>> Narrator: theCUBE presents Ignite 22. Brought to you by Palo Alto Networks. >> Hey, welcome back to Las Vegas. Lisa Martin here with Dave Vellante. This is day two of theCUBE's coverage of Palo Alto Ignite 2022. Dave we're just talking about how many times we're in Vegas. And we were here two weeks ago with our guest who's back in Alumni. And it's a blur, right? >> It's true, I lost count. Luckily I'm not flying red eye tonight. So that's good. >> I'm impressed. >> Excited about that. >> Yeah >> I'm actually going to enjoy the, nightlife here for a period of time. And, you know, we were at re-Invent. >> Yeah. >> And what a difference. This is nice and relaxed. You have time. You're not getting bumped in the hallway. >> Right. >> A lot of time for learning. So it's been great show. >> It's been great. And one of the things that we've been talking about is the supply chain. Securing the modern software supply chain is really complicated. We've got an Alumni back with us, to talk about what Palo Alto is doing in that respect. Ankur Shah joins us. The SVP and GM of Cloud Security at Palo Alto Networks. Welcome back. >> Yeah, happy to be back. Good to see you again. Dave and Lisa. >> It's been two long weeks. >> Ankur: I know. It's been two weeks, yeah >> Dave: It's kind of crazy. I mean, ReInvent really was a blur. And it's like you had everything coming at you. And there was obviously a big chunk of security, but you. It was just so much to absorb. >> Yeah. >> Right? >> Yeah, and I couldn't get into any of the sessions versus at Ignite. I mean, you could, you could learn a lot. To your point Dave. And 70,000 people versus 3000 in change. Big difference. >> Dave: Yeah. >> Lisa: Huge difference. >> Yeah. >> Lisa: Huge difference. So we touched on the Cider acquisition. >> Ankur: Yeah. >> Which was announced the intent to acquire last month. Let's dig into a little bit more of that, and then some of the great things that had been announced. >> Ankur: Yeah. >> In the last couple of days. >> Oh, absolutely. So, this is something that we have been marinating for last nine months. Thinking about how best to secure supply chain. And this is software supply chain. The modern application software is fairly complex. You know, back in the days when I was a developer, it was a simple three tier application. Ship the code once a year, et cetera. But now with microservices, new architectures, Kubernetes Public Cloud, we talked about this. It's getting super complicated, and the customers are really worried about securing their entire supply chain. Which is nothing but the software pipeline. And so we started looking at a whole bunch of companies and Cider really stood out. I mean, they had, they were the innovators in this space. Very early days, we've seen supply chain attack. But there hasn't been a really good and strong solution in that space. And Cider just delivered that incredible team. Great technology, super excited about what that integration will look like. in the coming quarters. >> What do we need to know about them? I mean, I'll be honest with you, I wasn't familiar with Cider until I saw you guys made the announcement of the intent to acquire them. What, what should we know about them? Why Cider? What was it that attracted you to them? >> Ankur: Yeah, so, you know, we have a history of technology acquisitions as you know, over the last four years, just in the public cloud. We acquire over half a a dozen companies, small and large. And typically we are always looking for companies who have the next gen technology available. Technology that is more in tune with how application software is going to look like in future. So we're not always going after companies that are making you know, tens of hundreds of millions of dollars in a year and all. We're looking for the right tech. The future. And that's what we found in Cider. Like they have a really strong application security background. And AppSec just broadly speaking, supply chain is part of it. But application security, just broadly speaking, is right for disruption. You've got a lot of vendors, who have been around for like last two decades. Old school stuff, lots and lots of false positives. So we've been bolstering, beefing up our portfolio in the application security space. And Cider really fits right nicely into it. Because it can like I said, secure a lot of technology and tooling, that software developers use as part of their software supply chain. So, great founding team, great technology. It was a perfect fit. >> Talk about integration. We spoke with Nikesh yesterday, with Nir, with a whole bunch of folks. Lee this morning. BJ yesterday as well. And one of the things that seems to stick out at me. With all the shows that we do, is the focus that Palo Alto has on ensuring that it's making the right acquisitions. But that it's the integration, is really seems to be like leading part of the strategy. That seems to be a little bit of a differentiator to me. >> Yeah, it absolutely is. There are two ways to integrate a technology into an existing platform. And Prisma Cloud is a platform as you know. Code-to-cloud, CNAPP platform as we call it. One is just kind of slotted in, put the whole thing in a box. And that's basically making one plus one equal to two. We're looking for high leverage in integrations, whereby once that integration comes along. It makes the rest of the platform even better and superior. It makes that technology look even better. So that's why there's a lot of focus on ensuring that we're delivering the right type of integration, that delivers instant customer value. And that makes the overall platform even superior. So customers don't feel like hey, like there's just one more add-on, on top of the other thing. >> Lisa: Right, not a bolt on. >> So that's why there's a lot of focus on that. Getting the strategy nailed. Because the founding teams generally have a preconceived notion about how the world looks like. Then they understand how Prisma cloud and Palo Alto Networks think about it. And then, we sort of merge the two ideas, and build something that's incredible. So I am, we're spending a lot of time in integration. That honeymoon phase of like, let's high five acquisitions done, that's over. Now it's the grinding work of actually getting this right. And you know, getting hundreds and thousands of customers. >> Well I like how you don't have the private equity mentality. It's not about EBITDA and cashflow. We'll take care of that. >> Ankur: Yeah. >> You know, it's about getting that integration. Getting that flywheel effect, inside the platform. You know, we said one plus one equals, maybe even more than two. Can you explain Prisma Cloud Secrets Security? What is that all about? What do we need to know about that? >> Ankur: Absolutely. So, the developers, you know generally store some stuff in the code repo for their automation work to build application. And that thing, the API keys or as Secrets are stored in code repo. It shouldn't be. Or even if they are, they should be encrypted, or locked down and things of that nature. But, you know, the need for speed trumps everything else. Developers want to go fast. And sometimes they're like, okay well. I guess my application needs this particular, you know API access token or secret. I'm just going to stick it in the code. Now the challenge with that is that, if somebody gets hold of your code repo. Now not only is your code repo, which has all your sensitive data. Your code is the life and blood of a technology company. That's in trouble. But also those secrets and API access keys can be used to log into your cloud accounts. And there you may have sensitive customer data. Everything that you have as a technology company stored in that public cloud accounts. So that's the worry. It's usually the initial access for the kill chain. Because that's where the attacks start. Let me get the secret, let me get the API access key. And let me see what I can do in public cloud. So we are now giving customers the visibility into where the secrets are stored. More importantly, it just right there on developer's face. In the code repo as they're checking in the code. They say why, hey, there's a secret here. Are you sure you want to, you want to keep it like this, no? Okay, well then you can either encrypt it, or just get rid of it. So we're making, we're bringing security where the developers are in their code repo, et cetera. >> So I can see a lot of developers saying, yeah, go ahead, encrypt it. So I don't have to do anything else, you know, extra. It's almost, the analogy is a very small you know, version of this. Its like, use a password manager. You store all your passwords in your contacts on your phone, right? I mean, somebody gets a hold of your contacts, you're screwed. >> Ankur: That's exactly right. >> And so, but I could still see a lot of developers say, check in the box. Say, yeah just encrypt it, leave it there. But you're saying best practice is to not to do that, right? >> Yeah, usually you're not supposed to, you know, store all your secrets, et cetera in code repo to begin with. But if you do, you know, you use a key wall like technology to really encrypt it and store it in a secret manner, yeah. >> Dave: There's an old saying, bad user behavior trump's great security every time. >> Ankur: Every time. >> But this is an example where, we know you're going to have bad behavior. So we're going to protect the bad behavior. >> Yeah, and actually, sorry Lisa, just to that point. The bad user behavior trumps good security. The classic example, this happened three weeks ago. Three, four weeks ago, where Dropbox, one of the file sharing companies there. 120 plus code repos were exposed. And the way their attack started, was a simple social engineering attack. Bad user behavior. There was an email, hey, like your passwords are updated for your, you know, this code plugin. Can you enter the password? And boom, now you have access to the code repo. And now if you have secrets inside of it, now, you know all bets are off. >> Are there hard-coded secrets versus like, I mean, like I think like, like you were saying, Dave. Like usernames and passwords and tokens, versus like soft coded secrets. >> Ankur: It's, I think it, this is more so two forms of it, you know. The most primary one is what we call the API access keys. And this keys are used to access cloud accounts, workloads and things of that nature. But there are actually secret secrets. Could be database login passwords, et cetera. The application is using it to spin up databases. Now, you know, you have access to the data stores. Any other application, there's a login password, all of that stuff. So it's less about the user password, but more the application and databases and things of that nature. >> Dave: So again, and, again, everybody should be using password managers. But when you use a password manager, it's going to give you a long list of passwords, that are either been compromised or are weak. And you just go uh, okay. So can you help? How do you help customers identify what the high risk? You know, API, you know, access are versus those ones that they may not have to worry about. >> Ankur: Yeah, look. You know, secrets aside. Risk prioritization is one of the biggest topics that our customers have across the board, in cloud security. All the security vendors are really, really good at one thing, generating alerts. Everybody does it. They generate an alert. You know, your ring camera, if you've got one. I mean this pop up every day, like every minute rather. Well like can you prioritize it for me? What should I really look at it? So that's a number one thing. What Prisma Cloud does is, you know, contextualize it. What the real risk is? They can tell you like, hey, here's the kill chain. If this thing, you know, goes to public internet. These are the potential exposures that you have. So we provide a prioritized risk of critical alerts that customers have to take care of before they can start taking care of more hygiene type of stuff, right? So that's how we do it. Like we leverage a lot of technology. We apply a lot of context. We tell you like, hey, this code repo is not protected by multifactor authentication. And then there's a secret inside. Are you sure, you know, you don't want to fix it? So that's what we do. But it's a great question. Top of mind for all our customers. And that's how we think about it across the board. Versus generating just alerts all the time. >> Dave: Is the strategy, Because we all know phishing is the sort of most, you know obvious way to. It's the top way in which people get hacked. >> Ankur: Yeah. >> Is your strategy essentially to say. Okay we know that's going to happen, so we're going to try to protect it at the back end. How much of the, maybe it's an industry question. more so than just a Palo Alto specifically, How much emphasis is do you think the industry is taking or should be taking on stopping that, you know that those phishing attacks? Because if that's the number one problem you know, maybe that's where we should be starting. >> Yeah, it's a great question. It's typically the initial vector, for a lot of attacks to your point. But there is one thing that technology and AI cannot solve. Which is the user behavior, to your point. Like we can't get into the heads of the user. I mean, you can train them, you can do everything. You can't prevent somebody from clicking a button. Of course there's technology out there for email security that does that. But your point is, right, it's going to happen. Now what do you do? How do you protect your applications, your crown jewel? You know, whether it's in the cloud or it's in the code repo. So a lot of what we are trying to do in code security, or cloud security, or in general at Palo Alto Networks. is to protect those crown jewel. Because we can't prevent somebody from doing something. User behavior is hard to change. >> Dave: So it's almost like, okay, you left your front door open. Somebody's going to walk in, but oh, they walk into a vault. And they don't know where to go. And there's nowhere they can- >> Ankur: Yeah. >> You know, nothing they can take. They can't get to the silverware or the jewelry. >> I think that's it, yeah. >> What are some of the things, like as we look at, we're wrapping up calendar year '22 heading into '23. That customers can look to Palo Alto Networks to help them achieve? One of the things that we talked about with Nikesh and Niri yesterday, is consolidation. Like, and you guys just did a recent, survey. >> Ankur: Yeah. >> About the state of Cyber, and organizations on average have 366 apps in their environment. 31 security tools, 30 to 50 security tools. >> Ankur: Yeah. >> Consolidation is really key there. What are some of the things that you are excited about to deliver to customers where consolidation is concerned? >> Ankur: Yeah. >> Where software supply chain security is concerned in the next year? >> Yeah, absolutely. Look, there are over 3000 security vendors. And this can be, I mean you talked about average customer having 300. I was talking to a CSO, this was last year for one of the largest financial institution I go, "How many security tools do you have?" He got 120. I said, why? He goes, we have a no vendor left behind policy. >> Wow. >> It's crazy. >> Dave: What? >> Obviously he was joking, but it's crazy, right? Like that's how the CSO's are. >> Dave: I mean, he was kidding. >> Yeah. >> Dave: But recognized that. Wow. >> Yeah, and, this is the state the security industry is in. And our mission has been, and Lee and Nikesh and Niri talked about it. Is just platforms, will platforms take moonshots, things long term. And especially the, macro headwinds that we're seeing. We're hearing more and more from the customers that, look we're not going to buy point product. Then we got to buy another product that stitches it all together. We need platforms, whether it's for zero trust, Prisma SaaS, whether it's cloud. Prisma cloud or for your sock transformation. You know XIM and Cortex line of products. So I think you're going to see more and more of that in 2023. I'm confident in that. >> We heard from Lee today, the world record's 400. >> Yes. >> Yeah. >> That's crazy. >> He's going for it. He's got a ways to go. 120 He's got to... >> Maybe he wasn't, that guy wasn't kidding about his no vendor left behind policy. (laughing) Do you have Ankur, a favorite customer story that really articulates the value of what Palo Alto delivers and continues to. You know, 'cause one of the things that Nikesh said in his keynote was that you know, security's a data problem. Well every company these days, in every industry has to be a data company. But really what they need to be able to be is a secured data company. >> Ankur: Yeah. >> How are you guys enabling that? >> Oh, absolutely. Look, many customer examples come to mind, but speaking of data. You know, one of, some of our largest customers who are protecting their PCI workers where they have sensitive data. They're using for example, Prisma Cloud, to ensure that malicious attacks don't happen. And those workloads are used for credit card processing. They're processing tens of thousands of credit card transactions a second. And make sure that nobody gets hold of that. And that's why they have to make sure that nobody is. No attacker is trying to get hold of the sensitive data, to your point, So we have customers across financial services, media and entertainment technology company. Where we are helping them go as fast as possible in public cloud. Go through digital transformation, by securing their applications. >> Dave: What's the T-shirt say? I see code. >> Oh yeah. >> Dave: Secure from Code to Cloud. >> Lisa: Shift Happens. >> Shift Happens, Secrets from Code to Cloud. >> I love that. I was looking at that, going back to that, what's next in cyber survey? >> Ankur: Yeah. >> It said 74% of respondents, and I believe there was 1300 CIO's, CXO's that were surveyed globally. Where they said security is slowing down DevOps. Can customers look to Palo Alto Networks to help them? >> Ankur: Be enablers? >> Yes. >> Yeah, hundred percent. Look, the conversation over the last few years have changed now. Security used to say like, oh, I don't know about these people who are building applications. The DevOps is like security slowing down. I think there's an opportunity for companies like Palo Alto Networks, to build the bridge between the two. And the way we do it is make the securities easy, simple and not super intrusive. Where developers have to do a natural thing. And one part of it, and I talked about it earlier, is bring security where the developers are. In their code repo, in their IDE. Make it super simple. Don't make them do unnatural things. And it just, this is no different from changing the behavior of our kids. Right? Like you make them do unnatural things, they're not going to do it. But if it is part of their regular, you know, day-to-day operating procedures. I think they're going to be more open to change. Yeah. So I think it's possible. And Palo Alto has a huge responsibility to bridge the divide between the apps team, or the DevOps and the security organization. >> Lisa: Lots of great stuff to come. We thank you so much for coming back, two weeks. Only being on two weeks ago. We appreciate your insights, learning more information. It's great to see you at Palo Alto Ignite. And we'll have to have you back on. 'Cause we know that there's so much more to follow with respect to what you're doing. And shifting left, shift happens. >> Awesome. Lisa, Dave, thank you so much. It's been a pleasure. >> Lisa: Thank you so much. For Ankur Shah and Dave Vellante. I'm Lisa Martin. You're watching theCUBE. The leader in live and emerging tech coverage.

