>>Welcome back everyone Cube's live coverage here. Day two, two sets, three days of cube coverage here at VMware Explorer. This is our 12th year covering VMware's annual conference, formally called world I'm Jean Dave ante. We'd love seeing the progress and we've got great security comes Tom Gill, senior rights, president general manager, networking and advanced security business group at VMware. Great to see you. Thanks for coming on. Thanks >>For having me. Yeah, really happy we could have you on, you know, I think, I think this is my sixth edition on the cube. Like, do I get freaking flyer points or anything? >>Yeah, you get first get the VIP badge. We'll make that happen. You can start getting credits. >>Okay. There we go. >>We won't interrupt you. No, seriously, you got a great story in security here. The security story is kind of embedded everywhere, so it's not like called out and, and blown up and talked specifically about on stage. It's kind of in all the narratives in, in the VM world for this year. Yeah. But you guys have an amazing security story. So let's just step back into set context. Tell us the security story for what's going on here at VMware and what that means to this super cloud multi-cloud and ongoing innovation with VMware. Yeah, >>Sure thing. So, so probably the first thing I'll point out is that, that security's not just built in at VMware it's built differently, right? So we're not just taking existing security controls and cut and pasting them into, into our software. But we can do things because of our platform because of the virtualization layer that you really can't do with other security tools and where we're very, very focused is what we call lateral security or east west movement of an attacker. Cuz frankly, that's the name of the game these days. Right? Attackers, you gotta assume that they're already in your network. Okay. Already assume that they're there, then how do we make it hard for them to get to what the, the stuff that you really want, which is the data that they're, they're going after. Right. And that's where we, >>We really should. All right. So we've been talking a lot coming into world VMware Explorer and here the event about two things security as a state. Yeah. I'm secure right now. Yeah. Or I, I think I'm secure right now, even though someone might be in my network or in my environment to the notion of being defensible. Yeah. Meaning I have to defend and be ready at a moment's notice to attack, fight, push back red team, blue team, whatever you're gonna call it, but something's happening. I gotta be a to defend. Yeah. >>So you, what you're talking about is the principle of zero trust. So the, the, when we, when I first started doing security, the model was we have a perimeter and everything on one side of the perimeter is dirty, ugly, old internet and everything on this side known good, trusted what could possibly go wrong. And I think we've seen that no matter how good you make that perimeter, bad guys find a way in. So zero trust says, you know what? Let's just assume they're already in. Let's assume they're there. How do we make it hard for them to move around within the infrastructure and get to the really valuable assets? Cuz for example, if they bust into your laptop, you click on a link and they get code running on your machine. They might find some interesting things on your machine, but they're not gonna find 250 million credit cards. Right. Or the, the script of a new movie or the super secret aircraft plans, right. That lives in a database somewhere. And so it's that movement from your laptop to that database. That's where the damage is done. Yeah. And that's where VMware shines. If they don't >>Have the right to get to that database, they're >>Not >>In and it's not even just the right, like, so they're so clever. And so sneaky that they'll steal a credential off your machine, go to another machine, steal a credential off of that. So it's like they have the key to unlock each one of these doors and we've gotten good enough where we can look at that lateral movement, even though it has a credential and a key where like, wait a minute, that's not a real CIS admin making a change. That's ransomware. Yeah. Right. And that's, that's where we, you have to earn your way in. That's right. That's >>Right. Yeah. And we're all, there's all kinds of configuration errors. But also some, some I'll just user problems. I've heard one story where there's so many passwords and username and passwords and systems that the bad guy's scour, the dark web for passwords that have been exposed. Correct. And go test them against different accounts. Oh one hit over here. Correct. And people don't change their passwords all the time. Correct? Correct. That's a known, known vector. We, >>We just, the idea that users are gonna be perfect and never make mistake. Like how long have we been doing this? Like humans with the weakest link. Right. So, so, so people are gonna make mistakes. Attackers are gonna be in here's another way of thinking about it. Remember log for J. Remember that whole ago, remember that was a Christmas time. That was nine months ago. And whoever came up with that, that vulnerability, they basically had a skeleton key that could access every network on the planet. I don't know if a single customer that was said, oh yeah, I wasn't impacted by log for J. So seers, some organized entity had access to every network on the planet. What was the big breach? What was that movie script that got stolen? So there wasn't one. Right? We haven't heard anything. So the point is the goal of attackers is to get in and stay in. Imagine someone breaks into your house, steals your laptop and runs. That's a breach. Imagine someone breaks into your house and stays for nine months. Like it's untenable, the real world. Right, right. >>We don't even go in there. They're still in there >>Watching your closet. Exactly. Moving around, nibbling on your ni line, your cookies. You know what I mean? Drinking your beer. >>Yeah. So, so let's talk about how this translates into the new reality of cloud native, because now know you hear about, you know, automated pen testing is a, a new hot thing right now you got antivirus on data. Yeah. Is hot is hot within APIs, for instance. Yeah. API security. So all kinds of new hot areas, cloud native is very iterative. You know, you, you can't do a pen test every week. Right. You gotta do it every second. Right. So this is where it's going. It's not so much simulation. It's actually real testing. Right. Right. How do you view that? How does that fit into this? Cuz that seems like a good direction to me. >>Yeah. It, it, it fits right in. And you were talking to my buddy AJ earlier about what VMware can do to help our customers build cloud native applications with, with Zu, my team is focused on how do we secure those applications? So where VMware wants to be the best in the world is securing these applications from within looking at the individual piece parts and how they talk to each other and figuring out, wait a minute. That, that, that, that, that should never happen by like almost having an x-ray machine on the ins of the application. So we do it for both for VMs and for container based applications. So traditional apps are VM based. Modern apps are container based and we, and we have a slightly different insertion mechanism. It's the same idea. So for VMs, we do it with the hypervisor, with NSX, we see all the inner workings in a container world. >>We have this thing called a service me that lets us look at each little snippet of code and how they talk to each other. And once you can see that stuff, then you can actually apply. It's almost like common sense logic of like, wait a minute. You know, this API is giving back credit card numbers and it gives five an hour. All of a sudden, it's now asking for 20,000 or a million credit card that doesn't make any sense. Right? The anomalies stick out like a sore thumb. If you can see them. And VMware, our unique focus in the infrastructure is that we can see each one of these little transactions and understand the conversation. That's what makes us so good at that east west or lateral >>Security. Yeah. You don't belong in this room, get out or that that's right. Some weird call from an in-memory database, something over >>Here. Exactly. Where other, other security solutions won't even see that. Right. It's not like there algorithms aren't as good as ours or, or better or worse. It's that, it's the access to the data. We see the, the, the, the inner plumbing of the app. And therefore we can protect >>The app from, and there's another dimension that I wanna get in the table here, cuz to my knowledge only AWS, Google, I, I believe Microsoft and Alibaba and VMware have this, it nitro the equivalent of a nitro. Yes. Project Monterey. Yeah. That's unique. It's the future of computing architectures. Everybody needs a nitro. I've I've written about this. Yeah. Right. So explain your version. Yeah. Project. It's now real. It's now in the market right. Or soon will be. Yeah. Here. Here's our mission salient aspects. Yeah. >>Here's our mission of VMware is that we wanna make every one of our enterprise customers. We want their private cloud to be as nimble, as agile, as efficient as the public cloud >>And secure >>And secure. In fact, I'll argue, we can make it actually more secure because we're thinking about putting security everywhere in this infrastructure. Right. Not just on the edges of it. So, so, so, okay. How do we go on that journey? As you pointed out, the public cloud providers realized, you know, five years ago that the right way to build computers was not just a CPU and a GPU graphics process, unit GPU, but there's this third thing that the industry's calling a DPU data processing unit. So there's kind of three pieces of a computer. And the DPU is sometimes called a smart Nick it's the network interface card. It does all that network handling and analytics and it takes it off the CPU. So they've been building and deploying those systems themselves. That's what nitro is. And so we have been working with the major Silicon vendors to bring that architecture to everybody. So, so with vSphere eight, we have the ability to take the network processing that east west inspection. I talked about, take it off of the CPU and put it into this dedicated processing element called the DPU and free up the CPU to run the applications that AJ and team are building. >>So no performance degradation at all, correct. >>To CPU >>Offload. So even the opposite, right? I mean you're running it basically bare metal speeds. >>Yes, yes. And yes. >>And, and, and you're also isolating the, the storage right from the, from the, the, the security, the management. And >>There's an isolation angle to this, which is that firewall that we're putting everywhere. Not just that the perimeter, we put it in each little piece of the server is running when it runs on one of these DPU, it's a different memory space. So even if, if an attacker gets to root in the OS, they it's very, very, never say never, but it's very difficult. >>So who has access to that? That, that resource >>Pretty much just the infrastructure layer, the cloud provider. So it's Google Microsoft, you know, and the enterprise, the >>Application can't get in, >>Can't get in there. Cause it, you would've to literally bridge from one memory space to another, never say never, but it would be very, very, >>It hasn't earned the trust >>To get it's more than Bob wire. It's, it's, it's multiple walls and, and >>It's like an air gap. It puts an air gap in the server itself so that if the server's compromised, it's not gonna get into the network really powerful. >>What's the big thing that you're seeing with this super cloud transition we're seeing, we're seeing, you know, multicloud and this new, not just SAS hosted on the cloud. Yeah. You're seeing a much different dynamic of combination of large scale CapEx, cloud native. And then now cloud native develops on premises and edge kind of changing what a cloud looks like if the cloud's on a cloud. So rubber customer, I'm building on a cloud and I have on-prem stuff. So I'm getting scale CapEx relief from the, from the cap, from the hyperscalers. >>I, I think there's an important nuance on what you're talking about, which is, is in the early days of the cloud customers. Remember those first skepticism? Oh, it'll never work. Oh, that's consumer grade. Oh, that's not really gonna work. And some people realize >>It's not secure. Yeah. >>It, it's not secure that one's like, no, no, no, it's secure. It works. And it, and it's good. So then there was this sort of over rush. Like let's put everything on the cloud. And I had a lot of customers that took VM based applications said, I'm gonna move those onto the cloud. You gotta take 'em all apart, put 'em on the cloud and put 'em all back together again. And little tiny details, like changing an IP address. It's actually much harder than it looks. So my argument is for existing workloads for VM based workloads, we are VMware. We're so good at running VM based workloads. And now we run them on anybody's cloud. So whether it's your east coast data center, your west coast data center, Amazon, Google, Microsoft, Alibaba, IBM keep going. Right. We pretty much every, and >>The benefit of the customer is what you >>Can literally vMotion and just pick it up and move it from private to public public, to private, private, to public, public, back and forth. >>Remember when we called VMO BS years ago. Yeah, yeah, yeah. >>We were really, skeptic is >>Powerful. We were very skeptical. We're like, that'll never happen. I mean, we were, I mean, it's supposed to be pat ourselves on the back. We, well, >>Because it's alchemy, it seems like what you can't possibly do that. Right. And so, so, so, and now we do it across clouds, right? So we can, you know, it's not quite VMO, but it's the same idea. You can just move these things over. I have one customer that had a production data center in the Ukraine, things got super tense, super fast, and they had to go from their private cloud data center in the Ukraine to a public cloud data center outta harm's way. They did it over a weekend, 48 hours. If you've ever migrated data, that's usually six months, right? And a lot of heartburn and a lot of angst, boom. They just drag and drop, moved it on over. That's the power of what we call the cloud operating model. And you can only do this when all your infrastructure's defined in software. >>If you're relying on hardware, load, balancers, hardware, firewalls, you can't move those. They're like a boat anchor. You're stuck with them. And by the way, really, really expensive. And by the way, they eat a lot of power, right? So that was an architecture from the nineties in the cloud operating model, your data center. And this goes back to what you were talking about is just racks and racks of X 86 with these magic DPU or smart necks to make any individual node go blisteringly fast and do all the functions that you used to do in network appliances. >>We just said, AJ taking us to school and everyone else to school on applications, middleware abstraction layer. Yeah. And kit Culver was also talking about this across cloud. We're talking super cloud, super pass. If this continues to happen, which we would think it will happen. What does the security posture look like? It has. It feels to me. And again, this is, this is your wheelhouse. If super cloud happens with this kind of past layer where there's B motioning going on, all kinds of yeah. Spanning applications and data. Yeah. Across environments. Yeah. Assume there's an operating system working on behind the scenes. Right. What's the security posture in all this. Yeah. >>So remember my narrative about like VA guys are getting in and they're moving around and they're so sneaky that they're using legitimate pathways. The only way to stop that stuff is you've gotta understand it at what, you know, we call layer seven at the application layer the in, you know, trying to do security, the infrastructure layer. It was interesting 20 years ago, kind of less interesting 10 years ago. And now it's becoming irrelevant because the infrastructure is oftentimes not even visible, right. It's buried in some cloud provider. So layer seven, understanding, application awareness, understanding the APIs and reading the content. That's the name of the game in security. That's what we've been focused on. Right. Nothing to do with >>The infras. And where's the progress bar on that, that paradigm early one at the 10, 10 being everyone's doing it >>Right now. Well, okay. So we, as a vendor can do this today. All the stuff I talked about about reading APIs, understanding the, the individual services looking at, Hey, wait a minute. This credit card anomalies, that's all shipping production code. Where is it in customer adoption life cycle, early days, 10%. So, so there's a whole lot of headroom. We, for people to understand, Hey, I can put these controls in place. There's software based. They don't require appliances. It's layer seven. So it has contextual awareness and it's works on every single cloud. >>You know, we talk about the pandemic. Being an accelerator really was a catalyst to really rethink. Remember we used to talk about pat his security a do over. He's like, yes, if it's the last thing I'm due, I'm gonna fix security. Well, he decided to go try to fix Intel instead, but, >>But, but he's getting some help from the government, >>But it seems like, you know, CISOs have totally rethought, you know, their security strategy. And, and at least in part is a function of the pandemic. >>When I started at VMware four years ago, pat sat me down in his office and he said to me what he said to you, which is like Tom, he said, I feel like we have fundamentally changed servers. We fundamentally changed storage. We fundamentally changed networking. The last piece of the puzzle of security. I want you to go fundamentally change it. And I'll argue that the work that we're doing with this, this horizontal security understanding the lateral movement east west inspection, it fundamentally changes how security works. It's got nothing to do with firewalls. It's got nothing to do with endpoint. It's a unique capability that VMware is uniquely suited to deliver on. And so pat, thanks for the mission. We delivered it and available >>Those, those wet like web applications firewall for instance are, are around. I mean, but to your point, the perimeter's gone. Exactly. And so you gotta get, there's no perimeter. So it's a surface area problem. Correct. And access and entry, correct. They're entering here easy from some manual error or misconfiguration or bad password that shouldn't be there. They're >>In. Think about it this way. You put the front door of your house, you put a big strong door and a big lock. That's a firewall bad guys, come in the window. Right. And >>Then the window's open and the window with a ladder room. Oh my >>God. Cause it's hot, bad user behavior. Trump's good security >>Every time. And then they move around room to room. We're the room to room people. Yeah. We see each little piece of the thing. Wait, that shouldn't happen. Right. >>I wanna get you a question that we've been seeing and maybe we're early on this, or it might be just a, a false data point. A lot of CSOs and we're talking to are, and people in industry in the customer environment are looking at CSOs and CSOs, two roles, chief information security officer, and then chief security officer Amazon, actually, Steven Schmidt is now CSO at reinforced. They actually called that out. Yeah. And the, and the interesting point that he made, we've had some other situations that verified. This is that physical security is now tied to online to your point about the service area. If I get a password, I still at the keys to the physical goods too. Right. Right. So physical security, whether it's warehouse for them is, or store or retail digital is coming in there. Yeah. So is there a CSO anymore? Is it just CSO? What's the role or are there two roles you see that evolving or is that just, >>Well, >>I circumstance, >>I, I think it's just one. And I think that, that, you know, the stakes are incredibly high in security. Just look at the impact that these security attacks are having on it. It, you know, companies get taken down, Equifax market cap was cut, you know, 80% with a security breach. So security's gone from being sort of a nuisance to being something that can impact your whole kind of business operation. And then there's a whole nother domain where politics get involved. Right. It determines the fate of nations. I know that sounds grand, but it's true. Yeah. And so, so, so companies care so much about it. They're looking for one liter, one throat to choke, you know, one person that's gonna lead security in the virtual domain, in the physical domain, in the cyber domain, in, in, you know, in the actual, well, it is, >>I mean, you mentioned that, but I mean, mean you look at Ukraine. I mean the, the, that, that, that cyber is a component of that war. I mean, that's very clear. I mean, that's, that's new, we've never seen >>This. And in my opinion, the stuff that we see happening in the Ukraine is small potatoes compared to what could happen. Yeah, yeah. Right. So the us, we have a policy of, of strategic deterrents where we develop some of the most sophisticated cyber weapons in the world. We don't use them and we hope never to use them because the, the, our adversaries who could do stuff like, oh, I don't know, wipe out every bank account in north America, or turn off the lights in New York city. They know that if they were to do something like that, we could do something back. >>I, this discuss, >>This is the red line conversation I wanna go there. So >>I had this discussion with Robert Gates in 2016 and he said, we have a lot more to lose, which is really >>Your point. So this brand, so I agree that there's the, to have freedom and Liberty, you gotta strike back with divorce and that's been our way to, to balance things out. Yeah. But with cyber, the red line, people are already in banks. So they're addresses are operating below the red line, red line, meaning before we know you're in there. So do we move the red line down because Hey, Sony got hacked the movie because they don't have their own militia. Yeah. If they were physical troops on the shores of LA breaking into the file cabinets. Yeah. The government would've intervened. >>I, I, I agree with you that it creates, it creates tension for us in the us because our, our adversaries don't have the clear delineation between public and private sector here. You're very, very clear if you're working for the government or you work for an private entity, there's no ambiguity on that. And so, so we have different missions in each department. Other countries will use the same cyber capabilities to steal intellectual, you know, a car design as they would to, you know, penetrate a military network. And that creates a huge hazard for us on the us. Cause we don't know how to respond. Yeah. Is that a civil issue? Is that a, a, a military issue? And so, so it creates policy ambiguity. I still love the clarity of separation of, you know, sort of the various branches of government separation of government from, >>But that, but, but bureau on multinational corporation, you then have to, your cyber is a defensible. You have to build the defenses >>A hundred percent. And I will also say that even though there's a clear D mark between government and private sector, there's an awful lot of cooperation. So, so our CSO, Alex toshe is actively involved in the whole intelligence community. He's on boards and standards and we're sharing because we have a common objective, right? We're all working together to fight these bad guys. And that's one of the things I love about cyber is that that even direct competitors, two big banks that are rivals on the street are working together to share security information and, and private, is >>There enough? Is collaboration Tom in the vendor community? I mean, we've seen efforts to try to, that's a good question, monetize private data, you know? Yeah. And private reports and, >>And, you know, like, so at VMware, we, we, I'm very proud of the security capabilities we've built, but we also partner with people that I think of as direct competitors, we've got firewall vendors and endpoint vendors that we work with and integrate. And so cooperation is something that exists. It's hard, you know, because when you have these kind of competing, you know, so could we do more? Of course we probably could, but I do think we've done a fair amount of cooperation, data sharing, product integration, et cetera, you know, and, you know, as the threats get worse, you'll probably see us continue to do more. >>And the governments is gonna trying to force that too. >>And, and the government also drives standards. So let's talk about crypto. Okay. So there's a new form of encryption coming out called quantum processing, calling out. Yeah. Yeah. Quantum, quantum computers have the potential to crack any crypto cipher we have today. That's bad. Okay. Right. That's not good at all because our whole system is built around these private communications. So, so the industry is having conversations about crypto agility. How can we put in place the ability to rapidly iterate the ciphers in encryption? So when the day quantum becomes available, we can change them and stay ahead of these quantum people. Well, >>Didn't this just put out a quantum proof algo that's being tested right now by the, the community. >>There's a lot of work around that. Correct. And, and, and this is taking the lead on this, but you know, Google's working on it, VMware's working on it. We're very, very active in how do we keep ahead of the attackers and the bad guys? Because this quantum thing is like a, it's a, it's a x-ray machine. You know, it's like, it's like a, a, a di lithium crystal that can power a whole ship. Right. It's a really, really, really powerful >>Tool. It's bad. Things will happen. >>Bad things could happen. >>Well, Tom, great to have you on the cube. Thanks for coming. Take the last minute to just give a plug for what's going on for you here at world this year, VMware explore this year. Yeah. >>We announced a bunch of exciting things. We announced enhancements to our, our NSX family, with our advanced load balancer, with our edge firewall. And they're all in service of one thing, which is helping our customers make their private cloud like the public cloud. So I like to say 0, 0, 0. If you are in the cloud operating model, you have zero proprietary appliances. You have zero tickets to launch a workload. You have zero network taps and zero trust built into everything you do. And that's, that's what we're working on and pushing that further and further. >>Tom Gill, senior vices president head of the networking at VMware. Thanks for coming up for you. Appreciate >>It. Yes. Thanks for having guys >>Always getting the security data. That's killer data and security of the two ops that get the most conversations around dev ops and cloud native. This is the queue bringing you all the action here in San Francisco for VMware. Explore 2022. I'm John furrier with Dave, Alan. Thanks for watching.

