(upbeat music) >> Okay, welcome back everyone. I'm John Furrier here in theCUBE, in Palo Alto for "CUBE Conversation" with Chris Jones, Director of Product Management at Platform9. I've got a series of questions, had a great conversation earlier. Chris, I have a couple questions for you, what do you think? >> Let's do it, John. >> Okay, how does Platform9 Solution, you- can it be used on any infrastructure anywhere, cloud, edge, on-premise? >> It can, that's the beauty of our control plane, right? It was born in the cloud, and we primarily deliver that SaaS, which allows it to work in your data center, on bare metal, on VMs, or with public cloud infrastructure. We now give you the ability to take that control plane, install it in your data center, and then use it with anything, or even in air gap. And that includes capabilities with bare metal orchestration as well. >> Second question. How does Platform9 ensure maximum uptime, and proactive issue resolution? >> Oh, that's a good question. So if you come to Platform nine we're going to talk about always on assurance. What is driving that is a system of three components around self-healing, monitoring, and proactive assistance. So our software will heal broken things on nodes, right? If something stops running that should be running, it will attempt to restart that. We also have monitoring that's deployed with everything. So you build a cluster in AWS, well, we put open source monitoring agents, that are actually Prometheus, on every single node. That means it's resilient, right? So if you lose a node, you don't lose monitoring. But that data importantly comes back to our control plane, and that's the control plane that you can put in your data center as well. That data is what alerts us, and you as a user, anytime of the day that something's going wrong. Let's say etcd latency, good example, etcd is going slow. We'll find out, we might not be able to take restorative action immediately, but we're definitely going to reach out and say,, "You have a problem, let's get ahead of this and let's prevent that from becoming a bigger problem." And that's what we're delivering. When we say always on assurance, we're talking about self-healing, we're talking about remote monitoring, we're talking about being proactive with our customers, not waiting for the phone call or the support desk ticket saying, "Oh we think something's not working." Or worse, the customer has an outage. >> Awesome. Thanks for sharing. Can you explain the process for implementing Platform9 within a company's existing infrastructure. >> Are we doing air gap, or on-prem or SaaS approached? SaaS approach I think is by far the easiest, right? We can build a dedicated Platform9 control plane instance in a manner of minutes, for any customer. So when we do a proof of concept or onboarding, we just literally put in an email address, put in the name you want for your fully qualified domain name, and your instance is up. From that point onwards, the user can just log in, and using our CLI, talk to any number of, say, virtual machines, or physical servers in their environment for, you know, doing this in a data center or colo, and say, "I want these to be my Kubernetes control plane nodes. Here's the five of them. Here's the VIP for the load balancing, the API server and here are all of my compute nodes." And that CLI will work with the SaaS control plane, and go and build the cluster. That's as simple as it, CentOS, Ubuntu, just plain old operating system. Our software takes care of all the prerequisites, installing all the pieces, putting down MetalLB, CoreDNS, Metrics Server, Kubernetes dashboard, etcd backups. You built some servers. That's essentially what you've done, and the rest is being handled by Platform9. It's as simple as that. >> Great, thanks for that. What are the two traditional paths for companies considering the cloud native journey? The two paths. >> The traditional paths. I think that's your engineering team running so fast that before you even realize that you've got, you know, 10 EKS clusters. Or, hey, we can do this. You know, I've got the I can build it mentality. Let's go DIY completely open source Kubernetes on our infrastructure, and we're going to piecemeal build it all up together. They're, I think the pathways that people traditionally look at this journey, as opposed to having that third alternative saying can I just consume it on my infrastructure, be it cloud or on-premise or at the edge. >> Third is the new way, you guys do that. >> That's been our focus since the company was, you know, brought together back in the open OpenStack days. >> Awesome, what's the makeup of your customer base? Is there a certain pattern to the size or environments that you guys work with? Is there a pattern or consistency to your customer base? >> It's a spread, right? We've got large enterprises like Juniper, and we go all the way down to people with 20, 30, 50 nodes in total. We've got people in banking and finance, we've got things all the way through to telecommunications and storage infrastructure. >> What's your favorite feature of Platform9? >> My favorite feature? You know, if I ask, should I say this as a pre-sales engineer, let me show you a favorite thing. My immediate response is, I should never do this. (John laughs) To me it's just being able to define my cluster and say, go. And in five minutes I have that environment, I can see everything that's running, right? It's all unified, it's one spot, right? I'm a cluster admin. I said I wanted three control plane, 25 workers. Here's the infrastructure, it creates it, and once it's built, I can see everything that's running, right? All the applications that are there. One UI, I don't have to go click around. I'm not trying to solve things or download things. It's the fact that it's unified and just delivered in one hit. >> What is the one thing that people should know about Platform9 that they might not know about it? >> I think it's that we help developers and engineers as much as we can help our operations teams. I think, for a long time we've sort of targeted that user and said, hey, we, we really help you. It's like, but why are they doing this? Why are they building any infrastructure or any cloud platform? Well, it's to run applications and services, to help their customers, but how do they get there? There's people building and writing those things, and we're helping them, right? For the last two years, we've been really focused on making it simple, and I think that's an important thing to know. >> Chris, thanks so much, appreciate it. >> Yeah, thank you, John. >> Okay, that's theCUBE Q&A session here with Platform9. I'm John Furrier, thanks for watching. (light music)

(upbeat music) >> Hi everyone. Welcome back to this Cube conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE." Got a great conversation around Cloud Native, Cloud Native Journey, how enterprises are looking at Cloud Native and putting it all together. And it comes down to operations, developer productivity, and security. It's the hottest topic in technology. We got Chris Jones here in the studio, director of Product Management for Platform9. Chris, thanks for coming in. >> Hey, thanks. >> So when we always chat about, when we're at KubeCon. KubeConEU is coming up and in a few, in a few months, the number one conversation is developer productivity. And the developers are driving all the standards. It's interesting to see how they just throw everything out there and whatever gets adopted ends up becoming the standard, not the old school way of kind of getting stuff done. So that's cool. Security Kubernetes and Containers are all kind of now that next level. So you're starting to see the early adopters moving to the mainstream. Enterprises, a variety of different approaches. You guys are at the center of this. We've had a couple conversations with your CEO and your tech team over there. What are you seeing? You're building the products. What's the core product focus right now for Platform9? What are you guys aiming for? >> The core is that blend of enabling your infrastructure and PlatformOps or DevOps teams to be able to go fast and run in a stable environment, but at the same time enable developers. We don't want people going back to what I've been calling Shadow IT 2.0. It's, hey, I've been told to do something. I kicked off this Container initiative. I need to run my software somewhere. I'm just going to go figure it out. We want to keep those people productive. At the same time we want to enable velocity for our operations teams, be it PlatformOps or DevOps. >> Take us through in your mind and how you see the industry rolling out this Cloud Native journey. Where do you see customers out there? Because DevOps have been around, DevSecOps is rocking, you're seeing AI, hot trend now. Developers are still in charge. Is there a change to the infrastructure of how developers get their coding done and the infrastructure, setting up the DevOps is key, but when you add the Cloud Native journey for an enterprise, what changes? What is the, what is the, I guess what is the Cloud Native journey for an enterprise these days? >> The Cloud Native journey or the change? When- >> Let's start with the, let's start with what they want to do. What's the goal and then how does that happen? >> I think the goal is that promise land. Increased resiliency, better scalability, and overall reduced costs. I've gone from physical to virtual that gave me a higher level of density, packing of resources. I'm moving to Containers. I'm removing that OS layer again. I'm getting a better density again, but all of a sudden I'm running Kubernetes. What does that, what does that fundamentally do to my operations? Does it magically give me scalability and resiliency? Or do I need to change what I'm running and how it's running so it fits that infrastructure? And that's the reality, is you can't just take a Container and drop it into Kubernetes and say, hey, I'm now Cloud Native. I've got reduced cost, or I've got better resiliency. There's things that your engineering teams need to do to make sure that application is a Cloud Native. And then there's what I think is one of the largest shifts of virtual machines to containers. When I was in the world of application performance monitoring, we would see customers saying, well, my engineering team have this Java app, and they said it needs a VM with 12 gig of RAM and eight cores, and that's what we gave it. But it's running slow. I'm working with the application team and you can see it's running slow. And they're like, well, it's got all of its resources. One of those nice features of virtualization is over provisioning. So the infrastructure team would say, well, we gave it, we gave it all a RAM it needed. And what's wrong with that being over provisioned? It's like, well, Java expects that RAM to be there. Now all of a sudden, when you move to the world of containers, what we've got is that's not a set resource limit, really is like it used to be in a VM, right? When you set it for a container, your application teams really need to be paying attention to your resource limits and constraints within the world of Kubernetes. So instead of just being able to say, hey, I'm throwing over the fence and now it's just going to run on a VM, and that VMs got everything it needs. It's now really running on more, much more of a shared infrastructure where limits and constraints are going to impact the neighbors. They are going to impact who's making that decision around resourcing. Because that Kubernetes concept of over provisioning and the virtualization concept of over provisioning are not the same. So when I look at this problem, it's like, well, what changed? Well, I'll do my scale tests as an application developer and tester, and I'd see what resources it needs. I asked for that in the VM, that sets the high watermark, job's done. Well, Kubernetes, it's no longer a VM, it's a Kubernetes manifest. And well, who owns that? Who's writing it? Who's setting those limits? To me, that should be the application team. But then when it goes into operations world, they're like, well, that's now us. Can we change those? So it's that amalgamation of the two that is saying, I'm a developer. I used to pay attention, but now I need to pay attention. And an infrastructure person saying, I used to just give 'em what they wanted, but now I really need to know what they've wanted, because it's going to potentially have a catastrophic impact on what I'm running. >> So what's the impact for the developer? Because, infrastructure's code is what everybody wants. The developer just wants to get the code going and they got to pay attention to all these things, or don't they? Is that where you guys come in? How do you guys see the problem? Actually scope the problem that you guys solve? 'Cause I think you're getting at I think the core issue here, which is, I've got Kubernetes, I've got containers, I've got developer productivity that I want to focus on. What's the problem that you guys solve? >> Platform operation teams that are adopting Cloud Native in their environment, they've got that steep learning curve of Kubernetes plus this fundamental change of how an app runs. What we're doing is taking away the burden of needing to operate and run Kubernetes and giving them the choice of the flexibility of infrastructure and location. Be that an air gap environment like a, let's say a telco provider that needs to run a containerized network function and containerized workloads for 5G. That's one thing that we can deploy and achieve in a completely inaccessible environment all the way through to Platform9 running traditionally as SaaS, as we were born, that's remotely managing and controlling your Kubernetes environments on-premise AWS. That hybrid cloud experience that could be also Bare Metal, but it's our platform running your environments with our support there, 24 by seven, that's proactively reaching out. So it's removing a lot of that burden and the complications that come along with operating the environment and standing it up, which means all of a sudden your DevOps and platform operations teams can go and work with your engineers and application developers and say, hey, let's get, let's focus on the stuff that, that we need to be focused on, which is running our business and providing a service to our customers. Not figuring out how to upgrade a Kubernetes cluster, add new nodes, and configure all of the low level. >> I mean there are, that's operations that just needs to work. And sounds like as they get into the Cloud Native kind of ops, there's a lot of stuff that kind of goes wrong. Or you go, oops, what do we buy into? Because the CIOs, let's go, let's go Cloud Native. We want to, we got to get set up for the future. We're going to be Cloud Native, not just lift and shift and we're going to actually build it out right. Okay, that sounds good. And when we have to actually get done. >> Chris: Yeah. >> You got to spin things up and stand up the infrastructure. What specifically use case do you guys see that emerges for Platform9 when people call you up and you go talk to customers and prospects? What's the one thing or use case or cases that you guys see that you guys solve the best? >> So I think one of the, one of the, I guess new use cases that are coming up now, everyone's talking about economic pressures. I think the, the tap blows open, just get it done. CIO is saying let's modernize, let's use the cloud. Now all of a sudden they're recognizing, well wait, we're spending a lot of money now. We've opened that tap all the way, what do we do? So now they're looking at ways to control that spend. So we're seeing that as a big emerging trend. What we're also sort of seeing is people looking at their data centers and saying, well, I've got this huge legacy environment that's running a hypervisor. It's running VMs. Can we still actually do what we need to do? Can we modernize? Can we start this Cloud Native journey without leaving our data centers, our co-locations? Or if I do want to reduce costs, is that that thing that says maybe I'm repatriating or doing a reverse migration? Do I have to go back to my data center or are there other alternatives? And we're seeing that trend a lot. And our roadmap and what we have in the product today was specifically built to handle those, those occurrences. So we brought in KubeVirt in terms of virtualization. We have a long legacy doing OpenStack and private clouds. And we've worked with a lot of those users and customers that we have and asked the questions, what's important? And today, when we look at the world of Cloud Native, you can run virtualization within Kubernetes. So you can, instead of running two separate platforms, you can have one. So all of a sudden, if you're looking to modernize, you can start on that new infrastructure stack that can run anywhere, Kubernetes, and you can start bringing VMs over there as you are containerizing at the same time. So now you can keep your application operations in one environment. And this also helps if you're trying to reduce costs. If you really are saying, we put that Dev environment in AWS, we've got a huge amount of velocity out of it now, can we do that elsewhere? Is there a co-location we can go to? Is there a provider that we can go to where we can run that infrastructure or run the Kubernetes, but not have to run the infrastructure? >> It's going to be interesting too, when you see the Edge come online, you start, we've got Mobile World Congress coming up, KubeCon events we're going to be at, the conversation is not just about public cloud. And you guys obviously solve a lot of do-it-yourself implementation hassles that emerge when people try to kind of stand up their own environment. And we hear from developers consistency between code, managing new updates, making sure everything is all solid so they can go fast. That's the goal. And that, and then people can get standardized on that. But as you get public cloud and do it yourself, kind of brings up like, okay, there's some gaps there as the architecture changes to be more distributed computing, Edge, on-premises cloud, it's cloud operations. So that's cool for DevOps and Cloud Native. How do you guys differentiate from say, some the public cloud opportunities and the folks who are doing it themselves? How do you guys fit in that world and what's the pitch or what's the story? >> The fit that we look at is that third alternative. Let's get your team focused on what's high value to your business and let us deliver that public cloud experience on your infrastructure or in the public cloud, which gives you that ability to still be flexible if you want to make choices to run consistently for your developers in two different locations. So as I touched on earlier, instead of saying go figure out Kubernetes, how do you upgrade a hundred worker nodes in place upgrade. We've solved that problem. That's what we do every single day of the week. Don't go and try to figure out how to upgrade a cluster and then upgrade all of the, what I call Kubernetes friends, your core DNSs, your metrics server, your Kubernetes dashboard. These are all things that we package, we test, we version. So when you click upgrade, we've already handled that entire process. So it's saying don't have your team focused on that lower level piece of work. Get them focused on what is important, which is your business services. >> Yeah, the infrastructure and getting that stood up. I mean, I think the thing that's interesting, if you look at the market right now, you mentioned cost savings and recovery, obviously kind of a recession. I mean, people are tightening their belts for sure. I don't think the digital transformation and Cloud Native spend is going to plummet. It's going to probably be on hold and be squeezed a little bit. But to your point, people are refactoring looking at how to get the best out of what they got. It's not just open the tap of spend the cash like it used to be. Yeah, a couple months, even a couple years ago. So okay, I get that. But then you look at the what's coming, AI. You're seeing all the new data infrastructure that's coming. The containers, Kubernetes stuff, got to get stood up pretty quickly and it's got to be reliable. So to your point, the teams need to get done with this and move on to the next thing. >> Chris: Yeah, yeah, yeah. >> 'Cause there's more coming. I mean, there's a lot coming for the apps that are building in Data Native, AI-Native, Cloud Native. So it seems that this Kubernetes thing needs to get solved. Is that kind of what you guys are focused on right now? >> So, I mean to use a customer, we have a customer that's in AI/ML and they run their platform at customer sites and that's hardware bound. You can't run AI machine learning on anything anywhere. Well, with Platform9 they can. So we're enabling them to deliver services into their customers that's running their AI/ML platform in their customer's data centers anywhere in the world on hardware that is purpose-built for running that workload. They're not Kubernetes experts. That's what we are. We're bringing them that ability to focus on what's important and just delivering their business services whilst they're enabling our team. And our 24 by seven proactive management are always on assurance to keep that up and running for them. So when something goes bump at the night at 2:00am, our guys get woken up. They're the ones that are reaching out to the customer saying, your environments have a problem, we're taking these actions to fix it. Obviously sometimes, especially if it is running on Bare Metal, there's things you can't do remotely. So you might need someone to go and do that. But even when that happens, you're not by yourself. You're not sitting there like I did when I worked for a bank in one of my first jobs, three o'clock in the morning saying, wow, our end of day processing is stuck. Who else am I waking up? Right? >> Exactly, yeah. Got to get that cash going. But this is a great use case. I want to get to the customer. What do some of the successful customers say to you for the folks watching that aren't yet a customer of Platform9, what are some of the accolades and comments or anecdotes that you guys hear from customers that you have? >> It just works, which I think is probably one of the best ones you can get. Customers coming back and being able to show to their business that they've delivered growth, like business growth and productivity growth and keeping their organization size the same. So we started on our containerization journey. We went to Kubernetes. We've deployed all these new workloads and our operations team is still six people. We're doing way more with growth less, and I think that's also talking to the strength that we're bringing, 'cause we're, we're augmenting that team. They're spending less time on the really low level stuff and automating a lot of the growth activity that's involved. So when it comes to being able to grow their business, they can just focus on that, not- >> Well you guys do the heavy lifting, keep on top of the Kubernetes, make sure that all the versions are all done. Everything's stable and consistent so they can go on and do the build out and provide their services. That seems to be what you guys are best at. >> Correct, correct. >> And so what's on the roadmap? You have the product, direct product management, you get the keys to the kingdom. What is, what is the focus? What's your focus right now? Obviously Kubernetes is growing up, Containers. We've been hearing a lot at the last KubeCon about the security containers is getting better. You've seen verification, a lot more standards around some things. What are you focused on right now for at a product over there? >> Edge is a really big focus for us. And I think in Edge you can look at it in two ways. The mantra that I drive is Edge must be remote. If you can't do something remotely at the Edge, you are using a human being, that's not Edge. Our Edge management capabilities and being in the market for over two years are a hundred percent remote. You want to stand up a store, you just ship the server in there, it gets racked, the rest of it's remote. Imagine a store manager in, I don't know, KFC, just plugging in the server, putting in the ethernet cable, pressing the power button. The rest of all that provisioning for that Cloud Native stack, Kubernetes, KubeVirt for virtualization is done remotely. So we're continuing to focus on that. The next piece that is related to that is allowing people to run Platform9 SaaS in their data centers. So we do ag app today and we've had a really strong focus on telecommunications and the containerized network functions that come along with that. So this next piece is saying, we're bringing what we run as SaaS into your data center, so then you can run it. 'Cause there are many people out there that are saying, we want these capabilities and we want everything that the Platform9 control plane brings and simplifies. But unfortunately, regulatory compliance reasons means that we can't leverage SaaS. So they might be using a cloud, but they're saying that's still our infrastructure. We're still closed that network down, or they're still on-prem. So they're two big priorities for us this year. And that on-premise experiences is paramount, even to the point that we will be delivering a way that when you run an on-premise, you can still say, wait a second, well I can send outbound alerts to Platform9. So their support team can still be proactively helping me as much as they could, even though I'm running Platform9s control plane. So it's sort of giving that blend of two experiences. They're big, they're big priorities. And the third pillar is all around virtualization. It's saying if you have economic pressures, then I think it's important to look at what you're spending today and realistically say, can that be reduced? And I think hypervisors and virtualization is something that should be looked at, because if you can actually reduce that spend, you can bring in some modernization at the same time. Let's take some of those nos that exist that are two years into their five year hardware life cycle. Let's turn that into a Cloud Native environment, which is enabling your modernization in place. It's giving your engineers and application developers the new toys, the new experiences, and then you can start running some of those virtualized workloads with KubeVirt, there. So you're reducing cost and you're modernizing at the same time with your existing infrastructure. >> You know Chris, the topic of this content series that we're doing with you guys is finding the right path, trusting the right path to Cloud Native. What does that mean? I mean, if you had to kind of summarize that phrase, trusting the right path to Cloud Native, what does that mean? It mean in terms of architecture, is it deployment? Is it operations? What's the underlying main theme of that quote? What's the, what's? How would you talk to a customer and say, what does that mean if someone said, "Hey, what does that right path mean?" >> I think the right path means focusing on what you should be focusing on. I know I've said it a hundred times, but if your entire operations team is trying to figure out the nuts and bolts of Kubernetes and getting three months into a journey and discovering, ah, I need Metrics Server to make something function. I want to use Horizontal Pod Autoscaler or Vertical Pod Autoscaler and I need this other thing, now I need to manage that. That's not the right path. That's literally learning what other people have been learning for the last five, seven years that have been focused on Kubernetes solely. So the why- >> There's been a lot of grind. People have been grinding it out. I mean, that's what you're talking about here. They've been standing up the, when Kubernetes started, it was all the promise. >> Chris: Yep. >> And essentially manually kind of getting in in the weeds and configuring it. Now it's matured up. They want stability. >> Chris: Yeah. >> Not everyone can get down and dirty with Kubernetes. It's not something that people want to generally do unless you're totally into it, right? Like I mean, I mean ops teams, I mean, yeah. You know what I mean? It's not like it's heavy lifting. Yeah, it's important. Just got to get it going. >> Yeah, I mean if you're deploying with Platform9, your Ops teams can tinker to their hearts content. We're completely compliant upstream Kubernetes. You can go and change an API server flag, let's go and mess with the scheduler, because we want to. You can still do that, but don't, don't have your team investing in all this time to figure it out. It's been figured out. >> John: Got it. >> Get them focused on enabling velocity for your business. >> So it's not build, but run. >> Chris: Correct? >> Or run Kubernetes, not necessarily figure out how to kind of get it all, consume it out. >> You know we've talked to a lot of customers out there that are saying, "I want to be able to deliver a service to my users." Our response is, "Cool, let us run it. You consume it, therefore deliver it." And we're solving that in one hit versus figuring out how to first run it, then operate it, then turn that into a consumable service. >> So the alternative Platform9 is what? They got to do it themselves or use the Cloud or what's the, what's the alternative for the customer for not using Platform9? Hiring more people to kind of work on it? What's the? >> People, building that kind of PaaS experience? Something that I've been very passionate about for the past year is looking at that world of sort of GitOps and what that means. And if you go out there and you sort of start asking the question what's happening? Just generally with Kubernetes as well and GitOps in that scope, then you'll hear some people saying, well, I'm making it PaaS, because Kubernetes is too complicated for my developers and we need to give them something. There's some great material out there from the likes of Intuit and Adobe where for two big contributors to Argo and the Argo projects, they almost have, well they do have, different experiences. One is saying, we went down the PaaS route and it failed. The other one is saying, well we've built a really stable PaaS and it's working. What are they trying to do? They're trying to deliver an outcome to make it easy to use and consume Kubernetes. So you could go out there and say, hey, I'm going to build a Kubernetes cluster. Sounds like Argo CD is a great way to expose that to my developers so they can use Kubernetes without having to use Kubernetes and start automating things. That is an approach, but you're going to be going completely open source and you're going to have to bring in all the individual components, or you could just lay that, lay it down, and consume it as a service and not have to- >> And mentioned to it. They were the ones who kind of brought that into the open. >> They did. Inuit is the primary contributor to the Argo set of products. >> How has that been received in the market? I mean, they had the event at the Computer History Museum last fall. What's the momentum there? What's the big takeaway from that project? >> Growth. To me, growth. I mean go and track the stars on that one. It's just, it's growth. It's unlocking machine learning. Argo workflows can do more than just make things happen. Argo CD I think the approach they're taking is, hey let's make this simple to use, which I think can be lost. And I think credit where credit's due, they're really pushing to bring in a lot of capabilities to make it easier to work with applications and microservices on Kubernetes. It's not just that, hey, here's a GitOps tool. It can take something from a Git repo and deploy it and maybe prioritize it and help you scale your operations from that perspective. It's taking a step back and saying, well how did we get to production in the first place? And what can be done down there to help as well? I think it's growth expansion of features. They had a huge release just come out in, I think it was 2.6, that brought in things that as a product manager that I don't often look at like really deep technical things and say wow, that's powerful. But they have, they've got some great features in that release that really do solve real problems. >> And as the product, as the product person, who's the target buyer for you? Who's the customer? Who's making that? And you got decision maker, influencer, and recommender. Take us through the customer persona for you guys. >> So that Platform Ops, DevOps space, right, the people that need to be delivering Containers as a service out to their organization. But then it's also important to say, well who else are our primary users? And that's developers, engineers, right? They shouldn't have to say, oh well I have access to a Kubernetes cluster. Do I have to use kubectl or do I need to go find some other tool? No, they can just log to Platform9. It's integrated with your enterprise id. >> They're the end customer at the end of the day, they're the user. >> Yeah, yeah. They can log in. And they can see the clusters you've given them access to as a Platform Ops Administrator. >> So job well done for you guys. And your mind is the developers are moving 'em fast, coding and happy. >> Chris: Yeah, yeah. >> And and from a customer standpoint, you reduce the maintenance cost, because you keep the Ops smoother, so you got efficiency and maintenance costs kind of reduced or is that kind of the benefits? >> Yeah, yep, yeah. And at two o'clock in the morning when things go inevitably wrong, they're not there by themselves, and we're proactively working with them. >> And that's the uptime issue. >> That is the uptime issue. And Cloud doesn't solve that, right? Everyone experienced that Clouds can go down, entire regions can go offline. That's happened to all Cloud providers. And what do you do then? Kubernetes isn't your recovery plan. It's part of it, right, but it's that piece. >> You know Chris, to wrap up this interview, I will say that "theCUBE" is 12 years old now. We've been to OpenStack early days. We had you guys on when we were covering OpenStack and now Cloud has just been booming. You got AI around the corner, AI Ops, now you got all this new data infrastructure, it's just amazing Cloud growth, Cloud Native, Security Native, Cloud Native, Data Native, AI Native. It's going to be all, this is the new app environment, but there's also existing infrastructure. So going back to OpenStack, rolling our own cloud, building your own cloud, building infrastructure cloud, in a cloud way, is what the pioneers have done. I mean this is what we're at. Now we're at this scale next level, abstracted away and make it operational. It seems to be the key focus. We look at CNCF at KubeCon and what they're doing with the cloud SecurityCon, it's all about operations. >> Chris: Yep, right. >> Ops and you know, that's going to sound counterintuitive 'cause it's a developer open source environment, but you're starting to see that Ops focus in a good way. >> Chris: Yeah, yeah, yeah. >> Infrastructure as code way. >> Chris: Yep. >> What's your reaction to that? How would you summarize where we are in the industry relative to, am I getting, am I getting it right there? Is that the right view? What am I missing? What's the current state of the next level, NextGen infrastructure? >> It's a good question. When I think back to sort of late 2019, I sort of had this aha moment as I saw what really truly is delivering infrastructure as code happening at Platform9. There's an open source project Ironic, which is now also available within Kubernetes that is Metal Kubed that automates Bare Metal as code, which means you can go from an empty server, lay down your operating system, lay down Kubernetes, and you've just done everything delivered to your customer as code with a Cloud Native platform. That to me was sort of the biggest realization that I had as I was moving into this industry was, wait, it's there. This can be done. And the evolution of tooling and operations is getting to the point where that can be achieved and it's focused on by a number of different open source projects. Not just Ironic and and Metal Kubed, but that's a huge win. That is truly getting your infrastructure. >> John: That's an inflection point, really. >> Yeah. >> If you think about it, 'cause that's one of the problems. We had with the Bare Metal piece was the automation and also making it Cloud Ops, cloud operations. >> Right, yeah. I mean, one of the things that I think Ironic did really well was saying let's just treat that piece of Bare Metal like a Cloud VM or an instance. If you got a problem with it, just give the person using it or whatever's using it, a new one and reimage it. Just tell it to reimage itself and it'll just (snaps fingers) go. You can do self-service with it. In Platform9, if you log in to our SaaS Ironic, you can go and say, I want that physical server to myself, because I've got a giant workload, or let's turn it into a Kubernetes cluster. That whole thing is automated. To me that's infrastructure as code. I think one of the other important things that's happening at the same time is we're seeing GitOps, we're seeing things like Terraform. I think it's important for organizations to look at what they have and ask, am I using tools that are fit for tomorrow or am I using tools that are yesterday's tools to solve tomorrow's problems? And when especially it comes to modernizing infrastructure as code, I think that's a big piece to look at. >> Do you see Terraform as old or new? >> I see Terraform as old. It's a fantastic tool, capable of many great things and it can work with basically every single provider out there on the planet. It is able to do things. Is it best fit to run in a GitOps methodology? I don't think it is quite at that point. In fact, if you went and looked at Flux, Flux has ways that make Terraform GitOps compliant, which is absolutely fantastic. It's using two tools, the best of breeds, which is solving that tomorrow problem with tomorrow solutions. >> Is the new solutions old versus new. I like this old way, new way. I mean, Terraform is not that old and it's been around for about eight years or so, whatever. But HashiCorp is doing a great job with that. I mean, so okay with Terraform, what's the new address? Is it more complex environments? Because Terraform made sense when you had basic DevOps, but now it sounds like there's a whole another level of complexity. >> I got to say. >> New tools. >> That kind of amalgamation of that application into infrastructure. Now my app team is paying way more attention to that manifest file, which is what GitOps is trying to solve. Let's templatize things. Let's version control our manifest, be it helm, customize, or just a straight up Kubernetes manifest file, plain and boring. Let's get that version controlled. Let's make sure that we know what is there, why it was changed. Let's get some auditability and things like that. And then let's get that deployment all automated. So that's predicated on the cluster existing. Well why can't we do the same thing with the cluster, the inception problem. So even if you're in public cloud, the question is like, well what's calling that API to call that thing to happen? Where is that file living? How well can I manage that in a large team? Oh my God, something just changed. Who changed it? Where is that file? And I think that's one of big, the big pieces to be sold. >> Yeah, and you talk about Edge too and on-premises. I think one of the things I'm observing and certainly when DevOps was rocking and rolling and infrastructures code was like the real push, it was pretty much the public cloud, right? >> Chris: Yep. >> And you did Cloud Native and you had stuff on-premises. Yeah you did some lifting and shifting in the cloud, but the cool stuff was going in the public cloud and you ran DevOps. Okay, now you got on-premise cloud operation and Edge. Is that the new DevOps? I mean 'cause what you're kind of getting at with old new, old new Terraform example is an interesting point, because you're pointing out potentially that that was good DevOps back in the day or it still is. >> Chris: It is, I was going to say. >> But depending on how you define what DevOps is. So if you say, I got the new DevOps with public on-premise and Edge, that's just not all public cloud, that's essentially distributed Cloud Native. >> Correct. Is that the new DevOps in your mind or is that? How would you, or is that oversimplifying it? >> Or is that that term where everyone's saying Platform Ops, right? Has it shifted? >> Well you bring up a good point about Terraform. I mean Terraform is well proven. People love it. It's got great use cases and now there seems to be new things happening. We call things like super cloud emerging, which is multicloud and abstraction layers. So you're starting to see stuff being abstracted away for the benefits of moving to the next level, so teams don't get stuck doing the same old thing. They can move on. Like what you guys are doing with Platform9 is providing a service so that teams don't have to do it. >> Correct, yeah. >> That makes a lot of sense, So you just, now it's running and then they move on to the next thing. >> Chris: Yeah, right. >> So what is that next thing? >> I think Edge is a big part of that next thing. The propensity for someone to put up with a delay, I think it's gone. For some reason, we've all become fairly short-tempered, Short fused. You know, I click the button, it should happen now, type people. And for better or worse, hopefully it gets better and we all become a bit more patient. But how do I get more effective and efficient at delivering that to that really demanding- >> I think you bring up a great point. I mean, it's not just people are getting short-tempered. I think it's more of applications are being deployed faster, security is more exposed if they don't see things quicker. You got data now infrastructure scaling up massively. So, there's a double-edged swords to scale. >> Chris: Yeah, yeah. I mean, maintenance, downtime, uptime, security. So yeah, I think there's a tension around, and one hand enthusiasm around pushing a lot of code and new apps. But is the confidence truly there? It's interesting one little, (snaps finger) supply chain software, look at Container Security for instance. >> Yeah, yeah. It's big. I mean it was codified. >> Do you agree that people, that's kind of an issue right now. >> Yeah, and it was, I mean even the supply chain has been codified by the US federal government saying there's things we need to improve. We don't want to see software being a point of vulnerability, and software includes that whole process of getting it to a running point. >> It's funny you mentioned remote and one of the thing things that you're passionate about, certainly Edge has to be remote. You don't want to roll a truck or labor at the Edge. But I was doing a conversation with, at Rebars last year about space. It's hard to do brake fix on space. It's hard to do a, to roll a someone to configure satellite, right? Right? >> Chris: Yeah. >> So Kubernetes is in space. We're seeing a lot of Cloud Native stuff in apps, in space, so just an example. This highlights the fact that it's got to be automated. Is there a machine learning AI angle with all this ChatGPT talk going on? You see all the AI going the next level. Some pretty cool stuff and it's only, I know it's the beginning, but I've heard people using some of the new machine learning, large language models, large foundational models in areas I've never heard of. Machine learning and data centers, machine learning and configuration management, a lot of different ways. How do you see as the product person, you incorporating the AI piece into the products for Platform9? >> I think that's a lot about looking at the telemetry and the information that we get back and to use one of those like old idle terms, that continuous improvement loop to feed it back in. And I think that's really where machine learning to start with comes into effect. As we run across all these customers, our system that helps at two o'clock in the morning has that telemetry, it's got that data. We can see what's changing and what's happening. So it's writing the right algorithms, creating the right machine learning to- >> So training will work for you guys. You have enough data and the telemetry to do get that training data. >> Yeah, obviously there's a lot of investment required to get there, but that is something that ultimately that could be achieved with what we see in operating people's environments. >> Great. Chris, great to have you here in the studio. Going wide ranging conversation on Kubernetes and Platform9. I guess my final question would be how do you look at the next five years out there? Because you got to run the product management, you got to have that 20 mile steer, you got to look at the customers, you got to look at what's going on in the engineering and you got to kind of have that arc. This is the right path kind of view. What's the five year arc look like for you guys? How do you see this playing out? 