(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, 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, 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 everyone to thecube's coverage here in monaco i'm john furrier host of thecube the monaco crypto summit is happening we're here for the full day and tonight at the yacht club for special presentations crypto team is here digital bits and the industry's gathering and we get some great guests lined up throughout the day our first guest is michael gord co-founder and ceo of gda capital michael welcome to thecube cube great lunch on so we're kicking off the day here we got a lot of a lot of commentary around crypto and also we're in monaco so kind of a special inaugural event why this event why are people gathering here in monaco monaco has traditionally been a top financial jurisdiction but and there has been crypto events here before but never with participation from from prince albert so this being the first event first blockchain focus event in monaco that has participation from prince albert has brought a has brought a global audience and the fact that digital bets is intending to there's a a lot of excitement and and what uh what digital bits is going to be coming to market with yeah and i think i talked to alberto the founder and ceo of digitalbits um i've known him for many years he's a tech guy by heart but he's been in the trenches doing a lot of work over the years in crypto and one of the things i think digital bits has nailed this first the name's amazing but they got real deals i saw our announcement a couple days ago less than 48 hours roma soccer team has a new player they brought the big roll out digitalbits is on the uniform on the front of it huge crowd great visibility so this is a real trend where the the assets of physical and digital coming together there's certainly a lot of hype and a lot of kind of like cleaning up right now in the market but this train is definition is happening training has left the station there's been a lot of over the past decade a lot of startups building in the on blockchains and some of those startups have become big companies but big traditional enterprises have been slow to adopt digital assets and uh digitalbits is really well positioned to bring a lot of those and bring a lot of enterprise participation to the blockchain yeah i mean we met a couple days ago and we were talking in um at the hotel um you're you've been at this for a while you got some great successes talk about your firm what are you guys doing gda what are some of the things you're working on uh you're doing some investment what are some of the angles you're taking bets you've made things you're looking at yeah so i'm a serial entrepreneur and investor i've been focused on the mainstream adoption digital assets for the last decade went about that in in various different ways as i have as i've matured but the way our business looks now is uh is focused on bridging the gap between institutional capital markets and the blockchain and helping institutional capital participate in the market um so we help digital assets with their with their public offering we've gotten into traditional public markets through uh the blockchain moon acquisition corp spac that one of my co-founders is director of we have a brokerage business that does a few hundred million dollars about the transaction volume collateralized lending business we just started some some funds principal investments and then we incubate our own companies internally in category new categories like the metaverse nfts and um other things like that so pretty diversified across the boxing cabinet market at this point and in general looking to create solutions to um help the traditional capital market and the boxing cabinet market get get deeper exposure here you know it's interesting i hear you're speaking about the um how you guys are handling your your view of the landscape multiple moving parts on the investment thesis a lot of integration of instruments and vehicles it's a new creative structural change i mean if you look at just the money how crypto and the future of money this this cultural shift it's also some structural change on how to invest how to manage the investments how to bring on like incubation into most capital public private at the same time on the other side of the coin you have the entrepreneurial energy of um a lot of entrepreneurial ideas you see a lot of creative artists the creator culture has emerged in the past year and a half as a massive wave but to me that's just an application on top of the new infrastructure if you look at all the big investment houses that are pouring billions of whether it's industrial horowitz or other big vcs moving and shifting it's all the same game it's the infrastructure platform applications and it's but it's different it's not what we used to see because it decentralized how do you react to that what's your view on that concept you see it the same way yeah i think that there's everything with blockchains is novel but almost all of it we've seen before so um we've had games before now with the blockchain we have the ability to earn income by playing games we've had exchanges before but they've always been a centralized organization that everything that is now built on blockchains exists in the traditional internet or capital market or game industry or or whatever uh that you know there has been art for generations there's been uh now the ability to have art on the blockchain with provable nft like every everything is innovative because of the decentralization aspect but it's not it's not the first thing the first time that we've seen any of this stuff it's almost interesting you're seeing it recycling all the same concepts on the old web kind of come in the new web and there's also a gen z angle especially the metaverse metaverse the constant theme i'm seeing is hey you want to watch sports you can watch in the metaverse and do it differently and not have to attend so you know the whole pandemic has shown us that hybrid virtual and hybrid is coming together and so i see a huge tsunami of innovation coming from just the tailwind post pandemic i think still massive value in a real event like this us being able to sit in front of each other as real people is uh not replicatable in the metaverse but to be in monaco is not possible for everyone because uh visa reasons because they have something you know it's just you have to be here today is not possible for a hundred percent of the world or for a sports game or for a concert or for a music premiere movie premiere really anything that's happening in the real world is not the metaverse is not gonna replace the real world but it is gonna create a massive additional audience to anything that's happening in the real world that anyone around the world can participate and how amazing would it be for uh for someone from zimbabwe someone from sydney and someone from brazil to all be interested in what digital bits is doing in monaco and what prince albert is you know how how how how the monarchical crypto summit is looking to position monaco in the future of cryptocurrency the kind of theme of this event and they have the amazing fortune to meet in the metaverse it doesn't replace well i mean i think i mean i think this is a great point this to me is going to be the holy grail in my opinion i agree if you look at the notion of presence we're face to face we're here there's people here so we peace we see each other in the lobby maybe he's out sightseeing at dinners so when you have that face to face that's the scarce resource right that's going to be the intimacy sometimes it's not even just to learn about what the pro what's going on but if we're present here how do we create that same experience when you have presence not just some icon chatting but like just movement knowing that you're there connected to people first party is going to be no one's really done it well i think the metaverse is to me is showing the path to being a first-class citizen digitally with a real-time event it's new so it is possible to communicate in the metaverse through through a microphone so if if you're beside someone then similar to the real world you can say you know hey how's it going what do you think about the presentation or or whatever you want and if you're speaking in a conversational way then the person beside you will hear what the person down the hall might might not um it's also that i've i've seen new features in certain like experiences that are coming to market that kind of take the google hangout or skype yeah like video infrastructure and put that in so we could choose to have our cameras on which is it's getting better but it of course doesn't replace real presence there's no doubt in my mind that in near future soon sooner or later there's gonna be a guest sitting right next to you that's not here okay there will be a hologram model where people will be interviewed will have capability to visualize that person they'll be in a metaverse they'll be queuing up for interviews this is a game this is a mind-blowing thing i mean if you just think about that concept that we could have participation in real time here with expressions with their with their digital expression their icon whatever whatever their nfts are so i think this is going to be the blending of how communities gather and i think ultimately how truth and and journalism and news is going to change so to me yeah we're super excited we're here obviously because we want to get the stories and you know we love what digital bits is doing prince albert certainly a relevant figure on the global stage um i think this is a signal for a lot of things to come indeed indeed all right so final question before we move on what's your hottest thing you got going on what are you looking at what are you most excited about um well just just this conference um we've got quite a lot of of companies we have exposure in that are that are presenting and a lot of them are coining new new new niches of the market so um we have uh um we've spoken about a lot about the metaverse we have you know i'm and i think the metaverse is probably the the thing that i'm overall most excited about i think it's the next multi-trillion dollar market that feels like bitcoins in but in addition to that we have the first regenerative finance platform that is that is presenting here that's using decentralized finance and and blockchain technology to create a model that people can earn income while mining carbon credits essentially with an objective of having first boxing all blocking protocols but eventually creating a leader board of carbon positive businesses where businesses will challenge their competitors to be more carbon positive in a way that actually earns them earn some income outside of the potential value what's the name of that company that's kyoto protocol uh we have the first entertained to earn a company that is is presenting here it's playgood um the first uh e-commerce metaverse platform so integrated directly into e-commerce without needing to i think the future of the metaverse is is social links you have you know finest in the metaverse and you have all of the all the logos of metaverses that you have experiences in which is cool yeah that that's uh but then you're you're going out of the native website instead of having a um instead of you know native to the to the website having a metabolism experience so they're doing that um yeah really cool awesome final question one more final question i got for you because you made me think of it so metaverse obviously hot is there going to be an open metaverse you start to see walled gardens and you got facebook they got slam dunk by the u.s uh in terms of monopolistic move for buying a exercise act which you know i can i i don't think that was a good move by the u.s i think i let him do that but but there they're they're kind of the wall garden model the old facebook i mean decentralized about open yeah historically if we go back in time there's always open and closed infrastructure in the internet um there was there is companies building open infrastructure companies building closed infrastructure and we could have been talking in 1992 about whether the private intranet will create mass adoption or the open internet will create mass adoption and not that the the intranet is probably is even today still a multi-billion dollar per year business but it's not a multi-trillion dollar per year per year you know infrastructure like the public internet same with the blockchain in 2012 2013 um private blockchains were all the rage by banking raising hundreds of millions of dollars to build up private boxing infrastructure and private blockchains are generating probably today still multi-billion dollars of revenue annually but they haven't accrued multi-trillion dollars like the public watching has i think the same thing will be in the metaverse there will be open and closed infrastructure um but event and there already is close you know fortnight and and games are are essentially closed metaverses just without ownable land um i always look at the i'm old school i look at aol they had they monopolized dial up internet like where the hell did that go you know history so again yeah we don't know it's going to be maybe a connection a connection point between these open metaverses we'll see maybe i'm investment update michael thanks for coming on thecube appreciate you kicking off the event here monaco crypto summit powered by digital bits presented by digital bits uh the company really and behind all the innovation here and the companies i'm john furrier with more coverage after this short break thanks john [Music] you

>> Hello, everyone. Welcome to theCUBE presentation of the AWS startup showcase, market MarTech, emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. Talking about the data analytics, all the news and all the hot stories. I'm John Furrier your host of theCUBE. And today we're excited to be joined by Rachel Ostler, VP of product at Heap, Heap.io. Here to talk about from what, to why the future of digital insights. Great to see you, thanks for joining us today. >> Thanks for having me, John. Thanks for having me back. >> Well, we had a great conversation prior to the event here, a lot going on, you guys had acquired Auryc in an acquisition. You kind of teased that out last time. Talk about this, the news here, and why is it important? And first give a little setup on Heap and then the acquisition with Auryc. >> Yeah. So heap is a digital insights platform. So as you mentioned, it's all about analytics and so Heap really excels at helping you understand what your users and customers are doing in your digital application at scale. So when it comes to Auryc, what we really saw was a broken workflow. Maybe, I would even call it a broken market. Where a lot of customers had an analytics tool like Heap. So they're using Heap on one hand to figure out what is happening at scale with their users. But on the other hand, they were also using, like a session replay tool separately, to look at individual sessions and see exactly what was happening. And no one was very effective at using these tools together. They didn't connect at all. And so as a result, neither one of them could really be fully leveraged. And so with this acquisition, we're able to put these two tools together, so that users can both understand the what at scale, and then really see the why, immediately together in one place. >> You know, that I love that word why, because there's always that, you know, that famous motivational video on the internet, "you got to know your why", you know, it's very a motivational thing, but now you're getting more practicality. What and why is the, is the lens you want, right? So, I totally see that. And again, you can teased that out in our last interview we did. But I want to understand what's under the covers, under the acquisition. What was the big thesis behind it? Why the joint forces? What does this all mean? Why is this so important to understand this new, what and why and the acquisition specifically? >> Yeah, so let me give you example of a couple used cases, that's really helpful for understanding this. So imagine that you are a product manager or a, maybe a growth marketer, but you're someone who owns a digital experience. And what you're trying to do, of course, is make that digital experience amazing for your users so that they get value and that may mean that they're using it more, it may mean that new features are easily discoverable, that you can upsell things on your own. There's all sorts of different things that that may mean, but it's all about making it easy to use, discoverable, understandable, and as self-service as possible too. And so most of these digital builders, we call 'em digital builders sometimes. They are trying to figure out when the application is not working the way that it should be working, where people are getting stuck, where they're not getting the value and figure out how to fix that. And so, one really great used case is, I just want to understand in mass, like, let's say I have a flow, where are people dropping off? Right, so I see that I have a four step funnel and between step three and four people are dropping off. Heap is great for getting very detailed on exactly what action they're taking, where they're dropping off. But then the second you find what that action is, quantitatively, you want to watch it, you want to see what they did exactly before it. You want to see what they did after it. You want to understand why they're getting stuck. What they're confused at, are they mouthing over two things, like you kind of want to watch their session. And so what this acquisition allows us to do, is to put those things together seamlessly, you find the point in friction, you watch a bunch of examples, very easily. In the past, this would take you at least hours, if you could do it at all. And then in other used cases, the other direction. So there's the kind of, I think of it as the max to the min, and then there's the other direction as well. Like you have the, or maybe it's the macro to micro. You have the micro to macro, which is you have one user that had a problem. Maybe they send in a support ticket. Well, you can validate the problem. You can watch it in the session, but then you want to know, did this only happen to them? Did this happen to a lot of users? And this is really worth fixing, because all these customers are having the same problem. That's the micro to macro flow that you can do as well. >> Yeah. That's like, that's like the quantitative qualitative, the what and the why. I truly see the value there and I liked the way you explained that, good call out. The question I have for you, because a lot of people have these tools. "I got someone who does that." "I got someone over here that does the quantitative." "I don't need to have one company do it, or do I?" So the question I have for you, what does having a single partner or vendor, providing both the quantitative and the qualitative nails mean for your customers? >> So it's all because now it's immediate. So today with the two tools being separate, you may find something quantitatively. But then to, then to find the sessions that you want to watch that are relevant to that quantitative data point is very difficult. At least it takes hours to do so. And a lot of times people just give up and they don't bother. The other way is also true, you can watch sessions, you can watch as many sessions as you want, you can spend hours doing it, you may never find anything of interest, right? So it just ends up being something that users don't do. And actually we've interviewed a lot of customers, they have a lot of guilt about this. A lot of product managers feel like they should be spending all this time, but they just don't have the time to spend. And so it not only brings them together, but it brings them together with immediacy. So you can immediately find the issue, find exactly where it is and watch it. And this is a big deal, because, if you think about, I guess, like today's economic conditions, you don't have a lot of money to waste. You don't have a lot of time to waste. You have to be very impactful with what you're doing and with your spending of development resources. >> Yeah. And totally, and I think one of the things that immediacy is key, because it allows you to connect dots faster. And we have the aha moments all the time. If you miss that, the consequences can be quantified in a bad product experience and lost customers. So, totally see that. Zooming out now, I want to get your thoughts on this, cause you're bringing, we're going down this road of essentially every company is digital now, right? So digitization, digital transformation. What do you want to call it? Data is digital. This video is an experience. It's also data as well. You're talking, we're going to share this and people are going to experience that. So every website that's kind of old school is now becoming essentially a digital native application or eCommerce platform. All the things that were once preserved for the big guys, the hyper-scalers and the categories, the big budgets, now are coming down to every company. Every company is a digital company. What challenges do they have to transition from? I got a website, I got a marketing team. Now I got to look like a world class, product, eCommerce, multifaceted, application with developers, with change, with agility? >> Well, so I think that last thing you said is a really important part of it, the agility. So, these products, when you're going from a, just a website to a product, they're a lot more complex. Right? And so maybe I can give an example. We have a customer, it's an insurance company. So they have this online workflow. And if you can imagine signing up for insurance online, it's a pretty long complicated workflow. I mean, Hey, better to do it online than to have to call someone and wait on, you know, on the phone. And so it's a good experience, but it's still fraught with like opportunities of people getting stuck and never coming back. And so one of the things that Heap allowed this customer to do was figure out something that wasn't working in their workflow. And so if you think about traditional analytics tools, typically what you're doing is you're writing tracking code and you're saying, "Hey, I'm going to track this funnel, this process." And so maybe it has, you know, five different forms or pages that you have to go through. And so what you're doing when you track it is you say, did you submit the first one? Did you submit the second one? Did you submit the third one? So you know, like where they're falling off. You know where they're falling off, but you don't know why, you don't know which thing got them stuck because each one of these pages has multiple inputs and it has maybe multiple steps that you need to do. And so you're completely blind to exactly what's happening. Well, it turned out because Heap collects all this data, that on one of these pages where users were dropping off, it was because they were clicking on a FAQ, there was a link to a FAQ, and because this was a big company, the FAQ took them to a completely different application. Didn't know how to get back from there and they just lost people. And imagine if you are doing this with traditional means today, right? You don't have any visibility into what's happening on that page, you just know that they fell off. You might think about what do I do to fix this? How do I make this flow work better? And you might come up with a bunch of ideas. One of your ideas could be, let's break it into multiple pages. Maybe there's too much stuff on this page. One of your ideas may have been, let's try a FAQ. They're getting stuck, let's give them some more help. That would be a very bad idea, right? Because that was actually the reason why they were leaving and never coming back. So, the point I'm making is that, if you don't know exactly where people are getting stuck and you can't see exactly what is happening, then you're going to make a lot of very bad decisions. You're going to waste a lot of resources, trying things that make no sense. It is hard enough as a digital builder and all the product managers and growth marketers and marketers out there can attest to this, it's hard enough when you know exactly what the problem is to figure out a good solution. Right? That's still hard. But if you don't know the problem, it's impossible. >> Okay, so let's just level up, the bumper sticker now for the challenges are what? Decision making, what's the, stack rank the top three challenges from that. So it's being agile, right? So being very fast, because you're competing with a lot of companies right now. It's about making really good decisions and driving impact, right? So you have to have all the data that you need. You have to have the, the specific information about what's going on. Cause if you don't have it, you're going to decide to invest in things and you're not going to drive the impact that you want. >> So now you got the acquisition of Auryc and Auryc and you have the, this visibility to the customers that are building, investing, you mentioned, okay. As they invest, whether it's the digital product or new technology in R and D, what feedback have you guys seen from these investments, from these customers, what results have come out of it? Could you share any specific answers to the problems and challenges you have outlined, because you know, there's growth hackers could be failing cause of stupid little product mistakes that could have been avoided in the feedback, you know what I'm saying? So it's like, where can you, where are these challenges addressed and what are some of the results? >> Yeah, so, what we've seen with our customers is that when they are applying this data and doing this analysis on say workflows or goals that they're trying to accomplish, they've been able to move the needle quite a bit. And so, whether it is, you know, increasing conversion rates or whether it is making sure that they don't have, you know, drop off of trial signups or making sure that their customers are more engaged than before, when they know exactly where they're failing, it is much easier to make an investment and move the needle. >> Awesome. Well, let's move on to the next big topic, which I love, it's about data science and data engineering. You guys are a data company and I want to ask you specifically, how Heap uniquely is positioned to help companies succeed, where in the old big tech world, they're tightening the ropes on secure cookies, privacy, data sharing. At the same time, there's been an explosion in cloud scale data opportunities and new technologies. So it seems like a new level of, capability, is going to replace the old cookies, privacy and data sharing, which seem to be constricting or going away. How do you, what's your reaction to that? Can you share how Heap fits into this next generation and the current situation going on with the cookies and this privacy stuff. >> Yep, so it is really important in this world to be collecting data compliantly, right? And so what that means is, you don't want to be reliant on third party cookies. You want to be reliant on just first party information. You want to make sure that you don't collect any PII. Heap is built to do that from the ground up. We by default will not collect information, like what do people put into forms, right? Because that's a obvious source of PII. The other thing is that, there's just so much data. So you kind of alluded to this, with this idea of data science. So first of all, you're collecting data compliantly, you're making sure that you have all the data of what your user actions are doing, compliantly, but then it's so much data that it like, how do you know where to start? Right? You want to know, you want to get to that specific point that users are dropping off, but there's so many different options out there. And so that's where Heap is applying data science, to automatically find those points of friction and automatically surface them to users, so that you don't have to guess and check and constantly guess at what the problem is, but you can see it in the product surface right for you. >> You know, Rachel, that's a great point. I want to call that out because I think a lot of companies don't underestimate, they may underestimate what you said earlier, capturing in compliance way means, you're opting in to say, not to get the data, to unwind it later, figure it out. You're capturing it in a compliant way, which actually reduces the risk and operational technical debt you might have to deploy to get it fixed on compliance. Okay, that's one thing, I love that. I want to make sure people understand that value. That's a huge value, especially for people that don't have huge teams and diverse platforms or other data sources. The other thing you mentioned is owning their own data. And that first party data is a strategic advantage, mainly around personalization and targeted customer interaction. So the question is, with the new data, I own the data, you got the comp- capture with compliance. How do you do personalization and targeted customer interactions, at the same time while being compliant? It just seems, it seems like compliance is restrictive and kind of forecloses value, but open means you can personalization and targeted interactions. How do you guys connect the dots there by being compliant, but yet being valuable on the personalization and targeted? >> Well, it all depends on how the customer is managing their information, but imagine that you have a logged in user, well, you know, who the logged in user is, right? And so all we really need is an ID. Doesn't have, we don't need to know any of the user information. We just need an ID and then we can serve up the information about like, what have they done, if they've done these three actions, maybe that means that this particular offer would be interested to them. And so that information is available within Heap, for our customers to use it as they want to, with their users. >> So you're saying you can enable companies to own their data, be compliant and then manage it end to end from a privacy standpoint. >> Yes. >> That's got to be a top seller right there. >> Well, it's not just a top seller, it's a necessity. >> It's a must have. I mean, think about it. I mean, what are people, what are the, what are people who don't do this? What do they face? What's the alternative? If you don't keep, get the Heap going immediately, what's the alternative? I'm going through logs, I got to have to get request to forget my data. All these things are all going on, right? Is, what's the consequence of not doing this? >> Well, there's a couple consequences. So one is, and I kind of alluded to it earlier that, you're just, you're blind to what your users are doing, which means that you're making investments that may not make sense, right? So you can, you can decide to add all the cool features in the world, but if the customers don't perceive them as being valuable or don't find them or don't understand them, it doesn't, it doesn't serve your business. And so, this is one of like the rule number one of being a product manager, is you're trying to balance what your customers need, with what is also good for your business. And both of those have to be in place. So that's basically where you are, is that you'll be making investments that just won't be hitting the mark and you won't be moving the needle. And as I mentioned, it's more important now in this economic climate than ever to make sure that the investments you're making are targeted and impactful. >> Yeah and I think the other thing to point out, is that's a big backlash against the whole, Facebook, you're the product, you're getting used, the users being used for product, but you're, you guys have a way to make that happen in a way that's safe for the user. >> Yes. Safe and compliant. So look, we're all about making sure that we certainly don't get our customers into trouble and we recommend that they follow all compliance rules, because the last thing you want to be is on the, on the wrong side of a compliance officer. >> Well, there's also the user satisfaction problem of, and the fines. So a lot going on there, great product. I got to ask you real quick before we kind of wrap up here. What's the reaction been to the acquisition? Quantitative, qualitative. What's been the vibe? What are some, what are people saying about it? >> We've got a lot of interest. So, I mentioned earlier that this is really a broken workflow in the market. And when users see the two products working together, they just love it because they have not been able to leverage them being separate before. And so it just makes it so much easier for these digital builders to figure out, what do I invest in because they know exactly where people are having trouble. So it's been really great, we've had a lot of reach outs already asking us how they can use it, try it, not quite available yet. So it's going to be available later this summer, but great, great response so far. >> Awesome. Well, I love the opportunity. Love the conversation, I have to ask you now, looking forward, what does the future look like for companies taking advantage of your platform and tool? What can they expect in terms of R and D investments, area moves you're making? You're the head of product, you get the keys to the kingdom. What's the future look like? What's coming next? >> Yeah, so other than pulling the qual and the quant together, you actually hinted at it earlier when you're asking me about data science, but continuing to automate as much of the analysis as we can. So, first of all, analysis, analytics, it should be easy for everyone. So we're continue to invest in making it easy, but part of making it easy is, like we can automate analysis. We can, we can see that your website has a login page on it and build a funnel for you automatically. So that's some of the stuff that we're working on, is how do we both automate getting up to speed and getting that initial analysis done easily, without any work. And then also, how do we automate more complex analysis? So you have, typically a lot of companies have a data science team and they end up doing a lot of analysis, it's a little bit more complex. I'm not saying data science teams will go away, they will be around forever. There's tons of very complex analysis that they're probably not even getting time to do. We're going to start chipping away at that, so we can help product managers do more and more of that self-service and then free up the data science team to do even more interesting things. >> I really like how you use the word product managers, product builders, digital builders, because while I got you, I want to get your thought on this, because it's a real industry shift. You're talking about it directly here, about websites going to eCommerce, CMOs, a C-suite, they generally observe that websites are old technology, but not going away, because the next level abstraction builds on top of it. What's the new capabilities because for the CMOs and the C-suites and the product folks out there, they're not building webpages, they're building applications. So what is it about this new world that's different from the old web architecture? How would you talk to a CMO or a leader? And to, when they ask what's this new opportunity to take my website, cause maybe it's not enough traffic. People are consuming out in the organic, what's this new expectation and how, what does a new product manager environment look like, if it's not the web, so to speak? >> Well, there's a couple things. So one is, and you alluded to it a bit, like the websites are also getting more complex and you need to start thinking of your website as a product. Now it's, it may not be the product that you sell, but it is, well for eCommerce it's the place that you get access to the product, for B2B SaaS, it is the window to the product. It's a place where you can learn about the product. And you need to think about, not just like, what pieces of content are being used, but you need to understand the user flow, through the application. So that's how it's a lot more like a product. >> Rachel, thanks so much for coming on theCUBE here for this presentation, final word, put a plugin for the company. What are you guys up to? What are you looking for? Take a minute to explain kind of that, what's going on. How do people contact you with a great value proposition? Put a plugin for the company. >> Yeah, well, if you want to up level your product experience or website experience, you want to be able to drive impact quickly, try Heap. You can go to Heap.io, you can try it for free. We have a free trial, we have a free product even. And yeah, and then if you have any questions, you want to talk to a live person, you can do that too, at sales@Heap.io. >> Rachel, thanks so much. Customer-scale experiences with the cloud house league. This is the season two, episode three of the ongoing series. I'm John Furrier, your host. 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.

>>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'm 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 2000 >>and eight, 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. DeVos 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. 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 DLC >>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 splc 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. >>No, 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. Yeah >>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 security administrator versus a security engineer. But perhaps most critically, I believe personas are immutable. Mhm. 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. Mhm 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. >>We're 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 that 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. The cops. 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, when and how and that is everyone's responsibility at every stage, site, reliability, engineering or SRE is a discipline and 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 through but 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 when 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 in 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 isn't 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. Mm.

