>>Hey everyone, welcome to the Cube's coverage of AWS Reinvent 2022. Lisa Martin here with you with Subaru ier, one of our alumni who's now the CEO of Aerospike. Sabu. Great to have you on the program. Thank you for joining us. >>Great as always, to be on the cube. Luisa, good to meet you. >>So, you know, every company these days has got to be a data company, whether it's a retailer, a manufacturer, a grocer, a automotive company. But for a lot of companies, data is underutilized, yet a huge asset that is value added. Why do you think companies are struggling so much to make data a value added asset? >>Well, you know, we, we see this across the board when I talk to customers and prospects. There's a desire from the business and from it actually to leverage data to really fuel newer applications, newer services, newer business lines, if you will, for companies. I think the struggle is one, I think one the, you know, the plethora of data that is created, you know, surveys say that over the next three years data is gonna be, you know, by 2025, around 175 zetabytes, right? A hundred and zetabytes of data is gonna be created. And that's really a, a, a growth of north of 30% year over year. But the more important, and the interesting thing is the real time component of that data is actually growing at, you know, 35% cagr. And what enterprises desire is decisions that are made in real time or near real time. >>And a lot of the challenges that do exist today is that either the infrastructure that enterprises have in place was never built to actually manipulate data in real time. The second is really the ability to actually put something in place which can handle spikes yet be cost efficient if you'll, so you can build for really peak loads, but then it's very expensive to operate that particular service at normal loads. So how do you build something which actually works for you, for both you, both users, so to speak? And the last point that we see out there is even if you're able to, you know, bring all that data, you don't have the processing capability to run through that data. So as a result, most enterprises struggle with one, capturing the data, you know, making decisions from it in real time and really operating it at the cost point that they need to operate it at. >>You know, you bring up a great point with respect to real time data access. And I think one of the things that we've learned the last couple of years is that access to real time data, it's not a nice to have anymore. It's business critical for organizations in any industry. Talk about that as one of the challenges that organizations are facing. >>Yeah. When, when, when we started Aerospike, right when the company started, it started with the premise that data is gonna grow, number one, exponentially. Two, when applications open up to the internet, there's gonna be a flood of users and demands on those applications. And that was true primarily when we started the company in the ad tech vertical. So ad tech was the first vertical where there was a lot of data both on the supply side and the demand side from an inventory of ads that were available. And on the other hand, they had like microseconds or milliseconds in which they could make a decision on which ad to put in front of you and I so that we would click or engage with that particular ad. But over the last three to five years, what we've seen is as digitization has actually permeated every industry out there, the need to harness data in real time is pretty much present in every industry. >>Whether that's retail, whether that's financial services, telecommunications, e-commerce, gaming and entertainment. Every industry has a desire. One, the innovative companies, the small companies rather, are innovating at a pace and standing up new businesses to compete with the larger companies in each of these verticals. And the larger companies don't wanna be left behind. So they're standing up their own competing services or getting into new lines of business that really harness and are driven by real time data. So this compelling pressures, one, the customer exp you know, customer experience is paramount and we as customers expect answers in, you know, an instant in real time. And on the other hand, the way they make decisions is based on a large data set because you know, larger data sets actually propel better decisions. So there's competing pressures here, which essentially drive the need. One from a business perspective, two from a customer perspective to harness all of this data in real time. So that's what's driving an inces need to actually make decisions in real or near real time. >>You know, I think one of the things that's been in short supply over the last couple of years is patients we do expect as consumers, whether we're in our business lives, our personal lives that we're going to be getting, be given information and data that's relevant, it's personal to help us make those real time decisions. So having access to real time data is really business critical for organizations across any industries. Talk about some of the main capabilities that modern data applications and data platforms need to have. What are some of the key capabilities of a modern data platform that need to be delivered to meet demanding customer expectations? >>So, you know, going back to your initial question Lisa, around why is data really a high value but underutilized or underleveraged asset? One of the reasons we see is a lot of the data platforms that, you know, some of these applications were built on have been then around for a decade plus and they were never built for the needs of today, which is really driving a lot of data and driving insight in real time from a lot of data. So there are four major capabilities that we see that are essential ingredients of any modern data platform. One is really the ability to, you know, operate at unlimited scale. So what we mean by that is really the ability to scale from gigabytes to even petabytes without any degradation in performance or latency or throughput. The second is really, you know, predictable performance. So can you actually deliver predictable performance as your data size grows or your throughput grows or your concurrent user on that application of service grows? >>It's really easy to build an application that operates at low scale or low throughput or low concurrency, but performance usually starts degrading as you start scaling one of these attributes. The third thing is the ability to operate and always on globally resilient application. And that requires a, a really robust data platform that can be up on a five, nine basis globally, can support global distribution because a lot of these applications have global users. And the last point is, goes back to my first answer, which is, can you operate all of this at a cost point? Which is not prohibitive, but it makes sense from a TCO perspective. Cuz a lot of times what we see is people make choices of data platforms and as ironically their service or applications become more successful and more users join their journey, the revenue starts going up, the user base starts going up, but the cost basis starts crossing over the revenue and they're losing money on the service, ironically, as the service becomes more popular. So really unlimited scale, predictable performance always on, on a globally resilient basis and low tco. These are the four essential capabilities of any modern data platform. >>So then talk to me with those as the four main core functionalities of a modern data platform. How does aerospace deliver that? >>So we were built, as I said, from the from day one to operate at unlimited scale and deliver predictable performance. And then over the years as we work with customers, we build this incredible high availability capability which helps us deliver the always on, you know, operations. So we have customers who are, who have been on the platform 10 years with no downtime for example, right? So we are talking about an amazing continuum of high availability that we provide for customers who operate these, you know, globally resilient services. The key to our innovation here is what we call the hybrid memory architecture. So, you know, going a little bit technically deep here, essentially what we built out in our architecture is the ability on each node or each server to treat a bank of SSDs or solid state devices as essentially extended memory. So you're getting memory performance, but you're accessing these SSDs, you're not paying memory prices, but you're getting memory performance as a result of that. >>You can attach a lot more data to each node or each server in your distributed cluster. And when you kind of scale that across basically a distributed cluster you can do with aerospike, the same things at 60 to 80% lower server count and as a result 60 to 80% lower TCO compared to some of the other options that are available in the market. Then basically, as I said, that's the key kind of starting point to the innovation. We layer around capabilities like, you know, replication change, data notification, you know, synchronous and asynchronous replication. The ability to actually stretch a single cluster across multiple regions. So for example, if you're operating a global service, you can have a single aerospace cluster with one node in San Francisco, one northern New York, another one in London. And this would be basically seamlessly operating. So that, you know, this is strongly consistent. >>Very few no SQL data platforms are strongly consistent or if they are strongly consistent, they will actually suffer performance degradation. And what strongly consistent means is, you know, all your data is always available, it's guaranteed to be available, there is no data lost anytime. So in this configuration that I talked about, if the node in London goes down, your application still continues to operate, right? Your users see no kind of downtime and you know, when London comes up, it rejoins the cluster and everything is back to kind of the way it was before, you know, London left the cluster so to speak. So the op, the ability to do this globally resilient, highly available kind of model is really, really powerful. A lot of our customers actually use that kind of a scenario and we offer other deployment scenarios from a higher availability perspective. So everything starts with HMA or hybrid memory architecture and then we start building out a lot of these other capabilities around the platform. >>And then over the years, what our customers have guided us to do is as they're putting together a modern kind of data infrastructure, we don't live in a silo. So aerospace gets deployed with other technologies like streaming technologies or analytics technologies. So we built connectors into Kafka, pulsar, so that as you're ingesting data from a variety of data sources, you can ingest them at very high ingest speeds and store them persistently into Aerospike. Once the data is in Aerospike, you can actually run spark jobs across that data in a, in a multithreaded parallel fashion to get really insight from that data at really high, high throughput and high speed, >>High throughput, high speed, incredibly important, especially as today's landscape is increasingly distributed. Data centers, multiple public clouds, edge IOT devices, the workforce embracing more and more hybrid these days. How are you ex helping customers to extract more value from data while also lowering costs? Go into some customer examples cause I know you have some great ones. >>Yeah, you know, I think we have, we have built an amazing set of customers and customers actually use us for some really mission critical applications. So, you know, before I get into specific customer examples, let me talk to you about some of kind of the use cases which we see out there. We see a lot of aerospace being used in fraud detection. We see us being used in recommendations and since we use get used in customer data profiles or customer profiles, customer 360 stores, you know, multiplayer gaming and entertainment, these are kind of the repeated use case digital payments. We power most of the digital payment systems across the globe. Specific example from a, from a specific example perspective, the first one I would love to talk about is PayPal. So if you use PayPal today, then you know when you actually paying somebody your transaction is, you know, being sent through aero spike to really decide whether this is a fraudulent transaction or not. >>And when you do that, you know, you and I as a customer not gonna wait around for 10 seconds for PayPal to say yay or me, we expect, you know, the decision to be made in an instant. So we are powering that fraud detection engine at PayPal for every transaction that goes through PayPal before us, you know, PayPal was missing out on about 2% of their SLAs, which was essentially millions of dollars, which they were losing because, you know, they were letting transactions go through and taking the risk that it, it's not a fraudulent transaction with the aerospace. They can now actually get a much better sla and the data set on which they compute the fraud score has gone up by, you know, several factors. So by 30 x if you will. So not only has the data size that is powering the fraud engine actually grown up 30 x with Aerospike. Yeah. But they're actually making decisions in an instant for, you know, 99.95% of their transactions. So that's, >>And that's what we expect as consumers, right? We want to know that there's fraud detection on the swipe regardless of who we're interacting with. >>Yes. And so that's a, that's a really powerful use case and you know, it's, it's a great customer, great customer success story. The other one I would talk about is really Wayfair, right? From retail and you know, from e-commerce. So everybody knows Wayfair global leader in really, you know, online home furnishings and they use us to power their recommendations engine and you know, it's basically if you're purchasing this, people who bought this but also bought these five other things, so on and so forth, they have actually seen the card size at checkout go by up to 30% as a result of actually powering their recommendations in G by through Aerospike. And they, they were able to do this by reducing the server count by nine x. So on one ninth of the servers that were there before aerospace, they're now powering their recommendation engine and seeing card size checkout go up by 30%. Really, really powerful in terms of the business outcome and what we are able to, you know, drive at Wayfair >>Hugely powerful as a business outcome. And that's also what the consumer wants. The consumer is expecting these days to have a very personalized, relevant experience that's gonna show me if I bought this, show me something else that's related to that. We have this expectation that needs to be really fueled by technology. >>Exactly. And you know, another great example you asked about, you know, customer stories, Adobe, who doesn't know Adobe, you know, they, they're on a, they're on a mission to deliver the best customer experience that they can and they're talking about, you know, great customer 360 experience at scale and they're modernizing their entire edge compute infrastructure to support this. With Aerospike going to Aerospike, basically what they have seen is their throughput go up by 70%, their cost has been reduced by three x. So essentially doing it at one third of the cost while their annual data growth continues at, you know, about north of 30%. So not only is their data growing, they're able to actually reduce their cost to actually deliver this great customer experience by one third to one third and continue to deliver great customer 360 experience at scale. Really, really powerful example of how you deliver Customer 360 in a world which is dynamic and you know, on a dataset which is constantly growing at north, north of 30% in this case. >>Those are three great examples, PayPal, Wayfair, Adobe talking about, especially with Wayfair when you talk about increasing their cart checkout sizes, but also with Adobe increasing throughput by over 70%. I'm looking at my notes here. While data is growing at 32%, that's something that every organization has to contend with data growth is continuing to scale and scale and scale. >>Yep. I, I'll give you a fun one here. So, you know, you may not have heard about this company, it's called Dream 11 and it's a company based out of India, but it's a very, you know, it's a fun story because it's the world's largest fantasy sports platform and you know, India is a nation which is cricket crazy. So you know, when, when they have their premier league going on, you know, there's millions of users logged onto the dream alone platform building their fantasy lead teams and you know, playing on that particular platform, it has a hundred million users, a hundred million plus users on the platform, 5.5 million concurrent users and they have been growing at 30%. So they are considered a, an amazing success story in, in terms of what they have accomplished and the way they have architected their platform to operate at scale. And all of that is really powered by aerospace where think about that they are able to deliver all of this and support a hundred million users, 5.5 million concurrent users all with you know, 99 plus percent of their transactions completing in less than one millisecond. Just incredible success story. Not a brand that is you know, world renowned but at least you know from a what we see out there, it's an amazing success story of operating at scale. >>Amazing success story, huge business outcomes. Last question for you as we're almost out of time is talk a little bit about Aerospike aws, the partnership GRAVITON two better together. What are you guys doing together there? >>Great partnership. AWS has multiple layers in terms of partnerships. So you know, we engage with AWS at the executive level. They plan out, really roll out of new instances in partnership with us, making sure that, you know, those instance types work well for us. And then we just released support for Aerospike on the graviton platform and we just announced a benchmark of Aerospike running on graviton on aws. And what we see out there is with the benchmark, a 1.6 x improvement in price performance and you know, about 18% increase in throughput while maintaining a 27% reduction in cost, you know, on graviton. So this is an amazing story from a price performance perspective, performance per wat for greater energy efficiencies, which basically a lot of our customers are starting to kind of talk to us about leveraging this to further meet their sustainability target. So great story from Aero Aerospike and aws, not just from a partnership perspective on a technology and an executive level, but also in terms of what joint outcomes we are able to deliver for our customers. >>And it sounds like a great sustainability story. I wish we had more time so we would talk about this, but thank you so much for talking about the main capabilities of a modern data platform, what's needed, why, and how you guys are delivering that. We appreciate your insights and appreciate your time. >>Thank you very much. I mean, if, if folks are at reinvent next week or this week, come on and see us at our booth. We are in the data analytics pavilion. You can find us pretty easily. Would love to talk to you. >>Perfect. We'll send them there. So Ira, thank you so much for joining me on the program today. We appreciate your insights. >>Thank you Lisa. >>I'm Lisa Martin. You're watching The Cubes coverage of AWS Reinvent 2022. Thanks for watching.

