(upbeat music) >> Hello, and welcome to Supercloud2. I'm John Furrier, host of theCUBE here. We're exploring all the new Supercloud trends around multiple clouds, hyper scale gaps in their systems, new innovations, new applications, new companies, new products, new brands emerging from this big inflection point. Got a great guest who's going to unpack it with me today, Ramesh Prabagaran, who's the co-founder and CEO of Prosimo, CUBE alumni. Ramesh, legend in the industry, you've been around. You've seen many cycles. Welcome to Supercloud2. >> Thank you. You're being too kind. >> Well, you know, you guys have been a technical, great technical founding team, multiple ventures, multiple times around the track as they say, but now we're seeing something completely different. This is our second event, kind of we're doing to start the the ball rolling around unpacking this idea of Supercloud which evolved from a riff with me and Dave to now a working group paper, multiple definitions. People are saying they're Supercloud. CloudFlare says this is their version. Someone says there over there. Fitzi over there in the blog is always, you know, challenging us on our definitions, but it's, the consensus is though something's happening. >> Ramesh: Absolutely. >> And what's your take on this kind of big inflection point? >> Absolutely, so if you just look at kind of this in layers right, so you have hyper scalers that are innovating really quickly on underlying capabilities, and then you have enterprises adopting these technologies, right, there is a layer in the middle that I would say is largely missing, right? And one that addresses the gaps introduced by these new capabilities, by the hyper scalers. At the same time, one that actually spans, let's say multiple regions, multiple clouds and so forth. So that to me is kind of the Supercloud layer of sorts. One that helps enterprises adopt the underlying hyper scaler capabilities a lot faster, and at the same time brings a certain level of consistency and homogeneity also. >> What do you think the big driver of Supercloud is? Is it the industry growing up or is it the demand for new kinds of capabilities or both? Or just evolution? What's your take? >> I would say largely it depends on kind of who the entity is that you're talking about, right? And so I would say both. So if you look at one cohort here, it's adoption, right? If I have a externally facing digital presence, for example, then I'm going to scale that up and get to as many subscribers and users no matter what, right? And at that time it's a different set of problems. If you're looking at kind of traditional enterprise inward that are bringing apps into the cloud and so forth, it's a different set of care abouts, right? So both are, I would say, equally important problems to solve for. >> Well, one reality that we're definitely tracking, and it's not really a debate anymore, is hybrid. >> Ramesh: Yep >> Hybrid happened. It happened faster than most people thought. But, you know, we were talking about this in 2015 when it first got kicked around, but now you see hybrid in the cloud, on premises and the edge. This kind of forms that distributed computing paradigm that we've always been predicting. And so if that continues to play out the way it is, you're now going to have a completely distributed, connected internet and sets of systems, intra and external within companies. So again, the world is connected 100%. Everything's changing, right? >> And that introduces. >> It wasn't your grandfather's networking anymore or storage. The game is still the same, but the play, the components are acting differently. What's your take on this? >> Absolutely. No, absolutely. That's a very key important point, and it's one that we always ask our customers right at the front end, right? Because your starting assumptions matter. If you have workloads of workloads in the cloud and data center is something that you want to connect into, then you'll make decisions kind of keeping cloud in the center and then kind of bolt on technologies for what that means to extend it to the data center. If your center of gravity is in the data center, and then cloud is let's say 10% right now, but you see that growing, then what choices do you have? Right, do you want to bring your data center technologies into the cloud because you want that consistency in operations? Or do you want to start off fresh, right? So this is a really key, important question, and one that many of our customers are actually are grappling with, right? They have this notion that going cloud native is the right approach, but at the same time that means I have a bifurcation in kind of how do I operate my data center versus my cloud, right? Two different operating models, and slowly it'll shift over to one. But you're going to have to deal with dual reality for a while. >> I was talking to an old friend of mine, CIO, very experienced CIO. Big time company, large deployment, a lot of IT. I said, so what's the big trend everyone's telling me about IT's going. He goes no, not really. IT's not going away for me. It's going everywhere in the company. >> Ramesh: Exactly. >> So I need to scale my IT-like capabilities everywhere and then make it invisible. >> Ramesh: Correct. >> Which is essentially code words for saying it's going to be completely cloud native everywhere. This is what is happening. Do you agree? >> Absolutely right, and so if you look at what do enterprises care about it? The reason to go to the cloud is to get speed of operations, and it's apps, apps, apps, right? Do you ever have a conversation on networking and infrastructure first? No, that kind of gets brought into the conversation because you want to deal with users, applications and services, right? And so the end goal is essentially how do users communicate with apps and get the right experience, security and whatnot, and how do apps talk to each other and make sure that you get all of the connectivity and security requirements? Underneath the covers, what does this mean for infrastructure, networking, security and whatnot? It's actually going to be someone else's job, right? And you shouldn't have to think too much about it. So this whole notion of kind of making that transparent is real actually, right? But at the same time, us and all the guys that we talk to on the customer side, that's their job, right? Like we have to work towards making that transparent. Some are going to be in the form of capability, some are going to be driven by data, but that's really where the two worlds are going to come together. >> Lots of debates going on. We just heard from Bob Muglia here on Supercloud2. He said Supercloud's a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question that's being debated is is Supercloud a platform or an architecture in your view? >> Okay, that's a tough one actually. I'm going to side on the side on kind of the platform side right, and the reason for that is architectural choices are things that you make ahead of time. And you, once you're in, there really isn't a fork in the road, right? Platforms continue to evolve. You can iterate, innovate and so on and so forth. And so I'm thinking Supercloud is more of a platform because you do have a choice. Hey, am I going AWS, Azure, GCP. You make that choice. What is my center of gravity? You make that choice. That's kind of an architectural decision, right? Once you make that, then how do I make things work consistently across like two or three clouds? That's a platform choice. >> So who's responsible for the architecture as the platform, the vendor serving the platform or is the platform vendor agnostic? >> You know, this is where you have to kind of peel the onion in layers, right? If you talk about applications, you can't go to a developer team or an app team and say I want you to operate on Google or AWS. They're like I'll pick the cloud that I want, right? Now who are we talking to? The infrastructure guys and the networking guys, right? They want to make sure that it's not bifurcated. It's like, hey, I want to make sure whatever I build for AWS I can equally use that on Azure. I can equally use that on GCP. So if you're talking to more of the application centric teams who really want infrastructure to be transparent, they'll say, okay, I want to make this choice of whether this is AWS, Azure, GCP, and stick to that. And if you come kind of down the layers of the stack into infrastructure, they are thinking a little more holistically, a little more Supercloud, a little more multicloud, and that. >> That's a good point. So that brings up the deployment question. >> Ramesh: Exactly! >> I want to ask you the next question, okay, what is the preferred deployment in your opinion for a Supercloud narrative? Is it single instance, spread it around everywhere? What's the, do you have a single global instance or do you have everything synchronized? >> So I would say first layer of that Supercloud really kind of fix the holes that have been introduced as a result of kind of adopting the hyper scaler technologies, right? So each, the hyper scalers have been really good at innovating and providing really massive scale elastic capabilities, right? But once you start to build capabilities on top of that to help serve the application, there's a few holes start to show up. So first job of Supercloud really is to plug those holes, right? Second is can I get to an operating model, so that I can replicate this not just in a single region, but across multiple regions, same cloud, and then across multiple clouds, right? And so both of those need to be solved for in order to be (cross talking). >> So is that multiple instantiations of the stack or? >> Yeah, so this again depends on kind of the capability, right? So if you take a more solution view, and so I can speak for kind of networking security combined right? There you always take a solution view. You don't ever look at, you know, what does this mean for a single instance in a single region. You take a macro view, and then you then break it down into what does this mean for region, what does it mean for instance, what does this mean for AZs? And so on and so forth. So you kind of have to go top to bottom. >> Okay, welcome you down into the trap now. Okay, synchronizing the data, latency, these are all questions. So what does the network Supercloud look like to you? Because networking is big here. >> Ramesh: Yes, absolutely. >> This is what you guys do. >> Exactly, yeah. So the different set of problems as you go up the stack, right? So if you have hundreds of workloads in a single region, the set of problems you're dealing with there are kind of app native connectivity, how do I go from kind of east/west, all of those fun things, right? Which are usually bound in terms of latency. You don't have those challenges as much, but can you build your entire enterprise application architecture in one region? No, you're going to have to create multiple instances, right? So my data lake is invariably going to be in one place. My business logic is going to be spread across a few places. What does that bring in? I need to go across regions. Am I going to put those two regions right next to each other? No, I'm not going to, right? I'm going to have places in Europe. I'm going to have APAC, and I'm going to have a North American presence, and I need to bring all these things together. So this is where, back to your point, latency really matters, right? Because I need to be able to find out not just best path but also how do I reduce the millisecond, microseconds that my application cares about, which brings in a layer of optimization and then so on and so on and so forth. So this is what we call kind of to borrow the Prosimo language full stack networking, right? Because I'm not just dealing with how do I go from one region to another because that's laws of physics. I can only control so much. But there are a few elements up the application stack in software that you can tweak to actually bring these things closer and closer. >> And on that point, you're seeing security being talked a lot more at the network layer. So how do you secure the Supercloud at the network layer? What's that look like? >> Yeah, we've been grappling with essentially is security kind of foundational, and then is the network on top. And then we had an alternative viewpoint which is kind of network and then security on top. And the answer is actually it's neither, right? It's almost like a meshed up sandwich of sorts. So you need to have networking security work really well together, right? Case in point, I mean we were talking to a customer yesterday. He said, hey, I have my data lake in one region that needs to talk to an analytics service in a completely different region of a different cloud. These two things just need to be able to talk to each other, which means I need to bring elements of networking. I need to bring elements of security, secure access, app segmentation, all of those things. Very simple, I have an analytics service that needs to contact a data lake. That's what he starts with, but then before you know it, it actually brings up a whole stack underneath, so that's. >> VMware calls that cloud chaos. >> Ramesh: Yes, exactly. >> And then that's the halfway point between cloud smart. Cloud first, cloud chaos, cloud smart, and the next thing, you can skip that whole step. But again, again, it's pick your strategy right? Again, this comes back down to your earlier point. I want to ask you from a customer standpoint, you got the hyper scalers doing very, very well. >> Ramesh: Yep, absolutely. >> And I love what their Amazon's doing. I think Microsoft again though they had a little bit of downgrade are catching up fast, and they have their installed base. So you got the land of the installed bases. >> Correct. >> First and greater, better cloud. Install base getting better, almost as good, almost as good is a gift, but close. Now you have them specializing. Silicon, special silicon. So there's gaps for other services. >> Ramesh: Correct. >> And Amazon Web Services, Adam Selipsky's a open book saying, hey, we want our ecosystem to pick up these gaps and build on them. Go ahead, go to town. >> So this is where I think choices are tough, right? Because if you had one choice, you would work with it, and you would work around it, right? Now I have five different choices. Now what do I do? Our viewpoint is there are a bunch of things that say AWS does really, really well. Use that as a foundational layer, right? Like don't reinvent the wheel on those things. Transit gateways, global accelerators and whatnot, they exist for a reason. Billions of dollars have gone into building those things. Use that foundational layer, right? But what you want to build on top of that is actually driven by the application. The requirements of a lambda application that's serverless, it's very different than a packaged application that's responding for transactions, right? Like it's just completely very, very different. And so bring in the right set of capabilities required for those set of applications, and then you go based on that. This is also where I think whether something is a regional construct versus an overall global construct really, really matters, right? Because if you start with the assumption that everything is going to be built regionally, then it's someone else's job to make sure that all of these things are connected. But if you start with kind of the global purview, then the rest of them start to (cross talking). >> What are some of the things that the enterprises might want that are gaps that are going to be filled by the, by startups like you guys and the ecosystem because we're seeing the ecosystem form into two big camps. >> Ramesh: Yep. >> ISVs, which is an old school definition of independent software vendor, aka someone who writes software. >> Ramesh: Exactly. >> SaaS app. >> Ramesh: Correct. >> And then ecosystem software players that were once ISVs now have people building on top of them. >> Ramesh: Correct. >> They're building on top of the cloud. So you have that new hyper scale effect going on. >> Ramesh: Exactly. >> You got ISVs, which is software developers, software vendors. >> Ramesh: Correct. >> And ecosystems. >> Yep. >> What's that impact of that? Cause it's a new dynamic. >> Exactly, so if you take kind of enterprises, want to make sure that that their apps and the data center migrate to the cloud, new apps are developed the right way in the cloud, right? So that's kind of table stakes. So now what choices do they have? They listen to AWS and say, okay, I have all these cloud native services. I want to be able to instantiate all that. Now comes the interesting choice that they have to make. Do I go hire a whole bunch of people and do it myself or do I go there on the platform route, right? Because I made an architectural choice. Now I have to decide whether I want to do this myself or the platform choice. DIY works great for some, but you don't know what you're getting into, and it's people involved, right? People, process, all those fun things involved, right? So we show up there and say, you don't know what you don't know, right? Like because that's the nature of it. Why don't you invest in a platform like what what we provide, and then you actually build on top of it. We will, it's our job to make sure that we keep up with the innovation happening underneath the covers. And at the same time, this is not a closed ended system. You can actually build on top of our platform, right? And so that actually gives you a good mix. Now the care abouts are interesting. Some apps care about experience. Some apps care about latency. Some apps are extremely charty and extremely data intensive, but nobody wants to pay for it, right? And so it's a interesting Jenga that you have to play between experience versus security versus cost, right? And that makes kind of head of infrastructure and cloud platform teams' life really, really, really interesting. >> And this is why I love your background, and Stu Miniman, when he was with theCUBE, and now he's at Red Hat, we used to riff about the network and how network folks are now, those concepts are now up the top of the stack because the cloud is one big network effect. >> Ramesh: Exactly, correct. >> It's a computer. >> Yep, absolutely. No, and case in point, right, like say we're in let's say in San Jose here or or Palo Alto here, and let's say my application is sitting in London, right? The cloud gives you different express lanes. I can go down to my closest pop location provided by AWS and then I can go ride that all the way up to up to London. It's going to give me better performance, low latency, but I'm going to have to incur some costs associated with it. Or I can go all the wild internet all the way from Palo Alta up to kind of the ingress point into London and then go access, but I'm spending time on the wild internet, which means all kinds of fun things happen, right? But I'm not paying much, but my experience is not going to be so great. So, and there are various degrees of shade in them, of gray in the middle, right? So how do you pick what? It all kind of is driven by the applications. >> Well, we certainly want you back for Supercloud3, our next version of this virtual/live event here in our Palo Alto studios. Really appreciate you coming on. >> Absolutely. >> While you're here, give a quick plug for the company. Next minute, we can take a minute to talk about the success of the company. >> Ramesh: Absolutely. >> I know you got a fresh financing this past year. Plenty of money in the bank, going to ride this new wave, Supercloud wave. Give us a quick plug. >> Absolutely, yeah. So three years going on to four this calendar year. So it's an interesting time for the company. We have proven that our technology, product and our initial customers are quite happy with it. Now comes essentially more of those and scale and so forth. That's kind of the interesting phase that we are in. Also heartened to see quite a few of kind of really large and dominant players in the market, partners, channels and so forth, invest in us to take this to the next set of customers. I would say there's been a dramatic shift in the conversation with our customers. The first couple of years or so of the company, we are about three years old right now, was really about us educating them. This is what you need. This is what you need. Now actually it's a lot of just pull, right? We've seen a good indication, as much as a hate RFIs, a good indication is the number of RFIs that show up at our door saying we want you to participate in this because we want to understand more, right? And so as a, I think we are at an interesting point of the, of that shift. >> RFIs always like do all this work and hope for the best. Pray for a deal. You know, you guys on the right side of history. If a customer asks with respect to Supercloud, multicloud, is that your focus? Is that the direction you guys are going into? >> Yeah, so I would say we are kind of both, right? Supercloud and multicloud because we, our customers are hybrid, multiple clouds, all of the above, right? Our main pitch and kind of value back to the customers is go embrace cloud native because that's the right approach, right? It doesn't make sense to go reinvent the wheel on that one, but then make a really good choice about whether you want to do this yourself or invest in a platform to make your life easy. Because we have seen this story play out with many many enterprises, right? They pick the right technologies. They do a simple POC overnight, and they say, yeah, I can make this work for two apps, right? And then they say, yes, I can make this work for 100. You go down a certain path. You hit a wall. You hit a wall, and it's a hard wall. It's like, no, there isn't a thing that you can go around it. >> A lot of dead bodies laying around. >> Ramesh: Exactly. >> Dead wall. >> And then they have to unravel around that, and then they come talk to us, and they say, okay, now what? Like help me, help me through this journey. So I would say to the extent that you can do this diligence ahead of time, do that, and then, and then pick the right platform. >> You've got to have the talent. And you got to be geared up. You got to know what you're getting into. >> Ramesh: Exactly. >> You got to have the staff to do this. >> And cloud talent and skillset in particular, I mean there's lots available but it's in pockets right? And if you look at kind of web three companies, they've gone and kind of amassed all those guys, right? So enterprises are not left with the cream of the crop. >> John: They might be coming back. >> Exactly, exactly, so. >> With this downturn. Ramesh, great to see you and thanks for contributing to Supercloud2, and again, love your team. Very technical team, and you're in the right side of history in this one. Congratulations. >> Ramesh: No, and thank you, thank you very much. >> Okay, this is Supercloud2. I'm John Furrier with Dave Vellante. We'll be back right after this short break. (upbeat music)

(gentle music) >> Okay, welcome back to Supercloud 2, live here in Palo Alto, California for our live stage performance. Supercloud 2 is our second Supercloud event. We're going to get these out as fast as we can every couple months. It's our second one, you'll see two and three this year. I'm John Furrier, my co-host, Dave Vellante. A panel here to break down the Supercloud momentum, the wave, and the developer impact that we bringing back Vittorio Viarengo, who's a VP for Cross-Cloud Services at VMware. Sarbjeet Johal, industry influencer and Analyst at StackPayne, his company, Cube alumni and Influencer. Sarbjeet, great to see you. Vittorio, thanks for coming back. >> Nice to be here. >> My pleasure. >> Vittorio, you just gave a keynote where we unpacked the cross-cloud services, what VMware is doing, how you guys see it, not just from VMware's perspective, but VMware looking out broadly at the industry and developers came up and you were like, "Developers, developer, developers", kind of a goof on the Steve Ballmer famous meme that everyone's seen. This is a huge star, sorry, I mean a big piece of it. The developers are the canary in the coal mines. They're the ones who are being asked to code the digital transformation, which is fully business transformation and with the market the way it is right now in terms of the accelerated technology, every enterprise grade business model's changing. The technology is evolving, the builders are kind of, they want go faster. I'm saying they're stuck in a way, but that's my opinion, but there's a lot of growth. >> Yeah. >> The impact, they got to get released up and let it go. Those developers need to accelerate faster. It's been a big part of productivity, and the conversations we've had. So developer impact is huge in Supercloud. What's your, what do you guys think about this? We'll start with you, Sarbjeet. >> Yeah, actually, developers are the masons of the digital empires I call 'em, right? They lay every brick and build all these big empires. On the left side of the SDLC, or the, you know, when you look at the system operations, developer is number one cost from economic side of things, and from technology side of things, they are tech hungry people. They are developers for that reason because developer nights are long, hours are long, they forget about when to eat, you know, like, I've been a developer, I still code. So you want to keep them happy, you want to hug your developers. We always say that, right? Vittorio said that right earlier. The key is to, in this context, in the Supercloud context, is that developers don't mind mucking around with platforms or APIs or new languages, but they hate the infrastructure part. That's a fact. They don't want to muck around with servers. It's friction for them, it is like they don't want to muck around even with the VMs. So they want the programmability to the nth degree. They want to automate everything, so that's how they think and cloud is the programmable infrastructure, industrialization of infrastructure in many ways. So they are happy with where we are going, and we need more abstraction layers for some developers. By the way, I have this sort of thinking frame for last year or so, not all developers are same, right? So if you are a developer at an ISV, you behave differently. If you are a developer at a typical enterprise, you behave differently or you are forced to behave differently because you're not writing software.- >> Well, developers, developers have changed, I mean, Vittorio, you and I were talking earlier on the keynote, and this is kind of the key point is what is a developer these days? If everything is software enabled, I mean, even hardware interviews we do with Nvidia, and Amazon and other people building silicon, they all say the same thing, "It's software on a chip." So you're seeing the role of software up and down the stack and the role of the stack is changing. The old days of full stack developer, what does that even mean? I mean, the cloud is a half a stack kind of right there. So, you know, developers are certainly more agile, but cloud native, I mean VMware is epitome of operations, IT operations, and the Tan Zoo initiative, you guys started, you went after the developers to look at them, and ask them questions, "What do you need?", "How do you transform the Ops from virtualization?" Again, back to your point, so this hardware abstraction, what is software, what is cloud native? It's kind of messy equation these days. How do you guys grokel with that? >> I would argue that developers don't want the Supercloud. I dropped that up there, so, >> Dave: Why not? >> Because developers, they, once they get comfortable in AWS or Google, because they're doing some AI stuff, which is, you know, very trendy right now, or they are in IBM, any of the IPA scaler, professional developers, system developers, they love that stuff, right? Yeah, they don't, the infrastructure gets in the way, but they're just, the problem is, and I think the Supercloud should be driven by the operators because as we discussed, the operators have been left behind because they're busy with day-to-day jobs, and in most cases IT is centralized, developers are in the business units. >> John: Yeah. >> Right? So they get the mandate from the top, say, "Our bank, they're competing against". They gave teenagers or like young people the ability to do all these new things online, and Venmo and all this integration, where are we? "Oh yeah, we can do it", and then build it, and then deploy it, "Okay, we caught up." but now the operators are back in the private cloud trying to keep the backend system running and so I think the Supercloud is needed for the primarily, initially, for the operators to get in front of the developers, fit in the workflow, but lay the foundation so it is secure.- >> So, so I love this thinking because I love the rift, because the rift points to what is the target audience for the value proposition and if you're a developer, Supercloud enables you so you shouldn't have to deal with Supercloud. >> Exactly. >> What you're saying is get the operating environment or operating system done properly, whether it's architecture, building the platform, this comes back to architecture platform conversations. What is the future platform? Is it a vendor supplied or is it customer created platform? >> Dave: So developers want best to breed, is what you just said. >> Vittorio: Yeah. >> Right and operators, they, 'cause developers don't want to deal with governance, they don't want to deal with security, >> No. >> They don't want to deal with spinning up infrastructure. That's the role of the operator, but that's where Supercloud enables, to John's point, the developer, so to your question, is it a platform where the platform vendor is responsible for the architecture, or there is it an architectural standard that spans multiple clouds that has to emerge? Based on what you just presented earlier, Vittorio, you are the determinant of the architecture. It's got to be open, but you guys determine that, whereas the nirvana is, "Oh no, it's all open, and it just kind of works." >> Yeah, so first of all, let's all level set on one thing. You cannot tell developers what to do. >> Dave: Right, great >> At least great developers, right? Cannot tell them what to do. >> Dave: So that's what, that's the way I want to sort of, >> You can tell 'em what's possible. >> There's a bottle on that >> If you tell 'em what's possible, they'll test it, they'll look at it, but if you try to jam it down their throat, >> Yeah. >> Dave: You can't tell 'em how to do it, just like your point >> Let me answer your answer the question. >> Yeah, yeah. >> So I think we need to build an architect, help them build an architecture, but it cannot be proprietary, has to be built on what works in the cloud and so what works in the cloud today is Kubernetes, is you know, number of different open source project that you need to enable and then provide, use this, but when I first got exposed to Kubernetes, I said, "Hallelujah!" We had a runtime that works the same everywhere only to realize there are 12 different distributions. So that's where we come in, right? And other vendors come in to say, "Hey, no, we can make them all look the same. So you still use Kubernetes, but we give you a place to build, to set those operation policy once so that you don't create friction for the developers because that's the last thing you want to do." >> Yeah, actually, coming back to the same point, not all developers are same, right? So if you're ISV developer, you want to go to the lowest sort of level of the infrastructure and you want to shave off the milliseconds from to get that performance, right? If you're working at AWS, you are doing that. If you're working at scale at Facebook, you're doing that. At Twitter, you're doing that, but when you go to DMV and Kansas City, you're not doing that, right? So your developers are different in nature. They are given certain parameters to work with, certain sort of constraints on the budget side. They are educated at a different level as well. Like they don't go to that end of the degree of sort of automation, if you will. So you cannot have the broad stroking of developers. We are talking about a citizen developer these days. That's a extreme low, >> You mean Low-Code. >> Yeah, Low-Code, No-code, yeah, on the extreme side. On one side, that's citizen developers. On the left side is the professional developers, when you say developers, your mind goes to the professional developers, like the hardcore developers, they love the flexibility, you know, >> John: Well app, developers too, I mean. >> App developers, yeah. >> You're right a lot of, >> Sarbjeet: Infrastructure platform developers, app developers, yes. >> But there are a lot of customers, its a spectrum, you're saying. >> Yes, it's a spectrum >> There's a lot of customers don't want deal with that muck. >> Yeah. >> You know, like you said, AWS, Twitter, the sophisticated developers do, but there's a whole suite of developers out there >> Yeah >> That just want tools that are abstracted. >> Within a company, within a company. Like how I see the Supercloud is there shouldn't be anything which blocks the developers, like their view of the world, of the future. Like if you're blocked as a developer, like something comes in front of you, you are not developer anymore, believe me, (John laughing) so you'll go somewhere else >> John: First of all, I'm, >> You'll leave the company by the way. >> Dave: Yeah, you got to quit >> Yeah, you will quit, you will go where the action is, where there's no sort of blockage there. So like if you put in front of them like a huge amount of a distraction, they don't like it, so they don't, >> Well, the idea of a developer, >> Coming back to that >> Let's get into 'cause you mentioned platform. Get year in the term platform engineering now. >> Yeah. >> Platform developer. You know, I remember back in, and I think there's still a term used today, but when I graduated my computer science degree, we were called "Software engineers," right? Do people use that term "Software engineering", or is it "Software development", or they the same, are they different? >> Well, >> I think there's a, >> So, who's engineering what? Are they engineering or are they developing? Or both? Well, I think it the, you made a great point. There is a factor of, I had the, I was blessed to work with Adam Bosworth, that is the guy that created some of the abstraction layer, like Visual Basic and Microsoft Access and he had so, he made his whole career thinking about this layer, and he always talk about the professional developers, the developers that, you know, give him a user manual, maybe just go at the APIs, he'll build anything, right, from system engine, go down there, and then through obstruction, you get the more the procedural logic type of engineers, the people that used to be able to write procedural logic and visual basic and so on and so forth. I think those developers right now are a little cut out of the picture. There's some No-code, Low-Code environment that are maybe gain some traction, I caught up with Adam Bosworth two weeks ago in New York and I asked him "What's happening to this higher level developers?" and you know what he is told me, and he is always a little bit out there, so I'm going to use his thought process here. He says, "ChapGPT", I mean, they will get to a point where this high level procedural logic will be written by, >> John: Computers. >> Computers, and so we may not need as many at the high level, but we still need the engineers down there. The point is the operation needs to get in front of them >> But, wait, wait, you seen the ChatGPT meme, I dunno if it's a Dilbert thing where it's like, "Time to tic" >> Yeah, yeah, yeah, I did that >> "Time to develop the code >> Five minutes, time to decode", you know, to debug the codes like five hours. So you know, the whole equation >> Well, this ChatGPT is a hot wave, everyone's been talking about it because I think it illustrates something that's NextGen, feels NextGen, and it's just getting started so it's going to get better. I mean people are throwing stones at it, but I think it's amazing. It's the equivalent of me seeing the browser for the first time, you know, like, "Wow, this is really compelling." This is game-changing, it's not just keyword chat bots. It's like this is real, this is next level, and I think the Supercloud wave that people are getting behind points to that and I think the question of Ops and Dev comes up because I think if you limit the infrastructure opportunity for a developer, I think they're going to be handicapped. I mean that's a general, my opinion, the thesis is you give more aperture to developers, more choice, more capabilities, more good things could happen, policy, and that's why you're seeing the convergence of networking people, virtualization talent, operational talent, get into the conversation because I think it's an infrastructure engineering opportunity. I think this is a seminal moment in a new stack that's emerging from an infrastructure, software virtualization, low-code, no-code layer that will be completely programmable by things like the next Chat GPT or something different, but yet still the mechanics and the plumbing will still need engineering. >> Sarbjeet: Oh yeah. >> So there's still going to be more stuff coming on. >> Yeah, we have, with the cloud, we have made the infrastructure programmable and you give the programmability to the programmer, they will be very creative with that and so we are being very creative with our infrastructure now and on top of that, we are being very creative with the silicone now, right? So we talk about that. That's part of it, by the way. So you write the code to the particle's silicone now, and on the flip side, the silicone is built for certain use cases for AI Inference and all that. >> You saw this at CES? >> Yeah, I saw at CES, the scenario is this, the Bosch, I spoke to Bosch, I spoke to John Deere, I spoke to AWS guys, >> Yeah. >> They were showcasing their technology there and I was spoke to Azure guys as well. So the Bosch is a good example. So they are building, they are right now using AWS. I have that interview on camera, I will put it some sometime later on there online. So they're using AWS on the back end now, but Bosch is the number one, number one or number two depending on what day it is of the year, supplier of the componentry to the auto industry, and they are creating a platform for our auto industry, so is Qualcomm actually by the way, with the Snapdragon. So they told me that customers, their customers, BMW, Audi, all the manufacturers, they demand the diversity of the backend. Like they don't want all, they, all of them don't want to go to AWS. So they want the choice on the backend. So whatever they cook in the middle has to work, they have to sprinkle the data for the data sovereign side because they have Chinese car makers as well, and for, you know, for other reasons, competitive reasons and like use. >> People don't go to, aw, people don't go to AWS either for political reasons or like competitive reasons or specific use cases, but for the most part, generally, I haven't met anyone who hasn't gone first choice with either, but that's me personally. >> No, but they're building. >> Point is the developer wants choice at the back end is what I'm hearing, but then finish that thought. >> Their developers want the choice, they want the choice on the back end, number one, because the customers are asking for, in this case, the customers are asking for it, right? But the customers requirements actually drive, their economics drives that decision making, right? So in the middle they have to, they're forced to cook up some solution which is vendor neutral on the backend or multicloud in nature. So >> Yeah, >> Every >> I mean I think that's nirvana. I don't think, I personally don't see that happening right now. I mean, I don't see the parody with clouds. So I think that's a challenge. I mean, >> Yeah, true. >> I mean the fact of the matter is if the development teams get fragmented, we had this chat with Kit Colbert last time, I think he's going to come on and I think he's going to talk about his keynote in a few, in an hour or so, development teams is this, the cloud is heterogenous, which is great. It's complex, which is challenging. You need skilled engineering to manage these clouds. So if you're a CIO and you go all in on AWS, it's hard. Then to then go out and say, "I want to be completely multi-vendor neutral" that's a tall order on many levels and this is the multicloud challenge, right? So, the question is, what's the strategy for me, the CIO or CISO, what do I do? I mean, to me, I would go all in on one and start getting hedges and start playing and then look at some >> Crystal clear. Crystal clear to me. >> Go ahead. >> If you're a CIO today, you have to build a platform engineering team, no question. 