>> TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Spain, everybody. We're here at the Theater Live and MWC 23. You're watching theCUBE's Continuous Coverage. This is day two. I'm Dave Vellante with my co-host, Dave Nicholson. Lisa Martin is also in the house. John Furrier out of our Palo Alto studio covering all the news. Check out silicon angle.com. Okay, we're going to dig into the core infrastructure here. We're going to talk a little bit about servers. Manya Rastogi is here. She's in technical marketing at Dell Technologies. And Abdel Bagegni is technical program manager at the Telecom Infra Project. Folks, welcome to theCUBE. Good to see you. >> Thank you. >> Abdel, what is the Telecom Infras Project? Explain to our audience. >> Yeah. So the Telecom Infra Project is a US based non-profit organization community that brings together different participants, suppliers, vendors, operators SI's together to accelerate the adoption of open RAN and open interface solutions across the globe. >> Okay. So that's the mission is open RAN adoption. And then how, when was it formed? Give us the background and some of the, some of the milestones so far. >> Yeah. So the telecom infra project was established five years ago from different vendor leaders and operators across the globe. And then the mission was to bring different players in to work together to accelerate the adoption of, of open RAN. Now open RAN has a lot of potential and opportunities, but in the same time there's challenges that we work together as a community to facilitate those challenges and overcome those barriers. >> And we've been covering all week just the disaggregation of the network. And you know, we've seen this movie sort of before playing out now in, in telecom. And Manya, this is obviously a compute intensive environment. We were at the Dell booth earlier this morning poking around, beautiful booth, lots of servers. Tell us what your angle is here in this marketplace. >> Yeah, so I would just like to say that Dell is kind of leading or accelerating the innovation at the telecom edge with all these ruggedized servers that we are offering. So just continuing the mission, like Abdel just mentioned for the open RAN, that's where a lot of focus will be from these servers will be, so XR 8000, it's it's going to be one of the star servers for telecom with, you know, offering various workloads. So it can be rerun, open run, multi access, edge compute. And it has all these different features with itself and the, if we, we can talk more about the performance gains, how it is based on the Intel CPUs and just try to solve the purpose like along with various vendors, the whole ecosystem solve this challenge for the open RAN. >> So Manya mentioned some of those infrastructure parts. Does and do, do you say TIP or T-I-P for short? >> Abdel: We say TIP. >> TIP. >> Abdel: T-I-P is fine as well. >> Does, does, does TIP or T-I-P have a certification process or a, or a set of guidelines that someone like Dell would either adhere to or follow to be sort of TIP certified? What does that look like? >> Yeah, of course. So what TIP does is TIP accredits what solutions that actually work in a real commercial grade environment. So what we do is we bring the different players together to come up with the most efficient optimized solution. And then it goes through a process that the community sets the, the, the criteria for and accepts. And then once this is accredited it goes into TIP exchange for other operators and the participants and the industry to adopt. So it's a well structured process and it's everything about how we orchestrate the industry to come together and set those requirements and and guidelines. Everything starts with a use case from the beginning. It's based on operators requirements, use cases and then those use cases will be translated into a solution that the industry will approve. >> So when you say operator, I can think of that sort of traditionally as the customer side of things versus the vendor side of things. Typically when organizations get together like TIP, the operator customer side is seeking a couple of things. They want perfect substitutes in all categories so that they could grind vendors down from a price perspective but they also want amazing innovation. How do you, how do you deliver both? >> Yeah, I mean that's an excellent question. We be pragmatic and we bring all players in one table to discuss. MNO's want this, vendors can provide a certain level and we bring them together and they discuss and come up with something that can be deployed today and future proof for the future. >> So I've been an enterprise technology observer for a long time and, you know, I saw the, the attempt to take network function virtualization which never really made much of an impact, but it was a it was the beginning of the enterprise players really getting into this market. And then I would see companies, whether it was Dell or HPE or Cisco, they'd take an X 86 server, put a cool name on it, edge something, and throw it over the fence and that didn't work so well. Now it's like, Manya. We're starting to get serious. You're building relationships. >> Manya: Totally. >> I mentioned we were at the Dell booth you're actually building purpose built systems now for this, this segment. Tell us what's different about this market and the products that you're developing for this market than say the commercial enterprise. >> So you are absolutely right, like, you know, kind of thinking about the journey, there has been a lot of, it has been going for a long time for all these improvements and towards going more open disaggregated and overall that kind of environment and what Dell brings together with our various partners and particularly if you talk about Intel. So these servers are powered by the players four gen intel beyond processors. And so what Intel is doing right now is providing us with great accelerators like vRAN Boost. So it increases performance like doubles what it was able to do before. And power efficiency, it has been an issue for a long, long time and it still continues but there is some improvement. For example 20% reduction overall with the power savings. So that's a step forward in that direction. And then we have done some of our like own testing as well with these servers and continuing that, you know it's not just telecom but also going towards Edge or inferencing like all these comes together not just X 30,000 but for example XR 56 10, 70, 76 20. So these are three servers which combines together to like form telecom and Edge and covers altogether. So that's what it is. >> Great, thank you. So Abdel, I mean I think generally people agree that in the fullness of time all radio access networks are going to be open, right? It's just a matter of okay, how do we get there? How do we make sure that it has the same, you know, quality of service characteristics. So where are we on on that, that journey from your perspective? And, and maybe you could project what, what it's going to look like over this decade. 'Cause it's going to take, you know, years. >> It's going to take a bit of time to mature and be a kind of a plug and play different units together. I think there was a lot, there was a, was a bit of over-promising in a few, in the last few years on the acceleration of open RAN deployment. That, well, a TIP is trying to do is trying to realize the pragmatic approach of the open run deployment. Now we know the innovation cannot happen when you have a kind of closed interfaces when you allow small players to be within the market and bring the value to, to the RAN areas. This is where the innovation happens. I think what would happen on the RAN side of things is that it would be driven by use cases and the operators. And the minute that the operators are no longer can depend on the closed interface vendors because there's use cases that fulfill that are requires some open RAN functionality, be the, the rig or the SMO layers and the different configurations of the rUSE getting the servers to the due side of things. This kind of modular scalability on this layer is when the RAN will, the Open RAN, would boost. This would happen probably, yeah. >> Go ahead. >> Yeah, it would happen in, in the next few years. Not next year or the year after but definitely something within the four to five years from now. >> I think it does feel like it's a second half of the decade and you feel like the, the the RAN intelligent controller is going to be a catalyst to actually sort of force the world into this open environment. >> Let's say that the Rick and the promises that were given to, to the sun 10 years ago, the Rick is realizing it and the closed RAN vendors are developing a lot on the Rick side more than the other parts of the, of the open RAN. So it will be a catalyst that would drive the innovation of open RAN, but only time will tell. >> And there are some naysayers, I mean I've seen some you know, very, very few, but I've seen some works that, oh the economics aren't there. It'll, it'll never get there. What, what do you, what do you say to that? That, that it won't ever, open RAN won't ever be as cost effective as you know, closed networks. >> Open RAN will open innovations that small players would have the opportunity to contribute to the, to the RAN space. This opportunity is not given to small players today. Open RAN provides this kind of opportunity and given that it's a path for innovation, then I would say that, you know, different perspectives some people are making sure that, you know the status quo is the way forward. But it would certainly put barriers on on innovation and this is not the way forward. >> Yeah. You can't protect the past in the future. My own personal opinion is, is that it doesn't have to be comparable from a, from a TCO perspective it can be close enough. It's the innovative, same thing with like you watch the, the, the adoption of Cloud. >> Exactly. >> Like cloud was more expensive it's always more expensive to rent, but people seem to be doing public Cloud, you know, because of the the innovation capabilities and the developer capabilities. Is that a fair analogy in this space, do you think? >> I mean this is what all technologies happens. >> Yeah. >> Right? It starts with a quite costly and then the the cost will start dropping down. I mean the, the cost of, of a megabyte two decades ago is probably higher than what it costly terabyte. So this is how technology evolves and it's any kind of comparison, either copper or even the old generation, the legacy generations could be a, a valid comparison. However, they need to be at a market demand for something like that. And I think the use cases today with what the industry is is looking for have that kind of opportunity to pull this kind of demand. But, but again, it needs to go work close by the what happens in the technology space, be it, you know we always talk about when we, we used to talk about 5G, there was a lot of hypes going on there. But I think once it realized in, in a pragmatic, in a in a real life situation, the minutes that governments decide to go for autonomous vehicles, then you would have limitations on the current closed RAN infrastructures and you would definitely need something to to top it up on the- >> I mean, 5G needs open RAN, I mean that's, you know not going to happen without it. >> Exactly. >> Yeah, yeah. But, but what is, but what would you say the most significant friction is between here and the open RAN nirvana? What are, what are the real hurdles that need to be overcome? There's obviously just the, I don't want to change we've been doing this the same way forever, but what what are the, what are the real, the legitimate concerns that people have when we start talking about open RAN? >> So I think from a technology perspective it will be solved. All of the tech, I mean there's smart engineers in the world today that will fix, you know these kind of problems and all of the interability, interruptability issues and, and all of that. I think it's about the mindset, the, the interfaces between the legacy core and RAN has been became more fluid today. We don't have that kind of a hard line between these kind of different aspects. We have the, the MEC coming closer to the RAN, we have the RAN coming closer to the Core, and we have the service based architectures in the Core. So these kind of things make it needs a paradigm shift between how operators that would need to tackle the open RAN space. >> Are there specific deployment requirements for open RAN that you can speak to from your perspective? >> For sure and going in this direction, like, you know evolution with the technology and how different players are coming together. Like that's something I wanted to comment from the previous question. And that's where like, you know these servers that Dell is offering right now. Specific functionality requirements, for example, it's it's a small server, it's short depth just 430 millimeters of depth and it can fit anywhere. So things like small form factor, it's it's crucial because if you, it can replace like multiple servers 10 years ago with just one server and you can place it like near a base band unit or to a cell site on top of a roof wherever. Like, you know, if it's a small company and you need this kind of 5G connection it kind of solves that challenge with this server. And then there are various things like, you know increasing thermals for example temperatures. It is classified like, you know kind of compliant with the negative 5 to 55 degree Celsius. And then we are also moving towards, for example negative 20 to 65 degree Celsius. Which is, which is kind of great because in situations where, which are out of our hands and you need specific thermals for those situations that's where it can solve that problem. >> Are those, are those statistics in those measurements different than the old NEB's standards, network equipment building standards? Or are they, are they in line with that? >> It is, it is a next step. Like so most of our servers that we have right now are negative five to five degree Celsius, for especially the extremely rugged server series and this one XR 8,000 which is focused for the, it's telecom inspired so it's focused on those customers. So we are trying to come up like go a step ahead and also like offering this additional temperatures testing and yeah compliance. So, so it is. >> Awesome. So we, I said we were at the booth early today. Looks like some good traffic people poking around at different, you know, innovations you got going. Some of the private network stuff is kind of cool. I'm like how much does that cost? I think I might like one of those, you know, but- >> [Private 5G home network. >> Right? Why not? Guys, great to have you on the show. Thanks so much for sharing. Appreciate it. >> Thank you. >> Thank you so much. >> Okay. For Dave Nicholson and Lisa Martin this is Dave Vellante, theCUBE's coverage. MWC 23 live from the Fida in Barcelona. We'll be right back. (outro music)

>>The Cube presents Ignite 22, brought to you by Palo Alto Networks. >>Welcome back everyone. We're so glad that you're still with us. It's the Cube Live at the MGM Grand. This is our second day of coverage of Palo Alto Networks Ignite. This is takeaways from Ignite 22. Lisa Martin here with two really smart guys, Dave Valante. Dave, we're joined by one of our cube alumni, a friend, a friend of the, we say friend of the Cube. >>Yeah, F otc. A friend of the Cube >>Karala joins us. Guys, it's great to have you here. It's been an exciting show. A lot of cybersecurity is one of my favorite topics to talk about. But I'd love to get some of the big takeaways from both of you. Dave, we'll start with >>You. A breathing room from two weeks ago. Yeah, that was, that was really pleasant. You know, I mean, I know was, yes, you sat in the analyst program, interested in what your takeaways were from there. But, you know, coming into this, we wrote a piece, Palo Alto's Gold Standard, what they need to do to, to keep that, that status. And we hear it a lot about consolidation. That's their big theme now, which is timely, right? Cause people wanna save money, they wanna do more with less. But I'm really interested in hearing zeus's thoughts on how that's playing in the market. How customers, how easy is it to just say, oh, hey, I'm gonna consolidate. I wanna get into that a little bit with you, how well the strategy's working. We're gonna get into some of the m and a activity and really bring your perspectives to the table. Well, >>It's, it's not easy. I mean, people have been calling for the consolidation of security for decades, and it's, it's, they're the first company that's actually made it happen. Right? And, and I think this is what we're seeing here is the culmination of this long-term strategy, this company trying to build more of a platform. And they, you know, they, they came out as a firewall vendor. And I think it's safe to say they're more than firewall today. That's only about two thirds of their revenue now. So down from 80% a few years ago. And when I think of what Palo Alto has become, they're really a data company. Now, if you look at, you know, unit 42 in Cortex, the, the, the Cortex Data Lake, they've done an excellent job of taking telemetry from their products and from the acquisitions they have, right? And bringing that together into one big data lake. >>And then they're able to use that to, to do faster threat notification, forensics, things like that. And so I think the old model of security of create signatures for known threats, it's safe to say it never really worked and it wasn't ever gonna work. You had too many days, zero exploits and things. The only way to fight security today is with a AI and ML based analytics. And they have, they're the gold standard. I think the one thing about your post that I would add, they're the gold standard from a data standpoint. And that's given them this competitive advantage to go out and become a platform for security. Which, like I said, the people have tried to do that for years. And the first one that's actually done it, well, >>We've heard this from some of the startups, like Lacework will say, oh, we treat security as a data problem. Of course there's a startup, Palo Alto's got, you know, whatever, 10, 15 years of, of, of history. But one of the things I wanted to explore with you coming into this was the notion of can you be best of breed and develop a suite? And we, we've been hearing a consistent answer to that question, which is, and, and do you need to, and the answer is, well, best of breed in security requires that full spectrum, that full view. So here's my question to you. So, okay, let's take Estee win relatively new for these guys, right? Yeah. Okay. And >>And one of the few products are not top two, top three in, right? >>Exactly. Yeah. So that's why I want to take that. Yeah. Because in bakeoffs, they're gonna lose on a head-to-head best of breed. And so the customer's gonna say, Hey, you know, I love your, your consolidation play, your esty win's. Just, okay, how about a little discount on that? And you know, these guys are premium priced. Yes. So, you know, are they in essentially through their pricing strategies, sort of creating that stuff, fighting that, is that friction for them where they've got, you know, the customer says, all right, well forget it, we're gonna go stove pipe with the SD WAN will consolidate some of the stuff. Are you seeing that? >>Yeah, I, I, I still think the sales model is that way. And I think that's something they need to work on changing. If they get into a situation where they have to get down into a feature battle of my SD WAN versus your SD wan, my firewall versus your firewall, frankly they've already lost, you know, because their value prop is the suite and, and is the platform. And I was talking with the CISO here that told me, he realizes now that you don't need best of breed everywhere to have best in class threat protection. In fact, best of breed everywhere leads to suboptimal threat protection. Cuz you have all these data data sets that are in silos, right? And so from a data scientist standpoint, right, there's the good data leads to good insights. Well, partial data leads to fragmented insights and that's, that's what the best, best of breed approach gives you. And so I was talking with Palo about this, can they have this vision of being best of breed and platform? I don't really think you can maintain best of breed everywhere across this portfolio this big, but you don't need to. >>That was my second point of my question. That's the point I'm saying. Yeah. And so, cuz cuz because you know, we've talked about this, that that sweets always win in the long run, >>Sweets win. >>Yeah. But here's the thing, I, I wonder to your your point about, you know, the customer, you know, understanding that that that, that this resonates with them. I, my guess is a lot of customers, you know, at that mid-level and the fat middle are like still sort of wed, you know, hugging that, that tool. So there's, there's work to be done here, but I think they, they, they got it right Because if they devolve, to your point, if they devolve down to that speeds and feeds, eh, what's the point of that? Where's their >>Valuable? You do not wanna get into a knife fight. And I, and I, and I think for them the, a big challenge now is convincing customers that the suite, the suite approach does work. And they have to be able to do that in actual customer examples. And so, you know, I I interviewed a bunch of customers here and the ones that have bought into XDR and xor and even are looking at their sim have told me that the, the, so think of soc operations, the old way heavily manually oriented, right? You have multiple panes of glass and you know, and then you've got, so there's a lot of people work before you bring the tools in, right? If done correctly with AI and ml, the machines would do all the heavy lifting and then you'd bring people in at the end to clean up the little bits that were missed, right? >>And so you, you moved to, from something that was very people heavy to something that's machine heavy and machines can work a lot faster than people. And the, and so the ones that I've talked that have, that have done that have said, look, our engineers have moved on to a lot different things. They're doing penetration testing, they're, you know, helping us with, with strategy and they're not fighting that, that daily fight of looking through log files. And the only proof point you need, Dave, is look at every big breach that we've had over the last five years. There's some SIM vendor up there that says, we caught it. Yeah. >>Yeah. We we had the data. >>Yeah. But, but, but the security team missed it. Well they missed it because you're, nobody can look at that much data manually. And so the, I I think their approach of relying heavily on machines to fight the fight is actually the right way. >>Is that a differentiator for them versus, we were talking before we went live that you and I first hit our very first segment back in 2017 at Fort Net. Is that, where do the two stand in your >>Yeah, it's funny cuz if you talk to the two vendors, they don't really see each other in a lot of accounts because Fort Net's more small market mid-market. It's the same strategy to some degree where Fort Net relies heavily on in-house development in Palo Alto relies heavily on acquisition. Yeah. And so I think from a consistently feature set, you know, Fort Net has an advantage there because it, it's all run off their, their their silicon. Where, where Palo's able to innovate very quickly. The, it it requires a lot of work right? To, to bring the front end and back ends together. But they're serving different markets. So >>Do you see that as a differentiator? The integration strategy that Palo Alto has as a differentiator? We talk to so many companies who have an a strong m and a strategy and, and execution arm. But the challenge is always integrating the technology so that the customer to, you know, ultimately it's the customer. >>I actually think they're, they're underrated as a, an acquirer. In fact, Dave wrote a post to a prior on Silicon Angle prior to Accelerate and he, he on, you put it on Twitter and you asked people to rank 'em as an acquirer and they were in the middle of the pack, >>Right? It was, it was. So it was Oracle, VMware, emc, ibm, Cisco, ServiceNow, and Palo Alto. Yeah. Or Oracle got very high marks. It was like 8.5 out of, you know, 10. Yeah. VMware I think was 6.5. Naira was high emc, big range. IBM five to seven. Cisco was three to eight. Yeah. Yeah, right. ServiceNow was a seven. And then, yeah, Palo Alto was like a five. And I, which I think it was unfair. Well, >>And I think it depends on how you look at it. And I, so I think a lot of the acquisitions Palo Alto's made, they've done a good job of integrating the backend data and they've almost ignored the front end. And so when you buy some of the products, it's a little clunky today. You know, if you work with Prisma Cloud, it could be a little bit cleaner. And even with, you know, the SD wan that took 'em a long time to bring CloudGenix in and stuff. But I think the approach is right. I don't, I don't necessarily believe you should integrate the front end until you've integrated the back end. >>That's >>The hard part, right? Because UL ultimately what you're gonna get, you're gonna get two panes of glass and one pane of glass and it might look pretty and all mush together, but ultimately you're not solving the bigger problem, right. Of, of being able to create that big data lake to, to fight security. And so I think, you know, the approach they've taken is the right one. I think from a user standpoint, maybe it doesn't show up as neatly because you don't see the frontend integration, but the way they're doing it is the right way to do it. And I'm glad they're doing it that way versus caving to the pressures of what, you know, the industry might want or >>Showed up in the performance of the company. I mean, this company was basically gonna double revenues to 7 billion from 2020 to >>2023. Think about that at that. That makes, >>I mean that's unbelievable, right? I mean, and then and they wanna double again. Yeah. You know, so, well >>What did, what did Nikesh was quoted as saying they wanna be the first cyber company that's a hundred billion dollars. He didn't give a timeline market >>Cap. Right. >>Market cap, right. Do what I wanna get both of your opinions on what you saw and heard and felt this week. What do you think the likelihood is? And and do you have any projections on how, you know, how many years it's gonna take for them to get there? >>Well, >>Well I think so if they're gonna get that big, right? And, and we were talking about this pre-show, any company that's becoming a big company does it through ecosystem >>Bingo >>Go, right? And that when you look around the show floor, it's not that impressive. No. And if that, if there's an area they need to focus on, it's building that ecosystem. And it's not with other security vendors, it's with application vendors and it's with the cloud companies and stuff. And they've got some relationships there, but they need to do more. I actually challenge 'em on that. One of the analyst sessions. They said, look, we've got 800 cortex partners. Well where are they? Right? Why isn't there a cortex stand here with a bunch of the small companies here? So I do think that that is an area they need to focus on. If they are gonna get to that, that market caps number, they will do so do so through ecosystem. Because every company that's achieved that has done it through ecosystem. >>A hundred percent agree. And you know, if you look at CrowdStrike's ecosystem, it's, I mean, pretty similar. Yeah. You know, it doesn't really, you know, make much, much, not much different from this, but I went back and just looked at some, you know, peak valuations during the pandemic and shortly thereafter CrowdStrike was 70 billion. You know, that's what their roughly their peak Palo Alto was 56, fortune was 59 for the actually diverged. Right. And now Palo Alto has taken the, the top mantle, you know, today it's market cap's 52. So it's held 93% of its peak value. Everybody else is tanking. Even Okta was 45 billion. It's been crushed as you well know. But, so Palo Alto wasn't always, you know, the number one in terms of market cap. But I guess my point is, look, if CrowdStrike could got to 70 billion during Yeah. During the frenzy, I think it's gonna take, to answer your question, I think it's gonna be five years. Okay. Before they get back there. I think this market's gonna be tough for a while from a valuation standpoint. I think generally tech is gonna kind of go up and down and sideways for a good year and a half, maybe even two years could be even longer. And then I think there's gonna be some next wave of productivity innovation that that hits. And then you're gonna, you're almost always gonna exceed the previous highs. It's gonna take a while. Yeah. >>Yeah, yeah. But I think their ability to disrupt the SIM market actually is something that I, I believe they're gonna do. I've been calling for the death of the sim for a long time and I know some people of Palo Alto are very cautious about saying that cuz the Splunks and the, you know, they're, they're their partners. But I, I think the, you know, it's what I said before, the, the tools are catching them, but they're, it's not in a way that's useful for the IT pro and, but I, I don't think the SIM vendors have that ecosystem of insight across network cloud endpoint. Right. Which is what you need in order to make a sim useful. >>CISO at an ETR round table said, if, if it weren't for my regulators, I would chuck my sim. >>Yes. >>But that's the only reason that, that this person was keeping it. No. >>Yeah. And I think the, the fact that most of those companies have moved to a perpetual MO or a a recurring revenue model actually helps unseat them. Typically when you pour a bunch of money into something, you remember the old computer associate says nobody ever took it out cuz the sunk dollars you spent to do it. But now that you're paying an annual recurring fee, it's actually makes it easier to take out. So >>Yeah, it's just an ebb and flow, right? Yeah. Because the maintenance costs were, you know, relatively low. Maybe it was 20% of the total. And then, you know, once every five years you had to do a refresh and you were still locked into the sort of maintenance and, and so yeah, I think you're right. The switching costs with sas, you know, in theory anyway, should be less >>Yeah. As long as you can migrate the data over. And I think they've got a pretty good handle on that. So, >>Yeah. So guys, I wanna get your perspective as a whole bunch of announcements here. We've only been here for a couple days, not a big conference as, as you can see from behind us. What Zs in your opinion was Palo Alto's main message and and what do you think about it main message at this event? And then same question for you. >>Yeah, I, I think their message largely wrapped around disruption, right? And, and they, and The's keynote already talked about that, right? And where they disrupted the firewall market by creating a NextGen firewall. In fact, if you look at all the new services they added to their firewall, you, you could almost say it's a NextGen NextGen firewall. But, but I do think the, the work they've done in the area of cloud and cortex actually I think is, is pretty impressive. And I think that's the, the SOC is ripe for disruption because it's for, for the most part, most socks still, you know, run off legacy playbooks. They run off legacy, you know, forensic models and things and they don't work. It's why we have so many breaches today. The, the dirty little secret that nobody ever wants to talk about is the bad guys are using machine learning, right? And so if you're using a signature based model, all they gotta do is tweak their model a little bit and it becomes, it bypasses them. So I, I think the only way to fight the the bad guys today is with you're gonna fight fire with fire. And I think that's, that's the path they've, they've headed >>Down. Yeah. The bad guys are hiding in plain sight, you know? Yeah, >>Yeah. Well it's, it's not hard to do now with a lot of those legacy tools. So >>I think, I think for me, you know, the stat that we threw out earlier, I think yesterday at our keynote analysis was, you know, the ETR data shows that are, that are that last survey around 35% of the respondents said we are actively consolidating, sorry, 44%, sorry, 35 says who are actively consolidating vendors, redundant vendors today that number's up to 44%. Yeah. It's by far the number one cost optimization technique. That's what these guys are pitching. And I think it's gonna resonate with people and, and I think to your point, they're integrating at the backend, their beeps are technical, right? I mean, they can deal with that complexity. Yeah. And so they don't need eye candy. Eventually they, they, they want to have that cuz it'll allow 'em to have deeper market penetration and make people more productive. But you know, that consolidation message came through loud and clear. >>Yeah. The big change in this industry too is all the new startups are all cloud native, right? They're all built on Amazon or Google or whatever. Yeah. And when your cloud native and you buy a cloud native integration is fast. It's not like having to integrate this big monolithic software stack anymore. Right. So I, I think their pace of integration will only accelerate from here because everything's now cloud native. >>If a customer comes to you or when a customer comes to you and says, Zs help us with this cyber transformation we have, our board isn't necessarily aligned with our executives in terms of execution of a security strategy. How do you advise them where Palo Alto is concerned? >>Yeah. You know, a lot, a lot of this is just fighting legacy mindset. And I've, I was talking with some CISOs here from state and local governments and things and they're, you know, they can't get more budget. They're fighting the tide. But what they did find is through the use of automation technology, they're able to bring their people costs way down. Right. And then be able to use that budget to invest in a lot of new projects. And so with that, you, you have to start with your biggest pain points, apply automation where you can, and then be able to use that budget to reinvest back in your security strategy. And it's good for the IT pros too, the security pros, my advice to the IT pros is, is if you're doing things today that aren't resume building, stop doing them. Right. Find a way to automate the money your job. And so if you're patching systems and you're looking through log files, there's no reason machines can't do that. And you go do something a lot more interesting. >>So true. It's like storage guys 10 years ago, provisioning loans. Yes. It's like, stop doing that. Yeah. You're gonna be outta a job. So who, last question I have is, is who do you see as the big competitors, the horses on the track question, right? So obviously Cisco kind of service has led for a while and you know, big portfolio company, CrowdStrike coming at it from end point. You know who, who, who do you see as the real players going for that? You know, right now the market's three to 4%. The leader has three, three 4% of the market. You know who they're all going for? 10, 15, maybe 20% of the market. Who, who are the likely candidates? Yeah, >>I don't know if CrowdStrike really has the breadth of portfolio to compete long term though. I I think they've had a nice run, but I, we might start to see the follow 'em. I think Microsoft is gonna be for middle. They've laid down the gauntlet, right? They are a security vendor, right? We, we were at Reinvent and a AWS is the platform for security vendors. Yes. Middle, somewhere in the middle. But Microsoft make no mistake, they're in security. They've got some good products. I think a lot of 'em are kind of good enough and they, they tie it to the licensing and I'm not sure that works in security, but they've certainly got the ear of a lot of it pros. >>It might work in smb. >>Yeah, yeah. It, it might. And, and I do like Zscaler. I, I know these guys poo poo the proxy model, but they've, they've done about as much with prox as you can. And I, I think it's, it's a battle of, I love the, the, the near, you know, proxies are dead and Jay's model, you know, Jay over at csca, throw 'em back at 'em. So I, it's good to see that kind of fight going on between the >>Two. Oh, it's great. Well, and, and again, ZScaler's coming at it from their cloud security angle. CrowdStrike's coming at it from endpoint. I, I do think CrowdStrike has an opportunity to build out the portfolio through m and a and maybe ecosystem. And then obviously, you know, Palo Alto's getting it done. How about Cisco? >>Yeah, Cisco's interesting. And I I think if Cisco can make the network matter in security and it should, right? We're talking about how a lot of you need a lot of forensics to fight security today. Well, they're gonna see things long before anybody else because they have all that network data. If they can tie network security, I, I mean they could really have that business take off. But we've been saying that about Cisco for 20 years. >>But big install based though. Yeah. It's hard for a company, any company to say, okay, hey Cisco customer sweep the floor and come with us. That's, that's >>A tough thing. They have a lot of good peace parts, right? And like duo's a good product and umbrella's a good product. They've, they've not done a good job. >>They're the opposite of these guys. >>They've not done a good job of the backend integration and that, that's where Cisco needs to, to focus. And I do think g G two Patel there fixed the WebEx group and I think he's now, in fact when you talk to him, he's doing very little on WebEx that that group's running itself and he's more focused in security. So I, I think we could see a resurgence there. But you know, they have a, from a revenue perspective, it's a little misleading cuz they have this big legacy base that's in decline while they're moving to cloud and stuff. So, but they, but they, there's a lot of Rick there trying to, to tie to network. >>Lots of fuel for conversation. We're gonna have to carry this on, on Silicon angle.com guys. Yes. And Wi KeePon. Lets do see us. Thank you so much for joining Dave and me giving us your insights as to this event. Where are gonna be next? Are you gonna be on >>Vacation? There's nothing more fun than mean on the cube. So what's outside of that though? Yeah, you know, Christmas coming up, I gotta go see family and be the obligatory, although for me that's a lot of travel, so I guess >>More planes. Yeah. >>Hopefully not in Vegas. >>Not in Vegas. >>Awesome. Nothing against Vegas. Yeah, no, >>We love it. We love >>It. Although I will say my year started off with ces. Yeah. And it's finishing up with Palo Alto here. The bookends. Yeah, exactly. In Vegas bookends. >>Well thanks so much for joining us. Thank you Dave. Always a pleasure to host a show with you and hear your insights. Reading your breaking analysis always kicks off my prep for show. And it, it's always great to see, but predictions come true. So thank you for being my co-host bet. All right. For Dave Valante Enz as Carla, I'm Lisa Martin. You've been watching The Cube, the leader in live, emerging and enterprise tech coverage. Thanks for watching.

(upbeat music) >> Welcome back to Las Vegas, guys and girls. We're so happy that you're with us. This is our first full day of coverage live on theCube at AWS re:Invent '22. We're in Vegas, as I said at the Venetian Expo one of the biggest places to host, and there's probably about 50,000 people here or so. Lisa Martin and Dave Vellante Dave, we've had such great conversations. We talked about data, data, data. Every company is a data company. The most important thing is to make sure that data is accessible, that there's insights gained from it, but that it's protected and recoverable should anything happen. >> Yeah, security is the most important topic right now. We all know that it's the number one priority. The Cloud has changed the security model. the shared responsibility model is great, but at the same time, now you got shared responsibilities across multiple clouds, your developers are being asked to do more, right? It kind of the audit is like the last line of defense. So what the ecosystem does with AWS is really make the CISO's job easier. As opposed to, I mean AWS is a friendly place for security companies and I'm excited to talk about that. >> Yeah, we're going to be unpacking that. Rick Holtman is here, the VP of Advertising and Media Security at Human Security. Rick, welcome to theCUBE. >> Oh, thank you so much. Thanks for having me on. >> Pleasure to have you on here. So talk to us about Human Security. What do you do, what are the differentiators and what's in the name? >> Sure. Human is a cybersecurity company. It's been around for about 12 years right now, and our mission is truly to disrupt the economics of cyber crime. And right now, businesses are under attack like they have not been before. There's been a proliferation of bots on site that are truly hitting people's businesses. And what everyone will understand is that when bots hit your site and permeate your business, you'll never end up with a positive business outcome. >> Let's just say. What are in terms of competitive differentiators, when you're in customer conversations, what are those top three things that you say, this is why you go Human. >> Yeah, and that's great. This is why you go Human. We have a tremendous sensor network and what that gives us is observability. Because of our clients and partners, we're actually able to see 20 trillion transactions a week that we filter. And what that does is enables us to look across a broad spectrum of industry. Because of our partner networks, we're able to see all the media transacted across this ecosystem. And what we're working to do is preserve and protect that. So when we work with an SSP, DSP, ad servers and truly the pillars of technology across media, those are our core clients. And we very quickly, in under 10 milliseconds, let them know is this a bot or a human being you're about to serve an ad to, which is paramount to saving them money and not wasting their precious ad dollars. >> So what am I buying from you? Is it a subscription? Explain that. >> Sure. You're buying a subscription to the Human Defense Platform, and across that platform we've got multiple cyber tools. And what we do is we'll take different combinations of those tools and create a specific solution to address a use case. Each one of these businesses is very unique, so we had to be very flexible and malleable with the tools that we use and be able to create custom solutions, which is really what sets us apart in market. >> What are some of the key use cases that you're helping customers to address? >> Sure. It can be anything from simply guarding a website, and actually providing insights and the ability to mitigate bots, it can be guarding against account takeover, form fills. There are so many ways and attack vectors right now for people to get us at that we've got multiple disciplinary ways of looking at how to deploy solutions. It is going to continue to grow because we're seeing more and more new platforms and new types of innovation. A great example is in-game advertising. It is very new, but the industry is starting to look at it and say, hey, we know as growth comes, we're going to see fraud. How do we get out in front of that? How do we make sure that we don't have the same issue we had with CTV? Explosive growth happen before standards were in place, and now we're playing catch up and it's a huge issue. >> How are you doing that as the fraudsters are just getting more and more sophisticated? >> And that's really the problem. I think you hit it on the head. They'll continually change how they attack. They'll continually put resources behind it. And that's why I talk about disrupting the economics of cyber crime because the more we're able to mitigate and stop this, we actually make the cost of attack more and more expensive. Eventually, they're going to move on to a softer target and we want to harden up all of our clients so they're not that soft target. >> I always say, you're in the denominator business You get the bigger denominator, less value so they'll move on to somewhere else. What is your secret sauce? Is it your data? Is it your humans? >> You know, it's actually really three pillars. Part of what we talked about, which is observability. How much we're able to see because of the vast view through our partner network. And that's the other piece is this partner network. So we have what we'll call collective protection because we have so many different data inputs and understanding or what we'll call signal that we're able to interpret. And that is really one of our large differentiators. The last piece is disruption. So we'll use both the signal, our network, and truly go after these fraudsters and actually penalize 'em. And we are responsible for partly one of the largest ad fraud take downs, and someone is sitting in jail today because of it. >> Can you explain the anatomy of an ad hack? Like, what's that look like? I mean, I'm sure there's a lot of different profiles, but what's a common thing? >> And there's a few different profiles, right? One could simply be bots hitting your site, your homepage, right? That could skew data that will be used by a marketing team to make strategic decisions for a business. Form fills, account takeovers, there's all these different types of attack vectors. And then what we also specialize in across the programmatic industry is really reading what we'll call a bid stream. All these pieces of data that are going to come in, and that's how we can actually take a look at the device, the IP, and some of these signals when you put them all together, they give us a true picture of is this a human being or an automated bot swarm trying to permeate a business? >> Okay, and the automated bot swarm. So take it from the hacker's point of view. What's their objective of, you know, hitting you with those bots? What happens after they flood the zone? >> It really depends what they want. In certain cases it could be to actually take over someone's account and buy things. It can be, again, hitting the marketing component and actually driving differentiation on someone's site with form fills and surveys. So there's lots of different ways that they come to us. Inside the bid streams we're able to stop quickly because we're really high up in the actual food chain of that technology. So before some of these ad servers make a single decision, they'll make a call to Human and we'll quickly tell them serve this ad or do not. >> And the profile is largely criminals, not so much nation-state attack, or is it? >> Well, it really could be a little bit of everybody. That's the toughest part to tell. I would say we deal mostly with criminals more than I think nation-states. And people that are simply going after money, and when they see soft targets and people that don't have either they're site hardened or a true understanding of what they're fighting against, they get taken advantage of very quickly. >> What are some of the positive business outcomes that your customers are achieving? Maybe you have a favorite customer story example that you think really shines light on the value that Human is delivering. >> Sure. There's a huge customer inside the media ecosystem, and they truly serve as the gatekeepers or barriers to a lot of fraud. They look at Human as a strategic partner to make sure that when we bring on customers, they're all above board and we are not actually allowing anyone to permeate this advertising and media ecosystem with fraud. So we work hand in glove with lots of the largest platforms across media to really make sure this ecosystem is protected as it can be. >> So- >> You have the sets... Oh, go ahead please. I'm sorry. >> I was going to say, but you do more than media, is that right? >> Absolutely. We have a tremendous enterprise side of our business as well. And that is looking at financials, hospitality companies, travel companies. We really work across a full ecosystem. Bots aren't siloed. They don't care what industry you're in. So we set up industry expertise and domain expertise both across the media spectrum, as well as other components so that we can go as deep as we need to to really mitigate this. >> So you've got this huge observation space, this kind of sensor network if you will. what's the proportionality between the number of channels that we've seen evolve, and the way that that attackers are approaching the hacks? >> Sure. I think, you know, when we look at channels or platforms, the moment a new platform opens up, it gets attacked and we're continually seeing this. So the minute there is money moving towards any sort of industry, you'll see fraud right behind it. So we very carefully track industries, and we make sure we understand the changes and evolutions that are happening so we can get out in front. And a great example is in-game advertising and audio in-game advertising. They're brand new and we're starting to see money shift there for the first time. So those are the companies that have come to us immediately and said, hey, we know what's coming next. The money's here, fraud's on the way, how can Human help us? >> We haven't talked about 5G. It's rare that we don't talk about 5G, but how is that going to affect your customers? >> 5G is really going to give everybody ubiquity in terms of access, right? The more access we have, it allows your device `to become an attack vector. >> It's going to open up more channels. >> Rick: That's right. That's right. >> And so how are you planning as that becomes more mainstream to help customers combat that? As things just keep changing, there's so much flux going on. >> And that's it. You know, cyber is polymorphic. It will continue to change on us. So we are constantly evolving, and one of the things I always like to talk about with Human is the depth of the talent inside the company. And we source cyber talent globally, truly globally. All over the world, we have humans working with extreme expertise. So we've got this global perspective of what's happening everywhere in the world right now. And we're really leveraging that tremendously to fight the economics of cyber crime. >> How are you helping with your expertise at Human, companies address the massive skills gap in cybersecurity? >> Well, that's exactly it. I think there's a lot of education going on. When we meet customers or prospects, we make sure they understand the gravity of the situation and make sure we can help them see and provide insights so they understand who's attacking them, what they're being attacked with, and how to fight back. >> So what's the next step for your technology approach? How should we think about your roadmap? What are your customers asking you 'cause it's hard, right? Like you said, it's polymorphic. Sometimes it's hard to predict, but at the same time, you know, it's like you defend against yourself. You know, you say, okay let's flip the equation. You know, where are weaknesses? What are you guys thinking about in the future? >> Sure, it's a great question. We've continued to build out the Human defense platform. We merged with another company about six months ago, and we just acquired a company as well. The reason we continue on this growth path is to continue to put products and services in place so that we can continue to grow and really actually mitigate against all the different potential attacks out there. So we'll continue to add products, we'll continue to add services because as we see more and more attacks coming, we've got a greater understanding of the how and the why. So we're actually building out products that specifically hit these new pockets in industry so we can get there first and really create a beachhead. >> And how do you work with AWS? >> Sure, AWS is strategic partner and they've done a great job of helping lean in with us. We're not only working with AWS, but working across their ecosystem and working with some of their partners as well and some of their clients as well. So we're really standing up this Human Defense Platform for our partners and direct clients as well. >> Can you give us any examples of that? >> I'm not really allowed to name names when it comes to that. I apologize, but it's truly across their entire partner network. >> Got it. What are some of the things that you've heard? We're only at day one, obviously of re:Invent '22. Anything that you've heard today, maybe during the keynote or some of the things on the show floor that really excite you about the direction that AWS is moving, and the opportunities that it's going to deliver to Human? >> Sure. Absolutely. I think one of the things that was mentioned today was their clean room initiative, and I think that is an excellent place where Human has a great fit. And I think that our filtering technology and our layer there will really make sure that a clean room stays clean, and that the data that is actually joined and used is pure data and not rife with any bots. >> Got it. Humansecurity.com. Last question, Rick. If you had a bumper sticker to put on a fancy shiny new car and it was about Human, what would it say? >> It would say, know who's real. Keep it human. >> Love it. Know who's real, keep it human. Rick, thank you so much for joining us on the program. >> Thanks so much for having me. >> Introducing Human Security to our audience. We appreciate that. Really exciting stuff and so needed, especially in today's dynamic cyber landscape. We appreciate your insights. >> Rick: My pleasure. Thank you guys. >> All right. For our guest and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE. The leader in live enterprise and emerging tech coverage. (soft bright music)