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

(bright upbeat music) >> Hey, friends. Welcome back to theCUBE's Live coverage of AWS re:Invent 2022 in Sin City. We are so excited to be here with tens of thousands of people. This is our third day of coverage, really the second full day of the show, but we started Monday night. You're going to get wall-to-wall coverage on theCUBE. You probably know that because you've been watching. I'm Lisa Martin and I'm here with Paul Gill. Paul, this is great. We have had such great conversations. We've been talking a lot about data. Every company is a data company, has to be a data company. We've been talking about developers, the developer experience, and how that's so influential in business decisions for businesses in every industry. >> And it's a key element of what's going on here on the floor at re:Invent is developers, the theme of developers just permeates the show. Lots and lots of boots here devoted to DevOps and Agile approaches. And certainly that is one of the things that the Cloud enables is your team to rethink the way they develop software, and that's what we're going to talk about next. >> That is what we're going to talk about next. We have two guests from Split. split.io is the URL if you want to check it out. Chris Demars joins us Developer advocate. Chris, great to have you and PaaS, VP of Engineering guys thank you so much for joining us on the program. >> Thank you for having us. >> Thank you for having us. >> Talk to us Pierre, we'll start with you. For the audience that might not know Split what does the company do? What's the value in it for customers? What are you all about? >> Sure. So in very simple terms, for those who are familiar, we do feature flags, feature management and experimentation. And essentially that two essential feature of the Agile transformation as you were mentioning and elements that really helps getting as much art we can from the team in term of productivity and in term of impact. And we basically help with those elements. And so that's a very short... >> 'Excellent, very nice. Chris, you were saying before we went live you do a lot of speaking at conferences, you're often in front of large audiences. As the developer advocate, what are some of the key requirements you're hearing from the developer community that organizations need to be encompassing? >> I think community is key. Like community is at the forefront of developer advocacy and developer relations. Like you want to go where the developers are and developers want to hear those stories in those personalized pieces of the puzzle. And when you're able to talk about modern Web and software technology and loop in product with that and still keep talking about those things and bring that to them, like that is on top of the list when it comes to developer advocacy and being embedded within the developer community. >> Lisa: Yeah. >> Tell us about feature flags, because I would assume that for our viewers who are not developers, who are not familiar with Agile technologies, the Agile approaches that might be, may be a new term, what are feature flags? How do you use them? >> Sure, I can start with that. So feature flag is a tool that you embed in your code that allows you to control the activation of your code essentially. And that's allows you to really validate things in a much better and solve way and also attach measurement to it. So, when you're writing your new feature, you just put essentially an if statement around it, if my feature flag is on, then I actually do all those things with soft, then I don't do any of those things and then within our platform, then you can control the activation. Do you want to turn it on for yourself just to try it out? Do you want your QA team to start validating it? Do you want 5% of your users 10%? And start seeing how they interacting with the product. That's what feature flag is. >> It's an amazing piece of any part of the stack, right? 'Cause I'm a Web accessibility and an UI specialist and being able to control the UI with a feature flag and being able to turn on and off those features based on percentage, locale, all of those things. It's very, very powerful. >> What are some of the scenarios which you would use feature flags? You have been testing? >> Yeah, yeah. We actually, you can imagine we use it for pretty much everything. So, as Chris was saying, in the front-end, everything you want to change, you basically can validate and attach measurements. So you can do AB testing, so you can see the impact, you can see if there is a change in performance. We use it also for a lot of backend services and changes and a lot of even infrastructure changes where we can control the traffic and where it goes. So we can validate that things are operating the way that they should before we fully done the market I think. >> 'It can be as small as, you know having a checkout button here and then writing an AB test and running an experiment and moving that checkout button somewhere else because then you can get conversion rates and see which one performed better to a certain amount of people and whatever performed better, that's the feature you would go with. >> Chris, talk about the value of the impact in feature flags for the developer from a developer experience perspective, a productivity perspective. >> So I think that having that feature and being able to write that UI, let's say that you have a checkout button, right? And there's specific content there's verbiage on that checkout button. And then let's say that another team within the organization wants to change that because the conversion is different. You can make those changes, still have it in production and then have it tested. So you don't have to cut specific branches or like test URLs to give to QA, you can do all of that behind that flag. And then once everything is good to go, push it out there and then based on those metrics and that data, see which one performs better and then that's the one that you would go with. >> One of the things with feature flag and it goes to like our main theme of 'What a Release, What a Relief' is that it gives autonomy to the teams and to the developers, enable them to move independently from others. So the deployment can go but their code is not activated until they decide to. And so, they are not impeding anybody else. It makes releases a lot safer, a lot simpler and it gives a lot more speed to everybody because when you do releases with five teams, 10 teams, pushing the code at the same time, you have such a high-risk of breaking something that it's you know... So it's a huge effort and it requires a lot of attention from a lot of people. If anything happens, all those teams needs to investigate. When you decouple all those things, the deployments are essentially not doing anything per se until every individual team activate those things independently. So if anything goes wrong, only them are affected and they don't have to depend on anybody else to get their thing out. So it really helps them making their life a lot safer and gives them a lot more speed because they have autonomy. >> So, why come to re:Invent? What do you get with this audience that you don't get elsewhere? >> Why to re:Invent? I think like re:Invent in the Cloud and AWS is a lot about getting speed to companies to build better product and faster. And essentially like the tool we provide and the technology and the platform we provide is really at the heart of that in itself. And so that's why we feel we have really great conversation with all the people on the floor. >> 'the people who have the right mindset for adopting... >> For me, it's very much community and networking, I love developer community and just community in general is my lifeblood. That's why I travel so much and I talk about these things and I'm with people and if it's not about the products, the story and the story is what gets people. That's why I love being here and being with my team and it's amazing. >> And what is that story? If you had an elevator pitch to give, what would you tell me? >> Hoo, if you were in a late release or deploy at night. I've been there, I'm sure you've been there, it doesn't matter what you're doing. We don't want be up until two, three in the morning doing those things, right? Our product helps alleviate those stresses. And you talking about accessibility, what I do, you know, a big piece of that are hidden impairments like anxiety will stress and anxiety go hand in hand and you want to alleviate that all across the board for everybody involved. >> As you see organizations shift Agile technologies and to parallel development and continuous release cycles, what are some of the biggest barriers they encounter in changing that mindset? >> Ooh, what do you think? >> It depends on where they are in the organization. The Agile transformation is a journey and it's also a change of mindset, it's a change of process. So depending on where they are then they might have some areas where they need a little bit more effort in those directions. What we see is that feature flag just the control of the layout. It's usually something that's fairly easily adopted. Thinking about measurement and attaching measurement to it is often something that requires a little bit more thinking. Like engineers are not really used to thinking about AB testing. It feels like more of a product management thing but AB testing is important also for performance informations like errors and all those things. There is a lot of risk management to be done. We do that through monitoring with APMs, but with feature flag and with Split, you can do that at a feature level and it really gives a great insight. And that's usually something that takes a little bit more digestion from the developers to really get their mind around it and get to it. But there's a lot of value to it. >> I'm looking at the split I/O website and I like the tagline shorten time from code to customer. As customers in any industry, as consumers, we have this expectation that we can get whatever we want anytime 24 by 7 and it's going to be a relevant experience. So it sounds to me like from a speed perspective, there's a lot of business impact that Split can help organizations make from getting releases faster, getting cut faster time-to-market, delivering what customers expect because we all expect real-time these days. Nobody wants to wait. >> Yeah, that's right. Yeah, I think that has to do with the going back to the decoupling of things that, you know... Not having to go through so many teams to have it tested and getting away from all the meetings about meetings to review the metrics, right? We all love meetings about meetings. >> No. (laughs loudly) >> Right, exactly, exactly. So being able to take that away and being able to push all of that stuff into production, getting it tested while it's in production and then being able to turn those features on, it's already there without having to do another deployment. And I think, like that's really powerful to me at least. >> Does your solution have value at the security level as well? >> Yes. So that's one of the particularity on the way we do things is like the way you control the feature flag, you have kind of two ways of doing it. Either the piece of code, the SDKs that we provide, the library we provide, you that you put in your code could come back to our platform and check. The way we do it is we send the rules back to the SDK so the whole evaluation is local. The evaluation is extremely fast and it's very secure because it's all happening within your environment. You never have to share any information, no PI whatsoever, contrary it to some of the other tools that you might find on the market. >> So the theme of the booth is 'What a Release, What a Relief'. What are some of the things that you're hearing as you're engaging folks on the show floor this week? >> Oh, what is Aura Photography and can I take a picture of. (everyone laughs loudly) I think just a lot of the stresses of... They're like the release cycle and you know, having to go through so many teams. I feel like that's a common theme that I've heard of. >> Yeah, we see a number of teams organization that still have like really big deployments with like a lot of teams basically coming together, pushing the code together, and there's a lot of pain in it. It's like, it's a huge effort by huge teams. You get 10, 20 people that have to have watch over it at always weird hours, and I think there is a lot of pain to that and that resonate a lot with people. And when we talk about monitoring at the future level, that also helps a lot. Like I was part of organizations before where we had a dedicated staff engineer to just monitor and fix performance on a daily basis because it's such a huge problem and it affects so much the performance of the company. And so essentially, you have this person that tries to look at is a performance being degraded today with the deployment of yesterday and what went out yesterday and you have so many things that went out. It's so hard to control. With what we provide, we tell you exactly which feature flag is responsible for the degradation. And so, you don't need that person to focus on that anymore. And you can focus on delivering value a lot better. >> I think it also might take away the need for extensive release notebooks and playbooks, right? 'Cause when you do bring all those teams together, it's certain people that are in that meeting and there's a PDF saying, all right, we check this off the list, we check this off the list. I think that might alleviate some of that overhead as well. >> Streamlining processes, process efficiencies, workforce productivity improvements, big impact. >> And that gets code quicker to the user. >> You talk about decoupling deploy from release. What do you mean by that? What's the value? >> So the deployment in my definition is essentially getting the code out to production. The release is activating the code in production. And often people do both of those things at the same time, right? But there's a huge risk when you do that because if anything goes wrong, now you need to revert everything which is not a short operation often and takes a lot of effort. And so now, if you can basically push your code to production but separate the activation of it, the release of it, then it goes a lot faster. It's a lot. You have a lot of autonomy and decoupling and if anything goes wrong, it's the click of a button and it's off. So like there's a lot of safety that comes with it and we know that any outages as a high cost for all the companies. So it's like, if you can reduce the outage to like five seconds... >> Right. >> It's a lot better than basically several hours. >> Can you talk about the value out of Split versus DIY and where are most of your customers in this process? Do they have a bunch of tools, a bunch of processes, a bunch of teams, and you're really helping them consolidate streamline? >> The one thing I hear a lot is we rolled our own AB testing and feature flagging system, but some of the issues I've seen and I've heard are that they don't have all those metrics or they have to work with a specific data team to get those metrics. And then you go back to having those meetings about meetings... >> Lisa: Dependencies. >> Right, you have a data team that's putting together a report that is then presented to you and then that's got to be presented to a stakeholder and then that stakeholder makes a decision whether to turn on feature A or feature B, right? Our product from my understanding is we have those metrics already built in and you can have that at your disposal. >> Yeah, the other thing I would add to that is like we see a number of people, they start on the feature flag journey just because they have a high risk thing that they need to put out. So they do the minimal thing to basically control it somehow, but it works only in one part of the stacks. They can't basically leverage it anywhere else and it's very limited in capability so that it just serve the purpose that was needed at that time. They don't have a dedicated team to manage it. So it just there, but it's very constrained and it's not supported effectively. The other thing is like for those companies is like they have a question to ask themselves. It's like do they want to invest resources in managing that kind of tool or is it not so core to their business that they want essentially to have vendor deal with it at a much lower price and they would have to invest resources for them to support it, and... >> Sounds like feature flags are kind of a team building. Have you have a team building dimension to them? >> Yeah. >> Yeah. >> It takes a team for sure. >> Yeah, and then once you add like AB testing and the feature flag, it's the collaboration between product management and engineering. It can go even further. Like two executives like to basically, you know, view the impact, understand the impact. So it goes from the control to the risk management to the product and to the impact and measuring the flow of delivery and the communication around it. >> Here we are at re:Invent, so many thousands of people as I mentioned, we're on the second full-day of the event. What have you heard from AWS that really excites you about being in their ecosystem? Any news in particular that jumps out at you that really speaks to improving that developer experience as if we've heard a lot of focus on the developer? >> Chris: Yeah, I haven't heard much, have you? >> So, I arrived yesterday, I haven't followed yet all the announcement, I'm just like, >> there's so many- >> on the news, yeah, yeah. >> So I'm on the booth at the same time. >> I stopped counting at 15 during the Keynote this morning. >> Many of them just can't keep up, there's so much happening at one time's so much. >> This event is a can of content, can of news re:Invent. It is hard. But yesterday they were spent so much time talking about data and how... And I always think every company today has to be a data company, have to be a software company, we were just talking with Capital One and they think of themselves as a technology company that does banking. And sometimes, I'll talk with retailers that think of themselves as technology companies that do retail and they love that but that's what companies like Split have to enable these days. It's companies to become technology companies, deliver code faster to customer because the customer's demanding it. We're not going to want less stuff slower. >> Yeah, I mean it's so essential I think for me like I joined Split because of that premises. Like every company now is a software company and every company has really to compete in innovation. You know all those banks, Capital One like we see it a lot in the financial industry where our message resonates extremely strongly is really in a high-competitive environment and they have to be innovative and innovation comes when people have speed and autonomy. And if you basically provide that to teams and the tools to basically get some signals and some quick feedback loop, that's how you get innovation. Like you can't decide what to build but you can basically provide the tools to enable them to think about. >> Right, you can experiment more flexibly right, faster. >> And developers have to be empowered, right? >> Yes. >> I think that's the probably one of the number one messages I've heard at all the shows we've done this year. How influential the developer is in the direction of the business. >> Autonomy and empowerment are two main factors 'cause I'm a front end developer at heart and I want to work on cool stuff and we're doing cool stuff. Like we are doing cool stuff. We can't talk about all of it, right? But I think we're doing a lot of cool things at Split and I'm really stoked to be a part of the team and grow developer relations, grow developer advocacy and be along for the journey. >> Yeah, I love that. Last question for both of you, same question. If you had a bumper sticker and you were going to put it on a fancy shiny new car, car of your choice about Split, what would it say? Pierre I'll start with you then Chris. >> Bumper sticker. >> On the spot question. >> On the question, (everyone laughs happily) I mean the easy answer is probably written on my t-shirt. Like, you know, 'What a Release, What a Relief'. I think that the first step for teams is like, you can have a message that's very like even further, you know, the Agile transformation is a journey and I basically tell people, you need to first crawl, walk and run and I think the 'What a Release, What a Relief' is a good step to like getting to the working. And I think like that would be the first bumper sticker before I get to the further one about AP testing and innovative. >> Love it. Chris, what would your bumper sticker say? >> It would say Split software, feature flags for the masses. Hard stop. >> Mic drop. >> Done. >> Awesome guys, thank you so much for joining Paul and me on the program. It's been outstanding introducing Split to our audience, what you do, how you're impacting the developer experience and ultimately, the business and the end customer on the backend who just wants things to work. We appreciate your insights, we appreciate your time. >> Thanks so much for having us. >> Appreciate it. >> Our pleasure. For our guests and Paul Gillin, I'm Lisa Martin. You're watching theCUBE, which you know is the leader in live enterprise and emerging tech coverage. (bright upbeat music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

>> And it'll be the fastest 15 minutes of your day from there. >> In three- >> We go Lisa. >> Wait. >> Yes >> Wait, wait, wait. I'm sorry I didn't pin the right speed. >> Yap, no, no rush. >> There we go. >> The beauty of not being live. >> I think, in the background. >> Fantastic, you all ready to go there, Lisa? >> Yeah. >> We are speeding around the horn and we are coming to you in five, four, three, two. >> Hey everyone, welcome to theCUBE's coverage of AWS re:Invent 2022. Lisa Martin here with you with Subbu Iyer one of our alumni who's now the CEO of Aerospike. Subbu, great to have you on the program. Thank you for joining us. >> Great as always to be on theCUBE Lisa, good to meet you. >> So, you know, every company these days has got to be a data company, whether it's a retailer, a manufacturer, a grocer, a automotive company. But for a lot of companies, data is underutilized yet a huge asset that is value added. Why do you think companies are struggling so much to make data a value added asset? >> Well, you know, we see this across the board. When I talk to customers and prospects there is a desire from the business and from IT actually to leverage data to really fuel newer applications, newer services newer business lines if you will, for companies. I think the struggle is one, I think one the, the plethora of data that is created. Surveys say that over the next three years data is going to be you know by 2025 around 175 zettabytes, right? A hundred and zettabytes of data is going to be created. And that's really a growth of north of 30% year over year. But the more important and the interesting thing is the real time component of that data is actually growing at, you know 35% CAGR. And what enterprises desire is decisions that are made in real time or near real time. And a lot of the challenges that do exist today is that either the infrastructure that enterprises have in place was never built to actually manipulate data in real time. The second is really the ability to actually put something in place which can handle spikes yet be cost efficient to fuel. So you can build for really peak loads, but then it's very expensive to operate that particular service at normal loads. So how do you build something which actually works for you for both users, so to speak. And the last point that we see out there is even if you're able to, you know bring all that data you don't have the processing capability to run through that data. So as a result, most enterprises struggle with one capturing the data, making decisions from it in real time and really operating it at the cost point that they need to operate it at. >> You know, you bring up a great point with respect to real time data access. And I think one of the things that we've learned the last couple of years is that access to real time data it's not a nice to have anymore. It's business critical for organizations in any industry. Talk about that as one of the challenges that organizations are facing. >> Yeah, when we started Aerospike, right? When the company started, it started with the premise that data is going to grow, number one exponentially. Two, when applications open up to the internet there's going to be a flood of users and demands on those applications. And that was true primarily when we started the company in the ad tech vertical. So ad tech was the first vertical where there was a lot of data both on the supply set and the demand side from an inventory of ads that were available. And on the other hand, they had like microseconds or milliseconds in which they could make a decision on which ad to put in front of you and I so that we would click or engage with that particular ad. But over the last three to five years what we've seen is as digitization has actually permeated every industry out there the need to harness data in real time is pretty much present in every industry. Whether that's retail, whether that's financial services telecommunications, e-commerce, gaming and entertainment. Every industry has a desire. One, the innovative companies, the small companies rather are innovating at a pace and standing up new businesses to compete with the larger companies in each of these verticals. And the larger companies don't want to be left behind. So they're standing up their own competing services or getting into new lines of business that really harness and are driven by real time data. So this compelling pressures, one, you know customer experience is paramount and we as customers expect answers in you know an instant, in real time. And on the other hand, the way they make decisions is based on a large data set because you know larger data sets actually propel better decisions. So there's competing pressures here which essentially drive the need one from a business perspective, two from a customer perspective to harness all of this data in real time. So that's what's driving an incessant need to actually make decisions in real or near real time. >> You know, I think one of the things that's been in short supply over the last couple of years is patience. We do expect as consumers whether we're in our business lives our personal lives that we're going to be getting be given information and data that's relevant it's personal to help us make those real time decisions. So having access to real time data is really business critical for organizations across any industries. Talk about some of the main capabilities that modern data applications and data platforms need to have. What are some of the key capabilities of a modern data platform that need to be delivered to meet demanding customer expectations? >> So, you know, going back to your initial question Lisa around why is data really a high value but underutilized or under-leveraged asset? One of the reasons we see is a lot of the data platforms that, you know, some of these applications were built on have been then around for a decade plus. And they were never built for the needs of today, which is really driving a lot of data and driving insight in real time from a lot of data. So there are four major capabilities that we see that are essential ingredients of any modern data platform. One is really the ability to, you know, operate at unlimited scale. So what we mean by that is really the ability to scale from gigabytes to even petabytes without any degradation in performance or latency or throughput. The second is really, you know, predictable performance. So can you actually deliver predictable performance as your data size grows or your throughput grows or your concurrent user on that application of service grows? It's really easy to build an application that operates at low scale or low throughput or low concurrency but performance usually starts degrading as you start scaling one of these attributes. The third thing is the ability to operate and always on globally resilient application. And that requires a really robust data platform that can be up on a five nine basis globally, can support global distribution because a lot of these applications have global users. And the last point is, goes back to my first answer which is, can you operate all of this at a cost point which is not prohibitive but it makes sense from a TCO perspective. 