(upbeat music) >> Hello, everyone, welcome to theCUBE. I'm John Furrier, the host of theCUBE in Palo Alto, California. Also it's SiliconANGLE News. Got two great guests here to talk about AI, the impact of the future of the internet, the applications, the people. Amr Awadallah, the founder and CEO, Ed Alban is the CEO of Vectara, a new startup that emerged out of the original Cloudera, I would say, 'cause Amr's known, famous for the Cloudera founding, which was really the beginning of the big data movement. And now as AI goes mainstream, there's so much to talk about, so much to go on. And plus the new company is one of the, now what I call the wave, this next big wave, I call it the fifth wave in the industry. You know, you had PCs, you had the internet, you had mobile. This generative AI thing is real. And you're starting to see startups come out in droves. Amr obviously was founder of Cloudera, Big Data, and now Vectara. And Ed Albanese, you guys have a new company. Welcome to the show. >> Thank you. It's great to be here. >> So great to see you. Now the story is theCUBE started in the Cloudera office. Thanks to you, and your friendly entrepreneurship views that you have. We got to know each other over the years. But Cloudera had Hadoop, which was the beginning of what I call the big data wave, which then became what we now call data lakes, data oceans, and data infrastructure that's developed from that. It's almost interesting to look back 12 plus years, and see that what AI is doing now, right now, is opening up the eyes to the mainstream, and the application's almost mind blowing. You know, Sati Natel called it the Mosaic Moment, didn't say Netscape, he built Netscape (laughing) but called it the Mosaic Moment. You're seeing companies in startups, kind of the alpha geeks running here, because this is the new frontier, and there's real meat on the bone, in terms of like things to do. Why? Why is this happening now? What's is the confluence of the forces happening, that are making this happen? >> Yeah, I mean if you go back to the Cloudera days, with big data, and so on, that was more about data processing. Like how can we process data, so we can extract numbers from it, and do reporting, and maybe take some actions, like this is a fraud transaction, or this is not. And in the meanwhile, many of the researchers working in the neural network, and deep neural network space, were trying to focus on data understanding, like how can I understand the data, and learn from it, so I can take actual actions, based on the data directly, just like a human does. And we were only good at doing that at the level of somebody who was five years old, or seven years old, all the way until about 2013. And starting in 2013, which is only 10 years ago, a number of key innovations started taking place, and each one added on. It was no major innovation that just took place. It was a couple of really incremental ones, but they added on top of each other, in a very exponentially additive way, that led to, by the end of 2019, we now have models, deep neural network models, that can read and understand human text just like we do. Right? And they can reason about it, and argue with you, and explain it to you. And I think that's what is unlocking this whole new wave of innovation that we're seeing right now. So data understanding would be the essence of it. >> So it's not a Big Bang kind of theory, it's been evolving over time, and I think that the tipping point has been the advancements and other things. I mean look at cloud computing, and look how fast it just crept up on AWS. I mean AWS you back three, five years ago, I was talking to Swami yesterday, and their big news about AI, expanding the Hugging Face's relationship with AWS. And just three, five years ago, there wasn't a model training models out there. But as compute comes out, and you got more horsepower,, these large language models, these foundational models, they're flexible, they're not monolithic silos, they're interacting. There's a whole new, almost fusion of data happening. Do you see that? I mean is that part of this? >> Of course, of course. I mean this wave is building on all the previous waves. We wouldn't be at this point if we did not have hardware that can scale, in a very efficient way. We wouldn't be at this point, if we don't have data that we're collecting about everything we do, that we're able to process in this way. So this, this movement, this motion, this phase we're in, absolutely builds on the shoulders of all the previous phases. For some of the observers from the outside, when they see chatGPT for the first time, for them was like, "Oh my god, this just happened overnight." Like it didn't happen overnight. (laughing) GPT itself, like GPT3, which is what chatGPT is based on, was released a year ahead of chatGPT, and many of us were seeing the power it can provide, and what it can do. I don't know if Ed agrees with that. >> Yeah, Ed? >> I do. Although I would acknowledge that the possibilities now, because of what we've hit from a maturity standpoint, have just opened up in an incredible way, that just wasn't tenable even three years ago. And that's what makes it, it's true that it developed incrementally, in the same way that, you know, the possibilities of a mobile handheld device, you know, in 2006 were there, but when the iPhone came out, the possibilities just exploded. And that's the moment we're in. >> Well, I've had many conversations over the past couple months around this area with chatGPT. John Markoff told me the other day, that he calls it, "The five dollar toy," because it's not that big of a deal, in context to what AI's doing behind the scenes, and all the work that's done on ethics, that's happened over the years, but it has woken up the mainstream, so everyone immediately jumps to ethics. "Does it work? "It's not factual," And everyone who's inside the industry is like, "This is amazing." 'Cause you have two schools of thought there. One's like, people that think this is now the beginning of next gen, this is now we're here, this ain't your grandfather's chatbot, okay?" With NLP, it's got reasoning, it's got other things. >> I'm in that camp for sure. >> Yeah. Well I mean, everyone who knows what's going on is in that camp. And as the naysayers start to get through this, and they go, "Wow, it's not just plagiarizing homework, "it's helping me be better. "Like it could rewrite my memo, "bring the lead to the top." It's so the format of the user interface is interesting, but it's still a data-driven app. >> Absolutely. >> So where does it go from here? 'Cause I'm not even calling this the first ending. This is like pregame, in my opinion. What do you guys see this going, in terms of scratching the surface to what happens next? >> I mean, I'll start with, I just don't see how an application is going to look the same in the next three years. Who's going to want to input data manually, in a form field? Who is going to want, or expect, to have to put in some text in a search box, and then read through 15 different possibilities, and try to figure out which one of them actually most closely resembles the question they asked? You know, I don't see that happening. Who's going to start with an absolute blank sheet of paper, and expect no help? That is not how an application will work in the next three years, and it's going to fundamentally change how people interact and spend time with opening any element on their mobile phone, or on their computer, to get something done. >> Yes. I agree with that. Like every single application, over the next five years, will be rewritten, to fit within this model. So imagine an HR application, I don't want to name companies, but imagine an HR application, and you go into application and you clicking on buttons, because you want to take two weeks of vacation, and menus, and clicking here and there, reasons and managers, versus just telling the system, "I'm taking two weeks of vacation, going to Las Vegas," book it, done. >> Yeah. >> And the system just does it for you. If you weren't completing in your input, in your description, for what you want, then the system asks you back, "Did you mean this? "Did you mean that? "Were you trying to also do this as well?" >> Yeah. >> "What was the reason?" And that will fit it for you, and just do it for you. So I think the user interface that we have with apps, is going to change to be very similar to the user interface that we have with each other. And that's why all these apps will need to evolve. >> I know we don't have a lot of time, 'cause you guys are very busy, but I want to definitely have multiple segments with you guys, on this topic, because there's so much to talk about. There's a lot of parallels going on here. I was talking again with Swami who runs all the AI database at AWS, and I asked him, I go, "This feels a lot like the original AWS. "You don't have to provision a data center." A lot of this heavy lifting on the back end, is these large language models, with these foundational models. So the bottleneck in the past, was the energy, and cost to actually do it. Now you're seeing it being stood up faster. So there's definitely going to be a tsunami of apps. I would see that clearly. What is it? We don't know yet. But also people who are going to leverage the fact that I can get started building value. So I see a startup boom coming, and I see an application tsunami of refactoring things. >> Yes. >> So the replatforming is already kind of happening. >> Yes, >> OpenAI, chatGPT, whatever. So that's going to be a developer environment. I mean if Amazon turns this into an API, or a Microsoft, what you guys are doing. >> We're turning it into API as well. That's part of what we're doing as well, yes. >> This is why this is exciting. Amr, you've lived the big data dream, and and we used to talk, if you didn't have a big data problem, if you weren't full of data, you weren't really getting it. Now people have all the data, and they got to stand this up. >> Yeah. >> So the analogy is again, the mobile, I like the mobile movement, and using mobile as an analogy, most companies were not building for a mobile environment, right? They were just building for the web, and legacy way of doing apps. And as soon as the user expectations shifted, that my expectation now, I need to be able to do my job on this small screen, on the mobile device with a touchscreen. Everybody had to invest in re-architecting, and re-implementing every single app, to fit within that model, and that model of interaction. And we are seeing the exact same thing happen now. And one of the core things we're focused on at Vectara, is how to simplify that for organizations, because a lot of them are overwhelmed by large language models, and ML. >> They don't have the staff. >> Yeah, yeah, yeah. They're understaffed, they don't have the skills. >> But they got developers, they've got DevOps, right? >> Yes. >> So they have the DevSecOps going on. >> Exactly, yes. >> So our goal is to simplify it enough for them that they can start leveraging this technology effectively, within their applications. >> Ed, you're the COO of the company, obviously a startup. You guys are growing. You got great backup, and good team. You've also done a lot of business development, and technical business development in this area. If you look at the landscape right now, and I agree the apps are coming, every company I talk to, that has that jet chatGPT of, you know, epiphany, "Oh my God, look how cool this is. "Like magic." Like okay, it's code, settle down. >> Mm hmm. >> But everyone I talk to is using it in a very horizontal way. I talk to a very senior person, very tech alpha geek, very senior person in the industry, technically. they're using it for log data, they're using it for configuration of routers. And in other areas, they're using it for, every vertical has a use case. So this is horizontally scalable from a use case standpoint. When you hear horizontally scalable, first thing I chose in my mind is cloud, right? >> Mm hmm. >> So cloud, and scalability that way. And the data is very specialized. So now you have this vertical specialization, horizontally scalable, everyone will be refactoring. What do you see, and what are you seeing from customers, that you talk to, and prospects? >> Yeah, I mean put yourself in the shoes of an application developer, who is actually trying to make their application a bit more like magic. And to have that soon-to-be, honestly, expected experience. They've got to think about things like performance, and how efficiently that they can actually execute a query, or a question. They've got to think about cost. Generative isn't cheap, like the inference of it. And so you've got to be thoughtful about how and when you take advantage of it, you can't use it as a, you know, everything looks like a nail, and I've got a hammer, and I'm going to hit everything with it, because that will be wasteful. Developers also need to think about how they're going to take advantage of, but not lose their own data. So there has to be some controls around what they feed into the large language model, if anything. Like, should they fine tune a large language model with their own data? Can they keep it logically separated, but still take advantage of the powers of a large language model? And they've also got to take advantage, and be aware of the fact that when data is generated, that it is a different class of data. It might not fully be their own. >> Yeah. >> And it may not even be fully verified. And so when the logical cycle starts, of someone making a request, the relationship between that request, and the output, those things have to be stored safely, logically, and identified as such. >> Yeah. >> And taken advantage of in an ongoing fashion. So these are mega problems, each one of them independently, that, you know, you can think of it as middleware companies need to take advantage of, and think about, to help the next wave of application development be logical, sensible, and effective. It's not just calling some raw API on the cloud, like openAI, and then just, you know, you get your answer and you're done, because that is a very brute force approach. >> Well also I will point, first of all, I agree with your statement about the apps experience, that's going to be expected, form filling. Great point. The interesting about chatGPT. >> Sorry, it's not just form filling, it's any action you would like to take. >> Yeah. >> Instead of clicking, and dragging, and dropping, and doing it on a menu, or on a touch screen, you just say it, and it's and it happens perfectly. >> Yeah. It's a different interface. And that's why I love that UIUX experiences, that's the people falling out of their chair moment with chatGPT, right? But a lot of the things with chatGPT, if you feed it right, it works great. If you feed it wrong and it goes off the rails, it goes off the rails big. >> Yes, yes. >> So the the Bing catastrophes. >> Yeah. >> And that's an example of garbage in, garbage out, classic old school kind of comp-side phrase that we all use. >> Yep. >> Yes. >> This is about data in injection, right? It reminds me the old SQL days, if you had to, if you can sling some SQL, you were a magician, you know, to get the right answer, it's pretty much there. So you got to feed the AI. >> You do, Some people call this, the early word to describe this as prompt engineering. You know, old school, you know, search, or, you know, engagement with data would be, I'm going to, I have a question or I have a query. New school is, I have, I have to issue it a prompt, because I'm trying to get, you know, an action or a reaction, from the system. And the active engineering, there are a lot of different ways you could do it, all the way from, you know, raw, just I'm going to send you whatever I'm thinking. >> Yeah. >> And you get the unintended outcomes, to more constrained, where I'm going to just use my own data, and I'm going to constrain the initial inputs, the data I already know that's first party, and I trust, to, you know, hyper constrain, where the application is actually, it's looking for certain elements to respond to. >> It's interesting Amr, this is why I love this, because one we are in the media, we're recording this video now, we'll stream it. But we got all your linguistics, we're talking. >> Yes. >> This is data. >> Yep. >> So the data quality becomes now the new intellectual property, because, if you have that prompt source data, it makes data or content, in our case, the original content, intellectual property. >> Absolutely. >> Because that's the value. And that's where you see chatGPT fall down, is because they're trying to scroll the web, and people think it's search. It's not necessarily search, it's giving you something that you wanted. It is a lot of that, I remember in Cloudera, you said, "Ask the right questions." Remember that phrase you guys had, that slogan? >> Mm hmm. And that's prompt engineering. So that's exactly, that's the reinvention of "Ask the right question," is prompt engineering is, if you don't give these models the question in the right way, and very few people know how to frame it in the right way with the right context, then you will get garbage out. Right? That is the garbage in, garbage out. But if you specify the question correctly, and you provide with it the metadata that constrain what that question is going to be acted upon or answered upon, then you'll get much better answers. And that's exactly what we solved Vectara. >> Okay. So before we get into the last couple minutes we have left, I want to make sure we get a plug in for the opportunity, and the profile of Vectara, your new company. Can you guys both share with me what you think the current situation is? So for the folks who are now having those moments of, "Ah, AI's bullshit," or, "It's not real, it's a lot of stuff," from, "Oh my god, this is magic," to, "Okay, this is the future." >> Yes. >> What would you say to that person, if you're at a cocktail party, or in the elevator say, "Calm down, this is the first inning." How do you explain the dynamics going on right now, to someone who's either in the industry, but not in the ropes? How would you explain like, what this wave's about? How would you describe it, and how would you prepare them for how to change their life around this? >> Yeah, so I'll go first and then I'll let Ed go. Efficiency, efficiency is the description. So we figured that a way to be a lot more efficient, a way where you can write a lot more emails, create way more content, create way more presentations. Developers can develop 10 times faster than they normally would. And that is very similar to what happened during the Industrial Revolution. I always like to look at examples from the past, to read what will happen now, and what will happen in the future. So during the Industrial Revolution, it was about efficiency with our hands, right? So I had to make a piece of cloth, like this piece of cloth for this shirt I'm wearing. Our ancestors, they had to spend month taking the cotton, making it into threads, taking the threads, making them into pieces of cloth, and then cutting it. And now a machine makes it just like that, right? And the ancestors now turned from the people that do the thing, to manage the machines that do the thing. And I think the same thing is going to happen now, is our efficiency will be multiplied extremely, as human beings, and we'll be able to do a lot more. And many of us will be able to do things they couldn't do before. So another great example I always like to use is the example of Google Maps, and GPS. Very few of us knew how to drive a car from one location to another, and read a map, and get there correctly. But once that efficiency of an AI, by the way, behind these things is very, very complex AI, that figures out how to do that for us. All of us now became amazing navigators that can go from any point to any point. So that's kind of how I look at the future. >> And that's a great real example of impact. Ed, your take on how you would talk to a friend, or colleague, or anyone who asks like, "How do I make sense of the current situation? "Is it real? "What's in it for me, and what do I do?" I mean every company's rethinking their business right now, around this. What would you say to them? >> You know, I usually like to show, rather than describe. And so, you know, the other day I just got access, I've been using an application for a long time, called Notion, and it's super popular. There's like 30 or 40 million users. And the new version of Notion came out, which has AI embedded within it. And it's AI that allows you primarily to create. So if you could break down the world of AI into find and create, for a minute, just kind of logically separate those two things, find is certainly going to be massively impacted in our experiences as consumers on, you know, Google and Bing, and I can't believe I just said the word Bing in the same sentence as Google, but that's what's happening now (all laughing), because it's a good example of change. >> Yes. >> But also inside the business. But on the crate side, you know, Notion is a wiki product, where you try to, you know, note down things that you are thinking about, or you want to share and memorialize. But sometimes you do need help to get it down fast. And just in the first day of using this new product, like my experience has really fundamentally changed. And I think that anybody who would, you know, anybody say for example, that is using an existing app, I would show them, open up the app. Now imagine the possibility of getting a starting point right off the bat, in five seconds of, instead of having to whole cloth draft this thing, imagine getting a starting point then you can modify and edit, or just dispose of and retry again. And that's the potential for me. I can't imagine a scenario where, in a few years from now, I'm going to be satisfied if I don't have a little bit of help, in the same way that I don't manually spell check every email that I send. I automatically spell check it. I love when I'm getting type ahead support inside of Google, or anything. Doesn't mean I always take it, or when texting. >> That's efficiency too. I mean the cloud was about developers getting stuff up quick. >> Exactly. >> All that heavy lifting is there for you, so you don't have to do it. >> Right? >> And you get to the value faster. >> Exactly. I mean, if history taught us one thing, it's, you have to always embrace efficiency, and if you don't fast enough, you will fall behind. Again, looking at the industrial revolution, the companies that embraced the industrial revolution, they became the leaders in the world, and the ones who did not, they all like. >> Well the AI thing that we got to watch out for, is watching how it goes off the rails. If it doesn't have the right prompt engineering, or data architecture, infrastructure. >> Yes. >> It's a big part. So this comes back down to your startup, real quick, I know we got a couple minutes left. Talk about the company, the motivation, and we'll do a deeper dive on on the company. But what's the motivation? What are you targeting for the market, business model? The tech, let's go. >> Actually, I would like Ed to go first. Go ahead. >> Sure, I mean, we're a developer-first, API-first platform. So the product is oriented around allowing developers who may not be superstars, in being able to either leverage, or choose, or select their own large language models for appropriate use cases. But they that want to be able to instantly add the power of large language models into their application set. We started with search, because we think it's going to be one of the first places that people try to take advantage of large language models, to help find information within an application context. And we've built our own large language models, focused on making it very efficient, and elegant, to find information more quickly. So what a developer can do is, within minutes, go up, register for an account, and get access to a set of APIs, that allow them to send data, to be converted into a format that's easy to understand for large language models, vectors. And then secondarily, they can issue queries, ask questions. And they can ask them very, the questions that can be asked, are very natural language questions. So we're talking about long form sentences, you know, drill down types of questions, and they can get answers that either come back in depending upon the form factor of the user interface, in list form, or summarized form, where summarized equals the opportunity to kind of see a condensed, singular answer. >> All right. I have a. >> Oh okay, go ahead, you go. >> I was just going to say, I'm going to be a customer for you, because I want, my dream was to have a hologram of theCUBE host, me and Dave, and have questions be generated in the metaverse. So you know. (all laughing) >> There'll be no longer any guests here. They'll all be talking to you guys. >> Give a couple bullets, I'll spit out 10 good questions. Publish a story. This brings the automation, I'm sorry to interrupt you. >> No, no. No, no, I was just going to follow on on the same. So another way to look at exactly what Ed described is, we want to offer you chatGPT for your own data, right? So imagine taking all of the recordings of all of the interviews you have done, and having all of the content of that being ingested by a system, where you can now have a conversation with your own data and say, "Oh, last time when I met Amr, "which video games did we talk about? "Which movie or book did we use as an analogy "for how we should be embracing data science, "and big data, which is moneyball," I know you use moneyball all the time. And you start having that conversation. So, now the data doesn't become a passive asset that you just have in your organization. No. It's an active participant that's sitting with you, on the table, helping you make decisions. >> One of my favorite things to do with customers, is to go to their site or application, and show them me using it. So for example, one of the customers I talked to was one of the biggest property management companies in the world, that lets people go and rent homes, and houses, and things like that. And you know, I went and I showed them me searching through reviews, looking for information, and trying different words, and trying to find out like, you know, is this place quiet? Is it comfortable? And then I put all the same data into our platform, and I showed them the world of difference you can have when you start asking that question wholeheartedly, and getting real information that doesn't have anything to do with the words you asked, but is really focused on the meaning. You know, when I asked like, "Is it quiet?" You know, answers would come back like, "The wind whispered through the trees peacefully," and you know, it's like nothing to do with quiet in the literal word sense, but in the meaning sense, everything to do with it. And that that was magical even for them, to see that. >> Well you guys are the front end of this big wave. Congratulations on the startup, Amr. I know you guys got great pedigree in big data, and you've got a great team, and congratulations. Vectara is the name of the company, check 'em out. Again, the startup boom is coming. This will be one of the major waves, generative AI is here. I think we'll look back, and it will be pointed out as a major inflection point in the industry. >> Absolutely. >> There's not a lot of hype behind that. People are are seeing it, experts are. So it's going to be fun, thanks for watching. >> Thanks John. (soft 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)

