>>Everyone wants a cloud operating model. Since the introduction of the modern cloud. Last decade, the entire technology landscape has changed. We've learned a lot from the hyperscalers, especially from AWS. Now, one thing is certain in the technology business. It's so competitive. Then if a faster, better, cheaper idea comes along, the industry will move quickly to adopt it. They'll add their unique value and then they'll bring solutions to the market. And that's precisely what's happening throughout the technology industry because of cloud. And one of the best examples is Amazon's nitro. That's AWS has custom built hypervisor that delivers on the promise of more efficiently using resources and expanding things like processor, optionality for customers. It's a secret weapon for Amazon. As, as we, as we wrote last year, every infrastructure company needs something like nitro to compete. Why do we say this? Well, Wiki Bon our research arm estimates that nearly 30% of CPU cores in the data center are wasted. >>They're doing work that they weren't designed to do well, specifically offloading networking, storage, and security tasks. So if you can eliminate that waste, you can recapture dollars that drop right to the bottom line. That's why every company needs a nitro like solution. As a result of these developments, customers are rethinking networks and how they utilize precious compute resources. They can't, or won't put everything into the public cloud for many reasons. That's one of the tailwinds for tier two cloud service providers and why they're growing so fast. They give options to customers that don't want to keep investing in building out their own data centers, and they don't want to migrate all their workloads to the public cloud. So these providers and on-prem customers, they want to be more like hyperscalers, right? They want to be more agile and they do that. They're distributing, networking and security functions and pushing them closer to the applications. >>Now, at the same time, they're unifying their view of the network. So it can be less fragmented, manage more efficiently with more automation and better visibility. How are they doing this? Well, that's what we're going to talk about today. Welcome to changing the game for cloud networking made possible by pluribus networks. My name is Dave Vellante and today on this special cube presentation, John furrier, and I are going to explore these issues in detail. We'll dig into new solutions being created by pluribus and Nvidia to specifically address offloading, wasted resources, accelerating performance, isolating data, and making networks more secure all while unifying the network experience. We're going to start on the west coast and our Palo Alto studios, where John will talk to Mike of pluribus and AMI, but Donnie of Nvidia, then we'll bring on Alessandra Bobby airy of pluribus and Pete Lummus from Nvidia to take a deeper dive into the technology. And then we're gonna bring it back here to our east coast studio and get the independent analyst perspective from Bob Liberte of the enterprise strategy group. We hope you enjoy the program. Okay, let's do this over to John >>Okay. Let's kick things off. We're here at my cafe. One of the TMO and pluribus networks and NAMI by Dani VP of networking, marketing, and developer ecosystem at Nvidia. Great to have you welcome folks. >>Thank you. Thanks. >>So let's get into the, the problem situation with cloud unified network. What problems are out there? What challenges do cloud operators have Mike let's get into it. >>Yeah, it really, you know, the challenges we're looking at are for non hyperscalers that's enterprises, governments, um, tier two service providers, cloud service providers, and the first mandate for them is to become as agile as a hyperscaler. So they need to be able to deploy services and security policies. And second, they need to be able to abstract the complexity of the network and define things in software while it's accelerated in hardware. Um, really ultimately they need a single operating model everywhere. And then the second thing is they need to distribute networking and security services out to the edge of the host. Um, we're seeing a growth in cyber attacks. Um, it's, it's not slowing down. It's only getting worse and, you know, solving for this security problem across clouds is absolutely critical. And the way to do it is to move security out to the host. >>Okay. With that goal in mind, what's the pluribus vision. How does this tie together? >>Yeah. So, um, basically what we see is, uh, that this demands a new architecture and that new architecture has four tenants. The first tenant is unified and simplified cloud networks. If you look at cloud networks today, there's, there's sort of like discreet bespoke cloud networks, you know, per hypervisor, per private cloud edge cloud public cloud. Each of the public clouds have different networks that needs to be unified. You know, if we want these folks to be able to be agile, they need to be able to issue a single command or instantiate a security policy across all those locations with one command and not have to go to each one. The second is like I mentioned, distributed security, um, distributed security without compromise, extended out to the host is absolutely critical. So micro-segmentation and distributed firewalls, but it doesn't stop there. They also need pervasive visibility. >>You know, it's, it's, it's sort of like with security, you really can't see you can't protect what you can't see. So you need visibility everywhere. The problem is visibility to date has been very expensive. Folks have had to basically build a separate overlay network of taps, packet brokers, tap aggregation infrastructure that really needs to be built into this unified network I'm talking about. And the last thing is automation. All of this needs to be SDN enabled. So this is related to my comment about abstraction abstract, the complexity of all of these discreet networks, physic whatever's down there in the physical layer. Yeah. I don't want to see it. I want to abstract it. I wanted to find things in software, but I do want to leverage the power of hardware to accelerate that. So that's the fourth tenant is SDN automation. >>Mike, we've been talking on the cube a lot about this architectural shift and customers are looking at this. This is a big part of everyone who's looking at cloud operations next gen, how do we get there? How do customers get this vision realized? >>That's a great question. And I appreciate the tee up. I mean, we're, we're here today for that reason. We're introducing two things today. Um, the first is a unified cloud networking vision, and that is a vision of where pluribus is headed with our partners like Nvidia longterm. Um, and that is about, uh, deploying a common operating model, SDN enabled SDN, automated hardware, accelerated across all clouds. Um, and whether that's underlying overlay switch or server, um, hype, any hypervisor infrastructure containers, any workload doesn't matter. So that's ultimately where we want to get. And that's what we talked about earlier. Um, the first step in that vision is what we call the unified cloud fabric. And this is the next generation of our adaptive cloud fabric. Um, and what's nice about this is we're not starting from scratch. We have a, a, an award-winning adaptive cloud fabric product that is deployed globally. Um, and in particular, uh, we're very proud of the fact that it's deployed in over a hundred tier one mobile operators as the network fabric for their 4g and 5g virtualized cores. We know how to build carrier grade, uh, networking infrastructure, what we're doing now, um, to realize this next generation unified cloud fabric is we're extending from the switch to this Nvidia Bluefield to DPU. We know there's a, >>Hold that up real quick. That's a good, that's a good prop. That's the blue field and video. >>It's the Nvidia Bluefield two DPU data processing unit. And, um, uh, you know, what we're doing, uh, fundamentally is extending our SDN automated fabric, the unified cloud fabric out to the host, but it does take processing power. So we knew that we didn't want to do, we didn't want to implement that running on the CPU, which is what some other companies do because it consumes revenue generating CPU's from the application. So a DPU is a perfect way to implement this. And we knew that Nvidia was the leader with this blue field too. And so that is the first that's, that's the first step in the getting into realizing this vision. >>I mean, Nvidia has always been powering some great workloads of GPU. Now you've got DPU networking and then video is here. What is the relationship with clothes? How did that come together? Tell us the story. >>Yeah. So, you know, we've been working with pluribus for quite some time. I think the last several months was really when it came to fruition and, uh, what pluribus is trying to build and what Nvidia has. So we have, you know, this concept of a Bluefield data processing unit, which if you think about it, conceptually does really three things, offload, accelerate an isolate. So offload your workloads from your CPU to your data processing unit infrastructure workloads that is, uh, accelerate. So there's a bunch of acceleration engines. So you can run infrastructure workloads much faster than you would otherwise, and then isolation. So you have this nice security isolation between the data processing unit and your other CPU environment. And so you can run completely isolated workloads directly on the data processing unit. So we introduced this, you know, a couple of years ago, and with pluribus, you know, we've been talking to the pluribus team for quite some months now. >>And I think really the combination of what pluribus is trying to build and what they've developed around this unified cloud fabric, uh, is fits really nicely with the DPU and running that on the DPU and extending it really from your physical switch, all the way to your host environment, specifically on the data processing unit. So if you think about what's happening as you add data processing units to your environment. So every server we believe over time is going to have data processing units. So now you'll have to manage that complexity from the physical network layer to the host layer. And so what pluribus is really trying to do is extending the network fabric from the host, from the switch to the host, and really have that single pane of glass for network operators to be able to configure provision, manage all of the complexity of the network environment. >>So that's really how the partnership truly started. And so it started really with extending the network fabric, and now we're also working with them on security. So, you know, if you sort of take that concept of isolation and security isolation, what pluribus has within their fabric is the concept of micro-segmentation. And so now you can take that extended to the data processing unit and really have, um, isolated micro-segmentation workloads, whether it's bare metal cloud native environments, whether it's virtualized environments, whether it's public cloud, private cloud hybrid cloud. So it really is a magical partnership between the two companies with their unified cloud fabric running on, on the DPU. >>You know, what I love about this conversation is it reminds me of when you have these changing markets, the product gets pulled out of the market and, and you guys step up and create these new solutions. And I think this is a great example. So I have to ask you, how do you guys differentiate what sets this apart for customers with what's in it for the customer? >>Yeah. So I mentioned, you know, three things in terms of the value of what the Bluefield brings, right? There's offloading, accelerating, isolating, that's sort of the key core tenants of Bluefield. Um, so that, you know, if you sort of think about what, um, what Bluefields, what we've done, you know, in terms of the differentiation, we're really a robust platform for innovation. So we introduced Bluefield to, uh, last year, we're introducing Bluefield three, which is our next generation of Bluefields, you know, we'll have five X, the arm compute capacity. It will have 400 gig line rate acceleration, four X better crypto acceleration. So it will be remarkably better than the previous generation. And we'll continue to innovate and add, uh, chips to our portfolio every, every 18 months to two years. Um, so that's sort of one of the key areas of differentiation. The other is the, if you look at Nvidia and, and you know, what we're sort of known for is really known for our AI artificial intelligence and our artificial intelligence software, as well as our GPU. >>So you look at artificial intelligence and the combination of artificial intelligence plus data processing. This really creates the, you know, faster, more efficient, secure AI systems from the core of your data center, all the way out to the edge. And so with Nvidia, we really have these converged accelerators where we've combined the GPU, which does all your AI processing with your data processing with the DPU. So we have this convergence really nice convergence of that area. And I would say the third area is really around our developer environment. So, you know, one of the key, one of our key motivations at Nvidia is really to have our partner ecosystem, embrace our technology and build solutions around our technology. So if you look at what we've done with the DPU, with credit and an SDK, which is an open SDK called Doka, and it's an open SDK for our partners to really build and develop solutions using Bluefield and using all these accelerated libraries that we expose through Doka. And so part of our differentiation is really building this open ecosystem for our partners to take advantage and build solutions around our technology. >>You know, what's exciting is when I hear you talk, it's like you realize that there's no one general purpose network anymore. Everyone has their own super environment Supercloud or these new capabilities. They can really craft their own, I'd say, custom environment at scale with easy tools. Right. And it's all kind of, again, this is the new architecture Mike, you were talking about, how does customers run this effectively? Cost-effectively and how do people migrate? >>Yeah, I, I think that is the key question, right? So we've got this beautiful architecture. You, you know, Amazon nitro is a, is a good example of, of a smart NIC architecture that has been successfully deployed, but enterprises and serve tier two service providers and tier one service providers and governments are not Amazon, right? So they need to migrate there and they need this architecture to be cost-effective. And, and that's, that's super key. I mean, the reality is deep user moving fast, but they're not going to be, um, deployed everywhere on day one. Some servers will have DPS right away, some servers will have use and a year or two. And then there are devices that may never have DPS, right. IOT gateways, or legacy servers, even mainframes. Um, so that's the beauty of a solution that creates a fabric across both the switch and the DPU, right. >>Um, and by leveraging the Nvidia Bluefield DPU, what we really like about it is it's open. Um, and that drives, uh, cost efficiencies. And then, um, uh, you know, with this, with this, our architectural approach effectively, you get a unified solution across switch and DPU workload independent doesn't matter what hypervisor it is, integrated visibility, integrated security, and that can, uh, create tremendous cost efficiencies and, and really extract a lot of the expense from, from a capital perspective out of the network, as well as from an operational perspective, because now I have an SDN automated solution where I'm literally issuing a command to deploy a network service or to create or deploy our security policy and is deployed everywhere, automatically saving the oppor, the network operations team and the security operations team time. >>All right. So let me rewind that because that's super important. Get the unified cloud architecture, I'm the customer guy, but it's implemented, what's the value again, take, take me through the value to me. I have a unified environment. What's the value. >>Yeah. So I mean, the value is effectively, um, that, so there's a few pieces of value. The first piece of value is, um, I'm creating this clean D mark. I'm taking networking to the host. And like I mentioned, we're not running it on the CPU. So in implementations that run networking on the CPU, there's some conflict between the dev ops team who owned the server and the NetApps team who own the network because they're installing software on the, on the CPU stealing cycles from what should be revenue generating. Uh CPU's. So now by, by terminating the networking on the DPU, we click create this real clean DMARC. So the dev ops folks are happy because they don't necessarily have the skills to manage network and they don't necessarily want to spend the time managing networking. They've got their network counterparts who are also happy the NetApps team, because they want to control the networking. >>And now we've got this clean DMARC where the DevOps folks get the services they need and the NetApp folks get the control and agility they need. So that's a huge value. Um, the next piece of value is distributed security. This is essential. I mentioned earlier, you know, put pushing out micro-segmentation and distributed firewall, basically at the application level, right, where I create these small, small segments on an by application basis. So if a bad actor does penetrate the perimeter firewall, they're contained once they get inside. Cause the worst thing is a bad actor, penetrates a perimeter firewall and can go wherever they want and wreak havoc. Right? And so that's why this, this is so essential. Um, and the next benefit obviously is this unified networking operating model, right? Having, uh, uh, uh, an operating model across switch and server underlay and overlay, workload agnostic, making the life of the NetApps teams much easier so they can focus their time on really strategy instead of spending an afternoon, deploying a single villain, for example. >>Awesome. And I think also from my standpoint, I mean, perimeter security is pretty much, I mean, they're out there, it gets the firewall still out there exists, but pretty much they're being breached all the time, the perimeter. So you have to have this new security model. And I think the other thing that you mentioned, the separation between dev ops is cool because the infrastructure is code is about making the developers be agile and build security in from day one. So this policy aspect is, is huge. Um, new control points. I think you guys have a new architecture that enables the security to be handled more flexible. >>Right. >>That seems to be the killer feature here, >>Right? Yeah. If you look at the data processing unit, I think one of the great things about sort