(upbeat music) >> Okay, welcome back everyone to theCUBE's coverage of AWS re:Invent 2021. We're here live in Las Vegas for an in-person event. Of course, it's a hybrid event, virtual online. Many people online. A lot of people here on the event, a lot of action. cloud going next generation, mainframe transformation, more analytics, more chips, everything's faster and cheaper and getting better and better in the cloud. We've got the great coverage. We've got two great guests. We got Justin Hooper vice president of Global Operations Infrastructure Ingram Micro and JP Perot, EVP of Telecom Media and Technology and AWS executive sponsor for Atos. Gentlemen, thank you for joining me on theCUBE. >> Thank you. >> Thank you, glad to be here. >> So what is it about the conference so far? Pretty good, like a lot of people here? >> Super exciting. >> 27,000 people showing up. >> It's amazing. >> Real people not workers. >> Yeah, it feels almost normal. >> Yeah I can't believe the turnout. >> Got a great topic, you guys working together you got mainframe, you got analytics, transformation. Let's get into it. Let's start by introducing what you guys do, your company, and why you are here. JP, we'll start with you. >> Yeah, I can start. Okay, so yeah, so I'm leading, you know, in Atos all the cloud business and telecom media technology, Atos is a big company is a service and technology company, 11 billion Euro business, and we are leading all the transformation to cloud and also, all what is related to hybrid cloud transformation. Also with security. We are number two in the world in terms of security and cybersecurity. We have developed for so long lasting relationship with AWS. We have been an advanced technology partner of AWS for now many years, since 2013. And we have developed a specific program, you know, regarding manufacturing transformation and mega trends. So this is why we are super excited to be here with you Justin today, thank you, by the way having Ingram Micro with us, Justin. >> I appreciate it, it's good talking to you. Good to be here. >> And I'm Justin Hooper, I work for a Ingram Micro. I run their Global Infrastructure and IT operations. Ingram Micro is one of the world's largest technology suppliers, technology solutions, and cloud platform and services. >> Well, great for the intro. Thanks for that set up, a lot of action going on. You guys have recently purchased, you guys got the transformation in the cloud. What is the movement to the cloud? Take us through the current situation. >> Yeah, we see, a big acceleration and especially due to COVID situation. We have seen acceleration of transformation to cloud. There is a lot to do, a lot to do because many business critical application, which have not been transformed. And also, especially all the applications which are sitting on top of mainframe that is why executive discussion we are with Ingram at the moment is how we can help Ingram with some of the applications that are on mainframe to transform and design the future. >> Justin, take us through the transformation that they're helping you with, what's the key challenge? What problem are they solving? Take us through the specifics. >> Yeah, it's interesting because I'm actually a lover of the mainframe, I think most of the people at AWS would think, the mainframes, didn`t they put the rockets on the moon. That's old technology, but mainframes are still fantastic platforms. We, have great success, great resiliency with Atos . We are on the most modern chips, but there are a lot of restrictions. You know, you really have to size your mainframe for your peak workloads. You don't have the ability to separate segments, scale horizontally, and then there are really nuanced. Like it's hard to get resources that know mainframes, to be honest with you, it is just, there's a people issue there industry-wide, and we're not different than any other company and compete for resources, both on the system side and on the programming side. And we really want to look at how we can make a massive leave, if we're going to leave the mainframe, how do we start a journey where we can end up really being able to take advantage of horizontal scalability, the ability to have a utility compute model where we're really paying as we go, because that is the opposite how the mainframe model works today. >> Talk about the refactor 'cause I know I've covered a lot of mainframe stuff with IBM in the past and how banks are still using it. Everyone is they're real applications. They're mission critical. How are they integrating into the digital transformation. Containers, kubernetes are hot right now. You're starting to see a lot more integration. How do your customers and how do you guys see refactoring happening? I can see the integration, but that as the refactoring come in. >> There's really what we've learned with our partnership is there are really a couple of ways to do the refactoring. You can convert your old Cobalt code to something else like Java. And there are tools and companies out there that do that. Or you can really build a plan where you can effectively emulate your mainframe on commodity computing and through a relatively deep analysis with Atos, the recommendation that we're looking at is that ability to first get off of the hardware, get off of that reliance on the platform, but not jump all the way to modify your code to Java. There's not a lot of value in going from Cobalt to Java, for example, if you're not making improvements in your programs, adding business capabilities. So the journey starts with get off the hardware, but then it allows you to go and say, we are going to break up those complex programs. We are going to separate the data differently. And once you do that, you can start to take advantage of containers and start to separate yourself even more and really get into the cloud. But, there are ways to piece your way through that. >> You know that's really good insight, JP, I'd love to get your reaction on this too, because what Justin's getting at is what we hear a lot from experienced CIOs of large companies that have a lot of existing stuff. And the theme is and the word they use is you don't want to touch the white hot core. Meaning it's so mission critical that if you mangle it too hard, touch it too hard a lot of bad things happen. So this idea of push things out to the cloud that around the edges, and then work your way slowly in is a risk management and practical approach. >> Not exactly, you said it right, its exactly a risk management So, and Justin explain it different factors, which come to the end point in terms of decision there is one issue regarding competencies, because their lack of competency in the markets. There is what kind of business critical apps you have. There is a transformation as such, you know, as Justin explain you can record, or you can move, you know, to a different platform. So, each time it's a program, it's a program and analysis that we do with our customer advising the customer about, hey, based on your critical application, what is the right journey, what is the right transformation to do the right risk management? >> Justin you're taking the hot core I saw you nodding your head. You're like, yeah, what's your take on that? >> Well, yeah, I agree with you. And that fear, uncertainty and doubt it's kept people on the mainframe for a really long time. The technology has caught up and the expertise where just as JP said, you've got to be really careful in the way you plan it, and you've got to make sure that you can always get back. And so the approach that we're looking at taking is, you're able to accommodate more risk if there's an easy roll back plan, and some of the new new technologies and processes are going to allow that, so, you know, if I screw this up, I get to go find a job someplace else. So I'm aware of the white hot core, but I am confident it can be done. >> Yeah, and then technology, if you don't have to kill the old to bring in the new, you can do both, and I like your approach. I think that's a success path that people are talking about it's well documented. But at the end of the day, we're back in distributed computing, I mean, I want to get this at the end, but I want to give you guys some time to think about it. As cloud becomes everywhere as Adam Selipsky talks about, it's not just about mainframes, this it's a distributed computing paradigm. So we're going to come back to that, but let's get into the SAP Redshift `cause I think that's something that you guys are working on I think that's worth calling out here. Analytics is huge, tell us what's going on there, how you guys are working together on that. >> Yeah, so we have designed a high level of competency around SAP, and especially the migration and the SAP Redshift. So we have designed this program also with AWS and is something we are discussing at the moment also with Ingram. So we see an acceleration of this trajectory. It has been also highly pushed by SAP as well. And also we are one of the strongest partner of SAP and we see many many customers engage into this transformation at the moment. >> The cloud really gives you a lot of advantages when you're doing migration, especially around a pre-existing software, like SAP was pretty big, complex mission critical So you can throw compute at it, a lot of cool capabilities. >> Yeah, that's true, but you need, you still need to configure a lot of things as well, because it's, you need to customize and you have to really fine tune, you know, what is it, what is going to be available to the customer needs and to what you need in your company as well. >> Okay, lets get back to what Justin was saying about emulation, I mean, I can run SAP (laughs) on Amazon. I mean, we've talked about it, I wrote a story about this prior to the event called Superclouds. You can build these super applications that combine things that you never would have thought was possible. SAP running on Amazon or Ford can come to Redshift when you need it, so you have a lot more flexibility. This is now the new normal. >> Correct. >> Correct. Or Justin maybe you want also to comment on that, you know? >> You know, the great thing about being on Redshift is we pick that as a platform for our data warehouse a number of years ago, and there were basically analytics capabilities, but what we're seeing a lot here at re:Invent is as Amazon is catching up with their out of the box ML and AI capabilities in Redshift. So it feels good that we pick the platform that they're growing the capabilities in right, as we're advancing out of more of the traditional analytics and trying to go to that machine learning. And one of the things that we work at the Atos on is migrating off of SAPBW and saying, maybe we don't need that as a data and reporting platform, if we're solid with Redshift and we certainly don't need both. So we're working with them to look at the case to move all the way to Redshift, and then we can run our analytics and build the ML in that. >> And you know, that was a big theme in the keynote. This purpose-built capabilities, it's almost like having, you know, if you're building a building, you got iron steel girders made for you. You got this now better value in the platform to build on. This brings up the notion of distributed computing. >> JP: Yeah. >> In a way there's the same game, different generation. I mean, isn't it? You've got to integrate this still transformations inflection points, this is current. I feel like this now more than ever is a time where you can actually roll it all together with a little help from your friends or if Amazon's got somebody, you know, who want to reinvent the wheel. What's your reaction to that? 'Cause we've seen the movie before, when it's hard. Now, it seems easier, maybe its not. >> Yeah, we see three layers co-existing in more more. We see that, see application on data will be spread over three dimensions there will be edge computing there will be private cloud and there will be public cloud. And we see more more pressure in the direction that many customers are saying, hey, where should I put my data? This spot will go on and be processed at the edge, this spot will be process in the public cloud. There is also one of the capability where we in Atos we are able to advise customers about what is the best way to process your data if you have a lot of latency, you can process at the edge. You know, there's less equipment, you can process the public cloud. So, we see this coexistence of model. >> Justin what's your take on this distributed computing throwback concept, because look at the rise of companies like Snowflake. Where'd they come from? They're on Amazon, they pick the cloud. Now they're on going to other clouds. You can build a supercloud. You can actually build this out now faster. What's your take? >> Yeah, I, my take is that it's a pendulum and it swings back and forth, and like you said, there was client server and then everything was web-based. And a lot of things look a lot like the mainframe, put everything in the cloud and then attached to it. And then all of a sudden, you know what? We need edge computing, pull some stuff back out of the cloud and put it where we need it. So, it's going to continue to evolve. What I have noticed that I like more is, the major home one swings and statements like I want to get out of the data center business and go to the cloud, I hear those less. And people are realizing there's there's hybrid. There's purpose build computing like you said, and we need to make sure that we're putting our data where it needs to be, putting our compute where it needs to be. And that's going to change on our customer base and evolving technologies 5G is changing the whole world around edge computing. So I'm enjoying the ride, I'm glad I'm in technology because I get to move with the ebbs and flows, but I don't think we're ever going to land. I think it's going to keep moving. >> Yeah that's a totally fair point where it's fun as a technologist, but you're right. If you're operating with cloud, it doesn't matter if you're on premises or edge or public cloud, it's the same thing (laughs). >> Justin: Yeah. >> It's just pick your, pick, your use case. >> Justin: Right, your use case- >> I want a low latency at the edge. I'm not going to move my data, send it to cloud. Of course, we're going to leave it there. >> Yeah. >> If you're on premise before- >> We've already move workloads back and forth. And a lot of companies are doing that too, you know? >> I think that's what they're getting at when they talk about cloud everywhere. I think that's their way of saying, okay, hybrid is real. They won't ever say multicloud though. (all laughing) Not yet. (all laughing) >> Won't hear that here. >> All right, quick summary. What do you guys do? And what's the future hold for the relationship. You guys got a good thing going on? Take us through what's the future look like. >> Yeah, for me it's a big thank you for the partnership with Ingram. So we are extremely excited by what we can do for you. And in terms of advising your transformation and, you know, I hope that you get the right service and the right advice, you know, from Atos. >> Yeah, it's been great. We, we've appreciated. We've been, we started as a mainframe customer and now they're helping to advise on how we could get off the mainframe. I mean really cannibalizing one of the other areas there in the spirit of evolving and partnership, and you guys are bringing a ton of expertise and the way you guys attack the account and we centralized through our account team is very helpful. You're very aware of what's going on on all sides of the business. >> Well, congratulations. >> That's a big part of the theme, the keynote today on, on ad about mainframe transmission. But at the end of the day, it's about modern infrastructure, modern application development. >> Justin: Absolutely. >> Getting out, having set the table for the next generation. >> JP: Yeah. >> Thanks for coming on theCUBE and you guys want to get a quick plug in real quick for the company talk about Atos and Ingram. Give a quick plug for what you guys are working on. >> Sorry- >> Give a quick plug about what you`re working on. Give a quick commercial one minute about the company. >> One minute. >> Yeah. >> At Atos we're really transforming or leading the industry in terms of secured transformation to cloud security will be more and more important as data is everything about where is the value. So we are really making sure that our customers, they get to maximize, they can maximize the value around data transformation to cloud in a secured way. >> Justin, JP, thanks for coming on theCUBE. Really appreciate the insights. Don't touch the hot core and make, take your time. Have a good time, you're watching theCUBE, the official broadcasting of AWS re:Invent leader in tech coverage, theCUBE. Thanks for watching. (upbeat music)

>>Welcome to the cubes, continuing coverage of AWS reinvent 2021 find Lisa Martin and we are running one of the industry's most important and largest hybrid tech events with AWS in this ecosystem partners. This year, we have two live sets, two remote sites over 100 guests talking about the next decade in cloud innovation. And we're excited to be joined by Patrick Jeanne, the CTO of OutSystems Patrick. Welcome to the program. >>Thank you. I appreciate being one of those 100 guests, >>One of the 100, one of the elite, 100, we'll say it like that. Right? So, so OutSystems has some revolutionary news. You guys are saying, you know, what developer experience needs to change? Tell us more. >>It does. I mean, it needs to change. And I've been in the industry developing applications for too many years dimensions basically since I was 12 years old writing software and, you know, going over that time and thinking about it, doing the traditional software development route. So many applications that take too long was, you know, costly to build so much risk involved in it. Eventually it didn't meet all the requirements. And if you look at the investment we make in software, which is important, I mean, software is a, is a unique differentiator for, for businesses. That investment has such a high risk and a high cost, and that needs to change and it needs to change just because of the complexity that is in that process inherent in it that's. And that is what we are doing and OutSystems is tackling that problem. And, um, from a business standpoint, it must change. >>It must change that that is strong words there. So talk to me about what you're announcing, what, what were the gaps in the market customer feedback? Was it, or were there any catalysts from the pandemic going we've got to change this developer experience and this is the time >>For sure. I mean, if you think about from the pandemic and I mean, we were on a journey for digital transformation. We've been on this journey for a number of years and it really accelerated that the experiences that we have with each other, with you and me, we're not the same studio today. I mean, there's there reasons that we have used this experience remote, we have a technology that can do it, the pandemic accelerated that. And so, so much of the experiences we have are digital experiences. And if you think about it, there's a device in between us. There's going to be a device in between all the people viewing what we're looking at, that experience that, uh, that they will have with us will be basically surfaced through an application on that device. And the pandemic has really accelerated that. And that's an area that we play in, obviously for what's considered low code application development. >>And if you just think about application development in general, that's what powers all of these experiences. And going back to that, you know, statement about that, it needs to change if we need these experiences to be diverse, if we need these experiences to be meaningful, if we need them to make sure that when people engage, as far as what that device is, something that brings, you know, delight and pleasure to them, we need developers across the board. Investing in that today, there is a very constrained market for professional developers, but because of the inherent complexity in software development. And so if you think about how that's almost almost you're limiting access to the people who can create those experiences, that's not a good situation. There's about 25 million developers in the world that would consider themselves developers today, 7, 8, 9, 10 billion devices out there. Think of that disparity between those two numbers. >>And so we need a larger number of people to actually develop applications. So that experience can be much more diverse. We need to expose development to many more people. That is the problem today with software development is that it is complex. It is too specialized. It's too inherit as far as with failure when you get it together. And so either you shy away from that as an organization or as an individual to do development, or you go on these very long development as far as cycles to actually create these applications. What we do is we take the approach of let's make it very simple to get into, you know, some terms and call it citizen developer, low code, basically all they're saying is let's, let's reduce the risk of development. Let's go into a process where we make it accessible to more and more people. You can go through and develop applications with the lower risk. You can build change into that process and you can get value into end users as rapidly as possible. So that's, that is the value proposition. That is what needs to change >>Strong value proposition well said, Patrick, talking about reducing the complexity, uh, the risk as well. So, so go ahead and crack crack open what you guys are actually announcing today. >>Yeah, for sure. So with, we we've been doing this for many years, we have, um, software development, we have 14 million plus as far as end-users using applications that have been developed with the Al systems platform, what we're announcing is taking some of the great benefits that we have to what you'd consider as the first part of that low code process, where you have a, you have a developer that has an idea, and there's a canvas in front of you. You know, you're, you're an artist, right? But again, this is what you are as a developer. And so you go in and you create that application. We've been doing this for many years and it works really well. But thing that we're improving upon now is the ability to do that and scale that out to millions of end-users 10 millions of end-users. So if you think about that inherent speed of developing an application, using a platform like OutSystems, we're taking that same concept and rolling that into an internet scale application, hosting architecture. >>So any developer that uses our systems, basically like it would be comparable to a traditional development team that has application architects, cloud architects, security, engineers, database engineers, a whole team of very smart individuals that generally the, the biggest technology companies in the world can put together. Most companies can't do that. You don't have access to that type of that type of skillset. And so we're providing that with project Neo, which is what we're announcing today in our, um, at our user conference and customer conference, is this brand new as far as platform that allows you to build these applications at scale. And this is initially built on AWS using all the great AWS technologies. If you look at what AWS has done and provided to developers today, it's amazing. It is absolutely amazing. The amount of technologies that you can leverage. It's also daunting because as a traditional developer, you have to go in and choose, you know, what do you do? It's like, there's just massive cognitive load as far as upfront when you're going to design and application and what type of messaging what's at the data store. Well, how do I host my application? What type of network, you know, as far as security do I use, we're taking all that heavy lifting, all that undifferentiated, heavy lifting off of the developers, putting it into the project, Neo platform, allowing a single developer or a small group of developers to actually leverage that best in class architecture on AWS today. >>So when you're talking to developers, what are some of the things that you described as the unique differentiators of project Neo? It sounds like this was really apt and apt time for change, but when you're talking to those folks, what do you say? You know, 1, 2, 3, these are the things that make project Neo unique. >>Yeah. So you're the first is don't worry about the application architecture. Like I mentioned, don't when you go in that, the idea, the concept of that application and what it means to, to deliver some value, whether it's into a business or a hobby or whatever. I mean, however, you're developing application, you're doing it for a reason. You want that value to come out as quickly as possible. You want that experience. And so that first thing is you don't have to worry about the architecture anymore. So in the past, you know, you'd have to think about if it's a very large application, it's millions and millions of end-users. How do you structure that? How do you put it together? That concern is removed from you in that process? The other thing is we solve the problem of software disintegration. So with traditional development, when you develop an application and you get it into the hands of end, users get immediately starts to disintegrate. >>So there will be bugs that will appear. There will be, as far as, um, security flaws that will come up services that you use will become deprecated. We'll swap out cloud services, you know, AWS or Azure or Google, we'll swap out cloud services with different services behind the scenes version that we new versions of those that is software disintegration. As soon as you develop software today and all of these beautiful cloud services that you use and components, they often something will become outdated almost by the time you release it. A lot of times with software development projects, it literally is you start with some version or some component before you can get that out in a traditional mode. Something becomes outdated. We solve that issue. What I like to call software disintegration, we, as far as our systems, ensure we invest in that platform. And so when we need to change out those components, so services, those versions fix is for a security flaws, fixed bugs. >>We do that and it seamless. And so your application, you do not have to rewrite your application. You do not have to go through that process as a tradition, as a developer on our systems like you would, as your traditional developer, we solve that software disintegration issue. So it is it's, it's very empowering to developers to not have to worry about that. There are many, you look at the numbers today about how much is invested in innovation versus maintenance. You know, a lot of companies start out at 70% innovation, 30% as far as maintenance. And then over time that flips and you'll get to 30% of your time spent on innovations development, 70% maintenance, that burden we removed that burden. >>Those are some really powerful statements protect that you mean, I really liked the way that you described software disintegration. I've actually never heard that term before. And it kind of reminded me of, you know, when you buy a brand new car, you drive it off. The lot the value goes down right away, then before you even get things out. And on the consumer side, we know that as soon as we buy the newest iPhone, the next one's going to be out, or there's some part of it, that's going to be outdated in terms of technical debt. I was reading a stat that technical debt is expected to reach and costs businesses 5 trillion us dollars over the next 10 years. How does OutSystems helps customers address the challenges with technical debt and even reduce it? >>Yeah. If you think about the guy, the truest sense of technical debt, it's a, it's a decision that you make in the development process to basically, you know, load up the future with some work that you don't want to do right now. And so we're solving that issue where number one, we, you don't even have to make that decision. So you can go back to that concept of removing that cognitive load of, do I get the software out right now or do I get it out in the right way? And that's really what technical debt technical debt is saying. I need to get it out now. And there are some things I want to do that it'd be better if I did them now, but I'm going to go ahead and push that out into the future. You don't have to do that today with us. >>And so what happens with our systems? We invest in that platform, and this is hard. I mean, this is not an easy thing to do. This is why we have some of the best and brightest engineers focusing on this process at the heart of this, not to get too technical, but the heart of this is what we call the true change engine. But then, um, within our platform, we go through and we look at all of the changes that you need to make. So if you think of that concept of technical debt of like, oh, I want to get this into the hands of man users, but I don't want to invest in the time to do something right. It's always done right. As far as with the OutSystems platform. So we take that, we look at the intent of your change. So it's like a, it's like a process where you tell us the intent. >>When you, as a application developer, you're designing an application, you tell us the intent of the application is to look and feel. It could be some business processes can be some integrations. We determine what's the best way to do that. And then once again, from a software disintegration standpoint, we continue to invest in all the right ways to do that the best way possible. And so, I mean, we have customers that have written applications. That's 10, 15 years ago, they're still using our platform with those same applications they've added to them, but they actually have not rewritten those applications. And so if you think about the normal traditional development process, the technical debt incurred over that type of lifetime would be enormous with us. There's no technical debt. They're still using the same application. They have simply added capabilities to it. We invest in that platform. So they don't have to >>So big business outcomes there, obviously from a developer productivity perspective, but from the company wide perspective, the ability to eliminate technical debt, some significant opportunities there. Talk to me about the existing OutSystems customers. When are they going to be able to take advantage of this? What is the migration or upgrade path that they can take? >>Yeah. And so it's, it was very important to me and, and, uh, and the team, as far as our systems, to be able to integrate, to innovate as far as for customers, without disrupting customers. And we've probably all been through this path of great new technology is awesome. But then to actually utilize that technology when you're a current customer, it creates pain. And so we've invested heavily in making sure that the process is pain-free so you can use project Niamh. So we are announcing it as it was in public preview, as far as now, and then we will release it from GA as far as in the first quarter of next year. So over this timeframe, you'll be able to get in and try it out and all that continue to use your current version, which is OutSystems 11. So what we, what we affectionately call it 11, as far as Alice systems, Al systems, 11 version, and continued to use, and you can continue to use that today. >>Side-by-side and coexistence with the project, Neo and project Neo is a code name. So we will, we will have an official product name is for as at launch, but it's our it's. Our affectionate is kind of a unofficial mascot as Neo. So we call it project Neo bit of a fun thing, and you can use it side by side. And then in the future, you'll be able to migrate applications over, or you can just continue to coexist. I mean, we see a very long lifetime for OutSystems 11, it's a different platform, different technology behind the scenes project, Neos, Kubernetes base, Lennox containers. Based once again on the bill, we went in with the, just looked at it and said, rearchitect re-imagined, how would you do this? If you had the best and brightest, as far as engineers, architects, um, you know, we have, which we do, you know, very smart in those people. >>And we did that. And so we did that for our customers. And so Neo is that how systems 11 still a great choice. If you have applications on it, you can use it. And we have, we anticipate that customers will actually side by side, develop on both in which we have some customers in preview today. And that's the process that they have. They will develop on 11, they will develop on the Neo and they will continue to do that. And there's no, we, we are dedicated to making sure that there's no disruption and no pain in that process. And then when customers are ready to migrate over, if that's what they choose, we'll help them migrate over. >>You make it sound easy. And I was wondering if project Neo had anything to do with the new matrix movie, I just saw the trailer for it the other day. >>It was a happy coincidence. It is not easy. Let me, let me be clear. It is something we have been working on for three years and really this last year really kicked into high gear. And, um, you know, a lot of behind the scenes work, obviously for us, but once again, that's our value proposition. It's we do the hard work. So developers and customers don't have to do that hard work, uh, but no relations in the L I love, I do love the matrix movies. So it's a, it's a nice coincidence. >>It is a nice coincidence. Last question, Patrick, for you, you know, as we wrap up the calendar year 2021, we head into 20, 22. I think we're all very hopeful that 2022 will be a better year than the last two. What are some of the things that you see as absolutely critical for enterprises? What are they most concerned about right now? >>Yeah, I think it's look, I mean, it's, obviously it has been a crazy couple of years. And, um, and if you think about what enterprises want, I mean, they want to provide, uh, a great experiences for their customers, a great experience for their employees. Once again, digital transformation, we're where you don't even kind of talk about digital transformation more because we're in it. And I think that customers need to make sure that the experiences they provide these digital experiences are the best possible experiences. And these are differentiators. These are differentiators for employees is, are differentiators for customers. I believe that software is one of the big differentiators for businesses today and going forward, and that will continue to be so we're where businesses may be invested in supply chains and invested in certain types of technologies. Business will continue to invest in software because software is that differentiator. >>And if you look at where we fit, you can go, you can go buy, you know, some great satisfied where my software as a service off the shelf in the end, you're just like every other business you bought the same thing that everybody else has bought. You can go the traditional development route, where you invest a bunch of money. It's a high risk, takes a long time. And once again, you may not get what you want. We believe what is most important to businesses. Get that unique software that fits like a glove that is great for employees is great for their customers. And it is a unique differentiator for them. And I really see that in 2022, that's going to be big and, and going forward. They're the legs for that type of investment that companies make and their return on that is huge. >>I agree with you on that in terms of software as a differentiator. No, we're seeing every company become a software company in every industry these days to be first to survive in the last 20 months and now to be competitive, it's really kind of a must have. So Patrick, thank you for joining me on the program, talking about project Neo GA in quarter of calendar year 22 exciting stuff. We appreciate your feedback and your insights and congratulations on project Neil. Thanks, Lisa. Appreciate it for Patrick Jean I'm Lisa Martin, and you're watching the cubes continuous coverage of re-invent 2021.

(Upbeat intro music) >> Welcome to theCUBE's continuing coverage of AWS re:Invent 2021. I'm Lisa Martin and we are running one of the industry's most important and largest hybrid tech events with AWS in this ecosystem partners this year. We have two live sets, two remote sets over 100 guests talking about the next decade in cloud innovation. And we're excited to be joined by Patrick Jean the CTO of OutSystems, Patrick welcome to the program. >> Thank you, I appreciate being one of those 100 guests. >> One of the 100, one of the elite 100, we'll say it like that, right? >> Yes. >> So OutSystems has some revolutionary news. You guys are saying, you know what, developer experience needs to change, tell us more. >> It does I mean, it needs to change. And I've been in the industry developing applications for too many years to mention, basically since I was 12 years old writing software and going over that time and thinking about it, doing the traditional software development route. So many applications that take too long was costly to build, so much risk involved in it. Eventually it didn't meet all the requirements. And if you look at the investment we make in software, which is important, I mean, software is a unique differentiator for businesses. That investment has such a high-risk and a high cost and that needs to change. And it needs to change just because of the complexity that is in that process inherent in it. That's and that is what we are doing in OutSystems is tackling that problem. And from a business standpoint, it must change. >> It must change that is strong words there. So talk to me about what you're announcing what were the gaps in the market, customer feedback, were there any catalysts from the pandemic going we've got to change this developer experience and this is the time. >> For sure. I mean, if you think about from the pandemic and I mean, we were on a journey for digital transformation. We've been on this journey for a number of years the pandemic really accelerated that the experiences that we have with each other, you and me are not in the same studio today. I mean, there reasons that we use this experience remotely. We have a technology that can do it. The pandemic accelerated that. And so, so much of the experiences we have are digital experiences. And if you think about it, there's a device in between us. There's going to be a device in between all the people viewing what we're looking at. That experience that they will have with us will be basically surfaced through an application on that device. And the pandemic has really accelerated that. And that's an area that we play in, obviously for what's considered low-code application development. And if you just think about application development in general, that's what powers all of these experiences. And going back to that statement about that it needs to change. If we need these experiences to be diverse, if we need these experiences to be meaningful, if we need them to make sure that when people engage as far as what that device is something that brings, delight and pleasure to them. We need developers across the board investing in that. Today there is a very constrained market for professional developers because of the inherent complexity in software development. And so if you think about how that's almost, almost here limiting access to the people who can create those experiences, that's not a good situation. There's about 25 million developers in the world that would consider themselves developers today, seven, eight, nine, 10 billion devices out there. Think of that disparity between those two numbers. And so we need a larger number of people to actually develop applications so that experience can be much more diverse. We need to expose development to many more people. That is the problem today with software development is that it is complex, it is too specialized. It's too inherent as far with failure when you get it together. And so either you shy away from that as an organization or as an individual. To do development are you going on these very long development as far as cycles to actually create these applications? What we do is we take the approach of let's make it very simple to get into. Sometimes we call it citizen developer, low-code, basically all they're saying is let's reduce the risk of development. Let's go into a process where we make it accessible to more and more people. You can go through and develop applications with the lower risk. You can build change into that process. You can get value into end users as rapidly as possible. So that is the value proposition, that is what needs to change. >> Strong value proposition well said, Patrick. Talking about reducing the complexity, the risk as well. So go ahead and crack open what you guys are actually announcing today. >> Yeah, for sure. So we've been doing this for many years. We have software development, we have 14 million plus as far as end-users using applications that have been developed with the Allo systems platform. What we're announcing is taking some of the great benefits that we have to what you'd consider as the first part of that low-code process. Where you have a developer that has an idea, and there's a canvas in front of you. You're an artist, right, with a canvas that's what you are as a developer. And so you go in and you create that application. We've been doing this for many years and it worked really well. The thing that we're improving upon now is the ability to do that and scale that out to millions of end-users, 10 millions of end-users. So if you think about that inherent speed of developing an application, using a platform like OutSystems, we're taking that same concept and rolling that into an internet scale application, hosting architecture. So any developer that uses OutSystems, basically like it would be comparable to a traditional development team that has application architects, cloud architects, security engineers, database engineers, a whole team of very smart individuals that generally the biggest technology companies in the world can put together. Most companies can't do that, you don't have access to that type of skillset. And so we're providing that with Project Neo, which is what we're announcing today in our, at our user conference and customer conference. Is this brand new as far as platform that allows you to build these applications at scale. And this is initially built on AWS using all the great AWS technologies. If you look at what AWS has done and provided to developers today, it's amazing. It is absolutely amazing. The amount of technologies that you can leverage. It's also daunting because as a traditional developer, you have to go in and choose what do you do? It's like, there's just massive cognitive load. As far as upfront when you go in to design an application. What's up in messaging, what's up at data store, well, how do I host my application? What type of network as far as security do I use? We're taking all that heavy lifting, all that undifferentiated heavy lifting off of the developers, putting it into the Project Neo platform. Allowing a single developer or a small group of developers to actually leverage that best in class architecture on AWS today. >> So when you're talking to developers, what are some of the things that you describe as the unique differentiators of Project Neo? It sounds like this was really apt and apt time for change. But when you're talking to those folks, what do you say you know, one, two three, these are the things that make Project Neo unique. >> Yeah, so the first is don't worry about the application architecture. Like I mentioned when you go in, the idea, the concept of that application and what it means to deliver some value, whether it's into a business or a hobby or whatever. I mean, however you're developing application, you're doing it for a reason. You want that value to come out as quick as possible. You want that experience. And so that first thing is, you don't have to worry about the architecture anymore. So in the past you'd have to think about if it's a very large application, it's millions and millions of end-users. How do you structure that? How do you put it together? That concern is removed from you in that process. The other thing is we solve the problem of software disintegration. So with traditional development, when you develop an application and you get it into the hands of end users it immediately starts to disintegrate. So there will be bugs that will appear. There will be as far as security flaws that will come up services that you use will become deprecated. We'll swap out cloud services by AWS or Azure or Google. swap out cloud services with different services behind the scenes. Version, there'll be new versions of those that is software disintegration. As soon as you develop software today and all of these beautiful cloud services that you use and components. Something will become outdated almost by the time you release it. A lot of times with software development projects, it literally is you start with some version or some component before you can get that out in a traditional mode, something becomes outdated. We solved that issue. What I like to call software disintegration. We, as far as OutSystems, ensure we invest in that platform. And so when we may need to change out those components, those services, those versions fix is for security flaws, fixed bugs, we do that and it's seamless. And so your application, you do not have to rewrite your application. You do not have to go through that process as a tradition, as a developer on OutSystems like you would, as your traditional developer. We solve that software disintegration issue. So it's very empowering to developers to not have to worry about that. There are many, you look at the numbers today about how much is invested in innovation versus maintenance. A lot of companies start out at 70% innovation, 30% as far as maintenance, and then overtime that flips. And you'll get to 30% of your time spent on innovations development, 70% maintenance, that burden, we remove that burden. >> Those were some really powerful statements Patrick that you made and I really liked the way that you described software disintegration. I've actually never heard that term before. And it kind of reminded me of when you buy a brand new car, you drive it off the lot, the value goes down right away then before you even get things out. And on the consumer side, we know that as soon as we buy the newest iPhone, the next one's going to be out, or there's some part of it, that's going to be outdated. In terms of technical debt, I was reading a stat that technical debt is expected to reach in costs of businesses, 5 trillion, US dollars over the next 10 years. How does OutSystems help customers address the challenges with technical debt and even reduce it? >> Yeah, I mean if you think about in the kind of the truest sense of technical debt, it's a decision that you make in the development process to basically load up the future with some work that you don't want to do right now. And so we're solving that issue where not only, you don't even have to make that decision. So you can go back to that concept of removing that cognitive load of, do I get the software out right now or do I get it out in the right way? And that's really what technical debt, technical debt is saying I need to get it out now. And there are some things I want to do that it'd be better if I did them now, but I'm going to go ahead and push that out into the future. You don't have to do that today with us. And so what happens with OutSystems is we invest in that platform. And this is hard. I mean, this is not an easy thing to do. This is why we have some of the best and brightest engineers focusing on this process at the heart of this, not to get too technical, but the heart of this is what we call the true change engine within our platform. We go through and we look at all of the changes that you need to make. So you think of that concept of technical debt of like, ah, I want to get this in the hands of end users, but I don't want to invest in the time to do something right. It's always done right, as far as with the OutSystems platform. So we take that, we look at the intent of your change. So it's like a process where you tell us the intent. When you as a application developer, you're designing an application, you tell us the intent of the application is to look and feel. It could be some business processes this could be some integrations. We determine what's the best way to do that and then once again, from a software disintegration standpoint, we continue to invest in all the right ways to do that the best way possible. And so, I mean, we have customers that have written applications that's 10, 15 years ago. They're still using our platform with those same applications they've added to them, but they have not rewritten those applications. And so if you think about the normal traditional development process, the technical debt incurred over that type of lifetime would be enormous. With us there's no technical debt. They're still using the same application they've simply added capabilities to it. We invest in that platform so they don't have to. >> So big business outcomes down, obviously from a developer productivity perspective, but from the company wide perspective, the ability to eliminate technical debt, some significant opportunities there. Talk to me about the existing OutSystems customers. When are they going to be able to take advantage of this? What is the migration or upgrade path that they can take and when? >> Yeah and so it is very important to me and the team as far as OutSystems to be able to integrate, to innovate as far as for customers, without disrupting customers. And we've probably all been through this path of great new technology is awesome. But then to actually utilize that technology when you're a current customer, it creates pain. And so we've invested heavily in making sure that the process is pain-free. So you can use Project Neo. So we are announcing it as in, it was in public preview as far as now, and then we will release it from GA as far as in the first quarter of next year. So over this timeframe, you'll be able to get in and try it out and all that. Continue to use your current version, which is OutSystems 11. So what we affectionately call O-11, as far as Allo systems. The Allo systems 11 version continue to use, and you can continue to use that today side-by-side and coexistence with the Project Neo. And Project Neo is a code name. So we will have an official product name as for as at launch but it's our affectionate it's kind of a unofficial mascot as Neo. So we call the Project Neo is a little bit of a fun name and you can use it side by side and then in the future, you'll be able to migrate applications over. Or you can just continue to co-exist. I mean, we see a very long lifetime for OutSystems 11, it's a different platform, different technology behind the scenes. Project Neo's Kubernetes-base Linux containers. Based once again, on the ability, we went in with the gist and looked at it and said, re-architect, re-imagine, how would you do this if you had the best and brightest as far as engineers, architects, we have, which we do. Various market and those people and we did that. And so we did that for our customers. And so Neo is that OutSystems 11 still a great choice. If you have applications on it, you can use it. And we have, we anticipate the customers will actually side by side develop on both in which we have some customers in preview today. And that's the process that they have. They will develop on 11, they will develop on Neo and they will continue to do that. And there's no, we are dedicated to making sure that there's no disruption and no pain in that process. And then when customers are ready to migrate over, if that's what they choose, we'll help them migrate over. >> You make it sound easy. And I was wondering if Project Neo had anything to do with the new matrix movie I just saw the trailer for it the other day, I wonder if this is related. >> It was a happy coincidence. It is not easy let me, let me be clear. It is something we have been working on for three years and really this last year really kicked into high gear. And a lot of behind the scenes work, obviously for us, but once again, that's our value proposition. It's we do the hard work. So developers and the customers don't have to do that hard work. But no relations to Neo, I love, I do love the matrix movies. So it's a nice coincidence. (Lisa laughs) >> It is a nice coincidence. Last question, Patrick, for you, as we wrap up the calendar year 2021, we heading into 2022. I think we're all very hopeful that 2022 will be a better year than the last two. What are some of the things that you see as absolutely critical for enterprises? What are they most concerned about right now? >> Yeah, I think it's, look I mean, it's obviously it has been a crazy a couple of years. And if you think about what enterprises want, I mean, they want to provide a great experiences for their customers, a great experience for their employees. Once again, digital transformation, where you don't even kind of talk about digital transformation more because we're in it. And I think that customers need to make sure that the experiences they provide these digital experiences are the best possible experiences. And these are differentiators. These are differentiators for employees. These are differentiators for customers. I believe that software is one of the big differentiators for businesses today and going forward. And that will continue to be so where businesses may be invested in supply chains, invested in certain types of technologies. Business will continue to invest in software because software is that differentiator. And if you look at where we fit, you can go, you can go buy, some great set of software, my software as a service off the shelf. In the end, you're just like every other business you bought the same thing that everybody else had bought. You can go the traditional development route, where you invest a bunch of money, it's a high risk, takes a long time. And once again, you may not get what you want. We believe what is most important to businesses. Get that unique software that fits like a glove that is great for employees, it's great for their customers. And it is a unique differentiator for them. And I really see that in 2022, that's going to be big and going forward. They're the legs for that type of investment that companies make and they return on that is huge. >> I agree with you on that in terms of software as a differentiator. Now we're seeing every company become a software company in every industry these days to be, first to survive in the last 20 months and now to be competitive, it's really kind of a must have. So, Patrick thank you for joining me on the program, talking about Project Neo, GA in the first quarter of calendar year 22. Exciting stuff we appreciate your feedback and your insights and congratulations on Project Neo. >> Thanks, Lisa, appreciate it. >> For Patrick Jean, I'm Lisa Martin, and you're watching theCUBEs continuous coverage of re:Invent 2021. (Outro music)