'Cause KubeCon is coming up and we're you seeing Kubernetes kind of break away with security? They had, they didn't call it KubeCon Security, they call it CloudNativeSecurityCon, they just had in Seattle inaugural events seemed to go well. So security is kind of breaking out and you got Kubernetes. It's getting bigger. Certainly not going away, but what's your five year arc of of how Platform9 and Kubernetes and Ops evolve? >> It's to stay on that theme, it's focusing on what is most important to our users and getting them to a point where they can just consume it, so they're not having to operate it. So it's finding those big items and bringing that into our platform. It's something that's consumable, that's just taken care of, that's tested with each release. So it's simplifying operations more and more. We've always said freedom in cloud computing. Well we started on, we started on OpenStack and made that simple. Stable, easy, you just have it, it works. We're doing that with Kubernetes. We're expanding out that user, right, we're saying bring your developers in, they can download their Kube conflict. They can see those Containers that are running there. They can access the events, the log files. They can log in and build a VM using KubeVirt. They're self servicing. So it's alleviating pressures off of the Ops team, removing the help desk systems that people still seem to rely on. So it's like what comes into that field that is the next biggest issue? Is it things like CI/CD? Is it simplifying GitOps? Is it bringing in security capabilities to talk to that? Or is that a piece that is a best of breed? Is there a reason that it's been spun out to its own conference? Is this something that deserves a focus that should be a specialized capability instead of tooling and vendors that we work with, that we partner with, that could be brought in as a service. I think it's looking at those trends and making sure that what we bring in has the biggest impact to our users. >> That's awesome. Thanks for coming in. I'll give you the last word. Put a plug in for Platform9 for the people who are watching. What should they know about Platform9 that they might not know about it or what should? When should they call you guys and when should they engage? Take a take a minute to give the plug. >> The plug. I think it's, if your operations team is focused on building Kubernetes, stop. That shouldn't be the cloud. That shouldn't be in the Edge, that shouldn't be at the data center. They should be consuming it. If your engineering teams are all trying different ways and doing different things to use and consume Cloud Native services and Kubernetes, they shouldn't be. You want consistency. That's how you get economies of scale. Provide them with a simple platform that's integrated with all of your enterprise identity where they can just start consuming instead of having to solve these problems themselves. It's those, it's those two personas, right? Where the problems manifest. What are my operations teams doing, and are they delivering to my company or are they building infrastructure again? And are my engineers sprinting or crawling? 'Cause if they're not sprinting, you should be asked the question, do I have the right Cloud Native tooling in my environment and how can I get them back? >> I think it's developer productivity, uptime, security are the tell signs. You get that done. That's the goal of what you guys are doing, your mission. >> Chris: Yep. >> Great to have you on, Chris. Thanks for coming on. Appreciate it. >> Chris: Thanks very much. 0 Okay, this is "theCUBE" here, finding the right path to Cloud Native. I'm John Furrier, host of "theCUBE." Thanks for watching. (upbeat music)

(sparkly music) >> Welcome to the Cube Special Program series "Women of the Cloud", brought to you by AWS. I'm your host, Lisa Martin. I'm very pleased to welcome Veronica McCarthy to the program, Senior Sales Manager ISB for Amazon Web Services. Veronica, great to have you on the program. Thanks for joining me today. >> Thanks for having me. >> Tell me a little bit about your current role. A little bit about yourself. >> Absolutely. Yeah, so I've been at Amazon just about four years now. I am really passionate about technology. I've been in the tech industry for about 20 plus years. Right now I'm a sales leader, so I lead a team of folks that help software companies build technology in the cloud or move technology to the cloud and help them scale and innovate in the cloud. >> Awesome, I love that. Talk a little bit about for, for those looking to grow their careers in tech, what are some of the tactical recommendations that you have that you think are really, really pertinent for others that are looking to climb that ladder? >> Yeah, it's so important to have that passion for technology 'cause that's what we do every day. It excites me to jump out of bed and learn what's new, what's coming, what we're building together and how early we are in cloud computing and in technology as a whole. So really get curious and even, you know feel free to get, get hands on. I remember early as a kid just building computers with my dad in his room. So get hands on. Today there's so many things available on the internet for free tiers. You can just play with software to get building websites, games, whatever interests you. And oh by the way, watch the Cube 'cause you're going to learn a lot and you're going to get immersed in technology, which is so important when you're learning to grow a career here because it comes across when you're interviewing, when you're talking with others, when you're networking, that you're really interested in the topic and you're really here to, to grow and and help build tech to be what it can be in the future. >> These are all great recommendations for really building that authenticity. I love your advice of really from an immersion perspective. You're right, there's so many opportunities for people of all ages to start playing around with tech and, and, but that your point of opening up your mind and being curious and embracing the different learning paths is also that curiosity. I always think creativity as well are just really important recommendations for others that are looking to grow their career in tech. >> I want to understand some of, based on some of, of those tactical recommendations. Talk to us about a success story that you've had where you've solved problems for customers relating to cloud computing based on some of your recommendations. >> Totally, just picking up on the curiosity theme that we were talking about, one of the things that I did when I was earlier in my career and I was looking after a customer, is I got curious about their business. How did they interact with their customers? And I worked backwards from that experience 'cause they were selling to consumers and I said what if they could do all these other things that could open up the consumer's eyes? So I came up with a zany idea of what if they did a partnership with Amazon and we flew their goods directly to the end consumer by a drone, you know, just crazy stuff. And I wrote something called a PRFAQ which at Amazon we use very often. It's a press release, frequently asked questions. This PRFAQ was, what could you do in the future with tech? What could, you know things what could we unlock with tech in your business? The C-suite of this company said, "You know what, that's really interesting. We're not going to do that crazy drone thing. But we like the thinking, we like the learning we like thinking about the future. How does cloud help us unlock that future?" So the long story short, they had a monolith OnPrem getting their, getting their technology from a OnPrem monolith to microservices in the cloud unlocks and opens up APIs for them to partner with other organizations to grow their customer base and in turn grow their revenue. This company in particular, pandemic hit, market change. They had to pivot or else they were going to go out of business. And because we had moved their technology from an OnPrem monolith to the cloud they were able to make that pivot and they survived the pandemic and are thriving. So it's a real life example of a success story of just getting curious, understanding the customer's business, coming back from that and then aligning for the future and getting a customer to, to get curious with you and build for the future, which worked out. And who could have predicted the pandemic, but it worked >> Right. But getting the the customer to be curious with you kind of leads me into talking about, you know, and, and the customer wanting to embrace and, and embrace cloud computing is really a transformative business model. Also takes cultural impact. Sounds like what you've been able to achieve with this particular success story. The customer had the appetite from a cultural transformation perspective but that's a hard thing to accomplish. Talk a little bit about that maybe from that customer's perspective and how they really were able to transform into a culture that embraces cloud computing. >> Absolutely. You're spot on . With all of these transformations, it's people process technology. Technology's the easy part, right? The cloud's there, we can, the architecture's there, we can build software. It's the people and the process that's hard. So as part of that transformation and part of that engagement, they actually hired me. So I left Amazon and I went and became the VP of technology for this company and I led 650 engineers globally through this transformation from an OnPrem model with microservices in the cloud. So they put faith in me because they knew this was the outcome we needed to get to but they needed the people in the process to change. So bringing the, the engineers on that journey of I know you've been building this way for a really long time and in this place, we're going to bring you into the future and we're all going to do it together. So it's a learning journey because we're all going to learn how to build microservices in the cloud and we're going to do it together and then it opens up their future as well as they continue to grow as engineers. So it's not easy to do, but it takes time. But we were able to do it in that case. >> But you bring up a great point, it's a learning journey. Yeah. And for organizations to have that appetite and that understanding and appreciation, that is as critical as the technology. You talk about, you know, people across technology. The technology is easy, it's really changing the frames of mind at the speed at which they need to change for organizations to be competitive so they can leverage cloud to really help unlock the competitive advantage as as that success story customer that you mentioned. >> Absolutely. Absolutely. And building on that innovation, right which innovation is just a, a flywheel of learning. So absolutely. >> It is. Let's shift gears a little bit, but speaking of people and processes, you know, what are some of the challenges that you see from a diversity perspective whether it's thought diversity in tech today? >> Yeah, great question. Tech is an opportunity for a level playing ground because tech is a platform with which you can build things. The important piece of building tech though is we need to make sure that many diversities are represented in the room. So when we're making tech decisions of how we're going to build, what our consumers are going to, how they're going to interact with our technology. Not everyone is one individual person. It's not a monolith out there, you know consuming our technology. So let's make sure we have that diversity in the decision making and building the tech as well as in the user use case and, and working backwards from our end users of our technology. I think one of the most, one of the easiest ways to start to approach, approach that diversity of thought and getting that diversity within your teams is looking at a gender diversity ratio. And, and we've seen historically, whilst we've seen gains in gender diversity and technology over the last few years, it's still not where it needs to be. There's a stat that I read recently in a McKinsey study that only one in four C-suite leaders are women today. And of all of all the entry level jobs from entry level to manager of all, like let's say you take a hundred men only 87 of those are women that are concurrently being promoted. Only 82 are women of color. So it's an opportunity for us to really level the playing field and think about how do we intentionally put people in the room when tech decisions are being made that can make change and build tech for who we, we know is out there to consume and, and are be a part of our tech community. >> Intention you mentioned. That is so critical for organizations really need to be looking at diversity, DEI from a, from an an intentional perspective. It can't just be ad hoc here and there. They really have to have a strategy behind it. And when I see companies, and there are a few that I've worked with that really caught my eye that have done a phenomenal job of that thought diversity, gender diversity, cultural diversity within their leadership even the people that they put on stage to talk to their events, they stand out incredibly well. We also know that there's, you probably have numbers on this, that organizations with women in the C-suite are far more profitable than organizations that don't have that. So the data, we want to talk nerdy tech, the data is there. It's demonstrating what the potentials are the capabilities, the, the opportunities. Yet we're still so far behind and we have so much road to cover. We know the direction we need to go in, we just got to be able to get the teams behind that to get there. >> Absolutely. And data's key. I read a study recently that said if you don't have at least 30% diversity in the room when you're making decisions, you are statistically not going to make the right decision, which is incredible. So the powers and the data. We know better decisions are made. Companies do better when there's diversity in the room of all types. >> Absolutely. And can you imagine the sky's the limit, if organizations are actually able to just start making headway on that percentage number and shifting it towards that diversity. What incredible opportunities and technologies and services and solutions that can be developed and delivered to meet the demanding consumers needs. So much potential there. It's, it's a, it's kind of like a crystal ball. If only we had one, we could actually see what we could actually be. >> Yeah, you're absolutely right. And I think thinking about some of the older reasons why maybe women didn't stay in the workforce longer or maybe didn't take a a career in tech, a lot of those were minimized during the pandemic. So we think about the work from home concept, right? Like that's so normal now it's, we're no longer grinding you know, I have to leave early for daycare pickup or whatever the challenges or the perceived challenges there were to women progressing in their careers. A lot of that can be managed now. So there was some good things that have come out of that pandemic time that, you know, it's much more acceptable to be home remote working. I think the balance isn't making sure that we continue our in-person innovation where we can. I find with customers today, bringing executive teams together in a room to have them brainstorm and innovate is still priceless, right? Like we still have to spend that time, we're humans, but as a woman in technology, I love the flexibility that we are now taking and adopting as a norm. And even, you know, some of my male peers that have kids at home, they love being around the kids at home and and it's a, it's a real positive impact I think that we've had amongst a lot of negative impacts by the pandemic as well. >> It is, they're definitely silver linings. That's one of them. I was talking with somebody in, in Italy this morning we were filming and you said, "I don't think my daughters are going to run in here." And I thought, you know what, even if they do that's part of totally the remote workforce, that's part of the hybrid workforce that we're all embracing. But you bring up a great point about the in-person innovation. You know, events are starting to come back, so exciting. There's just certain things about event from an innovation perspective you just can't replicate by video. So getting those executives in a room together. Talk about what you guys are doing there and, and some of the things that you think of over the next few years that will really help drive evolution and innovation of tech. >> Absolutely, yeah. I have a lot of clients that often will say, "Oh well we're we're a remote first company." So it's okay that we do our innovation session online. But then I remind them of when was the last happy hour you had online? Like do you remember the early days of the pandemic? And we all sat on, you know pick your web conferencing platform and we, you know drank wine and but there was only one person that you could hear in that. So when they're, everybody's going around and all the boxes are on the screen, it was difficult to have multiple conversations. If you walk into a happy hour in, in real life people all over the room are having multiple conversations and a lot of different things are happening in the room at the same time. It's the same thing with innovation. If we bring an executive team into the room, guess what? There's going to be a couple sidebar conversations going on as the big room progresses. And that's really healthy and that's a great way to get people that may not be the one, the star of the happy hour that wants to speak the whole time to also get their inputs and their feedback into the innovation process. So that's just an example of why it's so important. One of the things we do here at Amazon is we have so called a digital innovation workshop which is exactly as it sounds, right? Just get in a room with some whiteboards, with some thought leaders and really let's innovate for the future and it's a blank sheet of paper kind of start and out of it we come up with a business plan, a PRFAQ, like a press release I mentioned in my story earlier. That's the seeds of that. So it's really powerful and I'm so excited we're continuing to do those face to face 'cause it's so important. >> It's so important, you know, to have diversity present in the room when decisions are being made, whether it's decisions about technology or not. That thought diversity is, and as the data show that you mentioned, demonstrates how much more successful and profitable organizations can be. I'm going to ask you kind of switching gears again. Last question. If we look kind of down the road from an evolution perspective of of you're in cloud, of your role evolving. What are some of the things that you see down down the pike? >> Yeah, so great question. I am in a field sales organization today, so when the pandemic first hit, I thought, oh boy, that's the end of our career. I think we're not going to be going out and calling on customers face to face anymore. But it's actually been the opposite. I've seen more engagement from our customers. They, they really do want to spend time with us innovating. When we come into those conversations we come in with a curious mindset. So I think from a field sales perspective, it's it's not, you know, going away. And I think it's going to continue to build and it's a great career for women in particular to get into. Super flexible, the privilege of travel which is a nice vacation from home life sometimes. And the, the benefit of working from home as well. So a good balance there. So I think from a, my role specifically it's going to continue to evolve and continue to be a growth area. >> From previous roles I've had where I've worked in technology and, and software development, I think are we're still such at early stages in cloud computing and cloud technology that there is so much technology that we're continuing to build from an engineering standpoint. And I think back to my, you know, 20 year old self if I was in those shoes today and I would absolutely be doing a career in engineering. I think it's such an exciting space and as a person of, of of a, as a female I want to be at the forefront of the engineering team. So I encourage anyone if they're, you know of a diverse background, like you are the people that I want in engineering in the future because that's how you're going to build the future is build the tech, which is really cool. >> So absolutely. It's, it's very cool. I do have one more question for you. What's of your lens, what's next in cloud? What are some of the things that you think are coming down the horizon? >> Yeah, so great question. So I, I actually have a son who's special needs and I think about some of the accommodations that we have to make for him today. And I think about the tech that's coming in terms of personal tech on helping him communicate or helping him read or helping him write. And I'm excited for his future where I think a diagnosis like his, if I'd gotten it many years ago, I would be very fearful about his future. But I know that tech is going to support people like him. So I'm excited for what it's going to do for humanity. I'm excited for what it's going to help us unlock for people that may have been hindered in previous lives. My, my mom grew up with a disability and she had to keep her career relatively low level because she couldn't overcome that disability without tech. And now that she has tech, you know it would've changed the game for her. So I'm excited for my son and his future. That's what inspires me and, and I'm excited about. >> I love that. Well, with a mom like you, he's sure to succeed and fly flying colors. Veronica, it's been such a pleasure having you on the Cube. >> Thank you. >> Exciting special series of women in the cloud. We so appreciate your insights and your time. You'll have to come back. >> Thank you so much. I appreciate it. >> All right, Veronica McCarthy. I'm Lisa Martin. You're watching The Cube's special program series Women of the Cloud, brought to you by AWS. Thanks for watching. (sparkly music)

>>Well, hello everybody at John Wallace here on the Cube, and glad to have you along here for day two of our coverage here at AWS Reinvent 22. We're up in the global startup program, which is part of AWS's Startup Showcase, and I've got Kevin Farley with me. He is the director of Strategic Alliances with Maria Day db. And Kevin, good to see you this morning. Good to see you, John. Thanks for joining us. Thank >>You. >>Appreciate it. Yeah. First off, tell us about Maria db. Sure. Obviously data's your thing. Yep. But to share that with some folks at home who might not be familiar with your offering. >>Yeah. So Maria DB's been around as a corporate entity for 10 plus years, and we have a massive customer base. You know, there's a billion downloads from Docker Hub, 75% of the Fortune 500. We have an enormous sea of really happy users. But what we realize is that all of these users are really thinking about what do we, what does it mean to transform it? What does cloud modernization mean? And how do we build a strategy on something we really love to drive it into the cloud and take it to the future. So what we launched about two years ago, two and a half years ago, is Skye. It's our database as a service. It leverages all the best elements, what we provide on the enterprise platform. It marries to the AWS cloud, and it really provides the best of both worlds for our >>Customers. So in your thought then, what, what problem is that solving? >>I think what you see in the overall database market is that many people have been using what we would call legacy technology. There's been lots of sort of stratification and mixes of different database solutions. All of them come with some promise, and all of 'em come with a lot of compromise. So I think what the market is really looking for is something that can take what they know and love, can bring it to the cloud and can survive the port drive the performance and scale. That completely changes the landscape, especially as you think about what modern data needs look like, right? What people did 10 years ago with the exponential scale of data no longer works. And what they need is something that not only can really deliver against their core business values and their core business deliverables, but gets 'em to the future. How do we drive something new? How do we innovate? How do we change the game? And I think what we built with AWS really delivers what we call cloud scale. It's taking something that is the best technology, and I as a V can build, marrying it to, you know, Kubernetes layer, marrying it to global availability, thinking about having true global high availability across all of your environments and really delivering that to customers through an integrated partnership. >>Could we see this coming? I mean, because you know data, right? I mean, yeah, we, we, everybody talked about the tsunami of growth, you know, >>Back 10 >>Sure. 11 years ago. But, but maybe the headlights didn't go far enough or, or, but, but you could see that there was going to be crunch time. >>There's no doubt. And I think that this has been a, there's, there's been these sort of pocket solutions, right? So if you think at the entire no sequel world, right? People said, oh, I need scale, I can get it, but what do I have to give up asset compliance? So I have to change the way I think about what data is and how I, I can govern it. So there's been these things that deliver on half the promise, but there's never been something that comes together and really drives what we deliver through CIQ is something called expand. So distributed SQL really tied to the SQL Query language, having that asset data. So having everything you need without the compromise built on the cloud allows you to scale out and allows you to think about, I can actually do exponential layers of, of data, data modeling, data querying, complete read, write, driving that forward. And I think it gives us a whole nother dynamic that we can deliver on in a way that hasn't been before. And I think that's kind of the holy grail of what people are looking for is how am I building modern applications and how do I have a database in the cloud that's really gonna support >>It? You know, you talk about distributed, you know, sequel and, and I mean, there's a little mystery behind it, isn't there? Or at least maybe not mystery. There's a little, I guess, confusion or, or just misunderstanding. I mean, I, how, nail that down a little bit. I >>Would say the best way to say it, honestly, this is the great thing, is it people believe it's too good to be true. And I think what we see over and over >>Again, you know, what they say about that. >>But this is the great part is, you know, you know, we've just had two taste studies recently with aws, with HIT labs and Certified power, both on expand, both proof in the pudding. They did the POCs, they're like, oh my God, this works. If you watch the keynote yesterday, you know, Adam had a slide that was, you know, as big as the entire room and it highlighted Samsung and they said, you know, we're doing 80,000 requests per second. So the, you know, the story there is that AWS is able as, as an entity with their scale and their breadth to handle that kind of workload. But guess what that is? That's MariaDB expand underneath there driving all of that utilization. So it's already there, it's already married, it's already in the cloud, and now we're taking it to a completely different level with a fully managed database solution. Right? >>How impressive is that? Right? I mean, you would think that somebody out there who, I mean that that volume, that kind of capacity is, is mind blowing. >>I mean, to your kind of previous point, it's like one of those things, do I see what's coming and it's here, right? You know, it's, is it actually ever gonna be possible? And now we're showing that it really is on a daily basis for some of the biggest brands in the world. We're also seeing companies moving off not only transitioning from, you know, MariaDB or myse, but all of the big licensed, you know, conversions as well. So you think about Oracle DBS Bank is one of our biggest customers, one of the largest Oracle conversions in the world onto MariaDB. And now thinking about what is the promise of connecting that to the cloud? How do you take things that you're currently doing, OnPrem delivering a hybrid model that also then starts to say, Hey, here's my path to cloud modernization. Skye gives me that bridge. And then you take it one layer farther and you think about multi-cloud, right? That's one of the things that's critical that ISVs can really only deliver in a meaningful way, is how can we have a solution for a customer that we can take to any availability zone. We can have performance, proximity, cost, proximity. We're always able to have that total data dexterity across any environment we need and we can build on that for the future. >>So if, if we're talking about cloud database and there's so many good things going forward here. You're talking about easy use and scalability and all that. But as with ever have you talked about this, there's some push and there's some pull. Yeah. So, so what's the, what's the other side that's still, you know, you that you think has to be >>Addressed? And I think that's a great question. So there's, we see that there's poll, right? We've seen these deals, this pipeline growth, this, there's great adoption. But what I think we're still not at the point of massive hockey stick adoption is that customers still don't fully understand the capabilities distributed SQL and the power they can actually deliver. So the more we drive case studies, the more we drive POCs, the more we prove the model, I think you're gonna see just a massive adoption scale. And I also think customers are tired of doing lots of different things in lots of different pockets. So neither one of the key elements of Sky SQL is we can do both transactional and analytical data out of the same database driven by the same proxy. So what, instead of having DBAs and developers try to figure out, okay, I'm gonna pull from this database here. >>Yeah. That there, it's, it's this big spaghetti wire concept that is super expensive and super time intensive. So the ability to write modern applications and pull data from both pockets and really be able to have that as a seamless entity and deliver that to customers is massive. I mean, another part of the keynote yesterday was a new deliverable, like kind of no etl. Adam talked about Aurora and Redshift and the massive complexity of what used to exist for getting data back and forth. You also have to pay for two different databases. It's super expensive. So I think the idea that you can take the real focus of AWS and US is customer value. How do you deliver that next thing that changes the game? Always utilizes AWS delivers on that promise, but then takes a net new technology that really starts to think about how do we bring things together? How do we make it more simple? How do we make it more powerful? And how do we deliver more customer value as we go forward? >>But you know, if, if I'm, I'm still an on-prim guy, just pretend I'm not saying I am. Just pretend I just for the sake of the discussion here, it's like I just can't let it go. Yeah. Right. I, I still, you know, there's control, there's the known versus the unknown. The uncertain. Yeah. So twist my arm just a little bit more and get me over the hum. >>Well, first of all, you don't have to, right? And there's gonna be some industries and some verticals that will always have elements of their business that will be OnPrem. Guess what? We make the best based in the world. It can be MariaDB, but there's those that then say, these, these elements of our business are gonna be far more effective moving to the cloud. So we give you Skye, there's a natural symbiotic bridge between everything we do and how we deliver it. Where you can be hybrid and it's great. You can adopt the cloud as your business needs grow. And you can have multi-cloud. This is that, that idea that you can, can have your cake and eat it too, right? You can literally have all these elements of your business met without these big pressure to say, you gotta throw that away. You gotta move to this. It's really, how do you kind of gracefully adopt the cloud in a way that makes sense for your business? Where are you trying to drive your business? Is it time to value, right? Is it governance? Is it is there's different elements of what matters the most to individual businesses. You know, we wanna address those and we can address >>Those. So you're saying you don't have to dive >>In, you don't have to dive >>In. You, you can, you can go ankle deep, knee deep, whatever you wanna >>Do. Absolutely. And you know, some of the largest MariaDB users still have massive, massive on-prem implementations. And that's okay. But there's elements that are starting to fall behind. There's cost savings, there's things that they need to do in the cloud that they can't do. OnPrem. And that's where expand Skye really says, okay, here is your platform. Grow as you want to, migrate as you want to. And we're there every step along the way. We, we also provide a whole Sky DBA team. Some guys just say, I wanna get outta the database world at all. This is, this is expensive, it's costly and it's difficult to be an expert. So you can bring in our DBA team and they'll man and run, they'll, they'll run your entire environment. They'll optimize it, you know, they'll troubleshoot it, they'll bug fix, they'll do everything for you. So you can just say, I just wanna focus on building phenomenal applications for my customers. And the database game as we knew it is not something that I know I want to invest in anymore. Right. I wanna make that transition >>That makes that really, yeah. You know, I mean really attractive to a lot of people because you are, you talk about a lot of headache there. Yeah. So let's talk about AWS before Sure. I let you go just about that relationship. Okay. You've talked about the platform that it provides you and, and obviously the benefits, but just talk about how you've worked with AWS over the years Yep. And, and how you see that relationship allowing you to expand your services, no pun intended. >>For sure. So, I mean, I would start with the way we even contemplated architecture. You know, we worked with the satisfactory team. We made sure that the things that we built were optimized in their environment. You know, I think it was a lot of collaboration on how does this combined entity really make the most value for our customers? How does it make the most sense for our developers as we build it out? Then we work in the, in the global startup team. So the strategic element of who we are, not all startups are created equal, right? We have, right, we have 75% of the Fortune 100, we've got over a billion downloads. So, you know, we come in with promise. And the reason this partnership is so valuable and the reason there's so much investment going forward is cuz what really, what do the cloud guys care about? >>The very, very most, they want all of these mission critical, big workloads that are on prem to land in their cloud. What do we have a massive, massive TAM sitting out there, these customers that could go to aws. So we both see, like if we can deliver incredible value to that customer base, these big workloads will end up in aws. They'll use other AWS services. And as we scale and grow, you know, we have that platform that's already built for it. So I think that when you go back to like the tenants, the core principles of aws, the one that always stands out, the one that we always kind of lean back on is, are we delivering customer value? Is this the best thing for the customer? Because we do have some competition just like many other, other partners do, right? So there is Aurora and there is rds and there is times when that's a great service for a customer. But when people are really thinking about where do I need my database to go? Where do I really need to be set for the future growth? Where am I gonna get the kind of ROI I need going forward? That's where you can go, Hey, sky sql, expand distributed sql. This is the best game in town. It's built on aws and collectively, you know, we're gonna present that to a customer. I'm >>Sold. Done. >>I love it. Right? >>Maria db, check 'em out, they're on the show floor. Great traffic. I know at at the, at the booth. They're here at AWS Reinvent. So check 'em out. Maria db. Thanks >>Kevin. Hey, thanks John. Appreciate your >>Time. Appreciate Great. That was great. Right back with more, you're watching the cube, the leader in high tech coverage.