(upbeat music) >> Hello, welcome back to theCUBE's AWS RE:Invent 2022 Coverage. I'm John Furrier, host of theCUBE. Got a great lineup here, Itamar Ankorion SVP Technology Alliance at Qlik and Peter McDonald, vice President, cloud partnerships and business development Snowflake. We're going to talk about bringing SAP data to life, for joint Snowflake, Qlik and AWS Solution. Gentlemen, thanks for coming on theCUBE Really appreciate it. >> Thank you. >> Thank you, great meeting you John. >> Just to get started, introduce yourselves to the audience, then going to jump into what you guys are doing together, unique relationship here, really compelling solution in cloud. Big story about applications and scale this year. Let's introduce yourselves. Peter, we'll start with you. >> Great. I'm Peter MacDonald. I am vice president of Cloud Partners and business development here at Snowflake. On the Cloud Partner side, that means I manage AWS relationship along with Microsoft and Google Cloud. What we do together in terms of complimentary products, GTM, co-selling, things like that. Importantly, working with other third parties like Qlik for joint solutions. On business development, it's negotiating custom commercial partnerships, large companies like Salesforce and Dell, smaller companies at most for our venture portfolio. >> Thanks Peter and hi John. It's great to be back here. So I'm Itamar Ankorion and I'm the senior vice president responsible for technology alliances here at Qlik. With that, own strategic alliances, including our key partners in the cloud, including Snowflake and AWS. I've been in the data and analytics enterprise software market for 20 plus years, and my main focus is product management, marketing, alliances, and business development. I joined Qlik about three and a half years ago through the acquisition of Attunity, which is now the foundation for Qlik data integration. So again, we focus in my team on creating joint solution alignment with our key partners to provide more value to our customers. >> Great to have both you guys, senior executives in the industry on theCUBE here, talking about data, obviously bringing SAP data to life is the theme of this segment, but this reinvent, it's all about the data, big data end-to-end story, a lot about data being intrinsic as the CEO says on stage around in the organizations in all aspects. Take a minute to explain what you guys are doing as from a company standpoint. Snowflake and Qlik and the solutions, why here at AWS? Peter, we'll start with you at Snowflake, what you guys do as a company, your mission, your focus. >> That was great, John. Yeah, so here at Snowflake, we focus on the data platform and until recently, data platforms required expensive on-prem hardware appliances. And despite all that expense, customers had capacity constraints, inexpensive maintenance, and had limited functionality that all impeded these organizations from reaching their goals. Snowflake is a cloud native SaaS platform, and we've become so successful because we've addressed these pain points and have other new special features. For example, securely sharing data across both the organization and the value chain without copying the data, support for new data types such as JSON and structured data, and also advance in database data governance. Snowflake integrates with complimentary AWS services and other partner products. So we can enable holistic solutions that include, for example, here, both Qlik and AWS SageMaker, and comprehend and bring those to joint customers. Our customers want to convert data into insights along with advanced analytics platforms in AI. That is how they make holistic data-driven solutions that will give them competitive advantage. With Snowflake, our approach is to focus on customer solutions that leverage data from existing systems such as SAP, wherever they are in the cloud or on-premise. And to do this, we leverage partners like Qlik native US to help customers transform their businesses. We provide customers with a premier data analytics platform as a result. Itamar, why don't you talk about Qlik a little bit and then we can dive into the specific SAP solution here and some trends >> Sounds great, Peter. So Qlik provides modern data integration and analytics software used by over 38,000 customers worldwide. Our focus is to help our customers turn data into value and help them close the gap between data all the way through insight and action. We offer click data integration and click data analytics. Click data integration helps to automate the data pipelines to deliver data to where they want to use them in real-time and make the data ready for analytics and then Qlik data analytics is a robust platform for analytics and business intelligence has been a leader in the Gartner Magic Quadrant for over 11 years now in the market. And both of these come together into what we call Qlik Cloud, which is our SaaS based platform. So providing a more seamless way to consume all these services and accelerate time to value with customer solutions. In terms of partnerships, both Snowflake and AWS are very strategic to us here at Qlik, so we have very comprehensive investment to ensure strong joint value proposition to we can bring to our mutual customers, everything from aligning our roadmaps through optimizing and validating integrations, collaborating on best practices, packaging joint solutions like the one we'll talk about today. And with that investment, we are an elite level, top level partner with Snowflake. We fly that our technology is Snowflake-ready across the entire product set and we have hundreds of joint customers together and with AWS we've also partnered for a long time. We're here to reinvent. We've been here with the first reinvent since the inaugural one, so it kind of gives you an idea for how long we've been working with AWS. We provide very comprehensive integration with AWS data analytics services, and we have several competencies ranging from data analytics to migration and modernization. So that's our focus and again, we're excited about working with Snowflake and AWS to bring solutions together to market. >> Well, I'm looking forward to unpacking the solutions specifically, and congratulations on the continued success of both your companies. We've been following them obviously for a very long time and seeing the platform evolve beyond just SaaS and a lot more going on in cloud these days, kind of next generation emerging. You know, we're seeing a lot of macro trends that are going to be powering some of the things we're going to get into real quickly. But before we get into the solution, what are some of those power dynamics in the industry that you're seeing in trends specifically that are impacting your customers that are taking us down this road of getting more out of the data and specifically the SAP, but in general trends and dynamics. What are you hearing from your customers? Why do they care? Why are they going down this road? Peter, we'll start with you. >> Yeah, I'll go ahead and start. Thanks. Yeah, I'd say we continue to see customers being, being very eager to transform their businesses and they know they need to leverage technology and data to do so. They're also increasingly depending upon the cloud to bring that agility, that elasticity, new functionality necessary to react in real-time to every evolving customer needs. You look at what's happened over the last three years, and boy, the macro environment customers, it's all changing so fast. With our partnerships with AWS and Qlik, we've been able to bring to market innovative solutions like the one we're announcing today that spans all three companies. It provides a holistic solution and an integrated solution for our customer. >> Itamar let's get into it, you've been with theCUBE, you've seen the journey, you have your own journey, many, many years, you've seen the waves. What's going on now? I mean, what's the big wave? What's the dynamic powering this trend? >> Yeah, in a nutshell I'll call it, it's all about time. You know, it's time to value and it's about real-time data. I'll kind of talk about that a bit. So, I mean, you hear a lot about the data being the new oil, but it's definitely, we see more and more customers seeing data as their critical enabler for innovation and digital transformation. They look for ways to monetize data. They look as the data as the way in which they can innovate and bring different value to the customers. So we see customers want to use more data so to get more value from data. We definitely see them wanting to do it faster, right, than before. And we definitely see them looking for agility and automation as ways to accelerate time to value, and also reduce overall costs. I did mention real-time data, so we definitely see more and more customers, they want to be able to act and make decisions based on fresh data. So yesterday's data is just not good enough. >> John: Yeah. >> It's got to be down to the hour, down to the minutes and sometimes even lower than that. And then I think we're also seeing customers look to their core business systems where they have a lot of value, like the SAP, like mainframe and thinking, okay, our core data is there, how can we get more value from this data? So that's key things we see all the time with customers. >> Yeah, we did a big editorial segment this year on, we called data as code. Data as code is kind of a riff on infrastructure as code and you start to see data becoming proliferating into all aspects, fresh data. It's not just where you store it, it's how you share it, it's how you turn it into an application intrinsically involved in all aspects. This is the big theme this year and that's driving all the conversations here at RE:Invent. And I'm guaranteeing you, it's going to happen for another five and 10 years. It's not stopping. So I got to get into the solution, you guys mentioned SAP and you've announced the solution by Qlik, Snowflake and AWS for your customers using SAP. Can you share more about this solution? What's unique about it? Why is it important and why now? Peter, Itamar, we'll start with you first. >> Let me jump in, this is really, I'll jump because I'm excited. We're very excited about this solution and it's also a solution by the way and again, we've seen proven customer success with it. So to your point, it's ready to scale, it's starting, I think we're going to see a lot of companies doing this over the next few years. But before we jump to the solution, let me maybe take a few minutes just to clarify the need, why we're seeing, why we're seeing customers jump to do this. So customers that use SAP, they use it to manage the core of their business. So think order processing, management, finance, inventory, supply chain, and so much more. So if you're running SAP in your company, that data creates a great opportunity for you to drive innovation and modernization. So what we see customers want to do, they want to do more with their data and more means they want to take SAP with non-SAP data and use it together to drive new insights. They want to use real-time data to drive real-time analytics, which they couldn't do to date. They want to bring together descriptive with predictive analytics. So adding machine learning in AI to drive more value from the data. And naturally they want to do it faster. So find ways to iterate faster on their solutions, have freedom with the data and agility. And I think this is really where cloud data platforms like Snowflake and AWS, you know, bring that value to be able to drive that. Now to do that you need to unlock the SAP data, which is a lot of also where Qlik comes in because typical challenges these customers run into is the complexity, inherent in SAP data. Tens of thousands of tables, proprietary formats, complex data models, licensing restrictions, and more than, you have performance issues, they usually run into how do we handle the throughput, the volumes while maintaining lower latency and impact. Where do we find knowledge to really understand how to get all this done? So these are the things we've looked at when we came together to create a solution and make it unique. So when you think about its uniqueness, because we put together a lot, and I'll go through three, four key things that come together to make this unique. First is about data delivery. How do you have the SAP data delivery? So how do you get it from ECC, from HANA from S/4HANA, how do you deliver the data and the metadata and how that integration well into Snowflake. And what we've done is we've focused a lot on optimizing that process and the continuous ingestion, so the real-time ingestion of the data in a way that works really well with the Snowflake system, data cloud. Second thing is we looked at SAP data transformation, so once the data arrives at Snowflake, how do we turn it into being analytics ready? So that's where data transformation and data worth automation come in. And these are all elements of this solution. So creating derivative datasets, creating data marts, and all of that is done by again, creating an optimized integration that pushes down SQL based transformations, so they can be processed inside Snowflake, leveraging its powerful engine. And then the third element is bringing together data visualization analytics that can also take all the data now that in organizing inside Snowflake, bring other data in, bring machine learning from SageMaker, and then you go to create a seamless integration to bring analytic applications to life. So these are all things we put together in the solution. And maybe the last point is we actually took the next step with this and we created something we refer to as solution accelerators, which we're really, really keen about. Think about this as prepackaged templates for common business analytic needs like order to cash, finance, inventory. And we can either dig into that a little more later, but this gets the next level of value to the customers all built into this joint solution. >> Yeah, I want to get to the accelerators, but real quick, Peter, your reaction to the solution, what's unique about it? And obviously Snowflake, we've been seeing the progression data applications, more developers developing on top of Snowflake, data as code kind of implies developer ecosystem. This is kind of interesting. I mean, you got partnering with Qlik and AWS, it's kind of a developer-like thinking real solution. What's unique about this SAP solution that's, that's different than what customers can get anywhere else or not? >> Yeah, well listen, I think first of all, you have to start with the idea of the solution. This are three companies coming together to build a holistic solution that is all about, you know, creating a great opportunity to turn SAP data into value this is Itamar was talking about, that's really what we're talking about here and there's a lot of technology underneath it. I'll talk more about the Snowflake technology, what's involved here, and then cover some of the AWS pieces as well. But you know, we're focusing on getting that value out and accelerating time to value for our joint customers. As Itamar was saying, you know, there's a lot of complexity with the SAP data and a lot of value there. How can we manage that in a prepackaged way, bringing together best of breed solutions with proven capabilities and bringing this to market quickly for our joint customers. You know, Snowflake and AWS have been strong partners for a number of years now, and that's not only on how Snowflake runs on top of AWS, but also how we integrate with their complementary analytics and then all products. And so, you know, we want to be able to leverage those in addition to what Qlik is bringing in terms of the data transformations, bringing data out of SAP in the visualization as well. All very critical. And then we want to bring in the predictive analytics, AWS brings and what Sage brings. We'll talk about that a little bit later on. Some of the technologies that we're leveraging are some of our latest cutting edge technologies that really make things easier for both our partners and our customers. For example, Qlik leverages Snowflakes recently released Snowpark for Python functionality to push down those data transformations from clicking the Snowflake that Itamar's mentioning. And while we also leverage Snowpark for integrations with Amazon SageMaker, but there's a lot of great new technology that just makes this easy and compelling for customers. >> I think that's the big word, easy button here for what may look like a complex kind of integration, kind of turnkey, really, really compelling example of the modern era we're living in, as we always say in theCUBE. You mentioned accelerators, SAP accelerators. Can you give an example of how that works with the technology from the third party providers to deliver this business value Itamar, 'cause that was an interesting comment. What's the example? Give an example of this acceleration. >> Yes, certainly. I think this is something that really makes this truly, truly unique in the industry and again, a great opportunity for customers. So we kind talked earlier about there's a lot of things that need to be done with SP data to turn it to value. And these accelerator, as the name suggests, are designed to do just that, to kind of jumpstart the process and reduce the time and the risk involved in such project. So again, these are pre-packaged templates. We basically took a lot of knowledge, and a lot of configurations, best practices about to get things done and we put 'em together. So think about all the steps, it includes things like data extraction, so already knowing which tables, all the relevant tables that you need to get data from in the contexts of the solution you're looking for, say like order to cash, we'll get back to that one. How do you continuously deliver that data into Snowflake in an in efficient manner, handling things like data type mappings, metadata naming conventions and transformations. The data models you build all the way to data mart definitions and all the transformations that the data needs to go through moving through steps until it's fully analytics ready. And then on top of that, even adding a library of comprehensive analytic dashboards and integrations through machine learning and AI and put all of that in a way that's in pre-integrated and tested to work with Snowflake and AWS. So this is where again, you get this entire recipe that's ready. So take for example, I think I mentioned order to cash. So again, all these things I just talked about, I mean, for those who are not familiar, I mean order to cash is a critical business process for every organization. So especially if you're in retail, manufacturing, enterprise, it's a big... This is where, you know, starting with booking a sales order, following by fulfilling the order, billing the customer, then managing the accounts receivable when the customer actually pays, right? So this all process, you got sales order fulfillment and the billing impacts customer satisfaction, you got receivable payments, you know, the impact's working capital, cash liquidity. So again, as a result this order to cash process is a lifeblood for many businesses and it's critical to optimize and understand. So the solution accelerator we created specifically for order to cash takes care of understanding all these aspects and the data that needs to come with it. So everything we outline before to make the data available in Snowflake in a way that's really useful for downstream analytics, along with dashboards that are already common for that, for that use case. So again, this enables customers to gain real-time visibility into their sales orders, fulfillment, accounts receivable performance. That's what the Excel's are all about. And very similarly, we have another one for example, for finance analytics, right? So this will optimize financial data reporting, helps customers get insights into P&L, financial risk of stability or inventory analytics that helps with, you know, improve planning and inventory management, utilization, increased efficiencies, you know, so in supply chain. So again, these accelerators really help customers get a jumpstart and move faster with their solutions. >> Peter, this is the easy button we just talked about, getting things going, you know, get the ball rolling, get some acceleration. Big part of this are the three companies coming together doing this. >> Yeah, and to build on what Itamar just said that the SAP data obviously has tremendous value. Those sales orders, distribution data, financial data, bringing that into Snowflake makes it easily accessible, but also it enables it to be combined with other data too, is one of the things that Snowflake does so well. So you can get a full view of the end-to-end process and the business overall. You know, for example, I'll just take one, you know, one example that, that may not come to mind right away, but you know, looking at the impact of weather conditions on supply chain logistics is relevant and material and have interest to our customers. How do you bring those different data sets together in an easy way, bringing the data out of SAP, bringing maybe other data out of other systems through Qlik or through Snowflake, directly bringing data in from our data marketplace and bring that all together to make it work. You know, fundamentally organizational silos and the data fragmentation exist otherwise make it really difficult to drive modern analytics projects. And that in turn limits the value that our customers are getting from SAP data and these other data sets. We want to enable that and unleash. >> Yeah, time for value. This is great stuff. Itamar final question, you know, what are customers using this? What do you have? I'm sure you have customers examples already using the solution. Can you share kind of what these examples look like in the use cases and the value? >> Oh yeah, absolutely. Thank you. Happy to. We have customers across different, different sectors. You see manufacturing, retail, energy, oil and gas, CPG. So again, customers in those segments, typically sectors typically have SAP. So we have customers in all of them. A great example is like Siemens Energy. Siemens Energy is a global provider of gas par services. You know, over what, 28 billion, 30 billion in revenue. 90,000 employees. They operate globally in over 90 countries. So they've used SAP HANA as a core system, so it's running on premises, multiple locations around the world. And what they were looking for is a way to bring all these data together so they can innovate with it. And the thing is, Peter mentioned earlier, not just the SAP data, but also bring other data from other systems to bring it together for more value. That includes finance data, these logistics data, these customer CRM data. So they bring data from over 20 different SAP systems. Okay, with Qlik data integration, feeding that into Snowflake in under 20 minutes, 24/7, 365, you know, days a year. Okay, they get data from over 20,000 tables, you know, over million, hundreds of millions of records daily going in. So it is a great example of the type of scale, scalability, agility and speed that they can get to drive these kind of innovation. So that's a great example with Siemens. You know, another one comes to mind is a global manufacturer. Very similar scenario, but you know, they're using it for real-time executive reporting. So it's more like feasibility to the production data as well as for financial analytics. So think, think, think about everything from audit to texts to innovate financial intelligence because all the data's coming from SAP. >> It's a great time to be in the data business again. It keeps getting better and better. There's more data coming. It's not stopping, you know, it's growing so fast, it keeps coming. Every year, it's the same story, Peter. It's like, doesn't stop coming. As we wrap up here, let's just get customers some information on how to get started. I mean, obviously you're starting to see the accelerators, it's a great program there. What a great partnership between the two companies and AWS. How can customers get started to learn about the solution and take advantage of it, getting more out of their SAP data, Peter? >> Yeah, I think the first place to go to is talk to Snowflake, talk to AWS, talk to our account executives that are assigned to your account. Reach out to them and they will be able to educate you on the solution. We have packages up very nicely and can be deployed very, very quickly. >> Well gentlemen, thank you so much for coming on. Appreciate the conversation. Great overview of the partnership between, you know, Snowflake and Qlik and AWS on a joint solution. You know, getting more out of the SAP data. It's really kind of a key, key solution, bringing SAP data to life. Thanks for coming on theCUBE. Appreciate it. >> Thank you. >> Thank you John. >> Okay, this is theCUBE coverage here at RE:Invent 2022. I'm John Furrier, your host of theCUBE. Thanks for watching. (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)

(upbeat music) >> Hello, welcome back to theCUBE's AWS RE:Invent 2022 Coverage. I'm John Furrier, host of theCUBE. Got a great lineup here, Itamar Ankorion SVP Technology Alliance at Qlik and Peter McDonald, vice President, cloud partnerships and business development Snowflake. We're going to talk about bringing SAP data to life, for joint Snowflake, Qlik and AWS Solution. Gentlemen, thanks for coming on theCUBE Really appreciate it. >> Thank you. >> Thank you, great meeting you John. >> Just to get started, introduce yourselves to the audience, then going to jump into what you guys are doing together, unique relationship here, really compelling solution in cloud. Big story about applications and scale this year. Let's introduce yourselves. Peter, we'll start with you. >> Great. I'm Peter MacDonald. I am vice president of Cloud Partners and business development here at Snowflake. On the Cloud Partner side, that means I manage AWS relationship along with Microsoft and Google Cloud. What we do together in terms of complimentary products, GTM, co-selling, things like that. Importantly, working with other third parties like Qlik for joint solutions. On business development, it's negotiating custom commercial partnerships, large companies like Salesforce and Dell, smaller companies at most for our venture portfolio. >> Thanks Peter and hi John. It's great to be back here. So I'm Itamar Ankorion and I'm the senior vice president responsible for technology alliances here at Qlik. With that, own strategic alliances, including our key partners in the cloud, including Snowflake and AWS. I've been in the data and analytics enterprise software market for 20 plus years, and my main focus is product management, marketing, alliances, and business development. I joined Qlik about three and a half years ago through the acquisition of Attunity, which is now the foundation for Qlik data integration. So again, we focus in my team on creating joint solution alignment with our key partners to provide more value to our customers. >> Great to have both you guys, senior executives in the industry on theCUBE here, talking about data, obviously bringing SAP data to life is the theme of this segment, but this reinvent, it's all about the data, big data end-to-end story, a lot about data being intrinsic as the CEO says on stage around in the organizations in all aspects. Take a minute to explain what you guys are doing as from a company standpoint. Snowflake and Qlik and the solutions, why here at AWS? Peter, we'll start with you at Snowflake, what you guys do as a company, your mission, your focus. >> That was great, John. Yeah, so here at Snowflake, we focus on the data platform and until recently, data platforms required expensive on-prem hardware appliances. And despite all that expense, customers had capacity constraints, inexpensive maintenance, and had limited functionality that all impeded these organizations from reaching their goals. Snowflake is a cloud native SaaS platform, and we've become so successful because we've addressed these pain points and have other new special features. For example, securely sharing data across both the organization and the value chain without copying the data, support for new data types such as JSON and structured data, and also advance in database data governance. Snowflake integrates with complimentary AWS services and other partner products. So we can enable holistic solutions that include, for example, here, both Qlik and AWS SageMaker, and comprehend and bring those to joint customers. Our customers want to convert data into insights along with advanced analytics platforms in AI. That is how they make holistic data-driven solutions that will give them competitive advantage. With Snowflake, our approach is to focus on customer solutions that leverage data from existing systems such as SAP, wherever they are in the cloud or on-premise. And to do this, we leverage partners like Qlik native US to help customers transform their businesses. We provide customers with a premier data analytics platform as a result. Itamar, why don't you talk about Qlik a little bit and then we can dive into the specific SAP solution here and some trends >> Sounds great, Peter. So Qlik provides modern data integration and analytics software used by over 38,000 customers worldwide. Our