>>I'm john free with the Q we are here. It's exciting news around the next evolution switching, Sony jean Donny, co founder and chief business officer Pensando and David Hughes chief product and technology officer Aruba HP. Welcome back. We just heard from Antonio neary and john Chambers about the HPV Ruba partnership with Pensando and the new switching platform. Tell me more about the exciting news you're announcing? >>Yeah, I'm really excited today to be introducing the CX 10,000 distributed services switch. It's a brand new class of switch way bringing together the best of Aruba switching technology adding to R C X portfolio combining with Pence Sandoz technology that technology embedded in the platform. The problem we're solving is that in a traditional data center, all of those services like fire walling and low balancing provided by centralized appliances. And while that might be okay for north south traffic traffic that's going in and out of the data center. It's not scalable and it's not cost effective to apply to every service in every port to every flow traversing their data center As we all know with microservices more and more of the traffickers east west over 70% today and growing and so what we're doing here with the C X 10,000 is giving enterprises away to take the smart nick technology that's been proven out by hyper scholars and introduce it into their data centers in a very cost effective and easy to deploy way we're embedding that capability in the top of rack switch so that we can apply Fireable services, low balancing services to every port To every flow, delivering 100 times a scale in terms of a CLS 10 times of performance, in terms of encryption at a third of the cost of those traditional network architectures. So it's a super exciting time, >>love the speed, love the energy there. But I gotta ask what makes this a new category of switch. >>Well if you take a look at the journey we have been on as we have evolved our data centers and the applications have evolved for our customers. Uh and the world is now a bold new world of multi cloud. Uh the architecture is in the data center which are leaves spine architectures have become the new norm. Software defined, networking is pervasively deployed by our customers but as this journey began five or seven or even about 10 years ago uh and has culminated into a much more mature set of building blocks. We have taken the problem from one space of automating networks in the data center to then introducing lots and lots of expensive appliances to bring about security for example, or the state full services, whether it's load balancing or whether it's encryption and visibility and telemetry types of services. Now the customers had to try, you know, trombone all the traffic in and out of these appliances driving up the cost uh and the complexity and when time comes to troubleshoot these environments, it's extremely complex because you're trying to rationalize fabrics coming from one place appliances coming from four or five different vendors, maintaining all the software elements that need to be kept track off. Uh and as more and more customers want to aspire towards zero trust security model. Uh we need to start to embrace a lot of the principles that have been implemented by the hyper scholars and the cloud vendors, which is doing away with the appliances doing away with agent technology on servers, but instead to bring that technology for east west uh into play as well as to ensure that if there are bad actors that are landing inside of the data centers that they do not have the ability to, you know, create attack surfaces with complete lateral movement. Today, that is possible. Uh if you look at 70% of all the attacks that have been happening here in the past few years, it's as a result of having a attack surface which is pretty large in the data centers. And that gets further complicated when you move towards a multi cloud environment where the perimeter of the data center is now moving into the edge. Whether that edges, whether fleet resides for our customers or whether that edge happens to be a co location edge where you're building your own rampant off ramps. So I think the compelling event essentially is driven by the whole notion of distribution of services and having them available from a security and from a services point of view and these are state full services as close to the workload as you possibly can get them. >>So you guys really hit on some key points, their cloud, native microservices East west, north south, um no perimeter edge. These are topics that we would talk about kind of individually over the years, it's happening now all at the same time, this is causing a lot of complexities and then the security challenges you just laid out are everywhere. This brings up a big conversation around solving this. How does this new architecture, this solution solve the complexity and the security challenges in the data center. >>If you look at the use cases that our customers are talking about. The first, the initial use case really is to bring about security and state full security for east west traffic right into the fabric of their data centers. So having the ability to deliver that while eliminating the complex appliances only to do the job which they do very well, which is not South protection of services. Uh that also allows us the ability then to start to deliver visibility and telemetry at the same time that we're delivering state full security firewall and micro segmentation services because what I cannot see, I cannot secure. Uh so those two elements are initial use cases out of the box for our customers as we deliver this platform to them and then as more and more use cases that are becoming evident to us through customer interactions come into play. For example, the co location edge that I would like. David to walk you through a bit more in terms of how we help solve for that use case. >>So for the cooler use case, I think we're moving from a world where people talk about data centers to now talking about centers of data and those centers of data. Yes, they can be in a core private data center, they could be in the cloud but more and more they're going to be distributed around the edge in co location environments. And what we need to be able to do is extend those services that were provided in the data center to be provided in those Kahlo's at the edge And again we want to do that without having to deploy a whole rack of appliances that may be cost more than a computer itself and so with the CX- 10,000 we can have that as a top of rack switch for that polo. And from that switch deploy all of the encryption and firewall ng services that that polo requires. And what's important is that we're doing it with the same policy framework under the same management system across the whole enterprise in the data center as well as in these co location environments and out into the cloud. >>So you guys mentioned visibility and a quick follow up on this question because you mentioned visibility can't see it, you can't protect it. But also there's a lot of workloads that people are trying to automate. These are two factors. Can you guys just double down on that? I want to just get that out there because I think this becomes a big thing. >>I think policy having the ability to have an intent based policy that is a foundational technology building block that we are brought together is a very important element. And then when you map it back to tools that Aruba is extending support for including this platform, become very valuable. So David, why don't you walk us >>through? You know, I think one of the advantages that we bring is that this is an extension of the Aruba C X switching portfolio. So yeah, it's a cloud native microservices, very modern switch architecture and we have a comprehensive management platform, the Aruba fabric controller. And so what we are doing is making sure that everything fits together nicely, that we're delivering a complete solution to our customers. But one important thing to mention here is that we are thinking about how customers can do this step by step. So no, we're not requiring them to rebuild their entire data center, They can do this one rack at a time. We can work with their existing spine and deploy one leaf at a time in a very measured way. And so we think it's a great way for enterprises to be able to consume this modern distributed platform. >>That's a great segment. The next question. I mean I totally see this as you guys are talking about the cloud native trend, driving a cloud operational model to every edge. The data center is just another edge. It's a center of data. Love that. I love that line. So I have to kind of ask the operational side of the question, how would an enterprise customers manage all this take us through the nuts and bolts of deploying and managing of his gum? A customer >>That's a very good question. If you take a look at the customer's deployment models and let's let's take the example of they want to now bring in this technology and build a part or highly secure part with it for east west and to make sure that they're protecting 100% of that east west traffic. I think that leveraging all the building blocks that we have innovated between us and Aruba. We want to make sure that the ecosystem that the customer has built, they want whether they have built it with companies like Splunk and service now or Guardianco, they want integration points will be made available to them. If you take a look at, take a step back and say for these environments as you aspire to go toward zero trade security. The issues of inserting security appliances into network flows and having the ability to map it to the knowledge of applications and their dependencies for policy becomes an important function to tackle. So once you accept that, Okay, I have state full security functions built into this top of rack device available for my applications and all workloads, whether they're container workloads, bare metal workload, virtualized workloads uh and I have complete visibility into those workloads without compromising on connectivity and I can control through enforcement of policy where I need it because now security is part of the fabric, it's not a bolt on. Then comes the job of integration with an ecosystem. So whether you're looking at seem and sold companies where we are delivering in close collaboration with Splunk, A Pensando app for Splunk there's also going to be the availability of an elastic module, A plug in module. Uh then turn attention to what's more automation and devops and civil playbooks for the C X 10-K will be made available day one so that where you do not have the ability to deploy the A. F. C. You can use your existing answerable toolkit and they're making those playbooks available to our customers. Uh They want integration with application discovery mapping companies like Guardianco, allowing them to discover who's talking to whom and push and enforce that policy through the C X 10-K will allow for more automated deployments of those policies and finally, compliance integration with vendors like too thin for continuous security compliance monitoring becomes extremely important as the screen depicts a lot of lot of visualization capabilities with companies like Elk which are in beta today and answerable and Splunk and Elk will all be targeted at first customer shipment. So again, telemetry visibility with the integration of the ecosystem. Uh, it becomes a very powerful combination for the customers as they look to operationalize this for day to day three and they, you know, day one, day two, day three automation. >>That's awesome. David, I'd like to let you weigh in on this whole question of operations because you're hitting all the marks here that are relevant cloud, native microservices, apps, explosion and data volume and velocity, hyper scale operational cloud operations, performance, price point security all in this one solution. This is big. Um, it's not like you mentioned earlier, it's not a rip and replace but you can roll it out how how do you see a customer best operational izing this new, >>You know, I think the answer is a little bit different for each customer but you are very careful at the beginning, we introduced this. It's an evolution of switching. It's not a revolution where we have to replace everything and I think that's really exciting is that it builds on the foundational architecture of leaf and spine. And what we're able to do is let that customer introduced these new capabilities one leaf at a time. So maybe when they're upgrading from 10 gigs to 25 gigs, it's a great time for them to introduce this capability into their data center um and then depending on their application, you know, it may be, as Sony said that they've got one particular application, a crown jewel application and so they want to build out that in one rack and provide, you know, very, very robust East west as well as north south um security around that application, but there's so many different ways that customers can deploy this technology and what's really exciting is now is we're beginning to work with our customers, learning about these new use cases and then feeding that back into our roadmap and we all >>know, as you get down lower in the network layer, security is distributed architecture. So everything is paramount like security, super relevant, great conversation, I gotta ask what's next with this technology. Yeah, >>well, you know the teams, the two engineering teams are working together and this is step one on, on a really exciting new path, I don't know, Sony, what would you say? >>I think there's a lot more to come here. This is just a starting point. We have an incredibly strong partnership and go to market partnership here with Uber team with this platform. It is just the beginning uh and it will lead our customers onto the multi cloud journey. Uh and last but not least, I would like to say that you know, in closing uh that are seldom opportunities where you look at disrupting the way things are happening while fitting into customers existing models. So this is, as I said with everything being software defined, you will continue to see as delivering at great velocity more and more software defined services, whether it's encryption, Lord balancing and other state full services over time. Making this technology easier to deploy by fitting into the existing ecosystem and continuing to provide them with the 100 extra scale, 10 X. The performance as well as the ability to do it at a third of the same, you know, at the third of the cost of what they would need to if they had to build this uh today with disparate devices, >>exciting news in the industry. You guys are the pros you've seen all the waves of innovation over the years. I guess my final final question would be, how would you summarize this point in time right now? This is pretty um exciting all this is all happening At the same time, customers are having opportunity to innovate the pandemic has shown a lot of scale and and the need for stability and security. This is a special moment. How would you guys weigh in on that? >>Yeah, I think about it every decade, there's a change in how data centers a belt. And so this is the change that's happening this decade. Moving to a distributed services, switch. The other big mega trend that I see is this move, as I said from data centers to stand as a data and the opportunity for customers to use this technology as they move out to the edge. Have distributed compute and tell us, what do you think Sony? >>I think I couldn't agree more. I think there are so many various technology transitions occurring now. The cloud being the biggest one. Uh the explosion of data and uh, you know, the customers making decisions of having a distributed model And if indeed two thirds, if not 75% of all data will be processed at the edge over the next few years. This architecture is prime for the enterprise to go leverage their best practices of today while they can gradually move that architecture is for the future, which is a multi cloud future >>centers of data, large scale cloud operations automation. The speed of innovation has never seen this before. Uh It's exciting time. Sunny, thank you for coming on. And David, thanks for chatting about this exciting new announcement. Thank you very much. >>Thank you. Thank you. >>This is the power of and hp. Ruba and Pensando partnership. I'm john forward the cube. Thanks for watching. Mhm

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle in 2000 >>nine. Hal Varian, Google's chief economist, said that statisticians would be the sexiest job in the coming decade. The modern big data movement >>really >>took off later in the following year. After the Second Hadoop World, which was hosted by Claudette Cloudera in New York City. Jeff Ham Abakar famously declared to me and John further in the Cube that the best minds of his generation, we're trying to figure out how to get people to click on ads. And he said that sucks. The industry was abuzz with the realization that data was the new competitive weapon. Hadoop was heralded as the new data management paradigm. Now, what actually transpired Over the next 10 years on Lee, a small handful of companies could really master the complexities of big data and attract the data science talent really necessary to realize massive returns as well. Back then, Cloud was in the early stages of its adoption. When you think about it at the beginning of the last decade and as the years passed, Maurin Mawr data got moved to the cloud and the number of data sources absolutely exploded. Experimentation accelerated, as did the pace of change. Complexity just overwhelmed big data infrastructures and data teams, leading to a continuous stream of incremental technical improvements designed to try and keep pace things like data Lakes, data hubs, new open source projects, new tools which piled on even Mawr complexity. And as we reported, we believe what's needed is a comm pleat bit flip and how we approach data architectures. Our next guest is Jean Marc de Connie, who is the director of emerging technologies That thought works. John Mark is a software engineer, architect, thought leader and adviser to some of the world's most prominent enterprises. She's, in my view, one of the foremost advocates for rethinking and changing the way we create and manage data architectures. Favoring a decentralized over monolithic structure and elevating domain knowledge is a primary criterion. And how we organize so called big data teams and platforms. Chamakh. Welcome to the Cube. It's a pleasure to have you on the program. >>Hi, David. This wonderful to be here. >>Well, okay, so >>you're >>pretty outspoken about the need for a paradigm shift in how we manage our data and our platforms that scale. Why do you feel we need such a radical change? What's your thoughts there? >>Well, I think if you just look back over the last decades you gave us, you know, a summary of what happened since 2000 and 10. But if even if we go before then what we have done over the last few decades is basically repeating and, as you mentioned, incrementally improving how we've managed data based on a certain assumptions around. As you mentioned, centralization data has to be in one place so we can get value from it. But if you look at the parallel movement off our industry in general since the birth of Internet, we are actually moving towards decentralization. If we think today, like if this move data side, if he said the only way Web would work the only way we get access to you know various applications on the Web pages is to centralize it. We would laugh at that idea, but for some reason we don't. We don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, you know, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organization there beyond the bounds of organization. And then look back and say Okay, if that's the trend off our industry in general, Um, given the fabric of computation and data that we put in, you know globally in place, then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me, that requires a paradigm shift, a full stack from how we organize our organizations, how we organize our teams, how we, you know, put a technology in place, um, to to look at it from a decentralized angle. >>Okay, so let's let's unpack that a little bit. I mean, you've spoken about and written that today's big architecture and you basically just mentioned that it's flawed, So I wanna bring up. I love your diagrams of a simple diagram, guys, if you could bring up ah, figure one. So on the left here we're adjusting data from the operational systems and other enterprise data sets and, of course, external data. We cleanse it, you know, you've gotta do the do the quality thing and then serve them up to the business. So So what's wrong with that picture that we just described and give granted? It's a simplified form. >>Yeah, quite a few things. So, yeah, I would flip the question may be back to you or the audience if we said that. You know, there are so many sources off the data on the Actually, the data comes from systems and from teams that are very diverse in terms off domains. Right? Domain. If if you just think about, I don't know retail, Uh, the the E Commerce versus Order Management versus customer This is a very diverse domains. The data comes from many different diverse domains. And then we expect to put them under the control off a centralized team, a centralized system. And I know that centralization. Probably if you zoom out, it's centralized. If you zoom in it z compartmentalized based on functions that we can talk about that and we assume that the centralized model will be served, you know, getting that data, making sense of it, cleansing and transforming it then to satisfy in need of very diverse set of consumers without really understanding the domains, because the teams responsible for it or not close to the source of the data. So there is a bit of it, um, cognitive gap and domain understanding Gap, um, you know, without really understanding of how the data is going to be used, I've talked to numerous. When we came to this, I came up with the idea. I talked to a lot of data teams globally just to see, you know, what are the pain points? How are they doing it? And one thing that was evident in all of those conversations that they actually didn't know after they built these pipelines and put the data in whether the data warehouse tables or like, they didn't know how the data was being used. But yet the responsible for making the data available for these diverse set of these cases, So s centralized system. A monolithic system often is a bottleneck. So what you find is, a lot of the teams are struggling with satisfying the needs of the consumers, the struggling with really understanding the data. The domain knowledge is lost there is a los off understanding and kind of in that in that transformation. Often, you know, we end up training machine learning models on data that is not really representative off the reality off the business. And then we put them to production and they don't work because the semantic and the same tax off the data gets lost within that translation. So we're struggling with finding people thio, you know, to manage a centralized system because there's still the technology is fairly, in my opinion, fairly low level and exposes the users of those technologies. I said, Let's say warehouse a lot off, you know, complexity. So in summary, I think it's a bottleneck is not gonna, you know, satisfy the pace of change, of pace, of innovation and the pace of, you know, availability of sources. Um, it's disconnected and fragmented, even though the centralizes disconnected and fragmented from where the data comes from and where the data gets used on is managed by, you know, a team off hyper specialized people that you know, they're struggling to understand the actual value of the data, the actual format of the data, so it's not gonna get us where our aspirations and ambitions need to be. >>Yes. So the big data platform is essentially I think you call it, uh, context agnostic. And so is data becomes, you know, more important, our lives. You've got all these new data sources, you know, injected into the system. Experimentation as we said it with the cloud becomes much, much easier. So one of the blockers that you've started, you just mentioned it is you've got these hyper specialized roles the data engineer, the quality engineer, data scientists and and the It's illusory. I mean, it's like an illusion. These guys air, they seemingly they're independent and in scale independently. But I think you've made the point that in fact, they can't that a change in the data source has an effect across the entire data lifecycle entire data pipeline. So maybe you could maybe you could add some color to why that's problematic for some of the organizations that you work with and maybe give some examples. >>Yeah, absolutely so in fact, that initially the hypothesis around that image came from a Siris of requests that we received from our both large scale and progressive clients and progressive in terms of their investment in data architectures. So this is where clients that they were there were larger scale. They had divers and reached out of domains. Some of them were big technology tech companies. Some of them were retail companies, big health care companies. So they had that diversity off the data and the number off. You know, the sources of the domains they had invested for quite a few years in, you know, generations. If they had multi generations of proprietary data warehouses on print that they were moving to cloud, they had moved to the barriers, you know, revisions of the Hadoop clusters and they were moving to the cloud. And they the challenges that they were facing were simply there were not like, if I want to just, like, you know, simplifying in one phrase, they were not getting value from the data that they were collecting. There were continuously struggling Thio shift the culture because there was so much friction between all of these three phases of both consumption of the data and transformation and making it available consumption from sources and then providing it and serving it to the consumer. So that whole process was full of friction. Everybody was unhappy. So its bottom line is that you're collecting all this data. There is delay. There is lack of trust in the data itself because the data is not representative of the reality has gone through a transformation. But people that didn't understand really what the data was got delayed on bond. So there is no trust. It's hard to get to the data. It's hard to create. Ultimately, it's hard to create value from the data, and people are working really hard and under a lot of pressure. But it's still, you know, struggling. So we often you know, our solutions like we are. You know, Technologies will often pointed to technology. So we go. Okay, This this version of you know, some some proprietary data warehouse we're using is not the right thing. We should go to the cloud, and that certainly will solve our problems. Right? Or warehouse wasn't a good one. Let's make a deal Lake version. So instead of you know, extracting and then transforming and loading into the little bits. And that transformation is that, you know, heavy process, because you fundamentally made an assumption using warehouses that if I transform this data into this multi dimensional, perfectly designed schema that then everybody can run whatever choir they want that's gonna solve. You know everybody's problem, but in reality it doesn't because you you are delayed and there is no universal model that serves everybody's need. Everybody that needs the divers data scientists necessarily don't don't like the perfectly modeled data. They're looking for both signals and the noise. So then, you know, we've We've just gone from, uh, et elles to let's say now to Lake, which is okay, let's move the transformation to the to the last mile. Let's just get load the data into, uh into the object stores into semi structured files and get the data. Scientists use it, but they're still struggling because the problems that we mentioned eso then with the solution. What is the solution? Well, next generation data platform, let's put it on the cloud, and we sell clients that actually had gone through, you know, a year or multiple years of migration to the cloud. But with it was great. 18 months I've seen, you know, nine months migrations of the warehouse versus two year migrations of the various data sources to the clubhouse. But ultimately, the result is the same on satisfy frustrated data users, data providers, um, you know, with lack of ability to innovate quickly on relevant data and have have have an experience that they deserve toe have have a delightful experience off discovering and exploring data that they trust. And all of that was still a missed so something something else more fundamentally needed to change than just the technology. >>So then the linchpin to your scenario is this notion of context and you you pointed out you made the other observation that look, we've made our operational systems context aware. But our data platforms are not on bond like CRM system sales guys very comfortable with what's in the CRM system. They own the data. So let's talk about the answer that you and your colleagues are proposing. You're essentially flipping the architecture whereby those domain knowledge workers, the builders, if you will, of data products or data services there now, first class citizens in the data flow and they're injecting by design domain knowledge into the system. So So I wanna put up another one of your charts. Guys, bring up the figure to their, um it talks about, you know, convergence. You showed data distributed domain, dream and architecture. Er this self serve platform design and this notion of product thinking. So maybe you could explain why this approach is is so desirable, in your view, >>sure. The motivation and inspiration for the approach came from studying what has happened over the last few decades in operational systems. We had a very similar problem prior to micro services with monolithic systems, monolithic systems where you know the bottleneck. Um, the changes we needed to make was always, you know, our fellow Noto, how the architecture was centralized and we found a nice nation. I'm not saying this is the perfect way of decoupling a monolith, but it's a way that currently where we are in our journey to become data driven, um is a nice place to be, um, which is distribution or decomposition off your system as well as organization. I think when we whenever we talk about systems, we've got to talk about people and teams that's responsible for managing those systems. So the decomposition off the systems and the teams on the data around domains because that's how today we are decoupling our business, right? We're decoupling our businesses around domains, and that's a that's a good thing and that What does that do really for us? What it does? Is it localizes change to the bounded context of fact business. It creates clear boundary and interfaces and contracts between the rest of the universe of the organization on that particular team, so removes the friction that often we have for both managing the change and both serving data or capability. So it's the first principle of data meshes. Let's decouple this world off analytical data the same to mirror the same way we have to couple their systems and teams and business why data is any different. And the moment you do that, So you, the moment you bring the ownership to people who understands the data best, then you get questions that well, how is that any different from silence that's connected databases that we have today and nobody can get to the data? So then the rest of the principles is really to address all of the challenges that comes with this first principle of decomposition around domain Context on the second principle is well, we have to expect a certain level off quality and accountability and responsibility for the teams that provide the data. So let's bring product thinking and treating data as a product to the data that these teams now, um share and let's put accountability around. And we need a new set of incentives and metrics for domain teams to share the data. We need to have a new set off kind of quality metrics that define what it means for the data to be a product. And we can go through that conversation perhaps later eso then the second principle is okay. The teams now that are responsible, the domain teams responsible for the analytical data need to provide that data with a certain level of quality and assurance. Let's call that a product and bring products thinking to that. And then the next question you get asked off by C. E. O s or city or the people who build the infrastructure and, you know, spend the money. They said, Well, it's actually quite complex to manage big data, and now we're We want everybody, every independent team to manage the full stack of, you know, storage and computation and pipelines and, you know, access, control and all of that. And that's well, we have solved that problem in operational world. And that requires really a new level of platform thinking toe provide infrastructure and tooling to the domain teams to now be able to manage and serve their big data. And that I think that requires reimagining the world of our tooling and technology. But for now, let's just assume that we need a new level of abstraction to hide away ton of complexity that unnecessarily people get exposed to and that that's the third principle of creating Selves of infrastructure, um, to allow autonomous teams to build their domains. But then the last pillar, the last you know, fundamental pillar is okay. Once you distributed problem into a smaller problems that you found yourself with another set of problems, which is how I'm gonna connect this data, how I'm gonna you know, that the insights happens and emerges from the interconnection of the data domains right? It does not necessarily locked into one domain. So the concerns around interoperability and standardization and getting value as a result of composition and interconnection of these domains requires a new approach to governance. And we have to think about governance very differently based on a Federated model and based on a computational model. Like once we have this powerful self serve platform, we can computational e automate a lot of governance decisions. Um, that security decisions and policy decisions that applies to you know, this fabric of mesh not just a single domain or not in a centralized. Also, really. As you mentioned that the most important component of the emissions distribution of ownership and distribution of architecture and data the rest of them is to solve all the problems that come with that. >>So very powerful guys. We actually have a picture of what Jamaat just described. Bring up, bring up figure three, if you would tell me it. Essentially, you're advocating for the pushing of the pipeline and all its various functions into the lines of business and abstracting that complexity of the underlying infrastructure, which you kind of show here in this figure, data infrastructure is a platform down below. And you know what I love about this Jama is it to me, it underscores the data is not the new oil because I could put oil in my car I can put in my house, but I can't put the same court in both places. But I think you call it polyglot data, which is really different forms, batch or whatever. But the same data data doesn't follow the laws of scarcity. I can use the same data for many, many uses, and that's what this sort of graphic shows. And then you brought in the really important, you know, sticking problem, which is that you know the governance which is now not a command and control. It's it's Federated governance. So maybe you could add some thoughts on that. >>Sure, absolutely. It's one of those I think I keep referring to data much as a paradigm shift. And it's not just to make it sound ground and, you know, like, kind of ground and exciting or in court. And it's really because I want to point out, we need to question every moment when we make a decision around how we're going to design security or governance or modeling off the data, we need to reflect and go back and say, um, I applying some of my cognitive biases around how I have worked for the last 40 years, I have seen it work. Or do I do I really need to question. And we do need to question the way we have applied governance. I think at the end of the day, the rule of the data governance and objective remains the same. I mean, we all want quality data accessible to a diverse set of users. And these users now have different personas, like David, Personal data, analyst data, scientists, data application, Um, you know, user, very diverse personal. So at the end of the day, we want quality data accessible to them, um, trustworthy in in an easy consumable way. Um, however, how we get there looks very different in as you mentioned that the governance model in the old world has been very commander control, very centralized. Um, you know, they were responsible for quality. They were responsible for certification off the data, you know, applying making sure the data complies. But also such regulations Make sure you know, data gets discovered and made available in the world of the data mesh. Really. The job of the data governance as a function becomes finding that equilibrium between what decisions need to be um, you know, made and enforced globally. And what decisions need to be made locally so that we can have an interoperable measure. If data sets that can move fast and can change fast like it's really about instead of hardest, you know, kind of putting the putting those systems in a straitjacket of being constant and don't change, embrace, change and continuous change of landscape because that's that's just the reality we can't escape. So the role of governance really the governance model called Federated and Computational. And by that I mean, um, every domain needs to have a representative in the governance team. So the role of the data or domain data product owner who really were understand the data that domain really well but also wears that hacks of a product owner. It is an important role that had has to have a representation in the governance. So it's a federation off domains coming together, plus the SMEs and people have, you know, subject matter. Experts who understands the regulations in that environmental understands the data security concerns, but instead off trying to enforce and do this as a central team. They make decisions as what need to be standardized, what need to be enforced. And let's push that into that computational E and in an automated fashion into the into the camp platform itself. For example, instead of trying to do that, you know, be part of the data quality pipeline and inject ourselves as people in that process, let's actually, as a group, define what constitutes quality, like, how do we measure quality? And then let's automate that and let Z codify that into the platform so that every native products will have a C I City pipeline on as part of that pipeline. Those quality metrics gets validated and every day to product needs to publish those SLOC or service level objectives. So you know, whatever we choose as a measure of quality, maybe it's the, you know, the integrity of the data, the delay in the data, the liveliness of it, whatever the are the decisions that you're making, let's codify that. So it's, um, it's really, um, the role of the governance. The objectives of the governance team tried to satisfies the same, but how they do it. It is very, very different. I wrote a new article recently trying to explain the logical architecture that would emerge from applying these principles. And I put a kind of light table to compare and contrast the roll off the You know how we do governance today versus how we will do it differently to just give people a flavor of what does it mean to embrace the centralization? And what does it mean to embrace change and continuous change? Eso hopefully that that that could be helpful. >>Yes, very so many questions I haven't but the point you make it to data quality. Sometimes I feel like quality is the end game. Where is the end game? Should be how fast you could go from idea to monetization with the data service. What happens again? You sort of address this, but what happens to the underlying infrastructure? I mean, spinning a PC to S and S three buckets and my pie torches and tensor flows. And where does that that lives in the business? And who's responsible for that? >>Yeah, that's I'm glad you're asking this question. Maybe because, um, I truly believe we need to re imagine that world. I think there are many pieces that we can use Aziz utilities on foundational pieces, but I but I can see for myself a 5 to 7 year roadmap of building this new tooling. I think, in terms of the ownership, the question around ownership, if that would remains with the platform team, but and perhaps the domain agnostic, technology focused team right that there are providing instead of products themselves. And but the products are the users off those products are data product developers, right? Data domain teams that now have really high expectations in terms of low friction in terms of lead time to create a new data product. Eso We need a new set off tooling, and I think with the language needs to shift from, You know, I need a storage buckets. So I need a storage account. So I need a cluster to run my, you know, spark jobs, too. Here's the declaration of my data products. This is where the data for it will come from. This is the data that I want to serve. These are the policies that I need toe apply in terms of perhaps encryption or access control. Um, go make it happen. Platform, go provision, Everything that I mean so that as a data product developer. All I can focus on is the data itself, representation of semantic and representation of the syntax. And make sure that data meets the quality that I have that I have to assure and it's available. The rest of provisioning of everything that sits underneath will have to get taken care of by the platform. And that's what I mean by requires a re imagination and in fact, Andi, there will be a data platform team, the data platform teams that we set up for our clients. In fact, themselves have a favorite of complexity. Internally, they divide into multiple teams multiple planes, eso there would be a plane, as in a group of capabilities that satisfied that data product developer experience, there would be a set of capabilities that deal with those need a greatly underlying utilities. I call it at this point, utilities, because to me that the level of abstraction of the platform is to go higher than where it is. So what we call platform today are a set of utilities will be continuing to using will be continuing to using object storage, will continue using relation of databases and so on so there will be a plane and a group of people responsible for that. There will be a group of people responsible for capabilities that you know enable the mesh level functionality, for example, be able to correlate and connects. And query data from multiple knows. That's a measure level capability to be able to discover and explore the measure data products as a measure of capability. So it would be set of teams as part of platforms with a strong again platform product thinking embedded and product ownership embedded into that. To satisfy the experience of this now business oriented domain data team teams s way have a lot of work to do. >>I could go on. Unfortunately, we're out of time. But I guess my first I want to tell people there's two pieces that you put out so far. One is, uh, how to move beyond a monolithic data lake to a distributed data mesh. You guys should read that in a data mesh principles and logical architectures kind of part two. I guess my last question in the very limited time we have is our organization is ready for this. >>E think the desire is there I've bean overwhelmed with number off large and medium and small and private and public governments and federal, you know, organizations that reached out to us globally. I mean, it's not This is this is a global movement and I'm humbled by the response of the industry. I think they're the desire is there. The pains are really people acknowledge that something needs to change. Here s so that's the first step. I think that awareness isa spreading organizations. They're more and more becoming aware. In fact, many technology providers are reach out to us asking what you know, what shall we do? Because our clients are asking us, You know, people are already asking We need the data vision. We need the tooling to support. It s oh, that awareness is there In terms of the first step of being ready, However, the ingredients of a successful transformation requires top down and bottom up support. So it requires, you know, support from Chief Data Analytics officers or above the most successful clients that we have with data. Make sure the ones that you know the CEOs have made a statement that, you know, we want to change the experience of every single customer using data and we're going to do, we're going to commit to this. So the investment and support, you know, exists from top to all layers. The engineers are excited that maybe perhaps the traditional data teams are open to change. So there are a lot of ingredients. Substance to transformation is to come together. Um, are we really ready for it? I think I think the pioneers, perhaps the innovators. If you think about that innovation, careful. My doctors, probably pioneers and innovators and leaders. Doctors are making making move towards it. And hopefully, as the technology becomes more available, organizations that are less or in, you know, engineering oriented, they don't have the capability in house today, but they can buy it. They would come next. Maybe those are not the ones who aren't quite ready for it because the technology is not readily available. Requires, you know, internal investment today. >>I think you're right on. I think the leaders are gonna lead in hard, and they're gonna show us the path over the next several years. And I think the the end of this decade is gonna be defined a lot differently than the beginning. Jammeh. Thanks so much for coming in. The Cuban. Participate in the >>program. Pleasure head. >>Alright, Keep it right. Everybody went back right after this short break.