>>Hey everyone, and welcome back to The Cube's live coverage of AWS Reinvented 2022 Live from the Venetian Expo in Las Vegas. We're happy to be back. This is first full day of coverage over here last night. We've got three full days of coverage in addition to last night, and there's about 50,000 people here. This event is ready, people are ready to be back, which is so exciting. Lisa Martin here with Paul Gill and Paul, it's great to be back in person. Great to be hosting with you >>And likewise with you, Lisa. I think the first time we hosted again, >>It is our first time exactly. >>And we come here to the biggest event that the cube ever does during the year. >>It's the Super Bowl of the >>Cube. It's it's elbow to elbow out there. It's, it's, it's full tackle football, totally on the, on the floor of reinvent. And very exciting. This, you know, I've been to a lot of conferences going back 40 years, long as I can remember. Been going to tech conferences. This one, the, the intensity, the excitement around this is really unusual. People are jazzed, they're excited to be here, and that's great to see, particularly coming back from two years of isolation. >>Absolutely. The energy is so palpable. Even yesterday, evening, afternoon when I was walking in, you just feel it with all the people here. You know, we talk to so many different companies on the Q Paul. Every company these days has to be a data company. The most important thing about data is making sure that it's backed up and it's protected, that it's secure, that it can be recovered if anything happens. So we're gonna be having a great conversation next about data resiliency with one of our alumni. >>And that would be Rick Scott, Rick, excuse me, Rick Scott, >>Rick Clark. Rick Clark, say Rick Scott, cloud sales Veritas. Rick, welcome back >>To the program. Thank you. Thank you so much. It's a pleasure being here, you know, thank you so much. You're definitely very excited to myself and 40,000 of my closest cousins and friends all in one place. Yep. Or I could possibly go wrong, right? So >>Yeah, absolutely nothing. So, Rick, so Veritas has made some exciting announcements. Talk to us about some of the new things that you've >>Unveiled. Yeah, we've been, we've been incredibly busy and, you know, the journey that we've been on, one of the big announcement that we made about three or four weeks ago is the introduction, really, of a brand new cloud native data management platform that we call Veritas Alta. And this is a journey that we've been on for the better part of seven years. We actually started it with our, our flex appliances. We continued, that was a containerization of our traditional net backup business in, into a highly secured appliance that was loved by our customers. And we continued that theme and that investment into what we call a scale out and scale up form factor appliance as well, what we called flex scale. And then we continued on that investment theme, basically spending over a billion dollars over that seven year journey in our cloud native. And we call that basically the Veritas altar platform with our cloud native platform. And I think if you really look at what that is, it truly is a data management platform. And I emphasize the term cloud native. And so our traditional technologies around data protection, obviously application resiliency and digital compliance or data compliance and governance. We are the only, the first and only company in the world to provide really a cloud optimized, cloud native platform, really, that addresses that. So it's been fun, it's been a fun journey. >>Talk a little bit about the customer experience. I see over 85% of the Fortune 100 trust Veritas with their data management. That's >>A big number. Yeah. Yeah. It's, it is incredible actually. And it really comes back to the Veritas older platform. We sort of built that with, with four tenants in mind, all driving back to this very similar to AWS's customer obsession. Everything we do each and every day of our waiting moments is a Veritas employee is really surrounds the customer. So it starts with the customer experience on how do they find us to, how do they procure our solutions through things like AWS marketplace and how do they deploy it? And the second thing is around really cost optimization, as we know, you know, to, to say that companies are going through a digital transformation and moving workloads to the cloud. I mean, I've got customers that literally were 20% in cloud a year ago and 80% a year later, we've never seen that kind of velocity. >>And so we've doubled down on this notion of cost optimization. You can only do that with these huge investments that I talked about. And so we're a very profitable company. We've been around, got a great heritage of over 30 years, and we've really taken those investments in r and d to provide that sort of cloud native technology to ultimately make it elastic. And so everything from will spin up and spin down services to optimize the cloud bill for our customers, but we'll also provide the greatest workload support. You know, obviously on-prem workloads are very different from cloud workloads and it's almost like turning the clock back 20 years to see all of those new systems. There's no standard API like s and MP on the network. And so we have to talk to every single PAs service, every single DB PAs, and we capture that information and protect it. So it's really has been a phenomenal journey. It's been great. >>You said this, that that al represents a shift from clouds from flex scale to cloud native. What is the difference there? >>The, the main difference really is we took, you know, obviously our traditional product that you've known for many media years, net backup. It's got, you know, tens of millions of lines of code in that. And we knew if we lifted and shifted it up into the cloud, into an I AEs infrastructure, it's just not, it obviously would perform extremely well, but it wasn't cost optimized for our customer. It was too expensive to to run. And so what we did is we rewrote with microservices and containerization, Kubernetes huge parts of that particular product to really optimize it for the cloud. And not only have we done it for that technology, what we now call alter data protection, but we've done it across our entire port portfolio. That was really the main change that we made as part of this particular transition. And >>What have you done to prepare customers for that shift? Is this gonna be a, a drop in simple upgrade for them? >>Absolutely. Yeah. In fact, one of the things that we introduced is we, we invest still very heavily with regards to our OnPrem solutions. We're certainly not abandoning, we're still innovating. There's a lot of data still OnPrem that needs to move to the cloud. And so we have a unique advantage of all of the different workload supports that we provide OnPrem. We continue that expansion into the cloud. So we, we create it as part of the Veritas AL Vision, a technology, we call it AL view. So it's a single painter glass across both OnPrem and cloud for our customers. And so now they can actually see all of their data protection, all our application availability, single collect, all through that single unified interface, which is really game changing in the industry for us. >>It's game changing for customers too, because customers have what generally six to seven different backup technologies in their environment that they're having to individually manage and provision. So the, the workforce productivity improvements I can imagine are, are huge with Veritas. >>Yeah. You you nailed it, right? You must have seen my script, but Absolutely. I mean, I look at the analogy of, you think about the airlines, what's one of the first things airlines do with efficiency? South Southwest Airlines was the best example, a standardized on the 7 37, right? And so all of their pilots, all of their mechanics, all know how to operate the 7 37. So we are doing the same thing with enterprise data protection. So whether you're OnPrem at the edge or in the cloud or even multi-cloud, we can provide that single painter glass. We've done it for our customers for 30 plus years. We'll continue to do it for another 30 something years. And so it's really the first time with Veritas altar that, that we're, we're coming out with something that we've invested for so long and put, put such a huge investment on that can create those changes and that compelling solution for our customers. So as you can see, we're pretty pumped and excited about it. >>Yes, I can >>Use the term data management to describe Alta, and I want to ask about that term because I hear it a lot these days. Data management used to be database, now data management is being applied to all kinds of different functions across the spectrum. How do you define data management in Veritas >>Perspective? Yeah, there's a, we, we see it as really three main pillars across the environment. So one is protection, and we'll talk a little bit about this notion of ransomware is probably the number one use case. So the ability to take the most complex and the biggest, most vast applications. SAP is an example with hundreds of different moving parts to it and being able to protect that. The second is application resiliency. If, if you look at the cloud, there's this notion of, of responsibility, shared responsibility in the cloud. You've heard it, right? Yep. Every single one of the cloud service providers, certainly AWS has up on their website, this is what we protect, here's the demarcation line, the line in the sand, and you, the customer are responsible for that other level. And so we've had a technology, you previously knew it as InfoScale, we now call it alter application resiliency. >>And it can provide availability zone to availability zone, real time replication, high availability of your mission critical applications, right? So not only do we do the traditional backups, but we can also provide application resiliency for mission critical. And then the third thing really from a data management standpoint is all around governance and compliance. You know, ac a lot of our customers need to keep data for five, 10 years or forever. They're audited. There's regulations and different geographies around the world. And, and those regulations require them to be able to really take control of their cloud, take control of their data. And so we have a whole portfolio of solutions under that data compliance, data government. So back to your, your question Paul, it's really the integration and the intersection of those three main pillars. We're not a one trick pony. We've been at this for a long time, and they're not just new products that we invented a couple of months ago and brought to market. They're tried and tested with eight 80,000 customers and the most complex early solutions on the planet that we've been supporting. >>I gotta ask you, you know, we talked about those three pillars and you talked about the shared responsibility model. And think of that where you mentioned aws, Salesforce, Microsoft 365, Google workspace, whatnot. Are you finding that most customers aren't aware of that and haven't been protecting those workloads and then come to you and saying, Hey guys, guess what, this is what this is what they're responsible for. The data is >>You Yeah, I, it's, it's our probably biggest challenge is, is one of awareness, you know, with the cloud, I mean, how many times have you spoken to someone? You just put it in the cloud. Your applications, like the cloud providers like aws, they'll protect everything. Nothing will ever go down. And it's kind like if you, unless your house was ever broken into, you're probably not gonna install that burglar alarm or that fire alarm, right? Hopefully that won't be an event that you guys have to suffer through. So yeah, it's definitely, it wasn't till the last year or so the cloud service providers really published jointly as to where is their responsibility, right? So a great example is an attack vector for a lot of corporations is their SAS applications. So, you know, whether it it's your traditional SA applications that is available that's available on the web to their customers as a sas. >>And so it's certainly available to the bad actors. They're gonna, where there's, there's gonna be a point they're gonna try to get in. And so no matter what your resiliency plan is, at the end of the day, you really need to protect it. And protection isn't just, for example, with M 365 having a snapshot or a recycle bin, that's just not good enough. And so we actually have some pretty compelling technology, what we call ALTA SAS protection, which covers the, pretty much the, the gamut of the major SAS technologies to protect those and make it available for our customers. So yeah, certainly it's a big part of it is awareness. Yeah. >>Well, I understand that the shared responsibility model, I, I realize there's a lot of confusion about that still, but in the SaaS world that's somewhat different. The responsibility of the SaaS provider for protecting data is somewhat different. How, how should, what should customers know about that? >>I think, you know, the, the related to that, if, if you look at OnPrem, you know, approximately 35 to 40% of OnPrem enterprise data is protected. It's kind of in a long traditional problem. Everyone's aware of it. You know, I remember going to a presentation from IBM 20 something years ago, and someone held their push hand up in the room about the dis drives and says, you need to back it up. And the IBM sales guy said, no, IBM dis drives never crash. Right? And so fast forward to here we are today, things have changed. So we're going through almost a similar sort of changes and culture in the cloud. 8% of the data in the cloud is protected today, 8%. That's incredible. Meaning >>That there is independent backup devoted >>To that data in some cases, not at all. And something many cases, the customer just assumes that it's in the cloud, therefore it's always available. I never have to worry about protecting it, right? And so that's a big problem that we're obviously trying to, trying to solve. And we do that all under the umbrella of ransomware. That's a huge theme, huge investment that, that Veritas does with regards to providing that resiliency for our >>Customers. Ransomware is scary. It is becoming so prolific. The bad actors have access to technologies. Obviously companies are fighting them, but now ransomware has evolved into, no longer are we gonna get hit, it's when, yeah, it's how often it's what's the damage going to be. So the ability to help customers recover from ransomware, that resiliency is table stakes for businesses in any industry these days. Does that, that one of the primary pain points that your customers are coming to you with? >>It's the number one pain point. Yeah, it's, it's incredible. I mean, there's not a single briefing that our teams are doing customer meetings where that term ransomware doesn't come up as, as their number one use case. Just to give you something, a couple of statistics. There's a ransomware attack attack that happens 11 times a second right around the globe. And this isn't just, you know, minor stuff, right? I've got friends that are, you know, executives of large company that have been hit that have that some, you know, multimillion dollar ransom attack. So our, our play on this is, when you think about it, is data protection is the last line of defense. Yes. And so if they break through, it's not a case, Lisa, as you mentioned, if it's a case of when Yeah. And so it's gonna happen. So one of the most important things is knowing how do you know you have a gold copy, a clean copy, and you can recover at speed in some cases. >>We're talking about tens of thousands of systems to do that at speed. That's in our dna. We've been doing it for many, many years. And we spoke through a lot of the cyber insurance companies on this particular topic as well. And what really came back from that is that they're actually now demanding things like immutable storage, malware detection, air gaping, right? Anomaly detection is sort of core technologies tick the box that they literally won't ensure you unless you have those core components. And so what we've done is we've doubled down on that investment. We use AI in ML technologies, particularly around the anomaly detection. One of the, the, the unique and ne differentiators that Verto provides is a ransomware resiliency scorecard. Imagine the ability to save uran a corporation. We can come in and run our analytics on your environment and kind of give you a grade, right? Wouldn't you prefer that than waiting for the event to take place to see where your vulnerability really is? And so these are some of the advantages that we can actually provide for our customers, really, really >>To help. Just a final quick question. There is a, a common perception, I believe that ransomware is an on premise problem. In fact, it is also a cloud problem. Is that not right? >>Oh, absolutely. I I think that probably the biggest attack vector is in the cloud. If it's, if it's OnPrem, you've certainly got a certain line of defense that's trying to break through. But, you know, you're in the open world there. Obviously with SAS applications in the cloud, it's not a case of if, but when, and it's, and it's gonna continue to get, you know, more and more prevalent within corporations. There's always gonna be those attack factors that they find the, the flash wounds that they can attack to break through. What we are concentrating on is that resiliency, that ability for customers to recover at speed. We've done that with our traditional appliances from our heritage OnPrem. We continue to do that with regard to resiliency at speed with our customers in the cloud, with partners like aws >>For sure. Almost done. Give me your 30 seconds on AWS and Veritas. >>We've had a partnership for the better part of 10 years. It's incredible when you think about aws, where they released the elastic compute back in 2006, right? We've been delivering data protection, a data management solutions for, for the better part of 30 years, right? So, so we're, we're Junos in our space. We're the leader in, in data protection and enterprise data protection. We were on-prem. We, we continue to be in the cloud as AWS was with the cloud service provided. So the synergies are incredible. About 80 to 85% of our, our joint customers are the same. We take core unique superpowers of aws, like AWS outposts and AWS Glacier Instant retrieval, for example, those core technologies and incorporate them into our products as we go to Mark. And so we released a core technology a few months ago, we call it ultra recovery vault. And it's an air gap, a mutable storage, worm storage, right Once, right? You can't change it even when the bad actors try to get in. They're independent from the customer's tenant and aws. So we manage it as a managed backup service for our customers. Got it. And so our customers are using that to really help them with their ransomware. So it's been a tremendous partnership with AWS >>Standing 10 years of accounting. Last question for you, Rick. You got a billboard on the 1 0 1 in Santa Clara, right? By the fancy Verto >>1 0 1? >>Yeah. Right. Well, there's no traffic. What does that billboard say? What's that bumper sticker about? Vertus, >>I think, I think the billboard would say, welcome to the new Veritas. This is not your grandfather's old mobile. We've done a phenomenal job in, in the last, particularly the last three or four years, to really reinvent ourselves in the cloud and the investments that we made are really paying off for our customers today. So I'm excited to be part of this journey and excited to talk to you guys today. >>Love it. Not your grandfather's Veritas. Rick, thank you so much for joining Paula, me on the forgot talking about what you guys are doing, how you're helping customers, really established that cyber of resiliency, which is absolutely critical these days. We appreciate your >>Time. My pleasure. Thank you so much. >>All right, for our guest and Paul Gilland, I'm Lisa Martin, you're watching the Queue, which as you know is the leader in live enterprise and emerging check coverage.

>>Hey everyone. Welcome back to the cube. Lisa Martin here with Dave ante, we're covering snowflake summit 22. This is Dave two of our wall to wall cube coverage of three days. We've been talking with a lot of customers partners, and we've got some more partners to talk with us. Next. Informatica two of our guests are back with us on the program. Rick TA Daniels joins us the G P global ecosystems and technology at Informatica and Peter COO vice president and chief strategist banking and financial services. Welcome guys. >>Thank you guys. Thanks for having us, Peter, >>Talk to us about what some of the trends are that you're seeing in the financial services space with respect to cloud and data and AI. >>Absolutely. You know, I'd say 10 years ago, the conversation around cloud was what is that? Right? How do we actually, or no way, because there was a lot of concerns about privacy and security and so forth. You know, now, as you see organizations modernizing their business capabilities, they're investing in cloud solutions for analytics applications, as well as data data being not only just a byproduct of transactions and interactions in financial services, it truly fuels business success. But we have a term here in Informatica where data really has no value unless it's fit for business. Use data has to be accessible in the systems and applications you use to run your business. It has to be clean. It has to be valid. It has to be transparent. People need to understand where it comes from, where it's going, how it's used and who's using it. It also has to be understood by the business. >>You can have all the data in the world and your business applications, but people don't know what they need it to use it for how they should use it. It has no value as well. And then lastly, it has to be protected when it matters most what we're seeing across financial services, that with the evolution of cloud now, really being the center of focus for many of the net new investments, data is scattered everywhere, not just in one cloud environment, but in multiple cloud environments, but they're still dealing with many of the on premise systems that have been running this industry for many, many years. So organizations need to have the ability to understand what they need to do with their data. More importantly, tie that to a measurable business outcome. So we're seeing the data conversation really at the board level, right? It's an asset of the business. It's no longer just owned by it. Data governance brings both business technology and data leaders together to really understand how do we use manage, govern and really leverage data for positive business outcomes. So we see that as an imperative that cuts across all sectors of financial services, both for large firms, as well as for the mid-market so >>Quick follow up. If I, may you say it's a board level. I totally agree. Is it also a line of business level? Are you seeing increasingly that line of businesses are leaning in owning the data, be building data products and the like >>Absolutely. Because at the end of the day business needs information in order to be successful. And data ownership now really belongs in the front office. Business executives understand that data again is not just a bunch of zeros and ones. These are critical elements for them make decisions and to run their business, whether it's to improve customer experience, whether it's to grow Wallace share, whether it's to comply with regulations, manage risks in today's environment. And of course being agile business knows that data's important. They have ownership of it and technology and data organizations help facilitate that solutions. And of course the investments to ensure that business can make the decisions and take the appropriate actions. >>A lot of asks and requirements on data. That's a big challenge for organizations. You mentioned. Well, one of the things that we've mentioned many times on this program recently is every company has to be a data company. There is no more, it's not an option anymore. If you wanna be successful, how does Informatica help customers navigate all of the requirements on data for them to be able to extract that business value and create new products and services in a timely fashion? >>So Informatica announced what we call the intelligent data management cloud platform. The platform has capabilities to help organizations access the data that they need, share it across to applications that run their business, be able to identify and deal with data, quality issues and requirements. Being able to provide that transparency, the lineage that people need across multiple environments. So we've been investing in this platform that really allows our customers to take advantage of these critical data management, data governance and data privacy requirements, all in one single solution. So we're no longer out there just selling piecemeal products. The platform is the offering that we provide across all industries. >>So how has that affected the way Informatica does business over the last several years? Snowflake is relatively new. You guys have been around a long time. How has your business evolved and specifically, how are you serving the snowflake yeah. Joint customers with >>Informatica? Yeah, I think then when I've been talking with folks here at the event, there are two big areas that keep coming up. So, so data governance, data governance, data governance, right? It's such a hot topic out there. And as Peter was mentioning, data governance is a critical enabler of access to data. In fact, there is an IDC study for last year that said that, you know, 80, 84% of executives, you know, no surprise, right? They wanna have data driven outcomes, data driven organizations, but only 30% of practitioners actually use data to make decisions. There's a huge gap there. And really that's where governance comes in and creating trust around data and not only creating trust, but delivering data to and users. So that's one big trend. The other one is departmental user adoption. We're seeing a, a huge push towards agility and rapid startup of new projects, new data driven transformations that are happening at the departmental level, you know, individual contributors, that sort of thing. So Informatica, we did a made announcement yesterday with snowflake of a whole host of innovations that are really targeting those two big trend areas. >>I wanna get into the announcements, but you know, the point about governance and, and users, business users being reluctant, it's kind of chicken and egg, isn't it. If, if I don't have the governance, I'm, I'm afraid to use it. But even if I do have it, there's the architecture of my, my, my company, my, my data organization, you know, may not facilitate that. And so I'm gonna change the architect, but then it's a wild west. So it has to be governed. Isn't that a challenge that company companies >>Absolutely, and, and governance is, is a lot more than just technology, right? It's of a people process problem. And there really is a community or an ecosystem inside every organization for governance. So it's really important that when you think about deploying governance and being successful, that every stakeholder have the ability to interact with this common framework, right. They get what they need out of it. It's tailored for how they wanna work. You've got your it folks, you got your chief data officer data stewards, you have your privacy folks and you have your business users. They're all different personas. So we really focus on creating a holistic, single pane of glass view with our cloud data governance and catalog offering that that really takes all the way from the raw technical data and actually delivers data in, in a shopping cart, like experience for actual enterprise users. Right? And, and so I think that's when data governance goes from historically data, governments was seen as an impediment. It was seen as a tax, I think, but now it's really an accelerator, an enabler and driving consumption of data, which in turn for our friends here at snowflake is exactly what they're looking for. >>Talk about the news. So data loader, what does that do? >>Well, it's all in the name. We say, no, the data loader it, it's a free utility that we announced here at, at snowflake summit that allows any user to sign up. It's completely free, no capacity limits. You just need an email address, three simple steps start rapidly loading data into snowflake. Right? So that first step is just get data in there. Start working with snowflake. Informatica is investing and making that easy for every single user out there. And especially those departmental users who wanna get started quickly. >>Yeah. So, I mean, that's a key part point of getting data into the snowflake data cloud, right? It's like any cloud, you gotta get data in. How does it work with, with customers? I mean, you guys are, are known, you have a long history of, you know, extract transform ETL. How does it work in the snowflake world? Is it, is it different? Is it, you remember the Hadoop days? It was, it was E LT, right? How are customers doing that today in this environment? >>Yeah, it's different. I mean, there, there are a lot of the, the same patterns are still in play. There's a lot more of a rapid data loading, right. Is a key theme. Just get it into snowflake and then work on the data, transform it inside of snowflake. So it's, it's a flavor of T right. But it's really pushing down to the snowflake data cloud as opposed to Hado with spark or something like that. Right. So that, that's definitely how customers are using it. And, you know, majority of our customers actually with snowflake are using our cloud technology, but we're also helping customers who are on premise customers, automate the migration from our on-premises technology to our cloud native platform as well. Yeah. >>And I'd say, you know, in addition to that, if you think about building a snowflake environment, Informatica helps with our data loader solution, but that's not enough. Then now you need to get value out of your data. So you can put raw data into the snowflake environment, but then you realize the data's not actually fit for business use, what do we need to do actually transform it to clean it, to govern it. And our customers that use Informatica with snowflake are managing the entire data management and data governance process so that they can allow the business to get value out of the snowflake investment. >>How quickly can you enable a business to get value from that data to be able to make business decisions that can transform right. Deliver competitive advantage? >>I think it really depends on an organization on a case by case basis. At the end of the day, you need to understand why are you doing this in the first place, right? What's the business outcome that you're trying to achieve next, identify what data elements do you actually need to capture, govern and manage in order to support the decisions and the actions that the business needs to take. If you don't have those things defined, that's where data governance comes into play. Then all you're doing is setting up a technical environment with a bunch of zeros in ones that no one knows what to do with. So we talk about data governance more holistically, say, you need to align it to your business outcomes, but ensure that you have people, processes, roles, and responsibilities, and the underlying technology to not just load data into snowflake, but to leverage it again for the business needs across the organization. >>Oh, good, please. >>I just wanted to add to that real quickly. Yeah. One of the things Informatica we're philosophically focused on is how do you accelerate the entire business of data management? So with our, our cloud platform, we have what's called our clear AI engine, right? So we use AI techniques, machine learning recommendations to accelerate with the, the knowledge of the metadata of what's gone on the organization. For example, that when we discover data assets figure out is this customer data, is it product data that dramatically shortens the time to find data assets deliver them? And so across our whole portfolio, we're taking things that were traditionally months to do. We're taking 'em down to weeks and days and even hours, right? So that's the whole goal is just accelerate that entire journey and life cycle through cloud native approaches and AI. Yeah, >>You kind of just answered my question. I think Rick, so you have this joint value statement together. We help customers. This is informatic and snowflake together. We help customers modernize their data. Architecture enable the most critical workloads, provide AI driven data governance and accelerate added value with advanced analytics. I mean, you definitely touched on some of those, but kind of unpack the rest of that. What do you mean by modernize? What is their data architecture? What is that? Let's start there. What does that look like? Modernizing a data. Yeah. >>So, so a lot with so many customers, right? They, they built data warehouses, core data and analytics systems on premises, right? They're using ETL technology using those, those either warehouse, appliances or databases. And what they're looking for is they wanna move to a cloud native model, right. And all the benefits of cloud in terms of TCO elasticity, instant scale up agility, all those benefits. So we're looking, we're looking to do with our, our modernization programs for our, for our current customer base that are on premises. We automate the process to get them to a fully cloud native, which means they can now do hybrid. They can do multi-cloud elastic processing. And it's all also in a consumption based model that we introduced about about a year and a half ago. So, so they're looking for all those elements of a cloud native platform and they're, but they're solving the same problems, right? We still have to connect data. We still have to transform data, prepare it, cleanse it, all those things exist, but in a, in a cloud native footprint, and that's what we're helping them get to. >>And the modern architecture these days, quite honestly, it's no longer about getting best breed tools and stitching them together and hoping that it will actually work. And Informatica is value proposition that our platform has all those capabilities as services. So our customers don't have to deal with the costs and the risks of trying to make everything work behind the scenes and what we've done with IDMC or intelligent data management cloud for financial services, retail, CPG, and healthcare and life sciences. In addition to our core capabilities and our clear AI machine learning engine, we also have industry accelerators, prebuilt data, quality rules for certain regulations in within banking. We've got master data management, customer models for healthcare insurance industry, all prebuilt. So these are accelerators that we've actually built over the years. And we're now making available to our customers who adopt informatic as intelligent data management cloud for their data management and governance needs. >>And then, and then the other part of this statement that that's interesting is provide AI driven data governance. You know, we are seeing a move toward, you know, decentralized data architectures and, and, and organizations. And we talk to snowflake about that. They go, yeah, we're globally distributed cloud. Okay, great. So that's decent place, but what we see a lot of customers doing to say, okay, we're gonna give lines of business responsibility for data. We're gonna argue about who owns what. And then once we settle that here's your own, here's your own data lake. Maybe they they'll try to cobble together a catalog or a super catalog. Right. And then they'll try to figure out, you know, some algorithms to, to determine data quality, you know, best, you know, okay. Don't use. Right, right. So that, so if I understand it, you automate all that. >>So what we're doing with AI machine learning is really helping the data professional, whether in the business, in technology or in between not only to get the job done faster, better, and cheaper, but actually do it intelligently. What do we mean by that? For example, our AI engine machine learning will look at data patterns and determine not only what's wrong with your data, but how should you fix it and recommend data quality rules to actually apply them and get those errors addressed. We also infer data relationships across a multi-cloud environment where those definitions were never there in the beginning. So we have the ability to scan the metadata and determine, Hey, this data set is actually related to that data set across multiple clouds. It makes the organization more productive, but more importantly, it increases the confidence level that these organizations have the right infrastructure in place in order to manage and govern their data for what they're trying to do from a business perspective. >>And I add that as well. I think you're talking a lot about data mesh architectures, right? That, that are really kind of popular right now. And I think those kind of, they live or die on, on data governance. Right? If you don't have data governance to share taxonomy, these things, it's very hard to, I think, scale those individual working groups. But if you have a platform where they, the data owners can publish out visibility to what their data means, how to use it, how to interpret it and get that insight, that context directly to the data consumers that's game changing. Right. And that's exactly what we're doing with our cloud data governance and catalog. >>Well, the data mesh, you talk about data mesh, there's four principles, right? It's like decentralized architecture data products. So if, once you figure out those two yep. You just created two more problems, which is the other two parts of the Princip four, two parts of the four principles, self service infrastructure, and computational governance. And that's like the hardest part of federated, federated, computational governance. That's the hardest part. That's the problem that you're solving. >>Yeah. Yeah, absolutely. I mean, think about the whole decentralization and self-service, well, I may be able to access my data in mesh architecture, but if I don't know what it means, how to use it for what purpose, when not to use it, you're creating more problems than what you originally expected to solve. So what we're doing is addressing the data management and the governance requirements, regardless of what the architecture is, whether it's a mesh architecture, a fabric architecture or a traditional data lake or a data store. >>Yeah. Mean, I say, I think data mesh is more of an organizational construct than it is. I, I'm not quite sure what data fabric is. I think Gartner confused the issue that data fabric was an old NetApp term. Yeah. You're probably working in NetApp at the time and it made sense in the NetApp context. And then I think Gartner didn't like the fact that Jamma Dani co-opted this cool term. So they created data fabric, but whatever. But my, my point being, I think when I talk to customers that are they're, they're trying to get more value outta data and they recognize that going through all these hyper specialized roles is time consuming and it's not working for them. And they're frustrated to your points and your joint statement. They want to accelerate that. And they're realizing, and the only way to do that is to distribute responsibility, get more people involved in the process. >>And, and that's, it kind of dovetails with some, the announcements we made on data governance for snowflake, right, is you're taking these, these operational controls of the snowflake layer that are typically managed by SQL and you, and that decentralized architecture data owner doesn't know how to set those patterns and things like that. Right. So we're saying, all right, we're, we're creating these deep integration so that again, we have a fit for persona type experience where they can publish data assets, they can set the rules and policies, and we're gonna push that down to snowflake. So when it actually comes to provisioning data and doing data sharing through snowflake, it's all a seamless experience for the end user and the data owner. Yeah. >>That's great. Beautiful, >>Seamless experience absolutely necessary these days for everybody above guys. Thanks so much for joining David me today, talking about Informatica what's new, what you're doing with snowflake and what you're enabling customers to do in terms of really extracting value from that data. We appreciate your insights. >>Thank you. Yep. >>Thank you for having us >>For our guests and Dave ante. I'm Lisa Martin. You're watching the cubes coverage of snowflake summit day two of the cubes coverage stick around Dave. And I will be right back with our next guest.

