 From around the globe, it's theCUBE with digital coverage of AWS re-invent 2020. Sponsored by Intel and AWS. Welcome to theCUBE's virtual coverage of AWS re-invent 2020, I'm John Furrier, host. We are theCUBE virtual, not there in person, but we are doing remote as is AWS. Although they're on stage live and we're here with Dave Brown, vice president of EC2 compute. Great to see you again. Great keynote last night, kicking off everything for the opening night. Great stuff. Yeah, well, John, it's always good to be on theCUBE and thanks for having me back. You know, you're in the hot seat these days in the sense of there's so much going on. I mean, Andy could do a three week announcement keynote. It was like even three hours of nonstop. You take a break to go to the bathroom, you missed two announcements, right? So much going on. You opened up re-invent 2020 with your announcement EC2 of Mac instances. And then there was a ton of compute and the theme was really, you know, reinventing and re-imagining compute both. So I want to get into that, but let's start with the hard news. Tell me about the Mac instances. You had a great use case there that kind of illustrated in your talk, but where's this coming from? It's obviously Mac developers are big, but is this market something that you guys saw from customers or was a necessity? Take us through the thinking around the Mac instance, EC2 for Mac instances and what is it for? Absolutely, absolutely. So I mean, me personally, I'm Mac user, long-time Mac user we've often thought about, could we ever bring Mac OS to AWS, right? This is the thing we've spoken about on and off for many, many years. And, you know, it was about the year and a half, about two years ago, you know, we always hearing new use cases from customers. And that's kind of what we're doing. So we're seeing what are customers trying to do that we don't support today and how would we support them in that? And we started a year from customers that they had been able to successfully migrate all of the AWS workloads, you know, to AWS. So most of their server workloads to AWS. And they've got this Mac build workload that they just weren't able to bring to us. We just didn't support Macs. Into it was a great example who I had on stage with me last night where, you know, they over the last couple of years have been moving a lot of their workloads to AWS. And then they had these Mac mini sitting around that they had to manage themselves. And so we said, could we actually do this? And so that was the one thing the customer asked. And the other thing that we realized was with the Nitro system and the work that we've been doing there over the last, you know, six years, seven years since 2012, really. And just where we are from a Nitro system point of view we were able to wrap a Mac mini without making any changes to it with Nitro cards plug in a firewire to the Thunderbolt port and actually control that device. And so it means that you get the best of Apple hardware which is what Apple's all about is the hardware that they make and the way that their software works with it together with the Nitro system and the cards around that integrating with the rest of AWS. So we've given you high speed, secure networking. We've given you great access to elastic block store which just integrates natively into the Mac mini as well. And so we realized that the technology was there the customer ask was there and then obviously went to Apple and worked with them very closely to make it happen. And so that's kind of how it all came together. And I was incredibly excited to announce it last night and the feedback today has just been amazing. A lot of excitement. Yeah, take me to the use case because obviously there's two trends going on. There's custom chips and serverless kind of thing happening where you guys, I mean, really doing a good job of the I as layer innovating there and then platform as a service, all that software on top. I totally get that. You can see that happening. Chips, custom chips to Intel AMD and others. Now you got Mac hardware. Where's the innovation use case? Because one would say, hey, why don't we care about whether it's Mac hardware or not because I'm serverless. I should be programming the infrastructure. I should be getting compute generically. Where does the Mac tie in come in? Cause that's the first question I was thinking of was, I'm a Mac user, I love Mac, but I'm also got some Windows action going on now. And ultimately, do I really care if it's compute? What's your reaction to that? Yeah, well, absolutely. I mean, so if you look at Apple's ecosystem today, right? They have millions of applications in the app store. They have 28 million developers worldwide actually building those applications. It's just incredible. And many of those applications while these millions in the app store itself, there's many more applications that are built by enterprises and companies, right? We have an application that we use internally at Amazon that's available on my phone. That's not in the app store. And many companies are doing that. And to build applications for the ecosystem, they have to be built on Mac hardware. And that's just how Apple works, right? So if you want to build for iPad or iPhone or even Apple TV and Apple Watch, you have to build those applications on a Mac. And so what we see companies doing is, you know, the old developer meme of, well, it works on my computer, right? When you build something, you don't want to be building on your local laptop for production. So they typically have a fleet of machines that they