'Cause if we agree that we cannot tell the great developers what to do, we have to create a platform engineering team that using pieces of the Supercloud can build, and let's make this very pragmatic and give examples. First you need to be able to lay down the run time, okay? So you need a way to deploy multiple different Kubernetes environment in depending on the cloud. Okay, now we got that. The second part >> That's like table stakes. >> That are table stake, right? But now what is the advantage of having a Supercloud service to do that is that now you can put a policy in one place and it gets distributed everywhere consistently. So for example, you want to say, "If anybody in this organization across all these different buildings, all these developers don't even know, build a PCI compliant microservice, They can only talk to PCI compliant microservice." Now, I sleep tight. The developers still do that. Of course they're going to get their hands slapped if they don't encrypt some messages and say, "Oh, that should have been encrypted." So number one. The second thing I want to be able to say, "This service that this developer built over there better satisfy this SLA." So if the SLA is not satisfied, boom, I automatically spin up multiple instances to certify the SLA. Developers unencumbered, they don't even know. So this for me is like, CIO build a platform engineering team using one of the many Supercloud services that allow you to do that and lay down. >> And part of that is that the vendor behavior is such, 'cause the incentive is that they don't necessarily always work together. (John chuckling) I'll give you an example, we're going to hear today from Western Union. They're AWS shop, but they want to go to Google, they want to use some of Google's AI tools 'cause they're good and maybe they're even arguably better, but they're also a Snowflake customer and what you'll hear from them is Amazon and Snowflake are working together so that SageMaker can be integrated with Snowflake but Google said, "No, you want to use our AI tools, you got to use BigQuery." >> Yeah. >> Okay. So they say, "Ah, forget it." So if you have a platform engineering team, you can maybe solve some of that vendor friction and get competitive advantage. >> I think that the future proximity concept that I talk about is like, when you're doing one thing, you want to do another thing. Where do you go to get that thing, right? So that is very important. Like your question, John, is that your point is that AWS is ahead of the pack, which is true, right? They have the >> breadth of >> Infrastructure by a lot >> infrastructure service, right? They breadth of services, right? So, how do you, When do you bring in other cloud providers, right? So I believe that you should standardize on one cloud provider, like that's your primary, and for others, bring them in on as needed basis, in the subsection or sub portfolio of your applications or your platforms, what ever you can. >> So yeah, the Google AI example >> Yeah, I mean, >> Or the Microsoft collaboration software example. I mean there's always or the M and A. >> Yeah, but- >> You're going to get to run Windows, you can run Windows on Amazon, so. >> By the way, Supercloud doesn't mean that you cannot do that. So the perfect example is say that you're using Azure because you have a SQL server intensive workload. >> Yep >> And you're using Google for ML, great. If you are using some differentiated feature of this cloud, you'll have to go somewhere and configure this widget, but what you can abstract with the Supercloud is the lifecycle manage of the service that runs on top, right? So how does the service get deployed, right? How do you monitor performance? How do you lifecycle it? How you secure it that you can abstract and that's the value and eventually value will win. So the customers will find what is the values, obstructing in making it uniform or going deeper? >> How about identity? Like take identity for instance, you know, that's an opportunity to abstract. Whether I use Microsoft Identity or Okta, and I can abstract that. >> Yeah, and then we have APIs and standards that we can use so eventually I think where there is enough pain, the right open source will emerge to solve that problem. >> Dave: Yeah, I can use abstract things like object store, right? That's pretty simple. >> But back to the engineering question though, is that developers, developers, developers, one thing about developers psychology is if something's not right, they say, "Go get fixing. I'm not touching it until you fix it." They're very sticky about, if something's not working, they're not going to do it again, right? So you got to get it right for developers. I mean, they'll maybe tolerate something new, but is the "juice worth the squeeze" as they say, right? So you can't go to direct say, "Hey, it's, what's a work in progress? We're going to get our infrastructure together and the world's going to be great for you, but just hang tight." They're going to be like, "Get your shit together then talk to me." So I think that to me is the question. It's an Ops question, but where's that value for the developer in Supercloud where the capabilities are there, there's less friction, it's simpler, it solves the complexity problem. I don't need these high skilled labor to manage Amazon. I got services exposed. >> That's what we talked about earlier. It's like the Walmart example. They basically, they took away from the developer the need to spin up infrastructure and worry about all the governance. I mean, it's not completely there yet. So the developer could focus on what he or she wanted to do. >> But there's a big, like in our industry, there's a big sort of flaw or the contention between developers and operators. Developers want to be on the cutting edge, right? And operators want to be on the stability, you know, like we want governance. >> Yeah, totally. >> Right, so they want to control, developers are like these little bratty kids, right? And they want Legos, like they want toys, right? Some of them want toys by way. They want Legos, they want to build there and they want make a mess out of it. So you got to make sure. My number one advice in this context is that do it up your application portfolio and, or your platform portfolio if you are an ISV, right? So if you are ISV you most probably, you're building a platform these days, do it up in a way that you can say this portion of our applications and our platform will adhere to what you are saying, standardization, you know, like Kubernetes, like slam dunk, you know, it works across clouds and in your data center hybrid, you know, whole nine yards, but there is some subset on the next door systems of innovation. Everybody has, it doesn't matter if you're DMV of Kansas or you are, you know, metaverse, right? Or Meta company, right, which is Facebook, they have it, they are building something new. For that, give them some freedom to choose different things like play with non-standard things. So that is the mantra for moving forward, for any enterprise. >> Do you think developers are happy with the infrastructure now or are they wanting people to get their act together? I mean, what's your reaction, or you think. >> Developers are happy as long as they can do their stuff, which is running code. They want to write code and innovate. So to me, when Ballmer said, "Developer, develop, Developer, what he meant was, all you other people get your act together so these developers can do their thing, and to me the Supercloud is the way for IT to get there and let developer be creative and go fast. Why not, without getting in trouble. >> Okay, let's wrap up this segment with a super clip. Okay, we're going to do a sound bite that we're going to make into a short video for each of you >> All right >> On you guys summarizing why Supercloud's important, why this next wave is relevant for the practitioners, for the industry and we'll turn this into an Instagram reel, YouTube short. So we'll call it a "Super clip. >> Alright, >> Sarbjeet, you want, you want some time to think about it? You want to go first? Vittorio, you want. >> I just didn't mind. (all laughing) >> No, okay, okay. >> I'll do it again. >> Go back. No, we got a fresh one. We'll going to already got that one in the can. >> I'll go. >> Sarbjeet, you go first. >> I'll go >> What's your super clip? >> In software systems, abstraction is your friend. I always say that. Abstraction is your friend, even if you're super professional developer, abstraction is your friend. We saw from the MFC library from C++ days till today. Abstract, use abstraction. Do not try to reinvent what's already being invented. Leverage cloud, leverage the platform side of the cloud. Not just infrastructure service, but platform as a service side of the cloud as well, and Supercloud is a meta platform built on top of these infrastructure services from three or four or five cloud providers. So use that and embrace the programmability, embrace the abstraction layer. That's the key actually, and developers who are true developers or professional developers as you said, they know that. >> Awesome. Great super clip. Vittorio, another shot at the plate here for super clip. Go. >> Multicloud is awesome. There's a reason why multicloud happened, is because gave our developers the ability to innovate fast and ever before. So if you are embarking on a digital transformation journey, which I call a survival journey, if you're not innovating and transforming, you're not going to be around in business three, five years from now. You have to adopt the Supercloud so the developer can be developer and keep building great, innovating digital experiences for your customers and IT can get in front of it and not get in trouble together. >> Building those super apps with Supercloud. That was a great super clip. Vittorio, thank you for sharing. >> Thanks guys. >> Sarbjeet, thanks for coming on talking about the developer impact Supercloud 2. On our next segment, coming up right now, we're going to hear from Walmart enterprise architect, how they are building and they are continuing to innovate, to build their own Supercloud. Really informative, instructive from a practitioner doing it in real time. Be right back with Walmart here in Palo Alto. Thanks for watching. (gentle music)

>>Hi, everybody. We're wrapping up day two of AWS reinforced the Cube's continuous coverage. My business partner, John furrier, and co-host is actually a Monaco, um, you know, getting ready to do a big crypto show over there. So they'll be reporting from there tomorrow. Check that out in the cube.net. Jeff Swain is here. He is the vice president of global programs store and tech alliances at CrowdStrike. Jeff, thanks for coming on. Thanks >>David. >>So tell us about your role, what store, help us understand that? >>Yeah, so CrowdStrike has a CrowdStrike store, which is, uh, effectively our marketplace within our application, and also available externally that allows customers to be able to review decide and trial products, not only from CrowdStrike, but also from our third party partners. So wherever we have a tech Alliance customer can come in, see the value of the integration, see how it works on our platform and the third parties platform, and then go and request a trial. So it's a very easy and dynamic way for a customer to understand that joint value proposition CrowdStrike has with various other, other vendors and our own products as well. >>So your role is to bring all these cool tech companies together and create incremental value. >>Yes. Um, we believe that the ecosystem is really a, a natural evolution of what's happened in terms of the crowd struck story. If you think that we started out with a, uh, you know, a very simple product in the very early days, 10, 10, 11 years ago, services company built a product. That product then became a platform with various modules in it. The next evolution of that is expanding out beyond our own platform and working into other areas of, of, of interest and value. So that's where the ecosystem comes into play. So you have to underpin that with some automations things like marketplaces and stores, you have to have integrations in place, joint applications and commercial vehicles to make that work. >>So I was walking around the other day and I, and it caught my eye and I sat there and listened for a better part of the presentation had to get back and do the queue, but it was a presentation between a CrowdStrike expert and an Okta expert. Yep. You know, better together was the whole thing. And, you know, I know it's kind of, and then they were describing how you guys compliment each other. So that would be an example, >>A perfect example. I mean, we, we, we compliment Okta and Okta complements us for very, in various different ways. And in fact, we sort of assemble that into different narratives that work well for our customers. So as an example with Okta, we ASEM, we work very well with them in zero trust. So we have a zero trust narrative that talks about how it works with Okta and also Zscaler. In fact, we have a, um, an Alliance through the cloud security Alliance where we're working to build practitioner guides, build, um, uh, a community of value across the different products to bring zero trust into some standardized, you know, uh, reference architectures and some standardized training that brings all of our products together for, for, for the user. That be example of a, of, one of the narratives that we have, they'd also play in our XDR narrative. Obviously XDR helps us bring telemetry in from different products. And again, we use XDR right across, you know, various, various, uh, tech >>Alliances. So, so take zero choice. So you'll take the concept of least privilege. Yep. And you'll apply that to what to end point to, you know, using identity Zscaler, you bring the cloud component. >>Correct. So then we are actually able to see how someone's traversing the entire organization. We can see who they are. We can see where they land. We can see what data they're accessing, where they're accessing. It gather a whole bunch of different telemetry around that and provide the security team with the ability to be able to see what someone's doing, enforce the, um, the, you know, access rights as, and where they need to see any anomalies or anomalous behavior within that and close it down before anything bad happens. So zero trust is a really important part of our, uh, of our, of, of, of our, um, narratives. >>And you have these plays or narratives with, with a bunch of ecosystem partners. Right? Correct. Mean, so take log management. >>Yep. >>Maybe add some context that, >>So, so around that happens, you may know we acquired, um, uh, humo, uh, right around that, where obviously we have to be able to ingest and have bridges out to a large variety of different platforms to be able to ship data into our platform. I mean, one of the values of humo is its ability to massively scale, um, and very, very easily cheaply bring, bring a lot of data into a simple place and have very fast searching. Well, what are you searching? You gotta go and have data sources. So, you know, very quickly we've built out a large number of integrations with, I think, over 30 partners to easily bring data into the Humira platform to let customers be able to have that advantage. >>So what role does AWS play in all this? >>AWS is a fantastic role in, um, both coordinating some of this in terms of, especially through the marketplace, the ability to, uh, coordinate our transactions between us and help us work together from a transactional basis, help the customer procure the right solutions together. But also AWS's nature. Natural, uh, inclination towards innovation means that they'll, they like to work with partners who, especially partners who are on their platform to drive a lot of innovation, to build out how customers are bringing more data together. Obviously it's beneficial to them in terms of the volumes of data that go computers that go across the AWS platform. But also they encourage us to work together. They, they, they say in some cases invest in those integrations. Um, they work with programs. They bring in third party reseller programs, uh, through C P O. So it gives us a, a platform gives us innovation. It gives us some structure. Um, it's been really exciting working with them. >>Now talk about CrowdStrike and your cloud strategy. How would you Des describe your cloud strategy? >>So we've been cloud native from day one. It's one of the, one of the founding principles of CrowdStrike. Um, as, as we were set up, uh, by a founder, so two elements, cloud native, and a single agent, and those two design principles have not been broken by us at any point through our history. It's very important that we, we stick to those two principles. Our cloud is, um, was born in AWS, um, and they've been supportive of us right through, right through our growth period. So we started out with one module, as I said, now we have, I think, 23 different modules and we're continually growing that. We also then have a lot of support for the cloud. So, you know, helping us understand what's happening within cloud environments so that our customers are better protected. In fact, the show here, we've announced two separate, um, uh, uh, incremental products to, to the cloud space. One that's very much focused on, um, adding, uh, better container or better visibility inside containers in our CNA product. And, um, and, and another area around how we do our threat hunting across the cloud. So we have a team of threat hunters, global best engineers who hunt right across our customers environments. We have a whole, whole bunch of additional cloud telemetry. So that's, that's been included into our, into our Overwatch threat hunting. >>So you'll ingest data from multiple clouds, right? You're running on AWS. Yes. But you can take data from anywhere from >>Anywhere, >>Including OnPrem. >>Um, so our sensor sits on laptops, servers, virtual servers devices. Do I devices wherever they need to say. Um, and then of it needs to be cloud connected. It comes into our, into our cloud. So we can, we can take information from instances in any cloud environment and any laptop, uh, to pretty much bring them in. And, uh, that's how it works, but it's a single cloud. I mean, our value proposition is that huge, um, uh, graph threat graph that we've built over the years, um, trillions and trillions of events per day, that we're now searching and using AI technologies to suite out. What's good. And what's bad. >>Yeah. So CrowdStrike, obviously we've reported on CrowdStrike in breaking analysis, a lot, CrowdStrike, Zscaler, Okta, a number of other, those, those companies you're partnering with all those guys, which is quite interesting. Yeah. You're all growing, you know, really nice, nice clips. I wonder, I always wonder in these situations, okay. As things get bigger and bigger and growth slows, we haven't seen that. See, you actually see the, we saw the cloud growth accelerating during the pandemic. Yeah. Right. But, but you know, you wonder, you see it all the time in this, in this industry is companies get big, they start doing M and a, they start getting it to adjacencies, you know, Google, apple, you know, uh, Cisco VMware, do you think you'll ever see a collision course with all these wonderful partners? Are we years away from that? Um, >>I think we're very careful with how we partner and who we partner with. Obviously we, we have discussions on what our future plans are to make sure that what we partner on is, is beneficial to both sides. Um, crowd strike itself. We're, we're growing all the time. You know, our platform has grown, as I said, the modules have grown, but in general, we've found is that our partners are taking the journey with us. Um, it's one of the advantages of, of the success that we've had is most of the partners want to be part of that journey rather than sort of, um, trying to go head on. But, you know, there's always opportunities for us to have open conversations and real dialogue to make sure that we do the right thing for the customer. And that's what drives everything that we do, you know, we're focused on the right products for the right >>Customers. What, what what's reinforcement like, what's the experience been? What, what's your takeaways from the show? >>Um, it's been a really excellent show for us in terms of, uh, getting out, meeting a lot, a lot of customers at a very decent senior level here. Actually's been very, very worthwhile. Um, we've had great response to the announcements that we've made. There's been a lot of, lot of activity through the booth, which is always great to see, um, from a, actually from a partnership perspective from my world, you know, I've had a large number of really great meetings with the AWSs leadership as well about what we can do together. Um, and the future looks really bright. >>Who's the, when you, when you think in thinking about, and I know you're not, you know, selling direct, but when you think about the constituencies, when you think about all the, the partners in your ecosystem that you're, you're building and collaborating with, who do you guys collectively talk to? You know, who do you appeal to? Is it the CISO? Is it the, you know, other security practitioners? Yeah. Is it the line of business? Is it the CIO architect who are the actors that you're sort of collaborating with in your customer >>Side? Yeah, it's really interesting obviously, cuz there's different personas depending on what it is that we're doing. Um, someone who's really interested in our log management narrative for example, is probably going to be maybe from the, the DevOps, um, uh, team or from, from that area for a C app. It's going to be someone in the cloud architecture, cloud security architecture space. Um, zero trust again will be someone who's got a bit of an identity, our area and privacy to them as well. Um, a lot of this comes up to the CISO and that's often our, you know, our, our, our economic buyer would be be in that space. But one of the things we have to do is we go into adjacent markets is learn the personas there and understand their habits and their buying cycles and, and, and build value propositions that work for those people. So it's an ongoing exercise. >>How do you see the CISO role evolving, uh, given, you know, cloud? One of my takeaways from Mr event is like, I feel like cloud is becoming the first line of defense. Mm-hmm <affirmative> the CISO and the developers becoming the second line of defense audit is like the third line of defense. Some people agree with that. Some people do so just merit bear said, no, no, it's all integrated into one thing. And I'm like, no, it's not, but okay. Yeah. But, but how is the CSO role evolving given that the cloud is becoming so much more prominent today? >>I think it's it's at this point, everyone said, you know, the CSO needs to evolve to being a direct member of the directly responsible to the board. This is something that we've all said for many years. Sure. If you look at what we see in the threat report, if you look at what we're seeing from the threat landscape, you know, the volume of threats that are coming through, not diminishing in any way, but in fact, the size and the impact of what they're doing is getting worse. So it, the risk that's being, um, uh, uh, that's being experienced is just getting worse all the time. However, we have different options for resolving that issue. You can go down a services led path with a, with an MDR player, like our file can complete, uh, process, or you can go down with an MSP. So the CISO's role is now not just on what products and how to Def, how to use them to best defend, but also what products, what services are available. >>What am I gonna invest in, in my team versus what am I going to push to a, to a, to a third party to look after for me. And we're seeing more and more companies at the going up the light up the, the, the enterprise stack, trusting us in our Falcon complete team, um, uh, with, with, with parts of their defense portfolio. So I think that role that you, you know, the CISO's role is developing all the time into something that's portfolio oriented. How am I getting value for service as well as value for money from products? It's a really interesting, it's really interesting development, um, in terms of what they have to deal with. Uh, you know, I still think that the, the visibility that you see from the endpoint is where's where it's where the, the Decron jewels are still it's where the data is. Mm-hmm <affirmative>. Um, and I think that's really why crowd strike is a unique proposition in that space. It's what >>We protect. So when you say the end point is where the data is, paint a picture of that. >>Well, if you think about, if a, if an actor is after at a personal information or IP, they're often going to be going down to the laptop or the, or the, or the virtual instance level to look for that within the weakest part, we've always said is people, um, and the more dive, the more open you are with that, the wider your audience there, the, the more risk you carry within that space, you know, we don't think endpoints laptops or phones, you know, servers, um, comput instances inside the cloud. They're all endpoint to us. Workloads is a better word. In fact, >>Those work, sorry, what's a better word >>Workloads >>Workloads. >>Okay. Yeah. We often talk about workloads rather than >>Is it data store and >>Endpoint? Yeah. If it's computer or not, it's, it's, it's basically, uh, it's a workload where, where we can put a sensor. How >>About a, how about a backup Corpus, uh, a backup backup Corpus of data? >>Well, I think if there's a, if there's a place that we can put a sensor on it to see whether it's being, you know, active or not, and we can track the telemetry from it, we would consider >>That sensor would be an agent. Yeah. An agent. Yeah. Yeah. Okay. And so you said single agent, >>We have one agent that runs all of our products this way, again, one of the design principles and, and the basics of our company, >>Because one of the things that we've seen, maybe tell me if you don't see this, is, is that a lot of times ransomware attackers will go after the, the, the backup Corpus mm-hmm <affirmative> disable it. Yeah. Because, you know, once you get that, you can't recover a hundred percent. Yeah. And they'll encrypt the, all the data on the network, and then they'll, they'll hold the backup Corpus hostage. >>This is one of the great advantages of how CrowdStrike and how our platform works. In fact, you know, um, a lot of other vendors talk in terms of, uh, you know, known bad known good, and, and, and indicators of compromise. Right. You know, I know this IP address has been compromised. I know that anything originating from here is bad. Um, what CrowdStrike looks at is, is, is we've built up a very, very, um, substantial, uh, library of what we call indicators of attack. Indications of attack are looking at the potential for attack. And whether, whether that in conjunction that specific piece of telemetry in conjunction with others makes the attack more likely. So for example, if someone, um, opens an email, we don't think that's necessarily, you know, a, a, a risk point, right. Um, but if someone opens an email and they click on an attachment, we think, well, maybe there's, there's, you know, that's happens billions of times a day, so still not bad, but if that then spills up, you know, a process, and if that process then starts to enumerate hard drives and start to look for backups, you know, we're getting more suspicious all the time. >>Um, and if they're then cause an encryption routine, we can be pretty certain at that point that what we've got in play is, is ransomware attack. Um, by looking at the holistic attack, the whole process of it, and having that sort of fingerprint of what that may look like. And in combining that with our knowledge of bad actors, our intelligence in the field, we've got a very good view on what may happen there. So exactly to your point, if we see, um, someone going after backups as part of a wider process that helps us identify that something of something bad is, is about to happen in terms of ransomware attack allows us to take action against it, put in the appropriate containment or blocking, >>And then explain. So, you know, when people hear agents, they're like, oh, another agent to manage, but I was talking to somebody the other day and saying, know, we're gonna integrate with the CrowdStrike agent because it's so robust. Correct. And what we are doing is, which is agent list is it's good, it's lightweight, but we can't get the data. Yep. You know, so explain that. So there's a trade off, right? I mean, you gotta manage an agent, right. But obviously it's working, your customers are, are adopting. >>So it's an extremely lightweight agent. That's always been the, the premise for this. And I think when George founded the company, one of the things he noticed was, you know, how long it was taking for someone to scan it, get us, get through a scan while they were trying to get an email out before a plane took off. And he said, you know, we can't have this. So, so he was looking at how do we make this as light as possible? Um, and, uh, and so that's one of been principle for us, right from day one. And you're right. Um, third parties do want to leverage our agent because of it's robustness. We look at pretty much everything that's happening as a telemetry event, once, once power hits the CPU through, till it drops out. So we've got very rich knowledge of what's happening on every single device or, or workload that's out there. >>And it's very usable for other people, as far as the customer's concerned, if a third party can use that information rather than have to deploy another agent, that's a huge win for the customer. I think we all know that proliferation of agents, Harrison, that's what, that was the old way of doing things. You know, people would acquire products and try and bundle 'em together and what they ended up with multiple agents competing for resources on the, on the system, by having one agent well defined, well architected, what we have is a modern, a modern software architecture to solve modern problems. >>Okay. So, uh, last question. Yep. When during the pandemic, we noticed that the, um, everything changed, obviously work from home remote work, and that the implications on the CISO were these permanent changes. And we reported on this and breaking analysis and other except endpoint, uh, you guys CrowdStrike, uh, uh, identity Okta got a boost, uh, cloud security, Zscaler. Yep. You know, got a boost, rethinking the network network. Security became top of mind that, and that we said is these are permanent changes, but now as we exit, but they were rushed as we exit the isolation economy. What can we expect going forward? >>I think to earlier point the ability for us to work across all of those areas and work better, you know, everyone was very much concentrating on delivered their own product as best as they could, as quickly as they could to meet the demands of the pandemic. Now we can go through a place of making sure that we work really, really well together as different units to solve the customer problem. So trim some of the trim trim, some of the, of, of, of the, the fat out of any integrations that we may have built quickly to solve a problem. Now we can focus on doing it really well. What we're seeing is a proliferation in our world of more applications in our store. So tighter integration inside our UI with our third party products, um, and a lot of demand for that. So really the, the customer experience is as seamless as possible. We talk about, you know, frictionless is what we want to see. Um, and that's, you know, the boost that the, the, the disruption got from the pan from the pandemic was fantastic start of the innovation. Right now, we have the opportunity to bring everything together, to really solve some excellent problems for customers, um, and make the world safer place. >>Jeff, great summary. Thank you for coming on. I'm gonna, I'm gonna give my quick take on, on this reinforc. I mean, I think very clearly AWS is, is enforcing the notion that that security is, is job one for them from the, the nitro chip, you know, all the way up the stack all the way through the culture. I mean, I think we heard that at, at this event. Um, I think you heard, you know, some great announcements, a lot of the stuff around, you know, threat detection and, and, and automation and, and, and reasoning, which is great. I don't think you heard a lot on how AWS are making the CISO's life simpler. I think a lot of that goes to the ecosystem. Mm-hmm <affirmative> maybe, uh, but the other thing is AWS leaving a lot of room, a lot of meat in the bone, as we like to say sometimes for the, for the ecosystem. >>Mm. Um, you know, security is a good example. I mean, you know, Microsoft makes a lot of money and security. AWS doesn't make a ton of money in security. It's just sort of comes with it. I think we're also seeing the changing role, the CISO, I think the cloud is becoming the first line of the fence, CISO and developers. The next line audit is really the third line and developer. The developer role is becoming increasingly important and, and frankly sophisticated, they gotta worry about securing the containers. They gotta worry about the run time. They have to worry about the platform as a service. And so, you know, developers need the team with the, with the, with the security operations team. So that's kind of my takeaway here. I think the event was, was, was good. It was not, it wasn't oversubscribed. I think people in, in Boston this time of year at the beach, um, whereas last 2019, you know, it was June. And so you get, you had a, a bigger attendance, but that's kind of my takeaway. Anything you'd add to that, Jeff, >>I think the quality has been here. Yeah. Um, you know, maybe not the quantity the quality has certainly been here. Um, I think, you know, there is, uh, a lot of innovation that's happening in the security industry. I think AWS has got some good products that they they're helping deliver, but as you said, they're there to help us support us and, and the other ISVs to really come together and build our best of breed overall solution that helps our customers and solve some of that complexity that you're seeing. And some of that uncertainty you're seeing is who has to solve what problem in the stack. Yeah. >>Well, thanks for that. Thanks for that. Thanks for help me wrap up here. The, the security space remains one that's highly fragmented, highly complex, you know, lack of talent is, is the, the problem that most organizations have. Lena smart of MongoDB doesn't have that problem nor does AWS, I guess cuz they're AWS and, and Mongo. Uh, but that's a wrap here from, from day two, the cube go to the cube.net. You'll see all these videos, youtube.com/silicon angle. If you want, you know, the YouTube link. Yeah. You can go there. Silicon angle.com is where we publish all the, the news of the day. wikibon.com for, for the research. This is Dave ante. Look for John furrier from Monica at, uh, the, the crypto event, uh, all this week. And we will see you next time. Thanks for watching.