'Cause a lot of times what we see is people make choices of data platforms and as ironically their service or applications become more successful and more users join their journey the revenue starts going up, the user base starts going up but the cost basis starts crossing over the revenue and they're losing money on the service, ironically as the service becomes more popular. So really unlimited scale predictable performance always on a globally resilient basis and low TCO. These are the four essential capabilities of any modern data platform. >> So then talk to me with those as the four main core functionalities of a modern data platform, how does Aerospike deliver that? >> So we were built, as I said from day one to operate at unlimited scale and deliver predictable performance. And then over the years as we work with customers we build this incredible high availability capability which helps us deliver the always on, you know, operations. So we have customers who are who have been on the platform 10 years with no downtime for example, right? So we are talking about an amazing continuum of high availability that we provide for customers who operate these, you know globally resilient services. The key to our innovation here is what we call the hybrid memory architecture. So, you know, going a little bit technically deep here essentially what we built out in our architecture is the ability on each node or each server to treat a bank of SSDs or solid-state devices as essentially extended memory. So you're getting memory performance but you're accessing these SSDs. You're not paying memory prices but you're getting memory performance. As a result of that you can attach a lot more data to each node or each server in a distributed cluster. And when you kind of scale that across basically a distributed cluster you can do with Aerospike the same things at 60 to 80% lower server count. And as a result 60 to 80% lower TCO compared to some of the other options that are available in the market. Then basically, as I said that's the key kind of starting point to the innovation. We lay around capabilities like, you know replication, change data notification, you know synchronous and asynchronous replication. The ability to actually stretch a single cluster across multiple regions. So for example, if you're operating a global service you can have a single Aerospike cluster with one node in San Francisco one node in New York, another one in London and this would be basically seamlessly operating. So that, you know, this is strongly consistent, very few no SQL data platforms are strongly consistent or if they are strongly consistent they will actually suffer performance degradation. And what strongly consistent means is, you know all your data is always available it's guaranteed to be available there is no data lost any time. So in this configuration that I talked about if the node in London goes down your application still continues to operate, right? Your users see no kind of downtime and you know, when London comes up it rejoins the cluster and everything is back to kind of the way it was before, you know London left the cluster so to speak. So the ability to do this globally resilient highly available kind of model is really, really powerful. A lot of our customers actually use that kind of a scenario and we offer other deployment scenarios from a higher availability perspective. So everything starts with HMA or Hybrid Memory Architecture and then we start building a lot of these other capabilities around the platform. And then over the years what our customers have guided us to do is as they're putting together a modern kind of data infrastructure, we don't live in the silo. So Aerospike gets deployed with other technologies like streaming technologies or analytics technologies. So we built connectors into Kafka, Pulsar, so that as you're ingesting data from a variety of data sources you can ingest them at very high ingest speeds and store them persistently into Aerospike. Once the data is in Aerospike you can actually run Spark jobs across that data in a multi-threaded parallel fashion to get really insight from that data at really high throughput and high speed. >> High throughput, high speed, incredibly important especially as today's landscape is increasingly distributed. Data centers, multiple public clouds, Edge, IoT devices, the workforce embracing more and more hybrid these days. How are you helping customers to extract more value from data while also lowering costs? Go into some customer examples 'cause I know you have some great ones. >> Yeah, you know, I think, we have built an amazing set of customers and customers actually use us for some really mission critical applications. So, you know, before I get into specific customer examples let me talk to you about some of kind of the use cases which we see out there. We see a lot of Aerospike being used in fraud detection. We see us being used in recommendations engines we get used in customer data profiles, or customer profiles, Customer 360 stores, you know multiplayer gaming and entertainment. These are kind of the repeated use case, digital payments. We power most of the digital payment systems across the globe. Specific example from a specific example perspective the first one I would love to talk about is PayPal. So if you use PayPal today, then you know when you're actually paying somebody your transaction is, you know being sent through Aerospike to really decide whether this is a fraudulent transaction or not. And when you do that, you know, you and I as a customer are not going to wait around for 10 seconds for PayPal to say yay or nay. We expect, you know, the decision to be made in an instant. So we are powering that fraud detection engine at PayPal. For every transaction that goes through PayPal. Before us, you know, PayPal was missing out on about 2% of their SLAs which was essentially millions of dollars which they were losing because, you know, they were letting transactions go through and taking the risk that it's not a fraudulent transaction. With Aerospike they can now actually get a much better SLA and the data set on which they compute the fraud score has gone up by you know, several factors. So by 30X if you will. So not only has the data size that is powering the fraud engine actually gone up 30X with Aerospike but they're actually making decisions in an instant for, you know, 99.95% of their transactions. So that's- >> And that's what we expect as consumers, right? We want to know that there's fraud detection on the swipe regardless of who we're interacting with. >> Yes, and so that's a really powerful use case and you know, it's a great customer success story. The other one I would talk about is really Wayfair, right, from retail and you know from e-commerce. So everybody knows Wayfair global leader in really in online home furnishings and they use us to power their recommendations engine. And you know it's basically if you're purchasing this, people who bought this also bought these five other things, so on and so forth. They have actually seen their cart size at checkout go up by up to 30%, as a result of actually powering their recommendations engine through Aerospike. And they were able to do this by reducing the server count by 9X. So on one ninth of the servers that were there before Aerospike, they're now powering their recommendations engine and seeing cart size checkout go up by 30%. Really, really powerful in terms of the business outcome and what we are able to, you know, drive at Wayfair. >> Hugely powerful as a business outcome. And that's also what the consumer wants. The consumer is expecting these days to have a very personalized relevant experience that's going to show me if I bought this show me something else that's related to that. We have this expectation that needs to be really fueled by technology. >> Exactly, and you know, another great example you asked about you know, customer stories, Adobe. Who doesn't know Adobe, you know. They're on a mission to deliver the best customer experience that they can. And they're talking about, you know great Customer 360 experience at scale and they're modernizing their entire edge compute infrastructure to support this with Aerospike. Going to Aerospike basically what they have seen is their throughput go up by 70%, their cost has been reduced by 3X. So essentially doing it at one third of the cost while their annual data growth continues at, you know about north of 30%. So not only is their data growing they're able to actually reduce their cost to actually deliver this great customer experience by one third to one third and continue to deliver great Customer 360 experience at scale. Really, really powerful example of how you deliver Customer 360 in a world which is dynamic and you know on a data set which is constantly growing at north of 30% in this case. >> Those are three great examples, PayPal, Wayfair, Adobe, talking about, especially with Wayfair when you talk about increasing their cart checkout sizes but also with Adobe increasing throughput by over 70%. I'm looking at my notes here. While data is growing at 32%, that's something that every organization has to contend with data growth is continuing to scale and scale and scale. >> Yap, I'll give you a fun one here. So, you know, you may not have heard about this company it's called Dream11 and it's a company based out of India but it's a very, you know, it's a fun story because it's the world's largest fantasy sports platform. And you know, India is a nation which is cricket crazy. So you know, when they have their premier league going on and there's millions of users logged onto the Dream11 platform building their fantasy league teams and you know, playing on that particular platform, it has a hundred million users a hundred million plus users on the platform, 5.5 million concurrent users and they have been growing at 30%. So they are considered an amazing success story in terms of what they have accomplished and the way they have architected their platform to operate at scale. And all of that is really powered by Aerospike. Think about that they're able to deliver all of this and support a hundred million users 5.5 million concurrent users all with, you know 99 plus percent of their transactions completing in less than one millisecond. Just incredible success story. Not a brand that is, you know, world renowned but at least you know from what we see out there it's an amazing success story of operating at scale. >> Amazing success story, huge business outcomes. Last question for you as we're almost out of time is talk a little bit about Aerospike AWS the partnership Graviton2 better together. What are you guys doing together there? >> Great partnership. AWS has multiple layers in terms of partnerships. So, you know, we engage with AWS at the executive level. They plan out, really roll out of new instances in partnership with us, making sure that, you know those instance types work well for us. And then we just released support for Aerospike on the Graviton platform and we just announced a benchmark of Aerospike running on Graviton on AWS. And what we see out there is with the benchmark a 1.6X improvement in price performance. And you know about 18% increase in throughput while maintaining a 27% reduction in cost, you know, on Graviton. So this is an amazing story from a price performance perspective, performance per watt for greater energy efficiencies, which basically a lot of our customers are starting to kind of talk to us about leveraging this to further meet their sustainability target. So great story from Aerospike and AWS not just from a partnership perspective on a technology and an executive level, but also in terms of what joint outcomes we are able to deliver for our customers. >> And it sounds like a great sustainability story. I wish we had more time so we would talk about this but thank you so much for talking about the main capabilities of a modern data platform, what's needed, why, and how you guys are delivering that. We appreciate your insights and appreciate your time. >> Thank you very much. I mean, if folks are at re:Invent next week or this week come on and see us at our booth and we are in the data analytics pavilion and you can find us pretty easily. Would love to talk to you. >> Perfect, we'll send them there. Subbu Iyer, thank you so much for joining me on the program today. We appreciate your insights. >> Thank you Lisa. >> I'm Lisa Martin, you're watching theCUBE's coverage of AWS re:Invent 2022. Thanks for watching. >> Clear- >> Clear cutting. >> Nice job, very nice job.

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

>> From the Cube studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While the precise direction of VMware's future is unknown, given the plan Broadcom acquisition, one thing is clear. The topic of what Broadcom plans will not be the main focus of the agenda at the upcoming VMware Explore event next week in San Francisco. We believe that despite any uncertainty, VMware will lay out for its customers what it sees as its future. And that future is multi-cloud or cross-cloud services, what we call Supercloud. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we drill into the latest survey data on VMware from ETR. And we'll share with you the next iteration of the Supercloud definition based on feedback from dozens of contributors. And we'll give you our take on what to expect next week at VMware Explorer 2022. Well, VMware is maturing. You can see it in the numbers. VMware had a solid quarter just this week, which was announced beating earnings and growing the top line by 6%. But it's clear from its financials and the ETR data that we're showing here that VMware's Halcion glory days are behind it. This chart shows the spending profile from ETR's July survey of nearly 1500 IT buyers and CIOs. The survey included 722 VMware customers with the green bars showing elevated spending momentum, ie: growth, either new or growing at more than 6%. And the red bars show lower spending, either down 6% or worse or defections. The gray bars, that's the flat spending crowd, and it really tells a story. Look, nobody's throwing away their VMware platforms. They're just not investing as rapidly as in previous years. The blue line shows net score or spending momentum and subtracts the reds from the greens. The yellow line shows market penetration or pervasiveness in the survey. So the data is pretty clear. It's steady, but it's not remarkable. Now, the timing of the acquisition, quite rightly, is quite good, I would say. Now, this next chart shows the net score and pervasiveness juxtaposed on an XY graph and breaks down the VMware portfolio in those dimensions, the product portfolio. And you can see the dominance of respondents citing VMware as the platform. They might not know exactly which services they use, but they just respond VMware. That's on the X axis. You can see it way to the right. And the spending momentum or the net score is on the Y axis. That red dotted line at 4%, that indicates elevated levels and only VMware cloud on AWS is above that line. Notably, Tanzu has jumped up significantly from previous quarters, with the rest of the portfolio showing steady, as you would expect from a maturing platform. Only carbon black is hovering in the red zone, kind of ironic given the name. We believe that VMware is going to be a major player in cross cloud services, what we refer to as Supercloud. For months, we've been refining the concept and the definition. At Supercloud '22, we had discussions with more than 30 technology and business experts, and we've gathered input from many more. Based on that feedback, here's the definition we've landed on. It's somewhat refined from our earlier definition that we published a couple weeks ago. Supercloud is an emerging computing architecture that comprises a set of services abstracted from the underlying primitives of hyperscale clouds, e.g. compute, storage, networking, security, and other native resources, to create a global system spanning more than one cloud. Supercloud is three essential properties, three deployment models, and three service models. So what are those essential elements, those properties? We've simplified the picture from our last report. We show them here. I'll review them briefly. We're not going to go super in depth here because we've covered this topic a lot. But supercloud, it runs on more than one cloud. It creates that common or identical experience across clouds. It contains a necessary capability that we call a superPaaS that acts as a cloud interpreter, and it has metadata intelligence to optimize for a specific purpose. We'll publish this definition in detail. So again, we're not going to spend a ton of time here today. Now, we've identified three deployment models for Supercloud. The first is a single instantiation, where a control plane runs on one cloud but supports interactions with multiple other clouds. An example we use is Kubernetes cluster management service that runs on one cloud but can deploy and manage clusters on other clouds. The second model is a multi-cloud, multi-region instantiation where a full stack of services is instantiated on multiple clouds and multiple cloud regions with a common interface across them. We've used cohesity as one example of this. And then a single global instance that spans multiple cloud providers. That's our snowflake example. Again, we'll publish this in detail. So we're not going to spend a ton of time here today. Finally, the service models. The feedback we've had is IaaS, PaaS, and SaaS work fine to describe the service models for Supercloud. NetApp's Cloud Volume is a good example in IaaS. VMware cloud foundation and what we expect at VMware Explore is a good PaaS example. And SAP HANA Cloud is a good example of SaaS running as a Supercloud service. That's the SAP HANA multi-cloud. So what is it that we expect from VMware Explore 2022? Well, along with what will be an exciting and speculation filled gathering of the VMware community at the Moscone Center, we believe VMware will lay out its future architectural direction. And we expect it will fit the Supercloud definition that we just described. We think VMware will show its hand on a set of cross-cloud services and will promise a common experience for users and developers alike. As we talked about at Supercloud '22, VMware kind of wants to have its cake, eat it too, and lose weight. And by that, we mean that it will not only abstract the underlying primitives of each of the individual clouds, but if developers want access to them, they will allow that and actually facilitate that. Now, we don't expect VMware to use the term Supercloud, but it will be a cross-cloud multi-cloud services model that they put forth, we think, at VMworld Explore. With IaaS comprising compute, storage, and networking, a very strong emphasis, we believe, on security, of course, a governance and a comprehensive set of data protection services. Now, very importantly, we believe Tanzu will play a leading role in any announcements this coming week, as a purpose-built PaaS layer, specifically designed to create a common experience for cross clouds for data and application services. This, we believe, will be VMware's most significant offering to date in cross-cloud services. And it will position VMware to be a leader in what we call Supercloud. Now, while it remains to be seen what Broadcom exactly intends to do with VMware, we've speculated, others have speculated. We think this Supercloud is a substantial market opportunity generally and for VMware specifically. Look, if you don't own a public cloud, and very few companies do, in the tech business, we believe you better be supporting the build out of superclouds or building a supercloud yourself on top of hyperscale infrastructure. And we believe that as cloud matures, hyperscalers will increasingly I cross cloud services as an opportunity. We asked David Floyer to take a stab at a market model for super cloud. He's really good at these types of things. What he did is he took the known players in cloud and estimated their IaaS and PaaS cloud services, their total revenue, and then took a percentage. So this is super set of just the public cloud and the hyperscalers. And then what he did is he took a percentage to fit the Supercloud definition, as we just shared above. He then added another 20% on top to cover the long tail of Other. Other over time is most likely going to grow to let's say 30%. That's kind of how these markets work. Okay, so this is obviously an estimate, but it's an informed estimate by an individual who has done this many, many times and is pretty well respected in these types of forecasts, these long term forecasts. Now, by the definition we just shared, Supercloud revenue was estimated at about $3 billion in 2022 worldwide, growing to nearly $80 billion by 2030. Now remember, there's not one Supercloud market. It comprises a bunch of purpose-built superclouds that solve a specific problem. But the common attribute is it's built on top of hyperscale infrastructure. So overall, cloud services, including Supercloud, peak by the end of the decade. But Supercloud continues to grow and will take a higher percentage of the cloud market. The reasoning here is that the market will change and compute, will increasingly become distributed and embedded into edge devices, such as automobiles and robots and factory equipment, et cetera, and not necessarily be a discreet... I mean, it still will be, of course, but it's not going to be as much of a discrete component that is consumed via services like EZ2, that will mature. And this will be a key shift to watch in spending dynamics and really importantly, computing economics, the things we've talked about around arm and edge and AI inferencing and new low cost computing architectures at the edge. We're talking not the near edge, like, Lowes and Home Depot, we're talking far edge and embedded devices. Now, whether this becomes a seamless part of Supercloud remains to be seen. Look, if that's how we see it, the current and the future state of Supercloud, and we're committed to keeping the discussion going with an inclusive model that gathers input from all parts of the industry. Okay, that's it for today. Thanks to Alex Morrison, who's on production, and he also manages the podcast. Ken Schiffman, as well, is on production in our Boston office. Kristin Martin and Cheryl Knight, they help us get the word out on social media and in our newsletters. And Rob Hoffe is our editor in chief over at Silicon Angle and does some helpful editing. Thank you, all. Remember these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast. I publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me @Dvellante or comment on our LinkedIn posts. Please do check out etr.ai. They've got some great enterprise survey research. So please go there and poke around, And if you need any assistance, let them know. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (lively music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante at our inaugural super cloud 22 event we further refined the concept of a super cloud iterating on the definition the salient attributes and some examples of what is and what is not a super cloud welcome to this week's wikibon cube insights powered by etr you know snowflake has always been what we feel is one of the strongest examples of a super cloud and in this breaking analysis from our studios in palo alto we unpack our interview with benoit de javille co-founder and president of products at snowflake and we test our super cloud definition on the company's data cloud platform and we're really looking forward to your feedback first let's examine how we defl find super cloudant very importantly one of the goals of super cloud 22 was to get the community's input on the definition and iterate on previous work super cloud is an emerging computing architecture that comprises a set of services which are abstracted from the underlying primitives of hyperscale clouds we're talking about services such as compute storage networking security and other native tooling like machine learning and developer tools to create a global system that spans more than one cloud super cloud as shown on this slide has five essential properties x number of deployment models and y number of service models we're looking for community input on x and y and on the first point as well so please weigh in and contribute now we've identified these five essential elements of a super cloud let's talk about these first the super cloud has to run its services on more than one cloud leveraging the cloud native tools offered by each of the cloud providers the builder of the super cloud platform is responsible for optimizing the underlying primitives of each cloud and optimizing for the specific needs be it cost or performance or latency or governance data sharing security etc but those primitives must be abstracted such that a common experience is delivered across the clouds for both users and developers the super cloud has a metadata intelligence layer that can maximize efficiency for the specific purpose of the super cloud i.e the purpose that the super cloud is intended for and it does so in a federated model and it includes what we call a super pass this is a prerequisite that is a purpose-built component and enables ecosystem partners to customize and monetize incremental services while at the same time ensuring that the common experiences exist across clouds now in terms of deployment models we'd really like to get more feedback on this piece but here's where we are so far based on the feedback we got at super cloud 22. we see three deployment models the first is one where a control plane may run on one cloud but supports data plane interactions with more than one other cloud the second model instantiates the super cloud services on each individual cloud and within regions and can support interactions across more than one cloud with a unified interface connecting those instantiations those instances to create a common experience and the third model superimposes its services as a layer or in the case of snowflake they call it a mesh on top of the cloud on top of the cloud providers region or regions with a single global instantiation a single global instantiation of those services which spans multiple cloud providers this is our understanding from a comfort the conversation with benoit dejaville as to how snowflake approaches its solutions and for now we're going to park the service models we need to more time to flesh that out and we'll propose something shortly for you to comment on now we peppered benoit dejaville at super cloud 22 to test how the snowflake data cloud aligns to our concepts and our definition let me also say that snowflake doesn't use the term data cloud they really want to respect and they want to denigrate the importance of their hyperscale partners nor do we but we do think the hyperscalers today anyway are building or not building what we call super clouds but they are but but people who bar are building super clouds are building on top of hyperscale clouds that is a prerequisite so here are the questions that we tested with snowflake first question how does snowflake architect its data cloud and what is its deployment model listen to deja ville talk about how snowflake has architected a single system play the clip there are several ways to do this you know uh super cloud as as you name them the way we we we picked is is to create you know one single system and that's very important right the the the um [Music] there are several ways right you can instantiate you know your solution uh in every region of a cloud and and you know potentially that region could be a ws that region could be gcp so you are indeed a multi-cloud solution but snowflake we did it differently we are really creating cloud regions which are superposed on top of the cloud provider you know region infrastructure region so we are building our regions but but where where it's very different is that each region of snowflake is not one in instantiation of our service our service is global by nature we can move data from one region to the other when you land in snowflake you land into one region but but you can grow from there and you can you know exist in multiple clouds at the same time and that's very important right it's not one single i mean different instantiation of a system is one single instantiation which covers many cloud regions and many cloud providers snowflake chose the most advanced level of our three deployment models dodgeville talked about too presumably so it could maintain maximum control and ensure that common experience like the iphone model next we probed about the technical enablers of the data cloud listen to deja ville talk about snow grid he uses the term mesh and then this can get confusing with the jamaicani's data mesh concept but listen to benoit's explanation well as i said you know first we start by building you know snowflake regions we have today furry region that spawn you know the world so it's a worldwide worldwide system with many regions but all these regions are connected together they are you know meshed together with our technology we name it snow grid and that makes it hard because you know regions you know azure region can talk to a ws region or gcp regions and and as a as a user of our cloud you you don't see really these regional differences that you know regions are in different you know potentially clown when you use snowflake you can exist your your presence as an organization can be in several regions several clouds if you want geographic and and and both geographic and cloud provider so i can share data irrespective of the the cloud and i'm in the snowflake data cloud is that correct i can do that today exactly and and that's very critical right what we wanted is to remove data silos and and when you instantiate a system in one single region and that system is locked in that region you cannot communicate with other parts of the world you are locking the data in one region right and we didn't want to do that we wanted you know data to be distributed the way customer wants it to be distributed across the world and potentially sharing data at world scale now maybe there are many ways to skin the other cat meaning perhaps if a platform does instantiate in multiple places there are ways to share data but this is how snowflake chose to approach the problem next question how do you deal with latency in this big global system this is really important to us because while snowflake has some really smart people working as engineers and and the like we don't think they've solved for the speed of light problem the best people working on it as we often joke listen to benoit deja ville's comments on this topic so yes and no the the way we do it it's very expensive to do that because generally if you want to join you know data which is in which are in different regions and different cloud it's going to be very expensive because you need to move you know data every time you join it so the way we do it is that you replicate the subset of data that you want to access from one region from other regions so you can create this data mesh but data is replicated to make it very cheap and very performant too and is the snow grid does that have the metadata intelligence yes to actually can you describe that a little bit yeah snow grid is both uh a way to to exchange you know metadata about so each region of snowflake knows about all the other regions of snowflake every time we create a new region diary you know the metadata is distributed over our data cloud not only you know region knows all the regions but knows you know every organization that exists in our clouds where this organization is where data can be replicated by this organization and then of course it's it's also used as a way to uh uh exchange data right so you can exchange you know beta by scale of data size and we just had i was just receiving an email from one of our customers who moved more than four petabytes of data cross-region cross you know cloud providers in you know few days and you know it's a lot of data so it takes you know some time to move but they were able to do that online completely online and and switch over you know to the diff to the other region which is failover is very important also so yes and no probably means typically no he says yes and no probably means no so it sounds like snowflake is selectively pulling small amounts of data and replicating it where necessary but you also heard him talk about the metadata layer which is one of the essential aspects of super cloud okay next we dug into security it's one of the most important issues and we think one of the hardest parts related to deploying super cloud so we've talked about how the cloud has become the first line of defense for the cso but now with multi-cloud you have multiple first lines of defense and that means multiple shared responsibility models and multiple tool sets from different cloud providers and an expanded threat surface so listen to benoit's explanation here please play the clip this is a great question uh security has always been the most important aspect of snowflake since day one right this is the question that every customer of ours has you know how you can you guarantee the security of my data and so we secure data really tightly in region we have several layers of security it starts by by encrypting it every data at rest and that's very important a lot of customers are not doing that right you hear these attacks for example on on cloud you know where someone left you know their buckets uh uh open and then you know you can access the data because it's a non-encrypted uh so we are encrypting everything at rest we are encrypting everything in transit so a region is very secure now you know you never from one region you never access data from another region in snowflake that's why also we replicate data now the replication of that data across region or the metadata for that matter is is really highly secure so snow grits ensure that everything is encrypted everything is you know we have multiple you know encryption keys and it's you know stored in hardware you know secure modules so we we we built you know snow grids such that it's secure and it allows very secure movement of data so when we heard this explanation we immediately went to the lowest common denominator question meaning when you think about how aws for instance deals with data in motion or data and rest it might be different from how another cloud provider deals with it so how does aws uh uh uh differences for example in the aws maturity model for various you know cloud capabilities you know let's say they've got a faster nitro or graviton does it do do you have to how does snowflake deal with that do they have to slow everything else down like imagine a caravan cruising you know across the desert so you know every truck can keep up let's listen it's a great question i mean of course our software is abstracting you know all the cloud providers you know infrastructure so that when you run in one region let's say aws or azure it doesn't make any difference as far as the applications are concerned and and this abstraction of course is a lot of work i mean really really a lot of work because it needs to be secure it needs to be performance and you know every cloud and it has you know to expose apis which are uniform and and you know cloud providers even though they have potentially the same concept let's say blob storage apis are completely different the way you know these systems are secure it's completely different the errors that you can get and and the retry you know mechanism is very different from one cloud to the other performance is also different we discovered that when we were starting to port our software and and and you know we had to completely rethink how to leverage blob storage in that cloud versus that cloud because just of performance too so we had you know for example to you know stripe data so all this work is work that's you know you don't need as an application because our vision really is that applications which are running in our data cloud can you know be abstracted of all this difference and and we provide all the services all the workload that this application need whether it's transactional access to data analytical access to data you know managing you know logs managing you know metrics all of these is abstracted too such that they are not you know tied to one you know particular service of one cloud and and distributing this application across you know many regions many cloud is very seamless so from that answer we know that snowflake takes care of everything but we really don't understand the performance implications in you know in that specific case but we feel pretty certain that the promises that snowflake makes around governance and security within their data sharing construct construct will be kept now another criterion that we've proposed for super cloud is a super pass layer to create a common developer experience and an enabler for ecosystem partners to monetize please play the clip let's listen we build it you know a custom build because because as you said you know what exists in one cloud might not exist in another cloud provider right so so we have to build you know on this all these this components that modern application mode and that application need and and and and that you know goes to machine learning as i say transactional uh analytical system and the entire thing so such that they can run in isolation basically and the objective is the developer experience will be identical across those clouds yes right the developers doesn't need to worry about cloud provider and actually our system we have we didn't talk about it but the marketplace that we have which allows actually to deliver we're getting there yeah okay now we're not going to go deep into ecosystem today we've talked about snowflakes strengths in this regard but snowflake they pretty much ticked all the boxes on our super cloud attributes and definition we asked benoit dejaville to confirm that this is all shipping and available today and he also gave us a glimpse of the future play the clip and we are still developing it you know the transactional you know unistore as we call it was announced in last summit so so they are still you know working properly but but but that's the vision right and and and that's important because we talk about the infrastructure right you mentioned a lot about storage and compute but it's not only that right when you think about application they need to use the transactional database they need to use an analytical system they need to use you know machine learning so you need to provide also all these services which are consistent across all the cloud providers so you can hear deja ville talking about expanding beyond taking advantage of the core infrastructure storage and networking et cetera and bringing intelligence to the data through machine learning and ai so of course there's more to come and there better be at this company's valuation despite the recent sharp pullback in a tightening fed environment okay so i know it's cliche but everyone's comparing snowflakes and data bricks databricks has been pretty vocal about its open source posture compared to snowflakes and it just so happens that we had aligotsy on at super cloud 22 as well he wasn't in studio he had to do remote because i guess he's presenting at an investor conference this week so we had to bring him in remotely now i didn't get to do this interview john furrier did but i listened to it and captured this clip about how data bricks sees super cloud and the importance of open source take a listen to goatzee yeah i mean let me start by saying we just we're big fans of open source we think that open source is a force in software that's going to continue for you know decades hundreds of years and it's going to slowly replace all proprietary code in its way we saw that you know it could do that with the most advanced technology windows you know proprietary operating system very complicated got replaced with linux so open source can pretty much do anything and what we're seeing with the data lake house is that slowly the open source community is building a replacement for the proprietary data warehouse you know data lake machine learning real-time stack in open source and we're excited to be part of it for us delta lake is a very important project that really helps you standardize how you lay out your data in the cloud and with it comes a really important protocol called delta sharing that enables you in an open way actually for the first time ever share large data sets between organizations but it uses an open protocol so the great thing about that is you don't need to be a database customer you don't even like databricks you just need to use this open source project and you can now securely share data sets between organizations across clouds and it actually does so really efficiently just one copy of the data so you don't have to copy it if you're within the same cloud so the implication of ellie gotzi's comments is that databricks with delta sharing as john implied is playing a long game now i don't know if enough about the databricks architecture to comment in detail i got to do more research there so i reached out to my two analyst friends tony bear and sanji mohan to see what they thought because they cover these companies pretty closely here's what tony bear said quote i've viewed the divergent lake house strategies of data bricks and snowflake in the context of their roots prior to delta lake databrick's prime focus was the compute not the storage layer and more specifically they were a compute engine not a database snowflake approached from the opposite end of the pool as they originally fit the mold of the classic database company rather than a specific compute engine per se the lake house pushes both companies outside of their original comfort zones data bricks to storage snowflake to compute engine so it makes perfect sense for databricks to embrace the open source narrative at the storage layer and for snowflake to continue its walled garden approach but in the long run their strategies are already overlapping databricks is not a 100 open source company its practitioner experience has always been proprietary and now so is its sql query engine likewise snowflake has had to open up with the support of iceberg for open data lake format the question really becomes how serious snowflake will be in making iceberg a first-class citizen in its environment that is not necessarily officially branding a lake house but effectively is and likewise can databricks deliver the service levels associated with walled gardens through a more brute force approach that relies heavily on the query engine at the end of the day those are the key requirements that will matter to data bricks and snowflake customers end quote that was some deep thought by by tony thank you for that sanjay mohan added the following quote open source is a slippery slope people buy mobile phones based on open source android but it's not fully open similarly databricks delta lake was not originally fully open source and even today its photon execution engine is not we are always going to live in a hybrid world snowflake and databricks will support whatever model works best for them and their customers the big question is do customers care as deeply about which vendor has a higher degree of openness as we technology people do i believe customers evaluation criteria is far more nuanced than just to decipher each vendor's open source claims end quote okay so i had to ask dodgeville about their so-called wall garden approach and what their strategy is with apache iceberg here's what he said iceberg is is very important so just to to give some context iceberg is an open you know table format right which was you know first you know developed by netflix and netflix you know put it open source in the apache community so we embrace that's that open source standard because because it's widely used by by many um many you know companies and also many companies have you know really invested a lot of effort in building you know big data hadoop solution or data like solution and they want to use snowflake and they couldn't really use snowflake because all their data were in open you know formats so we are embracing icebergs to help these companies move through the cloud but why we have been relentless with direct access to data direct access to data is a little bit of a problem for us and and the reason is when you direct access to data now you have direct access to storage now you have to understand for example the specificity of one cloud versus the other so as soon as you start to have direct access to data you lose your you know your cloud diagnostic layer you don't access data with api when you have direct access to data it's very hard to secure data because you need to grant access direct access to tools which are not you know protected and you see a lot of you know hacking of of data you know because of that so so that was not you know direct access to data is not serving well our customers and that's why we have been relented to do that because it's it's cr it's it's not cloud diagnostic it's it's you you have to code that you have to you you you need a lot of intelligence while apis access so we want open apis that's that's i guess the way we embrace you know openness is is by open api versus you know you access directly data here's my take snowflake is hedging its bets because enough people care about open source that they have to have some open data format options and it's good optics and you heard benoit deja ville talk about the risks of directly accessing the data and the complexities it brings now is that maybe a little fud against databricks maybe but same can be said for ollie's comments maybe flooding the proprietaryness of snowflake but as both analysts pointed out open is a spectrum hey i remember unix used to equal open systems okay let's end with some etr spending data and why not compare snowflake and data bricks spending profiles this is an xy graph with net score or spending momentum on the y-axis and pervasiveness or overlap in the data set on the x-axis this is data from the january survey when snowflake was holding above 80 percent net score off the charts databricks was also very strong in the upper 60s now let's fast forward to this next chart and show you the july etr survey data and you can see snowflake has come back down to earth now remember anything above 40 net score is highly elevated so both companies are doing well but snowflake is well off its highs and data bricks has come down somewhat as well databricks is inching to the right snowflake rocketed to the right post its ipo and as we know databricks wasn't able to get to ipo during the covet bubble ali gotzi is at the morgan stanley ceo conference this week they got plenty of cash to withstand a long-term recession i'm told and they've started the message that they're a billion dollars in annualized revenue i'm not sure exactly what that means i've seen some numbers on their gross margins i'm not sure what that means i've seen some numbers on their net retention revenue or net revenue retention again i'll reserve judgment until we see an s1 but it's clear both of these companies have momentum and they're out competing in the market well as always be the ultimate arbiter different philosophies perhaps is it like democrats and republicans well it could be but they're both going after a solving data problem both companies are trying to help customers get more value out of their data and both companies are highly valued so they have to perform for their investors to paraphrase ralph nader the similarities may be greater than the differences okay that's it for today thanks to the team from palo alto for this awesome super cloud studio build alex myerson and ken shiffman are on production in the palo alto studios today kristin martin and sheryl knight get the word out to our community rob hoff is our editor-in-chief over at siliconangle thanks to all please check out etr.ai for all the survey data remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcasts i publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante at siliconangle.com or dm me at devellante or comment on my linkedin posts and please as i say etr has got some of the best survey data in the business we track it every quarter and really excited to be partners with them this is dave vellante for the cube insights powered by etr thanks for watching and we'll see you next time on breaking analysis [Music] you

