the update? What's happening with Avere the company itself, and what brings you guys, which I think of you, no offense, you guys are infrastructure company I think of on there. How does cloud fit into the whole discussion you guys are having, and your customers? >> That's great, great segue. So, we started out as an infrastructure company and really what Avere learned to do, our whole IP, actually let me start this way. We started in 2008. Think about where the world was in 2008. People were trying to figure out how to get flash into the data center. And what we did is we came up with a storage system, a NAS server, that knew about two types of storage. It knew that there was very high performance nearby precious flash storage, but that big bulk storage, much cheaper, 1/10 the price disk was a high latency away. And we're able to take that solution, and we started out in the data center, we went after very high performance applications, but showed how you could do it at very low cost. >> It's great, nine years later, I mean, storage is infinite and free, right? >> That's right. The good news for us is the world is very much in the same place. The cost delta between flash and disk has stayed at 10 to one. Both have gotten a lot less expensive, but that difference between the two has stayed. It turns out a solution that knows how to use local high performance flash and store big bulk data at high latency away is an ideal solution for the cloud. And really what we're helping customers now is we're helping customers that are in the data center, in the Enterprise data center, we're helping them adopt cloud. And it works two ways. We support the gateway model where you can keep your compute on-prem and put your big bulk storage in the cloud, and we enable that model without seeing any delta, any change in performance or availability. But we also do the opposite of that, we enable customers to put their compute out in the cloud, and now the big bulk capacity could either stay in the cloud or could be on-prem. So really, I think about us as an enterprise data center play, just like you said, but now we're helping customers take baby steps and slowly adopt the cloud. >> All right, so terms I heard from Google this week, they talked about building the planetary scale computer. They talked about Google Spanner which gives us global, the time synchronization across the globe, the things that those of us with storage backgrounds, it's like, boy these are big, heavy challenges. >> Ron: Big words, right. >> Talking about some of the things, just physics that we try to figure all that. So, how do you guys fit into that? I mean, doesn't GFS, Google File System, solve all these issues for us? >> Right, great. So, one thing to understand is that enterprise storage uses a very different consistency model than Google Storage. So, there's a theorem called the CAP principle, C-A-P. It's consistency, availability, and partition tolerance. And basically what the CAP principle says is, of those three parameters, pick two, because it's impossible to build a storage system that does all three. And really, GFS is all about availability and partition tolerance, because they have big, scalable solutions. What it doesn't give you is exact consistency, and that's what NAS solutions do. NAS solutions are really the high consistency, still partition tolerant because you have big distributed scale systems, but you don't get that high availability piece. And it turns out, in the enterprise there are times when you need high availability storage, that's what you get from Google's file system, but then there are also times you need high consistency storage, that's what you get from an Avere solution. Imagine a bank account where you deposited a million dollars, and then you withdraw a million dollars from two locations, maybe 10 seconds apart. If you don't have a high consistency model, it might be possible to withdraw money from both places. That's what NAS guarantees. >> Ron, I want to get your viewpoint, I'm sure you talk to a lot of your customers. What's their mindset of cloud today, and what are the kinds of conversations that you're having with people stop by your booth at Moscone West. >> I think you said it right, Google is proposing big, scalable, huge features that the customers are trying to get access to, but moving everything from the data center into the cloud all at once to get them is a big, scary step. And so really what we enable people to do is to take baby steps. If you want to move a little bit of your capacity to the clouds, or petabytes of storage in the clouds, like one of our Genomics customers does, you could do that. Your compute and a lot of where they start in storage stays on-prem, but now they're leveraging the cloud for big, scalable capacity. Then we have other customers that want access to the compute and the performance of the scaling you can get. We allow them to get access to that as well. >> Any commentary on, I think about just the trend itself. There's no doubt how big cloud is and how fast it's growing. When we look on the data side Diane Green threw out a number that only 5% of the world's data sits in the public cloud, and that's going to shift. We know that there's a lot of compute-heavy workloads that really started out in those environments, or are leveraging that. So, there's a lot of kind of reasons why we haven't had the data there. We are starting to see some rapid acceleration. What do you see happening in the environment? >> I think that's right. I think the 5% number just gives us a window into how big this cloud movement is, how much is still left to be accomplished. We talk about cloud, cloud, cloud, as if it's already happened, but we're only at the cusp of what's possible. And that's really what we see as this next big phase of the cloud is ingest, is cloud adoption, it's migrating applications and storage into the cloud. >> Yeah, you said what, the future's already here, just unevenly distributed. >> That's right. It hasn't quite made it yet. >> You guys are headquartered in Pittsburgh. >> We are. >> I'm out of Boston. I always joke every time I come out here, it's like okay, I'm going to go spend a week in the Valley and in San Francisco, then I'm going to go back to the real world where I'm not seeing autonomous vehicles in front of me. You guys have some cool autonomous cars driving around Pittsburgh these days? >> Ron: We absolutely do. >> And not everybody is fully cloud-native, serverless and everything else like that. What are you seeing in the marketplace, what's interesting you these days? >> There's no doubt that in the future world all data, all applications, everything will be in the cloud unless there's a very important reason to have it nearby. We think with our Genomics customers, it has to start where the patients are. It has to start on-prem, and then it gets migrated to the cloud. But there's no doubt in the future all compute, especially the big, scalable things that we hear Google talk about will be there. The next five, seven years is all about how we get there from here. >> All right, and Ron, as people look at your company what should we be expecting kind of throughout the rest of this year as we look at you growing your future? >> It's all about making it easier to adopt the cloud. You're going to see higher levels of integration with our cloud partners, Google in particular. We do a lot of work with Google. You're going to see big steps as we move forward and make that integration better. >> You're working with the other cloud players, yes this is a Google show, but we want to talk about the environment. Lots of companies I talk to are like, "Look, yes Google's a player," but I talk to plenty of companies that, "Look, 3/4 of my customers are all on Amazon," and that's where a lot of the market is today. So, what's the breadth of the offering that you have to that? >> It is. We support all the three big cloud players, we support Amazon, Microsoft, and Google. What I will say is the Google team is very much focused on the enterprise, just like Avere is. And that actually helps us a lot. It's really helping us knock down customers and really helping get customers moved into the cloud. >> All right, Ron, I'll give you the final word. Takeaways for the week, anything else you want to share before we wrap. >> You know, it's exactly what you said. The cloud is coming, now it's just a matter of how we get there and watching the big momentum shift. >> I think Eric Schmidt said last year we were like kind of meet you were we are. This year it's, come on. It's, now's the time, we need to go. I think we understand how big cloud is going to be, it's one of the generational shifts that we're all going to be watching, and we're in the thick of it. So, thank you, Ron, for joining us, and we'll be back with lots more coverage here. We've got call-ins and people at the show itself doing dial-ins, pulling people in. Really broad community at this event, so stay tuned for lots more coverage, and you're watching The Cube. (upbeat music) (upbeat music)

>>When Oracle acquired my SQL via the Sun acquisition, nobody really thought the company would put much effort into the platform preferring to focus all the wood behind its leading Oracle database, Arrow pun intended. But two years ago, Oracle surprised many folks by announcing my SQL Heatwave a new database as a service with a massively parallel hybrid Columbia in Mary Mary architecture that brings together transactional and analytic data in a single platform. Welcome to our latest database, power panel on the cube. My name is Dave Ante, and today we're gonna discuss Oracle's MySQL Heat Wave with a who's who of cloud database industry analysts. Holgar Mueller is with Constellation Research. Mark Stammer is the Dragon Slayer and Wikibon contributor. And Ron Westfall is with Fu Chim Research. Gentlemen, welcome back to the Cube. Always a pleasure to have you on. Thanks for having us. Great to be here. >>So we've had a number of of deep dive interviews on the Cube with Nip and Aggarwal. You guys know him? He's a senior vice president of MySQL, Heatwave Development at Oracle. I think you just saw him at Oracle Cloud World and he's come on to describe this is gonna, I'll call it a shock and awe feature additions to to heatwave. You know, the company's clearly putting r and d into the platform and I think at at cloud world we saw like the fifth major release since 2020 when they first announced MySQL heat wave. So just listing a few, they, they got, they taken, brought in analytics machine learning, they got autopilot for machine learning, which is automation onto the basic o l TP functionality of the database. And it's been interesting to watch Oracle's converge database strategy. We've contrasted that amongst ourselves. Love to get your thoughts on Amazon's get the right tool for the right job approach. >>Are they gonna have to change that? You know, Amazon's got the specialized databases, it's just, you know, the both companies are doing well. It just shows there are a lot of ways to, to skin a cat cuz you see some traction in the market in, in both approaches. So today we're gonna focus on the latest heat wave announcements and we're gonna talk about multi-cloud with a native MySQL heat wave implementation, which is available on aws MySQL heat wave for Azure via the Oracle Microsoft interconnect. This kind of cool hybrid action that they got going. Sometimes we call it super cloud. And then we're gonna dive into my SQL Heatwave Lake house, which allows users to process and query data across MyQ databases as heatwave databases, as well as object stores. So, and then we've got, heatwave has been announced on AWS and, and, and Azure, they're available now and Lake House I believe is in beta and I think it's coming out the second half of next year. So again, all of our guests are fresh off of Oracle Cloud world in Las Vegas. So they got the latest scoop. Guys, I'm done talking. Let's get into it. Mark, maybe you could start us off, what's your opinion of my SQL Heatwaves competitive position? When you think about what AWS is doing, you know, Google is, you know, we heard Google Cloud next recently, we heard about all their data innovations. You got, obviously Azure's got a big portfolio, snowflakes doing well in the market. What's your take? >>Well, first let's look at it from the point of view that AWS is the market leader in cloud and cloud services. They own somewhere between 30 to 50% depending on who you read of the market. And then you have Azure as number two and after that it falls off. There's gcp, Google Cloud platform, which is further way down the list and then Oracle and IBM and Alibaba. So when you look at AWS and you and Azure saying, hey, these are the market leaders in the cloud, then you start looking at it and saying, if I am going to provide a service that competes with the service they have, if I can make it available in their cloud, it means that I can be more competitive. And if I'm compelling and compelling means at least twice the performance or functionality or both at half the price, I should be able to gain market share. >>And that's what Oracle's done. They've taken a superior product in my SQL heat wave, which is faster, lower cost does more for a lot less at the end of the day and they make it available to the users of those clouds. You avoid this little thing called egress fees, you avoid the issue of having to migrate from one cloud to another and suddenly you have a very compelling offer. So I look at what Oracle's doing with MyQ and it feels like, I'm gonna use a word term, a flanking maneuver to their competition. They're offering a better service on their platforms. >>All right, so thank you for that. Holger, we've seen this sort of cadence, I sort of referenced it up front a little bit and they sat on MySQL for a decade, then all of a sudden we see this rush of announcements. Why did it take so long? And and more importantly is Oracle, are they developing the right features that cloud database customers are looking for in your view? >>Yeah, great question, but first of all, in your interview you said it's the edit analytics, right? Analytics is kind of like a marketing buzzword. Reports can be analytics, right? The interesting thing, which they did, the first thing they, they, they crossed the chasm between OTP and all up, right? In the same database, right? So major engineering feed very much what customers want and it's all about creating Bellevue for customers, which, which I think is the part why they go into the multi-cloud and why they add these capabilities. And they certainly with the AI capabilities, it's kind of like getting it into an autonomous field, self-driving field now with the lake cost capabilities and meeting customers where they are, like Mark has talked about the e risk costs in the cloud. So that that's a significant advantage, creating value for customers and that's what at the end of the day matters. >>And I believe strongly that long term it's gonna be ones who create better value for customers who will get more of their money From that perspective, why then take them so long? I think it's a great question. I think largely he mentioned the gentleman Nial, it's largely to who leads a product. I used to build products too, so maybe I'm a little fooling myself here, but that made the difference in my view, right? So since he's been charged, he's been building things faster than the rest of the competition, than my SQL space, which in hindsight we thought was a hot and smoking innovation phase. It kind of like was a little self complacent when it comes to the traditional borders of where, where people think, where things are separated between OTP and ola or as an example of adjacent support, right? Structured documents, whereas unstructured documents or databases and all of that has been collapsed and brought together for building a more powerful database for customers. >>So I mean it's certainly, you know, when, when Oracle talks about the competitors, you know, the competitors are in the, I always say they're, if the Oracle talks about you and knows you're doing well, so they talk a lot about aws, talk a little bit about Snowflake, you know, sort of Google, they have partnerships with Azure, but, but in, so I'm presuming that the response in MySQL heatwave was really in, in response to what they were seeing from those big competitors. But then you had Maria DB coming out, you know, the day that that Oracle acquired Sun and, and launching and going after the MySQL base. So it's, I'm, I'm interested and we'll talk about this later and what you guys think AWS and Google and Azure and Snowflake and how they're gonna respond. But, but before I do that, Ron, I want to ask you, you, you, you can get, you know, pretty technical and you've probably seen the benchmarks. >>I know you have Oracle makes a big deal out of it, publishes its benchmarks, makes some transparent on on GI GitHub. Larry Ellison talked about this in his keynote at Cloud World. What are the benchmarks show in general? I mean, when you, when you're new to the market, you gotta have a story like Mark was saying, you gotta be two x you know, the performance at half the cost or you better be or you're not gonna get any market share. So, and, and you know, oftentimes companies don't publish market benchmarks when they're leading. They do it when they, they need to gain share. So what do you make of the benchmarks? Have their, any results that were surprising to you? Have, you know, they been challenged by the competitors. Is it just a bunch of kind of desperate bench marketing to make some noise in the market or you know, are they real? What's your view? >>Well, from my perspective, I think they have the validity. And to your point, I believe that when it comes to competitor responses, that has not really happened. Nobody has like pulled down the information that's on GitHub and said, Oh, here are our price performance results. And they counter oracles. In fact, I think part of