>>The cube presents, Dell technologies world brought to you by Dell. >>Welcome back to Las Vegas. We're here in the Venetian convention center. My name is Dave Alan. I'm here with my co-host John fur. You're watching the Cube's live coverage of Dell tech world 2022. Great crowd. I would say 7,000, maybe even 8,000 people. When you add in all the peripheral attendees, Jeff Clark is here. He's the vice chairman and co-chief operating officer of Dell technologies. Great to see you face to face, man. >>Hey guys. Good to see you again. Awesome. >>So really enjoyed your keynote this morning. You were pumped up, uh, I thought the, the presentations and the demos were crisp. So congratulations. Thank you. How you feeling? >>Doing a great job? How am I feeling? Uh, well, one relieved. If you know me well enough, I'm an engineer by heart. So trade the anxiety to do that is, uh, and build up is quite draining, but having it done, I feel pretty good now, but I feel good about what we discussed. Uh, it was a fun day to be able to talk to real customers and partners face to face like we're doing here and showcasing what we've been doing. I must admit that was a little bit of fun. Yeah. >>Well, we're chilling on the cube. Uh, we're laid back as you know. Um, what was your favorite moment? Cause you got a lot of highlights. The snowflake deal. We love been talking about it all, all show. Um, the, the, I IP of Dell with software define was pretty cool. Lot of great stuff. What's what >>Some cool laptop stuff too. That was interesting. You know, I don't have to. Where's the, where's the share button. >>We have a discord server now and all 18,000 people want to know. >>You're asking me to pick a monks, my should, which I like the most. >>How big is your monitor on your desk? >>Uh, I have a 49 on one side and a 42 on the other side. That's what both you guys need >><laugh> productivity, da >><laugh> well, in the world of zoom, it was incre incredibly productive to have that surface area in front of you. So, which of my announcements was my favorite, I think from a raw technology point of view, showcasing Dell, thinking about what we've done in a very differentiated way. It's hard not to say the power flex >>Engagement. Oh, look at that. Look, I wrote just, just wrote down power flex. Yep. Right. >><laugh> okay. Think about it. Softer defined. We, the leader and softer defined, uh, infrastructure that can be, think of it as independently, independent ability to scale compute from storage so we can linear scale and those no bounds, unlimited IO performance. The ability to put file block support, hyper hypervisors and bare metal all on a single platform. And then we made a, a bunch of other improvements around it. It's truly an area where we a leader we're differentiated in our core IP matters >>And that's Dell IP, Dell technology top >>The bottom. >>Okay, cool. >>So from a pure technical point of view, it's probably my favorite. What's not liked about PowerMax, the most mission critical, the most secure high end storage system in the world. And we made it better. We made it more secure. We put an isolated vault in it. We added some, uh, multifactor authentication. We improved the architecture for twice the performance, 50% better response time, blah, blah, blah, blah, blah. Yes, pretty cool. <laugh> and then you gotta put a notebook in front of everybody where you think about in this modern workplace. And what we've learned is hybrid users. What software that we've embedded into that latitude 93 30 was pretty interesting. I thought. And then if I pull day one into the conversation, sort of the direction of where we're going of, multi-cloud the role of multi-cloud and our ability to be sort at the center of our customers multi-cloud world. I loved how Chuck described moving from multi-cloud by default to multi cloud, by design, and then the subsequent architecture that we put behind it. And then probably cherry on the old cake was the snowflake announcement that got a lot of people excited about bringing a really differentiated view of cloud based analytics down on our object storage. I know that was more than one, but I can't help. >>I like the cherry on top >>You've um, said a number of times, I think the 85% of your engineers are software engineers. You talked about, is that the right number, roughly? Yes, sir. And, and so, uh, you talked also about 500 new features today and, and every time you're talking about those features, I inferred anyway, it was part of the OS. A lot of it anyway, a lot of software does hardware still matter? And if so, why? >>Of course hardware still >>Matter. Explain why. >>Well, last time I checked doesn't the software stuff work on the hardware. Exactly. Doesn't the software things make hardware calls to exploit the capability we built into the software. Of course it does says it absolutely does matter, but I think what we're trying to describe or to get across today is we're moving up the stack, we're adding more value. Basically our customers are dragging us into a broader set of problems and software is increasingly the answer to that running on the best hardware, the best infrastructure, being able to build the right software abstraction to hook into either data frameworks, like a snowflake, being able to present our storage assets of software in the pub book cloud, ultimately the ability to pull them and think of it as a pool of storage for developers to make developers lives easier. Yeah. That's where we're going >>And, and is accurate in your view, you're going up to stack more software content and