>>Hi, everyone. Good afternoon. Thank you for joining this session. I feel honored to be invited to speak here today. And I also appreciate entity research Summit members for organ organizing and giving this great opportunity. Please let me give a quick introduction. First, I'm a Takashi from Marvin American population, and I'm leading technology scouting and global ation with digital health companies such as Business Alliance and Strategically Investment in North America. And since we started to focus on this space in 2016 our team is growing. And in order to bring more new technologies and services to Japan market Thesis year, we founded the new service theories for digital health business, especially, uh, in medical diagnosis space in Japan. And today I would like to talk how health care has been transformed for my micro perspective, and I hope you enjoy reasoning it. So what's happened since the US identify the first case in the middle of January, As everyone knows, unfortunately, is the damaged by this pandemic was unequal amongst the people in us. It had more determined tal impact on those who are socially and economically vulnerable because of the long, long lasting structural program off the U. S. Society and the Light Charity about daily case rating elevator country shows. Even in the community, the infection rate off the low income were 4.5 times higher than, uh, those of the high income and due to czar straight off the Corvette, about 14 million people are unemployed. The unique point off the U. S. Is that more than 60% of insurance is tied with employment, so losing a job can mean losing access to health care. And the point point here is that the Corvette did not create healthcare disparity but, uh nearly highlighted the underlying program and necessity off affordable care for all. And when the country had a need to increase the testing capacity and geographic out, treat the pharmacies and retails joined forces with existing stakeholders more than 90% off the U. S Corporation live within five miles off a community pharmacy such as CVS and Walgreen, so they can technically provide the test to everyone in all the community. And they also have a huge workforce memory pharmacist who are eligible to perform the testing scale, and this very made their potential in community based health care. Stand out and about your health has provided on alternative way for people to access to health care. At affordable applies under the unusual setting where social distancing, which required required mhm and people have a fear of infection. So they are afraid to take a public transportacion and visit >>the doctor the same thing supplied to doctor and the chart. Here is a number of total visit cranes by service type after stay at home order was issued across the U. S. By Ali April patient physical visits to doctor's offices or clinics declined by ALAN 70%. On the other hand, that share, or telehealth, accounted for 25% of the total total. Doctor's visit in April, while many states studied to re opening face to face visit is gradually recovering. And overall Tele Health Service did not offset the crime. Physician Physical doctor's visit and telehealth John never fully replace in person care. However, Telehealth has established a new way to provide affordable care, especially to vulnerable people, and I don't explain each player's today. But as an example, the chart shows the significant growth of the tell a dog who is one of the largest badger care and tell his provider, I believe there are three factors off paradox. Success under the pandemic. First, obviously tell Doc could reach >>the job between those patients and doctors. Majority of the patients who needed to see doctors who are those who have underlying health conditions and are high risk for Kelowna, Bilis and Secondary. They showed their business model is highly scalable. In the first quarter of this year, they moved quickly to expand their physical physicians network to increase their capacity and catch up growing demand. To some extent, they also contributed to create flexible job for the doctors who suffered from Lydia's appointment and surgery. They utilized. There are legalism to maximize the efficiency for doctors and doing so, uh, they have university maintained high quality care at affordable applies Yeah, and at the same time, the government recognize the body of about your care and de regulated traditional rules to sum up she m s temporary automated to pay a wide range of tell Her services, including hospital visit and HHS temporarily waived hip hop minorities for telehealth cases and they're changed allowed provider to use communication tools such as facetime and the messenger. During their appointment on August start, the government issued a new executive order to expand tell his services beyond the pandemic. So the government is also moving to support about your health care. So it was a quick review of the health care challenges and somewhat advancement in the pandemic. But as you understand, since those challenges are not caused by the pandemic, problems will stay remain and events off this year will continuously catalyze the transformation. So how was his cherished reshaped and where will we go? The topic from here can be also applied to Japan market. Okay, I believe democratization and decentralization healthcare more important than ever. So what does A. The traditional healthcare was defined in a framework over patient and a doctor. But in the new normal, the range of beneficiaries will be expanded from patient to all citizens, including the country uninsured people. Thanks to the technology evolution, as you can download health management off for free on iTunes stores while the range of the digital health services unable everyone to participate in new health system system. And in this slide, I put three essential element to fully realize democratization and decentralization off health care, health, literacy, data sharing and security, privacy and safety in addition, taken. In addition, technology is put at the bottom as a foundation off three point first. Health stimulus is obviously important because if people don't understand how the system works, what options are available to them or what are the pros and cons of each options? They can not navigate themselves and utilize the service. It can even cause a different disparity. Issue and secondary data must be technically flee to transfer. While it keeps interoperability ease. More options are becoming available to patient. But if data cannot be shared among stakeholders, including patient hospitals in strollers and budget your providers, patient data will be fragmented and people cannot yet continue to care which they benefited under current centralized care system. And this is most challenging part. But the last one is that the security aspect more players will involving decentralized health care outside of conventional healthcare system. So obviously, both the number of healthcare channels and our frequency of data sharing will increase more. It's create ah, higher data about no beauty, and so, under the new health care framework, we needed to ensure patient privacy and safety and also re examine a Scott write lines for sharing patient data and off course. Corbett Wasa Stone Catalyst off this you saved. But what folly. Our drivers in Macro and Micro Perspective from Mark Lowe. The challenges in healthcare system have been widely recognized for decades, and now he's a big pain. The pandemic reminded us all the key values. Misha, our current pain point as I left the church shores. Those are increasing the population, health sustainability for doctors and other social system and value based care for better and more affordable care. And all the elements are co dependent on each other. The light chart explained that providing preventive care and Alan Dimension is the best way threes to meet the key values here. Similarly, the direction of community based care and about your care is in line with thes three values, and they are acting to maximize the number of beneficiaries form. A micro uh, initiative by nonconventional players is a big driver, and both CBS and Walmart are being actively engaged in healthcare healthcare businesses for many years. And CBS has the largest walking clinic called MinuteClinic, Ottawa 1100 locations, and Walmart also has 20 primary clinics. I didn't talk to them. But the most interesting things off their recent innovation, I believe, is that they are adjusted and expanded their focus, from primary care to community health Center to out less to every every customer's needs. And CBS Front to provide affordable preventive health and chronic health monitoring services at 1500 CBS Health have, which they are now setting up and along a similar line would Mark is deploying Walmart Health Center, where, utilizing tech driven solutions, they provide affordable one stop service for core healthcare. They got less, uh, insurance status. For example, more than 40% of the people in U. S visit will not every big, so liberating the huge customer base and physical locations. Both companies being reading decentralization off health care and consumer device company such as Apple and Fitbit also have helped in transform forming healthcare in two ways. First, they are growing the boundaries between traditional healthcare and consumer product after their long development airport available, getting healthcare device and secondary. They acted as the best healthcare educators to consumers and increase people's healthcare awareness because they're taking an important role in the enhancement, health, literacy and healthcare democratization. And based on the story so far, I'd like to touch to business concept which can be applied to both Japan and the US and one expected change. It will be the emergence of data integration plot home while the telehealth. While the healthcare data data volume has increased 15 times for the last seven years and will continuously increase, we have a chance to improve the health care by harnessing the data. So meaning the new system, which unify the each patient data from multiple data sources and create 360 degrees longitudinal view each individual and then it sensitized the unified data to gain additional insights seen from structure data and unable to provide personal lives care. Finally, it's aggregate each individual data and reanalyzed to provide inside for population health. This is one specific model I envision. And, uh, health care will be provided slew online or offline and at the hospital or detail store. In order to amplify the impact of health care. The law off the mediator between health care between hospital and citizen will become more important. They can be a pharmacy toe health stand out about your care providers. They provide wide range of fundamental care and medication instruction and management. They also help individuals to manage their health care data. I will not explain the details today, but Japan has similar challenges in health care, such as increasing healthcare expenditure and lack of doctors and care givers. For example, they people in Japan have physical physician visit more than 20 times a year on average, while those in the U. S. On >>the do full times it sounds a joke, but people say because the artery are healthy, say visit hospitals to see friends. So we need to utilize thes mediators to reduce cost while they maintained social place for citizens in Japan, the government has promoted, uh, usual family, pharmacist and primary doctors and views the community based medical system as a policy. There was division of dispensing fees in Japan this year to ship the core load or pharmacist to the new role as a health management service providers. And so >>I believe we will see the change in those spaces not only in the U. S, but also in Japan, and we went through so unprecedented times. But I believe it's been resulting accelerating our healthcare transformation and creating a new business innovation. And this brings me to the end of my presentation. Thank you for your attention and hope you could find something somehow useful for your business. And if you have any questions >>or comments, please for you feel free to contact me.

>>Hi, everyone. Good afternoon. Thank you for joining this session. I feel honored to be invited to speak here today. And I also appreciate entity research Summit members for organ organizing and giving this great opportunity. Please let me give a quick introduction. First, I'm a Takashi from Marvin American population, and I'm leading technology scouting and global ation with digital health companies such as Business Alliance and Strategically Investment in North America. And since we started to focus on this space in 2016 our team is growing. And in order to bring more new technologies and services to Japan market Thesis year, we founded the new service theories for digital health business, especially, uh, in medical diagnosis space in Japan. And today I would like to talk how health care has been transformed for my micro perspective, and I hope you enjoy reasoning it. So what's happened since the US identify the first case in the middle of January, As everyone knows, unfortunately, is the damaged by this pandemic was unequal amongst the people in us. It had more determined tal impact on those who are socially and economically vulnerable because of the long, long lasting structural program off the U. S. Society and the Light Charity about daily case rating elevator country shows. Even in the community, the infection rate off the low income were 4.5 times higher than, uh, those of the high income and due to czar straight off the Corvette, about 14 million people are unemployed. The unique point off the U. S. Is that more than 60% of insurance is tied with employment, so losing a job can mean losing access to health care. And the point point here is that the Corvette did not create healthcare disparity but, uh nearly highlighted the underlying program and necessity off affordable care for all. And when the country had a need to increase the testing capacity and geographic out, treat the pharmacies and retails joined forces with existing stakeholders more than 90% off the U. S Corporation live within five miles off a community pharmacy such as CVS and Walgreen, so they can technically provide the test to everyone in all the community. And they also have a huge workforce memory pharmacist who are eligible to perform the testing scale, and this very made their potential in community based health care. Stand out and about your health has provided on alternative way for people to access to health care. At affordable applies under the unusual setting where social distancing, which required required mhm and people have a fear of infection. So they are afraid to take a public transportacion and visit >>the doctor the same thing supplied to doctor and the chart. Here is a number of total visit cranes by service type after stay at home order was issued across the U. S. By Ali April patient physical visits to doctor's offices or clinics declined by ALAN 70%. On the other hand, that share, or telehealth, accounted for 25% of the total total. Doctor's >>visit in April, while many states studied to re opening face to face visit is gradually recovering. And overall Tele Health Service did not offset the crime. Physician Physical doctor's visit and telehealth John never fully replace in person care. However, Telehealth has established a new way to provide affordable care, especially to vulnerable people, and I don't explain each player's today. But as an example, the chart shows the significant growth of >>the tell a dog who is one of the largest badger care and tell his provider, I believe there are three factors off paradox. Success under the pandemic. First, obviously tell Doc could reach >>the job between those patients and doctors. Majority of the patients who needed to see doctors who are those who have underlying health conditions and are high risk for Kelowna, Bilis and Secondary. They showed their business model is highly scalable. In the first quarter of this year, they moved quickly to expand their physical physicians network to increase their capacity and catch up growing demand. To some extent, they also contributed to create flexible job for the doctors who suffered from Lydia's appointment and surgery. They utilized. There are legalism to maximize the efficiency for doctors and doing so, uh, they have university maintained high quality care at affordable applies Yeah, and at the same time, the government recognize the body of about your care and de regulated traditional rules to sum up she m s temporary automated to pay a wide range of tell Her services, including hospital visit and HHS temporarily waived hip hop minorities for telehealth cases and they're changed allowed provider to use communication tools such as facetime and the messenger. During their appointment on August start, the government issued a new executive order to expand tell his services beyond the pandemic. So the government is also moving to support about your health care. So it was a quick review of the health care challenges and somewhat advancement in the pandemic. But as you understand, since those challenges are not caused by the pandemic, problems will stay remain and events off this year will continuously catalyze the transformation. So how was his cherished reshaped and where will we go? The topic from here can be also applied to Japan market. Okay, I believe democratization and decentralization healthcare more important than ever. So what does A. The traditional healthcare was defined in a framework over patient and a doctor. But in the new normal, the range of beneficiaries will be expanded from patient to all citizens, including the country uninsured people. Thanks to the technology evolution, as you can download health management off for free on iTunes stores while the range of the digital health services unable everyone to participate in new health system system. And in this slide, I put three essential element to fully realize democratization and decentralization off health care, health, literacy, data sharing and security, privacy and safety in addition, taken. In addition, technology is put at the bottom as a foundation off three point first. Health stimulus is obviously important because if people don't understand how the system works, what options are available to them or what are the pros and cons of each options? They can not navigate themselves and utilize the service. It can even cause a different disparity. Issue and secondary data must be technically flee to transfer. While it keeps interoperability ease. More options are becoming available to patient. But if data cannot be shared among stakeholders, including patient hospitals in strollers and budget your providers, patient data will be fragmented and people cannot yet continue to care which they benefited under current centralized care system. And this is most challenging part. But the last one is that the security aspect more players will involving decentralized health care outside of conventional healthcare system. So obviously, both the number of healthcare channels and our frequency of data sharing will increase more. It's create ah, higher data about no beauty, and so, under the new health care framework, we needed to ensure patient privacy and safety and also re examine a Scott write lines for sharing patient data and off course. Corbett Wasa Stone Catalyst off this you saved. But what folly. Our drivers in Macro and Micro Perspective from Mark Lowe. The challenges in healthcare system have been widely recognized for decades, and now he's a big pain. The pandemic reminded us all the key values. Misha, our current pain point as I left the church shores. Those are increasing the population, health sustainability for doctors and other social system and value based care for better and more affordable care. And all the elements are co dependent on each other. The light chart explained that providing preventive care and Alan Dimension is the best way threes to meet the key values here. Similarly, the direction of community based care and about your care is in line with thes three values, and they are acting to maximize the number of beneficiaries form. A micro uh, initiative by nonconventional players is a big driver, and both CBS and Walmart are being actively engaged in healthcare healthcare businesses for many years. And CBS has the largest walking clinic called MinuteClinic, Ottawa 1100 locations, and Walmart also has 20 primary clinics. I didn't talk to them. But the most interesting things off their recent innovation, I believe, is that they are adjusted and expanded their focus, from primary care to community health Center to out less to every every customer's needs. And CBS Front to provide affordable preventive health and chronic health monitoring services at 1500 CBS Health have, which they are now setting up and along a similar line would Mark is deploying Walmart Health Center, where, utilizing tech driven solutions, they provide affordable one stop service for core healthcare. They got less, uh, insurance status. For example, more than 40% of the people in U. S visit will not every big, so liberating the huge customer base and physical locations. Both companies being reading decentralization off health care and consumer device company such as Apple and Fitbit also have helped in transform forming healthcare in two ways. First, they are growing the boundaries between traditional healthcare and consumer product after their long development airport available, getting healthcare device and secondary. They acted as the best healthcare educators to consumers and increase people's healthcare awareness because they're taking an important role in the enhancement, health, literacy and healthcare democratization. And based on the story so far, I'd like to touch to business concept which can be applied to both Japan and the US and one expected change. It will be the emergence of data integration plot home while the telehealth. While the healthcare data data volume has increased 15 times for the last seven years and will continuously increase, we have a chance to improve the health care by harnessing the data. So meaning the new system, which unify the each patient data from multiple data sources and create 360 degrees longitudinal view each individual and then it sensitized the unified data to gain additional insights seen from structure data and unable to provide personal lives care. Finally, it's aggregate each individual data and reanalyzed to provide inside for population health. This is one specific model I envision. And, uh, health care will be provided slew online or offline and at the hospital or detail store. In order to amplify the impact of health care. The law off the mediator between health care between hospital and citizen will become more important. They can be a pharmacy toe health stand out about your care providers. They provide wide range of fundamental care and medication instruction and management. They also help individuals to manage their health care data. I will not explain the details today, but Japan has similar challenges in health care, such as increasing healthcare expenditure and lack of doctors and care givers. For example, they people in Japan have physical physician visit more than 20 times a year on average, while those in the U. S. On the do full times it sounds a joke, but people say because the artery are healthy, say visit hospitals to see friends. So we need to utilize thes mediators to reduce cost while they maintained social place for citizens in Japan, the government has promoted, uh, usual family, pharmacist and primary doctors and views the community based medical system as a policy. There was division of dispensing fees in Japan this year to ship the core load or pharmacist to the new role as a health management service providers. And so I believe we will see the change in those spaces not only in the U. S, but also in Japan, and we went through so unprecedented times. But I believe it's been resulting accelerating our healthcare transformation and creating a new business innovation. And this brings me to the end of my presentation. Thank you for your attention and hope you could find something somehow useful for your business. And if you have any questions >>or comments, please for you feel free to contact me. Thank you.

