>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Cloud computing has been the single most transformative force in IT over the last decade. As we enter the 2020s, we believe that cloud will become the underpinning of a ubiquitous, intelligent and autonomous resource that will disrupt the operational stacks of virtually every company in every industry. Welcome to this week's special edition of Wikibon's CUBE Insights Powered by ETR. In this breaking analysis, and as part of theCUBE365's coverage of AWS re:Invent 2020, we're going to put forth our scenario for the next decade of cloud evolution. We'll also drill into the most recent data on AWS from ETR's October 2020 survey of more than 1,400 CIOs and IT professionals. So let's get right into it and take a look at how we see the cloud of yesterday, today and tomorrow. This graphic shows our view of the critical inflection points that catalyze the cloud adoption. In the middle of the 2000s, the IT industry was recovering from the shock of the dot-com bubble and of course 9/11. CIOs, they were still licking their wounds from the narrative, does IT even matter? AWS launched its Simple Storage Service and later EC2 with a little fanfare in 2006, but developers at startups and small businesses, they noticed that overnight AWS turned the data center into an API. Analysts like myself who saw the writing on the wall and CEO after CEO, they poo-pooed Amazon's entrance into their territory and they promised a cloud strategy that would allow them to easily defend their respective turfs. We'd seen the industry in denial before, and this was no different. The financial crisis was a boon for the cloud. CFOs saw a way to conserve cash, shift CAPEX to OPEX and avoid getting locked in to long-term capital depreciation schedules or constrictive leases. We also saw shadow IT take hold, and then bleed in to the 2010s in a big way. This of course created problems for organizations rightly concerned about security and rogue tech projects. CIOs were asked to come in and clean up the crime scene, and in doing so, realized the inevitable, i.e., that they could transform their IT operational models, shift infrastructure management to more strategic initiatives, and drop money to the bottom lines of their businesses. The 2010s saw an era of rapid innovation and a level of data explosion that we'd not seen before. AWS led the charge with a torrent pace of innovation via frequent rollouts or frequent feature rollouts. Virtually every industry, including the all-important public sector, got into the act. Again, led by AWS with the Seminole, a CIA deal. Google got in the game early, but they never really took the enterprise business seriously until 2015 when it hired Diane Green. But Microsoft saw the opportunity and leaned in heavily and made remarkable strides in the second half of the decade, leveraging its massive software stake. The 2010s also saw the rapid adoption of containers and an exit from the long AI winter, which along with the data explosion, created new workloads that began to go mainstream. Now, during this decade, we saw hybrid investments begin to take shape and show some promise. As the ecosystem realized broadly that it had to play in the AWS sandbox or it would lose customers. And we also saw the emergence of edge and IoT use cases like for example, AWS Ground Station, those emerge. Okay, so that's a quick history of cloud from our vantage point. The question is, what's coming next? What should we expect over the next decade? Whereas the last 10 years was largely about shifting the heavy burden of IT infrastructure management to the cloud, in the coming decade, we see the emergence of a true digital revolution. And most people agree that COVID has accelerated this shift by at least two to three years. We see all industries as ripe for disruption as they create a 360 degree view across their operational stacks. Meaning, for example, sales, marketing, customer service, logistics, etc., they're unified such that the customer experience is also unified. We see data flows coming together as well, where domain-specific knowledge workers are first party citizens in the data pipeline, i.e. not subservient to hyper-specialized technology experts. No industry is safe from this disruption. And the pandemic has given us a glimpse of what this is going to look like. Healthcare is going increasingly remote and becoming personalized. Machines are making more accurate diagnoses than humans, in some cases. Manufacturing, we'll see new levels of automation. Digital cash, blockchain and new payment systems will challenge traditional banking norms. Retail has been completely disrupted in the last nine months, as has education. And we're seeing the rise of Tesla as a possible harbinger to a day where owning and driving your own vehicle could become the exception rather than the norm. Farming, insurance, on and on and on. Virtually every industry will be transformed as this intelligent, responsive, autonomous, hyper-distributed system provides services that are ubiquitous and largely invisible. How's that for some buzzwords? But I'm here to tell you, it's coming. Now, a lot of questions remain. First, you may even ask, is this cloud that you're talking about? And I can understand why some people would ask that question. And I would say this, the definition of cloud is expanding. Cloud has defined the consumption model for technology. You're seeing cloud-like pricing models moving on-prem with initiatives like HPE's GreenLake and now Dell's APEX. SaaS pricing is evolving. You're seeing companies like Snowflake and Datadog challenging traditional SaaS models with a true cloud consumption pricing option. Not option, that's the way they price. And this, we think, is going to become the norm. Now, as hybrid cloud emerges and pushes to the edge, the cloud becomes this what we call, again, hyper-distributed system with a deployment and programming model that becomes much more uniform and ubiquitous. So maybe this s-curve that we've drawn here needs an adjacent s-curve with a steeper vertical. This decade, jumping s-curves, if you will, into this new era. And perhaps the nomenclature evolves, but we believe that cloud will still be the underpinning of whatever we call this future platform. We also point out on this chart, that public policy is going to evolve to address the privacy and concentrated industry power concerns that will vary by region and geography. So we don't expect the big tech lash to abate in the coming years. And finally, we definitely see alternative hardware and software models emerging, as witnessed by Nvidia and Arm and DPA's from companies like Fungible, and AWS and others designing their own silicon for specific workloads to control their costs and reduce their reliance on Intel. So the bottom line is that we see programming models evolving from infrastructure as code to programmable digital businesses, where ecosystems power the next wave of data creation, data sharing and innovation. Okay, let's bring it back to the current state and take a look at how we see the market for cloud today. This chart shows a just-released update of our IaaS and PaaS revenue for the big three cloud players, AWS, Azure, and Google. And you can see we've estimated Q4 revenues for each player and the full year, 2020. Now please remember our normal caveats on this data. AWS reports clean numbers, whereas Azure and GCP are estimates based on the little tidbits and breadcrumbs each company tosses our way. And we add in our own surveys and our own information from theCUBE Network. Now the following points are worth noting. First, while AWS's growth is lower than the other two, note what happens with the laws of large numbers? Yes, growth slows down, but the absolute dollars are substantial. Let me give an example. For AWS, Azure and Google, in Q4 2020 versus Q4 '19, we project annual quarter over quarter growth rate of 25% for AWS, 46% for Azure and 58% for Google Cloud Platform. So meaningfully lower growth rates for AWS compared to the other two. Yet AWS's revenue in absolute terms grows sequentially, 11.6 billion versus 12.4 billion. Whereas the others are flat to down sequentially. Azure and GCP, they'll have to come in with substantially higher annual growth to increase revenue from Q3 to Q4, that sequential increase that AWS can achieve with lower growth rates year to year, because it's so large. Now, having said that, on an annual basis, you can see both Azure and GCP are showing impressive growth in both percentage and absolute terms. AWS is going to add more than $10 billion to its revenue this year, with Azure growing nearly 9 billion or adding nearly 9 billion, and GCP adding just over 3 billion. So there's no denying that Azure is making ground as we've been reporting. GCP still has a long way to go. Thirdly, we also want to point out that these three companies alone now account for nearly $80 billion in infrastructure services annually. And the IaaS and PaaS business for these three companies combined is growing at around 40% per year. So much for repatriation. Now, let's take a deeper look at AWS specifically and bring in some of the ETR survey data. This wheel chart that we're showing here really shows you the granularity of how ETR calculates net score or spending momentum. Now each quarter ETR, they go get responses from thousands of CIOs and IT buyers, and they ask them, are you spending more or less than a particular platform or vendor? Net score is derived by taking adoption plus increase and subtracting out decrease plus replacing. So subtracting the reds from the greens. Now remember, AWS is a $45 billion company, and it has a net score of 51%. So despite its exposure to virtually every industry, including hospitality and airlines and other hard hit sectors, far more customers are spending more with AWS than are spending less. Now let's take a look inside of the AWS portfolio and really try to understand where that spending goes. This chart shows the net score across the AWS portfolio for three survey dates going back to last October, that's the gray. The summer is the blue. And October 2020, the most recent survey, is the yellow. Now remember, net score is an indicator of spending velocity and despite the deceleration, as shown in the yellow bars, these are very elevated net scores for AWS. Only Chime video conferencing is showing notable weakness in the AWS data set from the ETR survey, with an anemic 7% net score. But every other sector has elevated spending scores. Let's start with Lambda on the left-hand side. You can see that Lambda has a 65% net score. Now for context, very few companies have net scores that high. Snowflake and Kubernetes spend are two examples with higher net scores. But this is rarefied air for AWS Lambda, i.e. functions. Similarly, you can see AI, containers, cloud, cloud overall and analytics all with over 50% net scores. Now, while database is still elevated with a 46% net score, it has come down from its highs of late. And perhaps that's because AWS has so many options in database and its own portfolio and its ecosystem, and the survey maybe doesn't have enough granularity there, but in this competition, so I don't really know, but that's something that we're watching. But overall, there's a very strong portfolio from a spending momentum standpoint. Now what we want to do, let's flip the view and look at defections off of the