>> From around the globe it's the CUBE with digital coverage of Devops Virtual Forum, brought to you by Broadcom. >> Continuing our conversations here at Broadcom's DevOps Virtual Forum. Lisa Martin here, please do welcome back to the program. Serge Lucio, the general manager of the Enterprise Software Division at Broadcom. Hey Serge welcome. >> Thank you. Good to be here. >> So I know you were just participating with the BizOps manifesto that just happened recently. I just had the chance to talk with Jeffrey Hammond and he unlocked this really interesting concept but I wanted to get your thoughts on, spiritual co-location as really a necessity for BizOps to succeed in this unusual time in which we're living. What are your thoughts on spiritual co-location in terms of cultural change versus adoption of technologies? >> Yeah, it's quite interesting, right. When we think about the major impediments for DevOps implementation, that means all about culture, right? And swore over the last 20 years we've been talking about silos. We'd be talking about the paradox for these teams too when it goes to align. And in many ways it's not so much about these teams aligning but about being in the same car, in the same books, right? It's really about fusing those teams around kind of the common purpose, a common objective. So to me this is really about kind of changing this culture where people start to look at kind of OKRs instead of the key objective that drives the entire team. Now, what it means in practice is really that's we need to change a lot of behaviors, right? It's not about the ER key, it's not about roles. It's about, you know, who can do what and when, and, you know, driving a bias towards action. It's also means that we need, I mean, especially in this COVID times it becomes very difficult, right? To drive kind of a kind of collaboration and affinity between these teams. And so I think there's a significant role that especially tools can play in terms of providing this conference feedback from teams to be in that preface spiritual qualification. >> Well, and it talked about culture being it's something that, you know, we're so used to talking about DevOps with respect to velocity, all about speed here. But of course this time everything changed so quickly but going from the physical spaces to everybody being remote really does take. It's very different than you can't replicate it digitally but there are collaboration tools that can kind of really be essential to help that cultural shift, right? >> Yeah, so to me we tend to talk about collaboration in a very mundane way, right? Of course we can use zoom. We can all get into the same room. But the point when I think when Jeff says spiritual co-location, it's really about, we all share the same objective. Do we have a means for instance, our pipeline, right? When you talk about DevOps probably we all started thinking about this continuous delivery pipeline that basically drives the automation, the orchestration across the team. But just thinking about a pipeline, right? At the end of the day, it's all about what is the meantime to feed back to these teams. If I'm a developer and I commit code, how long does it take for, you know, that code to be processed through pipeline or quick and I get feedback? If I am a finance person, who's funding a product or a project, what is my meantime to beat back? And so a lot of, kind of a, when we think about the pipeline, I think what's been really inspiring to me in the last year or so is that there is much more of an adoption of that door effect metrics. There is way more of a focus around value stream management. And to me, this is really when we talk about collaboration it's really a balance. How do you provide that feedback to the different stakeholders across the life cycle in a very timely matter? And that's what we would need to get to in terms of kind of this notion of collaboration. It's not so much about people being in the same physical space. It's about, you know, when checking code, you know, to do I guess the system to automatically identify what I'm going to break. If I'm about to release some allocation, how can the system help me reduce my change builder rate? Because it's able to predict that some issue was introduced in the application or the product. So I think there's a great role of technology and AI candidates to actually provide kind of that new level of collaboration. >> So we'll get to AI in a second but I'm curious, what are some of the metrics you think that really matter right now is organizations are still in some form probably of transformation to this new almost 100% remote workforce. >> So I'll just say first I'm not a big fan of metrics. And the reason being that, you know, you can look at a change failure rate, right, or a leak time or cycle time. And those are interesting metrics, right? The trend on metric is absolutely critical. But what's more important these I'll do get to the root cause. What is taught to you lead to that metric to degrade or improve over time. And so I'm much more interested and we, you know, fruit for Broadcom. Are we more interested in understanding what are the patterns that contribute to this? So I'll use a very mundane example. You know, we know that cycle time is heavily influenced by organizational boundaries. So, you know, we talk a lot about silos, but we we've worked with many of our customers doing value stream mapping. And oftentimes what you see is that really the boundaries of your organization creates a lot of idle time, right? So to me, it's less about the metrics. I think the door metrics are pretty, you know, valid set metrics but what's way more important is to understand, what are the anti parents? What are the things that we can detect through the data that actually are affecting those metrics? And I mean, over the last 10, 20 years, we've learned a lot about kind of what are the anti parents within our large enterprise customers? And there are plenty of them. >> What are some of the things that you're seeing now with respect to patterns that have developed over the last seven to eight months? >> So I think the two areas which clearly are evolving very quickly are on kind of the front end of the life cycle where DevOps is more and more embracing value stream management, value stream mapping. And I think what's interesting is that in many ways, the product is becoming the new silo. The notion of a product is very difficult by itself to actually define. People are starting to recognize that a value stream is not its own little kind of island. That in reality, when I did find a product this product, oftentimes as dependencies on our products and that in fact, you're looking at kind of a network of value streams, if you will. So on that and there is clearly kind of a new sets if you will of anti-patterns where, you know, products are being defined as a set of OTRs. They have interdependencies and you have to have a new set of silos. On the other hand the other kind of key movement to ease around the SRE space, where I think there is a cultural clash. While the DevOps side is very much embracing this notion of OTRs and value stream mapping and value management. On the other end, you have IT operations teams. We still think business services, right? For them they think about configure items, think about infrastructure. And so, you know, it's not uncommon to see, you know, teams where, you know, the operations team is still thinking about hundreds of thousands, tens of thousands of business services. And so there is this boundary where I think, well, SRE has been put in place, and there's lots of thinking about what kind of metrics can be defined. I think, you know, going back to culture, I think there's a lot of cultural evolution that's still required for, you know, true operations teams. >> And that's a hard thing. Cultural transformation in any industry pandemic or not is a challenging thing. You now talked about AI and automation of minutes ago. How do you think those technologies can be leveraged by DevOps leaders to influence their successes and their ability to collaborate and maybe see eye to eye with the SREs? >> Yeah, so there're kind of too, so even for myself, right? As a leader of , you know, 1500 people organization, there's a number of things I don't see, right, on a daily basis. And I think the technologies that we have at our disposal today from the AI are able to mine a lot of data and expose a lot of issues that as leaders we may not be aware of. And some of these are pretty kind of easy to understand, right? We all think we're agile. And yet when you start to understand, for instance, what is the is a work in progress, right, during the sprint? When you start to analyze the data you can detect for instance, that maybe the teams are over committed, that there is too much work in profits. You can start to identify kind of interprocess either from a technology or from a people point of view, which were hidden. You can start to understand that maybe the change failure rate is dragging. So I believe that there is a fundamental role to be played by the tools to expose again these anti parents. To make these things visible to the teams to be able to even compare teams, right? One of the things that's amazing is now we have access to tons of data not just from a given customer, but across a large number of customers. And so we start to compare all of these teams kind of operate and what's working, what's not working. >> Thoughts on AI and automation as a facilitator of spiritual co-location? >> Yeah, absolutely. It's, you know, there's a the problem we all face is the unknown, right? The velocity, the volume, variety of the data, every day we don't really necessarily completely appreciate what is the impact of our actions, right? And so AI can really act as a safety net that enables us to understand what is the impact of our actions. And so, yeah, in many ways, the ability to be informed in a timely matter to be able to interact with people on the basis of data and collaborate on the data in the actual matter, I think is a very powerful enabler on, in that respect. I mean, I've seen countless of times that for instance at the SRE boundary to basically show that we'll turn the quality attributes of an incoming release, right? And exposing that to an operations person, an SRE person and enabling that collaboration dialogue through there is a very, very powerful tool. >> Do you have any recommendations for how teams can use, you know, the SRE folks, the DevOps says can use AI and automation in the right ways to be successful rather than some ways that aren't going to be non-productive. >> Yeah, so to me there's a part that the question really is when we talk about data. There are different ways you can use data, right? So you can do a lot of analytics, predictive analytics. So I think there is a tendency to look at, let's say a specific KPI, like an availability KPI or change failure rate. And to basically do a regression analysis and projecting all these things is going to happen in the future. To me that's a bad approach. The reason why I fundamentally think it's a better approach is because we, our systems the way we develop software is a non-leader kind of system, right? Software development is not linear in nature. And so I think there's a, this is probably the worst approach is to actually focus on metrics. On the other hand if you start to actually understand at a more granular level, what are the things which are contributing to this, right? So if you start to understand, for instance that whenever maybe, you know, you affect a specific part of the application that translates into production issues. So we have, I've actually a customer who identified that over 50% of their unplanned outages were related to specific components in your architecture. And whenever these components were changed this resulted in this implant outages. So if you start to be able to basically establish causality, right? Cause an effect between kind of data across the last cycle. I think this is the right way to use AI. And so pharma to be, I think it's way more about kind of a classification problem. What are the causes of problems that do exist and affect things as opposed to an hourly predictive which I don't think is as powerful? >> So I mentioned in the beginning of our conversation that just came off the BizOps manifesto. You're one of the authors of that. I want to get your thoughts on DevOps and BizOps overlapping, complimenting each other. What, from the BizOps perspective, what does it mean to the future of DevOps? >> Yeah, so it's interesting, right? If you think about DevOps, there's no founding document, right? We can refer to the Phoenix project. I mean, there are a set of documents which have been written, but in many ways there is no clear definition of what DevOps is. If you go to the DevOps Institute today you'll see that, you know, they are specific trainings for instance on value management on SRE. And so in many ways, the problem we have as an industry is that there are set practices between agile, DevOps, SRE, value stream management, Ital, right? And we all basically talk about the same things, right? We all talk about essentially accelerating in the meantime to feedback, but yet we don't have a common framework to talk about that. The other key thing is that we add to wait for genius, Jean Kim's last book to really start to get into the business aspect, right? And for value mapping to start to emerge for us to start as an industry, right? IT to start to think about what is our connection with the business aspect, what's our purpose, right? And ultimately it's all about kind of driving these business outcomes. And so to me, BizOps is really about kind of putting a lens on kind of this critical element that it's not business and IT that we in fact need to fuse business and IT. That I need needs to transform itself to recognize that it's this value generator, right? It's not a cost center. And so the relationship to me, it's more than BizOps provides kind of this over all kind of framework, if you will. That set the context for what is the reason for IT to exist. What are the core values and principles that IT needs to embrace to, again, change from cost center to value center. And then we need to start to use this as a way to start to unify some of, again, the core practices, whether it's agile, DevOps, value stream mapping, SRE. So, I think over time, my hope is that we start to organize a lot of our practices, language and cultural elements. >> Last question Serge in the last few seconds we have here, talking about this, the relation between BizOps and DevOps. What do you think as DevOps evolves? And as you talked to circle some of your insights, what should our audience keep their eyes on in the next six to 12 months? >> So to me the key challenge for the industry is really around. So we were seeing a very rapid shift towards kind of project to product, right? Which we don't want to do is to recreate kind of these new silos, these hard silos. So that's one of the big changes that I think we need to be really careful about. Because it is ultimately, it is about culture. It's not about kind of how we segment the work, right? And any true culture that we can overcome kind of silos. So back to, I guess, with Jeffrey's concept of kind of the spiritual co-location, I think it's really about that too. It's really about kind of focusing on the business outcomes on kind of aligning, on driving engagement across the teams, but not for create kind of a new set of silos which instead of being vertical are going to be these horizontal products. >> Great advice Serge that looking at culture as kind of a way of really addressing and helping to reduce, replace challenges. We thank you so much for sharing your insights and your time at today's DevOps Virtual Forum. >> Thank you. Thanks for your time. Serge Lucio, Lisa Martin, we'll be right back. (upbeat music)

>>From around the globe. It's the queue with digital coverage of dev ops virtual forum brought to you by Broadcom. >>Hi, Lisa Martin here covering the Broadcom dev ops virtual forum. I'm very pleased to be joined today by a cube alumni, Jeffrey Hammond, the vice president and principal analyst serving CIO is at Forester. Jeffrey. Nice to talk with you today. >>Good morning. It's good to be here. Yeah. >>So a virtual forum, great opportunity to engage with our audiences so much has changed in the last it's an understatement, right? Or it's an overstated thing, but it's an obvious, so much has changed when we think of dev ops. One of the things that we think of is speed, you know, enabling organizations to be able to better serve customers or adapt to changing markets like we're in now, speaking of the need to adapt, talk to us about what you're seeing with respect to dev ops and agile in the age of COVID, what are things looking like? >>Yeah, I think that, um, for most organizations, we're in a, uh, a period of adjustment, uh, when we initially started, it was essentially a sprint, you know, you run as hard as you can for as fast as you can for as long as you can and you just kind of power through it. And, and that's actually what, um, the folks that get hub saw in may when they ran an analysis of how developers, uh, commit times and a level of work that they were committing and how they were working, uh, in the first couple of months of COVID was, was progressing. They found that developers, at least in the Pacific time zone were actually increasing their work volume, maybe because they didn't have two hour commutes or maybe because they were stuck away in their homes, but for whatever reason, they were doing more work. >>And it's almost like, you know, if you've ever run a marathon the first mile or two in the marathon, you feel great and you just want to run and you want to power through it and you want to go hard. And if you do that by the time you get to mile 18 or 19, you're going to be gassed. It's sucking for wind. Uh, and, and that's, I think where we're starting to hit. So as we start to, um, gear our development chops out for the reality that most of us won't be returning into an office until 2021 at the earliest and many organizations will, will be fundamentally changing, uh, their remote workforce, uh, policies. We have to make sure that the agile processes that we use and the dev ops processes and tools that we use to support these teams are essentially aligned to help developers run that marathon instead of just kind of power through. >>So, um, let me give you a couple of specifics for many organizations, they have been in an environment where they will, um, tolerate Rover remote work and what I would call remote work around the edges like developers can be remote, but product managers and, um, you know, essentially scrum masters and all the administrators that are running the, uh, uh, the SCM repositories and, and the dev ops pipelines are all in the office. And it's essentially centralized work. That's not, we are anymore. We're moving from remote workers at the edge to remote workers at the center of what we do. And so one of the implications of that is that, um, we have to think about all the activities that you need to do from a dev ops perspective or from an agile perspective, they have to be remote people. One of the things I found with some of the organizations I talked to early on was there were things that administrators had to do that required them to go into the office to reboot the SCM server as an example, or to make sure that the final approvals for production, uh, were made. >>And so the code could be moved into the production environment. And so it actually was a little bit difficult because they had to get specific approval from the HR organizations to actually be allowed to go into the office in some States. And so one of the, the results of that is that while we've traditionally said, you know, tools are important, but they're not as important as culture as structure as organization as process. I think we have to rethink that a little bit because to the extent that tools enable us to be more digitally organized and to hiring, you know, achieve higher levels of digitization in our processes and be able to support the idea of remote workers in the center. They're now on an equal footing with so many of the other levers, uh, that, that, um, uh, that organizations have at their disposal. Um, I'll give you another example for years. >>We've said that the key to success with agile at the team level is cross-functional co located teams that are working together physically co located. It's the easiest way to show agile success. We can't do that anymore. We can't be physically located at least for the foreseeable future. So, you know, how do you take the low hanging fruits of an agile transformation and apply it in, in, in, in the time of COVID? Well, I think what you have to do is that you have to look at what physical co-location has enabled in the past and understand that it's not so much the fact that we're together looking at each other across the table. It's the fact that we're able to get into a shared mindspace, uh, from, um, uh, from a measurement perspective, we can have shared purpose. We can engage in high bandwidth communications. It's the spiritual aspect of that physical co-location that is actually important. So one of the biggest things that organizations need to start to ask themselves is how do we achieve spiritual colocation with our agile teams? Because we don't have the, the ease of physical co-location available to us anymore? >>Well, the spiritual co-location is such an interesting kind of provocative phrase there, but something that probably was a challenge here, we are seven, eight months in for many organizations, as you say, going from, you know, physical workspaces, co-location being able to collaborate face to face to a, a light switch flip overnight. And this undefined period of time where all we were living with with was uncertainty, how does spiritual, what do you, when you talk about spiritual co-location in terms of collaboration and processes and technology help us unpack that, and how are you seeing organizations adopted? >>Yeah, it's, it's, um, it's a great question. And, and I think it goes to the very root of how organizations are trying to transform themselves to be more agile and to embrace dev ops. Um, if you go all the way back to the, to the original, uh, agile manifesto, you know, there were four principles that were espoused individuals and interactions over processes and tools. That's still important. Individuals and interactions are at the core of software development, processes and tools that support those individual and interact. Uh, those individuals in those interactions are more important than ever working software over comprehensive documentation. Working software is still more important, but when you are trying to onboard employees and they can't come into the office and they can't do the two day training session and kind of understand how things work and they can't just holler over the cube, uh, to ask a question, you may need to invest a little bit more in documentation to help that onboarding process be successful in a remote context, uh, customer collaboration over contract negotiation. >>Absolutely still important, but employee collaboration is equally as important if you want to be spiritually, spiritually co-located. And if you want to have a shared purpose and then, um, responding to change over following a plan. I think one of the things that's happened in a lot of organizations is we have focused so much of our dev ops effort around velocity getting faster. We need to run as fast as we can like that sprinter. Okay. You know, trying to just power through it as quickly as possible. But as we shift to, to the, to the marathon way of thinking, um, velocity is still important, but agility becomes even more important. So when you have to create an application in three weeks to do track and trace for your employees, agility is more important. Um, and then just flat out velocity. Um, and so changing some of the ways that we think about dev ops practices, um, is, is important to make sure that that agility is there for one thing, you have to defer decisions as far down the chain to the team level as possible. >>So those teams have to be empowered to make decisions because you can't have a program level meeting of six or seven teams and one large hall and say, here's the lay of the land. Here's what we're going to do here are our processes. And here are our guardrails. Those teams have to make decisions much more quickly that developers are actually developing code in smaller chunks of flow. They have to be able to take two hours here or 50 minutes there and do something useful. And so the tools that support us have to become tolerant of the reality of, of, of, of how we're working. So if they work in a way that it allows the team together to take as much autonomy as they can handle, um, to, uh, allow them to communicate in a way that, that, that delivers shared purpose and allows them to adapt and master new technologies, then they're in the zone in their spiritual, they'll get spiritually connected. I hope that makes sense. >>It does. I think we all could use some of that, but, you know, you talked about in the beginning and I've, I've talked to numerous companies during the pandemic on the cube about the productivity, or rather the number of hours of work has gone way up for many roles, you know, and, and, and times that they normally late at night on the weekends. So, but it's a cultural, it's a mind shift to your point about dev ops focused on velocity, sprints, sprints, sprints, and now we have to, so that cultural shift is not an easy one for developers. And even at this folks to flip so quickly, what have you seen in terms of the velocity at which businesses are able to get more of that balance between the velocity, the sprint and the agility? >>I think, I think at the core, this really comes down to management sensitivity. Um, when everybody was in the office, you could kind of see the mental health of development teams by, by watching how they work. You know, you call it management by walking around, right. We can't do that. Managers have to, um, to, to be more aware of what their teams are doing, because they're not going to see that, that developer doing a check-in at 9:00 PM on a Friday, uh, because that's what they had to do, uh, to meet the objectives. And, um, and, and they're going to have to, to, um, to find new ways to measure engagement and also potential burnout. Um, friend of mine once had, uh, had a great metric that he called the parking lot metric. It was helpful as the parking lot at nine. And how full was it at five? >>And that gives you an indication of how engaged your developers are. Um, what's the digital equivalent equivalent to the parking lot metric in the time of COVID it's commit stats, it's commit rates. It's, um, you know, the, uh, the turn rate, uh, that we have in our code. So we have this information, we may not be collecting it, but then the next question becomes, how do we use that information? Do we use that information to say, well, this team isn't delivering as at the same level of productivity as another team, do we weaponize that data or do we use that data to identify impedances in the process? Um, why isn't a team working effectively? Is it because they have higher levels of family obligations and they've got kids that, that are at home? Um, is it because they're working with, um, you know, hardware technology, and guess what, they, it's not easy to get the hardware technology into their home office because it's in the lab at the, uh, at the corporate office, uh, or they're trying to communicate, uh, you know, halfway around the world. >>And, uh, they're communicating with a, with an office lab that is also shut down and, and, and the bandwidth just doesn't enable the, the level of high bandwidth communications. So from a dev ops perspective, managers have to get much more sensitive to the, the exhaust that the dev ops tools are throwing off, but also how they're going to use that in a constructive way to, to prevent burnout. And then they also need to, if they're not already managing or monitoring or measuring the level of developer engagement, they have, they really need to start whether that's surveys around developer satisfaction, um, whether it's, you know, more regular social events, uh, where developers can kind of just get together and drink a beer and talk about what's going on in the project, uh, and monitoring who checks in and who doesn't, uh, they have to, to, um, work harder, I think, than they ever have before. >>Well, and you mentioned burnout, and that's something that I think we've all faced in this time at varying levels and it changes. And it's a real, there's a tension in the air, regardless of where you are. There's a challenge, as you mentioned, people having, you know, coworker, their kids as coworkers and fighting for bandwidth, because everyone is forced in this situation. I'd love to get your perspective on some businesses that are, that have done this well, this adaptation, what can you share in terms of some real-world examples that might inspire the audience? >>Yeah. Uh, I'll start with, uh, stack overflow. Uh, they recently published a piece in the journal of the ACM around some of the things that they had discovered. Um, you know, first of all, just a cultural philosophy. If one person is remote, everybody is remote. And you just think that way from an executive level, um, social spaces. One of the things that they talk about doing is leaving a video conference room open at a team level all day long, and the team members, you know, we'll go on mute, you know, so that they don't have to, that they don't necessarily have to be there with somebody else listening to them. But if they have a question, they can just pop off mute really quickly and ask the question. And if anybody else knows the answer, it's kind of like being in that virtual pod. Uh, if you, uh, if you will, um, even here at Forrester, one of the things that we've done is we've invested in social ceremonies. >>We've actually moved our to our team meetings on, on my analyst team from, from once every two weeks to weekly. And we have built more time in for social Ajay socialization, just so we can see, uh, how, how, how we're doing. Um, I think Microsoft has really made some good, uh, information available in how they've managed things like the onboarding process. I think I'm Amanda silver over there mentioned that a couple of weeks ago when, uh, uh, a presentation they did that, uh, uh, Microsoft onboarded over 150,000 people since the start of COVID, if you don't have good remote onboarding processes, that's going to be a disaster. Now they're not all developers, but if you think about it, um, everything from how you do the interviewing process, uh, to how you get people, their badges, to how they get their equipment. Um, security is a, is another issue that they called out typically, uh, it security, um, the security of, of developers machines ends at, at, at the corporate desktop. >>But, you know, since we're increasingly using our own machines, our own hardware, um, security organizations kind of have to extend their security policies to cover, uh, employee devices, and that's caused them to scramble a little bit. Uh, so, so the examples are out there. It's not a lot of, like, we have to do everything completely differently, but it's a lot of subtle changes that, that have to be made. Um, I'll give you another example. Um, one of the things that, that we are seeing is that, um, more and more organizations to deal with the challenges around agility, with respect to delivering software, embracing low-code tools. In fact, uh, we see about 50% of firms are using low-code tools right now. We predict it's going to be 75% by the end of next year. So figuring out how your dev ops processes support an organization that might be using Mendix or OutSystems, or, you know, the power platform building the front end of an application, like a track and trace application really, really quickly, but then hooking it up to your backend infrastructure. Does that happen completely outside the dev ops investments that you're making and the agile processes that you're making, or do you adapt your organization? Um, our hybrid teams now teams that not just have professional developers, but also have business users that are doing some development with a low-code tool. Those are the kinds of things that we have to be, um, willing to, um, to entertain in order to shift the focus a little bit more toward the agility side, I think >>Lot of obstacles, but also a lot of opportunities for businesses to really learn, pay attention here, pivot and grow, and hopefully some good opportunities for the developers and the business folks to just get better at what they're doing and learning to embrace spiritual co-location Jeffrey, thank you so much for joining us on the program today. Very insightful conversation. >>My pleasure. It's it's, it's an important thing. Just remember if you're going to run that marathon, break it into 26, 10 minute runs, take a walk break in between each and you'll find that you'll get there. >>Digestible components, wise advice. Jeffery Hammond. Thank you so much for joining for Jeffrey I'm Lisa Martin, you're watching Broadcom's dev ops virtual forum >>From around the globe. It's the queue with digital coverage of dev ops virtual forum brought to you by Broadcom, >>Continuing our conversations here at Broadcom's dev ops virtual forum. Lisa Martin here, please. To welcome back to the program, Serge Lucio, the general manager of the enterprise software division at Broadcom. Hey, Serge. Welcome. Thank you. Good to be here. So I know you were just, uh, participating with the biz ops manifesto that just happened recently. I just had the chance to talk with Jeffrey Hammond and he unlocked this really interesting concept, but I wanted to get your thoughts on spiritual co-location as really a necessity for biz ops to succeed in this unusual time in which we're living. What are your thoughts on spiritual colocation in terms of cultural change versus adoption of technologies? >>Yeah, it's a, it's, it's quite interesting, right? When we, when we think about the major impediments for, uh, for dev ops implementation, it's all about culture, right? And swore over the last 20 years, we've been talking about silos. We'd be talking about the paradox for these teams to when it went to align in many ways, it's not so much about these teams aligning, but about being in the same car in the same books, right? It's really about fusing those teams around kind of the common purpose, a common objective. So to me, the, this, this is really about kind of changing this culture where people start to look at a kind of OKR is instead of the key objective, um, that, that drives the entire team. Now, what it means in practice is really that's, uh, we need to change a lot of behaviors, right? It's not about the Yarki, it's not about roles. It's about, you know, who can do what and when, and, uh, you know, driving a bias towards action. It also means that we need, I mean, especially in this school times, it becomes very difficult, right? To drive kind of a kind of collaboration between these teams. And so I think there there's a significant role that especially tools can play in terms of providing this complex feedback from teams to, uh, to be in that preface spiritual qualification. >>Well, and it talked about culture being, it's something that, you know, we're so used to talking about dev ops with respect to velocity, all about speed here. But of course this time everything changed so quickly, but going from the physical spaces to everybody being remote really does take it. It's very different than you can't replicate it digitally, but there are collaboration tools that can kind of really be essential to help that cultural shift. Right? >>Yeah. So 2020, we, we touch to talk about collaboration in a very mundane way. Like, of course we can use zoom. We can all get into, into the same room. But the point when I think when Jeff says spiritual, co-location, it's really about, we all share the same objective. Do we, do we have a niece who, for instance, our pipeline, right? When you talk about dev ops, probably we all started thinking about this continuous delivery pipeline that basically drives the automation, the orchestration across the team, but just thinking about a pipeline, right, at the end of the day, it's all about what is the meantime to beat back to these teams. If I'm a developer and a commit code, I don't, does it take where, you know, that code to be processed through pipeline pushy? Can I get feedback if I am a finance person who is funding a product or a project, what is my meantime to beat back? >>And so a lot of, kind of a, when we think about the pipeline, I think what's been really inspiring to me in the last year or so is that there is much more of an adoption of the Dora metrics. There is way more of a focus around value stream management. And to me, this is really when we talk about collaboration, it's really a balance. How do you provide the feedback to the different stakeholders across the life cycle in a very timely matter? And that's what we would