>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data-driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting cost could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data marts, data hubs, and yes, even data lakes were broken and left us wanting from more welcome to the data doesn't lie, or doesn't a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have featured parody with the data lake or vice versa is the so-called modern data stack, simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for hit that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience show? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know, right. You actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like star Oxley, for things like security for certainly very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited Jamma, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come. I think that's the story at Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenants of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about SAR, brain Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but what does that mean? Does that mean the E D w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems, maybe either those that either source systems for the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got to, you know, domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue are two, you know, challenges, self-serve infrastructure let's park that for a second. And then in your industry, the one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at emus is we have a single security layer that sits on top of our data match, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin, I mean, Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, do an analytic queries and with data that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah. I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively a almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself, >>Okay. G guys grab a sip of water. After this short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence, keep it right there. >>Your company has more data than ever, and more people trying to understand it, but there's a problem. Your data is stored across multiple systems. It's hard to access and that delays analytics and ultimately decisions. The old method of moving all of your data into a single source of truth is slow and definitely not built for the volume of data we have today or where we are headed while your data engineers spent over half their time, moving data, your analysts and data scientists are left, waiting, feeling frustrated, unproductive, and unable to move the needle for your business. But what if you could spend less time moving or copying data? What if your data consumers could analyze all your data quickly? >>Starburst helps your teams run fast queries on any data source. We help you create a single point of access to your data, no matter where it's stored. And we support high concurrency, we solve for speed and scale, whether it's fast, SQL queries on your data lake or faster queries across multiple data sets, Starburst helps your teams run analytics anywhere you can't afford to wait for data to be available. Your team has questions that need answers. Now with Starburst, the wait is over. You'll have faster access to data with enterprise level security, easy connectivity, and 24 7 support from experts, organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact our Trino experts to get started. >>We're back with Jess Borgman of Starburst and Richard Jarvis of EVAs health. Okay, we're gonna get to lie. Number two, and that is this an open source based platform cannot give you the performance and control that you can get with a proprietary system. Is that a lie? Justin, the enterprise data warehouse has been pretty dominant and has evolved and matured. Its stack has mature over the years. Why is it not the default platform for data? >>Yeah, well, I think that's become a lie over time. So I, I think, you know, if we go back 10 or 12 years ago with the advent of the first data lake really around Hudu, that probably was true that you couldn't get the performance that you needed to run fast, interactive, SQL queries in a data lake. Now a lot's changed in 10 or 12 years. I remember in the very early days, people would say, you you'll never get performance because you need to be column there. You need to store data in a column format. And then, you know, column formats we're introduced to, to data apes, you have Parque ORC file in aro that were created to ultimately deliver performance out of that. So, okay. We got, you know, largely over the performance hurdle, you know, more recently people will say, well, you don't have the ability to do updates and deletes like a traditional data warehouse. >>And now we've got the creation of new data formats, again like iceberg and Delta and Hodi that do allow for updates and delete. So I think the data lake has continued to mature. And I remember a, a quote from, you know, Kurt Monash many years ago where he said, you know, know it takes six or seven years to build a functional database. I think that's that's right. And now we've had almost a decade go by. So, you know, these technologies have matured to really deliver very, very close to the same level performance and functionality of, of cloud data warehouses. So I think the, the reality is that's become a line and now we have large giant hyperscale internet companies that, you know, don't have the traditional data warehouse at all. They do all of their analytics in a data lake. So I think we've, we've proven that it's very much possible today. >>Thank you for that. And so Richard, talk about your perspective as a practitioner in terms of what open brings you versus, I mean, look closed is it's open as a moving target. I remember Unix used to be open systems and so it's, it is an evolving, you know, spectrum, but, but from your perspective, what does open give you that you can't get from a proprietary system where you are fearful of in a proprietary system? >>I, I suppose for me open buys us the ability to be unsure about the future, because one thing that's always true about technology is it evolves in a, a direction, slightly different to what people expect. And what you don't want to end up is done is backed itself into a corner that then prevents it from innovating. So if you have chosen a technology and you've stored trillions of records in that technology and suddenly a new way of processing or machine learning comes out, you wanna be able to take advantage and your competitive edge might depend upon it. And so I suppose for us, we acknowledge that we don't have perfect vision of what the future might be. And so by backing open storage technologies, we can apply a number of different technologies to the processing of that data. And that gives us the ability to remain relevant, innovate on our data storage. And we have bought our way out of the, any performance concerns because we can use cloud scale infrastructure to scale up and scale down as we need. And so we don't have the concerns that we don't have enough hardware today to process what we want to do, want to achieve. We can just scale up when we need it and scale back down. So open source has really allowed us to maintain the being at the cutting edge. >>So Jess, let me play devil's advocate here a little bit, and I've talked to Shaak about this and you know, obviously her vision is there's an open source that, that the data meshes open source, an open source tooling, and it's not a proprietary, you know, you're not gonna buy a data mesh. You're gonna build it with, with open source toolings and, and vendors like you are gonna support it, but to come back to sort of today, you can get to market with a proprietary solution faster. I'm gonna make that statement. You tell me if it's a lie and then you can say, okay, we support Apache iceberg. We're gonna support open source tooling, take a company like VMware, not really in the data business, but how, the way they embraced Kubernetes and, and you know, every new open source thing that comes along, they say, we do that too. Why can't proprietary systems do that and be as effective? >>Yeah, well, I think at least with the, within the data landscape saying that you can access open data formats like iceberg or, or others is, is a bit dis disingenuous because really what you're selling to your customer is a certain degree of performance, a certain SLA, and you know, those cloud data warehouses that can reach beyond their own proprietary storage drop all the performance that they were able to provide. So it is, it reminds me kind of, of, again, going back 10 or 12 years ago when everybody had a connector to Haddo and that they thought that was the solution, right? But the reality was, you know, a connector was not the same as running workloads in Haddo back then. And I think similarly, you know, being able to connect to an external table that lives in an open data format, you know, you're, you're not going to give it the performance that your customers are accustomed to. And at the end of the day, they're always going to be predisposed. They're always going to be incentivized to get that data ingested into the data warehouse, cuz that's where they have control. And you know, the bottom line is the database industry has really been built around vendor lockin. I mean, from the start, how, how many people love Oracle today, but our customers, nonetheless, I think, you know, lockin is, is, is part of this industry. And I think that's really what we're trying to change with open data formats. >>Well, that's interesting reminded when I, you know, I see the, the gas price, the tees or gas price I, I drive up and then I say, oh, that's the cash price credit card. I gotta pay 20 cents more, but okay. But so the, the argument then, so let me, let me come back to you, Justin. So what's wrong with saying, Hey, we support open data formats, but yeah, you're gonna get better performance if you, if you keep it into our closed system, are you saying that long term that's gonna come back and bite you cuz you're gonna end up, you mentioned Oracle, you mentioned Teradata. Yeah. That's by, by implication, you're saying that's where snowflake customers are headed. >>Yeah, absolutely. I think this is a movie that, you know, we've all seen before. At least those of us who've been in the industry long enough to, to see this movie play over a couple times. So I do think that's the future. And I think, you know, I loved what Richard said. I actually wrote it down. Cause I thought it was an amazing quote. He said, it buys us the ability to be unsure of the future. Th that that pretty much says it all the, the future is unknowable and the reality is using open data formats. You remain interoperable with any technology you want to utilize. If you want to use spark to train a machine learning model and you want to use Starbust to query via sequel, that's totally cool. They can both work off the same exact, you know, data, data sets by contrast, if you're, you know, focused on a proprietary model, then you're kind of locked in again to that model. I think the same applies to data, sharing to data products, to a wide variety of, of aspects of the data landscape that a proprietary approach kind of closes you in and locks you in. >>So I, I would say this Richard, I'd love to get your thoughts on it. Cause I talked to a lot of Oracle customers, not as many te data customers, but, but a lot of Oracle customers and they, you know, they'll admit, yeah, you know, they're jamming us on price and the license cost they give, but we do get value out of it. And so my question to you, Richard, is, is do the, let's call it data warehouse systems or the proprietary systems. Are they gonna deliver a greater ROI sooner? And is that in allure of, of that customers, you know, are attracted to, or can open platforms deliver as fast in ROI? >>I think the answer to that is it can depend a bit. It depends on your businesses skillset. So we are lucky that we have a number of proprietary teams that work in databases that provide our operational data capability. And we have teams of analytics and big data experts who can work with open data sets and open data formats. And so for those different teams, they can get to an ROI more quickly with different technologies for the business though, we can't do better for our operational data stores than proprietary databases. Today we can back off very tight SLAs to them. We can demonstrate reliability from millions of hours of those databases being run at enterprise scale, but for an analytics workload where increasing our business is growing in that direction, we can't do better than open data formats with cloud-based data mesh type technologies. And so it's not a simple answer. That one will always be the right answer for our business. We definitely have times when proprietary databases provide a capability that we couldn't easily represent or replicate with open technologies. >>Yeah. Richard, stay with you. You mentioned, you know, you know, some things before that, that strike me, you know, the data brick snowflake, you know, thing is, oh, is a lot of fun for analysts like me. You've got data bricks coming at it. Richard, you mentioned you have a lot of rockstar, data engineers, data bricks coming at it from a data engineering heritage. You get snowflake coming at it from an analytics heritage. Those two worlds are, are colliding people like PJI Mohan said, you know what? I think it's actually harder to play in the data engineering. So I E it's easier to for data engineering world to go into the analytics world versus the reverse, but thinking about up and coming engineers and developers preparing for this future of data engineering and data analytics, how, how should they be thinking about the future? What, what's your advice to those young people? >>So I think I'd probably fall back on general programming skill sets. So the advice that I saw years ago was if you have open source technologies, the pythons and Javas on your CV, you commander 20% pay, hike over people who can only do proprietary programming languages. And I think that's true of data technologies as well. And from a business point of view, that makes sense. I'd rather spend the money that I save on proprietary licenses on better engineers, because they can provide more value to the business that can innovate us beyond our competitors. So I think I would my advice to people who are starting here or trying to build teams to capitalize on data assets is begin with open license, free capabilities, because they're very cheap to experiment with. And they generate a lot of interest from people who want to join you as a business. And you can make them very successful early, early doors with, with your analytics journey. >>It's interesting. Again, analysts like myself, we do a lot of TCO work and have over the last 20 plus years. And in world of Oracle, you know, normally it's the staff, that's the biggest nut in total cost of ownership, not an Oracle. It's the it's the license cost is by far the biggest component in the, in the blame pie. All right, Justin, help us close out this segment. We've been talking about this sort of data mesh open, closed snowflake data bricks. Where does Starburst sort of as this engine for the data lake data lake house, the data warehouse fit in this, in this world? >>Yeah. So our view on how the future ultimately unfolds is we think that data lakes will be a natural center of gravity for a lot of the reasons that we described open data formats, lowest total cost of ownership, because you get to choose the cheapest storage available to you. Maybe that's S3 or Azure data lake storage, or Google cloud storage, or maybe it's on-prem object storage that you bought at a, at a really good price. So ultimately storing a lot of data in a deal lake makes a lot of sense, but I think what makes our perspective unique is we still don't think you're gonna get everything there either. We think that basically centralization of all your data assets is just an impossible endeavor. And so you wanna be able to access data that lives outside of the lake as well. So we kind of think of the lake as maybe the biggest place by volume in terms of how much data you have, but to, to have comprehensive analytics and to truly understand your business and understand it holistically, you need to be able to go access other data sources as well. And so that's the role that we wanna play is to be a single point of access for our customers, provide the right level of fine grained access controls so that the right people have access to the right data and ultimately make it easy to discover and consume via, you know, the creation of data products as well. >>Great. Okay. Thanks guys. Right after this quick break, we're gonna be back to debate whether the cloud data model that we see emerging and the so-called modern data stack is really modern, or is it the same wine new bottle? When it comes to data architectures, you're watching the cube, the leader in enterprise and emerging tech coverage. >>Your data is capable of producing incredible results, but data consumers are often left in the dark without fast access to the data they need. Starers makes your data visible from wherever it lives. Your company is acquiring more data in more places, more rapidly than ever to rely solely on a data centralization strategy. Whether it's in a lake or a warehouse is unrealistic. A single source of truth approach is no longer viable, but disconnected data silos are often left untapped. We need a new approach. One that embraces distributed data. One that enables fast and secure access to any of your data from anywhere with Starburst, you'll have the fastest query engine for the data lake that allows you to connect and analyze your disparate data sources no matter where they live Starburst provides the foundational technology required for you to build towards the vision of a decentralized data mesh Starburst enterprise and Starburst galaxy offer enterprise ready, connectivity, interoperability, and security features for multiple regions, multiple clouds and everchanging global regulatory requirements. The data is yours. And with Starburst, you can perform analytics anywhere in light of your world. >>Okay. We're back with Justin Boardman. CEO of Starbust Richard Jarvis is the CTO of EMI health and Theresa tongue is the cloud first technologist from Accenture. We're on July number three. And that is the claim that today's modern data stack is actually modern. So I guess that's the lie it's it is it's is that it's not modern. Justin, what do you say? >>Yeah. I mean, I think new isn't modern, right? I think it's the, it's the new data stack. It's the cloud data stack, but that doesn't necessarily mean it's modern. I think a lot of the components actually are exactly the same as what we've had for 40 years, rather than Terra data. You have snowflake rather than Informatica you have five trend. So it's the same general stack, just, you know, a cloud version of it. And I think a lot of the challenges that it plagued us for 40 years still maintain. >>So lemme come back to you just, but okay. But, but there are differences, right? I mean, you can scale, you can throw resources at the problem. You can separate compute from storage. You really, you know, there's a lot of money being thrown at that by venture capitalists and snowflake, you mentioned it's competitors. So that's different. Is it not, is that not at least an aspect of, of modern dial it up, dial it down. So what, what do you say to that? >>Well, it, it is, it's certainly taking, you know, what the cloud offers and taking advantage of that, but it's important to note that the cloud data warehouses out there are really just separating their compute from their storage. So it's allowing them to scale up and down, but your data still stored in a proprietary format. You're still locked in. You still have to ingest the data to get it even prepared for analysis. So a lot of the same sort of structural constraints that exist with the old enterprise data warehouse model OnPrem still exist just yes, a little bit more elastic now because the cloud offers that. >>So Theresa, let me go to you cuz you have cloud first in your, in your, your title. So what's what say you to this conversation? >>Well, even the cloud providers are looking towards more of a cloud continuum, right? So the centralized cloud, as we know it, maybe data lake data warehouse in the central place, that's not even how the cloud providers are looking at it. They have news query services. Every provider has one that really expands those queries to be beyond a single location. And if we look at a lot of where our, the future goes, right, that that's gonna very much fall the same thing. There was gonna be more edge. There's gonna be more on premise because of data sovereignty, data gravity, because you're working with different parts of the business that have already made major cloud investments in different cloud providers. Right? So there's a lot of reasons why the modern, I guess, the next modern generation of the data staff needs to be much more federated. >>Okay. So Richard, how do you deal with this? You you've obviously got, you know, the technical debt, the existing infrastructure it's on the books. You don't wanna just throw it out. A lot of, lot of conversation about modernizing applications, which a lot of times is a, you know, a microservices layer on top of leg legacy apps. How do you think about the modern data stack? >>Well, I think probably the first thing to say is that the stack really has to include the processes and people around the data as well is all well and good changing the technology. But if you don't modernize how people use that technology, then you're not going to be able to, to scale because just cuz you can scale CPU and storage doesn't mean you can get more people to use your data, to generate you more, more value for the business. And so what we've been looking at is really changing in very much aligned to data products and, and data mesh. How do you enable more people to consume the service and have the stack respond in a way that keeps costs low? Because that's important for our customers consuming this data, but also allows people to occasionally run enormous queries and then tick along with smaller ones when required. And it's a good job we did because during COVID all of a sudden we had enormous pressures on our data platform to answer really important life threatening queries. And if we couldn't scale both our data stack and our teams, we wouldn't have been able to answer those as quickly as we had. So I think the stack needs to support a scalable business, not just the technology itself. >>Well thank you for that. So Justin let's, let's try to break down what the critical aspects are of the modern data stack. So you think about the past, you know, five, seven years cloud obviously has given a different pricing model. De-risked experimentation, you know that we talked about the ability to scale up scale down, but it's, I'm, I'm taking away that that's not enough based on what Richard just said. The modern data stack has to serve the business and enable the business to build data products. I, I buy that. I'm a big fan of the data mesh concepts, even though we're early days. So what are the critical aspects if you had to think about, you know, paying, maybe putting some guardrails and definitions around the modern data stack, what does that look like? What are some of the attributes and, and principles there >>Of, of how it should look like or, or how >>It's yeah. What it should be. >>Yeah. Yeah. Well, I think, you know, in, in Theresa mentioned this in, in a previous segment about the data warehouse is not necessarily going to disappear. It just becomes one node, one element of the overall data mesh. And I, I certainly agree with that. So by no means, are we suggesting that, you know, snowflake or Redshift or whatever cloud data warehouse you may be using is going to disappear, but it's, it's not going to become the end all be all. It's not the, the central single source of truth. And I think that's the paradigm shift that needs to occur. And I think it's also worth noting that those who were the early adopters of the modern data stack were primarily digital, native born in the cloud young companies who had the benefit of, of idealism. They had the benefit of it was starting with a clean slate that does not reflect the vast majority of enterprises. >>And even those companies, as they grow up mature out of that ideal state, they go buy a business. Now they've got something on another cloud provider that has a different data stack and they have to deal with that heterogeneity that is just change and change is a part of life. And so I think there is an element here that is almost philosophical. It's like, do you believe in an absolute ideal where I can just fit everything into one place or do I believe in reality? And I think the far more pragmatic approach is really what data mesh represents. So to answer your question directly, I think it's adding, you know, the ability to access data that lives outside of the data warehouse, maybe living in open data formats in a data lake or accessing operational systems as well. Maybe you want to directly access data that lives in an Oracle database or a Mongo database or, or what have you. So creating that flexibility to really Futureproof yourself from the inevitable change that you will, you won't encounter over time. >>So thank you. So there, based on what Justin just said, I, my takeaway there is it's inclusive, whether it's a data Mar data hub, data lake data warehouse, it's a, just a node on the mesh. Okay. I get that. Does that include there on Preem data? O obviously it has to, what are you seeing in terms of the ability to, to take that data mesh concept on Preem? I mean, most implementations I've seen in data mesh, frankly really aren't, you know, adhering to the philosophy. They're maybe, maybe it's data lake and maybe it's using glue. You look at what JPMC is doing. Hello, fresh, a lot of stuff happening on the AWS cloud in that, you know, closed stack, if you will. What's the answer to that Theresa? >>I mean, I, I think it's a killer case for data. Me, the fact that you have valuable data sources, OnPrem, and then yet you still wanna modernize and take the best of cloud cloud is still, like we mentioned, there's a lot of great reasons for it around the economics and the way ability to tap into the innovation that the cloud providers are giving around data and AI architecture. It's an easy button. So the mesh allows you to have the best of both worlds. You can start using the data products on-prem or in the existing systems that are working already. It's meaningful for the business. At the same time, you can modernize the ones that make business sense because it needs better performance. It needs, you know, something that is, is cheaper or, or maybe just tap into better analytics to get better insights, right? So you're gonna be able to stretch and really have the best of both worlds. That, again, going back to Richard's point, that is meaningful by the business. Not everything has to have that one size fits all set a tool. >>Okay. Thank you. So Richard, you know, talking about data as product, wonder if we could give us your perspectives here, what are the advantages of treating data as a product? What, what role do data products have in the modern data stack? We talk about monetizing data. What are your thoughts on data products? >>So for us, one of the most important data products that we've been creating is taking data that is healthcare data across a wide variety of different settings. So information about patients' demographics about their, their treatment, about their medications and so on, and taking that into a standards format that can be utilized by a wide variety of different researchers because misinterpreting that data or having the data not presented in the way that the user is expecting means that you generate the wrong insight. And in any business, that's clearly not a desirable outcome, but when that insight is so critical, as it might be in healthcare or some security settings, you really have to have gone to the trouble of understanding the data, presenting it in a format that everyone can clearly agree on. And then letting people consume in a very structured, managed way, even if that data comes from a variety of different sources in, in, in the first place. And so our data product journey has really begun by standardizing data across a number of different silos through the data mesh. So we can present out both internally and through the right governance externally to, to researchers. >>So that data product through whatever APIs is, is accessible, it's discoverable, but it's obviously gotta be governed as well. You mentioned you, you appropriately provided to internally. Yeah. But also, you know, external folks as well. So the, so you've, you've architected that capability today >>We have, and because the data is standard, it can generate value much more quickly and we can be sure of the security and, and, and value that that's providing because the data product isn't just about formatting the data into the correct tables, it's understanding what it means to redact the data or to remove certain rows from it or to interpret what a date actually means. Is it the start of the contract or the start of the treatment or the date of birth of a patient? These things can be lost in the data storage without having the proper product management around the data to say in a very clear business context, what does this data mean? And what does it mean to process this data for a particular use case? >>Yeah, it makes sense. It's got the context. If the, if the domains own the data, you, you gotta cut through a lot of the, the, the centralized teams, the technical teams that, that data agnostic, they don't really have that context. All right. Let's send Justin, how does Starburst fit into this modern data stack? Bring us home. >>Yeah. So I think for us, it's really providing our customers with, you know, the flexibility to operate and analyze data that lives in a wide variety of different systems. Ultimately giving them that optionality, you know, and optionality provides the ability to reduce costs, store more in a data lake rather than data warehouse. It provides the ability for the fastest time to insight to access the data directly where it lives. And ultimately with this concept of data products that we've now, you know, incorporated into our offering as well, you can really create and, and curate, you know, data as a product to be shared and consumed. So we're trying to help enable the data mesh, you know, model and make that an appropriate compliment to, you know, the, the, the modern data stack that people have today. >>Excellent. Hey, I wanna thank Justin Theresa and Richard for joining us today. You guys are great. I big believers in the, in the data mesh concept, and I think, you know, we're seeing the future of data architecture. So thank you. Now, remember, all these conversations are gonna be available on the cube.net for on-demand viewing. You can also go to starburst.io. They have some great content on the website and they host some really thought provoking interviews and, and, and they have awesome resources, lots of data mesh conversations over there, and really good stuff in, in the resource section. So check that out. Thanks for watching the data doesn't lie or does it made possible by Starburst data? This is Dave Valante for the cube, and we'll see you next time. >>The explosion of data sources has forced organizations to modernize their systems and architecture and come to terms with one size does not fit all for data management today. Your teams are constantly moving and copying data, which requires time management. And in some cases, double paying for compute resources. Instead, what if you could access all your data anywhere using the BI tools and SQL skills your users already have. And what if this also included enterprise security and fast performance with Starburst enterprise, you can provide your data consumers with a single point of secure access to all of your data, no matter where it lives with features like strict, fine grained, access control, end to end data encryption and data masking Starburst meets the security standards of the largest companies. Starburst enterprise can easily be deployed anywhere and managed with insights where data teams holistically view their clusters operation and query execution. So they can reach meaningful business decisions faster, all this with the support of the largest team of Trino experts in the world, delivering fully tested stable releases and available to support you 24 7 to unlock the value in all of your data. You need a solution that easily fits with what you have today and can adapt to your architecture. Tomorrow. 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>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data-driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting cost could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data marts, data hubs, and yes, even data lakes were broken and left us wanting from more welcome to the data doesn't lie, or doesn't a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have featured parody with the data lake or vice versa is the so-called modern data stack, simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for hit that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience show? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know, right. You actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like star Oxley, for things like security for certainly very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited Jamma, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come. I think that's the story at Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenants of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about SAR, brain Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but what does that mean? Does that mean the E D w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems, maybe either those that either source systems for the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got to, you know, domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue are two, you know, challenges, self-serve infrastructure let's park that for a second. And then in your industry, the one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at emus is we have a single security layer that sits on top of our data match, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin, I mean, Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, do an analytic queries and with data that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah. I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively a almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself, >>Okay. G guys grab a sip of water. After this short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence, keep it right there. >>Your company has more data than ever, and more people trying to understand it, but there's a problem. Your data is stored across multiple systems. It's hard to access and that delays analytics and ultimately decisions. The old method of moving all of your data into a single source of truth is slow and definitely not built for the volume of data we have today or where we are headed while your data engineers spent over half their time, moving data, your analysts and data scientists are left, waiting, feeling frustrated, unproductive, and unable to move the needle for your business. But what if you could spend less time moving or copying data? What if your data consumers could analyze all your data quickly? >>Starburst helps your teams run fast queries on any data source. We help you create a single point of access to your data, no matter where it's stored. And we support high concurrency, we solve for speed and scale, whether it's fast, SQL queries on your data lake or faster queries across multiple data sets, Starburst helps your teams run analytics anywhere you can't afford to wait for data to be available. Your team has questions that need answers. Now with Starburst, the wait is over. You'll have faster access to data with enterprise level security, easy connectivity, and 24 7 support from experts, organizations like Zolando Comcast and FINRA rely on Starburst to move their businesses forward. Contact our Trino experts to get started. >>We're back with Jess Borgman of Starburst and Richard Jarvis of EVAs health. Okay, we're gonna get to lie. Number two, and that is this an open source based platform cannot give you the performance and control that you can get with a proprietary system. Is that a lie? Justin, the enterprise data warehouse has been pretty dominant and has evolved and matured. Its stack has mature over the years. Why is it not the default platform for data? >>Yeah, well, I think that's become a lie over time. So I, I think, you know, if we go back 10 or 12 years ago with the advent of the first data lake really around Hudu, that probably was true that you couldn't get the performance that you needed to run fast, interactive, SQL queries in a data lake. Now a lot's changed in 10 or 12 years. I remember in the very early days, people would say, you you'll never get performance because you need to be column there. You need to store data in a column format. And then, you know, column formats we're introduced to, to data apes, you have Parque ORC file in aro that were created to ultimately deliver performance out of that. So, okay. We got, you know, largely over the performance hurdle, you know, more recently people will say, well, you don't have the ability to do updates and deletes like a traditional data warehouse. >>And now we've got the creation of new data formats, again like iceberg and Delta and Hodi that do allow for updates and delete. So I think the data lake has continued to mature. And I remember a, a quote from, you know, Kurt Monash many years ago where he said, you know, know it takes six or seven years to build a functional database. I think that's that's right. And now we've had almost a decade go by. So, you know, these technologies have matured to really deliver very, very close to the same level performance and functionality of, of cloud data warehouses. So I think the, the reality is that's become a line and now we have large giant hyperscale internet companies that, you know, don't have the traditional data warehouse at all. They do all of their analytics in a data lake. So I think we've, we've proven that it's very much possible today. >>Thank you for that. And so Richard, talk about your perspective as a practitioner in terms of what open brings you versus, I mean, look closed is it's open as a moving target. I remember Unix used to be open systems and so it's, it is an evolving, you know, spectrum, but, but from your perspective, what does open give you that you can't get from a proprietary system where you are fearful of in a proprietary system? >>I, I suppose for me open buys us the ability to be unsure about the future, because one thing that's always true about technology is it evolves in a, a direction, slightly different to what people expect. And what you don't want to end up is done is backed itself into a corner that then prevents it from innovating. So if you have chosen a technology and you've stored trillions of records in that technology and suddenly a new way of processing or machine learning comes out, you wanna be able to take advantage and your competitive edge might depend upon it. And so I suppose for us, we acknowledge that we don't have perfect vision of what the future might be. And so by backing open storage technologies, we can apply a number of different technologies to the processing of that data. And that gives us the ability to remain relevant, innovate on our data storage. And we have bought our way out of the, any performance concerns because we can use cloud scale infrastructure to scale up and scale down as we need. And so we don't have the concerns that we don't have enough hardware today to process what we want to do, want to achieve. We can just scale up when we need it and scale back down. So open source has really allowed us to maintain the being at the cutting edge. >>So Jess, let me play devil's advocate here a little bit, and I've talked to Shaak about this and you know, obviously her vision is there's an open source that, that the data meshes open source, an open source tooling, and it's not a proprietary, you know, you're not gonna buy a data mesh. You're gonna build it with, with open source toolings and, and vendors like you are gonna support it, but to come back to sort of today, you can get to market with a proprietary solution faster. I'm gonna make that statement. You tell me if it's a lie and then you can say, okay, we support Apache iceberg. We're gonna support open source tooling, take a company like VMware, not really in the data business, but how, the way they embraced Kubernetes and, and you know, every new open source thing that comes along, they say, we do that too. Why can't proprietary systems do that and be as effective? >>Yeah, well, I think at least with the, within the data landscape saying that you can access open data formats like iceberg or, or others is, is a bit dis disingenuous because really what you're selling to your customer is a certain degree of performance, a certain SLA, and you know, those cloud data warehouses that can reach beyond their own proprietary storage drop all the performance that they were able to provide. So it is, it reminds me kind of, of, again, going back 10 or 12 years ago when everybody had a connector to Haddo and that they thought that was the solution, right? But the reality was, you know, a connector was not the same as running workloads in Haddo back then. And I think similarly, you know, being able to connect to an external table that lives in an open data format, you know, you're, you're not going to give it the performance that your customers are accustomed to. And at the end of the day, they're always going to be predisposed. They're always going to be incentivized to get that data ingested into the data warehouse, cuz that's where they have control. And you know, the bottom line is the database industry has really been built around vendor lockin. I mean, from the start, how, how many people love Oracle today, but our customers, nonetheless, I think, you know, lockin is, is, is part of this industry. And I think that's really what we're trying to change with open data formats. >>Well, that's interesting reminded when I, you know, I see the, the gas price, the tees or gas price I, I drive up and then I say, oh, that's the cash price credit card. I gotta pay 20 cents more, but okay. But so the, the argument then, so let me, let me come back to you, Justin. So what's wrong with saying, Hey, we support open data formats, but yeah, you're gonna get better performance if you, if you keep it into our closed system, are you saying that long term that's gonna come back and bite you cuz you're gonna end up, you mentioned Oracle, you mentioned Teradata. Yeah. That's by, by implication, you're saying that's where snowflake customers are headed. >>Yeah, absolutely. I think this is a movie that, you know, we've all seen before. At least those of us who've been in the industry long enough to, to see this movie play over a couple times. So I do think that's the future. And I think, you know, I loved what Richard said. I actually wrote it down. Cause I thought it was an amazing quote. He said, it buys us the ability to be unsure of the future. Th that that pretty much says it all the, the future is unknowable and the reality is using open data formats. You remain interoperable with any technology you want to utilize. If you want to use spark to train a machine learning model and you want to use Starbust to query via sequel, that's totally cool. They can both work off the same exact, you know, data, data sets by contrast, if you're, you know, focused on a proprietary model, then you're kind of locked in again to that model. I think the same applies to data, sharing to data products, to a wide variety of, of aspects of the data landscape that a proprietary approach kind of closes you in and locks you in. >>So I, I would say this Richard, I'd love to get your thoughts on it. Cause I talked to a lot of Oracle customers, not as many te data customers, but, but a lot of Oracle customers and they, you know, they'll admit, yeah, you know, they're jamming us on price and the license cost they give, but we do get value out of it. And so my question to you, Richard, is, is do the, let's call it data warehouse systems or the proprietary systems. Are they gonna deliver a greater ROI sooner? And is that in allure of, of that customers, you know, are attracted to, or can open platforms deliver as fast in ROI? >>I think the answer to that is it can depend a bit. It depends on your businesses skillset. So we are lucky that we have a number of proprietary teams that work in databases that provide our operational data capability. And we have teams of analytics and big data experts who can work with open data sets and open data formats. And so for those different teams, they can get to an ROI more quickly with different technologies for the business though, we can't do better for our operational data stores than proprietary databases. Today we can back off very tight SLAs to them. We can demonstrate reliability from millions of hours of those databases being run at enterprise scale, but for an analytics workload where increasing our business is growing in that direction, we can't do better than open data formats with cloud-based data mesh type technologies. And so it's not a simple answer. That one will always be the right answer for our business. We definitely have times when proprietary databases provide a capability that we couldn't easily represent or replicate with open technologies. >>Yeah. Richard, stay with you. You mentioned, you know, you know, some things before that, that strike me, you know, the data brick snowflake, you know, thing is, oh, is a lot of fun for analysts like me. You've got data bricks coming at it. Richard, you mentioned you have a lot of rockstar, data engineers, data bricks coming at it from a data engineering heritage. You get snowflake coming at it from an analytics heritage. Those two worlds are, are colliding people like PJI Mohan said, you know what? I think it's actually harder to play in the data engineering. So I E it's easier to for data engineering world to go into the analytics world versus the reverse, but thinking about up and coming engineers and developers preparing for this future of data engineering and data analytics, how, how should they be thinking about the future? What, what's your advice to those young people? >>So I think I'd probably fall back on general programming skill sets. So the advice that I saw years ago was if you have open source technologies, the pythons and Javas on your CV, you commander 20% pay, hike over people who can only do proprietary programming languages. And I think that's true of data technologies as well. And from a business point of view, that makes sense. I'd rather spend the money that I save on proprietary licenses on better engineers, because they can provide more value to the business that can innovate us beyond our competitors. So I think I would my advice to people who are starting here or trying to build teams to capitalize on data assets is begin with open license, free capabilities, because they're very cheap to experiment with. And they generate a lot of interest from people who want to join you as a business. And you can make them very successful early, early doors with, with your analytics journey. >>It's interesting. Again, analysts like myself, we do a lot of TCO work and have over the last 20 plus years. And in world of Oracle, you know, normally it's the staff, that's the biggest nut in total cost of ownership, not an Oracle. It's the it's the license cost is by far the biggest component in the, in the blame pie. All right, Justin, help us close out this segment. We've been talking about this sort of data mesh open, closed snowflake data bricks. Where does Starburst sort of as this engine for the data lake data lake house, the data warehouse fit in this, in this world? >>Yeah. So our view on how the future ultimately unfolds is we think that data lakes will be a natural center of gravity for a lot of the reasons that we described open data formats, lowest total cost of ownership, because you get to choose the cheapest storage available to you. Maybe that's S3 or Azure data lake storage, or Google cloud storage, or maybe it's on-prem object storage that you bought at a, at a really good price. So ultimately storing a lot of data in a deal lake makes a lot of sense, but I think what makes our perspective unique is we still don't think you're gonna get everything there either. We think that basically centralization of all your data assets is just an impossible endeavor. And so you wanna be able to access data that lives outside of the lake as well. So we kind of think of the lake as maybe the biggest place by volume in terms of how much data you have, but to, to have comprehensive analytics and to truly understand your business and understand it holistically, you need to be able to go access other data sources as well. And so that's the role that we wanna play is to be a single point of access for our customers, provide the right level of fine grained access controls so that the right people have access to the right data and ultimately make it easy to discover and consume via, you know, the creation of data products as well. >>Great. Okay. Thanks guys. Right after this quick break, we're gonna be back to debate whether the cloud data model that we see emerging and the so-called modern data stack is really modern, or is it the same wine new bottle? When it comes to data architectures, you're watching the cube, the leader in enterprise and emerging tech coverage. >>Your data is capable of producing incredible results, but data consumers are often left in the dark without fast access to the data they need. Starers makes your data visible from wherever it lives. Your company is acquiring more data in more places, more rapidly than ever to rely solely on a data centralization strategy. Whether it's in a lake or a warehouse is unrealistic. A single source of truth approach is no longer viable, but disconnected data silos are often left untapped. We need a new approach. One that embraces distributed data. One that enables fast and secure access to any of your data from anywhere with Starburst, you'll have the fastest query engine for the data lake that allows you to connect and analyze your disparate data sources no matter where they live Starburst provides the foundational technology required for you to build towards the vision of a decentralized data mesh Starburst enterprise and Starburst galaxy offer enterprise ready, connectivity, interoperability, and security features for multiple regions, multiple clouds and everchanging global regulatory requirements. The data is yours. And with Starburst, you can perform analytics anywhere in light of your world. >>Okay. We're back with Justin Boardman. CEO of Starbust Richard Jarvis is the CTO of EMI health and Theresa tongue is the cloud first technologist from Accenture. We're on July number three. And that is the claim that today's modern data stack is actually modern. So I guess that's the lie it's it is it's is that it's not modern. Justin, what do you say? >>Yeah. I mean, I think new isn't modern, right? I think it's the, it's the new data stack. It's the cloud data stack, but that doesn't necessarily mean it's modern. I think a lot of the components actually are exactly the same as what we've had for 40 years, rather than Terra data. You have snowflake rather than Informatica you have five trend. So it's the same general stack, just, you know, a cloud version of it. And I think a lot of the challenges that it plagued us for 40 years still maintain. >>So lemme come back to you just, but okay. But, but there are differences, right? I mean, you can scale, you can throw resources at the problem. You can separate compute from storage. You really, you know, there's a lot of money being thrown at that by venture capitalists and snowflake, you mentioned it's competitors. So that's different. Is it not, is that not at least an aspect of, of modern dial it up, dial it down. So what, what do you say to that? >>Well, it, it is, it's certainly taking, you know, what the cloud offers and taking advantage of that, but it's important to note that the cloud data warehouses out there are really just separating their compute from their storage. So it's allowing them to scale up and down, but your data still stored in a proprietary format. You're still locked in. You still have to ingest the data to get it even prepared for analysis. So a lot of the same sort of structural constraints that exist with the old enterprise data warehouse model OnPrem still exist just yes, a little bit more elastic now because the cloud offers that. >>So Theresa, let me go to you cuz you have cloud first in your, in your, your title. So what's what say you to this conversation? >>Well, even the cloud providers are looking towards more of a cloud continuum, right? So the centralized cloud, as we know it, maybe data lake data warehouse in the central place, that's not even how the cloud providers are looking at it. They have news query services. Every provider has one that really expands those queries to be beyond a single location. And if we look at a lot of where our, the future goes, right, that that's gonna very much fall the same thing. There was gonna be more edge. There's gonna be more on premise because of data sovereignty, data gravity, because you're working with different parts of the business that have already made major cloud investments in different cloud providers. Right? So there's a lot of reasons why the modern, I guess, the next modern generation of the data staff needs to be much more federated. >>Okay. So Richard, how do you deal with this? You you've obviously got, you know, the technical debt, the existing infrastructure it's on the books. You don't wanna just throw it out. A lot of, lot of conversation about modernizing applications, which a lot of times is a, you know, a microservices layer on top of leg legacy apps. How do you think about the modern data stack? >>Well, I think probably the first thing to say is that the stack really has to include the processes and people around the data as well is all well and good changing the technology. But if you don't modernize how people use that technology, then you're not going to be able to, to scale because just cuz you can scale CPU and storage doesn't mean you can get more people to use your data, to generate you more, more value for the business. And so what we've been looking at is really changing in very much aligned to data products and, and data mesh. How do you enable more people to consume the service and have the stack respond in a way that keeps costs low? Because that's important for our customers consuming this data, but also allows people to occasionally run enormous queries and then tick along with smaller ones when required. And it's a good job we did because during COVID all of a sudden we had enormous pressures on our data platform to answer really important life threatening queries. And if we couldn't scale both our data stack and our teams, we wouldn't have been able to answer those as quickly as we had. So I think the stack needs to support a scalable business, not just the technology itself. >>Well thank you for that. So Justin let's, let's try to break down what the critical aspects are of the modern data stack. So you think about the past, you know, five, seven years cloud obviously has given a different pricing model. De-risked experimentation, you know that we talked about the ability to scale up scale down, but it's, I'm, I'm taking away that that's not enough based on what Richard just said. The modern data stack has to serve the business and enable the business to build data products. I, I buy that. I'm a big fan of the data mesh concepts, even though we're early days. So what are the critical aspects if you had to think about, you know, paying, maybe putting some guardrails and definitions around the modern data stack, what does that look like? What are some of the attributes and, and principles there >>Of, of how it should look like or, or how >>It's yeah. What it should be. >>Yeah. Yeah. Well, I think, you know, in, in Theresa mentioned this in, in a previous segment about the data warehouse is not necessarily going to disappear. It just becomes one node, one element of the overall data mesh. And I, I certainly agree with that. So by no means, are we suggesting that, you know, snowflake or Redshift or whatever cloud data warehouse you may be using is going to disappear, but it's, it's not going to become the end all be all. It's not the, the central single source of truth. And I think that's the paradigm shift that needs to occur. And I think it's also worth noting that those who were the early adopters of the modern data stack were primarily digital, native born in the cloud young companies who had the benefit of, of idealism. They had the benefit of it was starting with a clean slate that does not reflect the vast majority of enterprises. >>And even those companies, as they grow up mature out of that ideal state, they go buy a business. Now they've got something on another cloud provider that has a different data stack and they have to deal with that heterogeneity that is just change and change is a part of life. And so I think there is an element here that is almost philosophical. It's like, do you believe in an absolute ideal where I can just fit everything into one place or do I believe in reality? And I think the far more pragmatic approach is really what data mesh represents. So to answer your question directly, I think it's adding, you know, the ability to access data that lives outside of the data warehouse, maybe living in open data formats in a data lake or accessing operational systems as well. Maybe you want to directly access data that lives in an Oracle database or a Mongo database or, or what have you. So creating that flexibility to really Futureproof yourself from the inevitable change that you will, you won't encounter over time. >>So thank you. So there, based on what Justin just said, I, my takeaway there is it's inclusive, whether it's a data Mar data hub, data lake data warehouse, it's a, just a node on the mesh. Okay. I get that. Does that include there on Preem data? O obviously it has to, what are you seeing in terms of the ability to, to take that data mesh concept on Preem? I mean, most implementations I've seen in data mesh, frankly really aren't, you know, adhering to the philosophy. They're maybe, maybe it's data lake and maybe it's using glue. You look at what JPMC is doing. Hello, fresh, a lot of stuff happening on the AWS cloud in that, you know, closed stack, if you will. What's the answer to that Theresa? >>I mean, I, I think it's a killer case for data. Me, the fact that you have valuable data sources, OnPrem, and then yet you still wanna modernize and take the best of cloud cloud is still, like we mentioned, there's a lot of great reasons for it around the economics and the way ability to tap into the innovation that the cloud providers are giving around data and AI architecture. It's an easy button. So the mesh allows you to have the best of both worlds. You can start using the data products on-prem or in the existing systems that are working already. It's meaningful for the business. At the same time, you can modernize the ones that make business sense because it needs better performance. It needs, you know, something that is, is cheaper or, or maybe just tap into better analytics to get better insights, right? So you're gonna be able to stretch and really have the best of both worlds. That, again, going back to Richard's point, that is meaningful by the business. Not everything has to have that one size fits all set a tool. >>Okay. Thank you. So Richard, you know, talking about data as product, wonder if we could give us your perspectives here, what are the advantages of treating data as a product? What, what role do data products have in the modern data stack? We talk about monetizing data. What are your thoughts on data products? >>So for us, one of the most important data products that we've been creating is taking data that is healthcare data across a wide variety of different settings. So information about patients' demographics about their, their treatment, about their medications and so on, and taking that into a standards format that can be utilized by a wide variety of different researchers because misinterpreting that data or having the data not presented in the way that the user is expecting means that you generate the wrong insight. And in any business, that's clearly not a desirable outcome, but when that insight is so critical, as it might be in healthcare or some security settings, you really have to have gone to the trouble of understanding the data, presenting it in a format that everyone can clearly agree on. And then letting people consume in a very structured, managed way, even if that data comes from a variety of different sources in, in, in the first place. And so our data product journey has really begun by standardizing data across a number of different silos through the data mesh. So we can present out both internally and through the right governance externally to, to researchers. >>So that data product through whatever APIs is, is accessible, it's discoverable, but it's obviously gotta be governed as well. You mentioned you, you appropriately provided to internally. Yeah. But also, you know, external folks as well. So the, so you've, you've architected that capability today >>We have, and because the data is standard, it can generate value much more quickly and we can be sure of the security and, and, and value that that's providing because the data product isn't just about formatting the data into the correct tables, it's understanding what it means to redact the data or to remove certain rows from it or to interpret what a date actually means. Is it the start of the contract or the start of the treatment or the date of birth of a patient? These things can be lost in the data storage without having the proper product management around the data to say in a very clear business context, what does this data mean? And what does it mean to process this data for a particular use case? >>Yeah, it makes sense. It's got the context. If the, if the domains own the data, you, you gotta cut through a lot of the, the, the centralized teams, the technical teams that, that data agnostic, they don't really have that context. All right. Let's send Justin, how does Starburst fit into this modern data stack? Bring us home. >>Yeah. So I think for us, it's really providing our customers with, you know, the flexibility to operate and analyze data that lives in a wide variety of different systems. Ultimately giving them that optionality, you know, and optionality provides the ability to reduce costs, store more in a data lake rather than data warehouse. It provides the ability for the fastest time to insight to access the data directly where it lives. And ultimately with this concept of data products that we've now, you know, incorporated into our offering as well, you can really create and, and curate, you know, data as a product to be shared and consumed. So we're trying to help enable the data mesh, you know, model and make that an appropriate compliment to, you know, the, the, the modern data stack that people have today. >>Excellent. Hey, I wanna thank Justin Theresa and Richard for joining us today. You guys are great. I big believers in the, in the data mesh concept, and I think, you know, we're seeing the future of data architecture. So thank you. Now, remember, all these conversations are gonna be available on the cube.net for on-demand viewing. You can also go to starburst.io. They have some great content on the website and they host some really thought provoking interviews and, and, and they have awesome resources, lots of data mesh conversations over there, and really good stuff in, in the resource section. So check that out. Thanks for watching the data doesn't lie or does it made possible by Starburst data? This is Dave Valante for the cube, and we'll see you next time. >>The explosion of data sources has forced organizations to modernize their systems and architecture and come to terms with one size does not fit all for data management today. Your teams are constantly moving and copying data, which requires time management. And in some cases, double paying for compute resources. Instead, what if you could access all your data anywhere using the BI tools and SQL skills your users already have. 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>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting costs could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data, Mars, data hubs, and yes, even data lakes were broken and left us wanting for more welcome to the data doesn't lie, or does it a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have feature parody with the data lake or vice versa is the so-called modern data stack simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for IDU that was acquired by Teradata. And when I got to Teradata, of course, Terada is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on-prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience, Joe? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know? Right. But you actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like swans Oxley, for things like security, for certain very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited JAK, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come, I think that's the story of Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenets of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about, so Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and con contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but the, what does that mean? Does that mean the ed w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's gonna be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems. Maybe either those that either source systems, the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to lose all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got, you know, the domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue or two, you know, challenges self-serve infrastructure let's park that for a second. And then in your industry, one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And, and I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at EMI is we have a single security layer that sits on top of our data mesh, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. >>And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin mean Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, doing analytic queries and with data, that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah, I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively, almost eCommerce, like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself. >>Okay. G guys grab a sip of water. After the short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence. Keep it right there.