AWS platform. Okay, look at this chart. We find this mind-boggling. The chart shows the same portfolio view, but isolates on the bright red portion of that wheel that I showed you earlier, the replacements. And basically you're seeing very few defections show up for AWS in the ETR survey. Again, only Chime is the sore spot. But everywhere else in the portfolio, we're seeing low single digit replacements. That's very, very impressive. Now, one more data chart. And then I want to go to some direct customer feedback, and then we'll wrap. Now we've shown this chart before. It plots net score or spending velocity on the vertical axis and market share, which measures pervasiveness in the dataset on the horizontal axis. And in the table portion in the upper-right corner, you can see the actual numbers that drive the plotting position. And you can see the data confirms what we know. This is a two-horse race right now between AWS and Microsoft. Google, they're kind of hanging out with the on-prem crowd vying for relevance at the data center. We've talked extensively about how we would like to see Google evolve its business and rely less on appropriating our data to serve ads and focus more on cloud. There's so much opportunity there. But nonetheless, you can see the so-called hybrid zone emerging. Hybrid is becoming real. Customers want hybrid and AWS is going to have to learn how to support hybrid deployments with offerings like outposts and others. But the data doesn't lie. The foundation has been set for the 2020s and AWS is extremely well-positioned to maintain its leadership, in our view. Now, the last chart we'll show takes some verbatim comments from customers that sum up the situation. These quotes were pulled from several ETR event roundtables that occurred in 2020. The first one talks to the cloud compute bill. It spikes and sometimes can be unpredictable. The second comment is from a CIO at IT/Telco. Let me paraphrase what he or she is saying. AWS is leading the pack and is number one. And this individual believes that AWS will continue to be number one by a wide margin. The third quote is from a CTO at an S&P 500 organization who talks to the cloud independence of the architecture that they're setting up and the strategy that they're pursuing. The central concern of this person is the software engineering pipeline, the cICB pipeline. The strategy is to clearly go multicloud, avoid getting locked in and ensuring that developers can be productive and independent of the cloud platform. Essentially separating the underlying infrastructure from the software development process. All right, let's wrap. So we talked about how the cloud will evolve to become an even more hyper-distributed system that can sense, act and serve, and provides sets of intelligence services on which digital businesses will be constructed and transformed. We expect AWS to continue to lead in this build-out with its heritage of delivering innovations and features at a torrid pace. We believe that ecosystems will become the main spring of innovation in the coming decade. And we feel that AWS has to embrace not only hybrid, but cross-cloud services. And it has to be careful not to push its ecosystem partners to competitors. It has to walk a fine line between competing and nurturing its ecosystem. To date, its success has been key to that balance as AWS has been able to, for the most part, call the shots. However, we shall see if competition and public policy attenuate its dominant position in this regard. What will be fascinating to watch is how AWS behaves, given its famed customer obsession and how it decodes the customer's needs. As Steve Jobs famously said, "Some people say, give the customers what they want. "That's not my approach. "Our job is to figure out "what they're going to want before they do." I think Henry Ford once asked, "If I'd ask customers what they wanted, "they would've told me a faster horse." Okay, that's it for now. It was great having you for this special report from theCUBE Insights Powered by ETR. Keep it right there for more great content on theCUBE from re:Invent 2020 virtual. (cheerful music)

>> Announcer: Live from Washington D.C. it's The Cube covering AWS Public Sector Summit, brought to you by Amazon Web Services. >> Welcome back everyone to The Cube's live coverage of the AWS Public Sector summit here in our nation's capitol, I'm your host Rebecca Knight. Co-hosting alongside analyst John Furrier. We are welcoming today Troy Bertram. He is the GM Public Business Development Worldwide Public Sector at AWS. Thanks so much for coming on The Cube, Troy >> Thanks for having me Rebecca >> Rebecca: A first timer. >> It is the first time. >> Rebecca: Welcome. >> Yes, thank you John, thank you Rebecca. >> Let's talk about your partner organization. Why don't you let our viewers know how it's structured, what its mission is, how it works. >> Yes, certainly. Our public sector partner teams work with our partners around the world that really support the mission requirements of government, education, and non-profits. Our partners are part of the large Amazon partner network, so 35,000 plus partners, but really our customers choose, Whether it's technology partners that have really focused their SaaS, PaaS, ISV solutions on government customers and worked through accreditations and certifications, or it's the consulting partners that go to market and own the prime contract vehicles. Contracts are how our customers buy in public sector. What we've done is really focused our teams from start-ups, and venture capitalists, and incubators, through technology, ISVs, PaaS and SaaS partners to our large consulting partners; global consulting partners, but also really helping curate those consulting partners that meet socioeconomic requirements. Often times governments have laws, regulations to buy small woman owned 8(a), service disabled veteran, as veteran, one of my near and dear partner subset to me, and we work with them to help navigate through and develop programs to work through the APN, and often times it's a partner to partner activity of a consulting partner working with a specialized ISV technology solution that can meet a customer's mission requirements. >> What's interesting about the cloud, we've been talking about our intro this morning is the agility and government's now seeing it benefits, and it's not just and aha moment anymore cloud is really, it's driving a lot of change. That's been lifting up a lot of your partner profiles. You have start-ups to large entities all playing together because the requirements my change based upon either the agency or the public sector entity. >> Yes. >> Have unique needs, so you have a broad range of partners. How do you guys nurture that? That's good diversity. You have nice solution set from tech to business. How do you guys nurture that? What's some of the challenges and opportunities you guys are seeing with the growth. >> Cloud is really allowed a reset for many of our partners. Whether you are born in the cloud company, that doesn't necessarily have a long legacy, and haven't built an entire infrastructure, and you don't have an infrastructure of people, but also don't have technology debt that you've been burdened with because of your prior operating models. It's nurturing that born in the cloud company that maybe a services oriented migration partner that's focused on moving our customers applications and workloads, or it's nurturing the technology and helping them build, or it's a refactor and a legacy on premise solution or those solution providers that have traditionally operated in an on-prem environment. Helping them train, certify, and really build a new practice. >> And it's exciting too. You got the ecosystem kind of approach where, you know a thousand flowers can bloom. I've got to ask you, what do you see sprouting up? What's growing most? What is some of the trends that you see in the partner ecosystem? What's growing fast? What's the demand? What's the hot area? >> The real demand is for people with skill sets. In our business, skill sets also often include security clearances, and a knowledge of the working environment that they're migrating from. We're spending an inordinate amount training and educating. Also, our partner selling community of understanding the dynamics of how to go to market, and the contract vehicles, and how to navigate. The opportunities are really immense. It's nurturing those thousand flowers, and it is a challenge for many of us. How do we nurture those thousand flowers simultaneously? >> Are you finding the right people? A big theme on The Cube here is the skills gap. I just saw a Deloitte survey. 60% of executives, and these are executives, they're not in the public sector, said a skills gap hindered their AI initiatives and hindering their cloud computing initiatives. What are you seeing? What are you hearing from the people you're talking to? >> There's a thirst for both knowledge and training, but there's also, from the executive side, we have a need to fill. There's an abundance of roles, and all of us working together. One of our initiatives is even the job boards that we're working with our educate team and Ken Eisner a peer that leads that is, we're helping our partners promote their open roles. Allowing our partners to look for and curate the same talent that Amazon is helping train and develop because when our partners can find amazing talent, our customers win. It benefits AWS and the partner ecosystem. >> Education's huge. You got to have the ongoing digital course ware. Is that a top priority for you? What are some of your top goals for this year in your plan? >> When it comes to education, top goal is training many of our new partners through our emerging partner team. Many of the new partners have a commercial practice. We're also looking at those partners and actively recruiting those partners that have built a commercial practice that are looking to enter government. Whether it's our distributors or our resellers that own the prime contract vehicles, we're doing partner to partner activities. We call it partner speed dating. It's contract vehicles that exist across state and local government, US federal, or in the international community for those ISVs that want to enter new market regions is pairing with those existing local companies that have contract vehicles and then helping train and educate on the nuances of public sector. >> We were talking with General Keith Alexander and retired General Yesthidae came on and I asked them directly, if you could a magic wand, I think I said, something along the lines of if you had a magic wand, what would you do to change the government? It could go faster. He said the technology check we're doing very well, it's moving along great, it's the procurement process. It's just too long. He mentioned contracts. This is really the key point we keep hearing. The red tape. What's the update there? I'm sure partners aren't wanting more red tape. They want to cut through it, to your point. >> No. It's really an education process. When I started at Amazon over six and a half years ago, my first role was to stand up, and it still is the core of my role, I have individuals in 22 different countries around the world, and we're helping governments and VR partners through the procurement process. We did this past week in my home state of Minnesota, our 10,000th RFX, so we