of this new architecture, it's really the foundation for zero trust it's. So like you talked about the perimeter is getting breached. And so now each and every compute node has to be protected. And I think that's sort of what you see with the partnership between pluribus and Nvidia is the DPU is really the foundation of zero trust. And pluribus is really building on that vision with, uh, allowing sort of micro-segmentation and being able to protect each and every compute node as well as the underlying network. >>This is super exciting. This is an illustration of how the market's evolving architectures are being reshaped and refactored for cloud scale and all this new goodness with data. So I gotta ask how you guys go into market together. Michael, start with you. What's the relationship look like in the go to market with an Nvidia? >>Sure. Um, I mean, we're, you know, we're super excited about the partnership, obviously we're here together. Um, we think we've got a really good solution for the market, so we're jointly marketing it. Um, uh, you know, obviously we appreciate that Nvidia is open. Um, that's, that's sort of in our DNA, we're about open networking. They've got other ISV who are gonna run on Bluefield too. We're probably going to run on other DPS in the, in the future, but right now, um, we're, we feel like we're partnered with the number one, uh, provider of DPS in the world and, uh, super excited about, uh, making a splash with it. >>I'm in get the hot product. >>Yeah. So Bluefield too, as I mentioned was GA last year, we're introducing, uh, well, we now also have the converged accelerator. So I talked about artificial intelligence or artificial intelligence with the Bluefield DPU, all of that put together on a converged accelerator. The nice thing there is you can either run those workloads. So if you have an artificial intelligence workload and an infrastructure workload, you can warn them separately on the same platform or you can actually use, uh, you can actually run artificial intelligence applications on the Bluefield itself. So that's what the converged accelerator really brings to the table. Uh, so that's available now. Then we have Bluefield three, which will be available late this year. And I talked about sort of, you know, uh, how much better that next generation of Bluefield is in comparison to Bluefield two. So we will see Bluefield three shipping later on this year, and then our software stack, which I talked about, which is called Doka we're on our second version are Doka one dot two. >>We're releasing Doka one dot three, uh, in about two months from now. And so that's really our open ecosystem framework. So allow you to program the Bluefields. So we have all of our acceleration libraries, um, security libraries, that's all packed into this STK called Doka. And it really gives that simplicity to our partners to be able to develop on top of Bluefield. So as we add new generations of Bluefield, you know, next, next year, we'll have, you know, another version and so on and so forth Doka is really that unified unified layer that allows, um, Bluefield to be both forwards compatible and backwards compatible. So partners only really have to think about writing to that SDK once, and then it automatically works with future generations of Bluefields. So that's sort of the nice thing around, um, around Doka. And then in terms of our go to market model, we're working with every, every major OEM. So, uh, later on this year, you'll see, you know, major server manufacturers, uh, releasing Bluefield enabled servers. So, um, more to come >>Awesome, save money, make it easier, more capabilities, more workload power. This is the future of, of cloud operations. >>Yeah. And, and, and, uh, one thing I'll add is, um, we are, um, we have a number of customers as you'll hear in the next segment, um, that are already signed up and we'll be working with us for our, uh, early field trial starting late April early may. Um, we are accepting registrations. You can go to www.pluribusnetworks.com/e F T a. If you're interested in signing up for, um, uh, being part of our field trial and providing feedback on the product, >>Awesome innovation and network. Thanks so much for sharing the news. Really appreciate it. Thanks so much. Okay. In a moment, we'll be back to look deeper in the product, the integration security zero trust use cases. You're watching the cube, the leader in enterprise tech coverage, >>Cloud networking is complex and fragmented slowing down your business. How can you simplify and unify your cloud networks to increase agility and business velocity? >>Pluribus unified cloud networking provides a unified simplify and agile network fabric across all clouds. It brings the simplicity of a public cloud operation model to private clouds, dramatically reducing complexity and improving agility, availability, and security. Now enterprises and service providers can increase their business philosophy and delight customers in the distributed multi-cloud era. We achieve this with a new approach to cloud networking, pluribus unified cloud fabric. This open vendor, independent network fabric, unifies, networking, and security across distributed clouds. The first step is extending the fabric to servers equipped with data processing units, unifying the fabric across switches and servers, and it doesn't stop there. The fabric is unified across underlay and overlay networks and across all workloads and virtualization environments. The unified cloud fabric is optimized for seamless migration to this new distributed architecture, leveraging the power of the DPU for application level micro-segmentation distributed fireball and encryption while still supporting those servers and devices that are not equipped with a DPU. Ultimately the unified cloud fabric extends seamlessly across distributed clouds, including central regional at edge private clouds and public clouds. The unified cloud fabric is a comprehensive network solution. That includes everything you need for clouds, networking built in SDN automation, distributed security without compromises, pervasive wire speed, visibility and application insight available on your choice of open networking switches and DP use all at the lowest total cost of ownership. The end result is a dramatically simplified unified cloud networking architecture that unifies your distributed clouds and frees your business to move at cloud speed, >>To learn more, visit www.pluribusnetworks.com. >>Okay. We're back I'm John ferry with the cube, and we're going to go deeper into a deep dive into unified cloud networking solution from Clovis and Nvidia. And we'll examine some of the use cases with Alessandra Burberry, VP of product management and pullovers networks and Pete Bloomberg who's director of technical marketing and video remotely guys. Thanks for coming on. Appreciate it. >>Yeah. >>So deep dive, let's get into the what and how Alexandra we heard earlier about the pluribus Nvidia partnership and the solution you're working together on what is it? >>Yeah. First let's talk about the water. What are we really integrating with the Nvidia Bluefield, the DPO technology, uh, plugable says, um, uh, there's been shipping, uh, in, uh, in volume, uh, in multiple mission critical networks. So this advisor one network operating systems, it runs today on a merchant silicone switches and effectively it's a standard open network operating system for data center. Um, and the novelty about this system that integrates a distributed control plane for, at water made effective in SDN overlay. This automation is a completely open and interoperable and extensible to other type of clouds is not enclosed them. And this is actually what we're now porting to the Nvidia DPO. >>Awesome. So how does it integrate into Nvidia hardware and specifically how has pluribus integrating its software with the Nvidia hardware? >>Yeah, I think, uh, we leverage some of the interesting properties of the Bluefield, the DPO hardware, which allows actually to integrate, uh, um, uh, our software, our network operating system in a manner which is completely isolated and independent from the guest operating system. So the first byproduct of this approach is that whatever we do at the network level on the DPU card that is completely agnostic to the hypervisor layer or OSTP layer running on, uh, on the host even more, um, uh, we can also independently manage this network, know that the switch on a Neek effectively, um, uh, managed completely independently from the host. You don't have to go through the network operating system, running on x86 to control this network node. So you throw yet the experience effectively of a top of rack for virtual machine or a top of rack for, uh, Kubernetes bots, where instead of, uh, um, if you allow me with the analogy instead of connecting a server knee directly to a switchboard, now you're connecting a VM virtual interface to a virtual interface on the switch on an ache. >>And, uh, also as part of this integration, we, uh, put a lot of effort, a lot of emphasis in, uh, accelerating the entire, uh, data plane for networking and security. So we are taking advantage of the DACA, uh, Nvidia DACA API to program the accelerators. And these accomplished two things with that. Number one, uh, you, uh, have much greater performance, much better performance. They're running the same network services on an x86 CPU. And second, this gives you the ability to free up, I would say around 20, 25% of the server capacity to be devoted either to, uh, additional workloads to run your cloud applications, or perhaps you can actually shrink the power footprint and compute footprint of your data center by 20%, if you want to run the same number of compute workloads. So great efficiencies in the overall approach, >>And this is completely independent of the server CPU, right? >>Absolutely. There is zero code from running on the x86, and this is what we think this enables a very clean demarcation between computer and network. >>So Pete, I gotta get, I gotta get you in here. We heard that, uh, the DPU is enabled cleaner separation of dev ops and net ops. Can you explain why that's important because everyone's talking DevSecOps right now, you've got net ops, net, net sec ops, this separation. Why is this clean separation important? >>Yeah, I think it's a, you know, it's a pragmatic solution in my opinion. Um, you know, we wish the world was all kind of rainbows and unicorns, but it's a little, a little messier than that. And I think a lot of the dev ops stuff and that, uh, mentality and philosophy, there's a natural fit there. Right? You have applications running on servers. So you're talking about developers with those applications integrating with the operators of those servers. Well, the network has always been this other thing and the network operators have always had a very different approach to things than compute operators. And, you know, I think that we, we in the networking industry have gotten closer together, but there's still a gap there's still some distance. And I think in that distance, isn't going to be closed. And so, you know, again, it comes down to pragmatism and I think, you know, one of my favorite phrases is look good fences, make good neighbors. And that's what this is. >>Yeah. That's a great point because dev ops has become kind of the calling card for cloud, right. But dev ops is as simply infrastructure as code and infrastructure is networking, right? So if infrastructure is code, you know, you're talking about, you know, that part of the stack under the covers under the hood, if you will, this is super important distinction. And this is where the innovation is. Can you elaborate on how you see that? Because this is really where the action is right now. >>Yeah, exactly. And I think that's where, um, one from, from the policy, the security that the zero trust aspect of this, right? If you get it wrong on that network side, all of a sudden you, you can totally open up that those capabilities. And so security is part of that. But the other part is thinking about this at scale, right? So we're taking one top of rack switch and adding, you know, up to 48 servers per rack. And so that ability to automate, orchestrate and manage at scale becomes absolutely critical. >>I'll Sandra, this is really the why we're talking about here, and this is scale. And again, getting it right. If you don't get it right, you're going to be really kind of up, you know what you know, so this is a huge deal. Networking matters, security matters, automation matters, dev ops, net ops, all coming together, clean separation, um, help us understand how this joint solution with Nvidia fits into the pluribus unified cloud networking vision, because this is what people are talking about and working on right now. >>Yeah, absolutely. So I think here with this solution, we're attacking two major problems in cloud networking. One is, uh, operation of, uh, cloud networking. And the second is a distributing security services in the cloud infrastructure. First, let me talk about the first water. We really unifying. If we're unifying something, something must be at least fragmented or this jointed and the, what is this joint that is actually the network in the cloud. If you look holistically, how networking is deployed in the cloud, you have your physical fabric infrastructure, right? Your switches and routers, you'll build your IP clause fabric leaf in spine typologies. This is actually a well understood the problem. I, I would say, um, there are multiple vendors, uh, uh, with, uh, um, uh, let's say similar technologies, um, very well standardized, whether you will understood, um, and almost a commodity, I would say building an IP fabric these days, but this is not the place where you deploy most of your services in the cloud, particularly from a security standpoint, two services are actually now moved into the compute layer where you actually were called builders, have to instrument the, a separate, uh, network virtualization layer, where they deploy segmentation and security closer to the workloads. >>And this is where the complication arise. These high value part of the cloud network is where you have a plethora of options that they don't talk to each other. And they are very dependent on the kind of hypervisor or compute solution you choose. Um, for example, the networking API to be between an GSXI environment or an hyper V or a Zen are completely disjointed. You have multiple orchestration layers. And when, and then when you throw in also Kubernetes in this, in this, in this type of architecture, uh, you're introducing yet another level of networking. And when Kubernetes runs on top of VMs, which is a prevalent approach, you actually just stacking up multiple networks on the compute layer that they eventually run on the physical fabric infrastructure. Those are all ships in the nights effectively, right? They operate as completely disjointed. And we're trying to attack this problem first with the notion of a unified fabric, which is independent from any workloads, whether it's this fabric spans on a switch, which can be con connected to a bare metal workload, or can span all the way inside the DPU, uh, where, um, you have, uh, your multi hypervisor compute environment. >>It's one API, one common network control plane, and one common set of segmentation services for the network. That's probably the number one, >>You know, it's interesting you, man, I hear you talking, I hear one network month, different operating models reminds me of the old serverless days. You know, there's still servers, but they call it serverless. Is there going to be a term network list? Because at the end of the day, it should be one network, not multiple operating models. This, this is a problem that you guys are working on. Is that right? I mean, I'm not, I'm just joking server listen network list, but the idea is it should be one thing. >>Yeah, it's effectively. What we're trying to do is we are trying to recompose this fragmentation in terms of network operation, across physical networking and server networking server networking is where the majority of the problems are because of the, uh, as much as you have standardized the ways of building, uh, physical networks and cloud fabrics with IP protocols and internet, you don't have that kind of, uh, uh, sort of, uh, um, um, uh, operational efficiency, uh, at the server layer. And, uh, this is what we're trying to attack first. The, with this technology, the second aspect we're trying to attack is are we distribute the security services throughout the infrastructure, more efficiently, whether it's micro-segmentation is a stateful firewall services, or even encryption. Those are all capabilities enabled by the blue field, uh, uh, the Butte technology and, uh, uh, we can actually integrate those capabilities directly into the nettle Fabrica, uh, limiting dramatically, at least for east-west traffic, the sprawl of, uh, security appliances, whether virtual or physical, that is typically the way the people today, uh, segment and secure the traffic in the cloud. >>Awesome. Pete, all kidding aside about network lists and serverless kind of fun, fun play on words there, the network is one thing it's basically distributed computing, right? So I love to get your thoughts about this distributed security with zero trust as the driver for this architecture you guys are doing. Can you share in more detail the depth of why DPU based approach is better than alternatives? >>Yeah, I think what's, what's beautiful and kind of what the DPU brings. That's new to this model is a completely isolated compute environment inside. So, you know, it's the, uh, yo dog, I heard you like a server, so I put a server inside your server. Uh, and so we provide, uh, you know, armed CPU's memory and network accelerators inside, and that is completely isolated from the host. So the server, the, the actual x86 host just thinks it has a regular Nick in there, but you actually have this full control plane thing. It's just like taking your top of rack switch and shoving it inside of your compute node. And so you have not only the separation, um, within the data plane, but you have this complete control plane separation. So you have this element that the network team can now control and manage, but we're taking all of the functions we used to do at the top of rack switch, and we're just shooting them now. >>And, you know, as time has gone on we've, we've struggled to put more and more and more into that network edge. And the reality is the network edge is the compute layer, not the top of rack switch layer. And so that provides this phenomenal enforcement point for security and policy. And I think outside of today's solutions around virtual firewalls, um, the other option is centralized appliances. And even if you can get one that can scale large enough, the question is, can you afford it? And so what we end up doing is we kind of hope that of aliens good enough, or we hope that if the excellent tunnel is good enough