there's value. That's also flowing into Silicon, whether it's accelerators or Nicks and things like that, is that a right way to think about what's happening in hardware and software. We, >>You and I have had a number of conversations, David, the evolution of the architecture, where we're going from a general purpose CPU based thing to now specialty processors, whether that be a smart Nick purpose, built accelerators. If we leaped all the way out to quantum, really purpose built accelerators for a specific algorithm, there's certainly specialization going on. And as that happens, more software and software defined is necessary to knit together. And we have to be the person that does that. Mm-hmm <affirmative> yeah. >>Talk about how the software defined piece makes the innovation happen on the hardware. Is it, is it the relationship that it's decoupled or you guys are just building design Silicon to make the software better? Cuz that interplay is a design, uh, is designed in, right? >>Uh, I, I think it's a little bit of both clearly being able to exploit the underlying hardware features and capabilities in your software in a differentiated way is important. Something we've excelled at for many, many years, but then the ability to abstract. If you think about some of the things that we talk about as a data fabric or a data plane and a data plane working across different architectures, that's an abstracted piece of software that ultimately leads to a very different and that's where we're driving towards >>What's different now. And what's similar now from the past, I was just on a, a panel. I talking about space, Cal poly and California space symposium and this hardware and space and it's, software's driving everything you can't do break, fix and space. It's talk about the edge. You can't talk about. You can't do break hard to do break, fix and space. So you gotta rely on software in the supply chain. Big part of the design as software becomes more prevalent with open source and et cetera, that innovation equation is designed in. What's your, what's your thoughts on that? >>Help me understand John, what more of this specific of what you're looking for, where do you want to dive into >>The, as Silicon becomes more of a more efficient, what does that do for the software in things like edge, for instance, as the boxes move out and the, the devices move to the home, they gotta be faster, more intelligent, more secure. Uh, Michael says it's a, it's a compute tower now 5g for instance. >>Yeah. Uh, maybe another way to look at it. We've been in the industry a little while for the longest time hardware capabilities were always ahead of software. We built great hardware. We let software catch up. What's changed certainly in this time. And as we look going forward is the software capabilities are now ahead of those very hardware capabilities in bringing it. And to me, that's a, it's a very fundamental change. Certainly in my 35 years of doing this, that's very different. And if you believe that continues, which I do, particularly as we face increasingly more difficult challenges to continue with Moore's law, how do we continue to build out the transistor density? We've all benefited from for four, five decades now, softer innovation is going to lead, which is what we tried to hint at today. And I think that's the future. That's where you're gonna see us continue to drive and think about how we talk about, uh, technology today. I know Dave and I had this conversation not too long ago, whether it's infrastructure is code, who would've thought of that idea a decade ago. <laugh> uh, if we think about, uh, data as code we were talking about before we got on air, what data on code data's little bits, one's in zero stored in Silicon, you store >>It, <laugh> you move it >>Around now. So it, it opens the door or the door to, I think innovation done differently and perhaps even done it more scale as if we abstract it correctly. >>Yeah. And might led a good point on when he was on about all the good benefits that come from that in the customer and in society. And I guess the next question with the customer side, it take your, if the, if the flip, if the script is flipping, which I believe that it is, I agree with you. How does the customers deal with the innovation strategy? Because now they wanna take advantage of the new innovation, but what problems and opportunities are they facing? That's different now than say a decade ago, if you're in it or you're trying to create a great group within your CISO organization. I mean, there are problems now that we didn't see before. What do you, how do you see that? >>Well, I, I, I think the, the biggest change would be again, if you look and reflect on our careers, it was sort of in the business, it played a role. It was often put off to the corner, just make the place sort of work. And today, and I think the pandemic has the pandemic and global health crisis accelerated this technology is now part of people's business and you can't compete without technology. And in fact, we saw it during the early days of the pandemic, those CU customers that were further along on their digital transformation, generally weathered the storm in their sector better than those who were behind. >>Yeah, >>Absolutely. What does that tell us technology was an enabler. Technology helped them, whether the storm prepared them, made them more competitive. So now I think I don't meet many CIO and CEOs who don't have the conversation about their business model and technology being symbiotic, that they're integrated, that