either under somebody's desk or in a data center somewhere that they use for building these Mac applications. And so it's not possible to build a Mac application on anything other than a Mac itself. And we, when we looked at it, we really didn't feel that virtualization made sense, right? Apple, I mean, they have some virtualization that they're able to do within Mac OS itself. But if you think about, how do we solve the customer use case? It's really bringing Apple hardware to EC2 to solve the problem and giving customers that exactly same, the exact same experience that they have on-prem. And if you look at Intuit, like that models just worked, right? We gave them beta access. You know, they've been using our beta, which we normally say, hey, don't run production workloads on a beta. But, you know, I found out if I interview with the VP at Intuit critique that they'd actually moved 80% of their production build workloads to EC2 already to run on the Mac instances. And so that, and that's in the space of two months. And so just that seamless ability to move because it's the same hardware is kind of what we were getting after. Great, thanks for sharing that insight. One thing I want to point out is Mac does have their own chips as well. They're going custom chips. Amazon's going custom chips. And I think, I think you nailed what I was trying to understand, which is, this is a developer community for Mac. And there's some things that are purpose built for Mac devices. So, and Mac ecosystem, you have the marketplace as well as, you know, obviously hardware, you know, PCs and devices. And they're only doing more and more. So this brings me to the IoT piece of it because Apple does make devices that people wear. And the eye watches, iPhones, I mean, they're not computers anymore, they're everything. So this kind of brings up the edge conversation. So whether it's an iPhone or a 5G in a Metro or I'm a stadium watching a football game and there's some sensor, camera vision, industrial thing there. This is the new normal. This is where you guys are kind of eating, eating up the software side of that business because there's new capabilities here. Can you explain how compute is specifically EC2 gets to the edges? Because no one wants to move data around. They want to move compute, not data, because data is expensive and it's fat. So we talked about that with people on years ago, but you got to move compute. So how does that work? Take us through your vision. Absolutely. And this is a massively growing area for us. I mean, you mentioned Apple's new M1 silicon, that they just launched as well. And we're super excited about what Apple's been doing there. We've been doing the same thing with our Gravitson 2 processor and really saving customers and incredible amounts on price performance. Customers moving and getting 40% improvement in price performance just by moving to Gravitson 2. It's just incredible. But in terms of the edge, we started this journey quite some time ago in bringing Lambda functions to CloudWatch and things like that. How do we bring compute to the edge? We took a look at 5G, which I think it's going to fuel a lot of this, right? If we look at our cell phones today, I was actually just talking to the Apple team yesterday and the iPhone only came out 13 years ago. It's kind of amazing to think just how much progress we've had and what 4G did for the device that's in our pocket in terms of just how much we rely on that today and what we get. Well, 5G is just a step function in both in terms of latency, but also in terms of throughput. And so one of the projects we announced last year with Verizon, and we know Andy announced this morning, we were also going to be rolling up with KDDI and SKT Telecom and Vodafone next year is a project called WaveLake that brings AWS compute to the edge of the telco network. And so with Verizon, we now have eight locations around the US where we have AWS compute capacity. And what I mean by that is literally C5 instances, G4 GPU instances for customers that want to do inference and graphics processing on the edge. And that's embedded into the 5G network. And so customers, we've got a number of customers that are doing a lot of interesting things with 5G in the sports area where they have 5G cameras that are submitting directly to WaveLength where you no longer need to drive a truck to a stadium to record a game, you just have 5G cameras to automated factories where they're doing robotics in factories and you'd really low latency and they don't want the computer in the factory, they want it in 5G. And so just an exciting area for us that's growing really, really quickly. The other thing we did is obviously with local zones. We launched our first local zones in LAX last year, Los Angeles. And that's been used by the movie industry. So right now, there's a lot of exciting, they're up and running off the COVID and a shutdown for a period of time and filming the next release of all of our favorite episodes and across all of these various streaming platforms. And a lot of that work is actually the post production is being done on AWS, on G4 instances within the Los Angeles region. So very low latency for colorization, animation, special effects, all that sort of things happening there. And what we heard from a lot of customers was they love outposts as well, which is our offering to put a server into a data center. And you heard from Riot Games and Andy's keynote where they actually bought a number of outposts and put them all over the US and also other places of the world to really lower the latency for