the reason why that hasn't happened is that there's the risk if Oracle's coming out and saying, Hey, we can deliver 17 times better query performance using our capabilities versus say, Snowflake when it comes to, you know, the Lakehouse platform and Snowflake turns around and says it's actually only 15 times better during performance, that's not exactly an effective maneuver. And so I think this is really to oracle's credit and I think it's refreshing because these differentiators are significant. We're not talking, you know, like 1.2% differences. We're talking 17 fold differences, we're talking six fold differences depending on, you know, where the spotlight is being shined and so forth. >>And so I think this is actually something that is actually too good to believe initially at first blush. If I'm a cloud database decision maker, I really have to prioritize this. I really would know, pay a lot more attention to this. And that's why I posed the question to Oracle and others like, okay, if these differentiators are so significant, why isn't the needle moving a bit more? And it's for, you know, some of the usual reasons. One is really deep discounting coming from, you know, the other players that's really kind of, you know, marketing 1 0 1, this is something you need to do when there's a real competitive threat to keep, you know, a customer in your own customer base. Plus there is the usual fear and uncertainty about moving from one platform to another. But I think, you know, the traction, the momentum is, is shifting an Oracle's favor. I think we saw that in the Q1 efforts, for example, where Oracle cloud grew 44% and that it generated, you know, 4.8 billion and revenue if I recall correctly. And so, so all these are demonstrating that's Oracle is making, I think many of the right moves, publishing these figures for anybody to look at from their own perspective is something that is, I think, good for the market and I think it's just gonna continue to pay dividends for Oracle down the horizon as you know, competition intens plots. So if I were in, >>Dave, can I, Dave, can I interject something and, and what Ron just said there? Yeah, please go ahead. A couple things here, one discounting, which is a common practice when you have a real threat, as Ron pointed out, isn't going to help much in this situation simply because you can't discount to the point where you improve your performance and the performance is a huge differentiator. You may be able to get your price down, but the problem that most of them have is they don't have an integrated product service. They don't have an integrated O L T P O L A P M L N data lake. Even if you cut out two of them, they don't have any of them integrated. They have multiple services that are required separate integration and that can't be overcome with discounting. And the, they, you have to pay for each one of these. And oh, by the way, as you grow, the discounts go away. So that's a, it's a minor important detail. >>So, so that's a TCO question mark, right? And I know you look at this a lot, if I had that kind of price performance advantage, I would be pounding tco, especially if I need two separate databases to do the job. That one can do, that's gonna be, the TCO numbers are gonna be off the chart or maybe down the chart, which you want. Have you looked at this and how does it compare with, you know, the big cloud guys, for example, >>I've looked at it in depth, in fact, I'm working on another TCO on this arena, but you can find it on Wiki bod in which I compared TCO for MySEQ Heat wave versus Aurora plus Redshift plus ML plus Blue. I've compared it against gcps services, Azure services, Snowflake with other services. And there's just no comparison. The, the TCO differences are huge. More importantly, thefor, the, the TCO per performance is huge. We're talking in some cases multiple orders of magnitude, but at least an order of magnitude difference. So discounting isn't gonna help you much at the end of the day, it's only going to lower your cost a little, but it doesn't improve the automation, it doesn't improve the performance, it doesn't improve the time to insight, it doesn't improve all those things that you want out of a database or multiple databases because you >>Can't discount yourself to a higher value proposition. >>So what about, I wonder ho if you could chime in on the developer angle. You, you followed that, that market. How do these innovations from heatwave, I think you used the term developer velocity. I've heard you used that before. Yeah, I mean, look, Oracle owns Java, okay, so it, it's, you know, most popular, you know, programming language in the world, blah, blah blah. But it does it have the, the minds and hearts of, of developers and does, where does heatwave fit into that equation? >>I think heatwave is gaining quickly mindshare on the developer side, right? It's not the traditional no sequel database which grew up, there's a traditional mistrust of oracles to developers to what was happening to open source when gets acquired. Like in the case of Oracle versus Java and where my sql, right? And, but we know it's not a good competitive strategy to, to bank on Oracle screwing up because it hasn't worked not on Java known my sequel, right? And for developers, it's, once you get to know a technology product and you can do more, it becomes kind of like a Swiss army knife and you can build more use case, you can build more powerful applications. That's super, super important because you don't have to get certified in multiple databases. You, you are fast at getting things done, you achieve fire, develop velocity, and the managers are happy because they don't have to license more things, send you to more trainings, have more risk of something not being delivered, right? >>So it's really the, we see the suite where this best of breed play happening here, which in general was happening before already with Oracle's flagship database. Whereas those Amazon as an example, right? And now the interesting thing is every step away Oracle was always a one database company that can be only one and they're now generally talking about heat web and that two database company with different market spaces, but same value proposition of integrating more things very, very quickly to have a universal database that I call, they call the converge database for all the needs of an enterprise to run certain application use cases. And that's what's attractive to developers. >>It's, it's ironic isn't it? I mean I, you know, the rumor was the TK Thomas Curian left Oracle cuz he wanted to put Oracle database on other clouds and other places. And maybe that was the rift. Maybe there was, I'm sure there was other things, but, but Oracle clearly is now trying to expand its Tam Ron with, with heatwave into aws, into Azure. How do you think Oracle's gonna do, you were at a cloud world, what was the sentiment from customers and the independent analyst? Is this just Oracle trying to screw with the competition, create a little diversion? Or is this, you know, serious business for Oracle? What do you think? >>No, I think it has lakes. I think it's definitely, again, attriting to Oracle's overall ability to differentiate not only my SQL heat wave, but its overall portfolio. And I think the fact that they do have the alliance with the Azure in place, that this is definitely demonstrating their commitment to meeting the multi-cloud needs of its customers as well as what we pointed to in terms of the fact that they're now offering, you know, MySQL capabilities within AWS natively and that it can now perform AWS's own offering. And I think this is all demonstrating that Oracle is, you know, not letting up, they're not resting on its laurels. That's clearly we are living in a multi-cloud world, so why not just make it more easy for customers to be able to use cloud databases according to their own specific, specific needs. And I think, you know, to holder's point, I think that definitely lines with being able to bring on more application developers to leverage these capabilities. >>I think one important announcement that's related to all this was the JSON relational duality capabilities where now it's a lot easier for application developers to use a language that they're very familiar with a JS O and not have to worry about going into relational databases to store their J S O N application coding. So this is, I think an example of the innovation that's enhancing the overall Oracle portfolio and certainly all the work with machine learning is definitely paying dividends as well. And as a result, I see Oracle continue to make these inroads that we pointed to. But I agree with Mark, you know, the short term discounting is just a stall tag. This is not denying the fact that Oracle is being able to not only deliver price performance differentiators that are dramatic, but also meeting a wide range of needs for customers out there that aren't just limited device performance consideration. >>Being able to support multi-cloud according to customer needs. Being able to reach out to the application developer community and address a very specific challenge that has plagued them for many years now. So bring it all together. Yeah, I see this as just enabling Oracles who ring true with customers. That the customers that were there were basically all of them, even though not all of them are going to be saying the same things, they're all basically saying positive feedback. And likewise, I think the analyst community is seeing this. It's always refreshing to be able to talk to customers directly and at Oracle cloud there was a litany of them and so this is just a difference maker as well as being able to talk to strategic partners. The nvidia, I think partnerships also testament to Oracle's ongoing ability to, you know, make the ecosystem more user friendly for the customers out there. >>Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able to be best of breed. That's the kind of surprising thing that I'm hearing about, about heatwave. I want to, I want to talk about Lake House because when I think of Lake House, I think data bricks, and to my knowledge data bricks hasn't been in the sites of Oracle yet. Maybe they're next, but, but Oracle claims that MySQL, heatwave, Lakehouse is a breakthrough in terms of capacity and performance. Mark, what are your thoughts on that? Can you double click on, on Lakehouse Oracle's claims for things like query performance and data loading? What does it mean for the market? Is Oracle really leading in, in the lake house competitive landscape? What are your thoughts? >>Well, but name in the game is what are the problems you're solving for the customer? More importantly, are those problems urgent or important? If they're urgent, customers wanna solve 'em. Now if they're important, they might get around to them. So you look at what they're doing with Lake House or previous to that machine learning or previous to that automation or previous to that O L A with O ltp and they're merging all this capability together. If you look at Snowflake or data bricks, they're tacking one problem. You look at MyQ heat wave, they're tacking multiple problems. So when you say, yeah, their queries are much better against the lake house in combination with other analytics in combination with O ltp and the fact that there are no ETLs. So you're getting all this done in real time. So it's, it's doing the query cross, cross everything in real time. >>You're solving multiple user and developer problems, you're increasing their ability to get insight faster, you're having shorter response times. So yeah, they really are solving urgent problems for customers. And by putting it where the customer lives, this is the brilliance of actually being multicloud. And I know I'm backing up here a second, but by making it work in AWS and Azure where people already live, where they already have applications, what they're saying is, we're bringing it to you. You don't have to come to us to get these, these benefits, this value overall, I think it's a brilliant strategy. I give Nip and Argo wallet a huge, huge kudos for what he's doing there. So yes, what they're doing with the lake house is going to put notice on data bricks and Snowflake and everyone else for that matter. Well >>Those are guys that whole ago you, you and I have talked about this. Those are, those are the guys that are doing sort of the best of breed. You know, they're really focused and they, you know, tend to do well at least out of the gate. Now you got Oracle's converged philosophy, obviously with Oracle database. We've seen that now it's kicking in gear with, with heatwave, you know, this whole thing of sweets versus best of breed. I mean the long term, you know, customers tend to migrate towards suite, but the new shiny toy tends to get the growth. How do you think this is gonna play out in cloud database? >>Well, it's the forever never ending story, right? And in software right suite, whereas best of breed and so far in the long run suites have always won, right? So, and sometimes they struggle again because the inherent problem of sweets is you build something larger, it has more complexity and that means your cycles to get everything working together to integrate the test that roll it out, certify whatever it is, takes you longer, right? And that's not the case. It's a fascinating part of what the effort around my SQL heat wave is that the team is out executing the previous best of breed data, bringing us something together. Now if they can maintain that pace, that's something to to, to be seen. But it, the strategy, like what Mark was saying, bring the software to the data is of course interesting and unique and totally an Oracle issue in the past, right? >>Yeah. But it had to be in your database on oci. And but at, that's an interesting part. The interesting thing on the Lake health side is, right, there's three key benefits of a lakehouse. The first one is better reporting analytics, bring more rich information together, like make the, the, the case for silicon angle, right? We want to see engagements for this video, we want to know what's happening. That's a mixed transactional video media use case, right? Typical Lakehouse use case. The next one is to build more rich applications, transactional applications which have video and these elements in there, which are the engaging one. And the third one, and that's where I'm a little critical and concerned, is it's really the base platform for artificial intelligence, right? To run deep learning to run things automatically because they have all the data in one place can create in one way. >>And that's where Oracle, I know that Ron talked about Invidia for a moment, but that's where Oracle doesn't have the strongest best story. Nonetheless, the two other main use cases of the lake house are very strong, very well only concern is four 50 terabyte sounds long. It's an arbitrary limitation. Yeah, sounds as big. So for the start, and it's the first word, they can make that bigger. You don't want your lake house to be limited and the terabyte sizes or any even petabyte size because you want to have the certainty. I can put everything in there that I think it might be relevant without knowing what questions to ask and query those questions. >>Yeah. And you know, in the early days of no schema on right, it just became a mess. But now technology has evolved to allow us to actually get more value out of that data. Data lake. Data swamp is, you know, not much more, more, more, more logical. But, and I want to get in, in a moment, I want to come back to how you think the competitors are gonna respond. Are they gonna have to sort of do a more of a converged approach? AWS in particular? But before I do, Ron, I want to ask you a question about autopilot because I heard Larry Ellison's keynote and he was talking about how, you know, most security issues are human errors with autonomy and autonomous database and things like autopilot. We take care of that. It's like autonomous vehicles, they're gonna be safer. And I went, well maybe, maybe someday. So Oracle really tries to emphasize this, that every time you see an announcement from Oracle, they talk about new, you know, autonomous capabilities. It, how legit is it? Do people care? What about, you know, what's new for heatwave Lakehouse? How much of a differentiator, Ron, do you really think autopilot is in this cloud database space? >>Yeah, I think it will definitely enhance the overall proposition. I don't think people are gonna buy, you know, lake house exclusively cause of autopilot capabilities, but when they look at the overall picture, I think it will be an added capability bonus to Oracle's benefit. And yeah, I think it's kind of one of these age old questions, how much do you automate and what is the bounce to strike? And I think we all understand with the automatic car, autonomous car analogy that there are limitations to being able to use that. However, I think it's a tool that basically every organization out there needs to at least have or at least evaluate because it goes to the point of it helps with ease of use, it helps make automation more balanced in terms of, you know, being able to test, all right, let's automate this process and see if it works well, then we can go on and switch on on autopilot for other processes. >>And then, you know, that allows, for example, the specialists to spend more time on business use cases versus, you know, manual maintenance of, of the cloud database and so forth. So I think that actually is a, a legitimate value proposition. I think it's just gonna be a case by case basis. Some organizations are gonna be more aggressive with putting automation throughout their processes throughout their organization. Others are gonna be more cautious. But it's gonna be, again, something that will help the overall Oracle proposition. And something that I think will be used with caution by many organizations, but other organizations are gonna like, hey, great, this is something