(digital pulsing music) >> We're back at VeeamON 2022. My name is Dave Vellante. I'm here with my co-host David Nicholson. I've got another mass boy coming on. Patrick Osborne is the vice president of the storage business unit at HPE. Good to see you again, my friend. It's been a long time. >> It's been way too long, thank you very much for having me. >> I can't even remember the last time we saw each other. It might have been in our studios in the East Coast. Well, it's good to be here with you. Lots have been going on, of course, we've been following from afar, but give us the update, what's new with HPE? We've done some stuff on GreenLake, we've covered that pretty extensively and looks like you got some momentum there. >> Quite a bit of momentum, both on the technology front and certainly the customer acquisition front. The message is certainly resonating with our customers. GreenLake is, that's the transformation that's fueling the future of Hewlett Packard Enterprise. So the momentum is great on the technology side. We're at well over 50 services that we're providing on the GreenLake platform. Everything from solutions and workloads to compute, networking and storage. So it's been really fantastic to see the platform and being able to really delight the customers and then the momentum on the sales and the customer acquisition side, the customers are voting with their dollars, so they're very happy with the platform, certainly from an operational perspective and a financial consumption perspective and so our target goal, which we've said a bunch of times is we want to be the hyperscaler on on-prem. We want to provide that customer experience to the folks that are investing in the platform. It's going really well. >> I'll ask you a question, as a former analyst, it could be obnoxious and so forth, so I'll be obnoxious for a minute. I wrote a piece in 2010 called At Your Storage Service, saying the future of storage and infrastructure as a service, blah, blah, blah. Now, of course, you don't want to over-rotate when there's no market, there was no market for GreenLake in 2010. Do you feel like your timing was right on, a little bit late, little bit early? Looking back now, how do you feel about that? >> Well, it's funny you say that. On the timing side, we've seen iterations of this stops and start forever. >> That's true. Financial gimmicks. >> I started my career at Sun Microsystems. We talked about the big freaking Web-tone switch and a lot of the network is the computer. You saw storage networks, you've seen a lot, a ton of iterations in this category, and so, I think the timing's right right now. Obviously, the folks in the hyperscaler class have proved out that this is something that's working. I think for us, the big thing that's really resonating with the customers is they want the operational model and they want the consumption model that they're getting from that as a service experience, but they still are going to run a number of their workloads on-prem and that's the best place to do it for them economically and we've proved that out. So I think the time is here to have that bifurcated experience from operational and financial perspective and in the past, the technology wasn't there and the ability to deliver that for the customers in a manner that was useful wasn't there. So I think the timing's perfect right now to provide them. >> As you know, theCUBE has had a presence at HPE Discover. Previous, even HP Discover and same with Veeam. But we got a long history with HP/HPE. When Hewlett Packard split into two companies, we made the observation, Wow, this opens up a whole new ecosystem opportunity for HPE generally, in storage business specifically, especially in data protection and backup, and the Veeam relationship, the ink wasn't dry and all of a sudden you guys were partnering, throwing joint activities, and so talk about how that relationship has evolved. >> From my perspective, we've always been a big partnering company, both on the route to market side, so our distributors and partners, and we work with them in big channel business. And then on the software partnership side, that's always evolving and growing. We're a very open ecosystem and we like to provide choice for our customers and I think, at the end of the day, we've got a lot of things that we work on jointly, so we have a great value prop. First phase of that relationship was partnering, we've got a full boat of product integrations that we do for customers. The second was a lot of special sauce that we do for our customers for co-integration and co-development. We had a huge session today with Rick Vanover and Frederico on our team here to talk about ransomware. We have big customers suffering from this plague right now and we've done a lot together on the engineering side to provide a very, very well-engineered, well thought out process to help avoid some of these things. And so that wave, too, of how do we do a ton of co-innovation together to really delight our customers and help them run their businesses, and I think the evolution of where we're going now, we have a lot of things that are very similar, strategically, in terms of, we all talk about data services and outcomes for our customers. So at the end of the day, when we think about GreenLake, like our virtual machine backup as a service or disaster recovery, it's all about what workloads are you running, what are the most important ones, where do you need help protecting that data? And essentially, how can we provide that outcome to you and you pay it as an outcome. And so we have a lot of things that we're working on together in that space. >> Let's take a little bit of a closer look at that. First of all, I'm from California, so I'm having a really hard time understanding what either of you were saying. Your accents are so thick. >> We could talk in Boston. >> Your accents are so thick. (Dave laughing) I could barely, but I know I heard you say something about Veaam at one point. Take a closer look at that. What does that look like from a ransomware perspective in terms of this concept of air gaping or immutable, immutable volumes and just as an aside, it seems like Veeam is a perfect partnership for you since customers obviously are going to be in hybrid mode for a long time and Veeam overlays that nicely. But what does it look like specifically? Immutable, air gap, some of the things we've been hearing a lot about. >> I'm exec sponsor for a number of big HPE customers and I'll give you an example. One of our customers, they have their own cloud service for time management and essentially they're exploited and they're not able to provide their service. It has huge ripple effect, if you think about, on inability to do their service and then how that affects their customers and their customers' employees and all that. It's a disaster, no pun intended. And the thing is, we learn from that and we can put together a really good architectures and best practices. So we're talking today about 3-2-1-1, so having three copies of your data, two different types of media, having an offline copy, an offsite copy and an offline copy. And now we're thinking about all the things you need to do to mitigate against all the different ways that people are going to exploit you. We've seen it all. You have keys that are erased, primary storage that is compromised and encrypted, people that come in and delete your backup catalog, they delete your backups, they delete your snapshots. So they get it down to essentially, "I'm either going to have one set of data, it's encrypted, I'm going to make you pay for it," and 40 percent of the time they pay and they get the data back, 60 percent of the time they pay and they get maybe some of the data back. But for the most part, you're not getting your data back. The best thing that we can do for our customers that come with a very prescriptive set of T-shirt configuration sizes, standardization, best practices on how they can take this entire ecosystem together and make it really easy for the customers to implement. But I wouldn't say, it's never bulletproof, but essentially, do as much as you can to avoid having to pay that ransomware. >> So 3-2-1-1, three copies, meaning local. >> Patrick: Yeah. >> So you can do fast recovery if you need to. Two different types of media, so tape fits in here? Not necessarily flashing and spinning disks. Could it be tape? >> A lot of times we have customers that have almost four different types. So they are running their production on flash. We have Alletras with HPE networking and servers running specific workloads, high performance. We have secondary storage on-prem for fast recovery and then we have some form of offsite and offline. Offsite could be object storage in the cloud and then offline would be an actual tape backup. The tape is out of the tape library in a vault so no one can actually access it through the network and so it's a physical copy that's offline. So you always have something to restore. >> Patrick, where's the momentum today, specifically, we're at VeeamON, but with regard to the Veeam partnership, is it security and ransomware, which is a new thing for this world. The last two years, it's really come to the top. Is it cloud migration? Is it data services and data management? Where's the momentum, all of the above, but maybe you could help us parse that. >> What we're seeing here at Hewlett Packard Enterprise, especially through GreenLake, is just an overall focus on data services. So what we're doing is we've got great platforms, we always had. HPE is known as an engineering company. We have fantastic products and solutions that customers love. What we're doing right now is taking, essentially, a lot of the beauty of those products and elevating them into an operational experience in the cloud, so you have a set of platforms that you want to run, you have machine critical platform, business critical, secondary storage, archival, data analytics and I want to be able to manage those from the cloud. So fleet management, HCI management, protocol management, block service, what have you, and then I want a set of abstracted data services that are on top of it and that's essentially things like disaster recovery, backup, data immutability, data vision, understanding what kind of data you have, and so we'll be able to provide those services that are essentially abstracted from the platforms themselves that run across multiple types of platforms. We can charge them on outcome based. They're based on consumption, so you think about something like DR, you have a small set of VMs that you want to protect with a very tight RPO, you can pay for those 100 VMs that are the most important that you have. So for us driving that operational experience and then the cloud data service experience into GreenLake gives customers a really, gives them a cloud experience. >> So have you heard the term super cloud? >> Patrick: Yeah. (chuckles) >> Have you? >> Patrick: Absolutely. >> It's term that we kind of coined, but I want to ask you about it specifically, in terms of how it fits into your strategy. So the idea is, and you kind of just described it, I think, whether your data is on-prem, it's in the cloud, multiple clouds, we'll talk about the edge later, but you're hiding the underlying complexities of the cloud's APIs and primitives, you're taking care of that for your customers, irrespective of physical location. It's the common experience across all those platforms. Is that a reasonable vision, maybe, even from a technical standpoint, is it part of HPE strategy and what does it take to actually do that, 'cause it sounds nice, but it's probably pretty intense? >> So the proof's in the pudding for us. We have a number of platforms that are providing, whether it's compute or networking or storage, running those workloads that they plum up into the cloud, they have an operational experience in the cloud and now they have data services that are running in the cloud for us in GreenLake. So it's a reality. We have a number of platforms that support that. We're going to have a set of big announcements coming up at HPE Discover. So we led with Alletra and we have a block service, we have VM backup as a service and DR On top of that. That's something that we're providing today. GreenLake has over, I think, it's actually over 60 services right now that we're providing in the GreenLake platform itself. Everything from security, single sign on, customer IDs, everything, so it's real. We have the proof point for it. >> So, GreenLake is essentially, I've said it, it's the HPE cloud. Is that a fair statement? >> A hundred percent. >> You're redefining cloud. And one of the hallmarks of cloud is ecosystem. Roughly, and I want to talk more about you got to grow that ecosystem to be successful in cloud, no question about it. And HPE's got the chops to do that. What percent of those services are HPE versus ecosystem partners and how do you see that evolving over time? >> We have a good number of services that are based on HPE, our tried and true intellectual property. >> You got good tech. >> Absolutely, so a number of that. And then we have partners in GreenLake today. We have a pretty big ecosystem and it's evolving, too. So we have customers and partners that are focused, our customers want our focus on data services. We have a number of opportunities and partnerships around data analytics. As you know, that's a really dynamic space. A lot of folks providing support on open source, analytics and that's a fast moving ecosystem, so we want to support that. We've seen a lot of interest in security. Being able to bring in security companies that are focused on data security. Data analytics to understand what's in your data from a customer perspective, how to secure that. So we have a pretty big ecosystem there. Just like our path at HPE, we've always had a really strong partnership with tons of software companies and we're going to continue to do that with GreenLake. >> You guys have been partner-friendly, I'll give you that. I'm going to ask Antonio this at Discover in a couple of weeks, but I want to ask you, when you think about, again, to go back to AWS as the prototypical cloud, you look at a Snowflake and a Redshift. The Redshift guys probably hate Snowflake, but the EC2 guys love them, sell a lot of compute. Now you as a business unit manager, do you ever see the day where you're side by side with one of your competitors? I'm guessing Antonio would say absolutely. Culturally, how does that play inside of HPE? I'm testing your partner-friendliness. How would you- >> Who will you- >> How do you think about that? >> At the end of the day, for us, the opportunity for us is to delight our customers. So we've always talked about customer choice and how to provide that best outcome. I think the big thing for us is that, from a cost perspective, we've seen a lot of customers coming back to HPE repatriation, from a repatriation perspective for a certain class of workloads. From my perspective, we're providing the best infrastructure and the best operational services at the best price at scale for these costumers. >> Really? It definitely, culturally, HPE has to, I think you would agree, it has to open up. You might not, you're going to go compete, based on the merit- >> Absolutely. >> of your product and technology. The repatriation thing is interesting. 'Cause I've always been a repatriation skeptic. Are you actually starting to see that in a meaningful way? Do you think you'll see it in the macro numbers? I mean, cloud doesn't seem to be slowing down, the public cloud growth, I mean, the 35, 40 percent a year. >> We're seeing it in our numbers. We're seeing it in the new logo and existing customer acquisition within GreenLake. So it's real for us. >> And they're telling you? Pure cost? >> Cost. >> So it's that's simple. >> Cost. >> So, they get the cloud bill, you do, too. I'd get the email from my CFO, "Why the cloud bill so high this month?" Part of that is it's consumption-based and it's not predictable. >> And also, too, one of the things that you said around unlocking a lot of the customer's ability from a resourcing perspective, so if we can take care of all the stuff underneath, the under cloud for the customer, the platform, so the stores, the serving, the networking, the automation, the provisioning, the health. As you guys know, we have hundreds of thousands of customers on the Aruba platform. We've got hundreds of thousands of customers calling home through InfoSight. So we can provide a very rich set of analytics, automated environment, automated health checking, and a very good experience that's going to help them move away from managing boxes to doing operational services with GreenLake. >> We talk about repatriation often. There was a time when I think a lot of us would've agreed that no one who was born in the cloud will ever do anything other than grow in the cloud. Are you seeing organizations that were born in the cloud realizing, "Hey, we know what our 80 percent steady state is and we've modeled this. Why rent it when we can own it? Or why rent it here when we can have it as operational cost there?" Are you seeing those? >> We're seeing some of that. We're certainly seeing folks that have a big part of their native or their digital business. It's a cost factor and so I think, one of the other areas, too, that we're seeing is there's a big transformation going on for our partners as well, too, on the sell-through side. So you're starting to see more niche SaaS offerings. You're starting to see more vertically focused offerings from our service provider partners or MSPs. So it's not just in either-or type of situation. You're starting to see now some really, really specific things going on in either verticals, customer segmentation, specific SaaS or data services and for us, it's a really good ecosystem, because we work with our SP partners, our MSP partners, they use our tech, they use our services, they provide services to our joint customers. For example, I know you guys have talked to iland here in the past. It's a great example for us for customers that are looking for DR as a service, backup as a service hosting, so it's a nice triangle for us to be able to please those customers. >> They're coming on to tomorrow. They're on 11/11. I think you're right on. The one, I think, obvious place where this repatriation could happen, it's the Sarah Wong and Martin Casano scenario where a SaaS companies cost a good sold become dominated by cloud costs. And they say, "Okay, well, maybe, I'm not going to build my own data centers. That's probably not going to happen, but I can go to Equinix and do a colo and I'm going to save a ton of dough, managing my own infrastructure with automation or outsourcing it." So Patrick, got to go. I could talk with you forever. Thank you so much for coming back in theCUBE. >> Always a pleasure. >> Go, Celts. How you feeling about the, we always talk sports here in VeeamON. How are you feeling about the Celts today? >> My original call today was Celtics in six, but we'll see what happens. >> Stephen, you like Celtics? Celtics six. >> Stephen: Celtics six. >> Even though tonight, they got a little- >> Stephen: Still believe, you got to believe. >> All right, I believe. >> It'd be better than the Miami's Mickey Mouse run there, in the bubble, a lot of astronauts attached to that. (Dave laughing) >> I love it. You got to believe here on theCUBE. All right, keep it right- >> I don't care. >> Keep it right there. You don't care, 'cause you're not from a sports town. Where are you in California? >> We have no sports. >> All right, keep it right there. This is theCUBE's coverage of VeeamON 2022. Dave Vellante for Dave Nicholson. We'll be right back. (digital music)

More bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software and it starts with great technical founders with great products and great bottoms of emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart, but Myer of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies there's no, I mean, consumer is enterprise now, everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. <laugh> but remember, like right now there's also a tech and VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are, uh, may maybe students of history and have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely one web three. Yeah. >>But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east of Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, well, >>Let's get, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher, a direct sales force and SAS kind of crushed that now SAS is being redefined, right. So what is SAS is snowflake assassin or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data and you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of common across all successful startups and the overall adoption of technology. Um, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually like growth, right. They're one and the same. So sometimes people think the product, uh, is what is driving growth. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this, but maybe started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing. It's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the, and they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I have what been saying on the cube for probably about eight years now that we are gonna hit digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. You, we hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home group. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal it'll trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion yeah. Around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? Yeah. It's so it's something that people just believe to be true almost without, uh, necessarily caring >>About data. Data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of it's about believing in the person. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. >>Oh, AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur. Right. And the persona of the entrepreneur would be, you know, so somebody who was a great salesperson or somebody who tell a great story, and I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it gonna it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in the new economy that we live in, really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative of because their product begins exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Speak to the user, but let me ask a question now that for the people watching, who are maybe entrepreneurial entre, preneurs, um, masterclass here in session. So I have to ask you, do you prefer, um, an entrepreneur come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine with you an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do, do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way. And we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be the, of more likely somebody is gonna align with your vision and, and wanna invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta >>Show the >>Path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle. The journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living, we'll say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. <laugh> so you, you know, you sort of have to balance the, you know, we, we know that the world is going in this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but some times it happens in six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Bel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There's three big trends that we invest in. And the they're the only things we do day in, day out one is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen, an alwa timeline >>Happening forever. >>But, uh, it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need you do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cybersecurity as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is run $150 billion. And it still is a fraction of what we're, >>What we're and national security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital that's >>Right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters, your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cuban. Uh, absolutely not. Certainly EU maybe even north Americans in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Guess be VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After this short break, stay with us. Everyone. Welcome to the cue here. Live in San Francisco. K warn you for AWS summit 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here, Justin Kobe owner, and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to mid-size businesses that are moving to the cloud, or have already moved to the cloud and really trying to understand how to best control security, compliance, all the good stuff that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas, up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by a of us. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization, but obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small mids to size business. They're all trying to understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're of like, listen, we gotta move to the cloud or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then so, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to mid-size businesses who don't have the technology talent on staff to be able to do >>That. Yeah. And they want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is not it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem. And you guys solve >>In the SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and our hardened solutions. And so, um, what we try to do with, to technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to yeah. Feel like, listen, at the end of the day, I'm gonna be spending money in one place or another, whether that's on primer in the cloud, I just want know that I'm doing that way. That helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early, not worrying about it, you got it mean most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. >>Yeah. Frog and boiling water, as we used to say, oh, it's a great analogy. So I mean, this, this is a dynamic. That's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam? You know, the 5,000 announcement or whatever. They did huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>Values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a 10 a company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back and we're the safety net. So when a customer is saying, right, I'm gonna spend a couple thousand and dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say your high profile and you're gonna potentially be more vulnerable to security attacks. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a four, >>The training alone would be insane. A risk factor. I mean the cost. Yes, absolutely opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018. When, uh, when we, he made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious, it wasn't requirement. It still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front >>Desk and she could be running the Kubernetes clusters. I >>Love it. It's >>Amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people with. And that's a cultural factor that you guys have. So, so again, this is back to my whole point out SMBs and businesses in general, small and large it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the buildout, um, uh, return factor, ROI piece. At what point in time as an owner, SMB, do I get to ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. >>This is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, >>That's, that's what, at least a million in loading, if not three or more Just to get that app going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side. No. And they remind AI and ML. >>That's right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>So like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like it, >>But that's so true. I mean, when I think about how, if I was a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. It's something that we talk about every, with every one of our small to mid-size >>Businesses. So just, I want get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduced other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. Yeah. I came in, I did an internship for six months and I loved it. I learned more in those six months than I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2000 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner. But if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy the business with me. >>And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like, if we're own, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015 and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the BI cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us. And we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business to migrate completely to the cloud is as infrastructure was considered, that just didn't happen as often. Um, what we were seeing where the, a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plugin for the company. Awesome. >>So, uh, there's no question. Every customer is looking migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating into the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customer is not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so they can modernize. So >>Like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable win that's right. Seeing the value and ING down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate >>It. Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break >>Live on the floor in San Francisco for Aus summit. I'm John for host of the cube here for the next two days, getting all the actual back in person we're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be here. >>So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to be back through events. It's >>Amazing. This is the first, uh, summit I've been to, to in what two, three >>Years. That's awesome. We'll be at the, uh, a AWS summit in New York as well. A lot of developers and the big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything devs sec ops, everyone kind of sees that you got containers, you got Benet, he's got cloud native. So the, the game is pretty much laid out. Mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's >>Right. Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions. The at our around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running or FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam slaps in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listens to the customer. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. >>It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data in is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always use the riff on the cube, uh, cause it's basically Amazon in a box, pushed in the data center, running native, all this stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard. Deepak syncs group is doing some amazing work with opensource Raul's team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my datas center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone now happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware can go deploy EKS anywhere in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative. Does that get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is that they don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on what's making them money as a business. They wanna focus on their applications. They wanna focus on their customers. So they look towards AWS cloud and a AWS. You take the infrastructure, you take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it >>Works? Right. And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy fin in the Caribbean, we're gonna talk about hurricanes. And we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data and you have applications that are tapping into that, that requirement. It makes total sense. We're seeing that across the board. So it's not like it's a, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on >>It's interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, project going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain just for like smart contracts, for instance, or certain transactions. And they go to Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service. Well, what happened to decentralized? >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a, I also want all the benefit of the cloud. So I want the modern, and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. >>Yeah. Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment that, that manufacturing plant can be hooked up, they don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with a regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Inside of that manufacturing plant, we can do pre-procesing on things coming out of the robotics, depending on what we're manufacturing. Right. And then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data, data lake, or whatever, >>To the data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just time manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yeah. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Right. And then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are, and we have more and more people that, that want to talk less about databases and want to talk about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data. Uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session this, but the one pattern we're seeing come of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes co as we call it in our last showcase, we did a whole whole an event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are running petabyte level. Um, they're, they're essentially data factories on, on, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a, kind of a, um, fun, I was told to ask you about your personal background on premise architect, Aus cloud, and skydiving instructor. How does that all work together? What tell, what does this mean? >>Yeah. Uh, I, >>You jumped out a plane and got a job. You got a customer to jump >>Out kind of. So I was, you jumped out. I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and how his customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, I started in the first day there, we had a, and, uh, EC two had just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to premises. >>So it's such a great story. You know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people, right. Yeah. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting stuff like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here, lot in San Francisco for AWS summit, I'm John for your host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look at this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube, a summit 2022. We're back in person. I'm John furry host of the cube. We'll be at the, a us summit in New York city this summer, check us out then. But right now, two days in San Francisco getting all coverage, what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, Pam. Cool. How are you? Good. >>How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah so give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me. We're back to be business with you never while after. Great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like nor west Menlo, true ventures, coast, lo ventures, Ram Shera, and all those people, all known guys that Antibe chime Paul Mayard web. So a whole bunch of operating people and, uh, Silicon valley vs are involved. >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? Well, >>I love having you on the cube, Dave and I, and Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh>, >>You know, >>You >>Get, the comment is fun to talk to you though. >>You get the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud out scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on our $2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded observability there's 10 million observability companies. Data is the key. This is what's your angle on this. What's your take. Yeah, >>No, look, I think I'll give you the view that I see, right? I, from my side, obviously data is very clear. So the things that room system of record that you and me talked about, the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA NA is a new buzzword and using the AI for customer service, it operations. You talk about observability. I call it AI ops, applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI service desk. What needs to be helped desk with ServiceNow BMC <inaudible> you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, or is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. >>It's a feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be a, in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kind having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle and it was software was action. Now you have all kinds of workflows abstractions everywhere. Right? So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become all polyglot databases. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area, like, as you were talking about, it should be part of ServiceNow. It should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies could cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also will have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you got the expo hall. You got, um, we're back to vents, but you got, you know, am Clume Ove, uh, Dynatrace data dog, innovative all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later today. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders, how Amazon created the startups 15 years back, everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're gonna build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's the next level of <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis of a couple months ago called castles in the cloud where your Mo is what you do in the cloud. Not necessarily in, in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage, and guys, Charles Fitzgerald out there who we like was kind of shitting on us saying, Hey, you guys terrible, they didn't get it. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Now. They say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. It >>Is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake so I can build it on snowflake. I can use them for data layer if I really need to size build it on force.com Salesforce. Yeah. Right. So I think that's where you'll see. So >>Basically the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think they had Redshift. Amazon has got Redshift. Um, but Snowflake's a big customer in the, they're probably paying AWS, I think big bills too. So >>Joe on very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-optation will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouses or data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that it comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose, your, you that's right with some sort of internal hack. Uh, but I think, I think the general question that I have is that I, I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and do the people shopping up their knives, it gets more competitive or is it just an infinite growth? So >>I think it's growth. You call it cloud scale, you invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go >>Made. I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the more market, feel free to text me or DMing. The next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products, cuz you know, the big enterprises now and you know, small, medium, large and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't get your thoughts on that? What, >>No, it is. If I growing by or 2007 or eight, when I used to talk to you back then and Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO or line of business, it's gone. Yeah. Can it go more? I think it can in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure is code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself a lot of first is I see the AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution. We will go future towards predict to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service desk. Customers are give the data, share the data because we thought the data algorithms are useless. I can them, but I gotta train them, modify them, tweak them, make them >>Better, >>Make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know, >>Look at, look how much data Rick has grown. >>It is. They doubled the >>Key cloud air kinda went private. So good stuff, man. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk McAfee, uh, grand to so all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict is one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service. >>Great stuff, man. Great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of Aish summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's decipher all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're can see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with bill group. He's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank >>You. Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit hosting, but they don't know how to do it. Like they're not >>Doing it right? So there's something opportunity there. It's like here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a midsize island, do begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enter prize technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's of all the Adams, especially new CEO. Andy's move on to be the chief of all Amazon. Just so I'm the cover of was it time met magazine? Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to port eight of us is trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. <laugh> either way, sounds like more exciting. Like I better >>Have a replacement ready <laugh> I, in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in east sports with other people in pure simulation of the race car. You gotta get the latest and videographic card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter, check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late? Has there been uptick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do >>That. We should do that. Actually. I think you're people would call in, oh, >>I, I think >>I guarantee we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised about anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the >>Customer. You know, I always joke with Dave Alane about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't call, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented SU sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting. So they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination >>Of gots. You got EMR, you got EC two, you got S3 SQS. Well, RedShift's not an acronym you >>Gets is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, they >>Shook up bean stock or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, well, we built this thing in 2005 and everyone hates it, but while we certainly can't change it, now it has three customers on it. John three <laugh>. Okay. Simple BV still haunts our dreams. >>I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm I couldn't figure out. Why can you just like roll it over? Why, why are you telling me? Just like, give me something else. All right. Okay. So let me talk about, uh, the other things I want to ask you, is that like, okay. So as Amazon better in some areas where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So Redshift, snowflake data breach is out there. So you got this co-op petition. Yes. How's that going? And what do you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with, and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multicloud. Cause obviously the other cloud shows are coming up. Amazon hated that word multicloud. Um, a lot of people though saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Cloudant loves that term. Yeah. >>You know, you're building in multiple single points of failure, do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about my multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on, but my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah, course. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journeyman and the, and the cloud journey going to all the events and then the pandemic hit. We now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing or just big changes you've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck build group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is evenly. Distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smelled delightful. Let me assure you. But it was, but it's also nice to be. >>I have a product for you if you want, you know? Oh, >>Oh excellent. I look forward to it. What is it? Pudding? Why not? <laugh> >>What else have you seen? So when accessibility for talent. Yes. Which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentation have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. Yeah. >>And you turn off your iMessage too. >>Oh yes. It's always fun in the, in the meetings when you're ho to someone and their colleague is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. Why >>Not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't the only entire sure. It's >>Fine. My kids text. Yeah, it's fine. Again, that's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you or I want to put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Yeah. Tell me a story there. >>I, I think >>That gets a glimpse in a hook and makes >>More, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did a thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they call for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in pan or Singapore, uh, to access them. And now they're in the index, they're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content. >>Absolutely >>Content value plus and >>Effecting. And that is the next big revelation of this industry is going to realize you have different companies. And, and I Amazon's case different service teams all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna basically give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here at Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up from the beginning. His great guy, check out his blog, his site, his newsletter screaming podcast. Corey, final question for, uh, what are you here doing? What's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck bill group. We solved one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I in my continual and ongoing love affair with the sound of my own voice. >><laugh> and you're good. It's good content it's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No >>Thank you button. >>You. Okay. This the cube covers here in San Francisco, California, the cube is back going to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John fur. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS two great guests here from the APN global APN Sege chef Jenko and Jeff Grimes partner lead Jeff and Sege is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS. We'll start >>Program. That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, >>Of course. >>Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously we're in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. A lot of 'em getting funded, big growth and cloud big growth and data secure hot in all sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to pro vibe white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support. Dedicat at headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, AWS startup, AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall effort for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, you got a >>Lot. We've got a lot. >>There's a lot. I gotta, I gotta ask a tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it for what do I get out of it? What's >>A story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company, right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here a lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. So, um, I think what's been fun over the years for me personally, I came from a startup brand sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise is sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. But still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters. Right. Where ever everyone's going after similar things. >>Yeah. And I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, you guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake that built on top of AWS. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's all the foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps competencies, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching, certainly I asked this a lot. There's a lot of companies startups out there who makes the cut, is there a criteria cut? It's not like it's sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How, how do you guys focus? How do you guys focus? I mean, you got a good question, you know, thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the ISVs that we look after are infrastructure ISVs. That's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really, we're trying to find these ISVs that can solve, uh, really interesting AWS customer. >>You guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line, business line business, like web >>Marketing, business apps, >>Owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage back up ransomware kind of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startups that we cover is that they've got, they truly have support from a build market sell perspective, right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can wish that sock report, oh, download it on the console, which we use all the time. <laugh> exactly. But security's a big deal. I mean, you know, ask the res are evolving, that role of DevOps is taking on dev SecOps. Um, I, I can see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or that not part of, uh, uh, >>Yeah, >>So the partner development manager can be an escalation for absolutely. Think of that. 'em as an extension of your business inside of AWS. >>Great. And you guys, how is that partner managers, uh, measure >>On those three pillars? Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's very, >>I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top line. >>Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the star ups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. The challenge is they just might not have the brand recognition. The, at the big guys have mm-hmm <affirmative>. And so that's, our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF. And then outside of SF, you guys have a global pro, have you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here. That's doing, uh, a AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with a AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously see a ton of partners from the bay area that we support. Um, but we're seeing a lot of really interesting technology come out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy and real quick before you get into surge. It's interesting. The VC market in, in Europe is hot. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. Let's see if they crash, you know, but we don't see that happening. I mean, people have been predicting a crash now in, in the startup ecosystem for least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the demo because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Celski both say the same thing during the pandemic. Necessity's the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of what me through. Pretend me, I'm a start up. Hey, I'm on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Search? What, what do >>I do? That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement? Where do they want to go at the end of the day? Um, and oftentimes because we've worked with, so how many successful startups that have come out of our program, we have, um, either through intuition or a playbook determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time. Yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love startups here in the cube because one, um, they have good stories, they're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they, they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startups. Showcases startups.com. Check out AWS startups.com and she got the showcase. So is, uh, final word. I'll give you guys the last word. What's the bottom line bumper sticker for AP globe. The global APN program summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally. We'll start >>With you. Yeah. I think the AWS global startup programs here to help companies truly accelerate their business full stop. Right. And that's what we're here for. Love it. >>It's a good way to, it's a good way to put it. Dato yeah. >>All right. Thanks for coming out. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of realities here, open source and cloud. I'll making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for >>Watching Cisco, John. >>Hello and welcome back to the Cube's live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city coming up this summer will be there as well. Events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net. Check it out a lot of content this year more than ever a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability, Jeremy. Great to see you. Thanks. >>Coming on. Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability Smith hot area, but also you've been a senior executive president of Dell EMC. Um, 11 years ago you had a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here, you predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for sort of catching that bus early, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply snowflake, obviously you involved, uh, at the board level, the other found, you know, the people there, uh, cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applications. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflakes is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think right in more software than, than ever before are why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now, back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data. And the, you know, there's sort of the transactions, you know, what you bought today are something like that. But then there's what we do, which is all the telemetry, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then why not? Where did they drop off all of that? They wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code one of the insights that we got out of that, and I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data, cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and yeah, >>Yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that. Yeah, it is about the data. You know, if I can better understand my data better than my competitor, then I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. >>So let's talk about observing you the CEO of, okay. Given you've seen the ways before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of something from years gone by. >>Um, there's a guy called, um, Rudy Coleman in 1960s coiner term and, and, and the term was being able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of four years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. Um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike and our board. And, um, you know, part of the observed story is closely knit with snowflake all of that time with your data, you know, we, we store in there. >>So I want to get, uh, yeah. Pivot to that. Mike SP snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became. Yeah. Snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you, you're doing some stuff with snowflake. So as a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? I mean, >>Having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, 20 years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah, >>It's okay. Columbia, but hyperscale. Yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job are doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy, >>Happy. So you're building on top of snowflake, >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You're >>Still on the board. >>Yeah. I'm still on the board. Yeah. That's a risk I'm prepared to take. I am more on snowing. >>It sounds well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No, yeah. Serious one. But the, this is a real dynamic. It is. It's not a one off its >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is in order of magnitude, more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I've believe the opportunity for folks like snowflake and, and folks like observe it. It's an order of magnitude more than it was for the Oracle and the SAPs of the old world. >>Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite easy >>Or be the platform, but it's hard. There's only like how seats were at that table left >>Well value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, rack space and there's 1,000,001 infrastructure, a service platform as a service. My, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. Don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters within if the provision, the CapEx. Yeah. Now the CapEx is in the cloud. Then you build on, on top of that, you got snowflake. Now you got on top of that. >>The assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's almost free, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get >>Into. And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a series us multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me, uh, like, look you build in on snowflake. Um, you, you know, you, you, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying their money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well and observe, but then I've got half the development team working on something that will never be as good as snowflake. And so we made the call early on that. No, no, we, we want a eight above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's obviously a more on snowflake. I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS. >>Well, and for snowflake and, and any platform from VI, it's a beautiful thing because, you know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of >>Ecosystems. Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New product, you're scaling a step function with them. >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is inve >>You know, well, Jeremy great conversation. Thanks for sharing your insights on the industry. Uh, we got a couple minutes left, um, put a plug in for observe. What do you guys know? You got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting in traction. >>Yeah. Yeah. Scales >>Around the corner. Sounds like, are you, is that where you are scale? >>We've got a big that that's when coming up in two or three weeks, we've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, but it's gonna be exciting. And, and like I said, so hill continue to, to, >>I think capital one's a big snowflake customer as well. Right. >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. And, and today that, that is one of Snowflake's biggest accounts, >>Capital, one, very innovative cloud, obviously Atos customer, and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, >>Right? >>So you got POCs, what's that trajectory look like? Can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit this straight and narrow and, and gas it fast. >>Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage. His questions that the board are always about, like is the product, right? Is the product right? Is the product right? Have you got the product right? And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we we're, we're adding all the tracing visualizations. So people will be able to the kind of things that by in the day you could do with the new relics and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one, cuz we sort of complete the trifecta, you know, the, the >>Logs, what's the secret sauce observe. What if you had the, put it into a, a, a sentence what's the secret sauce? >>I, I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors and, and the biggest thing our investors give is it actually, it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. While I got you here, you've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their, this restructure. So, so a lot of happening in cloud, what's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B it prepared to take risks and it's, it's a race against time to you'll get their, their offerings in this, a new digital footprint. >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. Yeah, >>Better. It's an amazing story. I mean, you know, we're, we're on AWS as well. And so I, I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late nineties, it was, they stopped, uh, really caring about developers in the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing headstart and if they did more, you know, if they do more than that, that's, what's gonna keep this juggernaut rolling for many years to come. >>Yeah. They got the Silicon and got the stack. They're developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great startup. Thanks for coming on the cube. Always a pleasure. Okay. Live from San Francisco. It's to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers are the bay air at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics, AI. They all coming together. Lots of coverage stay with us today. We've got a great guest from Bel VC. John founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, man. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over decade. Um, >>It's been at least 10 years, >>At least 10 years more. And we don't wanna actually go back as bring back the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in a second. We, >>We are, it's a little bit of a throwback to the path though, in my opinion, >>It's all the same. It's all distributed computing and software. We ran each other in cube con. You're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software to take an old something old and make it better new, faster. So tell us about Bel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you, I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called IM logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of software companies, uh, early investor in open source companies and cloud companies and spent a really wonderful years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start an enterprise software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchase software that is traditionally bought and sold tops down. But you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great bottoms of motions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background. You're super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is, is all companies there's no, I mean, consumer is enterprise now. Everything is what was once a niche, not, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, well, >>MFTs is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are of may, maybe students of his stream have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely web >>Three. Yeah. But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case and maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30 a year. So it it's a, it's a just incredibly fast >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Lutman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, hire a direct sales force and sass kind of crushed that now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, and they own all my data. And you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all six of startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement may be started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the offic and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been saying on the cube for probably about eight years now that we are gonna hit a digital hippie Revolut, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one of group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on like, well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source. One example of that religion. Some people say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean, >>The data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the first. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. And I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it's gonna, it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy, that're, we live in really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their product begin for exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with for right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Exactly. Speak to the user. But let me ask a question now that for the people watching, who are maybe entrepreneurial entre entrepreneurs, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think will become, right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna to align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta show the path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the, the latest trends because it's over before you even get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens ins six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Tebel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There there's three big trends that we invest in. And then the, the only things we do day in day out one is the explosion at open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen an alwa timeline happening forever, but it is, it is accelerating faster than we've ever seen. So I, I think it's its one big mass of wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole like economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion and it still is a fraction of what >>We're, what we're and even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right. Arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say you gotta love your firm. Love who you're doing. We're big supporters of your mission. Congrat is on your entrepreneurial venture. And uh, we'll be, we'll be talking and maybe see a Cuban. Uh, >>Absolutely >>Not. Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Des bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California, after the short break, stay with us. Hey everyone. Welcome to the cue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here. Justin Colby, owner and CEO of innovative solutions they booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. Yeah. >><laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving to the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is. But now we have offices down in Austin, Texas up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? Yeah. >>It's a great question. Every CEO I talk to, that's a small to mid-size business. I'll try and understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the out or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>The SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has additional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start the, on your journey in one way, and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early and not worrying about it, you got it. I mean, most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say so, oh, it's a great analogy. So I mean this, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talk to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam, you know, five, a thousand announcement or whatever they did with huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just product. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>The values. >>Our mission is, is very simple. We want to help every small to mid-size business, leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the pro of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning know that we have their back and we're the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going on loan. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own, it would cost 'em a fortune. If >>It's training alone would be insane. A risk factor not mean the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I >>Love it. It's amazing. So I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get the right >>People involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and BIS is in general, small and large. It staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the why? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side now. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>Like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like >>It, >>But that's so true. I mean, when I think about how, if I were a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we tell, talk about every, with every one of our small to mid-size >>Businesses. So just, I wanna get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, on the value of this business and who knows where you guys are gonna be another five years, what do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy into the business with me. >>And they were the owners, no outside capital, none >>Zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons, they all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an early now process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting going all in on the cloud was important for us and we haven't looked back. >>And at that time the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly. And those kinds of big enterprises, the GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to mid-size business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing where a lot of our small to mid-size as customers, they wanted to leverage cloud-based backup or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is it the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strap and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and Ling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. >>Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break, >>Live on the floor and see San Francisco for a AWS summit. I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at a AWS reinvent a few months ago. Now we're back. Events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube. Check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be >>Here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the UHS summit in New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the game is pretty much laid out mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give an example, uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, it's interesting, Matthew is that we've been covering a, since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam's in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listen to the customers. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does computing. It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue at the edge what's driving the behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see that the data at the edge, you got 5g having. So it's pretty obvious, but there's a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation where today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube cause it's basically Amazon and a box pushed in the data center, running native, all the stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard Deepak syncs. Group's doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW, he was giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outposts. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere or in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative as that you get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are, they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They want on their applications. They want to focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping of these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we talk about hurricanes and we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where you now have data and you have applications that are tapping into that, that required. It makes total sense. We're seeing that across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming a, uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart concept. We use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decentralized. >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my ad. And I also want all the benefit of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercial available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-procesing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard for >>Data, data lake, or whatever, to >>The data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data, unless you have to, um, those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? This is a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud out? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe maybe decision can wait. Right? Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot too, doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And >>Well, I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern was income of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes code, as we call it our lab showcase, we did a whole, whole, that event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are run petabyte level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background on premise architect, a cloud and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You, you got a customer to jump out >>Kind of. So I was jump, I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Yeah. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his cus customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods teaching scout. I think I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started in the first day there, uh, we had a, a discussion, uh, EC two, just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that and through being an on premises migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to >>It's. So it's such a great story, you know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early day was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, um, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days, AWS, the same feeling we have when we >>It's pretty much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live and San Francisco for summit. I'm John Forry host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. look@thiscalendarforallthecubeactionatthecube.net. We'll be right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host to the cube. We'll be at the eight of his summit in New York city. This summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dudes, car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, sir. Chris. Cool. How are, are you >>Good? How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me back to be business with you. Never great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like Norwes Menlo, Tru ventures, coast, lo ventures, Ram Sheam and all those people, all well known guys. The Andy Beckel chime, Paul Mo uh, main web. So a whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it come? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? >>Well, I love having you on the cube, Dave and I, Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a GE, you're like a guest analyst. <laugh> >>You know who you >>Get to call this fun to talk. You though, >>You got the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about on cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing DACA just raised a hundred million on a 2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 million observability companies. Data is the key. What's your angle on this? What's your take. Yeah, >>No, look, I think I'll give you the view that I see right from my side. Obviously data is very clear. So the things that remember system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud NA it'll be called AI, NA AI native is a new buzzword and using the AI customer service it operations. You talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and service desk. What needs to be helped us with ServiceNow BMC G you see a new ELA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflow, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with a AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI pass? One will be at their event this summer? Um, is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. It's >>A feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company, or, but that automation should be embedded in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it. It was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all, all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become called poly databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you were talking about. It should be part of service. Now it should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you've got the expo hall. We got, um, we're back to vents, but you got, you know, AMD, Clum, Ove, uh, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Bel later today. He's a former NEA guy and we always talk to Jerry, Jen. We know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation, clouds bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically data is everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're going to build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's in the of, <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of shit on us saying, Hey, you guys terrible, they didn't get it. Like, yeah. I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> if he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake. So can build it on snowflake. I can use them for data layer. If I really need to size, I'll build it on four.com Salesforce. So I think that's where you'll see. So >>Basically if you're an entrepreneur, the north star in terms of the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. >>Yeah. Yeah. How are, how is Amazon and the clouds dealing with these big whales? The snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got red, um, but Snowflake's a big customer. They're probably paying AWS think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouse as a data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, You know, foreclose your value that's right. But some sort of internal hack, but I think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point. When does the rising tide stop >>And >>Do the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it cloud scale. You invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's, as long as there are more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers or practitioners, not suppliers to the market, feel free to, to XME or DMing. Next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and, you know, small, medium, large, and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or a growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't we get your thoughts on that? What, no, it is. >>If I remember going back to our 2007 or eight, it, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO line business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there, um, and gives back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself? No, I have a lot of thoughts that plus I see AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution will go future towards to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers are give the data, share the data because we thought the data algorithms are useless. I can come the best algorithm, but I gotta train them, modify them, tweak them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to our big data days back in 2009, you know, >>Look at, look how much data bricks has grown. >>It is uh, double, the key >>Cloud kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk, Mac of fee, uh, grandchildren, all the top customers. Um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict S one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of 80 summit, 2022. And we're gonna be at 80 summit in San, uh, in New York and the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This to cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back a little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove, psyched to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube, a lot of hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with duck, bill groove, he founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe as shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at Mark's been doing a lot of shit posting lately, all a billionaires are shit posting, but they don't know how to do it. Like they're not >>Doing it right. Something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. This >>Shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on the other side, I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enterprise tech, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you can see the growth of cloud native Amazons, all, all the Adams let see new CEO, Andy move on to be the chief of all. Amazon just saw him. The cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything these folks do. They they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. It's, it's sprawling, immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. Well, >>There's a lot of force for good conversations, seeing a lot of that going on, Amazon's trying to port and he was trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, sounds like more exciting >>Replacement ready <laugh> in case something goes wrong. I, the track highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other, in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's back any blow back late there been uptick. What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, >>I think >>Chief, we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave ante about how John Fort's always at, uh, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0 5, or we can't, >>We have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting, they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on a number of words. They can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service, ridiculous name. They have systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's >>Fun. What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, Redshift the on an acronym, you >>Gots is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation. >>They still up bean stalk. Or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it. John three <laugh>. >>Okay. >>Simple BV still haunts our dreams. >>I, I actually got an email. I saw one of my, uh, servers, all these C two S were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, give me something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay. So as Amazon gets better in some areas, where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database, Snowflake's got a database service. So Redshift, snowflake database is, so you got this co-op petition. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want and they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word, like multi sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multi-cloud >>Multiple single points? >>Dave loves that term. Yeah. >>Yeah. You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, talk about other clouds, bad direction to go in from a market cap perspective, it doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing, because it solves problems. That's when I shut up and listen. Yeah. >>Cool. Awesome. Corey, I gotta ask you a question, cause I know you, we you've been, you know, fellow journeymen and the, and the cloud journey going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You got a pretty big community growing and it's throwing like crazy. What's the weirdest or coolest thing, or just big chain angels. You've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating. You're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, fun, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is even distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smell delightful. Let make assure you, but it was, but it's also nice to be. >>I have a product for you if you want, you know. >>Oh, excellent. I look forward to it. What is it putting? Why not? <laugh> >>What else have you seen? So when accessibility for talent, which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentations have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. >>Yeah. And also turn off your IMEs too. >>Oh yes. It's always fun in the, in the meetings when you're talking to someone and their co is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. >>Why not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't. No, the only encourager it's fine. >>My kids. Excellent. Yeah. That's fun again. That's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you, or I wanna put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Tell me a story there. >>I, I >>Think that gets a glimpse in a hook and >>Makes more, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did it thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they called for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in Japan or Singapore to access them. And now they're in the index. They're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content, >>Absolutely >>Content value plus >>The networking. And that is the next big revelation of this industry is going to realize you have different companies. And in Amazon's case, different service teams, all, all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here with Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up in the beginnings. Great guy. Check out his blog, his site, his newsletter screaming podcast. Cory, final question for you. Uh, what do you hear doing what's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck build group. We solve one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I indulge my continual and ongoing law of affair with the sound of my own voice. >><laugh> and you good. It's good content. It's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No, thank you. Fun. You. Okay. This the cube covers here in San Francisco, California, the cube is back at to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John furry. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS. The two great guests here from the APN global APN se Jenko and Jeff Grimes partner leader, Jeff and se is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS global startup program. >>That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, of course. Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously were in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. Lot of 'em getting funded, big growth and cloud big growth and data security, hot and sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to provide white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support, dedicated headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, start AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall F for, for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, I got >>A lot. We've got a lot. >>There's a lot. I gotta, I gotta ask the tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it. What do I get out of it? What's >>A good story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company. Yeah. Right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. Sure. So, um, I think what's been fun over the years for me personally, I came from a startup, ran sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired, and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. Yeah. Still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters right. Where everyone's going after similar things. >>Yeah. I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, yeah. You guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake, they're built on top of AWS. Yeah. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's called a foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps compet, the, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching. Certainly I asked this a lot. There's a lot of companies startups out there who makes the, is there a criteria? Oh God, it's not like his sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How do you guys focus? How do you guys focus? I mean, you got a good question, you know, a thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the fees that we look after our infrastructure ISVs, that's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really we're trying to find these ISVs that can solve, uh, really interesting AWS customer challenges. >>So you guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line of business line, like web marketing >>Solutions, business apps, >>Business, this owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage, backup, ransomware of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startup that we cover is that they've got, they truly have support from a build market sell perspective. Right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can we waste that sock report? Oh, download it, the console, which we use all the time. Exactly. But security's a big deal. I mean, you know, SREs are evolving, that role of DevOps is taking on dev SecOps. Um, I, I could see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or not, not part of a, uh, >>Yeah, >>So the partner development manager can be an escalation point. Absolutely. Think of them as an extension of your business inside of AWS. >>Great. And you guys how's that partner managers, uh, measure >>On those three pillars. Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's >>Very important. I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top >>Line. Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the startups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. Mm-hmm <affirmative> the challenge is they just might not have the brand recognition that the big guys have. And so that it's our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF and then outside SF, you guys have a global program, you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here that's doing, uh, AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously a ton of partners, I, from the bay area that we support. Um, but we're seeing a lot of really interesting technology coming out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy real quick, before you get in the surge. It's interesting. The VC market in, in Europe is hot. Yeah. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. We'll see if they crash, you know, but we don't see that happening. I mean, people have been projecting a crash now in, in the startup ecosystem for at least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the pandemic because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Leski both say the same thing during the pandemic necessity, the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of walk me through, pretend me I'm a startup. Hey, I am on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Surge? What, what do I do? >>That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement and where do they want to go at the end of the day? Um, and oftentimes because we've worked with so many successful startups, they have come out of our program. We have, um, either through intuition or a playbook, determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love star rights here in the cube because one, um, they have good stories. They're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startup showcases startups.com. Check out AWS startups.com and you got the showcases, uh, final. We I'll give you guys the last word. What's the bottom line bumper sticker for AP the global APN program. Summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally start >>With you. Yeah. I think the AWS global startup program's here to help companies truly accelerate their business full stop. Right. And that's what we're here for. I love it. >>It's a good way to, it's a good way to put it Dito. >>Yeah. All right, sir. Thanks for coming on. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of the realities here. Open source and cloud all making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for watching >>John. >>Hello and welcome back to the cubes live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city. Coming up this summer, we'll be there as well at events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net, check it out a lot of content this year, more than ever, a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability Jeremy. Great to see you. Thanks >>Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability hot area, but also you've been a senior executive president of Dell, uh, EMC, uh, 11 years ago you had a, a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here. You predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for, for sort of catching that bus out, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved, uh, the board level, you know, the founders, you know, the people there cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applic. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflake is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think riding more software than, than ever fall. Why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data and the, you know, the sort of the transactions, you know, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then I not, where did they drop off all of that they wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code. One of the insights that we got out of that I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some query, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and >>Yeah, yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you, of enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I, I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that yeah, it is about the data. You know, if I can better understand my data better than my competitor than I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. So >>Let's talk about observing you the CEO of, okay. Given you've seen the wave before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of, of something from years gone by. >>But, um, there's a guy called, um, Rudy Coleman in 1960s, kinder term. And, and, and the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of the all years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. <affirmative> um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike on our board. And, um, you know, part of the observed story yeah. Is closely knit with snowflake because all of that time data know we, we still are in there. >>So I want to get, uh, >>Yeah. >>Pivot to that. Mike Pfizer, snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with snowflake. So a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? >>I mean, having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, to many years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operator and system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah. It's >>Okay. But hyperscale, yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generator data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snow snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy. >>So you're building on top of snowflake. >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You >>Still on the board. >>Yeah. I'm still on the board. Yeah. That that's a risk I'm prepared to take <laugh> I am long on snowflake you, >>Well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No know just doing, but the, this is a real dynamic. It is. It's not a one off it's. >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is an order of magnitude more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I believe the opportunity for folks like snowflake and folks like observe it's an order of magnitude more than it was for the Oracle and the SAPs of the old >>World. Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite >>Easy or be the platform, but it's hard. There's only like how many seats are at that table left. >>Well, value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, Rackspace and there's 1,000,001 infrastructure, a service platform as a service, my, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. You don't hear so much about it, these, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters. Cause then if the provision, the CapEx, now the CapEx is in the cloud. Then you build on top of that, you got snowflake you on top of that, the >>Assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's >>Almost free, >>But, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get into. >>And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a serious, multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me like, look, you're building on snowflake. Um, you, you know, you are, you are, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying them money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well in observe, but then I've got half the development team working on in that will never be as good as snowflake. And so we made the call early on that. No, no, we, we wanna innovate above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's actually more on snowflake. I I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS >>One and for snowflake and, and any platform provider, it's a beautiful thing. You know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of ecosystems. >>Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New products. You're scaling that function with the, >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is invaluable, >>You know, but Jeremy Greek conversation, thanks for sharing your insights on the industry. Uh, we got a couple minutes left. Um, put a plug in for observe. What do you guys, I know you got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting traction. Yeah. >>Yeah. >>Scales around the corner. Sounds like, are you, is that where you are scale? >>Got, we've got a big announcement coming up in two or weeks. We've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, uh, but it's gonna be exciting. And, and like I saids hill continued to, to, to stick, >>I think capital one's a big snowflake customer as well. Right. They, >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. Yeah. And, and today that, that is one of Snowflake's biggest accounts. >>So capital one, very innovative cloud, obviously AIOS customer and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, right? So you got POCs, what's that trick GE look like, can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit the straight and narrow and, and gas it >>Fast. Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage is questions that the board are always about, like, is the product, right? Is the product right? Is the product right? If you got the product right. And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we were, we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the new lakes and, and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us, this year's a big one, cuz we sort of complete the trifecta, you know, the, the logs, >>What's the secret sauce observe. What if you had the, put it into a, a sentence what's the secret sauce? I, >>I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors. And, and the biggest thing our investors give is actually it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. Why I got you here? You've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their business restructure. So a lot happening in cloud. What's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out out a way to take their, this to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B prepared to take risks and it's, it's a race against time to, you know, get their, their offerings in this. So a new digital footprint, >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10. Uh, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. >>Yeah. They're, they're, it's an amazing story. I mean, you know, we we're, we're on AWS as well. And so I, I think if they keep nurturing the builders in the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late it was, they stopped, uh, really caring about developers and the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing head start and if they did more, you know, if they do more than that, that's, what's gonna keep the jut rolling for many years to come. Yeah, >>They got the silicone and they got the staff act, developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great start. Thanks for coming on the cube. >>Always a pleasure. >>Okay. Live from San Francisco to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers of the bay area at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics AI thing, all coming together. Lots of coverage stay with us today. We've got a great guest from Deibel VC. John Skoda, founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, Matt. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over a decade. Um, >><affirmative>, it's been at least 10 years now, >>At least 10 years more. And we don't wanna actually go back as frees back, uh, the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in >>Second. We, we are, it's a little bit of a throwback to the path though, in my opinion, >><laugh>, it's all the same. It's all distributed computing and software. We ran each other in cube con you're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software is take old something old and make it better, new, faster. <laugh>. So tell us about Deibel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you're doing. I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called, I am logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of our companies, uh, early investor in open source companies and cloud companies and spent a really wonderful 12 years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start enter price software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting in an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building products that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchased software that has traditionally bought and sold tops down. But, you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early opts. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great and emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies. The is no, I mean, consumer is enterprise. Now everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. Well, and, >>And I think all of us here that are, uh, maybe students of history and have been involved in, open in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three movement. >>The hype is definitely that three. >>Yeah. But, but >>You know, for >>Sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many men over, uh, 500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant, but it's also the hype of like the web three, for instance. But you know, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher direct sales force and SAS kind of crushed the, at now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data. You know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all successful startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. You >>Just pull the >>Product through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement maybe started with open source where users were, are contributors, you know, contributors, we're users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a GenXer technically, so for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been staying on the cube for probably about eight years now that we are gonna hit a digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>It's the main for days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean >>The decision making, let me ask you this next question. As a VC. Now you look at pitch, well, you've made a VC for many years, but you also have the founder, uh, entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the person. So fing, so you make, it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. You, I still think that that's important, right? It still is a human need for people to believe in narratives and stories. But having said that you're right, the proof is in the pudding, right? At some point you click download and you try the product and it does what it says it it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy that we live in, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their products exactly >>The volume back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song was the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the, you know, it's gotta speak to >>The, speak to the user, but let me ask a question now that the people watching who are maybe entrepreneurial entrepreneur, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage, engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I >>Show >>The path. I think the single most important thing for any founder and VC relationship is that they have the same vision, uh, have the same vision. You can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens in six months. Sometimes it takes six years is sometimes like 16 years. >>Uh, what's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Desel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There, there's three big trends that we invest in. And they're the, they're the only things we do day in, day out. One is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen and on what timeline happening >>Forever. >>But it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a, a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is under invested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion. And it still is a fraction of what we're, what >>We're and security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters of your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cub gone. Uh, >>Absolutely. >>Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for having me on >>The show. Guess bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After the short break, stay with us. Everyone. Welcome to the queue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with the events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube got a great guest here. Justin Coby owner and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us a story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving into the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas up in Toronto, uh, key Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago and it's been a great ride. It >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small to midsize business. They're trying to understand how to leverage technology. It better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech ISNT really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the cloud or we move some things to cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strateg, always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want get set up. But then the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>In the SMB space? The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. >>Good. How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I, there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning the projects that early and not worrying about it, you got it. I mean, most people don't abandon cause like, oh, I own it. >>Exactly. And >>They get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say. So, oh, it's a great analogy. So I mean, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you, I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did am jazzy announce or Adam, you know, the 5,000 announcement or whatever. They do huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are, >>What's the values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your, or it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back Andre or the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner, that's all offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a fortune. If >>Training alone would be insane, a factor and the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement and still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I love it. It's amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and businesses in general, small en large, it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cybersecurity issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one and the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about. So that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side though. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And, and the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll >>Do all that >>Exactly. In it department. >>Exactly. >>Like, can we just call up, uh, you know, <laugh> our old vendor. That's >>Right. <laugh> right. Our old vendor. I like it, but that's so true. I mean, when I think about how, if I was a business owner, starting a business to today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we talk about every, with every one of our small to midsize business. >>So just, I want to get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at R I T long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that we're gonna also buy the business with >>Me. And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they care very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us and we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The game don't, won't say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing were a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud and a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on eight at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers, empathetic to where they are in their journey. And >>That's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and doubling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. Thank >>You very much for having >>Me. Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching with back with more great coverage for two days after this short break >>Live on the floor in San Francisco for 80 west summit, I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube, bringing all the action. Also virtual, we have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticketing off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad >>To be here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the, uh, New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the, the game is pretty much laid out. Mm. And the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud out for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and then became the CEO. Now Adam Slosky is in charge, but the edge has always been that thing they've been trying to, I don't wanna say, trying to avoid, of course, Amazon would listen to customers. They work backwards from the customers. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. It >>Does. >>That's not central lies in the public cloud. Now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the <affirmative> what's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over fit 15 AWS edge services, and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube, uh, cuz it's basically Amazon in a box, pushed in the data center, uh, running native, all the stuff, but now cloud native operations are kind of become standard. You're starting to see some standard Deepak sings group is doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see low the zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I wanna manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere in your VMware environment and it's increasing the speed of adoption >>For sure. So you guys are making a lot of good business decisions around managed cloud service. Innovative does that. You have the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their available ability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They wanna focus on their applications. They want focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. We help build out these things in local data centers for 32 plus year old company, we have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. >>So basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we're gonna talk about hurricanes and gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data, you have applications that are tapping into that, that requirement. It makes total sense. We're seeing across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech in, in the islands. There are a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto underly parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a tech technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. And I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead. It's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decent centralized. >>Yeah. And that's, and that's the conversation performance. >>Yeah. >>And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through a, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a and I also want all the benefits of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the good this of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-processing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take the, those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data lake or whatever, >>To the data lake. Yeah. Data Lakehouse, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but I'll lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going of the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you, what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacture, industrial, whatever the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture in the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about out. Customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern we're seeing of the past year is that throwing away data's bad, even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retraining their machine learning algorithms. Yep. So as data becomes code, as we call it in our last showcase, we did a whole whole event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw it away. It's not just business better. Yeah. There's all kinds of new scale. >>There are. And, and we have, uh, many customers that are running pay Toby level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move Aytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background, OnPrem architect, Aus cloud, and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You got a customer to jump out >>Kind of. So I was, you jumped out. I was teaching having, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a sky. I instructor, uh, I was teaching skydiving and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his customers are working. And he can't find an enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started and the first day there, uh, we had a, a discussion, uh, EC two had just come out <laugh> and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services tore >>It's. So it's such a great story, you know, was gonna, you know, you know, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You got the right equipment. You gotta do the right things. Exactly. >>Right. >>Yeah. Thanks for coming. You really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live in San Francisco for eight of us summit. I'm John for host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look up this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host of the cube. We'll be at the eighties summit in New York city this summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor in a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you. Cool. How are you? Good. >>How hello you. >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? >>First of all, thank you for having me. We're back to be business with you, never after to see you. Uh, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. We have raised close to a hundred million there. The investors are people like Norwes Menlo ventures, coastal ventures, Ram Shera, and all those people, all well known guys. And Beckel chime Paul me Mayard web. So whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISRA is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and service now to take you to the next stage? Well, >>I love having you on the cube, Dave and I, Dave LAN as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh> >>You know, who does >>You, >>You >>Get the call fund to talk to you though. You >>Get the commentary, your, your finger in the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on a $2 billion valuation back from the dead after they pivoted from enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control plan? Emerging AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 billion observability companies. Data is the key. This is what's your end on this. What's your take. >>Yeah, look, I think I'll give you the few that I see right from my side. Obviously data is very clear. So the things that rumor system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA AI enable is a new buzzword and using the AI for customer service. It, you talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI services. What used to be desk with ServiceNow BMC GLA you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you, you see AI going >>Off is RPA. A company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, is it a product company? I mean, or I mean, RPA is, should be embedded in everything. It's a >>Feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be embedded in every area. Yeah. Like we call cloud NATO and AI. They it'll become automation data. Yeah. And that's your, thinking's >>Interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed. Are they integrated? I mean, these are the challenges. This is crazy. What's the, >>So remember the databases became called polyglot databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you, you were talking about, it should be part of service. Now it should be part of ISRA. Like every company, every Salesforce. So that's why you see it MuleSoft and sales buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer embedded inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind, as you got the XPO hall got, um, we're back to vis, but you got, you know, AMD, Clum, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right? Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs, what does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be people don't just build on Amazon. They're going to build it on top of snow. Flake companies are snowflake becomes a data platform, right? People will build on snowflake, right? So I see my old boss playing ment, try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer, right? So I think that's the next level of companies trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last re invent, coined the term super cloud, right? It's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You're starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of hitting on us saying, Hey, you guys terrible, they didn't get him. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist and, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer room. The middle layer pass will be snowflake. So I cannot build it on snowflake. I can use them for data layer if I really need to size, I'll build it on force.com Salesforce. Yeah. Right. So I think that's where you'll >>See. So basically the, the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. It >>Is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got Redshift. Um, but snowflake big customer. The they're probably paying AWS big, >>I >>Think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with the snowflake to have native snowflake data warehouse as a data layer. So I think depending on the use case you have to use each of the above, I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose your value. That's right. With some sort of internal hack, but I've think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it closed skill you the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, on-prem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations, it helpless. Even the customer service service. Now the ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the market. Feel free to text me or DMing. Next question is really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and you know, small, medium, large, and large enterprise, they're all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean seeing some stuff, but why don't we get your thoughts on that? What it >>Is you, if I remember going back to our 2007 or eight, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or one person today. Most companies are already spending 20, 30% with startups. Like if I look at a C I will line our business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. Yeah. >>And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I, I reference the URL causes like there's like a bunch of companies we've been promoting because the solution that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share? >>I, a lot of thoughts that Fu I see the AI op solutions in the futures should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app dynamic, right? Dynatrace, all this solution will go future towards predict to pro so solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers give the data, share the data because we thought the data algorithms are useless. I can give the best algorithm, but I gotta train them, modify them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know that >>Look at, look how much data bricks has grown. >>It is doubled. The key cloud >>Air kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking year that growing customers and my customers, or some of them, you like it's zoom auto desk, McAfee, uh, grand <inaudible>. So all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on, predict ours. One area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of a us summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on the calendar, of course, go to a us startups.com. That's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be two with the cube on the set. We're getting back in the Groove's psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economist with duck bill groove, he's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit posting, but they don't know how to do it. They're >>Doing it right. There's something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what, what is shitposting >>It's more or less talking about the world of enterprise technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream, but it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a Jack ass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, Cuban coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's evolving Atos, especially new CEO. Andy move on to be the chief of all. Amazon just saw him the cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble. Imagine the logistics, it takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense, the nominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to a, is trying to portray themselves, you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it's same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car, our driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, it sounds like more exciting. Like they >>Better have a replacement ready in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula, the one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other people in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. Oh, >>It's great too. And I can see the appeal of these tech companies getting it into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great SA we've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late leads there been tick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's hi, I'm emailing an awful lot of people at last week in AWS every week and okay. They not have heard me. It. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, I >>Think >>I guarantee if we had that right now, people would call in and Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave Avante about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish, but that's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their product >>They're going in different directions. When they named Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonus on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, a session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store with is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage through parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, RedShift's not an acronym. You got >>Gas is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, >>They still got bean stock or is that still >>Around? Oh, they never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it, John. >>Okay. >>Simple BV still haunts our >>Dreams. I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, gimme something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay, so as Amazon gets better in some areas where do they need more work? And you, your opinion, because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So, you know, Redshift, snowflake database is out there. So you've got this optician. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Loves that term. Yeah. >>You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the, the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah. Cool. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journey mean in the, in the cloud journey, going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna end, certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing, or just big changes you've seen with the pan endemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who >>Can pony. >>Hello and welcome back to the live cube coverage here in San Francisco, California, the cube live coverage. Two days, day two of a summit, 2022 Aish summit, New York city coming up in summer. We'll be there as well. Events are back. I'm the host, John fur, the Cub got great guest here. Johnny Dallas with Ze. Um, here is on the queue. We're gonna talk about his background. Uh, little trivia here. He was the youngest engineer ever worked at Amazon at the age. 17 had to get escorted into reinvent in Vegas cause he was underage <laugh> with security, all good stories. Now the CEO of company called Z know DevOps kind of focus, managed service, a lot of cool stuff, Johnny, welcome to the cube. >>Thanks John. Great. >>So tell a story. You were the youngest engineer at AWS. >>I was, yes. So I used to work at a company called Bebo. I got started very young. I started working when I was about 14, um, kind of as a software engineer. And when I, uh, it was about 16. I graduated out of high school early, um, working at this company Bebo, still running all of the DevOps at that company. Um, I went to reinvent in about 2018 to give a talk about some of the DevOps software I wrote at that company. Um, but you know, as many of those things were probably familiar with reinvent happens in a casino and I was 16. So was not able to actually go into the, a casino on my own. Um, so I'd have <inaudible> security as well as casino security escort me in to give my talk. >>Did Andy jazzy, was he aware of >>This? Um, you know, that's a great question. I don't know. <laugh> >>I'll ask him great story. So obviously you started a young age. I mean, it's so cool to see you jump right in. I mean, I mean you never grew up with the old school that I used to grew up in and loading package software, loading it onto the server, deploying it, plugging the cables in, I mean you just rocking and rolling with DevOps as you look back now what's the big generational shift because now you got the Z generation coming in, millennials on the workforce. It's changing like no one's putting and software on servers. Yeah, >>No. I mean the tools keep getting better, right? We, we keep creating more abstractions that make it easier and easier. When I, when I started doing DevOps, I could go straight into E two APIs. I had APIs from the get go and you know, my background was, I was a software engineer. I never went through like the CIS admin stack. I, I never had to, like you said, rack servers, myself. I was immediately able to scale. I was managing, I think 2,500 concurrent servers across every Ables region through software. It was a fundamental shift. >>Did you know what an SRE was at that time? >>Uh, >>You were kind of an SRE on >>Yeah, I was basically our first SRE, um, was familiar with the, with the phrasing, but really thought of myself as a software engineer who knows cloud APIs, not a SRE. All >>Right. So let's talk about what's what's going on now as you look at the landscape today, what's the coolest thing that's going on in your mind in cloud? >>Yeah, I think the, I think the coolest thing is, you know, we're seeing the next layer of those abstraction tools exist and that's what we're doing with Z is we've basically gone and we've, we're building an app platform that deploys onto your cloud. So if you're familiar with something like Carku, um, where you just click a GitHub repo, uh, we actually make it that easy. You click a GI hub repo and it will deploy on ALS using a AWS tools. So, >>Right. So this is Z. This is the company. Yes. How old's the company about >>A year and a half old now. >>All right. So explain what it does. >>Yeah. So we make it really easy for any software engineer to deploy on a AWS. It's not SREs. These are the actual application engineers doing the business logic. They don't really want to think about Yamo. They don't really want to configure everything super deeply. They want to say, run this API on S in the best way possible. We've encoded all the best practices into software and we set it up for you. Yeah. >>So I think the problem you're solving is that there's a lot of want be DevOps engineers. And then they realize, oh shit, I don't wanna do this. Yeah. And some people want to do it. They loved under the hood. Right. People love to have infrastructure, but the average developer needs to actually be as agile on scale. So that seems to be the problem you solve. Right? >>Yeah. We, we, we give way more productivity to each individual engineer, you know? >>All right. So let me ask you a question. So let me just say, I'm a developer. Cool. I build this new app. It's a streaming app or whatever. I'm making it up cube here, but let's just say I deploy it. I need your service. But what happens about when my customers say, Hey, what's your SLA? The CDN went down from this it's flaky. Does Amazon have, so how do you handle all that SLA reporting that Amazon provides? Cuz they do a good job with sock reports all through the console. But as you start getting into DevOps <affirmative> and sell your app, mm-hmm <affirmative> you have customer issues. How do you, how do you view that? Yeah, >>Well, I, I think you make a great point of AWS has all this stuff already. AWS has SLAs. AWS has contract. Aw has a lot of the tools that are expected. Um, so we don't have to reinvent the wheel here. What we do is we help people get to those SLAs more easily. So Hey, this is AWS SLA as a default. Um, Hey, we'll fix you your services. This is what you can expect here. Um, but we can really leverage S's reliability of you. Don't have to trust us. You have to trust ALS and trust that the setup is good there. >>Do you handle all the recovery or mitigation between, uh, identification say downtime for instance? Oh, the server's not 99% downtime. Uh, went down for an hour, say something's going on? And is there a service dashboard? How does it get what's the remedy? Do you have a, how does all that work? >>Yeah, so we have some built in remediation. You know, we, we basically say we're gonna do as much as we can to keep your endpoint up 24 7 mm-hmm <affirmative>. If it's something in our control, we'll do it. If it's a disc failure, that's on us. If you push bad code, we won't put out that new version until it's working. Um, so we do a lot to make sure that your endpoint stay is up, um, and then alert you if there's a problem that we can't fix. So cool. Hey S has some downtime, this thing's going on. You need to do this action. Um, we'll let you know. >>All right. So what do you do for fun? >>Yeah, so, uh, for, for fun, um, a lot of side projects. <laugh> uh, >>What's your side hustle right now. You got going on >>The, uh, it's >>A lot of tools playing tools, serverless. >>Yeah, painless. A lot of serverless stuff. Um, I think there's a lot of really cool WAM stuff as well. Going on right now. Um, I love tools is, is the truest answer is I love building something that I can give to somebody else. And they're suddenly twice as productive because of it. Um, >>It's a good feeling, isn't it? >>Oh yeah. There's >>Nothing like tools were platforms. Mm-hmm <affirmative>, you know, the expression, too many tools in the tool. She becomes, you know, tools for all. And then ultimately tools become platforms. What's your view on that? Because if a good tool works and starts to get traction, you need to either add more tools or start building a platform platform versus tool. What's your, what's your view on a reaction to that kind of concept debate? >>Yeah, it's a good question. Uh, we we've basically started as like a, a platform. First of we've really focused on these, uh, developers who don't wanna get deep into the DevOps. And so we've done all of the pieces of the stacks. We do C I C D management. Uh, we do container orchestration, we do monitoring. Um, and now we're, spliting those up into individual tools so they can be used. Awesome in conjunction more. >>All right. So what are some of the use cases that you see for your service? It's DevOps basically nano service DevOps. So people who want a DevOps team, do clients have a DevOps person and then one person, two people what's the requirements to run >>Z. Yeah. So we we've got teams, um, from no DevOps is kind of when they start and then we've had teams grow up to about, uh, five, 10 men DevOps teams. Um, so, you know, as is more infrastructure people come in because we're in your cloud, you're able to go in and configure it on top you're we can't block you. Uh, you wanna use some new AWS service. You're welcome to use that alongside the stack that we deploy >>For you. How many customers do you have now? >>So we've got about 40 companies that are using us for all of their infrastructure, um, kind of across the board, um, as well as >>What's the pricing model. >>Uh, so our pricing model is we, we charge basically similar to an engineering salary. So we charge a monthly rate. We have plans at 300 bucks a month, a thousand bucks a month, and then enterprise plan for >>The requirement scale. Yeah. So back into the people cost, you must have her discounts, not a fully loaded thing, is it? >>Yeah, there's a discounts kind of asking >>Then you pass the Amazon bill. >>Yeah. So our customers actually pay for the Amazon bill themselves. So >>Have their own >>Account. There's no margin on top. You're linking your, a analyst account in, um, got it. Which is huge because we can, we are now able to help our customers get better deals with Amazon. Um, got it. We're incentivized on their team to drive your costs down. >>And what's your unit main unit of economics software scale. >>Yeah. Um, yeah, so we, we think of things as projects. How many services do you have to deploy as that scales up? Um, awesome. >>All right. You're 20 years old now you not even can't even drink legally. <laugh> what are you gonna do when you're 30? We're gonna be there. >>Well, we're, uh, we're making it better, better, >>Better the old guy on the queue here. <laugh> >>I think, uh, I think we're seeing a big shift of, um, you know, we've got these major clouds. ALS is obviously the biggest cloud and it's constantly coming out with new services, but we're starting to see other clouds have built many of the common services. So Kubernetes is a great example. It exists across all the clouds and we're starting to see new platforms come up on top that allow you to leverage tools for multiple times. At the same time. Many of our customers actually have AWS as their primary cloud and they'll have secondary clouds or they'll pull features from other clouds into AWS, um, through our software. I think that's, I'm very excited by that. And I, uh, expect to be working on that when I'm 30. <laugh> awesome. >>Well, you gonna have a good future. I gotta ask you this question cuz uh, you know, I always, I was a computer science undergrad in the, in the, and um, computer science back then was hardcore, mostly systems OS stuff, uh, database compiler. Um, now there's so much compi, right? Mm-hmm <affirmative> how do you look at the high school college curriculum experience slash folks who are nerding out on computer science? It's not one or two things. You've got a lot of, lot of things. I mean, look at Python, data engineering and emerging as a huge skill. What's it, what's it like for college kids now and high school kids? What, what do you think they should be doing if you had to give advice to your 16 year old self back a few years ago now in college? Um, I mean Python's not a great language, but it's super effective for coding and the datas were really relevant, but it's, you've got other language opportunities you've got tools to build. So you got a whole culture of young builders out there. What should, what should people gravitate to in your opinion and stay away from or >>Stay away from? That's a good question. I, I think that first of all, you're very right of the, the amount of developers is increasing so quickly. Um, and so we see more specialization. That's why we also see, you know, these SREs that are different than typical application engineering. You know, you get more specialization in job roles. Um, I think if, what I'd say to my 16 year old self is do projects, um, the, I learned most of my, what I've learned just on the job or online trying things, playing with different technologies, actually getting stuff out into the world, um, way more useful than what you'll learn in kind of a college classroom. I think classroom's great to, uh, get a basis, but you need to go out and experiment actually try things. >>You know? I think that's great advice. In fact, I would just say from my experience of doing all the hard stuff and cloud is so great for just saying, okay, I'm done, I'm banning the project. Move on. Yeah. Cause you know, it's not gonna work in the old days. You have to build this data center. I bought all this, you know, people hang on to the old, you know, project and try to force it out there. Now you >>Can launch a project now, >>Instant gratification, it ain't working <laugh> or this is shut it down and then move on to something new. >>Yeah, exactly. Instantly you should be able to do that much more quickly. Right. So >>You're saying get those projects and don't be afraid to shut it down. Mm-hmm <affirmative> that? Do you agree with that? >>Yeah. I think it's ex experiment. Uh, you're probably not gonna hit it rich on the first one. It's probably not gonna be that idea is the genius idea. So don't be afraid to get rid of things and just try over and over again. It's it's number of reps >>That'll win. I was commenting online. Elon Musk was gonna buy Twitter, that whole Twitter thing. And someone said, Hey, you know, what's the, I go look at the product group at Twitter's been so messed up because they actually did get it right on the first time. And we can just a great product. They could never change it because people would freak out and the utility of Twitter. I mean, they gotta add some things, the added button and we all know what they need to add, but the product, it was just like this internal dysfunction, the product team, what are we gonna work on? Don't change the product so that you kind of have there's opportunities out there where you might get the lucky strike right outta the gate. Yeah. Right. You don't know. >>It's almost a curse too. It's you're not gonna hit curse Twitter. You're not gonna hit a rich the second time too. So yeah. >><laugh> Johnny Dallas. Thanks for coming on the cube. Really appreciate it. Give a plug for your company. Um, take a minute to explain what you're working on. What you're look looking for. You hiring funding. Customers. Just give a plug, uh, last minute and kind the last word. >>Yeah. So, um, John Dallas from Ze, if you, uh, need any help with your DevOps, if you're a early startup, you don't have DevOps team, um, or you're trying to deploy across clouds, check us out z.com. Um, we are actively hiring. So if you are a software engineer excited about tools and cloud, or you're interested in helping getting this message out there, hit me up. Um, find us on z.co. >>Yeah. LinkedIn Twitter handle GitHub handle. >>Yeah. I'm the only Johnny on a LinkedIn and GitHub and underscore Johnny Dallas underscore on Twitter. All right. Um, >>Johnny Dallas, the youngest engineer working at Amazon, um, now 20 we're on great new project here in the cube. Builders are all young. They're growing into the business. They got cloud at their, at their back it's tailwind. I wish I was 20. Again, this is a I'm John for your host. Thanks for watching. Thanks. >>Welcome >>Back to the cubes. Live coverage of a AWS summit in San Francisco, California events are back, uh, ADAS summit in New York cities. This summer, the cube will be there as well. Check us out there lot. I'm glad we have events back. It's great to have everyone here. I'm John furry host of the cube. Dr. Matt wood is with me cube alumni now VP of business analytics division of AWS. Matt. Great to see you. Thank >>You, John. Great to be here. >>Appreciate it. I always call you Dr. Matt wood, because Andy jazzy always says Dr. Matt, we >>Would introduce you on the he's the one and only the one and >>Only Dr. Matt wood >>In joke. I love it. >>Andy style. And I think you had walkup music too on, you know, >>Too. Yes. We all have our own personalized walk. >>So talk about your new role. I not new role, but you're running up, um, analytics, business or AWS. What does that consist of right now? >>Sure. So I work, I've got what I consider to be the one of the best jobs in the world. Uh, I get to work with our customers and, uh, the teams at AWS, uh, to build the analytics services that millions of our customers use to, um, uh, slice dice, pivot, uh, better understand their day data, um, look at how they can use that data for, um, reporting, looking backwards and also look at how they can use that data looking forward. So predictive analytics and machine learning. So whether it is, you know, slicing and dicing in the lower level of, uh Hado and the big data engines, or whether you're doing ETR with glue or whether you're visualizing the data in quick side or building models in SageMaker. I got my, uh, fingers in a lot of pies. >>You know, one of the benefits of, uh, having cube coverage with AWS since 2013 is watching the progression. You were on the cube that first year we were at reinvent 2013 and look at how machine learning just exploded onto the scene. You were involved in that from day one is still day one, as you guys say mm-hmm <affirmative>, what's the big thing now. I mean, look at, look at just what happened. Machine learning comes in and then a slew of services come in and got SageMaker became a hot seller, right outta the gate. Mm-hmm <affirmative> the database stuff was kicking butt. So all this is now booming. Mm-hmm <affirmative> that was the real generational changeover for <inaudible> what's the perspective. What's your perspective on, yeah, >>I think how that's evolved. No, I think it's a really good point. I, I totally agree. I think for machine machine learning, um, there was sort of a Renaissance in machine learning and the application of machine learning machine learning as a technology has been around for 50 years, let's say, but, uh, to do machine learning, right? You need like a lot of data, the data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute. You need to be able to train the models <laugh> and so where you go. >>And so the cloud really enabled this Renaissance with machine learning, and we're seeing honestly, a similar Renaissance with, uh, with data, uh, and analytics. You know, if you look back, you know, five, 10 years, um, analytics was something you did in batch, like your data warehouse ran a analysis to do, uh, reconciliation at the end of the month. And then was it? Yeah. And so that's when you needed it, but today, if your Redshift cluster isn't available, uh, Uber drivers don't turn up door dash deliveries, don't get made. It's analytics is now central to virtually every business and it is central to every virtually every business is digital transformation. Yeah. And be able to take that data from a variety of sources here, or to query it with high performance mm-hmm <affirmative> to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form, you know, wisdom and information from raw data. That's kind of, uh, what most organizations are trying to do when they kind of go through this analytics journey. It's >>Interesting, you know, Dave LAN and I always talk on the cube, but out, you know, the future and, and you look back, the things we were talking about six years ago are actually happening now. Yeah. And it's not a, a, a, you know, hyped up statement to say digital transformation. It actually's happening now. And there's also times where we bang our fist on the table, say, I really think this is so important. And Dave says, John, you're gonna die on that hill <laugh>. >>And >>So I I'm excited that this year, for the first time I didn't die on that hill. I've been saying data you're right. Data as code is the next infrastructure as code mm-hmm <affirmative>. And Dave's like, what do you mean by that? We're talking about like how data gets and it's happening. So we just had an event on our 80 bus startups.com site mm-hmm <affirmative>, um, a showcase with startups and the theme was data as code and interesting new trends emerging really clearly the role of a data engineer, right? Like an SRE, what an SRE did for cloud. You have a new data engineering role because of the developer on, uh, onboarding is massively increasing exponentially, new developers, data science, scientists are growing mm-hmm <affirmative> and the, but the pipelining and managing and engineering as a system. Yeah. Almost like an operating system >>And as a discipline. >>So what's your reaction to that about this data engineer data as code, because if you have horizontally scalable data, you've gotta be open that's hard. <laugh> mm-hmm <affirmative> and you gotta silo the data that needs to be siloed for compliance and reasons. So that's got a very policy around that. So what's your reaction to data as code and data engineering and >>Phenomenon? Yeah, I think it's, it's a really good point. I think, you know, like with any, with any technology, uh, project inside an organization, you know, success with analytics or machine learning is it's kind of 50% technology and then 50% cultural. And, uh, you have often domain experts. Those are, could be physicians or drug experts, or they could be financial experts or whoever they might be got deep domain expertise. And then you've got technical implementation teams and it's kind of a natural often repulsive force. I don't mean that rudely, but they, they just, they don't talk the same language. And so the more complex the domain and the more complex the technology, the stronger that repulsive force, and it can become very difficult for, um, domain experts to work closely with the technical experts, to be able to actually get business decisions made. And so what data engineering does and data engineering is in some cases team, or it can be a role that you play. >>Uh, it's really allowing those two disciplines to speak the same language it provides. You can think of it as plumbing, but I think of it as like a bridge, it's a bridge between like the technical implementation and the domain experts. And that requires like a very disparate range of skills. You've gotta understand about statistics. You've gotta understand about the implementation. You've gotta understand about the, it, you've gotta understand and understand about the domain. And if you could pull all of that together, that data engineering discipline can be incredibly transformative for an organization, cuz it builds the bridge between those two >>Groups. You know, I was advising some, uh, young computer science students at the sophomore junior level, uh, just a couple weeks ago. And I told 'em, I would ask someone at Amazon, this questions I'll ask you since you're, you've been in the middle of of it for years, they were asking me and I was trying to mentor them on. What, how do you become a data engineer from a practical standpoint, uh, courseware projects to work on how to think, um, not just coding Python cause everyone's coding in Python mm-hmm <affirmative> but what else can they do? So I was trying to help them and I didn't really know the answer myself. I was just trying to like kind of help figure it out with them. So what is the answer in your opinion or the thoughts around advice to young students who want to be data engineers? Cuz data scientists is pretty clear in what that is. Yeah. You use tools, you make visualizations, you manage data, you get answers and insights and apply that to the business. That's an application mm-hmm <affirmative>, that's not the, you know, sta standing up a stack or managing the infrastructure. What, so what does that coding look like? What would your advice be to >>Yeah, I think >>Folks getting into a data engineering role. >>Yeah. I think if you, if you believe this, what I said earlier about like 50% technology, 50% culture, like the, the number one technology to learn as a data engineer is the tools in the cloud, which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the, the storage is kind of fungible or UND differentiated. That that's really not the case. Success requires you to really purpose built well crafted high performance, low cost engines for all of your data. So understanding those tools and understanding how to use 'em, that's probably the most important technical piece. Um, and yeah, Python and programming and statistics goes along with that, I think. And then the most important cultural part, I think is it's just curiosity. >>Like you want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem and to be able to engage, cuz you're probably, you're gonna have some choice as you go through your career about which domain you end up in, like maybe you're really passionate about healthcare. Maybe you're really just passionate about your transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity, but within those roles, like the domains are so broad, you kind of gotta allow your curiosity to develop and lead, to ask the right questions and engage in the right way with your teams. So because you can have all the technical skills in the world, but if you're not able to help the team's truths seek through that curiosity, you simply won't be successful. >>We just had a guest on 20 year old, um, engineer, founder, Johnny Dallas, who was 16 when he worked at Amazon youngest engineer at >>Johnny Dallas is a great name by the that's fantastic. It's his real name? >>It sounds like a football player. Rockstar. I should call Johnny. I have Johnny Johnny cube. Uh it's me. Um, so, but he's young and, and he, he was saying, you know, his advice was just do projects. >>Yeah. That's get hands on. >>Yeah. And I was saying, Hey, I came from the old days though, you get to stand stuff up and you hugged onto the assets. Cause you didn't wanna kill the cause you spent all this money and, and he's like, yeah, with cloud, you can shut it down. If you do a project that's not working and you get bad data, no one's adopting it or you don't want like it anymore. You shut it down. Just something >>Else. Totally >>Instantly abandoned it. Move onto something new. >>Yeah. With progression. Totally. And it, the, the blast radius of, um, decisions is just way reduced, gone. Like we talk a lot about like trying to, you know, in the old world trying to find the resources and get the funding. And it's like, right. I wanna try out this kind of random idea that could be a big deal for the organization. I need 50 million in a new data center. Like you're not gonna get anywhere. You, >>You do a proposal working backwards, document >>Kinds, all that, that sort of stuff got hoops. So, so all of that is gone, but we sometimes forget that a big part of that is just the, the prototyping and the experimentation and the limited blast radius in terms of cost. And honestly, the most important thing is time just being able to jump in there, get fingers on keyboards, just try this stuff out. And that's why at AWS, we have part of the reason we have so many services because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so, as your ideas developed, you may want to jump from, you know, data that you have, that's already in a database to doing realtime data. Yeah. And then you can just, you have the tools there. And when you want to get into real time data, you don't just have kineses, but you have real time analytics and you can run SQL again, that data is like the, the capabilities and the breadth, like really matter when it comes to prototyping and, and >>That's culture too. That's the culture piece, because what was once a dysfunctional behavior, I'm gonna go off the reservation and try something behind my boss's back or cause now as a side hustle or fun project. Yeah. So for fun, you can just code something. Yeah, >>Totally. I remember my first Haddo project, I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for like another month. And I installed her DUP on them and like, got them going. It's like, that just seems crazy to me now that I, I had to go and convince anybody not to turn these service off, but what >>It was like for that, when you came up with elastic map produce, because you said this is too hard, we gotta make it >>Easier. Basically. Yes. <laugh> I was installing Haddo version, you know, beta nor 0.9 or whatever it was. It's like, this is really hard. This is really hard. >>We simpler. All right. Good stuff. I love the, the walk down memory lane and also your advice. Great stuff. I think culture's huge. I think. And that's why I like Adam's keynote to reinvent Adam. Lesky talk about path minds and trail blazers because that's a blast radius impact. Mm-hmm <affirmative> when you can actually have innovation organically just come from anywhere. Yeah, that's totally cool. Totally. Let's get into the products. Serverless has been hot mm-hmm <affirmative> uh, we hear a lot about EKS is hot. Uh, containers are booming. Kubernetes is getting adopted. There's still a lot of work to do there. Lambda cloud native developers are booming, serverless Lambda. How does that impact the analytics piece? Can you share the hot, um, products around how that translates? Sure, absolutely. Yeah, the SageMaker >>Yeah, I think it's a, if you look at kind of the evolution and what customers are asking for, they're not, you know, they don't just want low cost. They don't just want this broad set of services. They don't just want, you know, those services to have deep capabilities. They want those services to have as lower operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, lot of services about getting up and running and experimenting and prototyping and turning things off and turn turning them on and turning them off. And like, that's all great. But actually the, you really only most projects start something once and then stop something once. And maybe there's an hour in between, or maybe there's a year, but the real expense in terms of time and, and complexity is sometimes in that running cost. Yeah. And so, um, we've heard very loudly and clearly from customers that they want, that, that running cost is just undifferentiated to them and they wanna spend more time on their work and in analytics that is, you know, slicing the data, pivoting the data, combining the data, labeling the data, training their models, uh, you know, running inference against their models, uh, and less time doing the operational pieces. >>So is that why the servers focus is there? >>Yeah, absolutely. It, it dramatically reduces the skill required to run these, uh, workloads of any scale. And it dramatically reduces the UND differentiated, heavy lifting, cuz you get to focus more of the time that you would've spent on the operation on the actual work that you wanna get done. And so if you look at something just like Redshift serverless that we launched a reinvent, you know, there's a kind of a, we have a lot of customers that want to run like a, uh, the cluster and they want to get into the, the weeds where there is benefit. We have a lot of customers that say, you know, I there's no benefit for me though. I just wanna do the analytics. So you run the operational piece, you're the experts we've run. You know, we run 60 million instant startups every single day. Like we do this a lot. Exactly. We understand the operation. I >>Want the answers come on. So >>Just give the answers or just let, give me the notebook or just give the inference prediction. So today for example, we announced, um, you know, serverless inference. So now once you've trained your machine learning model, just, uh, run a few, uh, lines of code or you just click a few buttons and then yeah, you got an inference endpoint that you do not have to manage. And whether you're doing one query against that endpoint, you know, per hour or you're doing, you know, 10 million, but we'll just scale it on the back end. You >>Know, I know we got not a lot of time left, but I want, wanna get your reaction to this. One of the things about the data lakes, not being data swamps has been from what I've been reporting and hearing from customers is that they want to retrain their machine learning algorithm. They want, they need that data. They need the, the, the realtime data and they need the time series data, even though the time has passed, they gotta store in the data lake mm-hmm <affirmative>. So now the data lakes main function is being reusing the data to actually retrain. Yeah, >>That's >>Right. It worked properly. So a lot of, lot of postmortems turn into actually business improvements to make the machine learning smarter, faster. You see that same way. Do you see it the same way? Yeah, >>I think it's, I think it's really interesting. No, I think it's really interesting because you know, we talk it's, it's convenient to kind of think of analytics as a very clear progression from like point a point B, but really it's, you are navigating terrain for which you do not have a map and you need a lot of help to navigate that terrain. Yeah. And so, you know, being, having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed, and we added PII detection today, you know, something you can do automatically, uh, to be able to use their, uh, any unstructured data run queries against that unstructured data. So today we added, you know, um, text extract queries. So you can just say, well, uh, you can scan a badge for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. So there's a often a, it's more like a branch than it is just a, a normal, uh, a to B path, a linear path. Uh, and that includes loops backwards. And sometimes you gotta get the results and use those to make improvements further upstream. And sometimes you've gotta use those. And when you're downstream, you'll be like, ah, I remember that. And you come back and bring it all together. So awesome. It's um, it's, uh, uh, it's a wonderful >>Work for sure. Dr. Matt wood here in the queue. Got just take the last word and give the update. Why you're here. What's the big news happening that you're announcing here at summit in San Francisco, California, and update on the, the business analytics >>Group? Yeah, I think, you know, one of the, we did a lot of announcements in the keynote, uh, encouraged everyone to take a look at that. Uh, this morning was Swami. Uh, one of the ones I'm most excited about, uh, is the opportunity to be able to take, uh, dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, uh, all over the place. However, what we've heard from customers is like, yes, I want those analytics. I want their visualization. I want it to be up to date, but you know, I don't actually want to have to go my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced, uh, one click public embedding for quick side dashboards. So today you can literally, as easily as embedding a YouTube video, you can take a dashboard that you've built inside, quick site cut and paste the HTML, paste it into your application and that's it. That's all you have to do. It takes seconds and >>It gets updated in real time. >>Updated in real time, it's interactive. You can do everything that you would normally do. You can brand it like this is there's no power by quick site button or anything like that. You can change the colors, make it fit in perfectly with your, with your applications. So that's sitting incredibly powerful way of being able to take a, uh, an analytics capability that today sits inside its own little fiefdom and put it just everywhere. It's, uh, very transformative. >>Awesome. And the, the business is going well. You got the serverless and your tailwind for you there. Good stuff, Dr. Matt with thank you. Coming on the cube >>Anytime. Thank >>You. Okay. This is the cubes cover of eight summit, 2022 in San Francisco, California. I'm John host cube. Stay with us with more coverage of day two after this short break.

