>>Like for Las Vegas, Nevada, that's the cue governor AWS reinvent 2016, brought to you by AWS and its ecosystem partners. Now, here are your hosts, John furrier and Stu minimum. >>We are here, live in Las Vegas with the cube all week. I'm John minimum. We are breaking down all the re-invent coverage. The cube is going on for three days. Um, Stu and I are going to break down here and studio B the analysis of Andy Jassy, his keynote. This is really day one of the event yesterday was kind of a preview at James Hamilton. Uh, Tuesday evening, I had a great band up there. Uh, and then he came on and delivered a really an Epic performance laying out as a, he's not a showman in the sense of, uh, uh, Steve jobs like, but he has a Steve jobs like cred, uh, James Hamilton, when it comes to the gigs in the community, he delivered the, what I call the secret sauce with AWS as data centers. And then Andy Jassy today with his keynote again is so high pack. >>They start at 8:00 AM, which is kind of not usual for events with so much to up their pack. Councilor came on stage AI Stu. First, I want to get your take on today's keynote with Andy Jassy. You were in the front row. What was going on inside the room? Tip, tell us your perspective, give us the vibe. What was the energy level and what was, what was it like? Yeah. John, as you said, starting at 8:00 AM, it's like a up, we must be talking to the tech audience because developers usually like to start a little bit later than that. Um, it was an embarrassment of riches. Uh, Andy gets on stage, as he told you, when you met with him up at his home in Seattle, uh, they've got, they're going to have about a thousand, you know, major new features updates. Uh, and you know, I think Andy went through a couple of hundred of them up on stage. >>Uh, you know, this is a group of true believers pack. Keynote people started streaming in over an hour ahead of time because only 10,000 could fit in the main tent. They had other remote locations where you could go get, you know, mimosas, bloody Marys or coffee. Uh, if you wanted to watch us, all over that. But it, it, it just to tell you, my fourth year here at the show and it's like, Oh yeah, another tech show. You're going to get keynotes. They're going to make some announcements yawn, no Amazon impresses every year. And they delivered this year. Andy might not be a showman, but you know, he was punching at a, you know, Larry Ellison and Oracle quite a bit. He got huge ovations. Like every time they announced a new compute instance, uh, in lots of these things, uh, and a little bit of show flare, uh, at the end, uh, certainly the going into the database market. >>Uh, but also they're making some really good infrastructure enhancements with the new services. What was your highlight if you're going to look at what the most significant, most important story this morning, what, what was squinting through all the great announcements? What ones you liked best? Oh boy. John, I have to pick one. I mean, here, here's a few number one is, you know, there's, there's some pushback from people in the community that, Oh, you know, they announced another ton of news, you know, compute instances, there's all these different storage configurations. Uh aren't we supposed to be making things simple. Uh, and that's when they had a one Amazon LightSail, which is the virtual private servers in seconds really goes after, you know, kind of a, you know, simple, low cost model, uh, really digital ocean's the leader in that space starting at like $5 a month, John, uh, you know, very exciting. A lot of people, uh, you know, really getting, uh, you know, as to where this could go every year, Amazon has a number of competitors that they're just like up, we see this opportunity. We can go after this. And John, this is not a high margin business. I mean, usually it's like, Oh, okay, database. I understand there's huge margin there. The storage market, of course, LightSail $5 a month. I mean, you know, they make it up in volume, but it's super fast. >>It was on a playbook. It drive the price down as low as possible, and then shift the value with the analytics. Um, and, uh, Aurora PA um, um, uh, pack housing or any chassis said fastest growing service in the history of Amazon last year, he said red shift was that this surpass red shift, uh, the announced Postgres equal on a roar, another big significant customer request. Um, just on and on the database seems to be the lock-in spec that they're trying to undo from Oracle. Um, they're not stopping. I mean, the rhetoric was all time high, John, the picture Larry Ellison popped out, popped in the Oracle. Oh, in the, in, in the O >>We know the long pole in the tent for enterprises is the applications you have making any changes in that, uh, doing any refactoring, you know, tinkering, you know, those are hard things to do. Um, but you know, we've heard a lot from Amazon this week as to how they're helping with migration, how they're giving options, how they're giving bridges, uh, things like VMware on AWS to bridge over from where you are, you know, you can lift and shift it. You can move it, you can rewrite it, lots of options there. Uh, and Amazon just has so many services and so many customers, thousands of systems integrators, uh, you know, thousands of ASVs, uh, and really big enterprises, you know, making statements up on stage. When you get Workday up on stage, John, you get McDonald's up on stage. Uh, you know, it's impressive. >>Some big name accounts, no doubt about it. That's do I want to get your thoughts on James Hamilton? Again, Amazon's got some of the announcements. I mean, some companies will launch entire conference keynote around maybe one or two of what they've done out of the many that they've had here also to note, there's been over 150 partner announcements. So the ecosystems do before we get to Hamilton, I want to talk about the ecosystem. This feels a lot like 2011, VMware. I was kind of joking with Sanjay Poonen the CEO of VMware was just on the cube with us and saying, what do you think about VMworld this year? I mean, re-invent, I was kind of tongue in cheek. I wanted to zinc them a little bit, but stew, this feels like, >>So John, I'm an infrastructure guy, and I want to talk about James Hamilton. One thing we got to cover first green grass. I, you know, green grass is how Amazon is taking their serverless architecture, really Lambda and taking it beyond the cloud. So how do I get, you know, that, that kind of hybrid edge, we talked about it a little bit with Sanjay, but number one, I can start pulling VMware into AWS. Number two, I can now get, you know, my Lambda services, uh, out on the edge, they talked about some IOT plays on, they talked about the snowball edge, uh, which is going to allow me to have kind of compute and storage, uh, down at that edge. Uh, I've seen huge excitement at this show, uh, on the serverless piece developers, it's really quick to work with, uh, twenty-five thousand Amazon echo dots were handed out and I've already talked to people that are already, you know, writing functions for that and figuring out how to can play with it. And God, we haven't even talked about the AI, John with voice and images. How many hours do we have John? >>I we'll get there. Let's stay on green grass for a minute, because if you think about what that's about, I want to get your thoughts on your thoughts on the impact of green grass. I mean, obviously the lamb done, that's got a little edge piece of snowball tied to it. Uh, you know, green grass and high ties forever. The old song by, you know, Southern rock band Outlaws back in the day, this is a significant announcement. What is the impact of that? >>Yeah, well, John, I mean the grass is greener in the cloud, right? So now we're going to bring the green grass, >>No ball when it snowball, my melts extends in the green grass. >>So we're going to be riffing all day on this stuff. So David foyer, uh, our CTO at Wiki bond has been talking for awhile, uh, that, you know, while cloud is great for data, the problem we have is that IOT is going to have most of the, you know, most of the data out on the edge. And we know the physics of moving large amounts of data is really tough. And especially if it's spread out things like sensors, things like wind farms, getting the networking to that last mile can be difficult. That's where things like green grass are going to be able to play in. How can I take really that cloud type of compute and put it on the edge. It really has potential to be a real game changer. I think John, we talked about what hybrid means, uh, and you know, we'll, we'll see a lot, a lot of buzz in the industry about what Microsoft's doing with Azure stack, uh, and you know, lots of pieces, but you know, grass, you know, it gives this new model of programming. It gives the developers, uh, it gives me, you know, I can use the arm processors, uh, out on the edge and, you know, we could try and talk about how that fits with James Hamilton too. >>We are inside the hall next to the cube studio, being so much content. We have to actually set up a separate set. Stu I want to get your thoughts on, I mean, obviously we can go on forever, but the significant innovation on multiple fronts for Amazon, you mentioned Greengrass, snowball, multiple instances. Um, and certainly they got all the analytics on Bubba, the top of the stack with Redshift and other stuff. And he says, streaming goes on and on the list goes on and on, but you look at what they're doing with Greengrass and snowball. And then you go look at what James Hamilton talked about yesterday. Now they're going down an innovating down to the actual physical chip level. They're doing stuff with the network routes, the control in the packet there, no one's touching the packets. They are significantly building the next global infrastructure backbone for themselves to power the world. This is, to me, I thought a subtle talk that James gave. There's a ton of nuance in there. Your thoughts on last, night's a really Epic presentation. I know we're gonna have a sit down exclusive interview with James Hamilton with Rob Hoff, our new editor in chief Silicon angle, but still give us a preview. What blew you away? What got you excited? I mean, it was certainly a geek dream. >>Yeah. I mean, John, you know, James Hamilton is just one of those. You talk about tech athletes, you know, just the, the real heroes in this space, uh, that so many of us look up to, uh, it's been one of the real pleasures of my career working, uh, with the cube that I've gotten to speak to James a few times. Uh, and the first article I wrote three years ago, uh, about what James Hamilton has done is it's hyper optimization. The misconception that people had about cloud is, Oh, it's just a white box. They're taking standard stuff, Amazon. And what James always talks about is how to, you know, really grow and innovate at scale. And that means they build for their environments and they really get down to every piece of the environment, all the software, all the hardware, they either customize it or make their own. So, you know, the big monitor >>And Stu to your point for their own use cases, the home, a prime Fridays and those spike days, he was talking about how they would have to provision months and months in advance to add, to understand some estimated peak that they were spinning up, literally thousands of servers. >>Yeah. So John, you know, Amazon doesn't make a lot of acquisitions, but one that they made is Annapurna labs. So they've got their own custom Silicon that they're making. Uh, so this will really allows them to control, uh, how they're doing their build-out. They can focus on things like performance. Uh, James talked about, uh, you know, how they're, they're really innovating on the network side. He was very early with 25 gigabit ethernet, uh, which really drove down. Some of the costs, gave them huge bandwidth advantages, uh, and kind of leading the way in the industry. Uh, the, the, the thing we've been poking out a bit is while Amazon leverages a lot of open source, they don't tend to give back as much. Uh, they've got the big MX net announcement as to how they're going to be involved in, in the machine learning. And that's good to see they hired Adrian Cockcroft, uh, you know, who lots of us knew from his Netflix days. Uh, and when he was a venture capitalist, he's going to be driving a lot of the open source activity. But James, you know, kind of went through everything from, >>By the way, on your point about source, I set it on the cube and I'll say it again. And you Mark my words. If Amazon does not start thinking about the open source equation, they could see a revolt that no one's ever seen before in the tech industry. And that is the open source community. Now as a tier one, it has been for a long time tier one contributor to innovation, and as a difference between using open source for an application like Facebook and a specific point application or Google for search, if you are building open source to build a company, to take territory from others, there will be a revolts. Do you, John, do you agree? Am I off, >>Uh, revolt might be a little strong, but absolutely. We already see some pushback there. And anytime a company gets large power in the marketplace, you see pushback. We saw it with Oracle, with salt, with Microsoft, we see it with VMware. Uh, so you know, and I think Amazon, here's this point, uh, Andy Jassy talks about how they're making meaningful contributions. I expect Adrian, uh, to make that much more visible. Um, we'll have to get into some of the James Hamilton stuff at a later date, but >>Down with him with Rob posts more on that later, you and I will hit James Hamilton analysis on the key later final thoughts you were giving me some help before we came on to talk here about me saying, I'm bullish on VMware's relationship with AWS. And you said, really? And I said, I am because I am a big fan of VMware, um, also AWS, but for their customers, for AI, for VMware customers, this is a good thing. Now you might have some thoughts on execution. Maybe what's your, why? Why did you roll your eyes when I said that? >>So, John, I mean, you know, I've lots of love for the VMware community. Uh, you know, spent lots of time in that space. Uh, and it, it's good to see, uh, VMware working with the public clouds. However, uh, I think the balance of power Shilton shifts in the side of Amazon being in control here. Uh, and you know, there's a lot of nuance. Where are the services where the value is what's going to be good for customer. Amazon's really good at listening. Uh, and you know, this embarrassment of riches that they do, right? >>A real summary, what bottom line, what happened this morning and your mind abstracted all the way in one soundbite, wait, >>They rolled a truck out, out stage, John, this snowmobile a hundred terabytes, a hundred petabytes of storage and a terabyte of information. Something that, you know, we were like, this is amazing. It's it's the, the maturation of the hybrid message is different from what people have been talking about hybrid, uh, you know, where SAS lives, all the ISV is. Where's the data, where's the application. Amazon's in a really good position. John, there's a big and growing ecosystem here. Uh, but there's a huge battles that I know we're going to get into, uh, out in the marketplace. You know, who's going to win voice, uh, you know, everybody's their apples, their Microsoft, >>Because everyone's jocking for position. Got Google, you got Oracle, you've got IBM. You've got Microsoft all looking at AWS and saying, how do we change the game on them? And we'll be covering this. The cute we are here in Las Vegas studio B cube three days of wall-to-wall Cubs, I'm Jeffers do minimum, breaking it down on day one, keynotes and analysis. Thanks for watching. We'll be right back. Stay tuned to the cube cube siliconangle.tv. You go to siliconangle.com for all the special exclusive stories from re-invent specifically to, with Andy Jassy, James Hamilton, and more thanks for watching.

(gentle, upbeat music) >> Live from the Sands Convention Center in Las Vegas, Nevada, it's theCUBE, at AWs re:Invent 2014. Brought to you by headline sponsors Amazon and Trend Micro. >> Okay, welcome back everyone, we are here live at Amazon Web Services re:Invent 2014, this is theCUBE, our flagship program, where we go out to the events and extract synth from the noise. I'm John Furrier, the Founder of SiliconANGLE, I'm joined with my co-host Stu Miniman from wikibon.org, our next guest is James Hamilton, who is Vice President and Distinguished Engineer at Amazon Web Services, back again, second year in a row, he's a celebrity! Everyone wants his autograph, selfies, I just tweeted a picture with Stu, welcome back! >> Thank you very much! I can't believe this is a technology conference. (laughs) >> So Stu's falling over himself right now, because he's so happy you're here, and we are too, 'cause we really appreciate you taking the time to come on, I know you're super busy, you got sessions, but, always good to do a CUBE session on kind of what you're workin' on, certainly amazing progress you've done, we're really impressed with what you guys've done other this last year or two, but this year, the house was packed. Your talk was very well received. >> Cool. >> Every VC that I know in enterprise is here, and they're not tellin' everyone, there's a lot of stuff goin' on, the competitors are here, and you're up there in a whole new court, talk about the future. So, quickly summarize what you talked about in your session on the first day. What was the premise, what was the talks objective, and what was some of the key content? >> Gotcha, gotcha. My big objective was the cloud really is fundamentally different, this is not another little bit of nomenclature, this is something that's fundamentally different, it's going to change the way our industry operates. And what I wanted to do was to step through a bunch of examples of innovations, and show how this really is different from how IT has been done for years gone by. >> So the data center obviously, we're getting quotes after quotes, obviously we're here at the Amazon show so the quotes tend to be skewed towards this statement, but, I'm not in the data center business seems to be the theme, and, people generally aren't in the data center business, they're doing a lot of other things, and they need the data centers to run their business. With that in mind, what are the new innovations that you see coming up, that you're working on, that you have in place, that're going to be that enabler for this new data center in the cloud? So that customers can say hey, you know, I just want to get all this baggage off my back, I just run my business agile and effectively. Is it the equipment, is it the software, is it the chips? What're you doing there from an innovation standpoint? >> Yeah, what I focused on this year, and I think it's a couple important areas are networking, because there's big cost problems in networking, and we've done a lot of work in that area that we think is going to help customers a lot; the second one's database, because databases, they're complicated, they're the core of all applications, when applications run into trouble, typically it's the database at the core of it, so those are the two areas I covered, and I think that's two of the most important areas we're working right now. >> So James, we've looked back into people that've tried to do this services angle before, networking has been one of the bottlenecks, I think one of the reasons XSBs failed in the '90s, it was networking and security, grid computing, even to today. So what is Amazon fundamentally doing different today, and why now is it acceptable that you can deliver services around the world from your environment? What's different about networking today? >> It's a good question. I think it's a combination of private links between all of the regions, every major region is privately linked today. That's better cost structure, better availability, lower latency, scaling down to the data center level we run all custom Amazon designed gear, all custom Amazon designed protocol stacks. And why is that important? It's because cost of networking is actually climbing, relative to the rest of compute, and so, we need to do that in order to get costs under control and actually continue to be able to draw up costs. Second thing is customers need more networking-- more networking bandwidth per compute right now, it's, East/West is the big focus of the industry, because more bandwidth is required, we need to invest more, fast, that's why we're doing private gear. >> Yeah, I mean, it's some fascinating statistics, it's not just bandwidth, you said you do have up to 25 terabytes per second between nodes, it's latency and jitter that are hugely important, especially when you go into databases. Can you talk about just architecturally, what you do with availability zones versus if I'm going to a Google or a Microsoft, what does differentiate you? >> It is a little bit different. The parts that are the same are: every big enterprise that needs highly available applications is going to run those applications across multiple data centers, that's, so-- The way our system works is you choose the region to get close to your users, or to get close to your customers, or to be within a jurisdictional boundary. From down below the region, normally what's in a region is a data center, and customers usually are replicating between two regions. What's different in the Amazon solution, is we have availability zones within region; each availability zone is actually at least one data center. Because we have multiple data centers inside the same region it enables customers to do realtime, synchronous replication between those data centers. And so if they choose to, they can run multi-region replication just like most high end applications do today, or, they can run within an AZ, synchronous multiplication to multiple data centers. The advantage of that, is it takes less administrative complexity, if there's a failure, you never lose a transaction, where in multi-region replication, it has to be asynchronous because of the speed of light. >> Yeah, you-- >> Also, there's some jurisdictional benefits too, right? Say Germany, for instance, with a new data center. >> Yep. Yeah, many customers want to keep their data in region, and so that's another reason why you don't necessarily want to replicate it out in order to get that level of redundancy, you want to have multiple data centers in region, 100% correct >> So, how much is it that you drive your entire stack yourself that allows you to do this, I think about replication solutions, you used SRDF as an example. I worked for that, I worked for EMC for 10 years, and just doing a two site replication is challenging, >> It's hard. >> A multi site is differently, you guys, six data centers and availabilities on a bungee, you fundamentally have a different way of handling replication. >> We do, the strategy inside Amazon is to say multi-region replication is great, but because of the latency between regions, they're a long way apart, and the reality of speed of light, you can't run synchronous. If data centers are relatively close together in the same region, the replication can be done synchronously, and what that means is if there's a failure anywhere, you lose no transactions. >> Yeah. So, there was a great line you had in your session yesterday, that networking has been anti-Moore's law when it comes to pricing. Amazon is such a big player, everybody watches what you do, you buy from the ODMs, you're changing the supply chain. What's your vision as to where networking needs to go from a supply chain and equipment standpoint? >> Networking needs to be the same place where servers went 20 years ago, and that is: it needs to be on a Moore's law curve where, as we get more and more transistors on a chip, we should get lower and lower costs in a server, we should get lower and lower costs in a network. Today, an ASIC is always, which is the core of the router, is always around the same price. Each generation we add more ports to that, and so effectively we got a Moore's law price improvement happening where that ASIC stays the same price, you just keep adding ports. >> So, I got to jump in and ask ya about Open Compute, last year you said it's good I guess, I'm a fan, but we do our own thing, still the case? >> Yeah, absolutely. >> Still the case, okay doing your own thing, and just watching Open Compute which is a like a fair for geeks. >> Open Compute's very cool, the thing is, what's happening in our industry right now is hyper-specialization, instead of buying general purpose hardware that's good for a large number of customers, we're buying hardware that's targeted to a specific workload, a specific service, and so, we're not--I love what happens with Open Compute, 'cause you can learn from it, it's really good stuff, but it's not what we use; we want to target our workloads precisely. >> Yeah, that was actually the title of the article I wrote from everything I learned from you last year was: hyper-specialization is your secret sauce, so. You also said earlier this week that we should watch the mobile suppliers, and that's where service should be in the future, but I heard a, somebody sent me a quote from you that said: unfortunately ARM is not moving quite fast enough to keep up with where Intel's going, where do you see, I know you're a fan of some of the chip manufacturers, where's that moving? >> What I meant with watch ARM and understanding where servers are going, sorry, not ARM, watch mobile and understand where servers is going is: power became important in mobile, power becomes important in servers. Most functionalities being pulled up on chip, on mobile, same thing's happening in server land, and so-- >> What you're sayin' is mobile's a predictor >> Predicting. >> of the trends in the data center, >> Exactly, exactly right. >> Because of the challenges with the form factor. >> It's not so much the form factor, but the importance of power, and the importance of, of, well, density is important as well, so, it turns out the mobile tends to be a few years ahead, but all the same kinds of innovations that show up there we end up finding them in servers a few years later. >> Alright, so James, we've been, at Wikibon have a strong background in the storage world, and David Floyer our CTO said: one of the biggest challenges we had with databases is they were designed to respond to disk, and therefore there were certain kind of logging mechanisms in place. >> It's a good point. >> Can you talk a little bit about what you've done at Amazon with Aurora, and why you're fundamentally changing the underlying storage for that? >> Yeah, Aurora is applying modern database technology to the new world, and the new world is: SSDs at the base, and multiple availability zones available, and so if you look closely at Aurora you'll see that the storage engine is actually spread over multiple availability zones, and, what was mentioned in the keynote, it's a log-structured store. Log-structured stores work very very nicely on SSDs, they're not wonderful choices on spinning magnetic media. So this, what we're optimized for is SSDs, and we're not running it on spinning disk at all. >> So I got to ask you about the questions we're seeing in the crowd, so you guys are obviously doing great on the scale side, you've got the availability zones which makes a lot of sense certainly the Germany announcement, with the whole Ireland/EU data governance thing, and also expansion is great. But the government is moving fast into some enterprises, >> It's amazing. >> And so, we were talking about that last night, but people out there are sayin' that's great, it's a private cloud, the governments implementing a private cloud, so you agree, that's a private cloud or is that a public-- >> (laughing) It's not a private cloud; if you see Amazon involved, it's not a private cloud. Our view of what we're good at, and the advantages cloud brings to market are: we run a very large fleet of servers in every region, we provide a standard set of services in all those regions, it's completely different than packaged software. What the CIA has is another AWS region, it happens to be on their site, but it is just another AWS region, and that's the way they want it. >> Well people are going to start using that against you guys, so start parsing, well if it's private, it's only them then it's private, but there's some technicalities, you're clarifying that. >> It's definitely not a private cloud, the reason why we're not going to get involved with doing private clouds is: product software is different, it's innefficient, when you deliver to thousands of customers, you can't make some of the optimizations that we make. Because we run the same thing everywhere, we actually have a much more reliable product, we're innovating more quickly, we just think it's a different world. >> So James, you've talked a lot that scale fundamentally changes the way you architect and build things; Amazon's now got over a billion customers, and it's got so many services, just adding more and more, Wikibon, actually Dave Vellante, wrote a post yesterday said that: we're trying to fundamentally change the economic model for enterprise IT, so that services are now like software, when Microsoft would print an extra disk it didn't cost anything. When you're building your environment, is there more strain on your environment for adding that next thousand customers or that next big service or, did it just, do you have the substrate built that's going to help it grow for the future? >> It's a good question, it varies on the service. Usually what happens is we get better year over year over year, and what we find is, once you get a service to scale, like S3 is definitely at scale, then growth, I won't say it's easy, but it's easier to predict because you're already on a large base, and we already know how to do it fairly well. Other services require a lot more thought on how to grow it, and end up being a lot more difficult. >> So I got some more questions for ya, go on to some of the personal questions I want to ask you. Looking at this booth right here, it's Netflix guys right there, I love that service, awesome founder, just what they do, just a great company, and I know they're a big customer. But you mentioned networks, so at the Google conference we went to, Google's got some chops, they have a developer community rockin' and rollin', and then it's pretty obvious what they're doin', they're not tryin' to compete with Amazon because it's too much work, but they're goin' after the front end developer, Rails, whatnot, PHP, and really nailing the back end transport, you see it appearing, really going after to enable a Netflix, these next generation companies, to have the backbone, and not be reliant on third party networks. So I got to ask you, so as someone who's a tinkerer, a mechanic if you will of the large scale stuff, you got to get rid of that middleman on the network. What's your plans, you going to do peering? Google's obviously telegraphing they're comin' down that road. Do you guys meet their objective? Same product, better, what's your strategy? >> Yeah, it's a great question. The reason why we're running private links between our regions is the same reason that Google is, it's lower cost, that's good, it's much, much lower latency, that's really good, and it's a lot less jitter, and that's extremely important, and so it's private links, peering, customers direct connecting, that's all the reality of a modern cloud. >> And you see that, and do you have to build that in? Almost like you want to build your own chips, I'd imagine on the mobile side with the phone, you can see that, everyone's building their own chips. You got to have your own network stuff. Is that where you guys see the most improvement on the network side? Getting down to that precise hyper-specialized? >> We're not doing our own chips today, and we don't, in the networking world, and we don't see that as being a requirement. What we do see as a requirement is: we're buying our own ASICs, we're doing our own designs, we're building our own protocol stack; that's delivering great value, and that is what's deployed, private networking's deployed in all of our data centers now >> Yeah, I mean, James I wonder, you must look at Google, they do have an impressive network, they've got the undersea cables, is there anything you, that you look at them and saying: we need to move forward and catch up to them on certain, in certain pieces of the network? >> I don't think so, I think when you look at any of the big providers, they're all mature enough that they're doing, at that level, I think what we do has to be kind of similar. If private links are a better solution, then we're all going to do it, I mean. >> It makes a lot of sense, 'cause it, the impact on inspection, throttling traffic, that just creates uncertainty, so. I'm a big fan, obviously, of that direction. Alright, now a personal question. So, in talking to your wife last night, getting to know you over the years here, and Stu is obviously a big fan. There's a huge new generation of engineers coming into the market, Open Compute, I bring that up because it's such a great initiative, you guys obviously have your own business reasons to do your own stuff, I get that. But there's a whole new culture of engineering coming out, a new home brew computer club is out there forming right now my young son makes his own machines, assembling stuff. So, you're an inspiration to that whole group, so I would like you to share just some commentary to this new generation, what to do, how to approach things, what you've learned, how do you come over, on top of failure, how do you resolve that, how do you always grow? So, share some personal perspective. >> Yeah, it's an interesting question. >> I know you're humble, but, yeah. >> Interesting question. I think being curious is the most important thing possible, if anybody ever gets an opportunity to meet somebody that's the top of any business, a heart surgeon, a jet engine designer, an auto mechanic, anyone that's in the top of their business is always worth meeting 'cause you can always learn from them. One of the cool things that I find with my job is: because it spans so many different areas, it's amazing how often I'll pickup a tidbit one day talking to an expert sailor, and the next day be able to apply that tidbit, or that idea, solving problems in the cloud. >> So just don't look for your narrow focus, your advice is: talk to people who are pros, in whatever their field is, there's always a nugget. >> James a friend of mine >> Stay curious! >> Steve Todd, he actually called that Venn diagram innovation, where you need to find all of those different pieces, 'cause you're never going to know where you find the next idea. So, for the networking guys, there's a huge army of CCIEs out there, some have predicted that if you have the title administrator in your name, that you might be out of a job in five years. What do you recommend, what should they be training on, what should they be working toward to move forward to this new world? >> The history of computing is one of the-- a level of abstraction going up, never has it been the case those jobs go away, the only time jobs have ever gone away is when someone stated a level of abstraction that just wasn't really where the focus is. We need people taking care of systems, as the abstraction level goes up, there's still complexity, and so, my recommendation is: keep learning, just keep learning. >> Alright so I got to ask you, the big picture now, ecosystems out here, Oracle, IBM, these big incumbents, are looking at Amazon, scratching their head sayin': it's hard for us to change our business to compete. Obviously you guys are pretty clear in your positioning, what's next, outside of the current situation, what do you look at that needs to be built out, besides the network, that you see coming around the corner? And you don't have to reveal any secrets, just, philosophically, what's your vision there? >> I think our strategy is maybe a little bit, definitely a little bit different from some of the existing, old-school providers. One is: everyone's kind of used to, Amazon passes on value to customers. We tend to be always hunting and innovating and trying to lower costs, and passing on the value to customers, that's one thing. Second one is choice. I personally choose to run my XQL because I like the product I think it's very good value, some of our customers want to run Oracle, some of our customers want to run my XQL, and we're absolutely fine doing that, some people want to run SQL server. And so, the things that kind of differentiate us is: enterprise software hasn't dropped prices, ever, and that's just the way we were. Enterprise software is not about choice, we're all about choice. And so I think those are the two big differences, and I think those ones might last. >> Yeah, that's a good way to look at that. Now, back to the IT guy, let's talk about the CIO. Scratchin' his head sayin': okay, I got this facilities budget, and it's kind of the-- I talked to once CIO, hey says: I spend more time planning meetings around facilities, power, and cooling, than anything else on innovation, so. They have challenges here, so what's your advice, as someone who's been through a lot of engineering, a lot of large scale, to that team of people on power and cooling to really kind of go to the next level, and besides just saying okay throw some pots out there, or what not, what should they be doing, what's their roadmap? >> You mean the roadmap for doing a better job of running their facilities? >> Yeah, well there's always pressure for density, there's power's a sacred (laughs) sacred resource right now, I mean power is everything, power's the new oil, so, power's driving everything, so, they have to optimize for that, but you can't generate more power, and space, so, they want smaller spaces, and more efficiency. >> The biggest gains that are happening right now, and the biggest innovations that have been happening over the last five years in data centers is mostly around mechanical systems, and driving down the cost of cooling, and so, that's one odd area. Second one is: if you look closely at servers you'll see that as density goes up, the complexity and density of cooling them goes up. And so, getting designs that are optimized for running at higher temperatures, and certified for higher temperatures, is another good step, and we do both. >> So, James, there's such a diverse ecosystem here, I wonder if you've had a chance to look around? Anything cool outside of what Amazon is doing? Whether it's a partner, some startup, or some interesting idea that's caught your attention at the show. >> In fact I was meeting with western--pardon me, Hitachi Data Systems about three days ago, and they were describing some work that was done by Cycle Computing, and several hundred thousand doors-- >> We've had Cycle-- >> Jason came on. >> Oh, wow! >> Last year, we, he was a great guest. >> No, he was here too, just today! >> Oh, we got him on? Okay. >> So Hitachi's just, is showing me some of what they gained from this work, and then he showed me his bill, and it was five thousand six hundred and some dollars, for running this phenomenally big, multi-hundred thousand core project, blew me away, I think that's phenomenal, just phenomenal work. >> James, I really appreciate you coming in, Stu and I really glad you took the time to spend with our audience and come on theCUBE, again a great, pleasurable conversation, very knowledgeable. Stay curious, and get those nuggets of information, and keep us informed. Thanks for coming on theCUBE, James Hamilton, Distinguished Engineer at Amazon doing some great work, and again, the future's all about making it smaller, faster, cheaper, and passing those costs, you guys have a great strategy, a lot of your fans are here, customers, and other engineers. So thanks for spending time, this is theCUBE, I'm John Furrier with Stu Miniman, we'll be right back after this short break. 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(mellow electronic music) >> Welcome back, we're here live in Las Vegas. This is SiliconANGLE and Wikibon's theCUBE, our flagship program. We go out to the events, extract the signal from the noise. We are live in Las Vegas at Amazon Web Services re:Invent conference, about developers, large-scale cloud, big data, the future. I'm John Furrier, the founder of SiliconANGLE. I'm joined by co-host, Dave Vellante, co-founder of Wikibon.org, and our guest is James Hamilton, VP and Distinguished Engineer at Amazon Web Services. Welcome to theCUBE. >> Well thank you very much. >> You're a tech athlete, certainly in our book, is a term we coined, because we love to use sports analogies You're kind of the cutting edge. You've been the business and technology innovating for many years going back to the database days at IBM, Microsoft, and now Amazon. You gave a great presentation at the analyst briefing. Very impressive. So I got to ask you the first question, when did you first get addicted to the notion of what Amazon could be? When did you first taste the Cool-Aide? >> Super good question. Couple different instances. One is I was general manager of exchange hosts and services and we were doing a decent job, but what I noticed was customers were loving it, we're expanding like mad, and I saw opportunity to improve by at least a factor of two I'm sorry, 10, it's just amazing. So that was a first hint that this is really important for customers. The second one was S3 was announced, and the storage price pretty much froze the whole industry. I've worked in storage all my life, I think I know what's possible in storage, and S3 was not possible. It was just like, what is this? And so, I started writing apps against it, I was just blown away. Super reliable. Unbelievably priced. I wrote a fairly substantial app, I got a bill for $7. Wow. So that's really the beginnings of where I knew this was going to change the world, and I've been, as you said, addicted to it since. >> So you also mentioned some stats there. We'll break it down, 'cause we love to talk about the software defined data center, which is basically not even at the hype stage yet. It's just like, it's still undefined, but software virtualization, network virtualization really is pushing that movement of the software focus, and that's essentially you guys are doing. You're talking about notifications and basically it's a large-scale systems problem. That you guys are building a global operating system as Andy Jassy would say. Well, he didn't say that directly, he said internet operating system, but if you believe that APIs are critical services. So I got to ask you that question around this notion of a data center, I mean come on, nobody's really going to give up their data center. It might change significantly, but you pointed out the data center costs are in the top three order, servers, power circulation systems, or cooling circulation, and then actual power itself. Is that right, did I get that right? >> Pretty close, pretty close. Servers dominate, and then after servers if you look at data centers together, that's power, cooling, and the building and facility itself. That is the number two cost, and the actual power itself is number three. >> So that's a huge issue. When we talk like CIOs, it's like can you please take the facility's budget off my back? For many reasons, one, it's going to be written off soon maybe. All kinds of financial issues around-- >> A lot of them don't see it, though, which is a problem. >> That is a problem, that is a problem. Real estate season, and then, yes. >> And then they go, "Ah, it's not my problem" so money just flies out the window. >> So it's obviously a cost improvement for you. So what are you guys doing in that area and what's your big ah-ha for the customers that you walk in the door and say, look, we have this cloud, we have this system and all those headaches can be, not shifted, or relieved if you will, some big asprin for them. What's the communication like? What do you talk to them about? >> Really it depends an awful lot on who it is. I mean, different people care about different things. What gets me excited is I know that this is the dominate cost of offering a service is all of this muck. It's all of this complexity, it's all of this high, high capital cost up front. Facility will run 200 million before there's servers in it. This is big money, and so from my perspective, taking that way from most companies is one contribution. Second contribution is, if you build a lot of data centers you get good at it, and so as a consequence of that I think we're building very good facilities. They're very reliable, and the costs are plummeting fast. That's a second contribution. Third contribution is because... because we're making capacity available to customers it means they don't have to predict two years in advance what they're going to need, and that means there's less wastage, and that's just good for the industry as a whole. >> So we're getting some questions on our crowd chat application. If you want to ask a question, ask him anything. It's kind of like Reddit. Go to crowdchat.net/reinvent. The first question came in was, "James, when do you think ARM will be in the data center?" >> Ah ha, that's a great question. Well, many people know that I'm super excited about ARM. It's early days, the reason why I'm excited is partly because I love seeing lots of players. I love seeing lots of innovation. I think that's what's making our industry so exciting right now. So that's one contribution that ARM brings. Another is if you look at the history of server-side computing, most of the innovation comes from the volume-driven, usually on clients first. The reason why X86 ended up in such a strong position is so many desktops we running X86 processors and as a consequence it became a great server processor. High R&D flow into it. ARM is in just about every device that everyone's carrying around. It's almost every disk drive, it's just super broadly deployed. And whenever you see a broadly deployed processor it means there's an opportunity to do something special for customers. I think it's good for the industry. But in a precise answer to your question, I really don't have one right now. It's something that we're deeply interested in and investigating deeply, but at this point it hasn't happened yet, but I'm excited by it. >> Do you think that... Two lines of questioning here. One is things that are applicable to AWS, other's just your knowledge of the industry and what you think. We talked about that yesterday with OCP, right? >> Yep. >> Not a right fit for us, but you applaud the effort. We should talk about that, too, but does splitting workloads up into little itty, bitty processors change the utilization factor and change the need for things like virtualization, you know? What do you think? >> Yeah, it's a good question. I first got excited about the price performance of micro-servers back in 2007. And at that time it was pretty easy to produce a win by going to a lower-powered processor. At that point memory bandwidth wasn't as good as it could be. It was actually hard on some workloads to fully use a processor. Intel's a very smart company, they've done great work on improving the memory bandwidth, and so today it's actually harder to produce a win, and so you kind of have workloads in classes. At the very, very high end we've got database workloads. They really love single-threaded performance, and performance really is king, but there are lots of highly parallel workloads where there's an opportunity for a big gain. I still think virtualization is probably something where the industry's going to want to be there, just because it brings so many operational advantages. >> So I got to ask the question. Yesterday we had Jason Stowe on, CEO of Cycle Computing, and he had an amazing thing that he did, sorry, trumping it out kids say, but it's not new to you, but it's new to us. He basically created a supercomputer and spun up hundreds of thousands of cores in 30 minutes, which is like insane, but he did it for like 30 grand. Which would've cost, if you try to provision it to the TUCO calculator or whatever your model, it'd be months and years, maybe, and years. But the thing that he said I want to get your point on and I'm going to ask you questions specifically on is, Spot instances were critical for him to do that, and the creativity of his solutions, so I got to ask you, did you see Spot pricing instances being a big deal, and what impact has that done to AWS' vision of large scale? >> I'm super excited by Spot. In fact, it's one of the reasons I joined Amazon. I went through a day of interviews, I met a bunch of really smart people doing interesting work. Someone probably shouldn't have talked to me about Spot because it hadn't been announced yet, and I just went, "This is brilliant! "This is absolutely brilliant!" It's taking the ideas from financial markets, where you've got high-value assets, and saying why don't we actually sell it off, make a market on the basis of that and sell it off? So two things happen that make Spot interesting. The first is an observation up front that poor utilization is basically the elephant in the room. Most folks can't use more than 12% to 15% of their overall server capacity, and so all the rest ends up being wasted. >> You said yesterday 30% is outstanding. It's like have a party. >> 30% probably means you're not measuring it well. >> Yeah, you're lying. >> It's real good, yeah, basically. So that means 70% or more is wasted, it's a crime. And so the first thing that says is, that one of the most powerful advertisements for cloud computing is if you bring a large number of non-correlated workloads together, what happens is when you're supporting a workload you've got to have enough capacity to support the peak, but you only get to monetize the average. And so as the peak to average gets further apart, you're wasting more. So when you bring a large number of non-correlated workloads together what happens is it flattens out just by itself. Without doing anything it flattens out, but there's still some ups and downs. And the Spot market is a way of filling in those ups and downs so we get as close to 100%. >> Is there certain workloads that fit the spot, obviously certain workloads might fit it, but what workloads don't fit the Spot price, because, I mean, it makes total sense and it's an arbitrage opportunity for excess capacity laying around, and it's price based on usage. So is there a workload, 'cause it'll be torrent up, torrent down, I mean, what's the use cases there? >> Workloads that don't operate well in an interrupted environment, that are very time-critical, those workloads shouldn't be run in Spot. It's just not what the resource is designed for. But workloads like the one that we were talking to with Cycle Computing are awesome, where you need large numbers of resources. If the workload needs to restart, that's absolutely fine, and price is really the focus. >> Okay, and question from crowd chat. "Ask James what are his thoughts "on commodity networking and merchant silicon." >> I think an awful lot about that. >> This guy knows you. (both laughing) >> Who's that from? >> It's your family. >> Yeah, exactly! >> They're watching. >> No, network commoditization is a phenomenal thing that the whole industry's needed that for 15 years. We've got a vertical ecosystem that's kind of frozen in time. Vertically-integrated ecosystem kind of frozen in time. Costs everywhere are falling except in networking. We just got to do something, and so it's happening. I'm real excited by that. It's really changing the Amazon business and what we can do for customers. >> Let's talk a little bit about server design, because I was fascinated yesterday listening to you talk how you've come full circle. Over the last decade, right, you started with what's got to be stripped down, basic commodity and now you're of a different mindset. So describe that, and then I have some follow-up questions for you. >> Yeah, I know what you're alluding to. Is years ago I used to argue you don't want hardware specialization, it's crazy. It's the magic's in software. You want to specialize software running on general-purpose processors, and that's because there was a very small number of servers out there, and I felt like it was the most nimble way to run. However today, in AWS when we're running ten of thousands of copies of a single type of server, hardware optimizations are absolutely vital. You end up getting a power-performance advantage at 10X. You can get a price-performance advantage that's substantial and so I've kind of gone full circle where now we're pulling more and more down into the hardware, and starting to do hardware optimizations for our customers. >> So heat density is a huge problem in data centers and server design. You showed a picture of a Quanta package yesterday. You didn't show us your server, said "I can't you ours," but you said, "but we blow this away, "and this is really good." But you describe that you're able to get around a lot of those problems because of the way you design data centers. >> Yep. >> Could you talk about that a little bit? >> Sure, sure, sure. One of the problems when you're building a server it could end up anywhere. It could end up in a beautiful data center that's super well engineered. It could end up on the end of a row on a very badly run data center. >> Or in a closet. >> Or in a closet. The air is recirculating, and so the servers have to be designed with huge headroom on cooling requirements, and they have to be able to operate in any of those environments without driving warranty costs for the vendors. We take a different approach. We say we're not going to build terrible data centers. We're going to build really good data centers and we're going to build servers that exploit the fact those data centers are good, and what happens is more value. We don't have to waste as much because we know that we don't have to operate in the closet. >> We got some more questions coming here by the way. This is awesome. This ask me anything crowd chat thing is going great. We got someone, he's from Nutanix, so he's a geek. He's been following your career for many years. I got to ask you about kind of the future of large-scale. So Spot, in his comment, David's comment, Spot instances prove that solutions like WMare's distributed power management are not valuable. Don't power off the most expensive asset. So, okay, that brings up an interesting point. I don't want to slam on BMWare right now, but I just wanted to bring to the next logical question which is this is a paradigm shift. That's a buzz word, but really a lot's happening that's new and innovative. And you guys are doing it and leading. What's next in the large-scale paradigm of computing and computer science? On the science-side you mentioned merchant silicon. Obviously that's, the genie's out of the bottle there, but what's around the corner? Is it the notifications at the scheduling? Was it virtualization, is it compiler design? What are some of the things that you see out on the horizon that you got your eyes on? >> That's interesting, I mean. I've got, if you name your area, and I'll you some interesting things happening in the area, and it's one of the cool things of being in the industry right now. Is that 10 years ago we had a relatively static, kind of slow-pace. You really didn't have to look that far ahead, because of anything was coming you'd see it coming for five years. Now if you ask me about power distribution, we've got tons of work going on in power distribution. We're researching different power distribution topologies. We're researching higher voltage distribution, direct current distribution. Haven't taken any of those steps yet, but we're were working in that. We've got a ton going on in networking. You'll see an announcement tomorrow of a new instance type that is got some interesting characteristics from a networking perspective. There's a lot going on. >> Let's pre-announce, no. >> Gary's over there like-- >> How 'about database, how 'about database? I mean, 10 years ago, John always says database was kind of boring. You go to a party say, oh welcome to database business, oh yeah, see ya. 25 years ago it was really interesting. >> Now you go to a party is like, hey ah! Have a drink! >> It a whole new ballgame, you guys are participating. Google Spanner is this crazy thing, right? So what are your thoughts on the state of the database business today, in memory, I mean. >> No, it's beautiful. I did a keynote at SIGMOD a few years ago and what I said is that 10 years ago Bruce Linsey, I used to work with him in the database world, Bruce Linsey called it polishing the round ball. It's just we're making everything a little, tiny bit better, and now it's fundamentally different. I mean what's happening right now is the database world, every year, if you stepped out for a year, you wouldn't recognize it. It's just, yeah, it's amazing. >> And DynamoDB has had rapid success. You know, we're big users of that. We actually built this app, crowd chat app that people are using on Hadoop and Hbase, and we immediately moved that to DynamoDB and your stack was just so much faster and scalable. So I got to ask you the-- >> And less labor. >> Yeah, yeah. So it's just been very reliable and all the other goodness of the elastic B socket and SQS, all that other good stuff we're working with node, et cetera So I got to ask you, the area that I want your opinion around the corner is versioning control. So at large-scale one of the challenges that we have is as we're pushin' new code, making sure that the integrated stack is completely updated and synchronized with open-source projects. So where does that fit into the scaling up? 'Cause at large scale, versioning control used to be easy to manage, but downloading software and putting in patches, but now you guys handle all that at scale. So that, I'm assuming there's some automation involved, some real tech involved, but how are you guys handling the future of making sure the code is all updated in the stack? >> It's a great question. It's super important from a security perspective that the code be up to date and current. It's super important from a customer perspective and you need to make sure that these upgrades are just non-disruptive. One customer, best answer I heard was yesterday from a customer was on a panel, they were asked how did they deal with Amazon's upgrades, and what she said is, "I didn't even know when they were happening. "I can't tell when they're happening." Exactly the right answer. That's exactly our goal. We monitor the heck out of all of our systems, and our goal, and boy we take it seriously, is we need to know any issue before a customer knows it. And if you fail on that promise, you'll meet Andy really quick. >> So some other paradigm questions coming in. Floyd asks, "Ask James what his opinion of cloud brokerage "companies such as Jamcracker or Graviton. "Do they have a place, or is it wrong thinking?" (James laughs) >> From my perspective, the bigger and richer the ecosystem, the happier our customers all are. It's all goodness. >> It's Darwinism, that's the answer. You know, the fit shall survive. No, but I think that brings up this new marketplace that Spot pricing came out of the woodwork. It's a paradigm that exists in other industries, apply it to cloud. So brokering of cloud might be something, especially with regional and geographical focuses. You can imagine a world of brokering. I mean, I don't know, I'm not qualified to answer that. >> Our goal, honestly, is to provide enough diversity of services that we completely satisfy customer's requirements, and that's what we intend to do. >> How do you guys think about the make versus buy? Are you at a point now where you say, you know what, we can make this stuff for our specific requirements better than we can get it off the shelf, or is that not the case? >> It changes every few minutes. It really does. >> So what are the parameters? >> Years ago when I joined the company we were buying servers from OEM suppliers, and they were doing some tailoring for our uses. It's gotten to the point now where that's not the right model and we have our own custom designs that are being built. We've now gotten to the point where some of the components in servers are being customized for us, partly because we're driving sufficient volume that it's justified, and partly because the partners that the component suppliers are happy to work with us directly and they want input from us. And so it's every year it's a little bit more specialized and that line's moving, so it's shifting towards specialization pretty quickly. >> So now I'm going to be replaced by the crowd, gettin' great questions, I'm going to be obsolete! No earbud, I got it right here. So the question's more of a fun one probably for you to answer, or just kind of lean back and kind of pull your hair out, but how the heck does AWS add so much infrastructure per day? How do you do it? >> It's a really interesting question. I kind of know how much infrastructure, I know abstractly how much infrastructure we put out every day, but when you actually think about this number in context, it's mind boggling. So here's the number. Here's the number. Every day, we deploy enough servers to support Amazon when it was a seven billion dollar company. You think of how many servers a seven billion dollar e-commerce company would actually require? Every day we deploy that many servers, and it's just shocking to me to think that the servers are in the logistics chain, they're being built, they're delivered to the appropriate data centers, there's back positions there, there's networking there, there's power there. I'm actually, every day I'm amazed to be quite honest with you. >> It's mind-boggling. And then for a while I was there, okay, wait a minute. Would that be Moors' Law? Uh no, not even in particular. 'Cause you said every day. Not every year, every day. >> Yeah, it really is. It's a shocking number and one, my definition of scale changes almost every day, where if you look at the number of customers that are trusting with their workloads today, that's what's driving that growth, it's phenomenal! >> We got to get wrapped up, but I got to ask the Hadoob World SQL over Hadoob question solutions. Obviously Hadoob is great, great for storing stuff, but now you're seeing hybrids come out. Again this comes back down to the, you can recognize the database world anymore if you were asleep for a year. So what's your take on that ecosystem? You guys have a lasting map or a decent a bunch of other things. There's some big data stuff going on. How do you, from a database perspective, how do you look at Hadoob and SQL over Hadoob? >> I personally love 'em both, and I love the diversity that's happening in the database world. There's some people that kind of have a religion and think it's crazy to do anything else. I think it's a good thing. Map reduce is particularly, I think, is a good thing, because it takes... First time I saw map reduce being used was actually a Google advertising engineer. And what I loved about his, I was actually talking to him about it, and what I loved is he had no idea how many servers he was using. If you ask me or anyone in the technology how many servers they're using, they know. And the beautiful thing is he's running multi-thousand node applications and he doesn't know. He doesn't care, he's solving advertising problems. And so I think it's good. I think there's a place for everything. >> Well my final question is asking guests this show. Put the bumper sticker on the car leaving re:Invent this year. What's it say? What does the bumper sticker say on the car? Summarize for the folks, what is the tagline this year? The vibe, and the focus? >> Yeah, for me this was the year. I mean, the business has been growing but this is the year where suddenly I'm seeing huge companies 100% dependent upon AWS or on track to be 100% dependent upon AWS. This is no longer an experiment, something people want to learn about. This is real, and this is happening. This is running real businesses. So it's real, baby! >> It's real baby, I like, that's the best bumper... James, distinguished guest now CUBE alum for us, thanks for coming on, you're a tech athlete. Great to have you, great success. Sounds like you got a lot of exciting things you're working on and that's always fun. And obviously Amazon is killing it, as we say in Silicon Valley. You guys are doing great, we love the product. We've been using it for crowd chats. Great stuff, thanks for coming on theCUBE. >> Thank you. >> We'll be right back with our next guest after this short break. This is live, exclusive coverage with siliconANGLE theCUBE. We'll be right back.