they can't do one without the other. That's a very different mindset than when we grew up in this industry where this stuff was. So now you take that as a basis. We got data everywhere. Most of the data's gonna come out of the data, not in the data center's gonna be created outside of the data center. The attack surface has grown disproportionately >>People, people sharing data, too, their data with other data, very much so generating >>Data in places. Sometimes they don't know where it is and hope to get it back. So the role to be able to protect that estate, if you will, to be able to protect the information, which increasingly data is companies fuel, but makes 'em go, how do you protect it? How do you ultimately analyze it? How do you provide them the insights to ultimately run and drive their business? That's the opportunity. >>So we are in the same wavelength with Powerflex and, and I'm a little concerned about confirmation bias, but, but I, I wanna say this, I really like the way your Dell's language and yours specifically has evolved. You talk about abstraction layers, hiding that underlying complexity, building value on top of the hyperscalers on prem connecting sore, we call it super cloud. You guys call it multi-cloud. We saw two examples of that today, project Alpine and the snowflake is early examples. Uh, I'm trying to gauge how real this is. We think it's real. Uh, we talked to customers who clearly say, this is what they want. Um, I wonder if you could add a little detail to that, some color on your thoughts on, on how real this is, how it will evolve over time. >>Well, from our, from our seat and the way that I, that, that I see it in driving our underlying product development, roadmaps, people want to drag into conversation about public and private and this, and what have you. And, and that's not how customers work today. Uh, customers really have got to this point where they want to use the best capabilities regardless of where they lie. And if that's keeping mission critical data on premise taking advantage of analytic tools in the cloud, doing some test dev in the public cloud, moving out to edge, they want to be able to do that reasonably quickly and not. We were talking about this before we got on the air in an easy fashion. It can't be complex. Yeah. So how do you actually knit this together in a way that is not complex and enables customers? That's what I think customers want. So you think about our multi-cloud vision. It's about building an ecosystem across all of the public clouds, which we've made announcement and announcement to do that. Well, >>You said earlier default versus by design, which referencing to the multi-cloud. But I think the design is the key word here. The design is a system architecture you're talking about. You said also technology and business models are tied together and enable or that's. If you believe that, then you have to believe that it's a business operating system that they want, they wanna leverage whatever they can. And at the end of the day, they have to differentiate what they do >>Well, that that's exactly right. If I take that in what, what Dave was saying. And, and, and I summarize it the following way. If we can take these cloud assets in Cape capabilities, combine them in an orchestrated way to delivery, distributed platform, game over, >>Tell us we gotta wrap, which bummed me out because I, we had so much, we haven't covered. We haven't talked about 5g. We really haven't hit on apex. Uh, what else is exciting? You something, you know, let's let's in the last minute or so, let's do a wrap. >>We just, >>I know we just got started. We had >>A schedule, >>Two guys, the boss, this >>Is great. We wanna go the next, >>Not when it comes to the schedule, just laid >>Out the, just laid out the checkmate move right there. You know, um, >>Look, what I get excited about, uh, >>Edge to me is a domain that we're gonna see in this part of our careers have the same level of innovation and discovery that we just saw in the early part of our careers and probably times 10 or times a hundred. And I, and I think about the world we live in and matching up what's happening in this digitization of our world and everything, having a sensor in it, collecting data everywhere on everything, and then being able to synthesize it in a way that we can derive reasonable insight from to be able to make real time decisions from whether that be in healthcare, a smart city, a factory of the transportation area, our own website of how the traffic comes in and how we present our offers more effectively to what you want, which are different than what Dave wants. The possibilities are unlimited and, or on the half of the first ending, if you like baseball, analogies, absolutely. And a long way to go and a tremendous amount of innovation that'll happen here. I get excited about that place. Now. It's not gonna happen overnight every once say, oh, we're smoking edge. Wasn't at IOT, stop putting a timeframe on it. Yeah. Know, the foundation is built to be able to develop, evolve and innovate from here. Like I've never seen. >>And the playbook to get back to your game overcome is whoever can simplify the comp and reduce the complexity and make things simpler and easier. That's, I mean, that's kind of the formula for success basically. I mean, it sounds kind of easy, right? Like >>Spot on, >>Just do it, but what, but that's hard. >>Remember it's hard and being able to build data centers and, and millions of places. So for example, what we'll leave in a little 5g, you think about all of the public