that is really answering a real problem. And that is just easing the use of these databases, but also being able to better handle the automation capabilities and benefits that come with it without having, you know, a major screwup happened and the process of transitioning to more automated capabilities. >>Now, I didn't attend cloud world, it's just too many red eyes, you know, recently, so I passed. But one of the things I like to do at those events is talk to customers, you know, in the spirit of the truth, you know, they, you know, you'd have the hallway, you know, track and to talk to customers and they say, Hey, you know, here's the good, the bad and the ugly. So did you guys, did you talk to any customers my SQL Heatwave customers at, at cloud world? And and what did you learn? I don't know, Mark, did you, did you have any luck and, and having some, some private conversations? >>Yeah, I had quite a few private conversations. The one thing before I get to that, I want disagree with one point Ron made, I do believe there are customers out there buying the heat wave service, the MySEQ heat wave server service because of autopilot. Because autopilot is really revolutionary in many ways in the sense for the MySEQ developer in that it, it auto provisions, it auto parallel loads, IT auto data places it auto shape predictions. It can tell you what machine learning models are going to tell you, gonna give you your best results. And, and candidly, I've yet to meet a DBA who didn't wanna give up pedantic tasks that are pain in the kahoo, which they'd rather not do and if it's long as it was done right for them. So yes, I do think people are buying it because of autopilot and that's based on some of the conversations I had with customers at Oracle Cloud World. >>In fact, it was like, yeah, that's great, yeah, we get fantastic performance, but this really makes my life easier and I've yet to meet a DBA who didn't want to make their life easier. And it does. So yeah, I've talked to a few of them. They were excited. I asked them if they ran into any bugs, were there any difficulties in moving to it? And the answer was no. In both cases, it's interesting to note, my sequel is the most popular database on the planet. Well, some will argue that it's neck and neck with SQL Server, but if you add in Mariah DB and ProCon db, which are forks of MySQL, then yeah, by far and away it's the most popular. And as a result of that, everybody for the most part has typically a my sequel database somewhere in their organization. So this is a brilliant situation for anybody going after MyQ, but especially for heat wave. And the customers I talk to love it. I didn't find anybody complaining about it. And >>What about the migration? We talked about TCO earlier. Did your t does your TCO analysis include the migration cost or do you kind of conveniently leave that out or what? >>Well, when you look at migration costs, there are different kinds of migration costs. By the way, the worst job in the data center is the data migration manager. Forget it, no other job is as bad as that one. You get no attaboys for doing it. Right? And then when you screw up, oh boy. So in real terms, anything that can limit data migration is a good thing. And when you look at Data Lake, that limits data migration. So if you're already a MySEQ user, this is a pure MySQL as far as you're concerned. It's just a, a simple transition from one to the other. You may wanna make sure nothing broke and every you, all your tables are correct and your schema's, okay, but it's all the same. So it's a simple migration. So it's pretty much a non-event, right? When you migrate data from an O LTP to an O L A P, that's an ETL and that's gonna take time. >>But you don't have to do that with my SQL heat wave. So that's gone when you start talking about machine learning, again, you may have an etl, you may not, depending on the circumstances, but again, with my SQL heat wave, you don't, and you don't have duplicate storage, you don't have to copy it from one storage container to another to be able to be used in a different database, which by the way, ultimately adds much more cost than just the other service. So yeah, I looked at the migration and again, the users I talked to said it was a non-event. It was literally moving from one physical machine to another. If they had a new version of MySEQ running on something else and just wanted to migrate it over or just hook it up or just connect it to the data, it worked just fine. >>Okay, so every day it sounds like you guys feel, and we've certainly heard this, my colleague David Foyer, the semi-retired David Foyer was always very high on heatwave. So I think you knows got some real legitimacy here coming from a standing start, but I wanna talk about the competition, how they're likely to respond. I mean, if your AWS and you got heatwave is now in your cloud, so there's some good aspects of that. The database guys might not like that, but the infrastructure guys probably love it. Hey, more ways to sell, you know, EC two and graviton, but you're gonna, the database guys in AWS are gonna respond. They're gonna say, Hey, we got Redshift, we got aqua. What's your thoughts on, on not only how that's gonna resonate with customers, but I'm interested in what you guys think will a, I never say never about aws, you know, and are they gonna try to build, in your view a converged Oola and o LTP database? You know, Snowflake is taking an ecosystem approach. They've added in transactional capabilities to the portfolio so they're not standing still. What do you guys see in the competitive landscape in that regard going forward? Maybe Holger, you could start us off and anybody else who wants to can chime in, >>Happy to, you mentioned Snowflake last, we'll start there. I think Snowflake is imitating that strategy, right? That building out original data warehouse and the clouds tasking project to really proposition to have other data available there because AI is relevant for everybody. Ultimately people keep data in the cloud for ultimately running ai. So you see the same suite kind of like level strategy, it's gonna be a little harder because of the original positioning. How much would people know that you're doing other stuff? And I just, as a former developer manager of developers, I just don't see the speed at the moment happening at Snowflake to become really competitive to Oracle. On the flip side, putting my Oracle hat on for a moment back to you, Mark and Iran, right? What could Oracle still add? Because the, the big big things, right? The traditional chasms in the database world, they have built everything, right? >>So I, I really scratched my hat and gave Nipon a hard time at Cloud world say like, what could you be building? Destiny was very conservative. Let's get the Lakehouse thing done, it's gonna spring next year, right? And the AWS is really hard because AWS value proposition is these small innovation teams, right? That they build two pizza teams, which can be fit by two pizzas, not large teams, right? And you need suites to large teams to build these suites with lots of functionalities to make sure they work together. They're consistent, they have the same UX on the administration side, they can consume the same way, they have the same API registry, can't even stop going where the synergy comes to play over suite. So, so it's gonna be really, really hard for them to change that. But AWS super pragmatic. They're always by themselves that they'll listen to customers if they learn from customers suite as a proposition. I would not be surprised if AWS trying to bring things closer together, being morely together. >>Yeah. Well how about, can we talk about multicloud if, if, again, Oracle is very on on Oracle as you said before, but let's look forward, you know, half a year or a year. What do you think about Oracle's moves in, in multicloud in terms of what kind of penetration they're gonna have in the marketplace? You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at the, the Microsoft Azure deal. I think that's really interesting. I've, I've called it a little bit of early days of a super cloud. What impact do you think this is gonna have on, on the marketplace? But, but both. And think about it within Oracle's customer base, I have no doubt they'll do great there. But what about beyond its existing install base? What do you guys think? >>Ryan, do you wanna jump on that? Go ahead. Go ahead Ryan. No, no, no, >>That's an excellent point. I think it aligns with what we've been talking about in terms of Lakehouse. I think Lake House will enable Oracle to pull more customers, more bicycle customers onto the Oracle platforms. And I think we're seeing all the signs pointing toward Oracle being able to make more inroads into the overall market. And that includes garnishing customers from the leaders in, in other words, because they are, you know, coming in as a innovator, a an alternative to, you know, the AWS proposition, the Google cloud proposition that they have less to lose and there's a result they can really drive the multi-cloud messaging to resonate with not only their existing customers, but also to be able to, to that question, Dave's posing actually garnish customers onto their platform. And, and that includes naturally my sequel but also OCI and so forth. So that's how I'm seeing this playing out. I think, you know, again, Oracle's reporting is indicating that, and I think what we saw, Oracle Cloud world is definitely validating the idea that Oracle can make more waves in the overall market in this regard. >>You know, I, I've floated this idea of Super cloud, it's kind of tongue in cheek, but, but there, I think there is some merit to it in terms of building on top of hyperscale infrastructure and abstracting some of the, that complexity. And one of the things that I'm most interested in is industry clouds and an Oracle acquisition of Cerner. I was struck by Larry Ellison's keynote, it was like, I don't know, an hour and a half and an hour and 15 minutes was focused on healthcare transformation. Well, >>So vertical, >>Right? And so, yeah, so you got Oracle's, you know, got some industry chops and you, and then you think about what they're building with, with not only oci, but then you got, you know, MyQ, you can now run in dedicated regions. You got ADB on on Exadata cloud to customer, you can put that OnPrem in in your data center and you look at what the other hyperscalers are, are doing. I I say other hyperscalers, I've always said Oracle's not really a hyperscaler, but they got a cloud so they're in the game. But you can't get, you know, big query OnPrem, you look at outposts, it's very limited in terms of, you know, the database support and again, that that will will evolve. But now you got Oracle's got, they announced Alloy, we can white label their cloud. So I'm interested in what you guys think about these moves, especially the industry cloud. We see, you know, Walmart is doing sort of their own cloud. You got Goldman Sachs doing a cloud. Do you, you guys, what do you think about that and what role does Oracle play? Any thoughts? >>Yeah, let me lemme jump on that for a moment. Now, especially with the MyQ, by making that available in multiple clouds, what they're doing is this follows the philosophy they've had the past with doing cloud, a customer taking the application and the data and putting it where the customer lives. If it's on premise, it's on premise. If it's in the cloud, it's in the cloud. By making the mice equal heat wave, essentially a plug compatible with any other mice equal as far as your, your database is concern and then giving you that integration with O L A P and ML and Data Lake and everything else, then what you've got is a compelling offering. You're making it easier for the customer to use. So I look the difference between MyQ and the Oracle database, MyQ is going to capture market more market share for them. >>You're not gonna find a lot of new users for the Oracle debate database. Yeah, there are always gonna be new users, don't get me wrong, but it's not gonna be a huge growth. Whereas my SQL heatwave is probably gonna be a major growth engine for Oracle going forward. Not just in their own cloud, but in AWS and in Azure and on premise over time that eventually it'll get there. It's not there now, but it will, they're doing the right thing on that basis. They're taking the services and when you talk about multicloud and making them available where the customer wants them, not forcing them to go where you want them, if that makes sense. And as far as where they're going in the future, I think they're gonna take a page outta what they've done with the Oracle database. They'll add things like JSON and XML and time series and spatial over time they'll make it a, a complete converged database like they did with the Oracle database. The difference being Oracle database will scale bigger and will have more transactions and be somewhat faster. And my SQL will be, for anyone who's not on the Oracle database, they're, they're not stupid, that's for sure. >>They've done Jason already. Right. But I give you that they could add graph and time series, right. Since eat with, Right, Right. Yeah, that's something absolutely right. That's, that's >>A sort of a logical move, right? >>Right. But that's, that's some kid ourselves, right? I mean has worked in Oracle's favor, right? 10 x 20 x, the amount of r and d, which is in the MyQ space, has been poured at trying to snatch workloads away from Oracle by starting with IBM 30 years ago, 20 years ago, Microsoft and, and, and, and didn't work, right? Database applications are extremely sticky when they run, you don't want to touch SIM and grow them, right? So that doesn't mean that heat phase is not an attractive offering, but it will be net new things, right? And what works in my SQL heat wave heat phases favor a little bit is it's not the massive enterprise applications which have like we the nails like, like you might be only running 30% or Oracle, but the connections and the interfaces into that is, is like 70, 80% of your enterprise. >>You take it out and it's like the spaghetti ball where you say, ah, no I really don't, don't want to do all that. Right? You don't, don't have that massive part with the equals heat phase sequel kind of like database which are more smaller tactical in comparison, but still I, I don't see them taking so much share. They will be growing because of a attractive value proposition quickly on the, the multi-cloud, right? I think it's not really multi-cloud. If you give people the chance to run your offering on different clouds, right? You can run it there. The multi-cloud advantages when the Uber offering comes out, which allows you to do things across those installations, right? I can migrate data, I can create data across something like Google has done with B query Omni, I can run predictive models or even make iron models in different place and distribute them, right? And Oracle is paving the road for that, but being available on these clouds. But the multi-cloud capability of database which knows I'm running on different clouds that is still yet to be built there. >>Yeah. And >>That the problem with >>That, that's the super cloud concept that I flowed and I I've always said kinda snowflake with a single global instance is sort of, you know, headed in that direction and maybe has a league. What's the issue with that mark? >>Yeah, the problem with the, with that version, the multi-cloud is clouds to charge egress fees. As long as they charge egress fees to move data between clouds, it's gonna make it very difficult to do a real multi-cloud implementation. Even Snowflake, which runs multi-cloud, has to pass out on the egress fees of their customer when data moves between clouds. And that's really expensive. I mean there, there is one customer I talked to who is beta testing for them, the MySQL heatwave and aws. The only reason they didn't want to do that until it was running on AWS is the egress fees were so great to move it to OCI that they couldn't afford it. Yeah. Egress fees are the big issue but, >>But Mark the, the point might be you might wanna root query and only get the results set back, right was much more tinier, which been the answer before for low latency between the class A problem, which we sometimes still have but mostly don't have. Right? And I think in general this with fees coming down based on the Oracle general E with fee move and it's very hard to justify those, right? But, but it's, it's not about moving data as a multi-cloud high value use case. It's about doing intelligent things with that data, right? Putting into other places, replicating it, what I'm saying the same thing what you said before, running remote queries on that, analyzing it, running AI on it, running AI models on that. That's the interesting thing. Cross administered in the same way. Taking things out, making sure compliance happens. Making sure when Ron says I don't want to be American anymore, I want to be in the European cloud that is gets migrated, right? So tho those are the interesting value use case which are really, really hard for enterprise to program hand by hand by developers and they would love to have out of the box and that's yet the innovation to come to, we have to come to see. But the first step to get there is that your software runs in multiple clouds and that's what Oracle's doing so well with my SQL >>Guys. Amazing. >>Go ahead. Yeah. >>Yeah. >>For example, >>Amazing amount of data knowledge and, and brain power in this market. Guys, I really want to thank you for coming on to the cube. Ron Holger. Mark, always a pleasure to have you on. Really appreciate your time. >>Well all the last names we're very happy for Romanic last and moderator. Thanks Dave for moderating us. All right, >>We'll see. We'll see you guys around. Safe travels to all and thank you for watching this power panel, The Truth About My SQL Heat Wave on the cube. Your leader in enterprise and emerging tech coverage.