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation everyone welcome to this cube conversation here in the cubes Palo Alto Studios we're here with the quarantine crew I'm John for your host we've got a great guest John Madison CMO an EVP of products of Fortinet and today more than ever in this changing landscape accelerating faster and faster certainly as this covin 19 crisis has forced business to realize a lot of the at scale problems are at hand and a lot of things are exposed in terms of problems and opportunities you have to take care of one of them security John thanks for coming on cube and looking forward to chatting about your recent event you had this week and also the updates at Florida thanks for joining me yeah it's great to be here John so more than ever the innovation strategies are not just talking points anymore in board meetings or companies there's they actually have to come out of this pandemic and operate through it with real innovation with actionable outcomes they've got to get their house in order you're seeing projects really focusing in on the at scale problems which is essentially keep the network's run and keep the sick the security fabric in place this is critical path stuff but the innovation coming out of it has to be a growth play for companies and this has been a big thing so you guys are in the middle of it we've chatted about all the four to guard stuff and all this you're seeing all the traffic you're seeing all the all the impact this work at home has forced companies to not only deal to new realities but it's exposed some things they need to double down on and things they need to either get rid of or fix fast what's your take on all this yeah you know I think it took a lot of people by surprise and the first thing I would like to do is you know spank our employees our customers and partners for the work they've done in the last six to seven weeks now what was happening was a lot of customers had built their work from home programs around a certain percentage 5% 10% 15% and that's what they scaled it for then all of a sudden you know everybody had to work from home and so you went from maybe a thousand people to 10,000 or 5,000 to 50,000 they had to scale very quickly because this had to be implemented in hours and days not weeks and months luckily our systems are able to gaile very quickly we can scale using a security processing units which offload the CPU and allow a lot of users simultaneously to access through VPN SSL VPN IPSec VPN and then we have an implementation at home ranging from a very simple Microsoft Wyant all the way to our clients all the way to even off Buda gate firewalls at home so we really did work very hard to make sure that our customers could maintain their business proposition during these times you know I want to get those work at home and I think it's a little big Sdn story and you guys have been on for a long time I mean we've talked with your you and your folks many times around st Wynn and what it means to to have that in place but this work at home those numbers are off the charts strange and this is disruption this was an unforeseen disruption it's not like a hurricane or flood this is real and we've also talked with you guys and your team around the endpoint you know the edge of the network that's the explosion of the billions of edges this is just an industry kind of inside baseball conversation and then also the immersion of the lifestyle we now live in so you have a world where it was inside baseball for this industry now every company and everyone's feeling it this is a huge issue I'm at home I got to protect myself I got data I gotta have a VPN I mean this is a reality that just wasn't seen I mean what do you guys are what are you guys doing in this area well I think it changes that this long-term architect and so you know the past we talked about there being millions of edges and people go how many billions of edges and what's happened is if you're working from home that's an edge and so the long term architecture means that companies need to take care of where their network edges are now the SEM at home they had them at the branch office they have them at the end of prize and the data center in the cloud then we need to decide know where to apply the security is it at the endpoint is it at the edges is the data center or bout an S T one is absolutely essential because every edge you'll have whether that were home now whether it be in your data center or eCampus on the cloud needs that st-1 technology and make sure you can guide the applications in a secure manner what's interesting is I actually deployed st-1 in my home here I've got two ISP connections one week I'm casting off with AT&T now that may be overkill right now for most people about putting st-1 in their homes but I think long-term homes are gonna be part of the enterprise network it's just another eight take a minute to explain the SD win I would call it the this is a mill especially this is not your grandfather's st win I mean it's changed st when is the internet I mean basically at home what does that mean if users don't know care what the products are at the end of the day they're working at home so kind of SD win has taken on a new broader scope if you will it's not just the classic SD win or is it can you take us through I mean and this is a category that's becoming much broader what's your what's your nails is there yeah again I'm not saying that you know consumers are gonna be putting SD wine in the homes right now but if I'm an executive and I rely on my communication out there are lots of meetings during the day work from home I want it to be as reliable as possible so if my one is pee goes down and I can't get on the internet that's an issue if I have to ISPs I have much higher availability but more importantly us you and I can guide the applications where I want when they want I can make sure you know my normal home traffic goes off certain direction the certain on a VLAN and segmentation policy whereas my war can be completely set out so again I you know I think SDRAM technology is important for the home long term is important for the branch for the enterprise and the data center and Earls St ones built into all up all our forty gates have sp1 you just switch it on we think it's a four essential technology going forward to drive that cloud on-ramp real quick follow-up on that for the folks in the enterprise I see the enterprise will make it easier for their customers their users who are at home so it feels consumer II invisible if you will I think that's the short-term what's what are what are you seeing your customers and prospective customers thinking when they come back or as they operate now in this new reality when they say you know what we really miss forecasted this now they have to get back to business what are they gonna do do they do more sta on I mean what's the architecture how does that get done what's the conversation like you know as this evolved for the next it's gonna slowly open up it still it's going to be a new reality for at least 12 months what's the conversation with the customer right now when it comes to going in and taking care of this so it doesn't happen again yeah what I'm doing actually actually what I'm doing a lot of virtual ABC's obviously we usually have 200 our customers that come to our corporate quarters or executive briefings and I'm doing actually more virtually and a lot of the opening conversations is they don't think they're gonna go completely Hunter's under percent back to where they were there's always going to be now a fraction of work-from-home people they may move around some of their physical location so as I said the ST when is that piece on the edge whether it be your home ranch campus or data centers gonna be there to guide the applications guide the users and devices to the right applications of wherever they may be as it could be in the cloud of communion data center it could be anywhere and then the key conversation thereafter for customers long-term architecture wise is where do I apply my security stack and the security spat consists of basic things like antivirus all right yes more detection capabilities even even response to Isis given that stack how much do I put in the edge how much do I put in my endpoint how much do I put my branch how much I put in my campus data center and cloud and then how do I maintain a policy a single policy across all of those and then now and again maybe I have to move that stack cross so that's going to be the key long term architecture question for enterprises as they move to a slightly different composition of workforce in different locations is hey I've got to make sure every edge that I have I identify and I secure when SP ran and then how do I apply the security stack cross all the diff tell great insight thanks for sharing that I want to get your take on now speaking of working at home you're also the CMO as well as the EVP of products which is a unique job because you can talk about any think when the cube we love it you had an event accelerate 2020 the folks watching go to the hashtag on Twitter hashtag accelerate 20 that's the hash tag you'll see a lot of the the pictures of the slides and some commentary I was laying down some tweets all the analysts were as well what are some of the highlights for you is a great presentation by the CEO you gave a talk and there's a lot of breakouts you had to do a digital event because you couldn't hold the physical event so you kind of had a shelter-in-place kind of and how did it go and what are some of the highlights yeah on the one side I was a bit sad you know we had or what we call accelerates arrange for this year in Barcelona and New York Mexico and San Jose we had to cancel war for them and I'm very quickly spin up a digital event a virtual event and you know we end up there's some initial targets around you know you know each of our physical events we get between two and three thousand and so we're thinking you know if we got to ten thousand this would be great we actually ended up with thirty thirty-two thousand or something like that registered and actually the percentage that showed off was even higher so we had over 20,000 people actually come online and go through our keynotes we built it so you go through the keynotes then you can go off to the painting what we call the breakouts for more detail we did verticals oh it did more technology sessions and so it's great and you know we tried our best to answer the questions online because these things are on demand we had three we had one for the u.s. one premiere and won't write back and so there was times but to get that sort of exposure to me is amazing twenty thousand people on there listening and it connects into another subject which is education and fun yet for some time as invested I would say you know my CEO says but I'll invest a bit more in education versus the marketing advertising budget now go okay okay that's that hey we'll work on that but education for us we announced a few weeks ago that education is now training is free for customers for everybody and we'd also been you know leading the way by providing free training for our partners now it's completely free for everybody we have something called the network security expert which goes from one to eight one and two of that are actually open to the public right now and if I go to the end of last year we had about two to three thousand people maybe a week come on and do the training obviously majority doing the NSC one courses you get further through to eight it's more technical last week we had over eighty thousand people we just think about those numbers incredible because people you know having more time let's do the training and finding is as they're doing this training going up the stack more quickly and they're able to implement their tools more quickly so training for us is just exploded off the map and I and there's a new reality of all the unemployment and also people are at home and there's a lot of job about the skill gap before in another cube conversation it's it's more apparent than ever and why not make it free give people some hope give them some tools to be successful there's demand yes and it's not you know it's not just them you know IT professionals are Ennis e1 is a foundational course and you'll see kids and students and universities doing it and so Ben Mars granddad's dad's doing it so we we're getting all sorts of comments and social media about the training you know our foundation great stuff has a great we'll put a plug on that when should we get that amplified for its really good stuff I got to ask you about the event one of the things I really like about the presentation was from your CEO and you gave one as well was the clarity around the vision of security and a couple of things that were notable to me was the confluence of the collision between networking and security and at the intersection of those two forces you have an accelerated integrated policy dynamic to me this is the heart of DevOps of what used to be in cloud being kind of applied to security you have data you got all kinds of new things emerging new patterns new signals that's security so you got to be you got to be fast you got to identify things so you guys are in this business that's one force and the other one was the billions of edges and this idea that there's no perimeter so it's everything's immersive so illustrate some points of validation on that from your standpoint is that how you guys are seeing it unfold in the future is that happening now can you give us a feeling for whether where we are and that those those kind of paradigms yeah good point so I think it's been happening it's happening now has been happening the future you know if you look at networking and our CEO Enzi talked about this and that networking hasn't really cheer outing and switching we go back to 2000 we had 100 mega under megabit now you have formed a gigabit but the basic function we haven't really changed that much securities different we've gone from a firewall and we add VPN then we at next-gen firewall then we had SSL inspection now we've added sd1 and so this collisions kind of an equal in that you know networking's sped ahead and firewalling is stayed behind because it's just got too many applications on that so the basic principle premise of the company of putting net is to build and bring that together so it's best of all accelerate the basic security network security functions so you can consolidate multiple functions on one system and then bring networking and security together a really good example of security where or nexium firewall where you can accelerate and so our security processing units and my analogy simple analogy is GPUs inside games where their GPU offloads CPU to allow rendering to happen very quick it's the same for us RSP use way of a network SPU and we have a Content SPU which all flows the CPU to allow a security and networking do it be accelerated work now coming to your second point about the perimeter I I'm not quite sure whether the perimeters disappear and the reason I say that is customer still goes they have firewalls on the front of the networks they have endpoint protection they have protection in the cloud so it's not that the perimeters disappeared it's just but much larger and so now the perimeters sitting across all your infrastructure your endpoints your in factories you got IOT devices you've got workloads in different powered and that means you need to look very carefully at those and give visibility initially and then apply the control that control maybe it's a ten-point security it may be SD mine at the edge it may be a compliance template in the cloud but you need visibility of all those edges which have been created with the perimeters reading across the image it's interesting you bring up a good point we always have kind of debates over beers on this on this topic you know the old model was mote you know get the castle and the gate but here the perimeter of the edge if you believe there's an edge and I do believe you find it perfectly the edge is a perimeter it's an endpoint right so it's a door into the internet so are the network so is the perimeter just an end adorn there's more doors right so or service yeah just think about it the castle would did multiple doors is the back everyone's the door there's this dozle someday and you have to define those H's and have visibility of them and that's why things like network access control know for you know zero trust network access is really important making sure you kind of look at the edge inside your way and so your data center and then it's like you powd what workloads are spinning off and what's the configuration and what's there what's from a data perspective right your recommendation and I'm a customer looking at my network I got compute I got edge devices and users I realized there's a billions of edges on my network now and the realities hit me I wasn't really being proactive on investing what do I do what's the PlayBook for me as I start to rethink that and what do I put into place how do I get going now I got to rethink it I now recognize I got full validation I got to manage this I got to do something what's your recommendation to me if I'm a customer the key to me is and I've had this conversation now for the last five years and it's getting louder and louder and that is I suppose I spend a lot of money on point solution point but even end point may have five point products on there and so they're getting to the conclusion it's just too hard to manage I can't find all the right people I get so many alerts from so many security systems I can't work out what's going on and the conversation now is how do I deploy a platform we call it the security fabric now I don't deploy that fabric across my network I'm not saying you should go from 30 vendors to one vendor that would be nice of course but I what I'm saying as you go from 30 vendors down to maybe five or six platform the platform's perform multiple functions it could be they're out there you attach a platform a designer platform just birth protector or a particular organization or part of the network and so the platform allows you then to build automation and the automation allows you to see things more quickly and react to things more quickly and do things without manual intervention the platform approach it's absolutely starting to resonate yes you've still got very very large customers who put everything into segments of a C's Exedra book most customers now moving towards a yeah I think you know as you see and again back to that collision with the end of the intersection we have integrated policies if you're gonna do any integration which is the data problem so we talk about all the time to a lot of different tools can create silos and there's a use case for that but also creates problematic situations I mean a platform gives you a much more robust capability to be adaptive to be real time to program and automate yeah it's it's it's an issue if you've got 30 vendors and just be honest it's also an issue in the industry so I mean networking the story kind of worked out how to work together you can use the same different vendor switches and routers and they roughly work together with cybersecurity they've all been deal you know built totally separately not to even work and that's why you've got these multiple layers you've got a product the security problem then this got its own analytics engine and manager then you've got a manager of managers and an analyzer of analyzers and the sim system and then a saw I mean just goes on it makes it so complex for people and that's why I think they look into something a bit more simplified but most importantly the platform must be friendly from a consumption model you must be able to do an appliance where you need to do virtual machine SAS cloud native container whatever it may be because that network has changed in those ages as those edges move you've got them to have a platform that adaptable to the consumption model require you know I had a great cartridge with Phil Quaid you see your seaso over there and we were chatting around you know this idea of I won't say customization but there's no one turnkey monolithic application it seems to these platforms tend to be enabling where the seaso trend is to have teams building ok and and and almost a customized but building software to automate to solve their use case for their outcome so enabling that is a trend we're seeing so I think you guys are on the right track there any comment on your take on this enabling platform is that something that you guys are seeing that CSIS is looking at more in-house development more use case focus because they have the data they got real-time they need to be building on a platform not told what they could do yeah I think you've always had this this network team trying to build things fast and open and the security team trying to post things down and make it more secure you know it becomes even more problematic if you kind of go to the cloud where you've got pockets a developer's kind of thing do things in the DevOps way really as fast as possible and sometimes the controls are not put in place in fact no the big as I said the biggest issue for the cloud is not so much you know malware it it's more about miss configuration that's why you're seeing the big breaches and that's more of a customer thing to do and so I think what the seaso is trying to do is make sure they apply the controls appropriately and again their job has become much harder now we've got all the multitude of endpoints that they didn't have before they've got now there when that's not just the closed MPLS network is old off different types of broadband 5 G's coming towards the end of this year next year as well the data centers may have decreased a bit but they've still got datacenter capacity and they're probably got 5 or 6 hours and 20 different SAS applications that put a deal with and they've got to deal with developers in there so it's a harder job for them and they need to melt or add those tools but come back to that single point of management great stuff John Madison CMO EVP great insight there it's almost a master class right there you laid it all out on what's going on a final question any change is what any other news updates on the four net front I know you guys got some answer I didn't see the breakouts of the session I had something else going on I think I've been walking dog and do some other things but you know being at home and to take care of things what's new what's what's out that people might have missed that's coming out of for today you're telling me you didn't have 60 hour a breakout on dedicated I don't think yeah we've you know we've have a lot going on you know we have a big R&D team here in North America and Canada and with a lot of products coming out this time of the year we bring out our 40 OS network operating system with 6.4 over 300 new features inside there including new orchestration systems for sp1 and then also we actually launched on network processor seven and the board gate already 200 F powered by four network processor sevens it's some system out there and provide over 800 gigs of fire or capacities but in bill V explain acceleration they can do things like elephant flows huge flows of data so there's always there's always new products coming out of 14 it sure those are the two big ones for this quarter you guys certainly are great interviews to talk to great a lot of expertise there final final question you know everyone every company's got their culture Moore's laws cadence of Moore's laws Intel faster cheaper smaller what's the for Annette culture if you had to kind of boil it down what's it you guys are always pushing great products out there all high quality I'll see security you got to be buttoned up and have good ops and controls but you still need to push the envelope and have stadia what's the culture if you had to kind of boil the culture down for Porter net what would it be that's always an interesting question and so the company's been going since 2000 okay the founders are still there NZ's CEO and Michael Z's the CTO and I think that one of the philosophies is that listen to the customer very closely because you can get distracted by shiny objects all over the place I want to go and do this oh yeah let's build this what about this and in the end the customer and and what they want may get lost and so we listen very closely we use you know we have a very high content of technology people who can translate the customer use case into what we should build and so I think that's the culture we have and maintain that so we're very close to our customers we've been building very quickly for them make sure it works it needs tweaking then we'll look at it again a very very customer driven always great to hear from the founders you guys had a great event accelerate 20 that's the hashtag some great highlights on Twitter some commentary there and of course go to Ford a net site to check out the replays Sean man so thanks for taking the time to share your insights here on the cube conversation I really appreciate it thank you okay it's cube concert here in Palo Alto we're bringing you all the interviews during this time we have our quarantine crew the cube is virtual we'll do whatever it takes to get the interviews out there and get the stories out there and the people behind the tech making it happen I'm John Fourier thanks for watching [Music]