consider an FRP, FRI, an RFQ a tender, I need to buy, I want to buy something. We responded to 10,000 of those in six years and two months. That's an abundance of contract that ultimately, many of them are task orders and IDIQs and GWAX. There's an abundance of pathways as General Alexander stated for customers to buy the technology. Now it's educating the contracting officers, the COs, the KOs, around the world on the existing pathways and how to leverage them. We still see old procurement methodologies being applied to the cloud, and it does slow down the end customer's mission requirements. >> And the path to value. >> Yes, the path to value. Exactly. They want to move and move fast and contracts is how we buy, but it's also what slows us down. >> You know, you're with Amazon six years plus, so you know this, so the speeds of value's been the key thing for the cloud. As you look at success now with Amazon public sector, not only in the US, but abroad and internationally, you got massive tailwinds on the success. The growth is phenomenal. How does that feel? What's some observations? What's some learnings that you can take away from the past few years and where's it going? >> It feels like it's day one. It does feel like it's day one. There are tailwinds, but there's still an abundance of customer requirements, and they're evolving, and they're more complex. I personally really like my career's been public sector. Solving the mission requirements, whether it's helping a forward deployed airman, soldier, really keeping them at the cutting edge of technology, and out of harms way, or our first responders; some of the new product demonstrations that we've seen of evolving technology that's helping a firefighter see from an aerial drone vehicle. What does it look like on the other side of this building, and how can I now communicate across different agencies? Is phenomenal. In my home state, where Army Futures Command, I live in Austin, Texas. Army Futures Command is working with the state of Texas as well as the University of Texas to really collaborate as we've never seen before. The barriers of emerging technology to legacy government, to ministries, and health defenses around the world, ministries of defense, and health agencies around the world. >> The data, the scale of Amazon cloud is going to to make that possible. Ground Station's a great example of how that's growing like a weed. The DOD has got a great charter around using agility and AI. >> Collaboration, which is so critical too, as you said. >> It is, and our VM Ware partnership with VM Ware on AWS can really help, and that's a partner play. That's partners helping migrate using the co-developed technology to really move and move faster. Use those existing apps and vacate those data centers. >> Well, thanks for coming on The Cube. Got to be a quick plug, plug the organization, share with the audience, what you're looking for, and update on the partner network. Give a quick plug for your group. >> What we're really looking for is, we've got 105 different competency partners that have really invested in their government, their education, their non-profit competency, and we want to help. I personally want to help them promote their business, and what the opportunity is to connect to either other partners or to government mission requirements. Really welcome the opportunity, John, to come on and look forward to seeing my partners on The Cube in the future. Thank you. >> Well, Troy Bertram, you are now a Cube alum, >> A Cube alum >> Thank you. (panel laughing) >> Thank you. >> I'm Rebecca Knight for John Furrier, you are watching The Cube, stay tuned for more AWS Public Sector Summit.

>> Live from Washington DC. It's the Cube. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome to the Cube's live coverage of AWS Public Sector, here in our nation's capital. I'm your host Rebecca Knight, along with my co-host, John Furrier. We are joined by Sanjay Sardar, he is the VP Modernization and Digital Transformation at SAIC. Thank you so much for coming on the Cube. >> Thank you for having me. >> So, you are a twenty-five year veteran of data management. Why don't I start by asking you to... Sort of break down the principles of good data management. This is what we're here to talk about. >> Yeah. So... When you say it that way it makes me feel very old. I've done data management for a long time. The key to data management... Some of the principles are understanding, kind of what data you have. Where it is. What's the value of the data. That's the key that everyone's trying to bring. You know in the last twenty years, we've seen an explosion in the amount of data that we were handling. So, really, how do you get through all that data? How do you understand how to manage it? Where do you put it? And then really understand how to use it. What is that value of all of it coming through? Some of if is just machine data and noise. That you're looking at. That's important for certain aspects, but doesn't really add much value to the overall working of the agency or organization that you're with. And others are very valuable data, that you cannot really do anything with, unless you manipulate it in some way, or some fashion. So, data management takes a lot of different practices. And different ways to look at it. So, we've been doing master data management, meta data management for a long time, which helps understand what that data is. But then, what's the provenance of the data? What's the governance of data? What policies surround it? Where's the security of the data? All those factors play into, when you're looking at data as an enterprise. >> Sanjay, talk about SAIC specifically. I mean in long history working with the government and many, many contracts with broad range of services. But now at the modernization focus. The conversation is about agility, speed, modernizing government private, public sponsorships... Partnerships. Responsibility and accountability. All these things are in a melting pot. What is SAIC like today? What's your specific role here in Washington DC for Public Sector? >> Fair enough. So the SAIC is almost a fifty year old company. We've been around the government sector for about that long. We've done everything. We do everything from, data management, to software development, to infrastructure and hardware. Pretty much the whole gamut of IT services. And we've worked with almost every federal agency in the area, in the country. From a modernization perspective, what we're looking at is, the federal government is at this tipping point. We have a lot of legacy systems. We have a lot old aging infrastructure that... That needs to be replaced. That needs to be upgraded and modernized. This is a national security issue. We're getting into a point where things... If they start failing, it would be catastrophic for the US as a whole. So, where we are right now, as we're trying to work with the government, to bring in new technologies. As you said it's a melting pot of things that are happening. Not only has data exploded, but the technologies that are being used, have also exploded. You're seeing a massive consumerization happening. Biggest example is the apple iPhone. When the iPhone came out, that consumer... That model of the Apple iStore... Or, being able to do everything from your phone, is something the government has to get to. That's where you're looking at the UIUX models. That's where you're looking at different workflows being moved to the cloud. How do you handle all that? >> They used to be a government. They used to be a consumer of technology. Now they are a regulator of technology. That's what the discussions are. They're looking at using data and technology for their workload. So, it's not so much a supplier consumption relationship. They're much more active participants in the technology scene. The question is, do they really understand, what's going on? Cause, if you don't understand it, you can't control it, you can't regulate it, you can't utilize it properly. This is the number one conversation around modernization. What are the key factors in your opinion? The discovered needs to do better. Is it the procurement? Is it just awareness? (Sanjay laughing) What's your thoughts? >> That's a lot of questions. A lot of things going on there. And you're right. The government has become a consumer of technology. I mean it used to be back in the days when we were launching... Missions into space and putting men on the moon. The government was a leader in technology. Now with the commercialization, government has actually become a consumer of all these types of technologies, and a creator of tons of data. So, managing that data. Managing and understanding that data is very critical. How do you use it to add value to what the government is doing? And then further down the road, to what the citizens are doing. How do you add value to the citizens' life? In doing that, there's a lot of different things that have to come into play. One. As I said, technology is a big part of it. Understanding what technology to apply. It's not just about replacing technology. That's not what modernization is. Modernization, is how do you change and digitally transform your workloads. Your workflow. How you do business. That's really where the value add comes in. To get there, yeah you have to look at the technology. You have to look at the procurement practices. You have to look at different pricing and consumption models that the government hasn't been used to in a long time. When you look at these, traditional contracting models, they may not apply to some of the new ways of consuming technology. >> The world has changed for the government. >> The world has absolutely changed. >> What will it take though, for the government to become a more savvy buyer? I mean what are some of the things that... >> I think the government is already starting to become a more savvy buyer. Again. Remember the far, as when they talk about it, the federal acquisitions regulations. It's a massive volume that's probably, you know, a thousand pages long. So, there's a lot of opportunity to interpret that correctly. Where we're changing now, is how do you interpret it, so that there's fair practices for all competitors in the government market. And you're starting to see that. You're starting to see procurement officers looking at things differently. You're starting to see CIO's demand different services. They almost cannot do it. The compete in storage powers necessary? It's way too hard to go the old traditional route. >> You know what's interesting Rebecca, we talk about data all the time. We just read Infomatica World, they're kind of a supplier. They do the catalog and stuff for here at Amazon. Multi clouds of big countries, so Amazon is one of the biggest cloud. Andy Jackson who was just on stage last night in Arizona at a conference. Talking about response on recognition. All these hot AI data issues. Everything is a data problem. Right? But, yet we talk about government, but it's not just government. It's public sector. It's federal. But it's also international nation states. Competitiveness. So, there's a lot going on in such a short period in time, where analytics and data are key part, around the future value. So, it's almost the whole world is twisted upside down, from just ten years ago. >> Oh. Easily! >> Your thoughts on what's going on, and what