(upbeat music) >> Hello everyone, welcome back to theCUBE's coverage of splunk.com 2021 virtual. We're here live in the Splunk studios. We're all here gettin all the action, all the stories. Garth Fort, senior vice president, Chief Product Officer at Splunk is here with me. CUBE alumni. Great to see you. Last time I saw you, we were at AWS now here at Splunk. Congratulations on the new role. >> Thank you. Great to see you again. >> Great keynote and great team. Congratulations. >> Thank you. Thank you. It's a lot of fun. >> So let's get into the keynote a little bit on the product. You're the Chief Product Officer. We interviewed Shawn Bice, who's also working with you as well. He's your boss. Talk about the, the next level, cause you're seeing some new enhancements. Let's get to the news first. Talk about the new enhancements. >> Yeah, this was actually a really fun keynote for me. So I think there was a lot of great stuff that came out of the rest of it. But I had the honor to actually showcase a lot of the product innovation, you know, since we did .conf last year, we've actually closed four different acquisitions. We shipped 43 major releases and we've done hundreds of small enhancements, like we're shipping code in the cloud every six weeks and we're shipping new versions twice a year for our Splunk Enterprise customers. And so this was kind of like if you've seen that movie Sophie's Choice, you know, where you have to pick one of your children, like this was a really hard, hard thing to pick. Cause we only had about 25 minutes, but we did like four demos that I think landed really well. The first was what we call ingest actions and you know, there's customers that are using, they start small with gigabytes and they go to terabytes and up to petabytes of data per day. And so they wanted tools that allow them to kind of modify filter and then route data to different sort of parts of their infrastructure. So that was the first demo. We did another demo on our, our visual playbook editor for SOAR, which has improved quite a bit. You know, a lot of the analysts that are in the, in the, in the SOC trying to figure out how to automate responses and reduce sort of time to resolution, like they're not Python experts. And so having a visual playbook editor that lets them drag and drop and sort of with a few simple gestures create complex playbooks was pretty cool. We showed some new capabilities in our APM tool. Last year, we announced we acquired a company called Plumbr, which has expertise in basically like code level analysis and, and we're calling it "Always On" profiling. So we, we did that demo and gosh, we did one more, four, but four total demos. I think, you know, people were really happy to see, you know, the thing that we really tried to do was ground all of our sort of like tech talk and stuff that was like real and today, like this is not some futuristic vision. I mean, Shawn did lay out some, some great visions, visionary kind of pillars. But, what we showed in the keynote was I it's all shipping code. >> I mean, there's plenty of head room in this market when it comes to data as value and data in motion, all these things. But we were talking before you came on camera earlier in the morning about actually how good Splunk product and broad and deep the product portfolio as well. >> Garth: Yeah. >> I mean, it's, I mean, it's not a utility and a tooling, it's a platform with tools and utilities. >> Garth: Yeah >> It's a fully blown out platform. >> Yeah. Yeah. It is a platform and, and, you know, it's, it's one that's quite interesting. I've had the pleasure to meet a couple of big customers and it's kind of amazing, like what they do with Splunk. Like I was meeting with a large telco on the east coast and you know, they actually, for their set top boxes, they actually have to figure out in real time, which ads to display and the only tool they could find to process 15 million events in real time, to decide what ad to display, was Splunk. So that was, that was like really cool to hear. Like we never set out to be like an ad tech kind of platform and yet we're the only tool that operates at that level of scale and that kind of data. >> You know, it's funny, Doug Merritt mentioned this in my interview with him earlier today about, you know, and he wasn't shy about it, which was great. He was like, we're an enabling platform. We don't have to be experts in all these vertical industries >> Garth: Yep >> because AI takes care of that. That's where the machine learning >> Garth: Yeah >> and the applications get built. So others are trying to build fully vertically integrated stacks into these verticals when in reality they don't have to, if they don't want it. >> Yeah, and Splunk's kind of, it's quite interesting when you look across our top 100 customers, you know, Doug talks about like the, you know, 92 of the fortune 100 are kind of using Splunk today, but the diversity across industries and, you know, we have government agencies, we have, you know, you name the retail or the vertical, you know, we've got really big customers, they're using Splunk. And the other thing that I kind of, I was excited about, we announced the last demo I forgot was TruSTAR integration with Enterprise Security. That's pretty cool. We're calling that Splunk Threat Intelligence. And so That was really fun and we only acquired, we closed the acquisition to TruSTAR in May, but the good news is they've been a partner with us like for 18 months before we actually bought em. And so they'd already done a lot of the work to integrate. And so they had a running start in that regard, But other, one other one that was kind of a, it was a small thing. I didn't get to demo it, but we talked about the, the content pack for application performance monitoring. And so, you know, in some ways we compete in the APM level, but in many ways there's a ton of great APM vendors out there that customers are using. But what they wanted us to do was like, hey, if I'm using APM for that one app, I still want to get data out of that and into Splunk because Splunk ends up being like the core repository for observability, security, IT ops, Dev Sec Ops, et cetera. It's kind of like where the truth, the operational truth of how your systems works, lives in Splunk. >> It's so funny. The Splunk business model has actually been replicated. They call it data lake, whatever you want to call it. People are bringing up all these different metaphors. But at the end of the day, if you guys can create a value proposition where you can have data just be, you know, stored and dumped and dumped into whatever they call it stored in a way >> Garth: We call it ingest >> Ingested, ingested. >> Garth: Not dumped. >> Data dump. >> Garth: It's ingested. >> Well, I mean, well you given me a plan, but you don't have to do a lot of work to store just, okay, we can only get to it later, >> Garth: Yep. >> But let the machines take over >> Garth: Yep. >> With the machine learning. I totally get that. Now, as a pro, as a product leader, I have to ask you your, your mindset around optimization. What do you optimize for? Because a lot of times these use cases are emerging. They just pop out of nowhere. It's a net new use case that you want to operationalize. So balancing the headroom >> Yep. >> Or not to foreclose those new opportunities for customers. How are customers deciding what's important to them? How do you, because you're trying to read the tea leaves for the future >> Garth: A little bit, yeah. >> and then go, okay, what do our customers need, but you don't want to foreclose anything. How do you think about product strategy around that? >> There's a ton of opportunity to interact with customers. We have this thing called the Customer Advisory Board. We run, I think, four of them and we run a monthly. And so we got an opportunity to kind of get that anecdotal data and the direct contact. We also have a portal called ideas.splunk.com where customers can come tell us what they want us to build next. And we look at that every month, you know, and there's no way that we could ever build everything that they're asking us to, but we look at that monthly and we use it in sort of our sprint planning to decide where we're going to prioritize engineering resources. And it's just, it's kind of like customers say the darndest things, right? Sometimes they ask us for stuff and we never imagined building it in a million years, >> John: Yeah. >> Like that use case around ads on the set top box, but it's, it's kind of a fun place to be like, we, we just, before this event, we kind of laid out internally what, you know, Shawn and I kind of put together this doc, actually Shawn wrote the bulk of it, but it was about sort of what do we think? Where, where can we take Splunk to the next three to five years? And we talked about these, we referred to them as waves of innovation. Cause you know, like when you think about waves, there's multiple waves that are heading towards the beach >> John: Yeah. >> in parallel, right? It's not like a series of phases that are going to be serialized. It's about making a set of investments. that'll kind of land over time. And, and the first wave is really about, you know, what I would say is sort of, you know, really delivering on the promise of Splunk and some of that's around integration, single sign-on things about like making all of the Splunk Splunk products work together more easily. We've talked a lot in the Q and a about like edge and hybrid. And that's really where our customers are. If you watch the Koby Avital's sort of customer keynote, you know, Walmart by necessity, given their geographic breadth and the customers they serve has to have their own infrastructure. They use Google, they use Azure and they have this abstraction layer that Koby's team has built on top. And they use Splunk to manage kind of, operate basically all of their infrastructure across those three clouds. So that's the hybrid edge scenario. We were thinking a lot about, you mentioned data lakes. You know, if you go back to 2002, when Splunk was founded, you know, the thing we were trying to do is help people make sense of log files. But now if you talk to customers that are moving to cloud, everybody's building a data lake and there's like billions of objects flowing into millions of these S3 buckets all over the place. And we're kind of trying to think about, hey, is there an opportunity for us to point our indexing and analytics capability against structured and unstructured data and those data lakes. So that that'll be something we're going to >> Yeah. >> at least start prototyping pretty soon. And then lastly, machine learning, you know, I'd say, you know, to use a baseball metaphor, like in terms of like how we apply machine learning, we're like in the bottom of the second inning, >> Yeah. >> you know, we've been doing it for a number of years, but there's so much more. >> There's so, I mean, machine learning is only as good as the data you put into the machine learning. >> Exactly, exactly. >> And so if you have, if you have gap in the data, the machine learning is going to have gaps in it. >> Yeah. And we have, we announced a feature today called auto detect. And I won't go into the gory details, but effectively what it does is it runs a real-time analytics job over whatever metrics you want to look at and you can do what I would consider more statistics versus machine learning. You can say, hey, if in a 10 minute period, like, you know, we see more errors than we see on average over the last week, throw an alert so I can go investigate and take a look. Imagine if you didn't have to figure out what the right thresholds were, if we could just watch those metrics for you and automatically understand the seasonality, the timing, is it a weekly thing? Is it a monthly thing? And then like tell you like use machine learning to do the anomaly detection, but do it in a way that's more intelligent than just the static threshold. >> Yeah. >> And so I think you'll see things like auto detect, which we announced this week will evolve to take advantage of machine learning kind of under the covers, if you will. >> Yeah. It was interesting with cloud scale and the data velocity, automations become super important. >> Oh yeah. >> You don't have a lot of new disciplines emerge, like explainable AI is hot right now. So you got, the puck is coming. You can see where the puck is going. >> Yeah >> And that is automation at the app edge or the application layer where the data has got to be free-flowing or addressable. >> Garth: Yeah. >> This is something that is being talked about. And we talked about data divide with, with Chris earlier about the policy side of things. And now data is part of everything. It's part of the apps. >> Garth: Yeah. >> It's not just stored stuff. So it's always in flight. It should be addressable. This is what people want. What do you think about all of that? >> No, I think it's great. I actually just can I, I'll quote from Steve Schmidt in, in sort of the keynote, he said, look like security at the end of the day is a human problem, but it kind of manifests itself through data. And so being able to understand what's happening in the data will tell you, like, is there a bad actor, like wreaking havoc inside of my systems? And like, you can use that, the data trail if you will, of the bad actor to chase them down and sort of isolate em. >> The digital footprints, if you will, looking at a trail. >> Yeah. >> All right, what's the coolest thing that you like right now, when you look at the treasure trove of, of a value, as you look at it, and this is a range of value, Splunk, Splunk has had customers come in with, with the early product, but they keep the customers and they always do new things and they operationalize it >> Garth: Yep. >> and another new thing comes, they operationalize it. What's the next new thing that's coming, that's the next big thing. >> Dude that is like asking me which one of my daughters do I love the most, like that is so unfair. (laughing) I'm not going to answer that one. Next question please. >> Okay. All right. Okay. What's your goals for the next year or two? >> Yeah, so I just kind of finished roughly my first 100 days and it's been great to, you know, I had a whole plan, 30, 60, 90, and I had a bunch of stuff I wanted to do. Like I'm really hoping, sort of, we get past this current kind of COVID scare and we get to back to normal. Cause I'm really looking forward to getting back on the road and sort of meeting with customers, you know, you can meet over Zoom and that's great, but what I've learned over time, you know, I used to go, I'd fly to Wichita, Kansas and actually go sit down with the operators like at their desk and watch how they use my tools. And that actually teaches you. Like you, you come up with things when you see, you know, your product in the hands of your customer, that you don't get from like a CAB meeting or from a Zoom call, you know? >> John: Yeah, yeah. >> And so being able to visit customers where they live, where they work and kind of like understand what we can do to make their lives better. Like that's going to, I'm actually really excited to gettin back to travel. >> If you could give advice to CTO, CISO, or CIO or a practitioner out there who are, who is who's sitting at their virtual desk or their physical desk thinking, okay, the pandemic, were coming through the pandemic. I want to come out with a growth strategy, with a plan that's going to be expansive, not restrictive. The pandemic has shown what's what works, what doesn't work. >> Garth: Sure. >> So it's going to be some projects that might not get renewed, but there's doubling down on, certainly with cloud scale. What would advice would you give that person when they start thinking about, okay, I got to get my architecture right. >> Yeah. >> I got to get my playbooks in place. I got to get my people aligned. >> Yeah >> What's what do you see as a best practice for kind of the mindset to actual implementation of data, managing the data? >> Yeah, and again, I'm, I'm, this is not an original Garth thought. It actually came from one of our customers. You know, the, I think we all, like you think back to March and April of 2020 as this thing was really getting real. Everybody moved as fast as they could to either scale up or scale scaled on operations. If you were in travel and hospitality, you know, that was, you know, you had to figure how to scale down quickly and like what you could shut down safely. If you were like in the food delivery business, you had to figure out how you could scale up, like Chipotle hit two, what is it? $2 billion run rate on delivery last year. And so people scrambled as fast as they could to sort of adapt to this new world. And I think we're all coming to the realization that as we sort of exit and get back to some sense of new normal, there's a lot of what we're doing today that's going to persist. Like, I think we're going to have like flexible rules. I don't think everybody's going to want to come back into the office. And so I think, I think the thing to do is you think about returning to whatever this new normal looks like is like, what did we learn that was good. And like the pandemic had a silver lining for folks in many ways. And it sucked for a lot. I'm not saying it was a good thing, but you know, there were things that we did to adapt that I think actually made like the workplace, like stronger and better. And, and sort of. >> It showed that data's important, internet is important. Didn't break, the internet didn't break. >> Garth: Correct. >> Zoom was amazing. And the teleconferencing with other tools. >> But that's kind of, just to sort of like, what did you learn over the last 18 months that you're going to take for it into the next 18 years? You know what I mean? Cause there was a lot of good and I think people were creative and they figured out like how to adapt super quickly and take the best of the pandemic and turn it into like a better place to work. >> Hybrid, hybrid events, hybrid workforce, hybrid workflows. What's what's your vision on Splunk as a tier one enterprise? Because a lot of the news that I'm seeing that's, that's the tell sign to me in terms of this next growth wave is big SI deals, Accenture and others are yours working with and you still got the other Partnerverse going. You have the ecosystems emerging. >> Garth: Yep. >> That's a good, that means your product's enabling people to make money. >> Garth: Yeah. Yeah, yeah, yeah. >> And that's a good thing. >> Yeah, BlueVoyant was a great example in the keynote yesterday and they, you know, they've really, they've kind of figured out how, you know, most of their customers, they serve customers in heavily regulated industries kind of, and you know, those customers actually want their data in a Splunk tenant that they own and control and they want to have that secure boundary around that. But BlueVoyant's figured out how they can come in and say, hey, I'm going to take care of the heavy lifting of the day-to-day operations, the monitoring of that environment with the security. So, so BlueVoyant has done a great job sort of pivoting and figuring out how they can add value to customers and do, you know, because they they're managing not just one Splunk instance, but they're managing 100s of Splunk cloud instances. And so they've got best practices and automation that they can play across their entire client base. And I think you're going to see a lot more of that. And, and Teresa's just, Teresa is just, she loves Partners, absolutely loves Partners. And that was just obvious. You could, you could hear it in her voice. You could see it in her body language, you know, when she talked about Partnerverse. So I think you'll see us start to really get a lot more serious. Cause as big as Splunk is like our pro serve and support teams are not going to scale for the next 10,000, 100,000 Splunk customers. And we really need to like really think about how we use Partners. >> There's a real growth wave. And I, and I love the multiples wave in parallel because I think that's what everyone's consensus on. So I have to ask you as a final question, what's your takeaway? Obviously, there's been a virtual studio here where all the Splunk executives and, and, and customers and partners are here. TheCUBE's here doing all the presentations, live by the way. It was awesome. What would you say the takeaway is for this .conf, for the people watching and consuming all the content online? A lot of asynchronous consumption would be happening. >> Sure. >> What's your takeaway from this year's Splunk .conf? >> You know, I, it's hard cause you know, you get so close to it and we've rehearsed this thing so many times, you know, the feedback that I got and if you look at Twitter and you look at my Slack and everything else, like this felt like a conf that was like kind of like a really genuine, almost like a Splunk two dot O. But it's sort of true to the roots of what Splunk was true to the product reality. I mean, you know, I was really careful with my team and to avoid any whiff of vaporware, like what were, what we wanted to show was like, look, this is Splunk, we're acquiring companies, you know, 43 major releases, you know, 100s of small ones. Like we're continuing to innovate on your behalf as fast as we can. And hopefully this is the last virtual conf. But even when we go back, like there was so much good about the way we did this this week, that, you know, when we, when we broke yesterday on the keynote and we were sitting around with the crew and it kind of looking at that stage and everything, we were like, wow, there is a lot of this that we want to bring to an in-person event as well. Cause so for those that want to travel and come sit in the room with us, we're super excited to do that as soon as we can. But, but then, you know, there may be 25, 50, 100,000 that don't want to travel, but can access us via this virtual event. >> It's like a time. It's a moment in time that becomes a timeless moment. That could be, >> Wow, did you make that up right now? >> that could be an NFT. >> Yeah >> We can make a global cryptocurrency. Garth, great to see you. Of course I made it up right then. So, great to see you. >> Air bump, air bump? Okay, good. >> Okay. Garth Fort, senior vice president, Chief Product Officer. In theCUBE here, we're live on site at Splunk Studio for the .conf virtual event. I'm John Furrier. Thanks for watching. >> All right. Thank you guys. (upbeat music)

(upbeat music) >> From around the globe, it's theCUBE! With digital coverage of Postgres Vision 2021, brought to you by EDB. >> Welcome back to Postgres Vision 21, where theCUBE is covering the innovations in open source trends in this new age of application development and how to leverage open source database technologies to create world-class platforms that are cost-effective and also scale. My name is Dave Vellante, and with me is Roberto Giordano, who is the End User Computing, Corporate, and Database Services Manager at Borsa Italiana, the Italian Stock Exchange. Roberto, great to have you. Thanks for coming on. >> Thanks Dave, and thanks to the interview friend for the invitation. >> Okay, and we're going to dig in to the great customer story here. First, Roberto, tell us a little bit more about Borsa Italiana and your role at the organization. >> Absolutely. Well, as you mentioned, Borsa is the Italian Stock Exchange. We used to be part of the London Stock Exchange, but last month we left that group, and we joined another group called Euronext, so we are now part of another group, I would say. And right now within Euronext, Euronext provide the biggest liquidity pool in Europe, just to mention something. And basically we provide the market infrastructure to our customers across Europe and the whole world. So probably if it happens for you to buy a little of, I don't know, Ferrari for instance, probably use our infrastructure. >> So I wonder if you could talk about the key drivers in the exchange business in Italy. I don't know how closely you follow what's going on in the United States, but it's crypto madness, there's the Reddit army driving up stocks that have big short positions, and of course the regulators have to look at that, and there's a big debate going on. Well, I don't know what's it like in Italy, but what are the key drivers that are really informing the priorities for your technology strategy? >> Well, you mentioned, for instance, the stereotypical cases that are a little bit of laterally to the global markets and also to our markets as a it professional running market infrastructure is our first the goal to provide an infrastructure that is reliable and be with the lowest possible latency. So we are very focused on performance and reliability just to mention the two main drivers within our systems. >> Well, and you have end-user computing in your title and we're going to get into the database discussion, but I presumably with with COVID you had to pivot and that that piece of your job was escalated in 2020, I would imagine. And you mentioned latency which is a key factor in obviously in database access but that must've been a big challenge last year. >> Well, it was really a challenge, but basically we move just within a weekend, the wall organization working remotely. And it has been like this since February, 2020. Think about the challenge of moving almost 1000 people that used to come to the office every day to start to work remotely. And as within my team of the end user computing this was really a challenge but it was a good one at the end. We, we, we succeeded and everything work. It's fine from our perspective, no news is is a good news, you know, because normally when something doesn't work, we are on newspapers. So if you didn't heard about us it means that everything worked out just fine. >> Yeah. It's amazing, Roberto. We both in the technology business that you'll be you're a practitioner observer, but I mean if you're in the tech business most companies actually pivoted quite well. You're have always been a digital business, different. I mean, if you're a Ferrari and making cars and you can't get semiconductors, but but most technology companies actually made the transition you know, quite amazingly, let's get into the, the case study a bit of it. I wonder if you could paint a picture of your organization's infrastructure and applications what it looks like and and particularly your database infrastructure what does that look like? >> Well, we are a multi-vendor shop. So we would like to pick the right technology for for the right service. This means that my database services teams currently manage several different technology where possible that plays a big role in, in, in our portfolio. And because we, we, we currently support both the open source, fully open source version of Postgres, but also the EDB distribution in particular we prefer to use EDB distribution where we did specific functionalities that just EDB provide. And we, when we need a first class level of support that EDB in recent year was able to provide to us. >> When you say full functioning, are you talking about things like acid compliance, two phase commits? I mean, all these enterprise capabilities, is that right? Or maybe you could be >> Just too much just to mention one, for instance we recently migrated our wire intrasite availability solution using the ADB fail-over manager. That is an additional component that just it'll be provide. >> Yeah. Okay. So, so par recovery obviously is, is and so that's a solution that you to get from the EDB distro as opposed to having to build it yourself with open source tooling. >> Yeah, correct. Well, basically sterically, we used to rely on OSTP clustering from, from, from that perspective. But over the years we found that even if it's a technology that works fine, it has been around for four decades. And so on. We faced some challenges internally because within my team we don't own also the operative system layers. So we want a solution that was 100% within our control and perimeter. So just few months ago we asked the EDB EDB folks if they can provide something. And after a couple of meetings also with their pre-sales engineers, we found the the right solution for us. So we launched long story short, just a quick proof of concept to a tissue test together, again using the ADB consultancy. And, and then we, beginning of this year, we, we went live with the first mission critical service using this brand new technology, well brand new technology for us. You know, it'd be created a few years ago >> And I do have some follow-up questions but I want to understand what catalyzed the, you know what was the motivation for going with an open source database? I mean, you're, you're a great example because you have your multi-vendor so you have experienced with all of it, the full spectrum. What was it about open source database generally EDB specifically that triggered the, the choice? >> Well thanks for the question. It is, this is one of the, or one of the questions that I always, like. I think what really drove us was the right combination between easy to use, so simplicity and also good value for money. So we like to pick the right database technology for the right kind of service slash budget that the survey says and, and the open source solution for a specific service. It, it, it's, it's our, you know, first, first, first choice. So we are not going to say a company that use just one technology. We like to take the best of breed that the market can offer. In some cases, the open source and Postgres in particular is, is our choice. How involved was >> The line of business in this both the decision and the implementation? Was it kind of invisible to them, or this was really more of a technology decision based on the your interpretation of the requirements I'm interested in who was involved and how you actually got it done? >> Well, I, I think this decision was transplant for, for, for, for the business at the end of the day don't really have that