(smooth upbeat music) >> Hello, everybody, John Walls here. Welcome to "theCUBE," in our continuing coverage of Ansible Fest 2021. We now welcome onto "theCUBE," three representatives from Red Hat. Joining us is Ashesh Badani. Who's the Senior Vice President of Products at Red Hat. Ashesh, thank you for joining us today. >> Thanks for having me, John. >> You bet. Also with us Stefanie Chiras, who is the Senior Vice President of the Platforms Business Group also at Red Hat. And Stefanie, how are you doing? >> Good, thanks, it's great to be here with you, John. >> Excellent, thanks for joining us. And last, but certainly not least, Joe Fitzgerald, who is the Vice President and General Manager of the Ansible Business Unit at Red Hat. Joe, good to see you today, thanks for being with us. >> Good to see you again John, thanks for having us. >> It's like, like the big three at Red Hat. I'm looking forward to this. Stefanie, let's just jump in with you and let's talk about what's going on in terms of automation in the hybrid cloud environment these days. A lot of people making that push, making their way in that direction. Everybody trying to drive more value out of the hybrid cloud environment. How is automation making that happen? How's it making it work? >> We have been focused at Red Hat for a number of years now on the value of open hybrid cloud. We really believe in the value of being able to give your applications flexibility, to use the best technology, where you want it, how you need it, and pulling all of that together. But core to that value proposition is making sure that it is consistent, it is secure and it is able to scale. And that's really where automation has become a core space. So as we continue to work our portfolio and our ecosystems and our partnerships to make sure that that open hybrid cloud has accessibility to everything that's new and relevant in this changing market we're in, the automation space that Ansible drives is really about making sure that it can be done in a way that is predictable. And that is really essential as you start to move your workloads around and start to leverage the diversity that an open hybrid cloud can deliver. >> When you're bringing this to a client, and Joe, perhaps you can weigh in on this as well. I would assume that as you're talking about automation, there's probably a lot of, successful head-nodding this way, but also some kind of this way too. There's a little bit of fear, right? And maybe just, they have these legacy systems, there's maybe a little distrust, I don't want to give away control, all these things. So how do you all answer those kinds of concerns when you're talking to the client about this great value that you can drive, but you got to get them there, right? You have to bring them along a bit. >> It's a great question, John, and look, everybody wants to get the hybrid cloud, as Stefanie mentioned. That journey is a little complicated. And if you had silos and challenges before you went to a hybrid cloud, you're going to have more when you got there. We work with a lot of customers, and what we see is this sort of shift from, I would call it low-level task automation to much more of a strategic focus on automation, but there's also the psychology of automation. One of the analysts recently did some research on that. And imagine just getting in your car and letting the car drive you down the street to work. People are still not quite comfortable with that level of automation, they sort of want to be able to trust, but verify, and maybe have their hands near the wheel. You couldn't take the wheel away from them. We see the same thing with automation. They need automation and a lot automation, or they need to be able to verify what it is doing, what they do, what it's going to do. And once they build that confidence, then they tend to do it at scale. And we're working with a lot of customers in that area. >> Joe, you're talking about a self-driving car, that'll never work, right? (laughs) You us bring an interesting point though. Again, I get that kind of surrendering control a little bit and Ashesh, I would assume in the product development world, that's very much your focus, right? You're looking for products that people, not only can use, but they're also comfortable with. That they can accept and they can integrate, and there's buy-in, not only on the engineering level, but also on the executive level. So maybe walk us through that product development, staging or phases, however you want to put it, that you go through in terms of developing products that you think people, not only need, but they'll also accept. >> I think that's absolutely right. You know, I think both Stefanie and Joe, led us off here. I talked about hybrid cloud and Joe, started talking about moving automation forward and getting people comfortable. I think a lot of this is, meeting customers where they are and then helping them get on the journey, right? So we're seeing that today, right? So traditional configuration management on premise, but at the same time, starting to think about, how do we take them out into the cloud, bringing greater automation to bear there. But so that's true for us across our existing customer base, as well as the new customers that we see out there. So doing that in a way that Joe talked about, right? Ensuring the trust, but verify is in play, is critical. And then there's another area which I'm sure we'll talk a little bit more about, right? Is ensuring that security implications are taken into account as we go through it. >> Well, let's just jump into security, that's one of the many considerations these days. About ensuring that you have the secure operation, you're doing some very complex tasks here, right? And you're blending multi-vendor environments and multi-domain environments. I mean you've got a lot, you're juggling a lot. So I guess to that extent, how much of a consideration is security and those multiple factors today, for you. And again, I don't know which one of the three of you might want to jump on this, but I would assume, this is a high priority, if not the highest priority, because of the headlines that security and those challenges are garnering these days. >> Well, there's the general security question and answer, right? So this is the whole, shift-left DevSecOps, sort of security concerns, but I think specific to this audience, perhaps I can turn over to Joe to talk a little bit about how Ansible has been playing in the security domain. >> Now, it's a great way to start, Ashesh. People are trying to shift left, which means move, sort of security earlier on in the process where people are thinking about it and development process, right? So we've worked with a lot of customers who were trying to do DevSecOps, right? And to provide security, automation capabilities during application build and deployment. Then on the operational side, you have this ongoing issue of some vulnerability gets identified, how fast can I secure my environment, right? There's a whole new area of security, orchestration, automation, or remediation that's involved, and the challenge people have is just like with networking or other areas, they've got dozens in some cases, hundreds of different systems across their enterprise that they have to integrate with, in order to be able to close a vulnerability, whether it's deploying a patch or closing a port, or changing firewall configuration, this is really complicated and they're being measured by, okay, there's this vulnerability, how fast can we get secure? And that comes down to automation, it has to. >> Now, Joe, you mentioned customers, if you would maybe elaborate a little bit about the customers that we've been hearing from on the stage, the virtual stage, if you will, at Ansible Fest this year and maybe summarize for our audience, what you're hearing from those customers, and some of those stories when we're talking about the actual use of the platform. >> Yeah, so Ansible Fest is our annual, automation event, right? For Ansible users. And I think it's really important to hear from the customers. We're vendors, we can tell you anything you want and try and get you to believe it. Customers they're actually doing stuff, right? And so, at Ansible Fest, we've got a great mix of customers that are really pushing the envelope. I'll give you one example, JP Morgan Chase. They're talking about how in their environment with focus over the past couple of years, they've now gotten to a level of maturity with automation, where they have over 50,000 people that are using Ansible automation. They've got a community of practice where they've got people in over twenty-two countries, right? That are sharing over 10,000 playbooks, right? I mean, they've taken automation strategically and embraced it and scaled it out at a level that most other organizations are envious of, right? Another one, and I'm not going to go through the list, but another one I'll mention is Discover, which sort of stepped back and looked at automation strategically and said, we need to elevate this to a strategic area for the company. And they started looking at across all different areas, not just IT automation, business process automation, on their other practices internally. And they're doing a presentation on how to basically analyze where you are today and how to take your automation initiatives forward in a strategic way. Those are usually important to other organizations that maybe aren't as far along or aren't on a scale of that motivation. >> Yeah, so Stefanie, I see you nodding your head and you're talking about, when Joe was just talking about assessment, right? You have to kind of see where are we, how mature are we on our journey right now? So maybe if you could elaborate on that a little bit, and some of the key considerations that you're seeing from businesses, from clients and potential clients, in terms of the kind of thought process they're going through on their journey, on their evolution. >> I think there's a lot of sort of values that customers are looking for when they're on their automation journey. I think efficiency is clearly one. I think one that ties back to the security discussion that we talked about. And I use the term consistency, but it's really about predictability. And I think I have a lot of conversations with customers that if they know that it's consistently deployed, particularly as we move out and are working with customers at the edge, how do they know that it's done the same way every time and that it's predictable? There's a ton of security and confidence built into that. And I think coming back to Joe's point, it is a journey providing transparency and visibility is step one, then taking action on that is then step two. And I think as we look at the customers who are on this automation journey, it's them understanding what's the value they're looking for? Are they looking for consistency in the deployments? Are they looking for efficiency across their deployments? Are they looking for ways to quickly migrate between areas in the open hybrid cloud? What is the value they're looking for? And then they look at how do they start to build in confidence in how they deliver that. And I think it starts with transparency. The next step is starting to move into taking action, and this is a space where Joe and the whole team, along with the community have really focused on pulling together things like collections, right? Playbooks that folks can count on and deploy. We've looked within the portfolio, we're leveraging the capabilities of this type of automation into our products itself with Red Hat enterprise Linux, we've introduced systems roles. And we're seeing a lot of by pulling in that Ansible capability directly into the product, it provides consistency of how it gets deployed and that delivers a ton of confidence to customers. >> So, Ashesh I mean, Stefanie was talking about, the customers and obviously developing, I guess, cultural acceptance and political acceptance, within the ranks there. Where are we headed here, past what know now in terms of the traditional applications and traditional automations and whatever. Kind of where is this going, if you would give me your crystal ball a bit about automation and what's going to happen here in the next 12-18 months. >> So what I'm going to do, John, is try to marry two ideas. So we talked about hybrid cloud, right? Stefanie started talking about joining a hybrid cloud. I'm going to marry automation with containers, right? On this journey of hybrid cloud, right? And give you two examples, both some successful progress we've been making on that front, right? Number one, especially for the group here, right? Check out the Ansible collection for Kubernetes, it's been updated for Python Three, of course, with the end-of-life for Python Two, but more important, right? It's the focus on improving performance for large automation tasks, right? Huge area where Ansible shines, then taking advantage of turbo mode, where instead of the default being a single connection to a Culebra API, for every request that's out there with turbo mode turned on, the API connection gets reused significantly and obviously improving performance. Huge other set of enhancements as well, right? So I think that's an interesting area for the Ansible community to leverage and obviously to grow. And the second one that I wanted to call out was just kind of the, again, back to this sort of your notion of the marriage of automation with containers, right? Is the work that's going on, on the front of the integration, the tight integration between Ansible as well as Red Hat's, advanced cluster management, right? Which is helping to manage Kubernetes clusters at scale. So now Red Hat's ACM technology can help our monthly trigger Ansible playbooks, upon key lifecycle actions that have happened. And so taking advantage of technologies like operators, again, core Kubernetes construct for the hybrid cloud environment. This integration between advanced cluster management and Ansible, allows for much more efficient execution of tasks, right? So I think that's really powerful. So wrapping that up, right? This world of hybrid cloud really can be brought together by just a tighter integration between working Ansible as well as the work that's going on on the container plant. >> Great, well, thank you. Ashesh, Stefanie, Joe, thank you all for sharing the time here. Part of our Ansible Fest coverage here, enjoy the conversation and continuous success at Red Hat. Thank you for the time today. >> Thank you so much John. >> Thank you. >> You bet. I'm joined here by three executives at Red Hat, talking about our Ansible Fest 2021 coverage. I'm John Walls, and you're watching "theCUBE." (bright music)

>>Really excited about this year's data, citizens with so many of you together. Uh, I'm going to talk today about accessible data, because what good is the data. If you can get it into your hands and shop for it, but you can't understand it. Uh, and I'm here today with, uh, bald, really thrilled to be here with Paul. Paul is an award-winning author on all topics data. I think 20 books with 21st on the way over 300 articles, he's been a frequent speaker. He's an expert in future trends. Uh, he's a VP at cognitive systems, uh, over at IBM teachers' data also, um, at the business school and as a champion of diversity initiatives. Paul, thank you for being here, really the conformance, uh, to the session with you. >>Oh, thanks for having me. It's a privilege. >>So let's get started with, uh, our origins and data poll. Um, and I'll start with a little story of my own. So, uh, I trained as an engineer way back when, uh, and, um, in one of the courses we got as an engineer, it was about databases. So we got the stick thick book of CQL and me being in it for the programming. I was like, well, who needs this stuff? And, uh, I wanted to do my part in terms of making data accessible. So essentially I, I was the only book that I sold on. Uh, obviously I learned some hard lessons, uh, later on, as I did a master's in AI after that, and then joined the database research lab at the university that Libra spun off from. Uh, but Hey, we all learned along the way. And, uh, Paula, I'm really curious. Um, when did you awaken first to data? If you will? >>You know, it's really interesting Stan, because I come from the opposite side, an undergrad in economics, uh, with some, uh, information systems research at the higher level. And so I think I was always attuned to what data could do, but I didn't understand how to get at it and the kinds of nuances around it. So then I started this job, a database company, like 27 years ago, and it started there, but I would say the awakening has never stopped because the data game is always changing. Like I look at these epochs that I've been through data. I was a real relational databases thinking third normal form, and then no SQL databases. And then I watch no SQL be about no don't use SQL, then wait a minute. Not only sequel. And today it's really for the data citizens about wait, no, I need SQL. So, um, I think I'm always waking up in data, so I'll call it a continuum if you will. But that was it. It was trying to figure out the technology behind driving analytics in which I took in school. >>Excellent. And I fully agree with you there. Uh, every couple of years they seem to reinvent new stuff and they want to be able to know SQL models. Let me see. I saw those come and go. Uh, obviously, and I think that's, that's a challenge for most people because in a way, data is a very abstract concepts, um, until you get down in the weeds and then it starts to become really, really messy, uh, until you, you know, from that end button extract a certain insights. Um, and as the next thing I want to talk about with you is that challenging organizations, we're hearing a lot about data, being valuable data, being the new oil data, being the new soil, the new gold, uh, data as an asset is being used as a slogan all over. Uh, people are investing a lot in data over multiple decades. Now there's a lot of new data technologies, always, but still, it seems that organizations fundamentally struggle with getting people access to data. What do you think are some of the key challenges that are underlying the struggles that mud, that organizations seem to face when it comes to data? >>Yeah. Listen, Stan, I'll tell you a lot of people I think are stuck on what I call their data, acumen curves, and you know, data is like a gym membership. If you don't use it, you're not going to get any value on it. And that's what I mean by accurate. And so I like to think that you use the analogy of some mud. There's like three layers that are holding a lot of organizations back at first is just the amount of data. Now, I'm not going to give you some stat about how many times I can go to the moon and back with the data regenerate, but I will give you one. I found interesting stat. The average human being in their lifetime will generate a petabyte of data. How much data is that? If that was my apple music playlist, it would be about 2000 years of nonstop music. >>So that's some kind of playlist. And I think what's happening for the first layer of mud is when I first started writing about data warehousing and analytics, I would be like, go find a needle in the haystack. But now it's really finding a needle in a stack of needles. So much data. So little time that's level one of mine. I think the second thing is people are looking for some kind of magic solution, like Cinderella's glass slipper, and you put it on her. She turns into a princess that's for Disney movies, right? And there's nothing magical about it. It is about skill and acumen and up-skilling. And I think if you're familiar with the duper, you recall the Hadoop craze, that's exactly what happened, right? Like people brought all their data together and everyone was going to be able to access it and give insights. >>And it teams said it was pretty successful, but every line of business I ever talked to said it was a complete failure. And the third layer is governance. That's actually where you're going to find some magic. And the problem in governance is every client I talked to is all about least effort to comply. They don't want to violate GDPR or California consumer protection act or whatever governance overlooks, where they do business and governance. When you don't lead me separate to comply and try not to get fine, but as an accelerant to your analytics, and that gets you out of that third layer of mud. So you start to invoke what I call the wisdom of the crowd. Now imagine taking all these different people with intelligence about the business and giving them access and acumen to hypothesize on thousands of ideas that turn into hundreds, we test and maybe dozens that go to production. So those are three layers that I think every organization is facing. >>Well. Um, I definitely follow on all the days, especially the one where people see governance as a, oh, I have to comply to this, which always hurts me a little bit, honestly, because all good governance is about making things easier while also making sure that they're less riskier. Um, but I do want to touch on that Hadoop thing a little bit, uh, because for me in my a decade or more over at Libra, we saw it come as well as go, let's say around 2015 to 2020 issue. So, and it's still around. Obviously once you put your data in something, it's very hard to make it go away, but I've always felt that had do, you know, it seemed like, oh, now we have a bunch of clusters and a bunch of network engineers. So what, >>Yeah. You know, Stan, I fell for, I wrote the book to do for dummies and it had such great promise. I think the problem is there wasn't enough education on how to extract value out of it. And that's why I say it thinks it's great. They liked clusters and engineers that you just said, but it didn't drive lineup >>Business. Got it. So do you think that the whole paradigm with the clouds that we're now on is going to fundamentally change that or is just an architectural change? >>Yeah. You know, it's, it's a great comment. What you're seeing today now is the movement for the data lake. Maybe a way from repositories, like Hadoop into cloud object stores, right? And then you look at CQL or other interfaces over that not allows me to really scale compute and storage separately, but that's all the technical stuff at the end of the day, whether you're on premise hybrid cloud, into cloud software, as a service, if you don't have the acumen for your entire organization to know how to work with data, get value from data, this whole data citizen thing. Um, you're not going to get the kind of value that goes into your investment, right? And I think that's the key thing that business leaders need to understand is it's not about analytics for kind of science project sakes. It's about analytics to drive. >>Absolutely. We fully agree with that. And I want to touch on that point. You mentioned about the wisdom of the crowds, the concept that I love about, right, and your organization is a big grout full of what we call data citizens. Now, if I remember correctly from the book of the wisdom of the crowds, there's, there's two points that really, you have to take Canada. What is, uh, for the wisdom of the grounds to work, you have to have all the individuals enabled, uh, for them to have access to the right information and to be able to share that information safely kept from the bias from others. Otherwise you're just biasing the outcome. And second, you need to be able to somehow aggregate that wisdom up to a certain decision. Uh, so as Felix mentioned earlier, we all are United by data and it's a data citizen topic. >>I want to touch on with you a little bit, because at Collibra we look at it as anyone who uses data to do their job, right. And 2020 has sort of accelerated digitization. Uh, but apart from that, I've always believed that, uh, you don't have to have data in your title, like a data analyst or a data scientist to be a data citizen. If I take a look at the example inside of Libra, we have product managers and they're trying to figure out which features are most important and how are they used and what patterns of behavior is there. You have a gal managers, and they're always trying to know the most they can about their specific accounts, uh, to be able to serve as them best. So for me, the data citizen is really in its broadest sense. Uh, anyone who uses data to do their job, does that, does that resonate with you? >>Yeah, absolutely. It reminds me of myself. And to be honest in my eyes where I got started from, and I agree, you don't need the word data in your title. What you need to have is curiosity, and that is in your culture and in your being. And, and I think as we look at organizations to transform and take full advantage of their, their data investments, they're going to need great governance. I guarantee you that, but then you're going to have to invest in this data citizen concept. And the first thing I'll tell you is, you know, that kind of acumen, if you will, as a team sport, it's not a departmental sport. So you need to think about what are the upskilling programs of where we can reach across to the technical and the non-technical, you know, lots and lots of businesses rely on Microsoft Excel. >>You have data citizens right there, but then there's other folks who are just flat out curious about stuff. And so now you have to open this up and invest in those people. Like, why are you paying people to think about your business without giving the data? It would be like hiring Tom Brady as a quarterback and telling him not to throw a pass. Right. And I see it all the time. So we kind of limit what we define as data citizen. And that's why I love what you said. You don't need the word data in your title and more so if you don't build the acumen, you don't know how to bring the data together, maybe how to wrangle it, but where did it come from? And where can you fixings? One company I worked with had 17 definitions for a sales individual, 17 definitions, and the talent team and HR couldn't drive to a single definition because they didn't have the data accurate. So when you start thinking of the data citizen, concept it about enabling everybody to shop for data much. Like I would look for a USB cable on Amazon, but also to attach to a business glossary for definition. So we have a common version of what a word means, the lineage of the data who owns it, who did it come from? What did it do? So bring that all together. And, uh, I will tell you companies that invest in the data, citizen concept, outperform companies that don't >>For all of that, I definitely fully agree that there's enough research out there that shows that the ones who are data-driven are capturing the most markets, but also capturing the most growth. So they're capturing the market even faster. And I love what you said, Paul, about, um, uh, the brains, right? You've already paid for the brains you've already invested in. So you may as well leverage them. Um, you may as well recognize and, and enable the data citizens, uh, to get access to the assets that they need to really do their job properly. That's what I want to touch on just a little bit, if, if you're capable, because for me, okay. Getting access to data is one thing, right? And I think you already touched on a few items there, but I'm shopping for data. Now I have it. I have a cul results set in my hands. Let's say, but I'm unable to read and write data. Right? I don't know how to analyze it. I don't know maybe about bias. Uh, maybe I, I, I don't know how to best visualize it. And maybe if I do, maybe I don't know how to craft a compelling persuasion narrative around it to change my bosses decisions. So from your viewpoint, do you think that it's wise for companies to continuously invest in data literacy to continuously upgrade that data citizens? If you will. >>Yeah, absolutely. Forest. I'm going to tell you right now, data literacy years are like dog years stage. So fast, new data types, new sources of data, new ways to get data like API APIs and microservices. But let me take it away from the technical concept for a bit. I want to talk to you about the movie. A star is born. I'm sure most of you have seen it or heard it Bradley Cooper, lady Gaga. So everyone knows the movie. What most people probably don't know is when lady Gaga teamed up with Bradley Cooper to do this movie, she demanded that he sing everything like nothing could be auto-tuned everything line. This is one of the leading actors of Hollywood. They filmed this remake in 42 days and Bradley Cooper spent 18 months on singing lessons. 18 months on a guitar lessons had a voice coach and it's so much and so forth. >>And so I think here's the point. If one of the best actors in the world has to invest three and a half years for 42 days to hit a movie out of the park. Why do we think we don't need a continuous investment in data literacy? Even once you've done your initial training, if you will, over the data, citizen, things are going to change. I don't, you don't. If I, you Stan, if you go to the gym and workout every day for three months, you'll never have to work out for the rest of your life. You would tell me I was ridiculous. So your data literacy is no different. And I will tell you, I have managed thousands of individuals, some of the most technical people around distinguished engineers, fellows, and data literacy comes from curiosity and a culture of never ending learning. That is the number one thing to success. >>And that curiosity, I hire people who are curious, I'll give you one more story. It's about Mozart. And this 21 year old comes to Mozart and he says, Mozart, can you teach me how to compose a symphony? And Mozart looks at this person that says, no, no, you're too young, too young. You compose your fourth symphony when you were 12 and Mozart looks at him and says, yeah, but I didn't go around asking people how to compose a symphony. Right? And so the notion of that story is curiosity. And those people who show up in always want to learn, they're your home run individuals. And they will bring data literacy across the organization. >>I love it. And I'm not going to try and be Mozart, but you know, three and a half years, I think you said two times, 18 months, uh, maybe there's hope for me yet in a singing, you'll be a good singer. Um, Duchy on the, on the, some of the sports references you've made, uh, Paul McGuire, we first connected, uh, I'm not gonna like disclose where you're from, but, uh, I saw he did come up and I know it all sorts of sports that drive to measure everything they can right on the field of the field. So let's imagine that you've done the best analysis, right? You're the most advanced data scientists schooled in the classics, as well as the modernist methods, the best tools you've made a beautiful analysis, beautiful dashboards. And now your coach just wants to put their favorite player on the game, despite what you're building to them. How do you deal with that kind of coaches? >>Yeah. Listen, this is a great question. I think for your data analytics strategy, but also for anyone listening and watching, who wants to just figure out how to drive a career forward? I would give the same advice. So the story you're talking about, indeed hockey, you can figure out where I'm from, but it's around the Ottawa senators, general manager. And he made a quote in an interview and he said, sometimes I want to punch my analytics, people in the head. Now I'm going to tell you, that's not a good culture for analytics. And he goes on to say, they tell me not to play this one player. This one player is very tough. You know, throws four or five hits a game. And he goes, I'd love my analytics people to get hit by bore a wacky and tell me how it feels. That's the player. >>Sure. I'm sure he hits hard, but here's the deal. When he's on the ice, the opposing team gets more shots on goal than the senators do on the opposing team. They score more goals, they lose. And so I think whenever you're trying to convince a movement forward, be it management, be it a project you're trying to fund. I always try to teach something that someone didn't previously know before and make them think, well, I never thought of it that way before. And I think the great opportunity right now, if you're trying to get moving in a data analytics strategy is around this post COVID era. You know, we've seen post COVID now really accelerate, or at least post COVID in certain parts of the world, but accelerate the appetite for digital transformation by about half a decade. Okay. And getting the data within your systems, as you digitize will give you all kinds of types of projects to make people think differently than the way they thought before. >>About data. I call this data exhaust. I'll give you a great example, Uber. I think we're all familiar with Uber. If we all remember back in the days when Uber would offer you search pricing. Okay? So basically you put Uber on your phone, they know everything about you, right? Who are your friends, where you going, uh, even how much batteries on your phone? Well, in a data science paper, I read a long time ago. They recognize that there was a 70% chance that you would accept a surge price. If you had less than 10% of your battery. So 10% of battery on your phone is an example of data exhaust all the lawns that you generate on your digital front end properties. Those are logs. You can take those together and maybe show executive management with data. We can understand why people abandoned their cart at the shipping phase, or what is the amount of shipping, which they abandoned it. When is the signal when our systems are about to go to go down. So, uh, I think that's a tremendous way. And if you look back to the sports, I mean the Atlanta Falcons NFL team, and they monitor their athletes, sleep performance, the Toronto Raptors basketball, they're running AI analytics on people's personalities and everything they tweet and every interview to see if the personality fits. So in sports, I think athletes are the most important commodity, if you will, or asset a yet all these teams are investing in analytics. So I think that's pretty telling, >>Okay, Paul, it looks like we're almost out of time. So in 30 seconds or less, what would you recommend to the data citizens out there? >>Okay. I'm going to give you a four tips in 30 seconds. Number one, remember learning never ends be curious forever. You'll drive your career. Number two, remember companies that invest in analytics and data, citizens outperform those that don't McKinsey says it's about 1.4 times across many KPIs. Number three, stop just collecting the dots and start connecting them with that. You need a strong governance strategy and that's going to help you for the future because the biggest thing in the future is not going to be about analytics, accuracy. It's going to be about analytics, explainability. So accuracy is no longer going to be enough. You're going to have to explain your decisions and finally stay positive and forever test negative. >>Love it. Thank you very much fall. Um, and for all the data seasons is out there. Um, when it comes down to access to data, it's more than just getting your hands on the data. It's also knowing what you can do with it, how you can do that and what you definitely shouldn't be doing with it. Uh, thank you everyone out there and enjoy your learning and interaction with the community. Stay healthy. Bye-bye.