the public sector community... Because a lot of these environments, don't have huge IT budgets. But now we're seeing things like Ground Station. Satellite. New stuff happening. >> So you're right. The explosion of data has really caused government... And in fact, every industry to change. More industries are becoming digital industries than when they were manufacturing ones You know, things like Uber, and all those industries that popped up because of the data. That's where government is also turning into. They are starting to understand that all the decisions that government makes, has to be done through a data driven model. They have to have this evidence based decision making process. And you're seeing that, because of the federal data practices. The data management act. The creation of CDOs in every agency. This is really pushing. The government is really recognizing, data is an asset. It's a value added asset, that they have to use better, to add value to the citizens life. To what they're providing. >> And it wasn't necessarily front and center on the... Quote, "data balance sheet". If you will.. Or the evaluation of data wasn't always looked at that way. >> No. >> Cause that changed the perspective. Understanding and... >> It's a huge shift. Like I said. When you look at the rise of the CDO. The Chief Data Officer in the federal government. That's a really big indication that data is now become and looked at as an asset. The CIO was responsible for all the technology and... They're governing all the technology. And they're the... Owner of that. The Chief Data Officer's now doing the same thing from the data side. The governance. The policy. The usage. The cooperation across multiple agencies. Multiple countries, as you said. >> Are agencies deploying CDOs across all agencies now? >> I think you're seeing more and more of the CDO being put out there. In fact almost all the agencies that I work with, have a CDO already in place, or are hiring one in the next three months. >> Why is modernization such a contentious topic? Is it because everyone has a different definition of what modernization is? It seems to be contentious when I talk about it with folks. It's like, what does it mean? >> I don't know if modernization is a contentious topic in the sense of... I think everybody recognizes that they have to modernize. It's how do you do it? You know, we are in a world where we have so much legacy infrastructure, legacy applications, that are tied so closely to mission. There's a risk of how do you modernize. You don't modernize correctly, you might in fact mission. And when you're talking about thing like in the DOD, where that leads to potential, you know, in theater situations and problems. That's a big problem from the DOD side. In the civilian side of the house, same thing. If your taxes go up by forty five percent because someone messed up on the modernization side, that's a problem. So, we have to be careful. Every agency has a personal journey. SAIC, when we look at this working with our partner systems, we look at an agency's personal journey. Everybody's going to do it differently. So, I think the contention comes in is, how do you do it? When do you do it? What do you attack first? Where do you look at the challenges and value adds are? Because everybody has to do it. Budgets are shrinking, and security is important. >> And workload has kicked around a lot. Applications used to be the old worry. Now an application sits on a server. It runs kind of monolithic. But, the applications are what... And the workloads are what really is the goal. Agency's got their own unique solution. That taxes is for taxes. Make that go better. So. Data and cloud, is different per workload. Per environment. Per mission. >> It very well could be. I think it's ubiquitous that there is a compute and storage factor, that everybody has to use. But the workloads that really transform the digital mission, are very different from agency to agency. So, you have to look at, what are they valuing, and where they are going with it. So, agencies like PTO, they're looking at, how do I more effectively our examiner's time? Versus, agencies like NASA, which are looking at, how do I do higher level compute, and HPC type work? So. >> One of the things you talked about when we first began our conversation. Is not only the explosion in data, but the explosion around the technologies and tools that are used to store and manipulate, and execute decisions on the data. Can you talk a little about what you're seeing. For example AI. I mean this is all the buzz, and all the big technology shows that we go to around the country. And it's maturing... But there's not a lot of adoption in the government. >> So, you're right. Along with this data explosion, we've seen a technology explosion. And with the different types of tools, handling the different sectors of managing data. Storage is one we talk about all the time. Because you have so much data, you can't actually access all that data at once. So, there's segmentation in the data that you have to look at. Companies at Cohesity are doing a good job of handling and managing that segmentation, in their hyper converged storage architectures. But we're also looking at in the AI world. Yes. AI is artificial intelligence. Deep learning. Machine learning. These are all techniques that are working very well for certain types of data usage and data problems. But the adoption is not as wide spread. Because, they're new technologies. I mean AI is where data was, like I said, twenty years ago. So, they're starting to understand, how do I use it. What do I use it for? You know that natural... That learning process that AI goes through. To say, "Okay, I'm going to make something more efficient." How do I do posturing of that data? Where do I actually use that? When you have large volumes of data. Security for example, is a great example. When you look at security logs, lots of volume of data coming out of that. But to use AI to learn which vectors the next security threat's going to to come through? That's a pretty daunting challenge, and not an easy one. And you have to find used cases like that. So, artificial intelligence I think has a large promise in the world. There's image recognition that's working very very well. Image recognition and classification. Natural language processing to look at different core sets of data in the research community. Or, in the pattern community. Those are very good examples of how AI is being used today. But there's a long way to go. And there's a lot to be learnt still. >> There's a lot of technology behind storing, and one of our sponsors that sponsors the Cube, Rebecca's cohesity. They sponsor us and invest in events. I think, always thank the sponsors. They're in the business of scaling up storage. So, it's not that easy to store it. So, you have to not only figure out the business model behind how to use the data. There's also the technology around storing it cleanly without hiring away. Talk about the dynamics around tech, in terms of managing the data. >> Well, so as you said it. There's a storage aspect of it. There's a retrieval aspect of it. There's a time aspect of it. All of that leads to... Yes, data is so valuable and so large and so limitless now. Doing all of those things matter. I mean if you're waiting, even nowadays... If you're waiting even three seconds for any response to come back? You're going to look at it and be like, I got to change my computer out cause it's too slow. That's the kind of area where we're in. When you look at the segmentation of data, nearline storage versus online storage. Well, the nearline has to be almost as fast as the online, cause now we're looking at things where, as you put it. The AI models are looking across vast amounts of data. They're looking at everything. How do you do that well? So that... All of that technology factor plays into it. >> One final thing. And this is just about the mindset of the government right now. Because what you're talking about, is a lot of exploration, and a lot of experimentation that's needed. How would you describe, sort of the federal approach to this? I mean, in fail fast is the motto of Silicone Valley. (Sanjay laughing) But that's a lot harder to do in the government. When lives are at stake. >> Well yeah. And it's cautious to be fair. It's not only lives at stake, but it's tax per dollars. Everybody is putting in there. And we want to make sure that we're doing right. To be fair. The government is looking at a fail fast prototype type models. That do work with, like you know, hackathons, and competitions. That really bring together public sector and private companies, like SAIC and others. To do different things that help kind of with this technology explosion. So for example, We work with USDA. We did multiple hackathons for precision agriculture. That kind of work is... It helps understand, what do we need to do with precision agriculture? What tools make sense? So, we have something we called our innovation factory. Where we have contracted out with multiple Silicone Valley. So we bring that to us, and then we bring that to government. That way the government does not, you know, not precluded by some of the rules that they have. But those type of things really help, that public, private partnership... It has to happen. >> I just want to... On that point real quick. Then we got to break. >> One of the things that you mentioned there is that this new generation kind of mindset. Talk about that dynamic, because there seems to be a new generation, digital natives, emerging into the work force. >> Absolutely. >> Enforcing the change, within the government. Can you validate that? Can you see... Can you share your opinion on how that's impacting everyone? >> Absolutely. Since I joined government over, God, now it's over twelve or thirteen years ago. And I left four years ago. We've been talking about this cliff that's coming up in the human resources side of the house. Where thirty-five percent of the top tier leadership is retiring. That's all getting replaced by new folks entering the market. And all these folks grew up in the iPhone era. None of these guys do anything that is... They are all mobile. They'll work anytime, anywhere. >> Very impatient too. >> Very different mindset. >> Cut the red tape. >> Right. Very different mindset and how to make government work. And that's a good thing. That kind of shake up is actually necessary. As these folks grow into leadership positions. They're going to change how government works. So we got to be ready for it. >> Great. Well Sanjay, thank you so much for coming on the Cube. >> Absolutely. Thank you for having me. >> We'll have more from AWS public sector. I'm Rebecca Knight, for John Furrier. Stay tuned. (theme music)