focus is to help our customers turn data into value and help them close the gap between data all the way through insight and action. We offer click data integration and click data analytics. Click data integration helps to automate the data pipelines to deliver data to where they want to use them in real-time and make the data ready for analytics and then Qlik data analytics is a robust platform for analytics and business intelligence has been a leader in the Gartner Magic Quadrant for over 11 years now in the market. And both of these come together into what we call Qlik Cloud, which is our SaaS based platform. So providing a more seamless way to consume all these services and accelerate time to value with customer solutions. In terms of partnerships, both Snowflake and AWS are very strategic to us here at Qlik, so we have very comprehensive investment to ensure strong joint value proposition to we can bring to our mutual customers, everything from aligning our roadmaps through optimizing and validating integrations, collaborating on best practices, packaging joint solutions like the one we'll talk about today. And with that investment, we are an elite level, top level partner with Snowflake. We fly that our technology is Snowflake-ready across the entire product set and we have hundreds of joint customers together and with AWS we've also partnered for a long time. We're here to reinvent. We've been here with the first reinvent since the inaugural one, so it kind of gives you an idea for how long we've been working with AWS. We provide very comprehensive integration with AWS data analytics services, and we have several competencies ranging from data analytics to migration and modernization. So that's our focus and again, we're excited about working with Snowflake and AWS to bring solutions together to market. >> Well, I'm looking forward to unpacking the solutions specifically, and congratulations on the continued success of both your companies. We've been following them obviously for a very long time and seeing the platform evolve beyond just SaaS and a lot more going on in cloud these days, kind of next generation emerging. You know, we're seeing a lot of macro trends that are going to be powering some of the things we're going to get into real quickly. But before we get into the solution, what are some of those power dynamics in the industry that you're seeing in trends specifically that are impacting your customers that are taking us down this road of getting more out of the data and specifically the SAP, but in general trends and dynamics. What are you hearing from your customers? Why do they care? Why are they going down this road? Peter, we'll start with you. >> Yeah, I'll go ahead and start. Thanks. Yeah, I'd say we continue to see customers being, being very eager to transform their businesses and they know they need to leverage technology and data to do so. They're also increasingly depending upon the cloud to bring that agility, that elasticity, new functionality necessary to react in real-time to every evolving customer needs. You look at what's happened over the last three years, and boy, the macro environment customers, it's all changing so fast. With our partnerships with AWS and Qlik, we've been able to bring to market innovative solutions like the one we're announcing today that spans all three companies. It provides a holistic solution and an integrated solution for our customer. >> Itamar let's get into it, you've been with theCUBE, you've seen the journey, you have your own journey, many, many years, you've seen the waves. What's going on now? I mean, what's the big wave? What's the dynamic powering this trend? >> Yeah, in a nutshell I'll call it, it's all about time. You know, it's time to value and it's about real-time data. I'll kind of talk about that a bit. So, I mean, you hear a lot about the data being the new oil, but it's definitely, we see more and more customers seeing data as their critical enabler for innovation and digital transformation. They look for ways to monetize data. They look as the data as the way in which they can innovate and bring different value to the customers. So we see customers want to use more data so to get more value from data. We definitely see them wanting to do it faster, right, than before. And we definitely see them looking for agility and automation as ways to accelerate time to value, and also reduce overall costs. I did mention real-time data, so we definitely see more and more customers, they want to be able to act and make decisions based on fresh data. So yesterday's data is just not good enough. >> John: Yeah. >> It's got to be down to the hour, down to the minutes and sometimes even lower than that. And then I think we're also seeing customers look to their core business systems where they have a lot of value, like the SAP, like mainframe and thinking, okay, our core data is there, how can we get more value from this data? So that's key things we see all the time with customers. >> Yeah, we did a big editorial segment this year on, we called data as code. Data as code is kind of a riff on infrastructure as code and you start to see data becoming proliferating into all aspects, fresh data. It's not just where you store it, it's how you share it, it's how you turn it into an application intrinsically involved in all aspects. This is the big theme this year and that's driving all the conversations here at RE:Invent. And I'm guaranteeing you, it's going to happen for another five and 10 years. It's not stopping. So I got to get into the solution, you guys mentioned SAP and you've announced the solution by Qlik, Snowflake and AWS for your customers using SAP. Can you share more about this solution? What's unique about it? Why is it important and why now? Peter, Itamar, we'll start with you first. >> Let me jump in, this is really, I'll jump because I'm excited. We're very excited about this solution and it's also a solution by the way and again, we've seen proven customer success with it. So to your point, it's ready to scale, it's starting, I think we're going to see a lot of companies doing this over the next few years. But before we jump to the solution, let me maybe take a few minutes just to clarify the need, why we're seeing, why we're seeing customers jump to do this. So customers that use SAP, they use it to manage the core of their business. So think order processing, management, finance, inventory, supply chain, and so much more. So if you're running SAP in your company, that data creates a great opportunity for you to drive innovation and modernization. So what we see customers want to do, they want to do more with their data and more means they want to take SAP with non-SAP data and use it together to drive new insights. They want to use real-time data to drive real-time analytics, which they couldn't do to date. They want to bring together descriptive with predictive analytics. So adding machine learning in AI to drive more value from the data. And naturally they want to do it faster. So find ways to iterate faster on their solutions, have freedom with the data and agility. And I think this is really where cloud data platforms like Snowflake and AWS, you know, bring that value to be able to drive that. Now to do that you need to unlock the SAP data, which is a lot of also where Qlik comes in because typical challenges these customers run into is the complexity, inherent in SAP data. Tens of thousands of tables, proprietary formats, complex data models, licensing restrictions, and more than, you have performance issues, they usually run into how do we handle the throughput, the volumes while maintaining lower latency and impact. Where do we find knowledge to really understand how to get all this done? So these are the things we've looked at when we came together to create a solution and make it unique. So when you think about its uniqueness, because we put together a lot, and I'll go through three, four key things that come together to make this unique. First is about data delivery. How do you have the SAP data delivery? So how do you get it from ECC, from HANA from S/4HANA, how do you deliver the data and the metadata and how that integration well into Snowflake. And what we've done is we've focused a lot on optimizing that process and the continuous ingestion, so the real-time ingestion of the data in a way that works really well with the Snowflake system, data cloud. Second thing is we looked at SAP data transformation, so once the data arrives at Snowflake, how do we turn it into being analytics ready? So that's where data transformation and data worth automation come in. And these are all elements of this solution. So creating derivative datasets, creating data marts, and all of that is done by again, creating an optimized integration that pushes down SQL based transformations, so they can be processed inside Snowflake, leveraging its powerful engine. And then the third element is bringing together data visualization analytics that can also take all the data now that in organizing inside Snowflake, bring other data in, bring machine learning from SageMaker, and then you go to create a seamless integration to bring analytic applications to life. So these are all things we put together in the solution. And maybe the last point is we actually took the next step with this and we created something we refer to as solution accelerators, which we're really, really keen about. Think about this as prepackaged templates for common business analytic needs like order to cash, finance, inventory. And we can either dig into that a little more later, but this gets the next level of value to the customers all built into this joint solution. >> Yeah, I want to get to the accelerators, but real quick, Peter, your reaction to the solution, what's unique about it? And obviously Snowflake, we've been seeing the progression data applications, more developers developing on top of Snowflake, data as code kind of implies developer ecosystem. This is kind of interesting. I mean, you got partnering with Qlik and AWS, it's kind of a developer-like thinking real solution. What's unique about this SAP solution that's, that's different than what customers can get anywhere else or not? >> Yeah, well listen, I think first of all, you have to start with the idea of the solution. This are three companies coming together to build a holistic solution that is all about, you know, creating a great opportunity to turn SAP data into value this is Itamar was talking about, that's really what we're talking about here and there's a lot of technology underneath it. I'll talk more about the Snowflake technology, what's involved here, and then cover some of the AWS pieces as well. But you know, we're focusing on getting that value out and accelerating time to value for our joint customers. As Itamar was saying, you know, there's a lot of complexity with the SAP data and a lot of value there. How can we manage that in a prepackaged way, bringing together best of breed solutions with proven capabilities and bringing this to market quickly for our joint customers. You know, Snowflake and AWS have been strong partners for a number of years now, and that's not only on how Snowflake runs on top of AWS, but also how we integrate with their complementary analytics and then all products. And so, you know, we want to be able to leverage those in addition to what Qlik is bringing in terms of the data transformations, bringing data out of SAP in the visualization as well. All very critical. And then we want to bring in the predictive analytics, AWS brings and what Sage brings. We'll talk about that a little bit later on. Some of the technologies that we're leveraging are some of our latest cutting edge technologies that really make things easier for both our partners and our customers. For example, Qlik leverages Snowflakes recently released Snowpark for Python functionality to push down those data transformations from clicking the Snowflake that Itamar's mentioning. And while we also leverage Snowpark for integrations with Amazon SageMaker, but there's a lot of great new technology that just makes this easy and compelling for customers. >> I think that's the big word, easy button here for what may look like a complex kind of integration, kind of turnkey, really, really compelling example of the modern era we're living in, as we always say in theCUBE. You mentioned accelerators, SAP accelerators. Can you give an example of how that works with the technology from the third party providers to deliver this business value Itamar, 'cause that was an interesting comment. What's the example? Give an example of this acceleration. >> Yes, certainly. I think this is something that really makes this truly, truly unique in the industry and again, a great opportunity for customers. So we kind talked earlier about there's a lot of things that need to be done with SP data to turn it to value. And these accelerator, as the name suggests, are designed to do just that, to kind of jumpstart the process and reduce the time and the risk involved in such project. So again, these are pre-packaged templates. We basically took a lot of knowledge, and a lot of configurations, best practices about to get things done and we put 'em together. So think about all the steps, it includes things like data extraction, so already knowing which tables, all the relevant tables that you need to get data from in the contexts of the solution you're looking for, say like order to cash, we'll get back to that one. How do you continuously deliver that data into Snowflake in an in efficient manner, handling things like data type mappings, metadata naming conventions and transformations. The data models you build all the way to data mart definitions and all the transformations that the data needs to go through moving through steps until it's fully analytics ready. And then on top of that, even adding a library of comprehensive analytic dashboards and integrations through machine learning and AI and put all of that in a way that's in pre-integrated and tested to work with Snowflake and AWS. So this is where again, you get this entire recipe that's ready. So take for example, I think I mentioned order to cash. So again, all these things I just talked about, I mean, for those who are not familiar, I mean order to cash is a critical business process for every organization. So especially if you're in retail, manufacturing, enterprise, it's a big... This is where, you know, starting with booking a sales order, following by fulfilling the order, billing the customer, then managing the accounts receivable when the customer actually pays, right? So this all process, you got sales order fulfillment and the billing impacts customer satisfaction, you got receivable payments, you know, the impact's working capital, cash liquidity. So again, as a result this order to cash process is a lifeblood for many businesses and it's critical to optimize and understand. So the solution accelerator we created specifically for order to cash takes care of understanding all these aspects and the data that needs to come with it. So everything we outline before to make the data available in Snowflake in a way that's really useful for downstream analytics, along with dashboards that are already common for that, for that use case. So again, this enables customers to gain real-time visibility into their sales orders, fulfillment, accounts receivable performance. That's what the Excel's are all about. And very similarly, we have another one for example, for finance analytics, right? So this will optimize financial data reporting, helps customers get insights into P&L, financial risk of stability or inventory analytics that helps with, you know, improve planning and inventory management, utilization, increased efficiencies, you know, so in supply chain. So again, these accelerators really help customers get a jumpstart and move faster with their solutions. >> Peter, this is the easy button we just talked about, getting things going, you know, get the ball rolling, get some acceleration. Big part of this are the three companies coming together doing this. >> Yeah, and to build on what Itamar just said that the SAP data obviously has tremendous value. Those sales orders, distribution data, financial data, bringing that into Snowflake makes it easily accessible, but also it enables it to be combined with other data too, is one of the things that Snowflake does so well. So you can get a full view of the end-to-end process and the business overall. You know, for example, I'll just take one, you know, one example that, that may not come to mind right away, but you know, looking at the impact of weather conditions on supply chain logistics is relevant and material and have interest to our customers. How do you bring those different data sets together in an easy way, bringing the data out of SAP, bringing maybe other data out of other systems through Qlik or through Snowflake, directly bringing data in from our data marketplace and bring that all together to make it work. You know, fundamentally organizational silos and the data fragmentation exist otherwise make it really difficult to drive modern analytics projects. And that in turn limits the value that our customers are getting from SAP data and these other data sets. We want to enable that and unleash. >> Yeah, time for value. This is great stuff. Itamar final question, you know, what are customers using this? What do you have? I'm sure you have customers examples already using the solution. Can you share kind of what these examples look like in the use cases and the value? >> Oh yeah, absolutely. Thank you. Happy to. We have customers across different, different sectors. You see manufacturing, retail, energy, oil and gas, CPG. So again, customers in those segments, typically sectors typically have SAP. So we have customers in all of them. A great example is like Siemens Energy. Siemens Energy is a global provider of gas par services. You know, over what, 28 billion, 30 billion in revenue. 90,000 employees. They operate globally in over 90 countries. So they've used SAP HANA as a core system, so it's running on premises, multiple locations around the world. And what they were looking for is a way to bring all these data together so they can innovate with it. And the thing is, Peter mentioned earlier, not just the SAP data, but also bring other data from other systems to bring it together for more value. That includes finance data, these logistics data, these customer CRM data. So they bring data from over 20 different SAP systems. Okay, with Qlik data integration, feeding that into Snowflake in under 20 minutes, 24/7, 365, you know, days a year. Okay, they get data from over 20,000 tables, you know, over million, hundreds of millions of records daily going in. So it is a great example of the type of scale, scalability, agility and speed that they can get to drive these kind of innovation. So that's a great example with Siemens. You know, another one comes to mind is a global manufacturer. Very similar scenario, but you know, they're using it for real-time executive reporting. So it's more like feasibility to the production data as well as for financial analytics. So think, think, think about everything from audit to texts to innovate financial intelligence because all the data's coming from SAP. >> It's a great time to be in the data business again. It keeps getting better and better. There's more data coming. It's not stopping, you know, it's growing so fast, it keeps coming. Every year, it's the same story, Peter. It's like, doesn't stop coming. As we wrap up here, let's just get customers some information on how to get started. I mean, obviously you're starting to see the accelerators, it's a great program there. What a great partnership between the two companies and AWS. How can customers get started to learn about the solution and take advantage of it, getting more out of their SAP data, Peter? >> Yeah, I think the first place to go to is talk to Snowflake, talk to AWS, talk to our account executives that are assigned to your account. Reach out to them and they will be able to educate you on the solution. We have packages up very nicely and can be deployed very, very quickly. >> Well gentlemen, thank you so much for coming on. Appreciate the conversation. Great overview of the partnership between, you know, Snowflake and Qlik and AWS on a joint solution. You know, getting more out of the SAP data. It's really kind of a key, key solution, bringing SAP data to life. Thanks for coming on theCUBE. Appreciate it. >> Thank you. >> Thank you John. >> Okay, this is theCUBE coverage here at RE:Invent 2022. I'm John Furrier, your host of theCUBE. Thanks for watching. (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)

>>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco, where all the developers are the bay air at Silicon valley. And of course, eights summit in New York city is coming up in this summer. We'll be there as well. SF and NYC cube coverage. Look for us, of course, reinforcing Boston and re Mars with the whole robotics AI thing, all coming together. Lots of coverage. Stay with us. Say we've got a great guest from Deibel VC. John Skoda, founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, Matt. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over a decade. Um, >>It's been at least 10 years, at >>Least 10 years more, and we don't wanna actually go back as freeze back the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in >>It's a little bit of a throwback to the path though, in my opinion, >>It's all the same. It's all distributed computing and software. We ran each other in Cuban. You're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software, take old something old and make it better new, faster. So tell us about decibel. What's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you're doing. I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, sort of my was company when I was 24, if you remember before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called IM logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of software companies, uh, early investor in open source companies and cloud companies and spent a really wonderful 12 years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software C is, and I'll tell you, there's never been a better time than right now to start an enterprise software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or builder. Uh, they are building products that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchase software that is traditionally bought and sold tops down. But you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community. So source or open source companies where you have a large technical cook community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great bottoms of motions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great grow, super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies there's no, I mean, consumer is enterprise now everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech and VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. Well, >>And, and I think all of us here that are, uh, may maybe students of history and have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three. >>The hype is definitely one, three. You >>Yeah, but, >>But you know, for >>Sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and caught infrastructure spend, you know, it is by many measures over, uh, 500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, >>Well, let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get at it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher, a direct sales force and SAS kind of crushed that now SAS is being redefined, right. So what is SAS? Is snowflake a SaaS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data. And you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the Tech's better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all successful startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big, giant revolution. I call it the user driven revolution, right? It's the rise of the user. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one and the same. So sometimes people think the product, uh, is what is driving. >>You just pull the >>Product through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see and it, and it does extend into things like crypto or currencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement maybe started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. These end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the beneficiaries and the most, you know, kind of valued people in this. >>I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've been saying on the cube for probably about eight years now that we are gonna hit a digital hippie revolution, meaning a rebellion against the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it, it it's just like the, the, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign. >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion yeah. Around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either, it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try. I you, and sometimes, um, like it or not, it's a religious decision, right? Yeah. It's some, it's something that people just believe to be true almost without, uh, necessarily caring >>About I data, data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the person. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't think, oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. And I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and does it, is it gonna, it's gonna do, or it doesn't, or it either stands out to the load test or it doesn't. And so I, I feel like in this new economy that we live in really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product stand out for on the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their products exactly >>The volume back to the user led >>Growth. Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of Joe security used to say, Hey, like, you know, the, the really like today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's, if the, you know, it's gotta speak >>To the, to the user. But let me ask you a question for the people watching, who are maybe entrepreneurial entre entrepreneurs, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer? Just say, here's where I'm at. Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make bad vision of reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna align with your vision and, and want to invest in you wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta show the path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle. The journey can happen. Yeah. But it doesn't matter as much. If you share the long term vision, >>Don't flake out and, and be fashionable with the, the latest trends. Cause it's over before you even get >>There. Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens in six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Desel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There, there's three big trends that we invest in. And they're the, they're the only things we do day in, day out. One is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen on AMWA timeline >>Happening forever. >>But, uh, it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now a category of software. It's not just that we store data. It's now we move data and we develop applications. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more, more. Yeah. Uh, and those are the three major trends that we >>Run and security, you think we all need a dessert do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cybersecurity as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relat to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion and it still is a fraction of what >>We're, what we're national security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital that's >>Right. You mean arguably, right. Arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta outta say, I gotta love your firm. Love what you're doing. We're big supporters of your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking we'll maybe see a Coon. Uh, absolutely certainly EU maybe even north Americans in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the >>Show. Guess a bell V see Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After this short break, stay with us.