need to get to in terms of kind of this, this notion of collaboration. It's not so much about people being in the same physical space. It's about, you know, when I checked in code, you know, to do I guess the system to automatically identify what I'm going to break. If I'm about to release some allegation, how can the system help me reduce my change pillar rates? Because it's, it's able to predict that some issue was introduced in the outpatient or work product. Um, so I think there's, there's a great role of technology and AI candidate Lynch to, to actually provide that new level of collaboration. >>So we'll get to AI in a second, but I'm curious, what are some of the, of the metrics you think that really matter right now is organizations are still in some form of transformation to this new almost 100% remote workforce. >>So I'll just say first, I'm not a big fan of metrics. Um, and the reason being that, you know, you can look at a change killer rate, right, or a lead time or cycle time. And those are, those are interesting metrics, right? The trend on metric is absolutely critical, but what's more important is you get to the root cause what is taught to you lean to that metric to degrade or improve or time. And so I'm much more interested and we, you know, fruit for Broadcom. Are we more interested in understanding what are the patterns that contribute to this? So I'll give you a very mundane example. You know, we know that cycle time is heavily influenced by, um, organizational boundaries. So, you know, we talk a lot about silos, but, uh, we we've worked with many of our customers doing value stream mapping. And oftentimes what you see is that really the boundaries of your organization creates a lot of idle time, right? So to me, it's less about the metrics. I think the door metrics are a pretty, you know, valid set metrics, but what's way more important is to understand what are the antiperspirants, what are the things that we can detect through the data that actually are affecting those metrics. And, uh, I mean, over the last 10, 20 years, we've learned a lot about kind of what are, what are the antiperspirants within our large enterprise customers. And there are plenty of them. >>What are some of the things that you're seeing now with respect to patterns that have developed over the last seven to eight months? >>So I think the two areas which clearly are evolving very quickly are on kind of the front end of the life cycle, where DevOps is more and more embracing value stream management value stream mapping. Um, and I think what's interesting is that in many ways the product is becoming the new silo. Uh, the notion of a product is very difficult by itself to actually define people are starting to recognize that a value stream is not its own little kind of Island. That in reality, when I define a product, this product, oftentimes as dependencies on our products and that in fact, you're looking at kind of a network of value streams, if you will. So, so even on that, and there is clearly kind of a new sets, if you will, of anti-patterns where products are being defined as a set of OTRs, they have interdependencies and you have have a new set of silos on the operands, uh, the Abra key movement to Israel and the SRE space where, um, I think there is a cultural clash while the dev ops side is very much embracing this notion of OTRs and value stream mapping and Belgium management. >>On the other end, you have the it operations teams. We still think business services, right? For them, they think about configure items, think about infrastructure. And so, you know, it's not uncommon to see, you know, teams where, you know, the operations team is still thinking about hundreds of thousands, tens of thousands of business services. And so the, the, there is there's this boundary where, um, I think, well, SRE is being put in place. And there's lots of thinking about what kind of metrics can be fined. I think, you know, going back to culture, I think there's a lot of cultural evolution that's still required for true operations team. >>And that's a hard thing. Cultural transformation in any industry pandemic or not is a challenging thing. You talked about, uh, AI and automation of minutes ago. How do you think those technologies can be leveraged by DevOps leaders to influence their successes and their ability to collaborate, maybe see eye to eye with the SRS? >>Yeah. Um, so th you're kind of too. So even for myself, as a leader of a, you know, 1500 people organization, there's a number of things I don't see right. On a daily basis. And, um, I think the, the, the, the technologies that we have at our disposal today from the AI are able to mind a lot of data and expose a lot of, uh, issues that's as leaders we may not be aware of. And some of the, some of these are pretty kind of easy to understand, right? We all think we're agile. And yet when you, when you start to understand, for instance, uh, what is the, what is the working progress right to during the sprint? Um, when you start to analyze the data you can detect, for instance, that maybe the teams are over committed, that there is too much work in progress. >>You can start to identify kind of, interdepencies either from a technology, from a people point of view, which were hidden, uh, you can start to understand maybe the change filler rates he's he is dragging. So I believe that there is a, there's a fundamental role to be played by the tools to, to expose again, these anti parents, to, to make these things visible to the teams, to be able to even compare teams. Right. One of the things that's, that's, uh, that's amazing is now we have access to tons of data, not just from a given customer, but across a large number of customers. And so we start to compare all of these teams kind of operate, and what's working, what's not working >>Thoughts on AI and automation as, as a facilitator of spiritual co-location. >>Yeah, absolutely. Absolutely. It's um, you know, th there's, uh, the problem we all face is the unknown, right? The, the law city, but volume variety of the data, uh, everyday we don't really necessarily completely appreciate what is the impact of our actions, right? And so, um, AI can really act as a safety net that enables us to, to understand what is the impact of our actions. Um, and so, yeah, in many ways, the ability to be informed in a timely matter to be able to interact with people on the basis of data, um, and collaborate on the data. And the actual matter, I think is, is a, is a very powerful enabler, uh, on, in that respect. I mean, I, I've seen, um, I've seen countless of times that, uh, for instance, at the SRE boundary, um, to basically show that we'll turn the quality attributes, so an incoming release, right. And exposing that to, uh, an operations person and a sorry person, and enabling that collaboration dialogue through data is a very, very powerful tool. >>Do you have any recommendations for how teams can use, you know, the SRE folks, the dev ops says can use AI and automation in the right ways to be successful rather than some ways that aren't going to be nonproductive. >>Yeah. So to me, the th there, there's a part of the question really is when, when we talk about data, there are there different ways you can use data, right? Um, so you can, you can do a lot of an analytics, predictive analytics. So I think there is a, there's a tendency, uh, to look at, let's say a, um, a specific KPI, like a, an availability KPI, or change filler rate, and to basically do a regression analysis and projecting all these things, going to happen in the future. To me, that that's, that's a, that's a bad approach. The reason why I fundamentally think it's a better approach is because we are systems. The way we develop software is, is a, is a non-leader kind of system, right? Software development is not linear nature. And so I think there's a D this is probably the worst approach is to actually focus on metrics on the other end. >>Um, if you, if you start to actually understand at a more granular level, what har, uh, which are the things which are contributing to this, right? So if you start to understand, for instance, that whenever maybe, you know, you affect a specific part of the application that translates into production issues. So we, we have, I've actually, uh, a customer who, uh, identified that, uh, over 50% of their unplanned outages were related to specific components in your architecture. And whenever these components were changed, this resulted in these plant outages. So if you start to be able to basically establish causality, right, cause an effect between kind of data across the last cycle. I think, I think this is the right way to, uh, to, to use AI. And so pharma to be, I think it's way more God could have a classification problem. What are the classes of problems that do exist and affect things as opposed to analytics, predictive, which I don't think is as powerful. >>So I mentioned in the beginning of our conversation, that just came off the biz ops manifesto. You're one of the authors of that. I want to get your thoughts on dev ops and biz ops overlapping, complimenting each other, what, from a, the biz ops perspective, what does it mean to the future of dev ops? >>Yeah, so, so it's interesting, right? If you think about DevOps, um, there's no felony document, right? Can we, we can refer to the Phoenix project. I mean, there are a set of documents which have been written, but in many ways, there's no clear definition of what dev ops is. Uh, if you go to the dev ops Institute today, you'll see that they are specific, um, trainings for instance, on value management on SRE. And so in many ways, the problem we have as an industry is that, um, there are set practices between agile dev ops, SRE Valley should management. I told, right. And we all basically talk about the same things, right. We all talk about essentially, um, accelerating in the meantime fee to feedback, but yet we don't have the common framework to talk about that. The other key thing is that we add to wait, uh, for, uh, for jeans, Jean Kim's Lascaux, um, to, uh, to really start to get into the business aspect, right? >>And for value stream mapping to start to emerge for us to start as an industry, right. It, to start to think about what is our connection with the business aspect, what's our purpose, right? And ultimately it's all about driving these business outcomes. And so to me, these ops is really about kind of, uh, putting a lens on this critical element that it's not business and it, that we in fact need to fuse business 19 that I need needs to transform itself to recognize that it's, it's this value generator, right. It's not a cost center. And so the relationship to me, it's more than BizOps provides kind of this Oliver or kind of framework, if you will. That set the context for what is the reason, uh, for it to exist. What's part of the core values and principles that it needs to embrace to, again, change from a cost center to a value center. And then we need to start to use this as a way to start to unify some of the, again, the core practices, whether it's agile, DevOps value, stream mapping SRE. Um, so, so I think over time, my hope is that we start to optimize a lot of our practices, language, um, and, uh, and cultural elements. >>Last question surgeon, the last few seconds we have here talking about this, the relation between biz ops and dev ops, um, what do you think as DevOps evolves? And as you talked to circle some of your insights, what should our audience keep their eyes on in the next six to 12 months? >>So to me, the key, the key, um, challenge for, for the industry is really around. So we were seeing a very rapid shift towards kind of, uh, product to product, right. Which we don't want to do is to recreate kind of these new silos, these hard silos. Um, so that, that's one of the big changes, uh, that I think we need to be, uh, to be really careful about, um, because it is ultimately, it is about culture. It's not about, uh, it's not about, um, kind of how we segment the work, right. And, uh, any true culture that we can overcome kind of silos. So back to, I guess, with Jeffrey's concept of, um, kind of the spiritual co-location, I think it's, it's really about that too. It's really about kind of, uh, uh, focusing on the business outcomes on kind of aligning on driving engagement across the teams, but, but not for create a, kind of a new set of silos, which instead of being vertical are going to be these horizontal products >>Crazy by surge that looking at culture as kind of a way of really, uh, uh, addressing and helping to, uh, re re reduce, replace challenges. We thank you so much for sharing your insights and your time at today's DevOps virtual forum. >>Thank you. Thanks for your time. >>I'll be right back >>From around the globe it's the cube with digital coverage of devops virtual forum brought to you by Broadcom. >>Welcome to Broadcom's DevOps virtual forum, I'm Lisa Martin, and I'm joined by another Martin, very socially distanced from me all the way coming from Birmingham, England is Glynn Martin, the head of QA transformation at BT. Glynn, it's great to have you on the program. Thank you, Lisa. I'm looking forward to it. As we said before, we went live to Martins for the person one in one segment. So this is going to be an interesting segment guys, what we're going to do is Glynn's going to give us a really kind of deep inside out view of devops from an evolution perspective. So Glynn, let's start. Transformation is at the heart of what you do. It's obviously been a very transformative year. How have the events of this year affected the >> transformation that you are still responsible for driving? Yeah. Thank you, Lisa. I mean, yeah, it has been a difficult year. >>Um, and although working for BT, which is a global telecommunications company, um, I'm relatively resilient, I suppose, as a, an industry, um, through COVID obviously still has been affected and has got its challenges. And if anything, it's actually caused us to accelerate our transformation journey. Um, you know, we had to do some great things during this time around, um, you know, in the UK for our emergency and, um, health workers give them unlimited data and for vulnerable people to support them. And that's spent that we've had to deliver changes quickly. Um, but what we want to be able to do is deliver those kinds of changes quickly, but sustainably for everything that we do, not just because there's an emergency. Um, so we were already on the kind of journey to agile, but ever more important now that we are, we are able to do those, that kind of work, do it more quickly. >>Um, and that it works because the, the implications of it not working is, can be terrible in terms of you know, we've been supporting testing centers,  new hospitals to treat COVID patients. So we need to get it right. And then therefore the coverage of what we do, the quality of what we do and how quickly we do it really has taken on a new scale and what was already a very competitive market within the telco industry within the UK. Um, you know, what I would say is that, you know, we are under pressure to deliver more value, but we have small cost challenges. We have to obviously, um, deal with the fact that, you know, COVID 19 has hit most industries kind of revenues and profits. So we've got this kind of paradox between having less costs, but having to deliver more value quicker and  to higher quality. So yeah, certainly the finances is, um, on our minds and that's why we need flexible models, cost models that allow us to kind of do growth, but we get that growth by showing that we're delivering value. Um, especially in these times when there are financial challenges on companies. So one of the things that I want to ask you about, I'm again, looking at DevOps from the inside >>Out and the evolution that you've seen, you talked about the speed of things really accelerating in this last nine months or so. When we think dev ops, we think speed. But one of the things I'd love to get your perspective on is we've talked about in a number of the segments that we've done for this event is cultural change. What are some of the things that you've seen there as, as needing to get, as you said, get things right, but done so quickly to support essential businesses, essential workers. How have you seen that cultural shift? >>Yeah, I think, you know, before test teams for themselves at this part of the software delivery cycle, um, and actually now really our customers are expecting that quality and to deliver for our customers what they want, quality has to be ingrained throughout the life cycle. Obviously, you know, there's lots of buzzwords like shift left. Um, how do we do shift left testing? Um, but for me, that's really instilling quality and given capabilities shared capabilities throughout the life cycle that drive automation, drive improvements. I always say that, you know, you're only as good as your lowest common denominator. And one thing that we were finding on our dev ops journey was that we  would be trying to do certain things quick, we had automated build, automated tests. But if we were taking a weeks to create test scripts, or we were taking weeks to manually craft data, and even then when we had taken so long to do it, that the coverage was quite poor and that led to lots of defects later on in the life cycle, or even in our production environment, we just couldn't afford to do that. >>And actually, focusing on continuous testing over the last nine to 12 months has really given us the ability to deliver quickly across the whole life cycle. And therefore actually go from doing a kind of semi agile kind of thing, where we did the user stories, we did a few of the kind of agile ceremonies, but we weren't really deploying any quicker into production because our stakeholders were scared that we didn't have the same control that we had when we had more waterfall releases. And, you know, when we didn't think of ourselves. So we've done a lot of work on every aspect, um, especially from a testing point of view, every aspect of every activity, rather than just looking at automated tests, you know, whether it is actually creating the test in the first place, whether it's doing security testing earlier in the lot and performance testing in the life cycle, et cetera. So, yeah,  it's been a real key thing that for CT, for us to drive DevOps, >>Talk to me a little bit about your team. What are some of the shifts in terms of expectations that you're experiencing and how your team interacts with the internal folks from pipeline through life cycle? >>Yeah, we've done a lot of work on this. Um, you know, there's a thing that I think people will probably call it a customer experience gap, and it reminds me of a Gilbert cartoon, where we start with the requirements here and you're almost like a Chinese whisper effects and what we deliver is completely different. So we think the testing team or the delivery teams, um, know in our teeth has done a great job. This is what it said in the acceptance criteria, but then our customers are saying, well, actually that's not working this isn't working and there's this kind of gap. Um, we had a great launch this year of agile requirements, it's one of the Broadcom tools. And that was the first time in, ever since I remember actually working within BT, I had customers saying to me, wow, you know, we want more of this. >>We want more projects to have extra requirements design on it because it allowed us to actually work with the business collaboratively. I mean, we talk about collaboration, but how do we actually, you know, do that and have something that both the business and technical people can understand. And we've actually been working with the business , using agile requirements designer to really look at what the requirements are, tease out requirements we hadn't even thought of and making sure that we've got high levels of test coverage. And what we actually deliver at the end of it, not only have we been able to generate tests more quickly, but we've got much higher test coverage and also can more smartly, using the kind of AI within the tool and then some of the other kinds of pipeline tools, actually deliver to choose the right tasks, and actually doing a risk based testing approach. So that's been a great launch this year, but just the start of many kinds of things that we're doing >>Well, what I hear in that, Glynn is a lot of positives that have come out of a very challenging situation. Talk to me about it. And I liked that perspective. This is a very challenging time for everybody in the world, but it sounds like from a collaboration perspective you're right, we talk about that a lot critical with devops. But those challenges there, you guys were able to overcome those pretty quickly. What other challenges did you face and figure out quickly enough to be able to pivot so fast? >>I mean, you talked about culture. You know, BT is like most companies  So it's very siloed. You know we're still trying to work to become closer as a company. So I think there's a lot of challenges around how would you integrate with other tools? How would you integrate with the various different technologies. And BT, we have 58 different IT stacks. That's not systems, that's stacks, all of those stacks can have hundreds of systems. And we're trying to, we've got a drive at the moment, a simplified program where we're trying to you know, reduce that number to 14 stacks. And even then there'll be complexity behind the scenes that we will be challenged more and more as we go forward. How do we actually highlight that to our users? And as an it organization, how do we make ourselves leaner, so that even when we've still got some of that legacy, and we'll never fully get rid of it and that's the kind of trade off that we have to make, how do we actually deal with that and hide that from our users and drive those programs, so we can, as I say, accelerate change,  reduce that kind of waste and that kind of legacy costs out of our business. You know, the other thing as well, I'm sure telecoms is probably no different to insurance or finance. When you take the number of products that we do, and then you combine them, the permutations are tens and hundreds of thousands of products. So we, as a business are trying to simplify, we are trying to do that in an agile way. >>And haven't tried to do agile in the proper way and really actually work at pace, really deliver value. So I think what we're looking more and more at the moment is actually  more value focused. Before we used to deliver changes sometimes into production. Someone had a great idea, or it was a great idea nine months ago or 12 months ago, but actually then we ended up deploying it and then we'd look at the users, the usage of that product or that application or whatever it is, and it's not being used for six months. So we haven't got, you know, the cost of the last 12 months. We certainly haven't gotten room for that kind of waste and, you know, for not really understanding the value of changes that we are doing. So I think that's the most important thing of the moment, it's really taking that waste out. You know, there's lots of focus on things like flow management, what bits of our process are actually taking too long. And we've started on that journey, but we've got a hell of a long way to go. But that involves looking at every aspect of the software delivery cycle. >> Going from, what 58 IT stacks down to 14 or whatever it's going to be, simplifying sounds magical to everybody. It's a big challenge. What are some of the core technology capabilities that you see really as kind of essential for enabling that with this new way that you're working? >>Yeah. I mean, I think we were started on a continuous testing journey, and I think that's just the start. I mean as I say, looking at every aspect of, you know, from a QA point of view is every aspect of what we do. And it's also looking at, you know, we've started to branch into more like AI, uh, AI ops and, you know, really the full life cycle. Um, and you know, that's just a stepping stone to, you know, I think autonomics is the way forward, right. You know, all of this kind of stuff that happens, um, you know, monitoring, uh, you know, watching the systems what's happening in production, how do we feed that back? How'd you get to a point where actually we think about change and then suddenly it's in production safely, or if it's not going to safety, it's automatically backing out. So, you know, it's a very, very long journey, but if we want to, you know, in a world where the pace is in ever-increasing and the demands for the team, and, you know, with the pressures on, at the moment where we're being asked to do things, uh, you know, more efficiently and as lean as possible, we need to be thinking about every part of the process and how we put the kind of stepping stones in place to lead us to a more automated kind of, um, you know, um, the future. >>Do you feel that that planned outcomes are starting to align with what's delivered, given this massive shift that you're experiencing? >>I think it's starting to, and I think, you know, as I say, as we look at more of a value based approach, um, and, um, you know, as I say, print, this was a kind of flow management. I think that that will become ever, uh, ever more important. So, um, I think it starting to people certainly realize that, you know, teams need to work together, you know, the kind of the cousin between business and it, especially as we go to more kind of SAS based solutions, low code solutions, you know, there's not such a gap anymore, actually, some of our business partners that expense to be much more tech savvy. Um, so I think, you know, this is what we have to kind of appreciate what is its role, how do we give the capabilities, um, become more of a centers of excellence rather than actually doing mounds amounts of work. And for me, and from a testing point of view, you know, mounds and mounds of testing, actually, how do we automate that? How do we actually generate that instead of, um, create it? I think that's the kind of challenge going forward. >>What are some, as we look forward, what are some of the things that you would like to see implemented or deployed in the next, say six to 12 months as we hopefully round a corner with this pandemic? >>Yeah, I think, um, you know, certainly for, for where we are as a company from a QA perspective, we are, um, you let's start in bits that we do well, you know, we've started creating, um, continuous delivery and DevOps pipelines. Um, there's still manual aspects of that. So, you know, certainly for me, I I've challenged my team with saying how do we do an automated journey? So if I put a requirement in JIRA or rally or wherever it is and why then click a button and, you know, with either zero touch for one such, then put that into production and have confidence that, that has been done safely and that it works and what happens if it doesn't work. So, you know, that's, that's the next, um, the next few months, that's what our concentration, um, is, is about. But it's also about decision-making, you know, how do you actually understand those value judgments? >>And I think there's lots of the things dev ops, AI ops, kind of that always ask aspects of business operations. I think it's about having the information in one place to make those kinds of decisions. How does it all try and tie it together? As I say, even still with kind of dev ops, we've still got elements within my company where we've got lots of different organizations doing some, doing similar kinds of things, but they're all kind of working in silos. So I think having AI ops as it comes more and more to the fore as we go to cloud, and that's what we need to, you know, we're still very early on in our cloud journey, you know, so we need to make sure the technologies work with cloud as well as you can have, um, legacy systems, but it's about bringing that all together and having a full, visible pipeline, um, that everybody can see and make decisions. >>You said the word confidence, which jumped out at me right away, because absolutely you've got to have be able to have confidence in what your team is delivering and how it's impacting the business and those customers. Last question then for you is how would you advise your peers in a similar situation to leverage technology automation, for example, dev ops, to be able to gain the confidence that they're making the right decisions for their business? >>I think the, the, the, the, the approach that we've taken actually is not started with technology. Um, we've actually taken a human centered design, uh, as a core principle of what we do, um, within the it part of BT. So by using human centered design, that means we talk to our customers, we understand their pain points, we map out their current processes. Um, and then when we mapped out what this process does, it also understand their aspirations as well, you know? Um, and where do they want to be in six months? You know, do they want it to be, um, more agile and, you know, or do they want to, you know, is, is this a part of their business that they want to do one better? We actually then looked at why that's not running well, and then see what, what solutions are out there. >>We've been lucky that, you know, with our partnership, with Broadcom within the payer line, lots of the tools and the PLA have directly answered some of the business's problems. But I think by having those conversations and actually engaging with the business, um, you know, especially if the business hold the purse strings, which in, in, uh, you know, in some companies include not as they do there is that kind of, you know, almost by understanding their, their pain points and then starting, this is how we can solve your problem. Um, is we've, we've tended to be much more successful than trying to impose something and say, well, here's the technology that they don't quite understand. It doesn't really understand how it kind of resonates with their problems. So I think that's the heart of it. It's really about, you know, getting, looking at the data, looking at the processes, looking at where the kind of waste is. >>And then actually then looking at the right solutions. Then, as I say, continuous testing is massive for us. We've also got a good relationship with Apple towards looking at visual AI. And actually there's a common theme through that. And I mean, AI is becoming more and more prevalent. And I know, you know, sometimes what is AI and people have kind of this semantics of, is it true AI or not, but it's certainly, you know, AI machine learning is becoming more and more prevalent in the way that we work. And it's allowing us to be much more effective, be quicker in what we do and be more accurate. And, you know, whether it's finding defects running the right tests or, um, you know, being able to anticipate problems before they're happening in a production environment. >>Well, thank you so much for giving us this sort of insight outlook at dev ops sharing the successes that you're having, taking those challenges, converting them to opportunities and forgiving folks who might be in your shoes, or maybe slightly behind advice enter. They appreciate it. We appreciate your time. >>Well, it's been an absolute pleasure, really. Thank you for inviting me. I have a extremely enjoyed it. So thank you ever so much. >>Excellent. Me too. I've learned a lot for Glenn Martin. I'm Lisa Martin. You're watching the cube >>Driving revenue today means getting better, more valuable software features into the hands of your customers. If you don't do it quickly, your competitors as well, but going faster without quality creates risks that can damage your brand destroy customer loyalty and cost millions to fix dev ops from Broadcom is a complete solution for balancing speed and risk, allowing you to accelerate the flow of value while minimizing the risk and severity of critical issues with Broadcom quality becomes integrated across the entire DevOps pipeline from planning to production, actionable insights, including our unique readiness score, provide a three 60 degree view of software quality giving you visibility into potential issues before they become disasters. Dev ops leaders can manage these risks with tools like Canary deployments tested on a small subset of users, or immediately roll back to limit the impact of defects for subsequent cycles. Dev ops from Broadcom makes innovation improvement easier with integrated planning and continuous testing tools that accelerate the flow of value product requirements are used to automatically generate tests to ensure complete quality coverage and tests are easily updated. >>As requirements change developers can perform unit testing without ever leaving their preferred environment, improving efficiency and productivity for the ultimate in shift left testing the platform also integrates virtual services and test data on demand. Eliminating two common roadblocks to fast and complete continuous testing. When software is ready for the CIC CD pipeline, only DevOps from Broadcom uses AI to prioritize the most critical and relevant tests dramatically improving feedback speed with no decrease in quality. This release is ready to go wherever you are in your DevOps journey. Broadcom helps maximize innovation velocity while managing risk. So you can deploy ideas into production faster and release with more confidence from around the globe. It's the queue with digital coverage of dev ops virtual forum brought to you by Broadcom. >>Hi guys. Welcome back. So we have discussed the current state and the near future state of dev ops and how it's going to evolve from three unique perspectives. In this last segment, we're going to open up the floor and see if we can come to a shared understanding of where dev ops needs to go in order to be successful next year. So our guests today are, you've seen them all before Jeffrey Hammond is here. The VP and principal analyst serving CIO is at Forester. We've also Serge Lucio, the GM of Broadcom's enterprise software division and Glenn Martin, the head of QA transformation at BT guys. Welcome back. Great to have you all three together >>To be here. >>All right. So we're very, we're all very socially distanced as we've talked about before. Great to have this conversation. So let's, let's start with one of the topics that we kicked off the forum with Jeff. We're going to start with you spiritual co-location that's a really interesting topic that we've we've uncovered, but how much of the challenge is truly cultural and what can we solve through technology? Jeff, we'll start with you then search then Glen Jeff, take it away. >>Yeah, I think fundamentally you can have all the technology in the world and if you don't make the right investments in the cultural practices in your development organization, you still won't be effective. Um, almost 10 years ago, I wrote a piece, um, where I did a bunch of research around what made high-performance teams, software delivery teams, high performance. And one of the things that came out as part of that was that these teams have a high level of autonomy. And that's one of the things that you see coming out of the agile manifesto. Let's take that to today where developers are on their own in their own offices. If you've got teams where the team itself had a high level of autonomy, um, and they know how to work, they can make decisions. They can move forward. They're not waiting for management to tell them what to do. >>And so what we have seen is that organizations that embraced autonomy, uh, and got their teams in the right place and their teams had the information that they needed to make the right decisions have actually been able to operate pretty well, even as they've been remote. And it's turned out to be things like, well, how do we actually push the software that we've created into production that would become the challenge is not, are we writing the right software? And that's why I think the term spiritual co-location is so important because even though we may be physically distant, we're on the same plane, we're connected from a, from, from a, a shared purpose. Um, you know, surgeon, I worked together a long, long time ago. So it's been what almost 15, 16 years since we were at the same place. And yet I would say there's probably still a certain level of spiritual co-location between us, uh, because of the shared purposes that we've had in the past and what we've seen in the industry. And that's a really powerful tool, uh, to build on. So what do tools play as part of that, to the extent that tools make information available, to build shared purpose on to the extent that they enable communication so that we can build that spiritual co-location to the extent that they reinforce the culture that we want to put in place, they can be incredibly valuable, especially when, when we don't have the luxury of physical locate physical co-location. Okay. That makes sense. >>It does. I shouldn't have introduced us. This last segment is we're all spiritually co-located or it's a surge, clearly you're still spiritually co located with jump. Talk to me about what your thoughts are about spiritual of co-location the cultural impact and how technology can move it forward. >>Yeah. So I think, well, I'm going to sound very similar to Jeff in