>> Voiceover: Live from Washington D.C., it's the Cube. Covering AWS Public Sector Summit. (upbeat music) Brought to you by Amazon Web Services. >> Welcome back everyone to the Cube's live coverage of the AWS Public Sector Summit here in wonderful Washington D.C. I'm your host, Rebecca Knight along with my co-host, John Furrier. We are welcoming Dave Levy to the program, he is the Vice President, Federal Government at AWS. Thank you so much for coming on the Cube. >> Yeah, thank you for having me. >> Rebecca: This is your first time, your first rodeo. >> It is my first time. >> Rebecca: Welcome. >> Glad to be here. >> You're now a Cube alumni, welcome to the Cube alumni club. >> Well exactly, right, exactly. So you have been with AWS for about two years now. AWS famously has this day one mentality. I want you to talk a little bit about the culture of the company and how the culture helps create more innovative products and services. >> Yeah, and it is always day one. You hear about that but truly working in my first two years, you really get the experience when you're here everyday, that excitement and that enthusiasm for customers. It's interesting and somebody was asking me the other day, how do you get influence inside of Amazon, how do you get you points across? And in large part because Amazon's not a PowerPoint culture, being charismatic or having some of those traits really doesn't carry the day. What really carries the day inside of Amazon is what customers want and so I can't tell you how many times in the first few years that I've been here that we have been in meetings, going through our customer working backwards process, where somebody has said, wait a minute, we heard customers say we prioritize these four things versus these three things. And that kind of sentiment carries a lot of currency inside of the business for what we prioritize and what's important to us and it's how we innovate on behalf of customers. So that's what happens everyday, it happens day one at AWS and it's been really exciting these first few years. >> That's been a great formula for Amazon. That long game as Bezos always says, Andy always says, customer first, customer-centric thinking. But this working backwards process we've learned, come to learn, it's really critical within Amazon. But also making sure customers have the right journey, right, they get what they need, they get value, lower costs, living with undifferentiated heavy lifting. I feel like I'm messaging for Amazon. (laughing) Got it memorized. I sit down and interview so many people from Amazon, I got the rap down but digital transformation is about the long game 'cause all the shifts that are going on now aren't incremental, small improvements, it's really moving the ball down the field, big time. So you're seeing major shifts within customer bases saying, like the CIA did in 2013, >> Dave: Sure. >> which was initially a hedge against big data, we heard on stage today, turned out to be a critical decision for their innovation, this modernization. Could you share some other customer experiences around this IT modernization trend that's, it's totally real, it's happening right now in D.C. in Public Sector. >> Sure, there are a lot of examples. IT modernization is something that takes on a lot of different forms and a lot of different agencies think about it in different ways but fundamentally, it's about taking the systems that are serving citizens or a war fighter and allowing for an ability and an agility to do things better and faster and cheaper and doing it in a way that continues to innovate. And you see a lot of examples of that. CMS has the 76 million records of Americans on AWS. You see large data sets starting to be hosted on AWS from agencies across the civilian sector. DOD is really starting to lean in on workloads that are traditional things like ERP. >> DOD is more than leaning in, they're really going big. There's a paper that they put out was very comprehensive-- >> Yeah, I think there's a tremendous advantage from this digital transformation and agencies are really just at the beginning of it. They're really beginning to see what flexibility it provides. I think the other thing that it's doing is it's really helping to modernize the workforce. It's allowing the IT workforce to start focusing on things that are really valuable instead of managing hardware or managing IT environment strictly. It's giving the ability to deliver solutions and that's really exciting, that's what modernization is doing. >> One of the things that comes up in the modernization talks, it's not that obvious on the mainstream press, but the whole red tape argument of government process. People process technology, again, we've done these conversations all the time but in each one, the process piece, there's red tape in all of them. People who go slower, the process has red tape in it but this idea of busting through and cutting the red tape. >> Dave: Yeah. >> All these bottlenecks, Teresa calls them blockers. >> Yeah. >> Right. That's her different word. >> Yeah, yeah. >> These are real, now people are identifying that they can be taken away, not just dealing with them. Your thoughts and reaction to that. >> Yeah, well, I agree. There's a lot of opportunity. Digitizing work flows gives you the opportunity to re-examine all of these operational processes which frankly, may have been in place for very sound reasons in the past but when you modernize and you digitize and you do it in a cloud way, you're going to start to see that some of those things and those processes that were in place, really aren't necessary any more. And it allows you to move faster, it gives you more speed and we're seeing that across customers and the US government. We're seeing it really everywhere. >> And one of the things you were saying too about the digitizing the work flow, it's really about ensuring that citizens, civilians or members of the armed forces are interacting with government in a more meaningful way. That is the overarching problem that you're trying to solve here. >> It is and it can be as simple as citizens getting the kind of content that they need from a modern website, accessing it quickly, going to higher level functions around chatbots and things like that. So these modern cloud architectures are allowing agencies to deliver services faster, deliver things to citizens in a way they haven't before. Could be citizens that need assistive technology. It's giving agencies the opportunity to do things around 508 compliance that they haven't done before. So it's really opening up the aperture for a lot of agencies on what they can deliver. >> We've been doing a lot of reporting around Jedi, the DOD, actually been following a lot of the white papers from a cloud perspective. We're not really in the political circle so we don't know sometimes whose toes we're stepping on when we poke round but one thing that's very clear from the agencies that I report, even here in the hallways this week, CIA and other agencies I've talked to, all talk about the modernization in the context of one common theme, data. Data is the critical piece of the equation and it's multifold, this single cloud with the workload objective or multiple clouds in an architecture like the DOD put out. So there's clear visibility on what it looks like architecturally, multicloud, some hybrid, some pure public cloud based on workloads, the right cloud with the right job and people are getting that. But data is evolving, the role of data 'cause you got AI which is fed by machine learning. This really is a game changer. How is that playing out in conversations that you're seeing with customers and talk about that dynamic because if you get it right, good things happen, if you get it wrong, you could be screwed. It's really one of those linchpin, core items, your thoughts. >> Every agency, virtually every agency we talk to, every customer we're talking to is saying that data is the most important thing, their data strategy. Data, you know, we've all heard the sayings, data has gravity, data is the new oil. So there's a lot of ways to characterize it but once you have the opportunity to get your data both unstructured and structured, in a place, in a cloud, in an environment where you can start to do things with it, create data lakes, you can start to apply analytics to it, build machine learning models in AI. Then you're really starting to get into delivering things that you haven't thought about before. And up until then it's been tough because the data, in a lot of our customers, has been spread out. It's been in different data centers, it's been in different environments, sometimes it's under somebody's desk. So this idea of data and data management is really exciting to a lot of our customers. >> Now a lot of people don't understand that there's also down, and this is what we're getting, we're hearing from customers as well is that, they set up the data lakes or whatever they're calling it, data strategy, data lake, whatever, then there's downstream benefits to having that data just materialize and as an anecdote to what is, you look at the Ground Station after we've had a couple great interviews here about Ground Station which I love by the way. I think that's totally the coolest thing because of the, well, the real impact is going to be great back hog, IoT is going to boom, blossom from it but it only happens because you got Amazon scale. So again, data has that similar dynamic where as you start collecting and managing it in a holistic way, new things emerge, new value emerges. >> Yeah, I would say-- >> What are some of those things that you're seeing with your customers there? >> I would say there are real-world challenges that our customers have to deal with with data, right. When you start to have volumes, terabytes, petabytes of data, they've got decisions to make. Do they expand the wall, knock out a wall and expand their data center and buy more appliances which require more heating, more cooling? Maybe they do do that but there's an alternative now. There's a place for that data to go and be safe and secure and they can start doing the things that they want to do with that data. And like you said, downstream effects. There are some things that they can do with that data that they don't even know about today, right, and Ground Station's a good example of that. >> You talk to people in the military, for example, because we just had Keith Alexander, our General, the General was on. They think tactical ads using data, save lives, protect our nation, et cetera but there's also the other benefit of it that has nothing to do with the tactical, it's a business value. The enablement is a huge conversation >> Dave: Sure. >> that you hear in these modernization trends. Not just the benefits tactically, but the enablement setup, talk about that dynamic. >> Well, you think about the data that is collected. You think about the valuable data at the VA and that has potential implications for population health and so this day is just enormously valuable. I think we're at the very beginning of what we can do with some of these things across federal and you look at agencies like Department of Interior and some of the data sets they have are just fascinating. What we can do. We've got millions of visitors to our national parks every day and we don't know what's possible with a lot of those data sets. >> Talk about some of the tools and techniques that are being used to work with that data and talk about AI and machine learning and how they have been a real game changer for some of your federal customers. >> Well, ML and AI is really, we're really at the very beginning of this transformation. I think in the fullness of time, the vast majority of applications are going to be effused with machine learning and artificial intelligence. I think that day is not too far away and they're using tools on our platform like SageMaker to make predictions in this data. And one of the great things about having a platform that has