(upbeat music) >> Hello, welcome to this CUBE conversation I'm John Furrier your host here in theCUBE in Palo Alto, California, featuring Cribl a hot startup taking over the enterprise when it comes to data pipelining, and we have a CUBE alumni who's the co-founder and CEO, Clint Sharp. Clint, great to see you again, you've been on theCUBE, you were on in 2013, great to see you, congratulations on the company that you co-founded, and leading as the chief executive officer over $200 million in funding, doing this really strong in the enterprise, congratulations thanks for joining us. >> Hey, thanks John it's really great to be back. >> You know, remember our first conversation the big data wave coming in, Hadoop World 2010, now the cloud comes in, and really the cloud native really takes data to a whole nother level. You've seeing the old data architectures being replaced with cloud scale. So the data landscape is interesting. You know, Data as Code you're hearing that term, data engineering teams are out there, data is everywhere, it's now part of how developers and companies are getting value whether it's real time, or coming out of data lakes, data is more pervasive than ever. Observability is a hot area, there's a zillion companies doing it, what are you guys doing? Where do you fit in the data landscape? >> Yeah, so what I say is that Cribl and our products and we solve the problem for our customers of the fundamental tension between data growth and budget. And so if you look at IDCs data data's growing at a 25%, CAGR, you're going to have two and a half times the amount of data in five years that you have today, and I talk to a lot of CIOs, I talk to a lot of CISOs, and the thing that I hear repeatedly is my budget is not growing at a 25% CAGR so fundamentally, how do I resolve this tension? We sell very specifically into the observability in security markets, we sell to technology professionals who are operating, you know, observability in security platforms like Splunk, or Elasticsearch, or Datadog, Exabeam, like these types of platforms they're moving, protocols like syslog, they're moving, they have lots of agents deployed on every endpoint and they're trying to figure out how to get the right data to the right place, and fundamentally you know, control cost. And we do that through our product called Stream which is what we call an observability pipeline. It allows you to take all this data, manipulate it in the stream and get it to the right place and fundamentally be able to connect all those things that maybe weren't originally intended to be connected. >> So I want to get into that new architecture if you don't mind, but let me first ask you on the problem space that you're in. So cloud native obviously instrumentating, instrumenting everything is a key thing. You mentioned data got all these tools, is the problem that there's been a sprawl of things being instrumented and they have to bring it together, or it's too costly to run all these point solutions and get it to work? What's the problem space that you're in? >> So I think customers have always been forced to make trade offs John. So the, hey I have volumes and volumes and volumes of data that's relevant to securing my enterprise, that's relevant to observing and understanding the behavior of my applications but there's never been an approach that allows me to really onboard all of that data. And so where we're coming at is giving them the tools to be able to, you know, filter out noise and waste, to be able to, you know, aggregate this high fidelity telemetry data. There's a lot of growing changes, you talk about cloud native, but digital transformation, you know, the pandemic itself and remote work all these are driving significantly greater data volumes, and vendors unsurprisingly haven't really been all that aligned to giving customers the tools in order to reshape that data, to filter out noise and waste because, you know, for many of them they're incentivized to get as much data into their platform as possible, whether that's aligned to the customer's interests or not. And so we saw an opportunity to come out and fundamentally as a customers-first company give them the tools that they need, in order to take back control of their data. >> I remember those conversations even going back six years ago the whole cloud scale, horizontally scalable applications, you're starting to see data now being stuck in the silos now to have high, good data you have to be observable, which means you got to be addressable. So you now have to have a horizontal data plane if you will. But then you get to the question of, okay, what data do I need at the right time? So is the Data as Code, data engineering discipline changing what new architectures are needed? What changes in the mind of the customer once they realize that they need this new way to pipe data and route data around, or make it available for certain applications? What are the key new changes? >> Yeah, so I think one of the things that we've been seeing in addition to the advent of the observability pipeline that allows you to connect all the things, is also the advent of an observability lake as well. Which is allowing people to store massively greater quantities of data, and also different types of data. So data that might not traditionally fit into a data warehouse, or might not traditionally fit into a data lake architecture, things like deployment artifacts, or things like packet captures. These are binary types of data that, you know, it's not designed to work in a database but yet they want to be able to ask questions like, hey, during the Log4Shell vulnerability, one of all my deployment artifacts actually had Log4j in it in an affected version. These are hard questions to answer in today's enterprise. Or they might need to go back to full fidelity packet capture data to try to understand that, you know, a malicious actor's movement throughout the enterprise. And we're not seeing, you know, we're seeing vendors who have great log indexing engines, and great time series databases, but really what people are looking for is the ability to store massive quantities of data, five times, 10 times more data than they're storing today, and they're doing that in places like AWSS3, or in Azure Blob Storage, and we're just now starting to see the advent of technologies we can help them query that data, and technologies that are generally more specifically focused at the type of persona that we sell to which is a security professional, or an IT professional who's trying to understand the behaviors of their applications, and we also find that, you know, general-purpose data processing technologies are great for the enterprise, but they're not working for the people who are running the enterprise, and that's why you're starting to see the concepts like observability pipelines and observability lakes emerge, because they're targeted at these people who have a very unique set of problems that are not being solved by the general-purpose data processing engines. >> It's interesting as you see the evolution of more data volume, more data gravity, then you have these specialty things that need to be engineered for the business. So sounds like observability lake and pipelining of the data, the data pipelining, or stream you call it, these are new things that they bolt into the architecture, right? Because they have business reasons to do it. What's driving that? Sounds like security is one of them. Are there others that are driving this behavior? >> Yeah, I mean it's the need to be able to observe applications and observe end-user behavior at a fine-grain detail. So, I mean I often use examples of like bank teller applications, or perhaps, you know, the app that you're using to, you know, I'm going to be flying in a couple of days. I'll be using their app to understand whether my flight's on time. Am I getting a good experience in that particular application? Answering the question of is Clint getting a good experience requires massive quantities of data, and your application and your service, you know, I'm going to sit there and look at, you know, American Airlines which I'm flying on Thursday, I'm going to be judging them based on off of my experience. I don't care what the average user's experience is I care what my experience is. And if I call them up and I say, hey, and especially for the enterprise usually this is much more for, you know, in-house applications and things like that. They call up their IT department and say, hey, this application is not working well, I don't know what's going on with it, and they can't answer the question of what was my individual experience, they're living with, you know, data that they can afford to store today. And so I think that's why you're starting to see the advent of these new architectures is because digital is so absolutely critical to every company's customer experience, that they're needing to be able to answer questions about an individual user's experience which requires significantly greater volumes of data, and because of significantly greater volumes of data, that requires entirely new approaches to aggregating that data, bringing the data in, and storing that data. >> Talk to me about enabling customer choice when it comes around controlling their data. You mentioned that before we came on camera that you guys are known for choice. How do you enable customer choice and control over their data? >> So I think one of the biggest problems I've seen in the industry over the last couple of decades is that vendors come to customers with hugely valuable products that make their lives better but it also requires them to maintain a relationship with that vendor in order to be able to continue to ask questions of that data. And so customers don't get a lot of optionality in these relationships. They sign multi-year agreements, they look to try to start another, they want to go try out another vendor, they want to add new technologies into their stack, and in order to do that they're often left with a choice of well, do I roll out like get another agent, do I go touch 10,000 computers, or a 100,000 computers in order to onboard this data? And what we have been able to offer them is the ability to reuse their existing deployed footprints of agents and their existing data collection technologies, to be able to use multiple tools and use the right tool for the right job, and really give them that choice, and not only give them the choice once, but with the concepts of things like the observability lake and replay, they can go back in time and say, you know what? I wanted to rehydrate all this data into a new tool, I'm no longer locked in to the way one vendor stores this, I can store this data in open formats and that's one of the coolest things about the observability late concept is that customers are no longer locked in to any particular vendor, the data is stored in open formats and so that gives them the choice to be able to go back later and choose any vendor, because they may want to do some AI or ML on that type of data and do some model training. They may want to be able to forward that data to a new cloud data warehouse, or try a different vendor for log search or a different vendor for time series data. And we're really giving them the choice and the tools to do that in a way in which was simply not possible before. >> You know you are bring up a point that's a big part of the upcoming AWS startup series Data as Code, the data engineering role has become so important and the word engineering is a key word in that, but there's not a lot of them, right? So like how many data engineers are there on the planet, and hopefully more will come in, come from these great programs in computer science but you got to engineer something but you're talking about developing on data, you're talking about doing replays and rehydrating, this is developing. So Data as Code is now a reality, how do you see Data as Code evolving from your perspective? Because it implies DevOps, Infrastructure as Code was DevOps, if Data as Code then you got DataOps, AIOps has been around for a while, what is Data as Code? And what does that mean to you Clint? >> I think for our customers, one, it means a number of I think sort of after-effects that maybe they have not yet been considering. One you mentioned which is it's hard to acquire that talent. I think it is also increasingly more critical that people who were working in jobs that used to be purely operational, are now being forced to learn, you know, developer centric tooling, things like GET, things like CI/CD pipelines. And that means that there's a lot of education that's going to have to happen because the vast majority of the people who have been doing things in the old way from the last 10 to 20 years, you know, they're going to have to get retrained and retooled. And I think that one is that's a huge opportunity for people who have that skillset, and I think that they will find that their compensation will be directly correlated to their ability to have those types of skills, but it also represents a massive opportunity for people who can catch this wave and find themselves in a place where they're going to have a significantly better career and more options available to them. >> Yeah and I've been thinking about what you just said about your customer environment having all these different things like Datadog and other agents. Those people that rolled those out can still work there, they don't have to rip and replace and then get new training on the new multiyear enterprise service agreement that some other vendor will sell them. You come in and it sounds like you're saying, hey, stay as you are, use Cribl, we'll have some data engineering capabilities for you, is that right? Is that? >> Yup, you got it. And I think one of the things that's a little bit different about our product and our market John, from kind of general-purpose data processing is for our users they often, they're often responsible for many tools and data engineering is not their full-time job, it's actually something they just need to do now, and so we've really built tool that's designed for your average security professional, your average IT professional, yes, we can utilize the same kind of DataOps techniques that you've been talking about, CI/CD pipelines, GITOps, that sort of stuff, but you don't have to, and if you're really just already familiar with administering a Datadog or a Splunk, you can get started with our product really easily, and it is designed to be able to be approachable to anybody with that type of skillset. >> It's interesting you, when you're talking you've remind me of the big wave that was coming, it's still here, shift left meant security from the beginning. What do you do with data shift up, right, down? Like what do you, what does that mean? Because what you're getting at here is that if you're a developer, you have to deal with data but you don't have to be a data engineer but you can be, right? So we're getting in this new world. Security had that same problem. Had to wait for that group to do things, creating tension on the CI/CD pipelining, so the developers who are building apps had to wait. Now you got shift left, what is data, what's the equivalent of the data version of shift left? >> Yeah so we're actually doing this right now. We just announced a new product a week ago called Cribl Edge. And this is enabling us to move processing of this data rather than doing it centrally in the stream to actually push this processing out to the edge, and to utilize a lot of unused capacity that you're already paying AWS, or paying Azure for, or maybe in your own data center, and utilize that capacity to do the processing rather than having to centralize and aggregate all of this data. So I think we're going to see a really interesting, and left from our side is towards the origination point rather than anything else, and that allows us to really unlock a lot of unused capacity and continue to drive the kind of cost down to make more data addressable back to the original thing we talked about the tension between data growth, if we want to offer more capacity to people, if we want to be able to answer more questions, we need to be able to cost-effectively query a lot more data. >> You guys had great success in the enterprise with what you got going on. Obviously the funding is just the scoreboard for that. You got good growth, what are the use cases, or what's the customer look like that's working for you where you're winning, or maybe said differently what pain points are out there the customer might be feeling right now that Cribl could fit in and solve? How would you describe that ideal persona, or environment, or problem, that the customer may have that they say, man, Cribl's a perfect fit? >> Yeah, this is a person who's working on tooling. So they administer a Splunk, or an Elastic, or a Datadog, they may be in a network operations center, a security operation center, they are struggling to get data into their tools, they're always at capacity, their tools always at the redline, they really wish they could do more for the business. They're kind of tired of being this department of no where everybody comes to them and says, "hey, can I get this data in?" And they're like, "I wish, but you know, we're all out of capacity, and you know, we have, we wish we could help you but we frankly can't right now." We help them by routing that data to multiple locations, we help them control costs by eliminating noise and waste, and we've been very successful at that in, you know, logos, like, you know, like a Shutterfly, or a, blanking on names, but we've been very successful in the enterprise, that's not great, and we continue to be successful with major logos inside of government, inside of banking, telco, et cetera. >> So basically it used to be the old hyperscalers, the ones with the data full problem, now everyone's got the, they're full of data and they got to really expand capacity and have more agility and more engineering around contributions of the business sounds like that's what you guys are solving. >> Yup and hopefully we help them do a little bit more with less. And I think that's a key problem for our enterprises, is that there's always a limit on the number of human resources that they have available at their disposal, which is why we try to make the software as easy to use as possible, and make it as widely applicable to those IT and security professionals who are, you know, kind of your run-of-the-mill tools administrator, our product is very approachable for them. >> Clint great to see you on theCUBE here, thanks for coming on. Quick plug for the company, you guys looking for hiring, what's going on? Give a quick update, take 30 seconds to give a plug. >> Yeah, absolutely. We are absolutely hiring cribl.io/jobs, we need people in every function from sales, to marketing, to engineering, to back office, GNA, HR, et cetera. So please check out our job site. If you are interested it in learning more you can go to cribl.io. We've got some great online sandboxes there which will help you educate yourself on the product, our documentation is freely available, you can sign up for up to a terabyte a day on our cloud, go to cribl.cloud and sign up free today. The product's easily accessible, and if you'd like to speak with us we'd love to have you in our community, and you can join the community from cribl.io as well. >> All right, Clint Sharp co-founder and CEO of Cribl, thanks for coming to theCUBE. Great to see you, I'm John Furrier your host thanks for watching. (upbeat music)

(bright music) >> Welcome back to theCUBE's coverage of AWS re:Invent 2021. I'm John Furrier, your host of theCUBE. We have Michael D´aniello, platform architect at VMware's Carbon Black. Michael, great to see you. We're here at re-Invent virtual hybrid in person. Great to have you on theCUBE. Thanks for coming on. >> Yeah, thanks a lot. Glad to be here. >> So one of the big stories that we're tracking, obviously, is workloads. All cloud for all workloads. Obviously the data is a big part of things, but under the covers and optimizing cloud for the application developers, this modern application movement is more and more at the top of the stack. People just wanting to code. Infrastructure as code. You've seen DevSecOps is a big trend that's driving all new microservices, all new greatness for developers, but still, there's an optimization question. I want to get your thoughts on this, is what you do. Take a minute to explain what your role is at Carbon Black around this cloud optimization. >> Yeah, absolutely. Yeah, so my name is Michael D'aniello. I am a platform architect of VMware Carbon Black. I work across all the different engineering teams. And our main objective is to develop scalable platform tools and that includes, yeah, cloud security, automation pieces, pipelines, cost optimization, like we'll be talking about today, developer enablement tooling and observability tooling. >> One of the big things about instances is that, you know, do I have enough instances? 'Cause honestly, the elastic cloud is amazing, all kinds of new resources there, but talk about the AMD portion of the instances. How do we identify these instances? How to developers understand it, what's in them, and what's the selection criteria? Take us through that whole process of the Amazon web service and the AMD instances. >> Yeah, sure. So essentially, we're leveraging a lot of our instances to run our EKS clusters, which is a managed service for me and for us to run our Kubernetes clusters. And we identify that we can take a bunch of those instances and gain some cost optimization benefits by selecting from Intel to AMD processors. And, you know, initially, we had measured out to be roughly a 10% reduction in cost just for selecting that instance type. But yeah, we actually learned we gained quite a bit more, so. >> John: You know, developers are always like, I want more power, and this is what, you know, the whole idea of Cloud is. Cloud scale has been a big competitive advantage, but also the cost aspect of it. What's the balance between maximizing performance and cost optimization? Because now, you know, people don't want to, you know, they want more power. They also don't want to have a lot of extra spend. And this is kind of one of those things they talk about in Cloud where it's been so successful, cost is important. >> Yeah, yeah, for sure. And it's got to be easy, too, to get that cost optimization benefit. Otherwise, you're spending all your cycles and burning that money there in the human capital and the team and the engineering effort. So luckily, this change is a one-line change. We use Terraform for our automated provisioning, a layer, and we were able to make that one line change and then developers didn't have to make any application changes, which was great. So it was a no-brainer for us to pursue this. >> Talk about the EC2 instances that leverage AMD based process for the EKS, you mentioned that earlier, what is that all about? What's the benefits, what's in it for you guys? >> Yeah, for sure. So essentially, the workloads that are running on these instance types are actual Carbon Black Cloud application. So, all the backend systems that support our customers. And so in that use case, we're, you know, we're spinning up all of our containers that are running our applications and essentially, that's our use case for those instance types. >> How did you come to use the AWS EC2 instances on the AMD? Did you have an evaluation process? Did you just go select it? I mean, take us through that migration aspect of it. >> Yeah, sure, yeah. So originally, we're looking across the board. How can we do better cost optimization, right? And that goes across every different AWS resource, but we targeted this one specifically. We worked alongside with their AWS TAMs and representatives to basically find out, "Hey, is this financially worth the effort?" And we did reach that conclusion with some analysis, basically targeting these instance types and doing some analysis on that cost optimization specifically. And it ended up, you know, being the right thing to target. >> What was the ease of use of the switch? Take us through that. Was it a heavy lift? Was it seamless? Take us through the impact, there, on the move over and what were the results of that? >> Yeah, so I mean, that's the greatest thing. Like I said before, I mean, we had to make just a single line change just to change that instance type in our config and then roll that out across our regions. We did slow roll that in order to make sure that those changes in our development environments didn't make any, you know, performance hits or we didn't run into any snags with the applications themselves. But yeah, I mean, that's the greatest part about the story from my perspective is the ease to migrate over and to switch to these instance types, and then you just immediately gain that cost optimization benefit. >> You know what I love about what your job is, platform architect, that word kind of had a lot of meaning even 10, 15 years ago, but now with the Cloud, it's almost like you're always finagling and managing and massaging and nurturing the infrastructure to enable it. More new things are coming online as well, more high level services. So you've got a fun job and it's always evolving. How do you stay on top of it? What's the impact been for your customers, too, as you start deploying some of these new instance capabilities? Take us through kind of a day in the life of what you do and then what's the impact of customers? >> Yeah, sure. So, you know, like you said, there's quite a bit now to look at. You know, you got to stay on top of different blogs and keep connected with your network to see what your other colleagues are doing across different companies. You know, you can go into conferences like AWS re:Invent, right, to keep on the cutting edge here. But yeah, that's essentially, you know, one of the key aspects is just trying to look at all the different aspects, all the new technologies that are coming out, making sure you're making the right choices there and trying to get the most bang for your buck while you're at it. >> What are some of the big factors that you see in cloud native as you start to look at what customers are doing? Obviously with Kubernetes, you're starting to see that platform develop inside the industry as well as de facto, kind of orchestration layer. But now as customers start to look at it, they want to have more ease of use there, too. At the same time, they don't want to have to do a lot of front end work. They want to get instant benefits in the Cloud, obviously, whether it's from a security standpoint or just rolling out a modern application. Okay, so as having all this infrastructure under the covers, how do you look at that problem and how do you capture that opportunity? >> Yeah, and I think that's why we're seeing a movement here on platform teams. It's kind of a newer terminology, usually a band of developers and SREs come together and say, "Well, we've got a lot of different things to look at. We're onboarding applications to Kubernetes, and we need to make tools so that developers don't have to think much about the transition and the underlying platform." And so that's one of our success metrics on the platform engineering team is just to almost, you know, be non-existent, right? To just have everything flow through our systems and then have just a high ease of use to onboard the applications to the new platform. >> You know, it looks like you have some great success with the AMD based instances. Can I ask you a question? 