cloud data centers today. I think there's roughly 600 locations. You've got 7 million cell towers. Yeah. 7 million cell towers gonna >>Be like how reach right there. >>Data center at the edge of the network. Yeah. As we just aggregate the telecom infrastructure. Sure. From a monolithic big black box into a disaggregated standards based architecture with virtualization and containerization in it. >>I mean, outta compute, I love the whole Metro operating model there, like having that data center at that edge, all that wire wireless coming in. >>I >>Agree. Pretty impressive. Powering the Teslas and all the cars out there sending telematics to, uh, people's phones. And >>Let's wait to next wearables >>Here >>To, I was gonna say next Dell technology world choose to have some fun. <laugh> >>Jeff Clark. Thanks so much for coming to the cube. You're awesome guest and, uh, congratulations on all the success and really appreciate your time. Yeah. Thanks for >>Having me. Thanks for kind words. >>All right. Thank you for watching. This is Dave for John furrier, Dell tech world 2022 live. We'll be right back. You're watching the cube. >>That was great. Mean you great riff.

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020, sponsored by Intel and AWS. >>Welcome back to the cubes coverage of AWS reinvent 2020 I'm Lisa Martin. Joining me next is one of our cube alumni. Breton McMillan is back the director of us, federal for AWS. Right. It's great to see you glad that you're safe and well. >>Great. It's great to be back. Uh, I think last year when we did the cube, we were on the convention floor. It feels very different this year here at reinvent, it's gone virtual and yet it's still true to how reinvent always been. It's a learning conference and we're releasing a lot of new products and services for our customers. >>Yes. A lot of content, as you say, the one thing I think I would say about this reinvent, one of the things that's different, it's so quiet around us. Normally we're talking loudly over tens of thousands of people on the showroom floor, but great. That AWS is still able to connect in such an actually an even bigger way with its customers. So during Theresa Carlson's keynote, want to get your opinion on this or some info. She talked about the AWS open data sponsorship program, and that you guys are going to be hosting the national institutes of health, NIH sequence, read archive data, the biologist, and may former gets really excited about that. Talk to us about that because especially during the global health crisis that we're in, that sounds really promising >>Very much is I am so happy that we're working with NIH on this and multiple other initiatives. So the secret greed archive or SRA, essentially what it is, it's a very large data set of sequenced genomic data. And it's a wide variety of judge you gnomic data, and it's got a knowledge human genetic thing, but all life forms or all branches of life, um, is in a SRA to include viruses. And that's really important here during the pandemic. Um, it's one of the largest and oldest, um, gen sequence genomic data sets are out there and yet it's very modern. It has been designed for next generation sequencing. So it's growing, it's modern and it's well used. It's one of the more important ones that it's out there. One of the reasons this is so important is that we know to find cures for what a human ailments and disease and death, but by studying the gem genomic code, we can come up with the answers of these or the scientists can come up with answer for that. And that's what Amazon is doing is we're putting in the hands of the scientists, the tools so that they can help cure heart disease and diabetes and cancer and, um, depression and yes, even, um, uh, viruses that can cause pandemics. >>So making this data, sorry, I'm just going to making this data available to those scientists. Worldwide is incredibly important. Talk to us about that. >>Yeah, it is. And so, um, within NIH, we're working with, um, the, um, NCBI when you're dealing with NIH, there's a lot of acronyms, uh, and uh, at NIH, it's the national center for, um, file type technology information. And so we're working with them to make this available as an open data set. Why, why this is important is it's all about increasing the speed for scientific discovery. I personally think that in the fullness of time, the scientists will come up with cures for just about all of the human ailments that are out there. And it's our job at AWS to put into the hands of the scientists, the tools they need to make things happen quickly or in our lifetime. And I'm really excited to be working with NIH on that. When we start talking about it, there's multiple things. The scientists needs. One is access to these data sets and SRA. >>It's a very large data set. It's 45 petabytes and it's growing. I personally believe that it's going to double every year, year and a half. So it's a very large data set and it's hard to move that data around. It's so much easier if you just go into the cloud, compute against it and do your research there in the cloud. And so it's super important. 