 Hi there, welcome back to Las Vegas. This is Dave Vellante with Paul Gillin. Reinvent day one and a half, where he started last night, Monday, the cube after dark, now we're going wall to wall today. Today was of course the big keynote. Adam Salipsky, the baton now handing. You know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his groove swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swami in the keynote. Adrian Cockroft is here, former AWS, former Netflix CTO. Currently an analyst, you got your own firm now. You're out there, great to see you again. Thanks for coming on the cube. Yeah, thanks. We had you on a super cloud. You gave some really good insights there back in August. So now as an outsider, you come in, obviously you got to be impressed with the size and the ecosystem and the energy of course. What were your thoughts on, you know, what you've seen so far, today's keynotes, last night, Peter DeSantis, what stood out to you? Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the largest one that we had before and everyone's turned up. It just feels like we're back. So that's really good to see. And it's sort of a slightly different style. I think there were, there was more sort of video production, things happening, I think in this keynote, more storytelling. I'm not sure it really all stitched together very well, right? Some of the stories like, how does that follow that? So there were a few things there and some of, there were spelling mistakes on the slides. You know, that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure. Just maybe a few things were sort of rushed at the last minute. Not really AWS-like, was it? It's kind of reminds me of the Patriots Paul, you know? Bill Belichick's teams are fumbling all over the place. That's right, that's right. Part of it may be, I mean, there's sort of the market. There is the, they don't have a leader in marketing right now, but they don't have a CMO. So that's sort of maybe a lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, maybe, I mean, it's all fixable and it's mine, this is mine and stuff. I'm just sort of looking at it and going, there's a few things that looked like they were not quite as good as they could have been in the way it was put together, right? But I mean, you're taking a year of not doing reinvent, being isolated, you know, we've certainly seen it with theCUBE, it's like, okay, it's not like riding a bike, you know, this sort of things that, you know, you've got to kind of relearn the muscle memory. It's more like golf than it is bicycle riding. Well, I've done AWS keynotes myself and they are pretty much scramble, it looks nice, but there's a lot of scrambling leading up to when it actually goes, right? And sometimes you can, you sometimes see a little kind of the edges of that and sometimes it's much more polished. But, you know, overall, it's pretty good. I think Peter DeSantis' keynote yesterday was a lot of really good meet there. There was some nice presentations and some great announcements there. And today I was, I thought, I was a little disappointed with some of the, I thought there could have been more. I think the way Andy Jassy did it, he crammed more announcements into his keynote and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the week. It was more poetic, right? He took the universe as the analogy for data, the ocean for security, all right, the Antarctic was sort of the event. Yeah, it looked pretty. Yeah. But I'm not sure that that was like, we're not here really to watch, you know, nature videos, right? Well, as analysts and journalists, you're like, come on, give me the meat. Yeah, that was kind of the thing. Yeah. The AWS has always been, re-invent has always been a shock and awe approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. There's, their position at the top of the market seems to be unshakable. There's no, there's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken, more fine tuning than, than grandiose statements. I think, so AWS for a long time was so far out that they basically said, we don't think about the competition. We listen to the customers. And that was always the statement. That works as long as you're always in the lead, right? Because you're the, you're introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas, they aren't leading, right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading. And they don't want to talk about some of these areas. And database, I mean, arguably. And they're pretty strong there. But the areas when you're behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game. And it's hard to be good at both, I think. And I'm not sure that they've really used the following somebody into a market and making a success of that. So there's some, it's a little harder, do you see what I mean? I get your opinion on this. So when I say database, David Floyer was two years ago predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift, you know, end to end. Not sure it's fully end to end, but it's getting there. That's a really good, that is an excellent piece of work because there's a lot of work that it eliminates. There's a clear pain points. But then you've got sort of the competing thing is like the MongoDB and it's like, it's just a one database, keeps it simple. Snowflake. Or you've got, on Snowflake maybe, you've got all these 20 different things you're trying to integrate at AWS. But it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas. You want a toy Formula One racing car since that seems to be the theme, right? Do you want the fully built model that you can play with right now or do you want the Lego Technic version that you have to spend three days building, right? And AWS is the Lego Technic thing. You have to spend some time building it, but once you've built it, you can evolve it. And you'll still be playing. Those are still good bricks years later. Whereas that pre-built toy is probably broken, gathering dust, right? So there's something about having an evolvable architecture which is harder to get into, but more durable in the long term. So AWS tends to play the long game in many ways and that's one of the elements that they do that. And that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top and here's the solution, you know? And Paul, that was always Andy Jassy's answer to when we would ask him, you know, all these primitives, you're going to make it simpler. You say the primitives give us the advantage to turn on a dime in the marketplace and that's true. Yeah, so you're seeing, you know, that you take all these things together and you wrap it up and you put a snowflake on top and now you've got a simple thing. Or a Mongo or Mongo Atlas or whatever. So you've got these layered platforms now which are making it simpler to consume. But now you're kind of, you know, you're all stuck in that ecosystem, you know? So it's like what layer of abstraction do you want to tie yourself to, right? And Databricks coming at it from more of an open source approach, but similar. We're seeing Amazon direct more into vertical markets. They've spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted, custom built for vertical markets. How successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? I think so. There's usually if you look at, you know, the MongoDB or DataStacks or the other sort of, or Elastic, you know, they've got the specific solution with the people that really are developing the core technology. There's the open source equivalent version. The AWS is running. And it's usually maybe they've got a price advantage or it's, you know, there's some better integration in there. Or it's, you know, it's somehow easier to integrate, but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got, you know, basically Elastic, Mongo and Cassandra, you know, the DataStacks is being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to