>>Hello, Ron. Welcome to AWS reinforce here. Live in Boston, Massachusetts. I'm John feer, host of the cube. We're here at Carl Matson. CSO at no name security. That's right, no name security, no name securities, also a featured partner at season two, episode four of our upcoming eightish startup showcase security themed event happening in the end of August. Look for that at this URL, AWS startups.com, but we're here at reinforc Carl. Thanks for joining me today. Good to see >>You. Thank you for having us, John. >>So this show security, it's not as packed as the eight of us summit was in New York. That just happened two weeks ago, 19,000 people here, more focused crowd. Lot at stake operations are under pressure. The security teams are under a lot of pressure as apps drive more and more cloud native goodness. As we say, the gen outta the bottle, people want more cloud native apps. Absolutely. That's put a lot of pressure on the ops teams and the security teams. That's the core theme here. How do you see it happening? How do you see this unfolding? Do you agree with that? And how would you describe today's event? >>Well, I think you're, you're spot on. I think the, the future of it is increasingly becoming the story of developers and APIs becoming the hero, the hero of digital transformation, the hero of public cloud adoption. And so this is really becoming much more of a developer-centric discussion about where we're moving our applications and, and where they're hosted, but also how they're designed. And so there's a lot of energy around that right now around focusing security capabilities that really appeal to the sensibilities and the needs of, of modern applications. >>I want to get to know name security a second, and let you explain what you guys do. Then I'll have a few good questions for you to kind of unpack that. But the thing about the structural change that's happened with cloud computing is kind of, and kind of in the past now, DevOps cloud scale, large scale data, the rise of the super cloud companies like snowflake capital, one there's examples of companies that don't even have CapEx investments building on the cloud. And in a way, our, the success of DevOps has created another sea of problems and opportunities that is more complexity as the benefits of DevOps and open source, continue to rise, agile applications that have value can be quantified. There's no doubt with the pandemic that's value there. Yeah. Now you have the collateral damage of success, a new opportunity to abstract away, more complexity to go to the next level. Yep. This is a big industry thing. What are the key opportunities and areas as this new environment, cuz that's the structural change happening now? Yep. What's the key dynamics right now. That's driving this new innovation and what are some of those problem areas that are gonna be abstracted away that you see? >>Well, the, the first thing I I'd suggest is is to, to lean into those structural changes and take advantage of them where they become an advantage for governance, security risk. A perfect example is automation. So what we have in microservices, applications and cloud infrastructures and new workloads like snowflake is we have workloads that want to talk, they want to be interoperated with. And because of that, we can develop new capabilities that take advantage of those of those capabilities. And, and so we want to have on our, on our security teams in particular is we wanna have the talent and the tools that are leaning into and capitalizing on exactly those strengths of, of the underlying capabilities that you're securing rather than to counter that trend, that the, the security professional needs to get ahead of it and, and be a part of that discussion with the developers and the infrastructure teams. >>And, and again, the tructure exchange could kill you too as well. I mean, some benefits, you know, data's the new oil, but end of the day it could be a problematic thing. Sure. All right. So let's get that. No names talk about the company. What you guys do, you have an interesting approach, heavily funded, good success, good buzz. What's going on with the company? Give the quick overview. >>Well, we're a company that's just under three years old and, and what APIs go back, of course, a, a decade or more. We've all been using APIs for a long time, but what's really shifted over the last couple of years is the, is the transition of, of applications and especially business critical processes to now writing on top of public facing APIs where API used to be the behind the scenes interconnection between systems. Now those APIs are exposed to their public facing. And so what we focus on as a company is looking at that API as a, as a software endpoint, just like any other endpoint in our environments that we're historically used to. That's an endpoint that needs full life cycle protection. It needs to be designed well secure coding standards for, for APIs and tested. Well, it also has to be deployed into production configured well and operated well. And when there's a misuse or an attack in progress, we have to be able to protect and identify the, the risks to that API in production. So when you add that up, we're looking at a full life cycle view of the API, and it's really it's about time because the API is not new yet. We're just starting to now to apply like actual discipline and, and practices that help keep that API secure. >>Yeah. It's interesting. It's like what I was saying earlier. They're not going anywhere. They're not going, they're the underpinning, the underlying benefit of cloud yes. Cloud native. So it's just more, more operational stability, scale growth. What are some of the challenges that, that are there and what do you guys do particularly to solve it? You're protecting it. Are you scaling it? What specifically are you guys addressing? >>But sure. So I think API security, even as a, as a discipline is not new, but I think the, the, the traditional look at API security looks only at, at the quality of the source code. Certainly quality of the source code of API is, is sort of step one. But what we see in, in practices is most of the publicly known API compromises, they weren't because of bad source code that they because of network misconfiguration or the misapplication of policy during runtime. So a great example of that would be developer designs, an API designs. It in such a way that Gar that, that enforces authentication to be well designed and strong. And then in production, those authentication policies are not applied at a gateway. So what we add to the, we add to the, to the conversation on API security is helping fill all those little gaps from design and testing through production. So we can see all of the moving parts in the, the context of the API to see how it can be exploited and, and how we can reduce risk in independent of. >>So this is really about hardening the infrastructure yep. Around cuz the developer did their job in that example. Yep. So academic API is well formed working, but something didn't happen on the network or gateway box or app, you know, some sort of network configuration or middleware configuration. >>Absolutely. So in our, in our platform, we, we essentially have sort of three functional areas. There's API code testing, and then we call next is posture management posture. Management's a real thing. If we're talking about a laptop we're talking about, is it up to date with patches? Is it configured? Well, is it secure network connectivity? The same is true with APIs. They have to be managed and cared for by somebody who's looking at their posture on the network. And then of course then there's threat defense and run time protection. So that posture management piece, that's really a new entrant into the discussion on API security. And that's really where we started as a company is focusing on that sort of acute gap of information, >>Posture, protection, >>Posture, and protection. Absolutely >>Define that. What does that, what does posture posture protection mean? How would you define that? >>Sure. I think it's a, it's identifying the inherent risk exposure of an API. Great example of that would be an API that is addressable by internal systems and external systems at the same time. Almost always. That is, that is an error. It's a mistake that's been made so well by, by identifying that misconfiguration of posture, then we can, we can protect that API by restricting the internet connectivity externally. That's just a great example of posture. We see almost every organization has that and it's never intended. >>Great, great, great call out. Thanks for sharing. All right, so I'm a customer. Yep. Okay. Look at, Hey, I already got an app firewall API gateway. Why do I need another tool? >>Well, first of all, web application firewalls are sort of essential parts of a security ecosystem. An API management gateway is usually the brain of an API economy. What we do is we, we augment those platforms with what they don't do well and also when they're not used. So for example, in, in any environment, we, we aspire to have all of our applications or APIs protected by web application firewall. First question is, are they even behind the web? Are they behind the w at all? We're gonna find that the WAFF doesn't know if it's not protecting something. And then secondary, there are attack types of business logic in particular of like authentication policy that a WAFF is not gonna be able to see. So the WAFF and the API management plan, those are the key control points and we can help make those better. >>You know what I think is cool, Carl, as you're bringing up a point that we're seeing here and we've seen before, but now it's kind of coming at the visibility. And it was mentioned in the keynote by one of the presenters, Kurt, I think it was who runs the platform. This idea of reasoning is coming into security. So the idea of knowing the topology know that there's dynamic stuff going on. I mean, topes aren't static anymore. Yep. And now you have more microservices. Yep. More APIs being turned on and off this runtime is interesting. So you starting to see this holistic view of, Hey, the secret sauce is you gotta be smarter. Yep. And that's either machine learning or AI. So, so how does that relate to what you guys do? Does it, cuz it sounds like you've got something of that going on with the product. Is that fair or yeah. >>Yeah, absolutely. So we, yeah, we talked about posture, so that's, that's really the inherent quality or secure posture of a, of an API. And now let's talk about sending traffic through that API, the request and response. When we're talking about organizations that have more APIs than they have people, employees, or, or tens of thousands, we're seeing in some customers, the only way to identify anomalous traffic is through machine learning. So we apply a machine learning model to each and every API in independently for itself because we wanna learn how that API is supposed to be behave. Where is it supposed to be talking? What kind of data is it supposed to be trafficking in, in, in all its facets. So we can model that activity and then identify the anomaly where there's a misuse, there's an attacker event. There's an, an insider employee is doing something with that API that's different. And that's really key with APIs is, is that no, a no two APIs are alike. Yeah. They really do have to be modeled individually rather than I can't share my, my threat signatures for my API, with your organization, cuz your APIs are different. And so we have to have that machine learning approach in order to really identify that >>Anomaly and watch the credentials, permissions. Absolutely all those things. All right. Take me through the life cycle of an API. There's pre-production postproduction what do I need to know about those two, those two areas with respect to what you guys do? >>Sure. So the pre-production activities are really putting in the hands of a developer or an APSEC team. The ability to test that API during its development and, and source code testing is one piece, but also in pre-production are we modeling production variables enough to know what's gonna happen when I move it into production? So it's one thing to have secure source code, of course, but then it's also, do we know how that API's gonna interact with the world once it's sort of set free? So the testing capabilities early life cycle is really how we de-risk in the long term, but we all have API ecosystems that are existing. And so in production we're applying the, all of those same testing of posture and configuration issues in runtime, but really what it, it may sound cliche to say, we wanna shift security left, but in APIs that's, that's a hundred percent true. We want to keep moving our, our issue detection to the earliest possible point in the development of an API. And that gives us the greatest return in the API, which is what we're all looking for is to capitalize on it as an agent of transformation. >>All right, let's take the customer perspective. I'm the customer, Carl, Carl, why do I need you? And how are you different from the competition? And if I like it, how do I get started? >>Sure. So the, the, the first thing that we differentiate selves from the customer is, or from our competitors is really looking at the API as an entire life cycle of activities. So whether it's from the documentation and the design and the secure source code testing that we can provide, you know, pre-development, or pre-deployment through production posture, through runtime, the differentiator really for us is being a one-stop shop for an entire API security program. And that's very important. And as that one stop shop, the, the great thing about that when having a conversation with a customer is not every customer's at the same point in their journey. And so if, if a customer discussion really focuses on their perhaps lack of confidence in their code testing, maybe somebody else has a lack of confidence in their runtime detection. We can say yes to those conversations, deliver value, and then consider other things that we can do with that customer along a whole continuum of life cycle. And so it allows us to have a customer conversation where we don't need to say, no, we don't do that. If it's an API, the answer is, yes, we do do that. And that's really where we, you know, we