>>Okay, welcome back to everyone. Cube's live coverage of VMware Explorer, 2022. I'm John fur, host of the cube. Two sets three days of live coverage. Dave Ante's here. Lisa Martin, Dave Nicholson, all host of the cube 12 interviews today, just we're with Rocklin and rolling, getting down to the end of the show. As we wind down and look back and look at the future. We've got Steven Jones. Here's the general manager of the VMware cloud on AWS. He's with Amazon web service. Steven Jones. Welcome to the cube. >>Thanks John. >>Welcome back cube alumni. I've been on many times going back to 2015. Yeah. >>Pleasure to be here. Great >>To see you again. Thanks for coming on. Obviously 10 years at AWS, what a ride is that's been, come on. That's fantastic. Tell me it's been crazy. >>Wow. Learned a lot of stuff along the way, right? I mean, we, we, we knew that there was a lot of opportunity, right? Customers wanting the agility and flexibility of, of the cloud and, and we, we still think it's early days, right? I mean, you'll hear Andy say that animals say that, but it really is. Right. If you look at even just the amount of spend that's being spent on, on clouds, it's in the billions, right. And the amount of, of spend in it is still in the trillion. So there's, there's a long way to go and customers are pushing us hard. Obviously >>It's been interesting a lot going on with VM. We're obviously around with them, obviously changing the strategy with their, their third generation and their narrative. Obviously the Broadcom thing is going on around them. And 10 years at abs, we've been, we've been, this'll be our ninth year, no 10th year at reinvent coming up for us. So, but it's 10 years of everything at Amazon, 10 years of S three, 10 years of C two. So if you look at the, the marks of time, now, the history books are starting to be written about Amazon web services. You know, it's about 10 years of full throttle cube hyperscaler in action. I mean, I'm talking about real growth, like >>Hardcore, for sure. I'll give you just one anecdote. So when I first joined, I think we had maybe two EC two instances back in the day and the maximum amount of memory you could conversion into one of these machines was I think 128 gig of Ram fast forward to today. You literally can get a machine with 24 terabytes of Ram just in insane amounts. Right? My, my son who's a gamer tells me he's got 16 gig in his, in his PC. You need to, he thinks that's a lot. >>Yeah. >>That's >>Excited about that. That's not even on his graphics card. I mean, he's, I know it's coming next. The GPU, I mean, just all >>The it's like, right? >>I mean, all the hardware innovation that you guys have done, I mean, look at every it's changed. Everyone's changed their strategy to copy AWS nitro, Dave ante. And I talk about this all the time, especially with James Hamilton and the team over there, Peter DeSantos, these guys have, are constantly going at the atoms and innovating at the, at the level. I mean that, that's how hardcore it is over there right now. I mean, and the advances on the Silicon graviton performance wise is crazy. I mean, so what does that enabling? So given that's continuing, you guys are continuing to do great work there on the CapEx side, we think that's enabling another set of new net new applications because we're starting to see new things emerge. We saw snowflake come on, customer of AWS refactor, the data warehouse, they call it a data cloud. You're starting to see Goldman Sachs. You see capital one, you see enterprise customers building on top of AWS and building a cloud business without spending the CapEx >>Is exactly right. And Ziggy mentioned graviton. So graviton is one of our fastest growing compute families now. And you know, you mentioned a couple of ISVs and partners of ours who are leaning in heavily on porting their own software. Every event Adam announced that we're working with SAP to, to help them port their HANA cloud, which is a, a database of service offering HANA flagship to graviton as well. So it's, it's definitely changing. >>And I think, you know, one of the, and we're gonna circle back to VMware is kind of a point to this. This conversation is that, is that if you look at the trends, right, okay. VMware really tried hard to do cloud and they had a good shot at it V cloud air, but it just, they didn't have the momentum that you guys had at AWS. We saw a lot, lot of other stragglers try to do cloud. They fell off the road, OpenStack, HP, and the list goes on and on. I don't wanna get into that, but the point is, as you guys become more powerful and you're open, right? So you have open ecosystem, you have people now coming back, taking advantage and refactoring and picking up where they left off. VMware was the one of the first companies that actually said, you know what pat Gelsinger said? And I was there, let's clear up the positioning. Let's go all in with AWS. That's >>Right >>At that time, 2016. >>Yeah. This was new for us, for >>Sure. And then now that's set the standard. Now everybody else is kind of doing it. Where is the VMware cloud relationship right now? How is that going out? State's worked. >>It's working well very well. It's I mean, we're celebrating, I think we made the announcement what, five years ago at this conference. Yeah. 2016. So, I mean, it's, it's been a tremendous ride. The best part are the customers who were coming and adopting and proving to us that our vision back then was the right vision. And, and, and what's been different. I think about this relationship. And it was new for us was that we, we purposely went after a jointly engineered solution. This wasn't a, we've got a, a customer or a partner that's just going to run and build something on us. This is something where we both bring muscle and we actually build a, a joint offering together. Talk about, about the main difference. >>Yeah. And that, and that's been working, but now here at this show, if you look at, if you squint through the multi-cloud thing, which is like just, I think positioning for, you know, what could happen in, in a post broad Broadcom world, the cloud native has traction they're Tansu where, where customers were leaning in. So their enterprise customer is what I call the classic. It, you know, mainstream enterprise, which you guys have been doing a lot of business with. They're now thinking, okay, I'm gonna go on continu, accelerate on, in the public cloud, but I'm gonna have hybrid on premise as well. You guys have that solution. Now they're gonna need cloud native. And we were speculating that VMware is probably not gonna be able to get 'em all of it. And, and that there's a lot more cloud native options as customers want more cloud native. How do you see that piece on Amazon side? Because there's a lot of benefits between the VMware cloud on AWS and the services that you guys have natively in your cloud. So we see customers really taking advantage of the AWS goodness, as well as expanding the cloud side at VMware cloud on AWS. >>Yeah. There's probably two ways I would look at this. Right? So, so one is the combination of VMware cloud on AWS. And then both native services just generally brings more options to customers. And so typically what we're seeing now is customers are just able to move much faster, especially as it comes to data center, evacuations, migrating all their assets, right? So it used to be that, and still some customers they're like, I I've gotta think through my entire portfolio of applications and decide what to refactor. And the only way I can move it to cloud is to actually refactor it into some net new application, more and more. We're actually seeing customers. They've got their assets. A lot of them are still on premises in a VMware state, right. They can move those super quick and then modernize those. And so I think where you'll see VMware and AWS very aligned is on this, this idea of migrate. Now you need to get the benefits of TCO and, and the agility that comes with being in the cloud and then modernize. We took a step further, which is, and I think VMware would agree here too, but all of the, the myriad of services, I think it's 200 plus now AWS native services are for use right alongside any that a customer wants to run in VMware. And so we have examples of customers that are doing just, >>And that's, that's how you guys see the native and, and VMware cloud integrating in. Yeah, that's, that's important because this, I mean, if I always joke about, you know, we've been here 12 years listening in the hallways and stuff, you know, on the bus to the event last night, walking the parties and whatnot, listening in the streets, there's kind of two conversations that rise right to the top. And I wanna get your reaction to this Steven, because this seems to be representative of this demographic here at VMware conference, there's conversations around ransomware and storage and D dub and recovery. It's all, a lot of those happen. Yeah. Clearly a big crowd here that care about, you know, Veeam and NetApp and storage and like making sure stuff's secure and air gapped. And a lot of that kind of, I call nerdy conversations and then the other one is, okay, I gotta get the cloud story. >>Right. So there's kind of the operational security. And then there's like, okay, what's my path to true cloud. I need to get this moving. I need to have better applications. My company is the application now not it serves some sort of back office function. Yeah. It's like, my company is completely using technology as its business. So the app is the business. So that means everything's technology driven, not departmental siloed. So there's a, that's what I call the true cloud conversation. How do you, how do you see that evolving because VMware customers are now going there. And I won't say, I won't say they're behind, but they're certainly going there faster than ever before. >>I think, I think, I mean, it's an interesting con it's an interesting way to put it and I, I would completely agree. I think it's, it's very clear that I think a lot of customer companies are actually being disrupted. Right. And they have to move fast and reinvent themselves. You said the app is now becoming the company. Right. I mean, if, if you look at where not too many years back, there were, you know, big companies like Netflix that were born in the cloud. Right. Airbnb they're disruptors. >>There's, that's the >>App, right? That's the app. Yeah. So I, I would exactly agree. And, and that's who other companies are competing with. And so they have to move quickly. You talked about some, some technology that allows them to do that, right? So this week we announced the general availability of a NetApp on tap solution. It's been available on AWS for some time as a fully managed FSX storage solution. But now customers can actually leverage it with, with VMC. Now, why is that important? Well, there's tens of thousands of customers running VMware. On-premises still, there's thousands of them that are actually using NetApp filers, right? NetApp, NetApp filers, and the same enterprise features like replication. D do you were talking about and Snapp and clone. Those types of things can be done. Now within the V VMware state on AWS, what's even better is they can actually move faster. So consider replicating all this, you know, petabytes and petabytes of data that are in these S from on-premises into AWS, this, this NetApp service, and then connected connecting that up to the BMC option. So it just allows customers much, much. >>You guys, you guys have always been customer focus. Every time I sat down with the Andy jazzy and then last year with Adam, same thing we worked back from, I know it's kind of a canned answer on some of the questions from media, but, but they do really care. I've had those conversations. You guys do work backwards from the customer, actually have documents called working backwards. But one of the things that I observed, we talked about here yesterday on the cube was the observations of reinvent versus say, VM world. Now explore is VM world's ecosystem was very partner-centric in the sense of the partners needed to rely on VMware. And the customers came here for both more of the partners, not so much VMware in the sense there wasn't as much, many, many announcements can compare that to the past, say eight years of reinvent, where there's so much Amazon action going on the partners, I won't say take as a second, has a backseat to Amazon, but the, the attendees go there generally for what's going on with AWS, because there's always new stuff coming out. >>And it's, it's amazing. But this year it starts to see that there's an overlap or, or change between like the VMware ecosystem. And now Amazon there's, a lot of our interviews are like, they're on both ecosystems. They're at Amazon's show they're here. So you start to see what I call the naturalization of partners. You guys are continuing to grow, and you'll probably still have thousands of announcements at the event this year, as you always do, but the partners are much more part of the AWS equation, not just we're leasing all these new services and, and oh, for sure. Look at us, look at Amazon. We're growing. Cause you guys were building out and look, the growth has been great. But now as you guys get to this next level, the partners are integral to the ecosystem. How do you look at that? How has Amazon thinking about that? I know there's been some, some, a lot of active reorgs around AWS around solving this problem or no solve the problem, addressing the need and this next level of growth. What's your reaction to >>That? Well, I mean, it's, it's a, it's a good point. So I have to be honest with you, John. I, I, I spent eight of my 10 years so far at AWS within the partner organization. So partners are very near and dear to my heart. We've got tens of thousands of partners and you are you're right. You're starting to see some overlap now between the VMware partner ecosystem and what we've built now in AWS and partners are big >>By the way, you sell out every reinvent. So it's, you have a lot of partners. I'm not suggesting that you, that there's no partner network there, but >>Partners are critical. I mean, absolutely naturally we want a relationship with a customer, but in order to scale the way we need to do to meet the, the needs of customers, we need partners. Right. We, we can't, we can't interact with every single customer as much as we would like to. Right. And so partners have long built teams and expertise that, that caters to even niche workloads or opportunity areas. And, and we love partners >>For that. Yeah. I know you guys do. And also we'll point out just to kind of give props to you guys on the partner side, you don't, you keep that top of the stack open on Amazon. You've done some stuff for end to end where customers want all Amazon, but for the most part, you let competition come in, even on, so you guys are definitely partner friendly. I'm just observing more the maturization of partners within the reinvent ecosystem, cuz we're there every year. I mean, it's, I mean, first of all, they're all buzzing. I mean, it's not like there's no action. There's a lot of customers there it's sold out as big numbers, but it just seems that the partners are much more integrated into the value proposition of at a AWS because of the, the rising tide and, and now their enablement, cuz now they're part of the, of the value proposition. Even more than ever before >>They, they really are. And they, and they're building a lot of capabilities and services on us. And so their customers are our customers. And like you say, it's rising tide, right. We, we all do better together. >>Okay. So let's talk about the VMware cloud here. What's the update here in terms of the show, what's your, what's your main focus cuz a lot of people here are doing, doing sessions. What's been some of the con content that you guys are producing here. >>Yeah. So the best part obviously is a always the customer conversations to partner conversations. So a, a lot of, a lot of sessions there, we did keynote yesterday in Ryan and I, where we talked about a number of announcements that are, I think pretty material now to the offering a joint announcement with NetApp yesterday as well around the storage solution I was talking about. And then some, some really good technical deep dives on how the offering works. Customers are still interested in like how, how do I take what I've got on premises and easily move into AWS and technology like HSX H CX solution with VMware makes it really easy without having to re IP applications. I mean, you know, it is super difficult sometimes to, to move an application. If you've got figure out where all the firewall rules are and re iPing those, those things source. But yeah, it's, it's been fantastic. >>A lot of migrations to the cloud too. A lot of cloud action, new cloud action. You guys have probably seen an uptake on services right on the native side. >>Yes. Yes. For sure. So maybe I just outlined some of the, some of the assets we made this week. So absolutely >>Go ahead. >>We, we announced a new instance family as a, a major workhorse underneath the VMware cloud offering called I, I, you mentioned nitro earlier, this is on, based on our latest generation of nitro, which allows us to offer as you know, bare metal instances, which is, which is what VMware actually VMware was our first partnership and customer that I would say actually drove us to really get Nira done and out the door. And we've continued to iterate on that. And so this I four, I instance, it's based on the, the latest Intel isolate processor with more than double the Ram double the compute, a whopping 75 gigabytes per second network. So it's a real powerhouse. The cool thing is that with the, with the NetApp storage solution that we, we discussed, we're now disaggregating the need to provision, compute and storage at the same time. It used to be, if you wanted to add more storage to your VSAN array, that was on a V VMware cloud. Yeah. You'd add another note. You might not need more compute for memory. You'd have to add another note. And so now customers can simply start adding chunks of storage. And so this opens up customers. I had a customer come to me yesterday and said, there's no reason for us not to move. Now. We were waiting for something that like this, that allowed us to move our data heavy workloads yeah. Into VMware cloud. It's >>Like, it's like the, the alignment. You mentioned alignment earlier. You know, I would say that VMware customers are lined up now almost perfectly with the hybrid story that's that's seamless or somewhat seems it's never truly seamless. But if you look at like what Deepak's doing with Kubernetes and open source, you, you guys have that there talking that big here, you got vs a eight vSphere, eight out it's all cloud native. So that's lined up with what you guys are doing on your services and the horsepower. They have their stuff, you have yours that works better together. So it seems like it's more lined up than ever before. What's your take on that? Do you agree? And, and if so, what folks watching here that are VMware customers, what's, what's the motivation now to go faster? >>Look, it is, it is absolutely lined up. We are, as, as I mentioned earlier, we are jointly engineering and developing this thing together. And so that includes not just the nuts and bolts underneath, but kind of the vision of where it's going. And so we're, we're collectively bringing in customer feedback. >>What is that vision real quick? >>So that vision has to actually help an under help meet even the most demanding customer workloads. Okay. So you've got customer workloads that are still locked in on premises. And why is that? Well, it used to be, there was big for data and migration, right? And the speed. And so we continue to iterate this and that again is a joint thing. Instead of say, VMware, just building on AWS, it really is a, a tight partnership. >>Yeah. The lift and shift is a, an easy thing to do. And, and, and by the way, that could be a hassle too. But I hear most people say the reason holding us back on the workloads is it's just a lot of work, a hassle making it easier is what they want. And you guys are doing that. >>We are doing that. Absolutely. And by the way, we've got not just engineering teams, but we've got customer support teams on both sides working together. We also have flexible commercial options, right? If a customer wants to buy from AWS because they've negotiated some kind of deal with us, they can do that. They wanna buy from VMware for a similar reason. They could buy from VMware. So are >>They in the marketplace? >>They are in the market. There, there are some things in the marketplace. So you talked about Tansu, there's a Tansu offering in the marketplace. So yes. Customers can >>Contract. Yeah. Marketplaces. I'm telling you that's very disruptive. I'm Billy bullish on the market AIOS marketplace. I think that's gonna be a transformative way. People have what they procure and fully agree, deploy and how, and channel relationships are gonna shift. I think that's gonna be a disruptive enabler to the partner equation and, and we haven't even seen it yet. We're gonna be up there in September for their inaugural event. I think it's a small group, but we're gonna be documenting that. So even final question for you, what's next for you? What's on the agenda. You got reinvent right around the corner. Your P ones are done. Right? I know. Assuming all that, I turn that general joke. That's an internal Amazon joke. FYI. You've got your plan. What's next for the world. Obviously they're gonna go this, take this, explore global. No matter what happens with Broadcom, this is gonna be a growth wave with hybrid. What's next for you and your team with AWS and VMware's relationship? >>Yeah. So both of us are hyper focused on adding additional options, both from a, an instance compute perspective. You know, VMware announced some, some, some additional offerings that we've got. We've got a fully complete, like, so they're, they announce things like VMware flex compute V VMware flex storage. You mentioned earlier, there was a conversation around ransomware. There's a new ransomware based offering. So we're hyper focused on rounding out, continuing to round out the offering and giving customers even more choice >>Real quick. Jonathan made me think about the ransomware we were at reinforce Steven Schmidtz now the CSO. Now you got a CSO. AJ's the CSO. You got a whole focus, huge emphasis on security right now. I know you always have, but now it's much more public. It's PO more positive, I think, than some of the other events I've been to. It's been more Lum and doom. What's the security tie in here with VMware. Can you share a little bit real quick on the security piece update around this relationship? >>Yeah, you bet. So as you know, security for us is job zero. Like you don't have anything of security. And so what are the things that, that we're excited about specifically with VMware is, is the latest offering that, that we put together and it's called this, this ransomware offering. And it's, it's a little bit different than other ransomware. I mean, a lot of people have ransomware offerings today, just >>Air gap. >>Right, right, right. Exactly. No, that's easy. No, this one is different. So on the back end, so within VMC, there's this, this option where CU we can be to be taking iterative snapshots of a customer environment. Now, if an event were to occur, right. And a customer is like, I have to know if I'm compromised, we can actually spin up super easy. This is cloud. Remember? Yeah. We can spin up a, a copy of this environment, throw a switch, pick a snapshot with NSX. So VMware NSX firewall it off and then use some custom tooling from VMware to actually see if it's been compromised or not. And then iterate through that until you actually know you're clean. And that's different than just tools that do maybe a >>Little bit of scam. We had Tom gills on yesterday and, and one of the things Dave ante had to leave is taking the sun to college is last one in the house and B nester now, but Tom Gill was on. We were talking about how good their security story is ware. And they really weren't showboating it as much as they could have here. I thought they could have done a better job, but this is an example of kind of them really leaning in with you guys. That's the key part of the relationship. >>Yeah, it really is. And I think this is something is materially different than what you can get elsewhere. And it's exciting for, >>Okay. Now the, the real question I want to know is what's your plans for AWS reinvent the blockbuster end of the year, Amazon surf show that gets bigger and bigger. I know it's still hybrid now, but it's looking be hybrid, but people are back in person last year. You guys were the first event really come back and still had massive numbers. AWS summit, New York at 19,000. I heard last week in Chicago, big numbers. So we're expecting reinvent to be pretty large this year. What are you, what are you gonna do there? What's your role there? >>We are expecting, well, I'll be there. I cover multiple businesses. Obviously. We're, we're planning on some additional announcements, obviously in the VMware space as well. And one of the other businesses I run is around SAP. And you should look for some things there as well. Yeah. Really looking forward to reinvent, except for the fact that it's right after Thanksgiving. But I think it >>Always ruins my, I always get an article out. I like, why are you we're having, we're having Thanksgiving dinner. I gotta write this article. It's gotta get Adam, Adam. Leski exclusive. We, every year we do a, a CEO sit down with Andy was the CEO and then now Adam. But yeah, it's a great event to me. I think it sets the tone. And it's gonna be very interesting to see the big clouds are coming to the big cloud. You guys, and you guys are now called hyperscalers. Now, multiple words. It's interesting. You guys are providing the CapEx goodness for everybody else now. And that relationship seems to be the new, the new industry standard of you guys provide the enablement and then everyone you get paid, cuz it's a service. A whole nother level of cloud is emerging in the partner network, GSI other companies. Yeah. >>Yeah. I mean we're really scaling. I mean we continue to iterate and release regions at a fast clip. We just announced support for VMware in Hong Kong. Yeah. So now we're up to 21 regions for this service, >>The sovereign clouds right around the corner. Let's we'll talk about that soon. Steven. Thanks for coming. I know you gotta go. Thank you for your valuable time. Coming in. Put Steven Jones. Who's the general manager of the VMware cloud on AWS business. Four AWS here inside the cube day. Three of cube coverage. I'm John furrier. Thanks for watching. We'll be right back.