kind of visibility. You know, they just provide requirements in particular in terms of performance and rehabil area, the reliability. And so, so this this is something they are not really involved about. And obviously if they, if we are in opposition to save a little bit of money everybody's at the, even the business >> No. So what did you have to do? So that makes sense to me, I figured that was the case. Who would, who were the stakeholders on your team? I mean, what kind of technical resources did you require an implementation resources? What take us through what the project if you will look like, wh how did you do it? >> Well, it's a combination of database expertise. I got the pleasure to run a team that is paid by very, very senior, very, very skilled database services professional that are able to support more than one more than what the county and also are very open to innovation and changes. Plus obviously we need also the development teams the relevant development teams on board, when you when you run this kind of transformations and it looks like also, they liked the idea to use PostgreSQL for for this specific service I got in mind. So it, it, it was quite, quite easy, not be discussion. You know. >> What was the, what was the elapsed time from from when you said, okay, we're in, you know signed the agreement we're going here you made the decision to actually getting into production. >> Well, as I mentioned, we, we, we were on we're on services and application that are really focused on high availability and performance. So generally speaking, we are not a peak organization. Also we run a business that is highly regulated. So as you know, as you can imagine we are an organization that don't have a lot of appetite for risk, you know, so generally speaking in order to run this kind of transformation is a matter of several months, I will say six nine months to have something delivered in that space. >> Okay. Well, that's, I mean, that's reasonable. I mean, if you could do it inside of a year that's I think quite good especially in the highly regulated industry. And then you mentioned kind of the fail over the high availability Cape Cape capabilities. Were there other specific EDB tools that that you utilize to sort of address the objectives? >> Yeah, absolutely. We were in particular, we used Postgres enterprise, AKA Pam. Okay. And very recently we were involved within ADB about per se specifically developing one functionality that, that that we needed back in the day. I think together with Bart these are the free EDB specific tools that, that we, that that we use right now. >> And, and I'm, I'm interested in, I want to get to the business impact and I know it's early days for you but the real motivation was to save money and simplify. I would actually, I would imagine your developers were happy because they get to use modern tooling and open source. But, but really though if your industry is bottom line, right, I mean that's really what the, the business case was all about. But I wonder if you could add some color there in terms of the business impact that you expect. And then, I mean I don't know how much visibility you have now but anything you can share with us. >> Well, thinking about the EFM implementation that the business impact the, was that in case of a failure or the DBA team that a services team is it is able to provide a solution that is within our 100% within our perimeter. So this means that we are fully accountable for it. So in a nutshell, when you run a service, the less people the less teams you have to involve the more control you can deliver. And in some, again, very critical services that is a great value. >> Okay. So, and, and where do you want to take this? I mean, how do you see w what's your, if you're thinking about your Postgres and, and generally an EDB you know, roadmap, where do you want it to go? >> Well, I stay to, to trends within within the organization, the, the, the, the the first one is about migrating more existing services to open source solution for database is going to be, is going to be prosperous. And other trends that I see within my organization is about designing applications, not really to be, to to use PostgreSQL as the base, as it does a base layer. I think both trends are more or less surroundings at the same state right now. >> Yeah. A lot of the audience members at Postgres vision 21 is just like you they they're managing day-to-day infrastructure. They're there they're expert practitioners. What advice would you give to somebody that is thinking about, you know taking this journey, maybe if you had to do something over again maybe what would you do differently? How can you help your peers here? >> Well, I think in particular, if you are going to say a big organization that runs a highly regulated business in some cases, you are a little bit afraid of open source because there is this, I can say general consideration about the lack of enterprise level support. I would like to say that it is just about the past because they're around bunch of companies like EDB that are we're a hundred percent capable of providing enterprise level of support, even on, on, on even on the open source distribution of Paul's presser. Obviously Dan is you're going to go with their specific distribution. The level of support is going to be even more accurate but as we know, it could be currently is they across say main contributor of the pollsters community. And I think is, is that an insurance for every organization? >> Your advice is don't be afraid. >> Yeah. My advice is done is absolutely, don't be, don't be afraid. And if, if, if I can, if we can mention about also about, you know, the cloud called technologies this is also another, another topic where if possible I would like to suggest to not being afraid EDB as every every I would say organization within the it industry is really pushing for it. And I think for a very, for, for a lot of cases not all of them, but a lot of cases, there is a great value about the design services application to be cloud native or migrating existing application into the cloud. >> Okay. But, but being a highly regulated industry and being a, you know, very much aware of the the narrative around open source, et cetera, you, you must've had just a little piece of your mind saying, okay I have to manage this risk. So there's anything specifically you did with managing the risks that you would advise? Was it, was it or is it really just about good change management? >> I think it was mainly about a good change management when you got, you know the relevant stakeholders that you need on board and we are, everybody's going the same direction. That basically is about executing. >> Excellent. Well, Roberto, I really appreciate your time and your knowledge that you share with the audience. So thanks so much for coming on the cube. >> Thank you, Dave. It was a great pleasure. >> And thank you for watching the cubes continuous coverage of Postgres vision 21. We'll be right back. (upbeat music)

>> Presenter: From San Francisco, it's theCUBE. Covering GitLab Commit 2020. Brought to you by GitLab. >> Hi, I'm Stu Miniman, and this is theCUBE's coverage of GitLab Commit 2020 here in San Francisco. You might notice some of our guests have some jackets on. It is a little cooler than normal here in San Francisco, but the community and knowledge is keeping us all warm. Joining us for the first time on the program is Nicholas Klick, who is an engineering manager at GitLab. Thanks so much for joining us. >> Thanks for inviting me. >> Alright, so you had an interesting topic. The state of serverless in 2020 was the session that you gave. Definitely a topic we love covering on theCUBE, something I personally have been digging into, trying to understand. Definitely something that the developers, and especially the app devs that I speak with, are very bullish on, so what is the state of serverless in 2020? >> That's actually a good question. So, my talk was actually broken into two parts. One was, like initially I just wanted to help provide a clear definition of what serverless is. In my opinion, serverless is more than just functions. There are a lot of other a lot of other technologies, like backend is a service, API gateways, service integration proxies that you can stitch together to create dynamic applications. So, I created a more expanded definition of what serverless is from my perspective, and the other part was to really talk about three things that I'm finding exciting right now in the serverless space. The first was Knative, and the fact that Knative is likely going to go to GA pretty soon, so it'll be production ready, and we can finally build production workloads on it. The second is that running serverless at the edge I find to be an exciting topic. And then finally, talking more in depth on those, the service integrations. Of how you can actually create applications that don't include functions at all, so functionless serverless. >> Yeah, so a lot of things I definitely want to tease out of that, but Nicholas, I guess maybe we should step back a second-- >> Nicholas: Okay. >> And was there survey work, or was there something done, or is this kind of something related to your job that you put together as just an important topic? >> Yeah, I know this is just me speaking as someone that works in the space and sees the technology is evolving and just my opinions, I guess. >> Okay, when I talk to the practitioners, when you go and say, "Oh, they're interested in it." Chances are they're doing stuff on Amazon, is like what kind of the first piece of it tends to be. There are lots of open source projects out there, but it's still this kind of dominated by Amazon. Azure has some pieces, of course. Google has things they're doing. I liked how you teased out that serverless definitely isn't a thing, and the definition, and even the term itself, gets people all riled up and things like that, so I hate getting into the ontological arguments, but the promise of it is that I can build applications in a different way, and I shouldn't have to think about some of the underlying components, hence the name serverless, kind of-- >> Right. >> does that, but it definitely is a change in mindset as to how I build and consume environments. >> Right. Right, and like another point that I made in the talk, that I believe pretty strongly, is that serverless is not something that's going to replace monoliths and microservices. I believe it's another tool in the tool belt of the developer, of the operator, to solve problems, and that we should look at it like that. It shouldn't be, it's not the next progression in application architecture. >> Yeah, I've met some companies that are 100%, they've built everything on serverless, but that's like saying I've met plenty of companies that are all in the cloud. It depends on what you do and what your business is. >> Nicholas: Right. >> When we look at the enterprise, it is a broad spectrum, and making changes along that path is something that typically takes a decade or more, and they have hundreds, if not thousands of applications, and therefore, we understand. I've got my stuff running on my mainframe through my latest microservice architecture, and everything in between. >> Right, and I mean I'm speaking as an employee of GitLab, and we have a very well known monolith that we deploy, and so for my opinion, I don't believe that monoliths are going to die any time soon. >> Alright, I'd love you to tease out some of those pieces that you talked about, the three items you talked about: Knative. You know, Knative is interesting. The thing I poked at when I go to KubenCon and CloudNativeCon is today I mentioned when I think about customers, most of them are using Amazon. The second choice is they're probably doing Azure, and today Knative directly doesn't work with EKS, AKS, or the like. I know there's a solution like trigger match that actually will interact-- >> Right. >> Between the Amazon and there, but don't you need the buy-in of Amazon and Microsoft for Knative to be taken seriously. And the other thing is, Google still hasn't opened up the-- >> Right. >> the Google controls, the governance of both Istio and Knative, and there are some concerns in the ecosystem about that, so what makes you so bullish on Knative. >> Yeah, so I'm definitely aware of some of the discussions around Knative. From my perspective, I think that Knative is, if someone is already operating a lot of Kubernetes infrastructure, if they already have those, that infrastructure running, then deploying Knative to it is not that much more of a it doesn't require additional resources and expense, so it could be, again it depends on their use case, and I think that, when I think about serverless, I try to remain pragmatic, so if I'm already using Kubernetes, and I want a simple serverless runtime, Knative would be a great option in that situation. If I want to be able to work cross-cloud, like this is another opportunity that Knative provides, is the ability of deploying to any Kubernetes cluster anywhere, so it has that, you know, that, there's not a vendor lock-in issue with Knative. >> Yeah, and absolutely there was initially some concern that, could serverless actually be the ultimate lock-in? >> Right. >> I'm going to go deep on one provider and don't have a way. There, open source groups like the CNCF trying to help along those ways-- >> Sure. >> Knative absolutely along those ways looking at that environment. From a GitLab customer's standpoint, GitLab's not tied to whether you're doing containers or serverless or VMs or in the environment. What does it mean for GitLab customers? If I want to look at serverless, how does that fit into my overall work flow? >> Yeah, so initially at GitLab we focused on providing the ability to deploy to Knative. That was, we were very early in the Knative space, and I think that as it's matured, as those APIs have matured, then our product has kind of developed, and so right now we enable you to be able to create Kubernetes clusters through our interface and then deploy your function run times directly from your GitLab repo. We've also, are kind of growing in our our examples and documentation of how to integrate GitLab CI/CD with Lambda. That's another big area that we're moving into as well. >> Great. As you look forward to 2020, we've got a whole new decade in front of us, what should, what do you think people should be watching on in the maturity of this space. >> Yeah, so I think that the point that I touched on earlier of the service integrations, I think that that is something you're going to see more and more of. Of the providers themselves linking together their different services and enabling you to create these dynamic applications without a lot of glue that you have to manually create in between. I think that we're going to see, you know, more open source frameworks, like, for example, Service Framework or Terraform that people want the, I mean, I know that a lot of people use, for example, AWS SAM. People want easier ways, and faster ways, to be able to deploy their serverless, so you have the bootstrapping of serverless. I guess, another thing that I expect is that the serverless, the serverless development life cycle will mature, in that whether going from bootstrapping to testing, deployment, monitoring security, I believe you're going to see companies that will start to really fill in that entire space, the same way that they do for monoliths and microservices. >> Yeah, absolutely. Thank you so much, Nicholas. Definitely something we've been tracking over the last year or so. You start to see many in the tool chain of cloud native environments digging into serverless, helping to mature those solutions, and definitely an area to watch closely. >> Great. >> Alright. Lot's more coverage. Check out theCUBE.net for all the events that we will be at through 2020 as well. If you can go back and see we've actually done Serverlessconf a couple of years, many of the other cloud and cloud native shows. Search in our index. I'm Stu Miniman, and thank you for watching theCUBE. (energetic electronic music)

>>live from Las Vegas. It's the two covering AWS executive Something >>brought to you by Accenture >>everyone to the ex Center Executive Summit here in AWS. Reinvent I'm your host, Rebecca Knight. I'm joined by John. Match it. He is the managing director. Applied Intelligence, North America Attic Center Thank you so much for coming on the Q. So we're gonna have a fun conversation about a I today. We tend to think of a I as this futuristic Star Trek Jetsons kind of thing. But in fact, a i a. I is happening here and now >>it's all around us. I think it's intricate zoologist, sort of blood into the fabric girl of our lives without really even knowing about, I mean, just to get here, Let me lives took a new burst. There's a I in the route navigation. We may have listened to Spotify, and there's a I and the recommendation engine. And if you want to check the weather with Alexa, there's a lot of agents in the natural language processing, and none of that was really impossible 10 years ago. So without even trying, just wake up and I sort of like in your system in your blood. >>So as consumers, we deal with a I every day. But it's all but businesses are also using a I, and it's already having an impact. >>I think >>what is absolutely true it and really interesting is that information is just the new basis of competition. Like like you know, companies used to compete with physical objects and look better cars and blenders and stereos and, you know, thermometers. But today, you know, they're all like on a device, and so information is how they compete. And what's interesting to me about that for our clients is that if you have a good idea, you can probably do it. And so you're limited, really by your own imagination on. So I just as an example of like how things are playing out a lover classroom, the farmer space to make better drugs, and every every form of company I know of is using some sort of machine learning a I to create better pharmaceuticals, the big ones, but also the new entrance. One of the companies that we followed numerator really issued company. What they've been able to do is like in just just a massive amount of data like all day, like good data, bad bias on buying >>its ingesting, this kind of data the data is about. >>It's about like drug efficacy, human health, the human genome like like like doctors visits like all this diverse information. And historically, if you put all that data together just to have a way to actually examine it, there's no way that was too much. Humans can't deal with it, but but But machine learning can. And so what? We just all this date up and we let the robots decided sort of less meaningful. And what's happened is you can now deal with instead, just a very fraction that data, but all of it. And the result, like in pharmaceuticals. Is it wearable? Come with new HIV drugs in six months? It used to be years and millions of dollars, tens of millions of dollars. But now it's, you know, it's months, and so it's really changing the way humans live. And certainly the associated industries. They're producing the drugs. >>So it's as you said, I was already being used to reimagine medicine. So many of the high tech jobs openings today are not necessarily in technology there in pharmaceuticals and automotive's. And these and these involved artificial intelligence, their skills in artificial intelligence. What can you tell us about how a eyes having an impact? And that's what I think. >>This is a really good question. What is interesting is that industry she wouldn't think, or digital companies are now actually digital competitors. I'll give you two examples. One is a lot of clients make liquefied natural gas. Now that that is a mucky business. It's full of science, like geology and chemistry and chemical engineering, and they work with these like small refineries. But the questions like, how we gonna get better if you make you know Ellen G. And so what they do is they use a I, and the way they do that is likely have these small refineries. Each piece of equipment has a sensor on it, so there may be 5000 sensors, and each sensor has three or four like bots looking at it, and one might be looking at vibration heat and and what they're doing is they're making predictions. Millions of predictions every every day about you know whether quality is good. The machine's about to have a problem that safety is jeopardise something like that. And so So you've gone from a place where, you know, the best competitors were chemists to the best competitors are actually using machine learning to make the plants work better. You know, another entry. We see this really was brewing. You know, you don't think no one would think brewing is like a digital business like his beer? The Egyptians may be right, like so everyone knows how to do it. So But think about if you make beer like how you're gonna get better and again do what you do is you begin to touch customers more effectively with better digital marketing, you know? Hey, I tow target to understand who your best customers are, how to make offers to them, had a price head of both new product introduction, and even had a formulate new brands of beer that might appeal to different segments of society. So brewing, like they're all about, like ml in the eye. And they really are, like a digital competitive these days, which I think it's interesting, like no one would have thought about that, you know, is they were consuming beer on a Friday with their friends >>and craft brewing is so hot right now. I mean, it is one of those things. As you said, it is attracting new, different kinds of segments of customers. >>Right? And so the questions like if you are a craft brewer like, how do you go find the people that that you want? So what we're doing is we're way have new digital ways to go touch them very personalized offer like, if you like running, you know we can We can give you an offer like fun run followed by a brew. But we know who you are and what you like your friends like to do to get very specific A CZ we like examined the segments of society to do very personal marketing. It's actually fun, like, you know, it gives you things to go Dio we did one event where he looked at cos we we had a a beer tasting with barbecue teach you no instruction. So if you wanna learn how to cook barbecue and also do a beer tasting can get 20 people together and you have a social experience and you you buy more the product. But what's interesting is like, Well, how do you find those people? How do you reach them? How do you identify these of the right folks? That'll actually participate? And that's where a I comes into play. >>So this is fascinating, and you just you just described a number of different industries and companies beer, brewers, liquefied natural gas, pharmaceuticals that are using a I to transform themselves. What is your What do you recommend for the people out there watching and say, I want to do that? How could I get on >>board or what we advise Companies are clients to really get good at three things, and the first is just to do things differently. So you got to go into your core operations and figure out how you can extract more cash and more profit from your existing operations. And so that's like we talked about natural gas, right? Like you could produce it more profitably and effectively, but that's not enough. The next thing you do step to would be to actually grow your core business. Everyone wants to leave to the new right away, but but you're getting all your cash and your legacy businesses and so like like we saw in the brewing history. If you can find new customers, more profitable customers interact with them, create a better digital experience with them, then you'll grow both your top line in your bottom line. But for our from our perspective, the reason you do both of those things is cash. Then make investments into New Net new businesses on DSO. The last thing you do is to do different things, so find in adjacency and grow. And it's important to talk about the role of a I and that because that's the way you develop outcomes with speed, right? Like you're not gonna build a factory and we're gonna build a service or some sort of, you know, information centric offerings. And so what we like to do is talk about like the wise pivot from your old legacy businesses. We generate cash and you make selective investments in the new and how you regulate that is a really important question, because you're too fast and you start the Lexie businesses like to slow, and you're gonna be sort of left out of the new economy. So doing those three things correctly with the right sort of managing processes is what we advise our clients to focus on. >>So I see all of this from the business side. But do you because you're also a consumer? Do you ever see any sort of concerns about privacy and security in the sense of why does anyone need to know if I like to run or I like barbecue with my beer? I mean, how do you How do you sort of think about those things and and talk to clients about those issues >>too? Well, I think, you know, actually, for censure. Ah, large part of our focus is what we call just ethical a eye on. And so it's important to us to actually have offerings that we think that we're comfortable with that are legally comfortable, but also just societally are acceptable. And it's actually like there's a lot of focus in this area, right, how you do it. And there's actually a lot to learn. Like like what we see, for example, is there could be biased in the data which effects the actual algorithm. So a lot of times were the folks in the algorithm, you need to go back to the data and look at that. But it's something we spend a lot of time on. Its important us because we to our consumers and we care about our privacy. >>So when you talk about the wise pivot and the regulation, this is a This is a big question. There's a lot of bills on the table in Washington. It's certainly dominating our national conversation, how we think about regulating thes new emerging technologies that that present a lot of opportunities, but also a lot of risks. So how how are you, how you are you a tech center thinking about regulation and working with regulators on these issues >>way get involved with talking to the government. They seek independent counsel, so we participate when they're seeking guidance and we'll give our offer. So we're a voice at the table. But you know, what I would say is there's a lot of discussion about privacy and ask. But if you look at, like, at a national level, particularly government, I think there used to be more focused just on the parts that are incontrovertibly not problematic with privacy. So I gave you the example of working with liquefied natural gas. Okay, we need better, eh? I'd run our factories better. There's a lot of a I that goes into those kind of problems or supply chain planning. Like, how do I predict demand more effectively, or where should I put my plants? And A. I is the new way supply chain is done right? And so there's There's very few of the consumer centric problems I think, actually is. A society like 90% of the use cases are gonna be in areas where they don't actually influence for privacy and a lot of art. Our time is actually working on those kind of use cases just to make you know the operations of our organization's Maur more effective than more efficient. >>So we talked about the very beginning of this conversation about the companies that are disrupting old industries. Using a lot of these technologies, I mean, is this is a I A case where you need to be using this you need to be using >>you need to be using it. My view, my personal view is that there is going to be no basis of competition in the future, except for a digital. It just is going to be the case. And so all of our clients, you know, they're at some state of maturity and they're all asking the question like, How did I grow up? I don't get more profitable. Like certainly the street. Once more results on DSO if you want to move quickly in the new space, is you. You you you only have 11 choice. Really? And that that is to get really, really, really good at managing in harnessing digital technologies, inclusive of >>a I >>two to compete in a different way. And so I mean, we're seeing really interesting examples were like, you know, like, retailers are getting into health care, right? Like, you see this like you go into Wal Mart and they have our Walgreens. They have, like a doc in the box, right? So we're seeing. But lots of companies that are making physical things that then turn around and use the developing service and what they used to use their know how they take everything they know about, like like something you know about, like healthcare or how to like, you know, offer service is to customers and retail setting, but then they need to do something different. And now how do I get the data and the know how to then offer, like a new differentiated health service? And so to do that, you know, you have a lot. You have a lot of understanding about your customers, but you need to get all the data sources in place. You may need certain help desk. You know you need ways to aggregate it on, and so you probably need a new partnerships that don't have. You probably need toe manage skill sets that you don't have. You may need to get involved with open source communities. You may need to be involved with universities that where they do research, so you'll need a different kind of partnerships to move a speed then companies have probably used in the past. But when they put all those those eco systems together, onda new emphasis on the required skill sets, they can take their legacy knowledge that's probably physically oriented and then create a service that can create. They can monetize their experience with the new service. What what we find usually doesn't work is just a monetized data. If you have a lot of data, it's not usually worth that much. But if you take the data and you create a new service that people care about, then you can monetize your legacy information that that that's what a lot of our class they're trying to do, think they've very mature and now, like Where do you go? And where they go is something may be nearby to their existing business, but it's not. It's not the same legacy business of the path for years. >>I want to take a little deeper on something you brought up about the skills, and there's a real skills gap in Silicon Valley and in companies in this area. How are you working with companies to make sure that they are attracting the right talent pool and retaining those workers once they have? Um, >>well, so this is, I think, one of the most important questions because, like what? What happened with technology in the past? We would put in these like ear piece systems, and that was a big part of our business, like 15 years ago. And once you learned one of those things, that's a P or oracle or, you know, like whatever your skill set was good for 10 years, You probably you were good. You could just, like, go to the work. But today it just just go down to like the convention center. Look at this vast array of like like >>humanity, humanity >>and new technologies. I mean, half these companies didn't even exist, like, five years ago, right? And so you're still set today is probably only good for a year. So I think the first thing you've got to realise is that there's got to be a new focus on actually cultivating talent as a strategy. It's it's the way to compete like people is your product, if you wanna look at that way. But we're doing actually starting very, uh, where we can very early in the process, like much beyond a corporation. So we work with charter schools over kids, we get them into college, we work with universities, we do a lot of internship. So we're trying to start, like, really early on when you ask a question like, what would our recommendation to the government be were actually advising, like, get kids involved in I t. Like earlier and so so we can get that problem resolved but otherwise, once companies work. I think you know you need your own talent strategy. But part of that might be again, like an eco system play like maybe you don't want all of those people and you'd rather sort of borrow on. And so I think, I think figuring out what your eco system is because I think I think in the future like competition will be like my eco system versus your eco system. And that's that is the way I think it's gonna work. And so thinking in an eco system way is, is what most of our clients need to do. >>Well, it's like you said about the old ways of it was a good idea for a good product versus good ideas. And I just keep looking. Thank you so much, John, for coming on the Cuba Really fascinating conversation >>was my pleasure. Thank you so much. >>I'm Rebecca Knight. Stay tuned for more of the cubes. Live coverage of the Accenture Executive Summit coming up in just a little bit

