>>from around >>the globe. It's >>the cube presenting future >>Cloud one >>event. A >>world of opportunities >>brought to you by Cisco. >>Okay. We're here with costume. Does, who is the Senior Vice President, General Manager of Cloud and compute at Cisco And VJ Venugopal, who is the Senior Director for Product management for Cloud, compute at Cisco. KTV J Good to see you guys welcome. >>Great to see you. Dave >>to be here. >>Katie. Let's talk about cloud. You. And I, last time we're face to face was in Barcelona where we love talking about cloud. And I always say to people look, Cisco is not a hyper scaler, but the big public cloud players, they're like giving you a gift. They spent almost actually over $100 billion last year on Capex. The big four. So you can build on that infrastructure. Cisco is all about hybrid cloud. So help us understand the strategy. There may be how you can leverage that build out and importantly what a customer is telling you they want out of hybrid cloud. >>Yeah, no, that's that's that's a perfect question to start with Dave. So yes, so the hybrid hyper scholars have invested heavily building out their assets. There's a great lot of innovation coming from that space. Um there's also a great innovation set of innovation coming from open source and and that's another source of uh a gift, in fact the I. T. Community. But when I look at my customers, they're saying, well how do I in the context of my business, implement a strategy that takes into consideration everything that I have to manage um in terms of my contemporary work clothes, in terms of my legacy, in terms of everything my developer community wants to do on devops and really harness that innovation that's built in the public cloud, that built an open source that built internally to me and that naturally leads them down the path of a hybrid cloud strategy. And Siskel's mission is to provide for that imperative, the simplest, more power, more powerful platform to deliver hybrid cloud. And that platform uh is inter site, we've been investing in Inner side, it's a it's a SAS um service um inner side delivers to them that bridge between their estates of today. There were clothes of today, the need for them to be guardians of enterprise grade resiliency with the agility uh that's needed for the future. The embracing of cloud, Native of new paradigms of deVOPS models, the embracing of innovation coming from public cloud and an open source and bridging those two is what inner side has been doing. That's kind of, that's kind of the crux of our strategy. Of course, we have the entire portfolio behind it to support any any version of that, Whether that is on prem in the cloud, hybrid, cloud, multi, cloud and so forth. >>But but if I understand it correctly from what I heard earlier today, the inter site is really a linchpin of that strategy, is it not? >>It really is and may take a second to uh to totally familiarize those who don't know inner side with what it is. We started building this platform quite a few years back and we we built a ground up to be an immensely scalable SAs super simple hybrid cloud platform and it's a platform that provides a slew of service is inherently. And then on top of that there are suites of services, the sweets of services that are tied to infrastructure, automation. Cisco, as well as Cisco partners, their suite of services that have nothing to do with Cisco um products from a hardware perspective and it's got to do with more cloud orchestration and cloud native and inner side and its suite of services um continue to kind of increase in pace and velocity of delivery video. It's just over the last two quarters we've announced a whole number of things will go a little bit deeper into some of those, but they span everything from infrastructure automation to kubernetes and delivering community than service to workload optimization and having visibility into your cloud estate. How much it's costing into your on premise state into your work clothes and how they're performing. It's got integrations with other tooling with both Cisco Abdi uh as well as non Cisco um, assets. And then and then it's got a whole slew of capabilities around orchestration because at the end of the day, the job of it is to deliver something that works and works at scale that you can monitor and make sure is resilient and that includes that. That includes a workflow and ability to say, you know, do this and do this and do this. Or it includes other ways of automation, like infrastructure as code and so forth. So it includes self service that so that expand that. But inside the world's simplest hybrid cloud platform, rapidly evolving rapidly delivering new services. And uh, we'll talk about some more of those days. >>Great. Thank you. Katie VJ Let's bring you into the discussion. You guys recently made an announcement with the ASCII corp. I was stoked because even though it seemed like a long time ago, pre covid, I mean in my predictions post, I said, ha she was a name to watch our data partners. Et are you look at the survey data and they really have become mainstream. You know, particularly we think very important in the whole multi cloud discussion. And as well, they're attractive to customers. They have open source offerings. You can very easily experiment, smaller organizations can take advantage, but if you want to upgrade to enterprise features like clustering or whatever, you can plug right in. Not a big complicated migration. So a very, very compelling story there. Why is this important? Why is this partnership important to Cisco's customers? >>Mhm. Absolutely. When the spot on every single thing that you said, let me just start by paraphrasing what ambition statement is in the cloud and compute group right ambition statement is to enable a cloud operating model for hybrid cloud. And what we mean by that is the ability to have extreme amounts of automation orchestration and observe ability across your hybrid cloud idea operations now. Uh So developers >>and applications >>team get a great amount of agility in public clouds and we're on a mission to bring that kind of agility and automation to the private cloud and to the data centers. And inter site is a quickie platform and lynchpin to enable that kind of operations. Uh, Cloud like operations in the in the private clouds and the key uh as you rightly said, harsher Carp is the, you know, they were the inventors of the concept of infrastructure at school and in terra form, they have the world's number one infrastructure as code platform. So it became a natural partnership for Cisco to enter into a technology partnership with Harsher Card to integrate inter site with hardship cops, terra form to bring the benefits of infrastructure as code to the to hybrid cloud operations. And we've entered into a very tight integration and uh partnership where we allow developers devops teams and infrastructure or administrators to allow the use of infrastructure as code in a SAS delivered manner for both public and private club. So it's a very unique partnership and a unique integration that allows the benefits of cloud managed. I see to be delivered to hybrid cloud operations and we've been very happy and proud to be partnering with Russia Carbonara. >>Yeah, telephone gets very high marks from customers. The a lot of value there, the inner side integration adds to that value. Let's stay on cloud Native for a minute. We all talk about cloud native cady was sort of mentioning before you got the the core apps uh you want to protect those, make sure their enterprise create but they gotta be cool as well for developers. You're connecting to other apps in the cloud or wherever. How are you guys thinking about this? Cloud native trend. What other movies are you making in this regard? >>I mean cloud Native is there is one of the paramount I. D. Trends of today and we're seeing massive amounts of adoption of cloud native architecture in all modern applications. Now. Cloud native has become synonymous with kubernetes these days and communities has emerged as a de facto cloud native platform for modern cloud native app development. Now, what Cisco has done is we have created a brand new SAs delivered kubernetes service that is integrated with inter site, we call it the inter site community service for a. Ks and this just gave a little over one month ago now, what interstate Kubernetes service does is it delivers a cloud managed and cloud delivered kubernetes service that can be deployed on any supportive target infrastructure. It could be a Cisco infrastructure, it could be a third party infrastructure or it could even be public club. But think of it as kubernetes anywhere delivered, as says, managed from inside. It's a very powerful capability that we've just released into inter site to enable the power of communities and cognitive to be used to be used anywhere. But today we made a very important aspect because we have today announced the brand new Cisco service mess manager. The Cisco service mesh manager, which is available as an extension to I K s are doing decide basically we see service measures as being the future of networking. Right in the past we had layer to networking and layer three networking and now with service measures, application networking and layer seven networking is the next frontier of of networking. But you need to think about networking for the application age very differently, how it is managed, how it is deployed, it needs to be ready, developer friendly and developer centric. And so what we have done is we've built out an application networking strategy and built out the service match manager as a very simple way to deliver application networking through the consumers, like like developers and application teams. This is built on an acquisition that Cisco made recently of Banzai Cloud. And we've taken the assets of Banzai Cloud and deliver the Cisco service mash Manager as an extension to KS. That brings the promise of future networking and modern networking to application and development gives >>God thank you BJ. And so Katie, let's let's let's wrap this up. I mean, there was a lot in this announcement today, a lot of themes around openness, heterogeneity and a lot of functionality and value. Give us your final thoughts. >>Absolutely. So couple of things to close on. First of all. Um, inner side is the simplest, most powerful hybrid cloud platform out there. It enables that that cloud operating model that VJ talked about but enables that across cloud. So it's sad, it's relatively easy to get into it and give it a spin so that I'd highly encouraged anybody who's not familiar with it to try it out and anybody who is familiar with it to look at it again, because they're probably services in there that you didn't notice or didn't know last time you looked at it because we're moving so fast. So that's the first thing, the second thing I close with is, um we've been talking about this bridge that's kind of bridging, bridging uh your your on prem your open source, your cloud estates. And it's so important to to make that mental leap because uh in past generation we used to talk about integrating technologies together and then with Public cloud, we started talking about move to public cloud, but it's really how do we integrate, how do we integrate all of that innovation that's coming from the hyper scale is everything they're doing to innovate superfast. All of that innovation is coming from open source, all of that innovation that's coming from from companies around the world including Cisco. How do we integrate that to deliver an outcome? Because at the end of the day, if you're a cloud of Steam, if you're an idea of Steam, your job is to deliver an outcome and our mission is to make it super simple for you to do that. That's the mission we're on and we're hoping that everybody that's excited as we are about how simple we made that. >>Great, thank you a lot in this announcement today, appreciate you guys coming back on and help us unpack you know, some of the details. Thanks so much. Great having you. >>Thank you. Dave. >>Thank you everyone for spending some time with us. This is Dave Volonte and you're watching the cube, the leader in tech event >>coverage. >>Mm mm.

>> From around the globe. It's theCube. Presenting Future Cloud. One event, a world of opportunities brought to you by Cisco. >> Okay we're here with Kaustubh Das, Who is the senior vice president and general manager of cloud and compute at Cisco and Vijay Venugopal who is the senior director of product management for cloud compute at Cisco KD, Vijay, Good to see you guys. Welcome. >> Great to see you Dave. >> Good to be here. >> KD, let's talk about cloud. You- you and I last time we were face-to-face was in Barcelona where we love talking about cloud. And I always say to people, look Cisco is not a hyperscaler but the big public cloud players they're like giving you a gift. They spent almost- actually over a hundred billion dollars last year on CapEx, the big four. So you can build on that infrastructure. Cisco is all about Hybrid Cloud. So help us understand the strategy there and maybe how you can leverage that build out and importantly, what a customer is telling you they want out of Hybrid Cloud. >> Yeah, no, that's, that's that's a perfect question to start with Dave. So yes, so the hyperscalers have invested heavily building out their assets. That's a great, a lot of innovation coming from that space um there is also great innovation- sort of innovation coming from open source. And, and that's another source of a of a gift in fact to the IT community. But when I look at my customers, they're saying, well how do I, in the context of my business, implement a strategy that takes into consideration everything that I have to manage in terms of my contemporary workloads, in terms of my legacy, in terms of everything my developer community wants to do on DevOps and really harness that innovation that's built in the public cloud that is built an open source that is built internally to me, and that naturally leads them down the path of a hybrid cloud strategy. And Cisco's mission is to provide for that imperative, the simplest, most powerful platform to deliver Hybrid Cloud. And that platform is Intersight. We've been investing in Intersight, it's a it's a SaaS service. Intersight delivers to them that bridge between the states of today, their workload of today the need for them to be guardians of enterprise grade resiliency with the agility that's needed for the future, the embracing of cloud native of new paradigms of DevOps models, the embracing of innovation coming from public cloud and an opensource and bridging those two is what Intersight has been doing. That's kind of, that's kind of, the crux of our strategy of course we have the entire portfolio behind it to support any- any version of that whether that is on prem in the Cloud, Hybrid Cloud, Multi-Cloud and so forth. >> But, but, but if I understand it correctly from what I heard earlier today the Intersight is really a linchpin of that strategy. Is it not? >> It really is. And may take a second to, to to really familiarize those who don't know Intersight with what it is. We started building this platform quite a few years back and we, we built it ground up to be an immensely scalable SAS super simple hybrid cloud platform. And it's a platform that provides a slew of services inherently And then on top of that, there's suites of services there's suites of services that are tied to infrastructure automation, Cisco as well as Cisco partners, the suites of services that have nothing to do with Cisco products from a hardware perspective. And it's got to do with more cloud orchestration and cloud native and Intersight and its suite of services continue to kind of increase in, in pace and velocity of delivery. Well just, over the last two quarters we've announced a whole number of things. We'll go a little bit deeper into some of those but they span everything from infrastructure automation to Kubernetes, and delivering Kubernetes that service to workload optimization and having visibility into your cloud estate how much it's costing into your on prem state into your workloads and how they're performing. It's got integrations with other tooling, with both Cisco as well as non-Cisco assets. And then, and then it's got a whole slew of capabilities around orchestration because at the end of the day the job of IT is to deliver something that works and works at scale that you can monitor and make sure is resilient. And that includes a workflow and ability to say, you know, do this then do this and do this. Or it includes other ways of automation like infrastructures code and so forth. So it includes a self service that, so that spanned that but Intersight, the world's simplest Hybrid Cloud platform rapidly evolving, rapidly delivering new services. And we will talk about some more of those today. >> Great. Thank you, KD Vijay let's bring you into the discussion. You guys recently made an announcement with HashiCorp. I was stoked because even though it seemed like a long time ago, pre-COVID, I ma- in my predictions post, I said Hashi was a name to watch, our data partners ETR You look at the survey data and they really have become mainstream. You know, particularly we think very important in the whole multi-cloud discussion and as well they're attractive to customers they have open source offerings, You can very easily experiment smaller organizations can take advantage, but if you want to upgrade to enterprise features like clustering or whatever you can plug right in not a big complicated migration. So very, very compelling story there. Why is this important? Why is this partnership important to Cisco's customers? >> Absolutely Dave And spot on every single thing that you said. Let me just start by paraphrasing what our mission statement is in the cloud and compute group, right? Our mission statement is to enable a cloud operating model for Hybrid Cloud. And what we mean by that is the ability to have extreme amounts of automation, orchestration, and observability across your Hybrid Cloud IT operations. Now we- so developers and applications teams get a great amount of agility in public clouds. And we are on a mission to bring that kind of agility and automation to the private cloud and to the data centers. And Intersight is a key key platform and linchpin to enable that kind of operations cloud- like operations in the private clouds. And a key- as you rightly said- HashiCorp is the, you know, they were the inventors of the concept of Infrastructure as Code and in telephone, they have the world's number one Infrastructure as Code platform. So it became a natural partnership for Cisco to enter into a technology partnership with HasiCorp to integrate Intersight with HashiCorp's Terraform to bring the benefits of Infrastructure as Code to the two hybrid cloud operations. And we entered into a very tight integration and a partnership where we allow in our developers DevOps teams and infrastructure administrators to allow the use of Infrastructure as Code in a SAS delivered manner for both public and private cloud. So it's a very unique partnership and a unique integration that allows the benefits of cloud managed IAC to be delivered to hybrid cloud operations. And we're very, very happy and proud to be partnering with HasiCorp on that iniative >> Yeah, Terraform gets very high marks from customers. The- a lot of value there the Intersight integration adds to that value. Let's stay on cloud native for a minute. We all talk about cloud native. KD was sort of mentioning before you got the- the core apps. You want to protect those make sure they're enterprise grade but they got to be cool as well for developers you're connecting to other apps in the cloud or wherever. How are you guys thinking about this cloud native trend? What are the moves you are making in this regard? >> I mean, cloud native is the is one of the paramount IT trends of today. And you're seeing massive amounts of adoption of cloud native architectures in all modern applications now cloud native has become synonymous with Kubernetes these days. And Kubernetes has emerged as a de facto cloud native platform for modern cloud native app development. Now, what Cisco has done is we've created a brand new SaaS delivered Kubernetes service that is integrated with Intersight. We call it the Intersight Kubernetes service for IKS and this just g'd a little over one month ago. Now what Intersight Kubernetes service does is it delivers a cloud managed and cloud delivered Kubernetes service that can be deployed on any supported target infrastructure. It could be a Cisco infrastructure. It could be a third-party infrastructure or it could even be public cloud. But think of it as Kubernetes anywhere Delivered as SaaS managed from Intersight. So very powerful capability that we've just released into Intersight to enable the power of Kubernetes and cloud native to be used to be used anywhere. But today we made a very important announcement Because we have today, announced the brand new Cisco service Mesh Mangager The Cisco service mesh manager which is available as an extension to IKS or to Intersight basically we see service meshes as being the future of networking, right? In the past, we had layer two networking and layer three networking. And now with service meshes application networking and layer seven networking is the next frontier of networking. But you need to think about networking for the application age, very differently how it is managed, how it is deployed. It needs to be very developer friendly and developer centric And so what we've done is we've built out an application networking strategy and built out the Service Mesh Manager as a very simple way to deliver application networking to the consumers like developers and application teams. This is built on an acquisition that Cisco made recently of Banzai Cloud, and we've taken the assets of Banzai Cloud and delivered the Cisco service mesh manager as an extension to IKS that brings the promise of future networking and modern networking to application and development teams. >> Got it. Thank you, Vijay. And so KD let's-let's wrap this up. I mean, there was a lot in this announcement today a lot of themes around openness, heterogeneity and a lot of functionality and value. Give us your final thoughts. >> Absolutely. So a couple of things to close on first of all, Intersight is the simplest most powerful hybrid cloud platform out there. It enables that- that cloud operating model that that Vijay talked about, but enables that across cloud. So it's SAS, it's relatively easy to get into it and give it a spin so that I'd highly encourage anybody Who's not familiar with it to try it out. And anybody who is familiar with it to look at it again because there are probably services in there that you didn't notice, or didn't know last time you looked at it because we were moving so fast. So that's the first thing. The second thing I'll close with is we- we've been talking about this bridge. This kind of bridging- bridging your- your on prem your open source, your- your cloud estates. And it's so important to- to make that mental leap because in p- in past generation we used to talk about integrating technologies together. And then with public cloud we started talking about move to public cloud. But it's really, how do we integrate? How do we integrate all of that innovation that's coming from the hyperscale and everything they're doing to innovate super fast. All of that innovation has come from open source. All of that innovation that's coming from from companies around the world, including Cisco how do we integrate that to deliver an outcome? Because at the end of the day, if you're a cloud ops team if you're an IT ops team, your job is to deliver an outcome. And our mission is to make it super simple for you to do that. So that's the mission we're on. And we're hoping that everybody is as excited as we are about how simple they made that. >> Great. Thank you a lot, a lot in this announcement today. I appreciate you guys coming back on and helping us unpack some of the details. Thanks so much. Great having you. >> Thank you Dave >> Thank you >> And thank you everyone for spending some time with us. This is Dave Vellante and you're watching theCube the leader in tech event coverage. (Closing music)