and we can actually apply more advanced techniques there because we can't physically, you know, financially afford that appliance to see all of the traffic. And now that we have a distributed model with this accelerator, we could do it. >>So what's the what's in it for the customer. I real quick, cause I think this is interesting point. You mentioned policy, everyone in networking knows policy is just a great thing and it adds, you hear it being talked about up the stack as well. When you start getting to orchestrating microservices and whatnot, all that good stuff going on there, containers and whatnot and modern applications. What's the benefit to the customers with this approach? Because what I heard was more scale, more edge deployment, flexibility, relative to security policies and application enablement. I mean, is that what what's the customer get out of this architecture? What's the enablement. >>It comes down to, uh, taking again the capabilities that were in that top of rack switch and asserting them down. So that makes simplicity smaller blast radiuses for failure, smaller failure domains, maintenance on the networks, and the systems become easier. Your ability to integrate across workloads becomes infinitely easier. Um, and again, you know, we always want to kind of separate each one of those layers. So just as in say, a VX land network, my leaf and spine don't have to be tightly coupled together. I can now do this at a different layer. And so you can run a DPU with any networking in the core there. And so you get this extreme flexibility. You can start small, you can scale large. Um, you know, to me, the, the possibilities are endless. Yes, >>It's a great security control plan. Really flexibility is key. And, and also being situationally aware of any kind of threats or new vectors or whatever's happening in the network. Alessandra, this is huge upside, right? You've already identified some successes with some customers on your early field trials. What are they doing and why are they attracted to the solution? >>Yeah, I think the response from customers has been, uh, the most, uh, encouraging and, uh, exciting, uh, for, uh, for us to, uh, to sort of continue and work and develop this product. And we have actually learned a lot in the process. Um, we talked to tier two tier three cloud providers. Uh, we talked to, uh, SP um, software Tyco type of networks, uh, as well as a large enterprise customers, um, in, uh, one particular case. Um, uh, one, uh, I think, um, let me, let me call out a couple of examples here, just to give you a flavor. Uh, there is a service provider, a cloud provider, uh, in Asia who is actually managing a cloud, uh, where they are offering services based on multiple hypervisors. They are native services based on Zen, but they also are on ramp into the cloud, uh, workloads based on, uh, ESI and, uh, uh, and KVM, depending on what the customer picks from the piece on the menu. >>And they have the problem of now orchestrating through their orchestrate or integrating with the Zen center with vSphere, uh, with, uh, open stack to coordinate these multiple environments and in the process to provide security, they actually deploy virtual appliances everywhere, which has a lot of costs, complication, and eats up into the server CPU. The problem is that they saw in this technology, they call it actually game changing is actually to remove all this complexity of in a single network and distribute the micro-segmentation service directly into the fabric. And overall, they're hoping to get out of it, uh, uh, tremendous, uh, um, opics, uh, benefit and overall, um, uh, operational simplification for the cloud infrastructure. That's one potent a use case. Uh, another, uh, large enterprise customer global enterprise customer, uh, is running, uh, both ESI and hyper V in that environment. And they don't have a solution to do micro-segmentation consistently across hypervisors. >>So again, micro-segmentation is a huge driver security looks like it's a recurring theme, uh, talking to most of these customers and in the Tyco space, um, uh, we're working with a few types of customers on the CFT program, uh, where the main goal is actually to our Monet's network operation. They typically handle all the VNF search with their own homegrown DPDK stack. This is overly complex. It is frankly also as low and inefficient, and then they have a physical network to manage the, the idea of having again, one network, uh, to coordinate the provision in our cloud services between the, the take of VNF, uh, and, uh, the rest of the infrastructure, uh, is extremely powerful on top of the offloading capability of the, by the bluefin DPOs. Those are just some examples. >>That was a great use case, a lot more potential. I see that with the unified cloud networking, great stuff, feed, shout out to you guys at Nvidia had been following your success for a long time and continuing to innovate as cloud scales and pluribus here with the unified networking, kind of bring it to the next level. Great stuff. Great to have you guys on. And again, software keeps driving the innovation again, networking is just a part of it, and it's the key solution. So I got to ask both of you to wrap this up. How can cloud operators who are interested in, in this, uh, new architecture and solution, uh, learn more because this is an architectural shift. People are working on this problem. They're trying to think about multiple clouds of trying to think about unification around the network and giving more security, more flexibility, uh, to their teams. How can people learn more? >>Yeah, so, uh, all Sandra and I have a talk at the upcoming Nvidia GTC conference. Um, so that's the week of March 21st through 24th. Um, you can go and register for free and video.com/at GTC. Um, you can also watch recorded sessions if you ended up watching us on YouTube a little bit after the fact. Um, and we're going to dive a little bit more into the specifics and the details and what we're providing in the solution. >>Alexandra, how can people learn more? >>Yeah, absolutely. People can go to the pluribus, a website, www boost networks.com/eft, and they can fill up the form and, uh, they will contact durables to either know more or to know more and actually to sign up for the actual early field trial program, which starts at the end of April. >>Okay. Well, we'll leave it there. Thanks. You both for joining. Appreciate it up next. You're going to hear an independent analyst perspective and review some of the research from the enterprise strategy group ESG. I'm John ferry with the >>Cube. Thanks for watching. >>Okay. We've heard from the folks at networks and Nvidia about their effort to transform cloud networking and unify bespoke infrastructure. Now let's get the perspective from an independent analyst and to do so. We welcome in ESG, senior analysts, Bob LA Liberte, Bob. Good to see you. Thanks for coming into our east coast studios. >>Oh, thanks for having me. It's great to be >>Here. Yeah. So this, this idea of unified cloud networking approach, how serious is it? What's what's driving it. >>Yeah, there's certainly a lot of drivers behind it, but probably the first and foremost is the fact that application environments are becoming a lot more distributed, right? So the, it pendulum tends to swing back and forth. And we're definitely on one that's swinging from consolidated to distributed. And so applications are being deployed in multiple private data centers, multiple public cloud locations, edge locations. And as a result of that, what you're seeing is a lot of complexity. So organizations are having to deal with this highly disparate environment. They have to secure it. They have to ensure connectivity to it and all that's driving up complexity. In fact, when we asked in one of our last surveys and last year about network complexity, more than half 54% came out and said, Hey, our network environment is now either more or significantly more complex than it used to be. >>And as a result of that, what you're seeing is it's really impacting agility. So everyone's moving to these modern application environments, distributing them across areas so they can improve agility yet it's creating more complexity. So a little bit counter to the fact and, you know, really counter to their overarching digital transformation initiatives. From what we've seen, you know, nine out of 10 organizations today are either beginning in process or have a mature digital transformation process or initiative, but their top goals, when you look at them, it probably shouldn't be a surprise. The number one goal is driving operational efficiency. So it makes sense. I've distributed my environment to create agility, but I've created a lot of complexity. So now I need these tools that are going to help me drive operational efficiency, drive better experience. >>I mean, I love how you bring in the data yesterday. Does a great job with that. Uh, questions is, is it about just unifying existing networks or is there sort of a need to rethink kind of a do-over network, how networks are built? >>Yeah, that's a, that's a really good point because certainly unifying networks helps right. Driving any kind of operational efficiency helps. But in this particular case, because we've made the transition to new application architectures and the impact that's having as well, it's really about changing and bringing in new frameworks and new network architectures to accommodate those new application architectures. And by that, what I'm talking about is the fact that these new modern application architectures, microservices, containers are driving a lot more east west traffic. So in the old days, it used to be easier in north south coming out of the server, one application per server, things like that. Right now you've got hundreds, if not thousands of microservices communicating with each other users communicating to them. So there's a lot more traffic and a lot of it's taking place within the servers themselves. The other issue that you starting to see as well from that security perspective, when we were all consolidated, we had those perimeter based legacy, you know, castle and moat security architectures, but that doesn't work anymore when the applications aren't in the castle, right. >>When everything's spread out that that no longer happens. So we're absolutely seeing, um, organizations trying to, trying to make a shift. And, and I think much, like if you think about the shift that we're seeing with all the remote workers and the sassy framework to enable a secure framework there, this it's almost the same thing. We're seeing this distributed services framework come up to support the applications better within the data centers, within the cloud data centers, so that you can drive that security closer to those applications and make sure they're, they're fully protected. Uh, and that's really driving a lot of the, you know, the zero trust stuff you hear, right? So never trust, always verify, making sure that everything is, is, is really secure micro-segmentation is another big area. So ensuring that these applications, when they're connected to each other, they're, they're fully segmented out. And that's again, because if someone does get a breach, if they are in your data center, you want to limit the blast radius, you want to limit the amount of damage that's done. So that by doing that, it really makes it a lot harder for them to see everything that's in there. >>You know, you mentioned zero trust. It used to be a buzzword, and now it's like become a mandate. And I love the mode analogy. You know, you build a moat to protect the queen and the castle, the Queens left the castles, it's just distributed. So how should we think about this, this pluribus and Nvidia solution. There's a spectrum, help us understand that you've got appliances, you've got pure software solutions. You've got what pluribus is doing with Nvidia, help us understand that. >>Yeah, absolutely. I think as organizations recognize the need to distribute their services to closer to the applications, they're trying different models. So from a legacy approach, you know, from a security perspective, they've got these centralized firewalls that they're deploying within their data centers. The hard part for that is if you want all this traffic to be secured, you're actually sending it out of the server up through the rack, usually to in different location in the data center and back. So with the need for agility, with the need for performance, right, that adds a lot of latency. Plus when you start needing to scale, that means adding more and more network connections, more and more appliances. So it can get very costly as well as impacting the performance. The other way that organizations are seeking to solve this problem is by taking the software itself and deploying it on the servers. Okay. So that's a, it's a great approach, right? It brings it really close to the applications, but the things you start running into there, there's a couple of things. One is that you start seeing that the DevOps team start taking on that networking and security responsibility, which they >>Don't want to >>Do, they don't want to do right. And the operations teams loses a little bit of visibility into that. Um, plus when you load the software onto the server, you're taking up precious CPU cycles. So if you're really wanting your applications to perform at an optimized state, having additional software on there, isn't going to, isn't going to do it. So, you know, when we think about all those types of things, right, and certainly the other side effects of that is the impact of the performance, but there's also a cost. So if you have to buy more servers because your CPU's are being utilized, right, and you have hundreds or thousands of servers, right, those costs are going to add up. So what, what Nvidia and pluribus have done by working together is to be able to take some of those services and be able to deploy them onto a smart Nick, right? >>To be able to deploy the DPU based smart SMARTNICK into the servers themselves. And then pluribus has come in and said, we're going to unify create that unified fabric across the networking space, into those networking services all the way down to the server. So the benefits of having that are pretty clear in that you're offloading that capability from the server. So your CPU's are optimized. You're saving a lot of money. You're not having to go outside of the server and go to a different rack somewhere else in the data center. So your performance is going to be optimized as well. You're not going to incur any latency hit for every trip round trip to the, to the firewall and back. So I think all those things are really important. Plus the fact that you're going to see from a, an organizational aspect, we talked about the dev ops and net ops teams. The network operations teams now can work with the security teams to establish the security policies and the networking policies. So that they've dev ops teams. Don't have to worry about that. So essentially they just create the guardrails and let the dev op team run. Cause that's what they want. They want that agility and speed. >>Yeah. Your point about CPU cycles is key. I mean, it's estimated that 25 to 30% of CPU cycles in the data center are wasted. The cores are wasted doing storage offload or, or networking or security offload. And, you know, I've said many times everybody needs a nitro like Amazon nugget, but you can't go, you can only buy Amazon nitro if you go into AWS. Right. Everybody needs a nitro. So is that how we should think about this? >>Yeah. That's a great analogy to think about this. Um, and I think I would take it a step further because it's, it's almost the opposite end of the spectrum because pluribus and video are doing this in a very open way. And so pluribus has always been a proponent of open networking. And so what they're trying to do is extend that now to these distributed services. So leverage working with Nvidia, who's also open as well, being able to bring that to bear so that organizations can not only take advantage of these distributed services, but also that unified networking fabric, that unified cloud fabric across that environment from the server across the switches, the other key piece of what pluribus is doing, because they've been doing this for a while now, and they've been doing it with the older application environments and the older server environments, they're able to provide that unified networking experience across a host of different types of servers and platforms. So you can have not only the modern application supported, but also the legacy environments, um, you know, bare metal. You could go any type of virtualization, you can run containers, et cetera. So a wide gambit of different technologies hosting those applications supported by a unified cloud fabric from pluribus. >>So what does that mean for the customer? I don't have to rip and replace my whole infrastructure, right? >>Yeah. Well, think what it does for, again, from that operational efficiency, when you're going from a legacy environment to that modern environment, it helps with the migration helps you accelerate that migration because you're not switching different management systems to accomplish that. You've got the same unified networking fabric that you've been working with to enable you to run your legacy as well as transfer over to those modern applications. Okay. >>So your people are comfortable with the skillsets, et cetera. All right. I'll give you the last word. Give us the bottom line here. >>So yeah, I think obviously with all the modern applications that are coming out, the distributed application environments, it's really posing a lot of risk on these organizations to be able to get not only security, but also visibility into those environments. And so organizations have to find solutions. As I said, at the beginning, they're looking to drive operational efficiency. So getting operational efficiency from a unified cloud networking solution, that it goes from the server across the servers to multiple different environments, right in different cloud environments is certainly going to help organizations drive that operational efficiency. It's going to help them save money for visibility, for security and even open networking. So a great opportunity for organizations, especially large enterprises, cloud providers who are trying to build that hyperscaler like environment. You mentioned the nitro card, right? This is a great way to do it with an open solution. >>Bob, thanks so much for, for coming in and sharing your insights. Appreciate it. >>You're welcome. Thanks. >>Thanks for watching the program today. Remember all these videos are available on demand@thekey.net. You can check out all the news from today@siliconangle.com and of course, pluribus networks.com many thanks diplomas for making this program possible and sponsoring the cube. This is Dave Volante. Thanks for watching. Be well, we'll see you next time.