>>Live from Stanford university on your host. Lisa Martin. My next guest joins me with many I, our corporate vice president at Microsoft, Rick Minnie. It's great to have you on the program. Thank you for having me. Tell me a little bit about your background. So you run Microsoft advertising, engineering organizations. You also manage a multi-billion dollar marketplace globally. Yes. Big responsibilities. >>A little bit >>About you and your role at Microsoft. >>So basically online advertising, you know, funds a lot of the consumer services like search, you know, feeds. And so I run all of the online advertising pieces. And so my team is a combination of machine learning in theory, software engineers, online services. So you think of you think of what needs to happen for running an online advertising ecosystem? That's billions of dollars. I have all these people on my team when I get to work with these fantastic people. So that's my >>Roles. We have a really diverse team. >>Yes. My background itself is in AI. So my PhD was in language modeling and natural language processing. That's how I got into the space. And then I did, you know, machine learning. Then I did some auctions and then I'd, you know, I basically have touched almost all pieces of the puzzle. So from, I appreciate what's required to run a business the size. And so from that perspective, you know, yeah, it is a lot of diverse people, but at the same time, I feel like I know what they do >>Right then interdisciplinary collaboration must be incredibly important and >>Powerful. It is. I mean, for machine learning engineer or machine learning scientists to be successful, when you're running a production system, they have to really appreciate what constraints are there, you know, required online. So you have to look at how much CPU you use, how much memory you need, how fast can your model inference run with your model. And so they have to work very closely with the soft, soft engineering field. But at the same time, the software engineering guys need to know that their job is not to constrain the machine learning scientists. So, you know, as the models get larger, they have to get more creative. Right. And if that balance is right, then you get a really ambitious product. If that balance is not right, then you end up with a very small micro micro system. And so my job is to really make sure that the team is really ambitious in their thinking, not always liking, pushing the borders of what can be done. >>I like that pushing the borders of what can be done. You know, we, we often, when we talk about roles in, in stammered technology, we've talked about the hard skills, but the soft skills you've mentioned creativity. I always think creativity and curiosity are two soft skills that are really important in data science and AI. Talk to me about what your thoughts are. There >>Definitely creativity, because a lot of the problems that you, you know, when you're in school, the problems you face are very theoretical problems. And when you go into the industry and you realize that you need to solve a problem using the theory you learned, then you have to either start making different kinds of assumptions or realize that some assumptions just can be made because life is messy and online. You know, users are messy. They don't all interact with your system the same way. So you get creative in what can be solved. And then what needs to be controlled and folks who can't figure that piece out, they try to solve everything using machine learning, and they become a perfectionist, but nothing ever gets done then. So you need this balance and, and creativity plays a huge role in that space. And collaboration is you're always working with a diverse group of people. So explaining the problem space to someone who's selling your product, say someone is, you know, you build this automated bidding engine and they have to take this full mouth full and sell it to a customer. You've got to give them the terminology to use, tell, explain to them what are the benefits if somebody uses that. So I, I feel people who can empathize with the fact that this has to be explained, do a lot better when they're working in a product system, you know, bringing machine learning to a production system. >>Right. There's a lot of enablement >>There. Yes, exactly. Yeah. Yeah. >>Were you always interested in, in stem and engineering and AIS from when you were small? >>Somewhat? I mean, I've been, I got to my college degree. I was very certain by that point I wanted to be an engineer and my path to AI was kind of weird because I didn't really want to do computer science. So I ended up doing electrical engineering, but in my last year I did a project on speech recognition and I got introduced to computer programming. That was my first introduction to computer programming at the end of it, I knew I was going to work in the space. And so I came to the U S with less than three or four months of a computer engineering background. You know, I barely knew how to code. I had done some statistics, but not nearly enough to be in machine learning. And, but I landed in a good place. And I came to be in Boston university and I landed in a great lab. And I learned everything on my feet in that lab. I do feel like from that point onwards, I have always been interested and I'm never satisfied with just being interested in what's hot right now. I really want to know what can be solved later in the future. So that combination, I think, you know, really keeps me always learning, growing, and I'm never happy with just what's being done. >>Right? Yeah. We here, we've been hearing a lot about that today at weds. Just the tremendous opportunities that are here, the opportunities for data science, for good drones, for good data science and AI in healthcare and in public transportation. For example, you've been involved in with winds from the beginning. So you've gotten to see this small movement grow into this global really kind of is a >>Phenomenon. It is, >>It's a movement. Yes. You talk to me about your involvement with winds from the beginning and some of the things that you're helping them do. And now, >>So I, I first met Karen and marble initially when I was trying to get students from ICME to apply for roles in Microsoft. I really thought they had the right mix of applied and research mindset and the skill sets that were coming out of ICME rock solid in their math and theoretical foundations. So that's how I got to know them. And then they were just thinking about bids at that point in time. And so I said, you know, how can I help? And so I think I've been a keynote speaker, Pam list run a workshop. And then I got involved with the woods high school volunteer effort. And I'd say, that's the most rewarding piece of my visit involvement. And so I've been with them every year. I never Ms. Woods. I'm always here. And I think it is, you know, Grace Hopper was the technology conference for women and, and it's, it's, it's an awesome conference. I mean, it's amazing to sit next to so many women engineers, but data science was a part of it, but not a critical part of it. And so having this conference, that's completely focused on data science and making it accessible. The talks are accessible, making it more personable to, to all the invitees here. I think it creates a great community. So for me, I think it's, I hope they can run this and grow this for >>Yeah. Over 200 online events this year in 60 countries, they're aiming to reach a hundred thousand people annually. It's, it's grown dramatically in a short time period. Yes, >>Absolutely. Yeah. It hasn't been that long. It hasn't been that long and every year they add something new to the table. So for this year, I mean last year I thought the high schoolers, they started bringing in the high schoolers and this year again, I thought the high school. >>Yeah, >>Exactly. And I think the mix of getting data science from across a diversity, because a lot of the conferences are very focused. Like, you know, they, they will be the focused on healthcare and data science or pure AI or pure machine learning. This conference has a mix of a lot of different elements. And so attendees get to see how it's something is being used in healthcare and how something is being used in recommendations. And I think that diversity is really valuable. >>Oh, it's hugely valuable that the thought diversity is this is probably the conference where I discovered what thought diversity was if only a few years ago and the power and the opportunities that it can unlock for people everywhere for businesses in any industry. Yes. >>I want to kind of play off one of the things you said before, you know, data science for good, the, the incredible part of data sciences, you can do good wherever you are with data science. So take online advertising, you know, we build products for all advertisers, but we quickly figured out that are really large advertisers. They have their own data science teams and they are optimizing and, you know, creating new ads and making sure the best ads are serving at all times. They have figured out, you know, they have machine learning pipelines, so they are really doing their best already. But then there's this whole tale of small advertisers who just don't have the wherewithal or the knowledge to do any of that. Now, can you make data, use data science and your machine learning models and make it accessible for that long table? Pretty much any product you build, you will have the symptom of heavy users and then the tail users. And can you create an experience that is as valuable for those tailored users as it is for the heavy users. So data science for good exists, whatever problem you're solving, basically, >>That's nice to hear. And so you're going to be participating in some of the closing remarks today. What are some of the pearls of wisdom that you're going to enlighten the audience with today? >>Well, I mean the first thing I, to tell this audiences that they need to participate, you know, in whatever they shaped form, they need to participate in this movement of getting more women into stem and into data science. And my reasoning is, you know, I joined the lab and my professor was a woman and she was very strong scientists, very strong engineer. And that one story was enough to convince me that I belong. And if you can imagine that we create thousands of these stories, this is how you create that feeling of inclusion, where people feel like they belong. Yeah. Look, just look at those other 50 people here, those other a hundred stories here. This is how you create that movement. And so the first thing I want the audience to do is participate, come back, volunteer, you know, submit papers for keynote speeches, you know, be a part of this movement. >>So that's one. And then the second is I want them to be ambitious. So I don't want them to just read a book and apply the theory. I really want them to think about what problem are they solving and could they have solved it in the, in the scale manner that it can be solved. So I'll give a few examples and problems and I'll throw them out there as well. So for instance, experimentation, one of the big breakthroughs that happened in a lot of these large companies in data science is experimentation. You can AB experiment pretty much anything. You know, we can, Google has this famous paper where they talk about how they experimented with thousands of different blues just to get the right blue. And so experimentation has been evolving and data scientists are figuring out that if they can figure out interactions between experiments, you can actually run multiple experiments on the same user. >>So at any given time, you may be subject to four or five different experiments. Now, can we now scale that to infinity so that you can actually run as many experiments as you want questions like these, you shouldn't stop with just saying, oh, I know how AB experimentation works. The question you should be asking is how many such experiments can I run? How do I scale the system? As one of the keynote speakers initially talked about the unasked questions. And I think that's what I want to leave this audience with that don't stop at, you know, answering the questions that you're asked or solving the problems. You know, of you think about the problems you haven't solved your blind spots, you know, those blind spots and that I think I want ambitious data scientists. And so that's the message I want to give this audience. >>I can feel your energy when you say that. And you're involved with, with, with Stanford program for middle school and high school girls. If we look at the data and we see, there's still only about a quarter of stem positions are filled by females, what do you see? Do you see an inspiring group of young women in those middle school and high school girls that, that you see we're, we're on trend to start increasing that percentage. >>So I had a high schooler who just went, you know, she, she, she just, she's at UCLA now shout out to her and she, but she just went through high school. And what I realized is it's the same problem of not having enough stories around you, not having enough people around you that are all echoing the sentiment for, Hey, I love math. A lot of girls just don't talk about us. Yeah. And so I think the reason I want to start in middle school and high school is I think the momentum needs to start there. Yes. Because they get to college. And actually you heard my story. I didn't know any programming until I came here and I had already finished my four years of college and I still figured it out. Right. But a lot of women lose confidence to change fields after four years of college. >>Yes. And so if you don't catch them in early and you're catching them late, then you need to give them this boost of confidence or give them that ramp up time to learn, to figure out, like, I have a few people who are joining me from pure math nowadays. And these kids, these kids come in and within six months they're off and running. So, you know, in the interview phase, people might say, oh, they don't have any coding skills. Six months later, if you interview them, they pick up coding skills. Yeah. And so if you can get them started early on, I think, you know, they don't have this crisis of confidence of moving, changing fields. That's why I feel, and I don't think we are there yet, to be honest, I don't think yet. I think >>You still think there are plenty of girls being told. Now you can't do computer science. No, you can't do physics. No, you can't do math. >>Actually. They are denying it to themselves in many cases because they say, Hey, I go to physics class and there are two boys, two girls out of 50 boys. And I don't think girls are in, you know, you get the stereotype that maybe girls are not interested in physics. And it's not about, Hey, as a girl, I'm doing really well in physics. Maybe I should take this as my career. So I do feel we need to create more resounding stories in the area. And then I think we'll drum up that momentum. That's >>A great point. More stories, more and names to success here so that she can be what she can see exactly what many it's been great having you on the program. Thank you for joining me and sharing your background and some of the pearls of wisdom that you're gonna be dropping on the audience shortly today. We appreciate your insights. Thank you. My pleasure. Who Rick, Minnie, I are. I'm Lisa Martin. You're watching the cubes coverage weds 2022. We'll be right back after a short break.