>> Narrator: From around the globe, it's theCube. With digital coverage of VMworld 2020. Brought to you by VMware and its ecosystem partners. >> Hello, and welcome back to theCube virtual coverage of VMworld 2020. I'm John Furrier, host of theCube. VMworld's not in person this year, it's on the virtual internet. A lot of content, check it out, vmworld.com, a lot of great stuff, online demos, and a lot of great keynotes. Here we got a great conversation to unpack, the NVIDIA, the AI and all things Cloud Native. With Krish Prasad, who's the SVP and GM of Cloud Platform, Business Unit, and Manuvir Das head of enterprise computing at NVIDIA. Gentlemen, great to see you virtually. Thanks for joining me on the virtual Cube, for the virtual VMworld 2020. >> Thank you John. >> Pleasure to be here. >> Quite a world. And I think one of the things that obviously we've been talking about all year since COVID is the acceleration of this virtualized environment with media and everyone working at home remote. Really puts the pressure on digital transformation Has been well discussed and documented. You guys have some big news, obviously on the main stage NVIDIA CEO, Jensen there legend. And of course, you know, big momentum with with AI and GPUs and all things, you know, computing. Krish, what are your announcements today? You got some big news. Could you take a minute to explain the big announcements today? >> Yeah, John. So today we want to make two major announcements regarding our partnership with NVIDIA. So let's take the first one, and talk through it and then we can get to the second announcement later. In the first one, as you well know, NVIDIA is the leader in AI and VMware as the leader in virtualization and cloud. This announcement is about us teaming up, deliver a jointly engineered solution to the market to bring AI to every enterprise. So as you well know, VMware has more than 300,000 customers worldwide. And we believe that this solution would enable our customers to transform their data centers or AI applications running on top of their virtualized VMware infrastructure that they already have. And we think that this is going to vastly accelerate the adoption of AI and essentially democratize AI in the enterprise. >> Why AI? Why now Manuvir? Obviously we know the GPUs have set the table for many cool things, from mining Bitcoin to really providing a great user experience. But AI has been a big driver. Why now? Why VMware now? >> Yes. Yeah. And I think it's important to understand this is about AI more than even about GPUs, you know. This is a great moment in time where AI has finally come to life, because the hardware and software has come together to make it possible. And if you just look at industries and different parts of life, how is AI impacting? So for example, if you're a company on the internet doing business, everything you do revolves around making recommendations to your customers about what they should do next. This is based on AI. Think about the world we live in today, with the importance of healthcare, drug discovery, finding vaccines for something like COVID. That work is dramatically accelerated if you use AI. And what we've been doing in NVIDIA over the years is, we started with the hardware technology with the GPU, the Parallel Processor, if you will, that could really make these algorithms real. And then we worked very hard on building up the ecosystem. You know, we have 2 million developers today who work with NVIDIA AI. That's thousands of companies that are using AI today. But then if you think about what Krish said, you know about the number of customers that VMware has, which is in the hundreds of thousands, the opportunity before us really now is, how do we democratize this? How do we take this power of AI, that makes every customer and every person better and put it in the hands of every enterprise customer? And we need a great vehicle for that, and that vehicle is VMware. >> Guys, before we get to the next question, I would just want to get your personal take on this, because again, we've talked many times, both of you've been on theCube on this topic. But now I want to highlight, you mentioned the GPU that's hardware. This is software. VMware had hardware partners and then still software's driving it. Software's driving everything. Whether it's something in space, it's an IOT device or anything at the edge of the network. Software, is the value. This has become so obvious. Just share your personal take on this for folks who are now seeing this for the first time. >> Yeah. I mean, I'll give you my take first. I'm a software guy by background, I learned a few years ago for the first time that an array is a storage device and not a data structure in programming. And that was a shock to my system. Definitely the world is based on algorithms. Algorithms are implemented in software. Great hardware enables those algorithms. >> Krish, your thoughts. we live we're living in the future right now. >> Yeah, yeah. I would say that, I mean, the developers are becoming the center. They are actually driving the transformation in this industry, right? It's all about the application development, it's all about software, the infrastructure itself is becoming software defined. And the reason for that is you want the developers to be able to craft the infrastructure the way they need for the applications to run on top of. So it's all about software like I said. >> Software defined. Yeah, just want to get that quick self-congratulatory high five amongst ourselves virtually. (laughs) Congratulations. >> Exactly. >> Krish, last time we spoke at VMworld, we were obviously in person, but we talked about Tanzu and vSphere. Okay, you had Project Pacific. Does this expand? Does this announcement expand on that offering? >> Absolutely. As you know John, for the past several years, VMware has been on this journey to define the Hybrid Cloud Infrastructure, right? Essentially is the software stack that we have, which will enable our customers to provide a cloud operating model to their developers, irrespective of where they want to land their workloads. Whether they want to land their workloads On-Premise, or if they want it to be on top of AWS, Google, Azure, VMware stack is already running across all of them as you well know. And in addition to that, we have around, you know, 4,000, 5,000 service providers who are also running our Platform to deliver cloud services to their customers. So as part of that journey, last year, we took the Platform and we added one further element to it. Traditionally, our platform has been used by customers for running via VMs. Last year, we natively integrated Kubernetes into our platform. This was the big re architecture of vSphere, as we talked about. That was delivered to the market. And essentially now customers can use the same platform to run Kubernetes, Containers and VM workloads. The exact same platform, it is operationally the same. So the same skillsets, tools and processes can be used to run Kubernetes as well as VM applications. And the same platform runs, whether you want to run it On-Premise or in any of the clouds, as we talked about before. So that vastly simplifies the operational complexity that our customers have to deal with. And this is the next chapter in that journey, by doing the same thing for AI workload. >> You guys had great success with these Co-Engineering joined efforts. VMware and now with NVIDIA is interesting. It's very relevant and is very cool. So it's cool and relevant, so check, check. Manuvir, talk about this, because how do you bring that vision to the enterprises? >> Yeah, John, I think, you know, it's important to understand there is some real deep Computer Science here between the Engineers at VMware and NVIDIA. Just to lay that out, you can think of this as a three layer stack, right? The first thing that you need is, clearly you need the hardware that is capable of running these algorithms, that's what the GPU enable. Then you need a great software stack for AI, all the right Algorithmics that take advantage of that hardware. This is actually where NVIDIA spends most of its effort today. People may sometimes think of NVIDIA as a GPU company, but we have much more a software company now, where we have over the years created a body of work of all of the software that it actually takes to do good AI. But then how do you marry the software stack with the hardware? You need a platform in the middle that supports the applications and consumes the hardware and exposes it properly. And that's where vSphere, you know, as Krish described with either VMs or Containers comes into the picture. So the Computer Science here is, to wire all these things up together with the right algorithmics so that you get real acceleration. So as examples of early work that the two teams have done together, we have workloads in healthcare, for example. In cancer detection, where the acceleration we get with this new stack is 30X, right? The workload is running 30 times faster than it was running before this integration just on CPUs. >> Great performance increase again. You guys are hiring a lot of software developers. I can attest to knowing folks in Silicon Valley and around the world. So I know you guys are bringing the software jobs to the table on a great product by the way, so congratulations. Krish, Democratization of AI for the enterprise. This is a liberating opportunity, because one of the things we've heard from your customers and also from VMware, but mostly from the customer's successes, is that there's two types of extremes. There's the, I'm going to modernize my business, certainly COVID forcing companies, whether they're airlines or whatever, not a lot going on, they have an opportunity to modernize, to essentially modern apps that are getting a tailwind from these new digital transformation accelerated. How does AI democratize this? Cause you got people and you've got technology. (laughs) Right? So share your thoughts on how you see this democratizing. >> That's a very good question. I think if you look at how people are running AI applications today, like you go to an enterprise, you would see that there is a silo of bare metal sun works on the side, where the AI stack is run. And you have people with specialized skills and different tools and utilities that manage that environment. And that is what is standing in the way of AI taking off in the enterprise, right? It is not the use case. There are all these use cases which are mission critical that all companies want to do, right? Worldwide, that has been the case. It is about the complexity of life that is standing in the way. So what we are doing with this is we are saying, "hey, that whole solution stack that Manuvir talked about, is integrated into the VMware Virtualized Infrastructure." Whether it's On-Prem or in the cloud. And you can manage that environment with the exact same tools and processes and skills that you traditionally had for running any other application on VMware infrastructure. So, you don't need to have anything special to run this. And that's what is going to give us the acceleration that we talked about and essentially hive the Democratization of AI. >> That's a great point. I just want to highlight that and call that out, because AI's every use case. You could almost say theCube could have AI and we do actually have a little bit of AI and some of our transcriptions and work. But it's not so much just use cases, it's actually not just saying you got to do it. So taking down that blocker, the complexity, certainly is the key. And that's a great point. We're going to call that out after. Alright, let's move on to the second part of the announcement. Krish Project Monterey. This is a big deal. And it looks like a, you know, kind of this elusive, it's architectural thing, but it's directionally really strategic for VMware. Could you take a minute to explain this announcement? Frame this for us. >> Absolutely. I think John, you remember Pat got on stage last year at Vmworld and said, you know, "we are undertaking the biggest re architecture of the vSphere platform in the last 10 years." And he was talking about natively embedding Kubernetes, in vSphere, right? Remember Tanzu and Project Pacific. This year we are announcing Project Monterrey. It's a project that is significant with several partners in the industry, along with NVIDIA was one of the key partners. And what we are doing is we are reimagination of the data center for the next generation applications. And at the center of it, what we are going to do is rearchitect vSphere and ESX. So that the ESX can normally run on the CPU, but it'll also run on the Smart Mix. And what this gives us is the whole, let's say data center, infrastructure type services to be offloaded from running on the CPU onto the Smart Mix. So what does this provide the applications? The applications then will perform better. And secondly, it provides an extra layer of security for the next generation applications. Now we are not going to stop there. We are going to use this architecture and extended it so that we can finally eliminate one of the big silos that exist in the enterprise, which is the bare metal silo. Right? Today we have virtualized environments and bare metal, and what this architecture will do is bring those bare metal environments also under ESX management. So you ESX will manage environments which are virtualized and environments which are running bare metal OS. And so that's one big breakthrough and simplification for the elimination of silo or the elimination of, you know, specialized skills to keep it running. And lastly, but most importantly, where we are going with this. That just on the question you asked us earlier about software defined and developers being in control. Where we want to go with this is give developers, the application developers, the ability to really define and create their run time on the Fly, dynamically. So think about it. If dynamically they're able to describe how the application should run. And the infrastructure essentially kind of attaches computer resources on the Fly, whether they are sitting in the same server or somewhere in the network as pools of resources. Bring it all together and compose the runtime environment for them. That's going to be huge. And they won't be constrained anymore by the resources that are tied to the physical server that they are running on. And that's the vision of where we are taking it. It is going to be the next big change in the industry in terms of enterprise computing. >> Sounds like an Operating System to me. Yeah. Run time, assembly orchestration, all these things coming together, exciting stuff. Looking forward to digging in more after Vmworld. Manuvir, how does this connect to NVIDIA and AI? Tie that together for us. >> Yeah, It's an interesting question, because you would think, you know, okay, so NVIDIA this GPU company or this AI company. But you have to remember that INVIDIA is also a networking company. Because friends at Mellanox joined us not that long ago. And the interesting thing is that there's a Yin and Yang here, because, Krish described the software vision, which is brilliant. And what this does is it imposes a lot on the host CPU of the server to do. And so what we've be doing in parallel is developing hardware. A new kind of "Nick", if you will, we call it a DPU or a Data Processing Unit or a Smart Nick that is capable of hosting all this stuff. So, amusingly when Krish and I started talking, we exchanged slides and we basically had the same diagram for our vision of where things go with that software, the infrastructure software being offloaded, data center infrastructure on a chip, if you will. Right? And so it's a very natural confluence. We are very excited to be part of this, >> Yeah. >> Monterey program with Krish and his team. And we think our DPU, which is called the NVIDIA BlueField-2, is a pretty good device to empower the work that Krish's team is doing. >> Guys it's awesome stuff. And I got to say, you know, I've been covering Vmworld now 11 years with theCube, and I've known VMware since its founding, just the evolution. And just recently before VMworld, you know, you saw the biggest IPO in the history of Wall Street, Snowflake an Enterprise Data Cloud Company. The number one IPO ever. Enterprise tech is so exciting. This is really awesome. And NVIDIA obviously well known, great brand. You own some chip company as well, and get processors and data and software. Guys, customers are going to be very interested in this, so what should customers do to find out more? Obviously you've got Project Monterey, strategic direction, right? Framed perfectly. You got this announcement. If I'm a customer, how do I get involved? How do I learn more? And what's in it for me. >> Yeah, John, I would say, sorry, go ahead, Krish. >> No, I was just going to say sorry Manuvir. I was just going to say like a lot of these discussions are going to be happening, there are going to be panel discussions there are going to be presentations at Vmworld. So I would encourage customers to really look at these topics around Project Monterey and also about the AI work we are doing with NVIDIA and attend those sessions and be active and we will have a ways for them to connect with us in terms of our early access programs and whatnot. And then as Manuvir was about to say, I think Manuvir, I will give it to you about GTC. >> Yeah, I think right after that, we have the NVIDIA conference, which is GTC, where we'll also go over this. And I think some of this work is a lot closer to hand than people might imagine. So I would encourage watching all the sessions and learning more about how to get started. >> Yeah, great stuff. And just for the folks @vmworld.com watching, Cloud City's got 60 solution demos, go look for the sessions. You got the EX, the expert sessions, Raghu, Joe Beda amongst other people from VMware are going to be there. And of course, a lot of action on the content. Guys, thanks so much for coming on. Congratulations on the news, big news. NVIDIA on the Bay in Virtual stage here at VMworld. And of course you're in theCube. Thanks for coming. Appreciate it. >> Thank you for having us. Okay. >> Thank you very much. >> This is Cube's coverage of VMworld 2020 virtual. I'm John Furrier, host of theCube virtual, here in Palo Alto, California for VMworld 2020. Thanks for watching. (upbeat music)

(upbeat music) >> Announcer: Live from Barcelona, Spain it's theCUBE covering Cisco Live 2020, brought to you by Cisco and its ecosystem partners. >> Welcome back. This is theCUBE's live coverage of Cisco Live 2020 here in Barcelona, Spain. I'm Stu Miniman. My co-host for this segment is Dave Volante. John Furrier is also in the house. We're doing a little more than three days wall-to-wall coverage. One of the big themes we're talking about this week is in this complicated world, networking, containerization, applications going through transformation. Future work simplification is something that is very important and helping us to really tease through and understand some of the integration, some of the announcements where Cisco is helping to simplify the environment, happy to welcome back to the program one of our Cube alumni, Kaustubh Das who is a Vice President of Product Management at Cisco. KD, thanks so much for joining us. >> Oh, I'm delighted to be here, it's great to be here. >> All right. So but up on the main stage, they walk through a number of the announcement. Listen Tony, I was talking about some of the pieces and two of the announcements from the main stage are under your purview. So why don't we start there, walk us through the news. >> Yeah, so there's two two major announcements. The first one's called Cisco Intersight Workload Optimizer. And what it is, it's a way to have visibility into your data center, all the way from the applications and in fact, the user journeys within those applications, all the way down through the virtualization there, through the app servers, through the container platforms down into the servers, the networks, storage lands. So you have a map of the data center. You have a common data set that the application owner and the infrastructure owner can both look at and you finally have a common vocabulary so that it helps them to troubleshoot faster so on a fast reactor way, they talking the same language not pointing fingers at each other or do things proactively to prevent problems from happening when you see a server running hot, a virtual machine running hot, an application server running hot. You can diagnose it and have that conversation before it happens. >> My understanding is that Intersight and there's also some integrations with AppDynamics there, AppD which of course we know we talk to that team at the Amazon Cloud shows a lot. So that common vocabulary spans between my hybrid and multi cloud environments. Am I getting that right? >> Correct and there's two pieces even within that. So certainly that's integrations with AppD so from AppD we get information about the application performance. We get information about the business metrics associated with the application performance. We get information about the journeys that user take within the application and then we take that data then we stitch it together with infrastructure data to map how many applications are dependent on which application servers, how many VMs are those dependent on, what does those VMs run on? What hosts are they dependent on, what networks do they Traverse, what lands do they run on? And each one of these is an API call into that element in the infrastructure stack. Each API call gives us a little bit of data and then we piece together this data to create this map of the of the entire data center. There's a multi cloud aspect to it obviously and so we also make API calls into AWS and Azure and clouds out there and we get data about utilization of the various instance types. We get data about performance from the cloud as well. >> So two announcements. Insight Workload Optimizer and HyperFlex AppDynamics, is that right or they are separate? >> HyperFlex application platform. >> Okay. >> So if we look at the, let me just put these two in context. Every enterprise is doing two things. It's trying to run application that it already hosts and then it's writing some bespoke new applications. So the first announcement, the Cisco Intersight Workload Optimizer and the integration of the AppD, that helps us be more performant for applications we're running, to have troubleshoot faster, to have reduced cost in a multiply cloud environment. The second announcement Dave, the HyperFlex application platform, it's really targeted towards developers who are writing new applications on a container platform. And for those developers, IT needs to give them a simple appliance like easy to use container as a service platform. So what HX AP HyperFlex application platform is is a container as a service platform driven from the cloud so that the developer gets the same experience that they get when they go to an AWS and and request a pod. But they get it on-prem and it's fully 100% upstream Kubernetes compliant. It's curated by us so it's very simple appliance like feel for development environments on container. >> Okay. So Insight Workload Optimizer, it really attacks the problem of sort of the mystery of what goes on inside VMs and the application team, the infrastructure team, they're not talking to each other. You're bringing a common, like you said parlance together. >> Kaustubh: Correct. >> Really so they can solve problems and that that trickles down to cost optimization as well as performance. >> It does, aha. >> And I understand hyper HyperFlex app platform it's really bringing that cloud experience to on-prem for hybrid environments. >> For our new development. So if you're developing on containers, you're probably using Kubernetes but you're probably using this entire kind of ecosystem of open source tools. >> Yeah. >> And we make that simple. >> Okay. >> We make it simple for developers to use that and variety to provide that to developers. >> Okay. since underneath, there's HyperFlex. is there still virtualization involved in there and how does this tie in with the rest of the Kubernete solutions that we were talking about with your cloud partner? >> Great, great. Great question. So yes, there is HyperFlex underneath this. So to develop, you need a platform. The best platform we think is the elastic platform that is hyper-convergence. And with type of flex, we took storage networking and compute, packaged it together, made it super simple. We're doing the same thing with Kubernetes. So it's the same concept that how do you take complex things, package it together and make it almost appliance like. We said we're doing the same thing with Kubernetes. Now Stu, the point about virtualization is a good one. A lot of container deployments today are run in virtual machines. And they run in virtual machines for good reason, for isolation, for multi-tenancy, for all these kinds of ignition. However, the promise of containers was to sort of get rid of the tax that you pay when you deploy a virtualization environment. And what we're giving out right now is no tax, no virtualization tax virtualization environment. So we have a layer over transition in there. It's designed for this use case so it does give the isolation, it does give the multi-tenancy benefits but you don't need to need to pay additionally for it if you're deploying on containers-- >> Job wise it is some KB and base type solution >> Kaustubh: Correct. >> Underneath, it makes a lot of sense if you look at the large virtualization player out there. It's been talking about how do I enable the infrastructure that's all virtualized and everything and bring them along to that journey >> Correct. >> For that bridge if you will to the environment? Sure containerization sometimes I want to be able to spin it up super fast. It leaves, it dies, but if I'm putting something in my data center, probably the characteristics I'm looking at are a little bit different. >> Correct, correct. The other thing it does and you touched on it a little bit was we have a homogeneous environment with the major clouds out there. So one of the things developers want to do is they want to develop in one place and they want to deploy in another place so develop on Amazon and deploy on-prem or Azure. We've got an environment with very native integrations so that it's natively integrated into EKS and AKS. And we facilitate that develop anywhere, deploy anywhere motion for developers who are trying to build on this. >> So okay. What does the customer have to do to consume these solutions? >> So our customer right now for this one is IT operations. It maybe helps to bit back a little bit on why we did this. I had a lot of customers come to me and they said listen, I'm IT, I'm in the business of taking shrink-wrap software, taking enterprise-grade resilient infrastructure, putting that together. I'm not in the business of getting open source drops, every week, every day, every month, putting them together by making sure all the versions line up and doing that again and again and again. So the putting together an Ikea piece part of open source software has not been traditionally the IT operator's business. So our customer is that IT operator. What they need to do is they buy a, if they may have a HyperFlex system already, or they buy a HyperFlex effect system. They add on a license for the HyperFlex application platform. They have an Intersight license. This is delivered from the cloud so Intersight manages that deployment, manages the lifecycle, manages the upgrades and so forth. If they have a state that spreads across multiple sites, Intersight is cloud-based so it can actually reach all those sites and so they're in business. >> Okay, so very low prerequisite. You just got to have the product and you can add on to it. >> Yeah, I have the HyperFlex system, add on to the license, you're done. >> So I'm curious. How unique do you see this in the marketplace? I think the keynotes this morning is that there's no other company that can actually do this. I wonder if you can sort of add some color to that and just help our viewers understand the uniqueness of Cisco's offer. >> Sure. So I think it's unique on a number of different dimensions. The first dimension is HyperFlex itself. We've had an appliance mentality to this for a long time and we really co-designed the software and the hardware to build the most performance hyper-converged system out there. We took the same approach when we went down the path of Kubernetes and building this container platform. And so it's called design software and infrastructure together. The second thing is we said we're going to be 100% upstream Kubernetes compliant right, so if you look at the major offerings out there in this space, they're often several months actually behind where the open source is, where the upstream of the sources and developers don't want that. They want the latest and greatest, they want they want to be current, right. So we are far ahead of most of the other offerings out there in terms of how close they are to their upstream commodities. The final piece is Intersight. Intersight gives us immense ability to have scale where especially if you're developing on containers and micro services, you're talking tens of thousands, many tens of thousands of N nodes, maybe more. And being in the cloud, we have the scale and we have reached so a lot of our customers have distributed assets and branches and you know, hotel chains with hotels and so forth. Intersight allows us the ability to actually deploy across a distributed asset class with with the centralized kind of provisioning. >> You see a huge uptake right now and containers generally Kubernetes, specifically. It's sort of across the board but I wonder if you could comment on how much of that demand and activity is coming from sort of the traditional IT roles versus with other hoody developers? >> Yeah, that's that's a great question. So yes, there is a on a hype cycle it's at the top of the hype cycle. Everybody's in actual adoption. I think it's pretty good as well right. So that is every company I talk to is doing something in containers, every company. But usually, it starts at the developers. It starts with like you described with the folks in the hoodies and that's great. I mean they're experimenting, they're getting this thing. What hasn't happened is it hasn't gotten mainstream. And things can mainstream is when IT picks it up. It certifies hey this is resilient, this is enterprise-grade, I can stand behind it, I can manage the lifecycle of it. That's what we're enabling here. I'm giving IT a path to mainstream containers, to mainstream Kubernetes so that the adoption kind of takes it from that pipe cycle to mainstream adoption. >> Do you see K.D. new sort of data protection approaches or thinking as containers come into play? I mean they're ephemeral, you know microservices sometimes aren't so micro. Like you say, they're running often times inside a VM. So how are people thinking about protecting containers? >> Yeah, yeah, that's a big topic in itself. I mean one of the things that we found is even though they were supposed to be ephemeral, they require persistent storage so we've implemented within hyperflex a CSI plugin that provides that persistent storage layer to containers. Then once you do that, all of the data protection mechanism of HyperFlex come into play. So within the cluster, the resiliency, the triple replication, the backups, the partnerships we have with their other data protection pairs, all of those mechanisms become available instantly and those are enterprise-grade. Those are ones that IT knows and can stand behind. Those become available to containers right away >> Great. >> But it's great, great question. >> Awesome. >> Just want to go back to when you were talking about Intersight and the reach and the scale of the solution reminds me that Cisco has a strong legacy in global environment. What I'm curious about, we've talked a little bit about Edge computing in the past. >> Kaustubh: Yes. >> Where are you seeing Edge today? Where is that going? What should we be looking at in that space when it comes to Edge? >> Yeah, no, it's a big part of our customer demand. In fact, we haven't seen I think all flash was the other technology that took place so fast but Edge has been really phenomenal in its growth rate. Over the last year, we've seen I think probably up to 15% to 20% of my engagements are in this space on at least the hyper convert side. So we see that as a big growth area. More and more deployments are happening. They're being centrally managed, deployed at the edges and so the only solution that scales to something like that is something that's based on the cloud. But it's not just enough to be based in the cloud. You've got to maintain that entire lifecycle right? You've got to make sure you can do installs, upgrades, you know OS installs, health monitoring and so as we built that Intersight platform, we've added all those capabilities to it over time So we started with hey this is a SAS-based management platform and then we added telemetry and then we said if we can actually match signatures, now machines can manage machines. So a good amount of my support calls are now machines calling each other and then fixing themselves. So that's just path-breaking from an informant Edge environment. You don't have an IT person, add an Edge location. You want to drop, ship an appliance there, and you want to be able to see it remotely. So I think it's a completely new operating model. >> I know we got to go but I want to run your scenario by K.D.'s. Do share with me from one of my breaking analysis. Look Dave, you mentioned Flash, that's what triggered me. (laughing) So think of containers and Kubernetes, think of like Flash. Remember Flash used to be the separate thing which we used to think it was a separate market and now it's just everywhere, it's embedded in everything. >> Kaustubh: Yes. >> So the same thing is going to happen with Kubernetes. It's going to be embedded in solutions. This is exactly what it is. By 2023, we're probably not going to be talking about it as a separate thing, maybe that's sooner. It's really just going to be ubiquitous, yeah. >> No, I totally agree. I think the underpinnings that you need for that future, you need a common infrastructure platform and a common management platform. So you don't want to have a new Silo creator and this has been our philosophy even for hyperconvergence. We said hey, there's going to be converging infrastructure that will be hyper converted. But they need to be the same management system, they need to be the same fabric. And so if it's Silo is not going to work. Same thing for containers you know. It's got to be the same platform in this case, it's HyperFlex. Hyperflex runs virtualization, it runs containers with HXAP. You get all of those benefits that I've talked about. It's all management insights, it's a common management platform across both of those. At some point, these are all tools in somebody's tool kit and you pick the right one for the job. >> Kaustubh, it is wonderful to hear the company that has been dominant in one of the silos for so long of course helping to bring the silos together work across the domains. Congratulations on that good news, always great to have you. >> Yeah, always great to be here, thank you. >> Dave: Thank you. >> For Dave Folante, I'm Stu Miniman back from lunch where we hear more from Cisco live in Barcelona 2020. Thank you for watching theCUBE.