'Cause I wanted figure this out. How do you identify an AMD based instance when you're making the selections? >> Yeah, sure. It's as easy as just the A after the name. So for us, it was the C5.4XL. And if you want the AMD one, it's just the C5A.4XL. So I guess technically, instead of a one line change, it's actually a one letter change. So, quite easy there. >> Yeah, it's almost like back in the old glory days of command line, one quick update. The customer aspect of this is also important, too. If you don't mind, while I got you here, what are some of the things that you're hearing from your customers, from a performance standpoint, that they're looking for? Obviously, the cost optimization is key, but as they look to deploy more power and more performance, what are some of the things that your customers are looking for from Carbon Black? >> Yeah, so I mean, we are a security company, but we're really a data company because we have, you know, 8,000 customers, we processed over a trillion events per day, we ingress over a hundred terabytes of data per day. And so, our customers need high level performance. And if we can't provide that with low latency, we're not successful. So that's why, you know, performance on the underlying systems that are running our applications is super critical. >> Yeah, you're looking at trailblazer over there. I mean, the work that you guys are doing with the data is amazing. And that's a big theme at re:Invent this year is that data is a huge part. We look at the success of the cloud growth on this, I call gen-two cloud, happening. This whole modern movement is all about how people handle the data at scale, 'cause cloud scales here and now you've got processing all that data, The trailblazing that's going on, there's like this new wave of, I almost called it first-generation trailblazers, but you guys are doing that. What advice would you have for other architects out there and kind of the mainstream enterprises who are like, "Hey, I want to take advantage of the path that you guys have plowed through." What's your advice? >> Yeah, I think one of the key things in a place where we've had a lot of success is creating standards, making sure that we're choosing technology wisely, and making sure that your company isn't building the same solution in silos. And you know, that's a huge pattern that I've seen in my career. And if you can negate that, you're going to be in a great place. So, you know, choose the right technology, container first, cloud native first, push forward, and then make sure that everybody's kind of on that same ship running in the same direction. >> Well, great case study on this AMD based instance migration. Was there any uplift and experience that you've seen on the switch and the performance? Can you just talk about that? What does it mean to upgrade? What benefits are you seeing on the performance you have? >> Yeah, so I didn't hit on this yet and I really wanted to. Yeah, so upfront, the instance itself is 10% cheaper. However, we found out that we had to run far less instances because of that performance increase. So we ended up saving roughly 30% and we've continued to scale out. So at first, it was a couple of hundred instances. Now we're in the thousands and we're going to keep ramping up to over 10 thousands, tens of that. >> John: Let me get this right. So single line change, letter change, instance change. So you get not as many instances, and you save money, so you get cost optimization and higher performance. >> Yep. They say, if it's too good to be true, it's not. But in this case, it actually is. >> So why is it so good in your opinion? What did you discover? What was the big revelation that went down this path? Because that's good value proposition. >> Yeah, for sure. I mean, so initially, we were just chasing that initial BC to 10% and then as we kind of push it forward, we're looking at the metrics, month to month costs and we're actually saying, well, as we kind of swap over from one instance type to another, we're actually paying less. And then once we fully swapped over, it took five or six months to get to the same amount of costs as we continued to scale upward. So it's been a great story. >> It is a great story. It's super nuanced, but it's super important to know these platform benefits. I got to ask you on a personal question, if you don't mind. We love covering Cloud. We've been covering Amazon, it's our ninth year at re:Invent. Just love covering all the action and tech as this just total awesomeness environment. Cloud scale, innovation, capabilities, it's like surfing a big wave. But there's a bigger wave coming and we're seeing it now. I want to get your thoughts on this. As you look to the next big wave, beyond Cloud now, Cloud scale, data, new architecture is rolling out with Edge, basically distributing computing at large scale, and tons of security challenges, right? How do you look at this next big wave coming? Are you staring at it saying, wow, this is going to be huge? And how do you ride that wave? What's your mindset and how do you look at that? >> Well first of all, I'm extremely excited about it. Just the further this thing grows out, there's definitely more complexity, but just a whole slew of fun problems to solve. But when we look at these different problems and solving them at scale across multiple regions, it gets pretty exciting, right? So I can say one example of this is our security of our Cloud, not the security product, and we've developed automation for prevention and auto-remediation in our pipelines. It's been such a success story. And these type of technologies did not exist even a couple of years ago and we've been able to take advantage of them. So, there's going to be a lot more of that where that came from. So, yeah. >> Michael, great work. And again, you're truly a trailblazer, and this is, again, you got to do it. You got to screw your own cloud and stay on the cutting edge and ride that wave. Congratulations on the CostOp cloud optimization and the success with AMD based instances. Congratulations. Thanks. >> Thanks. >> Okay, this is theCUBEs coverage of AWS's re:Invent 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (inspirational music)

(bright music) >> Welcome back to theCUBE's coverage of AWS re:Invent 2021. I'm John Furrier, your host of theCUBE. We have Michael D´aniello, platform architect at VMware's Carbon Black. Michael, great to see you. We're here at re-Invent virtual hybrid in person. Great to have you on theCUBE. Thanks for coming on. >> Yeah, thanks a lot. Glad to be here. >> So one of the big stories that we're tracking, obviously, is workloads. All cloud for all workloads. Obviously the data is a big part of things, but under the covers and optimizing cloud for the application developers, this modern application movement is more and more at the top of the stack. People just wanting to code. Infrastructure as code. You've seen DevSecOps is a big trend that's driving all new microservices, all new greatness for developers, but still, there's an optimization question. I want to get your thoughts on this, is what you do. Take a minute to explain what your role is at Carbon Black around this cloud optimization. >> Yeah, absolutely. Yeah, so my name is Michael D'aniello. I am a platform architect of VMware Carbon Black. I work across all the different engineering teams. And our main objective is to develop scalable platform tools and that includes, yeah, cloud security, automation pieces, pipelines, cost optimization, like we'll be talking about today, developer enablement tooling and observability tooling. >> One of the big things about instances is that, you know, do I have enough instances? 'Cause honestly, the elastic cloud is amazing, all kinds of new resources there, but talk about the AMD portion of the instances. How do we identify these instances? How to developers understand it, what's in them, and what's the selection criteria? Take us through that whole process of the Amazon web service and the AMD instances. >> Yeah, sure. So essentially, we're leveraging a lot of our instances to run our EKS clusters, which is a managed service for me and for us to run our Kubernetes clusters. And we identify that we can take a bunch of those instances and gain some cost optimization benefits by selecting from Intel to AMD processors. And, you know, initially, we had measured out to be roughly a 10% reduction in cost just for selecting that instance type. But yeah, we actually learned we gained quite a bit more, so. >> John: You know, developers are always like, I want more power, and this is what, you know, the whole idea of Cloud is. Cloud scale has been a big competitive advantage, but also the cost aspect of it. What's the balance between maximizing performance and cost optimization? Because now, you know, people don't want to, you know, they want more power. They also don't want to have a lot of extra spend. And this is kind of one of those things they talk about in Cloud where it's been so successful, cost is important. >> Yeah, yeah, for sure. And it's got to be easy, too, to get that cost optimization benefit. Otherwise, you're spending all your cycles and burning that money there in the human capital and the team and the engineering effort. So luckily, this change is a one-line change. We use Terraform for our automated provisioning, a layer, and we were able to make that one line change and then developers didn't have to make any application changes, which was great. So it was a no-brainer for us to pursue this. >> Talk about the EC2 instances that leverage AMD based process for the EKS, you mentioned that earlier, what is that all about? What's the benefits, what's in it for you guys? >> Yeah, for sure. So essentially, the workloads that are running on these instance types are actual Carbon Black Cloud application. So, all the backend systems that support our customers. And so in that use case, we're, you know, we're spinning up all of our containers that are running our applications and essentially, that's our use case for those instance types. >> How did you come to use the AWS EC2 instances on the AMD? Did you have an evaluation process? Did you just go select it? I mean, take us through that migration aspect of it. >> Yeah, sure, yeah. So originally, we're looking across the board. How can we do better cost optimization, right? And that goes across every different AWS resource, but we targeted this one specifically. We worked alongside with their AWS TAMs and representatives to basically find out, "Hey, is this financially worth the effort?" And we did reach that conclusion with some analysis, basically targeting these instance types and doing some analysis on that cost optimization specifically. And it ended up, you know, being the right thing to target. >> What was the ease of use of the switch? Take us through that. Was it a heavy lift? Was it seamless? Take us through the impact, there, on the move over and what were the results of that? >> Yeah, so I mean, that's the greatest thing. Like I said before, I mean, we had to make just a single line change just to change that instance type in our config and then roll that out across our regions. We did slow roll that in order to make sure that those changes in our development environments didn't make any, you know, performance hits or we didn't run into any snags with the applications themselves. But yeah, I mean, that's the greatest part about the story from my perspective is the ease to migrate over and to switch to these instance types, and then you just immediately gain that cost optimization benefit. >> You know what I love about what your job is, platform architect, that word kind of had a lot of meaning even 10, 15 years ago, but now with the Cloud, it's almost like you're always finagling and managing and massaging and nurturing the infrastructure to enable it. More new things are coming online as well, more high level services. So you've got a fun job and it's always evolving. How do you stay on top of it? What's the impact been for your customers, too, as you start deploying some of these new instance capabilities? Take us through kind of a day in the life of what you do and then what's the impact of customers? >> Yeah, sure. So, you know, like you said, there's quite a bit now to look at. You know, you got to stay on top of different blogs and keep connected with your network to see what your other colleagues are doing across different companies. You know, you can go into conferences like AWS re:Invent, right, to keep on the cutting edge here. But yeah, that's essentially, you know, one of the key aspects is just trying to look at all the different aspects, all the new technologies that are coming out, making sure you're making the right choices there and trying to get the most bang for your buck while you're at it. >> What are some of the big factors that you see in cloud native as you start to look at what customers are doing? Obviously with Kubernetes, your starting to see that platform develop inside the industry as well as defacto, kind of orchestration layer. But now as customers start to look at it, they want to have more ease of use there, too. At the same time, they don't want to have to do a lot of front end work. They want to get instant benefits in the Cloud, obviously, whether it's from a security standpoint or just rolling out a modern application. Okay, so as having all this infrastructure under the covers, how do you look at that problem and how do you capture that opportunity? >> Yeah, and I think that's why we're seeing a movement here on platform teams. It's kind of a newer terminology, usually a band of developers and SREs come together and say, "Well, we've got a lot of different things to look at. We're onboarding applications to Kubernetes, and we need to make tools so that developers don't have to think much about the transition and the underlying platform." And so that's one of our success metrics on the platform engineering team is just to almost, you know, be non-existent, right? To just have everything flow through our systems and then have just a high ease of use to onboard the applications to the new platform. >> You know, it looks like you have some great success with the AMD based instances. Can I ask you a question? 'Cause I wanted figure this out. How do you identify an AMD based instance when you're making the selections? >> Yeah, sure. It's as easy as just the A after the name. So for us, it was the C5.4XL. And if you want the AMD one, it's just the C5A.4XL. So I guess technically, instead of a one line change, it's actually a one letter change. So, quite easy there. >> Yeah, it's almost like back in the old glory days of command line, one quick update. The customer aspect of this is also important, too. If you don't mind, while I got you here, what are some of the things that you're hearing from your customers, from a performance standpoint, that they're looking for? Obviously, the cost optimization is key, but as they look to deploy more power and more performance, what are some of the things that your customers are looking for from Carbon Black? >> Yeah, so I mean, we are a security company, but we're really a data company because we have, you know, 8,000 customers, we processed over a trillion events per day, we ingress over a hundred terabytes of data per day. And so, our customers need high level performance. And if we can't provide that with low latency, we're not successful. So that's why, you know, performance on the underlying systems that are running our applications is super critical. >> Yeah, you're looking at trailblazer over there. I mean, the work that you guys are doing with the data is amazing. And that's a big theme at re:Invent this year is that data is a huge part. We look at the success of the cloud growth on this, I call gen-two cloud, happening. This whole modern movement is all about how people handle the data at scale, 'cause cloud scales here and now you've got processing all that data, The trailblazing that's going on, there's like this new wave of, I almost called it first-generation trailblazers, but you guys are doing that. What advice would you have for other architects out there and kind of the mainstream enterprises who are like, "Hey, I want to take advantage of the path that you guys have plowed through." What's your advice? >> Yeah, I think one of the key things in a place where we've had a lot of success is creating standards, making sure that we're choosing technology wisely, and making sure that your company isn't building the same solution in silos. And you know, that's a huge pattern that I've seen in my career. And if you can negate that, you're going to be in a great place. So, you know, choose the right technology, container first, cloud native first, push forward, and then make sure that everybody's kind of on that same ship running in the same direction. >> Well, great case study on this AMD based instance migration. Was there any uplift and experience that you've seen on the switch and the performance? Can you just talk about that? What does it mean to upgrade? What benefits are you seeing on the performance you have? >> Yeah, so I didn't hit on this yet and I really wanted to. Yeah, so upfront, the instance itself is 10% cheaper. However, we found out that we had to run far less instances because of that performance increase. So we ended up saving roughly 30% and we've continued to scale out. So at first, it was a couple of hundred instances. Now we're in the thousands and we're going to keep ramping up to over 10 thousands, tens of that. >> John: Let me get this right. So single line change, letter change, instance change. So you get not as many instances, and you save money, so you get cost optimization and higher performance. >> Yep. They say, if it's too good to be true, it's not. But in this case, it actually is. >> So why is it so good in your opinion? What did you discover? What was the big revelation that went down this path? Because that's good value proposition. >> Yeah, for sure. I mean, so initially, we were just chasing that initial BC to 10% and then as we kind of push it forward, we're looking at the metrics, month to month costs and we're actually saying, well, as we kind of swap over from one instance type to another, we're actually paying less. And then once we fully swapped over, it took five or six months to get to the same amount of costs as we continued to scale upward. So it's been a great story. >> It is a great story. It's super nuanced, but it's super important to know these platform benefits. I got to ask you on a personal question, if you don't mind. We love covering Cloud. We've been covering Amazon, it's our ninth year at re:Invent. Just love covering all the action and tech as this just total awesomeness environment. Cloud scale, innovation, capabilities, it's like surfing a big wave. But there's a bigger wave coming and we're seeing it now. I want to get your thoughts on this. As you look to the next big wave, beyond Cloud now, Cloud scale, data, new architecture is rolling out with Edge, basically distributing computing at large scale, and tons of security challenges, right? How do you look at this next big wave coming? Are you staring at it saying, wow, this is going to be huge? And how do you ride that wave? What's your mindset and how do you look at that? >> Well first of all, I'm extremely excited about it. Just the further this thing grows out, there's definitely more complexity, but just a whole slew of fun problems to solve. But when we look at these different problems and solving them at scale across multiple regions, it gets pretty exciting, right? So I can say one example of this is our security of our Cloud, not the security product, and we've developed automation for prevention and auto-remediation in our pipelines. It's been such a success story. And these type of technologies did not exist even a couple of years ago and we've been able to take advantage of them. So, there's going to be a lot more of that where that came from. So, yeah. >> Michael, great work. And again, you're truly a trailblazer, and this is, again, you got to do it. You got to screw your own cloud and stay on the cutting edge and ride that wave. Congratulations on the CostOp cloud optimization and the success with AMD based instances. Congratulations. Thanks. >> Thanks. >> Okay, this is theCUBEs coverage of AWS's re:Invent 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (inspirational music)

(energetic music) >> Hello, welcome to the CUBE's coverage of Boomi's Out of This World event. I'm John Furrier, host of theCUBE. We've got two great guests here, Chris McNabb, CEO of Boomi, and Ed Macosky, SVP and Head of Products, talking about hyper automation and the future of connectivity. Gentlemen, thank you for coming on theCUBE, great to see you. >> John, it is great to see you again as well. Looking forward to the next in-person one. >> I miss the in-person events, you guys have had great events and a lot of action happening. Love the big news of going out on your own direction, big financing, change of control, all that good stuff happening, industries growing. Chris, this is a big move. You know, the industry is changing. Can you give us some context to, you know, what's going on in automation and connectivity, because iPaaS, which you guys have pioneered, have been a big part of Cloud and CloudScale, and now we're seeing next-generation things happening. Data, automation, edge, modern application development, all happening. Set some context, what's going on? >> Yeah John, listen, it's a great time to be in our space at this point in time. Our customers, at the end of the day, are looking to create what we announced at last year's thing, called Integrated Experiences, which is the combination of user engagement, more awesome connectivity, and making sure high quality data goes through that experience, and providing 21st century experiences. And we're right at the heart of that work. Our platform really drives all the services that are needed there. But what our customers really need and what we're here to focus on today, that this world is to make sure that we have the world's best cut connectivity capabilities, and process automation engagement of constituents to really do what they want to do, where they want to do it. >> So a lot of big moves happening, what's the story? Take us through the story. I mean, you guys have a transaction with big sum financing, setting up this intelligence connectivity and automation approach. Take us through the story, what happened? >> Yeah. So, you know, the lead business was sold outside of Dell and that deal closed. We are now owned by two top tier private equity firms, FP and TPG. That sale is completed and now we are ready to unleash the Boomi business on this market. I think it's a great, it's a great transaction for Dell, and it's a great transaction for FP, PTG but most specifically, it's really a world-class transaction for the Boomi business, the Boomi customer base, as well as the Boomi employee. So I really looked at this as a win-win-win and sets us up for really going after this one. >> Yeah, and there's a huge wave coming and you're seeing like the, the big wave coming. It's just like, no need to debate it. It's here. It's cloud 2.0, whatever you want to call it, it's scale. IT has completely figured out, that not only is replatforming the cloud, but you got to be in the cloud refactoring. This is driving the innovation. And, this is really I see where you guys are leading. So share with me what is hyper automation? What is that actually mean? >> So what hyper automation really is, is intelligent connectivity automation. So our customers have been doing this. It's very specifically related to taking workflows, taking automation within the business. That's been around for a long time anyway, but adding AI and ML to it. So, as you continue to automate your business, you're getting more and more steam, and you get more and more productivity out of the (mumbles) organization or productivity from the (mumbles). >> So Chris, tell us more about this hyper automation, because you guys have a large install base. Take us through some of the numbers of the customer base, and where the dots are connecting as they look at the new IT landscape as it transforms. >> Yeah. John, great question. You know, when I talk to, you know as many of our 18,000 customers worldwide as I can get to, you know, what they are saying very clearly is their IT news feed is getting more complicated, more distributed, more siloed, and it has more data. And as you work through that problem, what they're trying to accomplish, is they're trying to engage their constituents in a 21st century web, however they want, whether it be mobile web, portals, chat bots, old fashioned telephones. And in doing that, that complicated area is extraordinarily difficult. So that's the pervasive problem that Boomi is purpose-built to help solve. And our customers start out sometimes with just great connectivity. Hyper automation is where the real value comes in. That's where your constituents see a complete difference in how I inter-operate with (mumbles). >> So, first of all, I love the word hyper automation because it reminds me of hyper scale, which, you know, look at the Amazons and the cloud players. You know, that kind of game has kind of evolved. I mean, the old joke is what inning are we in, right? And, and I, to use a baseball metaphor, I think it's a doubleheader and game one is won by the cloud. Right? So, Amazon wins game one, game two is all about data. You guys, this is core to Boomi and I want to get your thoughts on this because data is the competitive advantage. But if you look at the pandemic and the stories that we're reporting on, and this reinvent specifically, that'll be a big story. The refactoring in the cloud is a big strategic effort, not just replatforming, refactoring in the cloud. So this is really where you guys are, I think, skating where the puck is. Am I getting it right, can you just share that vision? >> Yeah, John. From a vision perspective, I think the pandemic has really accelerated people's expectations. You know what we need to be more nimble, more flexible. And because they had a fair amount in the Cloud they have to understand what is the next tier, what is the next generation offerings that we put together tie together and connect. That is not only connecting systems, apps, databases, and clouds. You're connecting people, processes and devices. So we're going to have a great story here and out of this world about how we connect bio centric vest to a video system who a network monitoring hub to protect the officer's safety in Amsterdam in real-time. We can deploy officers to location all automatic. All decisions are automatic, all locations, cameras (mumbles) all automatically. And that's only possible, when we think about next generation technology that Boomi provides. Next generation capabilities by the other providers in that solution. >> Ed, before we get to the product announcements for the even, we'll get your reaction to that. I see in the cloud you can refactor, you got data, you got latency issues. These are all kind of go away when you start thinking about integrating it altogether. What's your reaction to refactoring as the next step? >> Yeah. So my regular, I mean, exactly what Chris said, but as our customers are moving to the cloud, they're not choosing any more, just one cloud. It is a multi-cloud it's multidimensional (mumbles), you got multi-cloud, you got hybrid cloud, you have edge devices, et cetera. And our technology just naturally puts this in the space to do that. And based on what we see with our customers, we actually have, we've connected over 189,000 different devices, application points, data endpoints, et cetera to people. And we're seeing that growth of 44% year on year. So, we're seeing that explosion in helping customers, and we just want to accelerate that, and help them react to these changes as quickly as they possibly can. And a lot of it doesn't require, you know, massive upload project technology. We've been lucky enough to be visionaries that with our deployment technology, being able to embrace this new environment that's coming up or we're right at the forefront of this (mumbles). >> Yeah. I love the intelligence saying, I love hyper automation. Okay, let's get into the product announcements of Out of This World event. What are some of the announcements, and share with us the key highlights. >> Yeah. So first and foremost, we've announced a vision in our tactic. So I talked about the 189,000 applications that we did data endpoints, et cetera, that our customers are picking today. And they're moving very, very rapidly with that and it's no longer about name, connections, and having these fixed auxiliary that connects to applications you need to be able to react intelligently, pick the next endpoint and connect very quickly and bring that into your ecosystem. So we've got this vision towards the connectivity service that we're working on that will basically normalize that connectivity across all of the applications that are plugging into Boomi's iPaaS ecosystem and allow customers to get up and running very quickly. So I'm really excited about that. The other thing we announced is Boomi event streams. So in order to complete this, we can't just, we've been on this EDA journey Event-Driven Architecture for the last couple of years, and embracing an open ecosystem. But we found that in order to go faster for our customers, it's very, very important that we bring this into Boomi's iPaaS platform. Our partnerships in this area are still very important for us. But there is an avenue that our customers are demanding that, "hey, bring us into your platform." And we need to move faster with this, and our new Boomi event