really three, different parts to the stack which are machine learning, that's where you have your frameworks. I say that's where all the really, really smart people live, all the data scientists that we're all so desperate for and then you've got that middle layer which are tools like our SageMaker which everyday developers can use. So if you've got geospatial data and you're trying to determine what's in a given area, everyday developers can use SageMaker to build machine learning models. Those are some of the things they're doing, very exciting. >> Hey, I want to get your thoughts on a comment that Teresa Carlson just made earlier today. I'm not sure she said this on camera or not but it was memorable. She said, "It used to be an aha moment with the cloud "but this year it's not, it's real, people now recognize "that cloud adoption is legit, proof is in the--" >> Rebecca: Cloud is the new normal. >> The proof is in the pudding, it's right there. You can start seeing evidence, all the doubting people out there can now see the evidence and make their own judgment, it's clear. >> Yeah. >> Cloud is of great benefit, creates disruption. As this continues to increase, and it is, numbers are there, see the business performance, what are the challenges and drivers for continued success? >> Yeah. I think the first conversation starter, so Teresa's spot on as she always is. I think the first conversation starter is always cost savings. That was the way everybody thought about the cloud in the beginning and I think there are cost savings that customers are going to realize. But I think the real value, the real reasons why customers do it is, there's an agility that happens when you move to cloud that you don't necessarily have in your other environments, there's the ability to move fast, to spin up a lot of capability in just a few minutes, in just even minutes and change the experience for users, change the experience for citizens. I think the other thing that cloud is delivering is this whole breadth of functionality that we didn't really have before. We talked about machine learning and AI but there are tools around IoT now. There's Greengrass on AWS which is simply AWS IoT inside. And places like John Deere, we have hundred thousands of telematically enabled tractors sending data back to planters. So customers are getting involved because there's this huge breadth of functionality. I think, and so that's exciting, those are the enablers, that's what's driving. I think some of the things that are getting in the way is, we've got a workforce by and large, especially in the federal government, well, this is new and that learning is happening, that enablement is happening about cloud. We're teaching about security in the cloud. It's a shared responsibility model. So it's the new normal, we know what can be done in the cloud but now there are some new paradigms about how to do it and AWS and a lot of our partners are out there talking about how to get that done. >> I want to get a double down on that because one of the things that we're doing a report on, I've been investigating, is kind of a boring topic but it's your world right on which is how Amazon bare-knuckled their way into this market through cost saving which for the federal government, I would say, is a great lead 'cause they care about cost savings. A financial institution in Wall Street might not care about cost savings. They might want arbitrage on the other side but again, government's government. You guys have earned, done the work to get all the certifications. Your team, Teresa's team has done that and now you're at the beginning of the next level. But procurement is really broken, right. I was talking to an official in an interview off the record and he said, I won't say his name till I can say it here, he said, "You know, we're living procurement in the 80s. "We still have a requirement to ship a manual "on a lot of these things." So the antiquated, inadequate procurement process is lagging so much that the technology shifts are happening in a shorter period of time. Amazon which produces thousands of new services every year and reinvents Jace's big slide thousands, next year it'll be probably 5000, who knows but it'll be a big number. That's happening, all this is happening right now, really fast but procurement's lagging behind it, really stunting the innovation equation, >> Dave: Yeah. >> the growth of innovation. Your thoughts on fixing that, how you get around it, all these old tripwire rules. >> Well, first I'll say, procurement reform is something that's on everybody's mind. This is, it's not just a blocker for cloud, it's a blocker for everybody. Technology is far outpacing what our federal government can do. So I don't, there's nobody that I talk to that thinks that we're headed in the right place with procurement reform, even our customers inside of the government. So I think what I'd say is it's really collective approach. It's an industry approach that's going to be taken to change a procurement, to help them adapt to modern laws. Do we need changes in the far perhaps, yes, but I think we need fundamental policy changes, a legislative approach to change procurement for technology. It's only going to move faster, you're right. Indie announced in 2018 I think, nearly 2000 services so you can expect there's going to be more this year. Part of that is understanding new models. Our marketplace, for example, is a way to buy and access software quickly, fast, even by the hour if necessary. That's a total-- >> Rebecca: Like Ground Station >> Yeah. >> in that way, yeah. >> By the minute if necessary. >> Yes, yes, yes. >> So it's a totally new paradigm. As far as how we're approaching now, it takes having good partners. We have good partners that are helping us with respect to contract vehicles. I think we're being transparent around how we bill, how these services translate, what's in the services that they're getting charged and I think agencies are starting to feel more comfortable with that. >> I learned a term from Charlie Bell, Engineer Lead for Amazon, did an interview, a term you guys use internally at Amazon called, dogs not barking. >> Dave: Yes. >> And it means that everyone, the barking dog everyone hears and they go after, they solve that problem. It's what you don't see, the blind spot, aka blind spots. What do you see in federal that's not barking >> Yeah, what are our dogs? >> that you're aware of? What keeps you up at night? >> What are our dogs not barking? >> John: Yeah. >> I would say, it really is our customer workforce. I think our customers really need to get enablement and training and support from us and the partner community on how to make this transition to cloud. It's incumbent upon us and it's incumbent upon the agencies to really deliver it. That does keep me up at night because this is new. This is new for, the ATO process is a little bit different. The accreditation process is different. So there's a lot of new things out there and if there's a dog that's not barking, it's somebody needs help and they're not really letting us-- >> They might not even know they need it. >> They don't know they need help or they're not saying that that they need help and they don't know where to go. >> Right. >> Right. >> They should come to you. >> Well, thanks for coming on. (laughing) >> Dave, thank you so much for coming on the Cube. >> Yeah, thank you, all right. >> Thank you, thank you. >> I'm Rebecca Knight for John Furrier. We will have more from the Cube AWS Public Sector Summit, stay tuned. (upbeat music)

>> live from Washington, D. C. It's the Cube covering a ws public sector summit by Amazon Web services. >> Welcome back, everyone to the cubes Live coverage of a ws public sector Here in our nation's capital Washington D. C. I'm your host Rebecca. Night hosting alongside of John Farrier. Always a pleasure being with you. >> So good to see you again. >> And we're joined by first time Cube guest Brett MacMillan. He is the GM ground station. Eight of us. Thanks so much for coming on >> the road to be here. Thank you. >> So why don't you start by telling our viewers a little bit about ground station? What? It is one of us. >> You're first of all really excited to be here at this conference yesterday we had our second annual Earth Science Day. Last year was really successful, and we're finding a huge amount of interest around a space and space primarily tto help save the earth. And so >> eight of >> us came out with the solution, and we made it generally available last month called Ground Station. And if you think back about 15 years ago, before the commercial cloud came out, uh, you had to do for a data center. You Hey, either had to buy the data center. You had to do a long term lease. And then >> we >> came out with the commercial cloud. And from that point forward, there was a tremendous number of innovations. That movie came out of that. I don't think any of us back then could have predicted things like Pin arrests O R. Spotify Or or that Netflix would have gone from shipping your DVDs to be in the online streaming company and all those innovations happening, we think that we're at the beginning of that stage of satellite industry. So what ground station is is It's a service that you can use like any other cloud service. Just pay for what you used on demand. You can scale up you, Khun scale down. And we think that we're in the early stages of opening up innovations in this >> industry >> and its satellite specific. So it's a satellite services of connectivity. How how's it work? What's that >> s what happened to you. You would have a you just go into the eight of us counsel on you schedule a contact. And most of these early use cases there for our low earth orbit. Satellites are medium earth orbit satellites, and we have deployed these satellite antennas. And what's really important about this is we put them right next to our data centers or availability zones. So now you're getting the entire power of the cloud. And so what happens is you would schedule contact and either up Linker downlink your data during that contact period. And we just charge per per minute. And >> so it's like the two was servers and still has three. With storage and thie used. Case wasn't solved. The provisioning problem. So you guys are doing it for up Lincoln down Lincoln to satellite usage and data over satellite. Pretty >> direct. Correct. And so And the other thing that's really nice about it is just like the cloud would announce enable people to go global and minutes ground station allowed you to go global also. So, traditionally, what would happen if you would buy a satellite antenna or you'd Lisa Sal? I'd intended somewhere in the world and you're only catching so many passes of those satellites. We are deploying these at our data centers through out the world, and so you're able to at a very low cost. Now touch these passes of the sound lights. >> You know, Brett, Rebekah and I were talking on the intro around the role of technology. How it's causing a lot of change. You mentioned that window of 10 years where, before YouTube, after YouTube, all these new services came on. Think about it. Those didn't exist around before. Two thousand four time frame. Roughly two thousand 10 2 4 2 4 to 5. Then the mobile revolution hit. Similar wave is coming into government and seeing it. Amazon Webster Public Sector Summit is our fourth