>> Live from San Diego, California It's the queue covering Sisqo Live US 2019 Tio by Cisco and its ecosystem barkers. >> Welcome back. It's the Cube here at Cisco Live, San Diego 2019 times. Two minute My co host is Day Volante. First, I want to welcome back custom dos Katie, who is the vice president. Product management with Cisco Compute. We talked with him a lot about Piper Flex anywhere in Barcelona. Wanna welcome to the program of first time guests Laura Crone, who's the vice president of sales and marketing group in NSG sales and marketing at Intel. Laura, thanks so much for joining us, All right, So since Katie has been our program, let let's start with you. You know, we know, you know. We've watched, you know, Cisco UCS and that compute, you know, since it rolled out for about a decade ago. Now on DH, you know Intel always up on stage with Cisco talking about the latest enhancements everywhere I go this year, people are talking about obtained and how technologies like envy me are baking in tow. The environment storage class memories, you know, coming there. So you know, let's start with kind of intel. What's happening in your world and you know your activities. Francisco live >> great. So I'm glad to hear you've heard a lot about octane because I have some marketing of my organization. So obtain is the first new memory architecture er in over 25 years. And it is different than Nanda, right? It is you, Khun, right? Data to the silicon that is programs faster and has greater endurance. So when you think of obtain its fast like D ram But it's persistent, like nay on three D now. And it has some industry leading combinations of capabilities such a cz high throughput, high endurance, high quality of service and low latent see. And for a storage device, what could be better than having fast performance and hi consistency. Oh, >> Laura's you say? Yeah, but 25 years since this move. You know, I remember when I when I started working with Dave, it was, you know, how do we get out of you know, the horrible, scuzzy stack is what we had lived on for decades there. And finally, Now it feels like we're coming through the clearing and there is just going to be wave after wave of new technologies that air free to get us high performance low latent c on the like. >> Yeah, And I think the other big part of that which is part of Cisco's hyper flex all in Vienna, is the envy me standards. So, you know, we've lived in a world of legacy satya controllers, which created a lot of bottlenecks and the performance Now that the industry is moving toe envy me, that even opens up it. Mohr And so, as we were developing, obtain, we knew we had Teo go move the industry to a new protocol. Otherwise, that pairing was not going to be very successful. >> Alright, so Katie all envy me, tell more. >> So we come here and we talk about all the cool innovations we do within the company. And then sometimes you come here and we talk about all the cool innovation we do with our partners, our technology partner, that intel being a fantastic technology partner, obviously being the server business, you've got a partner with intel on. We've really going away that across the walls ofthe two organizations to bring, uh, just do to life, right? So Cisco 80 I hyper flex is one of the products >> we >> talked about in the past. Hyper Flex, all in Miami that uses Intel's obtain technology is, well, it's Intel's three demand all envy me devices to power really the fastest workloads that customers want to put on this device. So you talked about free envy me. Pricing is getting to a point where it becomes that much more accessible to youth, ese for powering databases for par like those those work clothes required that leyton see characteristics and acquire those I ops on DH. That's what we've enabled with Cisco Hyper Flex collaborating with Intel of Envy Me portfolio. >> Remember when I started in the business, somebody was sharing with me to educate me on the head? A pyramid? Think of the period is a storage hierarchy. And at the top of it, was it actually an Intel solid state device, which back then was not It was volatile, right? So you had to put, you know, backup power supplies on it. Uh, so but any rate and then with all this memory architecture coming and flash towards people have been saying, well, it's going to flatten that pyramid. But now, with obtain. You're seeing the reemergence of that periods of that pyramid. So help us understand, sort of where it fits from a supplier standpoint and a no yam and ultimate customer. Because if I understand it, so obtain is faster than NAND, but it's going to be more expensive, but it's slower than D Ram, but it's cheaper, right? So where does it fit? What, the use cases? Where does it fit in that hierarchy? Maybe. >> Yeah. So if you think about the hierarchy at the very top is D RAM, which is going to be your fastest lowest Leighton see product. But right below that is obtained. Persistent memory, the dims and you get greater density because that's one of the challenges with the Ram is they're not dense enough, nor are they affordable enough, right? And so you get that creates a new tear in the store tire curry. Go below that and you have obtain assist ease, which bring even mohr density. So we go up to a 1.5 terabyte in a obtain sst, uh, and you that now get performance for your storage and memory expansion. Then you have three Dean and and then even below that, you have three thing and Q l c, which gives you cost effective, high density capacity. And then below that is the old fashioned hard disk drive. And then magnet. Yeah, you start inserting all these tears that give architects and both hardware and software an opportunity. Teo rethink how they wantto do storage. >> So the demand for this granularity obviously coming from your your buyers, your direct bars and your customers. So what does it do for you and specifically your customers? >> Yeah. So the name of the game is performance and the ability to have in a land where things are not very predictable, the ability to support any thing that the your end customers may throw at you if you're a 90 department. That may mean a bur internal of, uh, data scientist team are traditional architect off a traditional application. Now, what Intel and Cisco can do together is truly unique because we control all parts of the stack, everything from the sober itself to the to the storage devices to the distributed file system that sits on top ofit. So, for example, in Etienne, hyper flecks were using obtain as a cashing here on because we write the distributed file system. We can speak in a balance between what we put in the cash in care how it moved out data to the non cashing 3 90 year, as as Intel came out with their latest processors that support memory class torched last memory. We support that now we can engineer this whole system and to end so that we can deliver to customers the innovation that Intel is bringing to the table in a way that's consumable by their, uh, one more thing I'll throw out there. So technology is great, but it needs to be resilient because I D departments will occasionally yank out the wrong wire. They are barely yank out the wrong drive. One of the things that we work together with Intel What? How do we court rise into this? How to be with reliability, availability, serviceability? How do we prevent against accidental removal or accidental insertion on DH? Some of those go innovations have let Teo asked, getting out in the market a hyper flecked system that uses these technologies in a way that's really usable by teens in our customs. I'd >> love to double click on that in the context of envy. Envy? What you guys were talking about, You mentioned horrible storage deck. I think he called it the horrible, scuzzy stack. And Laura, you were talking about the You know, the cheap and deep now is a spinning disk. So my understanding is that you've got a lot of overhead in the traditional scuzzy protocol, but nobody ever noticed because you had this mechanical device. Now, with flash storage, it all becomes exposed. And VM e allows just a like a bat phone. Right? Okay, so correct me where I got that wrong, But maybe you could give us the perspective. You know what? Why Envy Emmy is important from your standpoint. And how are you guys using it? >> Yeah, I think envy and me is just a much faster protocol. And you're absolutely right. We have a graph that we show of the old world and how much overhead there is all the way down to when you have obtained in a dim solution with no overhead octane assist. E still has a tiny bit, but there's a graph that shows all of that Leyton C is removed when you deploy, obtain so envy me gives you much greater band with right. The CPU is not bottlenecked, and you get greater CPU efficiency when you have a faster interface like and >> and like hyper flexes taking advantage of this house. Oh, >> yeah? Let me give you a couple of examples. So anything performance, the first thing that comes to mind is databases. So for those kinds of workloads, this system gets about 25% better performance. Next thing that comes to mind is people really don't know what they're gonna put on the system. So sometimes they put databases, sometimes put mixed workloads. So when we look at mixed workloads way get about 65% or so better I ops, we get 37% better lately sees. So even in a mixed I opened Wyman wherever have databases you may have a Web theory may have other things. This thing is definite resilient to handle the workload. So it's it just opens up the splatter abuse cases. >> So any other questions I had was specific to obtain. D ram has consumer applications, as does Flash Anand was obtained. Have similar consumer applications can achieve that volume so that the prices, you can come down, not free, but continue to sort of drive the curves. >> Eso When we look at the overall tam, we see the tam growing out over time. I don't know exactly when it crosses. Over the volume are the bits of the ram, but we absolutely see it growing over time. And as a technology ramps, it'll have a you know, it costs ramping curves. Well, >> it'll follow that curve. Okay, good. >> Yeah, Just Katie. Give us a little bit. Broad view of hyper flex here. Att? The show, people, you know, play any labs with the brand new obtained pieces or what? What other highlights that you and the team have this week? >> Yeah, absolutely. So in in Barcelona, we talked about high, perfect for all that is live today. So in the show floor, people can look at the hyper flex at the edge combined with S t one. How do you control How did deploy thousands of edge locations from a centralized location to the part of the inner side which cloud based management too? So that whole experience is unable. Now, at the other end of the spectrum is how do we drive even more performance. So we were always, always the performance leader. Now we're comparing ourselves to ourselves to behavior 35% better than our previous all flash. With the innovation Intel is bringing to the table, some of the other pieces are actually use cases. So there's a big hospital chain where my kids go toe goto, get treated and look and see the doctor. There are lots of medical use cases which require epic the medical software company to power it, whether it is the end terminals or it is the back and database. So that epic hyperspace and happy cachet those have been out be invalidated on hyper flex, using the technology that we just talked about around update on doll in via me that can get me there is that much more power. That means that when my my doctor and the nurse pulls off, the records don't show up fast. But all the medical records, all of those other high performance seeking applications also run that much more streamlined, so I would encourage people little water solution. We've got a tremendous set off demos out there to go up there and check us out >> and there's a great white paper out on this, right? That e g s >> e g is made one of the a company that I've seen benchmarking Ah, a hyper flex. >> So whatever Elaborate where they do a lab report or >> it's what they do is they bench around different hyper converge infrastructure vendors. So they did this first time around and they and they said, Well, we could pack that much more We EMS on a on a hyper flex with rotating drives. And then they did it again And I said, Well, now that you got all flash Well, deacon, you got now the performance and the ladies see leadership and then they did it again and they said, Well, hang on, you you've kind of left the competition that does that. That's not going to make a pretty chart to show when we compare your all in Miami against your hyper so many. When you get that good, you compare against yourselves. We've been the performance theater on the estate has been doing the >> data obtained. The next generation added up, >> and this is what a database workload. OK, nowyou bringing obtain a little toast to the latest report >> has that measures >> measures obtain against are all flash report and then also ship or measure across vendors. So >> where can I get this? Is at some party or website or >> it's off all of this. All of this is off off the Cisco Hyper Flex website on artist go dot com. But F is the companies that want to go directly to their about getting a more >> I guess final final question for you is you know, I think back the early is ucs. It was the memory enhancements that they had that allowed the dentist virtual ization in the industry back when it started. It sounds like we're just taking that to the next level with this next generation of solutions. What what else would you out about? The relationship with Cisco and Intel? >> Eso, Intel and Cisco worked together for years right innovation around the CPU and the platform, and it's super exciting to be expanding our relationship to storage. And I'm even more excited that the Cisco hyper flex solution is endorsing Intel obtain and three thing and and we're seeing great examples of really use workloads where are in customers can benefit from this technology. >> Katie Laura. Thanks so much for the update. Congratulations on the progress that you've made so far for David Dante on Student, and we'll be back with more coverage here. It's just go live 2019 in San Diego. Thanks for watching the cue >> theme.

>> Live, from Barcelona, Spain it's theCUBE covering Cisco Live! Europe. Brought to you by Cisco and it's ecosystem partners. >> Welcome back to Barcelona everybody, this is theCUBE, the leader in live tech coverage. I'm Dave Vellante with my co-hosts. Stu Miniman, John Furrier has been here all week. Day three coverage of Cisco Live!, Barcelona. Cisco Live EMEA, and R. We learned the other day, add R for Russia. Kaustubh Das is back. KD is the vice president of product management for data center at Cisco and he's joined by Kevin Egan who is the director of the computer systems group for data center. Also from Cisco, gents, good to see you, welcome to theCUBE. >> Thank you. >> Great to be here. >> Thanks for having us. >> KD, Data center was a real focus of the announcements this week. The data center is exploding to a lot of different places. What's going on in the group? >> It's been a terrific weekend, you're right. Data center was a core of a lot of the announcements this week, and as we kicked off the key note with this concept that the data center is no longer centered. It's really, the data moves to the edges, the data center is moving to the edges. We had a lot of announcements around Hyperflex, Hyperflex anywhere, this product that we've been innovating on like monsters. Within a very short time, gone from a brand-new product on the market to a magic quarter liter with Gartner, and really kind of doing a lot of industry firsts with that. That's been a big focus. We had a lot of announcements with our technology partners, because we not only innovate within Cisco, but we work with Pure and NetApp and Citrix and Intel Optane and Nvidia to bring products to the market that get the richness of their innovation and our innovation together. The other big focus has been all about programmability. As the world becomes much more programmable, focus devops automation, it's been around Intersight and programmability and taking that to the next level. >> Interesting. So of course we always talk about shipping five megabytes of code as opposed to shipping petabytes through a straw into the god box. But so Kevin, programmability's a key theme here, of course we're in the devnet zone. We had Susie Wee on yesterday and she was just talking about the evolution of Cisco infrastructure and how early on you guys made the decision. Let's make all this stuff programmable. And that was sort of a game changer, your thoughts. >> Yeah, no it's been amazing. The growth of just Cisco devnet right? We've got half a million developers now developing against our SDKs, our devops, our opportunities all across our Cisco platforms. We've got thousands of Cisco resources doing work on that, producing those libraries, producing that, those sample sets of code and contributing to the communities. And today our customers are using it in a way that they've never really done. Previously it was a sort of a fix because vendor tools weren't getting it done. And now they're using these automation tools to really do every day tasks out to the mass, to reduce the complexity for their teams and reduce the burden. And then of course to have that repeatability and that security and that compliance aspect and it's been amazing the explosion. >> Yeah. The simplicity reminds me back you know the earliest days of UCS, you know UCS was built for that wave of virtualization and as KD has talked with us this week already about some of the partnerships that you've built. The wave of converged infrastructure, UCS really dominated in that marketplace, but here now we talk about AI with some of your partners, you talk about programmability, it's like that's not the Cisco UCS that I remember launching. So maybe give us the updates specifically that was announced this week. Where the platform has gone in more recent days. >> So I can start maybe, >> Yeah, absolutely. >> UCS came up with this concept of everything needs to be programmable, everything needs to be an API. And maybe we were a little ahead of our time, we conceived of this in 2007, got the product out in 09 and really from the very genesis of the program, of the UCS program, it's been a programmable platform, it's been everything's an API. The UI makes calls to the API, our SDKs make calls to the APIs. So that's been the core platform and in some ways it feels like the industry is coming to where we thought it would come to a little bit earlier. So they, this whole concept of infrastructure's code, softly defined what do we want to call it, this was core and germane to the product itself. What we've done lately is, it's taken that policy that we're encapsulated and taken out all of the silver into the fabric for scalability, we've taken that now into the cloud. And what that does is it leads to that velocity of innovation becoming even higher, the ability to create new and unique use cases becomes higher, the ability to conceive it becomes higher. And all of that coupled with where IT is going, which is becoming much more devops, much more around automation. I think those forces are coupling together to create some really unique use cases. >> You said, you gestured take it into the cloud, which is interesting, pointing. What does that mean? Taking it into the cloud? >> So let's speed back a little bit. So what we start off with was listen, a silver's a box, we need to abstract the silver, the personality of the silver out of that box into policy, put it in the fabric. And that allows us to really scale that and give the box different personalities depending upon the workload. What we've done is, we've launched a product called Intersight. Intersight takes that policy and makes it a SAS service, management of the service we want to call it. So now as data moves everywhere, as data centers move everywhere, as our applications no longer become monolithic but become these combinations of little applications communicating across data centers, it allows us to have a centralized dashboard for our infrastructure that we can access, because it's in the cloud, from anywhere. And because it's in the cloud it can kind of get, get that innovation wheel turning much faster. It's just been game changing, and obviously there's other things that can happen once you do that. You can have proactive guidance coming down from the cloud, you can have golden images come down from the cloud, you can do workload specific settings. So there's a lot of new areas that it opens up once you, >> Analytics, right? >> Analytics. >> Machine intelligence. >> So we've got the takeover happening in the devnet zone right now, so focus on the data center, everybody's got t shirts and I think it says Hyperflex on them, big announcement this week about Hyperflex anywhere. Kevin you know I think that when people heard HCI, they often picture a box, or it's a group of boxes it's in a rack, it's all that and everything, and the thing is as an analyst I was poking at it, it's like "well we virtualized a lot of the stuff "and we put it in a new form factor." That's great to modernize the platform but how do we make it cloud native, how does it fit into a hybrid and multi cloud world, and it feels like we're reaching that point now. So help us connect the dots as to how, what HCI was fits into this hybrid and multi cloud world today. >> Absolutely. I mean, HCI when it came out was an alternative to SAN, I mean it was an alternative and it was touting simplicity, touting you know grow with your applications. But really now, with the multi cloud instances that our customers are looking at, they have to have a way to deploy those, a way to connect to those remotely, manage those, monitor those, actually connect that back to the core so that you can take advantage of the analytics that are running at the core and make real time recommendations, make real time adjustments for services and those type of, you know that connectivity is really what we mean by Hyperflex anywhere. It's the evolution of how you deploy, how you manage, and then of course that day two, day five, day one hundred where you're actually making that experience simple for the customers. >> Help us understand exactly, is this, do I just have the backup image in a public cloud, do I actually have similar software stacks, what's the expanse? >> Let me try to unpack that a little bit. I think it's three different vectors that we're doing. So we want as we modernize, and as our customers modernize, they're looking for a much more cloud-like limber, elastic platform. That's the first vector, that's what HCI has done, that's what we've done. And we've actually done it on steroids because we've taken that code-designed hardware and software much like the public cloud guys are doing, but we control that and we can give that to our enterprise customers and our enterprise grade resilient infrastructure. The first thing is that, the second piece of it is what our customers and really our developers and the customers are wanting to do, is to create in one place and deploy in another. So create on the private cloud, deploy in the public cloud, or create in the public cloud, deploy in the private cloud, or actually have an application that bridges the two. So having a homogenous development environment whether it's, and a lot of this is around the container frameworks, whether it's on the public cloud, private cloud. That's key, and what we've done with Hyperflex, and the integrations we've got with our container platform, with open shift, with cloud center, which was again a big announcement this week. That's that second vector, is being able to port applications, develop one place, deploy any place. And the third piece is what we've been talking about all through this segment, which is the ability to now have the cloud drive your infrastructure. Everything's connected, everything's analyzed in the cloud, there's telemetry, there's proactive guidance, there's a common dashboard there's centralized monitoring, there's the ability to deploy, like we did in the key note demonstrating in the key note, multiple different sides spread out across the world, from a cental location. I think that's game changing. >> I'd like to get your take on differentiation. Obviously you guys are biased. Cisco's different, it's better. But I want to hear why. So relative to other infrastructure players, are you, in your words, however you want to describe it more cloud like more programmable, where's the differentiation? >> Go ahead and I'll later on. >> Yeah sure. So basically we started with a foundation of UCS and that foundation, virtualize compute bare metal compute, and of course now hyper-converge, and the reason that it allows us to do things, allows us to Hyperflex anywhere, allows us to have that cloud-based model is because we built that infrastructure around the API from day one. When we started this, that programmatic infrastructure, we were talking to customers, it was stateless it was desired state config, they didn't know what we were talking about. I mean, they had no idea when this came out. But that's the foundation that really allows us to drive the API integrations to our app layers, which is what KD was talking about, and then of course from there to our multi cloud integrations and that's really the foundation that laid, that we laid early on. And that's why all of our UCS platform really enables this cloud integration. >> Yeah, I mean the way I look at it is nobody else has a fully API driven infrastructure. Everything's an API for us, we don't expose APIs after the fact, it is built around, it's an API first infrastructure. And everything is built around them. Whether it's our STKs, our integrations with you know Pop and then Ansible, and those kind of tool sets, our integration with other tool sets that people use. It's all driven through that. The second thing that is different is, we have an emulator, so we can allow our customers to really time travel through the whole process of deployment. I mean, our customers can deploy the infrastructure before the infrastructure hits the loading dock because they can download the UCS emulator. They can actually configure, deploy, build the whole policy on our management platform, test it out, do the what ifs on the emulator. When the equipment shows up, we're ready to go, we are in business, nobody else can do that. And the final thing which is, aside from all of the cloud connected pieces I've talked about, the breadth of Cisco's portfolio spanning from all of our networking assets, our SD WAN assets, our security assets, our collaboration assets, our cloud assets, that breadth gets us to implement use cases for our customers that are just, it's just impossible for anybody else to do. >> We've heard lots of proof points here in the devnote zone specifically from programmability and the automation. I've talked to some service providers here at the show, we've also heard about the journey that enterprise customers are going through to kind of understand that space and learn places here like this. Kevin, I'm sure you're talking to a lot of customers here, maybe if you have examples as to you know the exemplars of who're doing this well, and what people can learn from customers like that. >> Yeah, I mean it's amazing right. In just devnet alone we've got sessions on UCS with Python, STKs, UCS with Powertool, how to integrate with Ansible, these are just becoming common terms, common household terms for our customers. As you go up to enterprise customers, service provider customers, they're using these tools in a day to day manner to do the automation on top of, to really deploy and manage their apps, right, and the way that, I mean, it's exciting, we have customers from all segments of all industry, and they really they use these programmatic, KD's simple example of platform emulator, you don't realize how powerful that is, where you can set that same exact state machine that's in your UCS, you can put it on your laptop, set up all your policies, and then when that gear hits the dock, you are up in hours. Literally we have very large e-commerce sites, they do this, thousands of servers hit it, and in a matter of hours, they've applied those policies and they're up and running. Python, we've got Python, Ruby, Powertool, software developer kits, we've got devops that sit on those, and Ansible, Puppet, Chef, and these are just the automation so if you want to do it yourself, we've got the world class API, nobody else gives you that programmatic API. That's how we built our foundation. If you want Cisco to call those APIs, we have Intersight and we'll make those calls for you. If you just want to do some simple scripting, Powertool. You can automate certain processes, it doesn't have to be the whole end to end. You know you can use all these, it's basically choice to really, what your applications are demanding and what your customers are demanding. >> That's a strong story, one of breadth and depth. We're out of time, but KD I wonder if you could sort of put a bow on Cisco Live! Europe this year, big takeaways from your point of view. >> Listen, we've been innovating like monsters and it's such a terrific week for us to come here, to really touch and feel and listen to our customers and see the delight on their faces as we show them what we've been doing. And this part of the show, day three the devnet takeover, this is where it gets really really real, because now we get to go down to the depths of looking at those APIs, looking at those use cases, getting people to play around with them. So it's just been terrific, I love it. >> I love it too, we're the interview monsters this week. So guys thanks very much for coming on theCUBE. >> Thanks for having us. >> You're welcome. Alright keep it right there everybody, we'll be back with our next guest right after this short break. You're watching theCUBE from Cicso Live! In Barcelona. Be right back. (upbeat electronic outro)