>>data by its very nature is distributed and siloed. But most data architectures today are highly centralized. Organizations are increasingly challenged to organize and manage data and turn that data into insights this idea of a single monolithic platform for data, it's giving way to new thinking. We're a decentralized approach with open cloud native principles and Federated governance will become an underpinning underpinning of digital transformations. Hi everybody, this is Day Volonte. Welcome back to HP discover 2021 the virtual version. You're watching the cubes continuous coverage of the event and we're here with Matt Mako is the field C T O for Israel software at H P E. And we're gonna talk about HP software strategy and esmeralda and specifically how to take a I analytics to scale and ensure the productivity of data teams. Matt, welcome to the cube. Good to see you. >>Good to see you again. Dave thanks for having me today. >>You're welcome. So talk a little bit about your role as CTO. Where do you spend your time? >>Yeah. So I spend about half of my time talking to customers and partners about where they are on their digital transformation journeys and where they struggle with this sort of last phase where we start talking about bringing those cloud principles and practices into the data world. How do I take those data warehouses, those data lakes, those distributed data systems into the enterprise and deploy them in a cloud like manner. And then the other half of my time is working with our product teams to feed that information back so that we can continually innovate to the next generation of our software platform. >>So when I remember I've been following HP and HP for a long, long time, the cube is documented. We go back to sort of when the company was breaking in two parts and at the time a lot of people were saying, oh HP is getting rid of the software business to get out of software. I said no, no, no hold on, they're really focusing and and the whole focus around hybrid cloud and and now as a service and so you're really retooling that business and sharpen your focus. So so tell us more about asthma, it's cool name. But what exactly is as moral software, >>I get this question all the time. So what is Israel? Israel is a software platform for modern data and analytics workloads using open source software components. And we came from some inorganic growth. We acquired a company called citing that brought us a zero trust approach to doing security with containers. We bought blue data who came to us with an orchestrator before kubernetes even existed in mainstream. They were orchestrating workloads using containers for some of these more difficult workloads, clustered applications, distributed applications like Hadoop. And then finally we acquired Map are which gave us this scale out, distributed file system and additional analytical capabilities. And so what we've done is we've taken those components and we've also gone out into the marketplace to see what open source projects exist, to allow us to bring those club principles and practices to these types of workloads so that we can take things like Hadoop and spark and Presto and deploy and orchestrate them using open source kubernetes, leveraging Gpu s while providing that zero trust approaches security. That's what Israel is all about. Is taking those cloud practices and principles but without locking you in again using those open source components where they exist and then committing and contributing back to the open source community where those projects don't exist. >>You know, it's interesting. Thank you for that history. And when I go back, I always been there since the early days of big data and Hadoop and so forth. The map are always had the best product. But but they can't get back then. It was like Kumbaya open source and they had this kind of proprietary system, but it worked and that's why it was the best product. And so at the same time they participated in open source projects because everybody that that's where the innovation is going. So you're making that really hard to use stuff easier to use with kubernetes orchestration. And then obviously I'm presuming with the open source chops, sort of leaning into the big trends that you're seeing in the marketplace. So my question is, what are those big trends that you're seeing when you speak to technology executives, which is a big part of what you do? >>Yeah. So the trends I think are a couple of fold and it's funny about Duke, I think the final nails in the coffin have been hammered in with the Hadoop space now. And so that that leading trend of of where organizations are going. We're seeing organizations wanting to go cloud first, but they really struggle with these data intensive workloads. Do I have to store my data in every cloud? Am I going to pay egress in every cloud? Well, what if my data scientists are most comfortable in AWS? But my data analysts are more comfortable in Azure. How do I provide that multi cloud experience for these data workloads? That's the number one question I get asked. And that's the probably the biggest struggle for these Chief Data Officers. Chief Digital Officer XYZ. How do I allow that innovation but maintaining control over my data compliance especially, we talk international standards like G. D. P. R. To restrict access to data, the ability to be forgotten in these multinational organizations. How do I sort of square all of those components and then how do I do that in a way that just doesn't lock me into another appliance or software vendors stack? I want to be able to work within the confines of the ecosystem. Use the tools that are out there but allow my organization to innovate in a very structured, compliant way. >>I mean I love this conversation. And just to me you hit on the key word which is organization. I want to I want to talk about what some of the barriers are. And again, you heard my wrap up front. I I really do think that we've created not only from a technology standpoint and yes, the tooling is important, but so is the organization. And as you said, you know, an analyst might want to work in one environment, a data scientist might want to work in another environment. The data may be very distributed. They maybe you might have situations where they're supporting the line of business. The line of business is trying to build new products. And if I have to go through this, hi this monolithic centralized organization, that's a barrier uh for me. And so we're seeing that change that kind of alluded to it upfront. But what do you see as the big, you know, barriers that are blocking this vision from becoming a reality? >>It very much is organization dave it's the technology is actually no longer the inhibitor here. We have enough technology, enough choices out there. That technology is no longer the issue. It's the organization's willingness to embrace some of those technologies and put just the right level of control around accessing that data because if you don't allow your data scientists and data analysts to innovate, they're going to do one of two things, they're either going to leave and then you have a huge problem keeping up with your competitors or they're gonna do it anyway, and they're gonna do it in a way that probably doesn't comply with the organizational standards. So the more progressive enterprises that I speak with have realized that they need to allow these various analytical users to choose the tools, they want to self provision those as they need to and get access to data in a secure and compliant way. And that means we need to bring the cloud to generally where the data is because it's a heck of a lot easier than trying to bring the data where the cloud is while conforming to those data principles. And that's, that's Hve strategy, you've heard it from our CEO for years now, everything needs to be delivered as a service. It's essential software that enables that capability, such as self service and secure data provisioning, etcetera. >>Again, I love this conversation because if you go back to the early days of the Duke, that was what was profound about. Do bring bring five megabytes of code, do a petabyte of data and it didn't happen. We shoved it all into a data lake and it became a data swamp. And so it's okay, you know, and that's okay. It's a one dato maybe maybe in data is is like data warehouses, data hubs data lake. So maybe this is now a four dot Oh, but we're getting there. Uh, so an open but open source one thing's for sure. It continues to gain momentum. It's where the innovation is. I wonder if you could comment on your thoughts on the role that open source software plays for large enterprises. Maybe some of the hurdles that are there, whether they're legal or licensing or or or just fears. How important is open source software today? >>I think the cloud native development, you know, following the 12 factor applications microservices based, pave the way over the last decade to make using open source technology tools and libraries mainstream, we have to tip our hats to red hat right for allowing organizations to embrace something. So core is an operating system within the enterprise. But what everyone realizes that its support, that's what has to come with that. So we can allow our data scientists to use open source libraries, packages and notebooks. But are we going to allow those to run in production? And so if the answer is no, then that if we can't get support, we're not going to allow that. So where HP es Merrill is taking the lead here is again embracing those open source capabilities, but if we deploy it, we're going to support it or we're going to work with the organization that has the committees to support it. You call HPD the same phone number you've been calling for years for tier 1 24 by seven support and we will support your kubernetes, your spark your presto your Hadoop ecosystem of components were that throat to choke and we'll provide all the way up to break fix support for some of these components and packages giving these large enterprises the confidence to move forward with open source but knowing that they have a trusted partner in which to do so >>and that's why we've seen such success with, say, for instance, managed services in the cloud or versus throwing out all the animals in the zoo and say, okay, figure it out yourself. But of course what we saw, which was kind of ironic was we, we saw people finally said, hey, we can do this in the cloud more easily. So that's where you're seeing a lot of data. A land. However, the definition of cloud or the notion of cloud is changing no longer. Is it just this remote set of services somewhere out there? In the cloud? Some data center somewhere. No, it's, it's moving on. Prem on prem is creating hybrid connections you're seeing, you know, co location facility is very proximate to the cloud. We're talking now about the edge, the near edge and the far edge deeply embedded, you know? And so that whole notion of cloud is, is changing. But I want to ask you, there's still a big push to cloud, everybody is a cloud first mantra. How do you see HP competing in this new landscape? >>I I think collaborating is probably a better word, although you could certainly argue if we're just leasing or renting hardware than it would be competition. But I think again, the workload is going to flow to where the data exists. So if the data is being generated at the edge and being pumped into the cloud, then cloud is prod, that's the production system. If the data is generated, the on system on premises systems, then that's where it's going to be executed, that's production. And so HBs approach is very much coexist, coexist model of if you need to do deaf tests in the cloud and bring it back on premises, fine or vice versa. The key here is not locking our customers and our prospective clients into any sort of proprietary stack, as we were talking about earlier, giving people the flexibility to move those workloads to where the data exists. That is going to allow us to continue to get share of wallet. Mindshare, continue to deploy those workloads and yes, there's going to be competition that comes along. Do you run this on a G C P or do you run it on a green lake on premises? Sure. We'll have those conversations. But again, if we're using open source software as the foundation for that, then actually where you run it is less relevant. >>So a lot of, there's a lot of choices out there when it comes to containers generally and kubernetes specifically, uh, you may have answered this, you get zero trust component, you've got the orchestrator, you've got the, the scale out, you know, peace. But I'm interested in hearing in your words why an enterprise would or should consider s morale instead of alternatives to kubernetes solutions? >>It's a fair question. And it comes up in almost every conversation. We already do kubernetes, so we have a kubernetes standard and that's largely true. And most of the enterprises I speak to their using one of the many on premises distributions of the cloud distributions and they're all fine. They're all fine for what they were built for. Israel was generally built for something a little different. Yes, everybody can run microservices based applications, devoPS based workloads, but where is Meryl is different is for those data intensive and clustered applications. Those sort of applications require a certain degree of network awareness, persistent storage etcetera, which requires either a significant amount of intelligence. Either you have to write in go lang or you have to write your own operators or Israel can be that easy button. We deploy those state full applications because we bring a persistent storage later that came from that bar we're really good at deploying those stable clustered applications and in fact we've open sourced that as a project cube director that came from Blue data and we're really good at securing these using spiffy inspire to ensure that there is that zero trust approach that came from side tail and we've wrapped all of that in kubernetes so now you can take the most difficult, gnarly, complex data intensive applications in your enterprise and deploy them using open source and if that means we have to coexist with an existing kubernetes distribution, that's fine. That's actually the most common scenario that I walk into is I start asking about what about these other applications you haven't done yet? The answer is usually we haven't gotten to him yet or we're thinking about it and that's when we talk about the capabilities of s role and I usually get the response, oh, a we didn't know you existed and be, well, let's talk about how exactly you do that. So again, it's more of a coexist model rather than a compete with model. Dave >>Well, that makes sense. I mean, I think again, a lot of people think, oh yeah, Kubernetes, no big deal, it's everywhere. But you're talking about a solution, I'm kind of taking a platform approach with capabilities, you've got to protect the data. A lot of times these microservices aren't some micro uh and things are happening really fast, You've got to be secure, you've got to be protected. And like you said, you've got a single phone number, you know, people say one throat to choke, Somebody said the other day said no, no single hand to shake, it's more of a partnership and I think that's a proposed for HPV met with your >>hair better. >>So you know, thinking about this whole, you know, we've gone through the pre big data days and the big data was all, you know, the hot buzz where people don't maybe necessarily use that term anymore, although the data is bigger and getting bigger, which is kind of ironic. Um where do you see this whole space going? We've talked about that sort of trends are breaking down the silos, decentralization. Maybe these hyper specialized roles that we've created maybe getting more embedded are lined with the line of business. How do you see it feels like the last, the next 10 years are going to be different than the last 10 years. How do you see it matt? >>I completely agree. I think we are entering this next era and I don't know if it's well defined, I don't know if I would go out on an edge to say exactly what the trend is going to be. But as you said earlier, data lakes really turned into data swamps. We ended up with lots of them in the enterprise and enterprises had to allow that to happen. They had to let each business unit or each group of users collect the data that they needed and I. T. Sort of had to deal with that down the road. And so I think the more progressive organizations are leading the way they are again taking those lessons from cloud and application developments, microservices and they're allowing a freedom of choice there, allowing data to move to where those applications are. And I think this decentralized approach is really going to be king. And you're gonna see traditional software packages, you're gonna see open source, you're going to see a mix of those. But what I think we'll probably be common throughout all of that is there's going to be this sense of automation, this sense that we can't just build an algorithm once released and then wish it luck that we've got to treat these these analytics and these these data systems as living things that there's life cycles that we have to support, which means we need to have devops for our data science. We need a ci cd for our data analytics. We need to provide engineering at scale like we do for software engineering. That's going to require automation and an organizational thinking process to allow that to actually occur. And so I think all of those things that sort of people process product, but it's all three of those things are going to have to come into play. But stealing those best ideas from cloud and application development, I think we're going to end up with probably something new over the next decade or so >>again, I'm loving this conversation so I'm gonna stick with it for a second. I it's hard to predict, but I'll some takeaways that I have matt from our conversation. I wonder if you could, you could comment. I think, you know, the future is more open source. You mentioned automation deV's are going to be key. I think governance as code, security designed in at the point of code creation is going to be critical. It's not no longer to be a bolt on and I don't think we're gonna throw away the data warehouse or the data hubs or the data lakes. I think they become a node. I like this idea and you know, jim octagon. But she has this idea of a global data mesh where these tools lakes, whatever their their node on the mesh, they're discoverable. They're shareable. They're they're governed uh in a way and that really I think the mistake a lot of people made early on in the big data movement, Oh we have data, we have to monetize our data as opposed to thinking about what products that I can I build that are based on data that then I can, you know, can lead to monetization. And I think and I think the other thing I would say is the business has gotten way too technical. All right. It's an alienated a lot of the business lines and I think we're seeing that change. Um and I think, you know, things like Edinburgh that simplify that are critical. So I'll give you the final thoughts based on my rent. >>I know you're ready to spot on. Dave. I think we we were in agreement about a lot of things. Governance is absolutely key. If you don't know where your data is, what it's used for and can apply policies to it, it doesn't matter what technology throw at it, you're going to end up in the same state that you're essentially in today with lots of swamps. Uh I did like that concept of of a note or a data mesh. It kind of goes back to the similar thing with a service smashed or a set of a P I is that you can use. I think we're going to have something similar with data that the trick is always how heavy is it? How easy is it to move about? And so I think there's always gonna be that latency issue. Maybe not within the data center, but across the land, latency is still going to be key, which means we need to have really good processes to be able to move data around. As you said, government determine who has access to what, when and under what conditions and then allow it to be free, allow people to bring their choice of tools, provision them how they need to while providing that audit compliance and control. And then again, as as you need to provision data across those notes for those use cases do so in a well measured and govern way. I think that's sort of where things are going. But we keep using that term governance. I think that's so key. And there's nothing better than using open source software because that provides traceability, the audit ability and this frankly openness that allows you to say, I don't like where this project is going. I want to go in a different direction and it gives those enterprises that control over these platforms that they've never had before. >>Matt. Thanks so much for the discussion. I really enjoyed it. Awesome perspectives. >>Well, thank you for having me. Dave are excellent conversation as always. Uh, thanks for having me again. >>All right. You're very welcome. And thank you for watching everybody. This is the cubes continuous coverage of HP discover 2021 of course, the virtual version next year. We're gonna be back live. My name is Dave a lot. Keep it right there. >>Yeah.