45 petabytes, give you an idea if it were all human data, that's equivalent to have a seven and a half million people or put another way 90% of everybody living in New York city. So that's how big this is. But then also what AWS is doing is we're bringing compute. So in the cloud, you can scale up your compute, scale it down, and then kind of the third they're. The third leg of the tool of the stool is giving the scientists easy access to the specialized tool sets they need. >>And we're doing that in a few different ways. One that the people would design these toolsets design a lot of them on AWS, but then we also make them available through something called AWS marketplace. So they can just go into marketplace, get a catalog, go in there and say, I want to launch this resolve work and launches the infrastructure underneath. And it speeds the ability for those scientists to come up with the cures that they need. So SRA is stored in Amazon S3, which is a very popular object store, not just in the scientific community, but virtually every industry uses S3. And by making this available on these public data sets, we're giving the scientists the ability to speed up their research. >>One of the things that Springs jumps out to me too, is it's in addition to enabling them to speed up research, it's also facilitating collaboration globally because now you've got the cloud to drive all of this, which allows researchers and completely different parts of the world to be working together almost in real time. So I can imagine the incredible power that this is going to, to provide to that community. So I have to ask you though, you talked about this being all life forms, including viruses COVID-19, what are some of the things that you think we can see? I expect this to facilitate. Yeah. >>So earlier in the year we took the, um, uh, genetic code or NIH took the genetic code and they, um, put it in an SRA like format and that's now available on AWS and, and here's, what's great about it is that you can now make it so anybody in the world can go to this open data set and start doing their research. One of our goals here is build back to a democratization of research. So it used to be that, um, get, for example, the very first, um, vaccine that came out was a small part. It's a vaccine that was done by our rural country doctor using essentially test tubes in a microscope. It's gotten hard to do that because data sets are so large, you need so much computer by using the power of the cloud. We've really democratized it and now anybody can do it. So for example, um, with the SRE data set that was done by NIH, um, organizations like the university of British Columbia, their, um, cloud innovation center is, um, doing research. And so what they've done is they've scanned, they, um, SRA database think about it. They scanned out 11 million entries for, uh, coronavirus sequencing. And that's really hard to do in a typical on-premise data center. Who's relatively easy to do on AWS. So by making this available, we can have a larger number of scientists working on the problems that we need to have solved. >>Well, and as the, as we all know in the U S operation warp speed, that warp speed alone term really signifies how quickly we all need this to be progressing forward. But this is not the first partnership that AWS has had with the NIH. Talk to me about what you guys, what some of the other things are that you're doing together. >>We've been working with NIH for a very long time. Um, back in 2012, we worked with NIH on, um, which was called the a thousand genome data set. This is another really important, um, data set and it's a large number of, uh, against sequence human genomes. And we moved that into, again, an open dataset on AWS and what's happened in the last eight years is many scientists have been able to compute about on it. And the other, the wonderful power of the cloud is over time. We continue to bring out tools to make it easier for people to work. So what they're not they're computing using our, um, our instance types. We call it elastic cloud computing. whether they're doing that, or they were doing some high performance computing using, um, uh, EMR elastic MapReduce, they can do that. And then we've brought up new things that really take it to the next layer, like level like, uh, Amazon SageMaker. >>And this is a, um, uh, makes it really easy for, um, the scientists to launch machine learning algorithms on AWS. So we've done the thousand genome, uh, dataset. Um, there's a number of other areas within NIH that we've been working on. So for example, um, over at national cancer Institute, we've been providing some expert guidance on best practices to how, how you can architect and work on these COVID related workloads. Um, NIH does things with, um, collaboration with many different universities, um, over 2,500, um, academic institutions. And, um, and they do that through grants. And so we've been working with doc office of director and they run their grant management applications in the RFA on AWS, and that allows it to scale up and to work very efficiently. Um, and then we entered in with, um, uh, NIH into this program called strides strides as a program for knowing NIH, but also all these other institutions that work within NIH to use the power of the cloud use commercial cloud for scientific discovery. And when we started that back in July of 2018, long before COVID happened, it was so great that we had that up and running because now we're able to help them out through the strides program. >>Right. Can you imagine if, uh, let's not even go there? I was going to say, um, but so, okay. So the SRA data is available through the AWS open data sponsorship program. You talked about strides. What are some of the other ways that AWS system? >>Yeah, no. So strides, uh, is, uh, you know, wide ranging through multiple different institutes. So, um, for example, over at, uh, the national heart lung and blood Institute, uh, do di NHL BI. I said, there's a lot of acronyms and I gel