>> Live from Barcelona, Spain, it's theCUBE, covering Cisco Live Europe. Brought to you by Cisco and its ecosystem partners. >> Welcome back to Barcelona, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. I'm here with my cohost, Stu Miniman. This is day one of Cisco Live Barcelona. Katie Colbert is here. She's the vice president of alliances at Pure Storage, and she's joined by Kaustubh Das, otherwise known as KD, who's the vice president of computing systems at Cisco. Katie and KD, welcome to theCUBE, good to see you. >> Thank you. >> Thank you. >> Alright, so let's start off, KD2, if you could just tell us about the partnership. Where did it start, how did it evolve? We'll get into it. >> We just had a terrific partnership, and the reason it's so great is it's really based on some foundational things that are super compatible. Pure Storage, Cisco, both super technology-driven companies, innovating. They're both also super programmatic companies. They'll do everything via API. It's very modern in that sense, the frameworks that we work on. And then from a business perspective, it's very compatible. We're chasing common markets, very few conflicts. So it's been rooted in solid foundations. And then, we've actually invested over the years to build more and more solutions for our customers jointly. So it's been terrific. >> So, Katie, I hate to admit how long we talk about partnering with Cisco >> It's going to age us. >> So you and I won't admit how many decades it's been partnering with Cisco, but here we are, 2019, Cisco's a very different company than it was a decade or two ago. >> Absolutely. >> Tell me what it's like working with them, especially as a company that's primarily in storage and data at Pure, what it means to partner with them. >> Absolutely, you're right. So, worked with Cisco as a partner for many years at the beginning of my career, then went away for, I'd say, a good 10 years, and joined Pure in June, and I will tell you one of the most exciting reasons why I joined Pure was the Pure and Cisco relationship. When I worked with them at the beginning of my career, it was great and I would tell you it's even better now. I will say that the momentum that these two companies have in the market is very phenomenal. A lot of differentiation from our products separately, but both together, I think that it's absolutely been very successful, and to KD's point, the investment that both companies are making really is just astronomical, and I see that our customers are the beneficiaries of that. It makes it so much easier for them to deploy and use the technologies together, which is exciting. >> So we always joke about Barney deals, I love you, you love me, I mean, it's clear you guys go much much deeper than that. So I want to probe at that a little bit. Particularly from an engineering standpoint, whether it's validated designs or other innovations that you guys are working on together, can we peel the onion on that one a little bit? Talk about what you guys are doing below that line. >> I'll start there then I'll hand it over to the engineering leader from Cisco. But if you think about the pace of this, the partnership, I think, is roughly 3 or so years old. We've 16 Cisco-validated designs for our FlashStack infrastructure. So that is just unbelievable. So, huge amount of investment from engineers, product managers, on both sides of the fence. >> Yeah, totally second that. We start out with the... Cisco-validated designs are like blueprints, so we start out with the blueprints for the standard workloads: Oracle, SAP. And we keep those fresh as new versions come out. But then I think we've taken it further into new spaces of late. ACI, we saw in the keynote this morning, it's going everywhere, it's going multi-site. We've done some work on marrying that with the clustering service of Pure Storage. On top of that, we're doing some work in AI and ML, which is super exciting, so we got some CBDs around that that's just coming out. We're doing some work on automation, coupling Intersight, which is Cisco's cloud-based automation suite, with Pure Storage and Pure Storage's ability to integrate into the Intersight APIs. We talked about it, in fact, I talked about it in my session at the Cisco Live in the summer last year, and now we've got that out as a product. So tremendous amount of work, both in traditional areas as well as some of these new spaces. >> Maybe we can unpack that Intersight piece a bit, because people might look at it initially and say, "Okay, multi-cloud, on-prem, all these environments, "but is this just a networking tool?" And working we're working with someone with Pure, maybe explain a little bit the scope and how, if I'm a Pure administrator, how I live into this world. >> Absolutely, so let's start with what is Intersight, just for a foundational thing. Intersight is our software management tool driven from the cloud. So everything from the personality of the server, the bios settings, the WLAN settings, the networking and the compute pieces of it, that gets administered from the cloud, but it does more. What it does is it can deliver playbooks from the cloud that give the server a certain kind of personality for the workload that it's supporting. So then the next question that anyone asks is, "Now that we have this partnership, "well can it do the same thing for storage? "Can it actually provision that storage, "get that up and running?" And the answer is yes, it can, but it's better because what it can not only do is, not only can it do that, getting that done is super simple. All Pure Storage needed to do was to write some of those Intersight APIs and deliver that playbook from the cloud, from a remote location potentially, into whatever your infrastructure is, provisioning compute, provisioning networking, provisioning storage, in a truly modern cloud-driven environment, right? So I think that's phenomenal what it does for our customers. >> Yeah, I'd agree with that. And I think it'll even become more important as the companies are partnering around our multi-cloud solutions. So, as you probably saw earlier this year in February, sorry, the end of 2018, Pure announced our first leaning into hybrid cloud, so that's Pure Cloud Data Services. That enables us to have Purity, which is our operating system on our storage, running in AWS to begin with. So you can pretty easily start to think about where this partnership is going to go, especially as it pertains to Intersight integration. >> And just to bounce on that, strategically, you can see the alignment there as well. I mean, Cisco's been talking about multi-cloud for a bit now, we've done work to enable similar development environments, whether we're doing something on-prem or in the cloud, so that you can move workloads from one to the other, or actually you can make workloads on both sides talk to each other, and, again, combined with what Katie just said, it makes it a really really compelling solution. >> Like you said, you've got pretty clear swimming lanes for the two companies. There's very little overlap here. You can't have too many of these types of partnerships, right, I mean, you got 25 thousand engineers almost, but still, you still have limited resources. So what makes this one so special, and why are you able to spend so much time and effort, each of you? >> I could start, so from a Pure perspective, I think the cultures are aligned, you called it out there, there's inherently not a lot of overlap in terms of where core competencies are. Pure is not looking at all to become a networking company. And just a lot of synergies in the market make it one that our engineers want to invest in. We have really picked Cisco as our lean-in partner, truthfully, I run all of the alliances at Pure, and a lion's share of my resources really are focused at that partnership. >> Yeah, and if you look at both these companies, Pure is a relative youngster among the storage companies, a new, modern, in a good way, a new, modern company built on modern software practices and so forth. Cisco, although a pretty veteran company, but Cisco compute is relatively new as well as a compute provider. So we are very similar in how our design philosophies work and how modern our infrastructures are, and that gets us to delivering results, delivering solutions to our customers with relatively less effort from our engineers. And that pace of innovation that we can do with Pure is not something we can do with every other company. >> We had a session earlier today, and we went pretty deep into AI, but it's probably worth touching on that. I guess my question here is, what are the customers asking you guys for in terms of AI infrastructure? What's that infrastructure look like that's powering the machine and intelligence era? >> You want to start? >> You want to go, I'll go first. This is a really exciting space, and not only is it exciting because AI is exciting, it's actually exciting because we've got some unique ingredients across Pure and Cisco to make this happen. What does AI feed on? AI feeds on data. The model requires that volume of data to actually train itself We've got an infrastructure, so we just released the C4ATML, the UCC4ATML, highly powered infrastructure, eight GPUs, interconnected, 180 terabytes on board, high network bandwidth, but it needs something to feed it the data, and what Pure's got with their FlashBlade is that ability to actually feed data to this AI infrastructure so that we can train bigger models or train these models faster. Makes for a fantastic solution because these ingredients are just custom made for each other. >> Anything you can add? >> Absolutely I'd agree with that. Really, if you look at AI and what it needs to be successful, and, first of all, all of our customers, if they're not thinking about it, they should be, and I will tell you most of them are, is, how do you ingest that amount of data? If you can't ingest that quickly, it's not going to be of use. So that's a big piece of it, and that's really what the new Cisco platform, I mean, the folks over at Pure are just thrilled about the new Cisco product, and then you take a look at the FlashBlade and how it's able to really scale out unstructured data, object it and file, really to make that useful, so when you have to scrub that data to be able to use it and correlate it, FlashBlade is the perfect solution. So really, this is two companies coming together with the best of breed technologies. >> And the tooling in that world is exploding, open source innovation, it needs a place to run all the Kafkas and the Caffes and the TensorFlows and the Pythons. It's not just confined to data scientists anymore. It's really starting to seep throughout the organization, are you seeing that? >> Yeah. >> What's happening is you've got the buzzwords going around, and that leads to businesses and the leaders of businesses saying, "We've got to have an AI strategy. "We've got to hire these data scientists." But at the same time, the data scientists can get started on the laptop, they can get started on the cloud. When they want to deploy this, they need an enterprise class, resilient, automated infrastructure that fits into the way they do their work. You've got to have something that's built on these components, so what we provide together is that infrastructure for the ITTs so that the data scientists, when they build their beautiful models, have a place to deploy them, have a place to put that into production, and can actually have that life cycle running in a much more smooth production-grade environment. >> Okay, so you guys are three years in, roughly. Where do you want to take this thing, what's the vision? Give us a little road map for the future as to what this partnership looks like down the road. >> Yeah, so I can start. So I think there's a few different vectors. We're going to continue driving the infrastructure for the traditional workloads. That's it, that's a big piece that we do, we continue doing that. We're going to drive a lot more on the automation side, I think there's such a lot of potential with what we've got on Intersight, with the automation that Pure supports, bring those together and really make it simple for our customers to get this up and running and manage that life cycle. And third vector's going to be imparting those new use cases, whether it be AI or more data analytics type use cases. There's a lot of potential that it unleashes for our customers and there's a lot of potential of bringing these technologies together to partner. So you'll see a lot more of that from us. I don't know, will you add something? >> Yeah, no, I absolutely agree. And I would say more FlashStack, look for more FlashStack CVDs, and AI, I think, is one to watch. We believe Cisco, really, this step that Cisco's made, is going to take AI infrastructure to the next level. So we're going to be investing much more heavily into that. And then cloud, from a hybrid cloud, how do these two companies leverage FlashStack and all the innovation we've done on prem together to really enable the multi-cloud. >> Great, alright, well Katie and KD, thanks so much for coming to theCUBE. It was great to have you. >> Great. Thanks for having us. >> Thank you very much. >> You're welcome, alright. Keep it right there everybody. Stu and I will be back with our next guest right after this short break. You're watching theCUBE Live from Cisco Live Barcelona. We'll be right back. (techy music)

>> Live from Barcelona, Spain, it's The Cube, covering Cisco Live Europe. Brought to you by Cisco and its ecosystem partners. >> Welcome back to Barcelona, everybody. You're watching The Cube, the leader in live tech coverage. My name is Dave Vellante. I'm here with my cohost, Stu Miniman. This is day one of Cisco Live Barcelona. Katie Colbert is here. She's the vice president of alliances at Pure Storage, and she's joined by Kaustubh Das, otherwise known as KD, who's the vice president of computing systems at Cisco. Katie and KD, welcome to The Cube, good to see you. >> Thank you. >> Thank you. >> Alright, so let's start off, KD2, if you could just tell us about the partnership. Where did it start, how did it evolve? We'll get into it. >> We just had a terrific partnership, and the reason it's so great is it's really based on some foundational things that are super compatible. Pure Storage, Cisco, both super technology-driven companies, innovating. They're both also super programmatic companies. They'll do everything via API. It's very modern in that sense, the frameworks that we work on. And then from a business perspective, it's very compatible. We're chasing common markets, very few conflicts. So it's been rooted in solid foundations. And then, we've actually invested over the years to build more and more solutions for our customers jointly. So it's been terrific. >> So, Katie, I hate to admit how long we talk about partnering with Cisco >> It's going to age us. >> So you and I won't admit how many decades it's been partnering with Cisco, but here we are, 2019, Cisco's a very different company than it was a decade or two ago. >> Absolutely. >> Tell me what it's like working with them, especially as a company that's primarily in storage and data at Pure, what it means to partner with them. >> Absolutely, you're right. So, worked with Cisco as a partner for many years at the beginning of my career, then went away for, I'd say, a good 10 years, and joined Pure in June, and I will tell you one of the most exciting reasons why I joined Pure was the Pure and Cisco relationship. When I worked with them at the beginning of my career, it was great and I would tell you it's even better now. I will say that the momentum that these two companies have in the market is very phenomenal. A lot of differentiation from our products separately, but both together, I think that it's absolutely been very successful, and to KD's point, the investment that both companies are making really is just astronomical, and I see that our customers are the beneficiaries of that. It makes it so much easier for them to deploy and use the technologies together, which is exciting. >> So we always joke about Barney deals, I love you, you love me, I mean, it's clear you guys go much much deeper than that. So I want to probe at that a little bit. Particularly from an engineering standpoint, whether it's validated designs or other innovations that you guys are working on together, can we peel the onion on that one a little bit? Talk about what you guys are doing below that line. >> I'll start there then I'll hand it over to the engineering leader from Cisco. But if you think about the pace of this, the partnership, I think, is roughly 3 or so years old. We've 16 Cisco-validated designs for our FlashStack infrastructure. So that is just unbelievable. So, huge amount of investment from engineers, product managers, on both sides of the fence. >> Yeah, totally second that. We start out with the... Cisco-validated designs are like blueprints, so we start out with the blueprints for the standard workloads: Oracle, SAP. And we keep those fresh as new versions come out. But then I think we've taken it further into new spaces of late. ACI, we saw in the keynote this morning, it's going everywhere, it's going multi-site. We've done some work on marrying that with the clustering service of Pure Storage. On top of that, we're doing some work in AI and ML, which is super exciting, so we got some CBDs around that that's just coming out. We're doing some work on automation, coupling Intersight, which is Cisco's cloud-based automation suite, with Pure Storage and Pure Storage's ability to integrate into the Intersight APIs. We talked about it, in fact, I talked about it in my session at the Cisco Live in the summer last year, and now we've got that out as a product. So tremendous amount of work, both in traditional areas as well as some of these new spaces. >> Maybe we can unpack that Intersight piece a bit, because people might look at it initially and say, "Okay, multi-cloud, on-prem, all these environments, "but is this just a networking tool?" And working we're working with someone with Pure, maybe explain a little bit the scope and how, if I'm a Pure administrator, how I live into this world. >> Absolutely, so let's start with what is Intersight, just for a foundational thing. Intersight is our software management tool driven from the cloud. So everything from the personality of the server, the bios settings, the WLAN settings, the networking and the compute pieces of it, that gets administered from the cloud, but it does more. What it does is it can deliver playbooks from the cloud that give the server a certain kind of personality for the workload that it's supporting. So then the next question that anyone asks is, "Now that we have this partnership, "well can it do the same thing for storage? "Can it actually provision that storage, "get that up and running?" And the answer is yes, it can, but it's better because what it can not only do is, not only can it do that, getting that done is super simple. All Pure Storage needed to do was to write some of those Intersight APIs and deliver that playbook from the cloud, from a remote location potentially, into whatever your infrastructure is, provisioning compute, provisioning networking, provisioning storage, in a truly modern cloud-driven environment, right? So I think that's phenomenal what it does for our customers. >> Yeah, I'd agree with that. And I think it'll even become more important as the companies are partnering around our multi-cloud solutions. So, as you probably saw earlier this year in February, sorry, the end of 2018, Pure announced our first leaning into hybrid cloud, so that's Pure Cloud Data Services. That enables us to have Purity, which is our operating system on our storage, running in AWS to begin with. So you can pretty easily start to think about where this partnership is going to go, especially as it pertains to Intersight integration. >> And just to bounce on that, strategically, you can see the alignment there as well. I mean, Cisco's been talking about multi-cloud for a bit now, we've done work to enable similar development environments, whether we're doing something on-prem or in the cloud, so that you can move workloads from one to the other, or actually you can make workloads on both sides talk to each other, and, again, combined with what Katie just said, it makes it a really really compelling solution. >> Like you said, you've got pretty clear swimming lanes for the two companies. There's very little overlap here. You can't have too many of these types of partnerships, right, I mean, you got 25 thousand engineers almost, but still, you still have limited resources. So what makes this one so special, and why are you able to spend so much time and effort, each of you? >> I could start, so from a Pure perspective, I think the cultures are aligned, you called it out there, there's inherently not a lot of overlap in terms of where core competencies are. Pure is not looking at all to become a networking company. And just a lot of synergies in the market make it one that our engineers want to invest in. We have really picked Cisco as our lean-in partner, truthfully, I run all of the alliances at Pure, and a lion's share of my resources really are focused at that partnership. >> Yeah, and if you look at both these companies, Pure is a relative youngster among the storage companies, a new, modern, in a good way, a new, modern company built on modern software practices and so forth. Cisco, although a pretty veteran company, but Cisco compute is relatively new as well as a compute provider. So we are very similar in how our design philosophies work and how modern our infrastructures are, and that gets us to delivering results, delivering solutions to our customers with relatively less effort from our engineers. And that pace of innovation that we can do with Pure is not something we can do with every other company. >> We had a session earlier today, and we went pretty deep into AI, but it's probably worth touching on that. I guess my question here is, what are the customers asking you guys for in terms of AI infrastructure? What's that infrastructure look like that's powering the machine and intelligence era? >> You want to start? >> You want to go, I'll go first. This is a really exciting space, and not only is it exciting because AI is exciting, it's actually exciting because we've got some unique ingredients across Pure and Cisco to make this happen. What does AI feed on? AI feeds on data. The model requires that volume of data to actually train itself We've got an infrastructure, so we just released the C4ATML, the UCC4ATML, highly powered infrastructure, eight GPUs, interconnected, 180 terabytes on board, high network bandwidth, but it needs something to feed it the data, and what Pure's got with their FlashBlade is that ability to actually feed data to this AI infrastructure so that we can train bigger models or train these models faster. Makes for a fantastic solution because these ingredients are just custom made for each other. >> Anything you can add? >> Absolutely I'd agree with that. Really, if you look at AI and what it needs to be successful, and, first of all, all of our customers, if they're not thinking about it, they should be, and I will tell you most of them are, is, how do you ingest that amount of data? If you can't ingest that quickly, it's not going to be of use. So that's a big piece of it, and that's really what the new Cisco platform, I mean, the folks over at Pure are just thrilled about the new Cisco product, and then you take a look at the FlashBlade and how it's able to really scale out unstructured data, object it and file, really to make that useful, so when you have to scrub that data to be able to use it and correlate it, FlashBlade is the perfect solution. So really, this is two companies coming together with the best of breed technologies. >> And the tooling in that world is exploding, open source innovation, it needs a place to run all the Kafkas and the Caffes and the TensorFlows and the Pythons. It's not just confined to data scientists anymore. It's really starting to seep throughout the organization, are you seeing that? >> Yeah. >> What's happening is you've got the buzzwords going around, and that leads to businesses and the leaders of businesses saying, "We've got to have an AI strategy. "We've got to hire these data scientists." But at the same time, the data scientists can get started on the laptop, they can get started on the cloud. When they want to deploy this, they need an enterprise class, resilient, automated infrastructure that fits into the way they do their work. You've got to have something that's built on these components, so what we provide together is that infrastructure for the ITTs so that the data scientists, when they build their beautiful models, have a place to deploy them, have a place to put that into production, and can actually have that life cycle running in a much more smooth production-grade environment. >> Okay, so you guys are three years in, roughly. Where do you want to take this thing, what's the vision? Give us a little road map for the future as to what this partnership looks like down the road. >> Yeah, so I can start. So I think there's a few different vectors. We're going to continue driving the infrastructure for the traditional workloads. That's it, that's a big piece that we do, we continue doing that. We're going to drive a lot more on the automation side, I think there's such a lot of potential with what we've got on Intersight, with the automation that Pure supports, bring those together and really make it simple for our customers to get this up and running and manage that life cycle. And third vector's going to be imparting those new use cases, whether it be AI or more data analytics type use cases. There's a lot of potential that it unleashes for our customers and there's a lot of potential of bringing these technologies together to partner. So you'll see a lot more of that from us. I don't know, will you add something? >> Yeah, no, I absolutely agree. And I would say more FlashStack, look for more FlashStack CVDs, and AI, I think, is one to watch. We believe Cisco, really, this step that Cisco's made, is going to take AI infrastructure to the next level. So we're going to be investing much more heavily into that. And then cloud, from a hybrid cloud, how do these two companies leverage FlashStack and all the innovation we've done on prem together to really enable the multi-cloud. >> Great, alright, well Katie and KD, thanks so much for coming to The Cube. It was great to have you. >> Great. Thanks for having us. >> Thank you very much. >> You're welcome, alright. Keep it right there everybody. Stu and I will be back with our next guest right after this short break. You're watching The Cube Live from Cisco Live Barcelona. We'll be right back. (techy music)

>> Announcer: Live, from Las Vegas, it's the Cube. Covering Dell Technologies World 2018. Brought to you by Dell EMC and it's ecosystem partners. >> And welcome back live here on the Cube as we continue our coverage of Dell Technologies World 2018. We're live at the Sands and it is now my pleasure for the first time today to say, "My partner's Stu Miniman". Stu, how you been? >> Awesome John, great to be talking on the Cube with you and our great guest. >> It's been too long, that's for sure! Good to see you again. We're joined by Manuvir Das who's the senior vice-president GM of unstructured data at Dell EMC. Thanks for being with us. We appreciate it. >> It's my pleasure to be here. >> Let's talk about your world, this exponential growth, this unpredictable growth, all this unstructured data, and now it's worth something, right? >> Yes, it is. >> So people are turning out to realize what an asset, what a resource that it's become. >> In fact, it's funny you say "Asset" because, the whole theme and tagline for my team is data capital, because I think people are coming to realize that just like you have capital assets in your factories and your people, data is part of the capital of a company now, right? And you really need to turn it into something, so I think it's an exciting time. For my team, we basically work in file and object storage, Isilon has been a market leader for some time. We have an object storage product called ECS, and we are the market leader, and we have been for some time, but it's a very interesting time because data is growing so greatly now that the leader today can be a nobody five years from now, right? So, what I tell my team every day is how are we going to disrupt ourselves before we get disrupted so that we can still be the leader five years from now when that exponential growth has continued, right? So that's what we do every day. We think about what are the ways, on behalf of the customer, the world of unstructured storage is being disrupted and how are we going to be there on the other side with the customer? >> Manuvir, I'm wondering if you could bring us inside the customers 'cuz we've been talking about unstructured data at least five years. Data data everywhere, but how is it changing customers' lives? How is it changing their businesses? What's the update on the customer's viewpoint on unstructured data? >> So, we have an interesting perspective because our business really grew up with working with specific verticals. Like media, entertainment, life sciences, automotive, and we see that there. For example, in the automotive industry, we have a lot of customers that are doing Adax and so they're basically driving vehicles around, capturing videos of a child running across the street, of a bicycle on the road, and they're bringing all that data back to our storage system so that they can train their software that runs the car, so that when the situation happens in real life, the software does the right thing, right? In media entertainment now, with 4K streaming and more and more digitized movies, how do you produce these movies, right? How does Pixar and everybody produce these movies? In life sciences, it's all about Genomix. It's started in the research domain with Genomix, and now it's going into hospitals where people want to use Genomix to make real-time decisions about what to do for their patients. And these are all ways in which these existing industries are really using unstructured data now as their lifeblood to change their business. So, it's an interesting change, really. >> You mentioned five years from now, we want to make sure that we're the disruptor, and I read a number that by five years out, all data or unstructured data, will be 93% of all data, So that kind of growth when you see that mushroom occurring, does that put a little fear, does that put the challenge? >> It's a great opportunity, right? It's a great opportunity, and it's an opportunity not just for us at Dell EMC, right? It's an opportunity for everybody. The public cloud vendors, start-ups, and our only interest is, let's take the customer to the right place, and if we can participate in that in some way, I believe there are opportunities so big, that we will be happy with whatever share of it we have. As long as the customer gets what they need. And I think every customer's going to have some mix of On-Premises storage, appliances, software defined storage, storage in the public cloud. It'll all sort of come together and I think we have a role to play, right? If I may, there's really four things we see about how the data is changing say from now to five years from now. The first thing is Flash, right? Flash is no longer just for high-end storage. Flash is everywhere in storage. The second thing is the public cloud. More and more data going into the public cloud. The fourth thing is analytics. Who is going to pay to store all of this data unless they can actually put it to use, right? And so, how do you provide the analytics? And then the fourth thing is archiving because the truth of the matter is, when you expand your data at that scale, most of the data is not useful at any point in time. It may be useful tomorrow, but it's not useful today. So how do you use technologies like optic storage to really economically store the bulk of the data? So these are the four trends we see, flash, the public cloud, analytics, and advent of object, and everything we're doing at Dell EMC with unstructured storage, is to embrace these four trends. So that we can come out the other side with the customer on these. >> There was one thing that caught my ear during the keynote this morning, there were many things that stood out, but one of them I could have sworn Michael said something about Isilon. We've googled cloud, and I'm googling, I'm looking around, obviously object storage, I think very much in the public crowd, seeing growth elsewhere, but maybe you can explain what that is and what's going on. >> So this is an Isilon file storage, is now available for customer's of Google in the Google Cloud. So, for years our customers have used Isilon On-Premise because it's really the only solution in the market where you can get a very large file system that performs well. You don't have this technology in the public cloud today. And, we have all these customers who run their workloads on prem using Isilon. And they're looking to use the computer in the public cloud, but if they don't have Isilon there, they would have to re-write their application. So, we worked out a model with Google where we host our Isilon gear, our physical Isilon clusters in the same place where Google has their cloud, and their compute, so now a customer can run their application, on the compute VMs of Google cloud, but they have some millisecond access to an Isilon cluster that is dedicated to them that is right there. So in this way, they can take the journey to the public cloud, but not have to change their application because they still use Isilon. So, this is the model we came up with. We just launched it, so that's what Michael was referring to. We're very excited about it. I think it's really an opportunity for the customer to embrace the cloud, and the thing I'm trying to tell every customer that we have because we've been on premises for a long time, is "Look, I believe in the public cloud." I actually worked on building one of those at Microsoft years ago, and all we want is, we want to help the customers get to the public cloud by giving them the same technology there, that they've had On-Premise. And, so I think everybody wins. >> Yeah, that's exciting. Thank you so much for going through that. Your team, it's up there in Seattle, so much going on. Have there been customers on beta on this? Is this available now? Give some of the speeds and feeds. >> So, in the cloud terminology, people usually start with a what they call a tech preview or an early adoptive program, so that's where we're at right now. We have the first customer already running operational on it, and they will talking about it in some of our breakout sessions as well, so we're in the early the adoptive program right now, so anybody's that's interested can join the early adoptive program. It's fully operational, but we're sort of controlling how many customers adopt it first, and then we expand from there. >> Look at the, if you would, the risk side of this, with all that data, it's a treasure trove in some respects to a company, but it's also a very alluring target. So from a security standpoint, what kind of emphasis are you shifting towards that, knowing that you have that much more waterfront to cover now? >> I think it is the key issue really, and so that's why, even John in this move to the public cloud, that we just talked about, we have not done this as some kind of multi-tenant, shared kind of environment. Every customer has a dedicated environment, their Isilon is in a cage, everybody can't get into that cage, and all the security protocols are in place. So that's a very important aspect of this. And then whether it's in the cloud or On-Premise, they're constantly raising the bar on the security protections. How does the data flow internally between the servers in the cluster? Everything's encrypted, authenticated, protected, so I think that is really the key issue going forward. Well, I know it's a challenge, but as you said, it's also an opportunity. So, good luck meeting the challenge, and I hope five years from now, we're still talking about you. >> Yes, we'll see where we are. >> Hey, how do you like the music, by the way? >> Uh, it's great. >> It's a little loud. >> That's right, a little loud. >> Manuvir, thanks for being with us. >> Sure my pleasure. >> We'll continue from a floor that's starting to get a little more energy to it. Here live at the Sands, we are at Dell Technologies World 2018.