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Hey, welcome back everybody Jeff Frick here with the cube. This is a special week it's Grace Hopper week, and Grace Hopper is the best name in tech conferences. The celebration of women in computing, and we've been going there for years we're not there this year, but one of the themes that comes up over and over at Grace Hopper is women and girls need to see women in positions that they can envision themselves being in someday. That is a really important piece of the whole diversity conversation is can I see people that I can role model after and I just want to bring up something from a couple years back from 2016 when we were there, we were there with Mimi Valdez, Christina Deoja and Dr. Jeanette Epps, Dr. Jeanette Epps is the astronaut on the right. They were there talking about "The Hidden Figures" movie. If you remember it came out 2016, it was about Katherine Johnson and all the black women working at NASA. They got no credit for doing all the math that basically keep all the astronauts safe and they made a terrific movie about it. And Janet is going up on the very first Blue Origin Space Mission Next year. This was announced a couple of months ago, so again, phenomenal leadership, black lady astronaut, going to go into space and really provide a face for a lot of young girls that want to get into that and its clearly a great STEM opportunity. So we're excited to have four terrific women today that well also are the leaders that the younger women can look up to and follow their career. So we're excited to have them so we're just going to go around. We got four terrific guests, our first one is Annabel Chang, She is the Head of State Policy and Government Regulations at Waymo. Annabel great to see you, where are you coming in from today? >> from San Francisco >> Jeff: Awesome. Next up is Inamarie Johnson. She is the Chief People and Diversity Officer for Zendesk Inamarie, great to see you. Where are you calling in from today? >> Great to be here. I am calling in from Palos Verdes the state >> Jeff: awesome >> in Southern California. >> Jeff: Some of the benefits of a virtual sometimes we can, we couldn't do that without the power of the internet. And next up is Jennifer Cabalquinto she is the Chief Financial Officer of the Golden State Warriors. Jennifer, great to see you Where are you coming in from today? >> Well, I wish I was coming in from the Chase Center in San Francisco but I'm actually calling in from Santa Cruz California today. >> Jeff: Right, It's good to see you and you can surf a lot better down there. So that's probably not all bad. And finally to round out our panelists, Kate Hogan, she is the COO of North America for Accenture. Kate, great to see you as well. Where are you coming in from today? >> Well, it's good to see you too. I am coming in from the office actually in San Jose. >> Jeff: From the office in San Jose. All right, So let's get into it . You guys are all very senior, you've been doing this for a long time. We're in a kind of a crazy period of time in terms of diversity with all the kind of social unrest that's happening. So let's talk about some of your first your journeys and I want to start with you Annabel. You're a lawyer you got into lawyering. You did lawyering with Diane Feinstein, kind of some politics, and also the city of San Francisco. And then you made this move over to tech. Talk about that decision and what went into that decision and how did you get into tech? 'cause we know part of the problem with diversity is a pipeline problem. You came over from the law side of the house. >> Yes, and to be honest politics and the law are pretty homogenous. So when I made the move to tech, it was still a lot of the same, but what I knew is that I could be an attorney anywhere from Omaha Nebraska to Miami Florida. But what I couldn't do was work for a disruptive company, potentially a unicorn. And I seized that opportunity and (indistinct) Lyft early on before Ride Hailing and Ride Sharing was even a thing. So it was an exciting opportunity. And I joined right at the exact moment that made myself really meaningful in the organization. And I'm hoping that I'm doing the same thing right now at Waymo. >> Great, Inamarie you've come from one of my favorite stories I like to talk about from the old school Clorox great product management. I always like to joke that Silicon Valley needs a pipeline back to Cincinnati and Proctor and Gamble to get good product managers out here. You were in the classic, right? You were there, you were at Honeywell Plantronics, and then you jumped over to tech. Tell us a little bit about that move. Cause I'm sure selling Clorox is a lot different than selling the terrific service that you guys provide at Zendesk. I'm always happy when I see Zendesk in my customer service return email, I know I'm going to get taken care of. >> Oh wow, that's great. We love customers like you., so thank you for that. My journey is you're right from a fortune 50 sort of more portfolio type company into tech. And I think one of the reasons is because when tech is starting out and that's what Zendesk was a few five years back or so very much an early stage growth company, two things are top of mind, one, how do we become more global? And how do we make sure that we can go up market and attract enterprise grade customers? And so my experience having only been in those types of companies was very interesting for a startup. And what was interesting for me is I got to live in a world where there were great growth targets and numbers, things I had never seen. And the agility, the speed, the head plus heart really resonated with my background. So super glad to be in tech, but you're right. It's a little different than a consumer products. >> Right, and then Jennifer, you're in a completely different world, right? So you worked for the Golden State Warriors, which everybody knows is an NBA team, but I don't know that everyone knows really how progressive the Warriors are beyond just basketball in terms of the new Chase Center, all the different events that you guys put on it. And really the leadership there has decided we really want to be an entertainment company of which the Golden State Warrior basketball team has a very, very important piece, you've come from the entertainment industry. So that's probably how they found you, but you're in the financial role. You've always been in the financial role, not traditionally thought about as a lot of women in terms of a proportion of total people in that. So tell us a little bit about your experience being in finance, in entertainment, and then making this kind of hop over to, I guess Uber entertainment. I don't know even how you would classify the warriors. >> Sports entertainment, live entertainment. Yeah, it's interesting when the Warriors opportunity came up, I naturally said well no, I don't have any sports background. And it's something that we women tend to do, right? We self edit and we want to check every box before we think that we're qualified. And the reality is my background is in entertainment and the Warriors were looking to build their own venue, which has been a very large construction project. I was the CFO at Universal Studios Hollywood. And what do we do there? We build large attractions, which are just large construction projects and we're in the entertainment business. And so that sort of B to C was a natural sort of transition for me going from where I was with Universal Studios over to the Warriors. I think a finance career is such a great career for women. And I think we're finding more and more women entering it. It is one that you sort of understand your hills and valleys, you know when you're going to be busy and so you can kind of schedule around that. I think it's really... it provides that you have a seat at the table. And so I think it's a career choice that I think is becoming more and more available to women certainly more now than it was when I first started. >> Yeah, It's interesting cause I think a lot of people think of women naturally in human resources roles. My wife was a head of human resources back in the day, or a lot of marketing, but not necessarily on the finance side. And then Kate go over to you. You're one of the rare birds you've been at Accenture  for over 20 years. So you must like airplanes and travel to stay there that long. But doing a little homework for this, I saw a really interesting piece of you talking about your boss challenging you to ask for more work, to ask for a new opportunity. And I thought that was really insightful that you, you picked up on that like Oh, I guess it's incumbent on me to ask for more, not necessarily wait for that to be given to me, it sounds like a really seminal moment in your career. >> It was important but before I tell you that story, because it was an important moment of my career and probably something that a lot of the women here on the panel here can relate to as well. You mentioned airplanes and it made me think of my dad. My father was in the air force and I remember him telling stories when I was little about his career change from the air force into a career in telecommunications. So technology for me growing up Jeff was, it was kind of part of the dinner table. I mean it was just a conversation that was constantly ongoing in our house. And I also, as a young girl, I loved playing video games. We had a Tandy computer down in the basement and I remember spending too many hours playing video games down there. And so for me my history and my really at a young age, my experience and curiosity around tech was there. And so maybe that's, what's fueling my inspiration to stay at Accenture for as long as I have. And you're right It's been two decades, which feels tremendous, but I've had the chance to work across a bunch of different industries, but you're right. I mean, during that time and I relate with what Jennifer said in terms of self editing, right? Women do this and I'm no exception, I did this. And I do remember I'm a mentor and a sponsor of mine who called me up when I'm kind of I was at a pivotal moment in my career and he said you know Kate, I've been waiting for you to call me and tell me you want this job. And I never even thought about it. I mean I just never thought that I'd be a candidate for the job and let alone somebody waiting for me to kind of make the phone call. I haven't made that mistake again, (laughing) but I like to believe I learned from it, but it was an important lesson. >> It's such a great lesson and women are often accused of being a little bit too passive and not necessarily looking out for in salary negotiations or looking for that promotion or kind of stepping up to take the crappy job because that's another thing we hear over and over from successful people is that some point in their career, they took that job that nobody else wanted. They took that challenge that really enabled them to take a different path and really a different Ascension. And I'm just curious if there's any stories on that or in terms of a leader or a mentor, whether it was in the career, somebody that you either knew or didn't know that was someone that you got kind of strength from kind of climbing through your own, kind of career progression. Will go to you first Annabel. >> I actually would love to talk about the salary negotiations piece because I have a group of friends about that we've been to meeting together once a month for the last six years now. And one of the things that we committed to being very transparent with each other about was salary negotiations and signing bonuses and all of the hard topics that you kind of don't want to talk about as a manager and the women that I'm in this group with span all types of different industries. And I've learned so much from them, from my different job transitions about understanding the signing bonus, understanding equity, which is totally foreign to me coming from law and politics. And that was one of the most impactful tools that I've ever had was a group of people that I could be open with talking about salary negotiations and talking about how to really manage equity. Those are totally foreign to me up until this group of women really connected me to these topics and gave me some of that expertise. So that is something I strongly encourage is that if you haven't openly talked about salary negotiations before you should begin to do so. >> It begs the question, how was the sensitivity between the person that was making a lot of money and the person that wasn't? And how did you kind of work through that as a group for the greater good of everyone? >> Yeah, I think what's really eye opening is that for example, We had friends who were friends who were on tech, we had friends who were actually the entrepreneurs starting their own businesses or law firm, associates, law firm partners, people in PR, so we understood that there was going to be differences within industry and frankly in scale, but it was understanding even the tools, whether I think the most interesting one would be signing bonus, right? Because up until a few years ago, recruiters could ask you what you made and how do you avoid that question? How do you anchor yourself to a lower salary range or avoid that happening? I didn't know this, I didn't know how to do that. And a couple of women that had been in more senior negotiations shared ways to make sure that I was pinning myself to a higher salary range that I wanted to be in. >> That's great. That's a great story and really important to like say pin. it's a lot of logistical details, right? You just need to learn the techniques like any other skill. Inamarie, I wonder if you've got a story to share here. >> Sure. I just want to say, I love the example that you just gave because it's something I'm super passionate about, which is transparency and trust. Then I think that we're building that every day into all of our people processes. So sure, talk about sign on bonuses, talk about pay parody because that is the landscape. But a quick story for me, I would say is all about stepping into uncertainty. And when I coach younger professionals of course women, I often talk about, don't be afraid to step into the role where all of the answers are not vetted down because at the end of the day, you can influence what those answers are. I still remember when Honeywell asked me to leave the comfort of California and to come to the East coast to New Jersey and bring my family. And I was doing well in my career. I didn't feel like I needed to do that, but I was willing after some coaching to step into that uncertainty. And it was one of the best pivotal moment in my career. I didn't always know who I was going to work with. I didn't know the challenges and scope I would take on, but those were some of the biggest learning experiences and opportunities and it made me a better executive. So that's always my coaching, like go where the answers aren't quite vetted down because you can influence that as a leader. >> That's great, I mean, Beth Comstock former vice chair at GE, one of her keynotes I saw had a great line, get comfortable with being uncomfortable. And I think that its a really good kind of message, especially in the time we're living in with accelerated change. But I'm curious, Inamarie was the person that got you to take that commitment. Would you consider that a sponsor, a mentor, was it a boss? Was it maybe somebody not at work, your spouse or a friend that said go for it. What kind of pushed you over the edge to take that? >> It's a great question. It was actually the boss I was going to work for. He was the CHRO, and he said something that was so important to me that I've often said it to others. And he said trust me, he's like I know you don't have all the answers, I know we don't have this role all figured out, I know you're going to move your family, but if you trust me, there is a ton of learning on the other side of this. And sometimes that's the best thing a boss can do is say we will go on this journey together. I will help you figure it out. So it was a boss, but I think it was that trust and that willingness for him to stand and go alongside of me that made me pick up my family and be willing to move across the country. And we stayed five years and really, I am not the same executive because of that experience. >> Right, that's a great story, Jennifer, I want to go to you, you work for two owners that are so progressive and I remember when Joe Lacob came on the floor a few years back and was booed aggressively coming into a franchise that hadn't seen success in a very long time, making really aggressive moves in terms of personnel, both at the coaches and the players level, the GM level. But he had a vision and he stuck to it. And the net net was tremendous success. I wonder if you can share any of the stories, for you coming into that organization and being able to feel kind of that level of potential success and really kind of the vision and also really a focus on execution to make the vision real cause vision without execution doesn't really mean much. If you could share some stories of working for somebody like Joe Lacob, who's so visionary but also executes so very, very effectively. >> Yeah, Joe is, well I have the honor of working for Joe, for Rick Welts to who's our president. Who's living legend with the NBA with Peter Guber. Our