>>Welcome to this exclusive discussion. IBM, the next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond. My name is Dave Volante from the Cuban today, we're going to take a deep dive into some of the most important trends impacting the life sciences industry in the next 60 minutes. Yeah, of course. We're going to hear how IBM is utilizing Watson and some really important in life impacting ways, but we'll also bring in real world perspectives from industry and the independent analyst view to better understand how technology and data are changing the nature of precision medicine. Now, the pandemic has created a new reality for everyone, but especially for life sciences companies, one where digital transformation is no longer an option, but a necessity. Now the upside is the events of the past 22 months have presented an accelerated opportunity for innovation technology and real world data are coming together and being applied to support life science, industry trends and improve drug discovery, clinical development, and treatment commercialization throughout the product life cycle cycle. Now I'd like to introduce our esteemed panel. Let me first introduce Lorraine Marshawn, who is general manager of life sciences at IBM Watson health. Lorraine leads the organization dedicated to improving clinical development research, showing greater treatment value in getting treatments to patients faster with differentiated solutions. Welcome Lorraine. Great to see you. >>Dr. Namita LeMay is the research vice-president of IDC, where she leads the life sciences R and D strategy and technology program, which provides research based advisory and consulting services as well as market analysis. The loan to meta thanks for joining us today. And our third panelist is Greg Cunningham. Who's the director of the RWE center of excellence at Eli Lilly and company. Welcome, Greg, you guys are doing some great work. Thanks for being here. Thanks >>Dave. >>Now today's panelists are very passionate about their work. If you'd like to ask them a question, please add it to the chat box located near the bottom of your screen, and we'll do our best to answer them all at the end of the panel. Let's get started. Okay, Greg, and then Lorraine and meta feel free to chime in after one of the game-changers that you're seeing, which are advancing precision medicine. And how do you see this evolving in 2022 and into the next decade? >>I'll give my answer from a life science research perspective. The game changer I see in advancing precision medicine is moving from doing research using kind of a single gene mutation or kind of a single to look at to doing this research using combinations of genes and the potential that this brings is to bring better drug targets forward, but also get the best product to a patient faster. Um, I can give, uh, an example how I see it playing out in the last decade. Non-oncology real-world evidence. We've seen an evolution in precision medicine as we've built out the patient record. Um, as we've done that, uh, the marketplace has evolved rapidly, uh, with, particularly for electronic medical record data and genomic data. And we were pretty happy to get our hands on electronic medical record data in the early days. And then later the genetic test results were combined with this data and we could do research looking at a single mutation leading to better patient outcomes. But I think where we're going to evolve in 2022 and beyond is with genetic testing, growing and oncology, providing us more data about that patient. More genes to look at, uh, researchers can look at groups of genes to analyze, to look at that complex combination of gene mutations. And I think it'll open the door for things like using artificial intelligence to help researchers plow through the complex number of permutations. When you think about all those genes you can look at in combination, right? Lorraine yes. Data and machine intelligence coming together, anything you would add. >>Yeah. Thank you very much. Well, I think that Greg's response really sets us up nicely, particularly when we think about the ability to utilize real-world data in the farm industry across a number of use cases from discovery to development to commercial, and, you know, in particular, I think with real world data and the comments that Greg just made about clinical EMR data linked with genetic or genomic data, a real area of interest in one that, uh, Watson health in particular is focused on the idea of being able to create a data exchange so that we can bring together claims clinical EMR data, genomics data, increasingly wearables and data directly from patients in order to create a digital health record that we like to call an intelligent patient health record that basically gives us the digital equivalent of a real life patient. And these can be used in use cases in randomized controlled clinical trials for synthetic control arms or natural history. They can be used in order to track patients' response to drugs and look at outcomes after they've been on various therapies as, as Greg is speaking to. And so I think that, you know, the promise of data and technology, the AI that we can apply on that is really helping us advance, getting therapies to market faster, with better information, lower sample sizes, and just a much more efficient way to do drug development and to track and monitor outcomes in patients. >>Great. Thank you for that now to meta, when I joined IDC many, many years ago, I really didn't know much about the industry that I was covering, but it's great to see you as a former practitioner now bringing in your views. What do you see as the big game-changers? >>So, um, I would, I would agree with what both Lorraine and Greg said. Um, but one thing that I'd just like to call out is that, you know, everyone's talking about big data, the volume of data is growing. It's growing exponentially actually about, I think 30% of data that exists today is healthcare data. And it's growing at a rate of 36%. That's huge, but then it's not just about the big, it's also about the broad, I think, um, you know, I think great points that, uh, Lorraine and Greg brought out that it's, it's not just specifically genomic data, it's multi omic data. And it's also about things like medical history, social determinants of health, behavioral data. Um, and why, because when you're talking about precision medicine and we know that we moved away from the, the terminology of personalized to position, because you want to talk about disease stratification and you can, it's really about convergence. >>Um, if you look at a recent JAMA paper in 2021, only 1% of EHS actually included genomic data. So you really need to have that ability to look at data holistically and IDC prediction is seeing that investments in AI to fuel in silico, silicone drug discovery will double by 20, 24, but how are you actually going to integrate all the different types of data? Just look at, for example, diabetes, you're on type two diabetes, 40 to 70% of it is genetically inherited and you have over 500 different, uh, genetic low side, which could be involved in playing into causing diabetes. So the earlier strategy, when you are looking at, you know, genetic risk scoring was really single trait. Now it's transitioning to multi rate. And when you say multi trade, you really need to get that integrated view that converging for you to, to be able to drive a precision medicine strategy. So to me, it's a very interesting contrast on one side, you're really trying to make it specific and focused towards an individual. And on the other side, you really have to go wider and bigger as well. >>Uh, great. I mean, the technology is enabling that convergence and the conditions are almost mandating it. Let's talk about some more about data that the data exchange and building an intelligent health record, as it relates to precision medicine, how will the interoperability of real-world data, you know, create that more cohesive picture for the, for the patient maybe Greg, you want to start, or anybody else wants to chime in? >>I think, um, the, the exciting thing from, from my perspective is the potential to gain access to data. You may be weren't aware of an exchange in implies that, uh, some kind of cataloging, so I can see, uh, maybe things that might, I just had no idea and, uh, bringing my own data and maybe linking data. These are concepts that I think are starting to take off in our field, but it, it really opens up those avenues to when you, you were talking about data, the robustness and richness volume isn't, uh, the only thing is Namita said, I think really getting to a rich high-quality data and, and an exchange offers a far bigger, uh, range for all of us to, to use, to get our work done. >>Yeah. And I think, um, just to chime, chime into that, uh, response from Greg, you know, what we hear increasingly, and it's pretty pervasive across the industry right now, because this ability to create an exchange or the intelligent, uh, patient health record, these are new ideas, you know, they're still rather nascent and it always is the operating model. Uh, that, that is the, uh, the difficult challenge here. And certainly that is the case. So we do have data in various silos. Uh, they're in patient claims, they're in electronic medical records, they might be in labs, images, genetic files on your smartphone. And so one of the challenges with this interoperability is being able to tap into these various sources of data, trying to identify quality data, as Greg has said, and the meta is underscoring as well. Uh, we've gotta be able to get to the depth of data that's really meaningful to us, but then we have to have technology that allows us to pull this data together. >>First of all, it has to be de-identified because of security and patient related needs. And then we've gotta be able to link it so that you can create that likeness in terms of the record, it has to be what we call cleaned or curated so that you get the noise and all the missing this out of it, that's a big step. And then it needs to be enriched, which means that the various components that are going to be meaningful, you know, again, are brought together so that you can create that cohort of patients, that individual patient record that now is useful in so many instances across farm, again, from development, all the way through commercial. So the idea of this exchange is to enable that exact process that I just described to have a, a place, a platform where various entities can bring their data in order to have it linked and integrated and cleaned and enriched so that they get something that is a package like a data package that they can actually use. >>And it's easy to plug into their, into their studies or into their use cases. And I think a really important component of this is that it's gotta be a place where various third parties can feel comfortable bringing their data together in order to match it with other third parties. That is a, a real value, uh, that the industry is increasingly saying would be important to them is, is the ability to bring in those third-party data sets and be able to link them and create these, these various data products. So that's really the idea of the data exchange is that you can benefit from accessing data, as Greg mentioned in catalogs that maybe are across these various silos so that you can do the kind of work that you need. And that we take a lot of the hard work out of it. I like to give an example. >>We spoke with one of our clients at one of the large pharma companies. And, uh, I think he expressed it very well. He said, what I'd like to do is have like a complete dataset of lupus. Lupus is an autoimmune condition. And I've just like to have like the quintessential lupus dataset that I can use to run any number of use cases across it. You know, whether it's looking at my phase one trial, whether it's selecting patients and enriching for later stage trials, whether it's understanding patient responses to different therapies as I designed my studies. And so, you know, this idea of adding in therapeutic area indication, specific data sets and being able to create that for the industry in the meta mentioned, being able to do that, for example, in diabetes, that's how pharma clients need to have their needs met is through taking the hard workout, bringing the data together, having it very therapeutically enriched so that they can use it very easily. >>Thank you for that detail and the meta. I mean, you can't do this with humans at scale in technology of all the things that Lorraine was talking about, the enrichment, the provenance, the quality, and of course, it's got to be governed. You've got to protect the privacy privacy humans just can't do all that at massive scale. Can it really tech that's where technology comes in? Doesn't it and automation. >>Absolutely. >>I, couldn't more, I think the biggest, you know, whether you talk about precision medicine or you talk about decentralized trials, I think there's been a lot of hype around these terms, but what is really important to remember is technology is the game changer and bringing all that data together is really going to be the key enabler. So multimodal data integration, looking at things like security or federated learning, or also when you're talking about leveraging AI, you're not talking about things like bias or other aspects around that are, are critical components that need to be addressed. I think the industry is, uh, it's partly, still trying to figure out the right use cases. So it's one part is getting together the data, but also getting together the right data. Um, I think data interoperability is going to be the absolute game changer for enabling this. Uh, but yes, um, absolutely. I can, I can really couldn't agree more with what Lorraine just said, that it's bringing all those different aspects of data together to really drive that precision medicine strategy. >>Excellent. Hey Greg, let's talk about protocols decentralized clinical trials. You know, they're not new to life silences, but, but the adoption of DCTs is of course sped up due to the pandemic we've had to make trade-offs obviously, and the risk is clearly worth it, but you're going to continue to be a primary approach as we enter 2022. What are the opportunities that you see to improve? How DCTs are designed and executed? >>I see a couple opportunities to improve in this area. The first is, uh, back to technology. The infrastructure around clinical trials has, has evolved over the years. Uh, but now you're talking about moving away from kind of site focus to the patient focus. Uh, so with that, you have to build out a new set of tools that would help. So for example, one would be novel trial, recruitment, and screening, you know, how do you, how do you find patients and how do you screen them to see if are they, are they really a fit for, for this protocol? Another example, uh, very important documents that we have to get is, uh, you know, the e-consent that someone's says, yes, I'm, well, I understand this study and I'm willing to do it, have to do that in a more remote way than, than we've done in the past. >>Um, the exciting area, I think, is the use of, uh, eco, uh, E-Pro where we capture data from the patient using apps, devices, sensors. And I think all of these capabilities will bring a new way of, of getting data faster, uh, in, in this kind of model. But the exciting thing from, uh, our perspective at Lily is it's going to bring more data about the patient from the patient, not just from the healthcare provider side, it's going to bring real data from these apps, devices and sensors. The second thing I think is using real-world data to identify patients, to also improve protocols. We run scenarios today, looking at what's the impact. If you change a cut point on a, a lab or a biomarker to see how that would affect, uh, potential enrollment of patients. So it, it definitely the real-world data can be used to, to make decisions, you know, how you improve these protocols. >>But the thing that we've been at the challenge we've been after that this probably offers the biggest is using real-world data to identify patients as we move away from large academic centers that we've used for years as our sites. Um, you can maybe get more patients who are from the rural areas of our countries or not near these large, uh, uh, academic centers. And we think it'll bring a little more diversity to the population, uh, who who's, uh, eligible, but also we have their data, so we can see if they really fit the criteria and the probability they are a fit for the trial is much higher than >>Right. Lorraine. I mean, your clients must be really pushing you to help them improve DCTs what are you seeing in the field? >>Yes, in fact, we just attended the inaugural meeting of the de-central trials research Alliance in, uh, in Boston about two weeks ago where, uh, all of the industry came together, pharma companies, uh, consulting vendors, just everyone who's been in this industry working to help define de-central trials and, um, think through what its potential is. Think through various models in order to enable it, because again, a nascent concept that I think COVID has spurred into action. Um, but it is important to take a look at the definition of DCT. I think there are those entities that describe it as accessing data directly from the patient. I think that is a component of it, but I think it's much broader than that. To me, it's about really looking at workflows and processes of bringing data in from various remote locations and enabling the whole ecosystem to work much more effectively along the data continuum. >>So a DCT is all around being able to make a site more effective, whether it's being able to administer a tele visit or the way that they're getting data into the electronic data captures. So I think we have to take a look at the, the workflows and the operating models for enabling de-central trials and a lot of what we're doing with our own technology. Greg mentioned the idea of electronic consent of being able to do electronic patient reported outcomes, other collection of data directly from the patient wearables tele-health. So these are all data acquisition, methodologies, and technologies that, that we are enabling in order to get the best of the data into the electronic data capture system. So edit can be put together and processed and submitted to the FDA for regulatory use for clinical trial type submission. So we're working on that. I think the other thing that's happening is the ability to be much more flexible and be able to have more cloud-based storage allows you to be much more inter-operable to allow API APIs in order to bring in the various types of data. >>So we're really looking at technology that can make us much more fluid and flexible and accommodating to all the ways that people live and work and manage their health, because we have to reflect that in the way we collect those data types. So that's a lot of what we're, what we're focused on. And in talking with our clients, we spend also a lot of time trying to understand along the, let's say de-central clinical trials continuum, you know, w where are they? And I know Namita is going to talk a little bit about research that they've done in terms of that adoption curve, but because COVID sort of forced us into being able to collect data in more remote fashion in order to allow some of these clinical trials to continue during COVID when a lot of them had to stop. What we want to make sure is that we understand and can codify some of those best practices and that we can help our clients enable that because the worst thing that would happen would be to have made some of that progress in that direction. >>But then when COVID is over to go back to the old ways of doing things and not bring some of those best practices forward, and we actually hear from some of our clients in the pharma industry, that they worry about that as well, because we don't yet have a system for operationalizing a de-central trial. And so we really have to think about the protocol it's designed, the indication, the types of patients, what makes sense to decentralize, what makes sense to still continue to collect data in a more traditional fashion. So we're spending a lot of time advising and consulting with our patients, as well as, I mean, with our clients, as well as CRS, um, on what the best model is in terms of their, their portfolio of studies. And I think that's a really important aspect of trying to accelerate the adoption is making sure that what we're doing is fit for purpose, just because you can use technology doesn't mean you should, it really still does require human beings to think about the problem and solve them in a very practical way. >>Great, thank you for that. Lorraine. I want to pick up on some things that Lorraine was just saying. And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, you had a prediction or IDC, did I presume your fingerprints were on it? Uh, that by 20 25, 70 5% of trials will be patient-centric decentralized clinical trials, 90% will be hybrid. So maybe you could help us understand that relationship and what types of innovations are going to be needed to support that evolution of DCT. >>Thanks, Dave. Yeah. Um, you know, sorry, I, I certainly believe that, uh, you know, uh, Lorraine was pointing out of bringing up a very important point. It's about being able to continue what you have learned in over the past two years, I feel this, you know, it was not really a digital revolution. It was an attitude. The revolution that this industry underwent, um, technology existed just as clinical trials exist as drugs exist, but there was a proof of concept that technology works that this model is working. So I think that what, for example, telehealth, um, did for, for healthcare, you know, transition from, from care, anywhere care, anytime, anywhere, and even becoming predictive. That's what the decentralized clinical trials model is doing for clinical trials today. Great points again, that you have to really look at where it's being applied. You just can't randomly apply it across clinical trials. >>And this is where the industry is maturing the complexity. Um, you know, some people think decentralized trials are very simple. You just go and implement these centralized clinical trials, but it's not that simple as it it's being able to define, which are the right technologies for that specific, um, therapeutic area for that specific phase of the study. It's being also a very important point is bringing in the patient's voice into the process. Hey, I had my first telehealth visit sometime last year and I was absolutely thrilled about it. I said, no time wasted. I mean, everything's done in half an hour, but not all patients want that. Some want to consider going back and you, again, need to customize your de-centralized trials model to, to the, to the type of patient population, the demographics that you're dealing with. So there are multiple factors. Um, also stepping back, you know, Lorraine mentioned they're consulting with, uh, with their clients, advising them. >>And I think a lot of, um, a lot of companies are still evolving in their maturity in DCTs though. There's a lot of boys about it. Not everyone is very mature in it. So it's, I think it, one thing everyone's kind of agreeing with is yes, we want to do it, but it's really about how do we go about it? How do we make this a flexible and scalable modern model? How do we integrate the patient's voice into the process? What are the KPIs that we define the key performance indicators that we define? Do we have a playbook to implement this model to make it a scalable model? And, you know, finally, I think what organizations really need to look at is kind of developing a de-centralized mature maturity scoring model, so that I assess where I am today and use that playbook to define, how am I going to move down the line to me reach the next level of maturity. Those were some of my thoughts. Right? >>Excellent. And now remember you, if you have any questions, use the chat box below to submit those questions. We have some questions coming in from the audience. >>At one point to that, I think one common thread between the earlier discussion around precision medicine and around decentralized trials really is data interoperability. It is going to be a big game changer to, to enable both of these pieces. Sorry. Thanks, Dave. >>Yeah. Thank you. Yeah. So again, put your questions in the chat box. I'm actually going to go to one of the questions from the audience. I get some other questions as well, but when you think about all the new data types that are coming in from social media, omics wearables. So the question is with greater access to these new types of data, what trends are you seeing from pharma device as far as developing capabilities to effectively manage and analyze these novel data types? Is there anything that you guys are seeing, um, that you can share in terms of best practice or advice >>I'll offer up? One thing, I think the interoperability isn't quite there today. So, so what's that mean you can take some of those data sources. You mentioned, uh, some Omix data with, uh, some health claims data and it's the, we spend too much time and in our space putting data to gather the behind the scenes, I think the stat is 80% of the time is assembling the data 20% analyzing. And we've had conversations here at Lilly about how do we get to 80% of the time is doing analysis. And it really requires us to think, take a step back and think about when you create a, uh, a health record, you really have to be, have the same plugins so that, you know, data can be put together very easily, like Lorraine mentioned earlier. And that comes back to investing in as an industry and standards so that, you know, you have some of data standard, we all can agree upon. And then those plugs get a lot easier and we can spend our time figuring out how to make, uh, people's lives better with healthcare analysis versus putting data together, which is not a lot of fun behind the scenes. >>Other thoughts on, um, on, on how to take advantage of sort of novel data coming from things like devices in the nose that you guys are seeing. >>I could jump in there on your end. Did you want to go ahead? Okay. So, uh, I mean, I think there's huge value that's being seen, uh, in leveraging those multiple data types. I think one area you're seeing is the growth of prescription digital therapeutics and, um, using those to support, uh, you know, things like behavioral health issues and a lot of other critical conditions it's really taking you again, it is interlinking real-world data cause it's really taking you to the patient's home. Um, and it's, it's, there's a lot of patients in the city out here cause you can really monitor the patient real-time um, without the patient having coming, you know, coming and doing a site visit once in say four weeks or six weeks. So, um, I, and, uh, for example, uh, suicidal behavior and just to take an example, if you can predict well in advance, based on those behavioral parameters, that this is likely to trigger that, uh, the value of it is enormous. Um, again, I think, uh, Greg made a valid point about the industry still trying to deal with resolving the data interoperability issue. And there are so many players that are coming in the industry right now. There are really few that have the maturity and the capability to address these challenges and provide intelligence solutions. >>Yeah. Maybe I'll just, uh, go ahead and, uh, and chime into Nikita's last comment there. I think that's what we're seeing as well. And it's very common, you know, from an innovation standpoint that you have, uh, a nascent industry or a nascent innovation sort of situation that we have right now where it's very fragmented. You have a lot of small players, you have some larger entrenched players that have the capability, um, to help to solve the interoperability challenge, the standards challenge. I mean, I think IBM Watson health is certainly one of the entities that has that ability and is taking a stand in the industry, uh, in order to, to help lead in that way. Others are too. And, uh, but with, with all of the small companies that are trying to find interesting and creative ways to gather that data, it does create a very fragmented, uh, type of environment and ecosystem that we're in. >>And I think as we mature, as we do come forward with the KPIs, the operating models, um, because you know, the devil's in the detail in terms of the operating models, it's really exciting to talk these trends and think about the future state. But as Greg pointed out, if you're spending 80% of your time just under the hood, you know, trying to get the engine, all the spark plugs to line up, um, that's, that's just hard grunt work that has to be done. So I think that's where we need to be focused. And I think bringing all the data in from these disparate tools, you know, that's fine, we need, uh, a platform or the API APIs that can enable that. But I think as we, as we progress, we'll see more consolidation, uh, more standards coming into play, solving the interoperability types of challenges. >>And, um, so I think that's where we should, we should focus on what it's going to take and in three years to really codify this and make it, so it's a, it's a well hum humming machine. And, you know, I do know having also been in pharma that, uh, there's a very pilot oriented approach to this thing, which I think is really healthy. I think large pharma companies tend to place a lot of bets with different programs on different tools and technologies, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. And I think that's good. I think that's kind of part of the process of figuring out what is going to work and, and helping us when we get to that point of consolidating our model and the technologies going forward. So I think all of the efforts today are definitely driving us to something that feels much more codified in the next three to five years. >>Excellent. We have another question from the audience it's sort of related to the theme of this discussion, given the FDA's recent guidance on using claims and electronic health records, data to support regulatory decision-making what advancements do you think we can expect with regards to regulatory use of real-world data in the coming years? It's kind of a two-parter so maybe you guys can collaborate on this one. What role that, and then what role do you think industry plays in influencing innovation within the regulatory space? >>All right. Well, it looks like you've stumped the panel there. Uh, Dave, >>It's okay to take some time to think about it, right? You want me to repeat it? You guys, >>I, you know, I I'm sure that the group is going to chime into this. I, so the FDA has issued a guidance. Um, it's just, it's, it's exactly that the FDA issues guidances and says that, you know, it's aware and supportive of the fact that we need to be using real-world data. We need to create the interoperability, the standards, the ways to make sure that we can include it in regulatory submissions and the like, um, and, and I sort of think about it akin to the critical path initiative, probably, I don't know, 10 or 12 years ago in pharma, uh, when the FDA also embrace this idea of the critical path and being able to allow more in silico modeling of clinical trial, design and development. And it really took the industry a good 10 years, um, you know, before they were able to actually adopt and apply and take that sort of guidance or openness from the FDA and actually apply it in a way that started to influence the way clinical trials were designed or the in silico modeling. >>So I think the second part of the question is really important because while I think the FDA is saying, yes, we recognize it's important. Uh, we want to be able to encourage and support it. You know, when you look for example, at synthetic control arms, right? The use of real-world data in regulatory submissions over the last five or six years, all of the use cases have been in oncology. I think there've been about maybe somewhere between eight to 10 submissions. And I think only one actually was a successful submission, uh, in all those situations, the real-world data arm of that oncology trial that synthetic control arm was actually rejected by the FDA because of lack of completeness or, you know, equalness in terms of the data. So the FDA is not going to tell us how to do this. So I think the second part of the question, which is what's the role of industry, it's absolutely on industry in order to figure out exactly what we're talking about, how do we figure out the interoperability, how do we apply the standards? >>How do we ensure good quality data? How do we enrich it and create the cohort that is going to be equivalent to the patient in the real world, uh, in the end that would otherwise be in the clinical trial and how do we create something that the FDA can agree with? And we'll certainly we'll want to work with the FDA in order to figure out this model. And I think companies are already doing that, but I think that the onus is going to be on industry in order to figure out how you actually operationalize this and make it real. >>Excellent. Thank you. Um, question on what's the most common misconception that clinical research stakeholders with sites or participants, et cetera might have about DCTs? >>Um, I could jump in there. Right. So, sure. So, um, I think in terms of misconceptions, um, I think the communist misconceptions that sites are going away forever, which I do not think is really happening today. Then the second, second part of it is that, um, I think also the perspective that patients are potentially neglected because they're moving away. So we'll pay when I, when I, what I mean by that neglected, perhaps it was not the appropriate term, but the fact that, uh, will patients will, will, will patient engagement continue, will retention be strong since the patients are not interacting in person with the investigator quite as much. Um, so site retention and patient retention or engagement from both perspectives, I think remains a concern. Um, but actually if you look at, uh, look at, uh, assessments that have been done, I think patients are more than happy. >>Majority of the patients have been really happy about, about the new model. And in fact, sites are, seem to increase, have increased investments in technology by 50% to support this kind of a model. So, and the last thing is that, you know, decentralized trials is a great model and it can be applied to every possible clinical trial. And in another couple of weeks, the whole industry will be implementing only decentralized trials. I think we are far away from that. It's just not something that you would implement across every trial. And we discussed that already. So you have to find the right use cases for that. So I think those were some of the key misconceptions I'd say in the industry right now. Yeah. >>Yeah. And I would add that the misconception I hear the most about is, uh, the, the similar to what Namita said about the sites and healthcare professionals, not being involved to the level that they are today. Uh, when I mentioned earlier in our conversation about being excited about capturing more data, uh, from the patient that was always in context of, in addition to, you know, healthcare professional opinion, because I think both of them bring that enrichment and a broader perspective of that patient experience, whatever disease they're faced with. So I, I think some people think is just an all internet trial with just someone, uh, putting out there their own perspective. And, and it's, it's a combination of both to, to deliver a robust data set. >>Yeah. Maybe I'll just comment on, it reminds me of probably 10 or 15 years ago, maybe even more when, um, really remote monitoring was enabled, right? So you didn't have to have the study coordinator traveled to the investigative site in order to check the temperature of the freezer and make sure that patient records were being completed appropriately because they could have a remote visit and they could, they could send the data in a via electronic data and do the monitoring visit, you know, in real time, just the way we're having this kind of communication here. And there was just so much fear that you were going to replace or supplant the personal relationship between the sites between the study coordinators that you were going to, you know, have to supplant the role of the monitor, which was always a very important role in clinical trials. >>And I think people that really want to do embrace the technology and the advantages that it provided quickly saw that what it allowed was the monitor to do higher value work, you know, instead of going in and checking the temperature on a freezer, when they did have their visit, they were able to sit and have a quality discussion for example, about how patient recruitment was going or what was coming up in terms of the consent. And so it created a much more high touch, high quality type of interaction between the monitor and the investigative site. And I think we should be looking for the same advantages from DCT. We shouldn't fear it. We shouldn't think that it's going to supplant the site or the investigator or the relationship. It's our job to figure out where the technology fits and clinical sciences always got to be high touch combined with high-tech, but the high touch has to lead. And so getting that balance right? And so that's going to happen here as well. We will figure out other high value work, meaningful work for the site staff to do while they let the technology take care of the lower quality work, if you will, or the lower value work, >>That's not an, or it's an, and, and you're talking about the higher value work. And it, it leads me to something that Greg said earlier about the 80, 20, 80% is assembly. 20% is actually doing the analysis and that's not unique to, to, to life sciences, but, but sort of question is it's an organizational question in terms of how we think about data and how we approach data in the future. So Bamyan historically big data in life sciences in any industry really is required highly centralized and specialized teams to do things that the rain was talking about, the enrichment, the provenance, the data quality, the governance, the PR highly hyper specialized teams to do that. And they serve different constituencies. You know, not necessarily with that, with, with context, they're just kind of data people. Um, so they have responsibility for doing all those things. Greg, for instance, within literally, are you seeing a move to, to, to democratize data access? We've talked about data interoperability, part of that state of sharing, um, that kind of breaks that centralized hold, or is that just too far in the future? It's too risky in this industry? >>Uh, it's actually happening now. Uh, it's a great point. We, we try to classify what people can do. And, uh, the example would be you give someone who's less analytically qualified, uh, give them a dashboard, let them interact with the data, let them better understand, uh, what, what we're seeing out in the real world. Uh, there's a middle user, someone who you could give them, they can do some analysis with the tool. And the nice thing with that is you have some guardrails around that and you keep them in their lane, but it allows them to do some of their work without having to go ask those centralized experts that, that you mentioned their precious resources. And that's the third group is those, uh, highly analytical folks that can, can really deliver, uh, just value beyond. But when they're doing all those other things, uh, it really hinders them from doing what we've been talking about is the high value stuff. So we've, we've kind of split into those. We look at people using data in one of those three lanes and it, and it has helped I think, uh, us better not try to make a one fit solution for, for how we deliver data and analytic tools for people. Right. >>Okay. I mean, DCT hot topic with the, the, the audience here. Another question, um, what capabilities do sponsors and CRS need to develop in-house to pivot toward DCT? >>Should I jump in here? Yeah, I mean, um, I think, you know, when, when we speak about DCTs and when I speak with, uh, folks around in the industry, I, it takes me back to the days of risk-based monitoring. When it was first being implemented, it was a huge organizational change from the conventional monitoring models to centralize monitoring and risk-based monitoring, it needs a mental reset. It needs as Lorraine had pointed out a little while ago, restructuring workflows, re redefining processes. And I think that is one big piece. That is, I think the first piece, when, you know, when you're implementing a new model, I think organizational change management is a big piece of it because you are disturbing existing structures, existing methods. So getting that buy-in across the organization towards the new model, seeing what the value add in it. And where do you personally fit into that story? >>How do your workflows change, or how was your role impacted? I think without that this industry will struggle. So I see organizations, I think, first trying to work on that piece to build that in. And then of course, I also want to step back for the second to the, uh, to the point that you brought out about data democratization. And I think Greg Greg gave an excellent point, uh, input about how it's happening in the industry. But I would also say that the data democratization really empowerment of, of, of the stakeholders also includes the sites, the investigators. So what is the level of access to data that you know, that they have now, and is it, uh, as well as patients? So see increasingly more and more companies trying to provide access to patients finally, it's their data. So why shouldn't they have some insights to it, right. So access to patients and, uh, you know, the 80, 20 part of it. Uh, yes, he's absolutely right that, uh, we want to see that flip from, uh, 20%, um, you know, focusing on, on actually integrating the data 80% of analytics, but the real future will be coming in when actually the 20 and 18 has gone. And you actually have analysts the insights out on a silver platter. That's kind of wishful thinking, some of the industries is getting there in small pieces, but yeah, then that's just why I should, why we share >>Great points. >>And I think that we're, we're there in terms that like, I really appreciate the point around democratizing the data and giving the patient access ownership and control over their own data. I mean, you know, we see the health portals that are now available for patients to view their own records, images, and labs, and claims and EMR. We have blockchain technology, which is really critical here in terms of the patient, being able to pull all of their own data together, you know, in the blockchain and immutable record that they can own and control if they want to use that to transact clinical trial types of opportunities based on their data, they can, or other real world scenarios. But if they want to just manage their own data because they're traveling and if they're in a risky health situation, they've got their own record of their health, their health history, uh, which can avoid, you know, medical errors occurring. So, you know, even going beyond life sciences, I think this idea of democratizing data is just good for health. It's just good for people. And we definitely have the technology that can make it a reality. Now >>You're here. We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from the crowd. Would it be curious to know if there would be any comments from the panel on cost comparison analysis between traditional clinical trials in DCTs and how could the outcome effect the implementation of DCTs any sort of high-level framework you can share? >>I would say these are still early days to, to drive that analysis because I think many companies are, um, are still in the early stages of implementation. They've done a couple of trials. The other part of it that's important to keep in mind is, um, is for organizations it's, they're at a stage of, uh, of being on the learning curve. So when you're, you're calculating the cost efficiencies, if ideally you should have had two stakeholders involved, you could have potentially 20 stakeholders involved because everyone's trying to learn the process and see how it's going to be implemented. So, um, I don't think, and the third part of it, I think is organizations are still defining their KPIs. How do you measure it? What do you measure? So, um, and even still plugging in the pieces of technology that they need to fit in, who are they partnering with? >>What are the pieces of technology they're implementing? So I don't think there is a clear cut as answered at this stage. I think as you scale this model, the efficiencies will be seen. It's like any new technology or any new solution that's implemented in the first stages. It's always a little more complex and in fact sometimes costs extra. But as, as you start scaling it, as you establish your workflows, as you streamline it, the cost efficiencies will start becoming evident. That's why the industry is moving there. And I think that's how it turned out on the long run. >>Yeah. Just make it maybe out a comment. If you don't mind, the clinical trials are, have traditionally been costed are budgeted is on a per patient basis. And so, you know, based on the difficulty of the therapeutic area to recruit a rare oncology or neuromuscular disease, there's an average that it costs in order to find that patient and then execute the various procedures throughout the clinical trial on that patient. And so the difficulty of reaching the patient and then the complexity of the trial has led to what we might call a per patient stipend, which is just the metric that we use to sort of figure out what the average cost of a trial will be. So I think to point, we're going to have to see where the ability to adjust workflows, get to patients faster, collect data more easily in order to make the burden on the site, less onerous. I think once we start to see that work eases up because of technology, then I think we'll start to see those cost equations change. But I think right now the system isn't designed in order to really measure the economic benefit of de-central models. And I think we're going to have to sort of figure out what that looks like as we go along and since it's patient oriented right now, we'll have to say, well, you know, how does that work, ease up? And to those costs actually come down and then >>Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, it's kind of a best fit question. You all have touched on this, but let me just ask it is what examples in which, in which phases suit DCT in its current form, be it fully DCT or hybrid models, none of our horses for courses question. >>Well, I think it's kind of, uh, it's, it's it's has its efficiencies, obviously on the later phases, then the absolute early phase trials, those are not the ideal models for DCTs I would say so. And again, the logic is also the fact that, you know, when you're, you're going into the later phase trials, the volume of number of patients is increasing considerably to the point that Lorraine brought up about access to the patients about patient selection. The fact, I think what one should look at is really the advantages that it brings in, in terms of, you know, patient access in terms of patient diversity, which is a big piece that, um, the cities are enabling. So, um, if you, if, if you, if you look at the spectrum of, of these advantages and, and just to step back for a moment, if you, if you're looking at costs, like you're looking at things like remote site monitoring, um, is, is a big, big plus, right? >>I mean, uh, site monitoring alone accounts for around a third of the trial costs. So there are so many pieces that fall in together. The challenge actually that comes when you're in defining DCTs and there are, as Rick pointed out multiple definitions of DCTs that are existing, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, or you're talking about acro or Citi or others. But the point is it's a continuum, it's a continuum of different pieces that have been woven together. And so how do you decide which pieces you're plugging in and how does that impact the total cost or the solution that you're implementing? >>Great, thank you. Last question we have in the audience, excuse me. What changes have you seen? Are there others that you can share from the FDA EU APAC, regulators and supporting DCTs precision medicine for approval processes, anything you guys would highlight that we should be aware of? >>Um, I could quickly just add that. I think, um, I'm just publishing a report on de-centralized clinical trials should be published shortly, uh, perspective on that. But I would say that right now, um, there, there was a, in the FDA agenda, there was a plan for a decentralized clinical trials guidance, as far as I'm aware, one has not yet been published. There have been significant guidances that have been published both by email and by, uh, the FDA that, um, you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various technology pieces, which support the DCD model. Um, but I, and again, I think one of the reasons why it's not easy to publish a well-defined guidance on that is because there are so many moving pieces in it. I think it's the Danish, uh, regulatory agency, which has per se published a guidance and revised it as well on decentralized clinical trials. >>Right. Okay. Uh, we're pretty much out of time, but I, I wonder Lorraine, if you could give us some, some final thoughts and bring us home things that we should be watching or how you see the future. >>Well, I think first of all, let me, let me thank the panel. Uh, we really appreciate Greg from Lily and the meta from IDC bringing their perspectives to this conversation. And, uh, I hope that the audience has enjoyed the, uh, the discussion that we've had around the future state of real world data as, as well as DCT. And I think, you know, some of the themes that we've talked about, number one, I think we have a vision and I think we have the right strategies in terms of the future promise of real-world data in any number of different applications. We certainly have talked about the promise of DCT to be more efficient, to get us closer to the patient. I think that what we have to focus on is how we come together as an industry to really work through these very vexing operational issues, because those are always the things that hang us up and whether it's clinical research or whether it's later stage, uh, applications of data. >>We, the healthcare system is still very fragmented, particularly in the us. Um, it's still very, state-based, uh, you know, different states can have different kinds of, uh, of, of cultures and geographic, uh, delineations. And so I think that, you know, figuring out a way that we can sort of harmonize and bring all of the data together, bring some of the models together. I think that's what you need to look to us to do both industry consulting organizations, such as IBM Watson health. And we are, you know, through DTRA and, and other, uh, consortia and different bodies. I think we're all identifying what the challenges are in terms of making this a reality and working systematically on those. >>It's always a pleasure to work with such great panelists. Thank you, Lorraine Marshawn, Dr. Namita LeMay, and Greg Cunningham really appreciate your participation today and your insights. The next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond has been brought to you by IBM in the cube. You're a global leader in high tech coverage. And while this discussion has concluded, the conversation continues. So please take a moment to answer a few questions about today's panel on behalf of the entire IBM life sciences team and the cube decks for your time and your feedback. And we'll see you next time.

>>Hey everyone. Welcome back to the cube. Live in Las Vegas, Lisa Martin, with Dave Nicholson, we are covering AWS reinvent 2021. This was probably one of the most important and largest hybrid tech events this year with AWS and its enormous ecosystem of partners. We're going to be talking with a hundred guests in the next couple of days. We started a couple of days ago and about really the innovation that's going to be going on in the cloud and tech in the next decade. We're pleased to welcome Rick Tam Daniel's as our next guest VP of strategic ecosystems at Informatica. Rick. Welcome to >>The program. Thank you for having me. It's a, it's a pleasure to be back. >>Isn't it nice to be back in person? Oh, it's amazing. All these conversations you just can't replicate by video conferencing. Absolutely >>Great to reconnect with folks haven't seen in a few years as well. >>Absolutely. That's been the sentiment. I think one of the, one of the sentiments that we've heard the last three days, so one of the things thematically that we've also been hearing about in, in between all of the plethora of AWS announcements, typical reinvent is that every company has to become a data company, public sector, private sector, small business, large business. Talk to us about how Informatica and AWS are helping companies become data companies so that they don't get left behind. >>But one of the biggest things that we're hearing at reinvent is that customers are really concerned with data, fragmentation, data silos, access to trusted data, and how do they, how do they get that information to really affect data led transformation? In fact, we did a survey earlier in the year of chief, the chief data officers were found that up to 80, almost 80% of organizations had 50% or more of their data in hybrid or multi-cloud environments. And also a 79% are looking to leverage more than 100 data sources. And 30% are looking to leverage more than 1000 data sources. So Informatica we, with our intelligent data management cloud, we're really focused on enabling customers to bring together the data assets, no matter where they live, what format they're in, on-premise cloud, multi-cloud bringing that all together. >>Well, we sold this massive scatter 22 months ago now, right? Of everyone just, and the edge exploded and data exploded and volumes and data sources exploded hard for organizations to get their head around that, to go or that the data is going to be living in all these different places. You talked about a lot of customers and every industry being hybrid multi-cloud because based on strategy, based on acquisition, but to get their arms around that data and to be able to actually extract value from it fast is going to be the difference between those businesses that succeed and those that don't >>Absolutely. And our partnership with AWS, that's a long standing partnership and we're very much focused on addressing the challenges you're talking about. Uh, and in fact, earlier this year we announced our cloud first, our cloud native, uh, data governance and data catalog on AWS, which is really focused on creating that central point of trusted data access and visibility for the organization. And just today, we had an announcement about how we're bringing data democratization and really accelerating data democratization for AWS lake formation. >>What is, when you, when you, we talk about data democratization often, what does that mean to you? What does that mean to Informatica? How do you deliver that to customers so that they can really be able to extract as much value as they can? >>Yeah. So a great question. And really that whole data management journey is a big piece of this. So it starts with data discovery. How do I even begin to find my data assets? How do I get them from where they are to where they need to go in the cloud? How do I make sure they're clean, they're ready to use. I trust them. I understand where they came from. And so the solution that we announced today is really focused on how do we provide a business users with a self-service way of getting access to data lake data, sitting in Amazon S3 with lake formation governance, but doing it in a way that doesn't create an undue burden on those business users, around data compliance and data policies. And so what we've done is we brought our business user-friendly self-service experience an axon data marketplace together with AWS lake formation. >>So Informatica has had a long history in the data world. Um, I think of terms like MDM and ETL. Yes. Where does, where does Informatica is history dovetail with the present day in terms of cloud the con does the concept of extract translate load? I think that's what ETL stood for too many TLAs running as far as trying to transform, uh, w where does that play in today's world? Are you focused separately on cloud from on-premise data center or do you, or do you link the two? Yeah, >>So we focus on, uh, addressing data management, uh, when, no matter where the data lives. So on-premise cloud multi-cloud, uh, on our intelligent data management cloud platform is a, is the industry's first end-to-end cloud native as a service data management platform that delivers all those capabilities. I mentioned before, uh, to customers. So we can manage all those workloads that are distributed from a single cloud-based as a service data management platform. So >>The platform is, is as a service in the cloud, but you could be managing data assets that are in traditional on premises, data centers, the like, absolutely. >>Okay. >>So congratulations on the IPO. Of course we can't, we can't not talk to Informatica without that. I imagined the momentum is probably pretty great right about now when we think of AWS, I, when I think of AWS, I always think of momentum. We, I mean the, the volume of announcements, but also when I think about AWS, I think about their absolute focus on the customer, that working backwards approach from a partnership perspective. Is there alignment there? I imagine, like I said, with the IPO, a lot of momentum right now, probably a lot of excitement are, is infant medical also was focused and customer obsessed as AWS's. >>Yeah. So, um, first of all, thank you so much. Congratulations. Uh, so we had a very successful IPO last month. And in fact, just yesterday, our CEO I'm at Wailea presented our Q3 results, uh, which showcase the continued growth of our subscription revenue or cloud revenue. And in fact, our cloud revenue grew 44% year over year, which is really reflective of our big shift to being a cloud first company and also the success of our intelligent data management cloud platform. Right. And, and that platform, again, as I mentioned, it's spanning all those aspects of data management and we're delivering that for more than 5,000 customers globally. Uh, and just from an adoption perspective, we processed about 23 trillion transactions a month for customers in our cloud platform. And that's doubling every six to 12 months. So it's incredible amount of adoption. Some of the biggest enterprises in the world like Unilever, Sanofi folks like that are using the cloud is their preferred data management platform of choice in the cloud. >>Well, you know, of course, congratulations is in order for the IPO, but also really on what you just mentioned, the trajectory of where Informatica is going, because Informatica wasn't born yesterday. Right. And, uh, we shouldn't overlook the fact that there are challenges associated with moving from the world as it exists on premises for still 80% of it spend at least navigating that transition, going from private to public, getting the right kind of investment where people realize that cloud is a significant barrier to entry, uh, for, for a lot of companies. I think it's, it's, you know, you have a lot of folks cheering for you as you navigate this transition. >>Well, one thing I do I say is, yes, we have it in the business of data for a long time, but we also then the business of cloud quite a long time. So this is true. This is the 10th reinvent. This is also the ten-year anniversary of the Informatica AWS partnership, right? So we've been working in the cloud with AWS for, for that long innovating all of these different, different core services. So, um, and from that perspective, you know, I think we're doing a tremendous amount of innovation together, you know, solutions like when we talked about for lake formation, but we also announced today a couple of key programs that we partnered with AWS around, around modernization and migration, right? So that's a big area of focus as well is how do we help customers modernize and take advantage of all the great services that AWS offers? So that's how we announced our membership and what's called the workload migration program and also the data lead migrations program, which is part of the public sector focus at AWS as well. >>The station perspective that was talked a lot about by Adam yesterday. And we've talked about it a lot today, every organization needs to monitorize, even some of those younger ones that you think, oh, aren't, they already, you know, fairly modern, but where, where are your customer conversations happening from a modernization perspective is that elevated up the, the C stat that we've got to modernize our or our organization get better handle of our data, be able to use it more protected, secure it so that we can be competitive and deliver outstanding customer experiences. >>What happens is the pain points that the legacy infrastructure has from the business perspective really do elevate the conversation to the C-suite. They're looking at saying, Hey, especially with the pandemic, right? We have to transform our business. We have to have data. We have to have trust in data. How do we do that? And we're not going to get there >>On rigid on-premise infrastructure. We need to be in a cloud native footprint. And so we've been focused on helping customers get to those cloud native end points, but also to a truly cloud native data management, we talked about earlier can manage all those different workloads, right? From a single that SAS serverless type experience. Right? What have been some of the interesting conversations that you've had here? Again, we are in person yep. Fresh off the IPO, lots of announcements coming out. You guys made announcements today. What's been the sentiment from the, those customers and partners that you've talked about. >>Well, I'll give you guys actually a little sneak preview of another announcement we have coming tomorrow, uh, with our friends at Databricks. So we, uh, we are announcing a data, data democratization solution with Databricks accelerating some of the same, you know, addressing some of the same challenges we were talking about here, but in the data breaks in the Lakehouse environment. Um, so, so, but around that, and I had a great conversation with some partners here, some of the global system integrators, and they're just so happy to see that, right, because a lot of the infrastructure that's around data lakes are lake formation. It's pretty technical it's for a technical audience. And, and Informatica has really been focused on how do we expand the base of users that are able to tap into data and that's through no code experiences, right? It's through visual experiences. And we bring that tightly coupled together with the performance and the power and scale of platforms like Databricks and the AWS Redshift and S3, it's really transformative for customers. >>What are some of the things that here we are wrapping up the 10th, re-invent almost as tomorrow, but also wrapping up the end of 2021. What are some of the things that th th that there's obviously a lot of momentum with Informatica right now that from a partnership perspective, anything that you, you just gave us some breaking news. Thank you. We always love that. What are some of the things that you're looking forward to in 2022 that you think are really going to help Informatica customers just be incredibly competitive and utilizing data in the cloud on prem to their maximum? >>Well, I think as we go into the next year data complexity data fragmentation, it's gonna continue to grow. It's, it's, it's exploding out there. Uh, and one of the key components of our platform or the IDMC platform is we call it Clare, which is the industry first kind of metadata driven AI engine. And what we've done is we've taken the intelligence of machine learning and AI, and brought that to the business of data management. And we truly believe that the way customers are going to tame that data, they're going to address those problems and continue to scale and keep up is leveraging the power of AI in a cloud native cloud, first data management platform. >>Excellent. Rick, thank you so much for joining us today. Again, congratulations on last month, Informatica IPO, great solid, strong, deep partnership with AWS. We thank you for your insights and best of luck next year. >>Awesome. Thank you so much. Pleasure being here. Our >>Pleasure to have you for my co-host David Nicholson, I'm Martin. You're watching the cube, the global leader in live tech coverage.

>>Well, hi everybody. I'm John Walls here and welcome back to the cubes, continuing coverage and splunk.com 21. And we've talked a lot about data, obviously, um, and a number of partnerships and the point of resources that it's going on in this space. And certainly a very valuable partnership that Splunk has right now is one with Intel. And with me to talk a little bit more about that is Rick Echavarria, who is the vice president of sales and the marketing group at Intel. Rick. Good to see it today. Thanks for joining us on the queue. It's >>Good to see you, John, and thanks for having us. >>You bet. No glad to have you as part of the.com coverage as well. Um, well, first off, let's just for folks at home, uh, who would like to learn more about this relationship, the Splunk Intel partnership, if you would give us that the 30,000 foot picture of it right now, in terms of, of how it began and how it's evolved to the point where it resides today. >>Yeah. Uh, sure. Glad to do that. You know, Splunk is had for many years, uh, position as, as one of the world's best, uh, security information and event management platform. So just like many customers in the cybersecurity space, they're probably trying to retire their technical debt. And, and what are the areas of important focuses to SIM space, right? The SIM segment within cybersecurity. And so the initial engagement between Intel and Splunk started with the information security group at Intel, looking to, again, retire the technical debt, bring next generation SIM technology. And that started, uh, the engagement with Splunk again, to go solve the cybersecurity challenges. One of the things that we quickly learned is that, uh, those flung offers a great platform, you know, from a SIM point of view, as you know, the cyber security segment, the surface area of attack, the number of attacks kids were increased. >>And we quickly realized that this needed to be a collaboration in order for us to be able to work together, to optimize our infrastructure. So it could scale, it could be performance, it could be reliable, uh, to protect Intel's business. And as we started to work with Splunk, we realized, Hey, this is a great opportunity. Intel is benefiting from it. Why don't we start working together and create a reference architecture so that our joint customers also benefit from the collaboration that we have in the cybersecurity space, as we were building the Intel cybersecurity infrastructure platform. So that re that was really the beginning of, uh, of the collaboration around described here and a little bit more, >>Right? So, so you had this, this good working relationship and said, Hey, why don't we get together? Let's get the band together and see what we can do for our car joint clients down the road. Right. So, so what about those benefits that, because you've now you've got this almost as force multiplier right. Of, of Intel's experience. And then what Splunk has been able to do in the data analytics world. Um, what kind of values are being derived, do you think with that partnership? >>Well, obviously we feel much better about our cyber security posture. Um, and, uh, and what's sort of interesting, John, is that we realized that we were what started out as a conversation on SIM. Uh, it really turned out to be an opportunity for us to look at Splunk as a data platform. And, you know, in the technology world, you sometimes hear people talk about the horizontal capabilities. Then the vertical usage is really the security. Uh, the SIM technology. It really became one of several, sorry about the noise in the background. One, uh, became a vertical application. And then we realized that we can apply this platform to some other usages. And in addition to that, you know, when you think about cybersecurity and what we use for SIM that tends to be part of your core systems in it, we started to explore what can we do with what could we do with other data types for other different types of applications. >>And so what we, what we decided to do is we would go explore usages of this data at the edge, uh, of, of the network, and really started to move into much more of that operational technology space. When we realized that Splunk could really, uh, that we could integrate that we can ingest other types of data. And that started a second collaboration around our open Vino technology and our AI capabilities at the edge with the ingestion and the machine learning capabilities of Splunk, so that we can take things like visual data and start creating dashboards for, for example, uh, managing the flow of people, you know, especially in COVID environment. So, uh, and understanding utilization of spaces. So it really started with SIM is moved to the edge. And now we realized that there's a continuum in this data platform that we can build other usages around. >>What was that learning curve like when you went out to the edge, because a lot of people are talking about it, right. And there was a lot of banter about this is where we have to be, but you guys put your money where your mouth was, right? Yeah. You went out, you, you explored that frontier. And, and so what was that like? And, and, and what I guess maybe kind of being early in, uh, what advantage do you think that has given you as that process has matured a little bit? >>Well, it's really interesting John, because what really accelerated our engagement with Splunk in that space was the pandemic. And we had, uh, in 2020 Intel announced the pandemic response technology initiative, where we decided we were going to invest $50 million in accelerating technologies and solutions and partnerships to go solve some of the biggest challenges that depend on them. It was presenting to the world at large. And one of those areas was around companies trying to figure out how to, how to manage spaces, how to manage, you know, the number of people that are in a particular space and social distancing and things of that nature. And, you know, we ended up engaging with Splunk and this collaboration, again, to start looking at visual data, right, integrating that with our open Vino platform and again, their machine learning and algorithms, and start then creating what you would call more operational technology types of application based on visual data. Now these will have other applications that could be used for security usages. It could be used for, again, social distancing, uh, the utilization of acids, but their pandemic and that program that ends the launch is really what became the catalyst for our collaboration with Splunk that allowed us to expand into space. >>Right. And you've done a tremendous amount of work in the healthcare space. I mean, especially in the last year and a half with Penn and the pandemic, um, can you give just a couple of examples of that maybe the variety of uses and the variety of, uh, processes that you've had an influence in, because I think it's pretty impressive. >>Yeah. We, um, there's quite a bit of breadth in the types of solutions we've deployed as part of the pandemic response. John, you can think of some of the, I wouldn't call these things basic things, but you think about telehealth and that improving the telehealth experience all the way to creating privacy aware or sorry, solutions for privacy sensitive usage is where you're doing things like getting multiple institutions to share their data with the right privacy, uh, which, you know, going back to secure and privacy with the right, uh, protections for that data, but being allowed, allowing organization a and organization B partner together use data, create algorithms that both organizations benefit from it. An example of that is, is work we've done around x-ray, uh, and using x-rays to detect COVID on certain populations. So we've gone from those, you know, data protection, algorithm, development, development type of solutions to, to work that we've done in tele-health. So, uh, and, and a lot of other solutions in between, obviously in the high-performance, uh, space we've invested in high-performance computing for, to help the researchers, uh, find cures, uh, for the current pandemic and then looking at future pandemic. So it's been quite a breadth of, uh, uh, of solutions and it's really a Testament also to the breadth of Intel's portfolio and partnerships to be able to, uh, enable so much in such a short amount of time. >>I totally agree, man. Just reading it a little bit about it, about that work, and you talk about the, the breadth of that, the breadth and the depth of that is certainly impressive. So just in general, we'll just put healthcare in this big lump of customers. So what, what do you think the value proposition of your partnership with Splunk is in terms of providing, you know, ultimate value to your customers, because you're dealing with so many different sectors. Um, but if you could just give a summary from your perspective, this is what we do. This is why this power. >>Yeah. Well, customers, uh, talk about transformation. You know, there's a lot of conversation around transformation, right before the pandemic and through and center, but there's a lot of talk about companies wanting to transform and, you know, in order to be able to transform what are the key elements of that is, uh, to be able to capture the right data and then take, turn that data into the right outcomes. And that is something that requires obviously the capabilities and the ability to capture, to ingest, to analyze the data and to do that on an infrastructure that is going to scale with your business, that is going to be reliable. And that is going to be, to give you the flexibility for the types of solutions that you're wanting to apply. And that's really what this blog, uh, collaboration with Intel is going to do. It's, it's just a great example, John, uh, of the strategy that our CEO, pat Gelsinger recently talked about the importance of software to our business. >>This plump collaboration is right in the center of that. They have capabilities in SIM in it observability, uh, in many other areas that his whole world is turning data into, you know, into outcomes into results. But that has to be done on an infrastructure that again, will scale with your business, just like what's the case with Intel and our cybersecurity platform, right? We need to collaborate to make sure that this was going to scale with the demand demands of our business, and that requires close integration of, of hardware and software. The other point that I will make is that the, what started out as a collaboration with between Intel and Splunk, it's also expanding to other partners in the ecosystem. So I like to talk to you a little bit on a work stream that we have ongoing between Intel Splunk, HPE and the Lloyd. >>And why is that important is because, uh, as customers are deploying solutions, they're going to be deploying applications and they're going to have data in multiple environments on premise across multiple clouds. And we have to give, uh, these customers the ability to go gather the data from multiple sources. And that's part of the effort that we're developing with HPE and the Lloyd's will allow people to gather data, perform their analytics, regardless, regardless of their where their data is and be able to deploy the Splunk platform across these multiple environments, whether it's going to be on prem or it's going to be in a pure cloud environment, or it's going to be in a hybrid with multiple clouds, and you're willing to give our customers the most flexibility that we can. And that's where that collaboration with Deloitte and HP is going to come into play. >>Right. And you understand Splunk, right? You will get the workload. I mean, it's, it's totally, there's great familiarity there, which is a great value for that customer base, because you could apply that. So, so, um, obviously you're giving us like multiple thumbs up about the partnership. What excites you the most about going forward? Because as you know, it's all about, you know, where are we going from here? Yes. Now where we've been. So in terms of where you're going together in that partnership, well, what excites you about that? >>Well, first of all, we're excited because it's just a great example of the value that we can deliver to customers when you really understand their pain points and then have the capability to integrate solutions that encompass software and hardware together. So I think that the fact that we've been able to do the work on, on that core SIM space, where we now have a reference architecture that shows how you could really scale and deliver that a Splunk solution for your cybersecurity needs in a, in a scale of one reliable and with high levels of security, of course. And the fact that we then also been able to co-develop fairly quickly solutions for the edge, allows customers now to have that data platform that can scale and can access a lot of different data types from the edge to the cloud. That is really unique. I think it provides a lot of flexibility and it is applicable to a lot of vertical industry segments and a lot of customers >>And be attractive to a lot of customers. That's for sure rec edge of area. We appreciate the time, always a good to see you. And we certainly appreciate your joining us here on the cube to talk about.com for 21. And your relationship with the folks at Splunk. >>Yeah. Thank you, John. >>You bet. Uh, talking about Intel spot, good partnership. Long time, uh, partnership that has great plans going forward, but we continue our coverage here of.com 21. You're watching the cube.