>>Hey, welcome to the live panel. My name is Brett. I am your host, and indeed we are live. In fact, if you're curious about that, if you don't believe us, um, let's just show a little bit of the browser real quick to see. Yup. There you go. We're live. So, all right. So how this is going to work is I'm going to bring in some guests and, uh, in one second, and we're going to basically take your questions on the topic designer of the day, that continuous integration testing. Uh, thank you so much to my guests welcoming into the panel. I've got Carlos, Nico and Mandy. Hello everyone. >>Hello? All right, >>Let's go. Let's go around the room and all pretend we don't know each other and that the internet didn't read below the video who we are. Uh, hi, my name is Brett. I am a Docker captain, which means I'm supposed to know something about Docker. I'm coming from Virginia Beach. I'm streaming here from Virginia Beach, Virginia, and, uh, I make videos on the internet and courses on you to me, Carlos. Hey, >>Hey, what's up? I'm Carlos Nunez. I am a solutions architect, VMware. I do solution things with computers. It's fun. I live in Dallas when I'm moving to Houston in a month, which is where I'm currently streaming. I've been all over the Northeast this whole week. So, um, it's been fun and I'm excited to meet with all of you and talk about CIA and Docker. Sure. >>Yeah. Hey everyone. Uh, Nico, Khobar here. I'm a solution engineer at HashiCorp. Uh, I am streaming to you from, uh, the beautiful Austin, Texas. Uh, ignore, ignore the golden gate bridge here. This is from my old apartment in San Francisco. Uh, just, uh, you know, keeping that, to remember all the good days, um, that that lived at. But, uh, anyway, I work at Patrick Corp and I work on all things, automation, um, and cloud and dev ops. Um, and I'm excited to be here and Mandy, >>Hi. Yeah, Mandy Hubbard. I am streaming from Austin, Texas. I am, uh, currently a DX engineer at ship engine. Um, I've worked in QA and that's kind of where I got my, uh, my Docker experience and, um, uh, moving into DX to try and help developers better understand and use our products and be an advocate for them. >>Nice. Well, thank you all for joining me. Uh, I really appreciate you taking the time out of your busy schedule to be here. And so for those of you in chat, the reason we're doing this live, because it's always harder to do things live. The reason we're here is to answer a question. So we didn't come with a bunch of slides and demos or anything like that. We're here to talk amongst ourselves about ideas and really here for you. So we've, we obviously, this is about easy CII, so we're, we're going to try to keep the conversation around testing and continuous integration and all the things that that entails with containers. But we may, we may go down rabbit holes. We may go veer off and start talking about other things, and that's totally fine if it's in the realm of dev ops and containers and developer and ops workflows, like, Hey, it's, it's kinda game. >>And, uh, these people have a wide variety of expertise. They haven't done just testing, right? We, we live in a world where you all kind of have to wear many hats. So feel free to, um, ask what you think is on the top of your mind. And we'll do our best to answer. It may, might not be the best answer or the correct answer, but we're going to do our best. Um, well, let's get it start off. Uh, let's, let's get a couple of topics to start off with. Uh, th the, the easy CGI was my, one of my three ideas. Cause he's the, one of the things that I'm most excited about is the innovation we're seeing around easier testing, faster testing, automated testing, uh, because as much as we've all been doing this stuff for, you know, 15 years, since 20 years since the sort of Jenkins early days, um, it it's, it seems like it's still really hard and it's still a lot of work. >>So, um, let's go around the room real quick, and everybody can just kind of talk for a minute about like your experience with testing and maybe some of your pain points, like what you don't like about our testing world. Um, and we can talk about some pains, cause I think that will lead us to kind of talk about what, what are the things we're seeing now that might be better, uh, ideas about how to do this. I know for me, uh, testing, obviously there's the code part, but just getting it automated, but mostly getting it in the hands of developers so that they can control their own testing. And don't have to go talk to a person to run that test again, or the mysterious Jenkins platform somewhere. I keep mentioning Jenkins cause it's, it is still the dominant player out there. Um, so for me, I'm, I'm, I, I don't like it when I'm walking into a room and there's, there's only one or two people that know how the testing works or know how to make the new tests go into the testing platform and stuff like that. So I'm always trying to free those things so that any of the developers are enabled and empowered to do that stuff. So someone else, Carlos, anybody, um, >>Oh, I have a lot of opinions on that. Having been a QA engineer for most of my career. Um, the shift that we're saying is everyone is dev ops and everyone is QA. Th the issue I see is no one asked developers if they wanted to be QA. Um, and so being the former QA on the team, when there's a problem, even though I'm a developer and we're all running QA, they always tend to come to the one of the former QA engineers. And they're not really owning that responsibility and, um, and digging in. So that's kind of what I'm saying is that we're all expected to test now. And some people, well, some people don't know how it's, uh, for me it was kind of an intuitive skill. It just kind of fit with my personality, but not knowing what to look for, not knowing what to automate, not even understanding how your API end points are used by your front end to know what to test when a change is made. It's really overwhelming for developers. And, um, we're going to need to streamline that and, and hold their hands a little bit until they get their feet wet with also being QA. >>Right. Right. So, um, uh, Carlos, >>Yeah, uh, testing is like, Tesla is one of my favorite subjects to talk about when I'm baring with developers. And a lot of it is because of what Mandy said, right? Like a lot of developers now who used to write a test and say, Hey, QA, go. Um, I wrote my unit tests. Now write the rest of the test. Essentially. Now developers are expected to be able to understand how testing, uh, testing methodologies work, um, in their local environments, right? Like they're supposed to understand how to write an integration tasks federate into and tasks, a component test. And of course, how to write unit tests that aren't just, you know, assert true is true, right? Like more comprehensive, more comprehensive, um, more high touch unit tests, which include things like mocking and stubbing and spine and all that stuff. And, you know, it's not so much getting those tests. Well, I've had a lot of challenges with developers getting those tests to run in Docker because of usually because of dependency hell, but, um, getting developers to understand how to write tests that matter and mean something. Um, it's, it's, it can be difficult, but it's also where I find a lot of the enjoyment of my work comes into play. So yeah. I mean, that's the difficulty I've seen around testing. Um, big subject though. Lots to talk about there. >>Yeah. We've got, we've already got so many questions coming in. You already got an hour's worth of stuff. So, uh, Nico 81st thoughts on that? >>Yeah, I think I definitely agree with, with other folks here on the panel, I think from a, um, the shift from a skillset perspective that's needed to adopt the new technologies, but I think from even from, uh, aside from the organizational, um, and kind of key responsibilities that, that the new developers have to kinda adapt to and, and kind of inherit now, um, there's also from a technical perspective as there's, you know, um, more developers are owning the full stack, including the infrastructure piece. So that adds a lot more to the plate in Tim's oaf, also testing that component that they were not even, uh, responsible for before. Um, and, um, also the second challenge that, you know, I'm seeing is that on, you know, the long list of added, um, uh, tooling and, you know, there's new tool every other day. Um, and, um, that kind of requires more customization to the testing, uh, that each individual team, um, any individual developer Y by extension has to learn. Uh, so the customization, uh, as well as the, kind of the scope that had, uh, you know, now in conferences, the infrastructure piece, um, uh, both of act to the, to the challenges that we're seeing right now for, um, for CGI and overall testing, um, uh, the developers are saying, uh, in, in the market today. >>Yeah. We've got a lot of questions, um, about all the, all the different parts of this. So, uh, let me just go straight to them. Cause that's why we're here is for the people, uh, a lot of people asking about your favorite tools and in one of this is one of the challenges with integration, right? Is, um, there is no, there are dominant players, but there, there is such a variety. I mean, every one of my customers seems like they're using a different workflow and a different set of tools. So, and Hey, we're all here to just talk about what we're, what we're using, uh, you know, whether your favorite tools. So like a lot of the repeated questions are, what are your favorite tools? Like if you could create it from scratch, uh, what would you use? Pierre's asking, you know, GitHub actions sounds like they're a fan of GitHub actions, uh, w you know, mentioning, pushing the ECR and Docker hub and, uh, using vs code pipeline, I guess there may be talking about Azure pipelines. Um, what, what's your preferred way? So, does anyone have any, uh, thoughts on that anyone want to throw out there? Their preferred pipeline of tooling? >>Well, I have to throw out mine. I might as Jenkins, um, like kind of a honorary cloud be at this point, having spoken a couple of times there, um, all of the plugins just make the functionality. I don't love the UI, but I love that it's been around so long. It has so much community support, and there are so many plugins so that if you want to do something, you don't have to write the code it's already been tested. Um, unfortunately I haven't been able to use Jenkins in, uh, since I joined ship engine, we, most of our, um, our, our monolithic core application is, is team city. It's a dotnet application and TeamCity plays really well with.net. Um, didn't love it, uh, Ms. Jenkins. And I'm just, we're just starting some new initiatives that are using GitHub actions, and I'm really excited to learn, to learn those. I think they have a lot of the same functionality that you're looking for, but, um, much more simplified in is right there and get hubs. So, um, the integration is a lot more seamless, but I do have to go on record that my favorite CICT tools Jenkins. >>All right. You heard it here first people. All right. Anyone else? You're muted? I'm muted. Carlin says muted. Oh, Carla says, guest has muted themselves to Carlos. You got to unmute. >>Yes. I did mute myself because I was typing a lot, trying to, you know, try to answer stuff in the chat. And there's a lot of really dark stuff in there. That's okay. Two more times today. So yeah, it's fine. Yeah, no problem. So totally. And it's the best way to start a play more. So I'm just going to go ahead and light it up. Um, for enterprise environments, I actually am a huge fan of Jenkins. Um, it's a tool that people really understand. Um, it has stood the test of time, right? I mean, people were using Hudson, but 15 years ago, maybe longer. And, you know, the way it works, hasn't really changed very much. I mean, Jenkins X is a little different, but, um, the UI and the way it works internally is pretty familiar to a lot of enterprise environments, which is great. >>And also in me, the plugin ecosystem is amazing. There's so many plugins for everything, and you can make your own if you know, Java groovy. I'm sure there's a perfect Kotlin in there, but I haven't tried myself, but it's really great. It's also really easy to write, um, CIS code, which is something I'm a big fan of. So Jenkins files have been, have worked really well for me. I, I know that I can get a little bit more complex as you start to build your own models and such, but, you know, for enterprise enterprise CIO CD, if you want, especially if you want to roll your own or own it yourself, um, Jenkins is the bellwether and for very good reason now for my personal projects. And I see a lot on the chat here, I think y'all, y'all been agreed with me get hub actions 100%, my favorite tool right now. >>Um, I love GitHub actions. It's, it's customizable, it's modular. There's a lot of plugins already. I started using getting that back maybe a week after when GA and there was no documentation or anything. And I still, it was still my favorite CIA tool even then. Um, and you know, the API is really great. There's a lot to love about GitHub actions and, um, and I, and I use it as much as I can from my personal project. So I still have a soft spot for Travis CAI. Um, you know, they got acquired and they're a little different now trying to see, I, I can't, I can't let it go. I just love it. But, um, yeah, I mean, when it comes to Seattle, those are my tools. So light me up in the comments I will respond. Yeah. >>I mean, I, I feel with you on the Travis, the, I think, cause I think that was my first time experiencing, you know, early days get hub open source and like a free CIA tool that I could describe. I think it was the ammo back then. I don't actually remember, but yeah, it was kind of an exciting time from my experience. There was like, oh, this is, this is just there as a service. And I could just use it. It doesn't, it's like get hub it's free from my open source stuff. And so it does have a soft spot in my heart too. So yeah. >>All right. We've got questions around, um, cam, so I'm going to ask some questions. We don't have to have these answers because sometimes they're going to be specific, but I want to call them out because people in chat may have missed that question. And there's probably, you know, that we have smart people in chat too. So there's probably someone that knows the answer to these things. If, if it's not us, um, they're asking about building Docker images in Kubernetes, which to me is always a sore spot because it's Kubernetes does not build images by default. It's not meant for that out of the gate. And, uh, what is the best way to do this without having to use privileged containers, which privileged containers just implying that yeah, you, you, it probably has more privileges than by default as a container in Kubernetes. And that is a hard thing because, uh, I don't, I think Docker doesn't lie to do that out of the gate. So I don't know if anyone has an immediate answer to that. That's a pretty technical one, but if you, if you know the answer to that in chat, call it out. >>Um, >>I had done this, uh, but I'm pretty sure I had to use a privileged, um, container and install the Docker Damon on the Kubernetes cluster. And I CA I can't give you a better solution. Um, I've done the same. So, >>Yeah, uh, Chavonne asks, um, back to the Jenkins thing, what's the easiest way to integrate Docker into a Jenkins CICB pipeline. And that's one of the challenges I find with Jenkins because I don't claim to be the expert on Jenkins. Is there are so many plugins because of this, of this such a huge ecosystem. Um, when you go searching for Docker, there's a lot that comes back, right. So I, I don't actually have a preferred way because every team I find uses it differently. Um, I don't know, is there a, do you know if there's a Jenkins preferred, a default plugin? I don't even know for Docker. Oh, go ahead. Yeah. Sorry for Docker. And jacon sorry, Docker plugins for Jenkins. Uh, as someone's asking like the preferred or easy way to do that. Um, and I don't, I don't know the back into Jenkins that well, so, >>Well, th the new, the new way that they're doing, uh, Docker builds with the pipeline, which is more declarative versus the groovy. It's really simple, and their documentation is really good. They, um, they make it really easy to say, run this in this image. So you can pull down, you know, public images and add your own layers. Um, so I don't know the name of that plugin, uh, but I can certainly take a minute after this session and going and get that. Um, but if you really are overwhelmed by the plugins, you can just write your, you know, your shell command in Jenkins. You could just by, you know, doing everything in bash, calling the Docker, um, Damon directly, and then getting it working just to see that end to end, and then start browsing for plugins to see if you even want to use those. >>The plugins will allow more integration from end to end. Some of the things that you input might be available later on in the process for having to manage that yourself. But, you know, you don't have to use any of the plugins. You can literally just, you know, do a block where you write your shell command and get it working, and then decide if, for plugins for you. Um, I think it's always under important to understand what is going on under the hood before you, before you adopt the magic of a plugin, because, um, once you have a problem, if you're, if it's all a lockbox to you, it's going to be more difficult to troubleshoot. It's kind of like learning, get command line versus like get cracking or something. Once, once you get in a bind, if you don't understand the underlying steps, it's really hard to get yourself out of a bind, versus if you understand what the plugin or the app is doing, then, um, you can get out of situations a lot easier. That's a good place. That's, that's where I'd start. >>Yeah. Thank you. Um, Camden asks better to build test environment images, every commit in CII. So this is like one of those opinions of we're all gonna have some different, uh, or build on build images on every commit, leveraging the cash, or build them once outside the test pile pipeline. Um, what say you people? >>Uh, well, I I've seen both and generally speaking, my preference is, um, I guess the ant, the it's a consultant answer, right? I think it depends on what you're trying to do, right. So if you have a lot of small changes that are being made and you're creating images for each of those commits, you're going to have a lot of images in your, in your registry, right? And on top of that, if you're building those images, uh, through CAI frequently, if you're using Docker hub or something like that, you might run into rate limiting issues because of Docker's new rate, limiting, uh, rate limits that they put in place. Um, but that might be beneficial if the, if being able to roll back between those small changes while you're testing is important to you. Uh, however, if all you care about is being able to use Docker images, um, or being able to correlate versions to your Docker images, or if you're the type of team that doesn't even use him, uh, does he even use, uh, virgins in your image tags? Then I would think that that might be a little, much you might want to just have in your CIO. You might want to have a stage that builds your Docker images and Docker image and pushes it into your registry, being done first particular branches instead of having to be done on every commit regardless of branch. But again, it really depends on the team. It really depends on what you're building. It really depends on your workflow. It can depend on a number of things like a curse sometimes too. Yeah. Yeah. >>Once had two points here, you know, I've seen, you know, the pattern has been at every, with every, uh, uh, commit, assuming that you have the right set of tests that would kind of, uh, you would benefit from actually seeing, um, the, the, the, the testing workflow go through and can detect any issue within, within the build or whatever you're trying to test against. But if you're just a building without the appropriate set of tests, then you're just basically consuming almond, adding time, as well as all the, the image, uh, stories associated with it without treaty reaping the benefit of, of, of this pattern. Uh, and the second point is, again, I think if you're, if you're going to end up doing a per commit, uh, definitely recommend having some type of, uh, uh, image purging, um, uh, and, and, and garbage collection process to ensure that you're not just wasting, um, all the stories needed and also, um, uh, optimizing your, your bill process, because that will end up being the most time-consuming, um, um, you know, within, within your pipeline. So this is my 2 cents on this. >>Yeah, that's good stuff. I mean, those are both of those are conversations that could lead us into the rabbit hole for the rest of the day on storage management, uh, you know, CP CPU minutes for, uh, you know, your build stuff. I mean, if you're in any size team, more than one or two people, you immediately run into headaches with cost of CIA, because we have now the problem of tools, right? We have so many tools. We can have the CIS system burning CPU cycles all day, every day, if we really wanted to. And so you re very quickly, I think, especially if you're on every commit on every branch, like that gets you into a world of cost mitigation, and you probably are going to have to settle somewhere in the middle on, uh, between the budget, people that are saying you're spending way too much money on the CII platform, uh, because of all these CPU cycles, and then the developers who would love to have everything now, you know, as fast as possible and the biggest, biggest CPU's, and the biggest servers, and have the bills, because the bills can never go fast enough, right. >>There's no end to optimizing your build workflow. Um, we have another question on that. This is another topic that we'll all probably have different takes on is, uh, basically, uh, version tags, right? So on images, we, we have a very established workflow in get for how we make commits. We have commit shots. We have, uh, you know, we know get tags and there's all these things there. And then we go into images and it's just this whole new world that's opened up. Like there's no real consensus. Um, so what, what are your thoughts on the strategy for teams in their image tag? Again, another, another culture thing. Um, commander, >>I mean, I'm a fan of silver when we have no other option. Um, it's just clean and I like the timestamp, you know, exactly when it was built. Um, I don't really see any reason to use another, uh, there's just normal, incremental, um, you know, numbering, but I love the fact that you can pull any tag and know exactly when it was created. So I'm a big fan of bar, if you can make that work for your organization. >>Yep. People are mentioned that in chat, >>So I like as well. Uh, I'm a big fan of it. I think it's easy to be able to just be as easy to be able to signify what a major changes versus a minor change versus just a hot fix or, you know, some or some kind of a bad fix. The problem that I've found with having teams adopt San Bernardo becomes answering these questions and being able to really define what is a major change, what is a minor change? What is a patch, right? And this becomes a bit of an overhead or not so much of an overhead, but, uh, uh, uh, a large concern for teams who have never done versioning before, or they never been responsible for their own versioning. Um, in fact, you know, I'm running into that right now, uh, with, with a client that I'm working with, where a lot, I'm working with a lot of teams, helping them move their applications from a legacy production environment into a new one. >>And in doing so, uh, versioning comes up because Docker images, uh, have tags and usually the tax correlate to versions, but some teams over there, some teams that I'm working with are only maintaining a script and others are maintaining a fully fledged JAK, three tier application, you know, with lots of dependencies. So telling the script, telling the team that maintains a script, Hey, you know, you should use somber and you should start thinking about, you know, what's major, what's my number what's patch. That might be a lot for them. And for someone or a team like that, I might just suggest using commit shots as your versions until you figure that out, or maybe using, um, dates as your version, but for the more for the team, with the larger application, they probably already know the answers to those questions. In which case they're either already using Sember or they, um, or they may be using some other version of the strategy and might be in December, might suit them better. So, um, you're going to hear me say, it depends a lot, and I'm just going to say here, it depends. Cause it really does. Carlos. >>I think you hit on something interesting beyond just how to version, but, um, when to consider it a major release and who makes those decisions, and if you leave it to engineers to version, you're kind of pushing business decisions down the pipe. Um, I think when it's a minor or a major should be a business decision and someone else needs to make that call someone closer to the business should be making that call as to when we want to call it major. >>That's a really good point. And I add some, I actually agree. Um, I absolutely agree with that. And again, it really depends on the team that on the team and the scope of it, it depends on the scope that they're maintaining, right? And so it's a business application. Of course, you're going to have a product manager and you're going to have, you're going to have a product manager who's going to want to make that call because that version is going to be out in marketing. People are going to use it. They're going to refer to and support calls. They're going to need to make those decisions. Sember again, works really, really well for that. Um, but for a team that's maintaining the scripts, you know, I don't know, having them say, okay, you must tell me what a major version is. It's >>A lot, but >>If they want it to use some birds great too, which is why I think going back to what you originally said, Sember in the absence of other options. I think that's a good strategy. >>Yeah. There's a, there's a, um, catching up on chat. I'm not sure if I'm ever going to catch up, but there's a lot of people commenting on their favorite CII systems and it's, and it, it just goes to show for the, the testing and deployment community. Like how many tools there are out there, how many tools there are to support the tools that you're using. Like, uh, it can be a crazy wilderness. And I think that's, that's part of the art of it, uh, is that these things are allowing us to build our workflows to the team's culture. Um, and, uh, but I do think that, you know, getting into like maybe what we hope to be at what's next is I do hope that we get to, to try to figure out some of these harder problems of consistency. Uh, one of the things that led me to Docker at the beginning to begin with was the fact that it wa it created a consistent packaging solution for me to get my code, you know, off of, off of my site of my local system, really, and into the server. >>And that whole workflow would at least the thing that I was making at each step was going to be the same thing used. Right. And that, that was huge. Uh, it was also, it also took us a long time to get there. Right. We all had to, like Docker was one of those ones that decade kind of ideas of let's solidify the, enter, get the consensus of the community around this idea. And we, and it's not perfect. Uh, you know, the Docker Docker file is not the most perfect way to describe how to make your app, but