their latest game. And so what Andy also just announced is the availability of three additional local zones. So Atlanta, Miami and Houston, sorry, Boston, Miami and Houston available today. And then an additional 12 available local zones next year. And what that does is that sort of spreads AWS capacity, compute capacity at the edge in all of our major metropolitan hubs, all of that capacity is on the AWS backbone as well, but brings customers that low latency connectivity that they're looking for gaming developers, where every millisecond counts in terms of gameplay. And so super excited to be going after that use case, which I think it's difficult to tell what the next 10 years are gonna be like, but I think latency is gonna have a big part to play in the types of applications we see on our phones going forward. Great stuff. Final question for you as we wrap up, obviously with virtualization with this, not virtualization, but the COVID as Andy pointed out, people are going to change. There's going to be winners and losers. He kind of clearly pointed out, but the people who do lean into the cloud, who have been on the cloud are taking advantage of the tailwinds of COVID because of the capabilities. Their EC2 bills are higher and you should be happy for that, but they're also going to have more demand for you to say, hey, I need more services. So how do you speak to those people who are leaning in, who are leveraging more compute? What should they be looking at? What kinds of services should they be connecting into compute? How should they be thinking about the future of compute so that they can take advantage of those capabilities to lower cost, higher performance? What things are complementary for these customers as they come in, not toe-dip in the water kind of things, really driving in, what do they need? Yeah, absolutely. And this has been a big focus on us. This has been as I cover in my keynote, which short leadership session that I'm doing tomorrow, Wednesday. A lot of this year has been helping customers through COVID and what COVID has meant for their business, whether that is cost savings for many of them or whether it's just demand that they've never experienced or expected before. I mean, we've been incredibly hard at work in servicing those customers, right? I actually catch up with Scott Sakura in my keynote who leads our capacity team. We talked through what it meant and how we actually provided the capacity that our customers needed during COVID times. But for a customer moving to us, the first thing is obviously we wanna find ways to make them very successful on the cloud, but more importantly, lower price performance for them. So what we wanna do is give them the best possible performance that's available at the lowest possible cost. And if you look at a number of the announcements that Andy made today, whether it's our latest Graviton processor where you can, when you move to ARM, I think customers often overestimate how much work it will be to move to ARM. And when I talk to them after they've moved, they say, hey, it wasn't actually that much work. We actually got it up and running relatively quickly. So that's simpler than people expect, but that's an opportunity to save 40% on price performance. And there's newer workloads like our graphics, we just launched a new G4AD, which is an AMD based GPU solution. The first time we've had an AMD GPU on the EC2. And that's also looking to save upwards of 40% price performance of our other GPU offerings. It's just incredibly exciting for graphics workloads. And then in the machine learning space, like I think if machine learning has just become the new normal, like everybody's doing it. And just three years ago, everybody was thinking about whether they should do it, how they would use it. Now that it's a lot of companies are doing it, it's really how do I use it more? And that comes down to again, saving costs. And so with our inferential chip and then the new Hibana chip, we just announced it with the work with Intel that we're doing. And then our new training chip for training, we're really working to lower the cost of machine learning. And so like we've seen many customers like Alexa was a great case the other day, being able to lower the cost of inference for Alexa by 35%. Again, just helps customers move to the cloud. But I mean, just generally, we're trying to support customers everywhere. Whether, you know, if there are many customers are in their own data centers looking to move to AWS, we have great models that can support them with our existing compute. Our new savings plan offering we announced last year, just great for saving costs and getting the price down. So a lot you can look at and see, I can go on forever already. It certainly is more, we'll do a deeper dive, follow up after reinvent, but it is a wake up call as I wrote in my post for a cloud. And finally, I've been saying this for years, horizontal scalability is a disruption on the infrastructure side, but you've got vertical specialization with data to create great modern apps with machine learning and AI actually playing out in full display here, as Andy said, right now. So all those benefits and all these opportunities to disrupt horizontally and then leverage the data all tied together, all coming together. You're leading the team. Dave Brown, vice president of EC2, in charge of the team that's driving the future of compute, thanks for coming on theCUBE for CUBE live coverage. Thanks. Thanks for having me. Okay, I'm John Furrier with theCUBE, back for more live coverage after this short break.