(upbeat music) >> Okay, welcome back everyone. CUBE's coverage of re:MARS, here in Las Vegas, in person. I'm John Furrier, host of theCUBE. This is the analyst panel wrap up analysis of the keynote, the show, past one and a half days. We got two great guests here. We got Andy Thurai, Vice President, Principal Consultant, Constellation Research. Larry Carvalho, Principal Consultant at RobustCloud LLC. Congratulations going out on your own. >> Thank you. >> Andy, great to see you. >> Great to see you as well. >> Guys, thanks for coming out. So this is the session where we break down and analyze, you guys are analysts, industry analysts, you go to all the shows, we see each other. You guys are analyzing the landscape. What does this show mean to you guys? 'Cause this is not obvious to the normal tech follower. The insiders see the confluence of robotics, space, automation and machine learning. Obviously, it's IoTs, industrials, it's a bunch of things. But there's some dots to connect. Let's start with you, Larry. What do you see here happening at this show? >> So you got to see how Amazon started, right? When AWS started. When AWS started, it primarily took the compute storage, networking of Amazon.com and put it as a cloud service, as a service, and started selling the heck out of it. This is a stage later now that Amazon.com has done a lot of physical activity, and using AIML and the robotics, et cetera, it's now the second phase of innovation, which is beyond digital transformation of back office processes, to the transformation of physical processes where people are now actually delivering remotely and it's an amazing area. >> So back office's IT data center kind of vibe. >> Yeah. >> You're saying front end, industrial life. >> Yes. >> Life as we know it. >> Right, right. I mean, I just stopped at a booth here and they have something that helps anybody who's stuck in the house who cannot move around. But with Alexa, order some water to bring them wherever they are in the house where they're stuck in their bed. But look at the innovation that's going on there right at the edge. So I think those are... >> John: And you got the Lunar, got the sex appeal of the space, Lunar Outpost interview, >> Yes. >> those guys. They got Rover on Mars. They're going to have be colonizing the moon. >> Yes. >> I made a joke, I'm like, "Well, I left a part back on earth, I'll be right back." (Larry and Andy laugh) >> You can't drive back to the office. So a lot of challenges. Andy, what's your take of the show? Take us your analysis. What's the vibe, what's your analysis so far? >> It's a great show. So, as Larry was saying, one of the thing was that when Amazon started, right? So they were more about cloud computing. So, which means is they try to commoditize more of data center components or compute components. So that was working really well for what I call it as a compute economy, right? >> John: Mm hmm. >> And I call the newer economy as more of a AIML-based data economy. So when you move from a compute economy into a data economy, there are things that come into the forefront that never existed before, never popular before. Things like your AIML model creation, model training, model movement, model influencing, all of the above, right? And then of course the robotics has come long way since then. And then some of what they do at the store, or the charging, the whole nine yards. So, the whole concept of all of these components, when you put them on re:Invent, such a big show, it was getting lost. So that's why they don't have it for a couple of years. They had it one year. And now all of a sudden they woke up and say, "You know what? We got to do this!" >> John: Yeah. >> To bring out this critical components that we have, that's ripe, mature for the world to next component. So that's why- I think they're pretty good stuff. And some of the robotics things I saw in there, like one of them I posted on my Twitter, it's about the robot dog, sniffing out the robot rover, which I thought was pretty hilarious. (All laugh) >> Yeah, this is the thing. You're seeing like the pandemic put everything on hold on the last re:Mars, and then the whole world was upside down. But a lot of stuff pulled forward. You saw the call center stuff booming. You saw the Zoomification of our workplace. And I think a lot of people got to the realization that this hybrid, steady-state's here. And so, okay. That settles that. But the digital transformation of actually physical work? >> Andy: Yeah. >> Location, the walk in and out store right over here we've seen that's the ghost store in Seattle. We've all been there. In fact, I was kind of challenged, try to steal something. I'm like, okay- (Larry laughs) I'm pulling all my best New Jersey moves on everyone. You know? >> Andy: You'll get charged for it. >> I couldn't get away with it. Two double packs, drop it, it's smart as hell. Can't beat the system. But, you bring that to where the AI machine learning, and the robotics meet, robots. I mean, we had robots here on theCUBE. So, I think this robotics piece is a huge IoT, 'cause we've been covering industrial IoT for how many years, guys? And you could know what's going on there. Huge cyber threats. >> Mm hmm. >> Huge challenges, old antiquated OT technology. So I see a confluence in the collision between that OT getting decimated, to your point. And so, do you guys see that? I mean, am I just kind of seeing mirage? >> I don't see it'll get decimated, it'll get replaced with a newer- >> John: Dave would call me out on that. (Larry laughs) >> Decimated- >> Microsoft's going to get killed. >> I think it's going to have to be reworked. And just right now, you want do anything in a shop floor, you have to have a physical wire connected to it. Now you think about 5G coming in, and without a wire, you get minute details, you get low latency, high bandwidth. And the possibilities are endless at the edge. And I think with AWS, they got Outposts, they got Snowcone. >> John: There's a threat to them at the edge. Outpost is not doing well. You talk to anyone out there, it's like, you can't find success stories. >> Larry: Yeah. >> I'm going to get hammered by Amazon people, "Oh, what're you're saying that?" You know, EKS for example, with serverless is kicking ass too. So, I mean I'm not saying Outpost was wrong answer, it was a right at the time, what, four years ago that came out? >> Yeah. >> Okay, so, but that doesn't mean it's just theirs. You got Dell Technologies want some edge action. >> Yeah. >> So does HPE. >> Yes. >> So you got a competitive edge situation. >> I agree with that and I think that's definitely not Amazon's strong point, but like everything, they try to make it easy to use. >> John: Yeah. >> You know, you look at the AIML and they got Canvas. So Canvas says, hey, anybody can do AIML. If they can do that for the physical robotic processes, or even like with Outpost and Snowcone, that'll be good. I don't think they're there yet, and they don't have the presence in the market, >> John: Yeah. >> like HPE and, >> John: Well, let me ask you guys this question, because I think this brings up the next point. Will the best technology win or will the best solution win? Because if cloud's a platform and all software's open source, which you can make those assumptions, you then say, hey, they got this killer robotics thing going on with Artemis and Moonshot, they're trying to colonize the moon, but oh, they discovered a killer way to solve a big problem. Does something fall out of this kind of re:Mars environment, that cracks the code and radically changes and disrupts the IoT game? That's my open question. I don't know the answer. I'd love to get your take on what might be possible, what wild card's out there around, disrupting the edge. >> So one thing I see the way, so when IoT came into the world of play, it's when you're digitizing the physical world, it's IoT that does digitalization part of that actually, right? >> But then it has its own set of problems. >> John: Yeah. >> You're talking about you installing sensor everywhere, right? And not only installing your own sensor, but also you're installing competitor sensors. So in a given square feet how many sensors can you accommodate? So there are physical limitations on liabilities of bandwidth and networking all of that. >> John: And integration. >> As well. >> John: Your point. >> Right? So when that became an issue, this is where I was talking to the robotic guys here, a couple of companies, and one of the use cases they were talking about, which I thought was pretty cool, is, rather than going the sensor route, you go the robot route. So if you have either a factor that you want to map out, you put as many sensors on your robot, whatever that is, and then you make it go around, map the whole thing, and then you also do a surveillance in the whole nine yards. So, you can either have a fixed sensors or you can have moving sensors. So you can have three or four robots. So initially, when I was asking them about the price of it, when they were saying about a hundred thousand dollars, I was like, "Who would buy that?" (John and Larry laugh) >> When they then explained that, this is the use case, oh, that makes sense, because if you had to install, entire factory floor sensors, you're talking about millions of dollars. >> John: Yeah. >> But if you do the moveable sensors in this way, it's a lot cheaper. >> John: Yeah, yeah. >> So it's based on your use case, what are your use cases? What are you trying to achieve? >> The general purpose is over. >> Yeah. >> Which you're getting at, and that the enablement, this is again, this is the cloud scale open question- >> Yep. >> it's, okay, the differentiations isn't going to be open source software. That's open. >> It's going to be in the, how you configure it. >> Yes. >> What workflows you might have, the data streams. >> I think, John, you're bringing up a very good point about general purpose versus special purpose. Yesterday Zoox was on the stage and when they talked about their vehicle, it's made just for self-driving. You walk around in Vegas, over here, you see a bunch of old fashioned cars, whether they're Ford or GM- >> and they put all these devices around it, but you're still driving the same car. >> John: Yeah, exactly. >> You can retrofit those, but I don't think that kind of IoT is going to work. But if you redo the whole thing, we are going to see a significant change in how IoT delivers value all the way from the industrial to home, to healthcare, mining, agriculture, it's going to have to redo. I'll go back to the OT question. There are some OT guys, I know Rockwell and Siemens, some of them are innovating faster. The ones who innovate faster to keep up with the IT side, as well as the MLAI model are going to be the winners on that one. >> John: Yeah, I agree. Andy, your thoughts on manufacturing, you brought up the sensor thing. Robotics ultimately is, end of the day, an opportunity there. Obviously machine learning, we know what that does. As we move into these more autonomous builds, what does that look like? And is Amazon positioned well there? Obviously they have big manufacturers. Some are saying that they might want to get out of that business too, that Jassy's evaluating that some are saying. So, where does this all lead for that robotics manufacturing lifestyle, walk in, grab my food? 'Cause it's all robotics and AI at the end of the day, I got sensors, I got cameras, I got non-humans moving heavy lifting stuff, fixing the moon will be done by robots, not humans. So it's all coming. What's your analysis? >> Well, so, the point about robotics is on how far it has come, it is unbelievable, right? Couple of examples. One was that I was just talking to somebody, was explaining to them, to see that robot dog over there at the Boston Dynamics one- >> John: Yeah. >> climbing up and down the stairs. >> Larry: Yeah. >> That's more like the dinosaur movie opening the doors scene. (John and Larry laugh) It's like that for me, because the coordinated things, it is able to go walk up and down, that's unbelievable. But okay, it does that, and then there was also another video which is going on viral on the internet. This guy kicks the dog, robot dog, and then it falls down and it gets back up, and the sentiment that people were feeling for the dog, (Larry laughs) >> you can't, it's a robot, but people, it just comes at that level- >> John: Empathy, for a non-human. >> Yeah. >> But you see him, hey you, get off my lawn, you know? It's like, where are we? >> It has come to that level that people are able to kind of not look at that as a robot, but as more like a functioning, almost like a pet-level, human-level being. >> John: Yeah. >> And you saw that the human-like walking robot there as well. But to an extent, in my view, they are all still in an experimentation, innovation phase. It doesn't made it in the industrial terms yet. >> John: Yeah, not yet, it's coming. >> But, the problem- >> John: It's coming fast. That's what I'm trying to figure out is where you guys see Amazon and the industry relative to what from the fantasy coming reality- >> Right. >> of space in Mars, which is, it's intoxicating, let's face it. People love this. The nerds are all here. The geeks are all here. It's a celebration. James Hamilton's here- >> Yep. >> trying to get him on theCUBE. And he's here as a civilian. Jeff Barr, same thing. I'm here, not for Amazon, I bought a ticket. No, you didn't buy a ticket. (Larry laughs) >> I'm going to check on that. But, he's geeking out. >> Yeah. >> They're there because they want to be here. >> Yeah. >> Not because they have to work here. >> Well, I mean, the thing is, the innovation velocity has increased, because, in the past, remember, the smaller companies couldn't innovate because they don't have the platform. Now Compute is a platform available at the scale you want, AI is available at the scale. Every one of them is available at the scale you want. So if you have an idea, it's easy to innovate. The innovation velocity is high. But where I see most of the companies failing, whether startup or big company, is that you don't find the appropriate use case to solve, and then don't sell it to the right people to buy that. So if you don't find the right use case or don't sell the right value proposition to the actual buyer, >> John: Mm hmm. >> then why are you here? What are you doing? (John laughs) I mean, you're not just an invention, >> John: Eh, yeah. >> like a telephone kind of thing. >> Now, let's get into next talk track. I want to get your thoughts on the experience here at re:Mars. Obviously AWS and the Amazon people kind of combined effort between their teams. The event team does a great job. I thought the event, personally, was first class. The coffee didn't come in late today, I was complaining about that, (Larry laughs) >> people complaining out there, at CUBE reviews. But world class, high bar on the quality of the event. But you guys were involved in the analyst program. You've been through the walkthrough, some of the briefings. I couldn't do that 'cause I'm doing theCUBE interviews. What would you guys learn? What were some of the key walkaways, impressions? Amazon's putting all new teams together, seems on the analyst relations. >> Larry: Yeah. >> They got their mojo booming. They got three shows now, re:Mars, re:inforce, re:invent. >> Andy: Yeah. >> Which will be at theCUBE at all three. Now we got that coverage going, what's it like? What was the experience like? Did you feel it was good? Where do they need to improve? How would you grade the Amazon team? >> I think they did a great job over here in just bringing all the physical elements of the show. Even on the stage, where they had robots in there. It made it real and it's not just fake stuff. And every, or most of the booths out there are actually having- >> John: High quality demos. >> high quality demos. (John laughs) >> John: Not vaporware. >> Yeah, exactly. Not vaporware. >> John: I won't say the name of the company. (all laugh) >> And even the sessions were very good. They went through details. One thing that stood out, which is good, and I cover Low Code/No Code, and Low Code/No Code goes across everything. You know, you got DevOps No Low-Code Low-Code. You got AI Low Code/No Code. You got application development Low Code/No Code. What they have done with AI with Low Code/No Code is very powerful with Canvas. And I think that has really grown the adoption of AI. Because you don't have to go and train people what to do. And then, people are just saying, Hey, let me kick the tires, let me use it. Let me try it. >> John: It's going to be very interesting to see how Amazon, on that point, handles this, AWS handles this data tsunami. It's cause of Snowflake. Snowflake especially running the table >> Larry: Yeah. >> on the old Hadoop world. I think Dave had a great analysis with other colleagues last week at Snowflake Summit. But still, just scratching the surface. >> Larry: Yeah. >> The question is, how shared that ecosystem, how will that morph? 'Cause right now you've got Data Bricks, you've got Snowflake and a handful of others. Teradata's got some new chops going on there and a bunch of other folks. Some are going to win and lose in this downturn, but still, the scale that's needed is massive. >> So you got data growing so much, you were talking earlier about the growth of data and they were talking about the growth. That is a big pie and the pie can be shared by a lot of folks. I don't think- >> John: And snowflake pays AWS, remember that? >> Right, I get it. (John laughs) >> I get it. But they got very unique capabilities, just like Netflix has very unique capabilities. >> John: Yeah. >> They also pay AWS. >> John: Yeah. >> Right? But they're competing on prime. So I really think the cooperation is going to be there. >> John: Yeah. >> The pie is so big >> John: Yeah. >> that there's not going to be losers, but everybody could be winners. >> John: I'd be interested to follow up with you guys after next time we have an event together, we'll get you back on and figure out how do you measure this transitions? You went to IDC, so they had all kinds of ways to measure shipments. >> Larry: Yep. >> Even Gartner had fumbled for years, the Magic Quadrant on IaaS and PaaS when they had the market share. (Larry laughs) And then they finally bundled PaaS and IaaS together after years of my suggesting, thank you very much Gartner. (Larry laughs) But that just performs as the landscape changes so does the scoreboard. >> Yep. >> Right so, how do you measure who's winning and who's losing? How can we be critical of Amazon so they can get better? I mean, Andy Jassy always said to me, and Adam Salassi same way, we want to hear how bad we're doing so we can get better. >> Yeah. >> So they're open-minded to feedback. I mean, not (beep) posting on them, but they're open to critical feedback. What do you guys, what feedback would you give Amazon? Are they winning? I see them number one clearly over Azure, by miles. And even though Azure's kicking ass and taking names, getting back in the game, Microsoft's still behind, by a long ways, in some areas. >> Andy: Yes. In some ways. >> So, the scoreboard's changing. What's your thoughts on that? >> So, look, I mean, at the end of the day, when it comes to compute, right, Amazon is a clear winner. I mean, there are others who are catching up to it, but still, they are the established leader. And it comes with its own advantages because when you're trying to do innovation, when you're trying to do anything else, whether it's a data collection, we were talking about the data sensors, the amount of data they are collecting, whether it's the store, that self-serving store or other innovation projects, what they have going on. The storage compute and process of that requires a ton of compute. And they have that advantage with them. And, as I mentioned in my last article, one of my articles, when it comes to AIML and data programs, there is a rich and there is a poor. And the rich always gets richer because they, they have one leg up already. >> John: Yeah. >> I mean the amount of model training they have done, the billion or trillion dollar trillion parametrization, fine tuning of the model training and everything. They could do it faster. >> John: Yeah. >> Which means they have a leg up to begin with. So unless you are given an opportunity as a smaller, mid-size company to compete at them at the same level, you're going to start at the negative level to begin with. You have a lot of catch up to do. So, the other thing about Amazon is that they, when it comes to a lot of areas, they admit that they have to improve in certain areas and they're open and willing and listen to the people. >> Where are you, let's get critical. Let's do some critical analysis. Where does Amazon Websters need to get better? In your opinion, what criticism would you, in a constructive way, share? >> I think on the open source side, they need to be more proactive in, they are already, but they got to get even better than what they are. They got to engage with the community. They got to be able to talk on the open source side, hey, what are we doing? Maybe on the hardware side, can they do some open-sourcing of that? They got graviton. They got a lot of stuff. Will they be able to share the wealth with other folks, other than just being on an Amazon site, on the edge with their partners. >> John: Got it. >> If they can now take that, like you said, compute with what they have with a very end-to-end solution, the full stack. And if they can extend it, that's going to be really beneficial for them. >> Awesome. Andy, final word here. >> So one area where I think they could improve, which would be a game changer would be, right now, if you look at all of their solutions, if you look at the way they suggest implementation, the innovations, everything that comes out, comes out across very techy-oriented. The persona is very techy-oriented. Very rarely their solutions are built to the business audience or to the decision makers. So if I'm, say, an analyst, if I want to build, a business analyst rather, if I want to build a model, and then I want to deploy that or do some sort of application, mobile application, or what have you, it's a little bit hard. It's more techy-oriented. >> John: Yeah, yeah. >> So, if they could appeal or build a higher level abstraction of how to build and deploy applications for business users, or even build something industry specific, that's where a lot of the legacy companies succeeded. >> John: Yeah. >> Go after manufacturing specific or education. >> Well, we coined the term 'Supercloud' last re:Invent, and that's what we see. And Jerry Chen at Greylock calls it Castles in the Cloud, you can create these moats >> Yep. >> on top of the CapEx >> Yep. >> of Amazon. >> Exactly. >> And ride their back. >> Yep. >> And the difference in what you're paying and what you're charging, if you're good, like a Snowflake or a Mongo. I mean, Mongo's, they're just as big as Snow, if not bigger on Amazon than Snowflake is. 'Cause they use a lot of compute. No one turns off their database. (John laughs) >> Snowflake a little bit different, a little nuanced point, but, this is the new thing. You see Goldman Sachs, you got Capital One. They're building their own kind of, I call them sub clouds, but Dave Vellante says it's a Supercloud. And that essentially is the model. And then once you have a Supercloud, you say, great, I'm going to make sure it works on Azure and Google. >> Andy: Yep. >> And Alibaba if I have to. So, we're kind of seeing a playbook. >> Andy: Mm hmm. >> But you can't get it wrong 'cause it scales. >> Larry: Yeah, yeah. >> You can't scale the wrong answer. >> Andy: Yeah. >> So that seems to be what I'm watching is, who gets it right? Product market fit. Then if they roll it out to the cloud, then it becomes a Supercloud, and that's pure product market fit. So I think that's something that I've seen some people trying to figure out. And then, are you a supplier to the Superclouds? Like a Dell? Or you become an enabler? >> Andy: Yeah. >> You know, what's Dell Technologies do? >> Larry: Yeah. >> I mean, how do the box movers compete? >> Larry: I, the whole thing is now hybrid and you're going to have to see just, you said. (Larry laughs) >> John: Hybrid's a steady-state. I don't need to. >> Andy: I mean, >> By the way we're (indistinct), we can't get the chips, cause Broadcom and Apple bought 'em all. (Larry laughs) I mean there's a huge chip problem going on. >> Yes. I agree. >> Right now. >> I agree. >> I mean all these problems when you attract to a much higher level, a lot of those problems go away because you don't care about what they're using underlying as long as you deliver my solution. >> Larry: Yes. >> Yeah, it could be significantly, a little bit faster than what it used to be. But at the end of the day, are you solving my specific use case? >> John: Yeah. >> Then I'm willing to wait a little bit longer. >> John: Yeah. Time's on our side and now they're getting the right answers. Larry, Andy, thanks for coming on. This great analyst session turned into more of a podcast vibe, but you know what? (Larry laughs) To chill here at re:Mars, thanks for coming on, and we unpacked a lot. Thanks for sharing. >> Both: Thank you. >> Appreciate it. We'll get you back on. We'll get you in the rotation. We'll take it virtual. Do a panel. Do a panel, do some panels around this. >> Larry: Absolutely. >> Andy: Oh this not virtual, this physical. >> No we're live right now! (all laugh) We get back to Palo Alto. You guys are influencers. Thanks for coming on. You guys are moving the market, congratulations. Take a minute, quick minute each to plug any work you're doing for the people watching. Larry, what are you working on? Andy? You go after Larry, what you're working on. >> Yeah. So since I started my company, RobustCloud, since I left IDC about a year ago, I'm focused on edge computing, cloud-native technologies, and Low Code/No Code. And basically I help companies put their business value together. >> All right, Andy, what are you working on? >> I do a lot of work on the AIML areas. Particularly, last few of my reports are in the AI Ops incident management and ML Ops areas of how to generally improve your operations. >> John: Got it, yeah. >> In other words, how do you use the AIML to improve your IT operations? How do you use IT Ops to improve your AIML efficiency? So those are the- >> John: The real hardcore business transformation. >> Yep. >> All right. Guys, thanks so much for coming on the analyst session. We do keynote review, breaking down re:Mars after day two. We got a full day tomorrow. I'm John Furrier with theCUBE. See you next time. (pleasant music)

>>Okay, welcome back everyone. This is the Cube's coverage here in Las Vegas. Back at events re Mars, Amazon re Mars. I'm your host, John fur with the cube. Mars stands for machine learning, automation, robotics, and space. It's great event brings together a lot of the industrial space machine learning and all the new changes in scaling up from going on the moon to, you know, doing great machine learning. And we've got two great guests here with kinda called lunar outpost, Justin Sears, CEO, Lauren, man. He's the co-founder and chief strategy officer lunar outpost. They're right next to us, watching their booth. Love the name, gentlemen. Welcome to the cube. >>Yeah. Thanks for having us, John. >>All right. So lunar outpost, I get the clues here. Tell us what you guys do. Start with that. >>Absolutely. So lunar outpost, we're a company based outta Colorado that has two missions headed to the moon over the course of the next 24 months. We're currently operating on Mars, which forest will tell you a little bit more about here in a second. And we're really pushing out towards expanding the infrastructure on the lunar surface. And then we're gonna utilize that to provide sustainable access to other planetary bodies. >>All right, far as teeing it up for you. Go, how cool is this? We don't, we wanna use every minute. What's the lunar surface look like? What's the infrastructure roads. You gonna pave it down. You what's going on. Well, >>Where we're going. No one has ever been. So, um, our first mission is going to Shackleton connecting Ridge on the south pole, the moon, and that's ripe to add infrastructure such as landing pads and other things. But our first Rover will be primarily driving across the surface, uh, exploring, uh, what the material looks like, prospecting for resources and testing new technologies. >>And you have a lot of technology involved. You're getting data in, you're just doing surveillance. What's the tech involved there. >>Yeah. So the primary technology that we're demonstrating is a 4g network for NOK. Um, we're providing them mobility services, which is basically like the old Verizon commercial. Can you hear me now? Uh, where the Rover drives farther and farther away from the Lander to test their signal strength, and then we're gonna have some other payloads ride sharing along with us for the ride >>Reminds me the old days of wifi. We used to call it war drive and you go around and try to find someone's wifi hotspot <laugh> inside the thing, but no, this is kind of cool. It brings up the whole thing. Now on lunar outpost, how big is the company? What's how what's to some of the stats heres some of the stats. >>Absolutely. So lunar outpost, 58 people, uh, growing quite quickly on track to double. So any of you watching, you want a job, please apply <laugh>. But with lunar outpost, uh, very similar to how launch companies provide people access to different parts of space. Lunar outpost provides people access to different spots on planetary bodies, whether it's the moon, Mars or beyond. So that's really where we're starting. >>So it's kinda like a managed service for all kinds of space utilities. If you kind of think about it, you're gonna provide services. Yeah, >>Absolutely. Yeah. It, it's definitely starting there and, and we're pushing towards building that infrastructure and that long term vision of utilizing space resources. But I can talk about that a little bit more here in a sec. >>Let's get into that. Let's talk about Mars first. You guys said what's going on with >>Mars. Absolutely. >>Yeah. So right now, uh, lunar outpost is part of the science team for, uh, Moxi, which is an instrument on the perseverance Rover. Yeah. Moxi is the first demonstration of space resource utilization on another planet. And what space resource utilization is basically taking resources on another planet, turning them into something useful. What Moxi does is it takes the CO2 from the atmosphere of Mars and atmosphere of Mars is mostly CO2 and it uses a process called solid oxide electrolysis to basically strip oxygen off of that CO2 to produce oh two and carbon monoxide. >>So it's what you need to self sustain on the surface. >>Exactly. It's not just sustaining, um, the astronauts, but also for producing oxygen for propellant. So it'll actually produce, um, it's a, it's a technology that'll produce a propellant for return rockets, um, to come back for Mars. So >>This is the real wildcard and all this, this, this exploration is how fast can the discoveries invent the new science to provide the life and the habitat on the surface. And that seems to be the real focus in the, in the conversations I heard on the keynote as well, get the infrastructure up so you can kinda land and, and we'll pull back and forth. Um, where are we on progress? You guys have the peg from one zero to 10, 10 being we're going, my grandmother's going, everyone's going to zero. Nothing's moving. >>We're making pretty rapid >>Progress. A three six, >>You know, I'll, I'll put it on an eight, John an >>Eight, I'll put it on >>Eight. This is why the mission force was just talking about that's launching within the next 12 months. This is no longer 10 years out. This is no longer 20 years away, 12 months. And then we have mission two shortly after, and that's just the beginning. We have over a dozen Landers that are headed to line surface this decade alone and heavy lift Landers and launchers, uh, start going to the moon and coming back by 2025. >>So, and you guys are from Colorado. You mentioned before you came on camera, right with the swap offices. So you got some space in Colorado, then the rovers to move around. You get, you get weird looks when people drive by and see the space gear. >>Oh yeah, definitely. So we have, um, you know, we have our facility in golden and our Nevada Colorado, and we'll take the vehicles out for strolls and you'll see construction workers, building stuff, and looking over and saying, what's >>Good place to work too. So you're, you're hiring great. You're doubling on the business model side. I can see a lot of demand. It's cheaper to launch stuff now in space. Is there becoming any rules of engagement relative to space? I don't wanna say verified, but like, you know, yet somehow get to the point where, I mean, I could launch a satellite, I could launch something for a couple hundred grand that might interfere with something legitimate. Do you see that on the radar because you guys are having ease of use so smaller, faster, cheaper to get out there. Now you gotta refine the infrastructure, get the services going. Is there threats from just random launches? >>It's a, it's a really interesting question. I mean, current state of the art people who have put rovers on other planetary bodies, you're talking like $3 billion, uh, for the March perseverance Rover. So historically there hasn't been that threat, but when you start talking about lowering the cost and the access to some of these different locations, I do think we'll get to the point where there might be folks that interfere with large scale operations. And that's something that's not very well defined in international law and something you won't really probably get any of the major space powers to agree to. So it's gonna be up to commercial companies to operate responsibly so we can make that space sustainable. And if there is a bad actor, I think it they'll weed themselves out over time. >>Yeah. It's gonna be of self govern, I think in the short term. Good point. Yeah. What about the technology? Where are we in the technology? What are some of the big, uh, challenges that we're overcoming now and what's that next 20 M stare in terms of the next milestone? Yeah, a tech perspective. >>Yeah. So the big technology technological hurdle that has been identified by many is the ability to survive the LUN night. Um, it gets exceptionally cold, uh, when the sun on the moon and that happens every 14 days for another, for, you know, for 14 days. So these long, cold lunar nights, uh, can destroy circuit boards and batteries and different components. So lunar outpost has invested in developing thermal technologies to overcome this, um, both in our offices, in the United States, but we also have opened a new office in, uh, Luxembourg in Europe. That's focusing specifically on thermal technologies to survive the lunar night, not just for rovers, but all sorts of space assets. >>Yeah. Huge. That's a hardware, you know, five, nine kind of like meantime between failure conversation, right. >><laugh> and it's, it gets fun, right? Because you talk five nines and it's such like, uh, you know, ingrained part of the aerospace community. But what we're pitching is we can send a dozen rovers for the cost of one of these historical rovers. So even if 25% of 'em fail, you still have eight rovers for the cost of one of the old rovers. And that's just the, economy's a scale. >>I saw James Hamilton here walking around. He's one of the legendary Amazonians who built out the data center. You might come by the cube. That's just like what they did with servers. Hey, if one breaks throw it away. Yeah. Why buy the big mainframe? Yeah. That's the new model. All right. So now about, uh, space space, that's a not space space, but like room to move around when you start getting some of these habitats going, um, how does space factor into the size of the location? Um, cuz you got the, to live there, solve some of the thermal problems. How do I live on space? I gotta have, you know, how many people gonna be there? What's your forecast? You think from a mission standpoint where there'll be dozens of people or is it still gonna be small teams? >>Yeah. >>Uh, what's that look like? >>I mean you >>Can guess it's okay. >>I mean, my vision's thousands of people. Yep. Uh, living and working in space because it's gonna be, especially the moon I think is a destination that's gonna grow, uh, for tourism. There's an insane drive from people to go visit a new destination. And the moon is one of the most unique experiences you could imagine. Yep. Um, in the near term for Artis, we're gonna start by supporting the Artis astronauts, which are gonna be small crews of astronauts. Um, you know, two to six in the near term. >>And to answer your question, uh, you know, in a different way, the habitat that we're actually gonna build, it's gonna take dozens of these robotic systems to build and maintain over time. And when we're actually talking, timelines, force talks, thousands of people living and working in space, I think that's gonna happen within the next 10 to 15 years. The first few folks are gonna be on the moon by 2025. And we're pushing towards having dozens of people living and working in space and by 2030. >>Yeah. I think it's an awesome goal. And I think it's doable question I'll have for you is the role of software in all this. I had a conversation with, uh, space nerd and we were talking and, and I said open sources everywhere now in the software. Yeah. How do you repair in space? Does you know, you don't want to have a firmware be down. So send down backhoe back to the United States. The us, wait a minute, it's the planet. I gotta go back to earth. Yeah. To get apart. So how does break fix work in space? How, how do you guys see that problem? >>So this one's actually quite fun. I mean, currently we don't have astronauts that can pick up a or change a tire. Uh, so you have to make robots that are really reliable, right. That can continuously operate for years at a time. But when you're talking about long-term repairs, there's some really cool ideas and concepts about standardization of some of these parts, you know, just like Lu knots on your car, right? Yeah. If everyone has the same Lu knots on their wheel, great. Now I can go change it out. I can switch off different parts that are available on the line surface. So I think we're moving towards, uh, that in the long >>Term you guys got a great company. Love the mission. Final question for both of you is I noticed that there's a huge community development around Mars, living on Mars, living on the moon. I mean, there's not a chat group that clubhouse app used, used to be around just kind of dying. But now it's when the Twitter spaces Reddit, you name it, there's a fanatical fan base that loves to talk about an engineer and kind of a collective intelligence, not, may not be official engineering, but they just love to talk about it. So there's a huge fan base for space. How does someone get involved if they really want to dive in and then how do you nurture that audience? How does that, is it developing? What's your take on this whole movement? It's it's beyond just being interested. It's it's become, I won't say cult-like but it's been, there's very, a lot of people in young people interested in space. >>Yeah. >>Yeah. There's, there's a whole, lots of places to get involved. There's, you know, societies, right? Like the Mar society there's technical committees, um, there's, you know, even potentially learning about these, you know, taking a space, resources master program and getting into the field and, and joining the company. So, um, we really, uh, thrive on that energy from the community and it really helps press us forward. And we hope to, uh, have a way to take everyone with us on the mission. And so stay tuned, follow our website. We'll be announcing some of that stuff soon. >>Awesome. And just one last, uh, quick pitch for you, John, I'll leave you with one thought. There are two things that space has an infinite amount of the first is power and the second is resources. And if we can find a way to access either of those, we can fundamentally change the way humanity operates. Yeah. So when you're talking about living on Mars long term, we're gonna need to access the resource from Mars. And then long term, once we get the transportation infrastructure in place, we can start bringing those resources back here to earth. So of course there are gonna be those people that sign up for that first mission out to Mars with SpaceX. But, uh, we'd love for folks to join on with us at lunar outpost and be a part of that kind of next leap accessing those resources. >>I love the mission, as always said, once in the cube, everything in star Trek will be invented someday. <laugh>, we're almost there except for the, the, uh, the transporter room. We don't have that done yet, but almost soon be there. All right. Well, thanks for coming. I, I really appreciate Justin for us for sharing. Great story. Final minute. Give a plug for the company. What are you guys looking for? You said hiring. Yep. Anything else you'd like to share? Put a plug in for lunar outpost. >>Absolutely. So we're hiring across the board, aerospace engineering, robotics engineering, sales marketing. Doesn't really matter. Uh, we're doubling as a company currently around 58 people, as we said, and we're looking for the top people that want to make an impact in aerospace. This is truly a unique moment. First time we've ever had continuous reliable operations. First time NASA is pushing really hard on the public private partnerships for commercial companies like ours to go out and create this sustainable presence on the moon. So whether you wanna work with us, our partner with us, we'd be excited to talk to you and, uh, yeah. Please contact us at info. Lunar outpost.com. >>We'll certainly follow up. Thanks for coming. I love the mission we're behind you and everyone else is too. You can see the energy it's gonna happen. It's the cube coverage from re Mars new actions happening in space on the ground, in the, on the moon you name it's happening right here in Vegas. I'm John furrier. Thanks for watching.