>> We're back at the Big Apple, theCUBE's coverage of MongoDB World 2022. Sahir Azam is here, he's the Chief Product Officer of MongoDB, and Guillermo Rauch who's the CEO of Vercel. Hot off the keynotes from this morning guys, good job. >> Thank you. >> Thank you. >> Thank you for joining us here. Thanks for having us. Guillermo when it comes to modern web development, you know the back-end, the cloud guys got to it kind of sewn up, >> you know- >> Guillermo: Forget about it. >> But all the action's in the front end, and that's where you are. Explain Vercel. >> Yeah so Vercel is the company that pioneers front-end development as serverless infrastructure. So we built Next.js which is the most popular React framework in the world. This is what front-end engineers choose to build innovative UI's, beautiful websites. Companies like Dior and GitHub and TikTok and Twitch, which we mentioned in the keynote, are powering their entire dot-coms or all of their new parts of their dot-coms with Next.js. And Vercel is the serverless platform where you can deploy frameworks like in Next.js and others like Svelte and Vue to create really fast experiences on the web. >> So I hear, so serverless, I hear that's the hot trend. You guys made some announcements today. I mean when you look at the, we have spending data with our friends at ETR right down the street. I mean it's just off the charts, whether it's Amazon, Google, Azure Functions, I mean it's just exploding. >> Sahir: Yeah, it's I think in many ways, it's a natural trend. You know, we talk a lot about, whether it be today's keynote or another industry talks you see around our industry that developers are constantly looking for ways to focus on innovation and the business logic that defines their application and as opposed to managing the plumbing, and management of infrastructure. And we've seen this happen over and over again across every layer of the stack. And so for us, you know MongoDB, we have a bit of, you know sort of a lens of a broad spectrum of the market. We certainly have you know, large enterprises that are modernizing existing kind of core systems, then we have developers all over the world who are building the next big best thing. And that's what led us to partner with Vercel is just the bleeding edge of developers building in a new way, in a much more efficient way. And we wanted to make sure we provide a data platform that fits naturally in the way they want to work. >> So explain to our audience the trade-offs of serverless, and I want to get into sort of how you've resolved that. And then I want to hear from Guillermo, what that means for developers. >> Sahir: Yeah in our case, we don't view it as an either or, there are certain workloads and definitely certain companies that will gravitate towards a more traditional database infrastructure where they're choosing the configuration of their cluster. They want full control over it. And that provides, you know, certain benefits around cost predictability or isolation or perceived benefits at least of those things. And customers will gravitate towards that. Now on the flip side, if you're building a new application or you want the ability to scale seamlessly and not have to worry about any of the plumbing, serverless is clearly the easier model. So over the long term, we certainly expect to see as a mix of things, more and more serverless workloads being built on our platform and just generally in the industry, which is why we leaned in so heavily on investing in Atlas serverless. But the flexibility to not be forced into a particular model, but to get the same database experience across your application and even switch between them is an important characteristic for us as we build going forward. >> And you stressed the cost efficiency, and not having to worry about, you know, starting cold. You've architected around that, and what does that mean for a developer? >> Guillermo: For a developer it means that you kind of get the best of both worlds, right? Like you get the best possible performance. Front-end developers are extremely sensitive to this. That's why us pioneering this concept, serverless front-end, has put us in a very privileged position because we have to deliver that really quick time to first buy, that really quick paint. So any of the old trade-offs of serverless are not accepted by the market. You have to be extremely fast. You have to be instant to deliver that front-end content. So what we talked about today for example, with the Vercel Edge network, we're removing all of the cost of that like first hit. That cold start doesn't really exist. And now we're seeing it all across the board, going into the back-end where Mongo has also gotten rid of it. >> Dave: How do you guys collaborate? What's the focus of integration specifically from, you know, an engineering resource standpoint? >> Yeah the main idea is, idea to global app in seconds, right? You have your idea. We give you the framework. We don't give you infrastructure primitives. We give you all the necessary tools to start your application. In practice this means you host it in a Git repo. You import it onto Vercel. You install the Mongo integration. Now your front-end and your data back-end are connected. And then your application just goes global in seconds. >> So, okay. So you've abstracted away the complexity of those primitives, is that correct? >> Guillermo: Absolutely. >> Do do developers ever say, "That's awesome but I'd like to get to them every now and then." Or do you not allow that? >> Definitely. We expose all the underlying APIs, and the key thing we hear is that, especially with the push for usage-based billing models, observability is of the essence. So at any time you have to be able to query, in real time, every data point that the platform is observing. We give you performance analytics in real time to see how your front-end is performing. We give you statistics about how often you're querying your back-end and so on, and your cache hit ratios. So what I talked about today in the keynote is, it's not just about throwing more compute at the problem, but the ability to use the edge to your advantage to memoize computation and reuse it across different visits. >> When we think of mission critical historically, you know, you think about going to the ATM, right? I mean a financial transaction. But Mongo is positioning for mission critical applications across a variety of industries. Do we need to rethink what mission critical means? >> I think it's all in the eye of the beholder so to speak. If you're a new business starting up, your software and your application is your entire business. So if you have a cold start latency or God forbid something actually goes down, you don't have a business. So it's just as mission critical to that founder of a new business and new technology as it is, you know, an established enterprise that's running sort of a more, you know, day-to-day application that we may all interact with. So we treat all of those scenarios with equal fervor and importance right? And many times, it's a lot of those new experiences that the become the day-to-day experiences for us globally, and are super important. And we power all of those, whether it be an established enterprise all the way to the next big startup. >> I often talk about COVID as the forced march to digital. >> Sahir: Mm-Hmm. >> Which was obviously a little bit rushed, but if you weren't in digital business, you were out of business. And so now you're seeing people step back and say, "All right, let's be more thoughtful about our digital transformation. We've got some time, we've obviously learned some things made some mistakes." It's all about the customer experience though. And that becomes mission critical right? What are you seeing Guillermo, in terms of the patterns in digital transformation now that we're sort of exiting the isolation economy? >> One thing that comes to mind is, we're seeing that it's not always predictable how fast you're going to grow in this digital economy. So we have customers in the ecommerce space, they do a drop and they're piggybacking on serverless to give them that ability to instantly scale. And they couldn't even prepare for some of these events. We see that a lot with the Web3 space and NFT drops, where they're building in such a way that they're not sensitive to this massive fluctuations in traffic. They're taking it for granted. We've put in so much work together behind the scenes to support it. But the digital native creator just, "Oh things are scaling from one second to the next like I'm hitting like 20,000 requests per second, no problem Vercel is handling it." But the amount of infrastructural work that's gone behind the scenes in support has been incredible. >> We see that in gaming all the time, you know it's really hard for a gaming company to necessarily predict where in the globe a game's going to be particularly hot. Games get super popular super fast if they're successful, it's really hard to predict. It's another vertical that's got a similar dynamic. >> So gaming, crypto, so you're saying that you're able to assist your customers in architecting so that the website doesn't crash. >> Guillermo: Absolutely. >> But at the same time, if the the business dynamic changes, they can dial down. >> Yeah. >> Right and in many ways, slow is the new down, right? And if somebody has a slow experience they're going to leave your site just as much as if it's- >> I'm out of here- >> You were down. So you know, it's really maintaining that really fast performance, that amazing customer experience. Because this is all measured, it's scientific. Like anytime there's friction in the process, you're going to lose customers. >> So obviously people are excited about your keynote, but what have they been saying? Any specific comments you can share, or questions that you got that were really interesting or? >> I'm already getting links to the apps that people are deploying. So the whole idea- >> Come on! >> All over the world. Yeah so it's already working I'm excited. >> So they were show they were showing off, "Look what I did" Really? >> Yeah on Twitter. >> That's amazing. >> I think from my standpoint, I got a question earlier, we were with a bunch of financial analysts and investors, and they said they've been talking to a lot of the customers in the halls. And just to see, you know, from the last time we were all in person, the number of our customers that are using multiple capabilities across this idea of a developer data platform, you know, certainly MongoDB's been a popular core database open source for a long time. But the new capabilities around search, analytics, mobile being adopted much more broadly to power these experiences is the most exciting thing from our side. >> So from 2019 to now, you're saying substantial uptick in adoption for these features? >> Yeah. And many of them are new. >> Time series as well, that's pretty new, so yeah. >> Yeah and you know, our philosophy of development at MongoDB is to get capabilities in the hands of customers early. Get that feedback to enrich and drive that product-market fit. And over the last three years especially, we've been transitioning from a single product kind of core, you know, non relational modern database to a data platform, a developer data platform that adds more and more capabilities to power these modern applications. And a lot of those were released during the pandemic. Certainly we talked about them in our virtual conferences and all the zoom meetings we had over the years. But to actually go talk to all these customers, this is the largest conference we've ever put on, and to get a sense of, wow all the amazing things they're doing with them, it's definitely a different feeling when we're all together. >> So that's interesting, when you have such a hot product, product-led growth which is what Mongo has been in, and you add these new features. They're coming from the developers who are saying, "Hey, we need this." >> Yip. >> Okay so you have a pretty high degree of confidence, but how do you know when you have product-market fit? I mean, is it adoption, usage, renewals? What's your metric? >> Yeah I think it's a mix of quantitative measures that you know, around conversion rates, the size of your funnel, the retention rate, NPS which obviously can be measured, but also just qualitative. You know when you're talking to a developer or a technology executive around what their needs are, and then you see how they actually apply it to solve a problem, it's that balance between the qualitative and the quantitative measurement of things. And you can just sort of, frankly you can feel it. You can see it in the numbers sure, but you can kind of feel that excitement, you can see that adoption and what it empowers people to do. And so to me, as a product leader, it's always a blend of those things. If you get too obsessed with purely the metrics, you can always over optimize something for the wrong reason. So you have to bring in that qualitative feedback to balance yourself out. >> Right. >> Guillermo, what's next? What do you not have that you want from Sahir and Mongo? >> So the natural next step for serverless computing is, is the Edge. So we have to auto-scale, we have to tolerate fares. We have to be avail. We have to be easy, but we have to be global. And right now we've been doing this by using a lot of techniques like caching and replication and things like this. But the future's about personalizing even more to each visitor depending on where they are. So if I'm in New York, I want to get the latest offers for New York on demand, just for me, and using AI to continue to personalize that experience. So giving the developer these tools in a way where it feels natural to build an application like this. It doesn't feel like, "Oh I'm going to do this year 10 if I make it, I'm going to do it since the very beginning." >> Dave: Okay interesting. So that says to me that I'm not going to make a round trip to the cloud necessarily for that experience. So I'm going to have some kind, Apple today, at the Worldwide Developer Conference announced the M2, right. I've been looking at the M1 Ultra, and I'm going wow look at that! And so- >> Sahir: You were talking about that new one backstage. >> I mean it's this amazing pace of Silicon development and they're focusing on the NPU and you look at what Tesla's doing. I mean it's just incredible. So you're going to have some new hardware architecture that emerges. Most of the AI that's done today is modeling in the cloud. You're going to have a real time inferencing at the Edge. So that's not going to do the round trip. There's going to be a data store there, I think it has to be. You're going to persist some of the data, maybe not all of it. So it's a whole new architecture- >> Sahir: Absolutely. >> That's developing. That sounds very disruptive. >> Sahir: Yeah. >> How do you think about that, and how does Mongo play there? Guillermo first. >> What I spent a lot of time thinking about is obviously the developer experience, giving the programmer a programming model that is natural, intuitive, and produces its great results. So if they have to think about data that's local because of regulatory reasons for example, how can we let the framework guide them to success? I'm just writing an application I deployed to the cloud and then everything else is figured out. >> Yeah or speed of light is another challenge. (Sahir and Guillermo laugh) >> How can we overcome the speed of light is our next task for sure. >> Well you're working on that aren't you? You've got the best engineers on that one. (Sahir and Guillermo laugh) >> We can solve a lot of problems, I'm not sure of that one. >> So Mongo plays in that scenario or? >> Yeah so I think, absolutely you know, we've been focused heavily on becoming the globally distributed cloud data layer. The back-end data layer that allows you to persist data to align with performance and move data where it needs to be globally or deal with data sovereignty, data nationalism that's starting to rise, but absolutely there is more data being pushed out to the Edge, to your point around processing or inference happening at the Edge. And there's going to be a globally distributed front-end layer as well, whether data and processing takes apart. And so we're focused on one, making sure the data connectivity and the layer is all connected into one unified architecture. We do that in combination with technologies that we have that do with mobility or edge distribution and synchronization of data with realm. And we do it with partnerships. We have edge partnerships with AWS and Verizon. We have partnerships with a lot of CVM players who are building out that Edge platform and making sure that MongoDB is either connected to it or just driving that synchronization back and forth. >> I call that unified experience super cloud, Robbie Belson from Verizon the cloud continuum, but that consistent experience for developers whether you're on Prim, whether you're in you know, Azure, Google, AWS, and ultimately the Edge. That's the big- >> That's where it's going. >> White space right now I'm hearing, Guillermo, right? >> I think it'll define the next generation of how software is built. And we're seeing this almost like a coalition course between some of the ideas that the Web3 developers are excited about, which is like decentralization almost to the extreme. But the Web2 also needs more decentralization, because we're seeing it with like, the data needs to be local to me, I need more privacy. I was looking at the latest encryption features in Mongo, like I think both Web2 need to incorporate more of the ideas of Web3 and vice versa to create the best possible consumer experience. Privacy matters more than ever before. Latency for conversion matters more than ever before. And regulations are changing. >> Sahir: Yeah. >> And you talked about Web3 earlier, talked about new protocols, a new distributed you know, decentralized system emerging, new hardware architectures. I really believe we really think that new economics are going to bleed back into the data center, and yeah every 15 years or so this industry gets disrupted. >> Sahir: Yeah. >> Guillermo: Absolutely. >> You know you ain't see nothing yet guys. >> We all talked about hardware becoming commoditized 10, 15 years ago- >> Yeah of course. >> We get the virtualization, and it's like nope not at all. It's actually a lot of invention happening. >> The lower the price the more the consumption. So guys thanks so much. Great conversation. >> Thank you. >> Really appreciate your time. >> Really appreciate it I enjoyed the conversation. >> All right and thanks for watching. Keep it right there. We'll be back with our next segment right after this short break. Dave Vellante for theCUBE's coverage of MongoDB World 2022. >> Man Offscreen: Clear. (clapping) >> All right wow. Don't get up. >> Sahir: Okay. >> Is that a Moonwatch? >> Sahir: It is a Speedmaster but it's that the-

>> Man Offscreen: Standby. Dave is coming you in 5, 4, 3, 2. >> We're back at the Big Apple, theCUBE's coverage of MongoDB World 2022. Sahir Azam is here, he's the Chief Product Officer of MongoDB, and Guillermo Rauch who's the CEO of Vercel. Hot off the keynotes from this morning guys, good job. >> Thank you. >> Thank you. >> Thank you for joining us here. Thanks for having us. Guillermo when it comes to modern web development, you know the back-end, the cloud guys got to it kind of sewn up, >> you know- >> Guillermo: Forget about it. >> But all the action's in the front end, and that's where you are. Explain Vercel. >> Yeah so Vercel is the company that pioneers front-end development as serverless infrastructure. So we built Next.js which is the most popular React framework in the world. This is what front-end engineers choose to build innovative UI's, beautiful websites. Companies like Dior and GitHub and TikTok and Twitch, which we mentioned in the keynote, are powering their entire dot-coms or all of their new parts of their dot-coms with Next.js. And Vercel is the serverless platform where you can deploy frameworks like in Next.js and others like Svelte and Vue to create really fast experiences on the web. >> So I hear, so serverless, I hear that's the hot trend. You guys made some announcements today. I mean when you look at the, we have spending data with our friends at ETR right down the street. I mean it's just off the charts, whether it's Amazon, Google, Azure Functions, I mean it's just exploding. >> Sahir: Yeah, it's I think in many ways, it's a natural trend. You know, we talk a lot about, whether it be today's keynote or another industry talks you see around our industry that developers are constantly looking for ways to focus on innovation and the business logic that defines their application and as opposed to managing the plumbing, and management of infrastructure. And we've seen this happen over and over again across every layer of the stack. And so for us, you know MongoDB, we have a bit of, you know sort of a lens of a broad spectrum of the market. We certainly have you know, large enterprises that are modernizing existing kind of core systems, then we have developers all over the world who are building the next big best thing. And that's what led us to partner with Vercel is just the bleeding edge of developers building in a new way, in a much more efficient way. And we wanted to make sure we provide a data platform that fits naturally in the way they want to work. >> So explain to our audience the trade-offs of serverless, and I want to get into sort of how you've resolved that. And then I want to hear from Guillermo, what that means for developers. >> Sahir: Yeah in our case, we don't view it as an either or, there are certain workloads and definitely certain companies that will gravitate towards a more traditional database infrastructure where they're choosing the configuration of their cluster. They want full control over it. And that provides, you know, certain benefits around cost predictability or isolation or perceived benefits at least of those things. And customers will gravitate towards that. Now on the flip side, if you're building a new application or you want the ability to scale seamlessly and not have to worry about any of the plumbing, serverless is clearly the easier model. So over the long term, we certainly expect to see as a mix of things, more and more serverless workloads being built on our platform and just generally in the industry, which is why we leaned in so heavily on investing in Atlas serverless. But the flexibility to not be forced into a particular model, but to get the same database experience across your application and even switch between them is an important characteristic for us as we build going forward. >> And you stressed the cost efficiency, and not having to worry about, you know, starting cold. You've architected around that, and what does that mean for a developer? >> Guillermo: For a developer it means that you kind of get the best of both worlds, right? Like you get the best possible performance. Front-end developers are extremely sensitive to this. That's why us pioneering this concept, serverless front-end, has put us in a very privileged position because we have to deliver that really quick time to first buy, that really quick paint. So any of the old trade-offs of serverless are not accepted by the market. You have to be extremely fast. You have to be instant to deliver that front-end content. So what we talked about today for example, with the Vercel Edge network, we're removing all of the cost of that like first hit. That cold start doesn't really exist. And now we're seeing it all across the board, going into the back-end where Mongo has also gotten rid of it. >> Dave: How do you guys collaborate? What's the focus of integration specifically from, you know, an engineering resource standpoint? >> Yeah the main idea is, idea to global app in seconds, right? You have your idea. We give you the framework. We don't give you infrastructure primitives. We give you all the necessary tools to start your application. In practice this means you host it in a Git repo. You import it onto Vercel. You install the Mongo integration. Now your front-end and your data back-end are connected. And then your application just goes global in seconds. >> So, okay. So you've abstracted away the complexity of those primitives, is that correct? >> Guillermo: Absolutely. >> Do do developers ever say, "That's awesome but I'd like to get to them every now and then." Or do you not allow that? >> Definitely. We expose all the underlying APIs, and the key thing we hear is that, especially with the push for usage-based billing models, observability is of the essence. So at any time you have to be able to query, in real time, every data point that the platform is observing. We give you performance analytics in real time to see how your front-end is performing. We give you statistics about how often you're querying your back-end and so on, and your cache hit ratios. So what I talked about today in the keynote is, it's not just about throwing more compute at the problem, but the ability to use the edge to your advantage to memoize computation and reuse it across different visits. >> When we think of mission critical historically, you know, you think about going to the ATM, right? I mean a financial transaction. But Mongo is positioning for mission critical applications across a variety of industries. Do we need to rethink what mission critical means? >> I think it's all in the eye of the beholder so to speak. If you're a new business starting up, your software and your application is your entire business. So if you have a cold start latency or God forbid something actually goes down, you don't have a business. So it's just as mission critical to that founder of a new business and new technology as it is, you know, an established enterprise that's running sort of a more, you know, day-to-day application that we may all interact with. So we treat all of those scenarios with equal fervor and importance right? And many times, it's a lot of those new experiences that the become the day-to-day experiences for us globally, and are super important. And we power all of those, whether it be an established enterprise all the way to the next big startup. >> I often talk about COVID as the forced march to digital. >> Sahir: Mm-Hmm. >> Which was obviously a little bit rushed, but if you weren't in digital business, you were out of business. And so now you're seeing people step back and say, "All right, let's be more thoughtful about our digital transformation. We've got some time, we've obviously learned some things made some mistakes." It's all about the customer experience though. And that becomes mission critical right? What are you seeing Guillermo, in terms of the patterns in digital transformation now that we're sort of exiting the isolation economy? >> One thing that comes to mind is, we're seeing that it's not always predictable how fast you're going to grow in this digital economy. So we have customers in the ecommerce space, they do a drop and they're piggybacking on serverless to give them that ability to instantly scale. And they couldn't even prepare for some of these events. We see that a lot with the Web3 space and NFT drops, where they're building in such a way that they're not sensitive to this massive fluctuations in traffic. They're taking it for granted. We've put in so much work together behind the scenes to support it. But the digital native creator just, "Oh things are scaling from one second to the next like I'm hitting like 20,000 requests per second, no problem Vercel is handling it." But the amount of infrastructural work that's gone behind the scenes in support has been incredible. >> We see that in gaming all the time, you know it's really hard for a gaming company to necessarily predict where in the globe a game's going to be particularly hot. Games get super popular super fast if they're successful, it's really hard to predict. It's another vertical that's got a similar dynamic. >> So gaming, crypto, so you're saying that you're able to assist your customers in architecting so that the website doesn't crash. >> Guillermo: Absolutely. >> But at the same time, if the the business dynamic changes, they can dial down. >> Yeah. >> Right and in many ways, slow is the new down, right? And if somebody has a slow experience they're going to leave your site just as much as if it's- >> I'm out of here- >> You were down. So you know, it's really maintaining that really fast performance, that amazing customer experience. Because this is all measured, it's scientific. Like anytime there's friction in the process, you're going to lose customers. >> So obviously people are excited about your keynote, but what have they been saying? Any specific comments you can share, or questions that you got that were really interesting or? >> I'm already getting links to the apps that people are deploying. So the whole idea- >> Come on! >> All over the world. Yeah so it's already working I'm excited. >> So they were show they were showing off, "Look what I did" Really? >> Yeah on Twitter. >> That's amazing. >> I think from my standpoint, I got a question earlier, we were with a bunch of financial analysts and investors, and they said they've been talking to a lot of the customers in the halls. And just to see, you know, from the last time we were all in person, the number of our customers that are using multiple capabilities across this idea of a developer data platform, you know, certainly MongoDB's been a popular core database open source for a long time. But the new capabilities around search, analytics, mobile being adopted much more broadly to power these experiences is the most exciting thing from our side. >> So from 2019 to now, you're saying substantial uptick in adoption for these features? >> Yeah. And many of them are new. >> Time series as well, that's pretty new, so yeah. >> Yeah and you know, our philosophy of development at MongoDB is to get capabilities in the hands of customers early. Get that feedback to enrich and drive that product-market fit. And over the last three years especially, we've been transitioning from a single product kind of core, you know, non relational modern database to a data platform, a developer data platform that adds more and more capabilities to power these modern applications. And a lot of those were released during the pandemic. Certainly we talked about them in our virtual conferences and all the zoom meetings we had over the years. But to actually go talk to all these customers, this is the largest conference we've ever put on, and to get a sense of, wow all the amazing things they're doing with them, it's definitely a different feeling when we're all together. >> So that's interesting, when you have such a hot product, product-led growth which is what Mongo has been in, and you add these new features. They're coming from the developers who are saying, "Hey, we need this." >> Yip. >> Okay so you have a pretty high degree of confidence, but how do you know when you have product-market fit? I mean, is it adoption, usage, renewals? What's your metric? >> Yeah I think it's a mix of quantitative measures that you know, around conversion rates, the size of your funnel, the retention rate, NPS which obviously can be measured, but also just qualitative. You know when you're talking to a developer or a technology executive around what their needs are, and then you see how they actually apply it to solve a problem, it's that balance between the qualitative and the quantitative measurement of things. And you can just sort of, frankly you can feel it. You can see it in the numbers sure, but you can kind of feel that excitement, you can see that adoption and what it empowers people to do. And so to me, as a product leader, it's always a blend of those things. If you get too obsessed with purely the metrics, you can always over optimize something for the wrong reason. So you have to bring in that qualitative feedback to balance yourself out. >> Right. >> Guillermo, what's next? What do you not have that you want from Sahir and Mongo? >> So the natural next step for serverless computing is, is the Edge. So we have to auto-scale, we have to tolerate fares. We have to be avail. We have to be easy, but we have to be global. And right now we've been doing this by using a lot of techniques like caching and replication and things like this. But the future's about personalizing even more to each visitor depending on where they are. So if I'm in New York, I want to get the latest offers for New York on demand, just for me, and using AI to continue to personalize that experience. So giving the developer these tools in a way where it feels natural to build an application like this. It doesn't feel like, "Oh I'm going to do this year 10 if I make it, I'm going to do it since the very beginning." >> Dave: Okay interesting. So that says to me that I'm not going to make a round trip to the cloud necessarily for that experience. So I'm going to have some kind, Apple today, at the Worldwide Developer Conference announced the M2, right. I've been looking at the M1 Ultra, and I'm going wow look at that! And so- >> Sahir: You were talking about that new one backstage. >> I mean it's this amazing pace of Silicon development and they're focusing on the NPU and you look at what Tesla's doing. I mean it's just incredible. So you're going to have some new hardware architecture that emerges. Most of the AI that's done today is modeling in the cloud. You're going to have a real time inferencing at the Edge. So that's not going to do the round trip. There's going to be a data store there, I think it has to be. You're going to persist some of the data, maybe not all of it. So it's a whole new architecture- >> Sahir: Absolutely. >> That's developing. That sounds very disruptive. >> Sahir: Yeah. >> How do you think about that, and how does Mongo play there? Guillermo first. >> What I spent a lot of time thinking about is obviously the developer experience, giving the programmer a programming model that is natural, intuitive, and produces its great results. So if they have to think about data that's local because of regulatory reasons for example, how can we let the framework guide them to success? I'm just writing an application I deployed to the cloud and then everything else is figured out. >> Yeah or speed of light is another challenge. (Sahir and Guillermo laugh) >> How can we overcome the speed of light is our next task for sure. >> Well you're working on that aren't you? You've got the best engineers on that one. (Sahir and Guillermo laugh) >> We can solve a lot of problems, I'm not sure of that one. >> So Mongo plays in that scenario or? >> Yeah so I think, absolutely you know, we've been focused heavily on becoming the globally distributed cloud data layer. The back-end data layer that allows you to persist data to align with performance and move data where it needs to be globally or deal with data sovereignty, data nationalism that's starting to rise, but absolutely there is more data being pushed out to the Edge, to your point around processing or inference happening at the Edge. And there's going to be a globally distributed front-end layer as well, whether data and processing takes apart. And so we're focused on one, making sure the data connectivity and the layer is all connected into one unified architecture. We do that in combination with technologies that we have that do with mobility or edge distribution and synchronization of data with realm. And we do it with partnerships. We have edge partnerships with AWS and Verizon. We have partnerships with a lot of CVM players who are building out that Edge platform and making sure that MongoDB is either connected to it or just driving that synchronization back and forth. >> I call that unified experience super cloud, Robbie Belson from Verizon the cloud continuum, but that consistent experience for developers whether you're on Prim, whether you're in you know, Azure, Google, AWS, and ultimately the Edge. That's the big- >> That's where it's going. >> White space right now I'm hearing, Guillermo, right? >> I think it'll define the next generation of how software is built. And we're seeing this almost like a coalition course between some of the ideas that the Web3 developers are excited about, which is like decentralization almost to the extreme. But the Web2 also needs more decentralization, because we're seeing it with like, the data needs to be local to me, I need more privacy. I was looking at the latest encryption features in Mongo, like I think both Web2 need to incorporate more of the ideas of Web3 and vice versa to create the best possible consumer experience. Privacy matters more than ever before. Latency for conversion matters more than ever before. And regulations are changing. >> Sahir: Yeah. >> And you talked about Web3 earlier, talked about new protocols, a new distributed you know, decentralized system emerging, new hardware architectures. I really believe we really think that new economics are going to bleed back into the data center, and yeah every 15 years or so this industry gets disrupted. >> Sahir: Yeah. >> Guillermo: Absolutely. >> You know you ain't see nothing yet guys. >> We all talked about hardware becoming commoditized 10, 15 years ago- >> Yeah of course. >> We get the virtualization, and it's like nope not at all. It's actually a lot of invention happening. >> The lower the price the more the consumption. So guys thanks so much. Great conversation. >> Thank you. >> Really appreciate your time. >> Really appreciate it I enjoyed the conversation. >> All right and thanks for watching. Keep it right there. We'll be back with our next segment right after this short break. Dave Vellante for theCUBE's coverage of MongoDB World 2022. >> Man Offscreen: Clear. (clapping) >> All right wow. Don't get up. >> Sahir: Okay. >> Is that a Moonwatch? >> Sahir: It is a Speedmaster but it's that the-