>> Announcer: Live From Las Vegas, it's The Cube, covering Dell EMC World 2017. Brought to you by Dell EMC. >> Hey, welcome back everyone. We're here live in Las Vegas for Dell EMC World 2017. This is The Cube, I'm John Furrier with my co-host, Paul Gillin. And our next guest Manuvir Das, Senior Vice President of Product Management, Dell EMC, former Microsoft Asure, historic role at Microsoft, been at the EMC for a few years. Welcome to The Cube, good to see you. >> Thank you, it's nice to be here. >> So the last year we had a conversation. We were talking about some of the technology and the kind of direction it was going, so first question is from last year to this year, what's changed and what's the news? >> We've brought together two pretty well-known platforms that we did, Isilon for Scalar file and ECS for Scalar object. It one team that are now around called the Unstructured Data Storage Team. And we've done this really big because from the point of view of the customer, what we see is this confluence between file and object really in the space of unstructured storage, and we think we have some ideas of how to put that together in just the right solution for the customer. So that's why we brought these teams together and we've got a lot of great stuff to talk about this year. >> How are you positioning file versus object right now? It seems like object is the rage, but file is still going to be around for a long time. How do you position that? >> Yes, I think it will be. I think basically, if I may, it's not just two, but we see three pillars of unstructured storage. The first is file, which is really more towards compatibility with traditional workloads. A lot of the application ecosystem is comfortable programming against NFS or SMB, and that ecosystem is going to remain for a long time. For instance, in the space-like video surveillance. So that's where we see file. It's optimized more for performance rather than Scale, although you do get Scale. The next level was really object, which is more for your modern workloads, for your web and mobile sort of workloads. Optimized more for Scale rather than performance. And then, the third pillar that we see that we'd be working on now is really realtime data, or what you call streaming data, from things like IOT, where you're getting a firehose of information coming out and you got to store it very, very quickly. So we see these are three different pillars of unstructured storage. And really, what we've been working on in our Unstructured Data Storage Team is how to bring all of these three together in the right solution for the customer. >> So tell us about the group that you're in because this is kind of a new, not new industry, we're talking about unstructured data for many years, going on eight years, but it's becoming super important now as you have this horizontal data fabric development. We talked a little bit about it last year, but you can see a clear line of sight now with apps using data very dynamically. So you need under-the-hood storage, but now you need addressability of data. And so, there's a challenge of getting the right data from the right database to the right place on the app in less than a hundred milliseconds. I mean, that's like the nirvana. >> So I think there's a couple of things happening. Firstly, the advances in hardware have changed the game a fair bit, because you can take a software stack that was not optimized for latency to begin with, you can put it on all Flash hardware and you can reduce the roundtrip a lot, that's one thing. The other thing I see is that especially with the advancement of object >> For the stage of life in IT, you have research background, PhD in Computer Science, I mean, it's a pretty awesome time to be in computer science right now. There's a ton of opportunity that applies from that. Machine learning, all this goodness there. What's your vision of how the next 30 years are going to play out? Because Michael Dell said, "Hey, it's been 33 years," since he's started the company, the next 33 are going to be amazing, and I believe that to be true as well given the science opportunities. How do you look at this, from a personal level and also from a Dell EMC? >> I think what's really going to change is, up 'til now, a lot of things that have been done with computing have started with the thought of, "How much data can I really have?" And then, once I've decided how much data I can really have, what am I going to do with it? And I think sort of the innovation that's happened in storage that I'm a part of, what has really changed is it said, "You don't have to stop and think "about how much data you're going to have." You can just keep all of it. And so, what that means is I don't have to figure out upfront what I'm going to do with this data. I'm just going to bring it all in, it's going to be really cheap, the systems are really scalable that can hold it, and everything is sort of tagged in such a way that after the fact, five years from now, I can go do something with this data that I hadn't envisioned when I brought it in. And I think that just opens up a range of things that were hard to imagine. The other thing I think is, >> Programmatically meaning, from a software standpoint. Discoverability, >> That's right, I think as you said, machine learning is a big part of it. Because I think machine learning unlocks opportunities to mind the data that people hadn't really thought of before. And it comes back to the same thing that when I bring data in, whether it's from sensors or aircraft engines or what have you, I have no idea what I'm going to do with the data, so I have no idea which part of the data is important and which part of the data is less important. But when I can apply things like machine learning after the fact, I don't actually have to worry about that. I just bring it all in, and the algorithms themselves will figure out which part of the data is the useful part of the data. >> Your ScaleUp product line and ScaleOut product line, how are you positioning those two application-wise to your customers? >> So I think there is distinction between tier one storage and tier two storage. I think when you think about tier one storage, it's not just about the numbers, like latency and IOPS, but it's about the whole experience of tier one storage. Do I have, for my disaster recovery, do I have RPO-0, which means I can recover to the exact point in time I was at when I failed over data center. How does my replication work, what data services that I have? So I think our ScaleUp technologies are very well oriented towards the tier one kind of capabilities. And then our ScaleOut technologies are very well oriented towards sort of the ubiquitous tier two storage, which is much more deployable at Scale. It's pretty good performance in two, actually, but not with that complete set of capabilities you think about with tier one in terms of RPO-0s, synchronist replication, those kinds of things. So I think there's a very natural sort of mace between the two. And really, I think from a storage vision, what we see is the tier two storage is so scalable and so cheap, that all of your bools of tier one storage on the top tier down automatically into the tier two storage. And what that means is for our customers, if you think about how much tier one storage they have to provision today, they should be able to provision less of that, because they should be able to tier more of that down to the tier two storage, which is now capable enough to hold the rest of the data. >> And be available. >> And be available, >> Okay so, customers want to do this, a no brainer. So when we hear Amazon talk about this all the time, Jeff Bezos was just talking about just the other day a new chassis, they've got the recognition software so you see facial recognition, a lot of great stuff happening all over the Cloud world with this kind of modeling, with the power of computes that's available. What are the customers do now? Because now they get it, it's a no brainer obviously. Now they've got to change how they did IT 30 years to be agile for tomorrow. What's the playbook? >> So what we're seeing is, the step one that we're seeing more and more today, and have seen really for the last couple of years with Isilon and with DCS, is what I would call Consolidation of the Tier Two. So where we had 12 different clustered silos of storage for the different use cases, let's buy into this model that I can just build one large storage cluster, and it can handle the 12 different use cases at the same time. And that's what we've been proving out for the last few years. I think customers have really, enterprise customers are really getting there. And now, what we're beginning to see this year is the next phase, whether it's the industrial internet with the automotives, et cetera, the more IOT style use cases. In fact, on Wednesday, we'll be talking about a new thing we've got called Project Nautilus, which is the third leg of our stool with the streaming storage that is built on top of Isilon and ECS. And we're now at the point where are first customers are beginning to work with that, where they're saying, "From my sensors, "in the automobiles, on the cameras, "I'm going to bring in this firehouse of data, "I'm going to store it all with you, "but later on, I'm going to do analytics on it. "As it's coming in, I'm going to do "some real-time analytics on it, "and then after the fact, I'm going to do "the more batch style." >> I know Paul Scott wants to jump in, but I want you to just back up because I missed the three pillars. >> The three pillars were file, for which we have Isilon, object for your modern applications and web workloads, for which we have ECS, and then streaming storage for IOT. >> Which is Nautilus? >> Which is Project Nautilus, >> Okay, got it. >> The way I put it to people is traditional storage systems, ScaleUp or ScaleOut, file or object, they need resilience. So when you write the data, you have to write and think at the same time, because you have to record all kinds of information about it, you have to take locks, et cetera. For IOT, you need a storage system that writes now, and thinks later, so that you can just suck it all in. >> It sounds like an operating system. You've got a storage that's turning into like LUNs, provisioning, hardware. It's essentially intelligence software that has to compile, runtime, assembly, all this stuff's going on. >> And there's all these fancy names like LAN Architecture and all that kind of stuff. And what that's all saying is, "I bring the data in "and as it's coming in, "there's some things I already want to do with it, "I do that analytics in real-time. "There's other things when I go tag it, "who was in the photo, where was it, "and then the rest of it, I'm going to do later." And who knows what and when, and that's a beautiful thing. >> You're way along the thinking curve on this obviously, but where are your customers? I mean, you're talking about a pretty radically, different approach to processing and storing data even in realtime. Machine learning, meta tagging, there's a lot for them to absorb. >> And I think that part, it's a vertical driven, use-case driven thing. So there's some industries where we see a lot of uptake on that. Automotive is a great example. >> Financial services, >> Financial services, fraud detection, those kinds of things. And there's other verticals where it's not time for that yet. Like I said, healthcare is a great example. So in those verticals, we see more of just the storage consolidation, let me build one pool of tier two storage, if you will, and consolidate my 12 use cases sort of what we refer to as the Data Lake in our words, but I think it's specific verticals. And that's fine, if you look at even the traditional unstructured storage, I think it really started with certain verticals like media and entertainment, life sciences, and that's sort of where it kicked up from. And I think for the streaming storage, it's these verticals that are more oriented towards IOT, your automotive, your fraud detection, those kinds of things where it's really kicking off, and then it'll sort of broaden from there. >> How is this playing into the Dell server strategy? >> It's really a fantastic thing, I don't want to say so much for us as for our customer, because I've talked to a number of people in these verticals where the customer wants a complete solution for IOT. And what that means is number one: on the edge, do I have the right equipment with the right horsepower and the right software on the edge to bring in all the data from the edge and do the part of the processing that needs to be done right there on the edge of realtime, and then it has to be backed by stuff in the backing environment that can process massive amounts of data. And with Dell, we have the opportunity for the first time that we didn't have with the EMC alone to do the complete solution on both ends of it, both the equipment on the edge as well as the backing IT, so I think it's a great opportunity. >> You bring up so many awesome conversations because it's boring storage, now storage is not boring anymore because it's fundamental to the heartbeat of a company. >> Exactly. >> So here's a question for you, kind of like thinking out loud and riffing with you. So some debate, like, "Listen, I want to find "the needle in the haystacks, "but the haystacks are getting bigger," so there's a problem with that. I got to do more design and more gig digging, if you will. And the second point is customers are saying, to at least to us on The Cube and privately is, "I got a data lake that's turning "into a data swamp, "so help me not have swamps of data, "and I want more needles, "but the stack's getting bigger." What's your advice to those CXOs? Could be a CDO, chief data officer, a CS CISCO, these are the fundamental questions. >> I would say this, whatever technology you're evaluating, whether it's an on-premise technology or a hosted technology from a vendor like us, or it's a service out there in the Public Cloud, if you will, ask yourself two questions. One is, "If I size out what I need right now, "and I multiply it by 10 or 100, "what is it going to cost? "And is it really going to work the same way, "is it going to scale the same way?" Look at the algorithmics inside the product, not the Power Point and say, "The way "they've designed this thing, "when I put 100 times the data "on 100 times the number of servers "on this storage system, "are things actually going to work the same way or not?" >> So it's a scale question, kind of what are the magnitude thinking you need to kind of go out and size it up a bit. >> Because I see right now, the landscape is full of new technologies for storage, and a lot of them sound great and look great on the PowerPoint, and you go do a POC with four nodes or eight nodes, and you put Flash in there and it works really well. But the thing is, when you have 200 nodes of that, when you've got a 30 petabyte cluster and you've got to fail it over because your data center went down, how does that go? >> Well, it's also who's going to run it, too. You want less obstacles, not more, and you don't them to be huge, expensive developers. >> TierPoint, that's the other thing. We really don't talk to our customers in terms of storage acquisition costs anymore, we talk in terms TCO, total cost of ownership. You look at power, you look at cooling. >> That killed the Duke, basically, it was so hard to run and total cost of of ownership. Michael Dell was just on, I was interviewing Michael and I asked him like, "Where's the Cloud strategy?" I was just busting his chops a little bit, 'cause I know he's messaging, trying to get him off his messaging. But he made an interesting comment and metaphor. He goes, "Well John, I remember the days "during the internet days, where's you internet strategy?" Look where that happened, the bubble popped. But ultimately, everything played out as according to plan. There's pet food online, now we've got food delivery, DoorDash, all this stuff's happening. So he kind of was using it to compare to the Cloud today. There's a lot of hope and promise, where's your Cloud strategy? But yet, his point was it's going to be everywhere. >> Yeah, and I would say this, I think people sometimes confuse Cloud with Public Cloud. And I think what happened is, having that issue myself, I would say that Public Cloud exposed a certain model that had some benefits for the customer base that were new. That is, I can use as a service, I don't worry about operationalizing things, I can pay as I go, so I get that, it's elastic. But it also came with a lot of drawbacks. I don't have the kind of control that I would like to have. A normal thing that any person who takes a dependency on infrastructure has is, "Today's my Superbowl Sunday. "Don't touch my environment today." Now you go to a Public Cloud and you use a service that is used by thousands of other customers, so which day is Superbowl Sunday? Every day is Superbowl Sunday for somebody. >> It was a metaphor, Public cloud was a metaphor for virtualization that would effect the entire environment. >> And so, I think the journey we're all in, all the vendors, the Public Cloud suppliers, everybody is, "What are the right set of models "that are going to cover the space for all our customers?" There's not going to be one. There's several. I think the dedicated private Cloud models are certainly very appealing in a number of ways if you do the economics right. And I think that's the journey we're all on sort of together. >> I tweeted a little bit of the jewels out there this morning. True, Private cloud is going to be a $265 billion dollar market, but they were the first ones to actually size that, let's say true private public means essentially hybrid, but on-prem with a data center. That's huge numbers, it's not like rounding errors. >> We believe that, too. And that's why one of the neatest things we've announced this year with ECS object storage is something called ECS Dedicated Cloud, which is basically saying, "You can take the object storage "from us, but it's going to run in our data centers." We operate it, it's actually the developers who wrote the code from my team who are actually operating it, and you can do a variety of hybrid things. You can keep some of it on-prem, some of it off-prem, you can keep all of it off-prem. But regardless, it's your stuff. You can hug it, it's dedicated to you. You're not sharing the cluster with anybody else. You get to decided when you update your version, when you take a maintenance window or what have you. So, we're all searching for that sweet spot, if you will. >> I want to ask you about something, some of the different containers. The hottest thing right now in infrastructure, lack of persistent storage has been a real problem for containers. Is that a problem that's yours to solve or is it Docker's to solve? >> No, I think it is ours to solve with them. So, I'll say a couple of things. Firstly, our modern products, ECS and object storage as well as ScaleIO, our block ScaleOut storage, these are built with containers. So for instance, if you take ECS today, every ECS appliance that we ship, if you look inside very server, it's running Linux with Docker. And all the ECS code is running on Docker containers. That's just how it works. So A: we believe in containers, and two: I think we have been doing the work to provide that persistence ecosystem for containers using our storage. So we have a great team at Dell EMC called EMC Code. And these are people, they do a lot of this integration stuff, they work very closely with Docker and a number of the other frameworks to really plug our storage in. And I think it's a very open ecosystem. There are APIs there now, so you can plug anybody's storage in. And I think that's really if you compare VM-based infrastructures with container-based infrastructures. That's really the gap, because when you operationalize the stuff, you need things like that. You need persistent storage, you need snapshots, you need a VR-storage, you need those kinds of things, but I think that'll all come. >> Well, we're looking to continuing the conversation, I know time's tight. We'd like to follow up with you after the show, maybe bring you into our studio via Skype. You're in a hot area, you got the storage, you got the software, you got some Cloud action going on. Thank you very much for coming on The Cube, appreciate it. >> My pleasure for being here, thank you for having me. >> This is TheCube, live coverage here at Dell EMC World 2017. And I'm John Furrier with Paul Gillin, we'll be right back. Stay with us. (bright tech tones)

>> Announcer: Live from Boston, Massachusetts, it's theCUBE covering OpenStack Summit 2017. Brought to you by the OpenStack Foundation, Red Hat, and additional ecosystem support. >> And we're back. I'm Stu Miniman with my cohost, John Troyer, getting to the end of day two of three days of coverage here at the OpenStack Summit in Boston. Happy to welcome the program Sujal Das, who is the chief marketing and strategy officer at Netronome. Thanks so much for joining us. >> Thank you. >> Alright, so we're getting through it, you know, really John and I have been digging into, you know, really where OpenStack is, talking to real people, deploying real clouds, where it fits into the multi cloud world. You know, networking is one of those things that took a little while to kind of bake out. Seems like every year we talk about Neutron and all the pieces that are there. But talk to us, Netronome, we know you guys make SmartNICs. You've got obviously some hardware involved when I hear a NIC, and you've got software. What's your involvement in OpenStack and what sort of things are you doing here at the show? >> Absolutely, thanks, Stu. So, we do SmartNIC platforms, so that includes both hardware and software that can be used in commercial office house servers. So with respect to OpenStack, I think the whole idea of STN with OpenStack is centered around the data plane that runs on the server, things such as the Open vSwitch, or Virtual Router, and they're evolving new data planes coming into the market. So we offload and accelerate the data plane in our SmartNICs, because the SmartNICs are programmable, we can evolve the feature set very quickly. So in fact, we have software releases that come out every six months that keep up to speed with OpenStack releases and Open vSwitches. So that's what we do in terms of providing a higher performance OpenStack environment so to say. >> Yeah, so I spent a good part of my career working on that part of the stack, if you will, and the balance is always like, right, what do you build into the hardware? Do I have accelerators? Is this the software that does, you know, usually in the short term hardware can take it care of it, but in the long term you follow the, you know, just development cycles, software tends to win in terms, so, you know. Where are we with where functionality is, what differentiates what you offer compared to others in the market? >> Absolutely. So we see a significant trend in terms of the role of a coprocessor to the x86 or evolving ARM-based servers, right, and the workloads are shifting rapidly. You know, with the need for higher performance, more efficiency in the server, you need coprocessors. So we make, essentially, coprocessors that accelerate networking. And that sits next to an x86 on a SmartNIC. The important differentiation we have is that we are able to pack a lot of cores on a very small form factor hardware device. As many as 120 cores that are optimized for networking. And by able to do that, we're able to deliver very high performance at the lowest cost and power. >> Can you speak to us, just, you know, what's the use case for that? You know, we talk about scale and performance. Who are your primary customers for this? Is this kind of broad spectrum, or, you know, certain industries or use cases that pop out. >> Sure, so we have three core market segments that we go after, right? One is the innovene construction market, where we see a lot of OpenStack use, for example. We also have the traditional cloud data center providers who are looking at accelerating even SmartNICs. And lastly the security market, that's kind of been our legacy market that we have grown up with. With security kind of moving away from appliances to more distributed security, those are our key three market segments that we go after. >> The irony is, in this world of cloud, hardware still matters, right? Not only does hardware, like, you're packing a huger number of cores into a NIC, so that hardware matters. But, one of the reasons that it matters now is because of the rise of this latest generation of solid-state storage, right? People are driving more and more IO. Do you see, what are the trends that you're seeing in terms of storage IO and IO in general in the data center? >> Absolutely. So I think the large data centers of the world, they showed the way in terms of how to do storage, especially with SSDs, what they call disaggregated storage, essentially being able to use the storage on each server and being able to aggregate those together into a pool of storage resources and its being called hyperconverged. I think companies like Nutanix have found a lot of success in that market. What I believe is going to happen in the next phase is hyperconvergence 2.0 where we're going to go beyond security, which essentially addressed TCO and being able to do more with less, but the next level would be hyperconvergence around security where you'd have distributed security in all servers and also telemetry. So basically your storage appliance is going away with hyperconvergence 1.0, but with the next generation of hyperconvergence we'd see the secured appliances and the monitoring appliances sort of going away and becoming all integrated in the server infrastructure to allow for better service levels and scalability. >> So what's the relationship between distributed security and then the need for more bandwidth at the back plane? >> Absolutely. So when you move security into the server, the processing requirements in the server goes up. And typically with all security processing, it's a lot of what's called flow processing or match-action processing. And those are typically not suitable for a general purpose server like the ARM or the x86, but that's where you need specialized coprocessors, kind of like the world of GPUs doing well in the artificial intelligence applications. I think the same example here. When you have security, telemetry, et cetera being done in each server, you need special purpose processing to do that at the lowest cost and power. >> Sujal, you mentioned that you've got solutioned into the public cloud. Are those the big hyperscale guys? Is it service providers? I'm curious if you could give a little color there. >> Yes, so these are both tier one and tier two service providers in the cloud market as well as the telco service providers, more in the NFV side. But we see a common theme here in terms of wanting to do security and things like telemetry. Telemetry is becoming a hot topic. Something called in-band telemetry that we are actually demonstrating at our booth and also speaking about with some our partners at the show, such as with Mirantis, Red Hat, and Juniper. Where doing all of these on each server is becoming a requirement. >> When I hear you talk, I think about here at OpenStack, we're talking about the hybrid or multi cloud world and especially something like security and telemetry I need to handle my data center, I need to handle the public cloud, and even when I start to get into that IoT edge environment, we know that the service area for attack just gets orders of magnitude larger, therefore we need security that can span across those. Are you touching all of those pieces, maybe give us a little bit of, dive into it. >> Absolutely, I think a great example is DDoS, right, distributed denial of service attacks. And today you know you have these kind of attacks happening from computers, right. Look at the environment where you have IoTs, right, you have tons and tons of small devices that can be hacked and could flood attacks into the data center. Look at the autonomous car or self-driving car phenomenon, where each car is equivalent to about 2,500 Internet users. So the number of users is going to scale so rapidly and the amount of attacks that could be proliferated from these kind of devices is going to be so high that people are looking at moving DDoS from the perimeter of the network to each server. And that's a great example that we're working with with a large service provider. >> I'm kind of curious how the systems take advantage of your technology. I can see it, some of it being transparent, like if you just want to jam more bits through the system, then that should be pretty transparent to the app and maybe even to the data plane and the virtual switches. But I'm guessing also there are probably some API or other software driven ways of doing, like to say, hey not only do I want you to jam more bits through there, but I want to do some packet inspection or I want to do some massaging or some QoS or I'm not sure what all these SmartNICs do. So is my model correct? Is that kind of the different ways of interacting with your technology? >> You're hitting a great point. A great question by the way, thank you. So the world has evolved from very custom ways of doing things, so proprietary ways of doing things, to more standard ways of doing things. And one thing that has kind of standardized so to say the data plane that does all of these functions that you mention, things like security or ACL roots or virtualization. Open vSwitch is a great example of a data plane that has kind of standardized how you do things. And there are a lot of new open source projects that are happening in the Linux Foundation, such as VPP for example. So each of these standardize the way you do it and then it becomes easier for vendors like us to implement a standard data plane and then work with the Linux kernel community in getting all of those things upstream, which we are working on. And then having the Red Hats of the world actually incorporate those into their distributions so that way the deployment model becomes much easier, right. And one of the topics of discussion with Red Hat that we presented today was exactly that, as to how do you make these kind of scales, scalability for security and telemetry, be more easily accessible to users through a Red Hat distribution, for example. >> Sujal, can you give us a little bit of just an overview of the sessions that Netronome has here at the show and what are the challenges that people are coming to that they're excited to meet with your company about? >> Absolutely, so we presented one session with Mirantis. Mirantis, as you know, is a huge OpenStack player. With Mirantis, we presented exactly the same, the problem statement that I was talking about. So when you try to do security with OpenStack, whether its stateless or stateful, your performance kind of tanks when you apply a lot of security policies, for example, on a per server basis that you can do with OpenStack. So when you use a SmartNIC, you essentially return a lot of the CPU cores to the revenue generating applications, right, so essentially operators are able to make more per server, make more money per server. That's a sense of what the value is, so that was the topic with Mirantis, who uses actually Open Contrail virtual router data plane in their solution. We also have presented with Juniper, which is also-- >> Stu: Speaking of Open Contrail. >> Yeah, so Juniper is another version of Contrail. So we're presenting a very similar product but that's with the commercial product from Juniper. And then we have yesterday presented with Red Hat. And Red Hat is based on Red Hat's OpenStack and their Open vSwitch based products where of course we are upstreaming a lot of these code bits that I talked about. But the value proposition is uniform across all of these vendors, which is when you do storage, sorry, security and telemetry and virtualization et cetera in a distributed way across all of your servers and get it for all of your appliances, you get better scale. But to achieve the efficiencies in the server, you need a SmartNIC such as ours. >> I'm curious, is the technology usually applied then at the per server level, is there a rack scale component too that needs to be there? >> It's on a per server basis, so it's the use cases like any other traditional NIC that you would use. So it looks and feels like any other NIC except that there is more processing cores in the hardware and there's more software involved. But again all of the software gets tightly integrated into the OS vendor's operating system and then the OpenStack environment. >> Got you. Well I guess you can never be too rich, too thin, or have too much bandwidth. >> That's right, yeah. >> Sujal, share with our audience any interesting conversation you had or other takeaways you want people to have from the OpenStack Summit. >> Absolutely, so without naming specific customer names, we had one large data center service provider in Europe come in and their big pain point was latency. Latency going form the VM on one server to another server. And that's a huge pain point and their request was to be able to reduce that by 10x at least. And we're able to do that, so that's one use case that we have seen. The other is again relates to telemetry, you know, how... This is a telco service provider, so as they go into 5G and they have to service many different applications such as what they call network slices. One slice servicing the autonomous car applications. Another slice managing the video distribution, let's say, with something like Netflix, video streaming. Another one servicing the cellphone, something like a phone like this where the data requirements are not as high as some TV sitting in your home. So they need different kinds of SLA for each of these services. How do they slice and dice the network and how are they able to actually assess the rogue VM so to say that might cause performance to go down and affect SLAs, telemetry, or what is called in-band telemetry is a huge requirement for those applications. So I'm giving you like two, one is a data center operator. You know an infrastructure as a service, just want lower latency. And the other one is interest in telemetry. >> So, Sujal, final question I have for you. Look forward a little bit for us. You've got your strategy hat on. Netronome, OpenStack in general, what do you expect to see as we look throughout the year maybe if we're, you know, sitting down with you in Vancouver a year from now, what would you hope that we as an industry and as a company have accomplished? >> Absolutely, I think you know you'd see a lot of these products so to say that enable seamless integration of SmartNICs become available on a broad basis. I think that's one thing I would see happening in the next one year. The other big event is the whole notion of hyperconvergence that I talked about, right. I would see the notion of hyperconvergence move away from one of just storage focus to security and telemetry with OpenStack kind of addressing that from a cloud orchestration perspective. And also with each of those requirements, software defined networking which is being able to evolve your networking data plane rapidly in the run. These are all going to become mainstream. >> Sujal Das, pleasure catching up with you. John and I will be back to do the wrap-up for day two. Thanks so much for watching theCUBE. (techno beat)