year. It gets bigger. The inclusion of space is a tell sign of commercialization of some of the tech coming in infiltrating process, change within government and use cases. So I would agree with you that that's relevant. >> Yeah, And >> next level is what? What was that window? What's gonna happen that 10 year? >> You don't change? It is hard to predict, but we know from our past experience on what we've done in the cloud. We know that when you remove the undifferentiated heavy lifting like buying servers are doing networks and things like that. It frees people up to do innovations on DH And when you look at what's happening in the satellite industry, virtually every industry, every person can benefit from a better understanding of this earth and from satellite imagery and satellite sensing. And so, if you start moving forward with that and you ask what can happen, we've got governments throughout the world that are very concerned about deforestation. And so, for example, today they find out 54 station after the trees are gone. And what if you could instead, for a very low cost, download pictures of satellite images and get it in more of a really time type basis? Or get it in that same hour that, uh, sound like took the picture. Now what you could do is catch the deforestation when the boulders air show up, not after the trees went down, so >> get in front of it. Used the data is a data business just about other use cases, because again, early adopters are easily the developers that are hungry for the resource. We saw that with cloud to industry, I mentioned now those service thousands and thousands of new services a year from a baby s jazz. He loves to talk about that at reinvent, and it's pretty impressive. But the early days was developers. They were the ones who have the value. They were thirsty for the resource. What are the sum of that resource? Is what's the low hanging fruit coming in for ground station that you could share that tell sign for >> where it's going? Interest not only for the his new developers in these new things, but large, established sound like companies are very interested in that, because when I was talking about earlier, you can cover areas with our service in ways that were very expensive to do. Like until you Ground Station would have been a little hard for us to roll out, had we not first on eight of us if you didn't first have things like Ace two and three and your ways of of storing your data or our petabytes scale worldwide network. And so when you look at that, you're able to get multiple different organizations doing some really cool things. We're in partnership with Cal Poly, Cal Poly and Cal Poly's been in the space industry for a long time. Back in 1999 they were one of the inventors of original Cube sat, and today what they're doing is they have this STDs, Sally Data Solutions service on. It's an initiative that they're doing and they did a hackathon. And when you look at all the areas that could benefit from from space and satellite tourists, all kinds of things pop up. So, for example, if your cattle rancher and you have a very large area, sometimes cat cat will get stuck in an area like a canyon or something. You don't find out about it. It's too. It's too late. So Cal Poly did this hackathon on DH. What they came up with is, it's very inexpensive now to put a I ot device on it on the cows on with the ground station. You can now download that information you can communicate to a satellite, and now we can find out how where those cows are and get them if they're in a dangerous situation. I >> think the eye OT impact is going to be huge. Rebecca, think about what we talked about around Coyote. I ot is the edge of the network, but there's no networks, not flat. It's in space. The earth is round right, so You know, it's kind of like a Christopher Columbus moment where if you have the data, all you need power and connectivity. So battery power is getting stronger every day. Long life batteries. But the connectivity with ground station literally makes a new eye ot surface area of the earth. Absolutely. I mean, that's pretty groundbreaking. >> This is a really exciting time to be in the space industry. A couple things are driving it. One is that the capabilities that were able to put up in space for the same amount of weight and the same amount of payload is increasing dramatically. The only thing that's happening is that the cost for lift the cost to put satellites and and orbit is dropping dramatically. And so what's happening with those two things is were able to get a lot more organisations putting satellites up there. And what's turning out is that there's a tremendous number of images and sensing capabilities. It's coming down actually more than the humans are able to analyze. And that's where the cloud comes in is that you take and you download this information and then you start using things like machine learning and artificial intelligence and you can see anomalies and point them out to the humans and say, for example, these balls are just showed up. Maybe we should go take a look at that. >> You know, imagery has always been a hot satellite thing. You see Google Earth map three D mapping is getting better. How is that playing into it? Is that a use case for you guys? I mean, you talk about the impact. Is that something we all relate to >> you and I would submit that we are in the early stages of that. It's amazing what we can do with their damaging today. And everybody on their phones get Google maps and all the other things that are out there. But we're in early stages of what we could do with that. So some areas that we're looking at very closely. So, for example, during the California wildfires last year, NASA worked on something to help out the people on the ground. You know, with ground station, what you'll be able to do is do more downloads and get more information than a more real time basis, and you'll actually be able to look at this and say the wildfires are happening in these areas and help the citizens with escape routes and help them understand things that were actually hard to determine from the ground. And so we're looking at this for natural disasters as well as just Data Day solutions. >> It's such an exciting time, and you and your pointing at so many different use cases that have a lot of potential to really be game changers. What keeps you up at night about this, though? I mean, I think that they're as we know, there's a lot of unintended consequences that comes with these new technologies and particularly explosion of these new technologies. What are what are your worries? What what is the future perils that you see? >> So So we definitely are working with these agencies of the federal government and commercial things on making sure that you can sit. You're the data. But again, that was one of the benefits of starting with a ws. We started with security being a primary of part of what we did. And so when when you have ground station, you do a satellite uplink for downlink, and then you immediately tell it where in the world you want the data to be stored. So, for example, we could download, Let's say, in another part of the world, and then you can bring it back to the nine states and store it in your we call a virtual private cloud. It's a way for our customers to be able to control their environment securely. And so we spent a lot of time explain to people how they could do that and how they could do it securely. And so, uh, well, it doesn't keep me awake at night, But we spend a tremendous amount of time working with these organisations, making sure that they are using best practices when they're using our solution. Right? >> Talk about the challenges you mentioned, storing the securely role of policy. We're living in a world now where the confluence of policy science tech people are all kind of exploding and studio innovation but also meet challenges. What are some of the things that you guys are doing? Obeys the bar improving? I mean, I'll say there's early days, so you're seeing areas to improve. What if some of the areas that you're improving on that are being worked on now on impact >> So you mentioned policy side of it. What I'd like Teo say is any time there's a new technology that comes out way. Have to do some catching up from, You know, the policy, the regulator point in front of you right now because the satellite industry is moving so fast. Um, there's a scale issues on. So governments throughout the world are looking at the number of satellites they're going up in, the number of communications are happening, and they're working with that scale on Andi. I I'm very proud to say that they're reacting. They were acting fairly quickly on DH. That's one of the areas that I think we're going to see more on is as this industry evolves, having things like having antennas insert and antennas and satellite certified quickly is one of the things that we need to talk. >> Some base infrastructure challenges mean Consider space kind of infrastructure. At this point, it plenty of room up there currently, but can envision a day with satellites, zillion satellites up there at some point. But that gets set up first. You're saying the posture. The government is pro innovation in this area. >> Oh, you're wasting a lot of interest in that way. We launched ground station governments both here in this country as well as throughout the world, very interested in this on DH. They see the potential on being able to make the satellite's on satellite imagery and detection available. And it's not just for those largest organizations like the governments. But it's also when you commercialize this and what we've made it so that small, medium sized businesses now, Khun, get into this business and do innovative things. >> Question. I want to ask. You know, we're tight on time, Rebecca, but we'll get this out. In your opinion. What? What do you think the modernization of public policy governments means? Because the paint on your definition, what modernization is This seems to be the focus of this conference here, a ws re public sector summit. This is the conversation we're having in other agencies. They want to modernize. >> What does that mean to you? It takes on many things. Many perspectives. What? What I find a lot is modernizations is making helping your workers be more productive. And so we do this with a number of different ways. So when you look at ground station. Really? Benefit of it isn't. Can I get the image? Can I get the data? But how can I do something with it? And so when you start applying machine learning artificial intelligence now you can put a point toe anomalies that are happening. And now you can have the people really focus on the anomalies and not look at a lot of pictures. They're exactly the same. So when you look at a modernization, I think it's some economists with How do we make the workforce that's in place more productive >> and find those missing cows? It's Fred McMillan. Thank you so much for coming on the Q. Thank >> you. It was a pleasure. We've >> got a lot of great mark. We got many more gas. Got Teresa Carlson. Jay Carney? >> Yeah. Yeah. General Keith Alexander, About how date is being used in the military. We got ground station connectivity. I really think this is a great opportunity for io. T wait to see how it progresses. >> Excellent. Thank you. >> Becca. Knight for John Furrier. Stay tuned to the Cube.