have an advantage, I think, in, in looking at this space and, and, and being able to talk with pretty much any customer in any vertical and having a, having a solution that, that gives them something value right away. >>And how do I get started? I like it. You sold me on, on operationalizing it. I like the one stop shop. I, my APIs are super important. I know that could be potential exposure, maybe access, and then lateral movement to a workload, all kinds of stuff could happen. Sure. How do I get started? What do I do to solve >>This? Well, no name, security.com. Of course we, we have, you know, most customers do sandboxing POVs as part of a trial period for us, especially with, you know, being here at AWS is wonderful because these are customers who's with whom we can integrate with. In a matter of minutes, we're talking about literally updating an IAM role. Permission is the complexity of implementation because cloud friendly workloads really allow us to, to do proofs of concept and value in a matter of minutes to, to achieve that value. So whether it's a, a dedicated sandbox for one customer, whether it's a full blown POC for a complicated organization, you know, whether it's here at AWS conference or, or, or Nona security.com, we would love to do a, do a, like a free demo test drive and assessment. >>Awesome. And now you guys are part of the elite alumni of our startup showcase yep. Where we feature the hot startups, obviously it's the security focuses episodes about security. You guys have been recognized by the industry and AWS as, you know, making it, making it happen. What specifically is your relationship with AWS? Are you guys doing stuff together? Cuz they're, they're clearly integrating with their partners. Yeah. I mean, they're going to companies and saying, Hey, you know what, the more we're integrated, the better security everyone gets, what are you doing with Amazon? Can you share any tidbits? You don't have to share any confidential information, but can you give us a little taste of the relationship? >>Well, so I think we have the best case scenario with our relationship with AWSs is, is as a, as a very, very small company. Most of our first customers were AWS customers. And so to develop the, the, the initial integrations with AWS, what we were able to do is have our customers, oftentimes, which are large public corporations, go to AWS and say, we need, we need that company to be through your marketplace. We need you to be a partner. And so that partnership with, with AWS has really grown from, you know, gone from zero to 60 to, you know, miles per hour in a very short period of time. And now being part of the startup program, we have a variety of ways that a customer can, can work with us from a direct purchase through the APS marketplace, through channel partners and, and VA, we really have that footprint now in AWS because our customers are there and, and they brought our customers to AWS with us. >>It's it nice. The customers pulls you to AWS. Yes. Its pulls you more customers. Yep. You get kind of intermingled there, provide the value. And certainly they got, they, they hyperscale so >>Well, that creates depth of the relationship. So for example, as AWS itself is evolving and changing new services become available. We are a part of that inner circle. So to speak, to know that we can make sure that our technology is sort of calibrated in advance of that service offering, going out to the rest of the world. And so it's a really great vantage point to be in as a startup. >>Well, Carl, the CISO for no name security, you're here on the ground. You partner with AWS. What do you think of the show this year? What's the theme. What's the top story one or two stories that you think of the most important stories that people should know about happening here in the security world? >>Well, I don't think it's any surprise that almost every booth in the, in the exhibit hall has the words cloud native associated with it. But I also think that's, that's, that's the best thing about it, which is we're seeing companies and, and I think no name is, is a part of that trend who have designed capabilities and technologies to take advantage and lean into what the cloud has to offer rather than compensating. For example, five years ago, when we were all maybe wondering, will the cloud ever be as secure as my own data center, those days are over. And we now have companies that have built highly sophisticated capabilities here in the exhibit hall that are remarkably better improvements in, in securing the cloud applications in, in our environments. So it's a, it's a real win for the cloud. It's something of a victory lap. If, if you hadn't already been there, you should be there at this point. >>Yeah. And the structural change is happening now that's clear and I'd love to get your reaction if you agree with it, is that the ops on security teams are now being pulled up to the level that the developers are succeeding at, meaning that they have to be in the boat together. Yes. >>Oh, lines of, of reporting responsibility are becoming less and less meaningful and that's a good thing. So we're having just in many conversations with developers or API management center of excellence teams to cloud infrastructure teams as we are security teams. And that's a good thing because we're finally starting to have some degree of conversions around where our interests lie in securing cloud assets. >>So developers ops security all in the boat together, sync absolutely together or win together. >>We, we, we win together, but we don't win on day one. We have to practice like we as organizations we have to, we have to rethink our, we have to rethink our tech stack. Yeah. But we also have to, you have to rethink our organizational models, our processes to get there, to get >>That in, keep the straining boat in low waters. Carl, thanks for coming on. No name security. Why the name just curious, no name. I love that name. Cause the restaurant here in Boston that used to be of all the people that know that. No name security, why no name? >>Well, it was sort of accidental at, in the, in the company's first few weeks, the there's an advisory board of CISOs who provides feedback on, on seed to seed companies on their, on their concept of, of where they're gonna build platforms. And, and so in absence of a name, the founders and the original investor filled out a form, putting no name as the name of this company that was about to develop an API security solution. Well, amongst this board of CSOs, basically there was unanimous feedback that the, what they needed to do was keep the name. If nothing else, keep the name, no name, it's a brilliant name. And that was very much accidental, really just a circumstance of not having picked one, but you know, a few weeks passed and all of a sudden they were locked in because sort of by popular vote, no name was, >>Was formed. Yeah. And now the legacy, the origination story is now known here on the cube call. Thanks for coming on. Really appreciate it. Thank you, John. Okay. We're here. Live on the floor show floor of AWS reinforced in Boston, Massachusetts. I'm John with Dave ALO. Who's out and about getting the stories in the trenches in the analyst meeting. He'll be right back with me shortly day tuned for more cube coverage. After this short break.

>>Hello, Ron. Welcome back to the manage risk across your extended attack service area with Armas asset intelligence platform. I'm Sean furier host we're here at the CSO perspective, Alex Chuck bin, who is the CSO of Colgate Colgate Palm mall of company. Alex, thanks for coming on. >>Thanks for having >>Me, you know, unified visibility across the enterprise surface area is about knowing what you gotta protect. You can't protect what you can't see. Tell me more about how you guys are able to centralize your view with network assets with Armas. >>Yeah, I think the, the most important part of any security program is really visibility. And, and that's one of, kind of the building blocks. When you're building a security program, you need to understand what's in your environment. What's what you control, what is being introduced new into the environment. And that's really what any solution that gives you full visibility to your infrastructure, to your environment, to all the assets that are there, that that's really one of your bread and butter pieces to your security program. >>What's been the impact on your business? >>You know, I, I think from, from an it point of view, running the security program, you know, our key thing is really enabling the business to do their job better. So if we can give them visibility into all the assets that are available in their individual environments, and we're doing that in an automated fashion with no manual collection, you know, that's yet another thing that they don't have to worry about. And then we're delivering because really it is an enabler for the business. And then they can focus really on what their job is, which is to, to deliver product. >>Yeah. And a lot of changes in their network. You got infrastructure, you got OT devices, OT devices. So vulnerability management becomes more important. It's been around for a while, but it's not just it devices anymore. There are gaps in vulnerability across the OT network. What can you tell us about Colgate's use of Armas as vulnerability management? What can you, can you see now what you couldn't you see before? Can you share your thoughts on this? >>Yeah, I, I think what's really interesting about the, the kind of manufacturing environments today is if you look back a number of years, most of the manufacturing equipment was really disconnected from the internet. It was really running in silos. So it was very easy to protect equipment that, that isn't internet connected. You could put a firewall, you could segment it off. And it was, it was really on an island on its own. Nowadays you have a lot of IOT devices. You have a lot of internet connected devices, sensors providing information to multiple different suppliers or vendor solutions. And you have to really then open up your ecosystem more, which of course means you have to change your security posture and you really have to embrace. If there's a vulnerability with one of those suppliers, then how do you mitigate the risk associated to vulnerability? Armas really helps us get a lot of information so that we can then make a decision with our business teams. >>That whole operational aspect of criticality is huge. How on the assets knowing what's what's key? How has that changed your, the, the security workload for you guys? >>Yeah, for us, I mean, it, it's all about being efficient. If we can have the, the visibility across our manufacturing environments, then, then my team can easily consume that information. You know, if we spend a lot of time trying to digest the information, trying to process it, trying to prioritize it, that, that, that really hurts our efficiency as, as a team where as a function, what we really like is being able to use technology to help us do that work. We're, we're not an it shop. We're a manufacturing shop, but we're a very technical shop so that we like to drive everything through automation and not be a bottleneck for any of the, the actions that take place. >>You know, the old expression is the juice worth. The squeeze. It comes up a lot when people are buying tools around vulnerability management and point, all this stuff. So SAS solution is key with no agents to deploy. They have that talk about how you operationalize Armas in your environment, how quickly did it AC achieve time to value, take us through that, that consumption of the product. And, and, and what was the experience like? >>Yeah, I I'll definitely say a in, in the security ecosystem that that's one of the, the biggest promises you hear across the industry. And when, when we started with Armas, we started with a very small deployment and we wanted to make sure if, if it was really worth the lift to your point, we implemented the, the first set of plants very quickly, actually, even quicker than we had put in our project plan, which is, is not typical for implementing complex security solutions. And then we were so successful with that. We expanded to cover more of our manufacturing plants, and we were able to get really true visibility across our entire manufacturing organization in the first year with the ability to also say that we extended that, that information, that visibility to our manufacturing organization, and they could also consume it just as easily as we could. >>That's awesome. How many assets did you guys discover? Just curious on the numbers? >>Oh, that, that's the really interesting part, you know, before we started this project, we would've had to do a, a manual audit of, of our plants, which is typical in, in our industry. You know, when, when we started this project and, and we put in estimates, we really, really didn't have a great handle on what we were gonna find. And what's really nice about the Arma solution is it it's truly giving you full visibility. So you're actually seeing, besides the servers and the PLCs and all the equipment that you're familiar with, you're also connecting it to your wireless access points. You're connecting it to see any of those IOT devices as well. And then you're really getting full visibility through all the integrations that they offer. You're amazed how many devices you're actually seeing across your entire ecosystem. >>It's like Google maps for your infrastructure. You get little street view. You wanna look at it, you get the, you know, fake tree in there, whatever, but it gives you the picture that's key, >>Correct. And with a nice visualization and an easy search engine, similar to your, your Google analogy, you know, everything is, is, is really at your fingertips. If you wanna find something, you just go to the search bar, click a couple entries and, and boom, you get your, your list of the associated devices or the, the associated locations devices. >>Well, I appreciate your time. I know you're super busy at CSIG a lot of your plate. Thanks for coming on sharing. Appreciate it. >>No problem, John. Thanks for having me. >>Okay. In a moment, Brian Inman, a sales engineer at Armas will be joining me. You're watching the cube, the leader in high tech coverage. Thanks for watching.