it is there and we're all using it. And now I'm looking for that next piece, right. Then hopefully the next step in that, um, that where we can all arrive at a consensus so that once you hop teams, you know, okay. We all knew Docker. We now, now we're all starting to get to know the manifests, but then there's this big gap in the middle where it's like, it might be one of a dozen things. Um, you know, so >>Yeah, yeah. To that, to that, Brett, um, you know, uh, just maybe more of a shameless plug here and wanting to kind of talk about one of the things that I'm on. So excited, but I work, I work at Tasha Corp. I don't know anyone, or I don't know if many people have heard of, um, you know, we tend to focus a lot on workflows versus technologies, right. Because, you know, as you can see, even just looking at the chat, there's, you know, ton of opinions on the different tooling, right. And, uh, imagine having, you know, I'm working with clients that have 10,000 developers. So imagine taking the folks in the chat and being partnered with one organization or one company and having to make decisions on how to build software. Um, but there's no way you can conversion one or, or one way or one tool, uh, and that's where we're facing in the industry. >>So one of the things that, uh, I'm pretty excited about, and I don't know if it's getting as much traction as you know, we've been focused on it. This is way point, which is a project, an open source project. I believe we got at least, uh, last year, um, which is, it's more of, uh, it's, it is aim to address that really, uh, uh, Brad set on, you know, to come to tool to, uh, make it extremely easy and simple. And, you know, to describe how you want to build, uh, deploy or release your application, uh, in, in a consistent way, regardless of the tools. So similar to how you can think of Terraform and having that pluggability to say Terraform apply or plan against any cloud infrastructure, uh, without really having to know exactly the details of how to do it, uh, this is what wave one is doing. Um, and it can be applied with, you know, for the CIA, uh, framework. So, you know, task plugability into, uh, you know, circle CEI tests to Docker helm, uh, Kubernetes. So that's the, you know, it's, it's a hard problem to solve, but, um, I'm hopeful that that's the path that we're, you know, we'll, we'll eventually get to. So, um, hope, you know, you can, you can, uh, see some of the, you know, information, data on it, on, on HashiCorp site, but I mean, I'm personally excited about it. >>Yeah. Uh I'm to gonna have to check that out. And, um, I told you on my live show, man, we'll talk about it, but talk about it for a whole hour. Uh, so there's another question here around, uh, this, this is actually a little bit more detailed, but it is one that I think a lot of people deal with and I deal with a lot too, is essentially the question is from Cameron, uh, D essentially, do you use compose in your CIO or not Docker compose? Uh, because yes I do. Yeah. Cause it, it, it, it solves so many problems am and not every CGI can, I don't know, there's some problems with a CIO is trying to do it for me. So there are pros and cons and I feel like I'm still on the fence about it because I use it all the time, but also it's not perfect. It's not always meant for CIA. And CIA sometimes tries to do things for you, like starting things up before you start other parts and having that whole order, uh, ordering problem of things anyway. W thoughts and when have thoughts. >>Yes. I love compose. It's one of my favorite tools of all time. Um, and the reason why it's, because what I often find I'm working with teams trying to actually let me walk that back, because Jack on the chat asked a really interesting question about what, what, what the hardest thing about CIS for a lot of teams. And in my experience, the hardest thing is getting teams to build an app that is the same app as what's built in production. A lot of CGI does things that are totally different than what you would do in your local, in your local dev. And as a result of that, you get, you got this application that either doesn't work locally, or it does work, but it's a completely different animal than what you would get in production. Right? So what I've found in trying to get teams to bridge that gap by basically taking their CGI, shifting the CII left, I hate the shift left turn, but I'll use it. >>I'm shifting the CIO left to your local development is trying to say, okay, how do we build an app? How do we, how do we build mot dependencies of that app so that we can build so that we can test our app? How do we run tests, right? How do we build, how do we get test data? And what I found is that trying to get teams to do all this in Docker, which is normally a first for a lot of teams that I'm working with, trying to get them all to do all of this. And Docker means you're running Docker, build a lot running Docker, run a lot. You're running Docker, RM a lot. You ran a lot of Docker, disparate Docker commands. And then on top of that, trying to bridge all of those containers together into a single network can be challenging without compose. >>So I like using a, to be able to really easily categorize and compartmentalize a lot of the things that are going to be done in CII, like building a Docker image, running tests, which is you're, you're going to do it in CII anyway. So running tests, building the image, pushing it to the registry. Well, I wouldn't say pushing it to the registry, but doing all the things that you would do in local dev, but in the same network that you might have a mock database or a mock S3 instance or some of something else. Um, so it's just easy to take all those Docker compose commands and move them into your Yammel file using the hub actions or your dankest Bob using Jenkins, or what have you. Right. It's really, it's really portable that way, but it doesn't work for every team. You know, for example, if you're just a team that, you know, going back to my script example, if it's a really simple script that does one thing on a somewhat routine basis, then that might be a lot of overhead. Um, in that case, you know, you can get away with just Docker commands. It's not a big deal, but the way I looked at it is if I'm, if I'm building, if I build something that's similar to a make bile or rate file, or what have you, then I'm probably gonna want to use Docker compose. If I'm working with Docker, that's, that's a philosophy of values, right? >>So I'm also a fan of Docker compose. And, um, you know, to your point, Carlos, the whole, I mean, I'm also a fan of shifting CEI lift and testing lift, but if you put all that logic in your CTI, um, it changes the L the local development experience from the CGI experience. Versus if you put everything in a compose file so that what you build locally is the same as what you build in CGI. Um, you're going to have a better experience because you're going to be testing something more, that's closer to what you're going to be releasing. And it's also very easy to look at a compose file and kind of, um, understand what the dependencies are and what's happening is very readable. And once you move that stuff to CGI, I think a lot of developers, you know, they're going to be intimidated by the CGI, um, whatever the scripting language is, it's going to be something they're going to have to wrap their head around. >>Um, but they're not gonna be able to use it locally. You're going to have to have another local solution. So I love the idea of a composed file use locally, um, especially if he can Mount the local workspace so that they can do real time development and see their changes in the exact same way as it's going to be built and tested in CGI. It gives developers a high level of confidence. And then, you know, you're less likely to have issues because of discrepancies between how it was built in your local test environment versus how it's built in NCI. And so Docker compose really lets you do all of that in a way that makes your solution more portable, portable between local dev and CGI and reduces the number of CGI cycles to get, you know, the test, the test data that you need. So that's why I like it for really, for local dev. >>It'll be interesting. Um, I don't know if you all were able to see the keynote, but there was a, there was a little bit, not a whole lot, but a little bit talk of the Docker, compose V two, which has now built into the Docker command line. And so now we're shifting from the Python built compose, which was a separate package. You could that one of the challenges was getting it into your CA solution because if you don't have PIP and you got down on the binary and the binary wasn't available for every platform and, uh, it was a PI installer. It gets a little nerdy into how that works, but, uh, and the team is now getting, be able to get unified with it. Now that it's in Golang and it's, and it's plugged right into the Docker command line, it hopefully will be easier to distribute, easier to, to use. >>And you won't have to necessarily have dependencies inside of where you're running it because there'll be a statically compiled binary. Um, so I've been playing with that, uh, this year. And so like training myself to do Docker going from Docker dash compose to Docker space, compose. It is a thing I I'm almost to the point of having to write a shell replacement. Yeah. Alias that thing. Um, but, um, I'm excited to see what that's going, cause there's already new features in it. And it, these built kit by default, like there's all these things. And I, I love build kit. We could make a whole session on build kit. Um, in fact there's actually, um, maybe going on right now, or right around this time, there is a session on, uh, from Solomon hikes, the seat, uh, co-founder of Docker, former CTO, uh, on build kit using, uh, using some other tool on top of build kit or whatever. >>So that, that would be interesting for those of you that are not watching that one. Cause you're here, uh, to do a check that one out later. Um, all right. So another good question was caching. So another one, another area where there is no wrong answers probably, and everyone has a different story. So the question is, what are your thoughts on CII build caching? There's often a debate between security. This is from Quentin. Thank you for this great question. There's often a debate between security reproducibility and build speeds. I haven't found a good answer so far. I will just throw my hat in the ring and say that the more times you want to build, like if you're trying to build every commit or every commit, if you're building many times a day, the more caching you need. So like the more times you're building, the more caching you're gonna likely want. And in most cases caching doesn't bite you in the butt, but that could be, yeah, we, can we get the bit about that? So, yeah. Yeah. >>I'm going to quote Carlos again and say, it depends on, on, you know, how you're talking, you know, what you're trying to build and I'm quoting your colors. Um, yeah, it's, it's got, it's gonna depend because, you know, there are some instances where you definitely want to use, you know, depends on the frequency that you're building and how you're building. Um, it's you would want to actually take advantage of cashing functionalities, um, for the build, uh, itself. Um, but if, um, you know, as you mentioned, there could be some instances where you would want to disable, um, any caching because you actually want to either pull a new packages or, um, you know, there could be some security, um, uh, disadvantages related to security aspects that would, you know, you know, using a cache version of, uh, image layer, for example, could be a problem. And you, you know, if you have a fleet of build, uh, engines, you don't have a good grasp of where they're being cashed. We would have to, um, disable caching in that, in that, um, in those instances. So it, it would depend. >>Yeah, it's, it's funny you have that problem on both sides of cashing. Like there are things that, especially in Docker world, they will cash automatically. And, and then, and then you maybe don't realize that some of that caching could be bad. It's, it's actually using old, uh, old assets, old artifacts, and then there's times where you would expect it to cash, that it doesn't cash. And then you have to do something extra to enable that caching, especially when you're dealing with that cluster of, of CIS servers. Right. And the cloud, the whole clustering problem with caching is even more complex, but yeah, >>But that's, that's when, >>Uh, you know, ever since I asked you to start using build kits and able to build kit, you know, between it's it's it's reader of Boston in, in detecting word, you know, where in, in the bill process needs to cash, as well as, uh, the, the, um, you know, the process. I don't think I've seen any other, uh, approach there that comes close to how efficient, uh, that process can become how much time it can actually save. Uh, but again, I think, I think that's, for me that had been my default approach, unless I actually need something that I would intentionally to disable caching for that purpose, but the benefits, at least for me, the benefits of, um, how bill kit actually been processing my bills, um, from the builds as well as, you know, using the cash up until, you know, how it detects the, the difference in, in, in the assets within the Docker file had been, um, you know, uh, pretty, you know, outweigh the disadvantages that it brings in. So it, you know, take it each case by case. And based on that, determine if you want to use it, but definitely recommend those enabling >>In the absence of a reason not to, um, I definitely think that it's a good approach in terms of speed. Um, yeah, I say you cash until you have a good reason not to personally >>Catch by default. There you go. I think you catch by default. Yeah. Yeah. And, uh, the trick is, well, one, it's not always enabled by default, especially when you're talking about cross server. So that's a, that's a complexity for your SIS admins, or if you're on the cloud, you know, it's usually just an option. Um, I think it also is this, this veers into a little bit of, uh, the more you cash the in a lot of cases with Docker, like the, from like, if you're from images and checked every single time, if you're not pinning every single thing, if you're not painting your app version, you're at your MPN versions to the exact lock file definition. Like there's a lot of these things where I'm I get, I get sort of, I get very grouchy with teams that sort of let it, just let it all be like, yeah, we'll just build two images and they're totally going to have different dependencies because someone happened to update that thing and after whatever or MPM or, or, and so I get grouchy about that, cause I want to lock it all down, but I also know that that's going to create administrative burden. >>Like the team is now going to have to manage versions in a very much more granular way. Like, do we need to version two? Do we need to care about curl? You know, all that stuff. Um, so that's, that's kind of tricky, but when you get to, when you get to certain version problems, uh, sorry, uh, cashing problems, you, you, you don't want those set those caches to happen because it, if you're from image changes and you're not constantly checking for a new image, and if you're not pinning that V that version, then now you, you don't know whether you're getting the latest version of Davion or whatever. Um, so I think that there's, there's an art form to the more you pen, the less you have, the less, you have to be worried about things changing, but the more you pen, the, uh, all your versions of everything all the way down the stack, the more administrative stuff, because you're gonna have to manually change every one of those. >>So I think it's a balancing act for teams. And as you mature, I to find teams, they tend to pin more until they get to a point of being more comfortable with their testing. So the other side of this argument is if you trust your testing, then you, and you have better testing to me, the less likely to the subtle little differences in versions have to be penned because you can get away with those minor or patch level version changes. If you're thoroughly testing your app, because you're trusting your testing. And this gets us into a whole nother rant, but, uh, yeah, but talking >>About penny versions, if you've got a lot of dependencies isn't that when you would want to use the cash the most and not have to rebuild all those layers. Yeah. >>But if you're not, but if you're not painting to the exact patch version and you are caching, then you're not technically getting the latest versions because it's not checking for all the time. It's a weird, there's a lot of this subtle nuance that people don't realize until it's a problem. And that's part of the, the tricky part of allow this stuff, is it, sometimes the Docker can be almost so much magic out of the box that you, you, you get this all and it all works. And then day two happens and you built it a second time and you've got a new version of open SSL in there and suddenly it doesn't work. Um, so anyway, uh, that was a great question. I've done the question on this, on, uh, from heavy. What do you put, where do you put testing in your pipeline? Like, so testing the code cause there's lots of types of testing, uh, because this pipeline gets longer and longer and Docker building images as part of it. And so he says, um, before staging or after staging, but before production, where do you put it? >>Oh man. Okay. So, um, my, my main thought on this is, and of course this is kind of religious flame bait, so sure. You know, people are going to go into the compensation wrong. Carlos, the boy is how I like to think about it. So pretty much in every stage or every environment that you're going to be deploying your app into, or that your application is going to touch. My idea is that there should be a build of a Docker image that has all your applications coded in, along with its dependencies, there's testing that tests your application, and then there's a deployment that happens into whatever infrastructure there is. Right. So the testing, they can get tricky though. And the type of testing you do, I think depends on the environment that you're in. So if you're, let's say for example, your team and you have, you have a main branch and then you have feature branches that merged into the main branch. >>You don't have like a pre-production branch or anything like that. So in those feature branches, whenever I'm doing CGI that way, I know when I freak, when I cut my poll request, that I'm going to merge into main and everything's going to work in my feature branches, I'm going to want to probably just run unit tests and maybe some component tests, which really, which are just, you know, testing that your app can talk to another component or another part, another dependency, like maybe a database doing tests like that, that don't take a lot of time that are fascinating and right. A lot of would be done at the beach branch level and in my opinion, but when you're going to merge that beach branch into main, as part of a release in that activity, you're going to want to be able to do an integration tasks, to make sure that your app can actually talk to all the other dependencies that it talked to. >>You're going to want to do an end to end test or a smoke test, just to make sure that, you know, someone that actually touches the application, if it's like a website can actually use the website as intended and it meets the business cases and all that, and you might even have testing like performance testing, low performance load testing, or security testing, compliance testing that would want to happen in my opinion, when you're about to go into production with a release, because those are gonna take a long time. Those are very expensive. You're going to have to cut new infrastructure, run those tests, and it can become quite arduous. And you're not going to want to run those all the time. You'll have the resources, uh, builds will be slower. Uh, release will be slower. It will just become a mess. So I would want to save those for when I'm about to go into production. Instead of doing those every time I make a commit or every time I'm merging a feature ranch into a non main branch, that's the way I look at it, but everything does a different, um, there's other philosophies around it. Yeah. >>Well, I don't disagree with your build test deploy. I think if you're going to deploy the code, it needs to be tested. Um, at some level, I mean less the same. You've got, I hate the term smoke tests, cause it gives a false sense of security, but you have some mental minimum minimal amount of tests. And I would expect the developer on the feature branch to add new tests that tested that feature. And that would be part of the PR why those tests would need to pass before you can merge it, merge it to master. So I agree that there are tests that you, you want to run at different stages, but the earlier you can run the test before going to production. Um, the fewer issues you have, the easier it is to troubleshoot it. And I kind of agree with what you said, Carlos, about the longer running tests like performance tests and things like that, waiting to the end. >>The only problem is when you wait until the end to run those performance tests, you kind of end up deploying with whatever performance you have. It's, it's almost just an information gathering. So if you don't run your performance test early on, um, and I don't want to go down a rabbit hole, but performance tests can be really useless if you don't have a goal where it's just information gap, uh, this is, this is the performance. Well, what did you expect it to be? Is it good? Is it bad? They can get really nebulous. So if performance is really important, um, you you're gonna need to come up with some expectations, preferably, you know, set up the business level, like what our SLA is, what our response times and have something to shoot for. And then before you're getting to production. If you have targets, you can test before staging and you can tweak the code before staging and move that performance initiative. Sorry, Carlos, a little to the left. Um, but if you don't have a performance targets, then it's just a check box. So those are my thoughts. I like to test before every deployment. Right? >>Yeah. And you know what, I'm glad that you, I'm glad that you brought, I'm glad that you brought up Escalades and performance because, and you know, the definition of performance says to me, because one of the things that I've seen when I work with teams is that oftentimes another team runs a P and L tests and they ended, and the development team doesn't really have too much insight into what's going on there. And usually when I go to the performance team and say, Hey, how do you run your performance test? It's usually just a generic solution for every single application that they support, which may or may not be applicable to the application team that I'm working with specifically. So I think it's a good, I'm not going to dig into it. I'm not going to dig into the rabbit hole SRE, but it is a good bridge into SRE when you start trying to define what does reliability mean, right? >>Because the reason why you test performance, it's test reliability to make sure that when you cut that release, that customers would go to your site or use your application. Aren't going to see regressions in performance and are not going to either go to another website or, you know, lodge in SLA violation or something like that. Um, it does, it does bridge really well with defining reliability and what SRE means. And when you have, when you start talking about that, that's when you started talking about how often do I run? How often do I test my reliability, the reliability of my application, right? Like, do I have nightly tasks in CGI that ensure that my main branch or, you know, some important branch I does not mean is meeting SLA is meeting SLR. So service level objectives, um, or, you know, do I run tasks that ensure that my SLA is being met in production? >>Like whenever, like do I use, do I do things like game days where I test, Hey, if I turn something off or, you know, if I deploy this small broken code to production and like what happens to my performance? What happens to my security and compliance? Um, you can, that you can go really deep into and take creating, um, into creating really robust tests that cover a lot of different domains. But I liked just using build test deploy is the overall answer to that because I find that you're going to have to build your application first. You're going to have to test it out there and build it, and then you're going to want to deploy it after you test it. And that order generally ensures that you're releasing software. That works. >>Right. Right. Um, I was going to ask one last question. Um, it's going to have to be like a sentence answer though, for each one of you. Uh, this is, uh, do you lint? And if you lint, do you lent all the things, if you do, do you fail the linters during your testing? Yes or no? I think it's going to depend on the culture. I really do. Sorry about it. If we >>Have a, you know, a hook, uh, you know, on the get commit, then theoretically the developer can't get code there without running Melinta anyway, >>So, right, right. True. Anyone else? Anyone thoughts on that? Linting >>Nice. I saw an additional question online thing. And in the chat, if you would introduce it in a multi-stage build, um, you know, I was wondering also what others think about that, like typically I've seen, you know, with multi-stage it's the most common use case is just to produce the final, like to minimize the, the, the, the, the, the image size and produce a final, you know, thin, uh, layout or thin, uh, image. Uh, so if it's not for that, like, I, I don't, I haven't seen a lot of, you know, um, teams or individuals who are actually within a multi-stage build. There's nothing really against that, but they think the number one purpose of doing multi-stage had been just producing the minimalist image. Um, so just wanted to kind of combine those two answers in one, uh, for sure. >>Yeah, yeah, sure. Um, and with that, um, thank you all for the great questions. We are going to have to wrap this up and we could go for another hour if we all had the time. And if Dr. Khan was a 24 hour long event and it didn't sadly, it's not. So we've got to make room for the next live panel, which will be Peter coming on and talking about security with some developer ex security experts. And I wanted to thank again, thank you all three of you for being here real quick, go around the room. Um, uh, where can people reach out to you? I am, uh, at Bret Fisher on Twitter. You can find me there. Carlos. >>I'm at dev Mandy with a Y D E N D Y that's me, um, >>Easiest name ever on Twitter, Carlos and DFW on LinkedIn. And I also have a LinkedIn learning course. So if you check me out on my LinkedIn learning, >>Yeah. I'm at Nicola Quebec. Um, one word, I'll put it in the chat as well on, on LinkedIn, as well as, uh, uh, as well as Twitter. Thanks for having us, Brett. Yeah. Thanks for being here. >>Um, and, and you all stay around. So if you're in the room with us chatting, you're gonna, you're gonna, if you want to go to see the next live panel, I've got to go back to the beginning and do that whole thing, uh, and find the next, because this one will end, but we'll still be in chat for a few minutes. I think the chat keeps going. I don't actually know. I haven't tried it yet. So we'll find out here in a minute. Um, but thanks you all for being here, I will be back a little bit later, but, uh, coming up next on the live stuff is Peter Wood security. Ciao. Bye.