>> "theCUBE," presents Dell Technologies World, brought to you by Dell. >> Hey, welcome back to "theCUBE's" live coverage of Dell Technologies World 2022. Live from the Venetian in Las Vegas, Lisa Martin, Dave Vellante joins me. Dan O'Brien joins us next. The senior vice president of technology solutions at Presidio. Dan, welcome to "theCUBE." >> It's great to be here. Great to be in Vegas too. >> Is it great to be back live in person, three dimensional? >> You have no idea. >> Oh, I know. >> Yeah. >> Just the seeing people again and the vibe here day-one is already fantastic. >> Yeah. >> Talk to us about Presidio and Dell's relationship? What's going on with Presidio? >> Yeah, so I'll tell you just Presidio as as a whole, and part of why I joined about a year ago and I'm still just excited as I was on day one. We're a digital services and solutions provider with deep engineering expertise in networking, cloud, security, collaboration, and modern technologies. And we'll help our customers acquire, deploy, and then operate and manage the solutions that we have. So, we're a Dell titanium black partner. We just got that, we're a super excited about it. And they're a critical part of how we deliver solutions to our customers. >> So, you joined during an interesting time during the pandemic. What are some of the challenges your customers are facing now? Aging infrastructure, labor shortages, supply chain. What do you, what are you seeing from the customers lens? >> Yeah, you know, all of the above. I think when the pandemic first hit, every customer that we spoke with basically said, Cash is king. We want to preserve it, we don't know what the future holds. So, all of the spend that happened was on the things that drove their business forward. So, I got a distributed workforce. How do I go invest in technology to make them productive? A lot of them had to take a digital agenda that was five years long and do it in three months to survive, so they spent it and that generally meant cloud. But what they didn't spend money on, was infrastructure inside the data center. And now what they're finding, is things are old, maintenance bills are going up, the cost to get it is going up. And sometimes supply chain is over 12 months long to be able to actually do something about it. >> You know, when "theCUBE" first started in 2010, it was EFC World 2010 now, 'cause Dell is really our legacy here. So, we said that companies that sell, it's kind of a pejorative, but sell boxes are going to be in trouble because of the cloud. Interesting, right? So, it was partly true because the cloud just intermediated a lot of that sort of box selling business. We said they have to become more value added players, identify. And so, when I watched Presidio, the transformation that you guys went through, and you're relatively new. Cloud has actually become an opportunity. And you're doing stuff around digital, a lot of stuff around security. It's cyber, probably automation, life cycle management. >> True. >> Talk about that transformation? And I'm interested in why you joined Presidio? >> So, I'll tell you why I joined Presidio, is I was talking to a lot of customers every day in my old role, I love doing that part. And the conversation started with, "Dan, I can't spend money on my data center right now because we're in a pandemic. I've got to innovate faster and the answer is to cloud. I don't know how to actually make my workforce productive because they're all over the place now. And we didn't invest in technology. And now I've got a threat surface with people working everywhere in workloads in different places. I don't know how to approach that." And I looked at what Presidio had built, I'm like, that's exactly what we did. But what's been fun for me, has been the answer to most of our customers is this the end? It's not the public cloud, it's not the private cloud. It's, you need to do both of them really well and have the skills and expertise to leverage 'em for the right application, or workload, or use case. And that's why I'm super excited to be here, 'cause we're really helping our customers in both areas. >> You mentioned security. We've seen a number of announcements today from Dell Technologies with respect to cybersecurity. We know the stats are what they are. It's no longer a matter of, if we're going to get hit by a cyber attack, it's when? Most organizations are going to get hit by 2025. Where is security in the conversation now? How high up in the priority is it? >> I would say it's, we don't have a single customer meeting without having that conversation. And what we're finding, is you look at the stats that say, you know, 30% of companies that have a cyber attack, don't come back from it. 20% pay the ransom, and then they don't even get their data back. So, while we want to stop the attacks, I think you're right on that the answer is, it's not a matter of if, it's a matter of when? But what's great about Dell Technologies, is we have a complete portfolio that can meet any SLA of our customers. It's in backup technology, it's in primary storage, they can do a mutable backups and recoveries everywhere. But what happened this week, where they announced partnerships with the cloud, that's huge because the same resource constraints that customers have in their data centers today, are the same ones you have to deploy infrastructure to be able to make this work and be able to accelerate recovery. So, the partnership and the integration with the public cloud, really gives a great integration point for a lot of our customers. >> At the analyst of the event today, we had a meeting with Jen Felch, the CIO of Dell. And I said to her, you know, our survey data from ETR shows that security now, number one priority, it kind of always was, but it's distance itself from the number two, which is cloud migration. And I asked her, I said, "Obviously, cloud migration is not your number two, 'cause number security number one was number two?" And she said, "Let me help you interpret that data. Because for us, we have the scale, we can do our own cloud essentially." What her interpretation, was what those customers are really saying is modernization. Now, you must see that. Now, of course, you're leaning into cloud. Dell is not defensive really more about cloud, like, hey, we could take advantage of it as well. So, what are you seeing in terms of the changing priorities of IT kind of pre-post pandemic? Is it like a rubber band that goes and then comes back to where it was, or is it kind of permanent? >> I think that the both worlds together are absolutely permanent. And there's no way we're going to go back from one or the other. And then we're always going to have a world where you might lean more into one. To innovate, you might lean more into one for disaster recovery. But I truly think the world and the answer for us and our perspective, has to be both. But you said something to interesting earlier, is the key I think to what customers are doing is you can't just pick up a workload and move it to the cloud, it doesn't solve a problem. You use that term modernize. And we've invested, acquisitions and continued engineering resources that were hiring around modernization because the economics and the true benefit of actually running a workload and running right at the right SLAs and meeting your customer's objectives, aren't going to work right if you're just picking an application up and moving it over there. So, we're really focused there. >> So, Couch Base, just ran a survey. We did a power panel on it with a bunch of database analysts. And it was a survey of 650 CIOs and CTOs. And it was really interesting 'cause it's an IT bias. But they said like 2/3 of the survey base said that IT is responsible for setting the digital transformation strategy of the company. And I went, "Well, I wonder what the business guys say to that. It was sort of a red flag to me. But I wonder what you're seeing 'cause there's obviously you get a difference when you talk to different worlds. So, I guess what is modernization, was kind of one of the big questions that came out of it? And who's driving the agenda? >> So, it really depends upon the customer, right? But the key to what you said, and there was an article that came out. I won't say where it was from, but it really kind of opened my eyes. But the article was titled that, "It's Time To Get Rid of the IT Department." And for someone like me and a lot of customers, that kind of scares people. But the whole underpin of it, was they were studying customers that took IT and actually disparaged, like broke 'em apart and put them into business units. So, it said, it's your turn to wake up every day and figure out what that business unit needs to be successful. Because the answer is, David, it's both, right? You need both parties on board, right? Where, you've got a business stakeholder that clearly knows want to do, understands technology's the answer but you need IT to be able to go make it work and be a true partner, and help go actually make it work. >> It reminds me of when Nicholas Carr wrote that article if you're, you guys are probably too young to remember, "But Does IT Matter?" It was kind of post Y2K, right? And then everybody went crazy. All the CIO was when nuts. And in fact, IT matters more than ever, but it's a different context, as you're saying. A question on things like skill shortages, supply chain, I mean, obviously, top of mind. >> Yeah. >> Are you helping people with that? And if so, how so? >> Yeah, so two ways I would look at this, is when you look at the supply chain, I mean, Intel I think spent a $100 million on standing up new Silicon plants. We won't see a benefit from that from 2025. So, it's real. So, a lot of what we're doing on a supply chain is how can we help a customer reach in and have certain targeted ways to leverage the cloud? Because we can't physically solve for the physics issue. The other part of it, the people shortage. I mean, it's real. I mean, everyone's sitting at home they're pondering whether or not, you know, what they're doing is fulfilling their dreams. Now, geography doesn't matter, you can do a job from anywhere. And technology is the heart of everything. So, the people shortage is real. So, we're finding that our focus on managed services we're essentially allowing our customers to run and deploy things across every technology aspect, is something that we used to have to drive to our customers. And now, we can't get out of a conversation without them asking for it 'cause they just don't have the people- >> Yeah, they're calling you into that need. >> Yeah. >> Can you share that customer example that you think really articulates the value of the Dell Technologies that Presidio is delivering? It's really been able to truly modernize in the last couple of years? >> Yeah, so looking specifically to Dell, I mean, for us, one of the taking technical data out of the data center and modernizing, their HCI portfolio together with VMware, is a complete home run. It takes multiple products, brings it into a single common solution, uses a common tool set for all the operators that are there so you don't need the number of people to run it. But if you do it right, it solves for the portability issue in some of the public cloud options, especially with things like VMC where you can have an on and off-prem and an automation between 'em, so you can pick and choose dynamically. That for us has been a home run in driving modernization strategies. >> From a multi-cloud perspective, it's going to be a big focus of this event the next couple of days. What are you seeing from customers' perspective? They're probably in multi-cloud environments for a variety of reasons, that's going to be persisting. The hyperscalers are all growing. What's going on there? How are you helping customers to manage the multi-cloud environment with just much more simplicity? >> Yeah, so I think there's a couple parts to that, right? I mean, obviously, Dell together with VMware has a great set of technologies to be able to manage the deployment of that. But what we're trying to do, is number one, help a customer determine which workload should be running in which place, right? Understand application dependencies. But as we work through a migration strategy with a lot of our customers, the key part that a lot of people don't realize, is we all think security but the networking is probably the hardest part if you want to have portability in a well running cloud. So, having years and years in network heritage, it's been a great synergy on us kind of moving in that direction to help our cloud customers make sure that the right SLA, the right connectivity, and the right availability to make that world work. >> Yeah, so multicloud, obviously, a big topic of of discussion this morning with Chuck Whitten. And that's another one of those, well, what do you mean by that? I have a sort of a premise I want to test on you, Dan. I've always said, it just comes from talking to customers, multi-cloud is kind of multi-vendor. I got to run some workloads in AWS, I run some On Prem. I run some in Google, some in Azure, and many of them, a handful like the big banks, for instance, they say, "Well we're building our own abstraction layer so we can control the policies, the security." And it seems like that's a direction that the industry generally in Dell specifically is headed. Do you buy that? And what's driving that need? >> Yeah, so I would buy it based on the size of the customer. So, when you take a big bank, a lot of what drives them to go to one cloud or the other, is that the big cloud providers they're innovating constantly. Every day there's a new tool or capability that exists there. And certain ones of them are going to match, a use case that, that large customer has- >> You can't resist? >> So, they're going to end up with multiple clouds, so it makes perfect sense. When you get into smaller customer, they really have to want to be successful. They got to pick one, right? They can't afford the people, and the scale, and the process. So, I think that's... The answer would depend based on the customer. The larger ones, I think they're going to build a full orchestration stack and small customers are going to look for one and someone maybe with managed services to help them augment the skills and staffing to make it work. >> For a while, I haven't heard it much lately, but you'd hear about repatriation, people come to me like, "Dave, you got to look into this repatriation thing." And I did, and I was like, "Eh, I really see, it a little bit, little pockets." But I do see hybrid. I mean, that's very clear. And I do see a lot of people went into the cloud, they didn't have a great experience. And okay, so there's some of that going on. I guess you could call that repatriation. But what are you seeing in terms of both of those? Is repatriation a trend or is it really an hybrid? >> So, I've interesting perspective coming from Dell, right? Where we're a very infrastructure focused in there. I see a little bit of repatriation in like a workload, like virtual desktops where you picked it up and you threw it in the cloud and make your workforce productive. But generally speaking, what we're seeing is not repatriation, which is, "Hey I move things. My cost is out of control, I don't know how to manage it. Can you help me get better controls on cost? Can you help me automate a lot of the things that are running here so I've got better control of cost and we're where things are running in my security posture?" So, it's much more about optimization that we're finding than it is. Let's bring it back. >> So, it's fine tuning the knobs? >> There you go. >> Right? And that seems to be the trend over the next couple of years? >> 110%. Yeah. >> Excellent. >> Have you seen any industries, in particular the last year that you've been with Presidio really leading edge in terms of modernization? >> Yeah. I mean, it's so interesting enough. I mean, I could give you a few examples, right? When we look in our public sector business, a lot of the educational institutions had to invest in new platforms they interact and engage with students. Our financial institutions, believe it or not, continue to innovate. I mean, what people don't realize, is the mainframe still has the transaction where your money lives in the ledger, but all the supporting ecosystem is digitalized and is completely modernized to interact with you. And, of course, retail for us. I mean, retail, they had to change their business model in many cases overnight, not even to survive, but to serve the communities they were working in. >> Yeah, I think one of the things that we've all learned in the last couple of years, is just the access, the e-commerce, the access online. We expect that now in the brick and mortar stores to be able to deliver that connected store, make sure that they have the inventory that I'm looking for with a frictionless experience. >> Yeah, and I tell you my favorite one, is you look at the healthcare industry, and while obviously with loans, and healthcare, and billing, all had to change. But that was really exciting for us, I mean, as consumers, right? Is the fact that we can interact with doctors online at the click of a button now. I mean, that part for us has been super exciting. >> Everything's at the click of the button now. >> Yeah. >> Oh, my gosh. Well, Dan, thank you so much for joining Dave and me on the program today, sharing what's new with Presidio, what you guys are doing together with Dell, and how you're helping companies in every industry to modernize. >> Perfect. I appreciate it. >> Great to have you. >> Likewise. >> Thank you. >> With Dave Vellante, I'm Lisa Martin, and you're watching "theCUBE's" coverage of Dell Technologies World live from the Venetian in Las Vegas. Stick around, and Dave and I will be right back with our next guest. (bright upbeat music)

(upbeat music) >> Hey guys and girls. Welcome back to theCUBE's coverage of Coupa Inspire 2022, from the Cosmopolitan, in bustling Las Vegas. Lisa Martin here, and as I mentioned, day two of our coverage and fresh from the main stage, Raja Hammoud joins me, the Executive Vice President of products at Coupa. Raja, welcome back to theCUBE and happy 10th anniversary at Coupa. >> Oh, thank you, thank you, thank you, and welcome back to Inspire. >> Thank you. It's so great- >> We're so happy you're here. >> It's great to be here. So you're just about coming up on your 10 anniversary with Coupa. You showed some great photos of your time there but you've seen, you've lived the evolution that is this rocket ship that's Coupa. >> Raja: It's been incredible journey. I really couldn't believe at first it's been 10. This is the longest I've ever been anywhere. And I honestly feel more refreshed and excited than even when I joined back in the day 10 years ago. And so much has changed, but also so much has not. >> Lisa: Yeah. >> The size of course. We were like 60 people when I joined, the product development team was one person in, in a product, roughly 12 engineers, and fast forward to the scale that's today, it's phenomenal difference. But what has not changed is the, the core values, how, the hustle, how people love working with each other, how we support customers, how we keep stepping up our game how we believe none of us is as smart as all of us, and the community keeps getting stronger and stronger. It's been, it's been really exciting journey. >> The theme of none of us is as smarter as all of us, I'm not sure if I got that right, but the idea is you feel that when you're talking to Coupa partners, I've had the opportunity to talk with Coupa partners and customers and Coupa folks that, that is not just a value statement, people are living that. >> Raja: Yeah. It's, it's everywhere. In the, in the company walls, outside the company walls, you often see product people in different organizations where, they start living in an ivory tower, they think they know everything, I mean, back to what we were discussing earlier about Barbara, when she talked about, get out of your doors, right? A lot of people can tend to do that. We always, from the beginning, believed in the best ideas are out there and you collaborate with each other. And I truly, truly believe that the success that we have achieved today to our community is in a large, large part, because we believed in that. So like on Monday, we hosted, I can't keep track of the number now, so, so many in-parallel Community Advisory Board meetings, and just talking to the products managers and everybody is buzzing with new ideas. And when we go back, there's so much new innovation that has just been co-created here in this conference, and this keeps going on and on and on. >> Lisa: Yeah. I like how you call it, the Community Advisory Board. I'm still used to hearing CAB as Customer Advisory Board, but what Coupa has built, especially with the launch of the Moonshot, the, the community AI, is, is just that. >> Yes. >> It's a very collaborative community. One of the things that's around here, hashtags everywhere, but #United by the Power of Spend. >> Yes. >> What does that mean to you as the EVP of products, and what do you think that means to the community? >> When I think... What we are doing, we're building this platform that is powering all these businesses out there. And the reality of it is you can only, only do so much when you try to do things alone. When we are doing things together, we are way more successful, we are more profitable, we are more sustainable, we are more efficient. And community.ai from a technology standpoint, is making that happen, because what we are doing is taking AI, applying it to all this 3.3 trillion in data, and then bringing back prescriptions that we give back to each and every customer so that everybody can see where they are, how they up their games, and we connect them with other people like them. Now, people love coming to conferences like this, but even in conferences like this, if you think about it, the people you're going to meet, it's, some people are going to do matchmaking but you are also losing an opportunities of meeting the maximum number of people who've done exactly the thing that you did. But when you have the ability to look at all of that data and you can match make people. So we did that already with, for sourcing professionals. So if you are somebody who source a certain category, we can tell somebody else has done something like this in this geography and we offer you to connect to each other. >> Lisa: Wow. >> So this is incredibly powerful way where we are really uniting the whole community by spend, making everybody truly stronger together. >> Lisa: Matchmaker in, in a sense. >> It is matchmaking. >> But it's, but it's- >> It's Spend matchmaking. >> Spend matchmaking, but it's also the opportunity to unite professionals across sourcing, procurement- >> Raja: Yes. >> ... finance, treasury. >> Raja: Yes. >> To your point, and, and Rob said this in his keynote, and he said it here on theCUBE, you know, we've got to break down these silos. >> Raja: Yes. >> People and companies functioning in silos are not going to be successful. >> Raja: Yes. This has been one of the, probably one of the things that we were talking earlier, what has changed, what hasn't. This is one of the fundamental things that has never changed since I've joined. The vision has been very clear. The execution on it, of how we drive successful business spend management program is by breaking down the silos and this idea of sweet synergy, where in product, you start building these capabilities that helps these professionals in the different organizations to actually connect on the touch points, where, where things really matter. >> Lisa: Sweet synergy, was that thing from a concept perspective, did that come from the community, in terms of Coupa going, this is actually what's happening, this synergy across the BSM suite? >> Yes. So in the very beginning, it was early idea. I would say in the first two Inspires that we did, we hadn't given it actually the name itself, and we used to call it unified capabilities, and it started with the first silos we broke down. The first silos we broke down were procurement and AP. And they didn't even used to talk in the same room or even want to care about each other. So we started building so many capabilities that brought these teams together and little by little the community started to feel that and see the value of that. And then the community started to ask us to go break down more silos. So in the beginning, I would say the, the vision before I even joined, the company was on that trajectory. And the early customers saw that and they championed it and then they drove us to do more. So they came to us and said could you please do what you did here in contract? Could you please do what you did here in sourcing? And I was in a meeting last week, a leadership meeting, and one question was asked to leaders in the services team about what are they hearing about, from the customers, about a particular area. And it was music to our ears when we heard the customers are asking for more synergy, right? So, they even have the name for it and they're asking for more and more, and we have built hundreds of these already, but the reality is there is so much opportunity. >> Lisa: Right. >> The world is siloed, no technology has attempted to do that. And I think that's what's a exciting is to go and forge new grounds and do something very special to unite everyone together. >> You guys talked about the waves. Rob talked about the waves yesterday. You talked about it again this morning. And when I think of Inspired community, as that third wave, I see it on both sides. I see the Inspired community that is the Coupa community, but also what you just talked about, that flywheel of that sort of symbiotic relationship that you guys have with your customers as Coupa in and of itself being in a community inspired by the community that it has built. >> Raja: Yes, it's, it's very, very, it's a circular effect. Like it, we inspire one another, and we strengthen one another, and it's, it's just a beautiful, beautiful thing. One of the special things that we are starting to do is we want to take the whole product experience itself, to be a complete community experience. So anywhere you are going to Coupa, when it makes sense, of course, you are not only looking at your data, you are getting connected with people for that particular thing. So we've done that already for 15 different product areas and we're constantly doing more and more and more and more. You can imagine one day we can, where we can start within the product pages themselves, where we host community experts to talk via video and connect with others. So you bring that whole community experience alive in a product in enterprise software, which has not been done. >> Kind of like creating your own influencer network. >> Yes, yes, yes. And give people their voice and, and, and it becomes exciting. It is very different when you're just working on your own and driving goals, and you have no idea how good that can pass on the world. And then when right then and there, you get to learn that some people have hit that, some people have achieved these goals, you just get excited, "I want to hit that goal too. Who are these people? Connect me with these leaders. Let's have a conversation. How did they do it?" And they start creating best practices together. We even have started places where they collaborate on actual documents and templates, and they put them in the community exchange as a way for people to share with others, even taking templates from the product putting them back into a community exchange. So it is sharing, being enabled on the platform, platform itself. >> Lisa: How did you guys function during the pandemic, the last two years when we couldn't get together? >> Raja: Yeah. >> I know that your customers are really the lifeblood of Coupa and vice versa. >> Raja: Yes. >> But talk to me about some of the things that Coupa did with its customers, you know, by video conferencing, for example, that really helped the evolution and some of the innovations that you announced this morning. >> When we first... when the pandemic first hit I think like we all didn't believe what, what is going on. And there was this, I would call it a beautiful period in a way, despite how horrific that was, and that period was where everyone rose to the occasion, everybody wanted to help one another. Across Coupa everywhere, we started having documents of how can step up and help our customers, help our communities. We started to look at how we get PPE, and get it in the hands of our customers. We have access to suppliers. We started looking at helping suppliers with digital payments to speed things up. So, so many things we started doing as a community to just help each other. And then as we got to the next level, then we started, of course, starting to do things over, over zoom. And the big surprise, was we were incredibly productive. If anything, we were worried about people feeling burnt out. >> Yeah. >> Because they were just in it, completely in it. And it created a lot of new avenues for us because often you go and do these meetings in person. Now you could have a user experience session with a customer very easily, they're available more often than they used to. >> Lisa: Right. >> So we did not miss a beat with the community. We moved into virtual caps. We had the advantage of having them recorded as well, where we could have the global development teams learn and see exactly what the, what the customers are are co-creating together. And our goal lives accelerated, because a lot of these implementations, they used to happen in person, so schedules, they actually got accelerated- >> Lisa: Right. >> ...through that. Now of course, there is nothing that matches to this. You can do it, you can do a lot, but a ton of the collaboration comes from real life dialogue and kind of conversation. So it's that balance between the two that I think will be great. >> Lisa: What are some of the things that you've heard the last few days? You mentioned the Partners Summit and, and the Community Advisory Boards on Monday, yesterday, everything kicked off today. What are some of the things that you've heard in your meetings that really inspire you on say the next 10 years at Coupa? >> Raja: By far, by far, by far, it's a validation of, that what we are doing is, we're absolutely on target with it, and that, we just can do so much more. The silos are massive and there are so so many opportunities that you hear in every different areas that we could be doing this, we could be doing this together. So we can break down more and more silos. And using community.ai is just the tip of the iceberg of what we are, what we are doing. Yes, we created tens and tens of capabilities, helping, helping the community with all of that, but data drives everything. And when you look at that, every single process in every single silo can be informed by the power of data within your own company, and then even better, data across. And, and to the point where we're talking about concepts that customers are really excited about, even thinking about this community, they're customers of each other. And when you are a customer of each other what are the different ways as a community, you can help one another more. So we're talking about community netting as new types of concepts. >> Lisa: Talk to me a little about that. You mentioned the community netting this morning but I didn't quite... Help me understand. >> Raja: It is very simple terms is if, if we are buying from each other and we have to do money movements every time I have to pay you, I have to incur fees and likewise, but since we are part of this community we can manage that relationship. So we just pay the Delta, we net it out. So it, it saves reconciliation times it saves money movement. And these are tip of the icebergs of these very cool things that we're doing together. >> Wow. That's fantastic. Last question for you, as you talk with prospects who are in the early stages, or, or still determining, do we go through like a supply chain digital transformation? I mean, I think of companies that probably haven't now or need to get on the bandwagon. >> Raja: Yeah. >> What are some of the things that you advise to those customers to be able to do what Mick Ebeling talked about this morning and that is, commit and then figure it out? >> Raja: Yes. The number one thing is just make sure you don't do the analysis paralysis. There are just so many opportunities so many opportunities start with a project, get going, and it creates incredible momentum, and then you can move on from one to another, to another, to another, instead of trying to just go for a year or two, trying to look at how the world has changed in that process. And so often you could see that projects pay for themselves within the first month of go life. You do that, you'll create another one. And it's not like you are coming in to do something so new nobody has done. Hundreds and hundreds and thousands as a matter of fact, of other community members have done that. It is proven. So get started with those and then continue. Other things I will be talking to them about is to make sure that they understand the way we work is all about partnerships spread. Often people who haven't worked with us in the enterprise software, they're used to working with vendors. We are not that. We never were that. Like the number one, if we're not going to be real partners, honest, transparent and work with each other, we don't waste each other's time. >> Lisa: Well, Raja, it's been great having you on the program. I've really enjoyed your keynote this morning. Congratulations on your 10 years at Coupa. >> Raja: Thank you. >> I'm excited to see what the next 10 years brings for you. We appreciate your insites and everything that Coupa is doing in partnership with its customers is very evident in an event like this. >> Raja: Thank you. And thank you for coming and covering us as well. We really appreciate it. >> Lisa: It's our pleasure to be here. >> Thank you. >> For Raja Hammoud, I'm Lisa Martin. You're watching theCUBE's coverage, day two of Coupa Inspire 2022, from Las Vegas. (upbeat music)

(upbeat music) >> Hi everybody, this is Dave Vellante. And welcome to this CUBE conversation where we welcome an ESG senior analyst, Bob Laliberte Bob, good to see you. >> Great to see you too. Thanks for having me >> Love it, I love to have the analyst sessions. Set it up. What's your scope, what's your area of expertise? >> So my coverage area right now is networking in its entirety. So that spans everything from enterprise networking, wired, wireless, campus, data center, et cetera. All the way up through telco and, in cloud networking. >> So how do you look at the landscape? One of the big things I think about a lot is how does the shift to cloud migration? How does that affect the existing, network layers? I mean, you got Cisco as the big whale and it's just, it's amazing to me. They still have whatever percent market share they have 60, 65% of the market. Are things, what's happening in the competitive landscape. How is cloud affecting that? >> That's a great question. I think the interesting piece is so many times organizations think about the network as plumbing. But the reality is the it's really important plumbing because as you talk about cloud and things get more distributed, well, guess what connects those distributed locations? It's the network. And so organizations as they've moved to the cloud you've seen a big shift with things like SD-WAN and so forth. How do I get more efficient connectivity up to that cloud? How do I not only enable able better connectivity between my data centers in the cloud, but now all my remote workers in the cloud. And so there's been a lot of big shifts going on that have driven the importance of having not only network, but secure networks. So like I said, cloud is one thing, and you're moving your applications there. But with the pandemic you saw the remote work. Think about the network administrators who we're managing, hey, I've got to control network connections between my data centers, a couple clouds and maybe dozens maybe a hundred remote branches. And now I'm connecting to 10,000 micro branches that I need to ensure that they can connect up to these applications and so forth. Hell of a lot more complex environment today than it used to be for these network teams. When we look at the, what we're seeing, how the networking providers are responding it's by driving comprehensive end-to-end solutions. So unifying, wired, wireless, and WAN. Driving efficiencies there. You're seeing even ThousandEyes for Cisco and things like that. Because they know the Internet's becoming more integral part of the corporate network. So being able to drive those types of things being able to, I think look at how to drive those operational efficiencies through AI and ML. So one of the big shifts we've seen in networking is the transition to cloud-based network management. And obviously that couple of things that helps with, first of all, the operations teams who are working remotely can more easily access it. But once all that data is up in the cloud, it creates a platform to be able to invest in AI/ML, and be able to drive intelligent alerting and even automation. And that's really what's needed because as the environments get more distributed and complex, you need to have that those operational efficiencies that automation, that intelligence to help them. >> How has remote work and hybrid work affected sort of network, spending priorities. Obviously when the pandemic hit you had to accommodate end points. And I always have this theory okay, when people come back to the office and I know it's going to be a different world but, the HQ probably needs some love as well. So has that been a tailwind for the industry? >> Absolutely, that's what we're seeing now. I think when the pandemic first hit, everyone said I've got to ramp up my VPNs. I've got to scale out my concentrators. I've got to add more firewalls in my data center. And then after a while, when they realized this was here to stay, they said, okay we just created that hub-and-spoke network that we just got rid of with SD-WAN. So what are the better solutions we can implement? So now you're seeing them not only implement better networking solutions for the remote workers. But reimagining what the campus looks like. Because it's not going to be ever 100% full or maybe it will, but how, for how many times a year will it be 100% full? So you've got to go from 80% cubes and 20% conference and collaboration areas, to 80% collaboration areas and 20% cubes. So we're seeing a lot of transition taking place in the campus environment as organizations are deploying newer technologies like Wi-Fi 6E. That have greater bandwidth to allow for those collaboration apps to run in those collaboration areas. Instead of just having the single wired conference room for video. Everyone's got to be able to run their video, voice and video collaboration apps. >> So how do you look at the landscape now? Again, you can't talk about networking without talking about Cisco. I think they, up there, I saw you and Zeus as talking about out, Cisco's quarter and other networking topics. Their long term guidance is for 60% growth for a company that size that's really outstanding. I mean, Cisco's, really has always been an execution machine of course. And it's a new era now under Chuck. There are more than ankle biters. If you look at Arista's doing pretty well there's guys like Extreme, there's others that are out there but nobody seemed to be able to unseat Cisco. What's happening in the landscape? >> I mean, that's a great question. Cisco's just been around for so long and been so big for so long. And you have to also keep in mind that with Cisco it's not just about the technology, but the fact from a if you think about it from a cultural standpoint these are workers who have been trained on Cisco since, some of them since high school. The educational component that Cisco has done has groomed generations of network technologists. So when they come into the market, they're fully familiar and used to Cisco. Plus they make a really good product and they've got products that cover everything. They cover the whole gambit. So they're still able to maintain their share. They're able to grow. They're able to move. They've made a shift last year. They announced in last spring that they were going to focus more on end-to-end. So instead of just having, hey, here's a point product, here's a point product. Here's a point product. Let's think about it in its entirety. Let's deliver a complete end-to-end solution solve bigger problems for customers, which obviously makes it much harder to remove when you're just trying to remove a piece of that single problem. But the other competitors are also having good years. And I think also the rising tide floats all boats. And so because of this distributed nature, the importance of the network, everyone is doing that. Plus obviously this has to be said, the supply chain issues where people are ordering ahead as well. But organizations, you look at Arista, they've gone from just being a data center company to expanding all the way down to the campus edge, wireless, right there creating an end-to-end environment Extreme did the same thing. They went out and made a lot of acquisitions. They pulled them all together, integrated. They're all moving to this cloud based end-to-end network management. Arista has been on a tear, bringing in a lot of, not only innovative technology, but innovative technologists. So if you look at some of the organizations they bought. I keep calling it Route 128, it's 128 Technologies. So sorry folks I live in Massachusetts. It's always been Route 128. >> You Remember when don't we. 128 Technology's Mist was their big. Mist was their, Mist was kind of like their VMware. VMware to EMC was Mist was to Juniper. And so we call it the Mistification of Juniper where every organization, every company they bring in they're rolling under