>> Announcer: Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel along with its eco-system partners. >> Hey, welcome back to theCUBE's coverage of AWS re:Invent '19. This is our third day in Vegas. That's a lot of Vegas. I am joined by my co-host Justin Warren, the founder and chief analyst at PivotNine, and Justin and I are welcoming back one of our CUBE alum. Joining us next from MongoDB is Sahir Azam, its chief product officer. Welcome back! >> Thank you so much, I'm happy to be here. >> So talk to us about what's going on at MongoDB, I know we've had you on the program before, we've had MongoDB, but what's sort of the latest and greatest? >> Yeah, so we're continuing to grow very fast, and especially our cloud product Atlas. We've got two million developers using the platform today, 13,000 customers, many of which are on the amazing AWS platform, and I think people are really embracing the idea of a multicloud database service and a data platform they can have the flexibility to work with no matter where they are. >> Talk about, sorry, Justin, about multicloud a little bit more because it is a symptom as one of our CEOs, Dave Vellante, calls it. A lot of companies have inherited it, it's more by whether it's organically, or it's by acquisition, or developer preference. It's a state in which a lot of businesses are operating, but it's challenging. >> Yes. >> What are some of the things that you're hearing with respect to customers? How can you help them deal better in that world? >> Sure. So, yeah we definitely see some of those exact trends, so, you know for large enterprises, many times, they have different use cases in different business units, where developers or application owners prefer different cloud providers. Oftentimes it's acquisition, but also at a strategic level, at the CTO, CIO, or even CEO level, you know, there is a forethought strategy that it's going to be a multicloud platform world, and now what we see is many customers are still very much focused on a single cloud provider to build-up the skills on, but with a close eye to a second or third tier provider in the architecture that they will scale and balance over time. So, I think it's early days, but the trend is definitely rising in what we're seeing. Now, one of the things that makes a multicloud strategy really hard to implement is the data. You know, especially transactional data that runs live applications that are serving real customers, that makes an application and a development team really stuck on a certain platform. So, what we're focused on at MongoDB is really de-coupling that data layer from the underlying cloud infrastructure providers such that if you want to leverage the benefits of the different services AWS has in their rich ecosystem, but then maybe plumb in something from another provider, we make that extremely easy to do with the click of a button, and move your data across those cloud providers. >> Yeah, so talk about the mechanism for doing that a little bit more, because that's really tricky to do, and that's one thing I think people have been concerned about the idea of multicloud, is that, well, are you actually running in multiple clouds simultaneously, or is it more that, well actually sometimes we just want to move a bit from here to there that we'll use for different applications? >> There's sort of three trends that we see you know, and we're a data platform player, so our use cases are sort of bounded around database technology, data analytics. So, the first is for customers who want high availability across multiple regions within a certain geography, so let's say you're dealing with personal information of German citizens in Germany, Amazon has a region in Germany, only one, and maybe you want Azure or GCP to be a second region for high availability, and you need to rely on a secondary provider, because there's only one from a particular cloud of choice in that geo, so that's sort of one high availability kind of use case. The second is leveraging the benefits of all these different services that the cloud providers themselves are releasing, so we hear a lot of customers that say, you know, Amazon's my preferred partner for operationalizing my app. We use their services, our database runs there, however, we may want to take some of that data, even if it's for a week, even for a few days, a month, and perhaps move it over to another provider to leverage some new analytic service or machine learning, or AI algorithm that they might have. Today, that's really challenging to do. It's the idea that you can click a button, and create that replica, and move that data over very easily is something that people are asking from us. And then the third is geographic reach. So, our database platform, Atlas runs in 70 global regions worldwide, across AWS, Azure, and GCP which makes it the most widely available databases service on the planet. And one of the interesting use cases for that is, let's say somebody is using a single cloud provider for 99% of their work load, but suddenly they see their app take off in Taiwan, you know, maybe another cloud provider has a region in Taiwan, just mix and match and add that region into the architecture very seamlessly. So, those kind of three categories, high availability within geos, the ability to leverage, you know, the rich service offerings and mix and match, and then the geographic reach, are the three things we see for multi plat at a strategic level, beyond the reactive angle of acquiring a company and learning how to have to manage multiple clouds that way. >> That does sound like it's a bit of a trend that we're hearing and particularly today, I think, Lisa, where enterprises want choice, and that customer choice, of being able to choose things that actually suit me, rather than necessarily which vendor I'm buying my infrastructure from. That sounds like something that we're hearing a lot. >> Yeah, and we've invested a lot of time, engineering effort, working with Amazon, working with Google, working with Microsoft, to unify that data layer across the three cloud providers, and I think that's something unique that Mongo's really focused on. >> But there were so many announcements that came out, in Andy Jassy's keynote a couple of days ago. I think I read 23 announcements just in the first 20 minutes, or something of his keynote. So much information, but I'm curious, did anything that they announced surprise you in terms of, hey, customers are living in this multicloud world, there's use cases, there's reasons for it? Any shift that Amazon is making or announced this week that you thought, yes, some of these things are becoming a reality? We have to go where the data is, and we have to deliver what's best for our customers. >> I mean, I think Amazon is a very customer-centric company. I don't think I heard any announcement that particularly acknowledged the fact that it's going to be a multicloud world, you know, I think they're still the market share leader, they have a rich set of offerings, and they're going to continue building on that which I think makes a lot of sense from the position that they're in. I think some of the announcements that are interesting to us, definitely the idea of having lower cost, higher performance ARM hardware and chips for our database vendor. If we can lower the price performance curve for customers on top of that infrastructure, that's exciting for us, and we always think it's interesting, in a AWS keynote that's two or three hours long that about a third or half of it is talk about data. We love data, so the more rich sets of services we can surround and integrate Mongo into, the better, so, exciting for us. >> Data seems to be like the next generation of cloud, data can become a huge asset for any business in any industry, whereas, there are companies and times where data was a risk, a vunerability. What is a great example, in your opinion, of a MongoDB customer who has done a great job of transforming to where data is now a huge asset, and a driver of business differentiation? >> So, one interesting customer example I really like is Axiom. They're a marketing data provider, data has been the heart of their business for a long time, but traditionally their business would be packaging up and shipping data sets to their end customers, in a very custom bespoke manner. What we worked with them on is leveraging our cloud platform Atlas, along with some API technologies that we have, and a product called Stitch, to make it very easy for them to create custom APIs to allow their end customers to access that data programmatically. And since we manage and run that on their behalf, their development team, their operations team don't have to worry about the plumbing and managing of all these API layers and all that, they just stamp out these custom APIs, we auto-scale them on top of the rich Mongo database on the back end, and so we've allowed them to really take the data business they were in, but really modernize it by exposing it directly to developers programmatically instead of just shipping data around which is expensive and cumbersome. So I think that's a really interesting example of a data company transforming itself, and kind of innovating in the cloud with some of the technologies we provide, obviously, on top of the Amazon platform. >> So, you mentioned transforming, that's definitely been a theme of the show. So MongoDB is a different way of actually managing data, so compared to traditional methods. A lot of enterprises still have a lot of investment in RDBMSs, more traditional kind of databases. What are you seeing when customers come to MongoDB and start using this different way of storing and managing data? What is that transition for them like? >> Sure, so I think the thing that MongoDB's inception 11 years ago through now, what drives our adoption, I should say, is really the fact that developers love our platform. The document model, the MongoDB API is just a much more flexible and natural way for developers to think about writing applications, so, you know, you're building an application, you might be managing a customer object, a product, an account. These are all sort of business objects that get represented in a developer's mind and then in an application, but then if you put that in a relational database, you're chopping that up into rows and tables, and then having to rejoin that back together just to make sense of the underlying information you're trying to represent. Mongo gets rid of all of that cognitive dissonance, and that's what really unlocks that developer productivity. Now, the interesting thing about MongoDB is as a non-relational database, we have looked at the legacy RDBMS providers and said, what are the things that are really strong about those platforms that we can bring forth and apply to this much more agile and natural data model? So things like data governance and schema, strong transactional guarantees, enterprise management functionality, enterprise security and encryption at a very deep level. These are things that large mission critical application developers and operators really need. And they don't typically find them in fast databases, scalable databases, like MongoDB. So what we've done is really merge the best of the legacy traditional databases, the things people expect in a rock-solid mission critical database, but brought it forward in a model that's much faster for developers to move quickly on, and so the way that represents itself in our business, roughly about a third of our business any given quarter, tends to come from legacy migrations off of some traditional relational database, and the driver for that is modernization. People want to move those apps to the cloud, they don't just want to lift and shift from one relational database to another necessarily, that might have certain cost benefits from one provider to another, but it doesn't unlock that developer agility, and that's why they're choosing MongoDB. >> So all in the spirit of transformation, the ability for MongoDB to unlock the developer productivity, one of the things Andy Jassy talked about on Tuesday was, one of the four essential pillars of transformation. It's got to come from the top down, it's got to come from that senior executive level, they've got to drive it down aggressively. As chief product officer, where are your conversations? Are you still, in terms of feedback and, you know, customer advisory information, are you still talking mostly to the developer folks who were the primary users, or are you also having those higher level-- >> Sahir: Both. >> Both, tell us a little bit about that. >> Now what's interesting about a data technology like Mongo is, it's not a top down sort of sell. No CIO, CTO, line-of-business executive is going to dictate down to their developers, thou shalt use this particular database technology, or what not. Every development team is going to choose a technology that allows them to move fast and meets their requirements. So, what we've really done is we've focused on engaging with our customers, our sales organization, our marketing organization, our developer relations organization, is merging a strategic top-down sort of model with those CIOs and business leaders about how MongoDB can transform their business as a data platform. Get that sponsorship, get that executive alignment, to be a strategic provider, but then at the same time, really fostering that community that MongoDB's always been known for bottoms up to make sure that more and more of these applications see the power and value of MongoDB. So we have to merge both those motions. If we were just bottoms up, then I think we wouldn't be as strategic as we are in many of these organizations in terms of how transformative as a vendor and a technology provider and partner we are. But at the same time, if we lost our roots with the developers, databases don't get chosen from the top down, they get introduced and put on the list, maybe, and sponsored into the account, but we've got to build and earn that trust with developers directly. >> Yeah, so you've had incredible success, incredible growth so far. >> Sahir: Thank you. >> What's next for Mongo? >> So, I think a big part of our journey for the last three or four years has been really, adding a second major growth engine to the company by building out our cloud business. So that was our MongoDB Atlas platform built on top of AWS, Azure, and GCP, and that is the fastest growing part of our business, and will clearly be, you know, the majority of our business in the future. The next year to two years, is really about transitioning from a single data product company to a data platform company. So earlier this year, we announced not just the core foundational database features we're always building on top of, but also a big step into analytics, with our Atlas Data Lake product, which allows development teams and analysts to run queries using the Mongo query language they love, but on top of S3, where they have mountains and mountains of data stored from all these different sources. And at the same time we've also added things like full text indexing, so instead of standing up a, search cluster next to your Mongo database, having to worry about copying data just to get full text search in your application, we merge that capability directly into the Atlas platform. So, a big part of our journey is saying, once we have so many customers on the platform, how can we add more value, and yet still merge that all in a very expressive developer experience with our query language? So they're not dealing with 13 different databases and four copies of their data and integrating and shuttling that all around, but is a very prescriptive experience for them. >> Wow, Sahir, thank you for sharing all the innovations that are going on at MongoDB with Justin and me on the program today. A lot going on. >> Yeah, thank you for having me. I really enjoyed the show and coming on theCUBE. >> Lisa: Good, we appreciate your time. >> Great. >> For my co-host Justin Warren, I'm Lisa Martin, and you've been watching theCUBE from Vegas, baby. AWS re:Invent '19. Thanks for watching. (electronic music)

>> From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE Conversation. >> Hello everyone, welcome to this special CUBE Conversation here in Palo Alto California, theCUBE headquarters. I'm John Furrier, host of theCUBE. We're here with Dheeraj Pandey CEO and Founder of Nutanix. Great guest, been with us for 10 years. Was on the cube in 2010 when we first started doing theCUBE coverage of events was at VMworld, Dheeraj, great to see you. >> Pleasure. >> Thanks for coming in. >> Thank you. >> You've had such a great journey. I've been so impressed with you as an entrepreneur, the hustle, the early days when you were misunderstood to the growth and going public and continuing to compete. Congratulations to you and your team. It's been great. >> Thank you, no, it's been a journey and it's going to continue to be a journey. >> A lot of competitive pressure. A lot of cloud happening, a lot of server dynamics in the marketplace with On-Premise now getting validated as a part of this multi-cloud hybrid equation, certainly not going away, but still growth of the cloud has been huge. What's the big focus, 'cause you have your Nutanix Next conference coming up in May. I'll be there with theCUBE, what's the focus, what is the theme of the event? What's the big focus? >> Yeah, no, in fact we complete 10 years this September, so it's a decade since the beginning of time for Nutanix. And we are focusing on the things that we're good at. We are good at what I call the three D's. So it's a three D view of the company. The first D's data, we are really good at data. And we're doubling down on data. We're very good at design, we've done a very good job of simplification making elegant consumer grade and taking clicks away rather than things taking months, how can it be done in seconds and hours, and we're very good at delivery, you know, the third D being delivery, you know, it's not just delivery of our software through all different form factors and our appliance and software and subscription and other servers, but also customer support, customer success, which has really endeared us to our customers. So if you think about what this conference is all about, obviously it's about the customers and as the power of social proof, the fact that they learn from each other and we learn from them. But it's really about reinforcing the three D's. Data, design, and delivery. >> And the theme is invisible clouds. Period, visible IT, invisible cloud, so I'm assuming that's, make that, abstract that away, multi-cloud in there, probably a theme. Visible IT, that's supposed to be invisible too, but what does that mean? I get the invisible cloud 'cause you want to make it seamless, multi-cloud, hybrid cloud. But what's visible IT, how do those words play? What's the play on words there? >> Yeah, I mean, you know, we, first of all the word invisible is really powerful and we use it a lot and it's very unique to Nutanix, you know, not everybody uses the word invisible as much as we do, but the idea is that machines should become invisible. Software and systems and tools and those things should become invisible. And then humans should become visible and by the way, there's this really good antithesis, sort of the polar opposites of machines versus humans that goes on in many other walks of life, I mean zero trust when it comes to security. Machines should not trust each other. But full trust, when people need to trust people. So when it's an organization of people you need to be the opposite of zero trust. Same thing is true for invisible machines invisible clouds with visible people visible careers and I think what's happening is that as the cloud hype cycle actually matures, CIOs are talking about cloud cloud cloud, but the grassroots is basically saying like do you even know the legacy apps of the last 20 years? Do you understand the challenges of what we call the laws of the land? Data compliance and regulations, laws of physics which is the gravity of data and the gravity of people and operations and laws of economics, owning and renting. So I think what's happening is that the cloud revolution is really being dug like a Eurotunnel, from two sides. Top down from C-level people are saying let's go transform ourselves to the cloud. And we are helping the grassroots really go and translate that, say look, this is only possible by doing these things because we have to be respectful of data sovereignty, data gravity, and applications and the economics of that. So, in really helping the CIOs build trust with the grassroots. As opposed to-- So essentially, you're operational as a cloud 'cause I can hear. We've interviewed a lot of CXOs on theCUBE as you know, take that hill, go to the cloud, move everything to the cloud. Wait a minute, we got, we're closing a pin. So to make sense of that vision, it's got to be operationalized, that's kind of what you're getting at. >> Absolutely, absolutely. And then finally there's a, I mean look what happens in computing, we make things smaller all the time, you know, we started with mainframes and we ended up with serverless. And along the way we had obviously Unix and x86 and container, VMs and containers and so on. Same thing with personal computing. We started with desktops and we ended up with wearables. So the fact that there's a billion dollar data center is the new mainframe. The fact that there's going to be a big cloud data center only two places in a big country is actually quite the antithesis of computing, we have to make cloud be everywhere and make it about software. To operationalizing the cloud and making it into a half a trillion dollar market will be about software. >> This whole mainframe is in the cloud or mainframe distributing computing. Software industry kind of come back in vogue. It doesn't go away, it's all the same game. It's just distributed out around in different formats, that's kind of what's going on here. >> Absolutely, I mean go back in time to distribution. Apple was a vertically integrated stack. So how does Microsoft come and really compete against Apple, they said look PC is about software, they said look PC's not about hardware, it's about software and the market becomes 10 times larger because they really bring in other partners who make money with the Windows Operating System. >> That's just more enabling. There's more demand, there's more growth. >> Absolutely, and the same thing happens again 15 years later with iOS versus Android. So Apple says smartphone is about vertically integrated stack, and Google comes and says no, to make the market 10 times larger, Android is about software. And then other handset manufacturers come and make money, so cloud is at this juncture where to take it beyond, 50, 60 billion dollars to half a trillion dollars, it has to be about software. >> Dheeraj, one of the things that I'm impressed with with you as an entrepreneur and your team is you fit the profile of the classic big idea. Be different, have good product leadership and pick a way that's going to have a big, totally adjustable market. You did that and you didn't waver, so I reviewed your analyst meeting from Wikibon and involved third party analysts. A hundred billion