>> Narrator: From around the globe, It's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Hello everybody, welcome back to IBM Think 2021. This is the cubes ongoing coverage. We go out to the events. Of course, in this case we do so virtually, to extract the signal from the noise. My name is Dave Vellante and now we're going to talk about the intersection of business success and sustainability. It's hot topic. We have a great panel for you. With me are Ally Karmali, Sustainability and Climate Practice Lead at IBM Canada. Lucy Baunay is a Senior Consultant in Customer Experience and Sustainability Strategy, also from IBM Canada, and Keric Morris, Executive Partner, Enterprise Strategy Global Energy and Sustainability Lead, IBM UK. Folks, welcome to the panel. Welcome to the cube. Thanks for coming on. >> Thank you. >> Thank you. >> Maybe Lucy, you could kick it off to talk about what is sustainability and how has it all of a sudden become such a hot topic amongst leadership? >> Yeah, sure. So first off, it's actually my pleasure that sustainability has finally become a trendy topic, and is now a key imperative in the business world. The pandemic really played a role in it, as it made people realize that there's an intricate link between global scale events, like the climate crisis, leading to the acceleration of viruses spreads and their own personal health or of their business. So sustainability really means that you're addressing the needs of the present without compromising the needs of future generations. To do so, companies use different frameworks and standards including ESG, standing for environmental, social, and governance criteria to really assess their progress on their journey to sustainability. It comes with many metrics that they track, or should track and choose to disclose for the greater benefit of all. One prerequisite I'd say to really building a successful sustainable company, is really the need for a new form of leadership style. One that is purpose driven, that really focuses on doing well, while doing the right thing. And I mean, you might need examples here to illustrate what I'm saying. You could take a Unilever, and the really radical transformation of the Palm oil industry they're leading. If Unilever did nothing, serious risk would really be posed in a few years on their whole business. So, the company has started working with all actors across its value chain, from training farmers, to building alliances with competitors and stakeholders. And you know, what Unilever is doing for the palm industry is actually cementing its reputation as an innovator. And they're already reaping the benefits of having, you know, being first movers. >> Dave: Right. Kerick, Lucy talked about an imperative, so take away there, it's not a checkbox, it's something that's sort of designed in. I wonder if you could, you could talk to that. >> Yeah. And I mean, sustainability at the end of the day now, it's built into every decision every process, every system, and you know, and leadership role in that space is about, you know, kind of developing new corporate strategies, new cultures, new approaches, which are around, you know, actually how do I sort of do this? This it's a real paradigm shift. It's not, it's not something you add to your business. It's something that needs to be core to your business. And then, you know, and that's requiring us to kind of re-imagining how we sort of go to work, how we do business, the processes, developing new products, leveraging new technologies. It's putting all of those pieces in and sort of making them work. And, and the key part of that is how do you do this in a way where we're not forcing people to make a choice between sustainability and profitability. Sustainability and, you know, and a way of quality of life. So there's how you kind of build that into kind of the core products and services. And again, use that ingenuity to kind of develop those, and sort of develop the components that you need to as part of that process. The other part of this is then sort of getting into, well actually from a leadership perspective, now how do I then change, and the way that I sort of work with with partners, with suppliers, with competitors. So it's, it's really fundamentally changing the way the business itself works as well. >> Dave: Yeah. Thank you. You know, Ally I, when I talk about ESG, I sometimes tongue in cheek say Milton Friedman's probably rolling over in his grave, cause he's the economist who said that the only job of a company is to make profits and drive shareholder value. And so that's a, I mean, that's a historical challenge, but there's, there's actually a business case for this. It's actually a good business. And we'll talk about that, but maybe you could address some of the challenges that organizations are facing to really lean in and address ESG. >> Yeah, that's right. You know, there are a lot of components that go into this. So then, as Lucy mentioned and Keric mentioned, the complexities that come with that, are a lot. They're significant. And so I'd say that the first challenge that I see is in regards to the alignment and integration of sustainability strategy within the organization's business model. So if we take a look at the typical life cycle, which includes sourcing, production, operations, distribution, and then end of life and recycling, each of these components must consider the conduits for driving positive social impact and environmental stewardship. But that also, as you said, drives opportunity and economic benefits for the organization. So these are components that could fall into three categories. The first one is what is the journey to net zero look like for you? How will I transform my operations, my strategy, my business models to achieve a net zero emission? What is circularity in the context of my business? How do I orchestrate for zero waste and include reuse regenerative processes restorative processes? And then how do I build in principles of sustainability into the design so that I integrate those components into the ways of working within this new world of sustainability that we're seeing? It's also the what and the how coming together to enable long-term value creation for the company. The second challenge that I see is around the performance monitoring and management. And as they say, you can't manage what you can't measure. And so many organizations might not have the complexity roadmap laid out for the systems and data that's required in order to enable a transparent and quality reporting. We think about data and knowing what you have, versus what you don't, data management, capturing and transforming that data, integrating that data in a way that has a simple but effective use of methodologies, as well as benchmarking. And then having a reporting system that allows you to see everything, almost a control tower of your E, your S, and your G. And then finally we see sustainability has become a board level priority. It is a hot topic, but it's not always properly understood below the board level. So senior executives sometimes approach the conformance to change in the way that we normally approach things like regulation. But I think in this case, it's quite, it's quite different. Because it is a bit of a shift to the person with a purpose, as the center leaders must lead, they must hire they must think design and share. You must meet the (indistinct) paradigms for diversity inclusion. And I think at the same time, encourage diversity, but also divergence where it needs to be. They have to have the head space to accept the truth, and the collaboration with all stakeholders. So I think there are ways for companies to do this and, and for them to be successful. And I think IBM is one of them >> Dave: For sure. And I think Keric, that sort of leads me to it from what Ally was saying about, you know, IBM, big company, has a big ecosystem. There are other large leaders within industry's that can leverage ecosystems, and then maybe set the tone and show the, point the way for the long tail of smaller companies. But maybe you could talk about that ecosystem flywheel. >> What we are also seeing is it's actually sort of quite a lot of differences between the way organizations are addressing this. And you are seen as leaders in this space. Then you ask these people, you're taking a stand around these components and actually trying to shape just not only what they do, but also what organizations do around them. Now, I mean, you know, and if you kind of look at this, there's almost kind of three categories to that, there are organizations that are sort of seeing this as an existential change, you know, if I'm looking at sort of mining, I'm looking at oil and gas I'm looking at travel and transport. Now what you're still seeing there is a fundamental shift in their business. That's requiring them to rethink how they do things in a very structured and actually quite an extended way. You know, if I'm looking at other organizations like retailers, it's actually a little less of of an existential change, it's more of an incremental one. But even so they still have to change all that they do, but they can do it in a, probably a more, staged approach. And then you've got influencers around that as well. So governments, financial services, players, et cetera, who are sort of shaping the agenda and who need help, and support around and thinking through how they kind of measure the change, how they sort of make sure the funding is seeing the right things, how they make, how they make sure they're actually still getting returns they expect. And actually, you know, the sustainability components are actually being driven by that. But I think that's, that's kind of sort sort of where an organization like IBM comes in. There's a lot of technical change in here. There's a lot of data change in here. And actually, these are the sorts of things that, you know, from a sustainability perspective are going to help to drive this in a more seamless and an achievable way, if you will. And so there's an awful lot that we're looking to try to do to enable that quickly to kind of take things off the shelf to, to rapidly test and to actually sort of show people both what, what can be done and the value that you then can create by sort of going down the sustainability journey. >> Okay, got it. Thank you. And Lucy, you touched on some examples at a high level in your opening remarks, and I'm interested in, kind of the starting point that you see companies, you know, taking and what's the right regime? I mean, you've got to put somebody, if somebody's going to be accountable for the measurements and the, and the, the cultural changes, but, but where do we start? >> Right. So one starting point is definitely to be looking at your data right? And, you know, it's, it's really tempting to forget when you're building products, or you're creating experiences, it's tempting to forget thinking about their repercussions on the environment, on communities, and on society. Their impact is, is made invisible for the sake of immediate user satisfaction, and short-term business value. And, you know, although 60% of executives consider sustainability to be an essential competitive advantage, 80% actually, other products ecological impacts are locked in at the design phase. So that's why, you know, with a team of four IBM superstars we've created the sustainable design thinking toolkit that was just launched and is in the process being integrated into the official IBM design thinking site. And that's really a great start, because it's meant to help design thinking practitioners take responsibility on making that impact visible from the very start of the process. And we've used it with multiple clients and for internal products and it's really helped infuse a sustainable mindset throughout the workflows. And, and actually from the very, very start of it. One recent example was in the CPG industry where we've applied our new sustainable design thinking activities to the problem at hand, to get consumers to recycle more by enhancing their recycling experience. And what it allowed us to do, is really to make sure that, you know, the prioritization process, as the first ideas that emerged, included sustainable value into the mix, so that the impact on the planet and communities wasn't a blind spot anymore. >> Dave : So, thank you for that Lucy, Keric I wonder, you know Lucy was talking about, you start with the data and that, that's cool. Sometimes, I get worried though, there's going to be analysis by paralysis and overthinking the strategy. Are there ways to, are there ways to get in and, and take smaller bites and iterate? What do, what are your thoughts on that? >> Yeah, I mean, I think there absolutely are, you know, with, with lots of organizations, they really have to kind of feel their way into this, this, this new approach. You know, you actually kind of have to learn both what sustainability means, but also sort of what it can deliver. So, you know, usually what we're sort of seeing is those organizations will start off with things which are under their control. So how can I change my manufacturing processes? How can I change some of the internal components of what it is that we do, to make them more sustainable, to, to reduce waste, to reduce sort of, kind of, the energy usage components, which associates with it, and those, that's quite a nice controlled starting point, using, you know, leveraging things like sort of manufacturing 4.0 intelligence processes, you know, (indistinct) sorry, Maximo Asset Management type approaches. The second step we're sort of seeing with lots of organizations. Is that they're then moving into, kind of their own ecosystem if you will. So, you know, actually, how do I manage my supply chain more effectively? How do I drive transparency? How do I, sort of also, drive efficiency and carbon management from that sort of perspective? but also, how do I sort of highlight the sustainable gains I'm making on my products and get those messages to customers and highlights of what we're doing with both new products and services, but also, with existing products and services. And then sort of your, your, kind of your final piece, then actually, this depends on, and it kind of goes back to what I was saying before, about what industry you're in, but, you know, a lot of industries are also having to, kind of, face the challenge of, I need to change fundamentally. You know, the business I'm in is not, not going to work the way it works in a sustainable world. So, so actually, how do I kind of build an ecosystem based approach? How do I kind of work with other partners? How do I kind of work with suppliers? How do I work with competitors? And actually, how do I build something at scale around a platform? And it will just be able to deliver these types of things? And at IBM, we've been kind of creating some of those, those platforms, and then scaling them quite rapidly, sort of across a variety of different sectors. >> Dave: Yeah, and that's where you're going to see the measurable impact. Ally, do you have a framework for what's, what a successful outcome looks like? Are there, are there companies that are sort of models of success? I mean, I think IBM is one of them, but maybe you could talk to that. >> Yeah. There are definitely companies to emulate, and companies have really started to think about the, the connection point between the value that's driven by their business model, as well as the effort and the impact that's being driven by their ESG, their ESG focus. And so, while there might be components of success, I think getting, getting it all together and all right is going to take time. And it's going to be a bit of a sequence. But a bit of a thought experiment, If you could sit into a boardroom, or at a senior level executive discussion, when you think about success, would you hear things or discussions around how the company is building the environmental and social inputs to its products and services? And what does that sound like? Are they tangible? Are they realistic? And what are the methods and the tools that they're using? Would you hear conversations about how the company is evaluating or infusing sustainability across the value chain from procurement all the way to end of life? Or how about the participation of the company into other ecosystems that's driving value into other industries? And we see the force multiplier effect that comes with that when, when companies partner together, because we are either vendors or providers, or consumers of every other product or service. And then I think lastly, would organizations start to think about how to generate value closer to home and how that value can be driven into communities, into where their employees are based. And those elements really, really improve the social elements. So what say lasts is there are elements of what good and success looks like when it comes to sustainability, but I think organizations can set their targets and meet industry benchmarks and frameworks which already exist and are really well established, but continuously increase their own targets to set better and more ambitious goals for themselves, to move beyond, to leverage technology, and be innovative and, and apply these, these tools and best practices in order to get there. And I think, and I think, I think we'll get there over time. So I'm really encouraged by the progress that we're seeing and, and, we hope at IBM to help accelerate that journey. >> Thank you. And Lucy, one of the things I'm excited about is the tech because this is where I think, you know, this business does meet sustainability. I mean, green tech, E.V. I mean, if I'm a nation, I want to be on top of that. If I'm a company, I think there's opportunities for invention and innovation. Can you talk about some of those innovative techs that we're likely to see? >> Right. Well, yeah, to piggy back on what Alex was just saying, and, you know, I think success can, can come in very different ways and forms, you know, be it creating entirely new business models, like, you know, some clients we help in the oil and gas industry, taking really bold commitments to shift to energy, electric energy. Or, you know significantly cutting costs such as, you know, those brands in the CPG industry that are doing amazing things to optimize their supply chains and make them more efficient, more transparent, more secure. Or, you know also protecting brand reputation and mitigating risks, or gaining market share by creating, differentiating value. You might've heard about L'Oreal taking really bold moves, and switching all their products to 95% renewable plant sources and circular processes. You know, it, it, can also be about capturing value, by charging a premium for sustainable products. Think about Tesla or whole foods, for example. I mean there's so many great examples out there already. >> Dave: Excellent. So we got to wrap it, so my last question, and I want to start with Ally, and then we'll go to Keric, and then Lucy, you can bring us home. Talk about why, you were talking about ESG reporting and transparency, and how it's, you know, great for the future and the economy and so forth. Why is this not going to be a fad? Why is it going to be sustainable? The sustainability, the sustainability of sustainable. Ally, please kick it off. And then we'll go to Keric and then Lucy >> You're right. You know, this is a big change for organizations. And I think naturally they're, you know, they're corporate social responsibility and, and, sustainability reports have really been externally focused. And I think that has been a great step in the right direction, but I think what's happening now is, is this convergence of sustainable material and transparent reporting, that is equivalent to material financial reporting that we're seeing. And, and eventually I think the end goal would be to be able to read a sustainable report and understand, and quantify, as well as qualify how much impact is an organization making year to year? And what are some of the initiatives that's driving what we have begun to see as a sustainable business strategy that is also a competitive advantage for organizations. So I think, the, the benefit in the long-term is going to create a lot of value for not just the shareholder but for the stakeholders like employees, like the communities in which these companies operate, like regulatory agencies, as well as municipal, federal governments, and state governments. So I think this is a step in the right direction for providing a very clear direction on their sustainable initiatives. >> Dave: Thank you. Thank you, Ally. Keric, could you weigh in here please? >> Yeah, I mean, I agree with all Ally said there, and I think with the stakeholders, the end of the day, this, this is a collective responsibility. You know, we have one planet, one rock we all live on, and we all need to be part of the process of actually sort of making it, making a change. And, and, you can't, you can't sort of change what you can't measure. So they're kind of holding people to account being able to share sort of the data that we've got, making sure everybody understands what the position is, how we're contributing and the role that we're actually still playing, is going to be an incredibly important part of collectively coming together, then making this change happen, and making this change happen quickly. Which is what it needs to do. >> Dave: Hey, Lucy, your passion shines through here. So it's appropriate that you, you close it out. >> Yeah, well, it all comes down to, you know, do you want your business to still exist in a hundred years from now? And you know, it does require courage and determination, but we all have it in ourselves. You know, trying to find the ways that we can change things for the greater good, find the energy in yourself to inspire others to act. That's why, you know, leaders with purpose and ingenuity are so, so, important today. Thank you. >> Folks, thanks so much for the perspectives you guys doing a great work. Really appreciate your time on the Cube today. >> Thank you. >> Thanks for having us. >> All right. It's been our pleasure and thank you for watching. This is the Cube's coverage of IBM Think 2021, the virtual edition. We'll be right back. (cheerful music)

>>thank you so much that sake for inviting me to the Entity Research Summit. And I'm really excited to talk to all of them today. So I will be talking about achieving indistinguishability obfuscation from well founded assumptions. And this is really the result of a wonderful two year collaboration with But now it's standing. Graduate student I use chain will be graduating soon on my outstanding co author, Rachel Lynde from the University of Washington. So let me jump right into it. We all know that constructing indistinguishable the obfuscation. Constructing Io has been perhaps the most consequential open problem in the foundations of photography. For several years now, they've seen over 100 papers written that show how to use Iot to achieve a number of remarkable cryptographic goals. Um, that really expand the scope of cryptography in addition to doing just remarkable, really interesting new things. Unfortunately, however, until this work, I told the work I'm about to tell you about all known constructions of Iove. All required new hardness, assumptions, heart assumptions that were designed specifically to prove that Iowa secure. And unfortunately, uh, this has a torture of history. And many of the assumptions were actually broken, which led to just a lot of doubt and uncertainty about the status of Iot, whether it really exists or doesn't exist. And the work I'm about to tell you about today changes that state of affairs in the continental way in that we show how to build io from the combination of four well established topographic assumptions. Okay, let me jump right into it and tell you how we do it. So before this work that I'm about to tell you about over the last two years with Rachel and Ayush, we actually constructed a whole sequence of works that have looked at this question. And what we showed was that if we could just build a certain special object, then that would be sufficient for constructing Io, assuming well established assumptions like L W E P R g s and M C zero and the 68 assumption of a violin. Your mouths. Okay, So what is this object? The object first starts with a P. R G and >>S zero. In other words, of trg with constant locality that stretches end bits of seed to M bits of output where am is ended one plus Epsilon for any constant Epsilon zero. Yes, but in addition to this prg, we also have these l w we like samples. So as usual, we have an elder Bluey Secret s which is random vector z b two k, where K is the dimension of the secret, which is much smaller than any way also have this public about vectors ai which are also going to be okay. And now what is given out is are the elderly samples where the error is this X I that is just brilliant value. Uh, where these excise air Also the input to our prg. Okay, unfortunately, we needed to assume that these two things together, this y and Z together is actually pseudo random. But if you think about it, there is some sort of kind of strange assumption that assumes some kind of special leakage resilience, property of elderly, we where elderly samples, even with this sort of bizarre leakage on the errors from all debris, is still surround or still have some surrounding properties. And unfortunately, we had no idea how to prove that. And we still don't have any idea how to prove this. Actually, So this is just a assumption and we didn't know it's a new assumption. So far, it hasn't been broken, but that's pretty much it. That's all we knew about it. Um and that was it. If we could. If this is true, then we could actually build. I'll now to actually use this object. We needed additional property. We needed a special property that the output of this prg here can actually be computed. Every single bit of the output could be computed by a polynomial over the public. Elder Louise samples Why? And an additional secret w with the property that this additional secret w is actually quite small. It's only excise em to the one minus delta or some constant delta gradients. Barroso polynomial smaller from the output of the prg. And crucially, the degree of this polynomial is on Lee to its violin e er can this secret double that's where the bottle in your mouth will come. Okay. And in fact, this part we did not approve. So in this previous work, using various clever transformations, we were able to show that in fact we are able to construct this in a way to this Parliament has existed only degree to be short secret values. Double mhm. So now I'm gonna show you how using our new ideas were actually gonna build. That's a special object just like this from standard assumptions. We're just gonna be sufficient for building io, and we're gonna have to modify it a little bit. Okay? One of the things that makes me so excited is that actually, our ideas are extremely simple. I want to try to get that across today. Thanks. So the first idea is let's take thes elder movie samples that we have here and change them up a little bit when it changed them up. Start before I get to that in this talk, I want you to think of K the dimension of the secret here as something very small. Something like end of the excellent. That's only for the stock, not for the previous work. Okay. All right. So we have these elderly samples right from the previous work, but I'm going to change it up instead of computing them this way, as shown in the biggest slide on this line. Let's add some sparse hair. So let's replace this error x i with the air e i plus x I where e is very sparse. Almost all of these IIs or zero. But when the I is not zero is just completely random in all of Z, pizza just completely destroys all information. Okay, so first I just want to point out that the previous work that I already mentioned applies also to this case. So if we only want to compute P R g of X plus E, then that can still be computer the polynomial. That's degree to in a short W that's previous work the jail on Guess work from 2019. I'm not going to recall that you don't have time to tell you how you do it. It's very simple. Okay, so why are we doing this? Why are we adding the sparse error? The key observation is that even though I have changed the input of the PRG to the X Plus E because he is so sparse, prg of explosive is actually the same as P. R. G of X. In almost every outlet location. It's only a tiny, tiny fraction of the outputs that are actually corrupted by the sparse Arab. Okay, so for a moment Let's just pretend that in fact, we knew how to compute PRGF X with a degree to polynomial over a short seeking. We'll come back to this, I promise. But suppose for a moment we actually knew how to compute care to your ex, Not just scared of explosive in that case were essentially already done. And the reason is there's the L. P n over zp assumption that has been around for many years, which says that if you look at these sort of elderly like samples ai from the A, I s but plus a sparse air e I where you guys most zero open when it's not serious, completely random then In fact, these samples look pseudo random. They're indistinguishable from a I r r. I just completely uniform over ZP, okay? And this is a long history which I won't go because I don't have time, but it's just really nice or something. Okay, so let's see how we can use it. So again, suppose for the moment that we were able to compute, not just appeared you've explosive but appeared to you that well, the first operation that since we're adding the sparse R E I This part the the L P N part here is actually completely random by the LP an assumption so by L P and G. P, we can actually replace this entire term with just all right. And now, no, there is no more information about X present in the samples, The only place where as is being used in the input to the prg and as a result, we could just apply to sit around this of the prg and say this whole thing is pseudo random and that's it. We've now proven that this object that I wanted to construct it is actually surrounded, which is the main thing that was so bothering us and all this previous work. Now we get it like that just for the snap of our fingers just immediately from people. Okay, so the only thing that's missing that I haven't told you yet is Wait, how do we actually compute prg attacks? Right? Because we can compute p r g of X plus e. But there's still gonna be a few outputs. They're gonna be wrong. So how can we correct those few corrupted output positions to recover PRGF s? So, for the purpose of this talks because I don't have enough time. I'm gonna make sort of a crazy simplifying assumption. Let's just assume that in fact, Onley one out the position of P r g of X plus e was correct. So it's almost exactly what PR gox. There's only one position in prg of Ecstasy which needs to be corrected to get us back to PR gox. Okay, so how can we do that? The idea is again really, really simple. Okay, so the output of the PRG is an M. Becker and so Dimension and Becker. But let's actually just rearrange that into a spirit of them by spirit of them matrix. And as I mentioned, there's only one position in this matrix that actually needs to be corrected. So let's make this correction matrix, which is almost everywhere. Zero just in position. I j it contains a single correction factor. Why, right? And if you can add this matrix to prg of explosive, then we'll get PR dribbles. Okay, so now the Onley thing I need to do is to compute this extremely sparse matrix. And here the observation was almost trivia. Just I could take a spirit of em by one maker That just has why in position I and I could take a one by spirit of them matrix. I just have one in position J zero everywhere else. If I just take the tensor product was music the matrix product of these two of these two off this column vector in a row vector. Then I will get exactly this correction matrix. Right? And note that these two vectors that's called them you and be actually really, really swamped their only spirit of n dimensional way smaller than them. Right? So if I want to correct PRGF Expo see, all I have to do is add you, Tenzer V and I can add the individual vectors u and V to my short secret w it's still short. That's not gonna make W's any sufficiently bigger. And you chancery is only a degree to computation. So in this way, using a degree to computation, we can quickly, uh, correct our our computation to recover prg events. And now, of course, this was oversimplifying situation, uh, in general gonna have many more areas. We're not just gonna have one error, like as I mentioned, but it turns out that that is also easy to deal with, essentially the same way. It's again, just a very simple additional idea. Very, very briefly. The idea is that instead of just having one giant square to them by sort of a matrix, you can split up this matrix with lots of little sub matrices and with suitable concentration bound simple balls and pins arguments we can show that we could never Leslie this idea this you Tenzer v idea to correct all of the remaining yet. Okay, that's it. Just, you see, he's like, three simple >>ah ha moments. What kind of all that it took, um, that allowed >>us to achieve this result to get idol from standard assumptions. And, um, of course I'm presenting to you them to you in this very simple way. We just these three little ideas of which I told you to. Um, but of course, there were only made possible because of years of struggling with >>all the way that didn't work, that all that struggling and mapping out all the ways didn't work >>was what allowed us toe have these ideas. Um, and again, it yields the first I'll construction from well established cryptographic assumptions, namely Theo Elgon, assumption over zp learning with errors, assumption, existence of PR GS and then zero that is PR juice with constant death circuits and the SX th assumption over by linear notes, all of which have been used many years for a number of other applications, including such things as publicly inversion, something simple public inversion that's the That's the context in which the assumptions have been used so very far from the previous state of affairs where we had assumptions that were introduced on Lee Professor constructing my own. And with that I will conclude, uh and, uh, thank you for your attention. Thanks so much.