leadership at the Warriors are truly visionary and they set audacious targets. And I would say from a story the most recent is, right now what we're living through today. And I will say Joe will not accept that we are not having games with fans. I agree he is so committed to trying to solve for this and he has really put the organization sort of on his back cause we're all like well, what do we do? And he has just refused to settle and is looking down every path as to how do we ensure the safety of our fans, the safety of our players, but how do we get back to live entertainment? And this is like a daily mantra and now the entire organization is so focused on this and it is because of his vision. And I think you need leaders like that who can set audacious goals, who can think beyond what's happening today and really energize the entire organization. And that's really what he's done. And when I talked to my peers and other teams in there they're talking about trying to close out their season or do these things. And they're like well, we're talking about, how do we open the building? And we're going to have fans, we're going to do this. And they look at me and they're like, what are you talking about? And I said, well we are so fortunate. We have leadership that just is not going to settle. Like they are just always looking to get out of whatever it is that's happening and fix it. So Joe is so committed His background, he's an epidemiologist major I think. Can you imagine how unique a background that is and how timely. And so his knowledge of just around the pandemic and how the virus is spread. And I mean it's phenomenal to watch him work and leverage sort of his business acumen, his science acumen and really think through how do we solve this. Its amazing. >> The other thing thing that you had said before is that you basically intentionally told people that they need to rethink their jobs, right? You didn't necessarily want to give them permission to get you told them we need to rethink their jobs. And it's a really interesting approach when the main business is just not happening, right? There's just no people coming through the door and paying for tickets and buying beers and hotdogs. It's a really interesting talk. And I'm curious, kind of what was the reception from the people like hey, you're the boss, you just figure it out or were they like hey, this is terrific that he pressed me to come up with some good ideas. >> Yeah, I think when all of this happened, we were resolved to make sure that our workforce is safe and that they had the tools that they needed to get through their day. But then we really challenged them with re imagining what the next normal is. Because when we come out of this, we want to be ahead of everybody else. And that comes again from the vision that Joe set, that we're going to use this time to make ourselves better internally because we have the time. I mean, we had been racing towards opening Chase Center and not having time to pause. Now let's use this time to really rethink how we're doing business. What can we do better? And I think it's really reinvigorated teams to really think and innovate in their own areas because you can innovate anything, right?. We're innovating how you pay payables, we're all innovating, we're rethinking the fan experience and queuing and lines and all of these things because now we have the time that it's really something that top down we want to come out of this stronger. >> Right, that's great. Kate I'll go to you, Julie Sweet, I'm a big fan of Julie Sweet. we went to the same school so go go Claremont. But she's been super aggressive lately on a lot of these things, there was a get to... I think it's called Getting to 50 50 by 25 initiative, a formal initiative with very specific goals and objectives. And then there was a recent thing in terms of doing some stuff in New York with retraining. And then as you said, military being close to your heart, a real specific military recruiting process, that's formal and in place. And when you see that type of leadership and formal programs put in place not just words, really encouraging, really inspirational, and that's how you actually get stuff done as you get even the consulting businesses, if you can't measure it, you can't improve it. >> Yeah Jeff, you're exactly right. And as Jennifer was talking, Julie is exactly who I was thinking about in my mind as well, because I think it takes strong leadership and courage to set bold bold goals, right? And you talked about a few of those bold goals and Julie has certainly been at the forefront of that. One of the goals we set in 2018 actually was as you said to achieve essentially a gender balance workforce. So 50% men, 50% women by 2025, I mean, that's ambitious for any company, but for us at the time we were 400,000 people. They were 500, 6,000 globally. So when you set a goal like that, it's a bold goal and it's a bold vision. And we have over 40% today, We're well on our path to get to 50%, I think by 2025. And I was really proud to share that goal in front of a group of 200 clients the day that it came out, it's a proud moment. And I think it takes leaders like Julie and many others by the way that are also setting bold goals, not just in my company to turn the dial here on gender equality in the workforce, but it's not just about gender equality. You mentioned something I think it's probably at as, or more important right now. And that's the fact that at least our leadership has taken a Stand, a pretty bold stand against social injustice and racism, >> Right which is... >> And so through that we've made some very transparent goals in North America in terms of the recruitment and retention of our black African American, Hispanic American, Latinex communities. We've set a goal to increase those populations in our workforce by 60% by 2025. And we're requiring mandatory training for all of our people to be able to identify and speak up against racism. Again, it takes courage and it takes a voice. And I think it takes setting bold goals to make a change and these are changes we're committed to. >> Right, that's terrific. I mean, we started the conversation with Grace Hopper, they put out an index for companies that don't have their own kind of internal measure to do surveys again so you can get kind of longitudinal studies over time and see how you're improving Inamarie, I want to go to you on the social justice thing. I mean, you've talked a lot about values and culture. It's a huge part of what you say. And I think that the quote that you use, if I can steal it is " no culture eats strategy for breakfast" and with the social injustice. I mean, you came out with special values just about what Zendesk is doing on social injustice. And I thought I was actually looking up just your regular core mission and value statement. And this is what came up on my Google search. So I wanted to A, you published this in a blog in June, taking a really proactive stand. And I think you mentioned something before that, but then you're kind of stuck in this role as a mind reader. I wonder if you can share a little bit of your thoughts of taking a proactive stand and what Zendesk is doing both you personally, as well as a company in supporting this. And then what did you say as a binder Cause I think these are difficult kind of uncharted waters on one hand, on the other hand, a lot of people say, hello, this has been going on forever. You guys are just now seeing cellphone footage of madness. >> Yeah Wow, there's a lot in there. Let me go to the mind reader comments, cause people are probably like, what is that about? My point was last December, November timing. I've been the Chief People Officer for about two years And I decided that it really was time with support from my CEO that Zendesk have a Chief Diversity Officer sitting in at the top of the company, really putting a face to a lot of the efforts we were doing. And so the mind reader part comes in little did I know how important that stance would become, in the may June Timing? So I joked that, it almost felt like I could have been a mind reader, but as to what have we done, a couple of things I would call out that I think are really aligned with who we are as a company because our culture is highly threaded with the concept of empathy it's been there from our beginning. We have always tried to be a company that walks in the shoes of our customers. So in may with the death of George Floyd and the world kind of snapping and all of the racial injustice, what we said is we wanted to not stay silent. And so most of my postings and points of view were that as a company, we would take a stand both internally and externally and we would also partner with other companies and organizations that are doing the big work. And I think that is the humble part of it, we can't do it all at Zendesk, we can't write all the wrongs, but we can be in partnership and service with other organizations. So we used funding and we supported those organizations and partnerships. The other thing that I would say we did that was super important along that empathy is that we posted space for our employees to come together and talk about the hurt and the pain and the experiences that were going on during those times and we called those empathy circles. And what I loved is initially, it was through our mosaic community, which is what we call our Brown and black and persons of color employee resource group. But it grew into something bigger. We ended up doing five of these empathy circles around the globe and as leadership, what we were there to do is to listen and stand as an ally and support. And the stories were life changing. And the stories really talked about a number of injustice and racism aspects that are happening around the world. And so we are committed to that journey, we will continue to support our employees, we will continue to partner and we're doing a number of the things that have been mentioned. But those empathy circles, I think were definitely a turning point for us as an organization. >> That's great, and people need it right? They need a place to talk and they also need a place to listen if it's not their experience and to be empathetic, if you just have no data or no knowledge of something, you need to be educated So that is phenomenal. I want to go to you Jennifer. Cause obviously the NBA has been very, very progressive on this topic both as a league, and then of course the Warriors. We were joking before. I mean, I don't think Steph Curry has ever had a verbal misstep in the history of his time in the NBA, the guy so eloquent and so well-spoken, but I wonder if you can share kind of inside the inner circle in terms of the conversations, that the NBA enabled right. For everything from the jerseys and going out on marches and then also from the team level, how did that kind of come down and what's of the perception inside the building? >> Sure, obviously I'm so proud to be part of a league that is as progressive and has given voice and loud, all the teams, all the athletes to express how they feel, The Warriors have always been committed to creating a diverse and equitable workplace and being part of a diverse and equitable community. I mean that's something that we've always said, but I think the situation really allowed us, over the summer to come up with a real formal response, aligning ourselves with the Black Lives Matter movement in a really meaningful way, but also in a way that allows us to iterate because as you say, it's evolving and we're learning. So we created or discussed four pillars that we wanted to work around. And that was really around wallet, heart, beat, and then tongue or voice. And Wallet is really around putting our money where our mouth is, right? And supporting organizations and groups that aligned with the values that we were trying to move forward. Heart is around engaging our employees and our fan base really, right? And so during this time we actually launched our employee resource groups for the first time and really excited and energized about what that's doing for our workforce. This is about promoting real action, civic engagement, advocacy work in the community and what we've always been really focused in a community, but this really hones it around areas that we can all rally around, right? So registration and we're really focused on supporting the election day results in terms of like having our facilities open to all the electorate. So we're going to have our San Francisco arena be a ballot drop off, our Oakland facilities is a polling site, Santa Cruz site is also a polling location, So really promoting sort of that civic engagement and causing people to really take action. heart is all around being inclusive and developing that culture that we think is really reflective of the community. And voice is really amplifying and celebrating one, the ideas, the (indistinct) want to put forth in the community, but really understanding everybody's culture and really just providing and using the platform really to provide a basis in which as our players, like Steph Curry and the rest want to share their own experiences. we have a platform that can't be matched by any pedigree, right? I mean, it's the Warriors. So I think really getting focused and rallying around these pillars, and then we can iterate and continue to grow as we define the things that we want to get involved in. >> That's terrific. So I have like pages and pages and pages of notes and could probably do this for hours and hours, but unfortunately we don't have that much time we have to wrap. So what I want to do is give you each of you the last word again as we know from this problem, right? It's not necessarily a pipeline problem, it's really a retention problem. We hear that all the time from Girls in Code and Girls in Tech. So what I'd like you to do just to wrap is just a couple of two or three sentences to a 25 year old, a young woman sitting across from you having coffee socially distanced about what you would tell her early in the career, not in college but kind of early on, what would the be the two or three sentences that you would share with that person across the table and Annabel, we'll start with you. >> Yeah, I will have to make a pitch for transportation. So in transportation only 15% of the workforce is made up of women. And so my advice would be that there are these fields, there are these opportunities where you can make a massive impact on the future of how people move or how they consume things or how they interact with the world around them. And my hope is that being at Waymo, with our self driving car technology, that we are going to change the world. And I am one of the initial people in this group to help make that happen. And one thing that I would add is women spend almost an hour a day, shuttling their kids around, and we will give you back that time one day with our self driving cars so that I'm a mom. And I know that that is going to be incredibly powerful on our daily lives. >> Jeff: That's great. Kate, I think I might know what you're already going to say, but well maybe you have something else you wanted to say too. >> I don't know, It'll be interesting. Like if I was sitting across the table from a 25 year old right now I would say a couple of things first I'd say look intentionally for a company that has an inclusive culture. Intentionally seek out the company that has an inclusive culture, because we know that companies that have inclusive cultures retain women in tech longer. And the companies that can build inclusive cultures will retain women in tech, double, double the amount that they are today in the next 10 years. That means we could put another 1.4 million women in tech and keep them in tech by 2030. So I'd really encourage them to look for that. I'd encouraged them to look for companies that have support network and reinforcements for their success, and to obviously find a Waymo car so that they can not have to worry where kids are on for an hour when you're parenting in a few years. >> Jeff: I love the intentional, it's such a great word. Inamarie, >> I'd like to imagine that I'm sitting across from a 25 year old woman of color. And what I would say is be authentically you and know that you belong in the organization that you are seeking and you were there because you have a unique perspective and a voice that needs to be heard. And don't try to be anything that you're not, be who you are and bring that voice and that perspective, because the company will be a better company, the management team will be a better management team, the workforce will be a better workforce when you belong, thrive and share that voice. >> I love that, I love that. That's why you're the Chief People Officer and not Human Resources Officer, cause people are not resources like steel and cars and this and that. All right, Jennifer, will go to you for the wrap. >> Oh my gosh, I can't follow that. But yes, I would say advocate for yourself and know your value. I think really understanding what you're worth and being willing to fight for that is critical. And I think it's something that women need to do more. >> Awesome, well again, I wish we could go all day, but I will let you get back to your very, very busy day jobs. Thank you for participating and sharing your insight. I think it's super helpful. And there and as we said at the beginning, there's no better example for young girls and young women than to see people like you in leadership roles and to hear your voices. So thank you for sharing. >> Thank you. >> All right. >> Thank you. >> Okay thank you. >> Thank you >> All right, so that was our diversity panel. I hope you enjoyed it, I sure did. I'm looking forward to chapter two. We'll get it scheduled as soon as we can. Thanks for watching. We'll see you next time. (upbeat music)

