 From around the globe, it's theCUBE with digital coverage of AWS re-invent 2020 sponsored by Intel, AWS, and our community partners. Hello everybody, this is Dave Vellante. Welcome back to theCUBE's continuous coverage of AWS re-invent 2020, the virtual version of theCUBE and re-invent. I'm here with David Floyer, who's the CTO of Wikibon and we're going to break down today's infrastructure keynote which was headlined by Peter DeSantis. David, good to see you. It's good to see you. So David, we have a very tight timeframe and I just want to cover a couple of things. Something that I've learned for many, many years working with you is the statement, it's all about recovery. And that really was the first part of Peter's discussion today. It was he laid out the operational practices of AWS and he talked a lot about, he actually had some really interesting things up there. There's no compression algorithm for experience but he talked a lot about availability and he compared AWS's availability philosophy with some of its competitors. And he talked about generators being concurrent and maintainable, he took it down to the batteries and the UPS. And the thing that impressed me most, the other thing that you've taught me over the years is system thinking. You got to look at the entire system that one little component could have, this is Peter DeSantis' words, a huge blast radius. So what AWS tries to do is constrict that blast radius so he can sleep at night. So non-disrupt replacements of things like batteries. He talked a lot about synchronous versus asynchronous trade-offs and it was like kind of async versus sync one-on-one, synchronous, you got latency, asynchronous, you got data loss to exposure. So a lot of discussions around that but what was most interesting is he compared and contrasted AWS's philosophy on availability zones with the competition. And he didn't specifically call out Microsoft and Google but he showed some screenshots of their websites. And the competition uses terms like usually available and generally available. This meaning that certain regions and availability zone may not be available. That's not the case with AWS. Your thoughts on that. They have a very impressive track record despite the failure the other day but they've got a very impressive track record. I think there is a big difference however between general-purpose computing and mission-critical computing. And when you've got to bring up databases and everything else like that, then I think there are other platforms which in the long-term, AWS in my view should be embracing that do a better job in mission-critical areas in terms of bringing things up and not losing data and recovery. So that's an area which I think AWS will need to partner with in the future. Yeah, so the other area of the keynote that was critical was you spent a lot of time on custom silicon. And you and I have talked about this a lot. Of course, AWS and Intel are huge partners but we know that Intel owns its own fabs. Its competitors will outsource to the other manufacturers. So Intel is motivated to put as much function on the real estate as possible to create general-purpose processors and get as much out of that real estate as they possibly can. So what AWS has been doing and they certainly didn't throw Intel under the bus. They were very complimentary and friendly but they also laid out that they're developing a number of components that are custom silicon. They talked about the nitro controllers, inferential which is specialized chips around inference to do things like PyTorch and TensorFlow. They talked about training them, the new training chip for training AI models or ML models. They spent a lot of time on Graviton which is a 64 bit like you say everything 64 bit these days but it's the ARM processor. And so, they didn't specifically mention Moore's law but they certainly talk, they gave a microprocessor 101 overview which I really enjoyed. They talked about, they didn't specifically talk about Moore's law but they talked about the need to put in more cores and then running multi-threaded apps and the whole new programming models that that brings out. And basically laid out the case that these specialized processors that they're developing are more efficient. They talked about all these cores and the overhead that those cores bring and the difficulty of keeping those processors, those cores busy. And so, they talked about symmetric or simultaneous multi-threading and sharing cores which it was like going back to the old days of microprocessor development. But the point being that as you add more cores and you have that overhead you get non-linear performance improvements. And so, it defeats the notion of scale out, right? And so, what I want to get to is get your take on this is you've been talking for a long, long time about ARM in the data center. And it reminded me just like object storage we talked for years about object storage it never went anywhere until Amazon brought forth simple storage service and then object storage obviously is a mainstream storage now. Is he the same thing happening with ARM in the data center specifically? Of course, alternative processors are taking off but what's your take on all this? You listen to the keynote, give us your takeaways. Well, let's go back to first principles for a second. Why is this happening? It's happening because of volume, volume, volume, volume. Volume is incredibly important obviously in terms of cost. And if you look at a volume ARM was based on the volumes that came from the handhelds and all of the mobile stuff that's been generating. So there's billions of chips being made on that. So let me interrupt you for a second, David. So we're showing a slide here and it relates to volume in somewhat. I mean, we talk a lot about the volume that Flash for instance gained from the consumer. And now we're talking about these emerging workloads. You call them matrix workloads. These are things like AI inferencing, Edge work and this gray area shows these alternative workloads. And that's really what Amazon's going after. So you show in this chart, basically