(upbeat music) >> The ascendancy of cloud and SAS has shown new light on how organizations think about, pay for, and value hardware. Once sought after skills for practitioners with expertise in hardware troubleshooting, configuring ports, tuning storage arrays, and maximizing server utilization has been superseded by demand for cloud architects, DevOps pros, developers with expertise in microservices, container, application development, and like. Even a company like Dell, the largest hardware company in enterprise tech touts that it has more software engineers than those working in hardware. Begs the question, is hardware going the way of Coball? Well, not likely. Software has to run on something, but the labor needed to deploy, and troubleshoot, and manage hardware infrastructure is shifting. At the same time, we've seen the value flow also shifting in hardware. Once a world dominated by X86 processors value is flowing to alternatives like Nvidia and arm based designs. Moreover, other componentry like NICs, accelerators, and storage controllers are becoming more advanced, integrated, and increasingly important. The question is, does it matter? And if so, why does it matter and to whom? What does it mean to customers, workloads, OEMs, and the broader society? Hello and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this breaking analysis, we've organized a special power panel of industry analysts and experts to address the question, does hardware still matter? Allow me to introduce the panel. Bob O'Donnell is president and chief analyst at TECHnalysis Research. Zeus Kerravala is the founder and principal analyst at ZK Research. David Nicholson is a CTO and tech expert. Keith Townson is CEO and founder of CTO Advisor. And Marc Staimer is the chief dragon slayer at Dragon Slayer Consulting and oftentimes a Wikibon contributor. Guys, welcome to theCUBE. Thanks so much for spending some time here. >> Good to be here. >> Thanks. >> Thanks for having us. >> Okay before we get into it, I just want to bring up some data from ETR. This is a survey that ETR does every quarter. It's a survey of about 1200 to 1500 CIOs and IT buyers and I'm showing a subset of the taxonomy here. This XY axis and the vertical axis is something called net score. That's a measure of spending momentum. It's essentially the percentage of customers that are spending more on a particular area than those spending less. You subtract the lesses from the mores and you get a net score. Anything the horizontal axis is pervasion in the data set. Sometimes they call it market share. It's not like IDC market share. It's just the percentage of activity in the data set as a percentage of the total. That red 40% line, anything over that is considered highly elevated. And for the past, I don't know, eight to 12 quarters, the big four have been AI and machine learning, containers, RPA and cloud and cloud of course is very impressive because not only is it elevated in the vertical access, but you know it's very highly pervasive on the horizontal. So what I've done is highlighted in red that historical hardware sector. The server, the storage, the networking, and even PCs despite the work from home are depressed in relative terms. And of course, data center collocation services. Okay so you're seeing obviously hardware is not... People don't have the spending momentum today that they used to. They've got other priorities, et cetera, but I want to start and go kind of around the horn with each of you, what is the number one trend that each of you sees in hardware and why does it matter? Bob O'Donnell, can you please start us off? >> Sure Dave, so look, I mean, hardware is incredibly important and one comment first I'll make on that slide is let's not forget that hardware, even though it may not be growing, the amount of money spent on hardware continues to be very, very high. It's just a little bit more stable. It's not as subject to big jumps as we see certainly in other software areas. But look, the important thing that's happening in hardware is the diversification of the types of chip architectures we're seeing and how and where they're being deployed, right? You refer to this in your opening. We've moved from a world of x86 CPUs from Intel and AMD to things like obviously GPUs, DPUs. We've got VPU for, you know, computer vision processing. We've got AI-dedicated accelerators, we've got all kinds of other network acceleration tools and AI-powered tools. There's an incredible diversification of these chip architectures and that's been happening for a while but now we're seeing them more widely deployed and it's being done that way because workloads are evolving. The kinds of workloads that we're seeing in some of these software areas require different types of compute engines than traditionally we've had. The other thing is (coughs), excuse me, the power requirements based on where geographically that compute happens is also evolving. This whole notion of the edge, which I'm sure we'll get into a little bit more detail later is driven by the fact that where the compute actually sits closer to in theory the edge and where edge devices are, depending on your definition, changes the power requirements. It changes the kind of connectivity that connects the applications to those edge devices and those applications. So all of those things are being impacted by this growing diversity in chip architectures. And that's a very long-term trend that I think we're going to continue to see play out through this decade and well into the 2030s as well. >> Excellent, great, great points. Thank you, Bob. Zeus up next, please. >> Yeah, and I think the other thing when you look at this chart to remember too is, you know, through the pandemic and the work from home period a lot of companies did put their office modernization projects on hold and you heard that echoed, you know, from really all the network manufacturers anyways. They always had projects underway to upgrade networks. They put 'em on hold. Now that people are starting to come back to the office, they're looking at that now. So we might see some change there, but Bob's right. The size of those market are quite a bit different. I think the other big trend here is the hardware companies, at least in the areas that I look at networking are understanding now that it's a combination of hardware and software and silicon that works together that creates that optimum type of performance and experience, right? So some things are best done in silicon. Some like data forwarding and things like that. Historically when you look at the way network devices were built, you did everything in hardware. You configured in hardware, they did all the data for you, and did all the management. And that's been decoupled now. So more and more of the control element has been placed in software. A lot of the high-performance things, encryption, and as I mentioned, data forwarding, packet analysis, stuff like that is still done in hardware, but not everything is done in hardware. And so it's a combination of the two. I think, for the people that work with the equipment as well, there's been more shift to understanding how to work with software. And this is a mistake I think the industry made for a while is we had everybody convinced they had to become a programmer. It's really more a software power user. Can you pull things out of software? Can you through API calls and things like that. But I think the big frame here is, David, it's a combination of hardware, software working together that really make a difference. And you know how much you invest in hardware versus software kind of depends on the performance requirements you have. And I'll talk about that later but that's really the big shift that's happened here. It's the vendors that figured out how to optimize performance by leveraging the best of all of those. >> Excellent. You guys both brought up some really good themes that we can tap into Dave Nicholson, please. >> Yeah, so just kind of picking up where Bob started off. Not only are we seeing the rise of a variety of CPU designs, but I think increasingly the connectivity that's involved from a hardware perspective, from a kind of a server or service design perspective has become increasingly important. I think we'll get a chance to look at this in more depth a little bit later but when you look at what happens on the motherboard, you know we're not in so much a CPU-centric world anymore. Various application environments have various demands and you can meet them by using a variety of components. And it's extremely significant when you start looking down at the component level. It's really important that you optimize around those components. So I guess my summary would be, I think we are moving out of the CPU-centric hardware model into more of a connectivity-centric model. We can talk more about that later. >> Yeah, great. And thank you, David, and Keith Townsend I really interested in your perspectives on this. I mean, for years you worked in a data center surrounded by hardware. Now that we have the software defined data center, please chime in here. >> Well, you know, I'm going to dig deeper into that software-defined data center nature of what's happening with hardware. Hardware is meeting software infrastructure as code is a thing. What does that code look like? We're still trying to figure out but servicing up these capabilities that the previous analysts have brought up, how do I ensure that I can get the level of services needed for the applications that I need? Whether they're legacy, traditional data center, workloads, AI ML, workloads, workloads at the edge. How do I codify that and consume that as a service? And hardware vendors are figuring this out. HPE, the big push into GreenLake as a service. Dale now with Apex taking what we need, these bare bone components, moving it forward with DDR five, six CXL, et cetera, and surfacing that as cold or as services. This is a very tough problem. As we transition from consuming a hardware-based configuration to this infrastructure as cold paradigm shift. >> Yeah, programmable infrastructure, really attacking that sort of labor discussion that we were having earlier, okay. Last but not least Marc Staimer, please. >> Thanks, Dave. My peers raised really good points. I agree with most of them, but I'm going to disagree with the title of this session, which is, does hardware matter? It absolutely matters. You can't run software on the air. You can't run it in an ephemeral cloud, although there's the technical cloud and that's a different issue. The cloud is kind of changed everything. And from a market perspective in the 40 plus years I've been in this business, I've seen this perception that hardware has to go down in price every year. And part of that was driven by Moore's law. And we're coming to, let's say a lag or an end, depending on who you talk to Moore's law. So we're not doubling our transistors every 18 to 24 months in a chip and as a result of that, there's been a higher emphasis on software. From a market perception, there's no penalty. They don't put the same pressure on software from the market to reduce the cost every year that they do on hardware, which kind of bass ackwards when you think about it. Hardware costs are fixed. Software costs tend to be very low. It's kind of a weird thing that we do in the market. And what's changing is we're now starting to treat hardware like software from an OPEX versus CapEx perspective. So yes, hardware matters. And we'll talk about that more in length. >> You know, I want to follow up on that. And I wonder if you guys have a thought on this, Bob O'Donnell, you and I have talked about this a little bit. Marc, you just pointed out that Moore's laws could have waning. Pat Gelsinger recently at their investor meeting said that he promised that Moore's law is alive and well. And the point I made in breaking analysis was okay, great. You know, Pat said, doubling transistors every 18 to 24 months, let's say that Intel can do that. Even though we know it's waning somewhat. Look at the M1 Ultra from Apple (chuckles). In about 15 months increased transistor density on their package by 6X. So to your earlier point, Bob, we have this sort of these alternative processors that are really changing things. And to Dave Nicholson's point, there's a whole lot of supporting components as well. Do you have a comment on that, Bob? >> Yeah, I mean, it's a great point, Dave. And one thing to bear in mind as well, not only are we seeing a diversity of these different chip architectures and different types of components as a number of us have raised the other big point and I think it was Keith that mentioned it. CXL and interconnect on the chip itself is dramatically changing it. And a lot of the more interesting advances that are going to continue to drive Moore's law forward in terms of the way we think about performance, if perhaps not number of transistors per se, is the interconnects that become available. You're seeing the development of chiplets or tiles, people use different names, but the idea is you can have different components being put together eventually in sort of a Lego block style. And what that's also going to allow, not only is that going to give interesting performance possibilities 'cause of the faster interconnect. So you can share, have shared memory between things which for big workloads like AI, huge data sets can make a huge difference in terms of how you talk to memory over a network connection, for example, but not only that you're going to see more diversity in the types of solutions that can be built. So we're going to see even more choices in hardware from a silicon perspective because you'll be able to piece together different elements. And oh, by the way, the other benefit of that is we've reached a point in chip architectures where not everything benefits from being smaller. We've been so focused and so obsessed when it comes to Moore's law, to the size of each individual transistor and yes, for certain architecture types, CPUs and GPUs in particular, that's absolutely true, but we've already hit the point where things like RF for 5g and wifi and other wireless technologies and a whole bunch of other things actually don't get any better with a smaller transistor size. They actually get worse. So the beauty of these chiplet architectures is you could actually combine different chip manufacturing sizes. You know you hear about four nanometer and five nanometer along with 14 nanometer on a single chip, each one optimized for its specific application yet together, they can give you the best of all worlds. And so we're just at the very beginning of that era, which I think is going to drive a ton of innovation. Again, gets back to my comment about different types of devices located geographically different places at the edge, in the data center, you know, in a private cloud versus a public cloud. All of those things are going to be impacted and there'll be a lot more options because of this silicon diversity and this interconnect diversity that we're just starting to see. >> Yeah, David. David Nicholson's got a graphic on that. They're going to show later. Before we do that, I want to introduce some data. I actually want to ask Keith to comment on this before we, you know, go on. This next slide is some data from ETR that shows the percent of customers that cited difficulty procuring hardware. And you can see the red is they had significant issues and it's most pronounced in laptops and networking hardware on the far right-hand side, but virtually all categories, firewalls, peripheral servers, storage are having moderately difficult procurement issues. That's the sort of pinkish or significant challenges. So Keith, I mean, what are you seeing with your customers in the hardware supply chains and bottlenecks? And you know we're seeing it with automobiles and appliances but so it goes beyond IT. The semiconductor, you know, challenges. What's been the impact on the buyer community and society and do you have any sense as to when it will subside? >> You know, I was just asked this question yesterday and I'm feeling the pain. People question, kind of a side project within the CTO advisor, we built a hybrid infrastructure, traditional IT data center that we're walking with the traditional customer and modernizing that data center. So it was, you know, kind of a snapshot of time in 2016, 2017, 10 gigabit, ARISTA switches, some older Dell's 730 XD switches, you know, speeds and feeds. And we said we would modern that with the latest Intel stack and connected to the public cloud and then the pandemic hit and we are experiencing a lot of the same challenges. I thought we'd easily migrate from 10 gig networking to 25 gig networking path that customers are going on. The 10 gig network switches that I bought used are now double the price because you can't get legacy 10 gig network switches because all of the manufacturers are focusing on the more profitable 25 gig for capacity, even the 25 gig switches. And we're focused on networking right now. It's hard to procure. We're talking about nine to 12 months or more lead time. So we're seeing customers adjust by adopting cloud. But if you remember early on in the pandemic, Microsoft Azure kind of gated customers that didn't have a capacity agreement. So customers are keeping an eye on that. There's a desire to abstract away from the underlying vendor to be able to control or provision your IT services in a way that we do with VMware VP or some other virtualization technology where it doesn't matter who can get me the hardware, they can just get me the hardware because it's critically impacting projects and timelines. >> So that's a great setup Zeus for you with Keith mentioned the earlier the software-defined data center with software-defined networking and cloud. Do you see a day where networking hardware is monetized and it's all about the software, or are we there already? >> No, we're not there already. And I don't see that really happening any time in the near future. I do think it's changed though. And just to be clear, I mean, when you look at that data, this is saying customers have had problems procuring the equipment, right? And there's not a network vendor out there. I've talked to Norman Rice at Extreme, and I've talked to the folks at Cisco and ARISTA about this. They all said they could have had blowout quarters had they had the inventory to ship. So it's not like customers aren't buying this anymore. Right? I do think though, when it comes to networking network has certainly changed some because there's a lot more controls as I mentioned before that you can do in software. And I think the customers need to start thinking about the types of hardware they buy and you know, where they're going to use it and, you know, what its purpose is. Because I've talked to customers that have tried to run software and commodity hardware and where the performance requirements are very high and it's bogged down, right? It just doesn't have the horsepower to run it. And, you know, even when you do that, you have to start thinking of the components you use. The NICs you buy. And I've talked to customers that have simply just gone through the process replacing a NIC card and a commodity box and had some performance problems and, you know, things like that. So if agility is more important than performance, then by all means try running software on commodity hardware. I think that works in some cases. If performance though is more important, that's when you need that kind of turnkey hardware system. And I've actually seen more and more customers reverting back to that model. In fact, when you talk to even some startups I think today about when they come to market, they're delivering things more on appliances because that's what customers want. And so there's this kind of app pivot this pendulum of agility and performance. And if performance absolutely matters, that's when you do need to buy these kind of turnkey, prebuilt hardware systems. If agility matters more, that's when you can go more to software, but the underlying hardware still does matter. So I think, you know, will we ever have a day where you can just run it on whatever hardware? Maybe but I'll long be retired by that point. So I don't care. >> Well, you bring up a good point Zeus. And I remember the early days of cloud, the narrative was, oh, the cloud vendors. They don't use EMC storage, they just run on commodity storage. And then of course, low and behold, you know, they've trot out James Hamilton to talk about all the custom hardware that they were building. And you saw Google and Microsoft follow suit. >> Well, (indistinct) been falling for this forever. Right? And I mean, all the way back to the turn of the century, we were calling for the commodity of hardware. And it's never really happened because you can still drive. As long as you can drive innovation into it, customers will always lean towards the innovation cycles 'cause they get more features faster and things. And so the vendors have done a good job of keeping that cycle up but it'll be a long time before. >> Yeah, and that's why you see companies like Pure Storage. A storage company has 69% gross margins. All right. I want to go jump ahead. We're going to bring up the slide four. I want to go back to something that Bob O'Donnell was talking about, the sort of supporting act. The diversity of silicon and we've marched to the cadence of Moore's law for decades. You know, we asked, you know, is Moore's law dead? We say it's moderating. Dave Nicholson. You want to talk about those supporting components. And you shared with us a slide that shift. You call it a shift from a processor-centric world to a connect-centric world. What do you mean by that? And let's bring up slide four and you can talk to that. >> Yeah, yeah. So first, I want to echo this sentiment that the question does hardware matter is sort of the answer is of course it matters. Maybe the real question should be, should you care about it? And the answer to that is it depends who you are. If you're an end user using an application on your mobile device, maybe you don't care how the architecture is put together. You just care that the service is delivered but as you back away from that and you get closer and closer to the source, someone needs to care about the hardware and it should matter. Why? Because essentially what hardware is doing is it's consuming electricity and dollars and the more efficiently you can configure hardware, the more bang you're going to get for your buck. So it's not only a quantitative question in terms of how much can you deliver? But it also ends up being a qualitative change as capabilities allow for things we couldn't do before, because we just didn't have the aggregate horsepower to do it. So this chart actually comes out of some performance tests that were done. So it happens to be Dell servers with Broadcom components. And the point here was to peel back, you know, peel off the top of the server and look at what's in that server, starting with, you know, the PCI interconnect. So PCIE gen three, gen four, moving forward. What are the effects on from an interconnect versus on performance application performance, translating into new orders per minute, processed per dollar, et cetera, et cetera? If you look at the advances in CPU architecture mapped against the advances in interconnect and storage subsystem performance, you can see that CPU architecture is sort of lagging behind in a way. And Bob mentioned this idea of tiling and all of the different ways to get around that. When we do performance testing, we can actually peg CPUs, just running the performance tests without any actual database environments working. So right now we're at this sort of imbalance point where you have to make sure you design things properly to get the most bang per kilowatt hour of power per dollar input. So the key thing here what this is highlighting is just as a very specific example, you take a card that's designed as a gen three PCIE device, and you plug it into a gen four slot. Now the card is the bottleneck. You plug a gen four card into a gen four slot. Now the gen four slot is the bottleneck. So we're constantly chasing these bottlenecks. Someone has to be focused on that from an architectural perspective, it's critically important. So there's no question that it matters. But of course, various people in this food chain won't care where it comes from. I guess a good analogy might be, where does our food come from? If I get a steak, it's a pink thing wrapped in plastic, right? Well, there are a lot of inputs that a lot of people have to care about to get that to me. Do I care about all of those things? No. Are they important? They're critically important. >> So, okay. So all I want to get to the, okay. So what does this all mean to customers? And so what I'm hearing from you is to balance a system it's becoming, you know, more complicated. And I kind of been waiting for this day for a long time, because as we all know the bottleneck was always the spinning disc, the last mechanical. So people who wrote software knew that when they were doing it right, the disc had to go and do stuff. And so they were doing other things in the software. And now with all these new interconnects and flash and things like you could do atomic rights. And so that opens up new software possibilities and combine that with alternative processes. But what's the so what on this to the customer and the application impact? Can anybody address that? >> Yeah, let me address that for a moment. I want to leverage some of the things that Bob said, Keith said, Zeus said, and David said, yeah. So I'm a bit of a contrarian in some of this. For example, on the chip side. As the chips get smaller, 14 nanometer, 10 nanometer, five nanometer, soon three nanometer, we talk about more cores, but the biggest problem on the chip is the interconnect from the chip 'cause the wires get smaller. People don't realize in 2004 the latency on those wires in the chips was 80 picoseconds. Today it's 1300 picoseconds. That's on the chip. This is why they're not getting faster. So we maybe getting a little bit slowing down in Moore's law. But even as we kind of conquer that you still have the interconnect problem and the interconnect problem goes beyond the chip. It goes within the system, composable architectures. It goes to the point where Keith made, ultimately you need a hybrid because what we're seeing, what I'm seeing and I'm talking to customers, the biggest issue they have is moving data. Whether it be in a chip, in a system, in a data center, between data centers, moving data is now the biggest gating item in performance. So if you want to move it from, let's say your transactional database to your machine learning, it's the bottleneck, it's moving the data. And so when you look at it from a distributed environment, now you've got to move the compute to the data. The only way to get around these bottlenecks today is to spend less time in trying to move the data and more time in taking the compute, the software, running on hardware closer to the data. Go ahead. >> So is this what you mean when Nicholson was talking about a shift from a processor centric world to a connectivity centric world? You're talking about moving the bits across all the different components, not having the processor you're saying is essentially becoming the bottleneck or the memory, I guess. >> Well, that's one of them and there's a lot of different bottlenecks, but it's the data movement itself. It's moving away from, wait, why do we need to move the data? Can we move the compute, the processing closer to the data? Because if we keep them separate and this has been a trend now where people are moving processing away from it. It's like the edge. I think it was Zeus or David. You were talking about the edge earlier. As you look at the edge, who defines the edge, right? Is the edge a closet or is it a sensor? If it's a sensor, how do you do AI at the edge? When you don't have enough power, you don't have enough computable. People were inventing chips to do that. To do all that at the edge, to do AI within the sensor, instead of moving the data to a data center or a cloud to do the processing. Because the lag in latency is always limited by speed of light. How fast can you move the electrons? And all this interconnecting, all the processing, and all the improvement we're seeing in the PCIE bus from three, to four, to five, to CXL, to a higher bandwidth on the network. And that's all great but none of that deals with the speed of light latency. And that's an-- Go ahead. >> You know Marc, no, I just want to just because what you're referring to could be looked at at a macro level, which I think is what you're describing. You can also look at it at a more micro level from a systems design perspective, right? I'm going to be the resident knuckle dragging hardware guy on the panel today. But it's exactly right. You moving compute closer to data includes concepts like peripheral cards that have built in intelligence, right? So again, in some of this testing that I'm referring to, we saw dramatic improvements when you basically took the horsepower instead of using the CPU horsepower for the like IO. Now you have essentially offload engines in the form of storage controllers, rate controllers, of course, for ethernet NICs, smart NICs. And so when you can have these sort of offload engines and we've gone through these waves over time. People think, well, wait a minute, raid controller and NVMe? You know, flash storage devices. Does that make sense? It turns out it does. Why? Because you're actually at a micro level doing exactly what you're referring to. You're bringing compute closer to the data. Now, closer to the data meaning closer to the data storage subsystem. It doesn't solve the macro issue that you're referring to but it is important. Again, going back to this idea of system design optimization, always chasing the bottleneck, plugging the holes. Someone needs to do that in this value chain in order to get the best value for every kilowatt hour of power and every dollar. >> Yeah. >> Well this whole drive performance has created some really interesting architectural designs, right? Like Nickelson, the rise of the DPU right? Brings more processing power into systems that already had a lot of processing power. There's also been some really interesting, you know, kind of innovation in the area of systems architecture too. If you look at the way Nvidia goes to market, their drive kit is a prebuilt piece of hardware, you know, optimized for self-driving cars, right? They partnered with Pure Storage and ARISTA to build that AI-ready infrastructure. I remember when I talked to Charlie Giancarlo, the CEO of Pure about when the three companies rolled that out. He said, "Look, if you're going to do AI, "you need good store. "You need fast storage, fast processor and fast network." And so for customers to be able to put that together themselves was very, very difficult. There's a lot of software that needs tuning as well. So the three companies partner together to create a fully integrated turnkey hardware system with a bunch of optimized software that runs on it. And so in that case, in some ways the hardware was leading the software innovation. And so, the variety of different architectures we have today around hardware has really exploded. And I think it, part of the what Bob brought up at the beginning about the different chip design. >> Yeah, Bob talked about that earlier. Bob, I mean, most AI today is modeling, you know, and a lot of that's done in the cloud and it looks from my standpoint anyway that the future is going to be a lot of AI inferencing at the edge. And that's a radically different architecture, Bob, isn't it? >> It is, it's a completely different architecture. And just to follow up on a couple points, excellent conversation guys. Dave talked about system architecture and really this that's what this boils down to, right? But it's looking at architecture at every level. I was talking about the individual different components the new interconnect methods. There's this new thing called UCIE universal connection. I forget what it stands answer for, but it's a mechanism for doing chiplet architectures, but then again, you have to take it up to the system level, 'cause it's all fine and good. If you have this SOC that's tuned and optimized, but it has to talk to the rest of the system. And that's where you see other issues. And you've seen things like CXL and other interconnect standards, you know, and nobody likes to talk about interconnect 'cause it's really wonky and really technical and not that sexy, but at the end of the day it's incredibly important exactly. To the other points that were being raised like mark raised, for example, about getting that compute closer to where the data is and that's where again, a diversity of chip architectures help and exactly to your last comment there Dave, putting that ability in an edge device is really at the cutting edge of what we're seeing on a semiconductor design and the ability to, for example, maybe it's an FPGA, maybe it's a dedicated AI chip. It's another kind of chip architecture that's being created to do that inferencing on the edge. Because again, it's that the cost and the challenges of moving lots of data, whether it be from say a smartphone to a cloud-based application or whether it be from a private network to a cloud or any other kinds of permutations we can think of really matters. And the other thing is we're tackling bigger problems. So architecturally, not even just architecturally within a system, but when we think about DPUs and the sort of the east west data center movement conversation that we hear Nvidia and others talk about, it's about combining multiple sets of these systems to function together more efficiently again with even bigger sets of data. So really is about tackling where the processing is needed, having the interconnect and the ability to get where the data you need to the right place at the right time. And because those needs are diversifying, we're just going to continue to see an explosion of different choices and options, which is going to make hardware even more essential I would argue than it is today. And so I think what we're going to see not only does hardware matter, it's going to matter even more in the future than it does now. >> Great, yeah. Great discussion, guys. I want to bring Keith back into the conversation here. Keith, if your main expertise in tech is provisioning LUNs, you probably you want to look for another job. So maybe clearly hardware matters, but with software defined everything, do people with hardware expertise matter outside of for instance, component manufacturers or cloud companies? I mean, VMware certainly changed the dynamic in servers. Dell just spun off its most profitable asset and VMware. So it obviously thinks hardware can stand alone. How does an enterprise architect view the shift to software defined hyperscale cloud and how do you see the shifting demand for skills in enterprise IT? >> So I love the question and I'll take a different view of it. If you're a data analyst and your primary value add is that you do ETL transformation, talk to a CDO, a chief data officer over midsize bank a little bit ago. He said 80% of his data scientists' time is done on ETL. Super not value ad. He wants his data scientists to do data science work. Chances are if your only value is that you do LUN provisioning, then you probably don't have a job now. The technologies have gotten much more intelligent. As infrastructure pros, we want to give infrastructure pros the opportunities to shine and I think the software defined nature and the automation that we're seeing vendors undertake, whether it's Dell, HP, Lenovo take your pick that Pure Storage, NetApp that are doing the automation and the ML needed so that these practitioners don't spend 80% of their time doing LUN provisioning and focusing on their true expertise, which is ensuring that data is stored. Data is retrievable, data's protected, et cetera. I think the shift is to focus on that part of the job that you're ensuring no matter where the data's at, because as my data is spread across the enterprise hybrid different types, you know, Dave, you talk about the super cloud a lot. If my data is in the super cloud, protecting that data and securing that data becomes much more complicated when than when it was me just procuring or provisioning LUNs. So when you say, where should the shift be, or look be, you know, focusing on the real value, which is making sure that customers can access data, can recover data, can get data at performance levels that they need within the price point. They need to get at those datasets and where they need it. We talked a lot about where they need out. One last point about this interconnecting. I have this vision and I think we all do of composable infrastructure. This idea that scaled out does not solve every problem. The cloud can give me infinite scale out. Sometimes I just need a single OS with 64 terabytes of RAM and 204 GPUs or GPU instances that single OS does not exist today. And the opportunity is to create composable infrastructure so that we solve a lot of these problems that just simply don't scale out. >> You know, wow. So many interesting points there. I had just interviewed Zhamak Dehghani, who's the founder of Data Mesh last week. And she made a really interesting point. She said, "Think about, we have separate stacks. "We have an application stack and we have "a data pipeline stack and the transaction systems, "the transaction database, we extract data from that," to your point, "We ETL it in, you know, it takes forever. "And then we have this separate sort of data stack." If we're going to inject more intelligence and data and AI into applications, those two stacks, her contention is they have to come together. And when you think about, you know, super cloud bringing compute to data, that was what Haduck was supposed to be. It ended up all sort of going into a central location, but it's almost a rhetorical question. I mean, it seems that that necessitates new thinking around hardware architectures as it kind of everything's the edge. And the other point is to your point, Keith, it's really hard to secure that. So when you can think about offloads, right, you've heard the stats, you know, Nvidia talks about it. Broadcom talks about it that, you know, that 30%, 25 to 30% of the CPU cycles are wasted on doing things like storage offloads, or networking or security. It seems like maybe Zeus you have a comment on this. It seems like new architectures need to come other to support, you know, all of that stuff that Keith and I just dispute. >> Yeah, and by the way, I do want to Keith, the question you just asked. Keith, it's the point I made at the beginning too about engineers do need to be more software-centric, right? They do need to have better software skills. In fact, I remember talking to Cisco about this last year when they surveyed their engineer base, only about a third of 'em had ever made an API call, which you know that that kind of shows this big skillset change, you know, that has to come. But on the point of architectures, I think the big change here is edge because it brings in distributed compute models. Historically, when you think about compute, even with multi-cloud, we never really had multi-cloud. We'd use multiple centralized clouds, but compute was always centralized, right? It was in a branch office, in a data center, in a cloud. With edge what we creates is the rise of distributed computing where we'll have an application that actually accesses different resources and at different edge locations. And I think Marc, you were talking about this, like the edge could be in your IoT device. It could be your campus edge. It could be cellular edge, it could be your car, right? And so we need to start thinkin' about how our applications interact with all those different parts of that edge ecosystem, you know, to create a single experience. The consumer apps, a lot of consumer apps largely works that way. If you think of like app like Uber, right? It pulls in information from all kinds of different edge application, edge services. And, you know, it creates pretty cool experience. We're just starting to get to that point in the business world now. There's a lot of security implications and things like that, but I do think it drives more architectural decisions to be made about how I deploy what data where and where I do my processing, where I do my AI and things like that. It actually makes the world more complicated. In some ways we can do so much more with it, but I think it does drive us more towards turnkey systems, at least initially in order to, you know, ensure performance and security. >> Right. Marc, I wanted to go to you. You had indicated to me that you wanted to chat about this a little bit. You've written quite a bit about the integration of hardware and software. You know, we've watched Oracle's move from, you know, buying Sun and then basically using that in a highly differentiated approach. Engineered systems. What's your take on all that? I know you also have some thoughts on the shift from CapEx to OPEX chime in on that. >> Sure. When you look at it, there are advantages to having one vendor who has the software and hardware. They can synergistically make them work together that you can't do in a commodity basis. If you own the software and somebody else has the hardware, I'll give you an example would be Oracle. As you talked about with their exit data platform, they literally are leveraging microcode in the Intel chips. And now in AMD chips and all the way down to Optane, they make basically AMD database servers work with Optane memory PMM in their storage systems, not MVME, SSD PMM. I'm talking about the cards itself. So there are advantages you can take advantage of if you own the stack, as you were putting out earlier, Dave, of both the software and the hardware. Okay, that's great. But on the other side of that, that tends to give you better performance, but it tends to cost a little more. On the commodity side it costs less but you get less performance. What Zeus had said earlier, it depends where you're running your application. How much performance do you need? What kind of performance do you need? One of the things about moving to the edge and I'll get to the OPEX CapEx in a second. One of the issues about moving to the edge is what kind of processing do you need? If you're running in a CCTV camera on top of a traffic light, how much power do you have? How much cooling do you have that you can run this? And more importantly, do you have to take the data you're getting and move it somewhere else and get processed and the information is sent back? I mean, there are companies out there like Brain Chip that have developed AI chips that can run on the sensor without a CPU. Without any additional memory. So, I mean, there's innovation going on to deal with this question of data movement. There's companies out there like Tachyon that are combining GPUs, CPUs, and DPUs in a single chip. Think of it as super composable architecture. They're looking at being able to do more in less. On the OPEX and CapEx issue. >> Hold that thought, hold that thought on the OPEX CapEx, 'cause we're running out of time and maybe you can wrap on that. I just wanted to pick up on something you said about the integrated hardware software. I mean, other than the fact that, you know, Michael Dell unlocked whatever $40 billion for himself and Silverlake, I was always a fan of a spin in with VMware basically become the Oracle of hardware. Now I know it would've been a nightmare for the ecosystem and culturally, they probably would've had a VMware brain drain, but what does anybody have any thoughts on that as a sort of a thought exercise? I was always a fan of that on paper. >> I got to eat a little crow. I did not like the Dale VMware acquisition for the industry in general. And I think it hurt the industry in general, HPE, Cisco walked away a little bit from that VMware relationship. But when I talked to customers, they loved it. You know, I got to be honest. They absolutely loved the integration. The VxRail, VxRack solution exploded. Nutanix became kind of a afterthought when it came to competing. So that spin in, when we talk about the ability to innovate and the ability to create solutions that you just simply can't create because you don't have the full stack. Dell was well positioned to do that with a potential span in of VMware. >> Yeah, we're going to be-- Go ahead please. >> Yeah, in fact, I think you're right, Keith, it was terrible for the industry. Great for Dell. And I remember talking to Chad Sakac when he was running, you know, VCE, which became Rack and Rail, their ability to stay in lockstep with what VMware was doing. What was the number one workload running on hyperconverged forever? It was VMware. So their ability to remain in lockstep with VMware gave them a huge competitive advantage. And Dell came out of nowhere in, you know, the hyper-converged market and just started taking share because of that relationship. So, you know, this sort I guess it's, you know, from a Dell perspective I thought it gave them a pretty big advantage that they didn't really exploit across their other properties, right? Networking and service and things like they could have given the dominance that VMware had. From an industry perspective though, I do think it's better to have them be coupled. So. >> I agree. I mean, they could. I think they could have dominated in super cloud and maybe they would become the next Oracle where everybody hates 'em, but they kick ass. But guys. We got to wrap up here. And so what I'm going to ask you is I'm going to go and reverse the order this time, you know, big takeaways from this conversation today, which guys by the way, I can't thank you enough phenomenal insights, but big takeaways, any final thoughts, any research that you're working on that you want highlight or you know, what you look for in the future? Try to keep it brief. We'll go in reverse order. Maybe Marc, you could start us off please. >> Sure, on the research front, I'm working on a total cost of ownership of an integrated database analytics machine learning versus separate services. On the other aspect that I would wanted to chat about real quickly, OPEX versus CapEx, the cloud changed the market perception of hardware in the sense that you can use hardware or buy hardware like you do software. As you use it, pay for what you use in arrears. The good thing about that is you're only paying for what you use, period. You're not for what you don't use. I mean, it's compute time, everything else. The bad side about that is you have no predictability in your bill. It's elastic, but every user I've talked to says every month it's different. And from a budgeting perspective, it's very hard to set up your budget year to year and it's causing a lot of nightmares. So it's just something to be aware of. From a CapEx perspective, you have no more CapEx if you're using that kind of base system but you lose a certain amount of control as well. So ultimately that's some of the issues. But my biggest point, my biggest takeaway from this is the biggest issue right now that everybody I talk to in some shape or form it comes down to data movement whether it be ETLs that you talked about Keith or other aspects moving it between hybrid locations, moving it within a system, moving it within a chip. All those are key issues. >> Great, thank you. Okay, CTO advisor, give us your final thoughts. >> All right. Really, really great commentary. Again, I'm going to point back to us taking the walk that our customers are taking, which is trying to do this conversion of all primary data center to a hybrid of which I have this hard earned philosophy that enterprise IT is additive. When we add a service, we rarely subtract a service. So the landscape and service area what we support has to grow. So our research focuses on taking that walk. We are taking a monolithic application, decomposing that to containers, and putting that in a public cloud, and connecting that back private data center and telling that story and walking that walk with our customers. This has been a super enlightening panel. >> Yeah, thank you. Real, real different world coming. David Nicholson, please. >> You know, it really hearkens back to the beginning of the conversation. You talked about momentum in the direction of cloud. I'm sort of spending my time under the hood, getting grease under my fingernails, focusing on where still the lions share of spend will be in coming years, which is OnPrem. And then of course, obviously data center infrastructure for cloud but really diving under the covers and helping folks understand the ramifications of movement between generations of CPU architecture. I know we all know Sapphire Rapids pushed into the future. When's the next Intel release coming? Who knows? We think, you know, in 2023. There have been a lot of people standing by from a practitioner's standpoint asking, well, what do I do between now and then? Does it make sense to upgrade bits and pieces of hardware or go from a last generation to a current generation when we know the next generation is coming? And so I've been very, very focused on looking at how these connectivity components like rate controllers and NICs. I know it's not as sexy as talking about cloud but just how these opponents completely change the game and actually can justify movement from say a 14th-generation architecture to a 15th-generation architecture today, even though gen 16 is coming, let's say 12 months from now. So that's where I am. Keep my phone number in the Rolodex. I literally reference Rolodex intentionally because like I said, I'm in there under the hood and it's not as sexy. But yeah, so that's what I'm focused on Dave. >> Well, you know, to paraphrase it, maybe derivative paraphrase of, you know, Larry Ellison's rant on what is cloud? It's operating systems and databases, et cetera. Rate controllers and NICs live inside of clouds. All right. You know, one of the reasons I love working with you guys is 'cause have such a wide observation space and Zeus Kerravala you, of all people, you know you have your fingers in a lot of pies. So give us your final thoughts. >> Yeah, I'm not a propeller heady as my chip counterparts here. (all laugh) So, you know, I look at the world a little differently and a lot of my research I'm doing now is the impact that distributed computing has on customer employee experiences, right? You talk to every business and how the experiences they deliver to their customers is really differentiating how they go to market. And so they're looking at these different ways of feeding up data and analytics and things like that in different places. And I think this is going to have a really profound impact on enterprise IT architecture. We're putting more data, more compute in more places all the way down to like little micro edges and retailers and things like that. And so we need the variety. Historically, if you think back to when I was in IT you know, pre-Y2K, we didn't have a lot of choice in things, right? We had a server that was rack mount or standup, right? And there wasn't a whole lot of, you know, differences in choice. But today we can deploy, you know, these really high-performance compute systems on little blades inside servers or inside, you know, autonomous vehicles and things. I think the world from here gets... You know, just the choice of what we have and the way hardware and software works together is really going to, I think, change the world the way we do things. We're already seeing that, like I said, in the consumer world, right? There's so many things you can do from, you know, smart home perspective, you know, natural language processing, stuff like that. And it's starting to hit businesses now. So just wait and watch the next five years. >> Yeah, totally. The computing power at the edge is just going to be mind blowing. >> It's unbelievable what you can do at the edge. >> Yeah, yeah. Hey Z, I just want to say that we know you're not a propeller head and I for one would like to thank you for having your master's thesis hanging on the wall behind you 'cause we know that you studied basket weaving. >> I was actually a physics math major, so. >> Good man. Another math major. All right, Bob O'Donnell, you're going to bring us home. I mean, we've seen the importance of semiconductors and silicon in our everyday lives, but your last thoughts please. >> Sure and just to clarify, by the way I was a great books major and this was actually for my final paper. And so I was like philosophy and all that kind of stuff and literature but I still somehow got into tech. Look, it's been a great conversation and I want to pick up a little bit on a comment Zeus made, which is this it's the combination of the hardware and the software and coming together and the manner with which that needs to happen, I think is critically important. And the other thing is because of the diversity of the chip architectures and all those different pieces and elements, it's going to be how software tools evolve to adapt to that new world. So I look at things like what Intel's trying to do with oneAPI. You know, what Nvidia has done with CUDA. What other platform companies are trying to create tools that allow them to leverage the hardware, but also embrace the variety of hardware that is there. And so as those software development environments and software development tools evolve to take advantage of these new capabilities, that's going to open up a lot of interesting opportunities that can leverage all these new chip architectures. That can leverage all these new interconnects. That can leverage all these new system architectures and figure out ways to make that all happen, I think is going to be critically important. And then finally, I'll mention the research I'm actually currently working on is on private 5g and how companies are thinking about deploying private 5g and the potential for edge applications for that. So I'm doing a survey of several hundred us companies as we speak and really looking forward to getting that done in the next couple of weeks. >> Yeah, look forward to that. Guys, again, thank you so much. Outstanding conversation. Anybody going to be at Dell tech world in a couple of weeks? Bob's going to be there. Dave Nicholson. Well drinks on me and guys I really can't thank you enough for the insights and your participation today. Really appreciate it. Okay, and thank you for watching this special power panel episode of theCube Insights powered by ETR. Remember we publish each week on Siliconangle.com and wikibon.com. All these episodes they're available as podcasts. DM me or any of these guys. I'm at DVellante. You can email me at David.Vellante@siliconangle.com. Check out etr.ai for all the data. This is Dave Vellante. We'll see you next time. (upbeat music)