Live from San Diego, California it's theCUBE! covering KubeCon and CloudNativeCon brought to you by Red Hat a CloudNative computing foundation and its ecosystem partners. >> Welcome back, this is theCube's coverage of KubeCon, CloudNativeCon 2019 in San Diego I'm Stu Miniman with my co-host for the week, John Troyer, and happy to welcome to the program, Tom Phelan, who's an HPE Fellow and was the BlueData CTO >> That's correct. >> And is now part of Hewlett-Packard Enterprise. Tom, thanks so much for joining us. >> Thanks, Stu. >> All right, so we talked with a couple of your colleagues earlier this morning. >> Right. >> About the HPE container platform. We're going to dig in a little bit deeper later. >> So, set the table for us as to really the problem statement that HP is going to solve here. >> Sure, so Blue Data which is what technologies we're talking about, we addressed the issues of how to run applications well in containers in the enterprise. Okay, what this involves is how do you handle security how do you handle Day-2 operations of upgrade of the software how do you bring CI and CD actions to all your applications. This is what the HPE container platform is all about. So, the announcement this morning, which went out was HPE is announcing the general availability of the HPE container platform, an enterprise solution that will run not only CloudNative applications, are typically called microservices applications, but also Legacy applications on Kubernetes and it's supported in a hybrid environment. So not only the main public cloud providers, but also on premise. And a little bit of divergence for HPE, HPE is selling this product, licensing this product to work on heterogeneous hardware. So not only HPE hardware, but other competitors' hardware as well. >> It's good, one of the things I've been hearing really over the last year is when we talked about Kubernetes, it resonated, for the most part, with me. I'm an infrastructure guy by background. When I talk in the cloud environment, it's really talking more about the applications. >> Exactly. >> And that really, we know why does infrastructure exist? Infrastructure is just to run my applications, it's about my data, it's about my business processes >> Right. >> And it seems like that is a y'know really where you're attacking with this solution. >> Sure, this solution is a necessary portion of the automated infrastructure for providing solutions as a service. So, um, historically, BlueData has been specializing in artificial intelligence, machine learning, deep learning, big data, that's where our strong suit came from. So we, uh, developed a platform that would containerize those applications like TensorFlow, um, Hadoop, Spark, and the like, make it easy for data scientists to stand up some clusters, and then do the horizontal scalability, separate, compute, and storage so that you can scale your compute independent of your storage capacity. What we're now doing is part of the HPE container platform is taking that same knowledge, expanding it to other applications beyond AI, ML, and DL. >> So what are some of those Day-2 implications then uh what is something that folks run into that then now with an HPE container platform you think will eliminate those problems? >> Sure, it's a great question, so, even though, uh, we're talking about applications that are inherently scalable, so, AI and ML and DL, they are developed so they can be horizontal- horizontally scalable, they're not stateless in the true sense of the word. When we say a stateless application, that means that, uh, there is no state in the container itself that matters. So if you destroy the container, reinstate it, there's no loss of continuity. That's a true stateless or CloudNative application. Uh, AI and ML and DL applications tend to have configuration information and state information that's stored in what's known as the Root Storage of the compute node, okay, what's in slash, so you might see, um, per node configuration information in a configuration file in the Etsy directory. Okay, today, if you just take standard off the shelf Kubernetes, if you deploy, um, Hadoop for example, or TensorFlow, and you configure that, you lose that state when the container goes down. With the HPE container platform, we are, we have been moving forward with a, or driving, a open source project known as KubeDirector. A portion of KubeDirector, of the functionality is to preserve that, uh, Root Storage so that if a container goes down, we are allowed- we are enabled to bring a Nether Instance of that container and have it have the same Root Storage. So it'll look like a just a reboot to the node rather than a reinstall of that node. So that's a huge value when you're talking about these, um, machine learning and deep learning applications that have the state in root. >> All right, so, Tom, how does KubeDirector fit compared to compare contrast it, does it kind of sit aside something like Rook, which was talked about in the keynote, talking about being able to really have that, uh, that kind of universal backplate across all of my clusters >> Right, you're going to have to be >> Is that specific for AI and ML or is this >> I, well, that's a great question, so KubeDirector itself is a Kubernetes operator, okay, uh, and we have implemented that, the open-source communities joining in, so, but what it allows us, KubeDirector is, um, application agnostic, so, you could author a YAML file with some pertinent information about the application that you want to deploy on Kubernetes. You give that YAML file to the KubeDirector operator, it will then deploy the application on your Kubernetes cluster and then manage the Day-2 activities, so this is beyond Helm, or beyond KubeFlow, which are deployment engines. So this also has, well, what happens if I lose my container? How do I bring the services back up, and those services are dependent upon the type of application that's there. That's what KubeDirector does. So, KubeDirector allows a new application to be deployed and managed on Kubernetes without having to write a operator in Go Code. Makes it much easier to bring a new application to the platform. >> Gotcha, so Tom, kind of a two-part question, first part, so, uh, you were one of the co-founders of BlueData >> And now with HPE, there's, sometimes I think with technology, some of them are kind of invented in a lab, or in a graduate student's head, others come out of real world experience. And, uh, you're smiling 'cause I think BlueData was really built around, uh, y'know, at least your experience was building these BlueData apps. >> This is a hundred percent real world experience. So we were one of the real early pioneers of bringing, um, these applications into containers y'know, truth be told, when BlueData first started, we were using VMs. We were using OpenStack, and VM more. And we realized that we didn't need to pay that overhead it was possible to go ahead and get the same thing out of a container. So we did that, and we suffered all the slings and arrows of how to make the, um, security of the container, uh, to meet enterprise class standards. How do we automatically integrate with active directory and LDAP, and Kerberos, with a single sign on all those things that enterprises require for their infrastructure, we learned that the hard way through working with, y'know, international banking organizations, financial institutions, investment houses, medical companies, so our, our, all our customers were those high-demand enterprises. Now that we're apart of HP, we're taking all that knowledge that we acquired, bringing it to Kubernetes, exposing it through KubeDirector, where we can, and I agree there will be follow on open-source projects, releasing more of that technology to the open-source community. >> Mhm that was, that was actually part-two of my question is okay, what about, with now with HPE, the apps that are not AI, ML and you nailed it, right, >> Yeah. >> All those enterprise requirements. >> Same problems exist, right, there is secure data, you have secure data in a public cloud, you have it on premise, how do you handle data gravity issues so that you store, you run your compute close to your data where it's necessary you don't want to pay for moving data across the web like that. >> All right, so Tom, platforms are used for lots of different things, >> Yes. >> Bring us inside, what do you feel from your early customers, some of the key use cases that should be highlighted? >> Our key use cases were those customers who were very interested, they had internal developers. So they had a lot of expertise in house, maybe they had medical data scientists, or financial advisors. They wanted to build up sandboxes, so we helped them stand up, cookie-cutter sandboxes within a few moments, they could go ahead and play around with them, if they screwed them up, so what? Right, we tear them down and redo it within moments, they didn't need a lot of DevOps, heavy weight-lifting to reinstall bare-metal servers with these complex stacks of applications. The data scientist that I want to use this software which just came out of the open-source community last week, deployed in a container and I want to mess it up, I want to tighten, y'know, really push the edge on this and so we did that. We developed this sandboxing platform. Then they said, okay, now that you've tested this, I have it in queue A, I've done my CI/CD, I've done my testing, now I want to promote it into production. So we did that, we allowed the customer to deploy and define different quality of service depending on what tier their application was running in. If it was in testing dev, it got the lowest tier. If it was in CI/CD, it got a higher level of resource priority. Once it got promoted to production, it got guaranteed resource priority, the highest solution, so that you could always make sure that the customer who is using the production cluster got the highest level of access to the resources. So we built that out as a solution, KubeDirector now allows us to deploy that same sort of thing with the Kubernetes container orchestrator. >> Tom, you mentioned blue metal, uh, bare-metal, we've talked about VMs, we've been hearing a lot of multicloud stories here, already today, the first day of KubeCon, it seems like that's a reality out in the world, >> Can you talk about where are people putting applications and why? >> Well, clearly, uh, the best practices today are to deploy virtual machines and then put containers in virtual machines, and they do that for two very legitimate reasons. One is concern about the security, uh, plane for containers. So if you had a rogue actor, they could break out of the container, and if they're confined within the virtual machine, you can limit the impact of the damage. One very good, uh, reason for virtual machines, also there's a, uh, feeling that it's necessary to maintain, um, the container's state running in a virtual machine, and then be allowed to upgrade the the Prom Code, or the host software itself. So you want to be able to vMotion a virtual machine from one physical host to another, and then maintain the state of the containers. What KubeDirector brings and what BlueData and HP are stating is we believe we can provide both of those functionalities on containers on bare-metal. Okay, and we've spoken a bit about today already about how KubeDirector allows the Root File System to be preserved. That is a huge component of of why vMotion is used to move the container from one host to another. We believe that we can do that with a reboot. Also, um, HPE container platform runs all virtual machines as, um, reduced priority. So you're not, we're not giving root priority or privileged priority to those containers. So we minimize the attack plane of the software running in the container by running it as an unprivileged user and then tight control of the container capabilities that are configured for a given container. We believe it's just enough priority or just enough functionality which is granted to that container to run the application and nothing more. So we believe that we are limiting the attack plane of that through the, uh and that's why we believe we can validly state we can run these containers on bare-metal without, without the enterprise having to compromise in areas of security or persistence of the data. >> All right, so Tom, the announcement this week, uh is HP container platform available today? >> It will be a- we are announcing it. It's a limited availability to select customers It'll be generally available in Queue 1 of 2020. >> All right, and y'know, give us, y'know, we come back to KubeCon, which will actually be in Boston >> Yes. >> Next year in November >> When we're sitting down with you and you say hugely successful >> Right. >> Give us some of those KPIs as to y'know >> Sure. >> What are your teams looking at? >> So, we're going to look at how many new customers these are not the historic BlueData customers, how many new customers have we convinced that they can run their production work loads on Kubernetes And we're talking about I don't care how many POCs we do or how many testing dev things I want to know about production workloads that are the bread and butter for these enterprises that HP is helping run in the industry. And that will be not only, as we've talked about, CloudNative applications, but also the Legacy, J2EE applications that they're running today on Kubernetes. >> Yeah, I, uh, I don't know if you caught the keynote this morning, but Dan Kohn, y'know, runs the CNCF, uh, was talking about, y'know, a lot of the enterprises have been quitting them with second graders. Y'know, we need to get over the fact that y'know things are going to break and we're worried about making changes y'know the software world that y'know we've been talking about for a number of years, absolutely things will break, but software needs to be a resilient and distributed system, so, y'know, what advice do you give the enterprise out there to be able to dive in and participate? >> It's a great question, we get it all the time. The first thing is identify your most critical use case. Okay, that we can help you with and, and don't try to boil the ocean. Let's get the container platform in there, we will show you how you have success, with that one application and then once that's you'll build up confidence in the platform and then we can run the rest of your applications and production. >> Right, well Tom Phelan, thanks so much for the updates >> Thank you, Stu. >> Congratulations on the launch >> Thank you. >> with the HP container platform and we look forward to seeing the results in 2020. >> Well I hope you invite me back 'cause this was really fun and I'm glad to speak with you today. Thank you. >> All right, for John Troyer, I'm Stu Miniman, still watch more to go here at KubeCon, CloudNativeCon 2019. Thanks for watching theCUBE. (energetic music)