>> Announcer: Live from Copenhagen, Denmark, it's theCUBE. Covering Nutanix.Next 2019. Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of .Next Copenhagen Nutanix. I'm your host Rebecca Knight, co-hosting alongside of Stu Miniman. We're joined by Craig Routledge, he is the vice president HPE GreenLake Sales. Thank you so much for coming on theCUBE. >> Yeah, good afternoon. >> So why don't you start by telling our viewers a little bit about HPE and GreenLake. >> So HPE is the part of the old HP empire that's focused specifically on the hybrid computing world. So in the data sensors, the hybrid cloud world, and the edge and we're providing technology and services to our customers and our channel partners. And will continue to do so. And the announcement that we've made this week here in Copenhagen, is the announcement of GreenLake for Nutanix. >> So I'm not sure how much of our audience is very familiar with it. I've got plenty of experience with the various HP cloud initiatives over the years. But this is you know, at it's core, as a service as my understanding and help us understand where that fits in a customers over all kind of cloud portfolio. >> Yeah if you kind of take it back to the go back to real basics, actually almost before cloud. The customers access HP technology and infrastructures through capital purchase, through leasing, and some cases through subscription models, as the industry calls them. And then GreenLake was born about nine years ago in fact to help customers match cost to revenue. So it's a pay-per-use model. And that's where it was originally born. Before really the cloud was almost it was kind of around but not really in any scale. And then over the years, we've adapted GreenLake to be the private cloud solution for many direct customers then for channel customers, for service providers and partners. And now we've added the Nutanix partnership as well which, we've been announced as being ready for sale today onstage. Which is great timing by my engineering team I'm pleased to say. They were up late last night finishing it off. So its gradually evolving but were not just doing the private world, we're increasingly working in an environment where the equipment is installed in a colo. But it's still dedicated to that customer. Its not a shared service. And we're also increasingly, through out analytics portal, connecting to the public cloud world. So we've announced we have significant partnerships with the public cloud providers. And we can meter and monitor the customers usage in that solution. So we can provide a single tool set that gives them the private cloud usage and who's using it, and connect them to the public cloud world so they can get the same functionality in the pubic cloud. So they can see how much our marketing department are spending on computing storage, and networking and virtualization et cetera. >> It's a very different way for customers to think about it and many ways it should become more natural. If I got it right, I heard you say, its by the VM, or the container or by a certain flash increment. Maybe explain that a little bit? And you know, when and where would a customer say, "Oh well I need an increment of something that underneath "has Nutanix." >> Ah well it's interesting, you make in interesting point there actually. It is about customers buying work clothes, its the same way you buy a film on Netflix, or you buy a series or you might choose to buy episodes two, three, five, ten and 12 but not the whole book effectively. Not the whole library. And you buy that by the units of measure. So in Netflix, its a video or something. In the GreenLake world, its by virtual machine, at the VRAM level effectively. It could be by container, so it's the actual kubernetes container level. It can be at the gigabyte of high performing storage level. So we've disconnected the linkage between infrastructures. So the customer doesn't choose that infrastructure. The customer gives us a workload, and then we specify how that workload is designed. We have some recommended architectures. We're just about to launch the second dissertation of our quoting tools, so that a customer can get a quote on their smartphone, or our sales people in the pilot stages will be able to produce a quote on the phone. Now when that moves into operation, its our service team that are monitoring the customers usage 24 by seven. We own the metering and the management technologies. So we can snapshot the customers usage in their infrastructure environment, as often as we need to. So on Black Friday, you can guarantee we snapshot every retail customer in our portfolio at least every 30 minutes. And if there's a financial services crisis, as various presidents pick a fight with a global trade war. Share prices bounce up and down >> Not naming names. >> And dollars go in different directions and the RMB goes you need to meter the usage very rapidly, very accurately, and very often. And that's what our metering technology does. Now the service part of this, is not only do we kind of make sure that's all running 24 by seven, part of our service is to do the capacity management for the customers. So we take that responsibility off them. And if we think that the portal is telling us and the intelligence built into the portal, and into the experienced service managers saying, "You need an upgrade, we need to upgrade this piece." Then we can produce a change control note, one or two days, sign it, and then we can get some more infrastructure capacity rolled in of the chosen architecture for that customer. >> Just describing what you were saying about the retailers on Black Friday, and then watching the currency fluctuate based on whatever our world leaders are tweeting about. How has this in your mind changed the way the business world works today? Just the fact that we can see all this information this real time data. >> Its changed the speed and I think it it's the change of speed at which companies like ourselves have got to operate. And I think it's changed the speed at which the IT teams inside the end customers got to operate. And they get, I think they probably got the harder job than we have. An IT manager in an organization these days, not only has to watch those macro factors, the dollar going up and down, Britain finally sorts out its position on Brexit, we won't go into that one. And the IT team have got to look at that and see the impact on the business. But they also got to cope with the very rapidly changing environment. And a whole user base, I mean I don't know if any of you I presume you had to download the app on your smart phones. You press it, and if it doesn't download in three seconds, you're going, "Is something wrong here?" and that level of expectation in terms of the delivery of new application requests, is inherent in the user base now. Particularly the younger people are coming through in the wave of early stage employees and our customers. They expect instant gratification almost. They want a new app. They're a bit vague about how they want it to run, but they want it today. Now. And they want to pay a low volume price per click basis. So that's kind of, we're partly reacting to many of those trends. Part of our solution is in fact we provide, if we think the initial sizes, lets just say we need 500 Vms. Or we need 400 Nutanix and GreenLake licenses. We always provide a buffer. And in the early stage, lets say its 20 percent buffer. And that gives the customer some overflow room. So not only when we provision above their utilization but without a buffer to de-risk it for them. At our risk. And that's to make sure the service is seamless. And that's something that IT departments are not used to. But it matches the expectation of the internalized, I call them the IT consumers really, in business. Or customers of a bank. You know you dial your bank up on your app and you want to know what your balance is. And if you want to move money from that account to that account, you want it to go straight away. But I had a chasting experience on Sunday. My bank, they've got the app is online on Sunday. But they don't move money on the weekends. Am I'm like what? (chuckles) That was a bit stunning. And so my expectation is fueled by this kind of instant society that we live in. Yeah. >> So its order able now? >> Craig: Yes. Its order able now, we finished it >> Available? >> Available within 30 days. I mean, we think we'll have it available by the end of the month for delivery. >> Great and from a customer standpoint, will the customer be asking for Nutanix GreenLake? How does it, how do you give them the decision tree or is it a customer saying, " I wanted Nutanix." >> We have some people that are far more technically oriented than I am, technically literate than I am. We have some pre sales specialists inside the Nutanix team and inside the HP team. And we have some sizing tools as well to help us. So if the customer comes to us and says they want a particular workload, because we've expanded the choice, if they are talking to HP we'll look at what's the right solution. And if its Nutanix, then we use the Nutanix pre sales teams to help us. And that seems to be a very popular message in the marketplace. And is resonating very well. So we're helping the customer make a choice and obviously in a indirect motion, the partners will be helping the customer make that choice. And then coming us to, they'll specify the technology solution and they'll come to us with a specification. We'll turn that into a detailed specification. And a detailed cost and contract. >> So just GreenLake has been around for nine years now is this the first HCI based offering in the GreenLake portfolio? >> We've been working on the, we've had GreenLake on SimplyVity, which is the HP owned HCI solution. Two and a half, maybe three years now. And very successfully, its working very well in a few large cases. But it works different it works at a different level with different scaling parameters. So this is actually, the Nutanix partnership, and the reason why the two CEO's were excited, was this gives the customer another choice. And it gives them another choice other than the default virtualization engine, which everybody uses. And it also brings in the Nutanix expertise in end user computing, they call it VDI as I would call it. But that expertise and in the database world, it brings their expertise in that space is very valuable to us. So it augments our portfolio, and it brings two solutions to them. Not just the GreenLake solution, pay per use solution. But it also bring the proven HP server technology into their appliance portfolio. >> And the alignment on the optionality ] is really what is also driving this. >> Yes. And it is, we're both genuinely believe in customer choice in options. If the customer only got one choice, A: you've only given what the customer one choice and you might win or might lose, but you're going to have a resentful customer. If the customer says they want to go with HP and we only give them one choice, or can only give them one choice. Doesn't make for a long term relationship. And certainly I think both companies, HP clearly we believe having you know, lifetime we value a customer for its lifetime relationship with us. So its very important that we offer the customer choice, then narrow down to the right solution, refine that solution and draw it up into a contract. >> Excellent, so it's the right choice. Craig Routledge you are now a Cube alum. Thank you so much for coming on theCUBE. >> Thank you very much Thank you. >> I'm Rebecca Knight for Stu Miniman. Stay tuned for more of theCUBE's live coverage from .Next.

>>Live from Atlanta, Georgia. It's the cube covering Ansible Fest 2019. Brought to you by red hat. >>Welcome back. Everyone's cubes live covers here in Atlanta for Ansible Fest. Here's the cube covers. Have red hats event around automation for all. John Ford's do many men. Our next guest is Joe Fitzgerald, Cuba Lum, vice president, general manager of the management business unit at red hat. Great timing for Ansible. Great to have you back on the cube. Good to see you. Thanks for coming on. Thanks for having me. And it's great to have you here at Ansible Fest. Super essential for camera timing about Ansible. Let's do an, I did our intro, uh, analysis and platformization of automation. Big, big move, big news. But there's a bigger trend at play here around automation. Why is the timing now for automation discussions with Ansible? So good. The demand for automation is so broad in enterprises, right? They're trying to do everything from, you know, dev ops, tool chains to IOT devices. >>I'm trying to deploy things faster, uh, you know, fix security vulnerabilities faster. It's all about speed, agility, efficiency. It all comes back to automation. And the news here is the general availability, although available in November as announced on keynote of the Ansible automation platform. So this is something that's been going on for a while and I suppose just been grown weighing now it's a platform. What's in the platform? Why is it important? Why should customers care? So, uh, you know, we've been on this journey with Ansible which started off as this incredibly simple, elegant architecture and a way to automate things. And what's happened over the past couple of years is it's exploded in terms of the number of people who are using it, the number of people who are generating automation integration. Um, and so in working with a lot of customers, right, what we saw the need for was really to help them collaborate and scale their automation efforts. >>Um, scale, you know, who could, you know, build, reuse, share, uh, score content and track it. Really important. So we put a lot of those efforts into the platform to take it to the next level. Really. You know, we've been talking about Ansible, gum stew, going back when you know, 2014 OpenStack, I think I remember we are first talking about the cube. It had a cult following when it emerged. You guys acquired it at what, the next year, 2015 roughly. Um, but Annabelle had this cult following of people who just loved to get into the configuration side of things, make them go better. You guys acquired it, done well with it, kept it going, get the community flywheel, keep rolling a lot of progress since then. So what are you most proud of? What's the most notable things? Oh, the growth of the Ansible journey. What's, what's the big story there? >>So, uh, it's almost four years since red hat acquired Ansible. And I remember when I proposed acquiring Ansible and swell was this small, you know, Eastern U S company with sort of a community cult following, but very small in terms of, you know, commercials and, and reach and stuff like that. Mostly focused on the configuration space. Like a lot of the other automation tools over the past four years. Probably the best thing we did that redhead is really good at is we let the community do what the community does best, right? The innovation, the number of contributors, the amount of Ansible integration modules, playbooks has exploded, right. Uh, if you were in the keynote this morning, um, it was number six on the, you know, repository list out of 100 million, you know, almost, you know, just a massive amount of projects and here it is at number six. >>So we didn't perturb the community, we actually helped it grow and we've been able to help the technology evolve from a config automation product and technology into this very broad spectrum. Now enterprise automation platform that crosses domains like, you know, networks and security and storage and cloud and windows. Just a phenomenal, uh, you know, growth in it. Yup. Show help. Explain how platform sets up Ansible for it future. They talked in the keynote a little bit about starting with some of the, uh, kinda core partners in the collections that they're offering. But in the future for a platform to really be a platform, it needs to be something that users themselves can build on top of. So, you know, help us understand where it is today. You know, when it first announced here for November, um, and where it shows shall be going in the future. >>So we didn't use the platform word lightly. Um, I think that, you know, platform has a set of connotations and, and it's sort of a set of requirements. What we saw was that different teams and groups inside organizations, we're bringing Ansible in and using the technology and having very good success in their particular area. Then what we saw was these teams were trying to share automation and collaborate across organizations. Then even in the community, there's tens of thousands of rolls and playbooks out there that the community has built. There might be 300 that do the same thing, which is the best one, which, which one are people using? Uh, you know, how successful is it? How long does it take? Um, what we found was that they needed a bunch of tools to be able to collaborate, track, uh, analytics about stuff so that they could share and collaborate at a higher scale. >>Yeah. I, that's one of the great value propositions when we talk about SAS is if it's done well, not only can I share internally, but I can learn from others that have used the platform and make it easier to take advantage of that. So is that part of that vision that you see with the platform? Yeah, so I mean, there's a couple different ways of sharing. If you're running a SAS service, then you know, a central person is coordinating the sharing and things like that. What we tried to do with the, with the Ansible platform is basically enabled the way that people can share content without having to go through a central, you know, agent, if you will. So we provide services and things to help them manage their, their content, you know, with uh, you know, uh, galaxy and collections and things like that. >>Um, it's all about organizing and being able to share content in a way, uh, to make them more efficient. Should I talk about the trends around, um, you've done it. First of all, you done a great job with Ann's book. Congratulations. Um, the big fan of that company and you guys did a good job of it. As it goes full, where you're thinking about cloud complexities as people start looking at the cloud equation, hybrid and cloud 2.0 and the enterprise complexity still is coming as more of it. How do you guys see that? How are you viewing that, um, that marketplace because it's not just one vertical, it's all categories. So how are you guys taking animal to the next level? How you guys look at that, managing those complexities that are around the corner? Yeah. So if you think about it, you know, everybody's moving towards a multi, multi hybrid cloud, you know, sort of configuration, right? >>Um, each one of these platforms and clouds has their own set of tools which work really well perhaps in their particular cloud or their silo or their environment. If you're an organization and you're running multi-cloud, you're responsible for automating things that might span these clouds. You don't want to have different silos of automation tools and teams that only work in one cloud or one environment. So the fact that Ansible can automate across these, both on premise and in the public clouds, multiple public clouds, across domains, network storage, compute, create accounts, uh, you know, do all sorts of things that you're gonna need to do. So it's one automation technology that will span the complexity of those environments. So it really, it's, I don't see how people are going to do it otherwise without fielding lots of people and lots of tools. You know, we were talking with Stephanie and Sue and I talked on our intro insights segment around the word scale has been kicked around, certainly is changing a lot of the landscape on how companies are modernizing the open source equation, but it's also changing the people equation. >>I want you to explain your vision on this because I think this is a key point that we're seeing in our community where people have told us that automation provides great efficiency, et cetera. Good security, but job satisfaction is a real big part of it. You know, people, it's a people challenge. This is about people, your view on scale and people. So organizations are under tremendous pressure right now to do more, right? Whether it's deploying new application faster to close security vulnerabilities faster, uh, to move things around to, to, to right size, you know, resources and applications and things like that. And you know, Ansible allows them to do that in a way where they can be much more efficient and be much more responsive to the business, right? Otherwise, you know, you see some of the customer testimonials here where the amount of time goes down from six hours to five minutes, the teams can be far more productive. >>Um, it, it really gives job satisfaction because they can do things that were almost impossible to automate before by using Ansible to automate network storage and compute in the same playbook. Before, those were three different tools or three teams and people of solving some of the same problems in different areas. And this is where playbooks can be a problem and an opportunity because we have too many playbooks, you have to know which playbook to be available. I mean you can almost have a playbook of playbooks and this is kind of a opportunity to use the sharing collaboration piece. What's your rich to thought on that as that playbook complexity comes in as more playbooks enter the organizations, you know, there's a lot of deployment of the same kind of stack or the same kind of configuration and things like that. So you know, it's really extending community beyond, you know, you know, working on code into working on content, right around automation. >>So if somebody wants to deploy engine X, I think there's over 300 different, you know, playbooks to deploy engine X, right? We don't want to have 5,000 playbooks to deploy engine X. Why can't there be a couple that people take and say, wow, this is perfect. I can tweak it from my organization, integrate my particular systems, and I can hit the ground running instead of trying to either start from a blank page or to go sift through hundreds of almost close, uh, you know, playbooks that do sort of the same thing a lot of times. David's big time. Enormous. Alright. >>So Joe, congratulations on the four years of just continued growth, you know, great momentum in the community wanting to touch on, you know, the, the, the big move, uh, you know, in the last year is, you know, IBM spending, you know, quite a few dollars to, to acquire red hat. What will this mean for kind of the reach and activity around Ansible in the community, the IBM acquisition. >>So IBM had been involved in Ansible in a number of their, you know, products, right? In terms of integration into Ansible. So they have teams and folks within IBM that obviously got Ansible all before the acquisition. Um, I think that it's, it's highly complimentary. IBM has very strong capabilities around management and monitoring, security and things like that. All of those things inevitably turn to automation. Right. Um, so I think it really, um, it only gives us access to IBM and, and they're sort of, you know, their their channel and their accounts in their, and their reach, but also their teams that have these, these sets of technologies, um, that are natural compliment, you know, whether it's Watson driving Ansible or security or network monitoring, driving Ansible automation. It's a really powerful combination. >>Yeah. I also just want to get your kind of macro level view on automation. I sat on a panel talking to CIS admins about careers and it was the number one thing that they felt they needed to embrace. We see like the RPA community probably in adjacency to what you see heavily pushing automation, uh, you know, help explain how important automation is and that it's not, you know, just a silver bullet also. >>Yeah. So, you know, a lot of times people are, you know, the, the sort of the easy, um, you know, description is automation's gonna eliminate jobs or things like that. I think it's more like sort of the power tool analogy. You know, you know, if you had a, you know, a hammer and a screwdriver before, now you've got a power screwdriver and a pneumatic hammer and uh, you know, all sorts of additional things. They're force multipliers for these people to do broader, bigger things faster, right? Um, and that's what every organization is driving them to do. How agile can you be our competition deployed something, how fast can we deploy it and how many, you know, new releases a week. Can we deploy, um, when security hits, you know, how fast can we close the vulnerabilities that hours, days, weeks, or can we do it in minutes? >>The old expression, if you, if you're a hammer, everything looks like a nail. But if you're an agile, you can adjust to figure out the opportunity. It's kind of awesome kind of quote there. This speaks to the changes. I want to get your thoughts. Last question for you is, as someone who's been in the industry for awhile, we've first interviewed and I think 2014 at OpenStack when we first started chatting around the industry. So much has changed now more than ever. The modern enterprise is looking at cloud impact, operating as an operating model, cloud one, Datto, Amazon compute, storage standups software, and they're piece of cake startups. We're doing it now as enterprises really want to crack the code on cloud software automation. Observability these new categories are emerging, kind of speaks to this cloud 2.0, how would you describe that to folks if, if asked, what's the modern era enterprise cloud architecture look like? >>What is cloud 2.0, how would you take a stab at that definition? So I would say after all these years, cloud is really entering its infancy and what does that mean? We're just starting now to appreciate what can be built in cloud and we're going to get a big boost soon with five G, which is gonna, you know, increase the amount of data, the amount of, uh, you know, edge devices, uh, IOT and things like that. Um, the cloud is becoming, you know, the first choice for people when they build their architectures and their business. Um, it's gonna fundamentally change everything. So I think, you know, some people, what's the quote? You know, some people overestimate, you know, what the technology can do in the short term and underestimate what it can do in the longterm. We're now getting to that point where people are starting to build some really powerful cloud based applications. See this as a big wave then big time wave. Yeah. I mean, we had a quote still on the cube last week. Data is the new software, so software, abstractions, automation. This is the new way. I mean, it's a whole new architecture. So exciting. Thanks for coming on the cube. Appreciate juncture having thanks. We're here at the Asheville Fest, the Cuban Chalfont stupid men. Break it down. The analysis, getting into the automation for all conversation. Big category developing. We're covering it here. Live back more after this short break.