>> Okay. We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid right. So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manuvir Das who's the head of enterprise computing at NVIDIA. And before I hand it off to Rob, I just want to say for those of you who follow me at the Cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise and it's being driven by the emergence of data intensive applications and workloads. No longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like NVIDIA. So let's learn more about this collaboration and what it means to your data business. Rob, take it away. >> Thanks Mick and Dave. That was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy in accelerating the path to value and hybrid environments. And I want to drill down on this aspect. Today, every business is facing accelerating change. Everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor now. Every engagement with coworkers, customers and partners is virtual. From website metrics to customer service records and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? At Cloudera, we believe this onslaught of data offers an opportunity to make better business decisions faster and we want to make that easier for everyone, whether it's fraud detection, demand forecasting, preventative maintenance, or customer churn. Whether the goal is to save money or produce income, every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit that cloud provides. And with security and edge to AI data intimacy, that's why the partnership between Cloudera and NVIDIA together means so much. And it starts with a shared vision, making data-driven decision-making a reality for every business. And our customers will now be able to leverage virtually unlimited quantities and varieties of data to power an order of magnitude faster decision-making. And together we turbo charged the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. We're joined today by NVIDIA's Manduvir Das, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, Manuvir, thank you for joining us. Over to you now. >> Thank you Rob, for having me. It's a pleasure to be here on behalf of NVIDIA. We're so excited about this partnership with Cloudera. You know, when, when NVIDIA started many years ago, we started as a chip company focused on graphics. But as you know, over the last decade, we've really become a full stack, accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, AI being a prime example. And when we think about Cloudera, and your company, your great company, there's three things we see Rob. The first one is that for the companies that were already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing we've seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about NVIDIA's mission going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies to date who have been the early adopters using the power acceleration by changing their technology and their stacks. But more and more we see the opportunity of meeting customers where they are with tools that they're familiar with, with partners that they trust. And of course, Cloudera being a great example of that. The second part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through. But as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. And so again, the power of your platform is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute, the machine learning compute, needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And, and Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where, literally, they took the workflow they had, they took the servers they had, they added GPUs into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >> How you doing? My name's Joe Ansaldi. I'm the branch chief of the technical branch in RAS. It's actually the research division, research and statistical division of the IRS. Basically, the mission that RAS has is we do statistical and research on all things related to taxes, compliance issues, fraud issues, you know, anything that you can think of basically, we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those algorithms, the number of parameters each of those algorithms have. So that's, that's really been our challenge now. The expectation was that with NVIDIA and Cloudera's help and with the cluster, we actually build out to test this on the actual fraud detection algorithm. Our expectation was we were definitely going to see some speed up in computational processing times. And just to give you context, the size of the data set that we were, the SME was actually working her algorithm against was around four terabytes. If I recall correctly, we had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them. It was really, really quick. The definite now term, short term, what's next is going to be the subject matter expert is actually going to take our algorithm run with that. So that's definitely the now term thing we want to do. Going down, go looking forward, maybe out a couple of months, we're also looking at procuring some A-100 cards to actually test those out. As you guys can guess, our datasets are just getting bigger and bigger and bigger, and it demands to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward and then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run a, you know, run to our heart's desire, wherever our imaginations takes our SMEs to actually develop solutions. Now have the platforms to run them on. Just kind of to close out, we really would be remiss, I've worked with a lot of companies through the year and most of them been spectacular. And you guys are definitely in that category, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't thank you guys. So thank you for the opportunity. Doing fantastic. and I'd have to also, I want to thank my guys. my staff, Raul, David worked on this, Richie worked on this, Lex and Tony just, they did a fantastic job and I want to publicly thank them for all the work they did with you guys and Chev, obviously also is fantastic. So thank you everyone. >> Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and NVIDIA? Is it primarily go to market or are you doing engineering work? What's the story there? >> It's really both. It's both go to market and engineering The engineering focus is to optimize and take advantage of NVIDIA's platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both. >> Great. Thank you. Manuvir, maybe you could talk a little bit more about why can't we just use existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do NVIDIA and Cloudera bring to the table that goes beyond the conventional systems that we've known for many years? >> Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So, the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now NVIDIA has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform so that regardless of the technique the customer is using to get insight from the data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >> So, I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going towards doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start. You think about AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems, and real-time AI inference, at least even at the edge, huge potential for business value. In a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the liking. So you're putting AI into these data intensive apps within the enterprise. The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >> Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint. And new platforms like these being developed by Cloudera and NVIDIA will dramatically lower the cost of enabling this type of workload to be done. And what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation engine, supply chain management, drug province. And increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots. That AR, VR and manufacturing so driving better quality. The power grid management, automated retail, IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >> I mean, Manufir, this is like your wheelhouse. Maybe you could add something to that. >> Yeah. I mean, I agree with Rob. I mean he listed some really good use cases, you know, The way we see this at NVIDIA, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled use cases, particular use cases like a chat bot from the ground up with the hardware and the software. Almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. Now, I think we are in the first phase of the democratization. For example, the work we do with Cloudera, which is for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. And you still come home and assemble it, but all the parts are there, the instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought a table and it showed up and somebody placed it in the right spot. Right? And they didn't really have to learn how to do AI. So these are the phases. And I think we're very excited to be going there. >> You know, Rob, the great thing about, for your customers is they don't have to build out the AI. They can, they can buy it. And just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations, and Mick I talked about this, the GIGO problem that we've all, you know, studied in college, you know, garbage in, garbage out. But, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob, over the next several years? >> So yeah, the combination of massive amounts of data that had been gathered across the enterprise in the past 10 years with an open APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency. And that's allowing us as an industry to democratize the data access while at the same time delivering the federated governance and security models. And hybrid technologies are playing a key role in making this a reality and enabling data access to be quote, hybridized, meaning access and treated in a substantially similar way, irrespective of the physical location of where that data actually resides. >> And that's great. That is really the value layer that you guys are building out on top of all this great infrastructure that the hyperscalers have have given us. You know, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you could go first and then Manuvir, you could bring us home. Where do you guys want to see the relationship go between Cloudera and NVIDIA? In other words, how should we as outside observers be, be thinking about and measuring your project, specifically in the industry's progress generally? >> Yes. I think we're very aligned on this and for Cloudera, it's all about helping companies move forward, leverage every bit of their data and all the places that it may be hosted and partnering with our customers, working closely with our technology ecosystem of partners, means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >> Yeah and I agree with Rob and for us at NVIDIA, you know, we, this partnership started with data analytics. As you know, Spark is a very powerful technology for data analytics. People who use Spark rely on Cloudera for that. And the first thing we did together was to really accelerate Spark in a seamless manner. But we're accelerating machine learning. We're accelerating artificial intelligence together. And I think for NVIDIA it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity.

>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.