that respect. I think, you know, it starts with kind of a shared purpose and the other understanding, Oh, individuals teams, uh, contributed to kind of a business outcome, what is our shared goal or shared vision? What's what is it we're trying to achieve collectively and keeping it kind of aligned to that? Um, and so, so it's really starts with that now, now the big challenge, always these over the last 20 years, especially in large organization, there's been specialization of roles and functions. And so we, we all that started to basically measure which we do, uh, on a daily basis using metrics, which oftentimes are completely disconnected from kind of a business outcome or purpose. We, we kind of reverted back to, okay, what is my database all the time? What is my cycle time? >>Right. And, and I think, you know, which we can do or where we really should be focused as an industry is to start to basically provide a lens or these different stakeholders to look at what they're doing in the context of kind of these business outcomes. So, um, you know, probably one of my, um, favorites experience was to actually weakness at one of a large financial institution. Um, you know, Tuesday Golder's unquote development and operations staring at the same data, right. Which was related to, you know, in calming changes, um, test execution results, you know, Coverity coverage, um, official liabilities and all the all ran. It could have a direction level links. And that's when you start to put these things in context and represent that to you in a way that these different stakeholders can, can look at from their different lens. And, uh, and it can start to basically communicate and, and understand have they joined our company to, uh, to, to that kind of common view or objective. >>And Glen, we talked a lot about transformation with you last time. What are your thoughts on spiritual colocation and the cultural part, the technology impact? >>Yeah, I mean, I agree with Jeffrey that, you know, um, the people and culture, the most important thing, actually, that's why it's really important when you're transforming to have partners who have the same vision as you, um, who, who you can work with, have the same end goal in mind. And w I've certainly found that with our, um, you know, continuing relationship with Broadcom, what it also does though, is although, you know, tools can accelerate what you're doing and can join consistency. You know, we've seen within simplify, which is BTS flagship transformation program, where we're trying to, as it can, it says simplify the number of systems stacks that we have, the number of products that we have actually at the moment, we've got different value streams within that program who have got organizational silos. We were trying to rewrite, rewrite the wheel, um, who are still doing things manually. >>So in order to try and bring that consistency, we need the right tools that actually are at an enterprise grade, which can be flexible to work with in BT, which is such a complex and very dev, uh, different environments, depending on what area of BT you're in, whether it's a consumer, whether it's a mobile area, whether it's large global or government organizations, you know, we found that we need tools that can, um, drive that consistency, but also flex to Greenfield brownfield kind of technologies as well. So it's really important that as I say, for a number of different aspects, that you have the right partner, um, to drive the right culture, I've got the same vision, but also who have the tool sets to help you accelerate. They can't do that on their own, but they can help accelerate what it is you're trying to do in it. >>And a really good example of that is we're trying to shift left, which is probably a, quite a bit of a buzz phrase in their kind of testing world at the moment. But, you know, I could talk about things like continuous delivery direct to when a ball comes tools and it has many different features to it, but very simply on its own, it allows us to give the visibility of what the teams are doing. And once we have that visibility, then we can talk to the teams, um, around, you know, could they be doing better component testing? Could they be using some virtualized services here or there? And that's not even the main purpose of continuous delivery director, but it's just a reason that tools themselves can just give greater visibility of have much more intuitive and insightful conversations with other teams and reduce those organizational silos. >>Thanks, Ben. So we'd kind of sum it up, autonomy collaboration tools that facilitate that. So let's talk now about metrics from your perspectives. What are the metrics that matter? Jeff, >>I'm going to go right back to what Glenn said about data that provides visibility that enables us to, to make decisions, um, with shared purpose. And so business value has to be one of the first things that we look at. Um, how do we assess whether we have built something that is valuable, you know, that could be sales revenue, it could be net promoter score. Uh, if you're not selling what you've built, it could even be what the level of reuse is within your organization or other teams picking up the services, uh, that you've created. Um, one of the things that I've begun to see organizations do is to align value streams with customer journeys and then to align teams with those value streams. So that's one of the ways that you get to a shared purpose, cause we're all trying to deliver around that customer journey, the value with it. >>And we're all measured on that. Um, there are flow metrics which are really important. How long does it take us to get a new feature out from the time that we conceive it to the time that we can run our first experiments with it? There are quality metrics, um, you know, some of the classics or maybe things like defect, density, or meantime to response. Um, one of my favorites came from a, um, a company called ultimate software where they looked at the ratio of defects found in production to defects found in pre production and their developers were in fact measured on that ratio. It told them that guess what quality is your job to not just the test, uh, departments, a group, the fourth level that I think is really important, uh, in, in the current, uh, situation that we're in is the level of engagement in your development organization. >>We used to joke that we measured this with the parking lot metric helpful was the parking lot at nine. And how full was it at five o'clock. I can't do that anymore since we're not physically co-located, but what you can do is you can look at how folks are delivering. You can look at your metrics in your SCM environment. You can look at, uh, the relative rates of churn. Uh, you can look at things like, well, are our developers delivering, uh, during longer periods earlier in the morning, later in the evening, are they delivering, uh, you know, on the weekends as well? Are those signs that we might be heading toward a burnout because folks are still running at sprint levels instead of marathon levels. Uh, so all of those in combination, uh, business value, uh, flow engagement in quality, I think form the backbone of any sort of, of metrics, uh, a program. >>The second thing that I think you need to look at is what are we going to do with the data and the philosophy behind the data is critical. Um, unfortunately I see organizations where they weaponize the data and that's completely the wrong way to look at it. What you need to do is you need to say, you need to say, how is this data helping us to identify the blockers? The things that aren't allowing us to provide the right context for people to do the right thing. And then what do we do to remove those blockers, uh, to make sure that we're giving these autonomous teams the context that they need to do their job, uh, in a way that creates the most value for the customers. >>Great advice stuff, Glenn, over to your metrics that matter to you that really make a big impact. And, and, and also how do you measure quality kind of following onto the advice that Jeff provided? >>That's some great advice. Actually, he talks about value. He talks about flow. Both of those things are very much on my mind at the moment. Um, but there was this, I listened to a speaker, uh, called me Kirsten a couple of months ago. It taught very much around how important flow management is and removing, you know, and using that to remove waste, to understand in terms of, you know, making software changes, um, what is it that's causing us to do it longer than we need to. So where are those areas where it takes long? So I think that's a very important thing for us. It's even more basic than that at the moment, we're on a journey from moving from kind of a waterfall to agile. Um, and the problem with moving from waterfall to agile is with waterfall, the, the business had a kind of comfort that, you know, everything was tested together and therefore it's safer. >>Um, and with agile, there's that kind of, you know, how do we make sure that, you know, if we're doing things quick and we're getting stuff out the door that we give that confidence, um, that that's ready to go, or if there's a risk that we're able to truly articulate what that risk is. So there's a bit about release confidence, um, and some of the metrics around that and how, how healthy those releases are, and actually saying, you know, we spend a lot of money, um, um, an investment setting up our teams, training our teams, are we actually seeing them deliver more quickly and are we actually seeing them deliver more value quickly? So yeah, those are the two main things for me at the moment, but I think it's also about, you know, generally bringing it all together, the dev ops, you know, we've got the kind of value ops AI ops, how do we actually bring that together to so we can make quick decisions and making sure that we are, um, delivering the biggest bang for our buck, absolutely biggest bang for the buck, surge, your thoughts. >>Yeah. So I think we all agree, right? It starts with business metrics, flow metrics. Um, these are kind of the most important metrics. And ultimately, I mean, one of the things that's very common across a highly functional teams is engagements, right? When, when you see a team that's highly functioning, that's agile, that practices DevOps every day, they are highly engaged. Um, that that's, that's definitely true. Now the, you know, back to, I think, uh, Jeff's point on weaponization of metrics. One of the key challenges we see is that, um, organizations traditionally have been kind of, uh, you know, setting up benchmarks, right? So what is a good cycle time? What is a good lead time? What is a good meantime to repair? The, the problem is that this is very contextual, right? It varies. It's going to vary quite a bit, depending on the nature of application and system. >>And so one of the things that we really need to evolve, um, as an industry is to understand that it's not so much about those flow metrics is about our, these four metrics ultimately contribute to the business metric to the business outcome. So that's one thing. The second aspect, I think that's oftentimes misunderstood is that, you know, when you have a bad cycle time or, or, or what you perceive as being a buy cycle time or better quality, the problem is oftentimes like all, do you go and explore why, right. What is the root cause of this? And I think one of the key challenges is that we tend to focus a lot of time on metrics and not on the eye type patterns, which are pretty common across the industry. Um, you know, if you look at, for instance, things like lead time, for instance, it's very common that, uh, organizational boundaries are going to be a key contributor to badly time. >>And so I think that there is, you know, the only the metrics there is, I think a lot of work that we need to do in terms of classifying, descend type patterns, um, you know, back to you, Jeff, I think you're one of the cool offers of waterscrumfall as a, as, as a key pattern, the industry or anti-spatter. Um, but waterscrumfall right is a key one, right? And you will detect that through kind of a defect arrival rates. That's where that looks like an S-curve. And so I think it's beyond kind of the, the metrics is what do you do with those metrics? >>Right? I'll tell you a search. One of the things that is really interesting to me in that space is I think those of us had been in industry for a long time. We know the anti-patterns cause we've seen them in our career maybe in multiple times. And one of the things that I think you could see tooling do is perhaps provide some notification of anti-patterns based on the telemetry that comes in. I think it would be a really interesting place to apply, uh, machine learning and reinforcement learning techniques. Um, so hopefully something that we'd see in the future with dev ops tools, because, you know, as a manager that, that, you know, may be only a 10 year veteran or 15 year veteran, you may be seeing these anti-patterns for the first time. And it would sure be nice to know what to do, uh, when they start to pop up, >>That would right. Insight, always helpful. All right, guys, I would like to get your final thoughts on this. The one thing that you believe our audience really needs to be on the lookout for and to put on our agendas for the next 12 months, Jeff will go back to you. Okay. >>I would say look for the opportunities that this disruption presents. And there are a couple that I see, first of all, uh, as we shift to remote central working, uh, we're unlocking new pools of talent, uh, we're, it's possible to implement, uh, more geographic diversity. So, so look to that as part of your strategy. Number two, look for new types of tools. We've seen a lot of interest in usage of low-code tools to very quickly develop applications. That's potentially part of a mainstream strategy as we go into 2021. Finally, make sure that you embrace this idea that you are supporting creative workers that agile and dev ops are the peanut butter and chocolate to support creative, uh, workers with algorithmic capabilities, >>Peanut butter and chocolate Glen, where do we go from there? What are, what's the one silver bullet that you think folks to be on the lookout for now? I, I certainly agree that, um, low, low code is, uh, next year. We'll see much more low code we'd already started going, moving towards a more of a SAS based world, but low code also. Um, I think as well for me, um, we've still got one foot in the kind of cow camp. Um, you know, we'll be fully trying to explore what that means going into the next year and exploiting the capabilities of cloud. But I think the last, um, the last thing for me is how do you really instill quality throughout the kind of, um, the, the life cycle, um, where, when I heard the word scrum fall, it kind of made me shut it because I know that's a problem. That's where we're at with some of our things at the moment we need to get beyond that. We need >>To be releasing, um, changes more frequently into production and actually being a bit more brave and having the confidence to actually do more testing in production and go straight to production itself. So expect to see much more of that next year. Um, yeah. Thank you. I haven't got any food analogies. Unfortunately we all need some peanut butter and chocolate. All right. It starts to take us home. That's what's that nugget you think everyone needs to have on their agendas? >>That's interesting. Right. So a couple of days ago we had kind of a latest state of the DevOps report, right? And if you read through the report, it's all about the lost city, but it's all about sweet. We still are receiving DevOps as being all about speed. And so to me, the key advice is in order to create kind of a spiritual collocation in order to foster engagement, we have to go back to what is it we're trying to do collectively. We have to go back to tie everything to the business outcome. And so for me, it's absolutely imperative for organizations to start to plot their value streams, to understand how they're delivering value into aligning everything they do from a metrics to deliver it, to flow to those metrics. And only with that, I think, are we going to be able to actually start to really start to align kind of all these roles across the organizations and drive, not just speed, but business outcomes, >>All about business outcomes. I think you guys, the three of you could write a book together. So I'll give you that as food for thought. Thank you all so much for joining me today and our guests. I think this was an incredibly valuable fruitful conversation, and we appreciate all of you taking the time to spiritually co-located with us today, guys. Thank you. Thank you, Lisa. Thank you. Thank you for Jeff Hammond serves Lucio and Glen Martin. I'm Lisa Martin. Thank you for watching the broad cops Broadcom dev ops virtual forum.

>>from around the globe. It's the Cube with digital coverage of AWS Public Sector online brought to you by Amazon Web services. Oven Welcome back to the cubes. Virtual coverage of Amazon Web services. Eight. Of his public sector summit online. We couldn't be there in person, but we're doing remote interviews. I'm John Curry. Your host of the Cube got a great segment from Asia Pacific on the other side of the world from California about social impact, transforming, teaching and learning with cloud technology. Got three great guests. You go. Richard is the CEO and co founder of Guys Tech and Jean Te'o, CEO and founder of Solve Education Founders and CEOs of startups is great. This is squad was the AIPAC regional head. Education, health care, not for profit and research. Ray Ws, he head start big program Vincent. Thanks for coming on, Janine. And you go Thank you for joining. >>Thanks for having us, John. >>We're not there in person. We're doing remote interviews. I'm really glad to have this topic because now more than ever, social change is happening. Um, this next generation eyes building software and applications to solve big problems. And it's not like yesterday's problems there. Today's problems and learning and mentoring and starting companies are all happening virtually digitally and also in person. So the world's changing. So, um, I gotta ask you, Vincent, we'll start with you and Amazon. Honestly, big started builder culture. You got two great founders here. CEO is doing some great stuff. Tell us a little bit what's going on. A pack, >>A lot of >>activity. I mean, reinvent and some it's out. There are really popular. Give us an update on what's happening. >>Thank you. Thank you for the question, John. I think it's extremely exciting, especially in today's context, that we are seeing so much activities, especially in the education technology sector. One of the challenges that we saw from our education technology customers is that they are always looking for help and support in many off the innovation that they're trying to develop the second area off observation that we had waas, that they are always alone with very limited resources, and they usually do not know where to look for in terms, off support and in terms off who they can reach out to. From a community standpoint, that is actually how we started and developed this program called A W s. At START. It is a program specifically for education technology companies that are targeting delivering innovative education solutions for the education sector. And we bring specific benefits to these education technology companies when they join the program. Aws ed start. Yeah, three specific areas. First one is that we support them with technical support, which is really, really key trying to help them navigate in the various ranges off A W S services that allows them to develop innovative services. The second area is leaking them and building a community off like minded education technology founders and linking them also to investors and VCs and lastly, off course, in supporting innovation. We support them with a bit off AWS cop credits promotional credits for them so that they can go on experiment and develop innovations for their customers. >>That's great stuff. And I want to get into that program a little further because I think that's a great example of kind of benefits AWS provides actually free credits or no one is gonna turn away free credits. We'll take the free credits all the time all day long, but really it's about the innovation. Um, Jean, I want to get your thoughts. How would solve education? Born? What problems were you solving? What made you start this company and tell us your story? >>Thank you so much for the question. So, actually, my co founder was invited to speak at an African innovation forum a couple of years back on the topic that he was sharing with. How can Africa skip over the industrialization face and go direct to the knowledge economy? Onda, the discussion went towards in orderto have access to the knowledge economy, unique knowledge. And how do you get knowledge Well through education. So that's when everybody in the conference was a bit stuck right on the advice waas. In order to scale first, we need to figure out a way to not well, you know, engaging the government and schools and teachers, but not depend on them for the successful education initiated. So and that's was what pain walk away from the conference. And when we met in in Jakarta, we started talking about that also. So while I'm Singaporean, I worked in many developing countries on the problem that we're trying to solve this. It might be shocking to you, but UNESCO recently published over 600 million Children and you are not learning on. That is a big number globally right on out of all the SDG per se from U N. Education. And perhaps I'm biased because I'm a computer engineer. But I see that education is the only one that can be solved by transforming bites. But since the other stg is like, you know, poverty or hunger, right, actually require big amount of logistic coordination and so on. So we saw a very, um, interesting trend with mobile phones, particularly smartphones, becoming more and more ubiquitous. And with that, we saw a very, uh, interesting. Fortunately for us to disseminate education through about technology. So we in self education elevate people out of poverty, true, providing education and employment opportunities live urging on tech. And we our vision is to enable people to empower themselves. And what we do is that we do an open platform that provides everyone effected education. >>You could How about your company? What problem you're you saw And how did it all get started? Tell us your vision. >>Thanks, John. Well, look, it all started. We have a joke. One of the co founder, Matthew, had a has a child with severe learning disorder and dyslexia, and he made a joke one day about having another one of them that would support those those kids on Duh. I took the joke seriously, So we're starting sitting down and, you know, trying to figure out how we could make this happen. Um, so it turns out that the dyslexia is the most common learning disorder in the world, with an estimated 10 to 20% off the worldwide population with the disorder between context between 750 million, up to 1.5 billion individual. With that learning disorder on DSO, where we where we sort of try and tackle. The problem is that we've identified that there's two key things for Children with dyslexia. The first one is that knowing that it is dislikes. Yeah, many being assessed. And the second is so what? What do we do about it? And so given or expertise in data science and and I, we clearly saw, unfortunately off, sort of building something that could assess individual Children and adults with dyslexia. The big problem with the assessment is that it's very expensive. We've met parents in the U. S. Specifically who paid up to 6000 U. S. Dollars for for diagnosis within educational psychologist. On the other side, we have parents who wait 12 months before having a spot. Eso What we so clearly is that the observable symptom of dyslexia are reading and everyone has a smartphone and you're smart. Smartphone is actually really good to record your voice. Eso We started collecting order recording from Children and adults who have been diagnosed with dyslexia, and we then trying a model to recognize the likelihood of this lecture by analyzing audio recording. So in theory, it's like diagnosed dyslexic, helping other undiagnosed, dyslexic being being diagnosed. So we have now an algorithm that can take about 10 minutes, which require no priors. Training cost $20. Andi, anyone can use it. Thio assess someone's likelihood off dyslexia. >>You know, this is the kind of thing that really changes the game because you also have learning progressions that air nonlinear and different. You've got YouTube. You got videos, you have knowledge bases, you've got community. Vincent mentioned that Johnny and you mentioned, you know making the bits driver and changing technology. So Jeannine and Hugo, please take a minute to explain, Okay? You got the idea. You're kicking the tires. You're putting it together. Now you gotta actually start writing code >>for us. We know education technology is not you. Right? Um, education games about you. But before we even started, we look at what's available, and we quickly realize that the digital divide is very real. Most technology out there first are not designed for really low and devices and also not designed for people who do not have Internet at hope so way. So with just that assessment, we quickly realized we need toe do something about on board, but something that that that problem is one eyes just one part of the whole puzzle. There's two other very important things. One is advocacy. Can we prove that we can teach through mobile devices, And then the second thing is motivation it again. It's also really obvious, but and people might think that, you know, uh, marginalized communities are super motivated to learn. Well, I wouldn't say that they are not motivated, but just like all of us behavioral changes really hard right. I would love to work out every day, but, you know, I don't really get identity do that. So how do we, um, use technology to and, um, you know, to induce that behavioral change so that date, so that we can help support the motivation to learn. So those are the different things that we >>welcome? >>Yeah. And then the motivated community even more impactful because then once the flywheel gets going and it's powerful, Hugo, your reaction to you know, you got the idea you got, You got the vision you're starting to put. Take one step in front of the other. You got a W s. Take us through the progression, understand the startup. >>Yeah, sure. I mean, what Jane said is very likely Thio what we're trying to do. But for us, there's there's free key things that in order for us to be successful and help as much people as we can, that is free things. The first one is reliability. The second one is accessibility, and the other one is affordability. Eso the reliability means that we have been doing a lot of work in the scientific approach as to how we're going to make this work. And so we have. We have a couple of scientific publications on Do we have to collect data and, you know, sort of published this into I conferences and things like that. So make sure that we have scientific evidence behind us that that support us. And so what that means that we had Thio have a large amount of data >>on and >>put this to work right on the other side. The accessibility and affordability means that, Julian said. You know it needs to be on the cloud because if it's on the cloud, it's accessible for anyone with any device with an Internet connection, which is, you know, covering most of the globe, it's it's a good start on DSO the clock. The cloud obviously allow us to deliver the same experience in the same value to clients and and parent and teacher and allied health professionals around the world. Andi. That's why you know, it's it's been amazing to to be able to use the technology on the AI side as well. Obviously there is ah lot of benefit off being able to leverage the computational power off off the cloud to to make better, argue with them and better training. >>We're gonna come back to both of you on the I question. I think that's super important. Benson. I want to come back to you, though, because in Asia Pacific and that side of the world, um, you still have the old guard, the incumbents around education and learning. But there is great penetration with mobile and broadband. You have great trends as a tailwind for Amazon and these kinds of opportunity with Head Start. What trends are you seeing that are now favoring you? Because with co vid, you know the world is almost kind of like been a line in the sand is before covert and after co vid. There's more demand for learning and education and community now than ever before, not just for education, the geopolitical landscape, everything around the younger generation. There's, um, or channels more data, the more engagement. How >>are you >>looking at this? What's your vision of these trends? Can you share your thoughts on how that's impacting learning and teaching? >>So there are three things that I want to quickly touch on number one. I think government are beginning to recognize that they really need to change the way they approach solving social and economic problems. The pandemic has certainly calls into question that if you do not have a digital strategy, you can't You can find a better time, uh, to now develop and not just developed a digital strategy, but actually to put it in place. And so government are shifting very, very quickly into the cloud and adopting digital strategy and use digital strategy to address some of the key problems that they are facing. And they have to solve them in a very short period of time. Right? We will talk about speed, three agility off the cloud. That's why the cloud is so powerful for government to adult. The second thing is that we saw a lot of schools closed down across the world. UNESCO reported what 1.5 billion students out of schools. So how then do you continue teaching and learning when you don't have physical classroom open? And that's where education, technology companies and, you know, heroes like Janine's Company and others there's so many of them around our ableto come forward and offer their services and help schools go online run classrooms online continue to allow teaching and learning, you know, online and and this has really benefited the overall education system. The third thing that is happening is that I think tertiary education and maybe even catch off education model will have to change. And they recognize that, you know, again, it goes back to the digital strategy that they got to have a clear digital strategy. And the education technology companies like, what? Who we have here today, just the great partners that the education system need to look at to help them solve some of these problems and get toe addressing giving a solution very, very quickly. >>Well, I know you're being kind of polite to the old guard, but I'm not that polite. I'll just say it. There's some old technology out there and Jenny and you go, You're young enough not to know what I t means because you're born in the cloud. So that's good for you. I remember what I t is like. In fact, there's a There's a joke here in the United States that with everyone at home, the teachers have turned into the I T department, meaning they're helping the parents and the kids figure out how to go on mute and how toe configure a network adds just translation. If they're routers, don't work real problems. I mean, this was technology. Schools were operating with low tech zooms out there. You've got video conferencing, you've got all kinds of things. But now there's all that support that's involved. And so what's happening is it's highlighting the real problems of the institutional technology. So, Vincent, I'll start with you. Um, this is a big problem. So cloud solves that one. You guys have pretty much helped. I t do things that they don't want to do any more by automation. This >>is an >>opportunity not necessary. There's a problem today, but it's an opportunity tomorrow. You just quickly talk about how you see the cloud helping all this manual training and learning new tools. >>We are all now living in a cloud empowered economy. Whether we like it or not, we are touching and using services. There are powered by the cloud, and a lot of them are powered by the AWS cloud. But we don't know about it. A lot of people just don't know, right Whether you are watching Netflix, um Well, in the old days you're buying tickets and and booking hotels on Expedia or now you're actually playing games on epic entertainment, you know, playing fortnight and all those kind of games you're already using and a consumer off the cloud. And so one of the big ideas that we have is we really want to educate and create awareness off club computing for every single person. If it can be used for innovation and to bring about benefits to society, that is a common knowledge that everyone needs to happen. So the first big idea is want to make sure that everyone actually is educated on club literacy? The second thing is, for those who have not embarked on a clear cloud strategy, this is the time. Don't wait for for another pandemic toe happen because you wanna be ready. You want to be prepared for the unknown, which is what a lot of people are faced with, and you want to get ahead of the curve and so education training yourself, getting some learning done, and that's really very, very important as the next step to prepare yourself toe face the uncertainty and having programs like AWS EC start actually helps toe empower and catalyzed innovation in the education industry that our two founders have actually demonstrated. So back to you Join. >>Congratulations on the head. Start. We'll get into that real quickly. Uh, head start. But let's first get the born in the cloud generation, Janine. And you go, You guys were competing. You gotta get your APS out there. You gotta get your solutions. You're born in the cloud. You have to go compete with the existing solutions. How >>do you >>view that? What's your strategy? What's your mindset? Janine will start with you. >>So for us, way are very aware that we're solving a problem that has never been solved, right? If not, we wouldn't have so many people who are not learning. So So? So this is a very big problem. And being able to liberate on cloud technology means that we're able to just focus on what we do best. Right? How do we make sure that learning is sufficient and learning is, um, effective? And how do we keep people motivated and all those sorts of great things, um, leveraging on game mechanics, social network and incentives. And then while we do that on the outside way, can just put almost out solved everything to AWS cloud technology to help us not worry about that. And you were absolutely right. The pandemic actually woke up a lot of people and hands organizations like myself. We start to get queries from governments on brother, even big NGOs on, you know, because before cove it, we had to really do our best to convince them until our troops are dry and way, appreciate this opportunity and and also we want to help people realized that in order to buy, adopting either blended approach are a adopting technology means that you can do mass customization off learning as well. And that's what could what we could do to really push learning to the next level. So and there are a few other creative things that we've done with governments, for example, with the government off East Java on top of just using the education platform as it is andare education platform, which is education game Donald Civilization. Um, they have added in a module that teaches Cove it because, you know, there's health care system is really under a lot of strain there, right and adding this component in and the most popular um mitigate in that component is this This'll game called hopes or not? And it teaches people to identify what's fake news and what's real news. And that really went very popular and very well in that region off 25 million people. So tech became not only just boring school subjects, but it can be used to teach many different things. And following that project, we are working with the federal government off Indonesia to talk about anti something and even a very difficult topic, like sex education as well. >>Yeah, and the learning is nonlinear, horizontally scalable, its network graft so you can learn share about news. And this is contextual data is not just learning. It's everything is not like, you know, linear learning. It's a whole nother ballgame, Hugo. Um, your competitive strategy. You're out there now. You got the covert world. How are you competing? How is Amazon helping you? >>Absolutely. John, look, this is an interesting one, because the current competitors that we have, uh, educational psychologist, they're not a tech, So I wouldn't say that we're competing against a competitive per se. I would say that we're competing against the old way of doing things. The challenge for us is to, um, empower people to be comfortable. We've having a machine, you know, analyzing your kids or your recording and telling you if it's likely to be dislikes. Yeah, and in this concept, obviously, is