dollar addressable market. So big market, check, private cloud trend which you called early and Stu Miniman also called that on Wikibon is not going away, you have a stack for that. Large customer base, you have what 12 thousand customers plus and growing. Great revenue, strong revenue, and you got refreshes coming because the technology continues to shift in the wave that you're on. So, congratulations, that's good health meters. But there's now competitive pressure. The genie's out of the bottle. People know what you're doing. They figured it out and they're going to try to compete with you. This economy of scale that you have there's economy of scales others have specifically Dell, Dell EMC, VMware have been highly competitive with you. How are you responding to that and what's the landscape look like? >> Yeah, look, we've always been about disrupting ourselves, and that's the way we've actually grown our company. Very contrarian way of thinking about it but if we go back in time four, five years ago we're an appliance company, and we said we're going to do an OEM relationship with Dell and then Lenovo and others. All of a sudden people started competing with yourself, and for us it was like the more we compete with ourselves the better it is, today I think if you think about where the company's real response to any competition is to really compete with ourselves. I typically don't get wavered or changed by what's out there, we don't compete with anybody else, if we can keep competing with ourselves and get better in solving our customers and those three D's I talked about being even deeper in data, that VMware can't even touch us on simply because they have to compete with EMC on that and I don't know whether they actually have the gumption to do that, we do actually. We have to be better at design. Make the control plane even simpler. Understand what it means to virtualize the cloud. And get better at delivery, so if we can keep getting better in the three D's and we can keep competing with ourselves. We just did a really good announcement at HPE where we're going to compete with ourselves one more time because-- >> Talk about that announcement 'cause I think this is different. So HPE bought Nimble Storage so they already got the storage piece. They've got tons of servers, they also compete with Dell, what's your position with HPE, what's the announcement? What's the partnership? >> Yeah, so we're going to do a two-way relationship where we're going to be able to our sellers can quote HP servers and their sellers can actually quote our operating system. We have this rainbow which we call core essentials enterprise, Nutanix Core which is about hyper-convergence. Modernize your infrastructure. Nutanix Essential which is how we build a private cloud, and then Nutanix Enterprise which is really about navigating and simplifying the multi-cloud journey of the customer. And HP's going to take this stack to its customers. Again, we started to compete with ourselves because our appliance business was not based on HP, but now it will. Similarly, they will compete with themselves. And that's how companies transform themselves. When they compete with themselves rather than somebody else. >> And it's always the old expression, eat your own before your competition does. That's a cannibalization, kind of MBA concept. You guys are aggressive on that. You don't mind doing that and taking that risk. >> No, in fact if you don't do it, someone else will. It's better to do it in the controlled way ourselves. >> Got great, great management styles. So let's talk about, you mentioned control plane earlier, you have a quote on your deck that says, that I reviewed, it says control plane matters, this speaks to some of the product leadership. What does that actually mean, the control plane message, 'cause we hear this a lot come up in multi-cloud hybrid, and certainly within the data conversation around data control planes, control planes. For you guys, what does that mean? Control plane matters? >> Well if you take back like 10 years ago. We were very bold and audacious. We were the only company to say look we will not be building a tab in vCenter. Contrarian, highly contrarian. Most people said you'll lose a lot of deals because you are not adjunct to vCenter. You're not a tab in vCenter, every hardware renderer was really bending over backwards to please VMware because that was the only way to the heart of the virtualization administrator. We took a very different stance. Prism was the control plane, they said if you do a really good job at Prism make it a distributed scale out platform. Make it consumer grade one click delight. Then customers will actually look at this as a very powerful thing, and then we virtualized the hypervisor. So Prism was a multi hypervisor platform. It worked for Vmware, it worked for Hyper-V and it worked for Nutanix AHV. So over time, we just kept doing more of it. So now we have a control plane for multi-cloud. We were saying look, the world does need an automation orchestration engine. That is multi-cloud come is that thing for us. We've taken Prism to the next level with Prism Pro which is about ML and AI and what does it mean to really do operations management and capacity planning and security and analytics. So, we've doubled down on design which is the second D that I talked about with these control planes and going forward and as you see us getting to multi-cloud desktop delivery, we acquired a company almost a year ago, which is really about a cloud native desktop delivery solution where, now the control plane of desktops could belong in the cloud but the desktop itself could be running on prem. And that's a very powerful concept that you can have these cloud enabled cloud holstered cloud serviced control planes but the data place could actually be anywhere. It could be running-- This is the invisible cloud concept you're talking about. Absolutely, yeah. In fact the fact that the controller could be running anywhere, and the thing it controls could be running someplace else. >> The question, that's great stuff and that's great product leadership and again, invisible cloud, people don't want to deal with multiple code bases They want to have seamless operations. So with that I got to ask you your cloud positioning because every enterprise now because it's from the top end. Now it's top comparative, what's the cloud positioning because we now see on premise, super important a-du-is-ca outpost. The data's going to reside on premise in the cloud, it's all going to move around. What is the cloud positioning that you talk to your customers about when they say hey, we like Nutanix but we got to go to cloud, what's the positioning? >> Well our positioning is that cloud has to be about software. It has to seep everywhere, it has to be injected everywhere, our software should run no just on prim but in an AWS bare metal. There's a bare metal service and our software should run there. There will be an Azure bare metal. We already run in GCP metal so our software can run on top of GCP as well. Of course it is on prem and we are already working on our own disaster recovery as a service, desktop as a service where we become the service provider for many of these hybrid services that customers actually need from us. So cloud is about ubiquity, it's about portability, I mean the strength of any software company is portability. If we can make ourselves available in every server, every hypervisor, and every cloud, I think we've done a very good job. >> My final question I want to ask you is when you go to your event coming up invisible clouds, visible IT, you got to give the customer the 20 mile stare. You got to show 'em the 20 mile vision and the bridge to the future that they want to cross with you, that's the main value every company has to do as CEO. What is that story, what's the pitch to the customer saying we've got you covered today as you're organically building that operational cloud path, but I really want to know that I have a partner for the next generation, what's that story that you tell them? >> Yeah, I mean, even as I said before. Any big project, whether it's Panama Canal Suez Canal, Eurotunnel, you have to dig it from both sides and then you eventually shake hands and it becomes a historic picture, which is what we've known about the way the English side and the French side met. I think the way CIOs are talking about the cloud, the way grassroots is perceiving more of the cloud as you called it operationalizing. I think we really have to do it from both sides. And we really don't talk about the three D's. Data, we've done so well in data. We've done so well in design, we've done so well in delivery, and then at times we've actually screwed up like in the last two, three, four years, we might have gotten more complicated, we might have gotten more complex, so we go and even ask for forgiveness and open ourselves up, talk about the evaluability of the company and people like that, they didn't want to connect to an auto machine, but they wanted to connect to humans on this other side. As a business, we are not machines. We're actually humans, and that's what resonates in the conference. >> Dheeraj, thanks for coming in and sharing your insight, great to see you again, congratulations on the business performance, we'll see you at Nutanix Next in May, May 7th, thanks for coming in. >> Thank you, my pleasure. >> I'm John Furrier here in Palo Alto for CUBE Conversation, thanks for watching. (jazz music)

>> Live from London, England, it's theCUBE. Covering .NEXT Conference Europe, 2018. Brought to you by Nutanix. >> Welcome back, I'm Stu Miniman, my cohost Joep Piscaer, and you're watching theCUBE here at Nutanix .NEXT, London, 2018. Happy to welcome back to the program the co-founder, CEO, and chairman of Nutanix, Dheeraj Pandey. Dheeraj, thanks so much. Congratulations on 3500 people here at the third annual European show, and thanks so much for having theCUBE. >> Thank you, my pleasure. >> All right. So, Dheeraj, first of all, you got a lot going on. Big company event here, last night you announced the Q1 2019 earnings. I guess, step back for a second. Nutanix is now, nine years since the founding, you've been public now for a little while, you got to be feeling good. The company's reached a certain size, very respected in the marketplace. So how are you and the team feeling? >> Yeah, well, I tell people that it's actually fun to be a public company. And obviously there is a cost to being a public company, because you're on a quarterly treadmill, in some sense. But Wall Street also keeps you honest. Just like Main Street keeps you honest on quality of product and customer service, Wall Street keeps you honest on spend and what does it really mean to grow at scale. So I like the fact that there is two good streets that are keeping the company honest. And it's really fun to think about capital allocation, one of the big things as you grow. I mean, you're going to spend more than a billion dollars this year alone. How do you allocate capital wisely is something that I think a lot about in (mumbles). >> Yeah. So, at this show, you kind of change some of the positioning of the portfolio. It's the Core, Essentials, and Enterprise, and right, that asset allocation, when I look at Essential, Xi Cloud, there's all these different pieces, some of them through acquisition, some of them created internally. You need to be careful that you don't over-commit, but when do you decide to kill stuff or keep it going, so you got a lot of plates to spin now, a lot more than you did a year or two ago. >> Yeah, absolutely, and it's not just product development. It's also marketing and sales and G&A. I mean, there's other departments we need to think hard about. Like, how do you create brand awareness for these new things? How do you do demand generation? How do you have a specialty sales force? All those things have to be considered, so, nine years, it's been a journey, but it still looks like it's nothing. And we're still a very small company, and we need to think hard about the next five years, in some sense. >> Yeah. So, one of the metrics you gave Wall Street to be able to look at is, what percentage of customers are using more than just the Core? So the Essentials or the Enterprise. And if I got it right, it's up to 19% from 15%, the quarter before. I wonder, is the packaging, how much of that is for Wall Street? Somebody cynically might look and be like, hey, is the Core market slowing down? And therefore you need to expand. We've all seen public companies that need to go into adjacencies, and shouldn't you stick to your knitting? You've got a great solid product with leadership in the marketplace. >> Yep, absolutely. Also, look, we are not bundling them in SKUs so we cannot force customers to actually buy them. We're not doing financial engineering of dollars, because these not SKUs or bundles. This is a journey which is mostly advisory, in some sense. This is how you should start, this is how you should go, and this is advisory for our sellers and our buyers and our channel people. Everybody needs to say, look, have the customer go through the journey. If you had to do what he just said, probably would've bundled them in SKUs and then allocated capital to one or the other. I think, to your other comment about just sticking to the core, Juniper stuck to the core. And many companies out there which just stayed as a single-box company, they stayed at the core. And eventually you realize the market has moved faster than your core itself. So there's this business school thinking, they call it the Icarus Effect. The Icarus Effect is all about, I'm so good at what I do that I can fly to the sun and nothing will happen. But you don't realize that Icarus, the wings were actually pasted using wax. And you go to the sun, and the sun actually melts the wax. So companies like FGI and SUN, Norca, many companies just stuck to one thing. And they couldn't evolve, actually. >> Obviously you're not sticking to the core alone, right? You're expanding the portfolio, I mean, you're not just an infrastructure company anymore. You do so much on top of the infrastructure on-prem. You have so many SAP services, so how do you manage the portfolio in terms of the customer journey? Because there's so much to tell to a customer. How do you sell it? How do you convince a customer to go from Core to Essentials to Enterprise? >> The most important thing is leverage. Is Essentials going to leverage Core, and is the Enterprise going to leverage Essentials and Core itself? Case in point, Files is completely built on top of Core. So every time somebody's using Files, they're also using Core. If you think about Flow, it uses AHV underneath. Frame, and case in point. When it's going to deliver desktops, it's going to use Files because every desktop needs a filer as well. And then when Frame delivers desktops on-prem, it's going to use all the Core. So the important thing is how they don't become disparate things, like they're all going in their own direction, is there a level of progressiveness where you say, well, if you're using the Enterprise features, a lot of them actually go in and drag in the Core as well as Essentials. So how do we build that progressive experience for the customer, where each of these layers are actually being utilized, is the important piece. >> Dheeraj, so, we're talking a lot about the expansion beyond the Core. But there was a pretty significant activity that your team did on Core itself. So the first time I heard about it, it basically said, we're doing an entire file system rewrite. Think of it almost as AoS 2.0. Now, from a product name, I believe it's 5.10, so I might have trouble remembering which release it was, but talk about what went involved in that. Obviously a lot has changed in the nine years since you created it, so. >> Absolutely. Yeah, yesterday in the earnings call I talked about it too, that people scoff at Core infrastructure. Like, oh, it's going to be a commodity because it's good enough infrastructure. But then I argue that there's no such thing as good enough infrastructure. And companies struggle when they don't focus on infrastructure itself. It's like food, shelter, clothing in the Maslow's hierarchy of needs. If you don't get that, then there's no point self-actualizing it. So, Core infrastructure completely destroys network insecurity. You got to get it right. I mean, look at Oracle, how it's struggling with IaaS. And look at Google, they're trying to figure out how to make it relevant for the Enterprise. Azure has like three or four different stacks for infrastructure. One for old 265, one for Azure DB, one for Azure, and now they're rewriting it for Azure itself. VMware has three different infrastructure stacks. One for three tier, where they are very happily, they're saying, look, let EMC, their NetApps actually are underneath, and Cisco's, and stuff like that. And then they have this software-defined infrastructure with commodity servers. And finally, they have VMware-enabled AWS which is going to use AWS services. So now you have three different forks of your core base, in some sense. And for us, what's important is how we use a single core base for everything. So architecture matters. I was arguing yesterday in the earnings call that good enough infrastructure is an oxymoron. You need to get core right before you can go and try to live the other layers of the Maslow's hierarchy of needs, actually. And that's why we went back and thought about, as the workloads were growing and increasing, and we had mission-critical stuff in memory databases, what do we need to really do about the way we lay out the data and lay out the metadata? So as you know, metadata is at the core of anything in systems, and especially storage systems. And the metadata of our erstwhile system was actually very completely distributed. And then we realized that some things can be local, and some things can be distributed, and that's better scale. Again, going back to this understanding of what things can be represented locally for a certain disk versus what things need to be global so that you can go and say, okay, where is this data really located? What drive? But once you go to the drive, you can actually get more metadata. So, again, you're getting more progressive scanning. So at the end of the day, our engineers are constantly thinking about performance and scalability, and how do you change the wings of the plane at 35,000 feet? It's a very big challenge. >> So that's one of the issues, right? So you're still focusing on your own infrastructure layer, right? But many customers do already have presence in a different hardware stack, or the public cloud, or some service provider. So not everything runs on your platform. So how are you planning to deliver the services ensemble to customers that don't necessarily run on AoS? >> So that's the multi-cloud journey, which is basically the enterprise journey of our customers. I said this yesterday in the earnings call as well, that all our services should be available both on-prem and off-prem. This idea of a VPC, that is multi-location, is what hybrid cloud is all about. So how do you get a virtual private cloud to really span multiple clouds in multiple locations? I think you saw from the demos today of how you're really running all of AoS on top of GCP virtual infrastructure. And in the course of the coming year or two, you'll see us do the same thing, BEM at Amazon, BEM at Azure. Because they deliver servers in their data centers and that's leverage for them because they've already gone and spent so much money on data centers that it's easy for them to deliver a physical server that our software can run on top of. And if people are not using AoS, they'll still want to use things like Frame and Beam and COM and other such things like that. >> Yep, Dheeraj, what are you hearing from customers and how do you think of hybrid, as it were? You know, a lot of attention gets played to things like Azure Stack from Microsoft from VMware on AWS, I know you've got some view points on this. >> Yeah, no, in fact, so if you go back five years, hyperconvergence had become a buzz word maybe three, four years ago. And there were a lot of companies doing hyperconvergence. And only one or two have survived and it's us and VMware, basically have survived that. Everybody else has a checkbox because the customers said well, what about that? Will we have a check box? But, it's really about operating system sort of hyperconvergence. And it has to be honest. And it has to really blur the lines between compute and storage and networking and security. I think hybrid needs to be honest and one of the killer things that hybrid needs is blurring the lines between networks, blurring the lines on storage so you can do one click replication and one click fail over. So a lot of those things have required a lot of innovations from us. That's why we were delayed in Xi. We didn't want to just put up data centers and just like that. I mean, if you go back in time to many hardware companies were putting open stack data centers and calling it their new cloud in response to Amazon. And VMware tried vCloud Air. And they had a charter to go spend money. They weren't going to spend a ton of money on hardware. Without even knowing that the cloud is not about data centers. Cloud is about an experience. It's about eCommerce and computing coming together. And you have to be passionate about a catalog. You know, the marketplace, the catalog so that people can really go and consume things from a catalog. I think that's what our experience has been that. Look, if you don't think of it like a retail giant or retail customer, which is what Amazon has done such a good job of. You know, they've thought about computing as an eCommerce problem as opposed to as a compute storage networking problem itself. And those are the lessons that we have learned about hybrid just as much >> Alright, you did a nice job on the keynote, laying out that Nutanix, like your customers, you're going through a journey. The crawl-walk-run, if you will. We got a tease in the keynote this morning about something cloud native. Where you're going. Final question for you is as you look at the company, you said it's still young, where are your customers going, where are some of the things they need to work on, and that Nutanix will mature with them as we look to move forward? >> Well, I mean, look. I think everybody knows where customers are headed. They're questioning who fulfills the promise because the requirements are all the same. They all want to go and use next generation infrastructure, they want to modernize their data centers, the infrastructure. They want to use some things that they want to own, some things they want to rent. The question is, where is the best experience possible? And by that, I mean not just systems experience of hybrid clouds but also customer service and having an ever-growing catalog and being able to deliver things for developers and devops. And technology will come and go. Two, three years ago, the Puppet and Chef were the hottest thing on, now today, it's Kubernetes. Tomorrow, it's going to be something else. It's the fact that what you see is what you do. And what you do is what you say. In our business, it's about integrity. I was arguing about this yesterday in the earnings call, as well, that building business software is a little bit easier. I shouldn't trivialize it as much but if people use business software, they can work around weaknesses of business software. But if you are in the business of infrastructure, applications cannot work around weaknesses of infrastructure. So integrity matters a lot in our space, actually, and that is about great products, great customer service, fast innovation, recovering fast, being resilient. Those are the things that we focus a lot on. >> Alright, well, Dheeraj, thanks again, always. We didn't even get to talk about the width part, the fourth H that you've been talking about for the honest, humble, and hungry. So, thank you. Congratulations to the team and always appreciate you having on our program. >> My pleasure. >> Alright, for Joep Piscaer, I'm Stu Miniman. Stay with us. Two days live of wall to wall coverage. Thanks for watching theCUBE. (light music) >> I have been in the software and technology industry for over 12 years now. And so I've had the opportunity as a marketer.