>>live from Atlanta, Georgia. It's the Q covering answerable Best 2019. Brought to you by Red Hat >>Welcome back. Everyone's cubes Live coverage here in Atlanta for answerable fest. Here's cube covers of red hats. Event around automation for all I'm John for a stupid man. Our next guest is Joe Fitzgerald cable. Um, vice President General manager of the management business Unit at Red Hat. Great timing for answerable. Great to have you back on the Cube. Good to see you. Thanks, Mom. Thanks for >>having me. It's great to have you here. A danceable fast, super >>tight before camera timing about answerable to do And I did our intro analysis and platform ization of automation. Big, big move, Big news. But there's a bigger trend at play here around automation. Why is the timing now for automation discussions danceable. So good. >>The demand for automation is so broad in enterprises right there trying to do everything from, you know, Dev ops tool chains to io ti devices trying deploy things faster, you know, fix security vulnerabilities faster. It's all about speed, agility, efficiency. It all comes back to automation >>and the news here is the general availability of the available November as announced on Keynote of the Answer Automation Platform. So this is something that's been going on for a while, and it's just been grown. Now it's a platform. What's in the platform? Why is it important? Why should customers care? >>So you know, we've been on this journey with answerable, which started off. Is this incredibly simple, elegant architecture and a way to automate things and what's happened over the past couple of years? It's exploded in terms of the number of people who are using it, the number people who are generating automation, integration. And so in working with a lot of customers, right. What we saw the need for was really to help them collaborate and scale there. Automation efforts scale. You know who could build re you share, score content and track it really important. So we put a lot of those efforts into the platform to take it to the next level. Really? You >>know, we've been talking about answerable comes stew going back when 2014 open stack. I think I remember were first talk about the Cube. It had a cult following. When it emerged, you guys acquired it what the next year? 2015? Roughly. Um, but Ansel had this cult following of people who just love to get into the configuration side of things. Make them go better. You guys acquired it, Done well with that. Kept it going that the community fly. We'll keep rolling a lot of progress and say So. What do you most proud of? What's the most notable things of the growth of the answerable journey? What's what's the big story there? >>So it's almost four years since Red had acquired danceable. And I remember when I proposed acquiring answerable insult was this small? You know, Eastern U S company with sort of, ah, community cult following, but very small in terms of commercials and reach and stuff like that mostly focused on the configuration space. Like a lot of the other automation tools over the past four years. Probably the best thing we did that redhead is really good at is we let the community do with community does best, right? The innovation, the number of contributors, the amount of answerable integration modules, playbooks has exploded, right? If you were in the keynote this morning, it was number six on the you know, repositories list out of 100 million almost, you know, just a massive amount of projects. And here it is at number six. So we didn't perturb the community. We actually helped it grow. And we've been able to help the technology evolved from a config automation product in technology into this very broad spectrum. Now, enterprise automation platform that crosses domains like networks and security and storage and cloud and windows just a phenomenal growth in it. >>So help explain how platforms sets up answerable for its future. They talked in the keynote a little bit about starting with some of the kind of core partners and the collections that they're offering. But in the future, for a platform to really be a platform, it needs to be something that users themselves can build on top of so, you know, help us understand where it is today when it first announced here for November, and where it shows shall be going in the future. >>So we didn't use the platform word lightly. I think that, you know, platform has a set of connotations, and it's sort of a set of requirements. What we saw was that different teams and groups inside organizations were bringing Ansel in and using the technology and having very good success in their particular area. Then what we saw was thes. Teams were trying to share automation and collaborate across organizations. Then, even in the community, there's tens of thousands of roles and play books out there that the community has built. There might be 300 that do the same thing, which is the best one, which, which one of people using How successful is that? How long does it take? What we found was that they needed a bunch of tools to be able to collaborate, track analytics about stuff so that they could share and collaborate at a higher scale. >>Yeah, that's one of the great value proposition when we talk about SAS is if it's done well, not only can I share internally, but I can learn from others that have used the platform and make it easier to take advantage of that. So it is that part of that vision that you see with the platform? >>Yes, so I mean, there's a couple of ways of sharing. If you're running a sass service, then you know a central person is coordinating the sharing and things like that. What we try to do with Sensible Platform is basically enable a way that people can share content without having to go through a central you know, agent, if you will. So we provide service is and things to help them manage there. They're content, you know, with galaxy and collections and things like that. It's all about organizing and being able to share content in a way to make them more efficient. >>You're talking about the trends around. You've done it for a while, you know, great job. And congratulations, big fan of that company. And you guys did a good job with it as it goes full where you're thinking about cloud complexities as people start looking at the cloud equation hybrid and cloud 2.0, on the enterprise, complexity still is coming. There's more of it. How do you guys see that? How you viewing that that marketplace? Because it's not just one vertical. It's all categories. So how are you guys taking animals? The next level how you guys look at that? Managing those complexities that are around the corner? >>Yes. So if you think about it. You know, everybody's moving towards a multi hybrid cloud, you know, sort of configuration, right? Each one of these platforms and clouds has their own set of tools, which worked really well, perhaps in their particular cloud or their silo, where their environment. If you're an organization and you're running multi cloud, you're responsible for automating things that might span these clouds. You don't want to have different silos of automation tools and teams that only work in one cloud or one environment. So the fact that answerable can automate across thes both on premise and in the public clouds multiple public clouds across domains, network storage, compute, create accounts, you know, do all sorts of things that you're gonna need to do. So it's one automation technology that will span the complexity of those environments. So it really it's I don't see how people gonna do it otherwise, without fielding lots of people and lots of tools. >>You know, we're talking with Stephanie, and soon I talked on our intro insights segment around. The word scale has been kicked around certainly is changing a lot of the landscape on how couples heir modernizing the open source equation, but it's also changing the people equation. I want you to explain your vision on this because I think this is a key point that we're seeing in our community, where people have told us that automation provides great efficiency, etcetera, good security. But job satisfaction is a real big part of it. You know people. It's a people challenge. This is about people, your view on scale and people. So >>organizations are under tremendous pressure right now to doom or right whether it's deployed new application faster, too close security vulnerabilities faster to move things around. T right side's resource is and applications and things like that. And, you know, answerable allows them to do that in a way where they could be much more efficient and be much more responsive to the business. Right? Otherwise, you know, you see some of the customer testimonials here where the amount of time goes down from six hours to five minutes, the teams could be far more productive, productive. It really gives job satisfaction because they can do things that were almost impossible to automate before by using insult, automate network storage and compute in the same playbook. Before, those were three different tools or three teams, >>and people are solving some of the same problems in different areas. And this is where playbooks can be a problem and an opportunity. Because we have too many playbooks. You know which playbook be available? You could almost have a playbook of playbooks. This is kind of ah, opportunity that used the sharing collaboration piece What you're Richard thought on this as that playbook complexity comes in as little playbooks enter the >>organizations. You know, there's a lot of deployment of the same kind of stack or the same kind of configuration and things like that. So, you know, it's really extending community beyond, you know, you know, working on code into working on content, right around automation. So if somebody wants to employ Engine X, I think there's over 300 different playbooks to deploy Engine X right. We don't wanna have 5000 playbooks to deploy Engine X. Why can't there be a couple that people take and say, Wow, this is perfect. I can tweak it for my organization, integrate my particular systems, and I can hit the ground running instead of trying to either start from a blank page. Let's go sift through hundreds of almost close playbooks. That sort of the same thing A >>lot of times, David. Big time. Enormous. >>So, Joe, you know, congratulations on the four years of just continued growth, you know, great momentum in the community wanting to touch on. You know, the big move, you know, in the last year is, you know, IBM spending, you know, quite a few dollars to acquire red hat. What will this mean for kind of the reach and activity around answerable in the community, the IBM acquisition. >>So IBM had been involved in answerable in a number of their products, right in terms of integration into danceable. So they have teams and folks within IBM that obviously got and some old before the acquisition. I think that it's it's highly complimentary. IBM has very strong capabilities, room management and monitoring security and things like that. All those things inevitably turned to automation, right? So I think it really it only gives us access to IBM in their sort of their channel and their accounts in their reach, but also their teams that have these sets of technologies that are natural complement, you know, whether it's Watson driving Ansel or security or network monitoring, driving danceable automation. It's a really powerful combination. >>Yeah, I just want to get your kind of macro level view on automation. I sat on a panel talking to sys. Admin is about careers, and it was the number one thing that they felt they needed to embrace. We see, like the r p a community, probably an adjacency toe. What you see, heavily pushing automation, you know, help explain. You know what? How important automation is in that it's it's not, you know, just a silver bullet also. >>Yeah. So, you know, a lot of times people are, you know, the sort of the easy description is automation is gonna eliminate jobs or things like that. I think it's more like sort of the power tool analogy. You know, you know, if you had a you know, a hammer and a screwdriver before now you've got a power screwdriver and automatic camera, and you know all sorts of additional things. Their force multipliers for these people to do broader, bigger things faster, right? Um and that's what every organization is driving them to do. How agile can be our competition deployed. Something How fast can we deploy it? How many new releases a week Can we deploy when security hits? You know how fast we closed the vulnerabilities of hours, days, weeks or we do it in minutes. >>The old expression. If you're a hammer, everything looks like a nail. But if you're an agile hammer, you can adjust the figure out. The opportunity is kind of awesome. Kind of quote there. This speaks to the changes. I want to get your thoughts. Last question for you is that someone's been in the industry a while. We first interviewed nothing 2014 and open staff when we first started chatting around the industry. So much has changed. Now more than ever, the modern enterprise is looking at cloud impact, operating as an operating model cloud one Dato Amazon Compute storage stand up software and there piece of cake start ups were doing it. Now it's enterprises really want to crack the code on cloud software automation, observe abilities, new categories emerging kind of speaks to this cloud. 2.0, how would you describe that to folks, if if asked, what's the modern error enterprise Cloud architecture look like? What is cloud two point. Oh, how would you take a stab at that definition? So >>I would say after all these years, Cloud is really entering its infancy. And what does that mean? We're just starting now to appreciate what can be built on cloud. And we're gonna get a big boost soon with five g, which is gonna increase the amount of data, the amount of edge devices I ot and things like that the cloud is becoming, you know, the first choice for people. When they build their architecture in the business, it's gonna fundamentally change everything. So I think you know some people. What what's the quote? You know, some people overestimate You know what a technology can do in the short term and underestimate what it can do in the long term. We're now getting to that point where people are going to build some really powerful, cloud based applicator. >>You see, this is a big wave that big time twice. Yeah. I mean, we had a quote stew on the Cube last week. Date is the new software software abstractions. Automation. This is the new way means the whole new architecture so exciting. Thanks for coming on the key Appreciate Just for having. We're here at the animal fests Acute I'm Jumper Stewed Minutemen breaking down The analysis. Getting into the automation for all conversation. Big category developing. We're covering here. Live with more after this short break.

>> Man: Live from San Francisco celebrating 10 years of high tech coverage, it's the Cube. (music) Covering VMworld 2019. (music) Brought to you by VMware and it's ecosystem partners. >> And welcome, indeed, here to the cube and our coverage of VMworld 2019. We are in the Moscone Center in San Francisco. They're open, they're back in business and so is VMware. And we're watching the folks stream out from this morning's keynote session, Pat Gelsinger hosting that session. And it was an impressive setup to say the least. Thousands packing that ballroom downstairs for a plethora of announcements, all from Pat Gelsinger. I'm John Walls, Justin Warren joins us. We haven't been together for a while, it's good to see you.- It's been a little while, yeah. >> How've you been? >> I've been well, I've been well. >> Yeah. >> Yeah. >> I'm surprised they brought us back together after the last time. >> I don't believe... let's not talk about that incident. >> I thought it went so well, we just end on a high note. But it is a pleasure to be with Justin, we'll be with him throughout the week, Monday, Tuesday, Wednesday, our coverage here. We're joined right now by two guests, Paul Savill, whose the SVP of Network and Technology Solutions at CenturyLink and Omar Sunna who is the Director of Digital Products at GE Health care. And gentlemen thanks for being with us, it's good to have you here on the Cube. >> Thank you John. >> First off, let's just, gimme, your both, your take just on VMWorld 2019. What you're looking for, what you're expecting, and kind of the early vibe that you have going on. Paul, why don't you take that first? >> Sure, one of the things I've really been impressed with is how VMware is expanding, the kind of open nature of it's relationships, it's developing it's ecosystem, really broadening it out, it's making a number of acquisitions to enable new capabilities. And we're really excited about that. CenturyLink and VMware have been partners for, I think, around 12, 15 years. As we've been building out our own cloud services and so it's a very exciting time to see all this technology coming together in the way that it is. >> I love with the way you put it too, acquisitions. Pat made a little comment about that, it's like, "I can't wait to find out who I'm "going to buy next." >> Yes. >> And they've been, certainly been in a full speed ahead modefor the past year, year and a half. Omar, you're take, early. >> Yeah, man, I think I look at it from a health care solutioning perspective and it's exciting to see this level of technology and kind of the building out of the ecosystem and what could it enable for health care consumers. Especially with the big focus around privacy and and data management. I think some of their, and security, some of their latest acquisitions could actually help grow that ecosystem and offer more options especially to the health care industry. >> All right, well now let's talk about your portfolio at work then, a little bit, at GE Healthcare. Obviously health systems, health care's a huge user you know, these days, well it's kind of simplifying it a bit, but just talk about what you're concerns are, what your attention is, and kind of the things that are keeping you up at night, these days, in terms of health care and what you're doing in the IT space. >> You know, I mean, I think the, you know when we look at our customer environment globally, you know, we tend to kind of summarize some of the key challenges for our customers around three pillars. Access, so being able to provide access to all the patients that need it, regardless of location. With aging population in a lot of developed countries, with also a lot of people having the means to receive more proactive health care, it is challenging the health systems to be able to provide adequate access to patients. Capacity, providing capacity when the resources, including the human capital resources, that health systems have. So how do you free up your specialists to make sure that they're able to provide the right level of patients who need it, patient care for the patients that need it. As well as clinical efficacy. How do we help with software applications, with technology, to help reduce the variation of care, and improve patient outcomes, regardless where the patient is receiving care, within the rural community or with advanced academic medical centers. So we try to kind of think of our solution technologies as helping our customers solve for access, capacity, and clinical efficacy. >> Yeah, so a lot of health care, it's kind of a retail setup in that there's lots of hospitals and other allied health professionals who have lots of different locations that they need to provide heath care for them and that technology needs to live where the patients are and where the doctors are. So it was interesting to see, in the key note, earlier this morning, talking about edge and different kinds of edge as well. We've got thin, medium, and thick edge, according to VMware. So how do you see that rise of edge computing effecting the way that you deal with health care. >> Yeah, I mean tremendous, actually, opportunity for us. And GE is working on capitalizing on the technology, on edge technology, to allow us to bring in AI application right to, where kind of within the customer network. And that is, that's helping us solve for a lot of concerns around private security as well as moving large data sets to the cloud to process, to be able to get benefit out of algorithm and additional applications. So that's actually an exciting area. And agree with you, I mean we're seeing more and more large distributed health care networks emorph, in the U.S. we've definitely seen huge merger and acquisition movement that we continue to see, and consolidation. And then we also see that globally. With regional delivery networks coming up and being able to have software applications live within this distributed network and provide information for the right clinician at the right time is a big initiative for us. And for us this makes a huge difference in the way our providers are able to deliver care for their patients. >> This seems like an ideal opportunity for the folks at CenturyLink to help you with that. >> Abso-- (nervous laughter) >> Yeah, that's right, I mean CenturyLink really, to that point, sees this landscape evolving rapidly. And we even have a phrase internally we use that, "The network is the data center." We believe that in the future, compute is going to be distributed so widely, in such a broad geography and dropped in places where it's most efficient to run it and where it's most efficient to connect it with network, that really, the data centers we think about it today, becomes this very widely distributed platform that is connected together with high performance networking solutions. And that's part of what we're working with GE Healthcare on. >> I'm old enough to remember when "The network is the computer" was the slogan that we're all following now, and it seems that's actually coming true now. Where we have this idea of it, it's not just cloud, and it's not just data centers, and it's not just edge, it's actually a combination of all of them. And you need to be able to deal with that technology wherever it needs to live. Which is, I think, is a positive change from what we were talking about a few years ago, where it seemed to be, we had to make one choice. Now the choice is you actually need a bit of everything. >> Right. >> Tell me about your decision, or at least in terms of on-prem, off-prem, and health care, I would assume, extremely sensitive, obviously, to security concerns and management and certain policies about who can access what, where, when and how, whatever. How are you going about making that decision in this new multi-cloud environment, this hybrid-cloud environment, when people are making migrations, you know, with their businesses, and they're going off-prem. But you, I would assume, have to be a lot more sensitive, or more sensitive to other factors than, perhaps, other businesses have to be. >> Yeah, we definitely do. There is, you know, with regulations, you know, and, for example in Europe, GDPR, there's in country regulations around where data resides. All of that kind of plays a factor in customer adoption of technologies and where they're comfortable. We've talked a lot of CIOs in the health care sector and a lot of them say, "Hey, listen we're on a journey, "we're used to hugging our servers, "we're used to controlling it, and technology has evolved. "But, in terms of our policies, ability to accept liability "of data breaches and what technology providers are willing "to sign up for. "All of that plays a roll in that journey." Like Justin had mentioned, it is actually a, in developing an ecosystem, where you have combination of on-prem and off-prem, is a lot of where health care health systems are investing their money. So we're seeing certain data that resides on-prem that is mission critical versus more historic data can go into cloud technology, cloud storage technology and others. But, there's no doubt that we're at an inflection point, we're seeing a lot more health systems sign up to cloud based SAS applications. Invest in private cloud hosting service, invest in also public cloud hosting services. And all of that actually will create, as a software provider, all that could actually help us create more opportunities and more solutioning for our customers. I love listening to some of the cloud computing power that would allow us to develop newer applications. So it's actually exciting, it's a journey with our customers, you know, we're choosing to kind of be alongside of our customers and help them. Doing a lot of education. And being able to have a relationship with CenturyLink, be able to see the advances and availability of resources that CenturyLink makes available for us as well as other partners that we have help us really make sure that we're able to build the right level of technology meeting the health care customer needs. >> So Paul, fill in the gaps a little bit about where CenturyLink is in trying to solve this, I wouldn't say dilemma, but it certainly is a puzzle of some sort, right, as decisions are made about what's going to be off loaded, what's not, how are we going to access, what do we allow. How do you see CenturyLink's role when you have a customer like Omar, like GE Healthcare, coming to you with their unique needs, and addressing those? >> Sure, well, as unique as GE Healthcare is in the health care industry, there are some common characteristics about how we are seeing enterprise customers look at these situations. And one of them is that placing compute on the premise itself, that, that is generally the most expensive real estate that an enterprise has when it has to go in the hospital, when it has to go at the retail store location. And a lot of enterprises today are doubling the amount of compute and storage that they're having at their premise locations every year because the volume is just growing so much. That's becoming a problem, because you don't want your, you don't want your hospital becoming a bigger and bigger data center, so to speak, right? And so the way that we're approaching the problem and working with this, is in VMware was actually, you know, expressing a very similar viewpoint about the edge and about how the thick edge and the thin edge, and the thin edge of the customer premise is where you want to have the lightest load, but you want to have the most critical applications that are sitting there, you want to have the information that you have to protect the most in a most guarded way that's most important for your operations there. But from there you can more efficiently run things from a distance backing out going all the way back to the public cloud core, if you connect it with high performance networking from end to end. And so what CenturyLink has been doing is putting together these solutions that make that balance of trade, so to speak, between the cost of compute, the cost of where you have to put it, to where it best can be housed, what kind of latency performance that it needs to have to meet it to the performance specification, all the way back to the public cloud design and how to tie it in to the public cloud. And that's where we've been building our competency and the solutions we've been putting together for customers. >> You mentioned the need for high performance networks in there so I've got to ask you about 5G. From what I know about 5G it looks like the kind of situation you have with health care, where you've got lots of mobile tablet devices, you've got lots of other actual equipment IoT devices in a health care situation. That seems like an ideal use case for 5G. Is that what hot 5G is actually for, is the hype real? >> Well, 5G is certainly going to transform the world in terms of it's ability to provide wireless high bandwidth connectivity and low latency connectivity to devices. But, edge compute is not about 5G. You can have edge compute without 5G. In fact, it's a bit of a myth that edge compute can't arrive until 5G comes, because edge compute is something that is available to do today. And, in fact, CenturyLink is deploying edge compute solutions with, by basically building fiber into enterprise locations and then housing compute at different areas of the network at the point that's most optimal for the solution. And there are a variety of wireless solutions that can be used in that campus environment other than 5G to connect wireless devices back securely and safely to that edge compute that sits there. >> But it seems like it still should be, or at least looks like it could be a game changer in what it's going to allow in terms of, I guess, advancing edge computing. >> Right? I mean, you're still going to provide new capabilities and new reach and new functionalities that don't currently exist. >> I take Paul's point, though, because there are other technologies like Wi-Fi 6, for example, which is, it's basically the same thing as 5G, it just uses a different radio communications mechanism. But, and I also take your point that you can do edge computing today, absolutely. You can put computing into retail situations and you can have, I mean we have tablet devices now. We have laptops. So we kind of have edge computing. We always have, it just now, now it has a name. >> Yes, that's correct. >> So, tell me before we let you go, Catalyst Award winner from CenturyLink and VMware, Paul, first off let's talk about how you assess that, what's the determination, the criteria, for that and then I'm going to let crow a little bit Omar, about receiving that award. But tell us about the Catalyst Award first. >> Yes, well we call it the Catalyst Award because, when you think about it, a catalyst is something that excites a chemical process. Technically that is the definition of catalyst. But catalyst, in the way we view it, is something that we wanted to recognize a person or a company, that we felt like was really driving innovation, that was really solving a problem and working, also collaboratively together with VMware and CenturyLink in solving some of these problems. So we looked at GE Healthcare and really felt like, in a place where certainly we have seen such great advances in health care administration and building to save people's lives. Oddly, medical errors is becoming an increasing amount of now the problems in terms of death rates. Because, while we have so many ways to solve problems, so many ways to address it, that portion of what's causing deaths is actually on the rise. And so GE Healthcare is taking the technology that they're deploying and helping to solve that problem, that's why we wanted to recognize Omar and the company today. >> An honor for you I would assume you're all pretty proud of that. >> Yeah, absolutely, and thank you, and, yeah, I mean it's was really fantastic to be recognized by our partners. And a great testimony to the team at GE Healthcare. And our team wakes up in the morning and our mission is to improve lives in the moment that matters. A lot of our technology is used in mission critical and the way we're able to deliver that to our customers relies heavily on our ability to leverage advances in technology and be able to improve our ability to deliver our different applications for our customers. So this, actually been fantastic, the relationship has been tremendous for us. Where we have hosted our solutions in CenturyLink, the level of support that we have received have really enabled us to deliver important application for our customers and meet their SLAs and meet their clinical use cases and the needs of software uptime. So that has been tremendous for us. >> Well congratulations. >> Thank you. >> Well then thanks for your time, both of you. And enjoy the show, enjoy San Francisco, we've got good weather this week. >> That's right, yeah. >> So get out and enjoy that, thank you Paul and Omar. Back with more on the Cube, you're watching our coverage here live in San Francisco in VMWorld 2019. (music)

(upbeat music) >> From our studios in the heart of Silicone Valley, Palo Alto, California, Nick is a Cube conversation. >> Hello, and welcome to the Palo Alto Cube Studios, I'm John Furrier, host of the Cube. We're here for great Cube conversation with Gilad Bracha who's a distinguished engineer at Shape Security, has a legacy in the programming world, one of the early folks working on Java, a variety of other great things: Small Talk, Newspeak, a variety of programming accomplishments. A legend in the industry, thanks for coming on. >> Well, thanks for having me, it's a pleasure to be here. >> You know, one of the things we always talk about on the Cube is how I work for a company, they do this, they do this great, here's our differentiator, here's our advantage, a lot of marketing speak, and then we also do a lot of interviews around disruption, around cloud computing, getting to DevOps, network effect, changes of network, moving packets around store and compute, all the benefits of cloud computing but we don't really talk about the underlying languages that are driving all the changes and this is something that you're an expert in and I want to get your thoughts on this because, you know, computer science is at an all time high. You can't go to Berkeley, you see what's going on at Berkeley, the number one major is computer science, the data classes, dreams of starting a company, but computer science is changing a lot. More people are coding but does that mean there still more computer science going on? So, a lot of people are trying to understand where the future is going to be and underneath it all is the programming languages themselves. >> Yeah, well-- >> Your thoughts on computer science and the languages out there. >> So, too much to say. But computer science is a lot, there are trends and there's a lot of emphasis now on machine learning and things like that. And it's interesting because that affects, which language you use can make these tasks a lot easier or a lot harder. And we've, you see certain languages being picked up for that purpose and new languages being done for numerical stuff like Julia, people are using R, God forbid and it's really interesting to see that. To me, it's interesting because there's a whole set of languages, the APL family of languages which really go back to the early 60s. But they're just phenomenally designed for these kind of large arrays of data for doing mathematical operations in parallel on large arrays or multi-dimensional arrays, essentially, tensors, back before that word was used in programming. And there's huge potential for doing better in terms of programming with those things. So that is one new, not new but area that's been kind of coming alive again. >> Yeah. >> That's really cool. >> You know, it's interesting, too, you bring up a point. We were talking before we came on camera about Lisp and all these other cool science out there. With, now, the advent of unlimited compute with cloud and, now, kind of new connected devices, a lot of the old science is coming back into vogue because of some of the use cases. I mean, I remember when I graduated college in the 80s, we had departments that were actually called data processing departments. And they used data processing, that's what they did, they processed data. That's the number one use case today is processing data. So, a lot of the old is coming back because it's relevant in this new era. So, I got to ask you, what is your favorite science and computer science that you think is relevant? You mentioned APL, what concepts, we TensorFlow with Google, things like that coming back, you see machine learning and AI, these are not new concepts. >> Well, some of them, I mean-- >> What's your thoughts? >> Machine learning, definitely, there have been breakthroughs in the past, I don't know, 10, 15 years and but the basis of it, the beauty of this is the basis of this is the real hardcore math in calculus and statistics, that stuff is golden and wherever it applies throughout the universe and you look at reasoning about these things and it comes up again. That's the root of it all. Making it so that you can manipulate things closer to level you can with math is really challenge for programming languages, so that you don't spend your life dealing with, sort of, irrelevant, boring details, oh, this has to be lowercase, that has to be tab, this tool doesn't work on that operating system. Most of our effort as software engineers goes, we're dealing with junk, really, and we should try and abstract over that and get over that. >> What are some of the exciting things that get you excited for programming language because there's a lot more excitement, a lot more opportunities now; you're seeing you can stand up software very quickly these days, and so there's some really quick and dirty ways to get software written with languages. Some want more principle-based design languages that have all the integrated components. What's the trade-off, what are some of the things you like around the new trends? >> So I'll give you something that meets both of the criteria that is both very principled but actually makes it much easier to put something together. One of my favorite new things that have come in the past few years is a thing called Elm which is a language, essentially, the main application, so far, has been to build websites, essentially, UI that's targeting a website but it is a functional programming language but it is much more approachable than the traditional academic stuff, even though the ideas are basically the same, but they're very well engineered. Actually, better engineered in many respects than a lot