couch base? And, you know, a few of the other ones, you know, they don't really fit like, how are you going to bait? You know, if you were, you're now becoming an also ran because you didn't get flown by the cloud vendor. So you, so the customers are going, is that a safe place to be? Right? Don't they want to encourage those partners though in the name of building the marketplace ecosystem? I mean, there's huge, 35,000 vendors. Yeah, the platform encourages people to do more, but, and there's always room around the edge, but the mainstream customers, like they're really like spending the good money are looking for something that's got a long-term life to it, right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting, and particularly AWS is adopting some of these technologies means that is a very long-term commitment. You can base, you can bet your future architecture on that for a decade, probably. So they have to pick winners. Yeah, so it's sort of picking winners and then if you're the cloud, if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, the top-level sponsors of re-invent and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win in both sides. So ever since we've been in the business, you hear the narrative of hardware is going to die, it's just, you know, it's commodity and there's some truth to that, but hardware is actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much because Intel sucked all the margin out of it, but let's face it, AWS makes most of its money, we know, on compute. It's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long-term to the infrastructure layer? Discussion, okay, commodity cloud. You know, we talk about super cloud. Do you think that AWS, that and the other cloud vendors that infrastructure IS gets commoditized and they have to go up market or do you see that continuing? I mean, history would say that still good margins in hardware. What are your thoughts on that? It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now and this is something, this almost goes back to, I mean, I was with some micro systems 20, 30 years ago and we developed our own chips and HP developed their own chips and SGI MIPS, right? We were like the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now, if you make a chip and it doesn't work immediately, you screwed up somewhere, right? It's become that the technology of building these immensely complicated, powerful chips has become, that has become commoditized. So the cost of building a custom chip is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips, your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip is becoming something that everybody's leveraging and the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think and this is Intel and AMD are, you know they've got the compatibility legacy but the most powerful, most interesting new things I think are going to be custom and we're seeing that with Graviton 3, particularly in the 3E that was announced last night with like 30, 30, 40%, whatever it was more performance for HBC workloads and that's, you know, the HBC market is going to have to deal with cloud. I mean, they are starting to and I was at supercomputing a few weeks ago and they are tiptoeing around the edge of cloud but those supercomputers are water cooled. They are monsters. I mean, you go around supercomputing there are plumbing vendors on the booth. Of course, yeah. Right and they are highly concentrated systems and that's really the only difference. It's like, is it water cooled or air cooled? The rest of the technology stack is pretty much off the shelf stuff with a few tweaks for the software. You point about, you know, the chips and what AWS is doing, the Annapurna acquisition they're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise really comes down to volume. The ARM wafer volumes are 10x those of x86. Volume always wins in the economics of semis. That kind of got us there but now there's also a risk five coming along in terms of licensing is becoming one of the bottlenecks like if the cost of building a chip is really low then it comes down to licensing costs and do you want to pay the ARM license and the risk five is an open source chipset which some people are starting to use for things. So your disk controller may have a risk five in it for example nowadays. Those kinds of things. So I think that that's kind of the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL computer express link which is going to be really interesting. I think that's probably two years out before we start seeing it for real but it lets you put glue together an entire rack in a very flexible way. So it's just, and that's the entire industry coming together around a single standard. In fact the whole industry except for Amazon in fact just about. Well maybe, I think eventually they'll get there don't you? System on a chip, CXL. I have no idea whether I have no knowledge about whether Amazon is going to do anything with the XL. I'm presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard? It's going to be lowest cost. Yeah. So that was one of the things out of supercomputing. The other thing is the low latency networking with the elastic fabric adapter, EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, it's a bit technical, but this scable datagram protocol that they've got, which basically says if I want to send a packet from one machine to another machine, instead of sending it over one wire, I can send it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order. The packets come in in order, this poster. But this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you're trying to move a large piece of data between two machines and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A 5X speedup with a protocol tweak that's run by the nitro. This is super interesting. You probably want to get all that AIML stuff is leveraging it underneath. But this is for everybody. Like you're just copying data around, right? And you're limited. Hey, this is going to get there five times faster if you're pushing a big enough chunk of data around. So this is turning on gradually as the nitro 5 comes out and you have to enable it at the instance level. But it's a super interesting announcement from last night. So the bottom line bumper sticker on commoditization is what? I don't think so. What's the APIs, your ARM compatible, your Intel X86 compatible, or your maybe RISC-5 one-day compatible in the cloud. Those are the APIs, right? That's the commodity level. The software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to ARM. It's really not an issue. The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the cloud providers as they all try and develop faster chips for doing more specific things. We've got Tranium for training. That instance has, they announced it last year with 800 gigabits going out of a single instance. 800 gigabits or never, and this year they doubled it. So 1.6 terabits out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These enormous clusters that they're being formed for doing these massive problems. And there is a market now for these incredibly large supercomputer clusters built for doing AI that's all bandwidth limited. And you think about the timeframe from design to tape out, is just getting compressed relative to it. It is, and the tooling. Next 86 is going the other way. The tooling's all there. Fantastic, Adrian, always a pleasure to have you on. Thanks so much. I really appreciate it. Thank you, Paul. All right, keep it right there, everybody. Don't forget, go to thecube.net. You'll see all these videos. Go to siliconangle.com. We've got features with Adam Salipski. We've got my breaking analysis. We have another feature with MongoDB's Dave Ithacharya. Ali Goatsy as well. Frank Slutman tomorrow, so check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech. Right back.