very small today, 2020 but you show a very large and growing position by the end of this decade really eating into the traditional space. That's absolutely correct. And that's being led by what's happening in the mobile market. If you look at all of the work that's going on on your Apple iPhone, the huge amount of modern matrix workloads that are going there to help you with your photography and everything like that. And that's going to come into the data center within two years. And that's what AWS is focusing on is capabilities of doing this type of new workload in real time and it's hundreds of times more processing to do these workloads and it's got to be done in real time. Yeah, so we have a chart on that, this bar chart that you've produced. I don't know if you can see the bars here. I can't see them, but maybe we can editorialize. So on the left hand side, you basically have traditional workloads in blue and you have matrix workloads, what you call these emerging workloads in red. You show performance 0.95 versus 50 then price performance for traditional 3.6 and it's more than 150 times greater for ARM-based workloads. And that's an analysis of the previous generation of ARM. And if you take the new ones, the M1 for example, which has come into the PC area, that's going to be even higher. So the ARM is producing hybrid computers, heterogeneous computers with multiple different things inside the computer. And that is making life a lot more efficient. And especially in the inference world, they're using NPUs instead of GPUs. They can fit about four times more NPUs that you can GPUs. And it's just a different world and ARM is ahead because it's done all the work in the volume area. And that's now going to go into PCs and it's going to go into the data center. Okay, great. Now, yeah, if we could guys bring up the other chart that's titled workloads moving to ARM-based servers. This one is just amazing to me, David. You'll see that for some reason, the slides aren't translating. So forget the slides. So, but basically you have the revenue coming from ARM as to be substantially higher in the out years or certainly substantially growing more than the traditional workload revenue. Now that's going to take a decade, but maybe you could explain why you see that. Yeah, the reason is that these matrix workloads and also the offload of like Nitro is doing is the offload of the storage and the networking from the main CPUs, the disaggregation of computing plus the traditional workloads which can move over, are moving over. And where AWS and Microsoft in the PC and Apple in the PC, where those leaders are leading us is that they are doing the hard work of making sure that their software and their APIs can utilize the capabilities of ARM. So it's, and the advantage that AWS has of course is that it enormous economies of scale across many, many users. That's going to take longer to go into the enterprise data center, much longer, but the Microsoft, Google and AWS are going to be leading the charge of this movement of ARM into the data center. It was amazing what some of the ARM customers, the AWS customers were saying today with much faster performance and much lower price. It was, they were affirming. And the fundamental reason is that ARM are two generations of production. They are at the moment at five nanometers, whereas Intel is still at 10. So that's a big, big issue that Intel have to address. Yeah, and so you've been getting this core creep, I'll call it, which brings a lot of overhead. And now you're seeing these very efficient specialized processors and your premises. We're going to see these explode for these new workloads. And in particular, the edge is such an enormous opportunity. I think you pointed out that you see a big market for edge, these edge emergent edge workloads, going to start in the data center and then push out to the edge. Andy Jassy says that the edge, or we're going to bring AWS to the edge, the data center is just another edge node. I like that vision, your thoughts. I think that is a compelling vision. I think things at the edge have many different form factors. So you will need an edge in a car, for example, which is cheap enough to fit into a car. But it's got to be a hundred times more processing than is in the computers in the car at the moment. That's a big leap to get to automated driving. But that's going to happen. And it's going to happen on ARM based systems and the amount of work that's going to go out to the edge is enormous. And the amount of data that's generated at the edge is enormous. That's not going to come back to the center. That's going to be processed at the edge. And the edge is going to be the center, if you like, of where computing is done. It doesn't mean to say that you're not going to have a lot of inference work inside the data center, but a lot of work in terms of data and processing is going to move into the edge over the next decade. Well, many of AWS's edge offerings today, assume data is going to be sent back, although of course you see outpost and then smaller versions of outposts. That's a, to me, that's a clue of what's coming. Basically again, bringing AWS to the edge. I want to also touch on Amazon's comments on renewable. Peter DeSantis talked a lot about what they're doing to reduce carbon. One of the interesting things was they're actually reusing their cooling water. They clean and reuse. I think he said three or multiple times and then they put it back out and they're able to purify it and reuse it. So that's a really great sustainable story. There was much more to it, but I think companies like Amazon, especially large companies really have a responsibility. So it's great to see Amazon stepping up. Anyway, we're out of time, David. Thanks so much for coming on and sharing your insights. I really appreciate it. By the way, those slides at wikibon.com has a lot of David's work on there. Apologize for some of the data not showing through, but working in real time here. This is Dave Vellante for David Floyer. You're watching theCUBE's continuous coverage of AWS re-invent 2020. We'll be right back.