(upbeat music) >> We're back at AWS re:Invent 2021. It's the biggest hybrid event of the year. One of the few physical events and we're psyched to be here. My name is Dave Vellante, and I'm really pleased to bring back the host emeritus, Stu Miniman, somebody I worked with side-by-side, Stu, for 10 years in a setting much like this, many like this. So, good to have you back. >> Dave, it's great to be here with theCUBE team, family here and re:Invent, Dave. I mean, this show, I remember back, Dave, going to you after the first re:Invent we talked, we were like, "We got to be there." Dave, remember the first year we came, the second year of re:Invent, this is the 10th year now, little card tables, gaming companies, all this stuff. You had Jerry Chen on yesterday and Jerry was comparing like, this is going to be like the next Microsoft. And we bet heavy on this ecosystem. And yeah, we all think this cloud thing, it might be real. 20,000 people here, it's not the 50 or 75,000 that we had in like 2018, 2019, but this ecosystem, what's happening in the cloud, multiple versions of hybrid going on with the event and the services, but yeah, phenomenal stuff. And yeah, it's so nice to see people. >> That's for sure. It's something that we've talked about a lot over the years is, and you remember the early days of re:Invent and to this day, just very a strong developer affinity that AWS has done a tremendous job of building that up and it's their raison d'etre, it's how they approach the market. But now you've been at Red Hat for a bit, obviously as well, developer affinity, what have you learned? Specifically as it relates to the cloud, Kubernetes, hottest thing going, you don't want to do an OpenShift commercial, but it's there, you're in the middle of that mix. What have you learned generally? >> Well, Dave, to the comment that you made about developers here, it's developers and the enterprise. We used to have a joke and say, enterprise developer is an oxymoron, but that line between developers doing stuff, early as a cloud, it was stealth computing. It's they're often doing this stuff and central IT is not managing it. So how do the pieces come together? How do apps and infrastructure, how do those pieces come together? And it's something that Red Hat has been doing a long time. Think about the Linux developer. They might've not have been the app developers, the people building Linux and everything, but they had a decent close tie to it. I'm on the OpenShift team. What we do is cloud, Dave, and we've got a partnership here with Amazon. We GAed our native cloud service earlier this year. Andy Jassy helped name it. It is the beautifully named Red Hat OpenShift Service on AWS or ROSA. But we've done OpenShift on AWS for more than five years, basically since we were doing Kubernetes, it's been here because of course customers doing cloud, where are they? A lot of them are here in Amazon. So I've been loving talking to a lot of customers, understanding how enterprise adoption is increasing, how we can enable developers and help them move faster. And yeah, I mean the quick plug on OpenShift is our service. We've got an SRE team that is going to manage all of that. A friend of the program, Corey Quinn, says, "Hey, an SRE team like that, because you don't want to manage as an enterprise." You don't want to manage Kubernetes. Yeah, you need to understand some of the pieces, but what is important to your business is the applications, your data and all those things and managing the undifferentiated heavy lifting. That's one of the reasons you went to the cloud. So therefore changing your model as to how you consume services in the cloud. And what are we seeing with Amazon, Dave? They're trying to build more solutions, simplify deployments, and offer more solutions including with their ecosystem. >> So I want to ask you. You said enterprise developer is kind of an oxymoron, and I remember, years ago I used to hang around with a lot of heads of application development and insurance companies and financial services, pharmaceutical, and they didn't wear hoodies, but they didn't wear suits either. And then when I talked to guys like Jeff Clark, for instance. He talks about we're building an abstraction layer across clouds, blah, blah, blah, which by the way, I think it is the right strategy. I'm like, "Okay, I'll drink some of that Kool-Aid." And then when I come here, we talked to Adam Selipsky. John flew out and I was on the chime. He goes, "Yeah, that's not hybrid. No, this is nothing like, it's not AWS, AWS is cloud." So, square that circle for me, 'cause you're in both worlds and certainly your strategy is to connect those words. Is that cloud? >> Yeah, right. I mean, Dave, we spent years talking about like is private cloud really a cloud? And when we started coming to the show, there is only one cloud. It is the public cloud and Amazon is the paragon of, I don't know what it was. >> Dave: Fake clouds, cloud washing. >> So today, Amazon's putting lots of things into your data center and extending the cloud out to that environment. >> So that's cloud. >> That's cloud. >> What do we call that cloud? What about the reverse? >> What's happening at the edge is that cloud is that extension of what we said from Amazon. If you look at not only Outpost, but Wavelengths and Local Zones and everything else like that. >> Let's say, yes, that's cloud. The APIs, primitives, check. >> Dave, I've always thought cloud is an operating model, not a location. And the hybrid definition is not the old, I did an ebook on this, Dave earlier this year. It's not the decade old NIS definition of an application that spans because I don't get up in the morning as an enterprise and say, "Oh, let me look at the table of how much Google is charging me or Microsoft or Amazon," or wake up one morning and move from one cloud to the other. Portability, follow the sun type stuff, does it ever happen? Yes, but it is rare thing. Applications oftentimes get pulled apart. So we've seen if you talk about AI, training the cloud, then transact and do things at the edge. If I'm in an autonomous vehicle or in a geosynchronous satellite, I can't be going back to the cloud to process stuff. So I get what I need and I process there. The same thing hybrid, oftentimes I will do my transactional activity in the public cloud because I've got unlimited compute capability, but I might have my repository of data for many different reasons, governance or security, all these things in my own data center. So parts of an application might live there, but I don't just span to go between the public cloud in my data center or the edge, it's specific architectural decisions as to how we do this. And by the way the developer, they don't want to have to think about location. I mean, my background, servers, storage, virtualization, all that stuff, that was very much an infrastructure up look of things. Developers want to worry about their code and make sure that it works in production. >> Okay, let me test that. If it's in the AWS cloud and I think it's true for the other hyperscale clouds too, they don't have to think about location, but they still have to think about location on-prem, don't they? >> Well, Dave, even in a public cloud, you do need to worry about sometimes it's like, "Okay, do I split it between availability zones? How do I build that? How do I do that?" So there are things that we build on top of it. So we've seen Amazon. >> I think that's fair, data sovereignty, you have to think about okay. >> Absolutely, a lot of those things. >> Okay, but the experience in Germany is going to be the same as it is in DC, is it not? >> More or less? There are some differences we'll see off and Amazon will roll things out over time and what's available, you've got cloud. >> For sure, though that's definitely true. That's a maturity thing, right? You've talked a bit, but ultimately they all sort of catch up. I guess my question would be is the delta between, let's say, Fed adoption and East Coast, is that delta narrower, significantly narrow than what you might see on-prem? >> The services are the same, sometimes for financial or political things, there might be some slight differences, but yes, the cloud experience should be the same everywhere from Amazon. >> Is it from a standpoint of hybrid, on-prem to cloud, across cloud? >> Many of the things when they go outside of the Amazon data centers are limited or a little bit different or you might have latency considerations that you have to consider. >> Now it's a tug of war. >> So it's not totally seamless because, David Foyer would tell us there, "You're not going to fight physics." There are certain things that we need to have and we've changed the way we architect things because it's no longer the bottleneck of the local scuzzy connection that you have there, it is now (indistinct). >> But the point I'm making is that gets into a tug of war of "Our way is better than your way." And the answer is depends in terms of your workload and the use case. >> You've looked at some of these new databases that span globes and do things of the like. >> Another question, I don't know if you saw the Goldman Sachs deal this morning, Goldman Sachs is basically turning its business into a SaaS and pointing it to their hedge funds and allowing people to access their data, their tools, their software that they built for their own purposes. And now they're outselling it. Similar to what NASDAQ has done. I can't imagine doing that without containers. >> Yeah, so interesting point, I think. At least six years ago now, Amazon launched serverless and serverless was going to take over the world. I dug into the space for a couple of years. And you had the serverless with camp and you had the container camp. Last year at re:Invent, I really felt a shift from Amazon's positioning that many of the abstraction layers and the tools that help you support those environments will now span between Lambda and containers. The container world has been adding serverless functionality. So Amazon does Fargate. The open-source community uses something called Knative, and just breaking this week. Knative was a project that Google started and it looks like that is going to move over to the CNCF. So be part of the whole Kubernetes ecosystem and everything like that. Oracle, VMware, IBM, Red Hat, all heavily involved in Knative, and we're all excited to see that go into the CNCF. So the reason I say that, I've seen from Amazon, I actually, John and I, when we interviewed Andy Jassy back in 2017, I asked him a follow-up question because he said if he was to build AWS in 2017, "I would start with everything underneath it serverless." I would wonder if following up with Adam or Andy today, I'd said, "Would it be all serverless or would containers be a piece of it?" Because sometimes underneath it doesn't matter or sometimes it can be containers and serverless. It's a single unit in Amazon and when they position things, it's now that spectrum of unit, everything from the serverless through the containers, through... James Hamilton wrote a blog post today about running Xen-on-Nitro and they have a migration service for a mainframe. So what do we know? That one of the only things about IT is almost nothing ever goes away. I mean, it sounded like Amazon declared coming soon the end of life of mainframe. My friends over at IBM might not be quite ready to call that era over but we shall see. All these things take time. Everything in IT is additive. I'm happy to see. It is very much usually an end world when I look at the container and Kubernetes space. That is something that you can have a broad spectrum of applications. So some of my more monolithic applications can move over, my cool new data, AI things, I can build on it, microservices in between. And so, it's a broad platform that spans the cloud, the edge, the data center. So that cloud operating model is easier to have consistency all the places that I go. >> Mainframe is in the cloud. Well, we'll see. Big banks by the next site unseen. So I think Amazon will be able to eat away at the edges of that, but I don't think there's going to be a major migration. They claim it. Their big thing is that you can't get COBOL programmers. So I'm like, "Yeah, call DXC, you'll get plenty." Let's talk about something more interesting. (Stu laughs softly) So the last 10 years was a lot of, a lot about IT transformation and there was a lot more room to grow there. I mean, the four big hyperscalers are going to do 120 billion this year. They're growing at 35%. Maybe it's not a trillion, but there's a $500 billion market that they're going after, maybe more. It looks like there's a real move. You saw that with NASDAQ, the Goldman deal, to really drive into business, deeper business integration in addition to IT transformation. So how do you see the next decade of cloud? What should we be watching? >> So, one of the interesting trends, I mean, Dave, for years we covered big data and big data felt very horizontal in it's approach thing. Hadoop take over the world. When I look at AI solutions, when I look at the edge computing technologies that happen, they're very vertically driven. So, our early customers in edge adoption tend to be like telco with the 5G rollout manufacturing in some of their environments. AI, every single industry has a whole set of use cases that they're using that go very deep. So I think cloud computing goes from, we talked about infrastructure as a service to it needs to be more, it is solution, some of these pieces go together. When Adam got up on stage and talked about how many instance types they have on Amazon, Dave, it's got to be 2X or 4X more different instant types than if I went to go to HPE or Dell and buy a physical server for my environment. So we need to have areas and guidance and blueprints and heck, use some of that ML and AI to help drive people to the right solutions because we definitely have the paradox of choice today. So I think you will find some gravity moving towards some of these environments. Gravatar has been really interesting to watch. Obviously that Annapurna acquisition should be down as one of the biggest ones in the cloud era. >> No lack of optionality to your point. So I guess to the point of deeper business integration, that's the big question, will Amazon provide more solution abstractions? They certainly do with Connect. We didn't hear a ton of that this show. >> Interestingly. (Dave speaking indistinctly) So the article that you and John Furrier wrote after meeting with Adam, the thing that caught my eye is discussion of community and ecosystems. And one of the things coming after, some, big communities out there like, you and I lived through the VMware ecosystem in that very tight community. There are forming little areas of community here in this group, but it's not a single cloud community. There are those focus areas that they have. And I do love to see, I mean, obviously working for Red Hat, talking about the ecosystem support. I was very happy to hear Adam mention Red Hat in the keynote as one of the key hybrid partners there. So, for Amazon to get from the 60 million, the 60 billion to the trillion dollar mark down the road, it's going to take a village and we're happy to be a part of it. >> Hey, great to have you back, enjoy the rest of the show. This is, let's see, day three, we're wrapping up. We're here again tomorrow so check it out. Special thanks to obviously AWS is our anchor sponsor and of course, AMD for sponsoring the editorial segments of our event. You're watching theCUBE, the leader in tech coverage. See you tomorrow. (bright upbeat music)

(upbeat music) >> Welcome back, everyone, to theCUBE's live coverage, day one wrap-up. I'm John Furrier, with Dave Vellante. We have Jerry Chen, special guest who's been with us every year on theCUBE since inception. Certainly every AWS re:Invent, nine years straight. Jerry Chen, great to see you for our guest analyst's wrap up VC general partner, Greylock partners, good to see you. >> John, Dave, it's great to see you guys. Thanks for having me again. It wouldn't be re:Invent without the three of us sitting here and we missed last year, right, because of COVID. So we have to make up for lost time. >> John: We did a virtual one- >> Dave: we did virtual stuff= >> John: wasn't the same as in-person. >> Dave: Definitely not the same. >> Jerry: Not the same thing. So, it's good to see you guys again in person, and less than 6 feet apart. >> Cheers, yeah. >> And 7,000 people here, showing that the event's still relevant. >> Jerry: Yeah. >> Some people would kill for those numbers, it's a bad year for Amazon, down from 60,000. >> Jerry: Yeah. >> So, ecosystem's booming. Okay, let's get to it. Day one in the books, new CEO, new sheriff in town, his name's Adam Selipsky. Your take? >> Well, Adam's new, but he's old, right? Something, you know, like something new, something old, something blue, right? It's so, Adam was early Amazon, so he had that founding DNA. Left, you know, CEO of Tableau, acquired by Salesforce, came back few months ago. So I think it was a great move, because one, he's got the history and culture under Jassy, so he's definitely the Bezos Jassy tree of leadership, but yet he's been outside the bubble. Right? So he actually knows what it means to run a company not on the Amazon platform. So, I think Adam's a great choice to lead AWS for what we call it, like maybe act two, right? Act one, the first X years with Jassy, and maybe this is the second act under Adam. >> Yeah. And he's got- and he was very technical, hung around all the techies, James Hamilton, DeSantis, all the engineers, built that core primitives. Now, as they say, this cloud next gen's here, act two, it's about applications. >> Jerry: Yeah. >> Infrastructure as code is in place. Interesting area. Where's the growth come from? So, look, you know, the ecosystem has got to build these super clouds, or as you say, Castles on the Cloud, which you coined, but you brought this up years ago, that the moats and the value has to be in there somewhere. Do you want to revise that prediction now that you see what's coming from Selipsky? >> Okay, well, so let's refresh. Greylock.com/castles has worked out, like we did, but a lot of thought leadership and the two of you, have informed my thinking at Castles in the Cloud, how to compete against Amazon in the cloud. So you'd argue act one, the startup phase, the first, you know, X years at Amazon was from 2008 to, you know, 2021, the first X years, building the platform, digging the moats. Right? So what did you have? You have castle the platform business, economies of scale, which means decreasing marginal costs and natural network effects. So once the moat's in place and you had huge market share, what do you for act two, right? Now the moats are in place, you can start exploring the moats for I think, Adam talked about in your article, horizontal and verticals, right? Horizontal solutions up the stack, like Amazon Connect, CRM solutions, right? Horizontal apps, maybe the app layer, and verticals, industrials, financials, healthcare, et cetera. So, I think Jassy did a foundation of the castle and now we're seeing, you know, what Adam and his generation would do for act two. >> So he's, so there's almost like an act one A, because if you take the four hyperscalers, they're about, maybe do 120 billion this year, out of, I don't know, pick a number, it's many hundreds of billions, at least in infrastructure. >> Jerry: Correct. >> And those four hyperscalers growing at 35% collectively, right? So there's some growth there, but I feel like there's got to be deeper business integration, right? It's not just about IT transformation, it's about deeper- So that's maybe where this Connect like stuff comes, but are there enough of those? You know, I didn't, I haven't, I didn't hear a lot of that this morning. I heard a little bit, ML- >> Jerry: Sure. >> AI into Connect, but where's the next Connect, right? They've got to do dozens of those in order to go deeper. >> Either, Dave, dozens of those Connects or more of those premise, so the ML announcement was today. So you look at what Twilio did by buying Segment, right? Deconstruct a CRM to compete against Adam Selipsky's old acquire of Salesforce.com. They bought Segment, so Twilio now has communicates, like texting, messaging, email, but all the data come from Segment. >> Dave: With consumption-based pricing. >> With consumption-based pricing. So, right? So that's an example of kind of what the second act of cloud looks like. It may not look like full SaaS apps like Salesforce.com, but these primitives, both horizontally vertically, because again, what does Amazon have as an asset that other guys don't? Install based developers. Developers aren't going to necessarily build or consume SaaS apps, but they're going to consume things like these API's and primitives. And so you look around, what's cloud act two look like? It may not be VM's or containers. It may be API's like Stripe and Billing, Twilio messaging, right? Concepts like that. So, we'll see what the next act at cloud looks like. And they announced a bunch of stuff today, serverless for the data analytics, right? So serverless is this move towards not consuming raw compute and storage, but APIs. >> What about competition? Microsoft is nipping at the heels of AWS. >> Dave: John put them out of business earlier today. [John and Dave Laugh] >> No, I said, quote, I'll just- let me rephrase. I said, if Amazon goes unchecked- >> Jerry: Sure. >> They'll annihilate Microsoft's ecosystem. Because if you're an ISV, why wouldn't you want to run on the best platform? >> Jerry: Sure. >> Speeds and feeds matter when you have these shifts of software development. >> Jerry: You want them both. >> So, you know, I mean, you thought about the 80's, if you were at database, you wanted the best processor. So I think this Annapurna vertical integrated stacks are interesting because if my app runs better and I have a platform, prefabricated or purpose-built platform, to be there for me, I'm going to build a great SaaS app. If it runs faster and it cost less, I'm going to flop to Amazon. That's just, that's my prediction. >> So I think better changes, right? And so I think if you're Amazon, you say cheaper, better, faster, and they're investing in chips, proprietary silicon to run better, faster, their machine learning training chips, but if you're Azure or Google, you got to redefine what better is. And as a startup investor, we're always trying to do category definition, right? Like here's a category by spin. So now, if you're Azure or Google, there are things you can say that are better, and Google argued their chips, their TensorFlow, are better. Azure say our regions, our security, our enterprise readiness is better. And so all of a sudden, the criteria "what's better" changes. So from faster and cheaper to maybe better compliance, better visibility, better manageability, different colors, I don't know, right? You have to change the game , because if you play the same game on Amazon's turf, to your point, John, it- it's game over because they have economies of scale. But I think Azure and Google and other clouds, the superclouds, or subclouds are changing the game, what it means to compete. And so I think what's going on, just two more seconds, from decentralized cloud, being Web 3 and crypto, that's a whole 'nother can of worms, to Edge compute, what Cloudflare are doing with R2 and storage, they're trying to change the name of the game. >> Well, that's right. If you go frontal against Amazon, you're got to get decimated. You got to move the goalposts for better. And I think that's a good way to look at it, Dave. What does better mean? So that's the question that's on the table. What does that look like? And I think that's an unknown, that's coming. Okay, back to the start-ups. Category definition. That's an awesome term. That to me is a key thing. How do you look at what a category is on your sub- on your Castles of the Cloud, you brought up how many categories of- >> Jerry: 33 markets and a bunch of submarkets, yeah. >> Yeah. Explain that concept. >> So, we did Castle in the Clouds where my team looked at all the services offered at Azure, Google, and Amazon. We downloaded the services and recategorized them to like, 30 plus markets and a bunch of submarkets. Because, the reason why is apples to apples, you know, Amazon, Google, Azure all have databases, but they might call them different things. And so I think first things first is, let's give developers and customers kind of apples to apples comparisons. So I think those are known markets. The key in investing in the cloud, or investing in general, is you're either investing in budget replacement, replacing a known market, cheaper, better database, to your point, or a net new market, right? Which is always tricky. So I think the biggest threat to a lot of the startups and incumbents, the biggest threat by startups and incumbents, is either one, do something cheaper, better in a current market, or find a net new market that they haven't thought about yet. And if you can win that net new market before the rest, then that's unbelievable. We call it the, you know, the blue ocean strategy, >> Dave: Is that essentially what Snowflake has done, started with cheaper, better, and now they're building the data cloud? >> Jerry: I think there's- it's evolution, correct. So they said cheaper, better. And the Castle in the Cloud, we talked about, they actually built deep IP. So they went a known category, data warehouses, right? You had Teradata, Redshift, Snowflake cheaper, better, faster. And now let's say, okay, once you have the customers, let's change the name of the game and create a data cloud. And it's TBD whether or not Snowflake can win data cloud. Like we talked about Rockset, one of my investments that's actually move the goalpost saying, oh, data cloud is nice, but real time data is where it's at, and Snowflake and those guys can't play in real time. >> Dave: No, they're not in a position to play in real time data. >> Jerry: Right. >> Dave: I mean, that's right. >> So again, so that's an example of a startup moving the goalpost on what previously was a startup that moved the goalpost on an incumbent. >> Dave: And when you think about Edge, it's going to be real-time AI inferencing at the Edge, and you're right, Snowflake's not set up well at all for that. >> John: So competition wise, how do the people compete? Because this is what Databricks did the same exact thing. I have Ali on the record going back years, "Well, we love Amazon. We're only on Amazon." Now he's talking multicloud. >> So, you know, once you get there, you kind of change your tune cause you've got some scale, but then you got new potential entrants coming in, like Rockset. >> Jerry: Correct. >> So. >> Dave: But then, and if you add up the market caps of just those two companies, Databricks and Snowflake, it's much larger than the database market. So this, we're defining new markets now. >> Jerry: I think there's market cap, especially Snowflake that's in the public market, Databricks is still private, is optimism that there's a second or third act in the database space left to be unlocked. And you look at what's going on in that space, these real-time analytics or real-time apps, for sure there's optimism there. But, but to John's point, you're right, like you earn the right to play the next act, but it's tricky because startups disrupt incumbents and become incumbents, and they're also victims their own success, right? So you're- there's technical debt, there's also business model debt. So you're victims of your own business model, victims of your own success. And so what got you here may not get you to the next phase. And so I think for Amazon, that's a question. For Databricks and Snowflake, that's a question, is what got them here? Can they play to the next act? And look, Apple did it, multiple acts. >> John: Well, I mean, I think I- [Crosstalk] >> John: I think it's whether you take shortcuts or not, if you have debt, you make it a little bit of a shortcut bet. >> Jerry: Yeah. >> Okay. That's cool. But ultimately what you're getting at here is beachhead thinking. Get a beachhead- >> Jerry: Correct. >> Get in the market, and then sequence to a different position. Classic competitive strategy, 101. That's hard to do because you want to win the beachhead- >> I know. >> John: And take a little technical debt and business model debt, cheat a little bit, and then, is it not fortified yet? So beachhead to expansion is the question. >> Jerry: That's every board meeting, John and Dave, that we're in, right? It's called you need a narrow enough wedge to land. And it is like, I don't want the tip of the spear, I want the poison on the tip of a spear, right? [Dave and John Laugh] >> You want, especially in this cloud market, a super focused wedge to land. And the problem is, as a founder, as investor, you're always thinking about the global max, right? Like the ultimate platform winner, but you don't get the right to play the early- the late innings if you don't make it out of the early innings. And so narrow beachhead, sharp wedge, but you got to land in a space, a place of real estate with adjacent tan, adjacent markets, right? Like Uber, black cars, taxi's, food, whatever, right? Snowflake, data warehouse, data cloud. And so I think the key with all startups is you'll hit some ceiling of market size. Is there a second ramp? >> Dave: So it's- the art is when to scale and how fast to scale. >> Right. Picking when, how fast, in which- which best place, it was tough. And so, the best companies are always thinking about their second or third act while the first act's still going. >> John: Yeah. And leveraging cloud to refactor, I think that's the key to Snowflake, was they had the wedge with data warehouse, they saw the position, but refactored and in the cloud with services that they knew Teradata wouldn't use. >> Jerry: Correct. >> And they're in. From there, it's just competitive IP, crank, go to market. >> And then you have the other unnatural things. You have channel, you have installed base of customers, right? And then you start selling more stuff to the same channel, to the same customers. That's what Amazon's doing. All the incumbent's do that. Amazon's got, you know, 300 services now, launching more this week, so now they have channel distribution, right? Every credit card for all the developers, and they have installed base of customers. And so they will just launch new things and serve the customers. So the startups had to disrupt them somehow. >> Well, it's always great to chat with Jerry. Every year we discover and we riff and we identify, in real time, new stuff. We were talking about this whole vertical, horizontal scale and kind of castles early on, years ago. And now it's happened. You were right. Congratulations. That's a great thesis. There's real advantages to build on a cloud. You can get the- you can build a business there. >> Jerry: Right. >> John: That's your thesis. And by the way, these markets are changing. So if you're smart, you can actually compete. >> Jerry: I think you beat, and to Dave's earlier point, you have to adapt, right? And so what's the Darwin thing, it's not the strongest, but the most adaptable. So both- Amazon's adapt and the startups who are the most adaptable will win. >> Dave: Where are you, you guys might've talked about this, where do you stand on the cost of goods sold issue? >> Jerry: Oh, I think everything's true, right? I think you can save money at some scale to repatriate your cloud, but again, Wall Street rewards growth versus COGS, right? So I think you've got a choice between a dollar of growth versus a dollar reducing COGS, people choose growth right now. That may not always be the case, but at some point, if you're a company at some scale and the dollars of growth is slowing down, you definitely have to reduce the dollars in cost. And so you start optimizing cloud costs, and that could be going to Amazon, Azure, or Google, reducing COGS. >> Dave: Negotiate, yeah. >> John: Or, you have no visibility on new net new opportunities. So growth is about new opportunities. >> Correct. >> If you repatriating things, there's no growth. >> Jerry: It's not either, or- >> That's my opinion. >> Jerry: COGS or growth, right? But they're both valid, definitely, so you can do both. And so I don't think- it's what's your priorities, you can't do everything at once. So if I'm a founder or CEO or in this case investor, and I said, "Hey, Dave, and John, if you said I can either save you 25 basis points in gross margin, or I can increase another 10% top line this year", I'm going to say increase the top line, we'll deal with the gross margin later. Not that it's not important, but right now the early phase- >> Priorities. >> Jerry: It's growth. >> Yeah. All right, Jerry Chen, great to see you. Great to have you on, great CUBE alumni, great guest analyst. Thanks for breaking it down. CUBE coverage here in Las Vegas for re:Invent, back in person. Of course, it's a virtual event, we've got a hybrid event for Amazon, as well as theCUBE. I'm John Furrier, you're watching the leader in worldwide tech coverage. Thanks for watching. (Gentle music)

>>Well, welcome back to the cubes coverage of AWS reinvent 2021. We're here joined by Ian buck, general manager and vice president of accelerated computing at Nvidia I'm. John Ford, your host of the QB. And thanks for coming on. So in video, obviously, great brand congratulates on all your continued success. Everyone who has does anything in graphics knows the GPU's are hot and you guys get great brand great success in the company, but AI and machine learning was seeing the trend significantly being powered by the GPU's and other systems. So it's a key part of everything. So what's the trends that you're seeing, uh, in ML and AI, that's accelerating computing to the cloud. Yeah, >>I mean, AI is kind of drape bragging breakthroughs innovations across so many segments, so many different use cases. We see it showing up with things like credit card, fraud prevention and product and content recommendations. Really it's the new engine behind search engines is AI. Uh, people are applying AI to things like, um, meeting transcriptions, uh, virtual calls like this using AI to actually capture what was said. Um, and that gets applied in person to person interactions. We also see it in intelligence systems assistance for a contact center, automation or chat bots, uh, medical imaging, um, and intelligence stores and warehouses and everywhere. It's really, it's really amazing what AI has been demonstrated, what it can do. And, uh, it's new use cases are showing up all the time. >>Yeah. I'd love to get your thoughts on, on how the world's evolved just in the past few years, along with cloud, and certainly the pandemics proven it. You had this whole kind of full stack mindset initially, and now you're seeing more of a horizontal scale, but yet enabling this vertical specialization in applications. I mean, you mentioned some of those apps, the new enablers, this kind of the horizontal play with enablement for specialization, with data, this is a huge shift that's going on. It's been happening. What's your reaction to that? >>Yeah, it's the innovations on two fronts. There's a horizontal front, which is basically the different kinds of neural networks or AIS as well as machine learning techniques that are, um, just being invented by researchers for, uh, and the community at large, including Amazon. Um, you know, it started with these convolutional neural networks, which are great for image processing, but as it expanded more recently into, uh, recurrent neural networks, transformer models, which are great for language and language and understanding, and then the new hot topic graph neural networks, where the actual graph now is trained as a, as a neural network, you have this underpinning of great AI technologies that are being adventure around the world in videos role is try to productize that and provide a platform for people to do that innovation and then take the next step and innovate vertically. Um, take it, take it and apply it to two particular field, um, like medical, like healthcare and medical imaging applying AI, so that radiologists can have an AI assistant with them and highlight different parts of the scan. >>Then maybe troublesome worrying, or requires more investigation, um, using it for robotics, building virtual worlds, where robots can be trained in a virtual environment, their AI being constantly trained, reinforced, and learn how to do certain activities and techniques. So that the first time it's ever downloaded into a real robot, it works right out of the box, um, to do, to activate that we co we are creating different vertical solutions, vertical stacks for products that talk the languages of those businesses, of those users, uh, in medical imaging, it's processing medical data, which is obviously a very complicated large format data, often three-dimensional boxes in robotics. It's building combining both our graphics and simulation technologies, along with the, you know, the AI training capabilities and different capabilities in order to run in real time. Those are, >>Yeah. I mean, it's just so cutting edge. It's so relevant. I mean, I think one of the things you mentioned about the neural networks, specifically, the graph neural networks, I mean, we saw, I mean, just to go back to the late two thousands, you know, how unstructured data or object store created, a lot of people realize that the value out of that now you've got graph graph value, you got graph network effect, you've got all kinds of new patterns. You guys have this notion of graph neural networks. Um, that's, that's, that's out there. What is, what is a graph neural network and what does it actually mean for deep learning and an AI perspective? >>Yeah, we have a graph is exactly what it sounds like. You have points that are connected to each other, that established relationships and the example of amazon.com. You might have buyers, distributors, sellers, um, and all of them are buying or recommending or selling different products. And they're represented in a graph if I buy something from you and from you, I'm connected to those end points and likewise more deeply across a supply chain or warehouse or other buyers and sellers across the network. What's new right now is that those connections now can be treated and trained like a neural network, understanding the relationship. How strong is that connection between that buyer and seller or that distributor and supplier, and then build up a network that figure out and understand patterns across them. For example, what products I may like. Cause I have this connection in my graph, what other products may meet those requirements, or also identifying things like fraud when, when patterns and buying patterns don't match, what a graph neural networks should say would be the typical kind of graph connectivity, the different kind of weights and connections between the two captured by the frequency half I buy things or how I rate them or give them stars as she used cases, uh, this application graph neural networks, which is basically capturing the connections of all things with all people, especially in the world of e-commerce, it's very exciting to a new application, but applying AI to optimizing business, to reducing fraud and letting us, you know, get access to the products that we want, the products that they have, our recommendations be things that, that excited us and want us to buy things >>Great setup for the real conversation that's going on here at re-invent, which is new kinds of workloads are changing. The game. People are refactoring their business with not just replatform, but actually using this to identify value and see cloud scale allows you to have the compute power to, you know, look at a note on an arc and actually code that. It's all, it's all science, all computer science, all at scale. So with that, that brings up the whole AWS relationship. Can you tell us how you're working with AWS before? >>Yeah. 80 of us has been a great partner and one of the first cloud providers to ever provide GPS the cloud, uh, we most more recently we've announced two new instances, uh, the instance, which is based on the RA 10 G GPU, which has it was supports the Nvidia RTX technology or rendering technology, uh, for real-time Ray tracing and graphics and game streaming is their highest performance graphics, enhanced replicate without allows for those high performance graphics applications to be directly hosted in the cloud. And of course runs everything else as well, including our AI has access to our AI technology runs all of our AI stacks. We also announced with AWS, the G 5g instance, this is exciting because it's the first, uh, graviton or ARM-based processor connected to a GPU and successful in the cloud. Um, this makes, uh, the focus here is Android gaming and machine learning and France. And we're excited to see the advancements that Amazon is making and AWS is making with arm and the cloud. And we're glad to be part of that journey. >>Well, congratulations. I remember I was just watching my interview with James Hamilton from AWS 2013 and 2014. He was getting, he was teasing this out, that they're going to build their own, get in there and build their own connections, take that latency down and do other things. This is kind of the harvest of all that. As you start looking at these new new interfaces and the new servers, new technology that you guys are doing, you're enabling applications. What does, what do you see this enabling as this, as this new capability comes out, new speed, more, more performance, but also now it's enabling more capabilities so that new workloads can be realized. What would you say to folks who want to ask that question? >>Well, so first off I think arm is here to stay and you can see the growth and explosion of my arm, uh, led of course, by grab a tiny to be. I spend many others, uh, and by bringing all of NVIDIA's rendering graphics, machine learning and AI technologies to arm, we can help bring that innovation. That arm allows that open innovation because there's an open architecture to the entire ecosystem. Uh, we can help bring it forward, uh, to the state of the art in AI machine learning, the graphics. Um, we all have our software that we released is both supportive, both on x86 and an army equally, um, and including all of our AI stacks. So most notably for inference the deployment of AI models. We have our, the Nvidia Triton inference server. Uh, this is the, our inference serving software where after he was trained to model, he wanted to play it at scale on any CPU or GPU instance, um, for that matter. So we support both CPS and GPS with Triton. Um, it's natively integrated with SageMaker and provides the benefit of all those performance optimizations all the time. Uh, things like, uh, features like dynamic batching. It supports all the different AI frameworks from PI torch to TensorFlow, even a generalized Python code. Um, we're activating how activating the arm ecosystem as well as bringing all those AI new AI use cases and all those different performance levels, uh, with our partnership with AWS and all the different clouds. >>And you got to making it really easy for people to use, use the technology that brings up the next kind of question I want to ask you. I mean, a lot of people are really going in jumping in the big time into this. They're adopting AI. Either they're moving in from prototype to production. There's always some gaps, whether it's knowledge, skills, gaps, or whatever, but people are accelerating into the AI and leaning into it hard. What advancements have is Nvidia made to make it more accessible, um, for people to move faster through the, through the system, through the process? >>Yeah, it's one of the biggest challenges. The other promise of AI, all the publications that are coming all the way research now, how can you make it more accessible or easier to use by more people rather than just being an AI researcher, which is, uh, uh, obviously a very challenging and interesting field, but not one that's directly in the business. Nvidia is trying to write a full stack approach to AI. So as we make, uh, discover or see these AI technologies come available, we produce SDKs to help activate them or connect them with developers around the world. Uh, we have over 150 different STKs at this point, certain industries from gaming to design, to life sciences, to earth scientist. We even have stuff to help simulate quantum computing. Um, and of course all the, all the work we're doing with AI, 5g and robotics. So, uh, we actually just introduced about 65 new updates just this past month on all those SDKs. Uh, some of the newer stuff that's really exciting is the large language models. Uh, people are building some amazing AI. That's capable of understanding the Corpus of like human understanding, these language models that are trained on literally the continent of the internet to provide general purpose or open domain chatbots. So the customer is going to have a new kind of experience with a computer or the cloud. Uh, we're offering large language, uh, those large language models, as well as AI frameworks to help companies take advantage of this new kind of technology. >>You know, each and every time I do an interview with Nvidia or talk about Nvidia my kids and their friends, they first thing they said, you get me a good graphics card. Hey, I want the best thing in their rig. Obviously the gaming market's hot and known for that, but I mean, but there's a huge software team behind Nvidia. This is a well-known your CEO is always talking about on his keynotes, you're in the software business. And then you had, do have hardware. You were integrating with graviton and other things. So, but it's a software practices, software. This is all about software. Could you share kind of more about how Nvidia culture and their cloud culture and specifically around the scale? I mean, you, you hit every, every use case. So what's the software culture there at Nvidia, >>And it is actually a bigger, we have more software people than hardware people, people don't often realize this. Uh, and in fact that it's because of we create, uh, the, the, it just starts with the chip, obviously building great Silicon is necessary to provide that level of innovation, but as it expanded dramatically from then, from there, uh, not just the Silicon and the GPU, but the server designs themselves, we actually do entire server designs ourselves to help build out this infrastructure. We consume it and use it ourselves and build our own supercomputers to use AI, to improve our products. And then all that software that we build on top, we make it available. As I mentioned before, uh, as containers on our, uh, NGC container store container registry, which is accessible for me to bus, um, to connect to those vertical markets, instead of just opening up the hardware and none of the ecosystem in develop on it, they can with a low-level and programmatic stacks that we provide with Kuda. We believe that those vertical stacks are the ways we can help accelerate and advance AI. And that's why we make as well, >>Ram a little software is so much easier. I want to get that plug for, I think it's worth noting that you guys are, are heavy hardcore, especially on the AI side. And it's worth calling out, uh, getting back to the customers who are bridging that gap and getting out there, what are the metrics they should consider as they're deploying AI? What are success metrics? What does success look like? Can you share any insight into what they should be thinking about and looking at how they're doing? >>Yeah. Um, for training, it's all about time to solution. Um, it's not the hardware that that's the cost, it's the opportunity that AI can provide your business and many, and the productivity of those data scientists, which are developing, which are not easy to come by. So, uh, what we hear from customers is they need a fast time to solution to allow people to prototype very quickly, to train a model to convergence, to get into production quickly, and of course, move on to the next or continue to refine it often. So in training is time to solution for inference. It's about our, your ability to deploy at scale. Often people need to have real time requirements. They want to run in a certain amount of latency, a certain amount of time. And typically most companies don't have a single AI model. They have a collection of them. They want, they want to run for a single service or across multiple services. That's where you can aggregate some of your infrastructure leveraging the trading infant server. I mentioned before can actually run multiple models on a single GPU saving costs, optimizing for efficiency yet still meeting the requirements for latency and the real time experience so that your customers have a good, a good interaction with the AI. >>Awesome. Great. Let's get into, uh, the customer examples. You guys have obviously great customers. Can you share some of the use cases, examples with customers, notable customers? >>Yeah. I want one great part about working in videos as a technology company. You see, you get to engage with such amazing customers across many verticals. Uh, some of the ones that are pretty exciting right now, Netflix is using the G4 instances to CLA um, to do a video effects and animation content. And, you know, from anywhere in the world, in the cloud, uh, as a cloud creation content platform, uh, we work in the energy field that Siemens energy is actually using AI combined with, um, uh, simulation to do predictive maintenance on their energy plants, um, and, and, uh, doing preventing or optimizing onsite inspection activities and eliminating downtime, which is saving a lot of money for the engine industry. Uh, we have worked with Oxford university, uh, which is Oxford university actually has over two, over 20 million artifacts and specimens and collections across its gardens and museums and libraries. They're actually using convenient GPS and Amazon to do enhance image recognition, to classify all these things, which would take literally years with, um, uh, going through manually each of these artifacts using AI, we can click and quickly catalog all of them and connect them with their users. Um, great stories across graphics, about cross industries across research that, uh, it's just so exciting to see what people are doing with our technology together with, >>And thank you so much for coming on the cube. I really appreciate Greg, a lot of great content there. We probably going to go another hour, all the great stuff going on in the video, any closing remarks you want to share as we wrap this last minute up >>Now, the, um, really what Nvidia is about as accelerating cloud computing, whether it be AI, machine learning, graphics, or headphones, community simulation, and AWS was one of the first with this in the beginning, and they continue to bring out great instances to help connect, uh, the cloud and accelerated computing with all the different opportunities integrations with with SageMaker really Ks and ECS. Uh, the new instances with G five and G 5g, very excited to see all the work that we're doing together. >>Ian buck, general manager, and vice president of accelerated computing. I mean, how can you not love that title? We want more, more power, more faster, come on. More computing. No, one's going to complain with more computing know, thanks for coming on. Thank you. Appreciate it. I'm John Farrell hosted the cube. You're watching Amazon coverage reinvent 2021. Thanks for watching.