>> Live, from Las Vegas, it's theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hey, welcome back everyone. Live, Cube here in Las Vegas for AWS re:Invent. I'm John Furrier with my co-host, Dave Vellante. Day three of wall to wall coverage, holding our voices together, excited for our next guest, Shayn Hawthorne, general manager at AWS, for the exciting project around the Ground Station, partnership with Lockheed Martin. Really kind of outside the box, announced on Tuesday, not at the keynote, but this is a forward thinking real project which satellites can be provisioned like cloud computing resources. Totally innovative, and will change the nature of edge computing, feeding connectivity to anything. So, thanks for joining us. >> Thank you guys for having me. You're right, my voice is going out this week too. We've been doing a lot of talking. (John laughs) >> Great service. This is really compelling, 'cause it changes the nature of the network. You can feed connectivity, 'cause power and connectivity drive everything. Power, you got battery. Connectivity, you got satellite. Totally obvious, now that you look at it, but, not before this. Where did it come from? How did it all start? >> You know, it came from listening to our customers. Our customers have been talking with us and they had a number of challenges in getting the data off of their satellites and down to the ground. So, we listened to these customers and we listened to the challenges they were experiencing in getting their data to the ground, having access to ground stations, having the ability at the network level, to move the data around the world quickly to where they wanted to process it. And then also, having complex business process logic and other things that were required to help them run their satellite downlinks and uplinks. And then finally, the ability to actually have AWS services right there where the data came down into the cloud, so that you could do great things with that data within milliseconds of it hitting the ground. >> So it's a essentially satellite as a service with a back end data capability, data ingestion, analytics, and management capability. That, how'd that idea come about? I mean, it just underscores the scale of AWS. And I'm thinking about other things that you might be able to, where'd the idea come from? How was it germinated? >> Well and actually, let me just say one thing, we actually would call it Ground Station as the service. It's the Ground Station on the surface of the earth that communicates with the satellite. It allows us to get the data off the satellite or send commands up to it. And so, like I was saying, we came up the idea by talking to our customers, and so we went into, I think this is an incredible part of working at Amazon, because we actually follow through with our leadership principals. We worked backwards from the customer. We actually put together a press release and a frequently asked questions document, a PR/FAQ, in a traditional six page format. And we started working it through our leadership and it got all the way to the point that Andy and the senior leadership team within AWS made the decision that they were going to support our idea and the concept and the architecture that we had come up with to meet these customers' requirements, we actually were able to get to that by about March of 2018. By the end of March, Andy had even had us go in and talk with Jeff. He gave us the thumbs up as well, and after six months, we've already procured 24 antennas. We've already built two Ground Stations in the United States and we've downlinked over hundreds of contacts with satellites, bringing Earth imagery down and other test data to prove that this system works. Get it ready for preview. >> It's unbelievable, because you're basically taking the principals of AWS, which is eliminating the heavy lifting, applying that to building Ground Stations, presumably, right, so, the infrastructure that you're building out, do you have partners that you're working with, are there critical players there, that are enabling this? >> Yeah, it's really neat. We've actually had some really great partnerships, both with helping us build AWS Ground Station, as well as partners that helped us learn what the customers need. Let me tell you, first off, about the partnership that we've had with Lockheed Martin to develop a new innovative antenna system that will collaboratively come together with the parabolic reflectors that AWS Ground Station uses. They've been working on this really neat idea that gives them ability to downlink data all over the entire United States in a very resilient way, which means if some of their Ground Stations antennas in Verge don't work, due to man made reasons or due to natural occurrences, then we're actually able to use the rest of the network to still continue to downlink data. And then, we complimentary bring in AWS Astra for certain types of downlinks and then also to provide uplink commanding to other satellites. The other customer partnership that we've worked with was working with the actual customers who are going to use AWS Ground Station, like DigitalGlobe, Black Sky, Capella SAR, HawkEye 360, who all provided valuable inputs to us about exactly what do they need in a Ground Station. They need the ability to rapidly downlink data, they need the ability to pay by the minute so that there are actually able to use variable expense to pay for satellite downlinks instead of capital expenses to go out and build it. And then by doing that, we're able to offer them a product that's 80% cheaper than if they'd had to go out and build a complete network similar to what we built. And, they're able to, like I said before, access great AWS services like Rekognition, or SageMaker, so that they can make sense of the data that they bring down to the Earth. >> It's a big idea and I'm just sort of curious as to, how and if you, sort of, validated it. How'd ya increase the probability that it was actually going to, you know, deliver a business return? Can you talk about that process? >> Well, we were really focused on validating that we could meet customer challenges and really give them the data securely and reliably with great redundancy. So we validated, first off by, we built our antennas and the Ground Stations in the previous software. We finished over a month and a half ago, and we've been rigorously testing it with our customer partners and then letting them validate that the information we've provided back to them was 100% as good as what they would've received on their own network, and we tested it out, and we've actually got a number of pictures and images downloaded over at our kiosk that were all brought in on AWS Ground Station, and its a superb products over there. >> So Shayn, how does it work? You write this press release, this working backwards document, describe that process. Was that process new to you? Had you done it at other companies? How did you find it? Was it a useful process, obviously it was, 'cause you got the outcome you're looking for, but, talk a little bit more about that approach. >> Yeah, it's actually very cool, I've only been at AWS for a year and a half. And so, I would say that my experience at AWS so far completely validates working backwards from customers. We were turned on to the idea by talking to our customers and the challenges they said. I started doing analysis after the job was assigned to me by Dave Nolton, my boss, and I started putting together the first draft of our PR/FAQ, started engaging with customers immediately. Believe it or not, we went through 28 iterations of the PR/FAQ before we even got to Andy. Everybody in our organization took part in helping to make it better, add in, ask hard questions, ensure that we were really thinking this idea through and that we were obsessing on the customer. And then after we got to Andy, and we got through approving that, it probably went through another 28 iterations before we got to Jeff. And then we went through talking with him. He asked additional hard questions to make sure that we were doing the right for the customer and that we were putting together the right kind of product. And finally we've been iterating it on it ever since until we launched it couple of days ago. >> Sounds like you were iterating, raising the bar, and it resonated with customers. >> Totally. And even as part of getting out of it-- >> That's Amazon's language of love. >> And then your engineering resource, you know, if people are asking you hard questions, you obviously need engineering folks to validate that it's doable. At what point do you get that engineering resource, how does that all work? >> Well, it's neat. In my division, Region Services Division, we actually were supporting it completely from within the division, all the way until we got approval from Andy. And then we actually went in and started hiring very good skills. To show you what kind of incredible people we have at Amazon, we only had to hire about 10% space expertise from outside of the company. We were actually able to bring together 80-90% of the needed skills to build AWS Ground Station from people who've been working at Amazon.com and AWS. And we came together, we really learned quickly, we iterated, failed fast, put things together, changed it. And we were able to deliver the product in time. The whole cloth made from our own expertise. >> So just to summarize, from idea to actual, we're going to do this, how long did that take? >> I'd say that took about three months. From idea to making a decision, three months. From decision to have a preview product that we could launch at re:Invent, six months. >> That's unbelievable. >> It is. >> If you think about something of this scope. >> And it was a joy, I mean it was an incredible to be a part of something like this. It was the best work I've ever done in my life. >> Yeah, space is fun. >> It is. >> Shayn, thanks for coming on theCUBE, sharing your story and insight, we love this. We're going to keep following it. And we're going see you guys at the Public Sector Summits, and all the events you guys are at, so, looking forward to seeing and provisioning some satellite. >> I'm looking forward to showing you what we do next. So thank you for having me. >> Great. We'll get a sneak peak. >> Congratulations. >> This is theCUBE here in Las Vegas, we'll be back with more coverage after this short break. (futuristic music)