>> Narrator: From around the globe, It's theCube, with digital coverage, of Actifio data-driven 2020, brought to you by Actifio. >> Welcome back, I'm Stu Miniman, and this is theCube coverage of Actifio Data-driven 2020. Really excited to, dig into a fun topic. I have a Cube alumni with us he is a DevOps author, and researcher Gene Kim. Unicorn Project is the most recent, Gene, great to see you, thanks so much for joining us. >> Stu, great to see you again, here at the Actifio conference, this is all fantastic. >> Yeah, so your new book, it was much awaited out there, you know, Unicorn's always discussed out there, but you know, the Phoenix Project, as I said, is really this seminal, book when people say, What is that DevOps thing and how do I do it? So, why don't you give us a little bit as to The Unicorn Project, why is it important? Why we're excited to dig into this and, we'll, we'll tie it into the discussion we're having here for the next normal, at Actifio. >> For sure, yeah, in fact, yeah. As you might have heard in the keynote address, you know, the what, what vexed me, after the Phoenix project came out in 2013 is that there is still looming problems that still remain, seven years after the Phoenix project was written. And, you know, these problems I think are very important, around you and what does it really take to enable developers to truly be productive, instead of being locked in a tundra of technical debt. Two is, you know, how do we unlock truly the power of data so that we can help everyone make better decisions, whether it's a developer, or anyone, within the business units and the organizations that we serve. And then three is like, what are really the behaviors that we need from leadership to make these amazing transformations possible? And so The Unicorn Project really is, the fifth project retold, but instead of through the eyes of Ops leadership, is told through the eyes, of a phenomenal developer. And so it was amazing to revisit the, the Phoenix project universe, I in the same timeline, but told from a different point of view. And it was such a fun project to work on, just because, you know, to relive the story, and just expose all these other problems, not happening, not on the side, but from, the development and data side. >> Yeah. They've always these characters in there that, I know I personally, and many people I talked to can, you know, really associate with, there was a return of certain characters, quite prominent, like Brent, you know, don't be the bottleneck in your system. It's great, if you're a fighter firefighter, and can solve everything, but if everything has to come through you, you know, Pedro is always going off, he's getting no sleep and, you know, you'd just get stressed out. You talked a bit more, about the organization and there are the five ideals in the book. So maybe if you can, you know, strongly recommend, of course, anybody at ending active you, got a copy of the books they'll be able to read the whole thing, but, you know, give us the bumper sticker on some of those key learnings. >> Yeah, for sure, yeah. So the five ideals represents five ideas, I think are just very important, for everyone, the organization, serves, especially leadership. The first ideal is locality and simplicity. In other words, when you need to get something done, we should be able to get it done within our team, without having to do a lot of communication coordination, with people outside of our team. The worst, the most horrible feeling is that in order, to do a small little thing, you actually have, to have a, coordinated action that spans 15 teams, right. And that's why you can't get anything done, right? And so that's so much the hallmark of large complex organizations. The second ideal is that what I think the outcomes are, which is focused flow and joy, you know, I've not just now started to for the first time in 20 years, self identify, not as an ops person, but as a developer. And, I really now understand, why we got into technology in the first place. This so that we can solve the business problem at hand unencumbered by minute share. And that allows for a sense of focus flow and even joy. And I love how Dr. Mihaly Csikszentmihalyi, describe it. He said, flow is a state that we feel when we love our work, so much that we lose track of time, and maybe even sense of self. And so I think we all in technology understand, you know, that that is how it is on the best of days and how terrible it is, you know, when we don't have that sense of flow. Third ideal is improvement of daily work, being even more important than daily work itself. The notion is greatness is never free, we must create it and must prioritize it, for the psychological safety. And the fifth is customer focus. So those are all the things I think are so important, for modern leaders, because it really defines the future of work. >> Yeah, we love that flow and it happens otherwise we're stuck, in that waiting place as you quoted Dr. Csi. So one of my favorite books there, there also. So Gene, for this audience here, there was, you know, yes, CICD is wonderful and I need to be able to move and ship fast, but the real transformational power, for that organization was unlocking the value of data, which is, I think something that everybody here can. So maybe to talk a little bit about that you know, we, there there's, we've almost talked too much, you know, data is the new oil and things like that, but it's that, you know, that allowing everybody to tap in and leverage, you know, real time what's happening there were just at the early parts of the industry being able to unlock that future. >> Oh yeah, I love that phrase. Data is new oil, especially since oil, you know, the last 50 years, the standard Port 500 was dominated by, you know, resource extraction oil company and so forth. And now that is no longer true, it's dominated by the tech giants. And, Columbia there was a Columbia journalism review article that said, data's not only the new oil, is really the new soil. And for me, you know, my area of passion for the last seven years has been studying the DevOps enterprise community where, we're taking all the learnings that were really pioneered by the tech giants, Facebook, Amazon, Netflix, Google, Microsoft, and seeing how they're being adopted by the largest, most complex organizations on the planet, the best known brands across every industry vertical. And it's so true that, you know, where the real learning gets exploited right, is through data. I realized, this is how we get to know our customers better. This is how we understand their wants and needs. This is how we test, and make offers to them to see if they like it or not to see if they value it or not. And, and so for me, one of the best examples, of this was, the target transformation and Adidas how it was just an amazing example of, to what links they went to, to liberate developers from, being shackled by ancient systems of records, data warehouses, and truly enabled developers to get access to the data they need modify it, even delete information, all without having to be dependent on, you know, integration teams that were essentially holding them hostage for six to nine months. And, these programs really enable some of the most strategic programs at their organizations, you know, enabling hundreds of projects over the years. So, I think that is really, just showing to what extent, the value that is created by unlocking data for individuals. And sorry Stu, one more thing that I'm just always dazzled by my friend, Chris Berg. He told me that, somewhere between a third and a half of all company employees use data in their daily work. They either use data or manipulate data as part of the daily work, which, you know, that, population is actually larger than the number of developers in an organization. So it just shows you how big this problem is, and how much value we can create by addressing this problem. >> Well, it's interesting if it's only a third, we still have work to do. What we've been saying for years is, you know, when you talk about digital transformation, the thing that separates those that have transformed and those that haven't is data needs to be at the core. I just can't be doing things the way I was or doing things off intuition, you know, being data-driven, I'm sure you know, the same Gene, if you're not, if you don't have data, you know, you're just some other person with an opinion. >> Yeah, yeah. That's it this is a great point. And in Risto Siilasmaa's amazing book, Transforming Nokia, I mean, he was, he said exactly that. And he said something that was even more astonishing. He said, there's not only at the core, but data also has to be at the edges. You know, he was describing at Amazon, anyone can do an experiment @booking.com. Anyone can do an experiment to see, if they can create value for the customer. They don't need approvals from, committees or their manager. This is something that is really truly part of everyone's daily work. And so, to me, that was a huge aha moment that says, you know, to what degree, you know. Our cultures need to change so that we can not only, use data, but also create learnings and create new data, you know, that the rest of the organization can learn from as well. >> Yeah. One of the other things I definitely, you know, felt in your book, you synthesize so much of the learnings that you've had over the years from like the DevOps enterprise summit. The question I have for you is, you know, you hear some of these, you know, great stories, but the question is, our companies, are they moving fast enough? Have they transformed the entire business or have they taken, you know, we've got one slice of the business that is kind of modernized and we're going to get to the other 30 pieces along the way, but you know, there's wholesale change, you know, 2020 has had such a big impact. What's your thoughts on, you know, how we are doing in the enterprise on pace of change these days? >> That's a great question. I mean, I think some people, when they ask me, you know, how far are we into kind of total adoption of DevOps? It's a newer better way of working. And I would say probably somewhere between 5 and 7%, right, and the math I would take them through is, you know, there are about 20 million developers on the planet of which at best, I think, a million of them are working in a DevOps type way. But yet now that's only growing. I think it was an amazing presentation at DevOps surprise summit in London that was virtual from nationwide building society, the largest organization of its kind. It's a large financially mutually owned organization for housing in the UK. And, they touched about how, you know, post COVID post lockdown suddenly they found themselves able to do them reckless things that would have normally taken four years, in four weeks. And I think that's what almost every organization is learning these days is, when survival is at stake, you know, we can throw the rules out of the window, right. And do things in a way that are safe and responsible, but, you know, create satisfy the business urgent needs, like, you know, provisioning tens of thousand people to work from home safely. You know, I think the shows, I think it's such a powerful proof point of what technology can do when it is unleashed from, you know, perhaps unnecessarily burdensome rules and process. And I think the other point I would make Stu is that, what has been so rewarding is the population of these technology leaders presenting at DevOps enterprise, they're all being promoted, they're all being, being given new responsibilities because they, are demonstrating that they have the best longterm interest of the organization at heart. And, they're being given even more responsibilities because, to make a bigger impact through the organization. So I'm incredibly optimistic about the direction we're heading and even the pace we're going at. >> Well, Gene definitely 2020 has put a real highlight on how fast things have changed, not just work from home, but, but the homeschooling, you know, telehealth, there are so many things out there where there was no choice, but to move forward. So the, the second presentation you participated in was talking about that next normal. So give us a little bit of, you know, what does that mean? You know, what, what we should be looking at going forward? >> Yeah, it was great to catch up with my friend Paul Forte, who I've known for many, many years, and now, now a VP of sales at the Actifio and yeah, I think it is amazing that academic Dr. Colada Perez, she said, you know, in every turning point, you know, where, there's such a the stage for decades of economic prosperity usually comes, by something exactly like what we're going through now, a huge economic recession or depression, following a period of intense re regulations there's new, technology that's unlocking, you know, new ways of working. And she pointed exactly to what's happening in the Covid pandemic in terms of, how much, the way we're working is being revolutionized, not by choice, but out of necessity. And, you know, as she said, you know, we're now learning to what degree we can actually do our daily work without getting on airplanes or, you know, meeting people in person. So, I'm a hue, I have so many friends in the travel industry, right. I think we all want normalcy to return, but I think we are learning, you know, potentially, you know, there are more efficient ways to do things, that don't require a day of travel for a couple hour meeting and day to return, right. So, yeah, I think this is being demonstrated. I think this will unlock a whole bunch of ways of interacting that will create efficiency. So I don't think we're going, as you suggested, right. There will be a new normal, but the new normal is not going to be the same as your old normal. And I think it will be, in general for the better. >> So, Gene, you, you've gone to gotten to see some of the transformation happening in the organizations when it comes to developers, you know, the, the DevOps enterprise summit, the, the state of DevOps, you know. I think five years ago, we knew how important developers were, but there was such a gap between, well, the developers are kind of in the corner, they don't pay for anything. They're not tied to the enterprise. And today it feels like we have a more cohesive story that there, there is that if you put in The Unicorn Project, it's, you know, business and IT, you know. IT, and the developers can actually drive that change and the survival of the business. So, you know, are we there yet success or net developers now have a seat at the table? Or, you know, what do you see on that, that we still need to do? >> Yeah, I think we're still, I mean, I think we're getting there, we're closer than ever. And as my friend, Chris O'Malley the CEO of the famously resurgent mainframe vendor Compuware said, you know, it is, everyone is aware that you can't do any major initiatives these days without some investment in technology, right? In fact, you can't invest in anything without technology. So I think that is now better understood than ever. And, yeah, just the digital, it's a whole digital disruption, I think is really, no one needs to be convinced that if we organize large complex organizations, don't change, they're at a risk of, you know, being decimated by the organizations that can change using an exploiting technology, you know, to their benefit and to the other person's detriment. So, and that primarily comes through software and who creates software developers. So I, by the way, I love the Stripe it was a CFO for Stripe who said, the largest, constraint for them is, and their peers is not access to capital, it is access development talent. I think when you have CFOs talking like that, right. It does says it's suggested something really has changed in the economic environment that we all compete in. >> So, I mentioned that on the research side, one of the things I've loved reading over the years is that, fundamental discussion that, going faster does not mean, that I am sacrificing security, or, you know, the product itself, you know, in the last couple of years, it's, you know, what separates those really high performing companies, and, you know, just kind of the middle of the ground. So, what, what, what advice would you give out there, to make sure that I'm moving my company more along to those high performing methods. >> Yeah, but just to resonate with that, I was interviewing a friend of mine, Mike Nygaard, long time friend of mine, and we were talking on and we were recalling the first time we both heard the famous 2009 presentation doing 10 deploys a day, every day at flicker, by John Allspaw and Paul Hammond. And we were both incredulous, right there? We thought it was irresponsible reckless, and maybe even immoral what they were doing, because, you know, I think most organizations were doing three a year, and that was very problematic. How could one do 10 deploys a day. And I think, what we now know, with the size of evidence, especially through the state of DevOps research, is that, you know, for six years, 35,000 plus respondents, the only way that you can be reliable, and secure, is to do smaller deployments more frequently, right? It makes you, be able to respond quicker in the marketplace, allows you to have better stability and reliability in the operational environment, allows you to be more secure. It allows you to be able to, you know, increase market share, increase productivity, and, you know, have happier employees. So, you know, at this point, I think the research is so decisive, that, you know, we can, as a whole book accelerate, that really makes the case for that, that this is something that I now have moral certainty or even absolute certainty oh, right. It's, you know, self evident to me, and it, I think we should have confidence that that really is true. >> Wonderful work, Gene, thanks so much for giving us the update. I really appreciate it, some really good sessions here in Actifio, as well as the book. Thanks so much, great to talk to you. >> Stu is always a pleasure to see you again, and thank you so much. >> Alright, that's our coverage from Actifio Data-driven, be sure to check out thecube.net for all of the, on demand content, as well as, as I said, if you were part of the show, definitely recommend reading Gene's book, The Unicorn Project. I'm Stu Miniman. And thank you for watching the cube. (soft upbeat music)

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation LeBron welcome to the cube studio I'm John Ferrier here in Palo Alto in our remote coverage of the tech industry we are in our quarantine crew here getting all the stories in the technology industry from all the thought leaders and all the newsmakers we've got a great story here about data data compliance and really about the platforms around how enterprises are using data I've got two great guests and some news to announce Kieran our CEO is the vice president of business development with elation and William Murphy vice president of technology alliances of big ID got some interesting news a integration partnership between the two companies really kind of compelling especially now as people have to look at the cloud scale what's happening in our world certainly in the new realities of kovin 19 and going forward the role of data new kinds of applications and the speed and agility are gonna require more and more automation more reality around making sure things are in place so guys thanks for coming on appreciate it Kieran William thanks for joining me thank you thank you so let's take a step back elation you guys have been on the cube many times we've been following you guys been a leader and Enterprise catalog a new approach it's a real new technology approach and methodology and team approach to building out the data catalogues so talk about the Alliance here why what's the news why you guys in Creighton is integration partnership well let me start and thank you for having us today you know as you know elation launched the data catalog a category seven years ago and even today we're acknowledging the leader as a leader in that space you know and but we really began with the core belief that ultimately data management will be drive driven more and more by business demand and less by information suppliers so you know another way to think about that is you know how people behave with data will drive how companies manage data so our philosophy put very simply is to start with people and not first not data and our customers really seem to agree with this approach and we've got close to 200 brands using our data you know our tool every single day to drive vibrant data communities and and foster a real data culture in the environment so one of the things that was really exciting to us is the in been in data privacy by large corporate customers to get their arms around this and you know we really strive to improve our ability to use the tool inside you know these enterprises across more use cases so the partnership that we're announcing with big ID today is really you know Big Ideas the leading modern data intelligence platform for privacy and what we're trying to do is to bring bring a level of integration between our two technologies so that enterprises in better manage and scale their their data privacy compliance capability William talked about big ID what you guys are doing you guys also have a date intelligence platform we've been covering gdpr for a very long time I once called I won't say it again because it wasn't really that complimentary but the reality has sit in and they and the users now understand more than ever privacy super important companies have to deal with this you guys have a solution take a minute to explain big-big ID and what you guys are doing yeah absolutely so our founders Demetri Shirota and Nimrod Beck's founded big idea in 2016 Sam you know gdpr was authored and the big reason there is that data changed and how companies and enterprises doubled data was changing pretty much forever that profound change meant that the status quo could no longer exist and so privacy was gonna have to become a day-to-day reality to these enterprises but what big ID realized is that to start to do to do anything with privacy you actually have to understand where your data is what it is and whose it is and so that's really the genesis of what dimitri nimrod created which which is a privacy centric data discovery and intelligence platform that allows our enterprise customers and we have over 70 customers in the enterprise space many within the Fortune hundred to be able to find classify and correlate sensitive data as they defined it across data sources whether its own Prem or in the cloud and this gives our users and kind of unprecedented ability to look into their data to get better visibility which if both allows for collaboration and also allows for real-time decision-making a big place with better accuracy and confidence that regulations are not being broken and that customers data is being treated appropriately great I'm just reading here from the release that I want to get you guys thoughts and unpack some of the concepts on here but the headline is elation strengthens privacy capabilities with big ID part nur ship empowering organizations to mitigate risks delivering privacy aware data use and improved adherence to data privacy regulations it's a mouthful but the bottom line is is that there's a lot of stuff to that's a lot of complexity around these rules and these platforms and what's interesting you mentioned discovery the enterprise discovery side of the business has always been a complex nightmare I think what's interesting about this partnership from my standpoint is that you guys are bringing an interface into a complex platform and creating an easy abstraction to kind of make it usable I mean the end of the day you know we're seeing the trends with Amazon they have Kendre which they announced and they're gonna have a ship soon fast speed of insights has to be there so unifying data interfaces with back-end is really what seems to be the pattern is that the magic going on here can you guys explain what's going on with this and what's the outcome gonna be for customers yeah I guess I'll kick off and we'll please please chime in I think really there's three overarching challenges that I think enterprises are facing is they're grappling with these regulations as as we'll talked about you know number one it's really hard to both identify and classify private data right it's it's not as easy as it might sound and you know we can talk a little bit more about that it's also very difficult to flag at the point of analysis when somebody wants to find information the relevant policies that might apply to the given data that they're looking to it to run an analysis on and lastly the enterprise's are constantly in motion as enterprises change and by new businesses and enter new markets and launch new products these policies have to keep up with that change and these are real challenges to address and you know with Big Idea halation we're trying to really accelerate that compliance right with the the you know the combination of our tools you know reduce the the cost and complexity of compliance and fundamentally keep up through a single interface so that users can know what to do with data at the point of consumption and I think that's the way to think about it well I don't know if you want to add something to that absolutely I think when Karen and I have been working on this for actually many months at this point but most companies don't have a business plan of just saying let's store as much data as possible without getting anything out of it but in order to get something out of it the ability to find that data rapidly and then analyze it so that decision makers make up-to-date decisions is pretty vital a lot of these things when they have to be done manually take a long time they're huge business issues there and so the ability to both automate data discovery and then cataloging across elation and big ID gives those decision makers whether the data steward the data analyst the chief data officer an ability to really dive deeper than they have previously with better speed you know one of the things that we've been talking about for a long time with big data as these data links and they're fairly easy to pull I mean you can put a bunch of data into a corpus and you you act on them but as you start to get across these silos there's a need for you know getting a process down around managing just not only