(bright music) >> Well, welcome back to theCUBE's coverage of AWS re:Invent 2021. We're here joined by Ian Buck, general manager and vice president of Accelerated Computing at NVIDIA. I'm John Furrrier, host of theCUBE. Ian, thanks for coming on. >> Oh, thanks for having me. >> So NVIDIA, obviously, great brand. Congratulations on all your continued success. Everyone who does anything in graphics knows that GPU's are hot, and you guys have a great brand, great success in the company. But AI and machine learning, we're seeing the trend significantly being powered by the GPU's and other systems. So it's a key part of everything. So what's the trends that you're seeing in ML and AI that's accelerating computing to the cloud? >> Yeah. I mean, AI is kind of driving breakthroughs and innovations across so many segments, so many different use cases. We see it showing up with things like credit card fraud prevention, and product and content recommendations. Really, it's the new engine behind search engines, is AI. People are applying AI to things like meeting transcriptions, virtual calls like this, using AI to actually capture what was said. And that gets applied in person-to-person interactions. We also see it in intelligence assistance for contact center automation, or chat bots, medical imaging, and intelligence stores, and warehouses, and everywhere. It's really amazing what AI has been demonstrating, what it can do, and its new use cases are showing up all the time. >> You know, Ian, I'd love to get your thoughts on how the world's evolved, just in the past few years alone, with cloud. And certainly, the pandemic's proven it. You had this whole kind of fullstack mindset, initially, and now you're seeing more of a horizontal scale, but yet, enabling this vertical specialization in applications. I mean, you mentioned some of those apps. The new enablers, this kind of, the horizontal play with enablement for, you know, specialization with data, this is a huge shift that's going on. It's been happening. What's your reaction to that? >> Yeah. The innovation's on two fronts. There's a horizontal front, which is basically the different kinds of neural networks or AIs, as well as machine learning techniques, that are just being invented by researchers and the community at large, including Amazon. You know, it started with these convolutional neural networks, which are great for image processing, but has expanded more recently into recurrent neural networks, transformer models, which are great for language and language and understanding, and then the new hot topic, graph neural networks, where the actual graph now is trained as a neural network. You have this underpinning of great AI technologies that are being invented around the world. NVIDIA's role is to try to productize that and provide a platform for people to do that innovation. And then, take the next step and innovate vertically. Take it and apply it to a particular field, like medical, like healthcare and medical imaging, applying AI so that radiologists can have an AI assistant with them and highlight different parts of the scan that may be troublesome or worrying, or require some more investigation. Using it for robotics, building virtual worlds where robots can be trained in a virtual environment, their AI being constantly trained and reinforced, and learn how to do certain activities and techniques. So that the first time it's ever downloaded into a real robot, it works right out of the box. To activate that, we are creating different vertical solutions, vertical stacks, vertical products, that talk the languages of those businesses, of those users. In medical imaging, it's processing medical data, which is obviously a very complicated, large format data, often three-dimensional voxels. In robotics, it's building, combining both our graphics and simulation technologies, along with the AI training capabilities and difference capabilities, in order to run in real time. Those are just two simple- >> Yeah, no. I mean, it's just so cutting-edge, it's so relevant. I mean, I think one of the things you mentioned about the neural networks, specifically, the graph neural networks, I mean, we saw, I mean, just go back to the late 2000s, how unstructured data, or object storage created, a lot of people realized a lot of value out of that. Now you got graph value, you got network effect, you got all kinds of new patterns. You guys have this notion of graph neural networks that's out there. What is a graph neural network, and what does it actually mean from a deep learning and an AI perspective? >> Yeah. I mean, a graph is exactly what it sounds like. You have points that are connected to each other, that establish relationships. In the example of Amazon.com, you might have buyers, distributors, sellers, and all of them are buying, or recommending, or selling different products. And they're represented in a graph. If I buy something from you and from you, I'm connected to those endpoints, and likewise, more deeply across a supply chain, or warehouse, or other buyers and sellers across the network. What's new right now is, that those connections now can be treated and trained like a neural network, understanding the relationship, how strong is that connection between that buyer and seller, or the distributor and supplier, and then build up a network to figure out and understand patterns across them. For example, what products I may like, 'cause I have this connection in my graph, what other products may meet those requirements? Or, also, identifying things like fraud, When patterns and buying patterns don't match what a graph neural networks should say would be the typical kind of graph connectivity, the different kind of weights and connections between the two, captured by the frequency of how often I buy things, or how I rate them or give them stars, or other such use cases. This application, graph neural networks, which is basically capturing the connections of all things with all people, especially in the world of e-commerce, is very exciting to a new application of applying AI to optimizing business, to reducing fraud, and letting us, you know, get access to the products that we want. They have our recommendations be things that excite us and want us to buy things, and buy more. >> That's a great setup for the real conversation that's going on here at re:Invent, which is new kinds of workloads are changing the game, people are refactoring their business with, not just re-platforming, but actually using this to identify value. And also, your cloud scale allows you to have the compute power to, you know, look at a note in an arc and actually code that. It's all science, it's all computer science, all at scale. So with that, that brings up the whole AWS relationship. Can you tell us how you're working with AWS, specifically? >> Yeah, AWS have been a great partner, and one of the first cloud providers to ever provide GPUs to the cloud. More recently, we've announced two new instances, the G5 instance, which is based on our A10G GPU, which supports the NVIDIA RTX technology, our rendering technology, for real-time ray tracing in graphics and game streaming. This is our highest performance graphics enhanced application, allows for those high-performance graphics applications to be directly hosted in the cloud. And, of course, runs everything else as well. It has access to our AI technology and runs all of our AI stacks. We also announced, with AWS, the G5 G instance. This is exciting because it's the first Graviton or Arm-based processor connected to a GPU and successful in the cloud. The focus here is Android gaming and machine learning inference. And we're excited to see the advancements that Amazon is making and AWS is making, with Arm in the cloud. And we're glad to be part of that journey. >> Well, congratulations. I remember, I was just watching my interview with James Hamilton from AWS 2013 and 2014. He was teasing this out, that they're going to build their own, get in there, and build their own connections to take that latency down and do other things. This is kind of the harvest of all that. As you start looking at these new interfaces, and the new servers, new technology that you guys are doing, you're enabling applications. What do you see this enabling? As this new capability comes out, new speed, more performance, but also, now it's enabling more capabilities so that new workloads can be realized. What would you say to folks who want to ask that question? >> Well, so first off, I think Arm is here to stay. We can see the growth and explosion of Arm, led of course, by Graviton and AWS, but many others. And by bringing all of NVIDIA's rendering graphics, machine learning and AI technologies to Arm, we can help bring that innovation that Arm allows, that open innovation, because there's an open architecture, to the entire ecosystem. We can help bring it forward to the state of the art in AI machine learning and graphics. All of our software that we release is both supportive, both on x86 and on Arm equally, and including all of our AI stacks. So most notably, for inference, the deployment of AI models, we have the NVIDIA Triton inference server. This is our inference serving software, where after you've trained a model, you want to deploy it at scale on any CPU, or GPU instance, for that matter. So we support both CPUs and GPUs with Triton. It's natively integrated with SageMaker and provides the benefit of all those performance optimizations. Features like dynamic batching, it supports all the different AI frameworks, from PyTorch to TensorFlow, even a generalized Python code. We're activating, and help activating, the Arm ecosystem, as well as bringing all those new AI use cases, and all those different performance levels with our partnership with AWS and all the different cloud instances. >> And you guys are making it really easy for people to use use the technology. That brings up the next, kind of, question I wanted to ask you. I mean, a lot of people are really going in, jumping in big-time into this. They're adopting AI, either they're moving it from prototype to production. There's always some gaps, whether it's, you know, knowledge, skills gaps, or whatever. But people are accelerating into the AI and leaning into it hard. What advancements has NVIDIA made to make it more accessible for people to move faster through the system, through the process? >> Yeah. It's one of the biggest challenges. You know, the promise of AI, all the publications that are coming out, all the great research, you know, how can you make it more accessible or easier to use by more people? Rather than just being an AI researcher, which is obviously a very challenging and interesting field, but not one that's directly connected to the business. NVIDIA is trying to provide a fullstack approach to AI. So as we discover or see these AI technologies become available, we produce SDKs to help activate them or connect them with developers around the world. We have over 150 different SDKs at this point, serving industries from gaming, to design, to life sciences, to earth sciences. We even have stuff to help simulate quantum computing. And of course, all the work we're doing with AI, 5G, and robotics. So we actually just introduced about 65 new updates, just this past month, on all those SDKs. Some of the newer stuff that's really exciting is the large language models. People are building some amazing AI that's capable of understanding the corpus of, like, human understanding. These language models that are trained on literally the content of the internet to provide general purpose or open-domain chatbots, so the customer is going to have a new kind of experience with the computer or the cloud. We're offering those large language models, as well as AI frameworks, to help companies take advantage of this new kind of technology. >> You know, Ian, every time I do an interview with NVIDIA or talk about NVIDIA, my kids and friends, first thing they say is, "Can you get me a good graphics card?" They all want the best thing in their rig. Obviously the gaming market's hot and known for that. But there's a huge software team behind NVIDIA. This is well-known. Your CEO is always talking about it on his keynotes. You're in the software business. And you do have hardware, you are integrating with Graviton and other things. But it's a software practice. This is software. This is all about software. >> Right. >> Can you share, kind of, more about how NVIDIA culture and their cloud culture, and specifically around the scale, I mean, you hit every use case. So what's the software culture there at NVIDIA? >> Yeah, NVIDIA's actually a bigger, we have more software people than hardware people. But people don't often realize this. And in fact, that it's because of, it just starts with the chip, and obviously, building great silicon is necessary to provide that level of innovation. But it's expanded dramatically from there. Not just the silicon and the GPU, but the server designs themselves. We actually do entire server designs ourselves, to help build out this infrastructure. We consume it and use it ourselves, and build our own supercomputers to use AI to improve our products. And then, all that software that we build on top, we make it available, as I mentioned before, as containers on our NGC container store, container registry, which is accessible from AWS, to connect to those vertical markets. Instead of just opening up the hardware and letting the ecosystem develop on it, they can, with the low-level and programmatic stacks that we provide with CUDA. We believe that those vertical stacks are the ways we can help accelerate and advance AI. And that's why we make them so available. >> And programmable software is so much easier. I want to get that plug in for, I think it's worth noting that you guys are heavy hardcore, especially on the AI side, and it's worth calling out. Getting back to the customers who are bridging that gap and getting out there, what are the metrics they should consider as they're deploying AI? What are success metrics? What does success look like? Can you share any insight into what they should be thinking about, and looking at how they're doing? >> Yeah. For training, it's all about time-to-solution. It's not the hardware that's the cost, it's the opportunity that AI can provide to your business, and the productivity of those data scientists which are developing them, which are not easy to come by. So what we hear from customers is they need a fast time-to-solution to allow people to prototype very quickly, to train a model to convergence, to get into production quickly, and of course, move on to the next or continue to refine it. >> John Furrier: Often. >> So in training, it's time-to-solution. For inference, it's about your ability to deploy at scale. Often people need to have real-time requirements. They want to run in a certain amount of latency, in a certain amount of time. And typically, most companies don't have a single AI model. They have a collection of them they want to run for a single service or across multiple services. That's where you can aggregate some of your infrastructure. Leveraging the Triton inference server, I mentioned before, can actually run multiple models on a single GPU saving costs, optimizing for efficiency, yet still meeting the requirements for latency and the real-time experience, so that our customers have a good interaction with the AI. >> Awesome. Great. Let's get into the customer examples. You guys have, obviously, great customers. Can you share some of the use cases examples with customers, notable customers? >> Yeah. One great part about working at NVIDIA is, as technology company, you get to engage with such amazing customers across many verticals. Some of the ones that are pretty exciting right now, Netflix is using the G4 instances to do a video effects and animation content from anywhere in the world, in the cloud, as a cloud creation content platform. We work in the energy field. Siemens energy is actually using AI combined with simulation to do predictive maintenance on their energy plants, preventing, or optimizing, onsite inspection activities and eliminating downtime, which is saving a lot of money for the energy industry. We have worked with Oxford University. Oxford University actually has over 20 million artifacts and specimens and collections, across its gardens and museums and libraries. They're actually using NVIDIA GPU's and Amazon to do enhanced image recognition to classify all these things, which would take literally years going through manually, each of these artifacts. Using AI, we can quickly catalog all of them and connect them with their users. Great stories across graphics, across industries, across research, that it's just so exciting to see what people are doing with our technology, together with Amazon. >> Ian, thank you so much for coming on theCUBE. I really appreciate it. A lot of great content there. We probably could go another hour. All the great stuff going on at NVIDIA. Any closing remarks you want to share, as we wrap this last minute up? >> You know, really what NVIDIA's about, is accelerating cloud computing. Whether it be AI, machine learning, graphics, or high-performance computing and simulation. And AWS was one of the first with this, in the beginning, and they continue to bring out great instances to help connect the cloud and accelerated computing with all the different opportunities. The integrations with EC2, with SageMaker, with EKS, and ECS. The new instances with G5 and G5 G. Very excited to see all the work that we're doing together. >> Ian Buck, general manager and vice president of Accelerated Computing. I mean, how can you not love that title? We want more power, more faster, come on. More computing. No one's going to complain with more computing. Ian, thanks for coming on. >> Thank you. >> Appreciate it. I'm John Furrier, host of theCUBE. You're watching Amazon coverage re:Invent 2021. Thanks for watching. (bright music)

>> Narrator: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> As you know by now, Jeff Bezos, CEO of Amazon, is stepping aside from his CEO role and AWS CEO, Andy Jassy, is being promoted to head all of Amazon. Bezos, of course, is going to remain executive chairman. Now, 15 years ago, next month, Amazon launched it's simple storage service, which was the first modern cloud offering. And the man who wrote the business plan for AWS, was Andy Jassy, and he's navigated the meteoric rise and disruption that has seen AWS grow into a $45 billion company that draws off the vast majority of Amazon's operating profits. No one in the media has covered Jassy more intimately and closely than John Furrier, the founder of SiliconANGLE. And John joins us today to help us understand on theCUBE this move and what we can expect from Jassy in his new role, and importantly what it means for AWS. John, thanks for taking the time to speak with us. >> Hey, great day. Great to see you as always, we've done a lot of interviews together over the years and we're on our 11th year with theCUBE and SiliconANGLE. But I got to be excited too, that we're simulcasters on Clubhouse, which is kind of cool. Love Clubhouse but not since the, in December. It's awesome. It's like Cube radio. It's like, so this is a Cube talk. So we opened up a Clubhouse room while we're filming this. We'll do more live hits in studio and syndicate the Clubhouse and then take questions after. This is a huge digital transformation moment. I'm part of the digital transformation club on Clubhouse which has almost 5,000 followers at the moment and also has like 500 members. So if you're not on Clubhouse, yet, if you have an iPhone go check it out and join the digital transformation club. Android users you'll have to wait until that app is done but it's really a great club. And Jeremiah Owyang is also doing a lot of stuff on digital transformation. >> Or you can just buy an iPhone and get in. >> Yeah, that's what people are doing. I can see all the influences are on there but to me, the digital transformation, it's always been kind of a cliche, the consumerization of IT, information technology. This has been the boring world of the enterprise over the past, 20 years ago. Enterprise right now is super hot because there's no distinction between enterprise and society. And that's clearly the, because of the rise of cloud computing and the rise of Amazon Web Services which was a side project at AWS, at Amazon that Andy Jassy did. And it wasn't really pleasant at the beginning. It was failed. It failed a lot and it wasn't as successful as people thought in the early days. And I have a lot of stories with Andy that he told me a lot of the inside baseball and we'll share that here today. But we started covering Amazon since the beginning. I was as an entrepreneur. I used it when it came out and a huge fan of them as a company because they just got a superior product and they have always had been but it was very misunderstood from the beginning. And now everyone's calling it the most important thing. And Andy now is becoming Andy Jassy, the most important executive in the world. >> So let's get it to the, I mean, look at, you said to me over holidays, you thought this might have something like this could happen. And you said, Jassy is probably in line to get this. So, tell us, what can you tell us about Jassy? Why is he qualified for this job? What do you think he brings to the table? >> Well, the thing that I know about Amazon everyone's been following the Amazon news is, Jeff Bezos has a lot of personal turmoil. They had his marriage fail. They had some issues with the smear campaigns and all this stuff going on, the run-ins with Donald Trump, he bought the Washington post. He's got a lot of other endeavors outside of Amazon cause he's the second richest man in the world competing with Elon Musk at Space X versus Blue Origin. So the guy's a billionaire. So Amazon is his baby and he's been running it as best he could. He's got an executive team committee they called the S team. He's been grooming people in the company and that's just been his mode. And the rise of AWS and the business performance that we've been documenting on SiliconANGLE and theCUBE, it's just been absolutely changing the game on Amazon as a company. So clearly Amazon Web Services become a driving force of the new Amazon that's emerging. And obviously they've got all their retail business and they got the gaming challenges and they got the studios and the other diversified stuff. So Jassy is just, he's just one of those guys. He's just been an Amazonian from day one. He came out of Harvard business school, drove across the country, very similar story to Jeff Bezos. He did that in 1997 and him and Jeff had been collaborating and Jeff tapped him to be his shadow, they call it, which is basically technical assistance and an heir apparent and groomed him. And then that's how it is. Jassy is not a climber as they call it in corporate America. He's not a person who is looking for a political gain. He's not a territory taker, but he's a micromanager. He loves details and he likes to create customer value. And that's his focus. So he's not a grandstander. In fact, he's been very low profile. Early days when we started meeting with him, he wouldn't meet with press regularly because they weren't writing the right stories. And everyone is, he didn't know he was misunderstood. So that's classic Amazon. >> So, he gave us the time, I think it was 2014 or 15 and he told us a story back then, John, you might want to share it as to how AWS got started. Why, what was the main spring Amazon's tech wasn't working that great? And Bezos said to Jassy, going to go figure out why and maybe explain how AWS was born. >> Yeah, we had, in fact, we were the first ones to get access to do his first public profile. If you go to the Google and search Andy Jassy, the trillion dollar baby, we had a post, we put out the story of AWS, Andy Jassy's trillion dollar baby. This was in early, this was January 2015, six years ago. And, we back then, we posited that this would be a trillion dollar total addressable market. Okay, people thought we were crazy but we wrote a story and he gave us a very intimate access. We did a full drill down on him and the person, the story of Amazon and that laid out essentially the beginning of the rise of AWS and Andy Jassy. So that's a good story to check out but really the key here is, is that he's always been relentless and competitive on creating value in what they call raising the bar outside Amazon. That's a term that they use. They also have another leadership principle called working backwards, which is like, go to the customer and work backwards from the customer in a very Steve Job's kind of way. And that's been kind of Jobs mentality as well at Apple that made them successful work backwards from the customer and make things easier. And that was Apple. Amazon, their philosophy was work backwards from the customer and Jassy specifically would say it many times and eliminate the undifferentiated heavy lifting. That was a key principle of what they were doing. So that was a key thesis of their entire business model. And that's the Amazonian way. Faster, cheaper, ship it faster, make it less expensive and higher value. While when you apply the Amazon shipping concept to cloud computing, it was completely disrupted. They were shipping code and services faster and that became their innovation strategy. More announcements every year, they out announced their competition by huge margin. They introduced new services faster and they're less expensive some say, but in the aggregate, they make more money but that's kind of a key thing. >> Well, when you, I was been listening to the TV today and there was a debate on whether or not, this support tends that they'll actually split the company into two. To me, I think it's just the opposite. I think it's less likely. I mean, if you think about Amazon getting into grocery or healthcare, eventually financial services or other industries and the IOT opportunity to me, what they do, John, is they bring in together the cloud, data and AI and they go attack these new industries. I would think Jassy of all people would want to keep this thing together now whether or not the government allows them to do that. But what are your thoughts? I mean, you've asked Andy this before in your personal interviews about splitting the company. What are your thoughts? >> Well, Jon Fortt at CNBC always asked the same question every year. It's almost like the standard question. I kind of laugh and I ask it now too because I liked Jon Fortt. I think he's an awesome dude. And I'll, it's just a tongue in cheek, Jassy. He won't answer the question. Amazon, Bezos and Jassy have one thing in common. They're really good at not answering questions. So if you ask the same question. They'll just say, nothing's ever, never say never, that's his classic answer to everything. Never say never. And he's always said that to you. (chuckles) Some say, he's, flip-flopped on things but he's really customer driven. For example, he said at one point, no one should ever build a data center. Okay, that was a principle. And then they come out and they have now a hybrid strategy. And I called them out on that and said, hey, what, are you flip-flopping? You said at some point, no one should have a data center. He's like, well, we looked at it differently and what we meant was is that, it should all be cloud native. Okay. So that's kind of revision, but he's cool with that. He says, hey, we'll revise based on what customers are doing. VMware working with Amazon that no one ever thought that would happen. Okay. So, VMware has some techies, Raghu, for instance, over there, super top notch. He worked with Jassy, directly in his team Sanjay Poonen when they went to business school together, they cut a deal. And now Amazon essentially saved VMware, in my opinion. And Pat Gelsinger drove that deal. Now, Pat Gelsinger, CEO, Intel, and Pat told me that directly in candid conversation off theCUBE, he said, hey, we have to make a decision either we're going to be in cloud or we're not going to be in cloud, we will partner. And I'll see, he was Intel. He understood the Intel inside mentality. So that's good for VMware. So Jassy does these kinds of deals. He's not afraid he's got a good stomach for business and a relentless competitor. >> So, how do you think as you mentioned Jassy is a micromanager. He gets deep into the technology. Anybody who's seen his two hour, three hour keynotes. No, he has a really fine grasp of the technology across the entire stack. How do you think John, he will approach things like antitrust, the big tech lash of the unionization of the workforce at Amazon? How do you think Jassy will approach that? >> Well, I think one of the things that emerges Jassy, first of all, he's a huge sports fan. And many people don't know that but he's also progressive person. He's very progressive politically. He's been on the record and off the record saying things like, obviously, literacy has been big on, he's been on basically unrepresented minorities, pushing for that, and certainly cloud computing in tech, women in tech, he's been a big proponent. He's been a big supporter of Teresa Carlson. Who's been rising star at Amazon. People don't know who Teresa Carlson is and they should check out her. She's become one of the biggest leaders inside Amazon she's turned around public sector from the beginning. She ran that business, she's a global star. He's been a great leader and he's been getting, forget he's a micromanager, he's on top of the details. I mean, the word is, and nothing gets approved without Andy, Andy seeing it. But he's been progressive. He's been an Amazon original as they call it internally. He's progressive, he's got the business acumen but he's perfect for this pragmatic conversation that needs to happen. And again, because he's so technically strong having a CEO that's that proficient is going to give Amazon an advantage when they have to go in and change how DC works, for instance, or how the government geopolitical landscape works, because Amazon is now a global company with regions all over the place. So, I think he's pragmatic, he's open to listening and changing. I think that's a huge quality >> Well, when you think of this, just to set the context here for those who may not know, I mean, Amazon started as I said back in 2006 in March with simple storage service that later that year they announced EC2 which is their compute platform. And that was the majority of their business, is still a very large portion of their business but Amazon, our estimates are that in 2020, Amazon did 45 billion, 45.4 billion in revenue. That's actually an Amazon reported number. And just to give you a context, Azure about 26 billion GCP, Google about 6 billion. So you're talking about an industry that Amazon created. That's now $78 billion and Amazon at 45 billion. John they're growing at 30% annually. So it's just a massive growth engine. And then another story Jassy told us, is they, he and Jeff and the team talked early on about whether or not they should just sort of do an experiment, do a little POC, dip their toe in and they decided to go for it. Let's go big or go home as Michael Dell has said to us many times, I mean, pretty astounding. >> Yeah. One of the things about Jassy that people should know about, I think there's some compelling relative to the newest ascension to the CEO of Amazon, is that he's not afraid to do new things. For instance, I'll give you an example. The Amazon Web Services re-invent their annual conference grew to being thousands and thousands of people. And they would have a traditional after party. They called a replay, they'd have a band like every tech conference and their conference became so big that essentially, it was like setting up a live concert. So they were spending millions of dollars to set up basically a one night concert and they'd bring in great, great artists. So he said, hey, what's been all this cash? Why don't we just have a festival? So they did a thing called Intersect. They got LA involved from creatives and they basically built a weekend festival in the back end of re-invent. This was when real life was, before COVID and they turned into an opportunity because that's the way they think. They like to look at the resources, hey, we're already all in on this, why don't we just keep it for the weekend and charge some tickets and have a good time. He's not afraid to take chances on the product side. He'll go in and take a chance on a new market. That comes from directly from Bezos. They try stuff. They don't mind failing but they put a tight leash on measurement. They work backwards from the customer and they are not afraid to take chances. So, that's going to board well for him as he tries to figure out how Amazon navigates the contention on the political side when they get challenged for their dominance. And I think he's going to have to apply that pragmatic experimentation to new business models. >> So John I want you to take on AWS. I mean, despite the large numbers, I talked about 30% growth, Azure is growing at over 50% a year, GCP at 83%. So despite the large numbers and big growth the growth rates are slowing. Everybody knows that, we've reported it extensively. So the incoming CEO of Amazon Web Services has a TAM expansion challenge. And at some point they've got to decide, okay, how do we keep this growth engine? So, do you have any thoughts as to who might be the next CEO and what are some of their challenges as you see it? >> Well, Amazon is a real product centric company. So it's going to be very interesting to see who they go with here. Obviously they've been grooming a lot of people. There's been some turnover. You had some really strong executives recently leave, Jeff Wilkes, who was the CEO of the retail business. He retired a couple of months ago, formerly announced I think recently, he was probably in line. You had Mike Clayville, is now the chief revenue officer of Stripe. He ran all commercial business, Teresa Carlson stepped up to his role as well as running public sector. Again, she got more power. You have Matt Garman who ran the EC2 business, Stanford grad, great guy, super strong on the product side. He's now running all commercial sales and marketing. And he's also on the, was on Bezos' S team, that's the executive kind of team. Peter DeSantis is also on that S team. He runs all infrastructure. He took over for James Hamilton, who was the genius behind all the data center work that they've done and all the chip design stuff that they've innovated on. So there's so much technical innovation going on. I think you still going to see a leadership probably come from, I would say Matt Garman, in my opinion is the lead dog at this point, he's the lead horse. You could have an outside person come in depending upon how, who might be available. And that would probably come from an Andy Jassy network because he's a real fierce competitor but he's also a loyalist and he likes trust. So if someone comes in from the outside, it's going to be someone maybe he trusts. And then the other wildcards are like Teresa Carlson. Like I said, she is a great woman in tech who's done amazing work. I've profiled her many times. We've interviewed her many times. She took that public sector business with Amazon and changed the game completely. Outside the Jedi contract, she was in competitive for, had the big Trump showdown with the Jedi, with the department of defense. Had the CIA cloud. Amazon set the standard on public sector and that's directly the result of Teresa Carlson. But she's in the field, she's not a product person, she's kind of running that group. So Amazon has that product field kind of structure. So we'll see how they handle that. But those are the top three I think are going to be in line. >> So the obvious question that people always ask and it is a big change like this is, okay, in this case, what is Jassy going to bring in? And what's going to change? Maybe the flip side question is somewhat more interesting. What's not going to change in your view? Jassy has been there since nearly the beginning. What are some of the fundamental tenets that he's, that are fossilized, that won't change, do you think? >> I think he's, I think what's not going to change is Amazon, is going to continue to grow and develop their platform business and enable more SaaS players. That's a little bit different than what Microsoft's doing. They're more SaaS oriented, Office 365 is becoming their biggest application in terms of revenue on Microsoft side. So Amazon is going to still have to compete and enable more ecosystem partners. I think what's not going to change is that Bezos is still going to be in charge because executive chairman is just a code word for "not an active CEO." So in the corporate governance world when you have an executive chairman, that's essentially the person still in charge. And so he'll be in charge, will still be the boss of Andy Jassy and Jassy will be running all of Amazon. So I think that's going to be a little bit the same, but Jassy is going to be more in charge. I think you'll see a team change over, whether you're going to see some new management come in, Andy's management team will expand, I think Amazon will stay the same, Amazon Web Services. >> So John, last night, I was just making some notes about notable transitions in the history of the tech business, Gerstner to Palmisano, Gates to Ballmer, and then Ballmer to Nadella. One that you were close to, David Packard to John Young and then John Young to Lew Platt at the old company. Ellison to Safra and Mark, Jobs to Cook. We talked about Larry Page to Sundar Pichai. So how do you see this? And you've talked to, I remember when you interviewed John Chambers, he said, there is no rite of passage, East coast mini-computer companies, Edson de Castro, Ken Olsen, An Wang. These were executives who wouldn't let go. So it's of interesting to juxtapose that with the modern day executive. How do you see this fitting in to some of those epic transitions that I just mentioned? >> I think a lot of people are surprised at Jeff Bezos', even stepping down. I think he's just been such the face of Amazon. I think some of the poll numbers that people are doing on Twitter, people don't think it's going to make a big difference because he's kind of been that, leader hand on the wheel, but it's been its own ship now, kind of. And so depending on who's at the helm, it will be different. I think the Amazon choice of Andy wasn't obvious. And I think a lot of people were asking the question who was Andy Jassy and that's why we're doing this. And we're going to be doing more features on the Andy Jassy. We got a tons, tons of content that we've we've had shipped, original content with them. We'll share more of those key soundbites and who he is. I think a lot of people scratching their head like, why Andy Jassy? It's not obvious to the outsiders who don't know cloud computing. If you're in the competing business, in the digital transformation side, everyone knows about Amazon Web Services. Has been the most successful company, in my opinion, since I could remember at many levels just the way they've completely dominated the business and how they change others to be dominant. So, I mean, they've made Microsoft change, it made Google change and even then he's a leader that accepts conversations. Other companies, their CEOs hide behind their PR wall and they don't talk to people. They won't come on Clubhouse. They won't talk to the press. They hide behind their PR and they feed them, the media. Jassy is not afraid to talk to reporters. He's not afraid to talk to people, but he doesn't like people who don't know what they're talking about. So he doesn't suffer fools. So, you got to have your shit together to talk to Jassy. That's really the way it is. And that's, and he'll give you mind share, like he'll answer any question except for the ones that are too tough for him to answer. Like, are you, is facial recognition bad or good? Are you going to spin out AWS? I mean these are the hard questions and he's got a great team. He's got Jay Carney, former Obama press secretary working for him. He's been a great leader. So I'm really bullish on, is a good choice. >> We're going to jump into the Clubhouse here and open it up shortly. John, the last question for you is competition. Amazon as a company and even Jassy specifically I always talk about how they don't really focus on the competition, they focus on the customer but we know that just observing these folks Bezos is very competitive individual. Jassy, I mean, you know him better than I, very competitive individual. So, and he's, Jassy has been known to call out Oracle. Of course it was in response to Larry Ellison's jabs at Amazon regarding database. But, but how do you see that? Do you see that changing at all? I mean, will Amazon get more publicly competitive or they stick to their knitting, you think? >> You know this is going to sound kind of a weird analogy. And I know there's a lot of hero worshiping on Elon Musk but Elon Musk and Andy Jassy have a lot of similarities in the sense of their brilliance. They got both a brilliant people, different kinds of backgrounds. Obviously, they're running different things. They both are builders, right? If you were listening to Elon Musk on Clubhouse the other night, what was really striking was not only the magic of how it was all orchestrated and what he did and how he interviewed Robin Hood. He basically is about building stuff. And he was asked questions like, what advice do you give startups? He's like, if you need advice you shouldn't be doing startups. That's the kind of mentality that Jassy has, which is, it's not easy. It's not for the faint of heart, but Elon Musk is a builder. Jassy builds, he likes to build stuff, right? And so you look at all the things that he's done with AWS, it's been about enabling people to be successful with the tools that they need, adding more services, creating things that are lower price point. If you're an entrepreneur and you're over the age of 30, you know about AWS because you know what, it's cheaper to start a business on Amazon Web Services than buying servers and everyone knows that. If you're under the age of 25, you might not know 50 grand to a hundred thousand just to start something. Today you get your credit card down, you're up and running and you can get Clubhouses up and running all day long. So the next Clubhouse will be on Amazon or a cloud technology. And that's because of Andy Jassy right? So this is a significant executive and he continue, will bring that mindset of building. So, I think the digital transformation, we're in the digital engine club, we're going to see a complete revolution of a new generation. And I think having a new leader like Andy Jassy will enable in my opinion next generation talent, whether that's media and technology convergence, media technology and art convergence and the fact that he digs music, he digs sports, he digs tech, he digs media, it's going to be very interesting to see, I think he's well-poised to be, and he's soft-spoken, he doesn't want the glamorous press. He doesn't want the puff pieces. He just wants to do what he does and he puts his game do the talking. >> Talking about advice at startups. Just a quick aside. I remember, John, you and I when we were interviewing Scott McNealy former CEO of Sun Microsystems. And you asked him advice for startups. He said, move out of California. It's kind of tongue in cheek. I heard this morning that there's a proposal to tax the multi-billionaires of 1% annually not just the one-time tax. And so Jeff Bezos of course, has a ranch in Texas, no tax there, but places all over. >> You see I don't know. >> But I don't see Amazon leaving Seattle anytime soon, nor Jassy. >> Jeremiah Owyang did a Clubhouse on California. And the basic sentiment is that, it's California is not going away. I mean, come on. People got to just get real. I think it's a fad. Yeah. This has benefits with remote working, no doubt, but people will stay here in California, the network affects beautiful. I think Silicon Valley is going to continue to be relevant. It's just going to syndicate differently. And I think other hubs like Seattle and around the world will be integrated through remote work and I think it's going to be much more of a democratizing effect, not a win lose. So that to me is a huge shift. And look at Amazon, look at Amazon and Microsoft. It's the cloud cities, so people call Seattle. You've got Google down here and they're making waves but still, all good stuff. >> Well John, thanks so much. Let's let's wrap and let's jump into the Clubhouse and hear from others. Thanks so much for coming on, back on theCUBE. And many times we, you and I've done this really. It was a pleasure having you. Thanks for your perspectives. And thank you for watching everybody, this is Dave Vellante for theCUBE. We'll see you next time. (soft ambient music)