>>Welcome back to Vegas. Lisa Martin here covering snowflake summit 22. We are live at Caesar's forum. A lot of guests here about 10,000 attendees, actually 10,000 plus a lot of folks here at the momentum and the buzz. I gotta tell you the last day and a half we've been covering this event is huge. It's probably some of the biggest we've seen in a long time. We're very pleased to welcome back. One of our cube alumni to the program, Ron Tayo principal and chief data officer at Deloitte one. It's great to have you joining us. >>Yeah, no, thank you. Super excited to be here with you today. >>Isn't it great to be back in person? Oh, >>I love it. I mean the, the energy, the, you know, connections that we're making definitely, definitely loving and loving the experience. >>Good experience, but the opportunity to connect with customers. Yes. I'm hearing a lot of conversations from snowflake folks from their partners like Deloitte from customers themselves. Like it's so great to be back in person. And they're really talking about some of the current challenges that are being faced by so many industries. >>That's right. Oh, that, that is, you know, I would say as a consultant, you know, it all comes down to that personal connection and that relationship. And so I am, I'm all for this and love, you know, being able to connect with our customers. >>Yeah. Talk to me about the Deloitte snowflake partnership. Obviously a ton of news announced from snowflake yesterday. Snowflake is a rocket ship. Talk to us about the partnership, what you guys do together, maybe some joint customer examples. >>Yeah. I mean, so snowflake is a strategic Alliance partner. We won the, you know, SI partner of the year award and for us, the, the shift and the opportunity to help our clients modernize and achieve a level of data maturity in their journey is, is strategically it's super important. And it's really about how do we help them leverage, you know, snowflake has underlying data platform to ultimately achieve, you know, broader goals around, you know, their business strategy. And our approach is always very much connected to overarching business strategies and sense of, is it a finance transformation, a supply chain transformation, a customer transformation, and what are the goals of those transformations and how do we ensure that data is a critical component to enabling that and with, you know, technologies and vendors and partners like snowflake, allowing us to even do that at a faster, better, cheaper pace only increases the overall business case and the value and the impact that it generates. >>And so we are super, super excited about our partnership with snowflake and we believe, you know, the journey is very, very bright. You know, we, this is the future, you know, often tell folks that, you know, data has and will continue to be more valuable than sort of the systems that own it and manage it. And I think we're starting to see that. I think the topic that I discussed today around data collaboration and data sharing is an example of how we're starting to see, you know, the importance and the value of data, you know, become way more important and more of the focus around the strategy for, for organizations >>As the chief data officer, what do data sharing and data collaboration mean to somebody in your position and what are some of the conversations you have with customer other CDOs at customer organizations? >>Yeah, so, so my role is, is sort of twofold. I, I am responsible for our internal data strategy. So when you think about Deloitte as a professional service organization, across four unique businesses, I am a customer of snowflake in our own data modernization journey, and we have our own strategy on how and what we share, not only internally across our businesses, but also externally across, you know, our partners. So, so I bring that perspective, but then I also am a client service professional and serve our clients in their own journey. So I often feel very privileged in, in the opportunity to be able to sort of not only share my own experience from a Deloitte perspective, but also in how we help our clients >>Talk about data maturation. You mentioned, you know, the volume of data just only continues to grow. We've seen so much growth in the last two years alone of data. We've seen all of us be so dependent on things like media and entertainment and retail, eCommerce, healthcare, and life sciences. What, how do you define data maturation and how does Deloitte and snowflake help companies create a pathway to get there? >>Yeah. Yeah. So I would say step one for us is all about the overarching business strategy. And when you sort of double click on the big, broad business strategy and what that means from a data strategy perspective, we have to develop business models where there is an economical construct to the value of data. And it's extremely important specifically when we talk about sharing and collaborating data, I would say the, the, the, the assumption or the, or, or, or, or the posture typically seems to be, it's a one way relationship, our strategy and what we're pushing, you know, again, not only internally within ourselves, but also with our clients, is it has to be a bidirectional relationship. And so you, you hear of, of the concepts of, you know, the, the, the data clean room where you have two partners coming together and agreeing with certain terms to share data bidirectionally. Like I do believe that is the future in how we need to do, you know, more data collaboration, more data sharing at a scale that we've not quite seen. Yes. Yet >>The security and privacy areas are increasingly critical. We've seen the threat landscape change so dramatically the last couple of years, it's not, will we get hit by a cyber talk? It's when yes. For every industry, right? The privacy legislation that just we've seen it with GDPR, CCPA is gonna become CPR in California, other states doing the same thing. How do you help customers kind of balance that line of being able to share data equitably between organizations between companies do so in a secure way, and in a way that ensures data privacy will be maintained. >>Yeah. Yeah. So first absolutely recognizing, evolving, recognize the evolving regulatory landscape. You mentioned, you know, California, there's actually now 22 states that have a, is it 22 now? Right? Yeah. 22 states that have a privacy act enacted. And our projection is in the next 12 to 18 months, all states will have one. And so absolutely a, a perceived challenge, but one that I think is, is addressable. And, and I think that gets to the spirit of the question for us. There's, there's four dimensions that an organization needs to work through when it comes to data sharing. The first one is back to the, the business goal and objective, like, is there truly a business need? And is there value in sharing data? And it needs to have a very solid business model. Okay. So, so that's the first step. The second step is what are the legal terms? >>What are the legal terms? What can you do? What can't you do? Do you have primary rights, secondary rights? The third dimension is around risk. What is the risk and exposure, not only from a data security perspective, but what is the risk if someone uses a data inappropriately, and then the fourth one is around ethics and the ethical use of data. And we see lots of examples where an organization has consent has rights to the data, but the way they used it might have not necessarily been, you know, among the kind of ethical framing. And so for us, those four dimensions is what guides us and our clients in developing a very robust data, sharing data collaboration framework that ensures it's connected to the overall business strategy, but it provides enough of the guardrails to minimize legal and ethical risk. So >>With that in mind, what do the customer conversations look like? Cause you gotta have a lot of players, the business folks, the data folks, every line of business needs data for its functions. Talk to us about how the customer conversations and projects have evolved as data is increasingly important to every line of business. >>Yes. I would say the biggest channel, or maybe the, the, the denominator at this point that we're seeing bring the, let's say diversity of needs to more common denominator has been AI. So every organization at this point is driving massive AI programs. And in order to really scale AI, you know, the, the algorithm cannot execute without data. Yeah. And so for us, at least in our experience with our customers, AI has almost been the, the, the mechanism to have these conversations across the different business stakeholders and do it in a way that, you know, you're not necessarily boiling the ocean, cuz I think that's the other element that makes this a bit hard is, well, what, what data do you want me to share and for what purpose? And when you start to bring it into sort of more individual swim lanes and, and, and our experience with our customers is AI has sort of been that mechanism to say, am I automating, you know, our factory floor? Am I bringing AI and how we engage and serve our customers? Right? Like it be, it be begins to sort of bring a little bit more of, of that repeatability at a, at an individual level. So that's been a, a really good strategy for us in our customers >>In terms of the customer's strategy and kind of looking forward, what are some of the things that excite you about the, the future of data collaboration, especially given all of the news that snowflake announced just yesterday? >>Yes. Yeah. I think for me, and this is both the little bit of the ambition, as well as the push, it's no longer a question of should it's it's how and for what? And so, so yes, I mean the, the, the snowflake data cloud is a network that allows us to integrate, you know, disparate and unique data assets that have never, you know, been possible before. Right. So we're in this network, it's now a matter of figuring out how to use that and for what purpose. And so I, I go back to, we, each individual organization needs to be figuring out the how, and for what not, when this is the future, we all need it. Yeah. And we just need to figure out how that fits in our individual businesses >>In terms of the, how that's such an interesting, I love how you bring that up. It's not, it's not when it's definitely how, because there's gonna be another competing business or several right there in the rear view mirror, ready to take your place. Yep. If you don't act quickly, how does Deloitte and snowflake help customers achieve the, how quickly enough to be able to really take advantage of data sharing and data collaboration so that they can be very competitive? >>Yeah. So there's two main, maybe even three driving forces in this. What we see is when there's a common purpose across director, indirect competitors and the need to share data. So I think the poster child of this was the pandemic, and we started to see organizations again, either competitively or non-com competitively share data in ways for a greater good, right. When there was a purpose, we believe when that element exists, the ability to share data is going to increase. We believe the next big sort of common purpose out there in the world is around ESG. And so that's gonna be a big driver for sharing data. So that's one element. The other one is the concept of developing integrated value chains. So when you think about any individual business and sort of where they are in that piece of the value chain, developing more integrated value across, let's say a manufacturer of goods with a distributor of those goods that ultimately get to an end customer. >>They're not sharing data in a meaningful way to really maximize their overall, you know, profitability. And so that's another really good, meaningful example that we're seeing is where there's value across, you know, a, what appears to be a siloed set of steps, and really looking at it more as an integrated value chain, the need to share data is the only way to unlock that. And so that's, that's the second one. The, the third one I would say is, is around the need to address the consumer across sort of the multiple personas that we all individually sit. Right? So I go into a bank and I'm, I'm a client. I walk into a retail store and I'm a customer. I walk into my physician's office and I'm a patient at the end of the day. I am still the same person. I am still one. And so that consumer element and the convergence of how we are engaging and serving that consumer is the third, big shift that is really going to bring data collaboration and sharing to the next level. >>Do you think snowflake is, is the right partner of the defacto for delight to do that with? >>Absolutely. I think, you know, the head start of the cloud, the data cloud platform and the network that it's already established with all the sort of data privacy and security constraints around it. Like that's a big, that's a big, you know, check right. That we don't have to worry about. It's there for sure. >>Awesome. Sounds like a great partnership, Juan. Thank you so much for joining me on the program. It's great to have you back on the cube in person sharing what Deloitte and snowflake are doing and how you're really helping to transform organizations across every industry. We appreciate >>Your insights. Yeah. No, thank you for having me here. My pleasure. Always a pleasure. Thank you. >>All right. For Juan. I am Lisa Martin. You're watching the cube live from snowflake summit 22 at Caesar's forum. You write back with our next guest.

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

>>Hello, everyone. Welcome to this cube conversation. I'm here in Palo Alto, California. I'm John furrier, host of the cube, and we have a great guest here. Barack Shuster. Who's in Tel-Aviv senior director of chief architect at bridge crew, a part of Palo Alto networks. He was formerly the co-founder of the company, then sold to Palo Alto networks Brock. Thanks for coming on this cube conversation. >>Thanks John. Great to be here. >>So one of the things I love about open source, and you're seeing a lot more of the trend now that talking about, you know, people doing incubators all over the world, having open source and having a builder, people who are starting companies, it's coming more and more, you you're one of them. And you've been part of this security open source cloud infrastructure infrastructure as code going back a while, and you guys had a lot of success. Now, open source infrastructure as code has moved up to the stack, certainly lot going down at the network layer, but developers just want to build security from day one, right? They don't want to have to get into the, the, the waiting game of slowing down their pipelining of code in the CIC D they want to move faster. And this has been one of the core conversations this year is how to make developers more productive and not just a cliche, but actually more productive and not have to wait to implement cloud native. Right. So you're in the middle of it. And you've got you're in, tell us, tell us what you guys are dealing with that, >>Right? Yeah. So I hear these needles working fast, having a large velocity of releases from many of my friends, the SRAs, the DevOps, and the security practitioners in different companies. And the thing that we asked ourselves three years ago was how can we simplify the process and make the security teams an enabler instead of a gatekeeper that blocks the releases? And the thing that we've done, then we understood that we should do is not only doing runtime scanning of the cloud infrastructure and the cloud native clusters, but also shift left the findings and fixings the remediation of security issues to the level of the code. So we started doing infrastructure is good. We Terraform Kubernetes manifests cloud formation, server less, and the list goes on and we created an open source product around it, named checkup, which has an amazing community of hundreds of contributors. Not all of them are Palo Alto employees. Most of them are community users from various companies. And we tried to and succeeded to the democratic side is the creation of policy as code the ability to inspect your infrastructure as code and tell you, Hey, this is the best practice that you should use consider using it before applying a misconfigured S3 bucket into production, or before applying a misconfigured Kubernetes cluster into your production or dev environment. And the goal, >>The goal, >>The goal is to do that from the ID from the moment that you write code and also to inspect your configuration in CGI and CD and in runtime. And also understand that if there is any drift out there and the ability to fix that in the source code, in the blueprint itself. >>So what I hear you saying is really two problems you're solving. One is the organizational policies around how things were done in a environment before all the old way. You know, the security teams do a review, you send a ticket, things are waiting, stop, wait, hurry up and wait kind of thing. And then there's the technical piece of it, right? Is that there's two pieces to that. >>Yeah, I think that one thing is the change of the methodologies. We understood that we should just work differently than what we used to do. Tickets are slow. They have priorities. You have a bottleneck, which is a small team of security practitioners. And honestly, a lot of the work is repetitive and can be democratized into the engineering teams. They should be able to understand, Hey, I wrote the code piece that provision this instance, I am the most suitable person as a developer to fix that piece of code and reapply it to the runtime environment. >>And then it also sets the table for our automation. It sets the table for policies, things that make things more efficient scaling. Cause you mentioned SRS are a big part of this to dev ops and SRE. Those, those folks are, are trying to move as fast as possible at scale, huge scale challenge. How does that impact the scale piece become into here? >>So both themes Esri's and security teams are about a link to deploying application, but new application releases into the production environment. And the thing that you can do is you can inspect all kinds of best practices, not only security, best practices, but also make sure that you have provision concurrencies on your serverless functions or the amount of auto-scaling groups is what you expect it to be. And you can scan all of those things in the level of your code before applying it to production. >>That's awesome. So good, good benefits scales a security team. It sounds like too as well. You could get that policy out there. So great stuff. I want to really quickly ask you about the