the data wrangling but the policies behind it and platforms are becoming more complex can you guys talk about the product market fit here because there's sass involved so there's also a customer activity what's the product market fit that you guys see with this integration what are some of the things that you're envisioning to emerge out of this value proposition I think I can start I think you're exactly right enterprises have made huge investments in you know historically data warehouses data Mart's data lakes all kinds of other technology infrastructure aimed at making the data easier to get to but they've effectively just layered on to the problem so elations catalog has made it incredibly much more effective at helping organizations to find to understand trust to reuse and use that data so that stewards and people who know about the data can inform users who may need need to run a particular report or conduct a specific analysis can accelerate that process and compress the time the insights much much more than then it's are possible with today's technologies and if you if you overlay that on to the data privacy challenge its compounded and I think you know will it would be great for you to comment on what the data discovery capability it's a big ID do to improve that that even further yeah absolutely so as to companies we're trying to bridge this gap between data governance and privacy and and John as you mentioned there's been a proliferation of a lot of tools whether their data lakes data analysis tools etc what Big Idea is able to do is we're looking across over 70 different types of data platforms whether they be legacy systems like SharePoint and sequel whether they be on pram or in the cloud whether it's data at rest or in motion and we're able to auto populate our metadata findings into relations data catalog the main purpose there being that those data stewards and have access to the most authentic real time data possible so on the terms of the customer value they're going to see what more built in privacy aware features is its speed but you know what I mean the problem is compounded with the data getting that catalog and getting insights out of it but for this partnership is it speed to outcome what does the outcome that you guys are envisioning here for the customer I think it's a combination of speed as you said you know they can much more rapidly get up to speed so an analyst who needs to make a decision about specific data set whether they can use it or not and know at the point of analysis if this data is governed by policies that has been informed by big IDs so the elation catalog user can make a much more rapid decision about how to use that the second piece is the complexity and costs of compliance they can really reduce and start to winnow down their technology footprint because with the combination of the discovery that big ID provides the the the ongoing discovery the big ID provides and the enterprise it data catalog provided violation we give the framework for being able to keep up with these changes in policies as rules and as companies change so they don't have to keep reinventing the wheel every time so we think that there's a significant speed time the market advantage as well as an ability to really consolidate technology footprint well I'll add to that yeah yeah just one moment so elation when they helped create this marketplace seven years ago one of the goals there and I think we're Big Ideas assisting as well as the trusting confidence that both the users of these software's the data store of the analysts have and the data that they're using and then the the trust and confidence are building with their end consumers is much better knowing that there is the this is both bi-directional and ongoing continuously you know I've always been impressed with relations vision it's big vision around the role of the human and data and it's always been impressive and yeah I think the world spinning in that direction you starting to see that now William I want to get your thoughts with big id because you know one of the things is challenging out there from what we're hearing is you know people want to protect the sensitive data obviously with the hacks and everything else and personal information there's all kinds of regulation and believe me state by state nation by nation it's crazy complex at the same time they've got to ensure this compliance tripwires everywhere right so you have this kind of nested complex web of stuff and some real security concerns at the same time you want to make data available for machine learning and for things like that this is the real kind of things that the problem has twisted around so if I'm an enterprise I'm like oh man this is a pain in the butt so how are you guys seeing this evolve because this solution is one step in that direction what are some of the pain points what are some of the examples can you share any insights around how people are overcoming that because they want to get the data out there they want to create applications that are gonna be modern robust and augmented with whether it's augmented AI of some sort or some sort of application at the same time protecting the information and compliance it's a huge problem challenge your thoughts absolutely so to your point regulations and compliance measures both state-by-state and internationally they're growing I mean I think when we saw GDP our four years ago in the proliferation of other things whether it be in Latin America in Asia Pacific or across the United States potentially even at the federal level in the future it's not making it easier to add complexity to that every industry and many companies individually have their own policies in the way that they describe data whether what's sensitive to them is it patent numbers is it loyalty card numbers is it any number of different things where they could just that that enterprise says that this type of data is particularly sensitive the way we're trying to do this is we're saying that if we can be a force multiplier for the individuals within our organization that are in charge of the stewardship over their data whether it be on the privacy side on the security side or on the data and analytics side that's what we want to do and automation is a huge piece of this so yes the ID has a number of patents in the machine learning area around data discovery and classification cluster analysis being able to find duplicate of data out there and when we put that in conjunction with what elations doing and actually gave the users of the data the kind of unprecedented ability to curate deduplicate secure sensitive data all by a policy driven automated platform that's actually I think the magic gear is we want to make sure that when humans get involved their actions can be made how do I say this minimum minimum human interaction and when it's done it's done for a reason of remediation so they're there the second step not the first step here I'll get your thoughts you know I always riff on the idea of DevOps and it's a cloud term and when you apply that the data you talk about programmability scale automation but the humans are making calls whether you're a programmer and devops world or to a data customer of the catalog and halation i'm making decisions with my business I'm a human I'm taking action at the point of design or whatever this is where I think the magic can happen your thoughts on how this evolves for that use case because what you're doing is you're augmenting the value for the user by taking advantage of these things is is that right or am i around the right area yeah I think so I think the one way to think about elation and that analogy is that the the biggest struggle that enterprise business users have and we target the the consumers of data we're not a provider to the information suppliers if you will but the people who had need to make decisions every single day on the right set of data we're here to empower them to be able to do that with the data that they know has been given the thumbs up by people who know about the data connecting stewards who know about the subject matter at hand with the data that the analyst wants to use at the time of consumption and that powerful connection has been so effective in our customers that enabling them to do in our analytical work that they just couldn't dream of before so the key piece here is with the combination with big ID we can now layer in a privacy aware consumption angle which means if you have a question about running some customer propensity model and you don't know if you can use this data or that data the big ID data discovery platform informs the elation catalog of the usage capabilities of that given data set at the moment the analyst wants conduct his or her analysis with the appropriate data set as identified by the stewards and and as endorsed by the steward so that point in time is really critical because that's where the we can we can fundamentally shrink the decision sight yeah it's interesting and so have the point of attack on the user in this case the person in the business who's doing some real work that's where the action is yeah it's a whole nother meaning of actionable data right so you know this seems to where the values quits its agility really it's kind of what we're talking about here isn't it it is very agile on the differentiation between elation and big idea in what we're bringing to the market now is we're also bringing flexibility and you meant that the point of agility there is because we allow our customers to say what their policies are what their sense of gait is define that themselves within our platforms and then go out find that data classify and catalog at etc like that's giving them that extra flexibility the enterprise's today need so that it can make business decisions and faster and I actually operationalize data guys great job good good news it's I think this is kind of a interesting canary in the coal mine around the trends that are going on around how data is evolving what's next how you guys gonna go to market partnership obviously makes a lot of sense technical integration business model integration good fit what's next for you guys I'm sorry I mean I think the the great thing is that you know from the CEO down our organizations are very much aligned in terms of how we want to integrate our two solutions and how we want to go to market so myself and will have been really focused on making sure that the skill sets of the various constituents within both of our companies have the level of education and knowledge to bring these results to bear coupled with the integration of our two technologies well your thoughts yeah absolutely I mean between our CEOs who have a good cadence to care to myself who probably spend too much time on the phone at this point we might have to get him a guest bedroom or something alignments a huge key here ensuring that we've enabled our field to - and to evangelize this out to the marketplace itself and then doing whether it's this or our webinars or or however we're getting the news out it's important that the markets know that these capabilities are out there because the biggest obstacle honestly to adoption it's not that other solutions or build-it-yourself it's just lack of knowledge that it could be easier it could be done better that you could have you could know your data better you could catalog it better great final question to end the segment message to the potential customer out there what it what about their environment that might make them a great prospect for this solution is it is it a known problem is it a blind spot when would someone know to call you guys up in this to ship and leverage this partnership is it too much data as it's just too much many applications across geographies I'm just trying to understand the folks watching when it's an opportunity to call you guys welcome a relation perspective there that can never be too much data they the a signal that may may indicate an interest or a potential fit for us would be you know the need to be compliant with one or more data privacy regulations and as well said these are coming up left and right individual states in the in addition to the countries are rolling out data privacy regulations that require a whole set of capabilities to be in place and a very rigorous framework of compliance those those requirements and the ability to make decisions every single day all day long about what data to use and when and under what conditions are a perfect set of conditions for the use of a data catalog evacuation coupled with a data discovery and data privacy solution like big I well absolutely if you're an organization out there and you have a lot of customers you have a lot of employees you have a lot of different data sources and disparate locations whether they're on prime of the cloud these are solid indications that you should look at purchasing best-of-breed solutions like elation and Big Ideas opposed to trying to build something internally guys congratulations relations strengthening your privacy capabilities with the big ID partnership congratulations on the news and we'll we'll be tracking it thanks for coming I appreciate it thank you okay so cube coverage here in Palo Alto on remote interviews as we get through this kovat crisis we have our quarantine crew here in Palo Alto I'm John Fourier thanks for watching [Music] okay guys

>> Announcer: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hi, I'm Stu Miniman, and welcome to a CUBE Conversation. We always love talking to founders of companies. We love supporting the Boston-area community, but even more, right now, we're of course talking to leaders in the industry about some of the challenges facing with the global pandemic, so, happy to welcome to the program first-time guest Paulo Rosado, who is the founder and CEO of OutSystems. You are based in Boston, your company is global. Paulo, thanks so much for joining us, and let's start out talking about kind of the age we are in right now and how you are supporting your customers, your employees, and the developer community that you engage with. >> Absolutely, and it's a pleasure to be here, Stu. Actually, since the 23rd of March, that our 1,100 employees are all working remote, so we've had more than 1,000 Zoom calls logged, at least among the people that I know. And we have dogs and kids everywhere, and we have to adjust, 'cause we have a lot of new parents, so the kids are all over them and whatever. But actually, productivity and morale is really at a high rate. The business is going really, really well. However, as in a very OutSystems type of way, actually, because we're so fast building these digital solutions that we've launched a program with our partners. We asked them for ideas, we got more than 200 ideas coming in, and we're sponsoring 20 of those ideas. One of them is with Deloitte, for instance, where we fundamentally, in one week, they've created a full logistics system to manage all the supplies within 16 municipalities, including ventilators, masks, PPEs and the like. >> Well, that's great to hear, right. So if people want to find out more on the OutSystems website, it's the COVID-19 Community Response Program, and love to see, Paulo, we're going to talk a bit about OutSystems and what you're doing for customers. Of course, the speed of development of new applications is what your company's been doing for a long time, and it kind of becomes a little bit bromide that we talk about, "Oh, well, software's eating the world." Well, in challenging times, how is software hoping to meet the challenges that communities, municipalities, employees, companies need to survive in these challenging situations? So anything else you want to talk about, kind of the community program? >> Yeah, well, so what we did is we opened up the community, worldwide community, actually, because today we serve about 60 countries, and so we wanted to have projects that really add impact. We had a couple from Germany, and some from Asia, and it's amazing. Today, we have sponsored 14, so we have 14 scalable installations already running. Some of these projects have gone live, some are still in development. But what's interesting is that the 200,000-plus communities, that they're getting together. We have all these virtual teams, subject matter experts, relationships with house officers and house offices, and developers, and we're just churning away. And the innovation of the people when they have, actually, something that they can build real solutions fast, they can iterate on top, it's absolutely amazing. And it's our contribution, also, to the world here, really. >> Yeah, very important, Paulo, thank you for doing that. Boy, I think, Paulo, you started the company back in 2001. The discussion around software and developers was rather nascent back in those days. So bring us a little bit through the journey of the company, if you would, and some of the major things that are different now in, really, you're entering the third decade of the company, so bring us back to some of the early days, as well as, what is significantly different today? >> Actually, the idea that we had initially was very much the one that has become truth. We were just about 14 years ahead of the market. So the company's called OutSystems because at the time, we believed that a large percent of systems would migrate out of the data center. That is what today is called the cloud. We believed, at the time, based on all the evidence, that a lot of software that companies were going to be building needed to be done in a very agile way, which is, you need to build fast, but not only build fast, but change very, very fast. And it took us a while until we reached about three to four years ago, when suddenly, everything became agile. Suddenly, everything that you build, all the software that you build, you no longer had one year or 18 months to build this project. Now, you had weeks, and those times have been compressing. And so, what's happening now is we encounter ourselves in a world where companies increasingly want to build more software because they want to be differentiated, they want to compete, but the talent available and the speed they have to build these pieces of software are becoming more and more challenging, and we help a lot in doing that. We are the most mature, the most advanced no-code/low-code platform in the market. And so, it's a great time for us now. >> Yeah, Paulo, I'd like to help understand software development, application modernization are very important topics for a number of years now. I think back to last year, Satya Nadella on stage at Microsoft Ignite, and he was talking about just the massive amounts of new applications that would be built over the next few years. And it's interesting, a company like Microsoft that, you go back 10 years ago, it'd be like, "Well, you'll be using all of our software, "not thinking about building your own software." So you've got partnerships with the public cloud providers, there's all sorts of new partners as well as competitors entering the space. So help us understand kind of where OutSystems fits in this ecosystem and differentiates itself from some of the other noise that's out there. >> No, absolutely. Well, we've woken up a lot of giants, definitely, with this approach. One of the differentiators is that these platforms are actually pretty hard to build, and so, if you look into what Satya said in that particular conference, he was mentioning the fact that fundamentally, every company needs to become a cloud software company. But in order for you to become a cloud software company, you need a very large number of talent skills. You need good web developers, front-end developers, back-end developers. You need to have people who understand DevOps, you need to understand scalability, security, all of these things. You can do that with the tens and even hundreds of tools that are in the market, but what the platform like OutSystems stands up by doing is ends up abstracting a lot of debt and just gives you a very fast capacity for you to build your mobile applications, your pricing engines, your workflows, your portals, in a very fast way. So leveraging the people that you have, leveraging the unique knowledge of the business that you have, and letting you catch up to disruptors that really have all those technical skill sets that today are so rare. >> Yeah, and I'd love to hear, tell us a little bit about your customer base. So you've been around for many years, so I'm sure it is quite diverse, but how many customers does OutSystems have? If you've got a key use case or two that might help us understand where this low-code/no-code solution is helping them through their journey. >> Oh, absolutely, we have companies like Safeway, Chevron, T-Mobile. All of them have somehow different use cases, because we are in the business of innovation, and so, whatever you want to innovate with, you innovate typically with OutSystems. We have a particular company which is the largest oil and gas terminal management company in the world. They have 73 terminals. And one of the things they built was a full ERP, a full platform, digital platform, to manage all logistics of the tankers that come into the ports, deploy the oil in the reservoirs, and then having trucks that come and take the oil away. It's a very complex business, and they were looking at, fundamentally, a four- to six-year project to build this, and they did it in seven months. And so, these type of compressions of time for these very large systems is a huge, huge differentiator. Then we have, on the other hand, companies that have built their front ends, typically mobile applications integrated with web applications, and those applications change, fundamentally, almost every day or every week. We have a bank, for instance, that's releasing a version per day in their applications. That speed of development gives them a huge competitive advantage but puts a lot of pressure on the stack and all the IT that's needed, and we help there because of the platform. >> Yeah, Paulo, we've been talking for years about some of the transformations that companies are going through, and that application transformation really is one of the bigger challenges that they face along those lines. In some of the events I go to, the communities I look at, there's a lot of talk about how containerization in Kubernetes is helping to move the infrastructure team to get ready for this. Of course, we've talked a bit already about how public cloud's changing things. Serverless is a different paradigm for how application developers should think about the platforms they're living on. How does OutSystems kind of plug in to these trends which have come along in the time since you've been out there? >> Oh, very well. The way these platforms work, at least, the way the OutSystems platform works, is that we have an automation layer who's responsible, fundamentally, for compressing time and making things increasingly easier. Basically, just give an IT department or company the capacity to build things 100 times faster. But underneath, we actually use the newest architectures that give us high scalability, also scaling resilience, 99.999% of uptime. And in those cases, for instance, for that, we use containers, Linux, Docker, all of those type of technologies. We run standard on AWS, we also run on Azure. And so, we can provide automation, but underneath, we're fundamentally using the same tools that all enterprise-grade architects are using. >> Okay, great, Paulo. Last question I have for you, give us a little bit your outlook on the future of software development, what we should be looking at when it comes to OutSystems and your community. >> Well, actually, it's not only about OutSystems, it's all about development of the software. We believe, and we see evidence of it, that while software development used to be done by some elites about 10, 15 years ago, today, every company needs to build their own software. And more than 65% of new software that's going to be built in the next three to five years is going to be done with a no-code or low-code platform. That's just too much, you just need that speed, you don't have enough talent. And actually, what we see, and we're doing a lot of research there, is that complementing the developers, we're seeing more and more AI bots that actually assist development in a lot of the boring tasks that are part of the development and deployment cycle, like validation of code, automatic testing, creating the right patterns of architecture for high scalability and maintainability. We're introducing a lot of those things in the platform. So in the next years, we believe we'll see more and more developers being helped by artificial intelligence bots, therefore progressing in that 100X to 1,000X automation productivity enhancement. >> Well, I tell you, you're hitting on one of our favorite topics to talk about. (Paulo chuckles) We did an event years ago with Andy McAfee and Erik Brynjolfsson from MIT, talking about how it really is about racing with the machines. So I've seen things that said, "Oh, computer programmers, you're the next things "that are going to be replaced by robots." And what I'm hearing from you is, of course, what we know is that really it is the combination of people plus this software that are really going to supercharge things going forward. And you're nodding, so you would agree. >> That's exactly it. And we already have evidence of that because we have a lot of our AI is already deployed inside the platform, and so we're measuring, we're learning with it. And we can see tremendous, almost exponential improvements. It's almost as if a developer, as they're creating these functional requirements, gets augmented with an extra brain. So it really works, and it's time now, it's reaching time for AI to be used to help the software development cycle. >> Right, well, Paulo, thank you so much for the conversation. Absolutely we hope that these kind of technologies are the ones that are going to help the global economy as we hopefully move forward from the results of the current global situation here. So thank you so much for joining us, and definitely look forward to keeping track of the company in the future. All right-- >> Thank you, Stu, it was a pleasure. Thank you very much. >> Thanks, I'm Stu Miniman, and as always, check out theCUBE.net for all of the digital events, as well as the archives of interviews that we've done, reach out to us if you have any questions, and as always, thank you for watching theCUBE. (upbeat electronic music)