that and this the AI engine. So they're bringing in 128 Technologies into that. They've got their own, their own stuff under that, their wired switches. So they've got this unified wired and wireless and WAN assurance now that they have. They've been gaining a lot of traction with that. And again, for the things we were talking about because it's far more distributed and complex. You need to have, It's not like people are getting replaced. It's not like, hey, we're leveraging this automation so that we can get rid of network teams. It's because it's getting so much more complex just to have the same number of people manage that more complex environment. We need those intelligence solutions. >> So I want to ask you about network and multi-cloud. And so it's kind of tongue in cheek because we coined this term super cloud. And so what we meant by that, so here's the premise. And I wonder you could give us your perspective. Multi-cloud, I've said many times is I think largely a symptom of multi-vendor I run in this, I run in AWS or, Azure, I've done the work to understand their primitives and or Google, whatever it is. But it's not like an abstraction layer that's floating above all those but now you're starting to see that. In fact, it re:Invent in November. The ecosystem it seemed like was everybody was focused on developing what we call these super clouds. And again, it's tongue in cheek, this abstraction layer it hides the underlying complexity of the primitives and the APIs adds incremental value on top of that. So there's a company Prosimo, which Steve Herrod, is invested in and others Praveen Akkiraju, whom I'm sure you know from Viptela. Aviatrix is another company that's sort of, Steve Malaney has come on theCUBE and talked about what they're doing. Like yeah, that's super cloud. It seems like it's something new and different than just multi-cloud which is kind of connecting in to different clouds. It's that value on top. What do you think about that? And what does that mean for networking? >> That's a really good point because we are starting to see the inception of organizations going beyond having multiple cloud providers and looking at starting to deploy applications across multiple clouds. It's still really early. The vast majority of organizations are still, I use this application for this cloud and this application for that cloud. But that's the next frontier. That's what they're trying to solve is how do I create this basically cloud fabric and make it as simple as possible. And again, all the things we've been talking about how do I, instead of you having to learn Amazon, Google, Azure networking technology, learn mine, I'll take care of it, but I'll abstract all that complexity from you and make it so much simpler to be able to connect to these interconnect, and connect to them in a seamless fashion. And so that's what they're really trying to do is they're. And the hard part is it takes really sophisticated solutions to remove that high level of complexity and make it simple for an organization to do that. So yeah, absolutely. >> If I had more time I'd make it shorter as somebody who writes a lot. And I think you're right. I think it is future. It's not definitely not here today, but the other thing is it ties into digital transformation. We used this again, throw that buzzword around but, companies not just tech company, I mean everybody's becoming like a tech company, but organizations, financial services companies, healthcare they're building their own clouds on top of the hyperscalers who spend $100 billion a year on CapEx. And that seems to be a trend that I think is going to take legs over this next decade. Just like in the previous decade everybody was thinking, okay, we're going to SaaSify our business softwares (indistinct) the world. And now it's software and cloud services are the way in which I'm going to create customer experiences. >> Correct, yeah. It's why should I go out and make an investment in technology when the technology's already there? And I can rent it for when I need it scale it as I need it and, and do all of that. I agree with that. I think that's something that we're seeing. The interesting part though is that when we look at our data points, probably let than 40% of the applications and workloads are in the cloud today. So there's still a role that the corporate data center plays. We are seeing over time. They expect that to progress and transition but I think there's still always going to be maybe a quarter of the workloads and applications may never leave. Depending on how they're built, et cetera. So there's always going to be that distributed environment where you've got workloads in the private data centers, workloads in multiple public clouds. And also, the big thing too is don't forget about the edge. We're seeing a lot more edge activity take place as organizations recognize, as they deploy more IOT devices, and want to get realtime business insights they've got to deploy the compute there. >> Well, and that's something that I wanted to ask you about, but going back to what you just said, which is, I agree with you. So that suggests to me, Bob that we're just kind of, with cloud just entering the steep part of the S curve. Amazon's headed toward $100 billion, run rate business. Maybe they probably won't get there this year but they will next year. We're entering that steep growth phase, really could be. It's incredible. But I wanted to ask you about the edge. Because you're right is we got to move compute to the edge, ARM is going to dominate. I would think, the edge. They already are with our smartphones. How do you see the cloud guys participating in the edge? Whether it was Andy Jassy, or now Adam Selipsky or anybody at Amazon. They have the dogma of in the fullness of time all workloads are going to be in the cloud. So they either have to change their definition of cloud. Or they're wrong. So what's your thought on that? >> I think it really starts coming down to what's your definition of edge. And so, much like when the cloud technologies first came about and you had all the shadow IT. Everyone running off, and everyone thought oh this is all great, until you realized you had to operationalize it and you had to pull the brakes. Stop doing that. We're going to make sure IT operations. >> Call the CIO up. Exactly, finding out where stuff was by going through accounting and seeing credit card charges. For the edge what we've seen I think is maybe organizations really saying I've got to deploy my servers in my own site. Right at that edge in order to get the lowest possible latency. And so what I think we're starting to see is organizations looking at that and saying, okay well I'm in a metro and I've got 25 locations in a metro. And I've deployed technology to every single one of those sites. Do I need it there? Or can I put it in an Equinix facility that's less than five milliseconds from all 25 sites? So I think there's starting to be this pragmatic approach of looking at let's look at the edge, let's take a look at what type of latencies. What is our definition of real time. When do we actually need the data and so forth? What kind of connectivity do we have? And then from there figure out how we go about connecting it. And so for companies like AWS and Google and Azure a lot of them there's local zones and things like that. They're deploying them in those colos because they don't have data centers in every metro but they can leverage an Equinix. They can leverage someone else's hardware that's there to deploy their software stack within that location. So I think that's something that we're starting to see more and more of as the edge. And obviously the association with the telcos as well. They've got a great footprint. If you want to get close to the edge with their colos Their home offices and things like that and whatnot. Their ability to move the compute closer to the edge, the base stations of the antennas and things like that, are certainly significant. And that's why you're seeing the wavelengths and things like that, programs like that. >> So I was going to close, but there some really interesting topics you just brought up. Call it whatever you going to call it near edge, far edge or deep edge. And you mentioned real time. Yeah. So for those Equinix data centers, I don't need, true real time. But for Tesla, I need real time. I need real time inference at the edge probably using a bunch of ARM cores and I can't go back to any cloud. How do you look at that? Both, I would think big markets. Do you have a sense as to, is one bigger than the other? Are they both just enormous or we don't even know yet. >> I'm not sure that we know yet. I think certainly, it's riding the tail of the IOTs. So the more sensors, the more things that are deployed the more that, that data businesses realize they can leverage that data to make real time business insights to drive either better experiences. And if you're in retail. So location based services and real time offer management it doesn't do any good to offer a coupon for something that you've, that's 40 yards behind you. That that's past, like you said with the cars there's, I've seen some studies recently. They say, well, based on the latency, if the command is to stop and you're at one millisecond, it stops within four inches. If you are at 50 milliseconds, it stops 10 feet later. That's a big difference. And I don't know if those numbers are right but you get the idea about the impact, what the real time impact is of. >> Margin is not huge. >> Exactly, so that's where organizations, I think first and foremost need to take a pragmatic approach to determine what is real time for us. What's our definition of it. And then that can lead them to where do I need to place this compute technology? And then that goes to how do I then connect to it? So for the Teslas and so forth, obviously you're going to want 5G connections if possible. Ultra low latency and not just any 5G. The good stuff, the millimeter bandwidth stuff that that's the ultra low latency. >> So let's wrap. So, what's going on in your research world obviously the big, big acquisition tech target they seem to be investing in ESG. You guys are really growing and hiring. That's awesome. Any research that you're working on? >> Yeah, there's a couple of couple of projects we have going on right now. We're wrapping up a four part distributed cloud research series. So we did it on distributed cloud infrastructure. Applications, observability. And now this last one is on the edge. Coincidentally. So we're working on that. We've got some new network modernization research that we've published. And we're going to be looking, from a networking perspective looking at end-to-end network modernization which will be coming out soon. >> Awesome, Bob, thanks so much for coming on theCUBE. I really would love to have you back and chat about some of those things. Observability hot space. God, I wish we had more time. >> Absolutely, appreciate it, thanks. >> And thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

>>Welcome everybody to the cubes live coverage of AWS reinvent 2021. We're here in the main hall. Yes, this is a physical event. It's a hybrid event, probably the industry's most important hybrid event in the year. We're super excited to be here. Of course, last year during the lockdown, reinvent was purely virtual. This year. They go in hybrid 20 plus thousand people. I hear the whisper numbers like 25, 20 7,000 hundreds of thousands of people online. The cubes here, two sets, we've got two remote studios, super excited. I'd like to introduce my co-host David Nicholson. He'll be here all week with us. Uh, John furrier is also here, Lisa Martin for the cubes wall-to-wall coverage. And we're so psyched to start off this session with Kenneth Chestnut. Who's the head of technology partnerships at Stripe. Stripe's an amazing company, Ken. Great to see you. Thanks for coming on. >>Thanks for having me, Dave and David. I greatly appreciate it. How about this? >>Right. Finally live event. We've done a few. We probably done four or five this year, but >>It's good to be back in person. It is. Yeah, absolutely. It's >>A Stripe. I mean, wow. Can a powering the new economy. Tell us a little bit more for those people who may not be familiar with Stripe. They probably use it without even knowing it when they sign it away. Yeah. So tell us about the >>Well, uh, Stripe was founded in 2010 by two brothers, Patrick and John Colson. And really it was from their first business and realizing how hard it was to actually charge for things on online. Um, you had to acquire a relationship with, uh, with a gateway provider to accept payments. You had to acquire a relationship with a, with a acquiring bank. Um, and you had to do that for each and every country that you wanted to service. Uh, so the same way that AWS reduced the barrier in terms of not having to procure, spend millions of dollars on storage, computers, networking, uh, effectively, what we we've done at Stripe is reduce the barriers around economic infrastructure, accepting payments online, >>Use that undifferentiated heavy lifting for payments. So describe Ken, what it was like kind of pre Stripe. You would literally have to install servers, get storage and put, put software on there, get a database. And then what if you had any money left over, you can actually do some business, but, but describe the sort of what the experience is like with Stripe. >>Sure. So, uh, the R R with, with Stripe, we literally talk about seven lines of code. So we, we allow any developer to, um, uh, provide a set of APIs for any developer to accept payments on online. And we do the undifferentiated heavy lifting in terms of accepting payments, accepting those payments, processing them revenue, reporting, and reconciliation, um, all ensuring compliance and security. Um, so it's like you said, uh, taking care of the undifferentiated heavy lifting are around accepting payments online in the enabling >>The enabler. There is the cloud. I mean, it was 2009, 2010. You guys were founded, the cloud was only like three years old. Right. And so you had to really sort of take a chance on leveraging the cloud or maybe early on you just installed it yourself and said, this isn't going to scale. So maybe tell us how you sort of leverage the cloud. >>Sure. Um, so we're a long time, uh, AWS, uh, customer and user, um, uh, back in the early days of, of Stripe in the early days of, of AWS. And we've just grown, uh, with, with AWS and the ecosystem. And it's interesting because a lot of, uh, a lot of the companies that have been built on, on AWS and grown to be successful, they're also Stripe customers as well. So they use Stripe for their economic infrastructure. >>We use Stripe, we run our company on AWS and we use Stripe. It it's true. The integration took like minutes. It was so simple. Hey it, test it, make sure it scales. But so what, what's the stack look like? What is there, is there such thing as a payment stack? What's the technology stuff? >>Sure. So we initially started with payments and being able to accept payments, uh, on online. Uh we've we brought in out our, our, our Stripe product portfolio now to effectively provide economic, uh, infrastructure for the internet. So that could be accepting payments. Uh, it could be setting up marketplaces. So companies like Lyft and Deliveroo, uh, use Stripe to power their marketplaces with their, with their drivers and, and, um, uh, delivers, um, uh, we provide, uh, a product called radar that, uh, that, um, prevents fraud, uh, around, around the globe. Um, based upon the data that we're seeing from our, from our customers, um, we have, uh, issuing and treasury so that companies can provide their users or their merchants with banking services. So loans, uh, issuing credit cards. So we we've really broadened out the product portfolio of Stripe to provide sort of economic infrastructure for the internet. So >>We talked about strike being in the cloud from an infrastructure perspective and how that enables certain things, but that in and of itself, doesn't change the dynamics around sovereignty and governance from country to country. Sure. Uh, I imagine that the global nature of AWS sort of dovetails with your strategy, but how, how do you address that? It's one thing to tell me in Northern California, you can process payments for me, but now globally go across 150 countries. How do you make that work? Yeah, >>Uh, absolutely. So we, we establish relationships, uh, within, within each company country that we operate in we're in about 47, uh, countries, uh, today, um, and that's rapidly expanding so that companies can, can process or accept payments and do, uh, financial transactions within, within, within those countries. So we're in 47 countries today. We, we accept a multitude of different payment, uh, different currencies, different payment types. So the U S is very, uh, credit card focused. But if you go to other, other parts of the globe, it could be a debit cards. It could be, um, uh, wallets, uh, uh, Google pay, Ali pay, uh, others. So really it's, uh, providing sort of the payment methods that users prefer in, in the different countries, uh, and meeting and meeting those users where, where they are. >>Are you out of the box compliant? What integration is required to do that? Uh, what about things like data sovereignty, is that taken care of by the cloud provider or you guys, and where, w w where does, where does AWS end and you guys pick up? Yes, >>We're, we're PCI compliant. Um, we, we leverage AWS as our, as our infrastructure, um, to grow, grow and scale. So, um, one of the things that we're, we're proud of is, uh, through, throughout 2020 and 2021, we've, we've had 11 nines of, uh, of, of, uh, or five nines of uptime, um, even through, um, uh, black Friday and cyber Monday. So providing AWS provides that, that infrastructure, which we built on top of to provide, uh, you know, five nines of uptime for our, for our users. >>You describe in more detail, Kenya, your ecosystem. I mean, you're responsible for tech partnerships. What does that ecosystem, how I paint a picture of it? >>Sure. So, um, uh, a number of users want to be able to use Stripe with, with their other, uh, it infrastructure and, and their business processes. So a customer may start, uh, with a salesperson may start with a quote or order, uh, in, in Salesforce, want to automate the invoicing and billing and payment of that with, with Stripe and then, uh, reconcile re revenue and an ERP solution like SAP or Oracle or NetSuite or into it, um, in the case of, of small, medium businesses. So really, um, what we're focused on is building out that, that ecosystem to allow, uh, um, our, our customers to streamline their business processes, um, and, and integrate Stripe into their existing it infrastructure and, and business processes. >>You mentioned a lot of different services, but broadly speaking, if I think about payments, correct me if I'm wrong, but you were one of the early, uh, sort of software companies, if I can call you that, um, platforms, whatever, but to really focus on a usage based pricing, but how do I, how do I engage with you? What's, what's the pricing model. Maybe you could describe that a little. >>Sure. So the pricing model is very, very transparent. Uh, it's on, it's on the website. So, uh, we, we take a, um, a percentage of each transaction. So literally you can, you can set up a, a Stripe account it's self-service, um, uh, we, we take a 2.9% plus 30 cents on every, uh, Tran transaction. Um, we don't, you don't start getting, um, uh, charged until, uh, you start accepting payments from your, from your customers or from your users. >>Um, can you give us a sense of the business scope, maybe any metrics you can share, customers, whatever. >>Sure. So there's a couple of things we can share publicly, just in terms of the size of the business. I think since, uh, since 2020, uh, more than 2 million businesses have launched on, on Stripe. Uh, so, uh, 2 million in, in, in, in 2020, um, we've, uh, uh, in the past 12 months, we've, uh, uh, uh, processed over 173 billion, uh, API calls. Uh, we do we process about, um, uh, hundreds of billions of, of, of, uh, payment volume, uh, every, every year. Um, if you look at sort of the macros of the business, the business is growing faster than the broader e-commerce space. So the amount of payment volume that we did in this past year is more than the entire industry did when Patrick and John founded the company. And in 2010, just to give you a, uh, an idea of the, the, the size of the business and sort of the pace of the business >>You're growing as e-commerce grows, but you're also stealing share from other sort of traditional payment systems. Okay. So that's a nice flywheel effect. And of course, Stripe's a private company they've raised well over a billion dollars of Peter teal, and it wasn't original founders, so are funders. So, you know, that's, he's talking scale. I want to go back to something you said about radar. Sure. So there's tech in your stack fraud detection, right. So some of >>That in machine learning, right. >>So, and so you guys, I mean, are you a technology company, are you a F a FinTech company? What are you? >>We're a software company. We provide software and we provide technology for developers, uh, to make online businesses and make, uh, uh, commerce, uh, more seamless and more frictionless >>Cloud-first API first. I mean, maybe describe how that is different maybe than, you know, the technical debt that's been built up over, you know, decades with traditional payment systems. >>Yes, it's very similar to the early, earlier days of AWS where a lot of tech forward companies leveraged Stripe, um, to, um, whether it be large enterprises to transform their businesses and move online, or, or, uh, uh, startups and developers that want to, uh, start a new business online and, and do that, uh, as quickly and seamlessly as possible. So it's, it's quite the gamut from large enterprises that are digitally transforming themselves companies like Marske and, and NASDAQ and others, as well as, uh, um, startups and developers that have started their businesses and born on born on Stripe. So >>When you talk about a startup, how small of an entity makes sense, uh, when you think of, if you look at, from an economic perspective, lowering the friction associated with transactions can lift up a large part of the world with sort of, you know, w with very, very small businesses. Is that something that this is all about? >>Yeah, absolutely. So, like I said, you know, two, 2 million business have sub launched on, on, on Stripe, uh, in, in the past year. And, and those businesses vary, but it could be literally a, a developer or a, uh, uh, a small, uh, SMB that wants to be able to accept payments on online. And it can just set up a Stripe account and start accepting payments. >>Yeah. So this is not a one hit wonder, um, lay out the vision for Stripe, right? I mean, you're, you're a platform, uh, you're, you're becoming a fundamental ingredient of the digital economy sounds pre pandemic. That was all a bunch of buzzwords, but today we all know how important that is, but what lay out the vision for us can, >>Yeah, it really are. The mission of Stripe is to grow the GDP of the internet. Um, and, and so what that means is, uh, more and more our, our, our basic belief is more and more and more businesses, uh, will, will, uh, go, go online, uh, with, uh, with the pandemic that that was, uh, accelerated. But I think that the general trend of businesses moving online, uh, will continue to accelerate, and we want to provide, uh, economic infrastructure to support those businesses. Um, you know, um, uh, uh, Andreessen talked about sort of software, software eating the world well fit. Our belief has FinTech is eating software. So in, in the fullness of time, I think the opportunity is for, uh, any, any company to be a financial services company. And we want to empower any company that wants to, or any user that wants to be a financial services company to, to provide the economic infrastructure for them to do so. >>And, and, you know, I mean your data company in that sense, you're moving bits around, you know, and those datas, I like to say data's eating software, you know, cause really you gotta have your data act together. Absolutely. And that's an evolving, I mean, you guys started to, to 2010, I would imagine your data strategy has evolved quite dramatically. Yeah. >>It's a great, it's a great call out Dave. Uh, one of our other products is a product called Sigma. So Sigma allows, uh, merchants or our customers to query payment and transaction data. So they want to be able to understand who, who, who are their customers, what are the payment methods that those customers prefer in different countries, in different regions? Um, so we're, we're starting to have some interesting use cases, um, working with, with AWS and other partners when you can start combining payment and transaction data in Stripe with other data to understand customer segmentation, customer 360 lifetime value of a customer customer acquisition costs, being able to close the books faster in your ERP, because you can apply that payment and transaction data to your general ledger to, to close the books faster at the end of the month or at the end of the, at the end of the year. So, uh, yeah, we we're, um, uh, as, as more and more companies are using Stripe, um, they want to be able to take advantage of that data and combine it with other, other sources of data to drive business. >>Yeah. You mentioned some of those key metrics that are, that are so important to companies today. I'll give you the last word re-invent this hall is packed, um, a little bit surprising, frankly, you know, but, uh, but exciting. Uh, what are you looking forward to this? >>Yeah, I'm just looking forward to meeting people in person again, it's, uh, it's great to be here and, and, you know, uh, uh, we have a strong relationship with AWS. We have lots of partners in, in, in common here, uh, as well, both consulting partners and technology partners. So really looking forward to meeting with partners and customers, and especially as we, as we plan for next year and, uh, launching our, our, our partner program beginning of next year. Uh, there's a lot of, uh, uh, groundwork and things to learn from, from here. As we, as we, we, we, we launch our, our, our partner business formula next >>I'll bet. Looking forward to that, Ken, thanks so much for coming to the cure. You so much. It was great to have a chat at the time. All right. And we want to thank our sponsors, uh, AWS, of course, and also AMD who's making the editorial segments that we bring you this week possible for Dave Nicholson. I'm Dave Volante. You're watching the cube at AWS reinvent 2021. Keep it right there, right back.

(Music) >> Welcome to the AWS executive summit presented by Accenture at AWS reinvent 2021. I'm Lisa Martin, and I've got two Cube alum here with me, please welcome Merim Becirovic, Managing Director of Global IT Enterprise Architecture at Accenture and Chris Wegmann, Accenture, AWS Business Group technology and practices, Senior Managing Director, gentlemen, welcome back to the program. >> Thank you, Lisa, great to be back. >> Thank you, Lisa. Great to be here. >> It is nice to be back in a way right here we are at this hybrid event, but we want to talk about what Accenture is doing with its, with AWS to serving its clients. And then we're going to get into your own internal use case, drinking your own champagne. Chris go ahead and start with you, talk to us about what Accenture is doing with AWS to serve its clients. >> Yeah, Lisa, it's exciting, as you said to be back in this hybrid event and you know, for me, this will be my 10th re-invent and for Accenture we're in year 14 of our partnership with AWS and actually year six of our partnership called Accenture AWS business group. And you know, the focus over the last year has been helping our clients come out of the pandemic stronger than, than where they started. Right? And a lot of that has been around focusing our customers, getting past cloud migration, past cloud modernization, and getting further into what we now call the cloud continuum, starting to truly leverage all the AWS assets and capabilities and services to, to truly speed their transformation. You know, we work with a lot of our customers who are needing to transform even faster today than they were before the pandemic. And, you know, we're focused on helping those customers do that with AWS services. >> So Merim, let's bring you into the conversation. Now Accenture's internal IT organization has been leveraging AWS and public cloud for a while. Talk to me about that you completed the journey a couple of years ago, 95% in the cloud. Talk to me about what you're doing there. >> Sure. Lisa, so our, our journey into the public cloud is complete. As you said, we put a bow on that project a couple of years ago. We started in 2015 and we went all in on public cloud. So we, the number 95%, 95% represents a true measure of everything it takes to run Accenture. Everything addressable is in the public cloud today. So the 95% just represents a small component of things that have to live outside of the cloud. But other than that, our journey to the cloud is complete, and we are very happy being in the cloud because it has opened tremendous doors for us as a business. I'm sure we'll talk about here as we go, but it's fundamentally a different place we live in today and where we were before we were in the cloud. >> Merim, you said something really powerful there a second ago. The Accenture's journey to the cloud is complete. I don't think I'd ever heard anybody say that. Talk to me about the impact, especially during the last 18 months that that cloud journey is delivered. >> I mean, one of the things I am extremely proud of for our collective global teams around the world, when the, obviously the, you know, when COVID hit and the pandemic engulf the world, the only difference for us was that people just did not come into an office to work. Our capabilities in the cloud, our capabilities of having everything in the cloud really made it that much easier for our people to go to work. We weren't fighting over resources around infrastructure. People could just work from home directly. So I'm extremely proud of the collective global team that made all of that happen as part of that execution of all those things. So it was really a very proud moment, I would say for all of us running IT. >> As well, it should be. Chris, talk about that from your perspective of facilitating that massive pivot 18, 19 months ago, and what your group was responsible for doing to enable this cloud journey to be complete. >> Yeah. I always laughed at, you know, Merim and our internal CIO organizations, we call it was our first customer, right. You know, way back when I started working in this partnership, you know, we were already starting to leverage AWS, S3 and EC2, and that insight Accenture, and we took a lot of those best practices and started helping, our clients leverages best practices. So, you know, from an Accenture, we always kind of harvest from internally what we're doing, but, you know, over the last several years, we really are our focused with the CIO organization, Merim's organization has been, you know, expanding the usage of non, you know, I, as I call Maya services, right? So past EC2, you know, past S3. Obviously there's always storage. There's always compute, but you know, truly doing and building serverless applications, truly using, you know, services, fully managed services. So, you know, the CIO organization doesn't have to spend their time doing that. And, for our customers, that's while it's, they're still early on in a lot of their journeys, that's a novel idea is a truly try to sunset IS services or EC2 and things like that, you know, and whether that's, you know, fix some containerization or things like that, I think the other big part is, is the maturing security footprint, right? Obviously, as you use one or more of these AWS services, your security posture, your presence, how you think about security. We created an asset called secure cloud foundation, leveraging many of the AWS services in the security space that have come out like guard duty and others really to help make that security foundation stronger, make it easier for our customers, including CIO to leverage those services and truly enable that move further up the cloud or further down the continuum as we call it. >> Merim, I want to get your thoughts on security from in a, because we have seen such a dramatic change in the threat landscape in the last 18, 19 months. We've seen a huge spike in ransomware. It's getting much more personal. It's now a household word. We've got the executive order. We had this rapid pivot to and hundreds of thousands of Accenture employees working from home. Talk to me about, you feel very confident in the cloud during that you didn't word where's your competence from a security perspective. >> As you said, security is the fastest growth in our business. Collectively, like you said, the bad guys don't sleep. We don't sleep either when it comes to security. One of the things that we're constantly thinking about is how do we turn on a lot of our capabilities as an example. So even, I would say at an enterprise level, it's different when you're running a big multinational corporation, 650,000 people like we do. We can't just turn everything on and hope for the best. We are very scripted in terms of how we think about those services, how we think about the processes, how we work with our CSO organization, so that we're very meticulous and very thorough in terms of what services we turn on, how we turn them on, when we turn them on? How long we make them available, because this is, this is the new world, right? We have extended our corporate structure out into the cloud. That means we have to think of different ways for how we want to consume those capabilities and services. So like Chris said, you know, the, the journey to the cloud for us is complete. A lot of it was I, as I would tell you, a lot of it was lift and shift for less. And we can talk about that if we get time, but it was more about getting into the cloud and taking advantage of the cloud where we are today, because now that we're there, we get to take advantage of all those capabilities that are there. And I would say the best part of being with on, in, in the cloud is also having the, the providers like AWS they are with us, helping us with that security posture. So it's not just us doing this by ourselves. >> So Chris, I want to talk about that Merim just said, this was mostly lift and shift. Talk to us about that. Cause when we talk to organizations in every industry, the cloud transition, the cloud journey is extremely challenging. It's complex. How did you do this? How did you facilitate this and in a relatively short time period, Chris? >> Yeah. And, and you're right. Everyone has conversations I have with my clients. You know, there's a huge debate whether to lift and shift or modernize or build new build cloud native, right? So, you know, in Accenture's situation, you know, very early on, it was identified that we can, we can do a large savings by doing a lift and shift migration, right. We were not a big data center owner, right. That wasn't, we're not a big capital intense organization. So for us, that, that journey we had, you know, colos and that stuff coming up for renewal. And we knew that we could, you know, get some early savings there and really, you know, reduce our footprint and take that investment and then invest it into, you know, true modernization. So Merim and his organization worked very closely to build the factory, to do the migrations, get that done in a very short amount of time and then turn their attention on truly refactoring rebuilding the applications. I'm super proud of the number of applications that we've rebuilt. I'm super proud of the number of applications that, that now are cloud native. And we live in these applications every day. You know, they they're everything from our performance to how we do our payroll and do our time charging and things like that. But which, you know, it was a big reason why, you know, we can access our systems remotely and at home versus going into different systems to get to that stuff. So, you know, it was very much heavily lift and shift early, then really focusing on modernization. And as Merim said, getting, you know, now it's about living there and continuing, continuing to modernize, continuing to accelerate what we're doing in the cloud. >> Yeah. Lisa, its little bit like, so our journey lift and shift was a core component of it. But the minute we decided to go to the cloud, one of the things, the first things we did, as I said, no more vans. So any new capability that we were going to build, we were going to build a cloud native micro-services based, and that's been our standard for the last 3 or 4 years ago. So any new capability that comes along today that we must do custom, we build a cloud native microservices because one of the other things that I've got on my plate is I'm trying to reduce our overall technical debt. So all of these IS platforms, I still have to maintain them, patch them, support them, upgrade them. And I would rather be much more efficient at doing those things as, as I can and reinvest money into refactoring and modernizing the rest of the application, plead through containers through microservices, et cetera, which then gives me the agility right back to actually go even faster, to enable more services for the business. >> Speed is something that we've seen become even more critical in the last 18, 19 months where we needed to everybody pivot businesses multiple times over and over. But part of the challenge there Merim, I want to get your thoughts on this is they are something cultural shift. Talk to me about, you've been at Accenture for a long time. Talk to me about the cultural shift needed to facilitate this massive transformation to cloud and how Chris's team was a facilitator of that. >> So, you know, one of the things for us, I have probably in the last five years spoken to a thousand of our clients, around our cloud journey and this culture conversation always comes up and I will say, you know, the biggest thing for us was interesting. We had those same fears. We had some same in when we first talked about going to the cloud, you know, six years ago, it was very, not everything was there, that's there today. So the teams were extremely nervous and they were confident that we could never be as, as good in the cloud as we were on, on site. Yet here we are six years later and we're constantly finding ways to add value and take, bring value back. And though, it's so same teams. And one of the things is just, we gave them the challenge to say, Hey, this is the future. We're telling our clients, this is where we're going. We have an opportunity here to do something different and they took it and the team really took it on. And they said, okay, let's do it. And they act, and we looked at how we run into cloud the many different ways, whether we're using reserved instances, whether we're using containers, whether we're using, you know, different computer capabilities, we went through all of it and we're running such a highly efficient machine right now that it's like, we're still able to continue to eat out savings even five years after the program. Even two years after the program is complete, we're still able to get savings. >> That's outstanding. That's ROI that every business and every industry hopes to be able to achieve from this. I want to switch gears a little bit now because this is actually pretty cool. Accenture is really focused also on sustainability. You guys have signed onto the Amazon climate pledge, which if you don't know what the Amazon climate pledge, and this is back in 2019, Amazon, co-founded this a commitment to be net zero carbon across businesses by 2040, which is actually 10 years ahead of the Paris agreement. You're in talk to us about that. And from Accenture's perspective, why it was important to sign on to that. >> So on a, on a personal level, I love obviously sustainability as a whole, that I think about the world park for my children that are growing up. So it's very important to me on a personal level as well. But I would say at a company level, what I love about the cloud is I am there right there with them as they make investments. All of our enterprise capabilities are there. We are able to very quickly shift and use those capabilities. So as Amazon, for example, in this scenario creates new capabilities, new compute offerings, new, new storage offerings, whatever it may be. They're doing it with a sustainability lens and me by being in the cloud already, I can then turn to start using those things too. So as much as I can, on that perspective, I'm in a great place with, as Amazon puts these sustainability capabilities out there, I'm right there consuming and making them more efficient. And then the other one is obviously as much of our workloads, as we can get to a cloud native perspective, microservices perspective, then we keep reducing that compute consumption and everything else that goes along with it. And lastly, I would say, you know, the, the other thing is we're very aggressive in managing all of our systems in terms of uptime. So for example, in a data center, most, most organizations don't think about turning off their development environments and everything else. But for us, we're very rigid in this process. And we have a, we have a target of all of our development environments being down 55% of the time. And primarily that's also a sustainability play in addition to a financial savings plan. >> Awesome. Great stuff, Chris, last question for you, as we wrap up here, what are some of the things that you were excited about that's coming in cloud in the next few years? Obviously here we are at, re-invent going to be hearing a lot of news, a lot of announcements about cloud in the coming days. What excites you most, Chris? >> Yeah. You know, obviously the machine learning and AI stuff is, is always the most exciting things right now in cloud. And, you know, we've put a lot of those to use here inside of Accenture as well. And, and our, you know, in our synopsis platform, which we use with our customers to run in a more intelligent operations, we use that internally as well. But you know, one of the things that excites me the most is the continued innovation at the core. Right. And you know, whether that be, you know, chip sets, you know, Merim talked a little bit about, you know, improvement and performance improvement and power consumption, you know, grabbing time, those types of stuff that, that excites me every year, I look forward to seeing what, what they come out with and, and then how we're going to put that to use. >> Well, I look forward to talking to you guys next year, you've done such a tremendous job. You should be proud of the massive transformation that you've done. I imagine this is, would be a great case study. If it's not already written up, it should be. It's really impressive. Merim and Chris, thank you for joining me at the summit. Talking to me about what's going on with Accenture and AWS and some of the things that you are looking forward to, we appreciate your insights and your time. >> Thanks, Lisa. >> Thanks, Lisa. >> You're welcome for my guests. I'm Lisa Martin. This is the AWS executive summit presented by Accenture at AWS reinvent 2021. (Music)