>>mhm, mm. All right. Mhm. Mhm, mm mm. Mhm. Yeah, mm. Mhm. Yeah, yeah. Mhm, mm. Okay. Mm. Yeah, Yeah. >>Mhm. Mhm. Yeah. Welcome to future cloud made possible by Cisco. My name is Dave Volonte and I'm your host. You know, the cloud is evolving like the universe is expanding at an accelerated pace. No longer is the cloud. Just a remote set of services, you know, somewhere up there. No, the cloud, it's extending to on premises. Data centers are reaching into the cloud through adjacent locations. Clouds are being connected together to each other and eventually they're gonna stretch to the edge and the far edge workloads, location latency, local laws and economics will define the value customers can extract from this new cloud model which unifies the operating experience independent of location. Cloud is moving rapidly from a spare capacity slash infrastructure resource to a platform for application innovation. Now, the challenge is how to make this new cloud simple, secure, agile and programmable. Oh and it has to be cloud agnostic. Now, the real opportunity for customers is to tap into a layer across clouds and data centers that abstracts the underlying complexity of the respective clouds and locations. And it's got to accommodate both mission critical workloads as well as general purpose applications across the spectrum cost, effectively enabling simplicity with minimal labor costs requires infrastructure i. E. Hardware, software, tooling, machine intelligence, AI and partnerships within an ecosystem. It's kind of accommodate a variety of application deployment models like serverless and containers and support for traditional work on VMS. By the way, it also requires a roadmap that will take us well into the next decade because the next 10 years they will not be like the last So why are we here? Well, the cube is covering Cisco's announcements today that connect next generation compute shared memory, intelligent networking and storage resource pools, bringing automation, visibility, application assurance and security to this new decentralized cloud. Now, of course in today's world you wouldn't be considered modern without supporting containers ai and operational tooling that is demanded by forward thinking practitioners. So sit back and enjoy the cubes, special coverage of Cisco's future cloud >>From around the globe. It's the Cube presenting future cloud one event, a world of opportunities brought to you by Cisco. >>We're here with Dejoy Pandey, a VP of emerging tech and incubation at Cisco. V. Joy. Good to see you. Welcome. >>Good to see you as well. Thank you Dave and pleasure to be here. >>So in 2020 we kind of had to redefine the notion of agility when it came to digital business or you know organizations, they had to rethink their concept of agility and business resilience. What are you seeing in terms of how companies are thinking about their operations in this sort of new abnormal context? >>Yeah, I think that's a great question. I think what what we're seeing is that pretty much the application is the center of the universe. And if you think about it, the application is actually driving brand recognition and the brand experience and the brand value. So the example I like to give is think about a banking app uh recovered that did everything that you would expect it to do. But if you wanted to withdraw cash from your bank you would actually have to go to the ATM and punch in some numbers and then look at your screen and go through a process and then finally withdraw cash. Think about what that would have, what what that would do in a post pandemic era where people are trying to go contact less. And so in a situation like this, the digitization efforts that all of these companies are going through and and the modernization of the automation is what is driving brand recognition, brand trust and brand experience. >>Yeah. So I was gonna ask you when I heard you say that, I was gonna say well, but hasn't it always been about the application, but it's different now, isn't it? So I wonder if you talk more about how the application is experience is changing. Yes. As a result of this new digital mandate. But how should organizations think about optimizing those experiences in this new world? >>Absolutely. And I think, yes, it's always been about the application, but it's becoming the center of the universe right now because all interactions with customers and consumers and even businesses are happening through that application. So if the application is unreliable or if the application is not available is untrusted insecure, uh, there's a problem. There's a problem with the brand, with the company and the trust that consumers and customers have with our company. So if you think about an application developer, the weight he or she is carrying on their shoulders is tremendous because you're thinking about rolling features quickly to be competitive. That's the only way to be competitive in this world. You need to think about availability and resiliency. Like you pointed out and experience, you need to think about security and trust. Am I as a customer or consumer willing to put my data in that application? So velocity, availability, Security and trust and all of that depends on the developer. So the experience, the security, the trust, the feature, velocity is what is driving the brand experience now. >>So are those two tensions that say agility and trust, you know, Zero Trust used to be a buzzword now it's a mandate. But are those two vectors counter posed? Can they be merged into one and not affect each other? Does the question makes sense? Right? Security usually handcuffs my speed. But how do you address that? >>Yeah that's a great question. And I think if you think about it today that's the way things are. And if you think about this developer all they want to do is run fast because they want to build those features out and they're going to pick and choose a piece and services that matter to them and build up their app and they want the complexities of the infrastructure and security and trust to be handled by somebody else is not that they don't care about it but they want that abstraction so that is handled by somebody else. And typically within an organization we've seen in the past where this friction between Netapp Sec ops I. T. Tops and and the cloud platform Teams and the developer on one side and these these frictions and these meetings and toil actually take a toll on the developer and that's why companies and apps and developers are not as agile as they would like to be. So I think but it doesn't have to be that way. So I think if there was something that would allow a developer to pick and choose, discover the apis that they would like to use connect those api is in a very simple manner and then be able to scale them out and be able to secure them and in fact not just secure them during the run time when it's deployed. We're right off the back when the fire up that I'd and start developing the application. Wouldn't that be nice? And as you do that, there is a smooth transition between that discovery connectivity and ease of consumption and security with the idea cops. Netapp psych ops teams and see source to ensure that they are not doing something that the organization won't allow them to do in a very seamless manner. >>I want to go back and talk about security but I want to add another complexity before we do that. So for a lot of organizations in the public cloud became a staple of keeping the lights on during the pandemic but it brings new complexities and differences in terms of latency security, which I want to come back to deployment models etcetera. So what are some of the specific networking challenges that you've seen with the cloud native architecture is how are you addressing those? >>Yeah. In fact, if you think about cloud, to me that is a that is a different way of seeing a distributed system. And if you think about a distributed system, what is at the center of the distributed system is the network. So my my favorite comment here is that the network is the wrong time for all distribute systems and modern applications. And that is true because if you think about where things are today, like you said, there's there's cloud assets that a developer might use in the banking example that I gave earlier. I mean if you want to build a contact less app so that you get verified, a customer gets verified on the app. They walk over to the ATM and they were broadcast without touching that ATM. In that kind of an example, you're touching the mobile Rus, let's say U S A P is you're touching cloud API is where the back end might sit. You're touching on primary PS maybe it's an oracle database or a mainframe even where transactional data exists. You're touching branch pipes were the team actually exists and the need for consistency when you withdraw cash and you're carrying all of this and in fact there might be customer data sitting in salesforce somewhere. So it's cloud API is a song premise branch. It's ass is mobile and you need to bring all of these things together and over time you will see more and more of these API is coming from various as providers. So it's not just cloud providers but saas providers that the developer has to use. And so this complexity is very, very real. And this complexity is across the wide open internet. So the application is built across this wide open internet. So the problems of discovery ability, the problems of being able to simply connect these apis and manage the data flow across these apis. The problems of consistency of policy and consumption because all of these areas have their own nuances and what they mean, what the arguments mean and what the A. P. I. Actually means. How do you make it consistent and easy for the developer? That is the networking problem. And that is a problem of building out this network, making traffic engineering easy, making policy easy, making scale out, scale down easy, all of that our networking problems. And so we are solving those problems uh Francisco. >>Yeah the internet is the new private network but it's not so private. So I want to go back to security. I often say that the security model of building a moat, you dig the moat, you get the hardened castle that's just outdated now that the queen is left her castle, I always say it's dangerous out there. And the point is you touched on this, it's it's a huge decentralized system and with distributed apps and data, that notion of perimeter security, it's just no longer valid. So I wonder if you could talk more about how you're thinking about this problem and you definitely address some of that in your earlier comments. But what are you specifically doing to address this and how do you see it evolving? >>Yeah, I mean, that's that's a very important point. I mean, I think if you think about again the wide open internet being the wrong time for all modern applications, what is perimeter security in this uh in this new world? I mean, it's to me it boils down to securing an API because again, going with that running example of this contact lists cash withdrawal feature for a bank, the ap wherever it's it's entre branch SAs cloud, IOS android doesn't matter that FBI is your new security perimeter. And the data object that is trying to access is also the new security perimeter. So if you can secure ap to ap communication and P two data object communication, you should be good. So that is the new frontier. But guess what software is buggy? Everybody's software not saying Cisco software, everybody's Softwares buggy. Uh software is buggy, humans are not reliable and so things mature, things change, things evolve over time. So there needs to be defense in depth. So you need to secure at the API layer had the data object layer, but you also need to secure at every layer below it so that you have good defense and depth if any layer in between is not working out properly. So for us that means ensuring ap to ap communication, not just during long time when the app has been deployed and is running, but during deployment and also during the development life cycle. So as soon as the developer launches an ID, they should be able to figure out that this api is security uses reputable, it has compliant, it is compliant to my to my organization's needs because it is hosted, let's say from Germany and my organization wants appears to be used only if they are being hosted out of Germany so compliance needs and and security needs and reputation. Is it available all the time? Is it secure? And being able to provide that feedback all the time between the security teams and the developer teams in a very seamless real time manner. Yes, again, that's something that we're trying to solve through some of the services that we're trying to produce in san Francisco. >>Yeah, I mean those that layered approach that you're talking about is critical because every layer has, you know, some vulnerability. And so you you've got to protect that with some depth in terms of thinking about security, how should we think about where where Cisco's primary value add is, I mean as parts of the interview has a great security business is growing business, Is it your intention to to to to add value across the entire value chain? I mean obviously you can't do everything so you've got a partner but so has the we think about Cisco's role over the next I'm thinking longer term over the over the next decade. >>Yeah, I mean I think so, we do come in with good strength from the runtime side of the house. So if you think about the security aspects that we haven't played today, uh there's a significant set of assets that we have around user security around around uh with with do and password less. We have significant assets in runtime security. I mean, the entire portfolio that Cisco brings to the table is around one time security, the secure X aspects around posture and policy that will bring to the table. And as you see, Cisco evolve over time, you will see us shifting left. I mean, I know it's an overused term, but that is where security is moving towards. And so that is where api security and data security are moving towards. So learning what we have during runtime because again, runtime is where you learn what's available and that's where you can apply all of the M. L. And I models to figure out what works what doesn't taking those learnings, Taking those catalogs, taking that reputation database and moving it into the deployment and development life cycle and making sure that that's part of that entire they have to deploy to runtime chain is what you will see. Cisco do overtime. >>That's fantastic phenomenal perspective video. Thanks for coming on the cube. Great to have you and look forward to having you again. >>Absolutely. Thank you >>in a moment. We'll talk hybrid cloud applications operations and potential gaps that need to be addressed with costume, Das and VJ Venugopal. You're watching the cube the global leader in high tech coverage. Mhm >>You were cloud. It isn't just a cloud. It's everything flowing through it. It's alive. Yeah, connecting users, applications, data and devices and whether it's cloud, native hybrid or multi cloud, it's more distributed than ever. One company takes you inside, giving you the visibility and the insight you need to take action. >>One company >>has the vision to understand it, all the experience, to securely connect at all on any platform in any environment. So you can work wherever work takes you in a cloud first world between your cloud and being cloud smart, there's a bridge. Cisco the bridge to possible. >>Okay. We're here with costume does, who is the Senior Vice President, General Manager of Cloud and compute at Cisco. And VJ Venugopal, who is the Senior Director for Product Management for cloud compute at Cisco. KTV. J. Good to see you guys welcome. >>Great to see you. Dave to be here. >>Katie, let's talk about cloud you And I last time we're face to face was in Barcelona where we love talking about cloud and I always say to people look, Cisco is not a hyper Scaler, but the big public cloud players, they're like giving you a gift. They spent almost actually over $100 billion last year on Capex. The big four. So you can build on that infrastructure. Cisco is all about hybrid cloud. So help us understand the strategy. There may be how you can leverage that build out and importantly what a customer is telling you they want out of hybrid cloud. >>Yeah, no that's that's that's a perfect question to start with. Dave. So yes. So the hybrid hyper scholars have invested heavily building out their assets. There's a great lot of innovation coming from that space. Um There's also a great innovation set of innovation coming from open source and and that's another source of uh a gift. In fact the I. T. Community. But when I look at my customers they're saying well how do I in the context of my business implement a strategy that takes into consideration everything that I have to manage um in terms of my contemporary work clothes, in terms of my legacy, in terms of everything my developer community wants to do on DEVOPS and really harnessed that innovation that's built in the public cloud, that built an open source that built internally to me, and that naturally leads them down the path of a hybrid cloud strategy. And Siskel's mission is to provide for that imperative, the simplest more power, more powerful platform to deliver hybrid cloud and that platform. Uh It's inter site we've been investing in. Inner side, it's a it's a SAS um service um inner side delivers to them that bridge between their estates of today that were closer today, the need for them to be guardians of enterprise grade resiliency with the agility uh that's needed for the future. The embracing of cloud. Native of new paradigms of deVOPS models, the embracing of innovation coming from public cloud and an open source and bridging those two is what inner side has been doing. That's kind of that's kind of the crux of our strategy. Of course we have the entire portfolio behind it to support any, any version of that, whether that is on prem in the cloud, hybrid, cloud, multi cloud and so forth. >>But but if I understand it correctly from what I heard earlier today, the inter site is really a linchpin of that strategy, is it not? >>It really is and may take a second to totally familiarize those who don't know inner side with what it is. We started building this platform quite a few years back and we we built a ground up to be an immensely scalable SAs, super simple hybrid cloud platform and it's a platform that provides a slew of service is inherently and then on top of that there are suites of services, the sweets of services that are tied to infrastructure, automation. Cisco, as well as Cisco partners. The streets of services that have nothing to do with Cisco um products from a hardware perspective. And it's got to do with more cloud orchestration and cloud native and inner side and its suite of services um continue to kind of increase in pace and velocity of delivery video. Just over the last two quarters we've announced a whole number of things will go a little bit deeper into some of those but they span everything from infrastructure automation to kubernetes and delivering community than service to workload optimization and having visibility into your cloud estate. How much it's costing into your on premise state into your work clothes and how they're performing. It's got integrations with other tooling with both Cisco Abdi uh as well as non Cisco um, assets and then and then it's got a whole slew of capabilities around orchestration because at the end of the day, the job of it is to deliver something that works and works at scale that you can monitor and make sure is resilient and that includes that. That includes a workflow and ability to say, you know, do this and do this and do this. Or it includes other ways of automation, like infrastructure as code and so forth. So it includes self service that so that expand that. But inside the world's simplest hybrid cloud platform, rapidly evolving rapidly delivering new services. And uh we'll talk about some more of those day. >>Great, thank you, Katie VJ. Let's bring you into the discussion. You guys recently made an announcement with the ASCIi corp. I was stoked because even though it seemed like a long time ago, pre covid, I mean in my predictions post, I said, ha, she was a name to watch our data partners. Et are you look at the survey data and they really have become mainstream? You know, particularly we think very important in the whole multi cloud discussion. And as well, they're attractive to customers. They have open source offerings. You can very easily experiment. Smaller organizations can take advantage. But if you want to upgrade to enterprise features like clustering or whatever, you can plug right in. Not a big complicated migration. So a very, very compelling story there. Why is this important? Why is this partnership important to Cisco's customers? Mhm. >>Absolutely. When the spot on every single thing that you said, let me just start by paraphrasing what ambition statement is in the cloud and computer group. Right ambition statement is to enable a cloud operating model for hybrid cloud. And what we mean by that is the ability to have extreme amounts of automation orchestration and observe ability across your hybrid cloud idea operations now. Uh So developers and applications team get a great amount of agility in public clouds and we're on a mission to bring that kind of agility and automation to the private cloud and to the data centers and inter site is a quickie platform and lynchpin to enable that kind of operations. Uh, Cloud like operations in the in the private clouds and the key uh As you rightly said, harsher car is the, you know, they were the inventors of the concept of infrastructure at school and in terra form, they have the world's number one infrastructure as code platform. So it became a natural partnership for Cisco to enter into a technology partnership with harsher card to integrate inter site with hardship cops, terra form to bring the benefits of infrastructure as code to the to hybrid cloud operations. And we've entered into a very tight integration and uh partnership where we allow developers devops teams and infrastructure or administrators to allow the use of infrastructure as code in a SAS delivered manner for both public and private club. So it's a very unique partnership and a unique integration that allows the benefits of cloud managed i E C. To be delivered to hybrid cloud operations. And we've been very happy and proud to be partnering with Russian government shutdown. >>Yeah, Terra form gets very high marks from customers. The a lot of value there. The inner side integration adds to that value. Let's stay on cloud native for a minute. We all talk about cloud native cady was sort of mentioning before you got the the core apps, uh you want to protect those, make sure their enterprise create but they gotta be cool as well for developers. You're connecting to other apps in the cloud or wherever. How are you guys thinking about this? Cloud native trend? What other movies are you making in this regard? >>I mean cloud native is there is one of the paramount I. D. Trends of today and we're seeing massive amounts of adoption of cloud native architecture in all modern applications. Now, Cloud Native has become synonymous with kubernetes these days and communities has emerged as a de facto cloud native platform for modern cloud native app development. Now, what Cisco has done is we have created a brand new SAs delivered kubernetes service that is integrated with inter site, we call it the inter site community service for A. Ks. And this just geared a little over one month ago. Now, what interstate kubernetes service does is it delivers a cloud managed and cloud delivered kubernetes service that can be deployed on any supported target infrastructure. It could be a Cisco infrastructure, it could be a third party infrastructure or it could even be public club. But think of it as kubernetes anywhere delivered as says, managed from inside. It's a very powerful capability that we've just released into inter site to enable the power of communities and clog native to be used to be used anywhere. But today we made a very important aspect because we are today announced the brand new Cisco service mess manager, the Cisco service mesh manager, which is available as an extension to the KS are doing decide basically we see service measures as being the future of networking right in the past we had layer to networking and layer three networking and now with service measures, application networking and layer seven networking is the next frontier of, of networking. But you need to think about networking for the application age very differently how it is managed, how it is deployed. It needs to be ready, developer friendly and developer centric. And so what we've done is we've built out an application networking strategy and built out the service match manager as a very simple way to deliver application networking through the consumers, like like developers and application teams. This is built on an acquisition that Cisco made recently of Banzai Cloud and we've taken the assets of Banzai Cloud and deliver the Cisco service mesh manager as an extension to KS. That brings the promise of future networking and modern networking to application and development gives >>God thank you. BJ. And so Katie, let's let's let's wrap this up. I mean, there was a lot in this announcement today, a lot of themes around openness, heterogeneity and a lot of functionality and value. Give us your final thoughts. >>Absolutely. So, couple of things to close on, first of all, um Inner side is the simplest, most powerful hybrid cloud platform out there. It enables that that cloud operating model that VJ talked about, but enables that across cloud. So it's sad, it's relatively easy to get into it and give it a spin so that I'd highly encouraged anybody who's not familiar with it to try it out and anybody who is familiar with it to look at it again, because they're probably services in there that you didn't notice or didn't know last time you looked at it because we're moving so fast. So that's the first thing. The second thing I close with is um, we've been talking about this bridge that's kind of bridging, bridging uh your your on prem your open source, your cloud estates. And it's so important to to make that mental leap because uh in past generation, we used to talk about integrating technologies together and then with public cloud, we started talking about move to public cloud, but it's really how do we integrate, how do we integrate all of that innovation that's coming from the hyper scale, is everything they're doing to innovate superfast, All of that innovation is coming from open source, all of that innovation that's coming from from companies around the world, including Cisco, How do we integrate that to deliver an outcome? Because at the end of the day, if you're a cloud of Steam, if you're an idea of Steam, your job is to deliver an outcome and our mission is to make it super simple for you to do that. That's the mission we're on and we're hoping that everybody that's excited as we are about how simple we made that. >>Great, thank you a lot in this announcement today, appreciate you guys coming back on and help us unpack you know, some of the details. Thank thanks so much. Great having you. >>Thank you >>Dave in a moment. We're gonna come back and talk about disruptive technologies and futures in the age of hybrid cloud with Vegas Rattana and James leach. You're watching the cube, the global leader in high tech coverage. >>What if your server box >>wasn't a box at >>all? What if it could do anything run anything? >>Be any box you >>need with massive scale precision and intelligence managed and optimized from the cloud integrated with all your clouds, private, public or hybrid. So you can build whatever you need today and tomorrow. The potential of this box is unlimited. Unstoppable unseen ever before. Unbox the future with Cisco UCS X series powered by inter site >>Cisco. >>The bridge to possible. Yeah >>we're here with Vegas Rattana who's the director of product management for Pcs at Cisco. And James Leach is the director of business development for U. C. S. At the Cisco as well. We're gonna talk about computing in the age of hybrid cloud. Welcome gentlemen. Great to see you. >>Thank you. >>Thank you because let's start with you and talk about a little bit about computing architectures. We know that they're evolving. They're supporting new data intensive and other workloads especially as high performance workload requirements. What's this guy's point of view on all this? I mean specifically interested in your thoughts on fabrics. I mean it's kind of your wheelhouse, you've got accelerators. What are the workloads that are driving these evolving technologies and how how is it impacting customers? What are you seeing? >>Sure. First of all, very excited to be here today. You're absolutely right. The pace of innovation and foundational platform ingredients have just been phenomenal in recent years. The fabric that's writers that drives the processing power, the Golden city all have been evolving just an amazing place and the peace will only pick up further. But ultimately it is all about applications and the way applications leverage those innovations. And we do see applications evolving quite rapidly. The new classes of applications are evolving to absorb those innovations and deliver much better business values. Very, very exciting time step. We're talking about the impact on the customers. Well, these innovations have helped them very positively. We do see significant challenges in the data center with the point product based approach of delivering these platforms, innovations to the applications. What has happened is uh, these innovations today are being packaged as point point products to meet the needs of a specific application and as you know, the different applications have no different needs. Some applications need more to abuse, others need more memory, yet others need, you know, more course, something different kinds of fabrics. As a result, if you walk into a data center today, it is very common to see many different point products in the data center. This creates a manageability challenge. Imagine the aspect of managing, you know, several different form factors want you to you purpose built servers. The variety of, you know, a blade form factor, you know, this reminds me of the situation we had before smartphones arrived. You remember the days when you when we used to have a GPS device for navigation system, a cool music device for listening to the music. A phone device for making a call camera for taking the photos right? And we were all excited about it. It's when a smart phones the right that we realized all those cool innovations could be delivered in a much simpler, much convenient and easy to consume through one device. And you know, I could uh, that could completely transform our experience. So we see the customers were benefiting from these innovations to have a way to consume those things in a much more simplistic way than they are able to go to that. >>And I like to look, it's always been about the applications. But to your point, the applications are now moving in a much faster pace. The the customer experience is expectation is way escalated. And when you combine all these, I love your analogy there because because when you combine all these capabilities, it allows us to develop new Applications, new capabilities, new customer experiences. So that's that I always say the next 10 years, they ain't gonna be like the last James Public Cloud obviously is heavily influencing compute design and and and customer operating models. You know, it's funny when the public cloud first hit the market, everyone we were swooning about low cost standard off the shelf servers in storage devices, but it quickly became obvious that customers needed more. So I wonder if you could comment on this. How are the trends that we've seen from the hyper scale, Is how are they filtering into on prem infrastructure and maybe, you know, maybe there's some differences there as well that you could address. >>Absolutely. So I'd say, first of all, quite frankly, you know, public cloud has completely changed the expectations of how our customers want to consume, compute, right? So customers, especially in a public cloud environment, they've gotten used to or, you know, come to accept that they should consume from the application out, right? They want a very application focused view, a services focused view of the world. They don't want to think about infrastructure, right? They want to think about their application, they wanna move outward, Right? So this means that the infrastructure basically has to meet the application where it lives. So what that means for us is that, you know, we're taking a different approach. We're we've decided that we're not going to chase this single pane of glass view of the world, which, frankly, our customers don't want, they don't want a single pane of glass. What they want is a single operating model. They want an operating model that's similar to what they can get at the public with the public cloud, but they wanted across all of their cloud options they wanted across private cloud across hybrid cloud options as well. So what that means is they don't want to just consume infrastructure services. They want all of their cloud services from this operating model. So that means that they may want to consume infrastructure services for automation Orchestration, but they also need kubernetes services. They also need virtualization services, They may need terror form workload optimization. All of these services have to be available, um, from within the operating model, a consistent operating model. Right? So it doesn't matter whether you're talking about private cloud, hybrid cloud anywhere where the application lives. It doesn't matter what matters is that we have a consistent model that we think about it from the application out. And frankly, I'd say this has been the stumbling block for private cloud. Private cloud is hard, right. This is why it hasn't been really solved yet. This is why we had to take a brand new approach. And frankly, it's why we're super excited about X series and inter site as that operating model that fits the hybrid cloud better than anything else we've seen >>is acute. First, first time technology vendor has ever said it's not about a single pane of glass because I've been hearing for decades, we're gonna deliver a single pane of glass is going to be seamless and it never happens. It's like a single version of the truth. It's aspirational and, and it's just not reality. So can we stay in the X series for a minute James? Uh, maybe in this context, but in the launch that we saw today was like a fire hose of announcements. So how does the X series fit into the strategy with inter site and hybrid cloud and this operating model that you're talking about? >>Right. So I think it goes hand in hand, right. Um the two pieces go together very well. So we have uh, you know, this idea of a single operating model that is definitely something that our customers demand, right? It's what we have to have, but at the same time we need to solve the problems of the cost was talking about before we need a single infrastructure to go along with that single operating model. So no longer do we need to have silos within the infrastructure that give us different operating models are different sets of benefits when you want infrastructure that can kind of do all of those configurations, all those applications. And then, you know, the operating model is very important because that's where we abstract the complexity that could come with just throwing all that technology at the infrastructure so that, you know, this is, you know, the way that we think about is the data center is not centered right? It's no longer centered applications live everywhere. Infrastructure lives everywhere. And you know, we need to have that consistent operating model but we need to do things within the infrastructure as well to take full advantage. Right? So we want all the sas benefits um, of a Ci CD model of, you know, the inter site can bring, we want all that that proactive recommendation engine with the power of A I behind it. We want the connected support experience went all of that. They want to do it across the single infrastructure and we think that that's how they tie together, that's why one or the other doesn't really solve the problem. But both together, that's why we're here. That's why we're super excited. >>So Vegas, I make you laugh a little bit when I was an analyst at I D C, I was deep in infrastructure and then when I left I was doing, I was working with application development heads and like you said, uh infrastructure, it was just a, you know, roadblock but but so the target speakers with Cisco announced UCS a decade ago, I totally missed it. I didn't understand it. I thought it was Cisco getting into the traditional server business and it wasn't until I dug in then I realized that your vision was really to transform infrastructure, deployment and management and change them all. I was like, okay, I got that wrong uh but but so let's talk about the the ecosystem and the joint development efforts that are going on there, X series, how does it fit into this, this converged infrastructure business that you've, you've built and grown with partners, you got storage partners like Netapp and Pure, you've got i SV partners in the ecosystem. We see cohesive, he has been a while since we we hung out with all these companies at the Cisco live hopefully next year, but tell us what's happening in that regard. >>Absolutely, I'm looking forward to seeing you in the Cisco live next year. You know, they have absolutely you brought up a very good point. You see this is about the ecosystem that it brings together, it's about making our customers bring up the entire infrastructure from the core foundational hardware all the way to the application level so that they can, you know, go off and running pretty quick. The converse infrastructure has been one of the corners 2.5 hour of the strategy, as you pointed out in the last decade. And and and I'm I'm very glad to share that converse infrastructure continues to be a very popular architecture for several enterprise applications. Seven today, in fact, it is the preferred architecture for mission critical applications where performance resiliency latency are the critical requirements there almost a de facto standards for large scale deployments of virtualized and business critical data bases and so forth with X series with our partnerships with our Stories partners. Those architectures will absolutely continue and will get better. But in addition as a hybrid cloud world, so we are now bringing in the benefits of canvas in infrastructure uh to the world of hybrid cloud will be supporting the hybrid cloud applications now with the CIA infrastructure that we have built together with our strong partnership with the Stories partners to deliver the same benefits to the new ways applications as well. >>Yeah, that's what customers want. They want that cloud operating model. Right, go ahead please. >>I was going to say, you know, the CIA model will continue to thrive. It will transition uh it will expand the use cases now for the new use cases that were beginning to, you know, say they've absolutely >>great thank you for that. And James uh have said earlier today, we heard this huge announcement, um a lot of lot of parts to it and we heard Katie talk about this initiative is it's really computing built for the next decade. I mean I like that because it shows some vision and you've got a road map that you've thought through the coming changes in workloads and infrastructure management and and some of the technology that you can take advantage of beyond just uh, you know, one or two product cycles. So, but I want to understand what you've done here specifically that you feel differentiates you from other competitive architectures in the industry. >>Sure. You know that's a great question. Number one. Number two, um I'm frankly a little bit concerned at times for for customers in general for our customers customers in general because if you look at what's in the market, right, these rinse and repeat systems that were effectively just rehashes of the same old design, right? That we've seen since before 2000 and nine when we brought you C. S to market these are what we're seeing over and over and over again. That's that's not really going to work anymore frankly. And I think that people are getting lulled into a false sense of security by seeing those things continually put in the market. We rethought this from the ground up because frankly future proofing starts now, right? If you're not doing it right today, future proofing isn't even on your radar because you're not even you're not even today proved. So we re thought the entire chassis, the entire architecture from the ground up. Okay. If you look at other vendors, if you look at other solutions in the market, what you'll see is things like management inside the chassis. That's a great example, daisy chaining them together >>like who >>needs that? Who wants that? Like that kind of complexity is first of all, it's ridiculous. Um, second of all, um, if you want to manage across clouds, you have to do it from the cloud, right. It's just common sense. You have to move management where it can have the scale and the scope that it needs to impact your entire domain, your world, which is much larger now than it was before. We're talking about true hybrid cloud here. Right. So we had to solve certain problems that existed in the traditional architecture. You know, I can't tell you how many times I heard you talk about the mid plane is a great example. You know, the mid plane and a chastity is a limiting factor. It limits us on how much we can connect or how much bandwidth we have available to the chassis. It limits us on air flow and other things. So how do you solve that problem? Simple. Just get rid of it. Like we just we took it out, right. It's not no longer a problem. We designed an architecture that doesn't need it. It doesn't rely on it. No forklift upgrades. So, as we start moving down the path of needing liquid cooling or maybe we need to take advantage of some new, high performance, low latency fabrics. We can do that with almost. No problem at all. Right, So, we don't have any forklift upgrades. Park your forklift on the side. You won't need it anymore because you can upgrade gradually. You can move along as technologies come into existence that maybe don't even exist. They they may not even be on our radar today to take advantage of. But I like to think of these technologies, they're really important to our customers. These are, you know, we can call them disruptive technologies. The reality is that we don't want to disrupt our customers with these technologies. We want to give them these technologies so they can go out and be disruptive themselves. Right? And this is the way that we've designed this from the ground up to be easy to consume and to take advantage of what we know about today and what's coming in the future that we may not even know about. So we think this is a way to give our customers that ultimate capability flexibility and and future proofing. >>I like I like that phrase True hybrid cloud. It's one that we've used for years and but to me this is all about that horizontal infrastructure that can support that vision of what true hybrid cloud is. You can support the mission critical applications. You can you can develop on the system and you can support a variety of workload. You're not locked into one narrow stovepipe and that does have legs, Vegas and James. Thanks so much for coming on the program. Great to see you. >>Yeah. Thank you. Thank you. >>When we return shortly thomas Shiva who leads Cisco's data center group will be here and thomas has some thoughts about the transformation of networking I. T. Teams. You don't wanna miss what he has to say. You're watching the cube. The global leader in high tech company. Okay, >>mm. Mhm, mm. Okay. Mhm. Yeah. Mhm. Yeah. >>Mhm. Yes. Yeah. Okay. We're here with thomas Shiva who is the Vice president of Product Management, A K A VP of all things data center, networking STN cloud. You name it in that category. Welcome thomas. Good to see you again. >>Hey Sam. Yes. Thanks for having me on. >>Yeah, it's our pleasure. Okay, let's get right into observe ability. When you think about observe ability, visibility, infrastructure monitoring problem resolution across the network. How does cloud change things? In other words, what are the challenges that networking teams are currently facing as they're moving to the cloud and trying to implement hybrid cloud? >>Yeah. Yeah, visibility as always is very, very important. And it's quite frankly, it's not just it's not just the networking team is actually the application team to write. And as you pointed out, the underlying impetus to what's going on here is the data center is where the data is. And I think we set us a couple years back and really what happens the applications are going to be deployed uh in different locations, right. Whether it's in a public cloud, whether it's on prayer, uh, and they are built differently right there, built as microservices, they might actually be distributed as well at the same application. And so what that really means is you need as an operator as well as actually a user better visibility. Where are my pieces and you need to be able to correlate between where the app is and what the underlying network is that is in place in these different locations. So you have actually a good knowledge while the app is running so fantastic or sometimes not. So I think that's that's really the problem statement. What what we're trying to go afterwards, observe ability. >>Okay, and let's double click on that. So a lot of customers tell me that you gotta stare at log files until your eyes bleed and you gotta bring in guys with lab coats who have phds to figure all this stuff out. So, so you just described, it's getting more complex, but at the same time you have to simplify things. So how how are you doing that, >>correct? So what we basically have done is we have this fantastic product that that is called 1000 Ice. And so what this does is basically as the name, which I think is a fantastic fantastic name. You have these sensors everywhere. Um, and you can have a good correlation on uh links between if I run from a site to aside from a site to a cloud, from a cloud to cloud and you basically can measure what is the performance of these links. And so what we're, what we're doing here is we're actually extending the footprint of these thousands agent. Right? Instead of just having uh inversion machine clouds, we are now embedding them with the Cisco network devices. Right? We announced this with the catalyst 9000 and we're extending this now to our 8000 catalyst product line for the for the SD were in products as well as to the data center products the next line. Um and so what you see is is, you know, half a saying, you have 1000 eyes, you get a million insights and you get a billion dollar of improvements uh for how your applications run. And this is really uh, the power of tying together the footprint of where the network is with the visibility, what is going on. So you actually know the application behavior that is attached to this network. >>I see. So okay. So as the cloud evolves and expands it connects your actually enabling 1000 eyes to go further, not just confined within a single data center location, but out to the network across clouds, et cetera, >>correct. Wherever the network is, you're going to have 1000 I sensor and you can't bring this together and you can quite frankly pick if you want to say, hey, I have my application in public cloud provider, a uh, domain one and I have another one domain to, I can't do monitor that link. I can also monitor have a user that has a campus location or branch location. I kind of put an agent there and then I can monitor the connectivity from that branch location all the way to the let's say corporations that data centre, our headquarter or to the cloud. And I can have these probes and just we have visibility and saying, hey, if there's a performance, I know where the issue is and then I obviously can use all the other foods that we have to address those. >>All right, let's talk about the cloud operating model. Everybody tells us it's really the change in the model that drives big numbers in terms of R. O. I. And I want you to maybe address how you're bringing automation and devops to this world of of hybrid and specifically how is Cisco enabling I. T. Organizations to move to a cloud operating model? Is that cloud definition expands? >>Yeah, no that's that's another interesting topic beyond the observe ability. So really, really what we're seeing and this is going on for uh I want to say a couple of years now, it's really this transition from operating infrastructure as a networking team more like a service like what you would expect from a cloud provider. Right? It's really around the network team offering services like a cloud provided us. And that's really what the meaning is of cloud operating model. Right? But this is infrastructure running your own data center where that's linking that infrastructure was whatever runs on the public club is operating and like a cloud service. And so we are on this journey for why? So one of the examples uh then we have removing some of the control software assets, the customers that they can deploy on prayer uh to uh an instance that they can deploy in a cloud provider and just busy, insane. She ate things there and then just run it that way. Right. And so the latest example for this is what we have our identity service engine that is now limited availability available on AWS and will become available in mid this year, both in Italy as unusual as a service. You can just go to market place, you can load it there and now you create, you can start running your policy control in a cloud, managing your access infrastructure in your data center, in your campus wherever you want to do it. And so that's just one example of how we see our customers network operations team taking advantage of a cloud operating model and basically employing their, their tools where they need them and when they need them. >>So what's the scope of, I hope I'm saying it right. Ice, right. I see. I think it's called ice. What's the scope of that like for instance, turn in effect my or even, you know, address simplify my security approach. >>Absolutely. That's now coming to what is the beauty of the product itself? Yes. What you can do is really is that there's a lot of people talking about else. How do I get to zero trust approach to networking? How do I get to a much more dynamic, flexible segmentation in my infrastructure. Again, whether this is only campus X as well as a data center and Ice help today, you can use this as a point to define your policies and then any connect from there. Right. In this particular case we would instant Ice in the cloud as a software load. You now can connect and say, hey, I want to manage and program my network infrastructure and my data center on my campus, going to the respective control over this DNA Center for campus or whether it is the A. C. I. Policy controller. And so yes, what you get as an effect out of this is a very elegant way to automatically manage in one place. What is my policy and then drive the right segmentation in your network infrastructure? >>zero. Trust that, you know, it was pre pandemic. It was kind of a buzzword. Now it's become a mandate. I wonder if we could talk about right. I mean I wonder if you talk about cloud native apps, you got all these developers that are working inside organizations. They're maintaining legacy apps. They're connecting their data to systems in the cloud there, sharing that data. I need these developers, they're rapidly advancing their skill sets. How is Cisco enabling its infrastructure to support this world of cloud? Native making infrastructure more responsive and agile for application developers? >>Yeah. So, you know, we're going to the top of his visibility, we talked about the operating model, how how our network operators actually want to use tools going forward. Now, the next step to this is it's not just the operator. How do they actually, where do they want to put these tools, how they, how they interact with these tools as well as quite frankly as how, let's say, a devops team on application team or Oclock team also wants to take advantage of the program ability of the underlying network. And this is where we're moving into this whole cloud native discussion, right? Which is really two angles, that is the cloud native way, how applications are being built. And then there is the cloud native way, how you interact with infrastructure. Right? And so what we have done is we're a putting in place the on ramps between clouds and then on top of it we're exposing for all these tools, a P I S that can be used in leverage by standard uh cloud tools or uh cloud native tools. Right. And one example or two examples we always have and again, we're on this journey for a while is both answerable uh script capabilities that exist from red hat as well as uh Ashitaka from capabilities that you can orchestrate across infrastructure to drive infrastructure, automation and what what really stands behind it is what either the networking operations team wants to do or even the ap team. They want to be able to describe the application as a code and then drive automatically or programmatically in situation of infrastructure needed for that application. And so what you see us doing is providing all these capability as an interface for all our network tools. Right. Whether it's this ice that I just mentioned, whether this is our D. C. And controllers in the data center, uh whether these are the controllers in the in the campus for all of those, we have cloud native interfaces. So operator or uh devops team can actually interact directly with that infrastructure the way they would do today with everything that lives in the cloud, with everything how they brought the application. >>This is key. You can't even have the conversation of op cloud operating model that includes and comprises on prem without programmable infrastructure. So that's that's very important. Last question, thomas our customers actually using this, they made the announcement today. There are there are there any examples of customers out there doing this? >>We do have a lot of customers out there that are moving down the past and using the D. D. Cisco high performance infrastructure, but also on the compute side as well as on an exercise one of the customers. Uh and this is like an interesting case. It's Rakuten uh record and is a large tackle provider, a mobile five G. Operator uh in Japan and expanding and is in different countries. Uh and so people something oh, cloud, you must be talking about the public cloud provider, the big the big three or four. But if you look at it, there's a lot of the tackle service providers are actually cloud providers as well and expanding very rapidly. And so we're actually very proud to work together with with Rakuten and help them building a high performance uh, data and infrastructure based on hard gig and actually phone a gig uh to drive their deployment to. It's a five G mobile cloud infrastructure, which is which is uh where the whole the whole world where traffic is going. And so it's really exciting to see this development and see the power of automation visibility uh together with the high performance infrastructure becoming reality and delivering actually services, >>you have some great points you're making there. Yes, you have the big four clouds, your enormous, but then you have a lot of actually quite large clouds. Telcos that are either approximate to those clouds or they're in places where those hyper scholars may not have a presence and building out their own infrastructure. So so that's a great case study uh thomas, hey, great having you on. Thanks so much for spending some time with us. >>Yeah, same here. I appreciate it. Thanks a lot. >>I'd like to thank Cisco and our guests today V Joy, Katie VJ, viscous James and thomas for all your insights into this evolving world of hybrid cloud, as we said at the top of the next decade will be defined by an entirely new set of rules. And it's quite possible things will evolve more quickly because the cloud is maturing and has paved the way for a new operating model where everything is delivered as a service, automation has become a mandate because we just can't keep throwing it labor at the problem anymore. And with a I so much more as possible in terms of driving operational efficiencies, simplicity and support of the workloads that are driving the digital transformation that we talk about all the time. This is Dave Volonte and I hope you've enjoyed today's program. Stay Safe, be well and we'll see you next time.