BI. Um, they've been working on, um, harmonizing, uh, genomic data. And so working with the university of Michigan, they've been analyzing through a program that they call top of med. Um, we've also been working with a NIH on, um, establishing best practices, making sure everything's secure. So we've been providing, um, AWS professional services that are showing them how to do this. So one portion of strides is getting the right data set and the right compute in the right tools, in the hands of the scientists. The other areas that we've been working on is making sure the scientists know how to use it. And so we've been developing these cloud learning pathways, and we started this quite a while back, and it's been so helpful here during the code. So, um, scientists can now go on and they can do self-paced online courses, which we've been really helping here during the, during the pandemic. And they can learn how to maximize their use of cloud technologies through these pathways that we've developed for them. >>Well, not education is imperative. I mean, there, you think about all of the knowledge that they have with within their scientific discipline and being able to leverage technology in a way that's easy is absolutely imperative to the timing. So, so, um, let's talk about other data sets that are available. So you've got the SRA is available. Uh, what are their data sets are available through this program? >>What about along a wide range of data sets that we're, um, uh, doing open data sets and in general, um, these data sets are, um, improving the human condition or improving the, um, the world in which we live in. And so, um, I've talked about a few things. There's a few more, uh, things. So for example, um, there's the cancer genomic Atlas that we've been working with, um, national cancer Institute, as well as the national human genomic research Institute. And, um, that's a very important data set that being computed against, um, uh, throughout the world, uh, commonly within the scientific community, that data set is called TCGA. Um, then we also have some, uh, uh, datasets are focused on certain groups. So for example, kids first is a data set. That's looking at a lot of the, um, challenges, uh, in diseases that kids get every kind of thing from very rare pediatric cancer as to heart defects, et cetera. >>And so we're working with them, but it's not just in the, um, uh, medical side. We have open data sets, um, with, uh, for example, uh, NOAA national ocean open national oceanic and atmospheric administration, um, to understand what's happening better with climate change and to slow the rate of climate change within the department of interior, they have a Landsat database that is looking at pictures of their birth cell, like pictures of the earth, so we can better understand the MCO world we live in. Uh, similarly, uh, NASA has, um, a lot of data that we put out there and, um, over in the department of energy, uh, there's data sets there, um, that we're researching against, or that the scientists are researching against to make sure that we have better clean, renewable energy sources, but it's not just government agencies that we work with when we find a dataset that's important. >>We also work with, um, nonprofit organizations, nonprofit organizations are also in, they're not flush with cash and they're trying to make every dollar work. And so we've worked with them, um, organizations like the child mind Institute or the Allen Institute for brain science. And these are largely like neuro imaging, um, data. And we made that available, um, via, um, our open data set, um, program. So there's a wide range of things that we're doing. And what's great about it is when we do it, you democratize science and you allowed many, many more science scientists to work on these problems. They're so critical for us. >>The availability is, is incredible, but also the, the breadth and depth of what you just spoke. It's not just government, for example, you've got about 30 seconds left. I'm going to ask you to summarize some of the announcements that you think are really, really critical for federal customers to be paying attention to from reinvent 2020. >>Yeah. So, um, one of the things that these federal government customers have been coming to us on is they've had to have new ways to communicate with their customer, with the public. And so we have a product that we've had for a while called on AWS connect, and it's been used very extensively throughout government customers. And it's used in industry too. We've had a number of, um, of announcements this weekend. Jasmine made multiple announcements on enhancement, say AWS connect or additional services, everything from helping to verify that that's the right person from AWS connect ID to making sure that that customer's gets a good customer experience to connect wisdom or making sure that the managers of these call centers can manage the call centers better. And so I'm really excited that we're putting in the hands of both government and industry, a cloud based solution to make their connections to the public better. >>It's all about connections these days, but I wish we had more time, cause I know we can unpack so much more with you, but thank you for joining me on the queue today, sharing some of the insights, some of the impacts and availability that AWS is enabling the scientific and other federal communities. It's incredibly important. And we appreciate your time. Thank you, Lisa, for Brett McMillan. I'm Lisa Martin. You're watching the cubes coverage of AWS reinvent 2020.