>> Good day, everyone. Thank you for joining me. I'm Cindy Maike, joined by Rick Taylor of Cloudera. We're here to talk about predictive maintenance for the public sector and how to increase asset service reliability. On today's agenda, we'll talk specifically around how to optimize your equipment maintenance, how to reduce costs, asset failure with data and analytics. We'll go into a little more depth on what type of data, the analytical methods that we're typically seeing used, the associated- Brooke will go over a case study as well as a reference architecture. So by basic definition, predictive maintenance is about determining when an asset should be maintained and what specific maintenance activities need to be performed either based upon an assets actual condition or state. It's also about predicting and preventing failures and performing maintenance on your time on your schedule to avoid costly unplanned downtime. McKenzie has looked at analyzing predictive maintenance costs across multiple industries and has identified that there's the opportunity to reduce overall predictive maintenance costs by roughly 50% with different types of analytical methods. So let's look at those three types of models. First, we've got our traditional type of method for maintenance, and that's really about uncorrective maintenance, and that's when we're performing maintenance on an asset after the equipment fails. The challenges with that is we end up with unplanned downtime. We end up with disruptions in our schedules, as well as reduce quality around the performance of the asset. And then we started looking at preventive maintenance and preventative maintenance is really when we're performing maintenance on a set schedule. The challenges with that is we're typically doing it regardless of the actual condition of the asset, which has resulted in unnecessary downtime and expense. And specifically we're really now focused on condition-based maintenance, which is looking at leveraging predictive maintenance techniques based upon actual conditions and real time events and processes. Within that, we've seen organizations and again, source from McKenzie, have a 50% reduction in downtime, as well as overall 40% reduction in maintenance costs. Again, this is really looking at things across multiple industries, but let's look at it in the context of the public sector and based upon some activity by the department of energy several years ago, they really looked at what does predictive maintenance mean to the public sector? What is the benefit of looking at increasing return on investment of assets, reducing, you know, reduction in downtime as well as overall maintenance costs. So corrective or reactive based maintenance is really about performing once there's been a failure and then the movement towards preventative, which is based upon a set schedule. We're looking at predictive where we're monitoring real-time conditions. And most importantly is now actually leveraging IOT and data and analytics to further reduce those overall down times. And there's a research report by the department of energy that goes into more specifics on the opportunity within the public sector. So Rick, let's talk a little bit about what are some of the challenges regarding data, regarding predictive maintenance? >> Some of the challenges include having data silos, historically our government organizations and organizations in the commercial space as well, have multiple data silos. They've spun up over time. There are multiple business units and note, there's no single view of assets. And oftentimes there's redundant information stored in these silos of information. Couple that with huge increases in data volume, data growing exponentially, along with new types of data that we can ingest there's social media, there's semi and unstructured data sources and the real time data that we can now collect from the internet of things. And so the challenge is to collect all these assets together and begin to extract intelligence from them and additional insights and and that in turn, then fuels machine learning and what we call artificial intelligence, which enables predictive maintenance. Next slide. >> Cindy: So let's look specifically at, you know, the types of use cases and I'm going to- Rick and I are going to focus on those use cases, where do we see predictive maintenance coming in to the procurement facility, supply chain, operations and logistics? We've got various level of maturity. So, you know, we're talking about predictive maintenance. We're also talking about using information, whether it be on a connected asset or a vehicle doing monitoring to also leveraging predictive maintenance on how do we bring about looking at data from connected warehouses facilities and buildings? I'll bring an opportunity to both increase the quality and effectiveness of the missions within the agencies to also looking at looking at cost efficiency, as well as looking at risk and safety. And the types of data, you know, that Rick mentioned around, you know, the new types of information. Some of those data elements that we typically have seen is looking at failure history. So when has an asset or a machine or a component within a machine failed in the past? We've also looking at bringing together a maintenance history, looking at a specific machine. Are we getting error codes off of a machine or assets looking at when we've replaced certain components to looking at how are we actually leveraging the assets? What were the operating conditions? Pulling up data from a sensor on that asset? Also looking at the features of an asset, whether it's, you know, engine size it's make and model, where's the asset located? To also looking at who's operated the asset, you know, whether it be their certifications, what's their experience, how are they leveraging the assets? And then also bringing in together some of the pattern analysis that we've seen. So what are the operating limits? Are we getting service reliability? Are we getting a product recall information from the actual manufacturer? So Rick, I know the data landscape has really changed. Let's, let's go over looking at some of those components. >> Rick: Sure. So this slide depicts sort of the, some of the inputs that inform a predictive maintenance program. So we've talked a little bit about the silos of information, the ERP system of record, perhaps the spares and the service history. So we want, what we want to do is combine that information with sensor data, whether it's a facility and equipment sensors, or temperature and humidity, for example. All this stuff is then combined together and then used to develop machine learning models that better inform predictive maintenance, because we do need to take into account the environmental factors that may cause additional wear and tear on the asset that we're monitoring. So here are some examples of private sector maintenance use cases that also have broad applicability across the government. For example, one of the busiest airports in Europe is running Cloudera on Azure to capture secure and correlate sensor data collected from equipment within the airport. The people moving equipment more specifically, the escalators, the elevators, and the baggage carousels. The objective here is to prevent breakdowns and improve airport efficiency and passenger safety. Another example is a container shipping port. In this case, we use IOT data and machine learning to help customers recognize how their cargo handling equipment is performing in different weather conditions to understand how usage relates to failure rates and to detect anomalies in transport systems. These all improve port efficiency. Another example is Navistar. Navistar is a leading manufacturer of commercial trucks, buses, and military vehicles. Typically vehicle maintenance, as Cindy mentioned, is based on miles traveled or based on a schedule or a time since the last service. But these are only two of the thousands of data points that can signal the need for maintenance. And as it turns out, unscheduled maintenance and vehicle breakdowns account for a large share of the total cost for vehicle owners. So to help fleet owners move from a reactive approach to a more predictive model, Navistar built an IOT enabled remote diagnostics platform called On Command. The platform brings in over 70 sensor data feeds for more than 375,000 connected vehicles. These include engine performance, trucks speed, acceleration, coolant temperature and break ware. This data is then correlated with other Navistar and third-party data sources, including weather, geolocation, vehicle usage, traffic, warranty, and parts inventory information. So the platform then uses machine learning and advanced analytics to automatically detect problems early and predict maintenance requirements. So how does the fleet operator use this information? They can monitor truck health and performance from smartphones or tablets and prioritize needed repairs. Also, they can identify that the nearest service location that has the relevant parts, the train technicians and the available service space. So sort of wrapping up the benefits. Navistar's helped fleet owners reduce maintenance costs by more than 30%. This same platform has also used to help school buses run safely and on time. For example, one school district with 110 buses that travel over a million miles annually reduce the number of tows needed year over year, thanks to predictive insights, delivered by this platform. So I'd like to take a moment and walk through the data life cycle as depicted in this diagram. So data ingest from the edge may include feeds from the factory floor or things like connected vehicles, whether they're trucks, aircraft, heavy equipment, cargo vessels, et cetera. Next, the data lands on a secure and governed data platform where it is combined with data from existing systems of record to provide additional insights. And this platform supports multiple analytic functions working together on the same data while maintaining strict security, governance and control measures. Once processed the data is used to train machine learning models, which are then deployed into production, monitored and retrained as needed to maintain accuracy. The process data is also typically placed in a data warehouse and use to support business intelligence analytics and dashboards. And in fact, this data life cycle is representative of one of our government customers doing condition-based maintenance across a variety of aircraft. And the benefits they've discovered include; less unscheduled maintenance and a reduction in mean man hours to repair, increased maintenance efficiencies, improved aircraft availability, and the ability to avoid cascading component failures, which typically costs more in repair cost and downtime. Also, they're able to better forecast the requirements for replacement parts and consumables and last, and certainly very importantly, this leads to enhanced safety. This chart overlays the secure open source Cloudera platform used in support of the data life cycle we've been discussing. Cloudera data flow, provides the data ingest, data movement and real time streaming data query capabilities. So data flow gives us the capability to bring data in from the asset of interest, from the internet of things. While the data platform provides a secure governed data lake and visibility across the full machine learning life cycle eliminates silos and streamlines workflows across teams. The platform includes a integrated suite of secure analytic applications. And two that we're specifically calling out here are Cloudera machine learning, which supports the collaborative data science and machine learning environment, which facilitates machine learning and AI and the Cloudera data warehouse, which supports the analytics and business intelligence, including those dashboards for leadership Cindy, over to you. >> Cindy: Rick, Thank you. And I hope that Rick and I provided you some insights on how predictive maintenance condition-based maintenance is being used and can be used within your respective agency, bringing together data sources that maybe you're having challenges with today, bringing that more real-time information in from a streaming perspective, blending that industrial IOT, as well as historical information together to help actually optimize maintenance and produce costs within each of your agencies. To learn a little bit more about Cloudera and our, what we're doing from a predictive maintenance, please visit us at Cloudera.com/Solutions/PublicSector And we look forward to scheduling a meeting with you. And on that, we appreciate your time today and thank you very much.

>>Hi, this is Cindy Mikey, vice president of industry solutions at caldera. Joining me today is chef is Molly, our solution engineer for the public sector. Today. We're going to talk about speed to insight. Why using machine learning in the public sector, specifically around fraud, waste and abuse. So topic for today, we'll discuss machine learning, why the public sector uses it to target fraud, waste, and abuse, the challenges. How do we enhance your data and analytical approaches the data landscape analytical methods and shad we'll go over reference architecture and a case study. So by definition, fraud, waste and abuse per the government accountability office is fraud. Isn't an attempt to obtain something about value through unwelcome misrepresentation waste is about squandering money or resources and abuse is about behaving improperly or unreasonably to actually obtain something of value for your personal benefit. So as we look at fraud, um, and across all industries, it's a top of mind, um, area within the public sector. >>Um, the types of fraud that we see is specifically around cyber crime, uh, looking at accounting fraud, whether it be from an individual perspective to also, uh, within organizations, looking at financial statement fraud, to also looking at bribery and corruption, as we look at fraud, it really hits us from all angles, whether it be from external perpetrators or internal perpetrators, and specifically from the research by PWC, the key focus area is we also see over half of fraud is actually through some form of internal or external, uh, perpetrators again, key topics. So as we also look at a report recently by the association of certified fraud examiners, um, within the public sector, the us government, um, in 2017, it was identified roughly $148 billion was attributable to fraud, waste and abuse. Specifically about 57 billion was focused on reported monetary losses and another 91 billion on areas where that opportunity or the monetary basis had not yet been measured. >>As we look at breaking those areas down again, we look at several different topics from permit out payment perspective. So breaking it down within the health system, over $65 billion within social services, over $51 billion to procurement fraud to also, um, uh, fraud, waste and abuse that's happening in the grants and the loan process to payroll fraud, and then other aspects, again, quite a few different topical areas. So as we look at those areas, what are the areas that we see additional type of focus, there's a broad stroke areas. What are the actual use cases that our agencies are using the data landscape? What data, what analytical methods can we use to actually help curtail and prevent some of the, uh, the fraud waste and abuse. So, as we look at some of the analytical processes and analytical use crate, uh, use cases in the public sector, whether it's from, uh, you know, the taxation areas to looking at, you know, social services, uh, to public safety, to also the, um, our, um, uh, additional agency methods, we're gonna use focused specifically on some of the use cases around, um, you know, fraud within the tax area. >>Uh, we'll briefly look at some of the aspects of, um, unemployment insurance fraud, uh, benefit fraud, as well as payment and integrity. So fraud has it it's, um, uh, underpinnings inquiry, like you different on government agencies and difficult, different analytical methods, and I usage of different data. So I think one of the key elements is, you know, you can look at your, your data landscape on specific data sources that you need, but it's really about bringing together different data sources across a different variety, a different velocity. So, uh, data has different dimensions. So we'll look at structured types of data of semi-structured data, behavioral data, as well as when we look at, um, you know, predictive models. We're typically looking at historical type information, but if we're actually trying to look at preventing fraud before it actually happens, or when a case may be in flight, which is specifically a use case that shad is going to talk about later is how do I look at more of that? >>Real-time that streaming information? How do I take advantage of data, whether it be, uh, you know, uh, financial transactions we're looking at, um, asset verification, we're looking at tax records, we're looking at corporate filings. Um, and we can also look at more, uh, advanced data sources where as we're looking at, um, investigation type information. So we're maybe going out and we're looking at, uh, deep learning type models around, uh, you know, semi or that, uh, behavioral, uh, that's unstructured data, whether it be camera analysis and so forth. So for quite a different variety of data and the, the breadth and the opportunity really comes about when you can integrate and look at data across all different data sources. So in a looking at a more extensive, uh, data landscape. So specifically I want to focus on some of the methods, some of the data sources and some of the analytical techniques that we're seeing, uh, being used, um, in the government agencies, as well as opportunities, uh, to look at new methods. >>So as we're looking at, you know, from a, um, an audit planning or looking at, uh, the opportunity for the likelihood of non-compliance, um, specifically we'll see data sources where we're maybe looking at a constituents profile, we might actually be investigating the forms that they've provided. We might be comparing that data, um, or leveraging internal data sources, possibly looking at net worth, comparing it against other financial data, and also comparison across other constituents groups. Some of the techniques that we use are some of the basic natural language processing, maybe we're going to do some text mining. We might be doing some probabilistic modeling, uh, where we're actually looking at, um, information within the agency to also comparing that against possibly tax forms. A lot of times it's information historically has been done on a batch perspective, both structured and semi-structured type information. And typically the data volumes can be low, but we're also seeing those data volumes on increase exponentially based upon the types of events that we're dealing with, the number of transactions. >>Um, so getting the throughput, um, and chef's going to specifically talk about that in a moment. The other aspect is, as we look at other areas of opportunity is when we're building upon, how do I actually do compliance? How do I actually look at conducting audits, uh, or potential fraud to also looking at areas of under-reported tax information? So there you might be pulling in some of our other types of data sources, whether it's being property records, it could be data that's being supplied by the actual constituents or by vendors to also pulling in social media information to geographical information, to leveraging photos on techniques that we're seeing used is possibly some sentiment analysis, link analysis. Um, how do we actually blend those data sources together from a natural language processing? But I think what's important here is also the method and the looking at the data velocity, whether it be batch, whether it be near real time, again, looking at all types of data, whether it's structured semi-structured or unstructured and the key and the value behind this is, um, how do we actually look at increasing the potential revenue or the, um, under reported revenue? >>Uh, how do we actually look at stopping fraudulent payments before they actually occur? Um, also looking at increasing the amount of, uh, the level of compliance, um, and also looking at the potential of prosecution of fraud cases. And additionally, other areas of opportunity could be looking at, um, economic planning. How do we actually perform some link analysis? How do we bring some more of those things that we saw in the data landscape on customer, or, you know, constituent interaction, bringing in social media, bringing in, uh, potentially police records, property records, um, other tax department, database information. Um, and then also looking at comparing one individual to other individuals, looking at people like a specific, like a constituent, are there areas where we're seeing, uh, >>Um, other >>Aspects of, of fraud potentially being occurring. Um, and also as we move forward, some of the more advanced techniques that we're seeing around deep learning is looking at computer vision, um, leveraging geospatial information, looking at social network entity analysis, uh, also looking at, uh, agent-based modeling techniques, where we're looking at simulation Monte Carlo type techniques that we typically see in the financial services industry, actually applying that to fraud, waste, and abuse within the, uh, the public sector. Um, and again, that really, uh, lends itself to a new opportunities. And on that, I'm going to turn it over to chef to talk about, uh, the reference architecture for, uh, doing these buckets. >>Thanks, Cindy. Um, so I'm gonna walk you through an example, reference architecture for fraud detection using, uh, Cloudera's underlying technology. Um, and you know, before I get into the technical details, uh, I want to talk about how this would be implemented at a much higher level. So with fraud detection, what we're trying to do is identify anomalies or novelists behavior within our datasets. Um, now in order to understand what aspects of our incoming data represents anomalous behavior, we first need to understand what normal behavior is. So in essence, once we understand normal behavior, anything that deviates from it can be thought of as an anomaly, right? So in order to understand what normal behavior is, we're going to need to be able to collect store and process a very large amount of historical data. And so incomes, clutters platform, and this reference architecture that needs to be for you. >>So, uh, let's start on the left-hand side of this reference architecture with the collect phase. So fraud detection will always begin with data collection. We need to collect large amounts of information from systems that could be in the cloud. It could be in the data center or even on edge devices, and this data needs to be collected so we can create our normal behavior profiles. And these normal behavioral profiles would then in turn, be used to create our predictive models for fraudulent activity. Now, uh, thinking, uh, to the data collection side, one of the main challenges that many organizations face, uh, in this phase, uh, involves using a single technology that can handle, uh, data that's coming in all different types of formats and protocols and standards with different velocities and velocities. Um, let me give you an example. Uh, we could be collecting data from a database that gets updated daily, uh, and maybe that data is being collected in Agra format. >>At the same time, we can be collecting data from an edge device that's streaming in every second, and that data may be coming in Jason or a binary format, right? So this is a data collection challenge that can be solved with cluttered data flow, which is a suite of technologies built on a patch NIFA in mini five, allowing us to ingest all of this data, do a drag and drop interface. So now we're collecting all of this data, that's required to map out normal behavior. The next thing that we need to do is enrich it, transform it and distribute it to, uh, you know, downstream systems for further process. Uh, so let's, let's walk through how that would work first. Let's taking Richmond for, uh, for enrichment, think of adding additional information to your incoming data, right? Let's take, uh, financial transactions, for example, uh, because Cindy mentioned it earlier, right? >>You can store known locations of an individual in an operational database, uh, with Cloudera that would be HBase. And as an individual makes a new transaction, their geolocation that's in that transaction data can be enriched with previously known locations of that very same individual. And all of that enriched data can be later used downstream for predictive analysis, predictable. So the data has been enrich. Uh, now it needs to be transformed. We want the data that's coming in, uh, you know, Avro and Jason and binary and whatever other format to be transformed into a single common format. So it can be used downstream for stream processing. Uh, again, this is going to be done through clutter and data flow, which is backed by NIFA, right? So the transformed semantic data is then going to be stricted to Kafka and coffin. It's going to serve as that central repository of syndicated services or a buffer zone, right? >>So coffee is going to pretty much provide you with, uh, extremely fast resilient and fault tolerance storage. And it's also gonna give you the consumer APIs that you need that are going to enable a wide variety of applications to leverage that enriched and transformed data within your buffer zone, uh, allowed that, you know, 17. So you can store that data in a distributed file system, give you that historical context that you're going to need later on for machine learning, right? So the next step in the architecture is to leverage a cluttered SQL stream builder, which enables us to write, uh, streaming SQL jobs on top of Apache Flink. So we can, uh, filter, analyze and, uh, understand the data that's in the Kafka buffer in real time. Uh I'll you know, I'll also add like, you know, if you have time series data, or if you need a lab type of cubing, you can leverage kudu, uh, while EDA or, you know, exploratory data analysis and visualization, uh, can all be enabled through clever visualization technology. >>All right, so we've filtered, we've analyzed and we've explored our incoming data. We can now proceed to train our machine learning models, uh, which will detect anomalous behavior in our historically collected data set, uh, to do this, we can use a combination of supervised unsupervised, uh, even deep learning techniques with neural networks. And these models can be tested on new incoming streaming data. And once we've gone ahead and obtain the accuracy of the performance, the scores that we want, we can then take these models and deploy them into production. And once the models are productionalized or operationalized, they can be leveraged within our streaming pipeline. So as new data is ingested in real-time knife, I can query these models to detect if the activity is anomalous or fraudulent. And if it is, they can alert downstream users and systems, right? So this in essence is how fraudulent activity detection works. >>Uh, and this entire pipeline is powered by clutters technology, right? And so, uh, the IRS is one of, uh, clutter's customers. That's leveraging our platform today and implementing, uh, a very similar architecture, uh, to detect fraud, waste, and abuse across a very large set of historical facts, data. Um, and one of the neat things with the IRS is that they've actually recently leveraged the partnership between Cloudera and Nvidia to accelerate their spark based analytics and their machine learning, uh, and the results have been nothing short of amazing, right? And in fact, we have a quote here from Joe and salty who's, uh, you know, the technical branch chief for the research analytics and statistics division group within the IRS with zero changes to our fraud detection workflow, we're able to obtain eight times to performance simply by adding GPS to our mainstream big data servers. This improvement translates to half the cost of ownership for the same workloads, right? So embedding GPU's into the reference architecture I covered earlier has enabled the IRS to improve their time to insights by as much as eight X while simultaneously reducing their underlying infrastructure costs by half, uh, Cindy back to you >>Chef. Thank you. Um, and I hope that you found, uh, some of the, the analysis, the information that Sheva and I have provided, um, to give you some insights on how cloud era is actually helping, uh, with the fraud waste and abuse challenges within the, uh, the public sector, um, specifically looking at any and all types of data, how the clutter platform is bringing together and analyzing information, whether it be you're structured you're semi-structured to unstructured data, both in a fast or in a real-time perspective, looking at anomalies, being able to do some of those on detection, uh, looking at neural network analysis, time series information. So next steps we'd love to have additional conversation with you. You can also find on some additional information around, I have caught areas working in the, the federal government by going to cloudera.com solutions slash public sector. And we welcome scheduling a meeting with you again, thank you for joining us Sheva and I today. We greatly appreciate your time and look forward to future progress. >>Good day, everyone. Thank you for joining me. I'm Sydney. Mike joined by Rick Taylor of Cloudera. Uh, we're here to talk about predictive maintenance for the public sector and how to increase assets, service, reliability on today's agenda. We'll talk specifically around how to optimize your equipment maintenance, how to reduce costs, asset failure with data and analytics. We'll go into a little more depth on, um, what type of data, the analytical methods that we're typically seeing used, um, the associated, uh, Brooke, we'll go over a case study as well as a reference architecture. So by basic definition, uh, predictive maintenance is about determining when an asset should be maintained and what specific maintenance activities need to be performed either based upon an assets of actual condition or state. It's also about predicting and preventing failures and performing maintenance on your time on your schedule to avoid costly unplanned downtime. >>McKinsey has looked at analyzing predictive maintenance costs across multiple industries and has identified that there's the opportunity to reduce overall predictive maintenance costs by roughly 50% with different types of analytical methods. So let's look at those three types of models. First, we've got our traditional type of method for maintenance, and that's really about our corrective maintenance, and that's when we're performing maintenance on an asset, um, after the equipment fails. But the challenges with that is we end up with unplanned. We end up with disruptions in our schedules, um, as well as reduced quality, um, around the performance of the asset. And then we started looking at preventive maintenance and preventative maintenance is really when we're performing maintenance on a set schedule. Um, the challenges with that is we're typically doing it regardless of the actual condition of the asset, um, which has resulted in unnecessary downtime and expense. Um, and specifically we're really now focused on pre uh, condition-based maintenance, which is looking at leveraging predictive maintenance techniques based upon actual conditions and real time events and processes. Um, within that we've seen organizations, um, and again, source from McKenzie have a 50% reduction in downtime, as well as an overall 40% reduction in maintenance costs. Again, this is really looking at things across multiple industries, but let's look at it in the context of the public sector and based upon some activity by the department of energy, um, several years ago, >>Um, they've really >>Looked at what does predictive maintenance mean to the public sector? What is the benefit, uh, looking at increasing return on investment of assets, reducing, uh, you know, reduction in downtime, um, as well as overall maintenance costs. So corrective or reactive based maintenance is really about performing once there's been a failure. Um, and then the movement towards, uh, preventative, which is based upon a set schedule or looking at predictive where we're monitoring real-time conditions. Um, and most importantly is now actually leveraging IOT and data and analytics to further reduce those overall downtimes. And there's a research report by the, uh, department of energy that goes into more specifics, um, on the opportunity within the public sector. So, Rick, let's talk a little bit about what are some of the challenges, uh, regarding data, uh, regarding predictive maintenance. >>Some of the challenges include having data silos, historically our government organizations and organizations in the commercial space as well, have multiple data silos. They've spun up over time. There are multiple business units and note, there's no single view of assets. And oftentimes there's redundant information stored in, in these silos of information. Uh, couple that with huge increases in data volume data growing exponentially, along with new types of data that we can ingest there's social media, there's semi and unstructured data sources and the real time data that we can now collect from the internet of things. And so the challenge is to collect all these assets together and begin to extract intelligence from them and insights and, and that in turn then fuels, uh, machine learning and, um, and, and what we call artificial intelligence, which enables predictive maintenance. Next slide. So >>Let's look specifically at, you know, the, the types of use cases and I'm going to Rick and I are going to focus on those use cases, where do we see predictive maintenance coming into the procurement facility, supply chain, operations and logistics. Um, we've got various level of maturity. So, you know, we're talking about predictive maintenance. We're also talking about, uh, using, uh, information, whether it be on a, um, a connected asset or a vehicle doing monitoring, uh, to also leveraging predictive maintenance on how do we bring about, uh, looking at data from connected warehouses facilities and buildings all bring on an opportunity to both increase the quality and effectiveness of the missions within the agencies to also looking at re uh, looking at cost efficiency, as well as looking at risk and safety and the types of data, um, you know, that Rick mentioned around, you know, the new types of information, some of those data elements that we typically have seen is looking at failure history. >>So when has that an asset or a machine or a component within a machine failed in the past? Uh, we've also looking at bringing together a maintenance history, looking at a specific machine. Are we getting error codes off of a machine or assets, uh, looking at when we've replaced certain components to looking at, um, how are we actually leveraging the assets? What were the operating conditions, uh, um, pulling off data from a sensor on that asset? Um, also looking at the, um, the features of an asset, whether it's, you know, engine size it's make and model, um, where's the asset located on to also looking at who's operated the asset, uh, you know, whether it be their certifications, what's their experience, um, how are they leveraging the assets and then also bringing in together, um, some of the, the pattern analysis that we've seen. So what are the operating limits? Um, are we getting service reliability? Are we getting a product recall information from the actual manufacturer? So, Rick, I know the data landscape has really changed. Let's, let's go over looking at some of those components. Sure. >>So this slide depicts sort of the, some of the inputs that inform a predictive maintenance program. So, as we've talked a little bit about the silos of information, the ERP system of record, perhaps the spares and the service history. So we want, what we want to do is combine that information with sensor data, whether it's a facility and equipment sensors, um, uh, or temperature and humidity, for example, all this stuff is then combined together, uh, and then use to develop machine learning models that better inform, uh, predictive maintenance, because we'll do need to keep, uh, to take into account the environmental factors that may cause additional wear and tear on the asset that we're monitoring. So here's some examples of private sector, uh, maintenance use cases that also have broad applicability across the government. For example, one of the busiest airports in Europe is running cloud era on Azure to capture secure and correlate sensor data collected from equipment within the airport, the people moving equipment more specifically, the escalators, the elevators, and the baggage carousels. >>The objective here is to prevent breakdowns and improve airport efficiency and passenger safety. Another example is a container shipping port. In this case, we use IOT data and machine learning, help customers recognize how their cargo handling equipment is performing in different weather conditions to understand how usage relates to failure rates and to detect anomalies and transport systems. These all improve for another example is Navistar Navistar, leading manufacturer of commercial trucks, buses, and military vehicles. Typically vehicle maintenance, as Cindy mentioned, is based on miles traveled or based on a schedule or a time since the last service. But these are only two of the thousands of data points that can signal the need for maintenance. And as it turns out, unscheduled maintenance and vehicle breakdowns account for a large share of the total cost for vehicle owner. So to help fleet owners move from a reactive approach to a more predictive model, Navistar built an IOT enabled remote diagnostics platform called on command. >>The platform brings in over 70 sensor data feeds for more than 375,000 connected vehicles. These include engine performance, trucks, speed, acceleration, cooling temperature, and break where this data is then correlated with other Navistar and third-party data sources, including weather geo location, vehicle usage, traffic warranty, and parts inventory information. So the platform then uses machine learning and advanced analytics to automatically detect problems early and predict maintenance requirements. So how does the fleet operator use this information? They can monitor truck health and performance from smartphones or tablets and prioritize needed repairs. Also, they can identify that the nearest service location that has the relevant parts, the train technicians and the available service space. So sort of wrapping up the, the benefits Navistar's helped fleet owners reduce maintenance by more than 30%. The same platform is also used to help school buses run safely. And on time, for example, one school district with 110 buses that travel over a million miles annually reduce the number of PTOs needed year over year, thanks to predictive insights delivered by this platform. >>So I'd like to take a moment and walk through the data. Life cycle is depicted in this diagram. So data ingest from the edge may include feeds from the factory floor or things like connected vehicles, whether they're trucks, aircraft, heavy equipment, cargo vessels, et cetera. Next, the data lands on a secure and governed data platform. Whereas combined with data from existing systems of record to provide additional insights, and this platform supports multiple analytic functions working together on the same data while maintaining strict security governance and control measures once processed the data is used to train machine learning models, which are then deployed into production, monitored, and retrained as needed to maintain accuracy. The process data is also typically placed in a data warehouse and use to support business intelligence, analytics, and dashboards. And in fact, this data lifecycle is representative of one of our government customers doing condition-based maintenance across a variety of aircraft. >>And the benefits they've discovered include less unscheduled maintenance and a reduction in mean man hours to repair increased maintenance efficiencies, improved aircraft availability, and the ability to avoid cascading component failures, which typically cost more in repair cost and downtime. Also, they're able to better forecast the requirements for replacement parts and consumables and last, and certainly very importantly, this leads to enhanced safety. This chart overlays the secure open source Cloudera platform used in support of the data life cycle. We've been discussing Cloudera data flow, the data ingest data movement and real time streaming data query capabilities. So data flow gives us the capability to bring data in from the asset of interest from the internet of things. While the data platform provides a secure governed data lake and visibility across the full machine learning life cycle eliminates silos and streamlines workflows across teams. The platform includes an integrated suite of secure analytic applications. And two that we're specifically calling out here are Cloudera machine learning, which supports the collaborative data science and machine learning environment, which facilitates machine learning and AI and the cloud era data warehouse, which supports the analytics and business intelligence, including those dashboards for leadership Cindy, over to you, Rick, >>Thank you. And I hope that, uh, Rick and I provided you some insights on how predictive maintenance condition-based maintenance is being used and can be used within your respective agency, bringing together, um, data sources that maybe you're having challenges with today. Uh, bringing that, uh, more real-time information in from a streaming perspective, blending that industrial IOT, as well as historical information together to help actually, uh, optimize maintenance and reduce costs within the, uh, each of your agencies, uh, to learn a little bit more about Cloudera, um, and our, what we're doing from a predictive maintenance please, uh, business@cloudera.com solutions slash public sector. And we look forward to scheduling a meeting with you, and on that, we appreciate your time today and thank you very much.

(gentle music) >> Welcome to today's session of the AWS Startup Showcase The Next Big Thing in AI, Security, & Life Sciences. Today we're featuring Protegrity for the life sciences track. I'm your host for theCUBE, Natalie Erlich, and now we're joined by our guest, Rick Farnell, the CEO of Protegrity. Thank you so much for being with us. >> Great to be here. Thanks so much Natalie, great to be on theCUBE. >> Yeah, great, and so we're going to talk today about the ransomware game, and how it has changed with kinetic data protection. So, the title of today's video segment makes a bold claim, how are kinetic data and ransomware connected? >> So first off kinetic data, data is in use, it's moving, it's not static, it's no longer sitting still, and your data protection has to adhere to those same standards. And I think if you kind of look at what's happening in the ransomware kind of attacks, there's a couple of different things going on, which is number one, bad actors are getting access to data in the clear, and they're holding that data ransom, and threatening to release that data. So kind of from a Protegrity standpoint, with our protection capabilities, that data would be rendered useless to them in that scenario. So there's lots of ways in which kind of backup data protection, really wonderful opportunities to do both data protection and kind of that backup mixed together really is a wonderful solution to the threat of ransomware. And it's a serious issue and it's not just targeting the most highly regulated industries and customers, we're seeing kind of attacks on pipeline and ferry companies, and really there is no end to where some of these bad actors are really focusing on and the damages can be in the hundreds of millions of dollars and last for years after from a brand reputation. So I think if you look at how data is used today, there's that kind of opposing forces where the business wants to use data at the speed of light to produce more machine learning, and more artificial intelligence, and predict where customers are going to be, and have wonderful services at their fingertips. But at the same time, they really want to protect their data, and sometimes those architectures can be at odds, and at Protegrity, we're really focusing on solving that problem. So free up your data to be used in artificial intelligence and machine learning, while making sure that it is absolutely bulletproof from some of these ransomware attacks. >> Yeah, I mean, you bring a really fascinating point that's really central to your business. Could you tell us more about how you're actually making that data worthless? I mean, that sounds really revolutionary. >> So, it sounds novel, right? To kind of make your data worthless in the wrong hands. And I think from a Protegrity perspective, our kind of policy and protection capability follows the individual piece of data no matter where it lives in the architecture. And we do a ton of work as the world does with Amazon Web Services, so kind of helping customers really blend their hybrid cloud strategies with their on-premise and their use of AWS, is something that we thrive at. So protecting that data, not just at rest or while it's in motion, but it's a continuous protection policy that we can basically preserve the privacy of the data but still keep it unique for use in downstream analytics and machine learning. >> Right, well, traditional security is rather stifling, so how can we fix this, and what are you doing to amend that? >> Well, I think if you look at cybersecurity, and we certainly play a big role in the cybersecurity world but like any industry, there are many layers. And traditional cybersecurity investment has been at the perimeter level, at the network level keeping bad actors out, and once people do get through some of those fences, if your data is not protected at a fine grain level, they have access to it. And I think from our standpoint, yes, we're last line of defense but at the same time, we partner with folks in the cybersecurity industry and with AWS and with others in the backup and recovery to give customers that level of protection, but still allow their kinetic data to be utilized in downstream analytics. >> Right, well, I'd love to hear more about the types of industries that you're helping, and specifically healthcare obviously, a really big subject for the year and probably now for years to come, how is this industry using kinetic protection at the moment? >> So certainly, as you mentioned, some of the most highly regulated industries are our sweet spot. So financial services, insurance, online retail, and healthcare, or any industry that has sensitive data and sensitive customer data, so think first name last name, credit card information, national ID number, social security number blood type, cancer type. That's all sensitive information that you as an organization want to protect. So in the healthcare space, specifically, some of the largest healthcare organizations in the world rely on Protegrity to provide that level of protection, but at the same time, give them the business flexibility to utilize that data. So one of our customers, one of the leaders in online prescriptions, and that is an AWS customer, to allow a wonderful service to be delivered to all of their customers while maintaining protection. If you think about sharing data on your watch with your insurance provider, we have lots of customers that bridge that gap and have that personal data coming in to the insurance companies. All the way to, if in a use case in the future, looking at the pandemic, if you have to prove that you've been vaccinated, we're talking about some sensitive information, so you want to be able to show that information but still have the confidence that it's not going to be used for nefarious purposes. >> Right, and what is next for Protegrity? >> Well, I think continuing on our journey, we've been around for 17 years now, and I think the last couple, there's been an absolute renaissance in fine-grained data protection or that connected data protection, and organizations are recognizing that continuing to protect your perimeter, continuing to protect your firewalls, that's not going to go away anytime soon. Your access points, your points of vulnerability to keep bad actors out, but at the same time, recognizing that the data itself needs to be protected but with that balance of utilizing it downstream for analytic purposes, for machine learning, for artificial intelligence. Keeping the data of hundreds of millions if not billions of people saved, that's what we do. If you were to add up the customers of all of our customers, the largest banks, the largest insurance companies, largest healthcare companies in the world, globally, we're protecting the private data of billions of human beings. And it doesn't just stop there, I think you asked a great question about kind of the industry and yes, insurance, healthcare, retail, where there's a lot of sensitive data that certainly can be a focus point. But in the IOT space, kind of if you think about GPS location or geolocation, if you think about a device, and what it does, and the intelligence that it has, and the decisions that it makes on the fly, protecting data and keeping that safe is not just a personal thing, we're stepping into intellectual property and some of the most valuable assets that companies have, which is their decision-making on how they use data and how they deliver an experience, and I think that's why there's been such a renaissance, if you will, in kind of that fine grain data protection that we provide. >> Yeah, well, what is Protegrity's role now in future proofing businesses against cyber attacks? I mean, you mentioned really the ramifications of that and the impact it can have on businesses, but also on governments. I mean, obviously this is really critical. >> So there's kind of a three-step approach, and this is something that we have certainly kind of felt for a long, long time, and we work on with our customers. One is having that fine-grain data protection. So tokenizing your data so that if someone were to get your data, it's worthless, unless they have the ability to unlock every single individual piece of data. So that's number one, and then that's kind of what Protegrity provides. Number two, having a wonderful backup capability to roll kind of an active-active, AWS being one of the major clouds in the world where we deploy our software regularly and work with our customers, having multi-regions, multi-capabilities for an active-active scenario where if there's something that goes down or happens you can bring that down and bring in a new environment up. And then third is kind of malware detection in the rest of the cyber world to make sure that you rinse kind of your architecture from some of those agents. And I think when you kind of look at it, ransomware, they take data, they encrypt your data, so they force you to give them Bitcoin, or whatnot, or they'll release some of your data. And if that data is rendered useless, that's one huge step in kind of your discussions with these nefarious actors and be like you could release it, but there's nothing there, you're not going to see anything. And then second, if you have a wonderful backup capability where you wind down that environment that has been infiltrated, prove that this new environment is safe, have your production data have rolling and then wind that back up, you're back in business. You don't have to notify your customers, you don't have to deal with the ransomware players. So it's really a three-step process but ultimately it starts with protecting your data and tokenizing your data, and that's something that Protegrity does really, really well. >> So you're basically able to eliminate the financial impact of a breach? >> Honestly, we dramatically reduce the risk of customers being at risk for ransomware attacks 100%. Now, tokenizing data and moving that direction is something that it's not trivial, we are literally replacing production data with a token and then making sure that all downstream applications have the ability to utilize that, and make sure that the analytic systems and machine learning systems, and artificial intelligence applications that are built downstream on that data have the ability to execute, but that is something that from our patent portfolio and what we provide to our customers, again, some of the largest organizations in retail, in financial services, in banking, and in healthcare, we've been doing that for a long time. We're not just saying that we can do this and we're in version one of our product, we've been doing this for years, supporting the largest organizations with a 24 by seven capability. >> Right, and tell us a bit about the competitive landscape, where do you see your offering compared to your competitors? >> So, kind of historically back, let's call it an era ago maybe even before cloud even became a thing, and hybrid cloud, there were a handful of players that could acquire into much larger organizations, those organizations have been dusting off those acquired assets, and we're seeing them come back in. There's some new entrants into our space that have some protection mechanisms, whether it be encryption, or whether it be anonymization, but unless you're doing fine grain tokenization, you're not going to be able to allow that data to participate in the artificial intelligence world. So, we see kind of a range of competition there. And then I'd say probably the biggest competitor, Natalie, is customers not doing tokenization. They're saying, "No, we're okay, we'll continue protecting our firewall, we'll continue protecting our access points, we'll invest a little bit more in maybe some governance, but that fine grain data protection, maybe it's not for us." And that is the big shift that's happening. You look at kind of the beginning of this year with the solar winds attack, and the vulnerability that caused the very large and important organizations found themselves the last few weeks with all the ransomware attacks that are happening on meat processing plants and facilities, shutting down meat production, pipeline, stopping oil and gas and kind of that. So we're seeing a complete shift in the types of organizations and the industries that need to protect their data. It's not just the healthcare organizations, or the banks, or the credit card companies, it is every single industry, every single size company. >> Right, and I got to ask you this questioning, what is your defining contribution to the future of cloud scale? >> Well, ultimately we kind of have a charge here at Protegrity where we feel like we protect the world's most sensitive data. And when we come into work every day, that's what every single employee thinks at Protegrity. We are standing behind billions of individuals who are customers of our customers, and that's a cultural thing for us, and we take that very serious. We have maniacal customer support supporting our biggest customers with a fall of the sun 24 by seven global capability. So that's number one. So, I think our part in this is really helping to educate the world that there is a solution for this ransomware and for some of these things that don't have to happen. Now, naturally with any solution, there's going to be some investment, there's going to be some architecture changes, but with partnerships like AWS, and our partnership with pretty much every data provider, data storage provider, data solution provider in the world, we want to provide fine-grain data protection, any data in any system on any platform. And that's our mission. >> Well, Rick Farnell, this has been really fascinating conversation with you, thank you so much. The CEO of Protegrity, really great to have you on this program for the AWS Startup Showcase, talking about how ransomware game has changed with the kinetic data protection. Really appreciate it. Again, I'm your host Natalie Erlich, thank you again very much for watching. (light music)