>>From around the globe. It's the Cube with digital coverage of IBM think 2021 brought to you by >>IBM. Welcome back to IBM Think 2021. This is the cubes ongoing coverage where we go out to the events, we extract the signal from the noise of course, virtually in this case now we're going to talk about ecosystems, partnerships in the flywheel, they deliver in the technology business and with me or Jason kelly, general manager, global strategic partnerships, IBM global business services and Mani Das Gupta, who is the vice president of marketing for IBM Global Business services folks. It's great to see you again in which we're face to face. But this will have to do >>good to see you Dave and uh same, I wish we were face to face but uh we'll we'll go with this >>soon. We're being patient, Jason. Let's start with you. You have a partner strategy. I wonder if you could sort of summarize that and tell us more about it. >>So it's interesting that we start with the strategy because you said we have a partner strategy dave and I'd say that the market has dictated back to us a partner strategy something that we it's not new and we didn't start it yesterday. It's something that we continue to evolve and build even stronger. This thought of a partner strategy is it nothing is better than the thought of a partner ship. And people say oh well you know you got to work together as one team and as a partner And it sounds almost as a 1-1 type relationship. Our strategies is much different than that. David our execution is even better and that that execution is focused on now. The requirement that the market our clients are showing to us and our strategic partners that one player can't deliver all their needs, they can't Design solution and deliver that from one place. It does take an ecosystem to the word that you called out. This thought of an ecosystem and our strategy and execution is focused on that. And the reason why I say it evolves is because the market will continue to evolve and this thought of being able to look at a client's let's call it a a workflow, let's call it a value chain from one end to the other, wherever they start their process to wherever it ultimately hits that end user. It's going to take many players to cover that. And then we, as IBM want to make sure that we are the general contractor of that capability with the ability to convene the right strategic partners, bring out the best value for that outcome, not just technology for technology's sake, but the outcome that the incline is looking for so that we bring value to our strategic partners and that in client. >>I think about when you talk about the value chain, you know, I'm imagining, you know, the business books years ago you see the conceptual value chain, you can certainly understand that you can put processes together to connect them and now you've got technology, I think of a P. I. S. It's it's really supports that everything gets accelerated and and uh money. I wonder if you could address some of the the go to market how this notion of of ecosystem which is so important, is impacting the way in which you go to market. >>Absolutely. So modern business, you know, demands a new approach to working the ecosystem. Thought that Jason was just alluding to, it's a mutual benefit of all these companies working together in the market, it's a mutual halo of the brands, so as responsible for the championship of the IBM and the global business services brand. I am very, very interested in this mutual working together. It should be a win win win, as we say in the market, it should be a win for our clients, first and foremost, it should be a win for our partners and it should be a win for IBM and we are working together right now on an approach to bring this, go to market strategy to life. >>So I wonder if we could maybe talk about how this actually works and and pull in some examples, uh you must have some favorites that that we can touch on. Uh is that, is that fair? Can we, can we name some names, >>sure names, always working debut, right. And it's always in context of reality that we can talk about, as I said, this execution and not just a strategy. And I'll start with probably what's right in the front of many people's minds as we're doing this virtually because of what because of an unfortunate pandemic, um, this disastrous loss of life and things that have taken us down a path. We go well, how do we, how do we address that? Well, any time there's a tough task, IBM raises its hand first. You know, whether it was putting a person on the moon and bringing them home safely or standing up a system behind the current Social Security Administration, you know, during the Depression, you pick it well here we are now. And why not start with that as an example? Because I think it calls out just what we mentioned here first day, this thought of a, of an ecosystem because the first challenge, how do we create uh and address the biggest data puzzle of our lives, which is how do we get this vaccine created in record time, which it was the fastest before that was four years. This was a matter of months. Visor created the first one out and then had to get it out to distribution. Behind. That is a wonderful partner of R. S. A. P. Trying to work with that. So us working with S. A. P. Along with Pfizer in order to figure out how to get that value chain. And some would say supply chain, but I'll address that in a second. But there's many players there. And so we were in the middle of that with fires are committed to saying, how do we do that with S. A. P. So now you see players working together as one ecosystem. But then think about the ecosystem that that's happening where you have a federal government agency, a state, a local, you have healthcare, life science industry, you have consumer industry. Oh wait a second day. This is getting very complicated, Right? Well, this is the thought of convening an ecosystem and this is what I'm telling you is our execution and it has worked well. And so it's it's it's happening now. We still it's we see it's still developing and being, being, you know, very productive in real time. But then I said there was another example and that's with me, you mani whomever you pick the consumer. Ultimately we are that outcome of of the value chain. That's why I said, I don't want to just call it a supply chain because at the end is a someone consuming and in this case we need a shot. And so we partnered with Salesforce, IBM and Salesforce saying, wait a minute, that's not a small task. It's not just get the content there and put it in someone's arm instead they're scheduling that must be done. There's follow up an entire case management like system sells force is a master at this, so work dot com team with IBM, we sit now let's get that part done for the right type of UI UX capability that the user experience, user interaction interface and then also in bringing another player in the ecosystem, one of ours Watson health along with our block changing, we brought together something called a Digital Health pass. So I've just talked about two ecosystems work multiple ecosystems working together. So you think of an ecosystem of ecosystems. I called out Blockchain technology and obviously supply chain but there's also a I I O T. So you start to see where look this is truly an orchestration effort. It has to happen with very well designed capability and so of course we master and design and tying that that entire ecosystem together and convening it so that we get to the right outcome you me money all getting into shot being healthy. That's a real time example of us working with an ecosystem and teeming with key strategic partners, >>you know, money, I mean Jason you're right. I mean pandemics been horrible, I have to say. I'm really thankful it didn't happen 20 years ago because it would have been like okay here's some big pcs and a modem and go ahead and figure it out. So I mean the tech industry has saved business. I mean with not only we mentioned ai automation data, uh even things basic things like security at the end point. I mean so many things and you're right, I mean IBM in particular, other large companies you mentioned ASAP you have taken the lead and it's really I don't money, I don't think the tech industry gets enough credit, but I wonder if there's some of your favorite, you know, partnerships that you can talk about. >>Yeah, so I'm gonna I'm gonna build on what you just said. Dave IBM is in this unique position amongst this ecosystem. Not only the fact that we have the world leading most innovative technologies to bring to bear, but we also have the consulting capabilities that go with it now to make any of these technologies work towards the solution that Jason was referring to in this digital health pass, it could be any other solution you would need to connect these disparate systems, sometimes make them work towards a common outcome to provide value to the client. So I think our role as IBM within this ecosystem is pretty unique in that we are able to bring both of these capabilities to bear. In terms of you know, you asked about favorite there are this is really a coop petition market where everybody has products, everybody has service is the most important thing is how how are we bringing them all together to serve the need or the need of the hour in this case, I would say one important thing in this. As you observe how these stories are panning out in an ecosystem in in part in a partnership, it is about the value that we provide to our clients together. So it's almost like a cell with model from from a go to market perspective, there is also a question of our products and services being delivered through our partners. Right? So think about the span and scope of what we do here. And so that's the sell through. And then of course we have our products running within our partner companies and our partner products, for example. Salesforce running within IBM. So this is a very interesting and a new way of doing business. I would say it's almost like the modern way of doing business with modernity. >>Well. And you mentioned cooperation. I mean you're you're part of IBM that will work with anybody because your customer first, whether it's a W. S. Microsoft oracle is a is a is a really tough competitor. But your customers are using oracle and they're using IBM. So I mean as a those are some good examples. I think of your point about cooper Titian. >>Absolutely. If you pick on any other client, I'll mention in this case. Delta, Delta was working with us on moving, being more agile. Now this pandemic has impacted the airline sector particularly hard, right With travel stopping and anything. So they are trying to get to a model which will help them scale up, scale down, be more agile will be more secure, be closer to their customers, try and understand how they can provide value to their customers and customers better. So we are working with Delta on moving them to cloud on the journey to cloud. Now that public cloud could be anything. The beauty of this model and a hybrid cloud approach is that you are able to put them on red hat open shift, you're able to do and package the services into a microservices kind of a model. You want to make sure all the applications are running on a portable, almost platform. Agnostic kind of a model. This is the beauty of this ecosystem that we are discussing is the ability to do what's right for the end customer at the end of the day, >>how about some of the like sass players, like some of the more prominent ones and we watched the ascendancy of service now and and, and work day, you mentioned Salesforce. How do you work with those guys? Obviously there's an Ai opportunity, but maybe you could add some, you know, color there. >>So I like the fact that you call out the different hyper scholars for example, uh whether it's a W. S, whether it's Microsoft, knowing that they have their own cloud instances, for example. And when you, when you mentioned, he had this happened a long time ago, you know, you start talking about the heft of the technology, I started thinking of all the truckloads of servers or whatever they have to pull up. We don't need that now because it can happen in the cloud and you don't have to pick one cloud or the other. And so when people say hybrid cloud, that's what comes out, you start to think of what I I call, you know, a hybrid of hybrids because I told you before, you know, these roles are changing. People aren't just buyers or suppliers, they're both. And then you start to say what we're different people supplying well in that ecosystem, we know there's not gonna be one player, there's gonna be multiple. So we partner by doing just what monty called out is this thought of integrating in hybrid environments on hybrid platforms with hybrid clouds, Multi clouds, maybe I want something on my premises, something somewhere else. So in giving that capability that flexibility we empower and this is what's doing that cooperation, we empower our partners are strategic partners, we want them to be better with us. And this is this thought of being able to actually bring more together and move faster which is almost counterintuitive. You're like wait a minute you're adding more players but you're moving faster. Exactly because we have the capability to integrate those those technologies and get that outcome that monty mentioned, >>I would add to this one. Jason you mentioned something very very interesting. I think if you want to go just fast you go alone but if you want to go further, you go together. And that is the core of our point of view in this case is that we want to go further and we want to create value that is long lasting. >>What about like so I get the technology players and there may be things that you do that others don't or vice versa. So the gap fillers etcetera. But what about how to maybe customers that they get involved? Perhaps government agencies, may they be they be customer or an N. G. O. As another example, Are they part of this value chain? Part of this ecosystem? >>Absolutely. I'll give you I'll stick with the same example when I mentioned a digital health past that Digital Health Pass is something that we have as IBM and it's a credential Think of it as a health credential not a vaccine passport because it could be used for a test for a negative test on Covid, it could be used for antibiotics. So if you have this credential, it's something that we, as IBM created years back and we were using it for learning. When you think of getting people uh certifications versus a four year diploma, how do we get people into the workforce? That was what was original. That was a jenny Rometty thought, let's focus on new collar workers. So we had this asset that we'd already created and then it's wait, there's a place for it to work with, with health, with validation verification on someone's option, it's optional. They choose it. Hey, I want to do it this way. Well, the state of new york said that they wanted to do it that way and they said, listen, we are going to have a digital health pass for all of our, all of our new york citizens and we want to make sure that it's equitable, it could be printed or on a screen and we want it to be designed in this way and we wanted to work on this platform and we want to be able to, to work with the strategic Partners, a Salesforce and ASAP and work. I mean, I can just keep and we said okay let's do this. And this is the start of collaboration and doing it by design. So we haven't lost that day but this only brings it to the forefront just as you said, yes, that is what we want. We want to make sure that in this ecosystem we have a way to ensure that we are bringing together convening not just point products or different service providers but taking them together and getting the best outcome so that that end user can have it configured in the way that they want it >>guys, we got to leave it there but it's clear you're helping your customers and your partners on this this digital transformation journey that we already we all talk about. You get this massive portfolio of capabilities, deep, deep expertise, I love the hybrid cloud and AI Focus, Jason and money really appreciate you coming back in the cubes. Great to see you both. >>Thank you so much. Dave Fantastic. All >>Right. And thank you for watching everybody's day Vigilante for the Cuban. Our continuous coverage of IBM, think 2021, the virtual edition. Keep it right there. Yeah. Mhm. Mhm. >>Mhm.

(upbeat music) >> Narrator: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is the Cube Conversation. >> Welcome to this Cube Conversation. I'm Lisa Martin, excited to talk to the CEO of Styra, Bill Mann today. Bill, welcome to the Cube. >> Hi Lisa, how are you doing? >> I'm doing well. I should say welcome back. You've been on the Cube at a previous company, but we're excited to talk to you today about Styra, what's going on? So let's go ahead and start informing our audience who Styra is and what you do? >> Sure, so who Styra is and what do we do? So Styra is a company that's focused on reinventing policy and authorization in the cloud native stack. We're the company that created an open source project called Open Policy Agent, it's part of CNCF. And on top of Open Policy Agent, we built a control plane, a management plane to help organizations really put OPA into production and operationalized OPA. >> An OPA is Open Policy Agent. That's what the company actually developed with CNCF, correct? >> So, we actually founded Open Policy Agent and then we contributed Open Policy Agent to CNCF. And the real goal of contributing the Open Policy Agent to CNCF was we believe that we want to get authorization defacto in the market, right? And the only way to get something out there that everybody uses is to put it into the open source and having an entity like the CNCF supporting the project. So, really it's about getting everybody, all enterprises and vendors to use Open Policy Agent as a way of solving authorization for the cloud native environment. >> So you say Styra is reinventing policy and authorization for cloud native applications, your target audience, security folks, developer folks, what changes has cloud native brought to security and development teams? >> Sure, so what changes has cloud native brought to security and development teams? So fundamentally there've been three changes in the marketplace. One, as you know we're shifting from this monolithic architecture of building applications to now this new distributed architectures of kubernetes, microservices and Deep-coupled architecture. So fundamentally the way we build applications is fundamentally changed because everybody wants to have scale up and scale down and so forth. Second, the way we actually developed software, we've moved now to a DevOps model where we're doing more things earlier on in the cycle so we can innovate faster and we're producing code on an hourly basis versus when I joined the industry which was probably three releases a year. And then thirdly which is kind of a major topic that all of us kind of understand is our focus on privacy and security is higher than it's been before. And if these applications are going to be way more complex and more distributed and we're going to innovate faster than the way we focus on security and privacy has to be done differently as well. And if we don't do it differently, then we're going to have to all the breaches that we had in the previous generation of the app stack. >> And we don't want that, but you're right privacy and security are increasing concerns in any environment. How do you help address those and also with the thought of privacy and security are going to be concerned for quite a long time? >> Yeah, so let me take a step back. So how do we address privacy and security? So, at a fundamental level, authorization is a foundational part of security and authorization has never really been solved or re-imagined ever for the last 50 years or so. Every application developer or security vendor has built authorization into their own stack and done it in a very proprietary way. And it's been locked away within these applications and these stacks and so forth. So what happens now when you've got a highly distributed environment is that you've got so many moving parts, you still need to apply authorization. So, the way we've tackled it is by building Open Policy Agent. And there's three fundamental kind of tenants around Open Policy Agent that make it really ideal for this cloud native environment. Number one, it's policy as code and everything in the market now, everything is as code. You buy infrastructure as code. So this is now policy as code. So you can describe in a declarative model, how you want the policy for a system to be developed and you can use the language called Rego to do that. Second is the fact that all the cloud native projects out there which are all developed based upon open source technologies, kubernetes, microservices, envoy, SDO, cafco, all these kinds of buzzwords you hear in the marketplace, they all integrate with Open Policy Agent already. And then thirdly the architecture of Open Policy Agent is that it's distributed, which means that it's ideally suited for this distributed architecture for cloud native. And those are the three kind of characteristics of Open Policy Agent leading to developers loving it. And when I say they love it, we've got hundreds and thousands of users of Open Policy Agent. When you go to the CNCF shows co op con earlier this year and there's two more coming this year. There's many, many talks on it. You've got cloud vendors like Google and Microsoft adopting Open Policy Agent, got a lot of enterprises adopting Open Policy Agent. So, that's really fundamentally what we've built is we've built an authorization architecture for this new world to really address the security and privacy concerns, which have always existed and I'm going to be more exponential in this new world. >> And I think you've also built a community around OPA. Can you share a little bit of information about that and how they help with the co-development and even some of the other things that you're commercializing? >> Sure, yeah. So, now what have we done in from a community point of view with Open Policy Agents? So yeah, the community is a integral part of any open source project and we're lucky to have a great community. We've got a great community of enterprise users of Open Policy Agents and vendors as well, vendors like Microsoft and Google who are now contributing to OPA and building it up. And for me, the most important part of a community is that you learn how enterprises are using your software and they share ideas and they share use cases and you're able to innovate really, really fast. And what we've learned from that is the use cases that they use Open Policy Agent for, for instance, one of the major use cases for Open Policy Agent is for kubernetes Admission Control. So, essentially we can test the configuration of an application which is described in a file called YAML before it goes into production. So, think of it as pre-production tests, but companies are using it for microservices and applications and data and so forth. So, it helps us understand what they're using it for, but also we use it to help us develop our commercial product, which is the management control plane for OPA. So, we learn about what they're missing in the open source project that we can use to build our commercial product >> which is ready for enterprise use. >> So you've had a lot of success with OPA. Talk to me about Styra DAS and why the need for that? >> Sure, so why do we need Styra DAS recognizing that OPA is very, very successful. So, the fundamental difference is OPA is a very focused on developers and it's very focused on an environment for an individual node or cluster, but it doesn't have all the enterprise features necessary for a real enterprise to go into production. So what we notice is companies use OPA for pre-production, but when they want to go into production, they need a user interface. They need a way to author policies, distribute policies, monitor policies, do impact analysis and a whole bunch of other features and capabilities that are needed for enterprise deployments and so forth. So that's a fundamental difference between OPA and the commercial product. The commercial product is really operationalizing in OPA for an enterprise deployment. >> So the relationship between Styra and OPA seems very collaborative to me that what you just described with the commercial product of Styra DAS is really one that was developed based on what the OPA community and Styra have learned together? >> Correct, Yes. So, OPA was created by the CTO, the founders of the company saw early on several years ago, the need for distributed architectures and the need for unified policy so they left and created OPA. And from day one they wanted to get OPA into everybody's hands. That's why they contributed it to open source as part of CNCF. And then the next kind of strategy is to focus on the control apps aspects, the enterprise aspect. So yes, the same team that created OPA is the same team that's creating the Styra DAS commercial offering as well. >> So from the enterprise perspective, talk to me about some of the companies that you're talking to. I imagine any organization that's focused on cloud native, but any industry in particular that you see is really kind of leading edge right now? >> Yeah, so which industries are we talking to in terms of using Styra DAS and OPA? What we've actually found it's across the board. And we've seen in the early days that financial services and high tech were using OPA, but now it's really across the board. So it's all verticals really. And what we've noticed is any organization which is going through a cloud transformation project where they're either building new applications based upon cloud native app stacks like kubernetes and microservices and so forth or shift to the cloud are the companies that are also adopting OPA and the Styra DAS product, right? Because it's all part of the same solution set. And what we're noticing now and this is a fundamental difference is platform architects and developers are kind of prime to use these technologies. They learn about these technologies by going to the conferences and unlike the past which was very much top down selling from the sea level down, this is very much bottomed up. So developers learn about OPA from going to the conferences. They use it within their own environment and then they tell their management that, "Look, we're using OPA already. "We're missing these capabilities," or they come to us and we educate them about the Styra DAS product and so forth. So it's a very different sales model as well and that's why it's very important for ourselves and any open source company to really keep developers happy and provide a solution, that's meeting their requirements. >> On that side with so many of us and developers included working from home for the past nearly four months. We now are doing things like this virtual conversations, virtual events, how is Styra helping to continue to feed and educate those developers so that they can understand how you can impact their job functions and how they can then elevate you guys up the stack. >> Sure, so what's changed over the last three months or so in the market as a consequence of COVID-19 and from an educational point of view. So, what we've seen is fundamentally in the early days of COVID-19 everybody was kind of get the head around how to work from home and so forth, but what we've seen across the all verticals is developers have now really focused on educating themselves and just as a data point and the audience that we get to the OPA website is as high as it's ever been for the last three months. And what we're doing as a company is a lot of training sessions, video content, write-ups, blogs and so forth, right? And really helping the community learn about OPA and how to solve these kind of fundamental problems around policy and authorization within the environment. We've also been helped by the community as well. So there's been talks about a number of companies, Microsoft, Google, Palo Alto had a talk and many many companies are talking about OPA now and I love it because ultimately being an open source company and building a project which we want to become defacto, we want to raise the bar for security across the world, right? And if we can do that then it's going to be an achievement for us and it's very gratifying knowing that we're really fixing security problems for organizations because ultimately we always want to be able to use an application or a banking service and not worry about privacy and security concerns and that's ultimately what we're all after. But this is such a fundamental component that once we want to have developers learn this now because if they can incorporate this into the DevOps app stack then in future years when these applications are built and they're exposed there'll be more secure. >> And so it sounds like maybe there's even more engagement now during COVID when everybody is at home. Tell me about some of the things that are coming down the pipe for Styra in light of all of this exciting collaboration with the community. >> Sure, yeah. There's definitely been way more collaboration as a consequence of COVID-19. People are at home and they're focusing and they're going through learning sessions and browsing the website going through the video content and so forth. So what we're engaging as much as we have ever been, in fact I would argue that we're engaging even more so now, because it's just a different environment to work in. And what we're focused on now is really adding more features to the Styra DAS product, just to step back for a second, Open Policy Agent works across the cloud native stack and Styra DAS has been focused first on the kubernetes use case and now it also supports microservices as well. And then what we're continuing to do is add more of those enterprise features into Styra DAS and move up and up across the stack. But it is all driven by developers that we're talking to on a daily basis and that's leading to where the project is moving forward and the development for the roadmap and so forth. >> And Styra DAS was only launched in 2019, is that correct? >> 2019 yes, that's correct. That's correct. Yes, time flies, right? So, yes. >> A lot of change and a lot of development in a short period of time. >> That's right and 2019 was a big year for us, right? We started last 2019 with a soft launch at the RSA conference and we finished 2019 with series a funding led by Xcel. And yeah, it's great to see how the commercial product has been gaining traction in the marketplace as well as OPA as well and I think it's a combination of events. One, the fact that cloud native is now really well understood. Second, the fact that kubernetes at the beginning of 2019, it was still, "What does kubernetes mean, "is it going into production?" Now kubernetes is absolutely going into production and there's such a desire for organizations to make sure that security and policy and compliance are resolved before applications go into production otherwise we're going to have the same kind of challenges we had with previous app stacks. >> Well, the momentum is certainly with you. I can definitely hear that in your voice bell. Thank you so much for joining me talking about Styra, how you're reinventing policy and authorization for cloud native applications. >> Thank you, Lisa. >> For my guest Bill Mann, I'm Lisa Martin. You're watching the Cube Conversation. Thanks for your time. (upbeat music)