of the traditional stuff that you see like the Haskells and OCamls and stuff. And it started for the web, so it's a different game but it's a joy to use, it has great error messages, it has a time traveling debugger which is one of my favorite hobby horses, so you can actually go back and roll the computation back to where a problem occurred. And that, kind of, is interesting because it meets both of those points. >> Talk about this live programming, you mentioned rolling back and this is around live programming. >> Yeah. >> This is an exciting area. >> Oh, yeah. >> Your thoughts on live programming because we're seeing collaboration where I can have a screen open. I saw a demo at Amazon Reinvent last year or year before where people can be in different parts of the world or different offices in the same building and coding the same, I get the collaboration piece but there's also live programming languages that have built-in compile that's changing the old ways of debugging. Your thoughts. >> Right, so, definitely, that is something that people who have a heritage in small talk or Lisp, kind of, remember those systems or, if they're very lucky, still get to use them. And the thing is that most program languages don't have that level of interactivity when you work with them as a developer because there is too much of a feedback loop between when you actually specify what you want to happen by writing code and when you actually see what actually happen when you run your code and it typically doesn't do remotely what you wanted it to. That feedback loop is too long 'cause you have to go through compiles and bills and whatever, and the idea of live programming is to shorten that so that you, ideally, instantly see you change something and you can see the output and the output gets changed accordingly and you don't have to wait and, in particular, you don't have to go and rerun your program, get to the same point where you were, especially when you're debugging, right? That's the beauty of fix and continue debugging which is sort of a small but important piece of live programming where you can basically go and change a function and, immediately, proceed with the computation. You don't have to restart, you don't have to get to where you were, recreate the state, make sure the heap is in the same thing and that just, A, it's productive, it saves time. It's just a joy to watch and play with this thing, it's much more tactile, you actually feel-- >> It's faster, too, you don't have to, all the steps involved, classic debugging, restart, do it all over again. >> It's faster and it's less error prone 'cause those steps, you make mistakes, you went through all these steps and you forgot one thing or whatever or you did something wrong and didn't notice and you chased some, you know, went on a wild goose chase trying to figure out a bug, so it really is a huge H to product, a huge help to productivity and it's just so much fun to work with these systems. >> Well, I got to get this question for you while you're here because I get this question all the time and it's common. A lot of the young kids want to program, they see the future, they know that coding is a good skill to have. What's your advice to parents out there or kids, whether they're in elementary, or high school, or college, that might have a focus on, say, you know, I'm a neuroscience major or I'm doing this but I want to learn how to code? What's your advice for how to learn how to code because I've seen, oh, learn Java, I'm like, okay-- >> God, no. >> Not really my first choice. >> Eat spinach. Do 50 push-ups. No, it's not that comfortable. >> No, no. >> Java's not my first choice for recomm-- >> It's also 50 push-ups and spinach are better for you. Java is actually possibly damaging, at an early age, you should not be doing that. >> Doing Java, in particular? >> No, no. >> Why is that, it's just too complex? >> Because it's a lot of irrelevant boiler plate. It's a lot of stuff that should've been obsolete before and will be obsolete by the time you, hopefully, get to work for real and it's painful and if you aren't really into it, it'll just turn you off of the whole field. >> What's going to get someone excited, is it Elm, is it gaming, is it some sort of-- >> Yeah, so, Elm is good because you can run it, you don't need much setup, you can run in a web browser. I'm a Smalltalker and I still love the Smalltalk systems and they're still, overall, is a complete programming experience, they're still unmatched. Except for list machines which are kind of hard to come by. And so, I'd focus on those-- >> People tend to talk about Python, they talk about some of these languages. If someone's going to tinker around, what's going to be the addictive, if someone's going to-- >> So, people get addicted to all kinds of things but I would-- >> In terms of a good-- >> I tend to avoid the mainstream. People tend to latch on to the mainstream because they think it's a good career move or whatever. My advice is, you get good, learn the fundamentals in the cleanest way possible, then the mainstream stuff will be easy, rather than focusing on it, 'cause there's so much irrelevant detail in those systems and the programming experience is not that great. So, try something a little less meaty, closure is a lisp that you can use and there's closure script as a version that runs on the web. Try Elm. Try Smalltalk. >> And all these languages, they can actually produce something of value? >> Yeah, they can definitely, I think, still 70% of the world's container traffic is still run by a Smalltalk application. >> Really, I did not know that. >> Yeah, well, few people do. In Smalltalk, you find that that sort of heyday, in some sense, for commercial applications was in the 90s or 80s, whatever, but replacing those applications, a typical story is, someone says, ah, we should use Java 'cause everybody's using Java and we can get lots of programmers and they spend a lot of money and the new application doesn't work 'cause they can't actually rebuild the thing they built in Smalltalk at any reasonable cost, at any reasonable reliability. So, there are a lot of those systems out there, Morgan Stanley's still running Capital, their Smalltalk system for managing money. So, yeah, you can certainly build things. >> Well, Gilad, I love your commentary here, so I love that you're not shy to hold back. I've got to get your thoughts on cryptocurrency and the Blockchain world. >> Oh, dear. >> A lot of different languages, you got Ethereum, you have, some say, oh, I'm going to use Linux. If you're using Java, we're going to import it in, Javascript supports it, so there's been kind of like this, every kind of crypto currency, Blockchain, has their own language for decentralized applications. Your general thoughts on this. >> So, there's a need for, to slow down and be more careful, all right. Ethereum lost God knows how much money. I've heard quotes but I don't know if it's 50 million or 150 million but a fair amount of money due to problems that were classical distributed programming problems and could have been avoided by, essentially, more careful design of language in the system. There's a pressure now to turn things out in a hurry, right? In the old days, these systems took years and years of research in their little corner and, now, everybody has to do something too fast and that hurts. And, often, it's people who don't have the expertise and the background 'cause there's lots of research on all kinds of problems and smart people get snippets of those and they don't quite know what they're doing. And I don't think there's a cure for that because the incentives are there but that's why we're seeing these problems. >> So be careful, the message is be careful. >> Be careful. >> But they're rushing, all this cash is rolling in, they got to have some language. >> Sure, as long it's not their 150 million dollars that they lost, that's fine, but someone was probably upset. >> And, by the way, the security problem was software-error based. >> Most of them are. >> So, this transitions into Shape Security where you're not working as a distinguished engineer, working on some hard problems. I know it's pretty confidential but you guys do power 200 million iOS apps, this is from the PR statement. >> Probably more by now but yeah. >> Past 24 hours, you blocked more than two billion fraudulent login attempts, two million legitimate attempts. Essentially, defending intrusion detects and seems to be the company's value properties, but I don't want to get too much into the company because you're, obviously, on the engineering side. But security from a programming language side is software and people. >> Mm-hm. >> Right, software gets bugs. >> And people make them worse. >> And people make mistakes. >> People make them worse. >> Yeah. >> This is the central process problem in security. Your thoughts in computer science. >> So, most of the time, I mean, Shape does real security and this is fascinating to me but, most of the time, I've been looking at security at the programming language level because, you know, still, I think 70% of intrusions often, not the intrusions but, basically, these big software fiasco security problems get down to array buffer overflows. Which is ridiculous 'cause this is problem that was solved decades ago. Why are we still dealing with this? That's because, you know, programming language design, the whole approach to security, access control lists, whatever, there was another approach which was capability-based. And these two grew up together in the 60 and the world, as typically, it makes the wrong choices, it takes what seems appealing in the short term and not what is sort of a more thorough thing. So, object capabilities is a really interesting way of looking at this thing. There are people working on putting some of this into Javascript so that you could use it somehow. Great work by Mark Miller and company at Agoric. I'll do a shout-out to them. So, I've usually been on that side of things, but real security, there's a lot more to it, that's just one small layer of things and, above that, there's all the humans and the multiple systems they build. The configurations, they're just mistakes, the things that happen through social engineering about which, basically, I don't know much about but I will say that making things simpler is key because that's why people make mistakes. Things are too complicated. Every piece of the system has some bunch of clever engineers who really think it through and make it really sophisticated but when you compose these, it becomes, no one understands, a thing that no one understands what's going on and we need to simplify. My work is to try to simplify at that programming language level which the typical languages people use are too complex. >> And this is really where the software always has holes in it and you just got to be on top of it and make it tight, as it were. >> Right, basically, you can't understand the consequences when you have too many moving parts, as it were, too many constructs in the programming language. The composition is endless and you can't, it's very hard to foresee how they're going to interact and what someone will come up with, eventually. Oh, you could use this to attack that. Or, this crates this bad scenario that people don't notice. And, really, there's no remedy to that. You can work and you should be careful, you should test things, you should verify, if you can, formally, but if you just try and keep it simple, clean abstractions that are very simple and composed well, you will simply avoid, by definition, most of these problems. >> Final talk track around open source. It's been well-documented that proprietary software that's funded by companies when kind of stopped and innovating, kind of, dies on the vine. Open source is great, got leverage, you get out in the open, yeah, it's great. So, open source has been growing like a weed over the past couple decades and, recently, it's been phenomenal. The open source people say, oh, security is better in open source. At the same time, you bring up the notion of language security and those programming languages. How do you see that rectifying itself? How is the security paradigm with open source going to be stabler? What do companies need to do because open source is being used everywhere. >> Open source is used everywhere for good reason but open source is not, by itself, a magic thing, right. It's still, you get problems, open source is also open to malicious contributors, to problems, and the systems are too big for, even though there are code reviews and everything, so it's a double-edged sword, in some respects and sometimes the quality just suffers. These are social organization and each one is different and they have problems, so I don't know that that is, it's good that you shine light on something, it tends to purify it, and certainly that's a great strength of open source that you cant have things buried in there that you don't know. By the same token, it is not a panacea because the other thing is someone has to fund this somehow. All the open source models have to find somewhere to keep this going. So it's a more complicated thing to pull off. >> Especially with all these appliances now, okay, which version of Linux are you running, do I review the code? How do people ensure the security know that whether it's an appliance, or a device, or phone, or anything and it doesn't have some sort of back door or security vulnerability? >> Well, backdoor, I don't-- >> Backdoor, side door. >> Or just code-- >> This is a conspiracy theory. >> Or poor code. >> Poor code, well, poor code, you know, the open source is full of poor code is the truth. And the other thing is that, one problem with the open source is it also makes it easier for people to attack it because they can see how it's engineered. So, there is a reason that secure systems tend to, actually, maintain a certain level of secrecy. So I wouldn't go overboard on the open source ideology that it's inherently more secure. It has the advantage that you can see what you're getting. It has the disadvantage that everyone, including your adversaries, can see that. >> You don't know that going in, buyer beware kind of philosophy. >> Yes. >> And so, ultimately, you need to trust, like, it always comes down to trust at some level 'cause there's no way you're going to verify the software or the hardware, the bits, the you know. You can have problems in the hardware, this is a big problem nowadays, actually, with certain vendors. I don't want to get into those political footballs but-- >> Yeah, super micro. >> Yeah, and so, you really have to see who, you do have to take a risk in who do you trust. Who has a reputation, who is responsible for things that have worked? And there are no easy answers and it's beyond my pay grade. >> Let me get your thoughts on Capital One because we know that story, as of this week and they're on an Amazon estuary bucket, firewall filtering failed, someone just stumbled into it. I mean, the person that hacked it wasn't like, probably, a famous hacker, she was bragging on Twitter and message groups like, saying, hey, I just got in. So, door's open, keys are running in the car, walked right to the safe, safe was open. >> So, I don't know anything about that incident specifically and, I mean, beyond what you and I have read on the web or somewhere-- >> That's a human error. >> But they're usually there's always, almost always human error involved. It's also why you need, sort of, it's like countermeasures, right, and counter, counter, countermeasures. You simply have to monitor, right? So that when something, when you have an intrusion, you check it, now, that's not easy but there are lots of clever things that people are doing. You can have security as an afterthought. It's really hard. That's generally the problem is that people don't think about it early enough. >> Final question before we break: What's the human problem that you see most with developers? 'Cause if humans make mistakes, which they do, what's the common mistake developers, programmers make when coding that could be avoided with just a little bit sharper focus? >> Well, it's not about focus but I'd say null pointer exceptions are the biggest, like, after array buffers, they're the other, Tony Hoare called it billion dollar mistake in 1980 in his award speech, I think. And we're talking now, it's probably a trillion dollars, right? And this is something that can be mechanically checked by the programming language and it's probably the number bang-for-a-buck feature that you might throw in. >> Just say no to null? >> Yeah. >> That's the philosophy. >> Yeah. >> Gilad, thanks for coming on the Cube, appreciate the conversation. >> Thank you very much. >> I'm John Furrier, here in Palo Alto at the Cube Studios. This has been a Cube Conversation, thanks for watching. (upbeat music)

>> Live from Barcelona, Spain, it's theCUBE! Covering KubeCon and CloudNativeCon Europe 2019. Brought to you by Red Hat, the Cloud Native Computing Foundation, and ecosystem partners. >> Welcome back. This is theCUBE's live coverage of KubeCon, CloudNativeCon 2019 here in Barcelona, Spain. 7,700 here in attendance, here about all the Cloud Native technologies. I'm Stu Miniman; my cohost to the two days of coverage is Corey Quinn. And to help us break down what's happening in this ecosystem, we've brought in Jason Bloomberg, who's the president at Intellyx. Jason, thanks so much for joining us. >> It's great to be here. >> All right. There's probably some things in the keynote I want to talk about, but I also want to get your general impression of the show and beyond the show, just the ecosystem here. Brian Liles came out this morning. He did not sing or rap for us this morning like he did yesterday. He did remind us that the dinners in Barcelona meant that people were a little late coming in here because, even once you've got through all of your rounds of tapas and everything like that, getting that final check might take a little while. They did eventually filter in, though. Always a fun city here in Barcelona. I found some interesting pieces. Always love some customer studies. Conde Nast talking about what they've done with their digital imprint. CERN, who we're going to have on this program. As a science lover, you want to geek out as to how they're finding the Higgs boson and how things like Kubernetes are helping them there. And digging into things like storage, which I worked at a storage company for 10 years. So, understanding that storage is hard. Well, yeah. When containers came out, I was like, "Oh, god, we just fixed it for virtualization, "and it took us a decade. "How are we going to do it this time?" And they actually quoted a crowd chat that we had in our community. Tim Hawken, of course one of the first Kubernetes guys, was in on that. And we're going to have Tim on this afternoon, too. So, just to set a little context there. Jason, what's your impressions of the show? Anything that has changed in your mind from when you came in here to today? Let's get into it from there. >> Well, this is my second KubeCon. The first one I went to was in Seattle in December. What's interesting from a big picture is really how quickly and broadly KubeCon has been adopted in the enterprise. It's still, in the broader scheme of things, relatively new, but it's really taking its place as the only container orchestrator anybody cares about. It sort of squashed the 20-or-so alternative container orchestrators that had a brief day in the sun. And furthermore, large enterprises are rapidly adopting it. It's remarkable how many of them have adopted it and how broadly, how large the deployment. The Conde Nast example was one. But there are quite a number. So we turned the corner, even though it's relatively immature technology. That's the interesting story as well, that there's still pieces missing. It's sort of like flying an airplane while you're still assembling it, which makes it that much more exciting. >> Yeah, one of the things that has excited me over the last 10 years in tech is how fast it takes me to go from ideation to production, has been shrinking. Big data was: "Let's take the thing that used to take five years "and get it down to 18 months." We all remember ERP deployments and how much money and people you need to throw at that. >> It still takes a lot of money and people. >> Right, because it's ERP. I was talking to one of the booths here, and they were doing an informal poll of, "How many of you are going to have Kubernetes "in production in the next six months?" Not testing it, but in production in the next six months, and it was more than half of the people were going to be ramping it up in that kind of environment. Anything architecturally? What's intriguing you? What's the area that you're digging down to? We know that we are not fully mature, and even though we're in production and huge growth, there's still plenty of work to do. >> An interesting thing about the audience here is it's primarily infrastructure engineers. And the show is aimed at the infrastructure engineers, so it's technical. It's focused on people who code for a living at the infrastructure level, not at the application level. So you have that overall context, and what you end up having, then, is a lot of discussions about the various components. "Here's how we do storage." "Here's how we do this, here's how we do that." And it's all these pieces that people now have to assemble, as opposed to thinking of it overall, from the broader context, which is where I like writing about, in terms of the bigger picture. So the bigger picture is really that Cloud Native, broadly speaking, is a new architectural paradigm. It's more than just an architectural trend. It's set of trends that really change the way we think about architecture. >> One interesting piece about Kubernetes, as well. One of the things we're seeing as we see Kubernetes start to expand out is, unlike serverless, it doesn't necessarily require the same level of, oh, just take everything you've done and spend 18 months rewriting it from scratch, and then it works in this new paradigm in a better way. It's much less of a painful conversion process. We saw in the keynote today that they took WebLogic, of all things, and dropped that into Kubernetes. If you can do it with something as challenging, in some respects, and as monolithic as WebLogic, then almost any other stack you're going to see winds up making some sense. >> Right, you mentioned serverless in contrast with Kubernetes, but actually, serverless is part of this Cloud Native paradigm as well. So it's broader than Kubernetes, although Kubernetes has established itself as the container orchestration platform of choice. But it's really an overall story about how we can leverage the best practices we've learned from cloud computing across the entire enterprise IT landscape, both in the cloud and on premises. And Kubernetes is driving this in large part, but it's bigger picture than the technology itself. That's what's so interesting, because it's so transformative, but people here are thinking about trees, not the forest. >> It's an interesting thing you say there, and I'm curious if you can help our community, Because they look at this, and they're like, "Kubernetes, Kubernetes, Kubernetes." Well, a bunch of the things sit on Kubernetes. As they've tried to say, it's a platform of platforms. It's not the piece. Many of the things can be with Kubernetes but don't have to be. So, the whole observability piece. We heard the merging of the OpenCensus, OpenTracing with OpenTelemetry. You don't have to have Kubernetes for that to be a piece of it. It can be serverless underneath it. It can be all these other pieces. Cloud Native architecture sits on top of it. So when you say Cloud Native architecture, what defines that? What are the pieces? How do I have to do it? Is it just, I have to have meditated properly and had a certain sense of being? What do we have to do to be Cloud Native? >> Well, an interesting way of looking at it is: What we have subtracted from the equation, so what is intentionally missing. Cloud Native is stateless, it is codeless, and it is trustless. Now, not to say that we don't have ways of dealing with state, and of course there's still plenty of code, and we still need trust. But those are architectural principals that really percolate through everything we do. So containers are inherently stateless; they're ephemeral. Kubernetes deals with ephemeral resources that come and go as needed. This is key part of how we achieve the scale we're looking for. So now we have to deal with state in a stateless environment, and we need to do that in a codeless way. By codeless, I mean declarative. Instead of saying, how are we going to do something? Let's write code for that, we're going to say, how are we going to do that? Let's write a configuration file, a YAML file, or some other declarative representation of what we want to do. And Kubernetes is driven this way. It's driven by configuration, which means that you don't need to fork it. You don't need to go in and monkey with the insides to do something with it. It's essentially configurable and extensible, as opposed to customizable. This is a new way of thinking about how to leverage open-source infrastructure software. In the past, it was open-source. Let's go in an monkey with the code, because that's one of the benefits of open-source. Nobody wants to do that now, because it's declaratively-driven, and it's configurable. >> Okay, I hear what you're saying, and I like what you're saying. But one of the things that people say here is everyone's a little bit different, and it is not one solution. There's lots of different paths, and that's what's causing a little bit of confusion as to which service mesh, or do I have a couple of pieces that overlap. And every deployment that I see of this is slightly different, so how do I have my cake and eat it, too? >> Well, you mentioned that Kubernetes is a platform of platforms, and there's little discussion of what we're actually doing with the Kubernetes here at the show. Occasionally, there's some talk about AI, and there's some talk about a few other things, but it's really up to the users of Kubernetes, who are now the development teams in the enterprises, to figure out what they want to do with it and, as such, figure out what capabilities they require. Depending upon what applications you're running and the business use cases, you may need certain things more than others. Because AI is very different from websites, it's very different from other things you might be running. So that's part of the benefit of a platform of platforms, is it's inherently configurable. You can pick and choose the capabilities you want without having to go into Kubernetes and fork it. We don't want 12 different Kubernetes that are incompatible with each other, but we're perfectly okay with different flavors that are all based on the same, fundamental, identical code base. >> We take a look at this entire conference, and it really comes across as, yes, it's KubeCon and CloudNativeCon. We look at the, I think, 36 projects that are now being managed by this. But if we look at the conversations of what's happening here, it's very clear that the focus of this show is Kubernetes and friends, where it tends to be taking the limelight of a lot of this. One of the challenges you start seeing as soon as you start moving up the stack, out through the rest of the stack, rather, and seeing what all of these Cloud Native technologies are is, increasingly, they're starting to be defined by what they aren't. I mean, you have the old saw of, serverless runs on servers, and other incredibly unhelpful sentiments. And we talk about what things aren't more so than we do what they are. And what about capabilities story? I don't have an answer for this. I think it's one of those areas where language is hard, and defining what these things are is incredibly difficult. But I see what you're saying. We absolutely are seeing a transformative moment. And one of the strangest things about it, to me at least, is the enthusiasm with which we're seeing large enterprises, that you don't generally think of as being particularly agile or fast-moving, are demonstrating otherwise. They're diving into this in fascinating ways. It's really been enlightening to have conversations for the last couple of days with companies that are embracing this new paradigm. >> Right. Well, in our perspective at Intellyx, we're focusing on digital transformation in the enterprise, which really means putting the customer first and having a customer-driven transformation of IT, as well as the organization itself. And it's hard to think in those terms, in customer-facing terms, when you're only talking about IT infrastructure. Be that as it may, it's still all customer-driven. And this is sometimes the missing piece, is how do we connect what we're doing on the infrastructure side with what customers require from these companies that are implementing it? Often, that missing piece centers on the workload. Because, from the infrastructure perspective, we have a notion of a workload, and we want workload portability. And portability is one of the key benefits of Kubernetes. It gives us a lot of flexibility in terms of scalability and deployment options, as well as resilience and other benefits. But the workload also represents the applications we're putting in front of our end users, whether they're employees or end customers. So that's they key piece that is like the keystone that ties the digital story, that is the customer-facing, technology-driven, technology-empowered story, with the IT infrastructure stories. How do we support the flexibility, scalability, resilience of the workloads that the business needs to meet its business goals? >> Yeah, I'm really glad you brought up that digital transformation piece, because I have two questions, and I want to make sure I'm allowing you to cover both of them. One is, the outcome we from people as well: "I need to be faster, and I need to be agile." But at the same point, which pieces should I, as an enterprise, really need to manage? Many of these pieces, shouldn't I just be able to consume it as a managed service? Because I don't need to worry about all of those pieces. The Google presentation this morning about storage was: You have two options. Path one is: we'll take care of all of that for you. Path two is: here's the level of turtles that you're going to go all the way down, and we all know how complicated storage is, and it's got to work. If I lose my state, if I lose my pieces there, I'm probably out of business or at least in really big trouble. The second piece on that, you talked about the application. And digital transformation. Speed's great and everything, but we've said at Wikibon that the thing that will differentiate the traditional companies and the digitally transformed is data will drive your business. You will have data, it will add value of business, and I don't feel that story has come out yet. Do you see that as the end result from this? And apologies for having two big, complex questions here for you. >> Well, data are core to the digital transformation story, and it's also an essential part of the Kubernetes story. Although, from the infrastructure perspective, we're really thinking more about compute than about data. But of course, everything boils down to the data. That is definitely always a key part of the story. And you're talking about the different options. You could run it yourself or run it as a managed service. This is a key part of the story as well, is that it's not about making a single choice. It's about having options, and this is part of the modern cloud storage. It's not just about, "Okay, we'll put everything in one public cloud." It's about having multiple public clouds, private clouds, on-premises virtualization, as well as legacy environments. This is what you call hybrid IT. Having an abstracted collection of environments that supports workload portability in order to meet the business needs for the infrastructure. And that workload portability, in the context of multiple clouds, that is becoming increasingly dependent on Kubernetes as an essential element of the infrastructure. So Kubernetes is not the be-all and end-all, but it's become an essentially necessary part of the infrastructure, to make this whole vision of hybrid IT and digital transformation work. >> For now. I mean, I maintain that, five years from now, no one is going to care about Kubernetes. And there's two ways that goes. Either it dries up, blows away, and something else replaces it, which I don't find likely, or, more likely, it slips beneath the surface of awareness for most people. >> I would agree, yeah. >> The same way that we're not sitting here, having an in-depth conversation about which distribution of Linux, or what Linux kernel or virtual memory manager we're working with. That stuff has all slipped under the surface, to the point where there are people who care tremendously about this, but you don't need to employ them at every company. And most companies don't even have to think about it. I think Kubernetes is heading that direction. >> Yeah, it looks like it. Obviously, things continue to evolve. Yeah, Linux is a good example. TCP/IP as well. I remember the network protocol wars of the early 90s, before the web came along, and it was, "Are we going to use Banyan VINES, "are we going to use NetWare?" Remember NetWare? "Or are we going to use TCP/IP or Token Ring?" Yeah! >> Thank you. >> We could use GDP, but I don't get it. >> Come on, KOBOL's coming back, we're going to bring back Token Ring, too. >> KOBOL never went away. Token Ring, though, it's long gone. >> I am disappointed in Corey, here, for not asking the question about portability. The concern we have, as you say: okay, I put Kubernetes in here because I want portability. Do I end up with least-common-denominator cloud? I'm making a decision that I'm not going to go deep on some of the pieces, because nice as the IPI lets things through, but we understand if I need to work across multiple environments, I'm usually making a trade-off there. What do you hear from customers? Are they aware that they're doing this? Is this a challenge for people, not getting the full benefit out of whichever primary or whichever clouds they are using? >> Well, portability is not just one thing. It's actually a set of capabilities, depending upon what you are trying to accomplish. So for instance, you may want to simply support backing up your workload, so you want to be able to move it from here to there, to back it up. Or you may want to leverage different public clouds, because different public clouds have different strengths. There may be some portability there. Or you may be doing cloud migration, where you're trying to move from on-premises to cloud, so it's kind of a one-time portability. So there could be a number of reasons why portability is important, and that could impact what it means to you, to move something from here to there. And why, how often you're going to do it, how important it is, whether it's a one-to-many kind of thing, or it's a one-to-one kind of thing. It really depends on what you're trying to accomplish. >> Jason, last thing real quick. What research do you see coming out of this? What follow-up? What should people be looking for from Intellyx in this space in the near future? >> Well, we continue to focus on hybrid IT, which include Kubernetes, as well as some of the interesting trends. One of the interesting stories is how Kubernetes is increasingly being deployed on the edge. And there's a very interesting story there with edge computing, because the telcos are, in large part, driving that, because of their 5G roll-outs. So we have this interesting confluence of disruptive trends. We have 5G, we have edge computing, we have Kubernetes, and it's also a key use case for OpenStack, as well. So it's like all of these interesting trends are converging to meet a new class of challenges. And AI is part of that story as well, because we want to run AI at the edge, as well. That's the sort of thing we do at Intellyx, is try to take multiple disruptive trends and show the big picture overall. And for my articles for SiliconANGLE, that's what I'm doing as well, so stay tuned for those. >> All right. Jason Bloomberg, thank you for helping us break down what we're doing in this environment. And as you said, actually, some people said OpenStack is dead. Look, it's alive and well in the Telco space and actually merging into a lot of these environments. Nothing ever dies in IT, and theCUBE always keeps rolling throughout all the shows. For Corey Quinn, I'm Stu Miniman. We have a full-packed day of interviews here, so be sure to stay with us. And thank you for watching theCUBE. (upbeat techno music)