event. You're hosting code two cloud summit. What are we going to see there? I'm going to host a panel. Of course, I'm looking forward to that as well. You get a lot of experts coming in there. Why are you having this event and what topics will be covered? >>So we wanted to talk on all of the shifts, left movement and all of the changes that have happened in the cloud security market since inception till today. And we brought in great people and great practitioners from both the dev ops side, the chaos engineering and the security practitioners, and everybody are having their opinion on what's the current status state, how things should be implemented in a mature environment and what the future might hold for the code and cloud security markets. The thing that we're going to focus on is all of the supply chain from securing the CCD itself, making sure your actions are not vulnerable to a shut injection or making sure your version control system are configured correctly with single sign-on MFA and having branch protection rules, but also open source security like SCA software composition analysis infrastructure as code security. Obviously Ron thinks security drifts and Kubernetes security. So we're going to talk on all of those different aspects and how each and every team is mitigating. The different risks that come with. >>You know, one of the things that you bring up when you hear you talking is that's the range of, of infrastructure as code. How has infrastructure as code changed? Cause you're, you know, there's dev ops and SRS now application developers, you still have to have programmable infrastructure. I mean, if infrastructure code is real realize up and down the stack, all aspects need to be programmable, which means you got to have the data, you got to have the ability to automate. How would you summarize kind of the state of infrastructure as code? >>So a few years ago, we started with physical servers where you carried the infrastructure on our back. I, I mounted them on the rack myself a few years ago and connected all of the different cables then came the revolution of BMS. We didn't do that anymore. We had one beefy appliance and we had 60 virtual servers running on one appliance. So we didn't have to carry new servers every time into the data center then came the cloud and made everything API first. And they bill and enabled us to write the best scripts to provision those resources. But it was not enough because he wanted to have a reproducible environment. The is written either in declarative language like Terraform or CloudFormation or imperative like CDK or polluted, but having a consistent way to deploy your application to multiple environments. And the stage after that is having some kind of a service catalog that will allow application developer to get the new releases up and running. >>And the way that it has evolved mass adoption of infrastructure as code is already happening. But that introduces the ability for velocity in deployment, but also new kinds of risks that we haven't thought about before as security practitioners, for example, you should vet all of the open source Terraform modules that you're using because you might have a leakage. Our form has a lot of access to secrets in your environment. And the state really contains sensitive objects like passwords. The other thing that has changed is we today we rely a lot on cloud infrastructure and on the past year we've seen the law for shell attack, for example, and also cloud providers have disclosed that they were vulnerable to log for shell attack. So we understand today that when we talk about cloud security, it's not only about the infrastructure itself, but it's also about is the infrastructure that we're using is using an open source package that is vulnerable. Are we using an open source package that is vulnerable, is our development pipeline is configured and the list goes on. So it's really a new approach of analyzing the entire software bill of material also called Asbell and understanding the different risks there. >>You know, I think this is a really great point and great insight because new opera, new solutions for new problems are new opportunities, right? So open source growth has been phenomenal. And you mentioned some of those Terraform and one of the projects and you started one checkoff, they're all good, but there's some holes in there and it's open source, it's free, everyone's building on it. So, you know, you have, and that's what it's for. And I think now is open source goes to the next level again, another generational inflection point it's it's, there's more contributors there's companies are involved. People are using it more. It becomes a really strong integration opportunity. So, so it's all free and it's how you use it. So this is a new kind of extension of how open source is used. And if you can factor in some of the things like, like threat vectors, you have to know the code. >>So there's no way to know it all. So you guys are scanning it doing things, but it's also huge system. It's not just one piece of code. You talking about cloud is becoming an operating system. It's a distributed computing environment, so whole new area of problem space to solve. So I love that. Love that piece. Where are you guys at on this now? How do you feel in terms of where you are in the progress bar of the solution? Because the supply chain is usually a hardware concept. People can relate to, but when you bring in software, how you source software is like sourcing a chip or, or a piece of hardware, you got to watch where it came from and you gotta track track that. So, or scan it and validate it, right? So these are new, new things. Where are we with? >>So you're, you're you're right. We have a lot of moving parts. And really the supply chain terms of came from the automobile industry. You have a car, you have an engine engine might be created by a different vendor. You have the wheels, they might be created by a different vendor. So when you buy your next Chevy or Ford, you might have a wheels from continental or other than the first. And actually software is very similar. When we build software, we host it on a cloud provider like AWS, GCP, Azure, not on our own infrastructure anymore. And when we're building software, we're using open-source packages that are maintained in the other half of the war. And we don't always know in person, the people who've created that piece. And we do not have a vetting process, even a human vetting process on these, everything that we've created was really made by us or by a trusted source. >>And this is where we come in. We help you empower you, the engineer, we tools to analyze all of the dependency tree of your software, bill of materials. We will scan your infrastructure code, your application packages that you're using from package managers like NPM or PI. And we scan those open source dependencies. We would verify that your CIC is secure. Your version control system is secure. And the thing that we will always focus on is making a fixed accessible to you. So let's say that you're using a misconfigured backup. We have a bot that will fix the code for you. And let's say that you have a, a vulnerable open-source package and it was fixed in a later version. We will bump the version for you to make your code secure. And we will also have the same process on your run time environment. So we will understand that your environment is secure from code to cloud, or if there are any three out there that your engineering team should look at, >>That's a great service. And I think this is cutting edge from a technology perspective. What's what are some of the new cloud native technologies that you see in emerging fast, that's getting traction and ultimately having a product market fit in, in this area because I've seen Cooper. And you mentioned Kubernetes, that's one of the areas that have a lot more work to do or being worked on now that customers are paying attention to. >>Yeah, so definitely Kubernetes is, has started in growth companies and now it's existing every fortune 100 companies. So you can find anything, every large growler scale organization and also serverless functions are, are getting into a higher adoption rate. I think that the thing that we seeing the most massive adoption off is actually infrastructure as code during COVID. A lot of organization went through a digital transformation and in that process, they have started to work remotely and have agreed on migrating to a new infrastructure, not the data center, but the cloud provider. So at other teams that were not experienced with those clouds are now getting familiar with it and getting exposed to new capabilities. And with that also new risks. >>Well, great stuff. Great to chat with you. I want to ask you while you're here, you mentioned depth infrastructure as code for the folks that get it right. There's some significant benefits. We don't get it. Right. We know what that looks like. What are some of the benefits that can you share personally, or for the folks watching out there, if you get it for sure. Cause code, right? What does the future look like? What does success look like? What's that path look like when you get it right versus not doing it or getting it wrong? >>I think that every engineer dream is wanting to be impactful, to work fast and learn new things and not to get a PagerDuty on a Friday night. So if you get infrastructure ride, you have a process where everything is declarative and is peer reviewed both by you and automated frameworks like bridge and checkoff. And also you have the ability to understand that, Hey, once I re I read it once, and from that point forward, it's reproducible and it also have a status. So only changes will be applied and it will enable myself and my team to work faster and collaborate in a better way on the cloud infrastructure. Let's say that you'd done doing infrastructure as code. You have one resource change by one team member and another resource change by another team member. And the different dependencies between those resources are getting fragmented and broken. You cannot change your database without your application being aware of that. You cannot change your load Bonser without the obligation being aware of that. So infrastructure skullduggery enables you to do those changes in a, in a mature fashion that will foes Le less outages. >>Yeah. A lot of people getting PagerDuty's on Friday, Saturday, and Sunday, and on the old way, new way, new, you don't want to break up your Friday night after a nice dinner, either rock, do you know? Well, thanks for coming in all the way from Tel-Aviv really appreciate it. I wish you guys, everything the best over there in Delhi, we will see you at the event that's coming up. We're looking forward to the code to cloud summit and all the great insight you guys will have. Thanks for coming on and sharing the story. Looking forward to talking more with you Brock thanks for all the insight on security infrastructures code and all the cool things you're doing at bridge crew. >>Thank you, John. >>Okay. This is the cube conversation here at Palo Alto, California. I'm John furrier hosted the cube. Thanks for watching.

>>Hello, and welcome to the cube unstoppable Doneen showcase. I'm John furrier, host of the cube. We got a great discussion here called the influencers around what's going on in web three and also this new sea change cultural change around this next generation, internet web cloud, all happening, Jeremiah yang industry analyst, and founding part of the cleaner insights. Share my great to see you. Thanks for coming on. Appreciate it. Uh, registered vice-president of marketing at unstoppable domains in the middle of all the actions. Gentlemen, thanks for coming on on the cube for this showcase. >>My pleasure. So I think it was done >>At Jeremy. I want to start with you. You've seen many ways, but fallen all of your work for over a decade now. Um, you've seen the web 2.0 wave. Now the web three's here. Um, and it's not, I wouldn't say hyped up. It's really just ramping up and you're seeing real practical examples. Uh, you're in the middle of all the action. What is this web three? Can you frame for us that mean you've seen many waves? What is web three mean? What is it? What is it all about? >>Well, John, you and I worked in the web to space and essentially that enabled peer to peer media where people could, could upload their thoughts and ideas and videos, um, without having to rely on centralized media. And unfortunately that distributed and decentralized movement actually became centralized on the platforms or the big social networks and big tech companies. And this has caused an uproar because the people who are creating the content did not have control, could not control their identities and could not really monetize or make decisions. So web three is what is, which is a moniker of a lot of different trends, including crypto blockchain. And sometimes the metaverse is to undo the controlling that has become centralized. And the power is now shifting back into the hands of the participants again, and then this movement, they want to have more control over their identities, their governance, the content that they're creating, how they're actually building it and then how they're monetizing it. So in many ways, it's, it's changing the power and it's a new economic model. So that's web three without really even mentioning the technologies. Is that helpful? >>Yeah, that's great. And ran. We were talking about, on the cute many times and one notable stat, I don't think it's been reported, but it's been more kind of a rumor. I hear that 30% of the, um, Berkeley computer science students are dropping out and going into crypto or blockchain or decentralized startups, which means that this there's a big wave coming in of talent. You seeing startups, you're seeing a lot more formation. You're seeing a lot more, I would say, kind of ramping up of real people, not just, you know, people with a dream it's actual builders out here doing stuff. What's your take on the web three, moving with all this kind of change happening, uh, from people and also the new ideas being refactored. >>I think that the competition for talent is extremely real. And we start looking at the stats. We see that there is an draft of people that are moving into this space. People that are fascinated by technology and are embracing the ethos of web three. And at this stage, I think it's not only engineers and developers, but we have moved into a second phase where we see that a lot of supporting functions know marketing, being one of them, sales, business development, uh, are being built up quite rapidly. It's not without actually reminding me of the mid two thousands. You know, when I started, uh, working with Google at that point in time, the walled gardens rightly absorbing vast, vast cohorts of young graduates and more experienced professionals that are passionate and moving into the web environment. And I think we are seeing a movement right now, which is not entirely dissimilar, except >>Yeah, Jeremiah. You've seen the conversations over the cloud. I call the cloud kind of revolution. You had mobile in 2007, but then you got Amazon web services changed the application space on how people developed in the cloud. And again, that created a lot of value. Now you're seeing the role of data as a huge part of how people are scaling and the decentralized movement. So you've got cloud, which is kind of classic today. State-of-the-art, you know, enterprise and or app developers and you've got now decentralized wave coming. Okay. You're seeing apps being developed on that, that architecture data is central in all of this, right. So how do you view this? As, as someone who's watching the landscape, you know, these walled gardens are hoarding all the data. I mean, LinkedIn Facebook, they're not sharing that data with anyone they're using it for themselves. So as they can control back, comes to the forefront, how do you see this market with the applications and what comes out of that? >>So the thing that we've seen and out of the five things that I had mentioned that are decentralizing, the ones that have been easier to move across have been the ability to monetize and to build. But the data aspect has actually stayed pretty much central. Frankly. What has decentralized is that the contracts to block blockchain ledgers to those of decentralized. But the funny thing is often a big portion of these blockchain networks are on Amazon 63 to 70%, same thing with Stelara. So they're still using the web 2.0 architectures. However, we're also seeing other farms like IPFS, where the data could be to spread it across a wider range of folks. But right now we're still dependent on what we're to point out. So the vision and the problem with 3.0, when it comes to full de-centralization is not here by any means. I'd say we're at a web 2.2, five, >>Pre-web 3m, no actions there. What do you guys, how do you guys see the, um, the dangers? Cause there's a lot of negative press, but also is a lot of positive press. You seeing, you know, a lot of fraud, we've seen a lot of the crypto fraud over the past years. You've seen a lot of now positives, it's almost a self-governance thing and environment, the way the culture is, but what are the dangers? How do you guys educate people? What should people pay attention to? What should people look for to understand, you know, where to position themselves? >>Yes. So we've learned a lot from web one, we to the sharing economy and we are walking into two and three with eyes wide open. So people have rightfully put forth a number of challenges, the sustainability issues with excess using of computing and mining, the, um, the excessive amount of scams that are happening in part due to unknown identities. Um, also the architecture breaks down in certain periods and there's a lack of regulation. Um, this, this is something different though in the last, uh, uh, periods that we've gone through, we didn't really know what was gonna happen. And we walked in big, this is going to be great. The sharing economy, the gig economy, the social media is going to change the world. Hurrah is very different. Now people are a little bit jaded. So I think that's the big change. And so I think we're going to see that, uh, you know, soar it out and suss out just like we've seen with other prints. It's still very much in the early years, >>Right. I got to get your take on this whole, uh, should influencers and should people be anonymous or should they be doxed out there? You saw the board eight guys that did, that were kind of docs a little bit there and that went, went viral. Um, this is an issue, right? Because we, we just had a problem of fake