very new. You know, we can see this in other industry with, you know, you have the app that stand Ford created to diagnose skin cancer by taking a photo of your skin. It's being done in different industry. Eso The biggest challenge for us is really about the old way of doing things. What's been really interesting for us is that, you know, education is lifelong, you know, you have a big part in school, but when you're an adult, you learn on Did you know we've been doing some very interesting work with the Justice Department where, you know, we look at inmate and you know, often when people go to jail, they have, you know, some literacy difficulty, and so we've been doing some very interesting working in this field. We're also doing some very interesting work with HR and company who want to understand their staff and put management in place so that every single person in the company are empowered to do their job and and and, you know, achieve success. So, you know, we're not competing against attack. And often when we talk to other ethnic company, we come before you know, we don't provide a learning solution. We provide a assessment solution on e assessment solution. So, really, John, what we're competing against is an old way of doing things. >>And that's exactly why clouds so successful. You change the economics, you're actually a net new benefit. And I think the cloud gives you speed and you're only challenges getting the word out because the economics air just game changing. Right, So that's how Amazon does so well, um, by the way, you could take all our recordings from the Cube, interviews all my interviews and let me know how ideo Okay, so, um, got all the got all the voice recordings from my interview. I'm sure the test will come back challenging. So take a look at that e. I wanna come back to you. But I wanna ask the two founders real quick for the folks watching. Okay on Dhere about Amazon. They know the history. They know the startups that started on Amazon that became unicorns that went public. I mean, just a long list of successes born in the cloud You get big pay when you're successful. Love that business model. But for the folks watching that were in the virtual garages, air in their houses, innovating and building out new ideas. What does Ed start mean for them? How does it work? Would you would recommend it on what are some of the learnings that you have from work with Head Start? >>But our relationship X s start is almost not like client supplier relationship. It's almost like business partners. So they not only help us with protect their providing the technology, but on top of that, they have their system architect to work with my tech team. And they have, you know, open technical hours for us to interact. And on top of that, they do many other things, like building a community where, you know, people like me and Google can meet and also other opportunities, like getting out the word out there. Right. As you know, all of their, uh, startups run on a very thin budget. So how do we not pour millions of dollars into getting out without there is another big benefit as well. So, um definitely very much recommend that start. And I think another big thing is this, right? Uh, what we know now that we have covert and we have demand coming from all over the place, including, like, even a lot of interest, Ally from the government off Gambia, you know? So how do we quickly deploy our technology right there? Or how do we deploy our technology from the the people who are demanding our solution in Nigeria? Right. With technology that is almost frameless. >>Yeah. The great enabling technology ecosystem to support you. And they got the region's too. So the region's do help. I love we call them Cube Region because we're on Amazon. We have our cloud, Hugo, um, and start your observations, experience and learnings from working with aws. >>Absolutely. Look, this is a lot to say, so I'll try and making sure for anyone, but but also for us on me personally, also as an individual and as a founder, it's really been a 365 sort of support. So like Johnny mentioned, there's the community where you can connect with existing entrepreneur you can connect with expert in different industry. You can ask technical expert and and have ah, you know office our every week. Like you said Jenny, with your tech team talking to cloud architect just to unlock any problem that you may have on day and you know, on the business side I would add something which for us has been really useful is the fact that when we when we've approached government being able to say that we have the support off AWS and that we work with them to establish data integrity, making sure everything is properly secured and all that sort of thing has been really helpful in terms off, moving forward with discussion with potential plant and and government as well. So there's also the business aspect side of things where when people see you, there's a perceived value that you know, your your entourage is smart people and and people who are capable of doing great things. So that's been also really >>helpful, you know, that's a great point. The APP SEC review process, as you do deals is a lot easier. When here on AWS. Vincent were a little bit over time with a great, great great panel here. Close us out. Share with us. What's next for you guys? You got a great startup ecosystem. You're doing some great work out there and education as well. Healthcare. Um, how's your world going on? Take a minute, Thio. Explain what's going on in your world, >>John, I'm part of the public sector Team Worldwide in AWS. We have very clear mission statements on by the first is you know, we want to bring about destructive innovation and the AWS Cloud is really the platform where so many off our techs, whether it's a text, healthtech golf text, all those who are developing solutions to help our governments and our education institutions or health care institutions to really be better at what they do, we want to bring about those disruptive innovations to the market as fast as possible. It's just an honor on a privilege for us to be working. And why is that important? It's because it's linked to our second mission, which is to really make the world a better place to really deliver. Heck, the kind of work that Hugo and Janina doing. You know, we cannot do it by ourselves. We need specialists and really people with brilliant ideas and think big vision to be able to carry out what they are doing. And so we're just honored and privileged to be part off their work And in delivering this impact to society, >>the expansion of AWS out in your area has been phenomenal growth. I've been saying to Teresa Carlson, Andy Jassy in the folks that aws for many, many years, that when you move fast with innovation, the public sector and the private partnerships come together. You're starting to see that blending. And you've got some great founders here, uh, making a social impact, transforming, teaching and learning. So congratulations, Janine and Hugo. Thank you for sharing your story on the Cube. Thanks for joining. >>Thank you. Thank >>you, John. >>I'm John Furry with the Cube. Virtual were remote. We're not in person this year because of the pandemic. You're watching a divest Public sector online summit. Thank you for watching

>> Narrator: Live from San Francisco, it's theCUBE, covering RSA Conference 2020 San Francisco. Brought to you by SiliconANGLE Media. >> Welcome back everyone. This is theCUBE's coverage from RSA Conference on Moscone South. I'm John Furrier, host of theCUBE. You know, cybersecurity is changing, and the next technology is right around the corner, and it's got to be invented somewhere, and of course Accenture Labs is part of it. Our next guest is Lisa O'Connor, Global Security R&D Lead for Accenture Labs. Lisa's working on some of those hard problems all around the world. Thank you for joining me today. Thanks for coming on. >> Thank you for having me. >> So, we always get the good scoop from Accenture, because you have a lot of smart people in that company. You know, they know their stuff. I know you got a huge analytics team. I've talked to Jean-Luc Chatelain before, and I know you got a massive amount of, deep bench of talent. But as you have to go do the applied R&D, and maybe some of the crazy ideas, you got to start thinking about where the puck is going to be. >> Absolutely. >> You got to understand that. Well, it's pretty clear to us that Cloud is certainly there. Palo Alto Networks had a disappointing earnings yesterday, because their on-premises business is shifting to the Cloud. You're seeing hybrid operating model and multicloud for the enterprise, but now you got global challenges. >> We absolutely do. >> Huge, so what are you guys working on that's coming? Tell us. >> So we're working on lots of exciting things, and Cloud is one of them. But, some of the things I'm so passionate about in labs, and I have the best job at Accenture. Don't tell anyone. (laughs) I do. So, we are working on, like Jean-Luc is working on applied intelligence, we are working on robust AI. So, when we think about AI in the future, how do we feel that, and know that it's okay? How do we put it out there and know it's safe in production, we've done the right training, we've made our model resilient to what's out there? One of the things we see happening, and I love AI, love it. It has great potential, and we get great insights out of it, but a lot of times we stop, we get the insights, and we say, "Okay, it's in the box, we got a couple hits there, "we're good, it's good." No, maybe not. And so really, it's learning and creating the actually applied attacks on AI, and then figuring out what the right defenses are. And, depending on what type of machine learning you're using, those defenses change. And so, we're having a great time in our lab in Washington D.C., working on basically defending AI and building those techniques, so that what we put out as Accenture is robust. >> You know, it's interesting, AI, you watch some of the hardcore, you know, social justice warriors out there going after Amazon, Google, you know, because they're doing some pretty progressive things. Oh, facial recognition, you got AI, you got Alexa. You know, a lot of people are like, "Oh, I'm scared." But, at the end of the day, they also have some challenges like network security, so you have all this AI up and down the stack. And, one thing I like about what's being talked about in the industry is the shared responsibility model. So, I got to ask you, as AI becomes exciting, but also, balancing, frightening to people, how do you get that shared responsibility model, so we get it right, do the experimentation, without people freaking out? (laughs) So, it's kind of like this weird mode we're in now, where I want to do more AI, because I think it benefits society, but everyone's freaking out. >> Yeah, so, in our tech vision that we just launched, The Tech Vision 2020, there's a lot of talk about value and values, which is really important when we think about AI because we can get great value out of it, but there's a values piece of it and it's how we're using it, how we're getting those insights. Because, the one thing, we have this circle, and it's between customer experience, because the companies that do customer experience well are going to excel, they're going to keep their clients, they're going to do amazing things, they're going to become sticky. But, to do that well, you have to be a good custodian of their data and their information, and curated experiences that they want, and not the creepy ones, not the ones they don't want. And so, we really look at that trust is necessary in that ecosystem, in building that, and keeping that with clients. So, that's something that came out of our technology vision. And, in fact, we're going to be talking at the Executive Women's Forum, this is tomorrow, and we're going to be having a panel on AI, and defending it, which will be very interesting. >> Make sure your people film that conference. We'd like to get a view of it on YouTube after. We love those conferences, really insightful. But, I want to get back to what you were talking about, the fun side. >> Yeah. >> You got a lot of new things on, your guys are kicking the tires on, scratching the surface on. You have two operating labs, one in Washington D.C., and one in Israel. What city in Israel? Is it in Tel Aviv or-- >> Herzliya. >> Okay, did not know. >> Yeah, the tech district, just north of Tel Aviv. It's the hotspot. >> So, Silicon Valley, D.C., and Israel, hotbeds of technology now. >> Yes. >> What's coming out of those labs, what's hot? >> Oh, there's so much exciting stuff coming out of our lab in Herzliya. One of the things that we have, and it's something that's been long and coming, it's been brewing for a while, but it's really looking at creating a model of the enterprise security posture. And, when I say a model of it, I'm talking about a cyber digital twin. Because, so much we can't do in our production networks, we don't have the capabilities. We can look around the room, but we don't have the capabilities on the SOCs team side, to ingest all this stuff. We need a playground where we can ask the what-ifs, where we can run high performance analytics, and we do that through a temporal knowledge graph. And, that's a hard thing to achieve, and it's a hard thing to do analytics at scale. So, that's one of the big projects that we're doing out of our Israel lab. >> Are you saying digital twins is a framework for that? >> Yeah. >> Does it really work well with that? >> So the knowledge graph, we can create digital twins around many things, because a digital twin is a model of processes, people, technologies, the statefulness of things, and configurations, whatever you want to pull in there. So, when we start thinking about, what would we take in to create the perfect enterprise security posture? What would give us all the insights? And, then we can ask the questions about, okay, how would an adversary do lateral movement through this? I can't fix everything that's a 10, but I could fix the right ones to reduce the risk impactfully. And, those are the kind of what-ifs that you can do. >> That's real sci-fi stuff, that's right around the corner. >> Yeah, it is. >> That simulation environment. >> It is. >> What-ifs. Oh my god, the company just got hacked, we're out of business. That's your simulation. You could get to, that's the goal, right? >> It absolutely is, to ask those good business questions about the data, and then to report on the risk of it. And, the other thing, as we move to 5G, this problem's getting bigger and bigger, and we're now bringing in very disparate kinds of compute platforms, computing-at-the-edge. And, what does that do to our nice little network model that we had, that our traditional systems are used to defending against? >> I mean, just the segmentation of the network, and the edge opens up so much more aperture-- >> Yes, it does (laughs). >> to the digital twin, or a knowledge graph. You brought up knowledge graph, I want to get your thoughts on this. I was just having dinner last night with an amazing woman out of New York. She's a Ph.D. in computer science. So, we're talking about graphs, and I love riffing on graph databases. But, the topic came up about databases in general, because with the cloud, it's horizontally scalable, you've got all kinds of simulation, a lot of elasticity going on, there's a lot of software being written on this. You got time series database, you got relational database, you got unstructured, and you got graphs. You got to make them all work together. This is kind of the unique challenge. And, with security, leveraging the right database, and the right construct is a super important thing. How do you guys look at that in the labs? Because, is it something that you guys think about, or is it going to be invisible someday? >> Oh, we think about it a lot. In fact, we've had a number of research projects over the last five years now, actually six years, where we've really pivoted hard in cyber security to graph databases. And, the reason for that is, the many-to-many relationships, and what we can do in terms of navigating, asking the questions, pulling on a thread, because in cyber hunting, that's what we're doing. In many of these use cases that we're trying to defend an enterprise, we're following the next new path based on the newest information of now what the challenge is, or what the current configuration is. So, that's really important. So, graph databases enable that so well. Now, there's still the architecture challenge of, okay, when I ask a query, what am I doing? Am I disrupting the whole apple cart? Do I have to process everything over, or is there a way to do that elegantly, where I can ask my query, and because of how I've structured it in storage, I can do it much better, and I can do it much more efficiently. And that, I think, is where the opportunities are. >> I got to tell you, I'm getting exited now on this whole database discussion, because you think about the logic around what you just said. A graph database with that kind of complexity, when you factor in contextually different things happening at any given time, the database needs to be parsed and managed differently. >> Yes. >> That's a huge challenge. >> It is a great research challenge, which is why we're doing it. >> What is that, how far along are we going to be able to have this dynamic, self-evolving, self-governing, self-healing data modeling? Is that coming soon, or... >> Yeah, I hope so. We wrote about it a couple of years ago. >> You did? >> The self-healing enterprise, aspirational. But I think, I mean, we try to get to real time, right? And, we try to get to real time, and again, refactoring. As we talk about what an adversary is going to do, or lateral movement through a business process, we're talking about a lot of computational horsepower to recalculate all that, process it again, update it, and then again present that back. So the number of things we're asking, how we're asking it becomes also very important to the structure. >> Just, it goes zooming up a little bit, high level, what we're really talking about here is value >> of the data. >> Absolutely. >> And, when you get into the valuation of the nodes, and the arcs, and all that graphs, and other databases, you got to know what to pay attention to. It's kind of like going into the hospital and hearing all these alarms going off. At some point you don't know what's, until they hear a flat line, or whatever. >> Right. That's a bad one. >> I mean, well that's obvious. But, now sometimes there's so many alerts, there's so many alarms. How do you understand at any given time what to pay attention to, because obviously when someone's having a problem you want to pay attention to it. If it's a security alert, that's prioritized. >> And the devil is in the analytics, right? What's the question we're asking, and the analytics that give us that prioritization? And that's non-trivial, because there are a lot of other folks that are doing prioritization in a different manner. To do it at scale, and to do it, not just one hop out, but I want to go all the way to the crown jewels, I want that whole path navigated, and I want to know where to cut along that path. That's a hard thing to do. And so, we've actually developed, and we've submitted patents for them, but we've developed new analytics that'll support that. >> Awesome. Well Lisa, I want to ask you kind of a, I'll give you a plug here, just going to get it out, because I think it's important. Skills gap's a big thing, so I want to give you a minute to explain, or share what you're looking for in your hiring. Who are you looking for? What kind of, the make-up of individual, obviously? Maybe, do you use straight, more academic paper kind of people, or practitioners? I mean, when you look to hire, what are some of the priorities that you look for, and who would thrive in an Accenture Lab's environment? >> Oh, my goodness. >> Take a minute to share what you're looking for. >> Yeah, so we love people that think out of the box, and those kinds of people come from very different backgrounds. And so, part of that is, some of them we look for Ph.D.'s, that have wonderful applied skills, and applied is a key word there. White papers are great, I need to be able to prove something, I need to be able to demo something that has value. So, having the applied skills to a business challenge is really important. So, that sort of ground, understanding the business, very important too. But, our talent comes from many different areas. I mean, I kind of joke, my lab looks like the UN, it's wonderful. I have people from across the globe that are in our cyber security lab. I have, in our Washington D.C. lab, we're 50% women, which is also exciting, because we want different experiences, and we shoot for cognitive diversity, right? So, we're looking for people that think differently about solving problems, and are not encumbered by what they've seen in the past, because we're trying to be tip of spear. And, I'm sure you know that from Paul Daugherty. >> Yeah. >> We are trying to be three to five years over the horizon. >> You guys got a good narrative. I always love talking to Accenture, they have a good vision. So, I got to ask you, the next logical question is, obviously, in the news, you see everyone talking about breaches, and ya know, it's not a breach if the door's open, you just walk in. They're really walking in, nothing was really breached, you're just giving it to them. >> Yeah. It's a passive invitation. >> (laughs) Hey come on in. Human error is a big part of it, but then, breach is obviously targeted, phishing, and all that good stuff. But, as those stories get told, there's a whole nother set of stories that aren't being told that are super important. So, I'd love to get your thoughts on, what are the most important stories that we should be talking about that aren't being talked about? >> Yeah, so I have two that are front-of-mind for me. One theme we come back to, and it's not sexy, it's hygiene. It is IT hygiene, and so many of the large companies, and even medium, small companies, we have legacy technology, and keeping that adds complexity, it adds to the whole breadth and depth of what we have to manage and defend. Keeping that attack surface simple and small, cloud-enabled, all those good things, is a real asset and it makes it much easier to defend. So, that's kind of the first non-sexy one, hygiene. The other one I'll say that I think is a challenge that we are not dealing with yet, quantum computing, right? And so, we're on the way to getting our post quantum cryptography in place, but there's another dimension to it, and it's our histories. So, all of the things that have passed on the wire, all the communications with the key exchanges, all that brilliant stuff, is sitting somewhere. Once we get to that point where this becomes very routine, and it's coming fast, we predicted eight years, two years ago. >> So, all that exhaust is somewhere, pent up. >> It's somewhere that, we have to think about how much data we're keeping as custodians, how we're managing it, and then we have to think about the exposure from our past, and say, "Okay, what does that mean that, that was out there?" "Is it aged enough that it doesn't have value?" And, I think there's a real triage that needs to be done, and certainly data management. >> I think, you know, the hygiene brings up a good point. It reminds me of the story Andy Jassy was telling about the mainframe customer that they couldn't find who had the password. They had to find their person, who was retired 10 years earlier to get the password. You don't forget things, but also, there's a human component in all this. Humans and machines are working together. >> Absolutely. >> And. that's a huge part of it. It's not just machines dominating it all, there's going to be a human component, there's a societal impact that we're seeing with information. And, whether that's out in the open, or behind closed doors, there's all kinds of things looming. >> There are, and I think one of the things in the companies that we're seeing who are embracing innovation well, are doing a lot of retraining. Because, the things that people are excellent at, AI is not good at, and the things that AI is good at, are not at all what people are good at. So, the good news is there is a beautiful teaming there, if we retool the skills, or if we re-envision those roles, so that people can get into those roles, and I think that's really important, because I'd rather see AI do all the heavy lifting well, and be trustworthy, and robust and all those great things, and the people be doing the much smarter things that require a human. >> Does the process serve the purpose? Does the purpose serve the process? Same kind of question, right? >> Exactly. >> AI, you can't have great AI that does nothing. >> That's right. >> (laughs) So, it has to be relevant. >> It absolutely does. >> Relevance is kind of a big thing. >> And we own that context, right? Humans own that context. >> Yeah. Yeah. Yeah. Well, thanks for coming in, and sharing the insight. Really appreciate it. Final question, it's always tough to pick your favorite child, but what is your most coolest thing you're working on right now? >> I'll tell you, the cyber digital twin stuff is so cool. >> The what? >> The cyber digital twin stuff is so cool. When you see the power of what that picture, and the analytics can do, we'll show ya. >> Do you have a demo of that now? >> We absolutely do. >> You do. Is it online, or is it more in person you got to see it? >> More in person. >> Okay. >> Folks can reach out, yeah. >> We'll have to get the exclusive on that. >> We do. >> I love those simulations. I think it's very beneficial. >> It is. >> A lot of learning. I mean, who doesn't want practice? >> Well, and a picture, you know that is worth a million dollars. It's just incredible to look at it, and it clicks. It clicks of all the potential things you could ask or do. And, that's the exciting part now, as we show this with customers' and we co-innovate with customers', they're coming up with a laundry list of questions. >> And, this is the beautiful thing about cloud, is that new capabilities are emerging every day, and you could use the good ones. Lisa O'Connor is here. Thank you very much for sharing your insights. Global Security R&D Lead for Accenture Labs. TheCUBE coverage, getting all the signal here on the show floor, extracting that from all the noise. I'm John Furrier, thanks for watching. (upbeat music)

>>from San Francisco. It's the queue covering our essay conference. 2020. San Francisco Brought to you by Silicon Angle Media's >>Welcome Back Around Here at the Cube. Coverage for our conference. Mosconi, South Floor. Bring you all the action day one of three days of cube coverage where the security game is changing, the big players are making big announcements. The market's changing from on premise to cloud. Then hybrid Multi cloud was seeing that wave coming. A great guest here. Barr, our VP of product strategy and co founder of the Mystery, was acquired by Palo Alto Networks. Worries employed now, Rishi. Thanks for coming on. Thank you. Absolutely happy to be here. So, first of all, great journey for your company. Closed a year ago. Half a 1,000,000,000. Roughly give or take 60. Congratulations. Thank you. Big accomplishments. You guys were taken out right in the growth phase. Now at Palo Alto Networks, which we've been following, you know, very careful. You got a new CMO over there, Jean English? No, we're very well. We're very bullish on Palo Alto. Even though that the on premise transitions happening cloud. You guys are well positioned. How's things going things are going fantastic. We're investing a lot in the next Gen security business across the board, as mentioned Prisma Cloud is big business. And then on the other side, which is what I'm part of the cortex family focused on the Security operations center and the efficiencies That's fantastic and, ah, lot off product innovations, investment and the customer pull from an operations perspective. So very excited. You guys had a big announcement on Monday, and then yesterday was the earnings, which really kind of points to the trend that we're seeing, which is the wave to the cloud, which you're well positioned for this transition going on. I want to get to the news first. Then we get into some of the macro industry questions you guys announced the X ore, which is redefining orchestration. Yes. What is this about? What's this news about? Tell us. >> So this news is about Mr was acquired about a year ago as well. This is taking that Mr Platform and expanding it on, expanding it to include a very core piece, which is Intel management. If you look at a traditional saw, what has happened is soccer teams have had the same dead and over the last few years acquired a sword platform such as a mystery security orchestration, automation and response platform. But the Edge Intel team has always been still separate the threat Intel feeds that came in with separate. With this, we are expanding the power of automation and applying doc to the threat intelligence as well. That is, thread intelligence, current state of the art right now. So the current state of the art of threat intelligence is are the larger organizations typically subscribe to a lot of faith, feeds open source feeds and aggregate them. But the challenge is to aggregate them the sit in a repository and nobody knows what to do with them. So the operationalization of those feeds is completely missing. >> So basically, that is going to have data pile. Corpus is sitting there. No one touches it, and then everyone has to. It's a heavy lift. It's a heavy lift, and nobody knows. Cisco sees the value coming out of it. How do you proactively hunt using those? How do you put them to protecting proactively to explain cortex X, or what is it? And what's the value? So the cortex X or as a platform. There are four core pieces, three off which for the core tenants of the misto since the big one is automation and orchestration. So today we roughly integrate with close to 400 different products security and I t products. Why are the FBI on let customers build these work flows come out of the box with close to 80 or 90 different workloads. The idea of these workloads is being able to connect to one product for the data go to another taken action there Automation, orchestration builds a visual book second s case management and this is very critical, right? I mean, if you look at the process side of security, we have never focused as an industry and the process and the human side of security. So how do you make sure every security alert on the process the case management escalation sl A's are all managed. So that's a second piece off cortex. Third collaboration. One of the core tenants of Mr Waas. We heard from customers that analysts do not talk to each other effectively on when they do. Nobody captures that knowledge. So the misto has an inbuilt boardroom which now Cortex X or has the collaboration war room on that is now available to be able to chat among analysts. But not only that charged with the board take actions. The fourth piece, which is the new expanded platform, is the personal management to be able to now use the power of orchestration, automation collaboration, all for threat intelligence feeds as well. Not only the alerts >> so and so you're adding in the threat. Intelligence feeds, yes. So is that visualize ai on the machine Learning on that? How is that being process in real time? How does that on demand work for that fills. So the biggest piece is applying the automation and intelligence to automatically score that on being able to customize the scoring the customer's needs. Customized confidence score perfect. And once you have the high fidelity indicators automatically go block them as an example. If you get a very high fidelity IOC from FBI that this particular domain is the militias domain, you would want to block that in. Your firewall is executed immediately, and that is not happening today. That is the core, and that's because of the constraint is I don't know the data the way we don't know the data and it's manual. Some human needs to review it. Some human needs to go just not being surfaced, just not. So let's get back into some of the human piece. I love the collaboration piece. One of things that I hear all the time in my cube interviews across all the hundreds of events we go to is the human component you mentioned. Yes, people have burnt out. I mean, like the security guys. I mean, the joke was CIOs have good days once in a while, CSOs don't have any good days, and it's kind of a job board pejorative to that. But that's the reality. Is that it works? Yes. We actually okay, if you have another job. Talking of jokes, we have this. Which is what do you call and overwork security analyst. A security analyst, because every one of them >>is over word. >>So this is a huge thing. So, like the ai and some of the predictive analytics trend Is tourist personalization towards the analyst Exactly. This is a trend that we're seeing. What's your view on this? What? You're absolutely We're seeing that trend which is How do you make sure analyst gets to see the data they're supposed to see at the right time? Right. So there's one aspect is what do you bring up to the analyst? What is relevant and you bring it up at the right time to be able to use it. Respond with that. So that comes in one from an ML perspective and machine learning. And our cortex. XDR suite of products actually does a fantastic job of bringing very rich data to the analyst at the right time. And then the second is, can we help analyst respond to it? Can we take the repetitive work away from them with a playbook approach? And that's what the cortex platform brings to that. I love to riff on some future scenarios kind of. I won't say sci fi, but I got to roll a little bit of a future to me. I think security has to get to like a multi player gaming environment because imagine like a first person shooter game, you know where or a collaborative game where it's fun. Because once you start that collaboration, yes, then you're gonna have some are oi around. I saw that already. Don't waste your time or you get to know people. So sharing has been a big part? Yes. How soon do you think we're gonna get to an environment where I won't say like gaming? But that notion of a headset on I got some data. I know you are your reputation. I think your armor, you're you're certifications. Metaphorically putting. I think way have a lot of these aspects and I think it's a very critical point. You mentioned right one of the things which we call the virtual war room and like sex or I was pointing out the fact that you can have analysts sit in front of a collaboration war room not only charge for the appears but charged with a boat to go take care of. This is equivalent to remember that matrix movie plugging and says, you know how to fly this helicopter data and now I do. That's exactly what it is. I think we need to point move to a point where, no matter what the security tool is what your endpoint is, you should not have to learn every endpoint every time the normalization off, running those commands via the collaboration War Room should be dead. I would say we're starting to see in some of the customers are topics or they're using the collaboration war room to run those commands intractably, I would say, though, there's a big challenge. Security vendors do not do a good job normalizing that data, and that is where we're trying to reach you. First of all, you get the award for bringing up a matrix quote in The Cube interview. So props to that. So you have blue teams. Red teams picked the pill. I mean, people are people picking their teams. You know what's what's going on. How do you see the whole Red Team Blue team thing happening? I think that's a really good stuff happening. In my opinion, John, what's going on is right now so far, if you see if I go back three years our adversaries were are committing. Then we started to see this trend off red teaming automation with beach automation and bunch of companies starting to >>do that >>with Cortex X or on similar products, we're starting to now automate the blue team side of things, which is how do you automatically respond how do you protect yourself? How do you put the response framework back there? I think the next day and I'm starting to see is these things coming together into a unified platform where the blue team and the team are part of the same umbrella. They're sharing the data. They're sharing the information on the threat Intel chair. So I see we are a very, very good part. Of course, the adversities. I'm not gonna sit idle like you said about the Dev ops mindset. Heavens, notion of knowledge coming your way and having sharing packages all baked out for you. She doesn't do the heavy lifting. That's really the problem. The data is a problem. So much demand so much off it. And you don't know what is good and what is not. Great. Great conversation again. The Matrix reference about your journey. You've been an entrepreneur and sold. You had a great exit again. Politics is world class blue chip company in the industry public going through a transition. What's it like from an entrepreneur now to the big company? What's the opportunity is amazing. I think journey has been very quick. One. We saw some crazy growth with the misto on. Even after the acquisition, it's been incredibly fast pace. It's very interesting lot of one of the doctors like, Hey, you must be no resting is like, No, the journey is amazing. I think he s Polito Networks fundamentally believe that. We need to know where it really, really fast to keep the adversaries out on. But that's been the journey. Um, and we have accelerated, in fact, some of our product plans that we hard as a start up on delivering much faster. So the journey has been incredible, and we have been seeing that growth Will they picked you guys write up? There's no vesting interesting going on when you guys were on the uphill on the upslope growth and certainly relevance for Palo Alto. So clearly, you know, you haven't fun. People vested arrest when they checked out, You guys look like you're doing good. So I got to ask you the question that when you started, what was the original mission? Where is it now? I mean this Is there any deviation? What's been the kind? Of course you know, this is very, very relevant questions. It's very interesting. Right after the acquisition, we went and looked at a pitch deck, which we presented overseas in mid 2015. Believe it or not, the mission has not changed, not changing iron. It had the same competent off. How do you make the life off a security person? A security analyst? Easy. It's all the same mission by automating more by applying AI and learning to help them further by letting them collaborate. All the aspects off case management process, collaboration, automation. It's not changed. That's actually very powerful, because if you're on the same mission, of course you're adding more and more capabilities. But we're still on the same path on going on that. So every company's got their own little nuanced. Moore's Law for Intel. What made you guys successful was that the culture of Dev ops? It sounds like you guys had a certain either it was cut in grain. I think I would say, by the way, making things easy. But you got to do it. You got to stay the course. What was that? I think that's a fundamental cultural feature. Yeah, there's one thing really stand by, and I actually tweeted about a few weeks ago, this which is every idea, is as good as good as its execution. So there's two things between really focus on which is customer focused on. We were really, really portable about customer needs to get the product needs to use the product, customer focus and execution. As we heard the customers loud and clear, every small better. And that's what we also did. You guys have this agile mindset as well, absolutely agile mindset and the development that comes with the customer focus because way kind of these micro payments customer wants this like, why do they want this? What is the end goal? Attributed learner. Move on to make a decision making line was on Web services Way debate argue align! Go Then go. And then once you said we see great success story again Startup right out of the gate 2015. Acquire a couple years later, conventions you and your team and looking forward to seeing your next Palo Alto Networks event. Or thanks for coming on. Great insight here on the cube coverage. I'm John Furrier here on the ground floor of our S e commerce on Mosconi getting all the signal extracting it from the noise here on the Cube. Thanks for watching. >>Yeah, yeah,