>> From the SiliconANGLE Media Office in Boston, Massachusetts, it's The Cube! Now, here's your host, Dave Velante. >> We're back with Patrick Osborne. All right Patrick, we've been talking about how customers want to be data-driven, they're doing digital transformation, they want to put data at the core of the enterprise. All sounds good. What's your strategy as HPE in terms of helping them get there? >> Yeah so, for our customers, this is a common theme, right. Some feel that they're going to be disrupted, they've been disrupted, right, and one of the key threads that runs through that is that they want to get more AI driven, right, so they want to use analytics as a way to provide new services around their products, get these services out faster, be able to use all that data they have in their enterprise. So for us, it's being able to have that conversation of whether the data sits out in the edge, right, you guys are very familiar with our Edge strategy, using Edgeline and Aruba, our core infrastructure in the data center, which we've had-- for a long history of helping customers with that, and then more recently around Hybrid Cloud, right, so most of the products, services, experiences we have there have Hybrid Cloud built in from the ground up. So for us, all those conversations have to do with data. >> So you recently made an acquisition of BlueData. >> Correct. >> What was that all about? Was that your AI play? Was it a software-as-a-service play? Explain that. >> Yeah, certainly a little bit of both. BlueData's a fantastic platform and it allows you to virtualize, containerize the application, so we know that in the market, you've got mode one applications, you've got mode two applications, a lot of mode one apps, you know, business applications, mission critical applications, have been virtualized. But what we also see is that a lot of the new product development is around these mode two applications that are using things like big data, whether it's a dupe in H-D-F-S, fast data - some of the streaming services - and now you're doing things around A-I inferencing, modeling, all using essentially containers as a way to do that, fuel that application development. So when we saw BlueData, it's essentially a platform to be able to virtualize all of these container-based applications. And as customers, big data and analytics and A-I platforms and their pipeline gets bigger and more complicated, it allows us to, A) manage that, increase their time to value, unlock a lot of the resources on the data scientists side, right, who have the responsibility of managing all of those applications, and it's a really great platform, great people, right, so they have a team of data scientists to be able to help customers implement this, not only within the product but within their own enterprise. And then we've got some really, really big logos that we're going to build off of for the BlueData ecosystem. >> So things are moving very fast. You've got all this data, you're applying machine intelligence and quickly moving from a world that was all batch to one that's real time, and we blinked and real time flew by. Now you've got this machine intelligence world where systems are acting, they're sensing, they're hearing, they're smelling... >> Yup. >> And so, is that what you're seeing with customers? Are they trying to build these sort of new systems that will act on their behalf? >> Absolutely. We see it on our own. If you take a look at some of our strategy, as HPE, especially within our storage and big data division, one of the big things that we're doing is introducing all of our products with the capability of A-I ops, right. And so all of our products that go out the door, using platforms like Infosite, will have this A-I ops capability to, not only just start with support automation, predictive analytics, and now you've got predictive A-I driving the actual management experience of these products. And it lets our customers ultimately unlock those resources that were doing mundane, repeatable tasks to focus on where they're going to add value. >> So I got to ask you, you guys do-- obviously a lot of your revenue comes from indirect channels. So you've seen the cloud, the cloud is not about selling boxes anymore, now you're seeing all this machine intelligence and automation. What does all this mean for partners? Where's the opportunity for those guys? >> Yeah so, I would say that when we go and make an acquisition like Blue Data, it's a great, like we said before, it's a great product, it's a good platform, right, they've got great engineers and great people within the organization and certainly some big logos. The reason why they got those logos was partly based on the product, but it's also a very services led methodology. So for-- I'd say for our partner community, being able to do discovery services, to understand what they're requirements are, a lot of folks that use BlueData and these type of platforms are builders. They're building a platform that has services on it for their end user customers. So being able to gather those requirements, do implementation, certainly be able to take a lot of this dynamic application ecosystem that is either very new, it's nascent, when you take a look at A-I or it's even in the open source arena, being able to de-risk that for the customers, from a services perspective, is a huge opportunity. >> Okay, great, so that's exciting because it's new frontier for those folks. So think about HPE, the tech that you guys have, the partner opportunity that you just described, how are you going to change the life of a data scientist? And maybe we could add in some other personas as well. >> Yeah, so, as a lot of our customers and partners certainly know, data scientists don't grow on trees, right, and they're very important folks within these large organizations, right, so you want to unlock their capabilities. So for us at the end of the day, we're trying to have a platform and as a service experience around A-I that unlocks the value of these data scientists. So for example, if I have a production environment or a U-A-T or a test dev environment, I can very quickly spin up your entire toolchain as a data scientist, right, so your toolchain, your models, your H-D-F-S data lakes, you can tap into existing data lakes, all of my streaming data, Kafka, Spark, all this stuff, very dynamic ecosystem, complex application dependencies. What I can do is I can sandbox that, I can test it, I can iterate, and I can very, very quickly provide that type of environment for your developers and your data scientists (snaps) just like that. >> So, in addition to the data scientist, is the chief data officer somebody that you guys are interacting with? There's also the application developer. Are you trying to sort of effect this collaboration amongst those different roles and personas? >> Yeah I think one of the greatest things for the partners and we've seen this at HPE too, is that you're going to be calling on new buyer personas. Right, so in the case of infrastructure, working a lot with enterprise architects, data center manager, infrastructure manager, C-I-O. In the case of BlueData and some of these A-I and analytics projects, right, you're at the front of the budget cycle, right, so you're talking to line of business, application developers, data scientists, analytics team, and now the rise of the C-D-O, the chief data officer. So you not only get to establish value with the infrastructure team, who are going to have to support this, right, you're going to go make some new friends and be able to get on the front of the budget cycle with a whole new set of buyer personas, and I think that's very exciting for partners. >> So, we talk a lot about A-I and, sort of this machine learning environment, machine intelligence. Software-defined is a hot topic. It's kind of a buzzword but it has meaning. What does it mean to you? Where does it fit in this whole equation? >> It's very adjacent to the big data and A-I analytics conversation. I think that what we see in software-defined, it's heavy on scale, right, so now that you're into petabytes, tens of petabytes, hundreds of petabytes, scaling, scaling, scaling, you need some new architectures to be able to do that cost-effectively. And you think about automated cars for example. They're-- each car is spinning off terabytes of data a day, so think about how am I going to store that, it's a monumental task. You got scale on your mind, you also have automation, right, so not only the scale of being able to store that effectively from a price-point, to be able to automate that. So you want to keep your-- the folks who are managing that infrastructure, they're going to have to increase the amount of systems, capacity under management, and the only way you can achieve that is through automation. And so, we see some themes around that and software-defined is really, kind of stepping in in that angle where you've got N-V-M-E, S-S-Ds, can saturate-- two N-V-M-E can saturate a C-P-U at this point, right, and now you're moving to hundred gig fabrics, so this rack-scale architecture that you can provide and paint on different software-defined personalities onto it is something that customers are definitely leaning in towards right now. >> And what you've been describing-- you mentioned autonomous vehicles-- data's at the edge, it's at the core, it's everywhere, and so, easier to bring, maybe, let's call it, ten meg of code to a petabyte of data than the reverse. >> Yeah, and what we see too is customers want to-- they want to dip their toe in this water, right, starting with very large enterprises, and we're able to, as HPE, bring a vetted ecosystem, whether from a workload perspective, 'cause we always talk about follow the workload, in software-defined, if you need something like scale-out file for A-I workloads, or you need scale-out file for more of a high performance, capacity-driven architecture, you're looking for object storage, you're looking for hyper-converged secondary, right, we bring an ecosystem of partners running on our infrastructure that's scalable, automated, and customers can feel confident in. >> Awesome. Well thank you Patrick, love the story. >> Yeah, thank you so much. >> You're welcome. (upbeat music)

>> Announcer: Live from Washington DC, it's theCUBE. Covering .conf2017. Brought to you by Splunk. >> Welcome back here on theCUBE, we're in Washington DC at the Walter Washington Convention Center, day one of .conf2017, Splunk's big get together here with some 7,000 plus attendees, 65 countries, and traveled something like some 30 million miles to get here? Incredible turn out, it really is impressive, and a great day we're having here on theCUBE. Which of course is the flagship broadcast of SiliconANGLE TV. Joining me is Jeff Chancey, who is a managing director within Accenture Technology Ecosystem and Ventures. Jeff, good to see you here in Washington, welcome to town. >> Likewise, thank you very much. Excited to be here. >> Yeah, it's certainly been a great day, great first day, let's talk about your partnership, Accenture with Splunk, and what do you see the future for the partnership, how is it evolving? >> Well it's interesting you might ask that, it's probably the $64,000 question. The future of the partnership is indeed exciting. Let me kind of articulate what I mean by that. We Accenture, we're a large professional services firm, our competencies around Accenture Strategy, Accenture Consulting, Accenture Digital Technology Operations, and Accenture Security. What makes the partnership with Splunk so interesting and unique, and also very dynamic, is the fact that Splunk as a transformational data platform applies across the full spectrum of business that Accenture does. So if you can bring the power of an Accenture and our presence in the market, across all the different industry verticals, all the horizontals, and the power of a transformational data engine like Splunk together, you could say it should be a very exciting future indeed. Probably our biggest objective is to really help, in Accenture we call it rotating to the new. So rotating to new technology, and Splunk is definitely part of our agenda to rotate to the new. We are looking to help our clients become data and digital driven businesses, by leveraging the enormous volumes of data that keep exponentially getting generated every single day, through connected devices, applications, infrastructure, across the board, the Internet of Things, everything is now connected, and everything is spooling data. So, we know that our enterprise executive clients, they're all struggling with this challenge that says, "how do I not only, get value out of my data, how do I solve this challenge with the exponential generation of data, so that I don't just survive in the market, but I win?" This is really what we're after as a partnership is that step change transformational agenda, with our enterprise clients. >> So you have this budding partnership, you've talked about all these fantastic opportunities and great potentials and whatever, is it possible, can you focus on one thing that you're most excited about when it comes to the partnership? >> The one thing I would say we're most excited about right now is our security agenda. We all know where Splunk sits, in terms of the security market. Accenture Security, our very first joint market offering is the Cyberdefense Engine, formally known as, our Cyberdefense Platform. That joint market offering stands to be, really what credentializes the partnership between Accenture and Splunk in the market. Very exciting. Every customer needs to mitigate risk, they must protect their enterprises, they're breaches happening every single day, it's in the news, and Splunk is a powerful technology to help our clients protect their enterprises. So, what you want to do, with Accenture and Splunk is we want to help our clients take out cost, take out cost out of the back office, to drive up their profitability and drive down their cost to serve their customers, we want to help them protect their enterprise through security, and then we want to help them drive step change value for their customers and for them through Internet of Things, and business analytics, automating away the work, and driving that value in the market. >> You're talking about this vast array of services, that you could provide, we know about your relationship with Splunk, you've got hordes and hordes of machine data right, pouring in all the time, how are your clients putting all that together, how are -- maybe some of the innovative ways that they're pulling these various resources and sources together and putting them to use? >> What our clients and what we're observing with our clients, is, with their data, they're data tends to reside in multiple silos, within the enterprise. This is normal, this is natural. What we can help do with a powerful technology like Splunk, is aggregate that data across all the different silos and bring it together in a single view. That not only helps the operations staff, as we said before, protecting the enterprise through security, and driving that value through business analytics, real time digital marketing, using geolocation services, for example. One of our exciting offerings is in the retail industry vertical. We're leveraging the power of Splunk to understand through Point of Sale data what product is going out the door, in say, a store operations environment, and also what inventory is coming through the back door, and triangulating that with the real time rate at which product is leaving the shelves, being able to help those retail customers actually do real time order management and trigger those events in real time. because if you're a retail custoner, the last thing you want to do is have products not on the shelf that your customers want to buy, and in the case of a grocery store for example, you don't want to have, your fresh foods spoil before you have a chance to sell it. So if you can bring together the dynamics of what's going in and out of the store with customer loyalty programs and geolocations, you can actually real time target those customers when they're in the vicinity of your store, and say, "The broccoli, we're offering you a special. Come in right now -- >> (laughing) >> We'll give you 15% off of broccoli", because we know you're a customer that likes to buy a lot of broccoli. That's a really exciting -- >> Inventory's everything, right? Inventory control. In this case -- >> And really applying it to the entire supply chain, 'cause obviously, the inventory from the manufacturing side, the consumer goods and services side, has to be available, has to be in the warehouses and the distribution centers, so, optimizing that entire, call it material and product movement, from the raw material and the manufacturing all the way to the consumer. >> We've heard a line, I know you have, greater insight, greater value. How are you at Accenture and Splunk bringing that statement to life for me as your customer? >> Clearly, if we can bring the power of data transformation leveraging next generation technologies like Splunk, and I have to say, we as a partnership, we view Splunk as an emerging technology. Not emerging in the sense that it -- doesn't exist yet, I mean they've been around for over a decade now, but emerging onto the world stage to really help power the way businesses drive their business by leveraging all of that data. The secret sauce that Splunk has, is that ability to aggregate that data from multiple disparate sources, and to do that in real time. If we can drive greater insight into the customer's data, we can collectively drive greater value. Interestingly enough, the greater than sign, is a coincidence, it's part of both Splunk and Accenture's logos. >> Yeah right, you both have it working for you, don't you? You're known for vertical industry practices, is there one or a specific vertical that you can think of that maybe where you all have teamed up and that you're creating this interest or some kind of innovative solution that you're able to specifically develop and apply? >> I mentioned retail, and I mentioned security previously. An interesting area that we're getting into now, is in Health and Life Sciences, so healthcare. We want to be able to predict and prevent hospital Code Blue's before they happen. How much would you be able to do that? All of the devices, all the monitors that all the hospitals have, they're all from different manufacturers, they're all spooling data, and most of the hospital staff are using eyes on glass. To understand, we have a Code Blue, you've seen it in the movies, everybody's running to resuscitate and save the patient. What we want to be able to do leveraging Splunk is to apply machine learning and predictive analytics, to understand what the monitors tell us, that in 15 minutes this patient is likely to be a Code Blue, and how do we predict and prevent that from happening in the first place. I really can't think of anything better than figuring out how to leverage technology to save lives. >> Absolutely. Well, if I'm in need, I want you around, okay? (laughing) >> Okay, you got it. >> We got a deal. Jeff Chancey, from Accenture, thanks for being with us here on theCUBE, appreciate the time and wish you success down the road. >> Thank you very much, appreciate it. >> You bet. We'll continue here, from .conf2017, we are live, in our nation's capital, Washington DC.