(Music) >> Welcome to the AWS executive summit presented by Accenture at AWS reinvent 2021. I'm Lisa Martin, and I've got two cube alum here with me, please welcome Merim Bertovic, managing director of global IT enterprise architecture at Accenture and Chris Wegmann, Accenture, AWS business group technology and practices, senior managing director, gentlemen, welcome back to the program. >> Thank you, Lisa, great to be back. >> Thank you, Lisa. Great to be here. >> It is nice to be back in a way right here we are at this hybrid event, but we want to talk about what Accenture is doing with its, with AWS to serving its clients. And then we're going to get into your own internal use case, drinking your own champagne. Chris go ahead and start with you, talk to us about what Accenture is doing with AWS to serve its clients. >> Yeah, Lisa, it's exciting, as you said to be back in this hybrid event and you know, for me, this will be my 10th re-invent and for Accenture we're in year 14 of our partnership with AWS and actually year six of our partnership called Accenture AWS business group. And you know, the focus over the last year has been helping our clients come out of the pandemic stronger than, than where they started. Right? And a lot of that has been around focusing our customers, getting past cloud migration, past cloud modernization, and getting further into what we now call the cloud continuum, starting to truly leverage all the AWS assets and capabilities and services to, to truly speed their transformation. You know, we work with a lot of our customers who are needing to transform even faster today than they were before the pandemic. And, you know, we're focused on helping those customers do that with AWS services. >> So Merim, let's bring you into the conversation. Now Accenture's internal IT organization has been leveraging AWS and public cloud for a while. Talk to me about that you completed the journey a couple of years ago, 95% in the cloud. Talk to me about what you're doing there. >> Sure. Lisa, so our, our journey into the public cloud is complete. As you said, we put a bow on that project a couple of years ago. We started in 2015 and we went all in on public cloud. So we, the number 95%, 95% represents a true measure of everything it takes to run Accenture. Everything addressable is in the public cloud today. So the 95% just represents a small component of things that have to live outside of the cloud. But other than that, our journey to the cloud is complete, and we are very happy being in the cloud because it has opened tremendous doors for us as a business. I'm sure we'll talk about here as we go, but it's fundamentally a different place we live in today and where we were before we were in the cloud. >> Merim, you said something really powerful there a second ago. The Accenture's journey to the cloud is complete. I don't think I'd ever heard anybody say that. Talk to me about the impact, especially during the last 18 months that that cloud journey is delivered. >> I mean, one of the things I am extremely proud of for our collective global teams around the world, when the, obviously the, you know, when COVID hit and the pandemic engulf the world, the only difference for us was that people just did not come into an office to work. Our capabilities in the cloud, our capabilities of having everything in the cloud really made it that much easier for our people to go to work. We weren't fighting over resources around infrastructure. People could just work from home directly. So I'm extremely proud of the collective global team that made all of that happen as part of that execution of all those things. So it was really a very proud moment, I would say for all of us running IT. >> As well, it should be. Chris, talk about that from your perspective of facilitating that massive pivot 18, 19 months ago, and what your group was responsible for doing to enable this cloud journey to be complete. >> Yeah. I always laughed at, you know, Merim and our internal CIO organizations, we call it was our first customer, right. You know, way back when I started working in this partnership, you know, we were already starting to leverage AWS, S3 and EC2, and that insight Accenture, and we took a lot of those best practices and started helping, our clients leverages best practices. So, you know, from an Accenture, we always kind of harvest from internally what we're doing, but, you know, over the last several years, we really are our focused with the CIO organization, Merim's organization has been, you know, expanding the usage of non, you know, I, as I call Maya services, right? So past EC2, you know, past S3. Obviously there's always storage. There's always compute, but you know, truly doing and building serverless applications, truly using, you know, services, fully managed services. So, you know, the CIO organization doesn't have to spend their time doing that. And, for our customers, that's while it's, they're still early on in a lot of their journeys, that's a novel idea is a truly try to sunset IS services or EC2 and things like that, you know, and whether that's, you know, fix some containerization or things like that, I think the other big part is, is the maturing security footprint, right? Obviously, as you use one or more of these AWS services, your security posture, your presence, how you think about security. We created an asset called secure cloud foundation, leveraging many of the AWS services in the security space that have come out like guard duty and others really to help make that security foundation stronger, make it easier for our customers, including CIO to leverage those services and truly enable that move further up the cloud or further down the continuum as we call it. >> Merim, I want to get your thoughts on security from in a, because we have seen such a dramatic change in the threat landscape in the last 18, 19 months. We've seen a huge spike in ransomware. It's getting much more personal. It's now a household word. We've got the executive order. We had this rapid pivot to and hundreds of thousands of Accenture employees working from home. Talk to me about, you feel very confident in the cloud during that you didn't word where's your competence from a security perspective. >> As you said, security is the fastest growth in our business. Collectively, like you said, the bad guys don't sleep. We don't sleep either when it comes to security. One of the things that we're constantly thinking about is how do we turn on a lot of our capabilities as an example. So even, I would say at an enterprise level, it's different when you're running a big multinational corporation, 650,000 people like we do. We can't just turn everything on and hope for the best. We are very scripted in terms of how we think about those services, how we think about the processes, how we work with our CSO organization, so that we're very meticulous and very thorough in terms of what services we turn on, how we turn them on, when we turn them on? How long we make them available, because this is, this is the new world, right? We have extended our corporate structure out into the cloud. That means we have to think of different ways for how we want to consume those capabilities and services. So like Chris said, you know, the, the journey to the cloud for us is complete. A lot of it was I, as I would tell you, a lot of it was lift and shift for less. And we can talk about that if we get time, but it was more about getting into the cloud and taking advantage of the cloud where we are today, because now that we're there, we get to take advantage of all those capabilities that are there. And I would say the best part of being with on, in, in the cloud is also having the, the providers like AWS they are with us, helping us with that security posture. So it's not just us doing this by ourselves. >> So Chris, I want to talk about that Merim just said, this was mostly lift and shift. Talk to us about that. Cause when we talk to organizations in every industry, the cloud transition, the cloud journey is extremely challenging. It's complex. How did you do this? How did you facilitate this and in a relatively short time period, Chris? >> Yeah. And, and you're right. Everyone has conversations I have with my clients. You know, there's a huge debate whether to lift and shift or modernize or build new build cloud native, right? So, you know, in Accenture's situation, you know, very early on, it was identified that we can, we can do a large savings by doing a lift and shift migration, right. We were not a big data center owner, right. That wasn't, we're not a big capital intense organization. So for us, that, that journey we had, you know, colos and that stuff coming up for renewal. And we knew that we could, you know, get some early savings there and really, you know, reduce our footprint and take that investment and then invest it into, you know, true modernization. So Merim and his organization worked very closely to build the factory, to do the migrations, get that done in a very short amount of time and then turn their attention on truly refactoring rebuilding the applications. I'm super proud of the number of applications that we've rebuilt. I'm super proud of the number of applications that, that now are cloud native. And we live in these applications every day. You know, they they're everything from our performance to how we do our payroll and do our time charging and things like that. But which, you know, it was a big reason why, you know, we can access our systems remotely and at home versus going into different systems to get to that stuff. So, you know, it was very much heavily lift and shift early, then really focusing on modernization. And as Miriam said, getting, you know, now it's about living there and continuing, continuing to modernize, continuing to accelerate what we're doing in the cloud. >> Yeah. Lisa, its little bit like, so our journey lift and shift was a core component of it. But the minute we decided to go to the cloud, one of the things, the first things we did, as I said, no more vans. So any new capability that we were going to build, we were going to build a cloud native micro-services based, and that's been our standard for the last 3 or 4 years ago. So any new capability that comes along today that we must do custom, we build a cloud native microservices because one of the other things that I've got on my plate is I'm trying to reduce our overall technical debt. So all of these IS platforms, I still have to maintain them, patch them, support them, upgrade them. And I would rather be much more efficient at doing those things as, as I can and reinvest money into refactoring and modernizing the rest of the application, plead through containers through microservices, et cetera, which then gives me the agility right back to actually go even faster, to enable more services for the business. >> Speed is something that we've seen become even more critical in the last 18, 19 months where we needed to everybody pivot businesses multiple times over and over. But part of the challenge there Merim, I want to get your thoughts on this is they are something cultural shift. Talk to me about, you've been at Accenture for a long time. Talk to me about the cultural shift needed to facilitate this massive transformation to cloud and how Chris's team was a facilitator of that. >> So, you know, one of the things for us, I have probably in the last five years spoken to a thousand of our clients, around our cloud journey and this culture conversation always comes up and I will say, you know, the biggest thing for us was interesting. We had those same fears. We had some same in when we first talked about going to the cloud, you know, six years ago, it was very, not everything was there, that's there today. So the teams were extremely nervous and they were confident that we could never be as, as good in the cloud as we were on, on site. Yet here we are six years later and we're constantly finding ways to add value and take, bring value back. And though, it's so same teams. And one of the things is just, we gave them the challenge to say, Hey, this is the future. We're telling our clients, this is where we're going. We have an opportunity here to do something different and they took it and the team really took it on. And they said, okay, let's do it. And they act, and we looked at how we run into cloud the many different ways, whether we're using reserved instances, whether we're using containers, whether we're using, you know, different computer capabilities, we went through all of it and we're running such a highly efficient machine right now that it's like, we're still able to continue to eat out savings even five years after the program. Even two years after the program is complete, we're still able to get savings. >> That's outstanding. That's ROI that every business and every industry hopes to be able to achieve from this. I want to switch gears a little bit now because this is actually pretty cool. Accenture is really focused also on sustainability. You guys have signed onto the Amazon climate pledge, which if you don't know what the Amazon climate pledge, and this is back in 2019, Amazon, co-founded this a commitment to be net zero carbon across businesses by 2040, which is actually 10 years ahead of the Paris agreement. You're in talk to us about that. And from Accenture's perspective, why it was important to sign on to that. >> So on a, on a personal level, I love obviously sustainability as a whole, that I think about the world park for my children that are growing up. So it's very important to me on a personal level as well. But I would say at a company level, what I love about the cloud is I am there right there with them as they make investments. All of our enterprise capabilities are there. We are able to very quickly shift and use those capabilities. So as Amazon, for example, in this scenario creates new capabilities, new compute offerings, new, new storage offerings, whatever it may be. They're doing it with a sustainability lens and me by being in the cloud already, I can then turn to start using those things too. So as much as I can, on that perspective, I'm in a great place with, as Amazon puts these sustainability capabilities out there, I'm right there consuming and making them more efficient. And then the other one is obviously as much of our workloads, as we can get to a cloud native perspective, microservices perspective, then we keep reducing that compute consumption and everything else that goes along with it. And lastly, I would say, you know, the, the other thing is we're very aggressive in managing all of our systems in terms of uptime. So for example, in a data center, most, most organizations don't think about turning off their development environments and everything else. But for us, we're very rigid in this process. And we have a, we have a target of all of our development environments being down 55% of the time. And primarily that's also a sustainability play in addition to a financial savings plan. >> Awesome. Great stuff, Chris, last question for you, as we wrap up here, what are some of the things that you were excited about that's coming in cloud in the next few years? Obviously here we are at, re-invent going to be hearing a lot of news, a lot of announcements about cloud in the coming days. What excites you most, Chris? >> Yeah. You know, obviously the machine learning and AI stuff is, is always the most exciting things right now in cloud. And, you know, we've put a lot of those to use here inside of Accenture as well. And, and our, you know, in our synopsis platform, which we use with our customers to run in a more intelligent operations, we use that internally as well. But you know, one of the things that excites me the most is the continued innovation at the core. Right. And you know, whether that be, you know, chip sets, you know, Merim talked a little bit about, you know, improvement and performance improvement and power consumption, you know, grabbing time, those types of stuff that, that excites me every year, I look forward to seeing what, what they come out with and, and then how we're going to put that to use. >> Well, I look forward to talking to you guys next year, you've done such a tremendous job. You should be proud of the massive transformation that you've done. I imagine this is, would be a great case study. If it's not already written up, it should be. It's really impressive. Merim and Chris, thank you for joining me at the summit. Talking to me about what's going on with Accenture and AWS and some of the things that you are looking forward to, we appreciate your insights and your time. >> Thanks, Lisa. >> Thanks, Lisa. >> You're welcome for my guests. I'm Lisa Martin. This is the AWS executive summit presented by Accenture at AWS reinvent 2021. (Music)

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by UI path. >>Welcome back to the queue. We are live at the Bellagio in Las Vegas, Lisa Martin, with Dave Volante UI path forward for it is so great to be sitting in an anchor desk next to Dave and with guests in person, we're going to be talking about automation workforce of the future. I've got two guests here with Dave and me. Kevin crone is here intelligent automation and digital upskilling leader from PWC. Kevin. Welcome. Thank you. Can't wait to talk about upskilling and Bettina Koblick is here the chief people officer at UiPath. Welcome to the program. Thanks for having me. So, as I understand that PWC has embedded UI path into a couple of product offerings. One of them we're going to talk about today, Kevin that's pro pro edge. Talk to me about that. What is that? >>So, um, as we look at, uh, challenges that C-suite leaders are facing, I think one of the biggest emerging challenges right now is around the topic of upscaling. There's the number of jobs that are being displaced, um, is growing by automation. But on the flip side, the number of jobs that are emerging is actually greater and there is a consistent challenge that gets cited there. All of our research through our CEO survey, their work we've done with the world economic forum and other sources around the need to fill that gap. And most leaders feel like they're not doing a good job to, to fill that. So, um, we at PWC have invested in developing a, a new software product called pro edge, which is really focused on, um, identifying the skills needed for the future, teaching those skills and helping to scale the usage of the skills and the organization. And one of the key skills as we look at the digital space is UI path. And we really think that, you know, teaching non technologists around the use of tools like robotic process automation is going to be one of those critical kind of must have skills in the future. >>And patina, you guys are using pro edge. Why, why, why? I mean, you're like the automation pros, what do you need? >>We need it because we have the same, um, challenges that every other company has that introduced us automation, right? People, um, people's time, their tasks that they have been doing are basically displaced. Um, and we're trying to figure out how do we up-skill re-skill how do we position people who now no longer are work working on maybe 50% of what they've done in the past for their next role? Um, so it's incredibly important for us, >>You know, you know this well, Tina and Kevin, you as well, when, when the automation trend RPA first hit, it was like, oh yeah, the trade press, come on. It's going to take away jobs, blah, blah, blah. Now we're working perpetual workdays, right? We all weekend all night, you never stopped working. You're always on. So I think people will brace automation, but as the chief people officer, first of all, how, how was it getting through the pandemic? And have you seen, I presume that UI path folks embrace automation, of course it's in your DNA, but have you seen others sort of, is that narrative done in, is COVID effected that >>I think COVID has affected it, um, for a number of reasons, because so many things shifted in how we do work. Number one, and I can talk about that a little more, but I yesterday I was in a customer advisory board meeting actually with Kevin. And the biggest conversation was not about the technology. It was around what happens when automation is introduced to a company and what happens with people, um, as to whether they want, they're willing to adopt, embrace, have an automation mindset. So that conversation isn't done at all. And it's probably one of the biggest conversations after, you know, adopting the technology, trying to introduce it as how do you drive adoption. And a lot of that is people's people's ability to understand how it will make their life easier, but then not be afraid about what's next. Uh, so I think it's absolutely still a conversation. I don't know if you feel the same. Yeah, >>Yeah. It it's been interesting. I think during the pandemic cause peoples, you know, day to day work lives have gone up ended and he start to think about, um, you know, the, the mixture between what I'll call kind of transaction oriented type work versus analytical type work. And if it just, you know, historically everyone's always said we should do less transaction work and more analytic work. But I think the pandemic was almost like forced that conversation on steroids and people's lot. You I've had to figure out that, like, I don't want to do this type of work and I'm being, I have more demands on me and I'm being asked to do other things, how can I do this more effectively? And so part of this becomes learning these skills to automate the things in front of you right now, the part of this becomes, I need to be able to, to actually have that analytical skill set in the future. And I think that is almost a precursor for what we see happening. And that was, that was the fun part of the conversation yesterday is thinking about, okay, well, what is the, you know, what is the, uh, the accounting analyst role five years from now and what someone does today versus what someone does in five years and how do you actually plan for that, >>The patina, where in your organization, like who's using it and talk to me about the adoption and their willingness to embrace it. >>Yeah. So we are, we've introduced it to our finance organization. One of the reasons we did that is because our finance organization is also a big user of automation, right? So, um, what's been really interesting is that because the technology or because pro edge kind of takes biases out of mapping, what a person can do, um, what learning paths there are for them and what their job will look like in the future, in which job do they go to or could be a potential path. I think it actually motivates people much beyond having work shifting because of automation. Because in addition, you also get to see a path, right. And everywhere you turn, just want to know what's the possibility for the future. So, um, while I'd like to say it was genius for us to envision that it's, it's a pleasant surprise and something, we should talk about more, >>I'm sensing a journey. It's always the case where I know I call it the force March to digital. We were thrown into this. And so, so much was unknown. And I know our team, I mean our producers and it's death by a thousand paper cuts in any one individual thing is not that bad, but yeah, the Moffitt, it's just, that's what kills your work day, your work week and your mental health. And so maybe it's, that's kind of the starting point is, are pigs a band-aid for, for, for, for that fundamental, but then it's wow. I can see the light bulb goes off. I can see the potential, that's where the digital upskilling comes in. I mean, maybe that's oversimplifying it, but how do you see that journey? Yeah. >>Yeah. I think there's a couple of different pieces with this cause, you know, and it goes back to the divide between the things you need to do now. And how do you think about making your life easier, but then it really goes to what you need to do in the future. And that journey to actually get there is tough because it's not just a question of, Hey, I need to pick up a textbook or pick up an online training module. And I'm just going to become an expert. It's really thinking about what are the, what's the combination of different skills. I need to learn. Some of that's going to be hands on technical skills. It's going to be platforms like UI path. It may be other complimentary platforms in the analytics space and other things. Um, some of this may also be on the kind of softer side. >>How do I learn how to work in a more agile way and have a design thinking mindset, have a product mindset, but then it's really how's that going to change my role in the future. And how do I actually, for lack of a better word, start to embed these practices in my job in a way that I'm actually learning these skills and it will stick. And how do you actually manage that co culture change? Um, for lack of better word over time. That was probably the biggest thing I picked up from yesterday was just some of this talk around change management and culture, uh, which is, you know, we, we have a lot of, for lack of better word techie. Cause if this conference would like to think about all the cool stuff that technology doing, but the big lesson learned is really, you know, you actually have to make the stick inside an organization. >>And in the last year, Kevin, I'm curious about the adoption because you know, everything we've seen so much acceleration in the last year that digital acceleration, the acceleration in automation, we've also seen tremendous, uh, people and from a cultural perspective, I'd love to, for you to shed some light on what you've seen since you've rolled this product out, how is the pandemic, has it been an enabler of that change management and that cultural change, which historically is very hard to do. >>It's very hard. And I think this, if, if I want to CFO or COO two years ago and talked about the skills gap in what was happening, the organization, I would probably get someone that would be on and say, okay, yeah, that, that, that is happening. We need to think about this, but I got 50 other things I need to worry about. You know, I think over the past year a while, things like, you know, TA TA, well, time is a big, uh, luxury or having excess time is a big luxury that most people don't have. I think there's a recognition that, um, it's a challenging work environment right now. We're trying to get more done. People are not in person. Um, people have, you know, there's issues with, with mental health and other challenges and there's, uh, almost like a renewed focus on how do we make employees lives better and better can mean different things. >>But when I think about it, it's, it's giving people a hope that they have a future career path, that their job is not going to be eliminated, that they're developing the right skills and they're being given the capacity to actually do that now. And so a lot of the discussions have really been are around that fact. And I would say probably more so than the traditional just cost saving discussion than most automation, um, threads in with RPA begin with this really, you know, became, um, we need to do this and we need to, you know, send a message to our employees that we really care about you. And this is something that is really going to be us investing in you as a perk in the future. >>What's the role of the head of human capital management in the context of automation? Is she the champion? Is she the therapist? Is she the change agent? Well, how do you see that? >>Well, clearly he should have been talking to the head of people, um, two years ago. We even, because, uh, the way I think about it, and I think a lot of people in my role think about it is, you know, a CFO really looks after the financial health of the company. Um, the focus for us is looking after the people, health of the company, right? And so I think, um, in my career, what I've learned is that change is constant. We all know this and, um, change for people is difficult. So the way I think about introducing new technology, introducing automation, introducing anything that changes or being forced to change because of something like a pandemic, um, what I really ended up thinking a lot about is how does that impact people and how do we, how do we help them through it? Um, so that's my lens. And I think that's a chief people officer lens to all of this, but makes a perfect partnership with platforms that make this easy for us. Because if you can imagine, uh, a C-suite person comes to, uh, comes to an HR department and says, tell me what we should do here. How do we develop all our people? And it's, it's an overwhelming task. What pro edge does is just beautifully delivers this on a platter, um, in a way that we could never do manually. So it's >>Talk to me a little bit Bettina about the last year and a half. And obviously as being the chief people, officer, you came in, you said about five months ago, but obviously during a very, very challenging time, I always think that the employee experience is directly related to the customer experience. I see them as inextricably linked, how have you been able to foster a good employee experience in your time here in a very strange world so that the customer experience, I mean, you guys are a fast moving company, 8,000 plus customers. So that, that customer experience is a stellar as UI path has always had to be. >>Yeah, I think for us, it came down to just some simple things. Um, one is just being flexible. Uh, there was not a one size fits all. We had to recognize that we have to meet people in a place that works for them, everybody, uh, dealt with a different reality and the same for our customers. Um, and I agree with you. I think employees that feel enabled that feel safe, that feel they have a future, um, have a much different relationship with their customers, um, then employees that are worried about their safety and security and whatnot. So we really took an approach of flexibility, safety, um, meeting people where they are jumping in when there were big crises in India and whatnot to really, really take care of our people and help them understand that we're here for >>Big impact on mental health. Did you see that, um, there was an insert in the wall street journal. I think it was last week, uh, women at work. Um, and it was a stat in there. I don't know if you're a working mom, but it said that, uh, 30, it was Qualtrics was the source. 30% of working moms said their mental health had declined since the pandemic. Interestingly only 15. I said only 15% of working dads. Um, so that was sort of interesting, uh, and notable, uh, but you know, to your point, CFO, financial health of the company, the chief people officer, the, the human capital health. Yeah. >>Um, very much so. And by the way, I'm not surprised by that stat as a woman. >>I thought it was, I thought it was low. I was talking to my wife about it the other day. She's not a working mom, but she's like my mental health, even though I'm not a working mom, I have my mental health. I'm a working dad, but, but I got it easier than she does, but, but, and I'm not surprised at the disparity. I'm surprised that the only 30% and 50%, I think it's a lot higher than that. And people may be just like, I don't know if that's actually, maybe some people like working at home and that's, I could see that both sides of that equation. Yeah. >>There's also a stigma around mental health that we've, that's been addressed in. So even during the Olympic coverage this last summer, but having your team be really focused and enabled and knowing that they took to your point, Kevin, from an upscale perspective, that they have a path where they can go, they can increase their own value to the company. >>I completely agree. And I think, uh, other studies show that what people really want is a future at work. And, and this is what I think privilege dresses. Beautiful. >>Yeah. It's interesting. Right. Cause I think when you talk about some of the mental health challenges, I think it can get down very quickly to a cab just on this crazy schedule or I'm on zoom for 14 hours a day. And I, I don't have the time to breathe in my time commuting where I may have had time to decompress. It's just been replaced with more meetings. And I think that that may be the, like the surface issue, but I actually think if you go below the surface, not being in the office, not having some of the in-person networking, not having some of that creates anxiety about the future. And you're not really sure around, okay, what does my career path look like? I may not be getting the amount of career counseling that I used to get just by impromptu conversations or, you know, just by more traditional ways. Um, but I think the reality is when we look at the way most companies are thinking about their future work models. It's not going to go back to the way the world operated two years ago, it's, we're going to be in some sort of hybrid model. And so it really becomes more important to actually dig below where maybe some of the challenges were in the passengers, not surfaced. And I think upskilling and thinking about, um, kind of role skills and roles, it just becomes a much more important conversation. >>Absolutely. Last question, Bettina for you, we're almost out of time, but you started this in the, in financial, in the finance organization. What do you see over the next couple of years in terms of being very much UI path land and expand with your customers? Where do you see it rolling out across two iPads. >>We're already talking to our sales enablement group. Um, for a couple of reasons we want them to experience it. We want them to have also, we want them to have the conversations with our customers much like what we learned yesterday, right? It's a multi-dimensional conversation. It's not just a financial ROI, it's a people journey, change management. So we'll, we're taking it to our sales enablement group. We're absolutely gonna use it in HR, uh, obviously. Um, and I, I would just think we'll use it in two years. It'll be enterprise wide >>Different is pro edge in the marketplace. And just in, particularly in terms of its business impact. >>Yeah. I take a stab. So when we think about the challenge in a topic like digital upskilling, I think in traditional approaches to learning, it would be okay, we're going to enroll someone in a learning program. You know, you're going to go through, do certain amount of self study. Maybe there's a class, the some classroom based training. And that's it. I think for us, we saw two different challenges on both sides of that. One was trying to identify who needs to learn, what, and what part of the organization, why is that important? What an executive may need to learn is going to be different from what someone who does the transaction processing, uh, for their, their full-time job needs to learn and learning kind of from basic digital acumen through kind of hands-on skills. What are the different, um, pieces? I think probably the more interesting part is the back end of that. >>And thinking about, you know, how do you actually put these skills into practice and how do you put scale? One of the buzzwords that's thrown around at this conference a lot is the concept of citizen led automation as a topic. And really how, how do you have your, does this users building bots or creating data dashboards or doing other things that is, um, that's challenging. So as we design the product, what we really wanted to think about was that end to end journey from kind of the point of identifying skills through the point of scaling a citizen led effort. It's one of the things we're really excited to be working with UI path on is one of the core technologies that we, that we view in this ecosystem is really thinking about how do you make that happen? And if the outcome is not just people are new things, but the outcome are, people are actually creating solutions that are, that are having an impact on their job on a day to day basis. We think that's a really powerful concept. >>It's really important work, what you guys are doing. Thank you both for joining David me on the program today, talking about this very interesting symbiotic relationship partners, PWC UI path customers. Really interesting, great work that you're doing. Thanks for joining us. Thank you so much for having us for Dave Volante. I'm Lisa Martin. You're watching the cube live from Las Vegas at the Bellagio UI path forward for it. We'll be right back, stick around.