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

>>Live from Las Vegas. It's the cube covering UI path forward Americas 2019 brought to you by UI path. Hello. We've already welcome to Las Vegas. This is day two of the year. >>Path forward conference UI path forward three. So what UI Pat does is they named their events one two three last year we were at Miami in the year before was one. Their North American event, which was in New York city. Here is three at the Bellagio hotel in in Las Vegas. 3000 people here for this rocket ship company growing revenues, they've got over $300 million in annual recurring revenue. That's up from 25 million in 2017 so you're talking about greater than 12 X increase in annual recurring revenues over 3000 employees. Now, Daniel Dienes, the CEO just named the industries the tech industry's latest billionaire. He's now dressing like a billionaire last year. He's in a tee shirt this year. He looks more like a more like a CEO. So we're going to be interviewing him later on today, but let's get right into it. The keynotes today comprised God Kirkwood who gave some predictions and that's her. >>I'm going to go, I'm going to talk about his predictions. I'm going to make some comments on those predictions and give you some thoughts of my own. Maybe throw in a few predictions of from Dave Vellante and then Craig LeClaire from Forrester gave a keynote. He was on the QBs today. Very knowledgeable analysts, probably one of the industry's top analysts, and I'll make some comments on some of the things he said. So let me get right into it. You got Kirkwood when you do these predictions, you know I put 'em out there. Of course it is smart. He's going to do these things and make them somewhat self-serving for RPA and UI path. So I'll make some comments on that as first one. One those was, there'll be a global economic downturn. I can't remember if he actually pinned a date, but I think he said it's in paint pending. >>Let's let's say 2020 he said that's good for RPA. Why would that be good for RPA? Because if there's an economic downturn, people are gonna want to get more. For less, and they're going to want to automate. They're gonna want to spend money and get fast ROI. And RPA potentially is a way to do that. It's not necessarily good news for low wage workers. They're doing mundane tasks. But nonetheless, he made the statement that it's good for our RPA. I would say this, I think a lot of this is going to depend on 2020 and the election in the United States as to what happens. I think it's very unclear right now. You saw the democratic debates last night. It's very clear that there's a, there's a swing to the left. Elizabeth Warren is, is kind of appears to be the front runner. So I would, I would make this prediction. >>I actually think Trump was gonna win the election. You know, don't hate me for saying that all you Trump haters, but I think whatever happens, maybe, maybe doesn't win the election. Maybe he wins the election and then, and then the subsequent election goes to the Democrats. But I think there's going to be a major swing back to the left. And I think that what that's gonna do, it's gonna open up the checkbooks and put more pressure on debt and I don't think there's a real issue right now of too fast economic growth of inflation. It's obviously something that economists watch, but if interest rates start rising back to the Clinton era levels, that means big trouble for the economy. But I don't see that necessarily happening in 2020 I think 2020 we'll see some moderation. I definitely think we're seeing less tech spending expected for Q four and I think that'll spill into 2020 based on the ETR and enterprise technology research data that we see. >>But I think it's actually a healthy pullback. I kind of agree with guy on that front. I actually think it is good for RPA. I think RPA is one of those sectors that you see in the ETR surveys that is gaining share relative to other tech spending and I think that will continue in any downturn. So I expect softness. However you define downturn, I don't think it's going to be falling off the cliff or a disaster, but I definitely think spending will be more tepid. Second thing he said is RPA will become the YouTube for automations. Think of YouTube as a container. I am not going to spend a lot of time on this one. A YouTube and RPA. I think no one's a consumer, but his, his analogy was around a container for automations, just like YouTube was a container for for video. I think they have aspirations to scale like YouTube, but if you look at RPA is a right now a back office, B2B business function and I think it'll stay that way for a couple of years. >>I'll make some statements on that. Automations will move from snowflake to snowball. What does he mean by that? Well today automations are all unique. Every company, and he made this statement feels like it's automations are a snowflake there. Everyone is different and what he's predicting is that over time these automations will become, there'd be more commonality in those automations. I think that's true. I do think while there are definite business processes that are unique to companies that there are a lot of similarities. Things like the UI path marketplace will allow people to share automations and I think there will be much more commonality. I think it's critical for scale. Number four, he said students entering the workforce will force employers to use automation. He didn't give a timeframe on this, but I'll tell you one thing. At a 2020 I've got three kids in college with two kids in college, one that's recently, recently graduated, who does something. >>Most kids in college have no clue what robotic process automation is, let alone what the acronym RPA stands for. So this is going to take some time. asked a hundred college kids what RPA is and I bet you maybe one or two have heard of it, even know what it is. So that's not happening today. I think that'll take probably another two cycles of graduate's before that really hits. We heard from the college of William and Mary yesterday where Tom Clancy and the college have partnered to really push in RPA into the curriculum and I think that's great. I'm going to talk, Tom Clancy's, a expert in the area of training and education that's going to take some time to bake out. So I would put that again. Guy didn't give a timeframe, but I would, I would say that's, that's five to eight years away. Number five, we'll continue to be surprised by the intelligence of machines and the stupidity of humans. >>Well, what he meant by that was there are some things that humans do that are repetitive, that are mistakes. They make the same mistakes over and over and over again, and machines won't necessarily do that. I do think this, that the gap or the number of things, if you make a list between the number of things that humans can do versus what robots can do with a physical or software robots, that gap is closing. There's no question about it. It's, you know, short few years ago, robots couldn't even climb stairs and now they can and you're, you're seeing things like chatbots improving. There's still, you know, a lot of them are still crap frankly, but, but you're going to see a lot of money go into chatbots. And so I do think that that gap will, will close. And I think it's, it's gonna, it's gonna come down to education and creativity in terms of the impact on job loss. >>And I'll make some comments about that in a moment. The six prediction, there are seven overall, so bear with me here. Automation will be discussed in the United nations con and the context will be jobs, wages and global economics. That's already happened. It's already happening. People are concerned about the impact on productivity and, and so, you know, that's a lock. The last one was consolidation amongst RPA vendors and automation led services will accelerate. I totally agree with this. He mentioned work fusion and amp works as two companies that are gonna. We're going to where we're going to see consolidation. We've already seen it. SAP got bought Contexto so you see in the big whales come into this market in four talks a lot about RPA. Anytime there's a fast growing software segment like RPA and as a leader like UI path, would you other companies all you know on their tail automation anywhere and blue prism automation anywhere in UI path have a ton of dough. >>You're going to see the big software companies say, wait a minute, I need a piece of that pie. Because software companies generally feel like every dime that's spent on software should go to them. That's the mentality of an SAP or an Oracle or even IBM and so either, unquestionably, you're going to see some consolidation. You mentioned service providers as well. Companies like symphony. I've been making a lot of comparisons this week between what I see in the UI path ecosystem and what I saw way back in the early part of this decade in the service now ecosystem. You had a company with Fritz like cloud sharper, which nobody ever heard of. They were a service management ITSMs expert and Accenture eventually snapped them up and came in. You saw DXC or CSC at the time do the same thing. And so I think you'll see the same thing here in this ecosystem. >>This ecosystem here is happening. It's buzzing, but it's got to grow and, and you're already seeing Deloitte and cognizant and E Y and PWC. The big guys could have jump in here. I often say that SIS love to eat at the trough and they know where the money is and the money appears to be in RPA because really there's so many screwed up processes inside companies. RPA is actually can give them a quick ROI. Now let me turn to some of my thoughts on this. Let me talk about the job impact of automation the vendors would have. You believe that it's all good, that people love this and and when they bring in software robots, it makes their lives better because they're doing less money, less money, less of the mundane tasks, and they're able to focus on new, more strategic things to our customer that we've talked to here in the cube. >>And also privately. This is true, people do love your software. Robots. When we were Jean younger yesterday from security benefit. If you Civ most excited she's ever been, you know, having said that, Craig Le Claire's research shows that over the next 10 years we will see a 16% job loss of jobs will disappear, rolls will disappear, and by the way, foresters at the low end of the spectrum of that forecast. Most forecast say 30 40% of jobs are going to get disrupted. I tend to believe that Craig's number is probably a better one at the lower end of that spectrum, but that's still a huge number. You are going to see unquestionably job impact from automation. Absolutely. No question in my mind. I think you're already seeing it now. Look it. Humans have always been replaced by machines, but for the first time in history we're seeing Keith cognitive functions replacing humans and as going to have a big disruptive impact on the workforce. >>And the other piece of this I would predict we are going to see a productivity boost. I think a significant productivity boost. Let me share you some data with the Bureau of labor statistics, which you know, you may look at that, you know in question some of their methodologies, but over the longterm, I think it's a viable metric from 2007 to 2018 productivity grew at 1.3% that's an anemic rate from from 1947 to 2018 productivity grew at 2.1% so Oh seven to 18 half the longterm productivity gain, 2000 to 2007 2.7% and then from, and then what we saw in Q one of 19 3.4% uptick in productivity. Is that sustainable? I think it is. I think we're now entering a, a new phase of productivity growth and I think it's gonna be driven by things like RPA and other automation. So that is going to have an impact back to the earlier statements on job loss. >>Okay. The other thing is I want to talk about the forecast, the market. Last year at UI path two in Miami, I said that I thought that forecast was low. They had like $4 billion by 2020 and I sort of called out Craig LaClaire on that, you know, and so I said this could be 10 billion by 2020 now he clarified that today up on stage. I was including services in, in my prediction, correct. Declares follows this market much more closely than I do. So I'll defer to him on, on on that. But he put in the services number and he showed the services to license ratio of around, you know, three X or so. But he actually had this very serial number about 10 billion by 2020 so I felt, felt good about that. That kind of bat my back of napkin prediction. I used to do this stuff at IDC for a living. >>So you know, actually got a little knack for that on an analog basis. Then he showed sort of his, his forecast for the market, you know, growing at a very linear rate. Now I'll say this, I think hot markets like RPA, they generally don't grow at a, at a, at a linear steady rate. If you look at some of the emerging forecasts that I, you know, for instance, IDC had in my years there, we would always have these linear like smooth growth forecasts. You know, some of those big markets, you know, think, you know, early days of the PC, the, the, the, the internet flash storage, you know, things of that nature. They tend to, these disruptive technologies tend to grow in an curve or an S curve. So what you see is sort of this momentum building where the market is being seeded. Know Gardner has RPA now in the trough of disillusionment. >>So you're seeing some of this, okay, the little engine that could, and then what you see is this steep part of the S curve growing and then after it explodes and hits escape velocity, it's sort of stretches out into maturity. And I think that's what you're going to see with RPA. But some things have to happen before that happens. And one is specifically the RPA has to move from the back office to the front office. It has to move from only really dealing with pretty simple, mundane tasks to more complicated automations. It's got to be able to deal with unstructured data. It's gotta be able to handle on attended or rather attended bots where you're injecting humans into the equation and you're actually using machine learning and artificial intelligence to to learn and then identify other areas of automation and actually have systems of agency that can act. >>In other words, a bot will call another bot that actually can complete a transaction and so you're going to see a lot of money spent here. This is a big chasm. I think that RPA has to cross. We're going to talk to Daniel DNAs about this. He's a big ticker. He's a go big or go home guy, and so I think those things I would predict those things actually are going to happen because you're going to see so much effort and money and emphasis put into AI and for competitive advantage that I actually think that RPA can lead that and then again come back to the consolidation. I think you will see some consolidation. I think you're seeing UI path. Try to take the lead automation anywhere is kind of pressing the lead if you will. Both companies have raised a couple of billion dollars if you combine them and I think the way this market shakes out is any and you're going to have some of the big whales come in like SAP. >>I think the way this happened is you're going to see one or two specialists emerge. I think UI path is on its way there automation anywhere as well and and the number one player is going to make a lot of money. The number two players going to do two. OK the number three player is going to struggle and everybody else is kinda be either break even or they're going to bundle it in like SAP as part of their overall portfolio and compete on that basis. So I would predict that UI path will maintain its lead. I think its got the culture to do that. I think automation anywhere also could company is going to keep pressing that lead and those should are two companies you know that you need to watch me. Interesting to see. Blue prism, I think they are somewhat under capitalized. They went to the public markets. >>The spending data actually shows all three of these companies as well as some of the legacy companies like Pega systems actually gaining could have more share relative to other initiatives. So I think even some of these legacy companies are going to continue to chug along and actually do pretty well in the business. But, but the real darling, you know, I think it's going to be UI path. All the bankers are hovering around earlier on this week trying to get their business. They know there's an IPO coming at some point. Again, we'll ask Daniel Dienes about that today. You have it. That's my intro. Some of my predictions. Some a guy Kirkwood's predictions. Wall-to-wall coverage on the cube today, day two at UI path forward three from Las Vegas. We'll be right back right after this short break.

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

(upbeat music) >> Announcer: Live from Las Vegas, it's theCUBE! Covering UIPath FORWARD America's 2019. Brought to you by UIPath. >> Welcome back, everyone, to theCUBE's live coverage of UIPath FORWARD, here in Sin City, Las Vegas Nevada. I'm your host, Rebecca Knight, co-hosting alongside Dave Velante. We have two guests for this segment. We have Kurt Carlson, Associate Dean for faculty and academic affairs of the Mason School of Business at the college of William and Mary. Thanks for coming on the show. >> Thanks you for having me. >> Rebecca: And we have Tom Clancy, the SVP of learning at UIPath, thank you so much. >> Great to be here. >> You're a Cube alum, so thank you for coming back. >> I've been here a few times. >> A Cube veteran, I should say. >> I think 10 years or so >> So we're talking today about a robot for every student, this was just announced in August, William and Mary is the first university in the US to provide automation software to every undergraduate student, thanks to a four million dollar investment from UIPath. Tell us a little bit about this program, Kurt, how it works and what you're trying to do here. >> Yeah, so first of all, to Tom and the people at UIPath for making this happen. This is a bold and incredible initiative, one that, frankly, when we had it initially, we thought that maybe we could get a robot for every student, we weren't sure that other people would be willing to go along with that, but UIPath was, they see the vision, and so it was really a meeting of the minds on a common purpose. The idea was pretty simple, this technology is transforming the world in a way that students, we think it's going to transform the way that students actually are students. But it's certainly transforming the world that our students are going into. And so, we want to give them exposure to it. We wanted to try and be the first business school on the planet that actually prepares students not just for the way RPA's being used today, but the way that it's going to be used when AI starts to take hold, when it becomes the gateway to AI three, four, five years down the road. So, we talked to UIPath, they thought it was a really good idea, we went all in on it. Yeah, all of our starting juniors in the business school have robots right now, they've all been trained through the academy live session putting together a course, it's very exciting. >> So, Tom, you've always been an innovator when it comes to learning, here's my question. How come we didn't learn this school stuff when we were in college? We learned Fortran. >> I don't know, I only learned BASIC, so I can't speak to that. >> So you know last year we talked about how you're scaling, learning some of the open, sort of philosophy that you have. So, give us the update on how you're pushing learning FORWARD, and why the College of William and Mary. >> Okay, so if you buy into a bot for every worker, or a bot for every desktop, that's a lot of bots, that's a lot of desktops, right? There's studies out there from the research companies that say that there's somewhere a hundred and 200 million people that need to be educated on RPA, RPA/AI. So if you buy into that, which we do, then traditional learning isn't going to do it. We're going to miss the boat. So we have a multi-pronged approach. The first thing is to democratize RPA learning. Two and a half years ago we made, we created RPA Academy, UIPath academy, and 100% free. After two and a half years, we have 451,000 people go through the academy courses, that's huge. But we think there's a lot more. Over the next next three years we think we'll train at least two million people. But the challenge still is, if we train five million people, there's still a hundred million that need to know about it. So, the second biggest thing we're doing is, we went out, last year at this event, we announced our academic alliance program. We had one university, now we're approaching 400 universities. But what we're doing with William and Mary is a lot more than just providing a course, and I'll let Kurt talk to that, but there is so much more that we could be doing to educate our students, our youth, upscaling, rescaling the existing workforce. When you break down that hundred million people, they come from a lot of different backgrounds, and we're trying to touch as many people as we can. >> You guys are really out ahead of the curve. Oftentimes, I mean, you saw this a little bit with data science, saw some colleges leaning in. So what lead you guys to the decision to actually invest and prioritize RPA? >> Yeah, I think what we're trying to accomplish requires incredibly smart students. It requires students that can sit at the interface between what we would think of today as sort of an RPA developer and a decision maker who would be stroking the check or signing the contract. There's got to be somebody that sits in that space that understands enough about how you would actually execute this implementation. What's the right buildout of that, how we're going to build a portfolio of bots, how we're going to prioritize the different processes that we might automate, How we're going to balance some processes that might have a nice ROI but be harder for the individual who's process is being automated to absorb against processes that the individual would love to have automated, but might not have as great of an ROI. How do you balance that whole set of things? So what we've done is worked with UIPath to bring together the ideas of automation with the ideas of being a strategic thinker in process automation, and we're designing a course in collaboration to help train our students to hit the ground running. >> Rebecca, it's really visionary, isn't it? I mean it's not just about using the tooling, it's about how to apply the tooling to create competitive advantage or change lives. >> I used to cover business education for the Financial Times, so I completely agree that this really is a game changer for the students to have this kind of access to technology and ability to explore this leading edge of software robotics and really be, and graduate from college. This isn't even graduate school, they're graduating from college already having these skills. So tell me, Kurt, what are they doing? What is the course, what does it look like, how are they using this in the classroom? >> The course is called a one credit. It's 14 hours but it actually turns into about 42 when you add this stuff that's going on outside of class. They're learning about these large conceptual issues around how do you prioritize which processes, what's the process you should go through to make sure that you measure in advance of implementation so that you can do an audit on the backend to have proof points on the effectiveness, so you got to measure in advance, creating a portfolio of perspective processes and then scoring them, how do you do that, so they're learning all that sort of conceptual straight business slash strategy implementation stuff, so that's on the first half, and to keep them engaged with this software, we're giving them small skills, we're calling them skillets. Small skills in every one of those sessions that add up to having a fully automated and programmed robot. Then they're going to go into a series of days where every one of those days they're going to learn a big skill. And the big skills are ones that are going to be useful for the students in their lives as people, useful in lives as students, and useful in their lives as entrepreneurs using RPA to create new ventures, or in the organizations they go to. We've worked with UIPath and with our alums who've implement this, folks at EY, Booz. In fact, we went up to DC, we had a three hour meeting with these folks. So what are the skills students need to learn, and they told us, and so we build these three big classes, each around each one of those skills so that our students are going to come out with the ability to be business translators, not necessarily the hardcore programmers. We're not going to prevent them from doing that, but to be these business translators that sit between the programming and the decision makers. >> That's huge because, you know, like, my son's a senior in college. He and his friends, they all either want to work for Amazon, Google, an investment bank, or one of the big SIs, right? So this is a perfect role for a consultant to go in and advise. Tom, I wanted to ask you, and you and I have known each other for a long time, but one of the reasons I think you were successful at your previous company is because you weren't just focused on a narrow vendor, how to make metrics work, for instance. I presume you're taking the same philosophy here. It transcends UIPath and is really more about, you know, the category if you will, the potential. Can you talk about that? >> So we listen to our customers and now we listen to the universities too, and they're going to help guide us to where we need to go. Most companies in tech, you work with marketing, and you work with engineering, and you build product courses. And you also try to sell those courses, because it's a really good PNL when you sell training. We don't think that's right for the industry, for UIPath, or for our customers, or our partners. So when we democratize learning, everything else falls into place. So, as we go forward, we have a bunch of ideas. You know, as we get more into AI, you'll see more AI type courses. We'll team with 400 universities now, by end of next year, we'll probably have a thousand universities signed up. And so, there's a lot of subject matter expertise, and if they come to us with ideas, you mentioned a 14 hour course, we have a four hour course, and we also have a 60 hour course. So we want to be as flexible as possible, because different universities want to apply it in different ways. So we also heard about Lean Six Sigma. I mean, sorry, Lean RPA, so we might build a course on Lean RPA, because that's really important. Solution architect is one of the biggest gaps in the industry right now so, so we look to where these gaps are, we listen to everybody, and then we just execute. >> Well, it's interesting you said Six Sigma, we have Jean Younger coming on, she's a Six Sigma expert. I don't know if she's a black belt, but she's pretty sure. She talks about how to apply RPA to make business processes in Six Sigma, but you would never spend the time and money, I mean, if it's an airplane engine, for sure, but now, so that's kind of transformative. Kurt, I'm curious as to how you, as a college, market this. You know, you're very competitive industry, if you will. So how do you see this attracting students and separating you guys from the pack? >> Well, it's a two separate things. How do we actively try to take advantage of this, and what effects is it having already? Enrollments to the business school, well. Students at William and Mary get admitted to William and Mary, and they're fantastic, amazingly good undergraduate students. The best students at William and Mary come to the Raymond A. Mason school of business. If you take our undergraduate GPA of students in the business school, they're top five in the country. So what we've seen since we've announced this is that our applications to the business school are up. I don't know that it's a one to one correlation. >> Tom: I think it is. >> I believe it's a strong predictor, right? And part because it's such an easy sell. And so, when we talk to those alums and friends in DC and said, tell us why this is, why our students should do this, they said, well, if for no other reason, we are hiring students that have these skills into data science lines in the mid 90s. When I said that to my students, they fell out of their chairs. So there's incredible opportunity here for them, that's the easy way to market it internally, it aligns with things that are happening at William and Mary, trying to be innovative, nimble, and entrepreneurial. We've been talking about being innovative, nimble, and entrepreneurial for longer than we've been doing it, we believe we're getting there, we believe this is the type of activity that would fit for that. As far as promoting it, we're telling everybody that will listen that this is interesting, and people are listening. You know, the standard sort of marketing strategy that goes around, and we are coordinating with UIPath on that. But internally, this sells actually pretty easy. This is something people are looking for, we're going to make it ready for the world the way that it's going to be now and in the future. >> Well, I imagine the big consultants are hovering as well. You know, you mentioned DC, Booz Allen, Hughes and DC, and Excensior, EY, Deloitte, PWC, IBM itself. I mean it's just, they all want the best and the brightest, and now you're going to have this skill set that is a sweet spot for their businesses. >> Kurt: That's the plan. >> I'm just thinking back to remembering who these people are, these are 19 and 20 year olds. They've never experienced the dreariness of work and the drudge tasks that we all know well. So, what are you, in terms of this whole business translator idea, that they're going to be the be people that sit in the middle and can sort of be these people who can speak both languages. What kind of skills are you trying to impart to them, because it is a whole different skill set. >> Our vision is that in two or three years, the nodes and the processes that are currently... That currently make implementing RPA complex and require significant programmer skills, these places where, right now, there's a human making a relatively mundane decision, but it's sill a model. There's a decision node there. We think AI is going to take over that. The simple, AI's going to simply put models into those decision nodes. We also think a lot of the programming that takes place, you're seeing it now with studio X, a lot of the programming is going to go away. And what that's going to do is it's going to elevate the business process from the mundane to the more human intelligent, what would currently be considered human intelligence process. When we get into that space, people skills are going to be really important, prioritizing is going to be really important, identifying organizations that are ripe for this, at this moment in time, which processes to automate. Those are the kind of skills we're trying to get students to develop, and what we're selling it partly as, this is going to make you ready of the world the way we think it's going to be, a bit of a guess. But we're also saying if you don't want to automate mundane processes, then come with us on a different magic carpet ride. And that magic carpet ride is, imagine all the processes that don't exist right now because nobody would ever conceive of them because they couldn't possibly be sustained, or they would be too mundane. Now think about those processes through a business lens, so take a business student and think about all the potential when you look at it that way. So this course that we're building has that, everything in the course is wrapped in that, and so, at the end of the course, they're going to be doing a project, and the project is to bring a new process to the world that doesn't currently exist. Don't program it, don't worry about whether or not you have a team that could actually execute it. Just conceive of a process that doesn't currently exist and let's imagine, with the potential of RPA, how we would make that happen. That's going to be, we think we're going to be able to bring a lot of students along through that innovative lens even though they are 19 and 20, because 19 and 20 year olds love innovation, while they've never submitted a procurement report. >> Exactly! >> A innovation presentation. >> We'll need to do a Cube follow up with that. >> What Kurt just said, is the reason why, Tom, I think this market is being way undercounted. I think it's hard for the IDCs and the forces, because they look back they say how big was it last year, how fast are these companies growing, but, to your point, there's so much unknown processes that could be attacked. The TAM on this could be enormous. >> We agree. >> Yeah, I know you do, but I think that it's a point worth mentioning because it touches so many different parts of every organization that I think people perhaps don't realize the impact that it could have. >> You know, when listening to you, Kurt, when you look at these young kids, at least compared to me, all the coding and setting up a robot, that's the easy part, they'll pick that up right away. It's really the thought process that goes into identifying new opportunities, and that's, I think, you're challenging them to do that. But learning how to do robots, I think, is going to be pretty easy for this new digital generation. >> Piece of cake. Tom and Kurt, thank you so much for coming on theCUBE with a really fascinating conversation. >> Thank you. >> Thanks, you guys >> I'm Rebecca Knight, for Dave Velante, stay tuned for more of theCUBEs live coverage of UIPath FORWARD. (upbeat music)