>>From Las Vegas. It's the cube covering Qualis security conference 2019 you buy quality. >>Hey, welcome back. You're ready. Jeff Frick here with the cube. We're in Las Vegas at the Bellagio, at the quality security conference. It's the 19th year they've been doing this. It's our first year here and we're excited to be here and it's great to have a veteran who's been in this space for so long, to give a little bit more of a historical perspective as to what happened in the past and where we are now and what can we look forward to in the future. So coming right off his keynote is Felipe korto, the chairman and CEO of Qualys. Phillip, great to see you. Thank you. Same, same, same for me. Absolutely. So you touched on so many great, um, topics in your conversation about kind of the shifts of, of, of modern computing from the mainframe to the mini. We've heard it over and over and over, but the key message was really about architecture. If you don't have the right architecture, you can't have the right solution. So how has the evolution of architects of architectures impacted your ability to deliver security solutions for your clients? >>So now that's a very good question. And in fact, you know, what happened is that we started in 1999 with a vision that we could use exactly like a salesforce.com this nascent internet technologies and apply that to security. And uh, so, and mod when you have applied that to essentially changing the way CRM was essentially used and deployed in enterprises and with a fantastic success as we know. So for us, the, I can say today that 19 years later the vision was right. It took a significant longer because the security people are not really, uh, warm at the idea of silently, uh, having the data in their view, which was in place that they could not control. And the it people, they didn't really like at all the fact that suddenly they were not in control anymore of the infrastructure. So we had a lot of resistance. >>I, wherever we always, I always believe, absolutely believe that the, the cloud will be the cloud architecture to go back. A lot of people make the confusion. That was part of the confusion that for people it was a cloud, that kind of magical things someplace would you don't know where. And when I were trying to explain, and I've been saying that so many times that well you need to look at the cloud like compute that can architecture which distribute the competing power far more efficiently than the previous one, which was client server, which was distributing the convening power far better than of course the mainframes and the mini computers. And so if you look at their architectures, so the mainframe were essentially big data centers in uh, in Fort Knox, like settings, uh, private lines of communication to a dump terminal. And of course security was not really issue then because it's security was built in by the IBM's and company. >>Same thing with the mini computer, which then was instead of just providing the computing power to the large, very large company, you could afford it. Nelson and the minicomputer through the advanced in semiconductor technology could reduce a foot Frank. And then they'll bring that computing power to the labs and to the departments. And was then the new era of the digital equipment, the prime, the data general, et cetera. Uh, and then kind of server came in. So what client server did, again, if you look at the architecture, different architecture now silently servers, the land or the internal network and the PC, and that was now allowing to distribute the computing power to the people in the company. And so, but then you needed to, so everybody, nobody paid attention to security because then you were inside of the enterprise. So it started inside the walls of the castle if you prefer. >>So nobody paid attention to that. It was more complex because now you have multiple actors. Instead of having one IBM or one digital equipment, et cetera, suddenly you have the people in manufacturing and the servers, the software, the database, the PCs, and on announcer, suddenly there was the complexity, increasing efficiency, but nobody paid attention to security because it wasn't a needed until suddenly we realized that viruses could come in through the front door being installed innocently. You were absolutely, absolutely compromised. And of course that's the era of the antivirus which came in. And then because of the need to communicate more and more now, Senator, you could not stay only in your castle. You needed to go and communicate to your customers, to your suppliers, et cetera, et cetera. And now he was starting to open up your, your castle to the world and hello so now so that the, the bad guy could come in and start to steal your information. >>And that was the new era of the forward. Now you make sure that those who come in, but of course that was a little bit naive because there were so many other doors and windows, uh, that people could come in, you know, create tunnels and create these and all of that trying to ensure your customers because the data was becoming more and more rich and more, more important or more value. So whenever there is a value, of course the bad guys are coming in to try to sell it. And that was that new era of a willing to pay attention to security. The problem has been is because you have so many different actors, there was nothing really central there that was just selling more and more solutions and no, absolutely like 800 vendors bolting on security, right? And boating on anything is short-lived at the end of the day because you put more and more weight and then you also increase the complexity and all these different solutions you need. >>They need to talk together so you have a better context. Uh, but they want the design to talk together. So now you need to put other system where they could communicate that information. So you complicated and complicated and complicated the solution. And that's the problem of today. So now cloud computing comes in and again, if you look at the architecture of cloud computing, it's again data centers, which is not today I've become thanks to the technology having infinite, almost competing power and storage capabilities. And like the previous that I sent her, the are much more fractured because you just one scale and they become essentially a little bit easier to secure. And by the way, it's your fewer vendors now doing that. And then of course the access can be controlled better. Uh, and then of course the second component is not the land and the one, it's now the internet. >>And the internet of course is the web communications extremely cheap and it brings you an every place on the planet and soon in Morris, why not? So and so. Now the issue today is that still the internet needs to be secure. And today, how are we going to secure the internet? Which is very important thing today because you see today that you can spoof your email, you can spoof your website, uh, you can attack the DNS who, yes, there's a lot of things that the bad guys still do. And in fact, they've said that leverage the internet of course, to access everywhere so they take advantage of it. So now this is obviously, you know, I created the, the trustworthy movement many years ago to try to really address that. Unfortunately, the quality's was too small and it was not really our place today. There's all the Google, the Facebook, the big guys, which in fact their business depend on the internet. >>Now need to do that. And I upload or be diabetic, criticized very much so. Google was the first one to essentially have a big initiative, was trying to push SSL, which everybody understand is secret encryption if you prefer. And to everybody. So they did a fantastic job. They really push it. So now today's society is becoming like, okay, as I said, you want to have, as I said it all in your communication, but that's not enough. And now they are pushing and some people criticize them and I absolutely applaud them to say we need to change the internet protocols which were created at a time when security, you were transferring information from universities and so forth. This was the hay days, you know, of everything was fine. There was no bad guys, you know, the, he'd be days, if you like, of the internet. Everybody was free, everybody was up and fantastic. >>Okay. And now of course, today this protocol needs to be upgraded, which is a lot of work. But today I really believe that if you put Google, Amazon, Facebook altogether, and they can fix these internet protocols. So we could forget about the spoofing and who forgot about all these phishing and all these things. But this is their responsibility. So, and then you have now on the other side, you have now very intelligent devices from in a very simple sensors and you know, to sophisticated devices, the phone, that cetera and not more and more and more devices interconnected and for people to understand what is going. So this is the new environment and whether we always believe is that if you adopt an architecture, which is exactly which fits, which is similar, then we could instead of bolting security in, we can now say that the build security in a voting security on, we could build security in. >>And we have been very proud of the work that we've done with Microsoft, which we announced in fact relatively recently, very recently, that in fact our agent technologies now is bundled in Microsoft. So we have built security with Microsoft in. So from a security perspective today, if you go to the Microsoft as your secretly center, you click on the link and now you have the view of your entire Azure environment. Crazier for quality Sagent. You click on a second link and now you have the view of your significant loss posture, crazy of that same quality. Say Sagent and then you click on the third name with us. Nothing to do with quality. It's all Microsoft. You create your playbook and you remediate. So security in this environment has become click, click, click, nothing to install, nothing to update. And the only thing you bring are your policies saying, I don't want to have this kind of measured machine expose on the internet. >>I want, this is what I want. And you can continuously audit in essentially in real time, right? So as you can see, totally different than putting boxes and boxes and so many things and then having to for you. So very big game changer. So the analogy that I want you that I give to people, it's so people don't understand that paradigm shift is already happening in the way we secure our homes. You put sensors everywhere, you have cameras, you have detection for proximity detection. Essentially when somebody tried to enter your home, all that data is continuously pumped up into an incidence restaurant system. And then from your phone, again across the internet, you can change the temperature of your rooms. You can do what you can see the person who knocks on the door. You can see its face, you can open the door, close the door, the garage door, you can do all of that remotely, another medically. >>And then if there's a burglar then in your house to try to raking immediately the incidents or some system called the cops or the far Marsha difficult fire. And that's the new paradigm. So security has to follow that paradigm. And then you have interesting of the problem today that we see with all the current secretly uh, systems, uh, incidents, response system. They have a lot of false positive, false positive and false negative are the enemy really of security. Because if you are forced visited, you cannot automate the response because then you are going to try to respond to something that is not true. So you are, you could create a lot of damage. And the example I give you that today in the, if you leave your dog in your house and if you don't have the ability, the dog will bark, would move. And then the sensors would say intruder alert. >>So that's becomes a false positive. So how do you eliminate that? By having more context, you can eliminate automatically again, this false positives. Like now you take a fingerprint of your dog and of these voice and now the camera and this and the sensors and the voice can pick up and say, Oh, this is my dog. So then of course you eliminate that for solar, right? Right. Now even if another dog managed to enter your home through a window which was open or whatever for soul, you will know her window was up and but you know you cannot necessarily fix it and the dog opens. Then you will know it's a, it's a, it's not sure about, right? So that's what security is evolving such a huge sea of change, which is happening because of all that internet and today companies today, after leveraging new cloud technology, which are coming, there's so much new technology. >>What people understand is where's that technology coming from? How come silently we have, you know, Dockers netics all these solutions today, which are available at almost no cost because it's all open source. So what happened is that, which is unlike the enterprise software, which were more the Oracle et cetera, the manufacturer of that software today is in fact the cloud public cloud vendors, the Amazon, the Google, the Facebook, the Microsoft. We suddenly needed to have to develop new technology so they could scale at the size of the planet. And then very shrewdly realized that effective that technology for me, I'm essentially going to imprison that technology is not going to evolve. And then I need other technologies that are not developing. So they realized that they totally changed that open source movement, which in the early days of opensource was more controlled by people who had more purity. >>If you prefer no commercial interests, it was all for the good of the civilization and humankind. And they say their licensing model was very complex. So they simplified all of that. And then nothing until you had all this technology coming at you extremely fast. And we have leverage that technology, which was not existing in the early days when when socials.com started with the Linux lamp pour called what's called Linux Apache. My SQL and PHP, a little bit limiting, but now suddenly all this technology, that classic search was coming, we today in our backend, 3 trillion data points on elastic search clusters and we return inflammation in a hundred milliseconds. And then onto the calf cabin, which is again something at open source. We, we, we, and now today 5 million messages a day and on and on and on. So the world is changing and of course, if that's what it's called now, the digital transformation. >>So now enterprises to be essentially agile, to reach out to the customers better and more, they need to embrace the cloud as the way they do, retool their entire it infrastructure. And essentially it's a huge sea of change. And that's what we see even the market of security just to finish, uh, now evolving in a totally different ways than the way it has been, which in the past, the market of security was essentially the market for the enterprise. And I'm bringing you my, my board, my board town solutions that you have to go and install and make work, right? And then you had the, the antivirus essentially, uh, for all the consumers and so forth. So today when we see the marketplace, which is fragmenting in four different segments, which is one is the large enterprise which are going to essentially consolidate those stock, move into the digital transformation, leveraging absolutely dev ops, which isn't becoming the new buyer and of course a soak or they could improve, uh, their it for, to reach out to more customers and more effectively than the cloud providers as I mentioned earlier, which are building security in the, no few use them. >>You don't have to worry about infrastructure, about our mini servers. You need, I mean it is, it's all done for you. And same thing about security, right? The third market is going to be an emergence of a new generation of managed security service providers, which are going to take to all these companies. We don't have enough resources. Okay, don't worry, I'm going to help you, you know, do all that digital transformation. And that if you build a security and then there's a totally new market of all these devices, including the phone, et cetera, which connects and that you essentially want to all these like OT and IOT devices that are all now connected, which of course presents security risk. So you need to also secure them, but you also need to be able to also not only check their edits to make sure that, okay, because you cannot send people anymore. >>So you need to automate the same thing on security. If you find that that phone is compromised, you need to make, to be able to make immediate decisions about should I kill that phone, right? Destroyed everything in it. Should I know don't let that phone connect anymore to my networks. What should I do? Should I, by the way detected that they've downloaded the application, which are not allowed? Because what we see is more and more companies now are giving tablets, do the users. And in doing so now today's the company property. So they could say, okay, you use these tablets and uh, you're not allowed to do this app. So you could check all of that and then automatically remote. But that again requires a full visibility on what you are. And that's why just to finish, we make a big decision about a few, three months ago that we have, we build the ability for any company on the planet to automatically build their entire global HSE inventory, which nobody knows what they have in that old networking environment. >>You don't know what connects to have the view of the known and the unknown, totally free of charge, uh, across on premise and pawn cloud containers, uh, uh, uh, whether vacations, uh, OT and IOT devices to come. So now there's the cornerstone of security. So with that totally free. So, and then of course we have all these additional solutions and we're build a very scalable, uh, up in platform where we can take data in, pass out data as well. So we really need to be and want to be good citizen here because security at the end of the day, it's almost like we used to say like the doctors, you have to have that kind of apricot oath that you cannot do no arm. So if you keep, if you try to take the data that you have, keep it with you, that's absolutely not right because it's the data of your customers, right? >>So, and you have to make sure that it's there. So you have to be a good warning of the data, but you have to make sure that the customer can absolutely take that data to whatever he wants with it, whatever he needs to do. So that's the kind of totally new field as a fee. And finally today there is a new Ash culture change, which is, which is happening now in the companies, is that security has become fronted centers, is becoming now because of GDPR, which has a huge of financial could over you challenge an impact on a company. A data breach can have a huge financial impact. Security has become a board level. More and more social security is changing and now it's almost like companies, if they want to be successful in the future, they need to embrace a culture of security. And now what I used to say, and that was the, the conclusion of my talk is that now, today it DevOps, uh, security compliance, people need to unite. Not anymore. The silos. I do that. This is my, my turf, my servers. You do that, you do this. Everybody in the company can work. I have to work together towards that goal. And the vendors need to also start to inter operate as well and working with our customers. So it's a tall, new mindset, which is happening, but the safes are big. That's what I'm very confident that we're now into that. Finally, we thought, I thought it would have happened 10 years ago, quite frankly. And uh, but now today's already happening. >>She touched on a lot, a lot there. And I'll speak for another two hours if we could. We could go for Tara, but I want to, I want to unpack a couple of things. We've had James Hamilton on you to at AWS. Um, CTO, super smart guy and it was, it was at one of his talks where it really was kind of a splash, a wet water in the face when he talked about the amount of resources Amazon could deploy to just networking or the amount of PhD power he could put on, you know, any little tiny sub segment of their infrastructure platform where you just realize that you just can't, you can't compete, you cannot put those kinds of resources as an individual company in any bucket. So the inevitability of the cloud model is just, it's, it's the only way to leverage those resources. But because of that, how has, how has that helped you guys change your market? How nice is it for you to be able to leverage infrastructure partners? Like is your bill for go to market as well as feature sets? And also, you know, because the other piece they didn't talk about is the integration of all these things. Now they all work together. Most apps are collection of API APIs. That's also changed. So when you look at the cloud provider GCP as well, how does that help you deliver value to your customers? >>Yeah, but the, the, the, the club, they, they don't do everything. You know, today what is interesting is that the clubs would start to specialize themselves more and more. So for example, if you look at Amazon, the, the core value of Amazon since the beginning has been elastic computing. Uh, now today we should look at Microsoft. They leverage their position and they really have come up with a more enterprise friendly solution. And now Google is trying to find also their way today. And so then you have Addy Baba, et cetera. So these are the public cloud, but life is not uniform like is by nature. Divers life wants to leave lunch to find better ways. We see that that's what we have so many different species and it just ended up. So I've also the other phenomena of companies also building their own cloud as well. >>So the word is entering into a more hybrid cloud. And the technology is evolving very fast as well. And again, I was selling you all these open source software. There's a bigger phenomenon at play, which I used to say that people don't really understand that much wood, but it's so obvious is if you look at the printing price, that's another example that gives the printing price essentially allowed, as we all know, to distribute the gospel, which has some advantage of, you know, creating more morality, et cetera. But then what people don't know for the most part, it distributed the treaties of the Arabs on technology, the scientif treaties, because the archives, which were very thriving civilization at the time, I'd collected all the, all the, all the information from India, from many other places and from China and from etc. And essentially at the time all of Europe was pretty in the age they really came up and it now certainty that scientific knowledge was distributed and that was in fact the seeds of the industrial revolution, which then you're up cat coats and use that and creating all these different technologies. >>So that confidence of this dimension of electricity and all of that created the industrial revolution seeded by now, today what is happening is that the internet is the new printing press, which now is distributing the knowledge that not to a few millions of people to billions of people. So the rate today of advancing technology is accelerating and it's very difficult. I was mentioning today, we know today that work and working against some quantum computing which are going to totally change things. Of course we don't know exactly how and you have also it's clear that today we could use genetic, uh, the, the, the, if you look at DNA, which stores so much information, so little place that we could have significant more, you know, uh, memory capabilities that lower costs. So we have embarked into absolutely a new world where things are changing. I've got a little girl, which is 12 years old and fundamentally that new generation, especially of girls, not boys, because the boys are still on, you know, at that age. >>Uh, they are very studious. They absorb so much information via YouTube. They are things like a security stream. They are so knowledgeable. And when you look back at history 2000 years plus ago in Greece, you at 95 plus percent of the population slaves. So a few percent could start to think now, today it's totally changed. And the amount of information they can, they learn. And this absolutely amazing. And you know, she, she's, I would tell you the story which has nothing to do with computing, but as a button, the knowledge of, she came to me the few, few weeks ago and she said, Oh daddy, I would like to make my mother more productive. Okay. So I said, Oh, that's her name is Avia, which is the, which is the, the, the either Greece or Zeus weathered here. And so I say, Evie, I, so that's a good idea. >>So how are you going to do it? I mean, our answer, I was flawed, but that is very simple. Just like with, for me, I'm going to ask her to go to YouTube to learn what she needs to learn. Exactly. And she learns, she draws very well. She learns how to draw in YouTube and it's not a gifted, she's a nice, very nice little girl and very small, but all her friends are like that. Right? So we're entering in a word, which thing are changing very, very fast. So the key is adaptation, education and democracy and democratization. Getting more people access to more. Absolutely. It's very, very important. And then kind of this whole dev ops continuous improve that. Not big. That's a very good point that you make because that's exactly today the new buyer today in security and in it is becoming the DevOps shipper. >>Because what? What are these people? There are engineers which suddenly create good code and then they want to of course ship their code and then all these old silos or you need to do these, Oh no, we need to put the new server, we don't have the capacity, et cetera. How is that going to take three months or a month? And then finally they find a way through, again, you know, all the need for scale, which was coming from the Google, from the Facebook and so forth. And by the way, we can shortcut all of that and we can create and we can run out to auto-ship, our code. Guess what are they doing today? They are learning how to secure all of that, right? So again, it's that ability to really learn and move. And today, uh, one of the problem that you alluded to is that, which the Amazon was saying is that their pick there, they have taken a lot of the talent resources in the U S today because of course they pay them extra to me, what? >>Of course they'll attract that talent. And of course there's now people send security. There's not enough people that even in, but guess what? We realized that few years ago in 2007, we'll make a big decision who say, well, never going to be able to attract the right people in the Silicon Valley. And we've started to go to India and we have now 750 people. And Jack Welch used to say, we went to India for the cost and discover the talent. We went to India for the talent and we discover the cost. And there is a huge pool of tenants. So it's like a life wants to continue to leave and now to, there are all these tools to learn, are there, look at the can Academy, which today if you want to go in nuclear physics, you can do that through your phone. So that ability to learn is there. So I think we need just more and more people are coming. So I'm a very optimistic in a way because I think the more we improve our technologies that we look at the progress we're making genetics and so everywhere and that confidence of technology is really creating a new way. >>You know, there's a lot of conversations about a dystopian future and a utopian future with all these technologies and the machines. And you know what? Hollywood has shown us with AI, you're very utopian side, very optimistic on that equation. What gives you, what gives you, you know, kind of that positive feeling insecurity, which traditionally a lot of people would say is just whack a mole. And we're always trying to chase the bad guys. Generally >>speaking, if I'm a topian in in a way. But on the other end, you'd need to realize that unfortunately when you have to technological changes and so forth, it's also create factors. And when you look at this story in Manatee, the same technological advancement that some countries to take to try to take advantage of fathers is not that the word is everything fine and everything peaceful. In fact, Richard Clark was really their kid always saying that, Hey, you know that there is a sinister side to all the internet and so forth. But that's the human evolution. So I believe that we are getting longterm. It's going to. So in the meantime there's a lot of changes and humans don't adapt well to change. And so that's in a way, uh, the big challenge we have. But I think over time we can create a culture of change and that will really help. And I also believe that probably at some point in time we will re-engineer the human race. >>All right, cool. We'll leave it there. That's going to launch a whole nother couple hours. They leave. Congratulations on the event and a great job on your keynote. Thanks for taking a few minutes with us. Alrighty. It's relief. I'm Jeff. You're watching the cube where the Qualice security conference at the Bellagio in Las Vegas. Thanks for watching. We'll see you next time.

>> from Cambridge, Massachusetts. It's the Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to Cambridge, Massachusetts. Everybody, You're watching the Cube, the leader in live tech coverage, and we're covering the M I t CDO conference M I t. CDO. My name is David Monty in here with my co host, Paul Galen. Mike Stone breakers here. The legend is founder CTO of Of Tamer, as well as many other companies. Inventor Michael. Thanks for coming back in the Cube. Good to see again. Nice to be here. So this is kind of ah, repeat pattern for all of us. We kind of gather here in August that the CDO conference You're always the highlight of the show. You gave a talk this week on the top 10. Big data mistakes. You and I are one of the few. You were the few people who still use the term big data. I happen to like it. Sad that it's out of vogue already, but people associated with the doo doop it's kind of waning, but regardless, so welcome. How'd the talk go? What were you talking about. >> So I talked to a lot of people who were doing analytics. We're doing operation Offer operational day of data at scale, and they always make most of them make a collection of bad mistakes. And so the talk waas a litany of the blunders that I've seen people make, and so the audience could relate to the blunders about most. Most of the enterprise is represented. Make a bunch of the blunders. So I think no. One blunder is not planning on moving most everything to the cloud. >> So that's interesting, because a lot of people would would would love to debate that, but and I would imagine you probably could have done this 10 years ago in a lot of the blunders would be the same, but that's one that wouldn't have been there. But so I tend to agree. I was one of the two hands that went up this morning, and vocalist talk when he asked, Is the cloud cheaper for us? It is anyway. But so what? Why should everybody move everything? The cloud aren't there laws of physics, laws of economics, laws of the land that suggest maybe you >> shouldn't? Well, I guess 22 things and then a comment. First thing is James Hamilton, who's no techies. Techie works for Amazon. We know James. So he claims that he could stand up a server for 25% of your cost. I have no reason to disbelieve him. That number has been pretty constant for a few years, so his cost is 1/4 of your cost. Sooner or later, prices are gonna reflect costs as there's a race to the bottom of cloud servers. So >> So can I just stop you there for a second? Because you're some other date on that. All you have to do is look at a W S is operating margin and you'll see how profitable they are. They have software like economics. Now we're deploying servers. So sorry to interrupt, but so carry. So >> anyway, sooner or later, they're gonna have their gonna be wildly cheaper than you are. The second, then yet is from Dave DeWitt, whose database wizard. And here's the current technology that that Microsoft Azure is using. As of 18 months ago, it's shipping containers and parking lots, chilled water in power in Internet, Ian otherwise sealed roof and walls optional. So if you're doing raised flooring in Cambridge versus I'm doing shipping containers in the Columbia River Valley, who's gonna be a lot cheaper? And so you know the economies of scale? I mean, that, uh, big, big cloud guys are building data centers as fast as they can, using the cheapest technology around. You put up the data center every 10 years on dhe. You do it on raised flooring in Cambridge. So sooner or later, the cloud guys are gonna be a lot cheaper. And the only thing that isn't gonna the only thing that will change that equation is For example, my lab is up the street with Frank Gehry building, and we have we have an I t i t department who runs servers in Cambridge. Uh, and they claim they're cheaper than the cloud. And they don't pay rent for square footage and they don't pay for electricity. So yeah, if if think externalities, If there are no externalities, the cloud is assuredly going to be cheaper. And then the other thing is that most everybody tonight that I talk thio including me, has very skewed resource demands. So in the cloud finding three servers, except for the last day of the month on the last day of the month. I need 20 servers. I just do it. If I'm doing on Prem, I've got a provision for peak load. And so again, I'm just way more expensive. So I think sooner or later these combinations of effects was going to send everybody to the cloud for most everything, >> and my point about the operating margins is difference in price and cost. I think James Hamilton's right on it. If he If you look at the actual cost of deploying, it's even lower than the price with the market allows them to their growing at 40 plus percent a year and a 35 $40,000,000,000 run rate company sooner, Sooner or >> later, it's gonna be a race to the lot of you >> and the only guys are gonna win. You have guys have the best cost structure. A >> couple other highlights from your talk. >> Sure, I think 2nd 2nd thing like Thio Thio, no stress is that machine learning is going to be a game is going to be a game changer for essentially everybody. And not only is it going to be autonomous vehicles. It's gonna be automatic. Check out. It's going to be drone delivery of most everything. Uh, and so you can, either. And it's gonna affect essentially everybody gonna concert of, say, categorically. Any job that is easy to understand is going to get automated. And I think that's it's gonna be majorly impactful to most everybody. So if you're in Enterprise, you have two choices. You can be a disrupt or or you could be a disruptive. And so you can either be a taxi company or you can be you over, and it's gonna be a I machine learning that's going going to be determined which side of that equation you're on. So I was a big blunder that I see people not taking ml incredibly seriously. >> Do you see that? In fact, everyone I talked who seems to be bought in that this is we've got to get on the bandwagon. Yeah, >> I'm just pointing out the obvious. Yeah, yeah, I think, But one that's not quite so obvious you're is a lot of a lot of people I talked to say, uh, I'm on top of data science. I've hired a group of of 10 data scientists, and they're doing great. And when I talked, one vignette that's kind of fun is I talked to a data scientist from iRobot, which is the guys that have the vacuum cleaner that runs around your living room. So, uh, she said, I spend 90% of my time locating the data. I want to analyze getting my hands on it and cleaning it, leaving the 10% to do data science job for which I was hired. Of the 10% I spend 90% fixing the data cleaning errors in my data so that my models work. So she spends 99% of her time on what you call data preparation 1% of her time doing the job for which he was hired. So data science is not about data science. It's about data integration, data cleaning, data, discovery. >> But your new latest venture, >> so tamer does that sort of stuff. And so that's But that's the rial data science problem. And a lot of people don't realize that yet, And, uh, you know they will. I >> want to ask you because you've been involved in this by my count and starting up at least a dozen companies. Um, 99 Okay, It's a lot. >> It's not overstated. You estimated high fall. How do you How >> do you >> decide what challenge to move on? Because they're really not. You're not solving the same problems. You're You're moving on to new problems. How do you decide? What's the next thing that interests you? Enough to actually start a company. Okay, >> that's really easy. You know, I'm on the faculty of M i t. My job is to think of news new ship and investigate it, and I come up. No, I'm paid to come up with new ideas, some of which have commercial value, some of which don't and the ones that have commercial value, like, commercialized on. So it's whatever I'm doing at the time on. And that's why all the things I've commercialized, you're different >> s so going back to tamer data integration platform is a lot of companies out there claim to do it day to get integration right now. What did you see? What? That was the deficit in the market that you could address. >> Okay, great question. So there's the traditional data. Integration is extract transforming load systems and so called Master Data management systems brought to you by IBM in from Attica. Talent that class of folks. So a dirty little secret is that that technology does not scale Okay, in the following sense that it's all well, e t l doesn't scale for a different reason with an m d l e t l doesn't scale because e t. L is based on the premise that somebody really smart comes up with a global data model For all the data sources you want put together. You then send a human out to interview each business unit to figure out exactly what data they've got and then how to transform it into the global data model. How to load it into your data warehouse. That's very human intensive. And it doesn't scale because it's so human intensive. So I've never talked to a data warehouse operator who who says I integrate the average I talk to says they they integrate less than 10 data sources. Some people 20. If you twist my arm hard, I'll give you 50. So a Here. Here's a real world problem, which is Toyota Motor Europe. I want you right now. They have a distributor in Spain, another distributor in France. They have a country by country distributor, sometimes canton by Canton. Distribute distribution. So if you buy a Toyota and Spain and move to France, Toyota develops amnesia. The French French guys know nothing about you. So they've got 250 separate customer databases with 40,000,000 total records in 50 languages. And they're in the process of integrating that. It was single customer database so that they can Duke custom. They could do the customer service we expect when you cross cross and you boundary. I've never seen an e t l system capable of dealing with that kind of scale. E t l dozen scale to this level of problem. >> So how do you solve that problem? >> I'll tell you that they're a tamer customer. I'll tell you all about it. Let me first tell you why MGM doesn't scare. >> Okay. Great. >> So e t l says I now have all your data in one place in the same format, but now you've got following problems. You've got a d duplicated because if if I if I bought it, I bought a Toyota in Spain, I bought another Toyota in France. I'm both databases. So if you want to avoid double counting customers, you got a dupe. Uh, you know, got Duke 30,000,000 records. And so MGM says Okay, you write some rules. It's a rule based technology. So you write a rule. That's so, for example, my favorite example of a rule. I don't know if you guys like to downhill downhill skiing, All right? I love downhill skiing. So ski areas, Aaron, all kinds of public databases assemble those all together. Now you gotta figure out which ones are the same the same ski area, and they're called different names in different addresses and so forth. However, a vertical drop from bottom to the top is the same. Chances are they're the same ski area. So that's a rule that says how to how to put how to put data together in clusters. And so I now have a cluster for mount sanity, and I have a problem which is, uh, one address says something rather another address as something else. Which one is right or both? Right, so now you want. Now you have a gold. Let's call the golden Record problem to basically decide which, which, which data elements among a variety that maybe all associated with the same entity are in fact correct. So again, MDM, that's a rule's a rule based system. So it's a rule based technology and rule systems don't scale the best example I can give you for why Rules systems don't scale. His tamer has another customer. General Electric probably heard of them, and G wanted to do spend analytics, and so they had 20,000,000 spend transactions. Frank the year before last and spend transaction is I paid $12 to take a cab from here here to the airport, and I charged it to cost center X Y Z 20,000,000 of those so G has a pre built classification system for spend, so they have parts and underneath parts or computers underneath computers and memory and so forth. So pre existing preexisting class classifications for spend they want to simply classified 20,000,000 spent transactions into this pre existing hierarchy. So the traditional technology is, well, let's write some rules. So G wrote 500 rules, which is about the most any single human I can get there, their arms around so that classified 2,000,000 of the 20,000,000 transactions. You've now got 18 to go and another 500 rules is not going to give you 2,000,000 more. It's gonna give you love diminishing returns, right? So you have to write a huge number of rules and no one can possibly understand. So the technology simply doesn't scale, right? So in the case of G, uh, they had tamer health. Um, solve this. Solved this classification problem. Tamer used their 2,000,000 rule based, uh, tag records as training data. They used an ML model, then work off the training data classifies remaining 18,000,000. So the answer is machine learning. If you don't use machine learning, you're absolutely toast. So the answer to MDM the answer to MGM doesn't scale. You've got to use them. L The answer to each yell doesn't scale. You gotta You're putting together disparate records can. The answer is ml So you've got to replace humans by machine learning. And so that's that seems, at least in this conference, that seems to be resonating, which is people are understanding that at scale tradition, traditional data integration, technology's just don't work >> well and you got you got a great shot out on yesterday from the former G S K Mark Grams, a leader Mark Ramsay. Exactly. Guys. And how they solve their problem. He basically laid it out. BTW didn't work and GM didn't work, All right. I mean, kick it, kick the can top down data modelling, didn't work, kicked the candid governance That's not going to solve the problem. And But Tamer did, along with some other tooling. Obviously, of course, >> the Well, the other thing is No. One technology. There's no silver bullet here. It's going to be a bunch of technologies working together, right? Mark Ramsay is a great example. He used his stream sets and a bunch of other a bunch of other startup technology operating together and that traditional guys >> Okay, we're good >> question. I want to show we have time. >> So with traditional vendors by and large or 10 years behind the times, And if you want cutting edge stuff, you've got to go to start ups. >> I want to jump. It's a different topic, but I know that you in the past were critic of know of the no sequel movement, and no sequel isn't going away. It seems to be a uh uh, it seems to be actually gaining steam right now. What what are the flaws in no sequel? It has your opinion changed >> all? No. So so no sequel originally meant no sequel. Don't use it then. Then the marketing message changed to not only sequel, So sequel is fine, but no sequel does others. >> Now it's all sequel, right? >> And my point of view is now. No sequel means not yet sequel because high level language, high level data languages, air good. Mongo is inventing one Cassandra's inventing one. Those unless you squint, look like sequel. And so I think the answer is no sequel. Guys are drifting towards sequel. Meanwhile, Jason is That's a great idea. If you've got your regular data sequel, guys were saying, Sure, let's have Jason is the data type, and I think the only place where this a fair amount of argument is schema later versus schema first, and I pretty much think schema later is a bad idea because schema later really means you're creating a data swamp exactly on. So if you >> have to fix it and then you get a feel of >> salary, so you're storing employees and salaries. So, Paul salaries recorded as dollars per month. Uh, Dave, salary is in euros per week with a lunch allowance minds. So if you if you don't, If you don't deal with irregularities up front on data that you care about, you're gonna create a mess. >> No scheme on right. Was convenient of larger store, a lot of data cheaply. But then what? Hard to get value out of it created. >> So So I think the I'm not opposed to scheme later. As long as you realize that you were kicking the can down the road and you're just you're just going to give your successor a big mess. >> Yeah, right. Michael, we gotta jump. But thank you so much. Sure appreciate it. All right. Keep it right there, everybody. We'll be back with our next guest right into the short break. You watching the cue from M i t cdo Ike, you right back