>>President. >>Hello everyone and welcome to wien on 2021. My name is Dave Volonte and you're watching the cubes continuous coverage of the event. You know, VM is a company that made its mark riding the virtualization wave, but quite amazingly has continued to extend its product portfolio and catch the other major waves of the industry. Of course, we're talking about cloud backup. SaS data protection was one of the early players there making moves and containers. And this is the VM on power panel with me or Danny Allen, who is the Ceo and Senior vice president of product strategy at VM. Dave Russell is the vice President of enterprise Strategy, of course, said Vin and Rick Vanover, senior director of product strategy at VM. It's great to see you again. Welcome back to the cube. >>Good to be here. >>Well, it had to be here. >>Yeah, let's do it. >>Let's do this. So Danny, you know, we heard you kind of your keynotes and we saw the general sessions and uh sort of diving into the breakouts. But the thing that jumps out to me is this growth rate that you're on. Uh you know, many companies and we've seen this throughout the industry have really struggled, you know, moving from the traditional on prem model to an an A. R. R. Model. Uh they've had challenges doing so the, I mean, you're not a public company, but you're quite transparent and a lot of your numbers 25% a our our growth year of a year in the last quarter, You know, 400,000 plus customers. You're talking about huge numbers of downloads of backup and replication Danny. So what are your big takeaways from the last, You know, 6-12 months? I know it was a strange year obviously, but you guys just keep cranking. >>Yeah, so we're obviously hugely excited by this and it really is a confluence of various things. It's our, it's our partners, it's the channel. Um, it's our customers frankly that that guide us and give us direction on what to do. But I always focus in on the product because I, you know, we run product strategy here, this group and we're very focused on building good products and I would say there's three product areas that are on maximum thrust right now. One is in the data center. So we built a billion dollar business on being the very best in the data center for V sphere, hyper V, um, for Nutanix, HV and as we announced also with red hat virtualization. So data center obviously a huge thrust for us going forward. The second assess Office 3 65 is exploding. We already announced we're protecting 5.8 million users right now with being back up for Office 3 65 and there's a lot of room to grow there. There's 145 million daily users of Microsoft teams. So a lot of room to grow. And then the third areas cloud, we moved over 100 petabytes of data into the public cloud in Q one and there's a lot of opportunity there as well. So those three things are driving the growth, the data center SaAS and cloud >>Davis. I want to get your kind of former analyst perspective on this. Uh you know, I know, you know, it's kind of become cliche but you still got that D. N. A. And I'm gonna tap it. So when you think about and you were following beam, of course very closely during its ascendancy with virtualization. And back then you wouldn't just take your existing, you know, approaches to back up in your processes and just slap them on to virtualization. That that wouldn't have worked. You had to rethink your backup. And it seems like I want to ask you about cloud because people talk about lift and shift and what I hear from customers is, you know, if I just lift and shift to cloud, it's okay, but if I don't have a plan to change my operating model, you know, I don't get the real benefit out of it. And so I would think back up data protection, data management etcetera is a key part of that. So how are you thinking about cloud and the opportunity there? >>Yeah, that's a good point, David. You know, I think the key area right there is it's important to protect the workload of the environment. The way that that environment is naturally is best suited to be protected and also to interact in a way that the administrator doesn't have to rethink, doesn't have to change their process so early on. Um I think it was very successful because the interface is the work experience looked like what an active directory administrator was used to, seeing if they went to go and protect something with me where to go recover an item. Same is true in the cloud, You don't want to just take what's working well in one area and just force it, you know, around round peg into a square hole. This doesn't work well. So you've got to think about the environment and you've got to think about what's gonna be the real use case for getting access to this data. So you want to really tune things and there's obviously commonality involved, but from a workflow perspective, from an application perspective and then a delivery model perspective, Now, when it comes to hybrid cloud multi cloud, it's important to look like that you belong there, not a fish out of water. >>Well, so of course, Danny you were talking to talking about you guys have product first, Right? And so rick your your key product guy here. What's interesting to me is when you look at the history of the technology industry and disruption, it's it's so often that the the incumbent, which you knew now an incumbent, you know, you're not the startup anymore, but the incumbent has challenges riding these these new waves because you've got to serve the existing customer base, but you gotta ride the new momentum as well. So how rick do you approach that from a product standpoint? Because based on the numbers that we see it doesn't you seem to be winning in both the traditional business and the new business. So how do you adapt from a product standpoint? >>Well, Dave, that's a good question. And Danny set it up? Well, it's really the birth of the Wien platform and its relevance in the market. In my 11th year here at Wien, I've had all kinds of conversations. Right. You know, the perception was that, you know, this smb toy for one hyper Advisor those days are long gone. We can check the boxes across the data center and cloud and even cloud native apps. You know, one of the things that my team has done is invest heavily in both people and staff on kubernetes, which aligns to our casting acquisition, which was featured heavily here at V Mon. So I think that being able to have that complete platform conversation Dave has really given us incredible momentum but also credibility with the customers because more than ever, this fundamental promise of having data backed up and being able to drive a recovery for whatever may happen to data nowadays. You know, that's a real emotional, important thing for people and to be able to bring that kind of outcome across the data center, across the cloud, across changes in what they do kubernetes that's really aligned well to our success and you know, I love talking to customers now. It's a heck of a lot easier when you can say yes to so many things and get the technical win. So that kind of drives a lot of the momentum Dave, but it's really the platform. >>So let's talk about the future of it and I want all you guys to chime in here and Danny, you start up, How do you see it? I mean, I always say the last 10 years, the next 10 years ain't gonna be like the last 10 years whether it's in cloud or hybrid et cetera. But so how Danny do you see I. T. In the future of I. T. Where do you see VM fitting in, how does that inform your roadmap, your product strategy? Maybe you could kick that segment off? >>Yeah. I think of the kind of the two past decades that we've gone through starting back in 2000 we had a lot of digital services built for end users and it was built on physical infrastructure and that was fantastic. Obviously we could buy things online, we could order close we could order food, we we could do things interact with end users. The second era about a decade later was based on virtualization. Now that wasn't a benefit so much to the end user is a benefit to the business. The Y because you could put 10 servers on a single physical server and you could be a lot more flexible in terms of delivery. I really think this next era that we're going into is actually based on containers. That's why the cost of acquisition is so strategic to us. Because the unique thing about containers is they're designed for to be consumption friendly. You spin them up, you spin them down, you provision them, you d provisions and they're completely portable. You can move it >>from on >>premises if you're running open shift to e k s a k s G k E. And so I think the next big era that we're going to go through is this movement towards containerized infrastructure. Now, if you ask me who's running that, I still think there's going to be a data center operations team, platform ups is the way that I think about them who run that because who's going to take the call in the middle of the night. But it is interesting that we're going through this transformation and I think we're in the very early stages of this radical transformation to a more consumption based model. Dave. I don't know what you think about that. >>Yeah, I would say something pretty similar Danny. It sounds cliche day valenti, but I take everything back to digital transformation. And the reason I say that is to me, digital transformation is about improving customer intimacy and so that you can deliver goods and services that better resonate and you can deliver them in better time frame. So exactly what Danny said, you know, I think that the siloed approaches of the past where we built very hard in environments and we were willing to take a long time to stand those up and then we have very tight change control. I feel like 2020 sort of a metaphor for where the data center is going to throw all that out the window we're compiling today. We're shipping today and we're going to get experience today and we're going to refine it and do it again tomorrow. But that's the environment we live in. And to Danny's point why containers are so important. That notion of shift left meaning experience things earlier in the cycle. That is going to be the reality of the data center regardless of whether the data center is on prem hybrid cloud, multi cloud or for some of us potentially completely in the cloud. >>So rick when you think about some of your peeps like the backup admit right and how that role is changing in a big discussion in the economy now about the sort of skills gap we got all these jobs and and yet there's still all this unemployment now, you know the debate about the reasons why, but there's a there's a transition enrolls in terms of how people are using products and obviously containers brings that, what what are you seeing when you talk to like a guy called him your peeps? Yeah, it's >>an evolving conversation. Dave the audience, right. It has to be relevant. Uh you know, we were afforded good luxury in that data center wheelhouse that Danny mentioned. So virtualization platform storage, physical servers, that's a pretty good start. But in the software as a service wheelhouse, it's a different persona now, they used to talk to those types of people, there's a little bit of connection, but as we go farther to the cloud, native apps, kubernetes and some of the other SAAS platforms, it is absolutely an audience journey. So I've actually worked really hard on that in my team, right? Everything from what I would say, parachuting into a community, right? And you have to speak their language. Number one reason is just number one outcomes just be present. And if you're in these communities you can find these individuals, you can talk their language, you can resonate with their needs, right? So that's something uh you know, everything from Levin marketing strategy to the community strategy to even just seating products in the market, That's a recipe that beam does really well. So yeah, it's a moving target for sure. >>Dave you were talking about the cliche of digital transformation and I'll say this may be pre Covid, I really felt like it was a cliche, there was a lot of, you know, complacency, I'll call it, but then the force marks the digital change that uh and now we kind of understand if you're not a digital business, you're in trouble. Uh And so my question is how it relates to some of the trends that we've been talking about in terms of cloud containers, We've seen the SAs ification for the better part of a decade now, but specifically as it relates to migration, it's hard for customers to just migrate their application portfolio to the cloud. Uh It's hard to fund it. It takes a long time. It's complex. Um how do you see that cloud migration evolving? Maybe that's where hybrid comes in And again, I'm interested in how you guys think about it and how it affects your strategy. >>Yeah. Well it's a complex answer as you might imagine because 400,000 customers, we take the exact same code. The exact same ice so that I run on my laptop is the exact same being backup and replication image that a major bank protects almost 20,000 machines and a petabytes of data. And so what that means is that you have to look at things on a case by case basis for some of us continuing to operate proprietary systems on prem might be the best choice for a certain workload. But for many of us the Genie is kind of out of the bottle with 2020 we have to move faster. It's less about safety and a lot more about speed and favorable outcome. We'll fix it if it's broken but let's get going. So for organizations struggling with how to move to the cloud, believe it or not, backup and recovery is an excellent way to start to venture into that because you can start to move data backup ISm data movement engine. So we can start to see data there where it makes sense. But rick would be quick to point out we want to offer a safe return. We have instances of where people want to repatriate data back and having a portable data format is key to that Rick. >>Uh yeah, I had a conversation recently with an organization managing cloud sprawl. They decided to consolidate, we're going to use this cloud, so it was removing a presence from one cloud that starts with an A and migrating it to the other cloud that starts with an A. You know, So yeah, we've seen that need for portability repatriation on prem classic example going from on prem apps to software as a service models for critical apps. So data mobility is at the heart of VM and with all the different platforms, kubernetes comes into play as well. It's definitely aligning to the needs that we're seeing in the market for sure. >>So repatriation, I want to stay on that for a second because you're, you're an arms dealer, you don't care if they're in the cloud or on prem and I don't know, maybe you make more money in one or the other, but you're gonna ride whatever waves the market gives you so repatriation to me implies. Or maybe I'm just inferring that somebody's moved to the cloud and they feel like, wow, we've made a mistake, it was too fast, too expensive. It didn't work for us. So now we're gonna bring it back on prem. Is that what you're saying? Are you saying they actually want their data in both both places. As another layer of data protection Danny. I wonder if you could address that. What are you seeing? >>Well, one of the interesting things that we saw recently, Dave Russell actually did the survey on this is that customers will actually build their work laid loads in the cloud with the intent to bring it back on premises. And so that repatriation is real customers actually don't just accidentally fall into it, but they intend to do it. And the thing about being everyone says, hey, we're disrupting the market, we're helping you go through this transformation, we're helping you go forward. Actually take a slightly different view of this. The team gives them the confidence that they can move forward if they want to, but if they don't like it, then they can move back and so we give them the stability through this incredible pace, change of innovation. We're moving forward so so quickly, but we give them the ability to move forward if they want then to recover to repatriate if that's what they need to do in a very effective way. And Dave maybe you can touch on that study because I know that you talked to a lot of customers who do repatriate workloads after moving them to the cloud. >>Yeah, it's kind of funny Dave not in the analyst business right now, but thanks to Danny and our chief marketing Officer, we've got now half a dozen different research surveys that have either just completed or in flight, including the largest in the data protection industry's history. And so the survey that Danny alluded to, what we're finding is people are learning as they're going and in some cases what they thought would happen when they went to the cloud they did not experience. So the net kind of funny slide that we discovered when we asked people, what did you like most about going to the cloud and then what did you like least about going to the cloud? The two lists look very similar. So in some cases people said, oh, it was more stable. In other cases people said no, it was actually unstable. So rick I would suggest that that really depends on the practice that you bring to it. It's like moving from a smaller house to a larger house and hoping that it won't be messy again. Well if you don't change your habits, it's eventually going to end up in the same situation. >>Well, there's still door number three and that's data reuse and analytics. And I found a lot of organizations love the idea of at least manipulating data, running test f scenarios on yesterday's production, cloud workload completely removed from the cloud or even just analytics. I need this file. You know, those types of scenarios are very easy to do today with them. And you know, sometimes those repatriations, those portable recoveries, Sometimes people do that intentionally, but sometimes they have to do it. You know, whether it's fire, flood and blood and you know, oh, I was looks like today we're moving to the cloud because I've lost my data center. Right. Those are scenarios that, that portable data format really allows organizations to do that pretty easily with being >>it's a good discussion because to me it's not repatriation, it has this negative connotation, the zero sum game and it's not Danny what you describe and rick as well. It was kind of an experimentation, a purposeful. We're going to do it in the cloud because we can and it's cheap and low risk to spin it up and then we're gonna move it because we've always thought we're going to have it on prem. So, so you know, there is some zero sum game between the cloud and on prem. Clearly no question about it. But there's also this rising tide lifts all ship. I want to, I want to change the subject to something that's super important and and top of mind it's in the press and it ain't going away and that is cyber and specifically ransomware. I mean, since the solar winds hack and it seems to me that was a new milestone in the capabilities and aggressiveness of the adversary who is very well funded and quite capable. And what we're seeing is this idea of tucking into the supply chain of islands, so called island hopping. You're seeing malware that's self forming and takes different signatures very stealthy. And the big trend that we've seen in the last six months or so is that the bad guys will will lurk and they'll steal all kinds of sensitive data. And then when you have an incident response, they will punish you for responding. And they will say, okay, fine, you want to do that. We're going to hold you ransom. We're gonna encrypt your data. And oh, by the way, we stole this list of positive covid test results with names from your website and we're gonna release it if you don't pay their. I mean, it's like, so you have to be stealthy in your incident response. And this is a huge problem. We're talking about trillions of dollars lost each year in, in in cybercrime. And so, uh, you know, it's again, it's this uh the bad news is good news for companies like you. But how do you help customers deal with this problem? What are you seeing Danny? Maybe you can chime in and others who have thoughts? >>Well we're certainly seeing the rise of cyber like crazy right now and we've had a focus on this for a while because if you think about the last line of defense for customers, especially with ransomware, it is having secure backups. So whether it be, you know, hardened Linux repositories, but making sure that you can store the data, have it offline, have it, have it encrypted immutable. Those are things that we've been focused on for a long while. It's more than that. Um it's detection and monitoring of the environment, which is um certainly that we do with our monitoring tools and then also the secure recovery. The last thing that you want to do of course is bring your backups or bring your data back online only to be hit again. And so we've had a number of capabilities across our portfolio to help in all of these. But I think what's interesting is where it's going, if you think about unleashing a world where we're continuously delivering, I look at things like containers where you have continues delivery and I think every time you run that helm commander, every time you run that terra form command, wouldn't that be a great time to do a backup to capture your data so that you don't have an issue once it goes into production. So I think we're going towards a world where security and the protection against these cyber threats is built into the supply chain rather than doing it on just a time based uh, schedule. And I know rick you're pretty involved on the cyber side as well. Would you agree with that? I >>would. And you know, for organizations that are concerned about ransomware, you know, this is something that is taken very seriously and what Danny explained for those who are familiar with security, he kind of jumped around this, this universally acceptable framework in this cybersecurity framework there, our five functions that are a really good recipe on how you can go about this. And and my advice to IT professionals and decision makers across the board is to really align everything you do to that framework. Backup is a part of it. The security monitoring and user training. All those other things are are areas that that need to really follow that wheel of functions. And my little tip here and this is where I think we can introduce some differentiation is around detection and response. A lot of people think of backup product would shine in both protection and recovery, which it does being does, but especially on response and detection, you know, we have a lot of capabilities that become impact opportunities for organizations to be able to really provide successful outcomes through the other functions. So it's something we've worked on a lot. In fact we've covered here at the event. I'm pretty sure it will be on replay the updated white paper. All those other resources for different levels can definitely guide them through. >>So we follow up to the detection is what analytics that help you identify whatever lateral movement or people go in places they shouldn't go. I mean the hard part is is you know, the bad guys are living off the land, meaning they're using your own tooling to to hack you. So they're not it's not like they're introducing something new that shouldn't be there. They're they're just using making judo moves against you. So so specifically talk a little bit more about your your detection because that's critical. >>Sure. So I'll give you one example imagine we capture some data in the form of a backup. Now we have an existing advice that says, you know what Don't put your backup infrastructure with internet connectivity. Use explicit minimal permissions. And those three things right there and keep it up to date. Those four things right there will really hedge off a lot of the different threat vectors to the back of data, couple that with some of the mutability offline or air gapped capabilities that Danny mentioned and you have an additional level of resiliency that can really ensure that you can drive recovery from an analytic standpoint. We have an api that allows organizations to look into the backup data. Do more aggressive scanning without any exclusions with different tools on a flat file system. You know, the threats can't jump around in memory couple that with secure restore. When you reintroduce things into the environment From a recovery standpoint, you don't want to reintroduce threats. So there's protections, there's there's confidence building steps along the way with them and these are all generally available technologies. So again, I got this white paper, I think we're up to 50 pages now, but it's a very thorough that goes through a couple of those scenarios. But you know, it gets the uh, it gets quickly into things that you wouldn't expect from a backup product. >>Please send me a copy if you, if you don't mind. I this is a huge problem and you guys are global company. I admittedly have a bit of a US bias, but I was interviewing robert Gates one time the former defense secretary and we're talking about cyber war and I said, don't we have the best cyber, can't we let go on the offense? He goes, yeah, we can, but we got the most to lose. So this is really a huge problem for organizations. All right, guys, last question I gotta ask you. So what's life like under, under inside capital of the private equity? What's changed? What's, what's the same? Uh, do you hear from our good friend ratner at all? Give us the update there. >>Yes. Oh, absolutely fantastic. You know, it's interesting. So obviously acquired by insight partners in February of 2020, right, when the pandemic was hitting, but they essentially said light the fuse, keep the engine's going. And we've certainly been doing that. They haven't held us back. We've been hiring like crazy. We're up to, I don't know what the count is now, I think 4600 employees, but um, you know, people think of private equity and they think of cost optimizations and, and optimizing the business, That's not the case here. This is a growth opportunity and it's a growth opportunity simply because of the technology opportunity in front of us to keep, keep the engine's going. So we hear from right near, you know, on and off. But the new executive team at VM is very passionate about driving the success in the industry, keeping abreast of all the technology changes. It's been fantastic. Nothing but good things to say. >>Yes, insight inside partners, their players, we watched them watch their moves and so it's, you know, I heard Bill McDermott, the ceo of service now the other day talking about he called himself the rule of 60 where, you know, I always thought it was even plus growth, you know, add that up. And that's what he was talking about free cash flow. He's sort of changing the definition a little bit but but so what are you guys optimizing for you optimizing for growth? Are you optimising for Alberta? You optimizing for free cash flow? I mean you can't do All three. Right. What how do you think about that? >>Well, we're definitely optimizing for growth. No question. And one of the things that we've actually done in the past 12 months, 18 months is beginning to focus on annual recurring revenue. You see this in our statements, I know we're not public but we talk about the growth in A. R. R. So we're certainly focused on that growth in the annual recovering revenue and that that's really what we tracked too. And it aligns well with the cloud. If you look at the areas where we're investing in cloud native and the cloud and SAAS applications, it's very clear that that recurring revenue model is beneficial. Now We've been lucky, I think we're 13 straight quarters of double-digit growth. And and obviously they don't want to see that dip. They want to see that that growth continue. But we are optimizing on the growth trajectory. >>Okay. And you see you clearly have a 25% growth last quarter in A. R. R. Uh If I recall correctly, the number was evaluation was $5 billion last january. So obviously then, given that strategy, Dave Russell, that says that your tam is a lot bigger than just the traditional backup world. So how do you think about tam? I'll we'll close there >>and uh yeah, I think you look at a couple of different ways. So just in the backup recovery space or backup in replication to paying which one you want to use? You've got a large market there in excess of $8 billion $1 billion dollar ongoing enterprise. Now, if you look at recent i. D. C. Numbers, we grew and I got my handy HP calculator. I like to make sure I got this right. We grew 44.88 times faster than the market average year over year. So let's call that 45 times faster and backup. There's billions more to be made in traditional backup and recovery. However, go back to what we've been talking around digital transformation Danny talking about containers in the environment, deployment models, changing at the heart of backup and recovery where a data capture data management, data movement engine. We envision being able to do that not only for availability but to be able to drive the business board to be able to drive economies of scale faster for our organizations that we serve. I think the trick is continuing to do more of the same Danny mentioned, he knows the view's got lit. We haven't stopped doing anything. In fact, Danny, I think we're doing like 10 times more of everything that we used to be doing prior to the pandemic. >>All right, Danny will give you the last word, bring it home. >>So our goal has always been to be the most trusted provider of backup solutions that deliver modern data protection. And I think folks have seen at demon this year that we're very focused on that modern data protection. Yes, we want to be the best in the data center but we also want to be the best in the next generation, the next generation of I. T. So whether it be sas whether it be cloud VM is very committed to making sure that our customers have the confidence that they need to move forward through this digital transformation era. >>Guys, I miss flying. I mean, I don't miss flying, but I miss hanging with you all. We'll see you. Uh, for sure. Vim on 2022 will be belly to belly, but thanks so much for coming on the the virtual edition and thanks for having us. >>Thank you. >>All right. And thank you for watching everybody. This keeps continuous coverage of the mon 21. The virtual edition. Keep it right there for more great coverage. >>Mm

>> Announcer: From around the globe. >> (upbeat music) It's the cube with digital coverage of IBM Think 2021 brought to you by IBM. >> Hi, welcome back everyone to the Cubes coverage of IBM Think 2021 virtual. I'm John Furrier, host of the cube. Got a great guest, Rick Smith, CTO of IBM Anthem client team. Rick. Great to see you. Thanks for coming on the cube. >> Yeah. Thank you, John. Nice to see you as well, virtually. >> First introduce yourself, what you do there, what's going on on your plate these days, honestly, COVID, we're coming out of it soon. Take a minute to introduce yourself. >> Yeah, so I've got about 15 years in the seat with Anthem. Previous to that I worked at Pretty university as the CTO in Indiana. So haven't really left, but started working with Anthem as a technical architect, eventually moved into the CTO role and have been part of, you know, a long journey with them that started at a managed services agreement in 2005. And here we are in 2021. So I've been through a lot of changes they've made to improve themselves and move into digitalization. And certainly the changes we've made too to accommodate that as we went through the years. >> Awesome. Well, thanks for that setup. I really want to dig into this expansion of project Cirrus. You guys have had a multi decade partnership with IBM and then last year you launched this expansion, project Cirrus. Can you describe this project? And what does it mean? And this new term I've heard, enterprise hybrid cloud as a service. Sounds very interesting. >> Yeah. So that's my term. I'm hoping you made it patent or something like that. But the reality is you hear our CEO talk and say that 75% of corporate workloads are not in the cloud yet. Right? And Anthem is no different, right? So they starting to go into cloud and those kinds of things. But they said to us, you know, "Hey, we've got a long series of excellence with you from a delivery perspective, reliability perspective is kind of the bedrock of what we do, but we don't want to be in the data center business, right? And we want to transform and move to cloud. We want to become a more of an AI company and these kinds of things. And we said, well, we think we can actually put together a program... Excuse me, program for you to allow you to do that, right? And so we formed something called project Cirrus which is really an expansion of our partnership. So if I look back, John, we did about 80% of the end-to-end delivery for Anthem from a managed services perspective. In other words, they did a few pieces and we said, we think we could improve that if we had the entire 100%. And so project Cirrus was about, you know, extending from 80% to 100%. It was also about taking a series of applications that were important to them and actually say, we'll actually take them on and transform them 100% all the way to cloud and take advantage of new things. It was about a commitment to closing those data centers, right? So they have five strategic data centers. And about 24,000 hosts that we said we will actually commit to getting those, you know, getting you out of the data centers and moving those to either IBM cloud or close to IBM cloud if you will, I'll come back to that in a minute. And we'll also build something called ATEC, Anthem Technology Excellent Center, if you will. And that's near and dear to my heart because that's sort of my baby, right? So it's a transformation engine and we can talk a little bit more about that in a second. But he said the key to this for us is that, if we look at our trend line, John, over the number of years with Anthem, when we started about 2007 looking at this data, we've grown the number of hosts. We've had to manage, over 600% during that time period. But we've driven down high priority incidents by over 90%. So think about that. You know, this is really important for them to have resiliency and stability in their organization. You know, huge acceleration number of hosts, but drive down the a P zero incidents, if you will. And they said, we need to maintain that and continue to improve upon that. Right? >> Yeah. >> So Cirrus was a commitment to take that further, right? Start driving AAN, AI into the operations, if you will in everything that we do. So Anthem is transforming to do AI and machine learning for their members. We're committed to transforming and doing the same kind of thing on our operational side if you will. >> Yeah, that's awesome. And I think one of the things that's interesting that jumps out at me just as you're talking, first of all super exciting that project you got out there, a lot going on to unpack, but let's do that. I mean, what I hear you saying which is getting me kind of all triggered in a good way is you got transformation going on and innovation same time. You're innovating with this new enterprise hybrid clouds of service concept. You take in more efficiency, you're doing the classic transformational things, making things more efficient, all that good stuff for agility, but it's actually innovative. So this idea of an enterprise hybrid cloud as a service is pretty innovative because now you're talking about things with AI and scale that come into play, right? So you got the setup, you got it moving into being innovative but scales right there. What is this enterprise hybrid cloud as a service? Because is it just agility, is it the AI piece? Where do you see that going? >> Yeah, that's a great question. Right? And you're a great stuff, man, Johnson. (Smith laughs) So again, Anthem's not ready to move all of their workload to cloud, right? And we recognize (indistinct)is going to be out of the data center business. So how can we take non traditional workloads, right? Get them close to cloud, right? Get them very close to cloud, get us out of the managing the data center and actually allow us to move seamlessly from non traditional workloads into cloud. And so what we did was something we think is very innovative. This is the enterprise hybrid cloud piece for me, right? 'Cause normally hybrid cloud says, you have a client data center location and you have cloud. We marry the two together. We said, you're not going to have a data center location anymore. We're going to have our data centers, you know, IBM cloud. And we're actually going to put some dedicated space right next to cloud. And when I say next to cloud, I literally mean within a few feet. And we're going to bring these non traditional workloads there, we're going to take the network operation brain and bring it there. And we're going to allow you then to basically be able to move seamlessly from that to directly into cloud and improve operations at the same time. There's other a side benefit to this too. The other unintended sort of benefit is that what any organization, right? That you find stuff in the data center that hasn't been looked at for a long period of time, right? Application teams haven't looked at it, et cetera, et cetera. We're literally touching every single host. Right? So this gives us an opportunity to also work with our teams and find things that really can just be thrown away. Right? And this is great because we're actually making them more efficient, optimizing the cost structures as we go about it. >> Yeah. I mean the operational model changes me. You mentioned that just that whole point about you're kind of doing some discovery on apps, this becomes kind of sets the table for AI ops which is just code word for day two operations or full cloud native environments, which now you're seeing cloud native include legacy. Yes. Because you can put containers into the mix and you can then create these integration points that you don't have to kind of get rid of the old to bring in the new. So the dimension of what's going on here is pretty interesting, right? When you start thinking about that, "Okay. I can modernize the same time as connect two existing systems." >> That's exactly right. And we put the things very close to one another. And if there's any concerns over data security compliance or healthcare regulated industry, of course, we can have the workloads located in the best location to ensure that security is in place. Right? So that's what's beautiful about it, right? We can kind of hit every layer that's possible from having it just as secure as completely privatized to going directly over to public cloud or connecting the two together as we go along. >> Well, you're definitely a pioneer. I love that enterprise hybrid cloud as a service. I think that's something that's relevant. We're living in a hybrid world. I mean, the cube, we used to go to events now it's virtual events, but when now the events come back, they're hybrid events. Every company is experiencing this phenomenon on hybrid something, not just technology. The ops got to adapt, so super cool. You mentioned something that was your baby. I want to get back to you. And you said you want to talk about, I want to just bring that up. This Anthem technology excellence center is your baby. ATech I think you said for short. >> Yeah. We call it Atech for short. And really, John, we said that it's got to be more than just taking that other 20% that we don't run today. And we're doing some very innovative things moving non-traditional workloads. Like I said, all that kind of stuff was very cool, right? But we need a transformation engine, right? And we need the ability to transform skills. Like upscale the people at Anthem as well as IBM, right there on the account team, it's a big account. We want to think of new ways to work together. Right? Traditional managed services is like, what? Someone cuts a ticket and says, "Give me X by her seat." Right? That's the traditional model. And we said, that's not good enough. We need to collaborate better together. And we are willing to redefining how we form our teams to work with Anthem. Right? So if we want to form, for example, a product ownership team that builds it, runs it, maintains it. And that team has Anthem plus IBM together. we're going to use ATEC as a vehicle to design that and drive it and make sure they have all the skills they need within that group to do that. Right? That's new ways of working together. And it's also to drive things like site reliability engineering, right? Cloud service management operations, make sure that Anthem has the right training, make sure we work together on these kinds of things. So it's really kind of an exciting thing. And it's intended to be a co-created model, right? So we actually work with the Anthem, we co-create using IBM garage methodologies and then the idea is to coast staff it, but it's tended to be a thin layer of world-class engineering. That's really the whole point of it. And yeah, I'm super excited about that. As you move forward, yeah. >> While you're speaking our language, the cube we'd love the co-creation we do with media. It's always fun to create content together. And sometimes in real time put it together like we're doing now. And it creates a bond. I mean, I got to bring this up because this is becoming more and more obvious. And now mainstream, the notion of co-creation, the notion of ecosystems and ecosystems really meaning network effect and integrating with other parties, right? Companies and our systems. If you look at the underlying business model as a systems management software bottle. Okay. So with that, these ecosystems, the network effect. If you build together, you stay together. I mean, this is a different mindset. It's different dynamic. It's a different relationship that companies are now looking for in what used to be called suppliers. Are you supplying something? Are you building together? Right. So this seems to be the theme. Can you expand on this new trend? >> Right. And get away from the strict racing, this person does, this person does that. Instead, we build a team together that has all the skills necessary and that team owns a product life cycle. They build it, run it and maintain it. And that's changing the way we deliver services from IBM perspective significantly, right? Because that's not our traditional model but that's what we're doing. So we're really out in the front end, on the front edge if you will. Changing that model completely. And it's one of the most exciting things for me, you know, as far as going forward. >> You know, this whole idea of partnerships has always kind of been there but now it gets modernized and uplifted if you will, to a new level. And it really is about watching each other's backs too when you have that kind of... 'Cause we're talking about like pushing the envelope on probably the biggest confluence of tech trends I've ever seen in my career. And I've seen many big waves, you know, from the different revolutions and inflection points. Now it's sort of all coming together, right? At scale too, it's happening very fast. I mean, the change over is happening in years that once you took decades before. So it's really is a team approach. >> Yeah. There's no doubt about it. And I see it every day in the work we're doing. And it's like, for example, at Atech where we're working with the data scientists at the Anthem, we're thinking of new ways to build things they've never done before. We're hoping to enable their science, enable the things they want to do for digitization standpoint, the same token I'm taking, you know, a data scientist and putting them on the operation side too. Right? So we're doing both these kinds of things together. And really I didn't say this before, but this whole thing is about driving automation, right? Driving down, no human touch, soft service, automation. That is kind of been the linchpin of this. And I also want to say John, that doing this all during a pandemic, you know, we signed our new agreement together with them at a quarter, at the end of March in 2020. And we went live in August 1st with all the changes, the extra 20% capacity to over 300 plus applications completely, started Atech from co-creation in a pandemic. And we both agreed as a company, I give great credit to our client and to the numbers involved that everyone set up front and during March. The pandemic's not an excuse to get anything done. So, we're going to go forward and make it happen. That's probably the thing I'm most proud about. That was just... It's crazy when you think of how big the project was and do pull it off during a pandemic. >> Yeah. There's going to be two sides of the street and this one, this pandemics over the ones who made it through and refactored and or innovated. Cause it's not just about being and having a tale, it's about taking advantage of the situation and the ones who didn't do anything. Whether they were in the cloud or not, that's not to me. That's not the issue of you're in the cloud you had an advantage. >> It's not. Right. >> But there's going to be two sides of the streets. And I think the one thing that the pandemic has shown us and I'd love to get your reaction as a final comment here is that when you pull back when the pandemic, it showed all the scabs, it shows everything. And you can see what's obvious and it becomes a forcing function. Necessity's the mother of all invention as expression goes so you can see what's worth doubling down on and you can see the productivity gains and that becomes clear. >> Yeah. Yeah. And I think there's good and bad with everything, right? Pros and cons, like you said, and you know, one of the cons I think is the having to schedule all interactions is definitely a con, right? Because when you spend time not only with the client virtually but in person, you do get the advantage of having, you know, chalk talks and things like that. They're not scheduled. Right? So that's definitely one of the cons side, but one of the pro side is it did provide some focus, right? Kind of extreme focus and on what's important and allowed us to, you know, I think dove some bonds with the Anthem leadership team and the application teams doing it virtually over cameras like this that maybe happen at a larger scale than they might have normally been because the pandemic kind of allowed us to do that and made that happen. >> Great stuff, Rick, great insight. Great to have you on the cube as always. Great to talk tech, talk business, talk about the transformation and innovation and the cloud scale. Thanks for coming on Rick Smith, CTO of the IBM Anthem client team. Thanks for coming on the cube. >> You're welcome. Thanks John. >> Okay. Cube coverage of IBM Think 2021. I'm John. For your host of the cube. Thanks for watching. (soft music) (upbeat music)