news, uh, fake people, fake information, and now you have a much more secure environment. Immutability is a wonderful thing. It's, it's a feature, not a bug, right. So how is this all coming down? And I know you guys are in the middle of it with, uh, NFTs as, as authentication tickets. What's your take on this because this is a big issue. >>Look, I think first I am extremely optimistic about technology in general. Uh, so I'm super, super bullish about this. And yet, you know, I think that while crypto has so many upsides, it's important to be super conscious and aware of the downsides that come with it too. You know, if you think about every fortune 500 company, there is always training required by all employees on internet safety reporting of potential attacks. And so on in web three, we don't have that kind of standard reporting mechanisms yet, uh, for bad actors in that space. And so when you think about influencers in particular, they do have a responsibility to educate people about, uh, the potential, but also the dangers of the technology of web three, uh, of crypto basically, uh, whether you're talking about hacks online safety, the need for hardware impersonators on discord, uh, security, uh, storing your, your seed phrase. >>So every actor in France or ELs has got a role to play. I think that, uh, in that context, to your point, it's very hard to tell whether influencers should be, uh, anonymous, opposite inverse or footy dogs. The decentralized nature of web three will probably lead us to see a combination of those anonymity levels, um, so to speak, um, and the, uh, movements that we've seen around some influencers, identities becoming public are particularly interesting. I think there's probably a convergence of web two and web three at play here. You know, maybe a on the notion of 2.5 for, I think in way to all business founders and employees are known and they're held accountable for their public comments and actions. Um, if web three enables us to be anonymous, if dials have 14 control, you know, what happens if people make comments and there is no way to know who they are basically, uh, what if the dowel doesn't take appropriate action? I think eventually there will be an element of community self-regulation where influencers will be, uh, acting in the best interest of their reputation. And I believe that the communities will self regulate themselves and we'll create natural boundaries around what can be said or not. >>I think that's a really good point about, um, influencers and reputation because Jeremiah doesn't matter that you're anonymous. I have an icon that could be a NFT or a picture, but if I have an ongoing reputation, I have trust there's trust there. It's not like a, you know, just a bot that was created just to spam someone. It was just, you know what I'm saying? They getting into you getting into this new way. >>You're right. And that, that word you said, trust, that's what really, this is about. But we've seen that public docks people with their full identities have made mistakes. They have pulled the hood over people's faces in and really scammed them out of a lot of money. We've seen that in it that doesn't change anything in human behavior. So I think over time that we will see a new form of a reputation system emerged even for pseudonyms and perhaps for people that are just anonymous that only show their a potential, a wallet address, a series of numbers and letters. Um, that form might take a new form of a web 3.0 FICO score, and you can look at their behaviors. Did they transact? You know, how do they behave? Do they, were they involved in projects that were not healthy? And because all of that information is public on the chain and you can go back in time and see that we might see a new form of, of, of a scoring emerge. >>Of course, who controls that scoring that's a whole nother topic, gong on control and trust. So right now, John, we do see that there's a number of projects, new NFG projects, where the founders will claim and use this as a point of differentiation that they are fully docs. So you know who they are and their names. Secondly, we're seeing a number of, um, uh, products or platforms that require KYC, know your customer so that self-identification often with a government ID or a credit card in order to bridge out your, your coins and turn that into a Fiat. In some cases that's required in some of these marketplaces. So we're seeing a coalition here between, uh, full names and pseudonyms and being anonymous. >>That's awesome. And that, and I think this is the new, again, a whole new form of governance ran. You mentioned some comments about Dow. So I want to get your thoughts again, you know, Jeremiah, we become historians over the years. We're getting old, I'm a little bit older than you, but we've seen the movie war. You know, I remember breaking in the business when the computer standards bodies were built to be more organic, and then they became much more of a kind of an anti-innovation environment where people, the companies would get involved the standards organization just to slow things down and muck things up a little bit. Um, so you know, you look at Dallas like, Hmm, is a Dal, a good thing, or a bad thing that the answer is from people I talked to, is it depends. So I'd love to get your thoughts on getting momentum and becoming defacto with value, a value proposition. Vis-a-vis just adapt for the sake of having a doubt. This has been a conversation that's been kind of in the inside the baseball here, inside the ropes of the industry, but there's trade-offs, can you guys share your thoughts on when to do a Dow and when not to do a Dow and the benefits and trade-offs of that? >>Sure. Maybe I'll start off with a definition and then we'll go to rent. So a Dao, a decentralized autonomous organization, the best way to think about this. It's a digital cooperative and we've heard of worker cooperatives before the differences that they're using blockchain technologies in order to do the three things, identity governance, and rewards and mechanisms. They're relying on web 2.0 tools and technologies like discord and telegram and social networks to communicate. And there's a cooperative they're trying to come up with a common goal, um, Ren, but what's your take, that's the setup? >>So, you know, for me, when I started my journey into crypto and web tree, I had no idea about, you know, what that actually meant and, uh, an easy way for me to think of it and to grasp the nature of it was about the comparison between a dowel and perhaps a more traditional company structure. Um, you know, in a traditional company structure, you have a Yorkie, the company is led by a CEO and other executives, uh, that that was a flat structure. And it's very much led by a group of core contributors. So, uh, to Jeremiah's point, you know, you get that notion of a co-operative, uh, type of structure. The decision-making is very different. You know, we're talking about a hot, super high level of transparency proposals getting submitted and, and voting systems, using applications, as opposed to, you know, management, making decisions behind closed doors. >>I think that speaks to a totally new form of governance. And I think we have hardly, hardly scratched the surface. We have seen recently, uh, very interesting moments in web tree culture. And we have seen how that was suddenly have to make certain decisions and then come to moments of claiming responsibility, uh, in order to, uh, put his behavior, uh, of some of the members. I think that's important. I think it's going to redefine how we're thinking about that, particularly new governance models. And I think he's going to pave the way for a lot of super interesting structure in the near future. >>That's a great point, ran around the transparency for governance. So John, you posed the question, does this make things faster or slower? And right now most dowels are actually pretty slow because they're set up as a flat organization. So as a response to that, they're actually shifting to become representative democracies. Does that sound familiar where you can appoint a delegates and use tokens to vote for them? And they have a decision power, almost like a committee and they can function. And so we've seen actually there are some times our hierarchies, except the person at the top is voted by those that have the tokens. In some cases, the people at the top had the most tokens, but that's a whole nother topic. So we're seeing a wide variety of governance structures, >>You know, rent. I was talking with Matt G the founder of, and I was telling him about the domain name system. And one little trivia note that many people don't know about is that the U S government cause unit it was started by the U S the department of commerce kept that on tight leash because the international telecommunications union wanted to get their hands on it because of ccTLDs and other things. So at that time, because the innovation yet wasn't yet baked out. It was organically growing the governance, the rules of the road, keeping it very stable versus meddling with it. So there's certain technologies that require Jeremiah that let's keep an eye on as a community. Let's not formalize anything like the government did with the domain name system. Let's keep it tight. And then finally released it, I think multiple years after 2004, I think it went over to the, to the ITU, but this is a big point. I mean, if you get too structured, organic innovation, can't go, what you guys' reaction to that. >>So I think to take a stab at it, um, we have as a business, you know, thinking of unstoppable domains, a strong incentive to innovate, uh, and this is what is going to be determining longterm value growth for the organization for, uh, partners, for users, for customers. So, you know, that degree of formalization actually gives us a sense of purpose and a sense of action. And if you compare that to Dows, for instance, you can see how some of the upsides and downsides can pan out either way. It's not to say that there is a perfect solution. I think one of the advantages of the Dow is that you can let more people contribute. You can probably remove bias quite effectively, and you can have a high level of participation and involvement in decisions and all the upside in many ways. Um, you know, as a company, it's a slightly different setup. We have the opportunity to coordinate a very, uh, diverse and part-time workforce in a very, uh, you know, different way. Um, and we do not have to deal with the inefficiencies that might be, you never run to some form of extreme decentralization so that those are balanced from an organizational structure, uh, that comes, uh, either side >>Sharon. I want to get your thoughts on, on, on a trend that you've been involved in. We both been involved in, and you're seeing it now with the kind of social media world, the world of a role of an influencer it's kind of moved from what was open source and influencer was a connect to someone who shared graded content, um, enabled things to much more of a vanity that the photo on Instagram and having a large audience. Um, so is there a new influencer model with web three or is it, is it the, I control the audience I'm making money that way. Is there a shift in the influencer role or, or ideas that you see that should be in place for what is the role of an influencer? Because as web three comes, you're going to see that role become instrumental. We've seen it in open source projects, influences, you know, the people who write code or ship code. So what's your take on that because there's been a conversation with people who have been having the word influencer and redefining and reframing it. >>Sure. The influence model really hasn't changed that much, but the way that they're behaving has when it comes to at three, this market, I mean, there's a couple of things. Some of the influencers are in investors. And so when you see their name on a project or a new startup, that's an indicator, there's a higher level of success. You might want to pay more attention to it or not. Secondly, influencers themselves are launching their own NFC projects. Gary Vaynerchuk, a number of celebrities, Paris Hilton is involved and they are also doing this as well. Steve Aoki, a famous DJ launched his as well. So they're going head first and participating in building in this model. And there are communities are coming around them and they're building economies. Now the difference is it's not, I speak as an influencer to the fans. The difference is that the fans are now part of the community and they hold, they literally holding own some of the economic value, whether it's tokens or the NFTs. So it's a collaborative economy, if you will, where they're all benefiting together. And that's a, that's a big difference as well. Lastly, there's, there's one little tactic we're seeing where marketers are airdropping in FTS, branded NFTs influencers with wallet. So you can see it in there. So there's new tactics that are forming as well. Yes. >>Super exciting. Ren, what's your reaction to that? Because he just hit on a whole new way of, of how engagement's happening, how people are closed, looping their, their votes, their, their votes of confidence or votes with their wallet. Um, and some brands which are artists now, influencers. I mean, this is a whole game-changing instrumentation level. >>I think that's what we are seeing right now is super re invigorating as a marketeer who has been around for a few years, basically. Um, I think that the shift in the web brands are going to communicate and engage with our audiences is profound. It's probably as revolutionary and even more revolutionary than the movement for, uh, brands in getting into digital. And you have that sentiment of a gold rush right now with a lot of brands that are trying to understand NFTs and, and how to actually engage with those communities and those audiences, um, dominate levels in which brands and influencers are going to engage. There are many influencers that actually advanced the message and the mission because the explosion of content on web tree has been crazy. Part of that is due to the network effect nature of crypto, because as Jeremiah mentioned, people are incentivized to promote projects, holders of an NFTA, also incentivized to promote it. So you end up with a flywheel, which is pretty unique of people that are hyping the project, and that are educating other people about it and commenting on the ecosystem, uh, with IP rights, being given to NFT holders, you're going to see people pull a brand since then of the brands actually having to. And so the notion of brands, again, judging and delivering, you know, elements of the value to their fans is something that's super attractive, extremely interesting. And I think, again, we've hardly scratched the surface of all that is possible in that. >>It's interesting. You guys are bringing some great insight here, Jeremiah, the old days, the word authentic was a kind of a cliche and brands like tried to be authentic and they didn't really know what to do. They called it organic, right? And now you have the trust concept with aura authenticity and environment like web three, where you can actually measure it and monetize it and capture it if you're actually authentic and trustworthy. >>That's right. And because it's on blockchain, you can see how somebody is behave with their economic behavior. In the past, of course, big corporations. Aren't going to have that type of trail on blockchain just yet. But the individuals and executives who participate in this market might be, and we'll also see a new types of affinity. Do you executives, do they participate in these NFT communities? Do they purchase them? We're seeing numerous brands like Adidas to acquire, uh, you know, different MTV projects to participate. And of course the big brands are grabbing their domains. Of course, you can talk to rant about that because it's owning your own name as a part of this trust and being >>That's awesome. Great insight guys. Closing comments, takeaways for the audience here. Each of you take a minute to give, share your thoughts on what you think is happening now, where it goes. All right, where's it going to go, Jeremy, we'll start with you. >>Sure. Um, I think the vision of web three, where full decentralization happens, where the power is completely shifted to the edges. I don't think it's going to happen. I think we will reach web 2.5 and I've been through so many tech trends where we said that the power is going to shift completely to the end. It just doesn't, there's two reasons. One is the venture capital are the ones who tend to own the pro programs in the first place. And secondly, the, the startups themselves end up becoming the one percenters. We see Airbnb and Uber are one-percenters now. So that trend happens over and over and over. Now with that said, the world will be in a better place. We will have more transparency. We will see economic power shifted to the people, the participants. And so they will have more control over the internet that they are building. >>Right. And final, final comments, >>Um, fully aligned with Jeremiah on the notions of control, being returned to users, the notion of ownership and the notion of redistribution of the economic value that is created across all the different chains, uh, uh, that we are going to see. And, and all those ecosystems. I believe that we are going to witness to palliate movements of expansion, one that is going to be very lateral. When you think of crypto and web three, essentially you think of a few hundred tribes. Uh, and I think that more projects are going to appear more, uh, coalitions of individuals and entities, and those are going to exist around those projects. So you're going to see an increase in the number of tribes that one might join. And I also think that we're going to progress rapidly from the low hundred millions of people and an FTE holders into the billions perfectly. Uh, and that's going to be extremely interesting. I think that the next wave of crypto users and Ft fans are going to look very different from the early adopters that we had witnessed in the very early days. So it's not going to be your traditional model of technology, adoption curves. I think the demographics going to shift and the motivations are going to be different as well, which is going to be a wonderful time to educate and engage with new community members. >>All right, Ron, Jeremy, thank you both for that great insight, great segment, uh, breaking down web three or web 2.5 as Jeremiah says, but we're in a better place. This is a segment with the influencers as part of the cubes and the unstoppable domain showcase. Um, John for your hosts. Thanks for watching.