>> Narrator: Live. From Atlanta Georgia. It's theCUBE. Covering, Citrix Synergy, Atlanta 2019. Brought to you by Citrix. >> Hey, Welcome back to theCUBE. Lisa Martin with Keith Townsend and we're comin' to you Live from Atlanta, Georgia. The Showfloor from Citrix Synergy 2019. We're excited to welcome to theCUBE for the first time Simon Bray. Principle and Head of Leadership and Culture at Vega Factor. Simon, welcome to theCUBE. >> Thanks very much. Great to be here. >> So, I was doing some stalkin' of you online as I do for every guest. >> Simon: Thank you. >> Yup. And I read you're a culture Agent based in New York City. >> Simon: Yes. >> Then you come on set and I'm like , you're not originally from New York City. >> Simon: That is correct. >> You're a transplant and you hail from Brooklyn. >> Simon: Yes, I do. >> Which is where my mom Cathy Dally is from. >> Simon: Very nice, very nice. >> She will love you automatically because you live in Brooklyn. >> Keith: (laughter) >> I consider myself to be a New Yorker. I moved to New York in early 2006. So 14 years, and I think I can make that claim. Although, I am originally form London. >> I would say so. Although your accent is still identifiable. >> Simon: I keep-- I try to keep the accent. >> I mistaked it for a Texas accent, so that's--. >> Texas? >> Yeah. >> Yeah, yeah. >> Got confused? Oh there you go. >> I get that a lot. >> I bet. Yeah. Well, regardless of that you're a Culture Agent. >> Simon: Yes. >> What is that? >> Simon: Okay. >> Because we talk about Cultural Transformation and Corporate Cultures and how employee experience is essential. But Culture Agent, I just thought that was very interesting. >> Yes, so my job is to help organizations create great cultures. Essentially, our theory at Vega Factor is that to create a great culture-- First of all you need to make sure that you build an adaptive organization. So one that is able to change, is able to flex is able to innovate. So that's kind of part one. So my role is really to help organizations become more adaptive. The way that I do that is by trying to -- create an operating model in an organization that is highly motivating. We've developed a way of measuring motivation. We call it TOMO. Where, essentially you look at trying to create a system which drives up the Play, Purpose and Potential the individuals feel. Play is enjoying the work. Purpose is when people feel like they're makin' a difference. And Potential, is when people feel like they're developing and growing. And minimizing the emotional pressure, economic pressure and inertia people feel. So were tyin' to design an operating model that drives that up in order to help people become more adaptive. So my work is to work with leaders and organizations all over the place to help them apply the science of that approach to become more adaptive. >> Lisa: That's awesome. So I've heard of FOMO. >> Okay. >> Fear of missing out. Which I imagine -- everybody that's not here at Citrix Synergy has FOMO. >> Well, of course. It's incredible. >> I know JOMO, I don't have that right now goin' on. >> (giggles). >> TOMO. >> Yes. >> Total, motivation? >> Total motivation. Yeah, so we were asking ourselves the question how do you get people to turn up and do their best work? You know, how do you get people to be motivated not just to do what it says on their job description. To actually lean into their role. To be constantly thinking about how to improve it. About how to innovate, about to problem solve. About how to collaborate. When times are tough. And really what it boiled down to is really simple insight. Which is why we work, determines how well we work. So we started lookin' at the psychology behind motivation. That's where we developed this frame work we call TOMO or total motivation. Which is where we're lookin' at trying to get people to turn up and be excited for themselves. Versus doing things because they're being pressured to do it by external forces. >> Keith: So a lot-- a lot of great conversation on stage this mornin' talking about employee experience, employee's not getting disenfranchised or feelin' unmotivated about their jobs. What are some of the largest factors you see, did what Citrix shared this morning correlate with what you're seeing when you're talkin' to clients? >> Simon: 100%, Yeah. I think what was interesting this morning was the focus on not just the technology but the peoples side of things. And making sure that there's a close partnership between people and technology. And really seeing that through the lens of the overall employee experience. The way that we see the employee experience is everything that affects somebody's motivation in an organization is part of the employee experience. So, everything from the way that you frame up your purpose and identity as an organization. To the way that you organize yourselves and design roles and teams. To the way that you work together as a team. To the way that you set up governance, planning, the talent and performance systems. All of these things can be designed poorly. And therefore create disengagement and lack of motivation. They can also be designed really well. To drive that play, purpose and potential that I talked about earlier on. And as I said before, our work is all about helping organizations design the system within which people work to maximize TOMO. And that's our answer to some of the issues that were raised this morning about employees being disengaged. Our view is that that's just not good enough. You need to make sure that you're really focusing on how to make sure that people turn up and do their best work. And then the technology side of it is making sure that they're equipped with the tools, of course, that they need to do that. >> So, where do you start when organizations come to you in the Vega Factor and say, Hey guys, whether it's a younger organization that I would think on one hand might have an advantage being younger, maybe less kind of cultural biases built in. Versus an organization that might be a competitor with Citrix. Who's been around for decades and has a very, probably I don't want to say static culture. But probably a lot of cultural elements really locked in. What's the starting point? For that fresher organization versus a legacy organization? Are there any overlaps with where you guys recommend, all right this where we got to go. >> Yeah, I think the same overall framework applies. But just in a slightly different way. So, the way we start our conversations often is by defining performance as being, having two parts. The first part of performance is tactical performance. Which is all about strategy, planning and execution. And doing that as efficiently as possible. So tactical performance is really important. And then there's also the adaptive performance. Adaptive performance is how effectively can you diverge from the plan. Reacting to context changes, innovating, problem solving, solving issues. And those two types of performance are both important but they're opposing. So if you have too much tactical performance, you end up being very rigid. And it kills your ability to be adaptive. If you have too much adaptive performance you end up reinventing things all of the time and having no tactical performance and being a bit chaotic. I share that because when we look at two different types of company. Call it a legacy organization and a high growth start up. We often find that that high growth start ups have too much adaptive performance and that eats their ability to be tactical performance. People go crazy, because they're reinventing themselves all the time. And they haven't got the processes and systems so a lot of times with those organizations it's all about getting clear, on some of the basics. What are the guard rails within which we operate. What is our purpose, and identity? How do we want to organize? So that's all about helping a highly adaptive organization improve their tactical performance. Then the other side of it is a legacy organization. You know, think of any big mega organization. Where, actually as they've grown they've shifted from being really adaptive into being really tactical. They put in place processes and policies and structures, to help them manage their scale. The issue is, is that in doing that they can often lose their ability to be adaptive, By becoming bureaucratic. So, with those organizations a lot of our work is how can you, without losing that tactical performance create the space, and autonomy for teams to be able to be adaptive at the same time? So that's kind of where we come. Same framework, but actually a start point that's really quite different. >> So, let's talk about scale. Small organizations, start ups, I can see how that approach can be very deliberate. You can, spend a percentage of your time building culture. Let's talk about the big battle ships. When your goin' into a large organization. How does a large organization where it's very difficult to impact change and culture change. How do large organization's tackle this challenge? >> That's a great question. You're right, it is much harder to work within a big organization to affect change. I think the way that we would typically approach it is first of all, not to try to change a big organization at the same time. You know, it's hard to change the behavior of a thousands of people quickly. And so what we try to do is to start by taking a small part of the organization. To actually, show using that organization what good looks like. To, and then build from that. So, show the rest of the organization how this can work, how you can manage both tactical and adaptive performance. How you can create a high TOMO way of working. Then we find, that people gradually follow on from there. What's really important about that is, one you're not trying to boil the ocean. But secondly, you're showing people what good looks like and you're giving them the opportunity to opt in. And I found that when people opt into change and they start pulling for it that's a much better way to affect change versus operate in a situation where change is something that's done to people. Where people are told what to do. >> Lisa: It's being pushed on them. >> Yeah exactly. >> Lisa: Right, naturally, you're going to get resistance there. >> Yeah. For sure. >> Some of the stats that we heard this morning and Keith and I are both living this. I think I heard, maybe it was within the last week that by 2020, which is literally around the corner that 50% of the work force is going to be remote. >> Simon: Yeah. >> And I think they were saying this morning that in the next few years there's going to be 65 billion connected devices. With each person having about eight different connected devices. Keith and I are here with out different devices. Where do you see, the necessity of delivering mobile experiences. But also, for cultural impact for businesses, small or large to enable workers to be remote and give them access? Rather than forcing that they sit on a train for an hour, or in the car, and be in the office. Where is that conversation in the Vega platform? >> Yeah, it's an interesting one. So, one of the things that we spend quite a lot of time doing, is working with individual teams to help them operate more as a team. One of the things I found quite surprising in my work with different types of organizations is that often teams are connected by a common manager, but essentially are a collection of individual contributors who aren't actually working on shared issues. So, one of the first things that we like to do is to help teams re-orient themselves around the shared purpose. And, set themselves challenges for things that they want to solve together to improve their collective performance. So that's a foundational piece. Once we've done that, then the next question becomes, to answer your question, how do you get teams to problem solve together effectively. And there's two different times when teams problem solve. One is what we would call synchronously. Synchronicity is where teams need to get together physically, and actually brain storm and kick around a problem. And there is a time and a place to do that. That's why its still important to have get-togethers and to create that human connection. But actually more and more we find that teams need to also be able to solve problems in parallel asynchronously. And I think that's where technology comes in. Technology allows teams to work together on problems but not all be in the same place at the same time. To be able to do that in parallel and whenever they want to. It's when you get that asynchronous problem solving and synchronous problem solving that you can get teams to generally work together and that way we find people perform at a much higher level than if they're essentially just focusing on the job that they have. >> So obviously, you work across industries, groups and type of functions. Can you share with us some correlation between TOMO, the rise in kind of this-- employee experience measure and performance? Like, what are some of the key indicators that culture is improving performance? >> That's a great question as well. So, one of the things that we spend a lot of time doing in our early research is trying to quantify culture. Because you know, most of us would agree that culture is important but it becomes something that can easily get shunted down the list. Or seen as a nice to have (mumbles) especially if times are tough. So we spend a lot of time trying to measure culture and then to be able to to show a correlation between that measure and the performance of a business. So, the first thing that we did is say well how do you measure culture? And our way of measuring culture is the degree to which people are motivated. So this comes back to TOMO. The way that we calculate TOMO is by adding up the play, purpose and potential that somebody feels. And subtracting the emotional pressure, economic pressure and inertia they feel. And these are weighted according to their proximity to the work. And they end up giving us a nice neat score between minus 100 and positive 100. Like a net promoters score. We get that number by asking them six multiple choice questions. So it's two or three minutes. That gives us an individual score but also of course, we can measure that organizationally. We then looked at the correlation between that score and the performances of business across a range of different industries. And we show a straight line correlation between TOMO and business performance. So as an example, we looked at the airline industry. And we looked at the TOMO of most of the U.S airlines. And we found that the highest TOMO airline -- Can you guess what the highest TOMO airline is? >> Lisa: JetBlue? Southwest? >> Southwest. >> Keith: I was going to say SouthWest. >> JetBlue is second. So we found that when you walk on a Southwest or JetBlue airplane you feel great. It feels different. Because the employees, the flight crew, turn up in a different way. That's because their TOMO is higher. And as a result the performance of Southwest particularly around elements like Customer Experience, Customer Satisfaction is significantly higher than the rest. The lowest TOMO airline in our data set is United. Now-- >> Lisa: I was going to guess that. >> Keith: (laughter) >> Now, if you think of TOMO low TOMO tends to be when people either have low play, purpose and potential. They're not enjoying their job they don't feel like their makin' a difference or they're not learning. Or the system they're in is very high pressured. High emotional pressure, economic pressure. That creates a lower business performance. It can also have a negative effects from a behavioral point of view. As an example, if you saw the story a couple of years ago where United had a big scandal where someone was pulled, man-handled off one of their planes. That's a predictable affect of low TOMO. Our data, our research was done two years before that happened. And we would've been able to predict that United would have issues based upon their low TOMO score. To try to explain, and I wasn't there of course. But to try to explain what happened through the lens of TOMO. If you create a very high pressure system where the ground staff, are being essentially measured on their ability to get the plane to take off on time. When a passenger sits, and refuses to move, because of the pressure the ground crew are under they forget what the right thing to do is. Because of their low TOMO and pressure they ended up man-handling the passenger off. United lost a billion dollars in their share price. And that's a predictable, what we call a cobra affects. Which, is where people kind of feel like they have to cheat or short cut the system, that we are predicting is a result of low TOMO. >> So, we're almost out of time here but I'm so curious, how do you -- what the incentives are, for United airlines to really look at that kind of experience that goes viral on social media and these things happen, I don't want to say all the time. But that was not an isolated incident. >> Simon: Absolutely not. >> So for a company like that that's making money hand over fist flights are always sold out. They're not hurting for business. What incentivizes a business like that to flip that TOMO scale? >> Yeah, it's a great question. I think it's really difficult to make any kind of change happen when you're doing okay. First of all. And that's difficult. But the reality is is that, if you had measured the TOMO of United, and there are many other examples I am not just trying to pick on them. You would've been able to guess that this would happen. And so, our advise to organizations is regardless of how successful you are regardless of how well your business results are in the short term. You need to be thinking long term about culture. You need to be thinking about what is the operating system that you're putting your employees into. And getting ahead of what could be consequences that happen down the stream as a result of well intended moves that you make now to improve your tactical performance. >> Awesome, Simon. This has been so interesting. I learned a new acronym >> Together: TOMO. >> It's some great stuff. >> Lisa: I want to have TOMO everyday, and I'm going to really work on that. Being on theCUBE it's not hard to achieve that. >> Simon: This is great. >> Well Simon, we, Keith and I so appreciate you comin' by and sharing what you guys are doin' at Vega. And really, really interesting. TOMO. >> Thank you very much. Thanks guys. >> Lisa: Our pleasure. For Keith Townsend, I am Lisa Martin. You're watching theCUBE Live on the show floor of Citrix Synergy 2019, from Atlanta Georgia. Thanks for watching.

>> Live from San Francisco, it's theCUBE. Covering Google Cloud Next 19. Brought to you by Google Cloud and its eco system partners. >> Hello everyone welcome back here to theCUBE live coverage here in San Francisco, California. We're in the Moscone Center on the ground floor here. Day three of three days of coverage for Google Cloud Next 2019. I'm John Furrier, my co-host, Dave Vellante, Stew Miniman out there getting stories out there He's also been hosting. Dave, great to see you! Evren, Director of Product Management at Google Cloud, doing all the data streaming the data. We're streaming data right now. >> Absolutely, this is it. This is it. >> So let's stream some data. So streaming data has certainly been around for awhile. Dave and I when we first started theCUBE ten years ago, it was part of Silk and Angle Media hadoop was just a small little project. That really kind of was the catalyst moment for around big data that's now evolved to it's own position. Now you have streaming data, you have cloud scale, the Cloud has really changed the game on big data. Changed the nature and dynamics of it and one of the things is streaming data, streaming analytics as a core value proposition for enterprises, and this is fairly new. >> Very true. >> What's your take on it and how does it relate to what's going on with Google Cloud? >> I am glad we're talking about that. This is an exciting time for us. Streaming like you said is growing. Batch is not going away, but streaming is actually overtaking a lot of the applications that we're seeing. Today we're seeing more streaming applications taking place than batch. One of the things that we're seeing is everybody is gathering data from all over the place from your websites, from your mobile phones, from your IoT devices, just like we're doing right now. There's data coming in and people want to make decisions real time whether it's in the banking industry, in your healthcare, retail, it doesn't matter which word cycle you're working with and we're seeing how those messages how those events are coming in and where the decisions are being made real time, milliseconds we're talking about. >> Why is it happening, what's the real catalyst here? Just tsunami of data, nature of the value, all of the above, what's the? >> We believe one of the things is like you mentioned Cloud really changed the game. Where people actually can reach globally data and messages at scale. We're talking about billions of messages coming in and processing capacity is available now we can actually process it and make a decision within milliseconds and get to the results. To me, that was the biggest catalyst. And we're seeing many of us have grown up using batch data, making decisions now everybody is talking about M.L. and A.I. You need that data coming in real time and we can actual process it and make the decision. To me, that's the catalyst. >> First of all we love streaming data, this topic. One we believe streaming where shooting video but data, real time, has been one of the keys you see self driving cars monging of data, mixing and matching of data to get better signal and better machine learning and I got to ask you, because batch is certainly the role for batch is kind of old school it's some old techniques it's been around for awhile, >> It's not going to go away though. >> It's not going to go away it's established it's place but the knee jerk reaction of existing old school people who haven't migrated to the new modern version they go to the batch kind of mind set. I want to get you're reaction. Data lakes, there's nothing flowing in a lake. Okay, so there is a role for a data lake streaming gives me the impression of like an ocean or a river or something moving fast. Talk about the differences because it's not just the data lake okay that's a batch kind of reaction. >> It is a complementary. Actually it's not going away because all of that data that we had in the back is something we're relying on to really augment and see what's changing. So if you're in a retail house you're buying something, you're going to make a decision and your support is actually behind it. OK here's Evren, he's actually shopping around this and he wants this for his son. That's what the models built around it is looking at what is my behavior and in the moment making a decision for me. So that's not going away. The other thing is batch users are able to take advantage of the technology today. If you look at our data flow, same set of codes, same set of capability can be used by the same folks that are used to batch. You don't have to change anything so that actually we help folks to be up skilled using the same set of tools and become much more experienced and experts in the streaming too. That's not going away we help both of the worlds. >> So, complementary. >> Very complementary. >> So data lakes are good for kind of setting the table if you have to store it somewhere but that's not the end game though. >> No. >> Okay. >> I wonder if we could talk about the evolution from batch to real time streaming. And my favorite example, because I think people can relate to it, is fraud detection. Ten years ago, it was up to the user to go through his or her bill, right? And then you started to get inundated with false positives, and now lately, last couple of years it's getting better and better. Fewer false positives, usually when you usually no news is good news. News is usually bad news now, so take that example and use that to describe how things have evolved. >> I am a student of AI I did my Master's and PhD in that and I went through that change in my career because we had to collect the data, batch it and analyze it, and actually make a decision about it and we had a lot of false positives and in some cases some negative misses too which you don't want that either. And what happened is our modeling capabilities became much better. With this rich data, and you actually tap into that data lake, you can go in there the data is there, and this is spread data we can pull in data from different sources and actually remove the outliers and make our decision real time right there. We didn't have the processing capability we didn't have a place like PostUp where globic can scan and bring in data at hundreds of gigabytes of data. That's messaging you want to deal with at scale no matter where it is and process that, that wasn't available for us. Now it's available it's like a candy shelf for technologists, all the technology is in our hands and we wanted all these things. >> You were talking about I think the simplicity of, I'm able to use my batch processes and apply them. One of the complaints I hear from developers sometimes is that the data pipeline is getting so complicated. You were talking about you're grabbing stuff from websites, from financial databases, and so depending on what data store you're using and what streaming tools you're using or other A.I. tools, the pipeline gets very complicated the A.P.Is start to get complicated but I'm hearing a story of simplicity. Can you elaborate on that and add some color? >> Yeah I'm glad you're asking that question you may have heard, yesterday we announced a whole bunch of new things and ease of use is the top of the line for us. Really are trying to make it easy. If you look at this eco pipeline we're building with data flow, it helps you end to end. Data engineered no matter which angle their coming in should be able to use their known skill sets and be able to build their pipelines end to end so that you can achieve your goals around streaming. We aren't really having to go through a lot of the clusters of the pipelines we are going to continue to push that ease of use over and over, we're not going to let it go because make it easier, everyone will adapt it faster. >> You mentioned you got a PhD in A.I., Master's in A.I., A.I. has been around for awhile. A lot of people have been saying that but machine learning certainly has changed the game. Machine learning plus cloud has been a real accelerant in the academic and now commercial aspects of A.I. So I want to get your thoughts on the notion of scale which you talk about, plus the diversity of data. So if you can bring in data at scale get more signaling points more access to data signaling the diversity of data becomes very key. But cleanliness, data cleaning, used to be an old practice of you get a bunch of data, stack it up, put it in a pile corpus, and you kind of go clean it. With streaming, if it's always flowing there's kind of a behavioral characteristic of data cleanliness, data monitoring, talk about that diversity of data clean data and how that feeds machine learning and makes better A.I. >> Good one, so that's where we actually are able to, if you look at PostUp, you're building joint your table set of datas with streaming set of datas you can actually put it into data filter it and make those analyses. And within both, we provide enough of a window for you to be able to go back, hey are there things that I should be looking at, up to seven days we can provide a snapshot because you will always find something you can go back, you know what I'm going to remove this outlier. All worrying about all the processing we do before we bring in the data so there's a lot of cleanliness that takes place but we have the built in tools we have the built in capabilities for everyone to get going. It's ready to scale for you from the moment you open it up. That's the beauty of it, that's the beauty of when you start from PostUp to data flow to streaming engine it's ready for you to run. >> Talk about what's changed though when people hear diversity of data they get scared, oh my god I work, heavy lifting. Now it's a benefit. What's easier now to deal with all of these diverse data sets, what's the easy revolution? >> So do you remember the big V's of big data right? Volume, velocity, variety. People were scared about the variety. Now I can actually bring in my data from different places. Again, let's go back to the shopping example. Where I shop, what I shop for, that actually defines my behavior around it. Those data sit somewhere else. We bring those in to make a decision about okay everyone wants to go buy a scooter or whatever else, that's the diversity of the data. We're now able to deal to with this at scale. That was not available we could actually bring in and render this, now everything is going to do this much more sequential. We're now able to bring all of them together process it at the same time and make the decision. >> What's the key products that will make all of those happen, take us through the portfolio if I want that would you just said which is a great value. It sounds like not a heavy lift all I have to do is point the data sources into this engine, what are the products that make up that capability? >> So if I look at the overall portfolio on Google Cloud from our data analysts point of view, so you actually can bring in your data through PostUp, lots of messaging capability globally and you can actually do it regionally because we have a lot of regional requirements coming from various countries and data flow is where we actually transfer the data. That's where you do the processing. And you use all of these advance analytics capabilities through your streaming engine that we released and you have your B query, you have your OMLs, you have all kinds of things that you can bring in you're big tables and what have you. That's all easily integrated end to end for any analyst to be able to use. >> What is beam? >> Beam ah that's great I'm so glad you asked that question I almost forgot! Beam is one of our open sources we donated the same set, just like we did with Koppernes few years ago, we donated to the open source it's growing. This year actually it won The Technology Awards. So the source is open the community really took it upon, they use that toolkit to build their pipelines you can use any kind of a code that you want Java, Gold, whatever you want to do it and they contribute. We use it internally and externally. It's one of those things that's going to grow. We have a lot of community events coming up this year. We might, and I've seen the increase, I'm really really proud of that community. >> Evren, I love the A.I. can't get my mind off your background and academic because I studied A.I. as well in the 80s and 90s all that good stuff. Young kids are flocking to computer science now because A.I. is very sexy, it's very intoxicating and it's so easy to deal with now. You guys had a hack-a-thon here with NCAA using data really kind of real time and kind of cool things are happening. So it's a moment now for A.I. this is the moment. What's your advice, you've been through the wars you've done your chore duty all those years now it's actually happening. What's your advice for young people who want to come in, get their hands dirty, build things, use A.I., what's your advice, how they should tackle that? >> I am living it, both of my sons one is finishing junior high, the other one is a senior in high school, their both in it. So when I hear my young kids come and say, "hey bubba we just built this using transfer flow." Like it is making me really proud. At the middle school level they were doing it. So the good news is we have all of this publicly available data for them. I encourage every one of them. If you look at what we provide from Google Cloud, you come in there, we have the data for them, we have the tools for them, it's all ready for them to play so schools get free access to it too. >> It's a major culture but how do they get someone who's interested but never coded before, how do they jump right in and get ingratiated and immersed into the code, what do they do? >> We have some community reaches that we're actually doing as Google. We go out to them and we're actually establishing centers to really build community events for them to really learn some new skills. And we're making this easy for them. And I'm happy to hear more and do it, but I'm an advocate I go to middle schools, I go to high schools, I go to colleges. Colleges are a different story. We provide school classes and we provide our technologies at the universities because enterprises need that talent, need that skill, when they graduate, their going to hire them just like I'm going to hire them into my organization. >> So my number one complaint my kids have about school, they're talking about kids that, oh school's going to be a waste it's so linear I can learn everything on YouTube and Google.com. All the stuff I learned in school I'm never going to use in the real world. So the question is, what skill should kids learn that could be applied to machine learning, thinking, the kind of constructs, data structures, or methodologies, what are some of the skills and classes that can tease out and be natural lead into computer science and machine learning A.I.? >> You know, actually their going to build up the skills. The languages will evolve and so forth. As long as they have that inner curiosity asking new questions, how can I find the answer a little faster, that will push them towards different sets of tools, different sets of areas. If you go to Berkeley in here, you will see a whole bunch of high school kids working side by side with graduate students asking those questions, developing those skill sets, but it's all coming down to their curiosity. >> And I think that applies for business too. I mean there's a big gap between the A.I. haves and have-nots I always say. And the good news here that my take away is, you're going to buy A.I, you're going to buy it from people like Google and you're going to build it and apply it, you're going to spend time applying it, and that's how these incumbents can close the gap and that's the good news here. >> Very true if you look at it, look at all the A.P.Is that we have. From text recognition to image recognition to whatever it is, those are all built models and I've seen some customers build some fantastic applications starting from there and they use their own data, bring it in, they update their model for their own businesses cases. >> It's composition it's composing. It's not coding it's composing. >> Exactly, it's composing. We are taking it to the next level. That abstraction is going to actually help others come into the field because they know their field of expertise, they can ask direct questions. You and I may not know it but, they will ask direct questions. And they will go with the tools available for them for the curiosity that they reach. >> Okay what's the coolest thing you're working on right now? >> Coolest thing, I just y'know streaming is my baby. We are working on, I want to solve all the streaming challenges, whatever the industry is. I really want to welcome everyone, bring you to us. I think, if I look at it, one of the things we discussed today was Antos was fantastic right? I mean we're really going to change the game for all enterprises to be able to provide those capabilities at the infrastructure. But imagine what we can do with all the data analytics capabilities we have on top of it. I think this is the next five years is going to be fantastic for us. >> What's the coolest use case thing you see emerging out of streaming? >> Ah you know, yesterday I actually had one of my clients with me onstage, AB Tasty. They had a fantastic capability that they built. They tried everything. And we were not their first choice, I'll be very open. They said the same thing to everybody, you guys were not our first choice. They went around, they looked at all the tool kits, everything. They came they used PostUp, they used data flow, they used engine, streaming engine. And they AB testing for marketing. And they do that at scale, billions of messages every minute, and they do it within seconds, milliseconds, 32 milliseconds at most. Because they have to make the decision. That was awesome, go check. I don't know if you're familiar with that. One of our customers, they provide these real time delivery. In India, imagine where things are. In global leaders, you can actually ask for a food to be delivered and they have to optimize, depending on what the traffic is and go with their scooters, and provide you this delivery. They aren't doing it as well. Okato, they believe, provide food in UK 70% of the population use our technologies for real time delivery. Those are some great examples. >> Evren, great insight, great to have you on. Just a final word here, next couple years, how do you see the trajectory of machine learning A.I. Analytics feeding into the value of making life easier society better, and businesses more productive? >> We are seeing really good pull from enterprises from every archival that you can think of. Regulated, retail, what have you. And we're going to solve some really hard problems whether it's in health care industry, financial industry, retail industry, we're going to make lives of people much easier. And their going to benefit from it at scale. And I believe we're just scratching the tip of it and you're seeing this energy in here. Year over year this has gotten better and better. I can't wait to see what's going to happen next year. >> Evren Eryurek great energy, expert at A.Is, streaming analytics, again this is early days of a brand new shift that's happening. You get on the right side of history it's A.I. machine learning, streaming analysts. Thanks for coming, I appreciate it. >> Thank you so much, take care guys. >> More live coverage here in theCUBE in San Francisco at Google next Cloud 2019. We'll be back after this short break.