streams will allow them to do that. We also recently just announced the Boomi Discover Catalog. So this is the, this is an ongoing vision us. We're, building up into a marketplace where customers and partners can all participate, whether it's inside of a customer's ecosystem or partners, or Boomi, et cetera, offering these quick onboarding solutions for their customers. So we will learn intelligently as people have these solutions to help customers onboard, and build, and connect to these systems faster. So that's kind of how they all come together for us In a hyper automation scenario the last thing too, is we are working on RPA as a last mile connectivity that's where we start RPAs today, you know, gone are going to be the days of having RPA at a desktop perspective where you have to have someone manually run that. Although its RPA our runtime technology extends the desktops anyway. So we are going to bring RPA technology into the IPaaS platform as we move forward here so that our customers can enjoy the benefits of that as well. >> That's real quick. It was going to ask about the fence stream. I love this RPA angle. Tell me more about how that impacts is that's that's what I think, pretty big what's the impact of when you bring robotic processes on our RPA into iPaaS, what's the, what's the impact of the customer? >> The impact of the customer is that we believe that customers can really enjoy true cloud when it comes to RPA technology today, most of the RPA technologies, like I said, are deployed at a desktop and they are, they are manually run by some folks. It helps speed up the business user and adds some value there. But our technology will surely bring it to the cloud and allow that connectivity of what an arm robotic process automation solution will be doing and can tap into the iPaaS ecosystem and extend and connect that data up into the cloud or even other operating systems that the customer (mumbles). >> Okay. So on the event streams that you did, you guys announced, obviously it's the best part of the embedded event driven architecture, You guys have been part of. What is, why is it important for customers? Can you just take a minute to explain why event streams and why event driven approaches are important. >> Because customers need access to the data real time. So, so there's two reasons why it's very important to the customers one is Event Driven Architectures are on the rise, in order to truly scale up an environment. If you're talking tens of millions of transactions, you need to have an Event Driven Architecture in place in order to manage that state. So you don't have any message loss or any of those types of things. So it's important that we continue to invest as we continue to scale on our customers and they scale up their environments with us. The other reason it is very important for us to bring it into our ecosystem, within our platform is that our customers enjoy the luxury of having an integrated experience themselves as they're building, you know, intelligent connectivity and automation solutions within our platform. So to ask a customer, to go work with a third party technology versus enjoying it in an integrated experience itself is why we want to bring it in and have them get their (mumbles) much faster. >> I really think you guys are onto something because it's a partnership world. Ecosystems are now everywhere. There's ecosystems, because everything's a platform now that's evolving from tools to platforms and it's not a one platform rules the world. This is the benefit of how the clouds emerging, almost a whole nother set of cloud capabilities. I love this vision and you start to see that, and you guys did talk about this thing called conductivity marketplace. And what is that? Is that a, is that a place where people are sharing instead of partnershipping? I know there's a lot of partners are connected with each other and they want to have it all automated. How does this all play in? Can you just quickly explain that? >> Yeah, so in the last year we launched and we actually launched open source community around connectors and that sort of thing we invested pretty heavily in RSDK. We see quite a big uptake in the ecosystem of them building specific connectors, as well as solution. And our partners were very excited about partnering with us and (mumbles) to markets and those sorts of things that they can offer solutions to their customers on a marketplace. So, so we are reacting to the popular demand that we have from our partners and customers where they say, Hey, we'd love to participate in this marketplace. We'd love to be able to work with you and publish solutions that we're delivering more customers. So, so we're, we're fulfilling that mission on behalf of our customers and partners. >> You know, Chris, when you look at the cloud native ecosystem at the high level, you're seeing opensource driving a big part of it, large enterprises, large customers are moving to that next level of modern application development. They're partnering, right? They're going to out, outsource and partner some, some edge components, maybe bring someone else over here, have a supplier everything's confide now in the cloud, AKA dev ops meets, you know, business logic. So this seems to be validated. How do you see this evolving? How does this iPaaS kind of environment just become the environment? I mean, it seems to me that that's what's happening. What's your reaction to the, to that trend? >> I think as iPaaS evolves we've extended the breadth of our iPaaS dramatically. We're not an integration platform. We're, we take the broadest definition of the word integration I guess I'll say it that way. You'll be integrating people. Connecting people is just as important as connecting cloud applications So, you know, that that's part one in terms of the vision of what it is two is going to be the importance of speed and productivity. It's critically important that people can figure out how to reconnect because endpoints are exploding. You have to connect these extraordinarily quickly infractions of the amount of time that it ever took and coding, code is just not the way that that works. You have to have it abstracted and you have to make it simpler, low-code, no-code environments, configuration based environments, make it simpler for more people outside of IT to actually use the solutions. So that's where these platforms become much more pervasive than the enterprise, solve a much bigger problem, and they solve it at speeds. So, you know, the vision for this is just to continue to accelerate that, you know, when we got started here, things used to take months and months, you know, it came down to weeks, it came down to days, it's in to hours. We're looking at seconds to define connectivity in an easy button, those get connected and get working. That's our vision for intelligent connectivity. >> Okay, so we're talking about hyper automation in the future context. That's the segment here? What is a feature conductivity? Take me through that. How does that evolve? I can see marketplace. I can see an ecosystem. I see people connecting with partners and applications and data. What is the future of connectivity? >> The vision, right? For connectivity, and they talk about our connectivity as a service, but you know, you have to think about it as connectivity instead of connectors, like an NBO, a thing that talks to it, and what we look at is like, you should be able to point to an endpoint, pick a cloud app, any cloud application.  You have an API. I should be able to automatically programmatically and dynamically, anytime I want go interrogate that, browse it in the button and I've established connectivity, and the amount of take, in the amount of time it's taken me to explain it, you should almost be able to work through it and be connected to that and talking to that endpoint, we're going to bring that kind of connectivity, that dynamic generated, automatic connectivity, in to our platform, and that's the vision >> And people connect to user from a product standpoint and this should be literally plug and play, so to speak, old, old term, but really seamlessly, automated play, automate and play kind of just connect. >> Yes, absolutely. And what Chris was talking, I was thinking about a customer to be named, but one of the, during one of the interviews coming up at Out of this World, the customer was describing to us today, already the capabilities that we have, where he is, a CTO was able to get an integration up and running before this team was able to write the requirements for the integration. So, so those are the types of things we're looking to continue add to, to add to. And we're also, you know, not asking our customers to make a choice. You can scale up and scale down. It's very important for our customers to realize whether the problem's really big or really small our platforms there to get it done fast and in a secure way. >> I see a lot of people integrating in the cloud with each other and themselves other apps, seeing huge benefits while still working on premise across multiple environments. So this kind of new operating models evolving, some people call it refactoring, whatever term you want to use. It's a change of, of a value creation, creates new value. So as you guys go out, Chris, take us through your vision on next steps. Okay. You're, you're going to be independent. You got the financing behind you. Dell got a nice deal. You guys are going forward. What's next for boomi? >> Well, listen John, we, we, you know, we couldn't be more excited having the opportunity to truly unleash, you know, this business out on the market and you know, our employees are super excited. Our customers are going to benefit. Our customers are going to get a lot more product innovation every single day, we are ready to put out 11 releases a year. There's literally a hundred different features we put in that product. We're looking to double down on that and really accelerate our path towards those things what we were talking about today. Engagement with our customers gets to get much better, you know, doubling down on customer success. People support people, PSL in the field gets us engaging our customers in so many different ways. There's so much more folks that when we partner with our customers, we care about their overall success, and this investment really gives us so many avenues now to double down on and making sure that their journey with us and their journey towards their success as a business and how we can help them. Some of them, we help them get there. >> You guys got a lot of trajectory and experience and knowledge in this industry I think. It's really kind of a great position to be in. And as you guys take on this next wave, Chris McNabb, CEO Boomi, Ed Macosky, SVP, head of projects, thanks for coming on the cube, and this is the cube coverage of Boomi's Out of This World. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> Welcome back to theCUBE's covering of AWS Public Sector Summit. In-person here in Washington, DC. I'm John Furrier, your host, great to be back face to face. We've got a great, special guest Clint Crosier, who is the Director of AWS' Aerospace & Satellite. Major General of The Air Force/Space Force. Retired. Great to see you in person again. Thanks for coming on theCUBE. >> Thank you for having me. I appreciate that. >> First of all, props to you for doing a great job at Amazon, bringing all your knowledge from Space Force and Air Force into the cloud. >> Thank you. >> So that's great, historical context. >> It's been valuable and it's provided a whole lot of insight into what we're building with the AWS space team, for sure. >> So number one question I get a lot is: We want more space content. What's the coolest thing going on in space? Is there a really a satellite behind the moon there, hidden there somewhere? What's the coolest thing going on in space? >> Well, the coolest thing that's going on in space, I think is you're seeing the rapid growth of the space industry, I mean, to me. I've been in the space industry for 34 years now, and there have been periods where we projected lots of growth and activity and it just didn't really come about, especially in the 80's and the 90's. But what we're seeing today is that growth is taking place. Whether it's the numbers of satellites that are being launched around the globe every year, there's some 3,000 objects on orbit today. Estimates are that there'll be 30,000 objects at the end of the decade, or the number of new companies, or the number of global spinning. It is just happening right now, and it's really exciting. >> So, when people say or hear space, there's a lot of economic changes in terms of the cost structures of how to get things deployed into space. That brings up the question of: Is space an opportunity? Is it a threat vector? What about congestion and security? >> Yeah, well three great things, absolutely an opportunity. We're seeing the rapid growth of the space industry, and we're seeing more commercialization than ever before. In my whole career, The Air Force or, NASA, or the NRO would sort of, hold things and do them themselves Today, you're seeing commercial contracts going out from the National Reconnaissance Office, NASA, from The Air Force, from the Space Force. So lots of opportunity for commercial companies. Security. Absolutely, priority number one should be security is baked into everything we do at AWS. And our customers, our Government classified customers tell us the reason they came to AWS is our security is top notch and certified for all their workloads. And as you well know, we have from unclassified all the way up to top secret capabilities on the AWS cloud. So just powerful opportunities for our customers. >> Yeah. And a lot of competitors will throw foot on that. I know, I've reported on some of that and not a lot of people have that same credential. >> Sure. >> Compared to the competition. >> Sure. >> Now I have to ask you, now that you have the top secret, all these clouds that are very tailorable, flexible with space: How are you helping customers with this Aerospace Division? Is it is a commercial? In the public sector together? What's the... >> All of the above. >> Take us through the value proposition. >> Yeah, happy to do this. So what we recognized over the last two years or so we, at AWS, recognized all this rapid growth that we're talking about within the space industry. Every sector from launch to on-orbit activities, to space exploration, all of it. And so AWS saw that and we looked at ourselves and said: "Do we have the right organization and expertise in place really to help our customers lean into that?" And the answer was: we decided to build a team that had deep experience in space, and that was the team that we grew because our thesis was: If you have a deep experience in space, a deep experience in cloud, you bring those two together and it's a powerful contribution. And so we've assembled a team with more than 500 years of collective hands-on experience, flying satellites, launching rockets. And when we sit down with our customers to innovate on their behalf, we're able to come up with some incredible solutions and I'm happy to talk about those. >> I'd love to, but tell you what, first of all, there's a lot of space nerds out there. I love space. I love space geeking out on the technology, but take us through the year you had, you've had a pretty incredible year with some results. You have that brain trust there. I know you're hiring. I know that people want to work for you. I'm sure the resumes are flying in, a lot of action. >> There is. >> What are the highlights from this year? >> So the highlights I think is, we've built a team that the industry is telling us was needed. Again, there was no organization that really served the space cloud industry. And so we're kind of building this industry within the industry, the space cloud industry. And so number one, just establishing that team and leaning into that industry has been valuable. The other thing that we're real proud of is we built a global team, because space is a global enterprise. We have teams in Europe and in Asia and South America here in the U.S., so we built a global team. One of the things that we did right up front, we weren't even six months old, when we envisioned the idea of doing the AWS Space Accelerator. And some of the folks told me: "Clint, six months under your belt, maybe you ought to get your feet under you." And I said: "No, no. We move fast to support our customers." And so we made a call for any space startup that wanted to come on board with AWS and go through our four week Space Accelerator. We partnered with Sarah from Capital. And the idea was: if you're a small company that wants to grow and build and learn how you can use the cloud to gain competitive advantage, come with us. And so John, I would have been happy if we had 50 companies applied, we had 194 companies across 44 countries that applied to our accelerator. We had to down select a 10, but that was a tremendous accomplishment, two of those are speaking this afternoon, where they met each other at our accelerator and now have formed a partnership: Ursa Space and HawkEye 360 on how they build on the cloud together. Fascinating. >> Well, I love that story. First of all, I love the military mindset. No, we're not going to wait. >> Move it out. >> It's not take that hill, it's take that planet. >> Our customers won't wait, innovation, doesn't wait, the future doesn't wait. We have to move out. >> So, this brings up the entrepreneurship angle. We got there a little early, but I want to talk about it because it's super important. There's an entrepreneurial culture happening right now in the space community >> There is. At large, and it's getting bigger and wider. >> Bigger every day. >> What is that? What if someone says: "Hey, what's going on with entrepreneurship in this space? What are the key dynamics? What's the power dynamics?" It's not money, there's money out there, but like what's the structural thing happening? >> The key dynamic, I think, is we're seeing that we can unlock things that we could never do before. And one of our goals is: the more space data we can make more accessible to more people around the world. It unlocks things we couldn't do. We're working with space companies who are using space data to track endangered whales off the coast of California. We're working with companies that are using space data to measure thermal and greenhouse emissions for climate change and climate management. We're working with one company, Edgybees, who has a small satellite constellation, and they're using it to build satellite based, augmented reality, to provide it to first responders as they go into a disaster response area. And they get a 3D-view of what they're going into. None of those workloads were possible five years ago. And the cloud and cloud-based technologies are really what opens those kinds of workloads up. >> What kind of higher level services do you see emerging from space cloud? Because you know, obviously you have to have some infrastructure. >> Absolutely. Got to put some stuff into space. That's a supply chain, reliability, also threat. I mean, I can have a satellite attack, another satellite, or I'm just making that up, but I'm sure there's other scenarios that the generals are thinking about. >> So space security and cyberspace security is critical. And as I said, it's built into everything we do in all of our platforms, so you're absolutely right about that, but when we think about the entrepreneurship, you know, what we're seeing is, and I'll give you a good example of why the industry is growing so fast and why cloud. So one company we work with, LeoLabs. So Leo identified the growth in the LEO: Low Earth Orbit segment. 3,000 objects on orbit today, 30,000 tomorrow. Who's going to do the space traffic management for 30,000 objects in space that are all in the same orbital regime? And so LeoLabs built a process to do space traffic management, collision avoidance. They were running it on premises. It took them eight hours to do a single run for a single satellite conjunction. We got them to help understand how to use the cloud. They moved all that to AWS. Now that same run they do in 10 seconds. Eight hours to 10 seconds. Those are the kind of workloads as space proliferates in and we grow, that we just can't execute without cloud and cloud-based technologies. >> It's interesting, you know, the cloud has that same kind of line: move your workloads to the cloud and then refactor. >> Yeah. So space workloads are coming to the cloud. >> They are. >> Just changing the culture. So I have to ask you, I know there's a lot of young people out there looking for careers and interests. I mean, Cal poly is going into the high school now offering classes. >> Yeah So high school, there's so much interest in space and technology. What is the cultural mindset to be successful? Andy Jassy last year, reading and talk about the mindset of the builder and the enterprise CXO: "Get off your butt and start building" There's a space ethos going on. What is the mindset? Would you share your view on it? >> The mindset is innovation and moving fast, right? We, we lived, most of my career, in the time where we had an unlimited amount of money and unlimited amount of time. And so we were really slow and deliberate about how we built things. The future won't wait, whether it's commercial application, or military application, we have to move fast. And so the culture is: the faster we can move, The more we'll succeed, and there's no way to move faster than when you're building on the AWS cloud. Ground station is a good example. You know, the proposition of the cloud is: Don't invest your limited resources in your own infrastructure that doesn't differentiate your capability. And so we did that same thing with ground station. And we've said to companies: "Don't spend millions of dollars on developing your own ground station infrastructure, pay by the minute to use AWS's and focus your limited resources back in your product, which differentiate your space mission." and that's just been power. >> How is that going from customer perspective? >> Great. It's going great. We continue to grow. We added another location recently. And just in the last week we announced a licensed accelerator. One of the things our customers told us is it takes too long to work with global governments to get licensed, to operate around the world. And we know that's been the case. So we put together a team that leaned in to solve that problem, and we just announced the licensed accelerator, where we will work with companies to walk them through that process, and we can shave an 18 month process into a three or four month process. And that's been... we've gotten great response on that from our company. >> I've always said: >> I remember when you were hired and the whole space thing was happening. I remember saying to myself: "Man, if democratization can bring, come to space" >> And we're seeing that happening >> You guys started it and you guys, props to your team. >> Making space available to more and more people, and they'll dazzle us with the innovative ways we use space. 10 years ago, we couldn't have envisioned those things I told you about earlier. Now, we're opening up all sorts of workloads and John, real quick, one of the reasons is, in the past, you had to have a specific forte or expertise in working with space data, 'cause it was so unique and formatted and in pipeline systems. We're making that democratized. So it's just like any other data, like apps on your phone. If you can build apps for your phone and manage data, we want to make it that easy to operate with space data, and that's going to change the way the industry operates. >> And that's fundamentally, that's great innovation because you're enabling that. That's why I have to ask you on that note Of the innovation trends that you see or activities: What excites you the most? >> So a lot of things, but I'll give you two examples very quickly: One is high-performance compute. We're seeing more and more companies really lean in to understanding how fast they can go on AWS. I told you about LeoLabs, eight hours to 10 seconds. But that high-performance computes going to be a game changer. The other thing is: oh, and real quick, I want to tell you, Descartes Labs. So Descartes Labs came to us and said: "We want to compete in the Annual Global Top 500 supercomputer challenge" And so we worked with them for a couple of weeks. We built a workload on the AWS standard platform. We came in number 40 in the globe for the Top 500 super computer lists, just by building some workloads on our standard platform. That's powerful, high-performance compute. But the second example I wanted to give you is: digital modeling, digital simulation, digital engineering. Boom Aerospace is a company, Boom, that we work with. Boom decided to build their entire supersonic commercial, supersonic aircraft, digital engineering on the AWS cloud. In the last three years, John, they've executed 6,000 years of high-performance compute in the last three years. How do you do 6,000 years in compute in three years? You spin up thousands of AWS servers simultaneously, let them do your digital management, digital analysis, digital design, bring back a million different perturbations of a wing structure and then pick the one that's best and then come back tomorrow and run it again. That's powerful. >> And that was not even possible, years ago. >> Not at that speed, no, not at that speed. And that's what it's really opening up in terms of innovation. >> So now you've done it so much in your career, okay? Now you're here with Amazon. Looking back on this past year or so, What's the learnings for you? >> The learning is, truly how valuable cloud can be to the space industry, I'll admit to you most people in the space industry and especially in the government space industry. If you ask us a year ago, two years ago: "Hey, what do you think about cloud?" We would have said: "Well, you know, I hear people talk about the cloud. There's probably some value. We should probably look at that" And I was in the same boat, but now that I've dug deeply into the cloud and understand the value of artificial intelligence, machine learning, advanced data analytics, a ground station infrastructure, all those things, I'm more excited than ever before about what the space industry can benefit from cloud computing, and so bringing that, customer by customer is just a really fulfilling way to continue to be part of the space industry. Even though I retired from government service. >> Is there a... I'm just curious because you brought it up. Is there a lot of people coming in from the old, the space industry from public sector? Are they coming into commercial? >> Absolutely. >> Commercial rising up and there's, I mean, I know there's a lot of public/private partnerships, What's the current situation? >> Yeah, lots of partnerships, but we're seeing an interesting trend. You know, it used to be that NASA led the way in science and technology, or the military led the way in science and technology, and they still do in some areas. And then the commercial industry would follow along. We're seeing that's reversed. There's so much growth in the commercial industry. So much money, venture capital being poured in and so many innovative solutions being built, for instance, on the cloud that now the commercial industry is leading technology and building new technology trends that the military and the DOD and their government are trying to take advantage of. And that's why you're seeing all these commercial contracts being led from Air Force, Space Force, NASA, and NRO. To take advantage of that commercialization. >> You like your job. >> I love my job. (laughing) -I can tell, >> I love my job. >> I mean, it is a cool job. I kind of want to work for you. >> So John, space is cool. That's our tagline: space is cool. >> Space is cool. Space equals ratings in the digital TV realm, it is really, super exciting a lot of young people are interested, I mean, robotics clubs in high schools are now varsity sports, eSports, all blend together. >> Space, robotics, artificial intelligence, machine learning, advanced analytics. It's all becoming a singular sector today and it's open to more people than ever before, for the reasons we talked about. >> Big wave and you guys are building the surf boards, everyone a ride it, congratulations. Great to see you in person. >> Thank you. Again, thanks for coming on theCUBE, appreciate that. >> Thanks for having us. >> Clint Crosier is the Director of AWS Aerospace & Satellite. Legend in the industry. Now at AWS. I'm John Furrier with theCUBE. Thanks for watching.