>> live from Las Vegas. It's the queue covering del Technologies. World twenty nineteen, brought to you by Del Technologies and its ecosystem partners. >> Okay, welcome back. Everyone's cubes. Live coverage. Day three wrap up of Del Technologies World twenty nineteen Java is Dave a lot. There's too many men on set one. We get set to over there blue set, White said. We got a lot of content. It's been a cube can, in guise of a canon of content firing into the digital sphere. Great gas. We had all the senior executive players Tech athletes. Adele Technology World. Michael Dell, Tom Sweet, Marius Haas, Howard Ally As we've had Pat Kelsey, rco v M were on the key partner in the family. They're of del technology world and we had the clients guys on who do alien where, as well as the laptops and the power machines. Um, we've had the power edge guys on. We talked about Hollywood. It's been a great run, but Dave, it's been ten years Stew. Remember, the first cube event we ever went to was DMC World in Boston. The chowder there he had and that was it wasn't slogan of of the show turning to the private cloud. Yeah, I think that was this Logan cheering to the private cloud that was twenty ten. >> Well, in twenty ten, it was Cloud Cloud Cloud Cloud Cloud twenty nineteen. It's all cloud now. That difference is back then it was like fake cloud and made up cloud and really was no substance to it. We really started to see stew, especially something that we've been talking about for years, which is substantially mimicking the public cloud on Prem. Now I know there are those who would say No, no, no, no, no. And Jessie. Probably in one of those that's not cloud. So there's still that dichotomy is a cloud. >> Well, Dave, if I could jump in on that one of the things that's really interesting is when Veum, where made that partnership with a ws It was the ripple through this ecosystem. Oh, what's that mean for Del you know Veum, wherein Del not working together Well, they set the model and they started rolling out bm where, and they took the learnings that they had. And they're bringing that data center as a service down to the Dell environment. So it's funny I always we always here, you know, eight of us, They're learning from their partners in there listening and everything like that. Well, you know, Dylan Veum where they've been listening, they've been learning to in this, and it brings into a little bit of equilibrium for me, that partnership and right, David, you said, you know that you could be that cloud washing discussion. And today it's, you know, we're talking about stacks that live in eight of us and Google and Microsoft. And now, in, you know, my hosted or service lighter or, you know, my own data center. If that makes sense, >> I mean, if you want to just simplify the high order bit, Dave Cloud. It's simply this Amazon's trying to be enterprised everyone, the enterprise, trying to claw Amazon, right? And so what? The what that basically means is it's all cloud. It's all a distributed computer system. OK, Scott McNealy had it right. The network is the computer. If you look at what's going on here, the traditional enterprise of vendors over decades of business model and technology, you know, had full stack solutions from mainframe many computers to PC the local area networking all cobble together wires it up creates applications, services. All that is completely being decimated by a new way to roll out storage, computing and networking is the same stuff. It's just being configured differently. Throw on massive computer power with Cloud and Moore's Law and Data and A. I U have a changing of the the architecture. But the end of the day the cloud is operating model of distributed computing. If you look at all the theories and pieces of computer science do and networking, all those paradigms are actually playing out in in the clouds. Everything from a IIE. In the eighties and nineties you got distributed networking and computing, but it's all one big computer. And Michael Dell, who was the master of the computer industry building PCs, looks at this. Probably leg. It's one big computer. You got a processor and subsystems. So you know this is what's interesting. Amazon has done that, and if they try to be like the enterprise, like the old way, they could fall into that trap. So if the enterprise stays in the enterprise, they know they're not going out. So I think it's interesting that I see the enterprise trying to like Amazon Amazon trying to get a price. So at the end of the day, whoever could build that system that's scalable the way I think Dell's doing, it's great. I was only scaleable using data for special. So it's a distributed computer. That's all that's going on in the world right now, and it's changing everything. Open source software is there. All that makes it completely different, and it's a huge opportunity. Whoever can crack the code on this, it's in the trillions and trillions of dollars. Total adjustable market >> well, in twenty ten we said that way, noted the gap. There's still a gap between what Amazon could do and what the on Prem guys Khun Dio, we'd argue, is a five years is seven years, maybe ten years, whatever it is. But at the time we said, if you recall, lookit, they got to close the gap. It's got to be good enough for I t to buy into it like we're starting to see that. But my view, it's still not cloud. It doesn't have to scale a cloud, doesn't have the economics cloud. When you peel the onion, it doesn't certainly doesn't have the SAS model and the consumption model of cloud nowhere close yet. Well, and you know, >> here's the drumbeat of innovation that we see from the public cloud. You know where we hit the shot to show this week, the public have allowed providers how many announcements that they probably had. Sure, there was a mega launch of announcements here, but the public lives just that regular cadence of their, you know, Public Cloud. See a CD. We're not quite there yet in this kind of environment, it's still what Amazon would say is. You put this in an environment and it's kind of frozen. Well, it's thought some, and it's now we can get data set. A service consumption model is something we can go. We're shifting in that model. It's easier to update things, but you know, how do I get access to the new features? But we're seeing that blurring of the line. I could start moving services that hybrid nature of the environment. We've talked a few times. We've been digging into that hybrid cloud taxonomy and some of the services to span because it's not public or private. It's now truly that hybrid and multi environment and customers are going to live in. And all of >> the questions Jonah's is good enough to hold serve >> well. I think the reality is is that you go back to twenty ten, the jury in the private cloud and it's enterprises almost ten years to figure out that it's real. And I think in that time frame Amazon is absolutely leveled. Everybody, we call that the tsunami. Microsoft quickly figures out that they got to get Cloud. They come in there, got a fast followers. Second, Google's trying to retool Oracle. I think Mr Bo completely get Ali Baba and IBM in there, so you got the whole cloud game happening. The problem of the enterprises is that there's no growth in terms of old school enterprise other than re consolidate in position for Cloud. My question to you guys is, Is there going to be true? True growth in the classic enterprise business or, well, all this SAS run on clouds. So, yes, if it's multi cloud or even hybrid for the reasons they talk about, that's not a lot of growth compared to what the cloud can offer. So again, I still haven't seen Dave the visibility in my mind that on premises growth is going to be massive compared to cloud. I mean, I think cloud is where Sassen lives. I think that's where the scale lives we have. How much scale can you do with consolidation? We >> are in a prolonged bull market that that started in twenty ten, and it's kind of hunger. In the tenth year of a of a decade of bull market, the enterprise market is cyclical, and it's, you know, at some point you're going to start to see a slowdown cloud. I mean, it's just a tiny little portion of the market is going to continue to gain share cloud can grow in a downturn. The no >> tell Motel pointed out on this, Michael Dell pointed out on the Cubans, as as those lieutenants, the is the consolidation of it is just that is a retooling to be cloud ready operationally. That's where hybrid comes in. So I think that realization has kicked in. But as enterprises aren't like, they're not like Google and Facebook. They're not really that fast, so So they've got to kind of get their act together on premises. That's why I think In the short term, this consolidation and new revitalisation is happening because they're retooling to be cloud ready. That is absolutely happen. But to say that's the massive growth studio >> now looked. It is. Dave pointed out that the way that there is more than the market growth is by gaining market share Share share are areas where Dell and Emcee didn't have large environment. You know, I spent ten years of DMC. I was a networking. I was mostly storage networking, some land connectivity for replication like srd Evan, like today at this show, I talked a lot of the telco people talk to the service of idle talk where the sd whan deny sirrah some of these pieces, they're really starting to do networking. That's the area where that software defined not s the end, but the only in partnership with cos like Big Switch. They're getting into that market, and they have such small market share their that there's huge up uplift to be able to dig into the giant. >> Okay, couple questions. What percent of Dell's ninety one billion today is multi cloud revenue. Great question. Okay, one percent. I mean, very small. Okay. Very small hero. Okay? And is that multi cloud revenue all incremental growth isat going to cannibalize the existing base? These? Well, these are the fundamentals weighs six local market that I'm talking to >> get into this. You led the defense of conversations. We had Tom Speed on the CFO and he nailed us. He said There's multiple levers to shareholder growth. Pay down the debt check. He's got to do that. You love that conversation. Margin expansion. Get the margins up. Use the client business to cover costs. As you said, increased go to market efficiency and leverage. The supply chain that's like their core >> fetrow of cash. And that all >> these. The one thing he said that was mind blowing to me is that no one gets the valuation of how valuable Del Technologies is. They're throwing off close to seven billion dollars in free cash flow free cash flow. Okay, so you can talk margin expansion all you want. That's great, but there got this huge cash flow coming in. You can't go out of business worth winning if you don't run out of cash >> in the market. When the market is good, these guys are it is good a position is anybody, and I would argue better position than anybody. The question on the table that I'm asking is, how long can it last? And if and when the market turns down and markets always cyclical we like again. We're in the tenth year of a bull market. I mean, it's someone >> unprecedented gel can use the war chest of the free cash flow check on these levers that they're talking about here, they're gonna have the leverage to go in during the downturn and then be the cost optimizer for great for customers. So right now, they're gonna be taking their medicine, creating this one common operating environment, which they have an advantage because they have all the puzzle pieces. You A Packer Enterprises doesn't have the gaping holes in the end to end. They can't address us, >> So that is a really good point that you're making now. So then the next question is okay. If and when the downturn turn comes, who's going to take advantage of it, who's going to come out stronger? >> I think Amazon is going to be continued to dominate, and as long as they don't fall into the enterprise trap of trying to be too enterprising, continue to operate their way for enterprises. I think jazz. He's got that covered. I think DEL Technologies is perfectly positioned toe leverage, the cash flow and the thing to do that. I think Cisco's got a great opportunity, and I think that's something that you know. You don't hear a lot of talk about the M where Cisco war happening. But Cisco has a network. They have a developer ecosystem just starting to get revitalized. That's an opportunity. So >> I got thoughts on Cisco, too. But one of things I want to say about Del being able to come out of that stronger. I keep saying I've said this a number of times and asked a lot of questions this week is the PC business is vital for Del. It's almost half the company's revenue. Maybe not quite, but it it's where the company started it. It sucks up a lot of corporate overhead. >> If Hewlett Packard did not spin out HP HP, they would be in the game. I think spinning that out was a huge mistake. I wrote about a publicly took a lot of heat for it, but you know I try to go along with the HPD focus. Del has proven bigger is better. HP has proven that smaller is not as leverage. And if it had the PC that bee have the mojo in gaming had the mojo in the edge, and Dale's got all the leverage to cross pollinate the front end and edge into the back and common cloud operate environment that is going to be an advantage. And that's going to something that will see Well, let me let me >> let me counter what you just said. I agree. You know this this minute. But the autonomy was the big mistake. Once hp autonomy, you know what Meg did was almost a fatal complete. They never should've bought autonomy >> makers. Levi Protector he was. So he was there. >> But she inherited that bag of rocks. And then what you gonna do with it? Okay, so that's why they had to spend out and did create shareholder value. If they had not purchased autonomy, then he would return much better shape, not to split it up. And they would be a much stronger competitor. >> And I share holder Pop. They had a pop on value. People made some cash with long game. I think that >> going toe peon base actually done pretty well for a first year holding a standalone PC company. So, but again, I think Del. With that leverage, assuming pieces, it's going to be really interesting. I don't know much about that market. You were loving that PC conversation, but the whole, you know, the new game or markets and and the new wayto work throwing an edge in there, I don't know is ej PC and edges that >> so the peanut butter. And so the big thing that Michael get the big thing, Michael Dell said on the Cube was We're not a conglomerate were an integrated company. And when you have an integrated company like this, with the tech the tech landscape shifting to their advantage, you have the ability to cross subsidize. So strategy game. Matt Baker was here we'd be talking about OK, I can cross subsidize margin. You've brought it up on the client side. Smaller margins, but it pays a lot of the corporate overhead. Absolutely. Then you got higher margin GMC business was, you know, those margins that's contributing. And so when you have this new configuration. You can cross, subsidize and move and shift, so I think that's a great advantage. I think that's undervalued in the market place. And I think, you know, I think Del stock price is, well, undervalue. Point out the numbers they got VM wear and their question is, What what point is? VM where blink and go All in on del technology stew. Orcas Remember that Gus was gonna partner. You don't think the phone was ringing off the hook in Palo Alto from their parties? What? What's this as your deal? So Vienna. There's gotta be the neutral party. Big problem. The opportunity. >> Well, look, if I'm a traditional historical partner of'Em are, it's not the Azure announcement that has me a little bit concerned because all of them partner with Microsoft to it is how tightly combined. Del and Veum, where are the emcee, always kept them in arms like now they're in the same. It's like Dave. They're blending it. It's like, you know Del, from a market cap standpoint, gets fifty cents on the dollar. VM wears a software company, and they get their multiples. Del is not a software company, but VM where well, people are. Well, if we can win that a little bit, maybe we could get that. >> Marty still Isn't it splendid? No, no, I think the strategy is absolutely right on. You have to go hard with VM wear and use it as a competitive weapon. But, Stuart, your point fifty cents and all, it's actually much worse than that. I mean the numbers. If you take out of'Em, wears the VM wear ownership, you take out the core debt and you look at the market value you're left with, like a billion dollars. Cordell is undervalued. Cordell is worth more than a billion or two billion dollars. Okay, so it's a really cheap way to buy Veum. Where Right that the Tom Sweet nailed this, he said. You know, basically, these company those the streets not used to tech companies having such big debt. But to your point, John, they're throwing off cash. So this company is undervalued, in my view. Now there's some risks associated with that, and that's why the investors of penalizing them for that debt there, penalizing him from Michael's ownership structure. You know, that's what this is, but >> a lack of understanding in my opinion. I think I think you're right. I just think they don't understand. Look at Dale and they think G You don't look a day Ellen Think distributed computing system with software, fill in those gaps and all that extra ten expansion. It's legit. I think they could go after new market opportunities as as a twos to us as the client business. I mean mere trade ins and just that's massive trillions of dollars. It's, I think I think that is huge. But I'm >> a bull. I'm a bull on the value of the company. I know >> guys most important developments. Del technology world. What's the big story that you think is coming out of the show here? >> Well, it's definitely, you know, the VM wear on del I mean, that is the big story, and it's to your point. It's Del basically saying we're going to integrate this. We're going to hard, we're going to go hard and you know Veum wear on Dell is a preferred solution. No doubt that is top for Dell and PacBell Singer said it. Veum wearing eight of us is the first and preferred solution. Those are the two primary vectors. They're going to drive hard and then Oh, yeah, we'Ll listen to customers Whatever else you want Google as you're fine, we're there. But those two vectors, they're going to Dr David >> build on that because we saw the, um we're building out of multi cloud strategy and what we have today is Del is now putting themselves in there as a first class citizen. Before it was like, Oh, we're doing VX rail and Anna sex and, you know, we'LL integrate all these pieces there, but infrastructure, infrastructure, infrastructure now it is. It is multi cloud. We want to see that the big table, >> right, Jeff, Jeff Clarke said, Why are you doing both? Let's just one strategy, one company. It's all one Cash registers that >> saying those heard that before. I think the biggest story to me is something that we've been seeing in the Cuban laud, you know, been Mom. This rant horizontally scaleable operating environment is the land grab and then vertically integrate with data into applications that allow each vertical industry leverage data for the kind of intimate, personalized experiences for user experiences in each industry. With oil and gas public sector, each one has got their own experiences that are unique. Data drives that, but the horizontal and tow an operating model when it's on premises hybrid or multi cloud is a huge land grab. And I think that is a major strategic win for Dell, and I think, as if no one challenges them on this. Dave, if HP doesn't go on, emanate change. If H h p e does not do it em in a complete changeover from strategy and pulling, filling their end to end, I think that going to be really hurting I think there's gonna be a tell sign and we'LL see, See who reacts and challenges Del on this in ten. And I think if they can pull it off without being contested, >> the only thing I would say that the only thing I would say that Jonah's you know, HP, you know very well I mean, they got a lot of loyal customers and is a huge market out there. So it's >> Steve. Look at economic. The economics are shifting in the new world. New use cases, new step function of user experiences. This is this is going to be new user experiences at new economic price points that's a business model. Innovation, loyal customers that's hard to sustain. They'Ll keep some clutching and grabbing, but everyone will move to the better mousetrap in the scenario. So the combination of that stability with software it's just this as a big market. >> So John twenty ten Little Table Back Corner, you know of'em See Dylan Blogger World double set. Beautiful says theatre of present lot of exchange and industry. But the partnership in support of this ecosystem. It's something that helped us along the way. >> You know, when we started doing this, Jeff came on board. The team has been amazing. We have been growing up and getting better every show. Small, incremental improvements here and there has been an amazing production, Amazing team all around us. But the support of the communities do this is has been a co creation project from day one. We love having this conversation's with smart people. Tech athletes make it unique. Make it organic, let the page stuff on on the other literature pieces go well. But here it's about conversations for four and with the community, and I think the community sponsorship has been part of funding mohr of it. You're seeing more cubes soon will be four sets of eight of US four sets of V M World four sets here. Global Partners sets I'm used to What have we missed? >> Yeah, it's phenomenal. You know, we're at a unique time in the industry and honored to be able to help documented with the two of you in the whole team. >> Dave, How it Elias sitting there giving him some kind of a victory lap because we've been doing this for ten years. He's been the one of the co captains of the integration. He says. There's a lot of credit. >> Yeah, Howard has had an amazing career. I I met him like literally decades ago, and he has always taken on the really hard jobs. I mean, that's I think, part of his secret success, because it's like he took on the integration he took on the services business at at AMC U members to when Joe did you say we're a product company? No services company. I was like, Give me services. Take it. >> It's been on the Cube ten years. Dave. He was. He was John away. He was on fire this week. I thought bad. Kelsey was phenomenal. >> Yeah, he's an amazing guest. Tom Tom Suite, You know, very strong moments. >> What's your favorite Cuban? I'LL never forget. Joe Tucci had my little camera out film and Joe Tucci, Anna. One of the sessions is some commentary in the hallway. >> Well, that was twenty ten, one of twenty eleven, I think one of my favorite twenty ten moments I go back to the first time we did. The cue was when you asked Joe Tucci, you know why a storage sexy. Remember that? >> A He never came on >> again. Ah, but that was a mean. If you're right, that was a cube mean all for the next couple of years. Remember, Tom Georges, we have because I'm not touching. That was >> so remember when we were critical of hybrid clouds like twenty, twelve, twenty, thirteen I go, Pat is a hybrid cloud, a halfway house to the final destination of public loud. He goes to a halfway house, three interviews. This was like the whole crowd was like, what just happened? Still favorite moment. >> Oh, gosh is a mean so money here, John. As you said, just such a community, love. You know, the people that we've had on for ten years and then, you know, took us, you know, three or four years to before we had Michael Dell on. Now he's a regular on our program with luminaries we've had on, you know, but yeah, I mean, twenty ten, you know, it's actually my last week working for him. See? So, Dave, thanks for popping me out. It's been a fun ride, and yeah, I mean, it's amazing to be able to talk to this whole community. >> Favorite moment was when we were at eighty bucks our first show. We're like, We still like hell on this. James Hamilton, Andy Jazzy Come on up, Very small show. Now it's a monster, David The Cube has had some good luck. Well, we've been on the right waves, and a lot of a lot of companies have sold their companies. Been part of Q comes when public Unicorns New Channel came on early on. No one understood that company. >> What I'm thrilled about to Jonah's were now a decade, and we're documenting a lot of the big waves. One of one of the most memorable moments for me was when you called me up. That said, Hey, we're doing a dupe world in New York. I got on a plane and went out. I landed in, like, two. Thirty in the morning. You met me. We did to dupe World. Nobody knew what to do was back then it became, like, the hottest thing going. Now nobody talks about her dupe. So we're seeing these waves and the Cube was able to document them. It's really >> a pleasure. The Cube can and we got the Cube studios sooner with cubes Stories with Cube Network too. Cue all the time, guys. Thanks. It's been a pleasure doing business with you here. Del Technologies shot out the letter. Chuck on the team. Sonia. Gabe. Everyone else, Guys. Great job. Excellent set. Good show. Closing down. Del Technologies rose two cubes coverage. Thanks for watching

(upbeat techno music) >> From Union Square in downtown San Francisco, it's theCUBE, covering PagerDuty Summit '18. Now, here's Jeff Frick. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're at PagerDuty summit in the Westin St. Francis, Union Square, San Francisco. We're excited to have our next guest, this guy likes to get into the weeds. We'll get some into the weeds, not too far in the weeds. Armon Dagar, he's a co-founder and CTO of HashiCorp. Armon, great to see you. >> Thanks so much for having me, Jeff. >> Absolutely, so you're just coming off your session so how did the session go? What did you guys cover? >> It's super good, I mean I think what we wanted to do was sort of take a broader look and not just talk too much just about monitoring and so the talk was really about zero trust networking. Sort of the what, the how, the why. >> Right, right, so that's very important topic. Did Bitcoin come up or blockchain? Or are you able to do zero trust with no blockchain? >> We were able to get through with no blockchain, thankfully I suppose. >> Right. >> But I think kind of the gist of it when we talk about, I think that the challenge is it's still sort of at that nascent point where people are like, okay, zero trust networking I've heard of it, I don't really know what it is or what mental category to put it in. So I think what we tried to do was sort not get too far in the weeds, as you know I tend to do but sort of start high level. >> Right, right. >> And say, what's the problem, right? And I think the problem is we live in this world today of traditional flat networks where, I have a castle and moat, right? I wrap my data center in four walls, all my traffic comes over a drawbridge, and you're either on the outside and you're bad and untrusted or your on the inside and you're good and trusted. And so what happens when a bad guy gets in, right? >> Right. >> It's sort of this all or nothing model, right? >> But now we know, the bad guys are going to get in, right? It's only a function of time, right? >> Right, and I think you see it with the Target breech, the Neiman Marcus breech, the Google breech, right? The list sort of goes on, right? It's like, Equifax, right? It's a bad idea to assume they never get in. (laughing) >> If you assume they get in, so then, if you know the bad guys are going to get in, you got to bake that security in all different levels of your applications, your data, all over the place. >> Exactly. >> So what are some of the things you guys covered in the session? >> So I think the core of it is really saying how do we get to a point where we don't trust our network, where we assume the attacker will get on the network and then what? How do you design around that assumption, right? And what you really have to do is push identity everywhere, right? So every application has to say, I'm a web server and I'm connecting to a database, and is this allowed, right? Is a web server allowed to talk to the database? And that's really the crux of what Google calls Beyond Crop, what other people call sort of zero trust networking, is this idea of identity based where I'm saying it's not IP one talking to IP two, it's web server talking to database. >> Right, right, because then you've got all the role and rules and everything associated at that identity level? >> Bingo, exactly. >> Yeah. >> Exactly, and I think what's made that very hard historically is when we say, what do you have at the network? You have IPs and ports. So how do we get to a point where we know one thing is a web server and one thing's a database, right? >> Right. >> And I think the crux of the challenge there, is kind of three pieces, right? You need application identity. You have to say this is a web server, this is a database. You need to distribute certificates to them and say, you get a certificate that says you're a web server, you get a certificate that says you're a database and you have to enforce that access, right? So everyone can't just randomly talk to each other. >> Right, well then what about context too, right? Because context is another piece that maybe somebody takes advantage of and has access to the identity but is using it in way or there's an interaction that's kind of atypical to what's expected behavior, it just doesn't make sense. So context really matters quite a bit as well. >> Yeah, you're super, super right and I think this is where it gets into not only do we need to assign identity to the applications but how do we tie that back into sort of rich access controls of who's allowed to do what, audit trails of, okay it seems odd, this web server that never connects to this database suddenly out of the blue doing so, why? >> Right, right. >> And do we need to react to it? Do we need to change the rule? Do we need to investigate what's going on? >> Right. >> But you're right. It's like, that context is important of what's expected versus what's unexpected. >> Right, then you have this other X factor called shared infrastructure and hybrid cloud and I've got apps running on AWS, I've got apps running at Google, I've got apps running at Microsoft, I got apps running in the database, I've got some dev here, I've got some prod here. You know that adds another little X factor to the zero trust. (laughing) >> Yeah, I think I aptly heard it called once, we have a service mess on our hands, right? (laughing) >> Right, right. >> We have this stuff so sort of sprawled everywhere now, how do we wrangle it? How do we get our hands around it? And so as much as I think service mess is a play on sort of the language, I think this is where that emerging category of service mesh does make sense. >> Right. >> It's really looking at that and saying, okay, I'm going to have stuff in private cloud, public cloud, maybe multiple public cloud providers, how do I treat all of that in a uniform way? I want to know what's running where. I want to have rules around who can talk to who. >> Right. >> And that's a big focus for us with Console, in terms of, how do we have a consistent way of knowing what's running where a consistent set of rules around who can talk to who. >> Right. >> And do it across all these hybrid environments, right? >> Right, right, but wait, don't buy it yet, there's more. (laughing) Because then I've got all the APIs right? So now you've got all this application integration, many of which are with cloud based applications. So now you've got that complexity and you're pulling all these bits and connections from different infrastructures, different applications, some in house, some outside, so how do you bring some organization to that madness? >> No, that's a super good question. If you ever want to role change, take a look at our marketing department, you've got this down. (laughing) You know, I would say what it comes down to a heterogeneity is going to be fundamental, right? You're going to have folks that are going to operate different tools, different technologies for whatever reasons, right? Might be a historical choice, might be just they have better relations with a particular vendor. So our view has been, how do you inter op with all these things? Part of it is focus on open source. Part of it is focus on API driven. Part of it is focused on you have to do API integrations with all these systems because you're never going to get sort of the end user to standardize everything on a single platform. >> Right, right. It's funny, we were at a show talking about RPA, robotic process automation, and they, they treat those processes as employees in the fact that they give them identities. >> Right. >> So they can manage them. You hire them, you turn 'em on, they work for you for a while and then you might want to turn them off after they're done whatever doing, that you've put them in place for. But literally they were treating them as an employee. >> Right. >> Treating them with like an employee lead identity that they could have all the assigned rules and restrictions to then let the RPA do what it was supposed to do. It's like interesting concept. >> Yeah, and I think it mirrors I think what we see in a lot of different spaces which is what we were maybe managing before was the sort of very physical thing. Maybe it was we called it Robot 1234, right? Or in the same way we might say, this is server at IP 1234. >> Right. >> On our network. And so we're managing this really physical unit, whether it's an IP, a machine, a serial number. How do we take up the level of abstraction and instead say, you know actually all of these machines, whether IP one, IP two, IP three, they're a web server and whether it's robots one, two or three, they're a door attach, right? >> Right, right. >> And so now we start talking about identity and it gives us this more powerful abstraction to sort of talk about these underlying bits. >> Right. >> And I think it sort of follows the history of everything, right? Which is like how do we add new layers of abstraction that let us manage the complexity that we have? >> Right, right, so it's interesting right in Ray Kurzweil's keynote earlier today, hopefully you saw that, he talked about, basically exponential curves and that's really what we're facing so the amount of data, the amount of complexity is only going to increase dramatically. We're trying to virtualize so much of this and abstract it away but then that adds a different layer of management. At the same time, you're going to have a lot more horsepower to work with on the compute side, so is it kind of like the old Wintel, I got a faster PC, it's getting eaten up by more windows? I mean, do you see the automation being able to keep up with kind of the increasing layers of abstraction? >> Yeah, I mean I think there's a grain of that. Are we losing, just because we're getting access to more resources are we using it more efficiently? I think there's some fairness in, with each layer of abstraction we're sort of introduction additional performance cost, sort of to reduce that, but I think overall what we might be doing is increasing the amount of compute tenfold, but adding a 5% additional management fee, so it's still, I think it's still net and net we're able to do much more productive work, go to much bigger scale but only if you have the right abstractions, right? And I think that's where this kind of stuff comes in is, okay great, I'm going to have 10 times as many machines, how do I deal with the fact that my current security model barely works at my current scale? How do I go to 10x the scale? Or if I'm pointing and clicking to provision a machine, how does that work when I'm going to manage a thousand machines, right? >> Yeah. >> You have to bring in additional tooling and automation and sort of think about it at the next higher level. >> Yeah. >> And I think that's all, all part of this process of adopting cloud and sort of getting that leverage. >> It's so interesting, just the whole scale discussion because at the end of the day, right, scale wins and there's a great interview with James Hamilton from AWS, and it's old, but he's talking about kind of scale and he talks about how many server that were sold in this whatever calendar year it was, versus how many mobile phones were sold and it's many ores of magnitude different and the fact that he's thinking in terms of these types of scales as opposed to, you know, which was a big number in the service sales side, but really the scale challenge introduced by these giant clouds and Facebook and the like really changed the game fundamentally in how do you manage these things. >> Totally, totally and I think that's been our view at HashiCorp, is that when you talk about about kinds of the tidal shift of infrastructure from on premise, relatively static VMware centric to AWS, plus Azure, plus Google, plus VMware, it's not just a change of, okay it's of one server here to one server there. It's like going from one server here to 50 servers that I'm changing at every other day rather than every other year, right? >> Right, right. >> And so it's this sort of order of magnitude of scale but also an order of magnitude in terms of sort of the rate of change as well. >> Right, right. >> And I think that puts downward pressure on how do I provision? How do I secure? How do I deploy applications? How do I secure all of this stuff, right? >> Right. >> I think ever layer of the infrastructure gets hit by this change. >> Right, right, alright so you're a smart guy. You're always looking forward. What are some of the things you're working on down the road? Big challenges that you're looking forward to tackling? >> Oh, okay, that's fun. I mean I think the biggest challenge is how do we get this stuff to be simpler for people to use? Because I think what we're going through is you get this sort of see-saw effect, right? Which is okay, we're getting access to all this new hardware, all this new compute, all these new APIs, but it's not getting simpler, right? >> Right, right. >> It's getting exponentially more complicated. >> Right, right. >> And so I think part of it is how do we go back to sort of looking at what's the core of drivers here? It's like, okay well we want to make it easier for people to deliver and deploy their applications, let's go back to sort of, in some sense, the drawing board, say how do we abstract all of these new goodies that we've been given but make it consumable and easy to learn? Because otherwise, you know, what's the point? It's like, here's a catalog of 50,000 things and no one knows how to use any of it. >> Right, right, right. (laughing) Yeah it's funny, I'm waiting for that next abstraction for AWS, instead of the big giant slide that Andy shows every year. (laughing) It's just that I just want to plug in and you figure out. >> Right. >> What connects on the backend. I can't even hardly read that stuff-- >> Maybe AI will save us. >> Let's hope so. Alright Armon, well thanks for taking a few minutes out of your day and sitting down with us. >> My pleasure, thanks so much, Jeff. >> Alright, he's Armon, I'm Jeff, you're watching theCUBE, we're at PagerDuty Summit in downtown San Francisco, thanks for watching. (upbeat techno music)

>> Announcer: From San Mateo, California, it's theCUBE! Covering SnapLogic, Innovation Day, 2018. Brought to you by SnapLogic. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are in San Mateo, at what they call the crossroads, it's 92 and 101. If you're coming by and probably sitting in a traffic, look up and you'll see SnapLogic. It's their new offices. We're really excited to be here for Innovation Day. We're excited to have this CTO, James Markarian. James, great to see you and I guess, we we last talked was a couple years ago in New York City. >> Yeah that's right, and why was I there? It was like a big data show. >> That's right. >> And we we are two years later talking about big data. >> Big data, big data is fading a little bit, because now big data is really an engine, that's powering this new thing that's so exciting, which is all about analytics, and machine learning, and we're going to eventually stop saying artificial intelligence and say augmented intelligence, 'cause there's really nothing artificial about it. >> Yeah and we might stop saying big data and just talk about data because it's becoming so ubiquitous. >> Jeff: Right. >> I know that big data, it's not necessarily going away but it's sort of how we're thinking about handling it is, like kind of evolved over time, especially in the last couple of years. >> Right. >> That's what we're kind of seeing from our customers. >> 'Cause there's kind of an ingredient now, right? It's no longer this new shiny object now. It's just part of the infrastructure that helps you get everything else done. >> Yeah, and I think when you think about it, from like, an enterprise point of view, that that shift is going from experimentation to operationalizing. I think that the things you look for in experimentation, there's like, one set of things here looking for proving out the overall value, regardless maybe of cost and uptime and other things and as you operationalize you start thinking about other considerations that obviously Enterprise IT has to think about. >> Right, so if you think back to like, Hadoop Summit and Hadoop World who were first cracking their teeth, like in 2010 or around that time frame, one of the big discussions that always comes up and that was before kind of the rise of public cloud, you know which has really taken off over the last several years, there's this kind of ongoing debate between, do you move the data to the compute or do you move the compute to the data? There was always like, this monster data gravity issue which was almost insurmountable and many would say, oh, you're never going to get all your data into the cloud. It's just way too hard and way too expensive. But, now Amazon has Snowball and Snowball isn't big enough. They actually had a diesel truck that'll come and help you come move your data. Amazon rolled that thing across the stage a couple of years ago. The data gravity thing seems to be less and if you think of a world with infinite compute, infinite stored, infinite networking asyndetically approaching zero, not necessarily good news for some vendors out there but that's a world that we're eventually getting to that changes the way that you organize all this stuff. >> Yeah, I think so and so much has changed. I was fortunate to be one of the early speakers, like I used to do Worlds and everything, and I was adamantly proclaiming you know, the destiny of Hadoop as bright and shiny and there's this question about what really happened. I think that there's a kind of a few different variables that kind of shifted at the same time. One, is of course, this like glut of computing in the cloud happened and there are so many variables moving at once. It's like, How much time do you have Jeff? >> Ask them to get a couple more drinks for us. >> Seeing our lovely new headquarters here and one of the things is that there is no big data center. We have a little closet with some of the servers we keep around but mostly, everything we do is on Amazon. You're even looking at things like, commercial real estate is changing because I don't need all the cooling and the power and the space for my data center that I once had. >> Jeff: Right, right. >> I become a lot more space efficient than I used to be and so the cloud is really kind of changing everything. On the data side, you mention this like, interesting philosophical shift, going from I couldn't possibly do it in the cloud to why in the world would we not do things in the cloud. Maybe the one stall word in there being some fears about security. Obviously there's been a lot of breaches. I think that there's still a lot of introspection everyone needs to do about, are my on premise systems actually more secure than some of these cloud providers? It's really not clear that we know the answer to that. In fact, we suspect that some of the cloud providers are actually more secure because they are professionals about it and they have the best practice. >> And a whole lot of money. >> The other thing that happened that you didn't mention, that's approaching infinity and we're not quite there yet, is interconnect speeds. So it used to be the case that I have a bunch of mainframes and I have a tier rating system and I have a high speed interconnect that puts the two together. Now with fiber networks and just in general, you can run super high speed, like WAN. Especially if you don't care quite as much about latency. So if 500 millisecond latency is still okay with you. >> Great. >> You can do a heck of a lot and move a lot to the cloud. In fact, it's so good, that we went from worrying, could I do this in the cloud at all to well, why wouldn't I do somethings in Amazon and some things in Microsoft and some things in Google? Even if it meant replicating my data across all these environments. The backdrop for some of that is, we had a lot of customers and I was thinking that people would approach it this way, they would install on premise Hadoop, whether it's like Apache or Cloud Air or the other vendors and I would hire a bunch of folks that are the administrators and retire terra data and I'm going to put all my ETL jobs on there, etc. It turned out to be a great theory and the practice is real for some folks but it turned out to be moving a lot of things to kind of shifting sands because Hadoop was evolving at the time. A lot of customers were putting a lot of pressure on it, operational pressure. Again, moving from experimentation phase over to like, operational phase. >> Jeff: Right, right. >> When you don't have the uptime guarantee and I can't just hire somebody off the street to administer this, it has to be a very sharp, knowledgeable person that's very expensive, people start saying, what am I really getting from this and can I just dump it all in S3 and apply a bunch of technology there and let Amazon worry about keeping this thing up and running? People start to say, I used to reject that idea and now it's sounding like a very smart idea. >> It's so funny we talk about people processing tech all the time, right? But they call them tech shows, they don't call them people in process shows. >> Right. >> At least not the ones we go to but time and time again I remember talking to some people about the Hadoop situation and there's just like, no Hadoop people. Sometimes technology all day long. There just aren't enough people with the skills to actually implement it. It's probably changed now but I remember that was such a big problem. It's funny you talk about security and cloud security. You know, at AWS, on Tuesday night of Reinvent, they have a special, kind of a technical keynote speak and like, James Hamilton would go. In the amount of resources, and I just remember one talk he gave just on their cabling across the ocean, and the amount of resources that he can bring to bear, relative to any individual company, is so different; much less a mid-tier company or a small company. I mean, you can bring so much more resources, expertise and knowledge. >> Yeah, the economy is a scale, their just there. >> They're just crazy. >> That's right and that why you know, you sort of assume that the cloud sort of, eventually eats everything. >> Right, right. >> So there's no reason to believe this won't be one of those cases. >> So you guys are getting Extreme. So what is Snaplogic Extreme? >> Well, Snaplogic Extreme is kind of like a response to this trend of data moving from on premise to the cloud and there are some interesting dynamics of that movement. First of all, you need to get data into the cloud, first of all and we've been doing that for years. Connect to everything, dump it in S3, ADLS, etc. No problem. The thing we're seeing with cloud computing is like, there's another interesting shift. Not only is it kind of like mess for less, and let Amazon manage all this, and I probably refer to Amazon more than other vendors would appreciate. >> Right, right. They're the leaders so let's call a spade a spade. >> Yeah. >> Certainly Google and Microsoft are out there as well so those are the top three and we've acknowledged that. >> One of the interesting things about it is that you couldn't really adequately achieve on premises is the burstiness of your compute. I run at a steady state where I need, you know, 10 servers or a 100 servers, but every once in a while, I need like, 1,000 or 10,000 servers to apply to something. So what's the on premise model? Rack and stack, 10,000 machines, and it's like waiting for the great pumpkin, waiting for that workload to come that I've been waiting months and months for and maybe it never comes but I've been paying for it. I paid for a software license for the thing that I need to run there. I'm paying for the cabling and the racking and everything and the person administering. Make sure the disks are all operating in the case where it gets used. Now, all of a sudden, we are taking Amazon and they're saying, hey, pay us for what you're using. You can use reserved pricing and pay a lower rate for the things you might actually care about on a consistent basis but then I'm going to allow you to spike, and I'll just run the meter. So this has caused software vendors like us, to look at the way we charge and the way that we deploy our resources and say, hey, that's a very good model. We want to follow that and so we introduced Snaplogic Extreme, which has a few different components. Basically, it enables us to operate in these elastic environments, shift our thinking in pricing so that we don't think about like, node based or god forbid, core based pricing and say like, hey, basically pay us for what you do with your data and don't worry about how many servers it's running on. Let Snaplogic worry about spinning up and spinning down these machines because a lot of these workloads are data integration or application workloads that we know lots about. >> Right. >> So first of all, we manage these ephemeral, what we call ephemeral or elastic clusters. Second of all, the way that we distribute our workload is by generating Spark code currently. We use the same graphic environment that you use for everything but instead of running on our engines, we kind of spit out Spark code on the end that takes advantage of the massive scale out potential for these ephemeral environments. >> Right. >> We've also kind of built this in such a way that it's Spark today but it could be like, Native or some other engine like Flank or other things that come up. We really don't care like what back end engine actually is as long as it can run certain types of data oriented jobs. It's actually like lots of things in one. We combine out data acquisition and distribution capability with this like, massive elastic scale out capability. >> Yeah, it's unbelievable how you can spin that up and then of course, most people forget you need to spin it down after the event. >> James: Yeah, that's right. >> We talked to a great vendor who talked about, you know, my customer spends no money with me on the weekend, zero. >> James: Right. >> And I'm thrilled because they're not using me. When they do use me, then they're buying stuff. I think what's really interesting is how that changes. Also, your relationship with your customer. If you have a recurring revenue model, you have to continue to deliver a value. You have to stay close to your customer. You have to stay engaged because it's not a one time pop and then you send them the 15% or 20% maintenance bill. It's really this ongoing relationship and they're actually gaining value from your products each and every time you use that. It's a very different way. >> Yeah, that's right. I think it creates better relationships because you feel like, what we do is unproportionate to what they do and vise versa, so it has this fundamental fairness about it, if you will. >> Right, it's a good relationship but I want to go down another path before you turn the cameras on. Talk a little bit about the race always between the need for compute and the compute. It used to be personified best with Microsoft and Intel until we come out with a new chip and then Microsoft OS would eat up all the extra capacity and then they'd come up with a new chip and it was an ongoing thing. You made an interesting comment that, especially in the cloud world where the scale of these things is much, much bigger, that ran a world now where the compute and the storage have kind of, outpaced the applications, if you will, and there's an opportunity for the application to catch up. Oh by the way, we have this cool new thing called machine learning and augmented intelligence. I wonder if you could, is that what's going to fill or kind of rebalance the consumption pattern? >> Yeah, it seems that way and I always think about kind of like, compute and software spiraling around each other like a helix. >> Like at one point, one is leading the other and they sort of just, one eventually surpasses the other and then you need innovation on the other side. I think for a while, like if you turn the clock way back to like, when the Pentium was introduced and everyone was like, how are we ever going to use all of the compute power. >> Windows 95, whoo! >> You know, power of like the Pentium. Do I really need to run my spreadsheets 100% faster? There's no business value whatsoever in transacting faster, or like general user interface or like graphical user interfaces or rendering web pages. Then you start seeing this new glut, often led by like researchers first. Like, software applications coming up that use all of this power because in academia you can start saying, what if I did have infinite compute? What would I do differently? You see things, you know like VR and advanced gaming, come up on the consumer side. Then I think the real answer on the business side is AI and ML. The general trend I start thinking of is something I used to talk about, back in the old days, which is conversion of like, having machines work for us instead of us working for machines. The only way we're ever going to get there is by having higher and higher intelligence on the application side so that it kind of intuits more based on what it's seen before and what it knows about you, etc., in terms of the task that needs to get done. Then there's this whole new breed of person that you need in order to wield all that power because like Hadoop, it's not just natural. You don't just have people floating around like, hey, you know, I'm going to be an Uzi expert or a yarn expert. You don't run into people everyday that's like, oh, yeah, I know neural nets well. I'm a gradient descent expert or whatever you're model is. It's really going to drive like, lots of changes I think. >> Right, well hopefully it does and especially like we were talking about earlier, you know, within core curriculums at schools and stuff. We were with Grace Hopper and Brenda Wilkerson, the new head of the Anita Borg organization, was at this Chicago public school district and they're actually starting to make CS a requirement, along with biology and and physics and chemistry and some of these other things. >> Right. >> So we do have a huge, a huge dearth of that but I want to just close out on one last concept before I let you go and you guys are way on top of this. Greg talked about what you just talked about, which is making the computers work for us versus the other way around. That's where the democratization of the power that we heard a lot about the democratization of big data and the tools and now you guys you guys are talking about the democratization of the integration, especially when you have a bunch of cloud based applications that everybody has access to and maybe, needs to stitch together a different way. But when you look at this whole concept of democratization of that power, how do you see that kind of playing out over the next several years? >> Yeah, that's a very big- >> Sorry I didn't bring you a couple of beer before I brought that up. >> Oh no, I got you covered. So it's a very big, interesting question because I think that you know, first of all, it's one of these, god knows, we can't predict with a lot of accuracy how exactly that's going to look because we're sort of juxtaposing two things. One is, part of the initial move to the cloud was the failure to properly democratize data inside the enterprise, for whatever reason, and we didn't do it. Now we have the computer resources and the central, kind of web based access to everything. Great. Now we have Cambridge Analytica and like, Facebook and people really thinking about data privacy and the fact that we want ubiquitous safe access. I think we know how to make things ubiquitous. The question is, do we know how to make it safe and fair so that the right people are using the right data and the right way? It's a little bit like, you know, there's all these cautionary tales out there like, beware of AI and robotics and everything and nobody really thinks about the danger of the data that's there. It's a much more immediate problem and yet it's sort of like the silent killer until some scandal comes up. We start thinking about these different ways we can tackle it. Obviously there's great solutions for tokenization and encryption and everything at the data level but even if you have the access to it, the question is, how do you control that wildfire that could happen as soon as the horse leaves the barn. Maybe not in it's current form, but when you look at things like Blockchain, there's been a lot of predictions about how Blockchain can be used around like, data. I think that this privacy and this curation and tracking of who has the data, who has access to it and can we control it, I think you are looking at even more like, centralized and guarded access to this private data. >> Great, interesting times. >> Yeah, yeah Jeff, for sure. >> Alright James, well thanks for taking a couple of minutes with us. I really enjoyed the conversation. >> Yeah, it's always great. Thanks for having me Jeff. >> It's James on Jeff and you're watching theCUBE We're at the Snaplogic headquarters in San Mateo, California and thanks for watching. (electronic music)