(upbeat music) >> Live in Washington, DC. This is day two of two days of coverage. I'm John Furr, your host. We're in person face-to-face event it's kicking off day two. Dave Levy's here, Vice President of US government Nonprofit and healthcare businesses for AWS Public Sector. Dave, great to see you again, welcome back. >> Dave: Great to see you, John. >> So, great time last time we were in person, 2019, looks like the event, the last year was virtual, what's new? >> Well, first of all, I think it's just exciting. I mean, I'm excited to be back and in-person and so much has happened in our personal lives in our communities and so I'm really glad that we can all be together and it's been great so far. >> I was talking yesterday with some folks and I saw people doing some networking. I heard someone, "Hey, I'm want to hire someone." So, the face-to-face is back, we're also streaming. Max Peterson told me they're pushing it everywhere on Facebook, LinkedIn, Twitter, everywhere, Twitch, so free content, but still a lot of registrations here in person, good stuff. >> Yeah, great registrations. We're thrilled with the support from partners and customers. And also too, like you said, the connections that people are making, so it does feel good that things are flowing and people are having conversations and- >> Well, you got healthcare, nonprofits, US government, healthcare has been a big focus so far in this show. A lot of action, local governments, governments and healthcare seem to be like pandemic enabled to change. What's the update? What's the highlights so far for you? >> Well, I think the highlights are in those areas that, what we've been able to help our customers with is the ability to respond and that's what Cloud is all about and their ability to react and to respond to things that they don't necessarily know is going to happen and the big thing that none of us knew was going to happen was the pandemic. And so that ability and agility and preparedness to respond has really been great to see from a lot of those customers. >> You know, Max Peterson had the CIO from the Air Force up on stage and she's known for her comments about data and data's our data, the US Air Force and so data's big part of it. They are having a transformation and the how's that project going? What's the update there? What's your impression on that? >> Yeah, well, it was great to see the Air Force on stage and great to see Laura up there and we're really proud to support the DOD and the Air Force. And the Air Force has a lot to be proud of in their transformation journey and what they're doing with Cloud One is pretty substantial and amazing transformation for them. And then they've got 35 applications running on AWS. And so we think their progress is really good and they're thinking the right way in terms of their software factories and other types of projects. >> What's interesting is it's watching like who's adopting, it's like you look at like the pandemic has really opened up the view of the projects, which ones are doing well. And how do I say this politely? The projects that were being blocked or hidden, or the KPIs camouflaging the value were exposed because I mean, once that pulled back the curtain, people realized, "Oh my God, we're stuck," Or "we're inadequate, we are antiquated. We need to change," because now the pressure to deliver shifted to digital. I mean, this literally exposed the good, bad, and the ugly. >> It did and some were more prepared than others. There are great examples. We worked with the SBA to help expand the portal for the payroll protection program to get more lenders access faster. And that was a great project. They were able to respond really quickly and we were able to support them in that. Others, not so much. I think it you're right, it did expose that there's an opportunity. There's an opportunity to accelerate some of the things that they were doing already in terms of digital transformation. >> How about the GovCloud and the federal customers that you have, what's the traction point? How has that going? Is there a new generation here? >> GovCloud has been a great success. GovCloud it's our- >> John: 10-year anniversary. >> It's our 10-year anniversary, so we're thrilled to celebrate that. I can't believe it's 2011. >> EC2 is 15. Is that 315? I guess 15, too is SQS, the original building blocks. >> So, we've got a lot of great success through GovCloud and GovCloud was really something that was born out of what customers wanted, primarily federal customers. But we've also seen over the last few years, real adoption from regulated industry, real adoption from partners that are going into GovCloud that really want to take advantage of the security and compliance that federal customers need and the larger defense industrial base organizations need. So, GovCloud's been a fabulous success and expect I expect a lot of growth going forward. >> Yeah, is there a cultural shift in the federal government now? I can imagine some countries have been exploring this. I did talk briefly about it with Ms. Shannon Kellogg and John Wood, about how, if you're under the age of 40 and you work in the federal government, you got to be like, "Why aren't we doing this?" Like there seems to be like a cultural shift, younger generation coming in and be like, looking at the old way and be like, "Why are we still doing that?" >> Well, I think look bipartisan support for digital transformation, for making sure that we have the competitive edge for generations and generations to come in the US both in business and in defense and national security, I think is an imperative. I mean nobody I've talked to disagrees that we need to do this. And I think that younger workforce coming in behind I'm jealous of the 40-year olds, I wish I was under 40, but none of workforce really sees the obstacles that maybe previous generation saw these emerging technologies are becoming, the basic unit of computer's getting smaller, the cost to do these things is coming way down and I think that younger workforce says, "Why aren't we doing this?" >> Yeah and I think the Air Force projects are interesting too because that shows us not just about the CIA or the DOD that you have, they're leaning into production workloads, and the mission critical workloads too, the DOD is also now continuing to adopt. What else are you guys doing with the DOD? >> Well, we're partnering with GDIT on milCloud and that's going to give DOD mission owners access to a whole suite of AWS services. So, we're really excited about that. And those are available now. We're the only Cloud provider that's making that accessible to them on milCloud. And so this is going to open up the opportunity for them to start doing that mission work that you described. A good example of that are programs like ABMS, Air Force's Advanced Battle Management System. It's part of their effort around JADC2 and a great set of capabilities that they're delivering there. We're happy to have participated. We did some testing and some show intel, if you will at Ramstein Air Force Base and we're really proud to support that effort and we're excited about what the Air Force is doing. >> You know, I've always been impressed with the DOD when the tactical edge concept came out, that was very impressive because they're really using the data properly and I know Amazon has been doing well in this area because you've got things like Outpost, Wavelength, Snowball products. How's that edge piece developing? Do you see that becoming more critical now? >> It's absolutely critical. It's not becoming critical, it is critical and I think if you look at what the DOD and all of their partners are trying to accomplish, it's really moving all of that data around from the very edge in theater, back home to where it needs to be analyzed, doing it fast, doing it secure, being able to deliver on their missions and that's what this is all about. So, we see huge, huge opportunities to really innovate around the edge. >> Yeah, the data equation really is fascinating to me. Just when you think about things like words, highly available versus high availability means something 'cause you're going to want real time, not just on available data, you got to have it real time so the pressure around these projects are high. And so technically, you've got to have low latency on all this stuff. >> That's true, that's true. You've got to either have near real time or real-time availability and in many cases there's high stakes. So, the ability the DOD to pull this off is really, really important and we're a big supporter of that. >> Dave, I want to get your perspective because you've been in the industry, you've seen that the ways, we talked before cameras about the '90s and data centers and stuff. 10 years of GovCloud, look at public sector, just to look at the 10 years, interesting evolution. I mean, you couldn't give Cloud a wait 15 years ago. They weren't moving, glacier speed of adoption, now, massive adoption, uptakes there, the transformations are happening, migrations are huge, healthcare, which is like silo the data, HIPAA compliance lock everything down, everything's opening up. This is causing a lot of change. What's your reaction to that? >> Well, my reaction to that is I think customers are starting to connect what their outcomes are, whether it's a business outcome or a mission outcome or both to what Cloud can actually do. And I think that's freeing them up to make decisions about enabling Cloud in their environment, enabling experimentation, because that's what you want. You don't know what you're going to be faced with. We don't know what the threats are. We don't know if there's going to be another major pandemic. We hope there's not, but we don't know and if you set goals around your outcomes for mission and tie those, Cloud becomes such an enabler for that. And I see customers embracing that. Customers across the spectrum, nonprofit, healthcare providers, everybody, Homeland Security, VA, they're all thinking about, "What are the mission outcomes we're trying to drive?" >> Yeah, what's interesting too on that is that, just to point out is that the applications now aren't as complex to build relatively to the speed. In other words, you can get the time to value. So, the pandemic showed people that if you were in the Cloud and had that agility or optionality to be agile, you could write software 'cause software is the key in this, and not let's do the waterfall, 12-weeks assessment, 10-month rollout. Now people are doing it in 10 days, new applications. >> Sure, sure. Well, I tell customers a lot, "Think about McDonald's during the pandemic and think about customers like that who had to react to a new environment of delivery and your fast food fresh and how quickly companies like that are able to roll out capabilities." And I don't know that federal customers will be able to do it in a week or two weeks, but it's certainly possible. And it certainly will shorten that lead time that they have now in their software development. >> Well, great to see you, Dave. Is there any customers you want to highlight and you want to talk about, get a plug in for? >> Yeah, a lot of great customers here representing today and we're really appreciative also just want to say it was really great to see Max on stage for his first summit and think it was great to see Laura and others as well too. We've got some great customers coming here, The Veteran's affairs is going to be here as well as the Navy presenting on a lot of their capabilities today. So, I'm really excited about that. >> Yeah, a lot of action and education, healthcare, really blooming, really changing and modernizing. Big-wave migration, modernization, all kinds of the big wave. >> Yeah, it is. Yeah, big things coming and some of these systems are ready, so these systems are 40 and 50 years old and we're here to help these customers deliver on the agility and the extensibility of these systems to really serve citizens. >> What's your outlook for next year? What are you seeing next year so happening? How do you see everything unfolding? So you mentioned the pandemic, we're still in it, Delta Virus, who knows what's going to happen next, the world stage is changing, the global economy, space. >> I see customers really leaning in and starting to see the benefits of moving their data to the Cloud, number one, and then also to getting the insights using AI and ML to really drive the insights that they need to make the decisions on that data and I see more and more customers doing that. I did a panel this week, moderated a panel with some great customers around that and getting started is probably the biggest thing that I see and we're going to have more and more customers getting started. >> Yeah, getting into the Cloud. Congratulations to milCloud by the way, too. That was a good call out. All right, thanks for coming, I appreciate it. >> John: Yeah, thanks, Sean. >> Okay, keep coverage here. The Public Sector Summit, live in Washington, D.C. in-person event also hybrid we're streaming out. We're doing remote interviews and Amazon is streaming all the keynotes and key sessions for the digital folks out there. Thanks for watching. (upbeat music)

>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. >>Hey guys, >>great to be here. So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity >>for the job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're >>going to hear from >>Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data >>measure it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it going really well. So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my >>flights. Uh, >>really looking forward >>to it. I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that >>are >>very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle >>where >>we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we >>how do we keep our workforce >>engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of >>help to make it happen >>real good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would >>never want to see someone >>sacrifice quality, >>but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just >>as much >>as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk. Brand new Premier, Okay, uh, lisa martin, Emily Freeman is here. She's ready to come in and we're going to preview her lightning talk Emily. Um, thanks for coming on, we really appreciate you coming on really, this is about to talk around deVOPS next gen and I think lisa this is one of those things we've been, we've been discussing with all the companies. It's a new kind of thinking it's a revolution, it's a systems mindset, you're starting to see the connections there she is. Emily, Thanks for coming. I appreciate it. >>Thank you for having me. So your teaser video >>was amazing. Um, you know, that little secret radical idea, something completely different. Um, you gotta talk coming up, what's the premise behind this revolution, you know, these tying together architecture, development, automation deployment, operating altogether. >>Yes, well, we have traditionally always used the sclc, which is the software delivery life cycle. Um, and it is a straight linear process that has actually been around since the sixties, which is wild to me um, and really originated in manufacturing. Um, and as much as I love the Toyota production system and how much it has shown up in devops as a sort of inspiration on how to run things better. We are not making cars, we are making software and I think we have to use different approaches and create a sort of model that better reflects our modern software development process. >>It's a bold idea and looking forward to the talk and as motivation. I went into my basement and dusted off all my books from college in the 80s and the sea estimates it was waterfall. It was software development life cycle. They trained us to think this way and it came from the mainframe people. It was like, it's old school, like really, really old and it really hasn't been updated. Where's the motivation? I actually cloud is kind of converging everything together. We see that, but you kind of hit on this persona thing. Where did that come from this persona? Because you know, people want to put people in buckets release engineer. I mean, where's that motivation coming from? >>Yes, you're absolutely right that it came from the mainframes. I think, you know, waterfall is necessary when you're using a punch card or mag tape to load things onto a mainframe, but we don't exist in that world anymore. Thank goodness. And um, yes, so we, we use personas all the time in tech, you know, even to register, well not actually to register for this event, but a lot events. A lot of events, you have to click that drop down. Right. Are you a developer? Are you a manager, whatever? And the thing is personas are immutable in my opinion. I was a developer. I will always identify as a developer despite playing a lot of different roles and doing a lot of different jobs. Uh, and this can vary throughout the day. Right. You might have someone who has a title of software architect who ends up helping someone pair program or develop or test or deploy. Um, and so we wear a lot of hats day to day and I think our discussions around roles would be a better, um, certainly a better approach than personas >>lease. And I've been discussing with many of these companies around the roles and we're hearing from them directly and they're finding out that people have, they're mixing and matching on teams. So you're, you're an S R E on one team and you're doing something on another team where the workflows and the workloads defined the team formation. So this is a cultural discussion. >>It absolutely is. Yes. I think it is a cultural discussion and it really comes to the heart of devops, right? It's people process. And then tools deVOps has always been about culture and making sure that developers have all the tools they need to be productive and honestly happy. What good is all of this? If developing software isn't a joyful experience. Well, >>I got to ask you, I got you here obviously with server list and functions just starting to see this kind of this next gen. And we're gonna hear from jerry Chen, who's a Greylock VC who's going to talk about castles in the clouds, where he's discussing the moats that could be created with a competitive advantage in cloud scale. And I think he points to the snowflakes of the world. You're starting to see this new thing happening. This is devops 2.0, this is the revolution. Is this kind of where you see the same vision of your talk? >>Yes, so DeVOps created 2000 and 8, 2000 and nine, totally different ecosystem in the world we were living in, you know, we didn't have things like surveillance and containers, we didn't have this sort of default distributed nature, certainly not the cloud. Uh and so I'm very excited for jerry's talk. I'm curious to hear more about these moz. I think it's fascinating. Um but yeah, you're seeing different companies use different tools and processes to accelerate their delivery and that is the competitive advantage. How can we figure out how to utilize these tools in the most efficient way possible. >>Thank you for coming and giving us a preview. Let's now go to your lightning keynote talk. Fresh content. Premier of this revolution in Devops and the Freemans Talk, we'll go there now. >>Hi, I'm Emily Freeman, I'm the author of devops for dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. I am really excited to share with you a kind of a wild idea, a complete re imagining of the S DLC and I want to be clear, I need your feedback. I want to know what you think of this. You can always find me on twitter at editing. Emily, most of my work centers around deVOps and I really can't overstate what an impact the concept of deVOPS has had on this industry in many ways it built on the foundation of Agile to become a default a standard we all reach for in our everyday work. When devops surfaced as an idea in 2008, the tech industry was in a vastly different space. AWS was an infancy offering only a handful of services. Azure and G C P didn't exist yet. The majority's majority of companies maintained their own infrastructure. Developers wrote code and relied on sys admins to deploy new code at scheduled intervals. Sometimes months apart, container technology hadn't been invented applications adhered to a monolithic architecture, databases were almost exclusively relational and serverless wasn't even a concept. Everything from the application to the engineers was centralized. Our current ecosystem couldn't be more different. Software is still hard, don't get me wrong, but we continue to find novel solutions to consistently difficult, persistent problems. Now, some of these end up being a sort of rebranding of old ideas, but others are a unique and clever take to abstracting complexity or automating toil or perhaps most important, rethinking challenging the very premises we have accepted as Cannon for years, if not decades. In the years since deVOps attempted to answer the critical conflict between developers and operations, engineers, deVOps has become a catch all term and there have been a number of derivative works. Devops has come to mean 5000 different things to 5000 different people. For some, it can be distilled to continuous integration and continuous delivery or C I C D. For others, it's simply deploying code more frequently, perhaps adding a smattering of tests for others. Still, its organizational, they've added a platform team, perhaps even a questionably named DEVOPS team or have created an engineering structure that focuses on a separation of concerns. Leaving feature teams to manage the development, deployment, security and maintenance of their siloed services, say, whatever the interpretation, what's important is that there isn't a universally accepted standard. Well, what deVOPS is or what it looks like an execution, it's a philosophy more than anything else. A framework people can utilize to configure and customize their specific circumstances to modern development practices. The characteristic of deVOPS that I think we can all agree on though, is that an attempted to capture the challenges of the entire software development process. It's that broad umbrella, that holistic view that I think we need to breathe life into again, The challenge we face is that DeVOps isn't increasingly outmoded solution to a previous problem developers now face. Cultural and technical challenge is far greater than how to more quickly deploy a monolithic application. Cloud native is the future the next collection of default development decisions and one the deVOPS story can't absorb in its current form. I believe the era of deVOPS is waning and in this moment as the sun sets on deVOPS, we have a unique opportunity to rethink rebuild free platform. Even now, I don't have a crystal ball. That would be very handy. I'm not completely certain with the next decade of tech looks like and I can't write this story alone. I need you but I have some ideas that can get the conversation started, I believe to build on what was we have to throw away assumptions that we've taken for granted all this time in order to move forward. We must first step back. Mhm. The software or systems development life cycle, what we call the S. D. L. C. has been in use since the 1960s and it's remained more or less the same since before color television and the touch tone phone. Over the last 60 or so odd years we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different with agile and deVOps we sort of looped it into a circle and then an infinity loop we've added pretty colors. But the sclc is more or less the same and it has become an assumption. We don't even think about it anymore, universally adopted constructs like the sclc have an unspoken permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent. If you were born after a construct was popularized. Nearly everything around us is a construct, a model, an artifact of a human idea. The chair you're sitting in the desk, you work at the mug from which you drink coffee or sometimes wine, buildings, toilets, plumbing, roads, cars, art, computers, everything. The sclc is a remnant an artifact of a previous era and I think we should throw it away or perhaps more accurately replace it, replace it with something that better reflects the actual nature of our work. A linear, single threaded model designed for the manufacturer of material goods cannot possibly capture the distributed complexity of modern socio technical systems. It just can't. Mhm. And these two ideas aren't mutually exclusive that the sclc was industry changing, valuable and extraordinarily impactful and that it's time for something new. I believe we are strong enough to hold these two ideas at the same time, showing respect for the past while envisioning the future. Now, I don't know about you, I've never had a software project goes smoothly in one go. No matter how small. Even if I'm the only person working on it and committing directly to master software development is chaos. It's a study and entropy and it is not getting any more simple. The model with which we think and talk about software development must capture the multithreaded, non sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations of agile and devops and represent the iterative nature of continuous innovation. Now, when I was thinking about this, I was inspired by ideas like extreme programming and the spiral model. I I wanted something that would have layers, threads, even a way of visually representing multiple processes happening in parallel. And what I settled on is the revolution model. I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario. And I'm going to dive into all the discrete elements. But I want to give you a moment to have a first impression, to absorb my idea. I call it revolution because well for one it revolves, it's circular shape reflects the continuous and iterative nature of our work, but also because it is revolutionary. I am challenging a 60 year old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow, but that would be super cool. And you should call me my mission with. This is to challenge the status quo to create a model that I think more accurately reflects the complexity of modern cloud native software development. The revolution model is constructed of five concentric circles describing the critical roles of software development architect. Ng development, automating, deploying and operating intersecting each loop are six spokes that describe the production considerations every engineer has to consider throughout any engineering work and that's test, ability, secure ability, reliability, observe ability, flexibility and scalability. The considerations listed are not all encompassing. There are of course things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model. We have long used personas as the default way to do divide audiences and tailor messages to group people. Every company in the world right now is repeating the mantra of developers, developers, developers but personas have always bugged me a bit because this approach typically either oversimplifies someone's career are needlessly complicated. Few people fit cleanly and completely into persona based buckets like developers and operations anymore. The lines have gotten fuzzy on the other hand, I don't think we need to specifically tailor messages as to call out the difference between a devops engineer and a release engineer or a security administrator versus a security engineer but perhaps most critically, I believe personas are immutable. A persona is wholly dependent on how someone identifies themselves. It's intrinsic not extrinsic. Their titles may change their jobs may differ, but they're probably still selecting the same persona on that ubiquitous drop down. We all have to choose from when registering for an event. Probably this one too. I I was a developer and I will always identify as a developer despite doing a ton of work in areas like devops and Ai Ops and Deverell in my heart. I'm a developer I think about problems from that perspective. First it influences my thinking and my approach roles are very different. Roles are temporary, inconsistent, constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied, but the persona I would identify as would remain an actress and artist lesbian. Your work isn't confined to a single set of skills. It may have been a decade ago, but it is not today in any given week or sprint, you may play the role of an architect. Thinking about how to design a feature or service, developer building out code or fixing a bug and on automation engineer, looking at how to improve manual processes. We often refer to as soil release engineer, deploying code to different environments or releasing it to customers or in operations. Engineer ensuring an application functions inconsistent expected ways and no matter what role we play. We have to consider a number of issues. The first is test ability. All software systems require testing to assure architects that designs work developers, the code works operators, that infrastructure is running as expected and engineers of all disciplines that code changes won't bring down the whole system testing in its many forms is what enables systems to be durable and have longevity. It's what reassures engineers that changes won't impact current functionality. A system without tests is a disaster waiting to happen, which is why test ability is first among equals at this particular roundtable. Security is everyone's responsibility. But if you understand how to design and execute secure systems, I struggle with this security incidents for the most part are high impact, low probability events. The really big disasters, the one that the ones that end up on the news and get us all free credit reporting for a year. They don't happen super frequently and then goodness because you know that there are endless small vulnerabilities lurking in our systems. Security is something we all know we should dedicate time to but often don't make time for. And let's be honest, it's hard and complicated and a little scary def sec apps. The first derivative of deVOPS asked engineers to move security left this approach. Mint security was a consideration early in the process, not something that would block release at the last moment. This is also the consideration under which I'm putting compliance and governance well not perfectly aligned. I figure all the things you have to call lawyers for should just live together. I'm kidding. But in all seriousness, these three concepts are really about risk management, identity, data, authorization. It doesn't really matter what specific issue you're speaking about, the question is who has access to what win and how and that is everyone's responsibility at every stage site reliability engineering or sorry, is a discipline job and approach for good reason. It is absolutely critical that applications and services work as expected. Most of the time. That said, availability is often mistakenly treated as a synonym for reliability. Instead, it's a single aspect of the concept if a system is available but customer data is inaccurate or out of sync. The system is not reliable, reliability has five key components, availability, latency, throughput. Fidelity and durability, reliability is the end result. But resiliency for me is the journey the action engineers can take to improve reliability, observe ability is the ability to have insight into an application or system. It's the combination of telemetry and monitoring and alerting available to engineers and leadership. There's an aspect of observe ability that overlaps with reliability, but the purpose of observe ability isn't just to maintain a reliable system though, that is of course important. It is the capacity for engineers working on a system to have visibility into the inner workings of that system. The concept of observe ability actually originates and linear dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs. If it is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared responsibility model of cloud storage compute and managed services require that engineering teams be able to quickly be alerted to identify and remediate issues as they arise. Flexible systems are capable of adapting to meet the ever changing needs of the customer and the market segment, flexible code bases absorb new code smoothly. Embody a clean separation of concerns. Are partitioned into small components or classes and architected to enable the now as well as the next inflexible systems. Change dependencies are reduced or eliminated. Database schemas accommodate change well components, communicate via a standardized and well documented A. P. I. The only thing constant in our industry is change and every role we play, creating flexibility and solutions that can be flexible that will grow as the applications grow is absolutely critical. Finally, scalability scalability refers to more than a system's ability to scale for additional load. It implies growth scalability and the revolution model carries the continuous innovation of a team and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles to consider everyone around us, our customers who use the system or rely on its services, our colleagues current and future with whom we collaborate and even our future selves. Mhm. Software development isn't a straight line, nor is it a perfect loop. It is an ever changing complex dance. There are twirls and pivots and difficult spins forward and backward. Engineers move in parallel, creating truly magnificent pieces of art. We need a modern model for this modern era and I believe this is just the revolution to get us started. Thank you so much for having me. >>Hey, we're back here. Live in the keynote studio. I'm john for your host here with lisa martin. David lot is getting ready for the fireside chat ending keynote with the practitioner. Hello! Fresh without data mesh lisa Emily is amazing. The funky artwork there. She's amazing with the talk. I was mesmerized. It was impressive. >>The revolution of devops and the creative element was a really nice surprise there. But I love what she's doing. She's challenging the status quo. If we've learned nothing in the last year and a half, We need to challenge the status quo. A model from the 1960s that is no longer linear. What she's doing is revolutionary. >>And we hear this all the time. All the cube interviews we do is that you're seeing the leaders, the SVP's of engineering or these departments where there's new new people coming in that are engineering or developers, they're playing multiple roles. It's almost a multidisciplinary aspect where you know, it's like going into in and out burger in the fryer later and then you're doing the grill, you're doing the cashier, people are changing roles or an architect, their test release all in one no longer departmental, slow siloed groups. >>She brought up a great point about persona is that we no longer fit into these buckets. That the changing roles. It's really the driver of how we should be looking at this. >>I think I'm really impressed, really bold idea, no brainer as far as I'm concerned, I think one of the things and then the comments were off the charts in a lot of young people come from discord servers. We had a good traction over there but they're all like learning. Then you have the experience, people saying this is definitely has happened and happening. The dominoes are falling and they're falling in the direction of modernization. That's the key trend speed. >>Absolutely with speed. But the way that Emily is presenting it is not in a brash bold, but it's in a way that makes great sense. The way that she creatively visually lined out what she was talking about Is amenable to the folks that have been doing this for since the 60s and the new folks now to really look at this from a different >>lens and I think she's a great setup on that lightning top of the 15 companies we got because you think about sis dig harness. I white sourced flamingo hacker one send out, I oh, okay. Thought spot rock set Sarah Ops ramp and Ops Monte cloud apps, sani all are doing modern stuff and we talked to them and they're all on this new wave, this monster wave coming. What's your observation when you talk to these companies? >>They are, it was great. I got to talk with eight of the 15 and the amount of acceleration of innovation that they've done in the last 18 months is phenomenal obviously with the power and the fuel and the brand reputation of aws but really what they're all facilitating cultural shift when we think of devoPS and the security folks. Um, there's a lot of work going on with ai to an automation to really kind of enabled to develop the develops folks to be in control of the process and not have to be security experts but ensuring that the security is baked in shifting >>left. We saw that the chat room was really active on the security side and one of the things I noticed was not just shift left but the other groups, the security groups and the theme of cultural, I won't say war but collision cultural shift that's happening between the groups is interesting because you have this new devops persona has been around Emily put it out for a while. But now it's going to the next level. There's new revolutions about a mindset, a systems mindset. It's a thinking and you start to see the new young companies coming out being funded by the gray locks of the world who are now like not going to be given the we lost the top three clouds one, everything. there's new business models and new technical architecture in the cloud and that's gonna be jerry Chen talk coming up next is going to be castles in the clouds because jerry chant always talked about moats, competitive advantage and how moats are key to success to guard the castle. And then we always joke, there's no more moz because the cloud has killed all the boats. But now the motor in the cloud, the castles are in the cloud, not on the ground. So very interesting thought provoking. But he's got data and if you look at the successful companies like the snowflakes of the world, you're starting to see these new formations of this new layer of innovation where companies are growing rapidly, 98 unicorns now in the cloud. Unbelievable, >>wow, that's a lot. One of the things you mentioned, there's competitive advantage and these startups are all fueled by that they know that there are other companies in the rear view mirror right behind them. If they're not able to work as quickly and as flexibly as a competitor, they have to have that speed that time to market that time to value. It was absolutely critical. And that's one of the things I think thematically that I saw along the eighth sort of that I talked to is that time to value is absolutely table stakes. >>Well, I'm looking forward to talking to jerry chan because we've talked on the queue before about this whole idea of What happens when winner takes most would mean the top 3, 4 cloud players. What happens? And we were talking about that and saying, if you have a model where an ecosystem can develop, what does that look like and back in 2013, 2014, 2015, no one really had an answer. Jerry was the only BC. He really nailed it with this castles in the cloud. He nailed the idea that this is going to happen. And so I think, you know, we'll look back at the tape or the videos from the cube, we'll find those cuts. But we were talking about this then we were pontificating and riffing on the fact that there's going to be new winners and they're gonna look different as Andy Jassy always says in the cube you have to be misunderstood if you're really going to make something happen. Most of the most successful companies are misunderstood. Not anymore. The cloud scales there. And that's what's exciting about all this. >>It is exciting that the scale is there, the appetite is there the appetite to challenge the status quo, which is right now in this economic and dynamic market that we're living in is there's nothing better. >>One of the things that's come up and and that's just real quick before we bring jerry in is automation has been insecurity, absolutely security's been in every conversation, but automation is now so hot in the sense of it's real and it's becoming part of all the design decisions. How can we automate can we automate faster where the keys to automation? Is that having the right data, What data is available? So I think the idea of automation and Ai are driving all the change and that's to me is what these new companies represent this modern error where AI is built into the outcome and the apps and all that infrastructure. So it's super exciting. Um, let's check in, we got jerry Chen line at least a great. We're gonna come back after jerry and then kick off the day. Let's bring in jerry Chen from Greylock is he here? Let's bring him in there. He is. >>Hey john good to see you. >>Hey, congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. >>All right, Well thanks for reading it. Um, always were being put a piece of workout out either. Not sure what the responses, but it seemed to resonate with a bunch of developers, founders, investors and folks like yourself. So smart people seem to gravitate to us. So thank you very much. >>Well, one of the benefits of doing the Cube for 11 years, Jerry's we have videotape of many, many people talking about what the future will hold. You kind of are on this early, it wasn't called castles in the cloud, but you were all I was, we had many conversations were kind of connecting the dots in real time. But you've been on this for a while. It's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles in the cloud? New research to come out from Greylock that you spearheaded? It's collaborative effort, but you've got data behind it. Give a quick overview of what is castle the cloud, the new modes of competitive advantage for companies. >>Yeah, it's as a group project that our team put together but basically john the question is, how do you win in the cloud? Remember the conversation we had eight years ago when amazon re event was holy cow, Like can you compete with them? Like is it a winner? Take all? Winner take most And if it is winner take most, where are the white spaces for Some starts to to emerge and clearly the past eight years in the cloud this journey, we've seen big companies, data breaks, snowflakes, elastic Mongo data robot. And so um they spotted the question is, you know, why are the castles in the cloud? The big three cloud providers, Amazon google and Azure winning. You know, what advantage do they have? And then given their modes of scale network effects, how can you as a startup win? And so look, there are 500 plus services between all three cloud vendors, but there are like 500 plus um startups competing gets a cloud vendors and there's like almost 100 unicorn of private companies competing successfully against the cloud vendors, including public companies. So like Alaska, Mongo Snowflake. No data breaks. Not public yet. Hashtag or not public yet. These are some examples of the names that I think are winning and watch this space because you see more of these guys storm the castle if you will. >>Yeah. And you know one of the things that's a funny metaphor because it has many different implications. One, as we talk about security, the perimeter of the gates, the moats being on land. But now you're in the cloud, you have also different security paradigm. You have a different um, new kinds of services that are coming on board faster than ever before. Not just from the cloud players but From companies contributing into the ecosystem. So the combination of the big three making the market the main markets you, I think you call 31 markets that we know of that probably maybe more. And then you have this notion of a sub market, which means that there's like we used to call it white space back in the day, remember how many whites? Where's the white space? I mean if you're in the cloud, there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. >>Sure. So first, the first problem was what we did. We downloaded all the services for the big three clowns. Right? And you know what as recalls a database or database service like a document DB and amazon is like Cosmo dB and Azure. So first thing first is we had to like look at all three cloud providers and you? Re categorize all the services almost 500 Apples, Apples, Apples # one number two is you look at all these markets or sub markets and said, okay, how can we cluster these services into things that you know you and I can rock right. That's what amazon Azure and google think about. It is very different and the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like oracle is a single database for all your needs. They're like 20 or 30 different databases from time series um analytics, databases. We're talking rocks at later today. Right. Um uh, document databases like Mongo search database like elastic. And so what happens is there's not one giant market like databases, there's a database market And 30, 40 sub markets that serve the needs developers. So the Great News is cloud has reduced the cost and create something that new for developers. Um also the good news is for a start up you can find plenty of white speeds solving a pain point, very specific to a different type of problem >>and you can sequence up to power law to this. I love the power of a metaphor, you know, used to be a very thin neck note no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services, but also there's big tam's and markets available at the top of the power law where you see coming like snowflake essentially take on the data warehousing market by basically sitting on amazon re factoring with new services and then getting a flywheel completely changing the economic unit economics completely changing the consumption model completely changing the value proposition >>literally you >>get Snowflake has created like a storm, create a hole, that mode or that castle wall against red shift. Then companies like rock set do your real time analytics is Russian right behind snowflakes saying, hey snowflake is great for data warehouse but it's not fast enough for real time analytics. Let me give you something new to your, to your parallel argument. Even the big optic snowflake have created kind of a wake behind them that created even more white space for Gaza rock set. So that's exciting for guys like me and >>you. And then also as we were talking about our last episode two or quarter two of our showcase. Um, from a VC came on, it's like the old shelf where you didn't know if a company's successful until they had to return the inventory now with cloud you if you're not successful, you know it right away. It's like there's no debate. Like, I mean you're either winning or not. This is like that's so instrumented so a company can have a good better mousetrap and win and fill the white space and then move up. >>It goes both ways. The cloud vendor, the big three amazon google and Azure for sure. They instrument their own class. They know john which ecosystem partners doing well in which ecosystems doing poorly and they hear from the customers exactly what they want. So it goes both ways they can weaponize that. And just as well as you started to weaponize that info >>and that's the big argument of do that snowflake still pays the amazon bills. They're still there. So again, repatriation comes back, That's a big conversation that's come up. What's your quick take on that? Because if you're gonna have a castle in the cloud, then you're gonna bring it back to land. I mean, what's that dynamic? Where do you see that compete? Because on one hand is innovation. The other ones maybe cost efficiency. Is that a growth indicator slow down? What's your view on the movement from and to the cloud? >>I think there's probably three forces you're finding here. One is the cost advantage in the scale advantage of cloud so that I think has been going for the past eight years, there's a repatriation movement for a certain subset of customers, I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessary against cloud, but you're gonna see more decentralized clouds and things pushed to the edge. Right? So you look at companies like Cloudflare Fastly or a company that we're investing in Cato networks. All ideas focus on secure access at the edge. And so I think that's not the repatriation of my own data center, which is kind of a disaggregated of cloud from one giant monolithic cloud, like AWS east or like a google region in europe to multiple smaller clouds for governance purposes, security purposes or legacy purposes. >>So I'm looking at my notes here, looking down on the screen here for this to read this because it's uh to cut and paste from your thesis on the cloud. The excellent cloud. The of the $38 billion invested this quarter. Um Ai and ml number one, um analytics. Number two, security number three. Actually, security number one. But you can see the bubbles here. So all those are data problems I need to ask you. I see data is hot data as intellectual property. How do you look at that? Because we've been reporting on this and we just started the cube conversation around workflows as intellectual property. If you have scale and your motives in the cloud. You could argue that data and the workflows around those data streams is intellectual property. It's a protocol >>I believe both are. And they just kind of go hand in hand like peanut butter and jelly. Right? So data for sure. I. P. So if you know people talk about days in the oil, the new resource. That's largely true because of powers a bunch. But the workflow to your point john is sticky because every company is a unique snowflake right? Like the process used to run the cube and your business different how we run our business. So if you can build a workflow that leverages the data, that's super sticky. So in terms of switching costs, if my work is very bespoke to your business, then I think that's competitive advantage. >>Well certainly your workflow is a lot different than the cube. You guys just a lot of billions of dollars in capital. We're talking to all the people out here jerry. Great to have you on final thought on your thesis. Where does it go from here? What's been the reaction? Uh No, you put it out there. Great love the restart. Think you're on point on this one. Where did we go from here? >>We have to follow pieces um in the near term one around, you know, deep diver on open source. So look out for that pretty soon and how that's been a powerful strategy a second. Is this kind of just aggregation of the cloud be a Blockchain and you know, decentralized apps, be edge applications. So that's in the near term two more pieces of, of deep dive we're doing. And then the goal here is to update this on a quarterly and annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us or he screwed up here. We got the big cloud vendors saying, Hey jerry, we just lost his new things. So our goal here is to update this every single year and then probably do look back saying, okay, uh, where were we wrong? We're right. And then let's say the castle clouds 2022. We'll see the difference were the more unicorns were there more services were the IPO's happening. So look for some short term work from us on analytics, like around open source and clouds. And then next year we hope that all of this forward saying, Hey, you have two year, what's happening? What's changing? >>Great stuff and, and congratulations on the southern news. You guys put another half a billion dollars into early, early stage, which is your roots. Are you still doing a lot of great investments in a lot of unicorns. Congratulations that. Great luck on the team. Thanks for coming on and congratulations you nailed this one. I think I'm gonna look back and say that this is a pretty seminal piece of work here. Thanks for sharing. >>Thanks john thanks for having us. >>Okay. Okay. This is the cube here and 81 startup showcase. We're about to get going in on all the hot companies closing out the kino lisa uh, see jerry Chen cube alumni. He was right from day one. We've been riffing on this, but he nails it here. I think Greylock is lucky to have him as a general partner. He's done great deals, but I think he's hitting the next wave big. This is, this is huge. >>I was listening to you guys talking thinking if if you had a crystal ball back in 2013, some of the things Jerry saying now his narrative now, what did he have a crystal >>ball? He did. I mean he could be a cuBA host and I could be a venture capital. We were both right. I think so. We could have been, you know, doing that together now and all serious now. He was right. I mean, we talked off camera about who's the next amazon who's going to challenge amazon and Andy Jassy was quoted many times in the queue by saying, you know, he was surprised that it took so long for people to figure out what they were doing. Okay, jerry was that VM where he had visibility into the cloud. He saw amazon right away like we did like this is a winning formula and so he was really out front on this one. >>Well in the investments that they're making in these unicorns is exciting. They have this, this lens that they're able to see the opportunities there almost before anybody else can. And finding more white space where we didn't even know there was any. >>Yeah. And what's interesting about the report I'm gonna dig into and I want to get to him while he's on camera because it's a great report, but He says it's like 500 services I think Amazon has 5000. So how you define services as an interesting thing and a lot of amazon services that they have as your doesn't have and vice versa, they do call that out. So I find the report interesting. It's gonna be a feature game in the future between clouds the big three. They're gonna say we do this, you're starting to see the formation, Google's much more developer oriented. Amazon is much more stronger in the governance area with data obviously as he pointed out, they have such experience Microsoft, not so much their developer cloud and more office, not so much on the government's side. So that that's an indicator of my, my opinion of kind of where they rank. So including the number one is still amazon web services as your long second place, way behind google, right behind Azure. So we'll see how the horses come in, >>right. And it's also kind of speaks to the hybrid world in which we're living the hybrid multi cloud world in which many companies are living as companies to not just survive in the last year and a half, but to thrive and really have to become data companies and leverage that data as a competitive advantage to be able to unlock the value of it. And a lot of these startups that we talked to in the showcase are talking about how they're helping organizations unlock that data value. As jerry said, it is the new oil, it's the new gold. Not unless you can unlock that value faster than your competition. >>Yeah, well, I'm just super excited. We got a great day ahead of us with with all the cots startups. And then at the end day, Volonte is gonna interview, hello, fresh practitioners, We're gonna close it out every episode now, we're going to do with the closing practitioner. We try to get jpmorgan chase data measures. The hottest area right now in the enterprise data is new competitive advantage. We know that data workflows are now intellectual property. You're starting to see data really factoring into these applications now as a key aspect of the competitive advantage and the value creation. So companies that are smart are investing heavily in that and the ones that are kind of slow on the uptake are lagging the market and just trying to figure it out. So you start to see that transition and you're starting to see people fall away now from the fact that they're not gonna make it right, You're starting to, you know, you can look at look at any happens saying how much ai is really in there. Real ai what's their data strategy and you almost squint through that and go, okay, that's gonna be losing application. >>Well the winners are making it a board level conversation >>And security isn't built in. Great to have you on this morning kicking it off. Thanks John Okay, we're going to go into the next set of the program at 10:00 we're going to move into the breakouts. Check out the companies is three tracks in there. We have an awesome track on devops pure devops. We've got the data and analytics and we got the cloud management and just to run down real quick check out the sis dig harness. Io system is doing great, securing devops harness. IO modern software delivery platform, White Source. They're preventing and remediating the rest of the internet for them for the company's that's a really interesting and lumbago, effortless acres land and monitoring functions, server list super hot. And of course hacker one is always great doing a lot of great missions and and bounties you see those success continue to send i O there in Palo alto changing the game on data engineering and data pipe lining. Okay. Data driven another new platform, horizontally scalable and of course thought spot ai driven kind of a search paradigm and of course rock set jerry Chen's companies here and press are all doing great in the analytics and then the cloud management cost side 80 operations day to operate. Ops ramps and ops multi cloud are all there and sunny, all all going to present. So check them out. This is the Cubes Adria's startup showcase episode three.

>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. Hey >>guys, great to be here. >>So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity for the >>job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're going to hear from Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data measure >>it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it >>going really well. >>So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my flights. Uh, really looking forward to it. >>I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that are very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle where we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we how do we keep our workforce engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of help to make it happen real >>good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would never want to see someone sacrifice quality, but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just as much as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk.