(soft corporate jingle) >> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat jingle intro) >> Welcome back to Barcelona. We're here live at the Fira. (laughs) Just amazing day two of MWC23. It's packed today. It was packed yesterday. It's even more packed today. All the news is flowing. Check out siliconangle.com. John Furrier is in the studio in Palo Alto breaking all the news. And, we are here live. Really excited to have Udayan Mukherjee who's the Senior Fellow and Chief Architect of wireless product at Network and Edge for Intel. And, Manish Singh is back. He's the CTO of Telecom Systems Business at Dell Jets. Welcome. >> Thank you. >> Thank you >> We're going to talk about greening the network. I wonder, Udayan, if you could just set up why that's so important. I mean, it's obvious that it's an important thing, great for the environment, but why is it extra important in Telco? >> Yeah, thank you. Actually, I'll tell you, this morning I had a discussion with an operator. The first thing he said, that the electricity consumption is more expensive nowadays that total real estate that he's spending money on. So, it's like that is the number one thing that if you can change that, bring that power consumption down. And, if you talk about sustainability, look what is happening in Europe, what's happening in all the electricity areas. That's the critical element that we need to address. Whether we are defining chip, platforms, storage systems, that's the number one mantra right now. You know, reduce the power. Electricity consumption, because it's a sustainable planet that we are living in. >> So, you got CapEx and OpEx. We're talking about the big piece of OpEx is now power consumption? >> Power Consumption >> That's the point. Okay, so in my experience, servers are the big culprit for power consumption, which is powered by core semiconductors and microprocessors. So, what's the strategy to reduce the power consumption? You're probably not going to reduce the bill overall. You maybe just can keep pace, but from a technical standpoint, how do you attack that? >> Yeah, there are multiple defined ways of adding. Obviously the process technology, that micro (indistinct) itself is evolving to make it more low-power systems. But, even within the silicon, the server that we develop, if you look in a CPU, there is a lot of power states. So, if you have a 32 code platform, as an example, every code you can vary the frequency and the C-states, power states. So, if you look into any traffic, whether it's a radio access network, packet code. At any given time the load is not peak. So, your power consumption, actual what we are drawing from the wall, it also needs to vary with that. So, that's how if you look into this there's a huge savings. If you go to Intel booth or Ericson booth or anyone, you will see right now every possible, the packet code, radio access network, everything network. They're talking about our energy consumption, how they're lowering this. These states, as we call it power states, C-state P-state they've built in intel chip for a long time. The cloud providers are taking advantage of it. But Telcos, with even two generation before they used to actually switch it off in the bios. I say no, we need peak. Now, that thing is changing. Now, it's all like, how do I take advantage of the built in technologies? >> I remember the enterprise virtualization, Manish, was a big play. I remember PG&E used to give rebates to customers that would install virtualized software, VMware. >> And SSDs. >> Yeah. And SSDs, you know, yes. Because, the spinning disc was, but, nowhere near with a server consumption. So, how virtualized is the telco network? And then, what I'm saying is there other things, other knobs, you can of course turn. So, what's your perspective on this as a server player? >> Yeah, absolutely. Let me just back up a little bit and start at the big picture to share what Udayan said. Here, day two, every conversation I've had yesterday and today morning with every operator, every CTO, they're coming in and first topic they're talking about is energy. And, the reason is, A, it's the right thing to do, sustainability, but, it's also becoming a P&L issue. And, the reason it's becoming a P&L issue is because we are in this energy inflationary environment where the energy costs are constantly going up. So, it's becoming really important for the service providers to really drive more efficiency onto their networks, onto their infrastructure. Number one. Two, then to your question on what all knobs need to be turned on, and what are the knobs? So, Udayan talked about within the intel, silicon, the C-states, P-states and all these capabilities that are being brought up, absolutely important. But again, if we take a macro view of it. First of all, there are opportunities to do infrastructure audit. What's on, why is it on, does it need to be on right now? Number two, there are opportunities to do infrastructure upgrade. And, what I mean by that is as you go from previous generation servers to next generation servers, better cooling, better performance. And through all of that you start to gain power usage efficiency inside a data center. And, you take that out more into the networks you start to achieve same outcomes on the network site. Think about from a cooling perspective, air cooling but for that matter, even liquid cooling, especially inside the data centers. All opportunities around PUE, because PUE, power usage efficiency and improvement on PUE is an opportunity. But, I'll take it even further. Workloads that are coming onto it, core, RAN, these workloads based on the dynamic traffic. Look, if you look at the traffic inside a network, it's not constant, it's varied. As the traffic patterns change, can you reduce the amount of infrastructure you're using? I.e. reduce the amount of power that you're using and when the traffic loads are going up. So, the workloads themselves need to become more smarter about that. And last, but not the least. From an orchestration layer if you think about it, where you are placing these workloads, and depending on what's available, you can start to again, drive better energy outcomes. And, not to forget acceleration. Where you need acceleration, can you have the right hardware infrastructures delivering the right kind of accelerations to again, improve those energy efficiency outcomes. So, it's a complex problem. But, there are a lot of levers, lot of tools that are in place that the service providers, the technology builders like us, are building the infrastructure, and then the workload providers all come together to really solve this problem. >> Yeah, Udayan, Manish mentioned this idea of moving from one generation to a new generation and gaining benefits. Out there on the street, if you will. Most of the time it's an N plus 2 migration. It's not just moving from last generation to this next generation, but it's really a generation ago. So, those significant changes in the dynamics around power density and cooling are meaningful? You talk about where performance should be? We start talking about the edge. It's hard to have a full-blown raised data center floor edge everywhere. Do these advances fundamentally change the kinds of things that you can do at the base of a tower? >> Yeah, absolutely. Manish talked about that, the dynamic nature of the workload. So, we are using a lot of this AIML to actually predict. Like for example, your multiple force in a systems. So, why is the 32 core as a system, why is all running? So, your traffic profile in the night times. So, you are in the office areas, in the night has gone home and nowadays everybody's working from remote anyway. So, why is this thing a full blown, spending the TDP, the total power and extreme powers. You bring it down, different power states, C-states. We talked about it. Deeper C-states or P-states, you bring the frequency down. So, lot of those automation, even at the base of the tower. Lot of our deployment right now, we are doing a whole bunch of massive MIMO deployment. Virtual RAN in Verizon network. All actually cell-site deployment. Those eight centers are very close to the cell-site. And, they're doing aggressive power management. So, you don't have to go to a huge data centers, even there's a small rack of systems, four to five, 10 systems, you can do aggressive power management. And, you built it up that way. >> Okay. >> If I may just build on what Udayan said. I mean if you look at the radio access network, right? And, let's start at the bottom of the tower itself. The infrastructure that's going in there, especially with Open RAN, if you think about it, there are opportunities now to do a centralized RAN where you could do more BBU pooling. And, with that, not only on a given tower but across a given given coverage area, depending on what the traffics are, you can again get the infrastructure to become more efficient in terms of what traffic, what needs are, and really start to benefit. The pooling gains which is obviously going to give you benefit on the CapEx side, but from an energy standpoint going to give you benefits on the OpEx side of things. So that's important. The second thing I will say is we cannot forget, especially on the radio access side of things, that it's not just the bottom of the tower what's happening there. What's happening on the top of the tower especially with the radio, that's super important. And, that goes into how do you drive better PA efficiency, how do you drive better DPD in there? This is where again, applying AI machine learning there is a significant amount of opportunity there to improve the PA performance itself. But then, not only that, looking at traffic patterns. Can you do sleep modes, micro sleep modes to deep sleep modes. Turning down the cells itself, depending on the traffic patterns. So, these are all areas that are now becoming more and more important. And, clearly with our ecosystem of partners we are continuing to work on these. >> So we hear from the operators, it's an OpEx issue. It's hitting the P&L. They're in search of PUE of one. And, they've historically been wasteful, they go full throttle. And now, you're saying with intelligence you can optimize that consumption. So, where does the intelligence live? Is it in the rig. Where is it all throughout the network? Is it in the silicon? Maybe you could paint a picture as to where those smarts exist. >> I can start. It's across the stack. It starts, we talked about the C-states, P-states. If you want to take advantage of that, that intelligence is in the workload, which has to understand when can I really start to clock things down or turn off the cores. If you really look at it from a traffic pattern perspective you start to really look at a rig level where you can have power. And, we are working with the ecosystem partners who are looking at applying machine learning on that to see what can we really start to turn on, turn off, throttle things down, depending on what the, so yes, it's across the stack. And lastly, again, I'll go back to cannot forget orchestration, where you again have the ability to move some of these workloads and look at where your workload placements are happening depending on what infrastructure is and what the traffic needs are at that point in time. So it's, again, there's no silver bullet. It has to be looked across the stack. >> And, this is where actually if I may, last two years a sea change has happened. People used to say, okay there are C-states and P-states, there's silicon every code. OS operating system has a governor built in. We rely on that. So, that used to be the way. Now that applications are getting smarter, if you look at a radio access network or the packet core on the control plane signaling application, they're more aware of the what is the underlying silicon power state sleep states are available. So, every time they find some of these areas there's no enough traffic there, they immediately goes to a transition. So, the workload has become more intelligent. The rig application we talked about. Every possible rig application right now are apps on xApps. Most of them are on energy efficiency. How are they using it? So, I think lot more even the last two years. >> Can I just say one more thing there right? >> Yeah. >> We cannot forget the infrastructure as well, right? I mean, that's the most important thing. That's where the energy is really getting drawn in. And, constant improvement on the infrastructure. And, I'll give you some data points, right? If you really look at the power at servers, right? From 2013 to 2023, like a decade. 85% energy intensity improvement, right? So, these gains are coming from performance with better cooling, better technology applications. So, that's super critical, that's important. And, also to just give you another data point. Apart from the infrastructure what cache layers we are running and how much CPU and compute requirements are there, that's also important. So, looking at it from a cache perspective are we optimizing the required infrastructure blocks for radio access versus core? And again, really taking that back to energy efficiency outcomes. So, some of the work we've been doing with Wind River and Red Hat and some of our ecosystem partners around that for radio access network versus core. Really again, optimizing for those different use cases and the outcomes of those start to come in from an energy utilization perspective >> So, 85% improvement in power consumption. Of course you're doing, I don't know, 2, 300% more work, right? So, let's say, and I'm just sort of spit balling numbers but, let's say that historically powers on the P&L has been, I don't know, single digits, maybe 10%. Now, it's popping up the much higher. >> Udayan: Huge >> Right? >> I mean, I don't know what the number is. Is it over 20% in some cases or is it, do you have a sense of that? Or let's say it is. The objective I presume is you're probably not going to lower the power bill overall, but you're going to be able to lower the percent of cost on the OpEx as you grow, right? I mean, we're talking about 5G networks. So much more data >> Capacity increasing. >> Yeah, and so is it, am I right about that the carriers, the best they can hope for is to sort of stay even on that percentage or maybe somewhat lower that percentage? Or, do you think they can actually cut the bill? What's the goal? What are they trying to do? >> The goal is to cut the bill. >> It is! >> And the way you get started to cut the bill is, as I said, first of all on the radio side. Start to see where the improvements are and look, there's not a whole lot there to be done. I mean, the PS are as efficient as they can be, but as I said, there are things in DPD and all that still can be improved. But then, sleep modes and all, yes there are efficiencies in there. But, I'll give you one important, another interesting data point. We did a work with ACG Research on our 16G platform. The power edge service that we have recently launched based on Intel's Sapphire Rapids. And, if you look at the study there. 30% TCR reduction, 10% in CapEx gains, 30% in OpEx gains from moving away from these legacy monolithic architectures to cloud native architectures. And, a large part of that OpEx gain really starts to come from energy to the point of 800 metric tonnes of carbon reduction to the point of you could have, and if you really translate that to around 160 homes electric use per year, right? So yes, I mean the opportunity there is to reduce the bill. >> Wow, that's big, big goal guys. We got to run. But, thank you for informing the audience on the importance and how you get there. So, appreciate that. >> One thing that bears mentioning really quickly before we wrap, a lot of these things we're talking about are happening in remote locations. >> Oh, back to that point of distributed nature of telecom. >> Yes, we talked about a BBU being at the base of a tower that could be up on a mountain somewhere. >> No, you made the point. You can't just say, oh, hey we're going to go find ambient air or going to go... >> They don't necessarily... >> Go next to a waterfall. >> We don't necessarily have the greatest hydro tower. >> All right, we got to go. Thanks you guys. Alright, keep it right there. Wall to wall coverage is day two of theCUBE's coverage of MWC 23. Stay right there, we'll be right back. (corporate outro jingle)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Welcome to the Fira in Barcelona, everybody. This is theCUBE's coverage of MWC 23, day one of that coverage. We have four days of wall-to-wall action going on, the place is going crazy. I'm here with Dave Nicholson, Lisa Martin is also in the house. Today's ecosystem day, and we're really excited to have Manish Singh who's the CTO of the Telecom Systems Business unit at Dell Technologies. He's joined by Doug Wolf who's the head of strategy for the Telecom Systems Business unit at Dell. Gents, welcome. What a show. I mean really the first major MWC or used to be Mobile World Congress since you guys have launched your telecom business, you kind of did that sort of in the Covid transition, but really exciting, obviously a huge, huge venue to match the huge market. So Manish, how did you guys get into this? What did you see? What was the overall thinking to get Dell into this business? >> Manish: Yeah, well, I mean just to start with you know, if you look at the telecom ecosystem today, the service providers in particular, they are looking for network transformation, driving more disaggregation into their network so that they can get better utilization of the infrastructure, but then also get more agility, more cloud native characteristics onto their, for their networks in particular. And then further on, it's important for them to really start to accelerate the pace of innovation on the networks itself, to start more supply chain diversity, that's one of the challenges that they've been having. And so there've been all these market forces that have been really getting these service providers to really start to transform the way they have built the infrastructure in the past, which was legacy monolithic architectures to more cloud native disaggregated. And from a Dell perspective, you know, that really gives us the permission to play, to really, given all the expertise on the work we have done in the IT with all the IT transformations to leverage all that expertise and bring that to the service providers and really help them in accelerating their network transformation. So that's where the journey started. We've been obviously ever since then working on expanding the product portfolio on our compute platforms to bring Teleco great compute platforms with more capabilities than we can talk about that. But then working with partners and building the ecosystem to again create this disaggregated and open ecosystem that will be more cloud native and really meet the objective that the service providers are after. >> Dave Vellante: Great, thank you. So, Doug the strategy obviously is to attack this market, as Manish said, from an open standpoint, that's sort of new territory. It's like a little bit like the wild, wild west. So maybe you could double click on what Manish was saying from a, from a strategy standpoint, yes, the Telecos need to be more flexible, they need to be more open, but they also need this reliability piece. So talk about that from a strategy standpoint of what you guys saw. >> Doug: Yeah, absolutely. As Manish mentioned, you know, Dell getting into open systems isn't something new. You know, Dell has been kind of playing in that world for years and years, but the opportunity in Telecom that came was opening of the RAN, the core network, the edge, all of these with 5G really created a wide opening for us. So we started developing products and solutions, you know, built our first Telecom grade servers for open RAN over the last year, we'll talk about those at the show. But you know, as, as Manish mentioned, an open ecosystem is new to Telecom. I've been in the Telecom business along with Manish for, you know, 25 plus years and this is a new thing that they're embarking on. So started with virtualization about five, six years ago, and now moving to cloud native architectures on the core, suddenly there's this need to have multiple parties partner really well, share specifications, and put that together for an operator to consume. And I think that's just the start of really where all the challenges are and the opportunities that we see. >> Where are we in this transition cycle? When the average consumer hears 5G, feels like it's been around for a long time because it was hyped beforehand. >> Doug: Yeah. >> If you're talking about moving to an open infrastructure model from a proprietary closed model, when is the opportunity for Dell to become part of that? Is it, are there specific sites that have already transitioned to 5G, therefore they've either made the decision to be open or not? Or are there places where the 5G transition has taken place, and they might then make a transition to open brand with 5G? Where, where are we in that cycle? What does the opportunity look like? >> I'll kind of take it from the typology of the operator, and I'm sure Manish will build on this, but if I look back on the core, started to get virtualized you know, back around 2015-16 with some of the lead operators like AT&T et cetera. So Dell has been partnering with those operators for some years. So it really, it's happening on the core, but it's moving with 5G to more of a cloud-like architecture, number one. And number two, they're going beyond just virtualizing the network. You know, they previously had used OpenStack and most of them are migrating to more of a cloud native architecture that Manish mentioned. And that is a bit different in terms of there's more software vendors in that ecosystem because the software is disaggregated also. So Dell's been playing in the core for a number of years, but we brought out new solutions we've announced at the show for the core. And the parts that are really starting that transition of maybe where the core was back in 2015 is on the RAN and on the edge in particular. >> Because NFV kind of predated the ascendancy of cloud. >> Exactly, yeah. >> Right, so it really didn't have the impact that people had hoped. And there's some, when you look back, 'cause it's not same wine, new bottle as the open systems movement, there are a lot of similarities but you know, you mentioned cloud, and cloud native, you really didn't have, back in the nineties, true engineered systems. You didn't really have AI that, you know, to speak of at the sort of volume of the data that we have. So Manish, from a CTO's perspective, how are you attacking some of those differences in bringing that to market? >> Manish: Yeah, I mean, I think you touched on some very important points there. So first of all, the duck's point, a lot of this transformation started in the core, right? And as the technology evolution progress, the opportunities opened up. It has now come into the edge and the radio access network as well, in particular with open RAN. And so when we talk about the disaggregation of the infrastructure from the software itself and an open ecosystem, this now starts to create the opportunity to accelerate innovation. And I really want to pick up on the point that you'd said on AI, for example. AI and machine learning bring a whole new set of capabilities and opportunities for these service providers to drive better optimization, better performance, better sustainability and energy efficiency on their infrastructure, on and on and on. But to really tap into these technologies, they really need to open that up to third parties implementation solutions that are coming up. And again, the end objective remains to accelerate that innovation. Now that said, all these things need to be brought together, right? And delivered and deployed in the network without any degradation in the KPIs and actually improving the performance on different vectors, right? So this is what the current state of play is. And with this aggregation I'm definitely a believer that all these new technologies, including AI, machine learning, and there's a whole area, host area of problems that can be solved and attacked and are actually getting attacked by applying AI and machine learning onto these networks. >> Open obviously is good. Nobody's ever going to, you know, argue that open is a bad thing. It's like democracy is a good thing, right? At least amongst us. And so, but, the RAN, the open RAN, has to be as reliable and performant, right, as these, closed networks. Or maybe not, maybe it doesn't have to be identical. Just has to be close enough in order for that tipping point to occur. Is that a fair summarization? What are you guys hearing from carriers in terms of their willingness to sort of put their toe in the water and, and what could we expect in terms of the maturity model of, of open RAN and adoption? >> Right, so I mean I think on, on performance that, that's a tough one. I think the operators will demand performance and you've seen experiments, you've really seen more of the Greenfield operators kind of launch. >> Okay. >> Doug: Open RAN or vRAN type solutions. >> So they're going to disrupt. >> Doug: Yeah, they're going to disrupt. >> Yeah. >> Doug: And there's flexibility in an open RAN architecture also for 5G that they, that they're interested in and I think the Brownfield operators are too, but let's say maybe the Greenfield jump first in terms of doing that from a mass deployment perspective. But I still think that it's going to be critical to meet very similar SLAs and end user performance. And, you know, I think that's where, you know, maturity of that model is what's required. I think Brownfield operators are conservative in terms of, you know, going with something they know, but the opportunities and the benefits of that architecture and building new flexible, potentially cost advantaged over time solutions, that's what the, where the real interest is going forward. >> And new services that you can introduce much more quickly. You know, the interesting thing about Dell to me, you don't compete with the carriers, the public cloud vendors though, the carriers are concerned about them sort of doing an end run on them. So you provide a potential partnership for the carriers that's non-threatening, right? 'Cause you're, you're an arms dealer, you're selling hardware and software, right? But, but how do you see that? Because we heard in the keynote today, one of the Teleco, I think it was the chairman of Telefonica said, you know, cloud guys can't do this alone. You know, they need, you know, this massive, you know, build out. And so, what do you think about that in terms of your relationship with the carriers not being threatening? I mean versus say potentially the cloud guys, who are also your partners, I understand, it's a really interesting dynamic, isn't it? >> Manish: Yeah, I mean I think, you know, I mean, the way I look at it, the carriers actually need someone like Dell who really come in who can bring in the right capabilities, the right infrastructure, but also bring in the ecosystem together and deliver a performance solution that they can deploy and that they can trust, number one. Number two, to your point on cloud, I mean, from a Dell perspective, you know, we announced our Dell Telecom Multicloud Foundation and as part of that last year in September, we announced what we call is the Dell Telecom Infrastructure Blocks. The first one we announced with Wind River, and this is, think of it as the, you know, hardware and the cashier all pre-integrated with lot of automation around it, factory integrated, you know, delivered to customers in an integrated model with all the licenses, everything. And so it starts to solve the day zero, day one, day two integration deployment and then lifecycle management for them. So to broaden the discussion, our view is it's a multicloud world, the future is multicloud where you can have different clouds which can be optimized for different workloads. So for example, while our work with Wind River initially was very focused on virtualization of the radio access network, we just announced our infrastructure block with Red Hat, which is very much targeted and optimized for core network and edge, right? So, you know, there are different workflows which will require different capabilities also. And so, you know, again, we are bringing those things to these service providers to again, bring those cloud characteristics and cloud native architecture for their network. >> And It's going to be hybrid, to your point. >> David N.: And you, just hit on something, you said cloud characteristics. >> Yeah. >> If you look at this through the lens of kind of the general world of IT, sometimes when people hear the word cloud, they immediately leap to the idea that it's a hyperscale cloud provider. In this scenario we're talking about radio towers that have intelligence living on them and physically at the base. And so the cloud characteristics that you're delivering might be living physically in these remote locations all over the place, is that correct? >> Yeah, I mean that, that's true. That will definitely happen over time. But I think, I think we've seen the hyperscalers enter, you know, public cloud providers, enter at the edge and they're dabbling maybe with private, but I think the public RAN is another further challenge. I think that maybe a little bit down the road for them. So I think that is a different characteristic that you're talking about managing the macro RAN environment. >> Manish: If I may just add one more perspective of this cloud, and I mean, again, the hyperscale cloud, right? I mean that world's been great when you can centralize a lot of compute capability and you can then start to, you know, do workload aggregation and use the infrastructure more efficient. When it comes to Telecom, it is inherently it distributed architecture where you have access, you talked about radio access, your port, and it is inherently distributed because it has to provide the coverage and capacity. And so, you know, it does require different kind of capabilities when you're going out and about, and this is where I was talking about things like, you know, we just talked, we just have been working on our bare metal orchestration, right? This is what we are bringing is a capability where you can actually have distributed infrastructure, you can deploy, you can actually manage, do lifecycle management, in a distributed multicloud form. So it does require, you know, different set of capabilities that need to be enabled. >> Some, when talking about cloud, would argue that it's always been information technology, it always will be information technology, and especially as what we might refer to as public cloud or hyperscale cloud providers, are delivering things essentially on premises. It's like, well, is that cloud? Because it feels like some of those players are going to be delivering physical infrastructure outside of their own data centers in order to address this. It seems the nature, the nature of the beast is that some of these things need to be distributed. So it seems perfectly situated for Dell. That's why you guys are both at Dell now and not working for other Telecom places, right? >> Exactly. Exactly, yes. >> It's definitely an exciting space. It's transformed, the networks are under transformation and I do think that Dell's very well positioned to, to really help the customers, the service providers in accelerating their transformation journey with an open ecosystem. >> Dave V.: You've got the brand, and the breadth, and the resources to actually attract an ecosystem. But I wonder if you could sort of take us through your strategy of ecosystem, the challenges that you've seen in developing that ecosystem and what the vision is that ultimately, what's the outcome going to be of that open ecosystem? >> Yeah, I can start. So maybe just to give you the big picture, right? I mean the big picture, is disaggregation with performance, right, TCO models to the service providers, right? And it starts at the infrastructure layer, builds on bringing these cloud capabilities, the cast layer, right? Bringing the right accelerators. All of this requires to pull the ecosystem. So give you an example on the infrastructure in a Teleco grade servers like XR8000 with Sapphire, the new intel processors that we've just announced, and an extended array of servers. These are Teleco grade, short depth, et cetera. You know, the Teleco great characteristic. Working with the partners like Marvel for bringing in the accelerators in there, that's important to again, drive the performance and optimize for the TCO. Working then with partners like Wind River, Red Hat, et cetera, to bring in the cast capabilities so you can start to see how this ecosystem starts to build up. And then very recently we announced our private 5G solution with AirSpan and Expeto on the core site. So bringing those workloads together. Similarly, we have an open RAN solution we announce with Fujitsu. So it's, it's open, it's disaggregated, but bringing all these together. And one of the last things I would say is, you know, to make all this happen and make all of these, we've also been putting together our OTEL, our open Telecom ecosystem lab, which is very much geared, really gives this open ecosystem a playground where they can come in and do all that heavy lifting, which is anyways required, to do the integration, optimization, and board. So put all these capabilities in place, but the end goal, the end vision again, is that cloud native disaggregated infrastructure that starts to innovate at the speed of software and scales at the speed of cloud. >> And this is different than the nineties. You didn't have something like OTEL back then, you know, you didn't have the developer ecosystem that you have today because on top of everything that you just said, Manish, are new workloads and new applications that are going to be developed. Doug, anything you'd add to what Manish said? >> Doug: Yeah, I mean, as Manish said, I think adding to the infrastructure layers, which are, you know, critical for us to, to help integrate, right? Because we kind of took a vertical Teleco stack and we've disaggregated it, and it's gotten a little bit more complex. So our Solutions Dell Technology infrastructure block, and our lab infrastructure with OTEL, helps put those pieces together. But without the software players in this, you know, that's what we really do, I think in OTEL. And that's just starting to grow. So integrating with those software providers with that integration is something that the operators need. So we fill a gap there in terms of either providing engineered solutions so they can readily build on or actually bringing in that software provider. And I think that's what you're going to see more from us going forward is just extending that ecosystem even further. More software players effectively. >> In thinking about O-RAN, are they, is it possible to have the low latency, the high performance, the reliability capabilities that carriers are used to and the flexibility? Or can you sort of prioritize one over the other from a go to market and rollout standpoint and optimize one, maybe get a foothold in the market? How do you see that balance? >> Manish: Oh the answer is absolutely yes you can have both We are on that journey, we are on that journey. This is where all these things I was talking about in terms of the right kind of accelerators, right kind of capabilities on the infrastructure, obviously retargeting the software, there are certain changes, et cetera that need to be done on the software itself to make it more cloud native. And then building all the surrounding capabilities around the CICD pipeline and all where it's not just day zero or day one that you're doing the cloud-like lifecycle management of this infrastructure. But the answer to your point, yes, absolutely. It's possible, the technology is there, and the ecosystem is coming together, and that's the direction. Now, are there challenges? Absolutely there are challenges, but directionally that's the direction the industry is moving to. >> Dave V.: I guess my question, Manish, is do they have to go in lockstep? Because I would argue that the public cloud when it first came out wasn't nearly as functional as what I could get from my own data center in terms of recovery, you know, backup and recovery is a perfect example and it took, you know, a decade plus to get there. But it was the flexibility, and the openness, and the developer affinity, the programmability, that attracted people. Do you see O-RAN following a similar path? Or does it, my question is does it have to have that carrier class reliability today? >> David N.: Everything on day one, does it have to have everything on day one? >> Yeah, I mean, I would say, you know, like again, the Greenfield operators I think we're, we're willing do a little bit more experimentation. I think the operators, Brownfield operators that have existing, you know, deployments, they're going to want to be closer. But I think there's room for innovation here. And clearly, you know, Manish came from, from Meta and we're, we've been very involved with TIP, we're very involved with the O-RAN alliance, and as Manish mentioned, with all those accelerators that we're working with on our infrastructure, that is a space that we're trying to help move the ball forward. So I think you're seeing deployments from mainstream operators, but it's maybe not in, you know, downtown New York deployment, they're more rural deployments. I think that's getting at, you know, kind of your question is there's maybe a little bit more flexibility there, they get to experiment with the technology and the flexibility and then I think it will start to evolve >> Dave V.: And that's where the disruption's going to come from, I think. >> David N.: Well, where was the first place you could get reliable 4K streaming of video content? It wasn't ABC, CBS, NBC. It was YouTube. >> Right. >> So is it possible that when you say Greenfield, are a lot of those going to be what we refer to as private 5G networks where someone may set up a private 5G network that has more functions and capabilities than the public network? >> That's exactly where I was going is that, you know, that that's why you're seeing us getting very active in 5G solutions that Manish mentioned with, you know, Expeto and AirSpan. There's more of those that we haven't publicly announced. So I think you'll be seeing more announcements from us, but that is really, you know, a new opportunity. And there's spectrum there also, right? I mean, there's public and private spectrum. We plan to work directly with the operators and do it in their spectrum when needed. But we also have solutions that will do it, you know, on non-public spectrum. >> So let's close out, oh go ahead. You you have something to add there? >> I'm just going to add one more point to Doug's point, right? Is if you look on the private 5G and the end customer, it's the enterprise, right? And they're, they're not a service provider. They're not a carrier. They're more used to deploying, you know, enterprise infrastructure, maintaining, managing that. So, you know, private 5G, especially with this open ecosystem and with all the open run capabilities, it naturally tends to, you know, blend itself very well to meet those requirements that the enterprise would have. >> And people should not think of private 5G as a sort of a replacement for wifi, right? It's to to deal with those, you know, intense situations that can afford the additional cost, but absolutely require the reliability and the performance and, you know, never go down type of scenario. Is that right? >> Doug: And low latencies usually, the primary characteristics, you know, for things like Industry 4.0 manufacturing requirements, those are tough SLAs. They're just, they're different than the operator SLAs for coverage and, you know, cell performance. They're now, you know, Five9 type characteristics, but on a manufacturing floor. >> That's why we don't use wifi on theCUBE to broadcast, we need a hard line. >> Yeah, but why wouldn't it replace wifi over time? I mean, you know, I still have a home phone number that's hardwired to align, but it goes to a voicemail. We don't even have handset anymore for it, yeah. >> I think, well, unless the cost can come down, but I think that wifi is flexible, it's cheap. It's, it's kind of perfect for that. >> Manish: And it's good technology. >> Dave V.: And it works great. >> David N.: For now, for now. >> Dave V.: But you wouldn't want it in those situations, and you're arguing that maybe. >> I'm saying eventually, what, put a sim in a device, I don't know, you know, but why not? >> Yeah, I mean, you know, and Dell offers, you know, from our laptop, you know, our client side, we do offer wifi, we do offer 4G and 5G solutions. And I think those, you know, it's a volume and scale issue, I think for the cost structure you're talking about. >> Manish: Come to our booth and see the connected laptop. >> Dave V.: Well let's, let's close on that. Why don't you guys talk a little bit about what you're going on at the show, I did go by the booth, you got a whole big lineup of servers. You got some, you know, cool devices going on. So give us the rundown and you know, let's end with the takeaways here. >> The simple rundown, a broad range of new powered servers, broad range addressing core, edge, RAN, optimized for those with all the different kind of acceleration capabilities. You can see that, you can see infrastructure blocks. These are with Wind River, with Red Hat. You can see OTEL, the open telecom ecosystem lab where all that playground, the integration, the real work, the real sausage makings happening. And then you will see some interesting solutions in terms of co-creation that we are doing, right? So you, you will see all of that and not to forget the connected laptops. >> Dave V.: Yeah, yeah, cool. >> Doug: Yeah and, we mentioned it before, but just to add on, I think, you know, for private 5G, you know, we've announced a few offers here at the show with partners. So with Expeto and AirSpan in particular, and I think, you know, I just want to emphasize the partnerships that we're doing. You know, we're doing some, you know, fundamental integration on infrastructure, bare metal and different options for the operators to get engineered systems. But building on that ecosystem is really, the move to cloud native is where Dell is trying to get in front of. And we're offering solutions and a much larger ecosystem to go after it. >> Dave V.: Great. Manish and Doug, thanks for coming on the program. It was great to have you, awesome discussion. >> Thank you for having us. >> Thanks for having us. >> All right, Dave Vellante for Dave Nicholson and Lisa Martin. We're seeing the disaggregation of the Teleco network into open ecosystems with integration from companies like Dell and others. Keep it right there for theCUBE's coverage of MWC 23. We'll be right back. (upbeat tech music)

(upbeat music) >> Welcome back to Supercloud 2, which is an open industry collaboration between technologists, consultants, analysts, and of course, practitioners, to help shape the future of cloud. And at this event, one of the key areas we're exploring is the intersection of cloud and data, and how building value on top of hyperscale clouds and across clouds is evolving, a concept we call supercloud. And we're pleased to welcome Harvir Singh, who's the chief data architect and global head of data at Western Union. Harvir, it's good to see you again. Thanks for coming on the program. >> Thanks, David, it's always a pleasure to talk to you. >> So many things stand out from when we first met, and one of the most gripping for me was when you said to me, "When data moves, money moves." And that's the world we live in today, and really have for a long time. Money has moved as bits, and when it has to move, we want it to move quickly, securely, and in a governed manner. And the pressure to do so is only growing. So tell us how that trend is evolved over the past decade in the context of your industry generally, and Western Union, specifically. Look, I always say to people that we are probably the first ones to introduce digital currency around the world because, hey, somebody around the world needs money, we move data to make that happen. That trend has actually accelerated quite a bit. If you look at the last 10 years, and you look at all these payment companies, digital companies, credit card companies that have evolved, majority of them are working on the same principle. When data moves, money moves. When data is stale, the money goes away, right? I think that trend is continuing, and it's not just the trend is in this space, it's also continuing in other spaces, specifically around, you know, acquisition of customers, communication with customers. It's all becoming digital, and it's, at the end of the day, it's all data being moved from one place or another. At the end of the day, you're not seeing the customer, but you're looking at, you know, the data that he's consuming, and you're making actionable items on it, and be able to respond to what they need. So I think 10 years, it's really, really evolved. >> Hmm, you operate, Western Union operates in more than 200 countries, and you you have what I would call a pseudo federated organization. You're trying to standardize wherever possible on the infrastructure, and you're curating the tooling and doing the heavy lifting in the data stack, which of course lessens the burden on the developers and the line of business consumers, so my question is, in operating in 200 countries, how do you deal with all the diversity of laws and regulations across those regions? I know you're heavily involved in AWS, but AWS isn't everywhere, you still have some on-prem infrastructure. Can you paint a picture of, you know, what that looks like? >> Yeah, a few years ago , we were primarily mostly on-prem, and one of the biggest pain points has been managing that infrastructure around the world in those countries. Yes, we operate in 200 countries, but we don't have infrastructure in 200 countries, but we do have agent locations in 200 countries. United Nations says we only have like 183 are countries, but there are countries which, you know, declare themselves countries, and we are there as well because somebody wants to send money there, right? Somebody has an agent location down there as well. So that infrastructure is obviously very hard to manage and maintain. We have to comply by numerous laws, you know. And the last few years, specifically with GDPR, CCPA, data localization laws in different countries, it's been a challenge, right? And one of the things that we did a few years ago, we decided that we want to be in the business of helping our customers move money faster, security, and with complete trust in us. We don't want to be able to, we don't want to be in the business of managing infrastructure. And that's one of the reasons we started to, you know, migrate and move our journey to the cloud. AWS, obviously chosen first because of its, you know, first in the game, has more locations, and more data centers around the world where we operate. But we still have, you know, existing infrastructure, which is in some countries, which is still localized because AWS hasn't reached there, or we don't have a comparable provider there. We still manage those. And we have to comply by those laws. Our data privacy and our data localization tech stack is pretty good, I would say. We manage our data very well, we manage our customer data very well, but it comes with a lot of complexity. You know, we get a lot of requests from European Union, we get a lot of requests from Asia Pacific every pretty much on a weekly basis to explain, you know, how we are taking controls and putting measures in place to make sure that the data is secured and is in the right place. So it's a complex environment. We do have exposure to other clouds as well, like Google and Azure. And as much as we would love to be completely, you know, very, very hybrid kind of an organization, it's still at a stage where we are still very heavily focused on AWS yet, but at some point, you know, we would love to see a world which is not reliant on a single provider, but it's more a little bit more democratized, you know, as and when what I want to use, I should be able to use, and pay-per-use. And the concept started like that, but it's obviously it's now, again, there are like three big players in the market, and, you know, they're doing their own thing. Would love to see them come collaborate at some point. >> Yeah, wouldn't we all. I want to double-click on the whole multi-cloud strategy, but if I understand it correctly, and in a perfect world, everything on-premises would be in the cloud is, first of all, is that a correct statement? Is that nirvana for you or not necessarily? >> I would say it is nirvana for us, but I would also put a caveat, is it's very tricky because from a regulatory perspective, we are a regulated entity in many countries. The regulators would want to see some control if something happens with a relationship with AWS in one country, or with Google in another country, and it keeps happening, right? For example, Russia was a good example where we had to switch things off. We should be able to do that. But if let's say somewhere in Asia, this country decides that they don't want to partner with AWS, and majority of our stuff is on AWS, where do I go from there? So we have to have some level of confidence in our own infrastructure, so we do maintain some to be able to fail back into and move things it needs to be. So it's a tricky question. Yes, it's nirvana state that I don't have to manage infrastructure, but I think it's far less practical than it said. We will still own something that we call it our own where we have complete control, being a financial entity. >> And so do you try to, I'm sure you do, standardize between all the different on-premise, and in this case, the AWS cloud or maybe even other clouds. How do you do that? Do you work with, you know, different vendors at the various places of the stack to try to do that? Some of the vendors, you know, like a Snowflake is only in the cloud. You know, others, you know, whether it's whatever, analytics, or storage, or database, might be hybrid. What's your strategy with regard to creating as common an experience as possible between your on-prem and your clouds? >> You asked a question which I asked when I joined as well, right? Which question, this is one of the most important questions is how soon when I fail back, if I need to fail back? And how quickly can I, because not everything that is sitting on the cloud is comparable to on-prem or is backward compatible. And the reason I say backward compatible is, you know, there are, our on-prem cloud is obviously behind. We haven't taken enough time to kind of put it to a state where, because we started to migrate and now we have access to infrastructure on the cloud, most of the new things are being built there. But for critical application, I would say we have chronology that could be used to move back if need to be. So, you know, technologies like Couchbase, technologies like PostgreSQL, technologies like Db2, et cetera. We still have and maintain a fairly large portion of it on-prem where critical applications could potentially be serviced. We'll give you one example. We use Neo4j very heavily for our AML use cases. And that's an important one because if Neo4j on the cloud goes down, and it's happened in the past, again, even with three clusters, having all three clusters going down with a DR, we still need some accessibility of that because that's one of the biggest, you know, fraud and risk application it supports. So we do still maintain some comparable technology. Snowflake is an odd one. It's obviously there is none on-prem. But then, you know, Snowflake, I also feel it's more analytical based technology, not a transactional-based technology, at least in our ecosystem. So for me to replicate that, yes, it'll probably take time, but I can live with that. But my business will not stop because our transactional applications can potentially move over if need to. >> Yeah, and of course, you know, all these big market cap companies, so the Snowflake or Databricks, which is not public yet, but they've got big aspirations. And so, you know, we've seen things like Snowflake do a deal with Dell for on-prem object store. I think they do the same thing with Pure. And so over time, you see, Mongo, you know, extending its estate. And so over time all these things are coming together. I want to step out of this conversation for a second. I just ask you, given the current macroeconomic climate, what are the priorities? You know, obviously, people are, CIOs are tapping the breaks on spending, we've reported on that, but what is it? Is it security? Is it analytics? Is it modernization of the on-prem stack, which you were saying a little bit behind. Where are the priorities today given the economic headwinds? >> So the most important priority right now is growing the business, I would say. It's a different, I know this is more, this is not a very techy or a tech answer that, you know, you would expect, but it's growing the business. We want to acquire more customers and be able to service them as best needed. So the majority of our investment is going in the space where tech can support that initiative. During our earnings call, we released the new pillars of our organization where we will focus on, you know, omnichannel digital experience, and then one experience for customer, whether it's retail, whether it's digital. We want to open up our own experience stores, et cetera. So we are investing in technology where it's going to support those pillars. But the spend is in a way that we are obviously taking away from the things that do not support those. So it's, I would say it's flat for us. We are not like in heavily investing or aggressively increasing our tech budget, but it's more like, hey, switch this off because it doesn't make us money, but now switch this on because this is going to support what we can do with money, right? So that's kind of where we are heading towards. So it's not not driven by technology, but it's driven by business and how it supports our customers and our ability to compete in the market. >> You know, I think Harvir, that's consistent with what we heard in some other work that we've done, our ETR partner who does these types of surveys. We're hearing the same thing, is that, you know, we might not be spending on modernizing our on-prem stack. Yeah, we want to get to the cloud at some point and modernize that. But if it supports revenue, you know, we'll invest in that, and get the, you know, instant ROI. I want to ask you about, you know, this concept of supercloud, this abstracted layer of value on top of hyperscale infrastructure, and maybe on-prem. But we were talking about the integration, for instance, between Snowflake and Salesforce, where you got different data sources and you were explaining that you had great interest in being able to, you know, have a kind of, I'll say seamless, sorry, I know it's an overused word, but integration between the data sources and those two different platforms. Can you explain that and why that's attractive to you? >> Yeah, I'm a big supporter of action where the data is, right? Because the minute you start to move, things are already lost in translation. The time is lost, you can't get to it fast enough. So if, for example, for us, Snowflake, Salesforce, is our actionable platform where we action, we send marketing campaigns, we send customer communication via SMS, in app, as well as via email. Now, we would like to be able to interact with our customers pretty much on a, I would say near real time, but the concept of real time doesn't work well with me because I always feel that if you're observing something, it's not real time, it's already happened. But how soon can I react? That's the question. And given that I have to move that data all the way from our, let's say, engagement platforms like Adobe, and particles of the world into Snowflake first, and then do my modeling in some way, and be able to then put it back into Salesforce, it takes time. Yes, you know, I can do it in a few hours, but that few hours makes a lot of difference. Somebody sitting on my website, you know, couldn't find something, walked away, how soon do you think he will lose interest? Three hours, four hours, he'll probably gone, he will never come back. I think if I can react to that as fast as possible without too much data movement, I think that's a lot of good benefit that this kind of integration will bring. Yes, I can potentially take data directly into Salesforce, but I then now have two copies of data, which is, again, something that I'm not a big (indistinct) of. Let's keep the source of the data simple, clean, and a single source. I think this kind of integration will help a lot if the actions can be brought very close to where the data resides. >> Thank you for that. And so, you know, it's funny, we sometimes try to define real time as before you lose the customer, so that's kind of real time. But I want to come back to this idea of governed data sharing. You mentioned some other clouds, a little bit of Azure, a little bit of Google. In a world where, let's say you go more aggressively, and we know that for instance, if you want to use Google's AI tools, you got to use BigQuery. You know, today, anyway, they're not sort of so friendly with Snowflake, maybe different for the AWS, maybe Microsoft's going to be different as well. But in an ideal world, what I'm hearing is you want to keep the data in place. You don't want to move the data. Moving data is expensive, making copies is badness. It's expensive, and it's also, you know, changes the state, right? So you got governance issues. So this idea of supercloud is that you can leave the data in place and actually have a common experience across clouds. Let's just say, let's assume for a minute Google kind of wakes up, my words, not yours, and says, "Hey, maybe, you know what, partnering with a Snowflake or a Databricks is better for our business. It's better for the customers," how would that affect your business and the value that you can bring to your customers? >> Again, I would say that would be the nirvana state that, you know, we want to get to. Because I would say not everyone's perfect. They have great engineers and great products that they're developing, but that's where they compete as well, right? I would like to use the best of breed as much as possible. And I've been a person who has done this in the past as well. I've used, you know, tools to integrate. And the reason why this integration has worked is primarily because sometimes you do pick the best thing for that job. And Google's AI products are definitely doing really well, but, you know, that accessibility, if it's a problem, then I really can't depend on them, right? I would love to move some of that down there, but they have to make it possible for us. Azure is doing really, really good at investing, so I think they're a little bit more and more closer to getting to that state, and I know seeking our attention than Google at this point of time. But I think there will be a revelation moment because more and more people that I talk to like myself, they're also talking about the same thing. I'd like to be able to use Google's AdSense, I would like to be able to use Google's advertising platform, but you know what? I already have all this data, why do I need to move it? Can't they just go and access it? That question will keep haunting them (indistinct). >> You know, I think, obviously, Microsoft has always known, you know, understood ecosystems. I mean, AWS is nailing it, when you go to re:Invent, it's all about the ecosystem. And they think they realized they can make a lot more money, you know, together, than trying to have, and Google's got to figure that out. I think Google thinks, "All right, hey, we got to have the best tech." And that tech, they do have the great tech, and that's our competitive advantage. They got to wake up to the ecosystem and what's happening in the field and the go-to-market. I want to ask you about how you see data and cloud evolving in the future. You mentioned that things that are driving revenue are the priorities, and maybe you're already doing this today, but my question is, do you see a day when companies like yours are increasingly offering data and software services? You've been around for a long time as a company, you've got, you know, first party data, you've got proprietary knowledge, and maybe tooling that you've developed, and you're becoming more, you're already a technology company. Do you see someday pointing that at customers, or again, maybe you're doing it already, or is that not practical in your view? >> So data monetization has always been on the charts. The reason why it hasn't seen the light is regulatory pressure at this point of time. We are partnering up with certain agencies, again, you know, some pilots are happening to see the value of that and be able to offer that. But I think, you know, eventually, we'll get to a state where our, because we are trying to build accessible financial services, we will be in a state that we will be offering those to partners, which could then extended to their customers as well. So we are definitely exploring that. We are definitely exploring how to enrich our data with other data, and be able to complete a super set of data that can be used. Because frankly speaking, the data that we have is very interesting. We have trends of people migrating, we have trends of people migrating within the US, right? So if a new, let's say there's a new, like, I'll give you an example. Let's say New York City, I can tell you, at any given point of time, with my data, what is, you know, a dominant population in that area from migrant perspective. And if I see a change in that data, I can tell you where that is moving towards. I think it's going to be very interesting. We're a little bit, obviously, sometimes, you know, you're scared of sharing too much detail because there's too much data. So, but at the end of the day, I think at some point, we'll get to a state where we are confident that the data can be used for good. One simple example is, you know, pharmacies. They would love to get, you know, we've been talking to CVS and we are talking to Walgreens, and trying to figure out, if they would get access to this kind of data demographic information, what could they do be better? Because, you know, from a gene pool perspective, there are diseases and stuff that are very prevalent in one community versus the other. We could probably equip them with this information to be able to better, you know, let's say, staff their pharmacies or keep better inventory of products that could be used for the population in that area. Similarly, the likes of Walmarts and Krogers, they would like to have more, let's say, ethnic products in their aisles, right? How do you enable that? That data is primarily, I think we are the biggest source of that data. So we do take pride in it, but you know, with caution, we are obviously exploring that as well. >> My last question for you, Harvir, is I'm going to ask you to do a thought exercise. So in that vein, that whole monetization piece, imagine that now, Harvir, you are running a P&L that is going to monetize that data. And my question to you is a there's a business vector and a technology vector. So from a business standpoint, the more distribution channels you have, the better. So running on AWS cloud, partnering with Microsoft, partnering with Google, going to market with them, going to give you more revenue. Okay, so there's a motivation for multi-cloud or supercloud. That's indisputable. But from a technical standpoint, is there an advantage to running on multiple clouds or is that a disadvantage for you? >> It's, I would say it's a disadvantage because if my data is distributed, I have to combine it at some place. So the very first step that we had taken was obviously we brought in Snowflake. The reason, we wanted our analytical data and we want our historical data in the same place. So we are already there and ready to share. And we are actually participating in the data share, but in a private setting at the moment. So we are technically enabled to share, unless there is a significant, I would say, upside to moving that data to another cloud. I don't see any reason because I can enable anyone to come and get it from Snowflake. It's already enabled for us. >> Yeah, or if somehow, magically, several years down the road, some standard developed so you don't have to move the data. Maybe there's a new, Mogli is talking about a new data architecture, and, you know, that's probably years away, but, Harvir, you're an awesome guest. I love having you on, and really appreciate you participating in the program. >> I appreciate it. Thank you, and good luck (indistinct) >> Ah, thank you very much. This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more great coverage from Supercloud 2. (uplifting music)

>>Hi everyone. Welcome to our event, pure Storage, the Path to Sustainable It. I'm your host, Lisa Martin. Very pleased to welcome back one of our cube alumni. AJ Singh joins me, the Chief Product Officer at Peer Storage. Aj, it's great to have you back on the program. >>Great to be back on, Lisa. Good morning. >>Good morning. And sustainability is such an important topic to talk about. So we're gonna really unpack what PI's doing. We're gonna get your viewpoints on what you're saying, and you're gonna leave the audience with some recommendations on how they can get started on our ESG journey. First question, we've been hearing a lot from pure RJ about the role that technology plays in organizations achieving sustainability goals. What's been the biggest environmental impact associated with, with customers achieving that given the massive volumes of data that keep being generated? >>Absolutely. Lisa, you can imagine that the data is only growing and exploding and, and, and, and there's a good reason for it. You know, data is the new currency. Some people call it the new oil. And the opportunity to go process this data gain insights is really helping customers drive an edge in the digital transformation. It's gonna make a difference between them being on the leaderboard a decade from now, when the digital transformation kind of pans out versus, you know, being kind of somebody that, you know, quite missed the boat. So data is super critical and, and obviously as part of that, we see all these big benefits, but it has to be stored. And, and, and that means it's gonna consume a lot of resources and, and the, and therefore data center usage has only accelerated, right? You can imagine the amount of data being generated, you know, a recent study pointed to roughly by twenty twenty five, a hundred and seventy five zetabytes, which where each zettabyte is a billion terabytes. So just think of that size and scale data. That's huge. And, and they also say that, you know, pretty soon, today, in fact, in the developed world, every person is having an interaction with the data center literally every 18 seconds. So whether it's on Facebook or Twitter or you know, your email, people are constantly interacting with data. So you can imagine this data is only exploding. It has to be stored and it consumes a lot of energy. In fact, >>It out, oh, go ahead. Sorry. >>No, I was saying in fact, you know, there was some studies have shown that data center usage literally consumes one to 2% of global energy consumption. So if there's one place we could really help climate change and, and all those aspects, if you can kind of really, you know, tamp down the data center, energy consumption, sorry, you were saying, >>I was just gonna say, it's, it's an incredibly important topic and the, the, the stats on data that you provided. And also I, I like how you talked about, you know, every 18 seconds we're interacting with a data center, whether we know it or not, we think about the long term implications, the fact that data is growing massively. As you shared with the stats that you mentioned, if we think about though the responsibility that companies have, every company in today's world needs to be a data company, right? And we consumers expect it. We expect that you are gonna deliver these relevant, personalized experiences, whether we're doing a transaction in our personal lives or in business. But what is the, what requirements do technology companies have to really start billing down their carbon footprints? >>No, absolutely. If you gonna think about it, just to kind of finish up the data story a little bit, the explosion is to the point where, in fact, if you just recently was in the news that Ireland went up and said, sorry, we can't have any more data centers here. We just don't have the power to supply them. That was big in the news. And you know, all the hyperscale that's crashing the head, I know they've come around that and figured out a way around it, but it's getting there. Some, some organizations and areas jurisdictions are saying pretty much no data center the law, you know, we're, we just can't do it. And so, as you said, so companies like Pure, I mean, our view is that it has an opportunity here to really do our bit for climate change and be able to, you know, drive a sustainable environment. >>And, and at Pure we believe that, you know, today's data success really ultimately hinges on energy efficiency, you know, so to to really be energy efficient means you are gonna be successful long term with data. Because if you think of classic data infrastructures, the legacy infrastructures, you know, we've got disc infrastructures, hybrid infrastructures, flash infrastructures, low end systems, medium end systems, high end systems. So a lot of silos, you know, a lot of inefficiency across the silos. Cause the data doesn't get used across that. In fact, you know, today a lot of data centers are not really built with kind of the efficiency and environmental mindsets. So they're the big opportunity there. >>So aj, talk to me about some of the steps that Pure is implementing as its chief product officer. Would love to get your your thoughts, what steps is it implementing to help Pures customers become more sustainable? >>No, absolutely. So essentially we're all inherently motivated, like pure and, and, and, and everybody else to solve problems for customers and really forward the status quo, right? You know, innovation, you know, that's what we were all about. And while we are doing that, the challenge is to how do you make technology and the data we feed into it faster, smarter, scalable obviously, but more importantly sustainable. But you can do all of that. But if you miss the sustainability bit, you're kind of missing the boat. And I also feel from an ethical perspective, that's really important for us, not only to do all the other things, but also kind of make it sustainable. In fact, today 80% of the companies, the companies are realizing this, 80% today are in fact report out on sustainability, which is, is great. And in fact, 80% of leadership at companies, you know, CEOs and senior executives say they've been impacted by some climate change event. >>You know, whether it's a fire in the place they had to evacuate or floods or storms or hurricanes, you, you name it, right? So mitigating the carbon impact can in fact today be a competitive advantage for companies because that's where the puck is going and everybody's, you know, is skating, wanting to skate towards the buck. And it's good, it's good business too, to be sustainable and, and, and meet these, you know, customer requirements. In fact, the the recent survey that we released today is saying that more and more organizations are kickstarting, their sustainability initiatives and many take are aiming to make a significant progress against that over the next decade. So that's, that's really, you know, part of the big, the relief. So our view is that that IT infrastructure, you know, can really make a big push towards greener it and not just gonna greenwash it, but actually, you know, you know, make things more greener and, and, and really take the, the lead in, in esg. And so it's important that organizations can reach alignment with their IT teams and challenge their IT teams to continue to lead, you know, for the organization, the sustainability aspects. >>I'm curious, aj, when you're in customer conversations, are you seeing that it's really the C-suite plus it coming together and, and how does peer help facilitate that? To your point, it needs to be able to deliver this, but it's, it's a board level objective these days. >>Absolutely. We're seeing increasingly, especially in Europe with the, you know, the war in Ukraine and the energy crisis that, you know, that's, that's, you know, unleashed we definitely see is becoming a bigger and bigger board level objective for, for a lot of companies. And we definitely see customers in starting to do that. So, so in particular, I do want to touch briefly on what steps we are taking as a company, you know, to to to make it sustainable. And obviously customers are doing all the things we talked about and, and, and we're also helping them become smarter with data. But the key difference is, you know, we have a big focus on efficiency, which is really optimizing performance for what with unmatched storage entities. So you can reduce the footprint and dramatically lower the power required. And and how efficient is that? You know, compared to other old flash systems, we tend to be one fifth, we tend to take one fifth the power compared to other flash systems and substantially lower compared to spinning dis. >>So you can imagine, you know, cutting your, if data center consumption is say 2% of global consumption, roughly 40% of that tends to be storage cause of all the spinning disc. So you at about, you know, 0.8% of global consumption and if you can cut that by four fifths, you know, you can already start to make an impact. So, so we feel we can do that. And also we're quite a bit more denser, 10 times more denser. So imagine one fifth the power, one 10th the density, but then we take it a step further because okay, you've got the storage system in the data center, but what about the end of life aspect? What about the waste and reclamation? So we also have something called non-disruptive upgrades where using our AI technology in pure one, we can start to sense when a particular part is going to fail and just before it goes through failure, we actually replace it in a non-disruptive fashion. So customers data is not impacted and then we recycle that so you get a full end to end life cycle, you know, from all the way from the time you deploy much lower power, much lower density, but then also at the back end in a reduction in e-waste and those kind of things. >>That's a great point you that you bring up in terms of the reclamation process. It sounds like Pure does that on its own. The customer doesn't have to be involved in that. >>That's right. And we do that, it's a part of our evergreen, you know, service that we offer. A lot of customers sign up for the service and in fact they don't even, we tell them, Hey, you know, that part's about to go, we're gonna come in, we're gonna swap it out and, and then we actually recycle that part. >>The power of ai. I love that. What are some of the, the things that companies can do if they're, if they're early in this journey on sustainability, what are some of the specific steps companies can take to get started and maybe accelerate that journey as it's becoming climate change and things are becoming just more and more of a, of a daily topic on the news? >>No, absolutely. There's a lot of things companies can do. In fact, the four four item that we're gonna highlight, the first one is, you know, they can just start by doing a materiality assessment and a materiality assessment essentially engages all the stakeholders to find out which specific issues are important for the business, right? So you identify your key priorities that intersect with what the stakeholders want, you know, your different groups from sales, customers, partners, you know, different departments in the organization. And for example, for us, when we conducted our materiality assessment, for us, our product we felt was the biggest area of focus that could contribute a lot towards, you know, making an impact in, in, in, from a sustainability standpoint. That's number one. I think number two companies will also think about taking an Azure service approach. The beauty of the Azure service approach is that you are buying a cardio customer, they're buying outcomes with SLAs and, and when you are starting to buy outcomes with SLAs, you can start small and then grow as you consume more. >>So that way you don't have systems sitting idle waiting for you to consume more, right? And that's the beauty of the Azure service approach. And so for example, for us, you know, we have something called Evergreen one, which is our as a service offer, where essentially customers are able to only use and have systems thrown onto as much as they're consuming. So, so that reduces the waste associated with underutilized systems, right? That's number two. Number three is also you can optimize your supply chains end to end, right? Basically by making sure you're moving, recycling, packaging and eliminating waste in that thing so you can recycle it back to your suppliers. And you can also choose a sustainable supplier network that's following sort of good practices, you know, you know, across the globe and such. Supply chains that are responsive and diverse can really help you also the business benefit that you can also handle surge in demand, for example, for us during the pandemic with these global supply chain shortages, you know, whereas most of our competitors, you know, lead time went to 40, 50 weeks, our lead times went from three to six weeks cuz you know, we had this sustainable, you know, supply chain. >>And so all of these things, you know, the three things are important, but the four thing I say is more cultural and, and the cultural thing is how do you actually begin to have sustainability become a core part of your ethos as a company, you know, across all the departments, you know, and we've at Pure, definitely it's big for us, you know, you know, around sustainability starting with a product design, but all other the areas as well. So if you follow those four items, they, they're the great place to start. >>That's great advice, great recommendations. You talk about the, the, the supply chain, sustainable supply chain optimization. We've been having a lot of conversations with businesses and vendors alike about that and how important it is. You bring up a great point too on supplier diversity. We could have a whole conversation on that. Yes. But I'm also glad Oji, that you brought up culture that's huge to, for organizations to adopt an ESG strategy and really drive sustainability in their business and has to become, to your point, part of their ethos. It's challenging. Cultural change management is challenging. Although I think with climate change and the things that are so public, it's, it's more on, on the top mindset folks. But it's a great point that the organization really as a whole needs to embrace the sustainability mindset so that it as a, as an organization lives and breathes that. Yes. My last question for you is advice. So you, you outlined the four Steps organizations can take. I look how you made that quite simple. What advice would you give organizations who are on that journey to adopting those, those actions, as you said, as they look to really build and deploy and execute an ESG strategy? >>No, absolutely. And so obviously, you know, the advice is gonna come from, you know, a company like Pure, you know, our background kind of, of being a supplier of products. And so, you know, our advice is for companies that have products, usually they tend to be the biggest generator, the products that you sell to your customers, especially if they've got hardware components in it. But, you know, the biggest generator of e-waste and, and and, and, and, and kind of from a sustainability standpoint. So it's really important to have an intentional design approach towards your products with sustainability in mind. So it's not something that's, that you kinda handle at the very back end. You design it upfront in the product and so that sustainable design becomes very intentional. So for us, for example, doing these non-disruptive upgrades had to be designed upfront so that, you know, a, you know, one of our repair person could go into a customer shop and be able to pull out a card and put in a new card without any change in the customer system. >>That non-disruptive approach, it has to be designed into the hardware software systems to be able to pull that on. And that intentional design enabled you to recover pieces just when they're about to fail and then putting them through a recovery, you know, waste recovery process. So that, that's kind of the one thing I would say that philosophy, again, it comes down to if that is, you know, seeping into the culture, into your core ethos, you will start to do, you know, the, you know, that type of work. So, so I mean it's an important thing, you know, look, this year, you know, with the spike in energy prices, you know, you know, gas prices going up, it's super important that all of us, you know, do our bit in there and start to drive products that are fundamentally sustainable, not just at the initial, you know, install point, but from an end to end full life cycle standpoint. >>Absolutely. And I love that you brought up intention that is everything that PI's doing is with, with such thought and intention and really for organizations and any industry to become more sustainable, to develop an ESG strategy. To your point, it all needs to start with intention. And of course that that cultural adoption, aj, it's been so great to have you on the program talking about what PEER is doing to help organizations really navigate that path to sustainable it. We appreciate your insights on your time. >>Thank you, Lisa. Pleasure being on board. >>Great to have you. For AJ saying, I'm Lisa Martin, you're watching this special event, peer Storage, the Path to Sustainable It.

(upbeat music) >> Welcome back to theCUBE's live coverage of AWS re:Invent. Friends, it's good to see you. Lisa Martin here with Dave Vellante. This is our fourth day of CUBE wall-to-wall coverage, Dave. I can't believe it. And the expo hall is still going incredibly strong. >> Yeah, it is. It feels like the biggest re:Invent ever. I'm told it's almost as big as 2019. I don't know, maybe I was half asleep at 2019. That's very possible. But I'm excited because in 2017 Andy Jassy came on theCUBE and he said if Amazon had to do it all over again, if it knew then what it had now, we would've done the whole thing in containers or using Lambda, using serverless and using containers. Didn't have that opportunity back then. And I'm excited 'cause Rafay Systems is someone we've worked with a lot as an innovator in this space. >> Yep, and we're going to be talking with Rafay again. I think it's your 10th time Haseeb on the show >> Like once or twice. >> And a great customer who's going to talk about their serverless journey. Haseeb Budhani joins us once again, the CEO of Rafay. Great to see you. Rakesh Singh is here as well, the Head of Cloud and DevOps at Regeneron. Guys, it's great to have you on the program. How you feeling on day four of re:Invent? >> Excitement is as high as ever basically. >> Isn't it amazing? >> Rakesh: That's true. >> Haseeb: I just need some sleep. >> I'm with you on that. Caffeine and sleep. >> So many parties. So many meetings, oh my God. >> But the great thing is, Haseeb, that people want to engage with you. They're loving what Rafay is doing. You guys are a great testament to that, which we're going to uncover on the show. What are some of the things that you're hearing in the booth from customers? What's been some of the feedback? >> So firstly, as I said, it feels like the biggest one ever. I've been coming to re:Invent a long time and I mean, I know the numbers say it's not, but oh my God, this is a lot of people. Every time we've spoken over the last year and the point I always make to you, and we've spoken enough time about this is that enterprises are truly adopting this idea of Kubernetes containers, serverless, et cetera. And they're all trying to figure out what is the enterprise strategy for these things? They're thinking beyond technology and thinking operationalization of these technologies. And that's not the same thing. There's a toy and then there's the real thing. And that's not the same thing. And that's the gap that every enterprise customer I talked to and the booth traffic has been just amazing. I mean, but coming here I was thinking, my God, this is really expensive. And I'm thinking, wow, this is a great investment. Because we met such amazing companies who all essentially are saying exactly the same thing, which is as we go and productize and bring our high value applications to the modern infrastructure space, like Kubernetes, Lambda, et cetera, solving for the automation governance is really, really hard because, well, at one point, I guess when the economy was doing crazy well, I could keep hiring people, but I can't do that anymore either. So they're out looking for automation strategies that allow them to do more with the teams they have. And that's exactly what Rafay is here for. >> Yeah. Lisa, Adam Selipsky in his keynote, I love the, he said, "If you want to save money, the cloud is the place to do it." >> Exactly. Yep. Let's talk about Regeneron. Everyone knows it's a household word especially over the last couple of years, but talk about, Rakesh, Regeneron as a technology company that delivers life-saving pharmaceuticals. And where does cloud and Rafay fit into your strategy? >> So cloud has been a backbone of our compute strategy within Regeneron for a very long time now. The evolution from a traditional compute structure to more serverless compute has been growing at a rapid pace. And I would say like we are seeing exponential growth within the adaption of the compute within containers and Kubernetes world. So we've been on this journey for a long time and I think it's not stopping anytime soon. So we have more and more workload, which is running on Kubernetes containers and we are looking forward to our partnership with Rafay to further enhance it, as Haseeb mentioned, the efficiency is the key. We need to do more with less. Resourcing is critical and cloud is evolved from that journey that do more things in a more efficient manner. >> That was the original catalyst as we got to help our development team, be more productive. >> That's correct. >> Eliminate the heavy lifting. And then you started presumably doing some of the less heavy, but still heavy lifting and we talked off camera and then you're increasingly moving toward serverless. >> Rakesh: That's correct. >> Can you describe that journey? What that's like? >> So I think like with the whole adoption that things are taking a much faster pace. Basically we are putting more compute onto containers and the DevOps journey is increasingly getting more, more faster. >> Go ahead. 'Cause I want to understand where Rafay sits in this whole equation. I was talking about, I'm not a developer, but I was talking to developer yesterday trying to really understand the benefits of containers and serverless and I said, take me through what you have to do when you're using containers. He said, I got to build the container image then I got to deploy an EC2 instance where I got to choose and I got to allocate memory of the fence the app in a VM then I got to run the computing instance against the app. And then, oh by the way, I got to pay 'cause all that EC2 that whole time. Depending on how you approach serverless you're going to eliminate a lot of those steps. >> That is correct. So what we do is basically like in a traditional sense, the computer is sitting idle at quite a lot basically. >> But you're paying. >> And you're still paying for that. Serverless technologies allows us to use the compute as needed basis. So whenever you need it, it is available. You run your workload on that and after that it shuts down or goes to minimal state and you don't need to pay as much as your paying. >> And then where do you guys fit in that whole equation? >> Look, serverless has a paradigm. If you step back from the idea of containers versus Lambda or whatever functions. The idea should be that the list you just read out of what developers have to do. Here's what they really should do. They should write their code, they should check it in, and they never have to think about it again. That should be the case. If they want to debug their application, there should be a nice front end where they go and they interact with their application and that's it. What is Kubernetes? I don't care. That's the right answer. And we did not start this journey as an industry there because usually the initial adopters are developers who do the heavy lifting. Developers want to learn, they want to solve these problems. But then eventually the expectation is that the platform organization and an enterprise is going to own this platform for me so I can go back to doing my job, which is writing code. And that's where Rakesh's team comes in. So Rakesh team is building the standard at Regeneron. Whether you're writing a long-lasting app, which is going to run in a container or you're going to write an event-driven application, which is going to be a function, whatever. You write your app, we will give you the necessary tooling and plumbing to take care of all these things. And this is my problem. My being Rakesh. Rakesh is my customer. He has his customers. We as Rafay, A, we have to make Rakesh's system successful because we have to give them right automation to do all these things so that he can service hundred, or in his case, thousands and thousands of different individuals. But then collectively, we have to make sure that the developer experience is optimal so that truly they just write their code and EC2, they don't want to deal with this. In fact, on Monday evening, in the Kubernetes keynote by Barry Cooks, one of the things he said was that in a CIO sort of survey they did, CIO said, 80% of the time of developers is wasted on infrastructure stuff and not on innovation. We need to bring that 80% back so that a hundred percent of the work is on innovation and today it's not. >> And that's what you do. >> That's what we do. >> In your world as a developer, I only have to worry about my writing my code and what functions I'm going to call. >> That is correct. And it is important because the efficiencies of a developer need to be focused on doing the things which business is asking for. The 80% of the work like to make sure the things are secure, they're done the right way, the standards are followed, scanning part of it, that work if we can offload to a platform, for example, Rafay, saves a lot of works, a lot of work cycles from the developers perspective. >> Thank you for that. It was nice little tutorial on the benefits. >> Absolutely. So you transform the developer experience. >> That's correct. >> How does that impact Regeneron overall business? We uplevel that. Give me that view. >> So with that, like what happens, the key thing is the developers productivity increases. We are able to do more with less. And that is the key thing to our strategy that like with the increase in business demand, with the increase in lot of compute things, which we are doing, we need to do and hiring resources is getting more difficult than ever. And we need to make sure that we are leveraging platforms and tools basically to do, enable our developers to focus on key business activity rather than doing redundant things and things which we can leverage some other tooling and platform for that business. >> Is this something in terms of improving the developer experience and their productivity faster time to market? Is this accelerating? >> That's correct. >> Is this even like accelerating drug discovery in some cases? >> So COVID is like a great example for that. Like we were able to fast track our drug discovery and like we were able to turn it into an experience where we were able to discover new drugs and get it to the market in a much faster pace. That whole process was expedited using these tools and processes basically. So we are very proud of that. >> So my understanding is you're running Rafay with EKS. A lot of choices out there. Why? Why did you choose to go in that direction? >> So Regeneron has heavily invested in cloud recently, over the years basically. And then we are focusing on hybrid cloud now that we we are like, again, these multiple cloud providers of platforms which are coming in are strategies to focus on hybrid cloud and Rafay is big leader in that particular space where we felt that we need to engage or partner with Rafay to enable those capabilities, not just on AWS, but across the board. One single tool, one single process, one single knowledge base helps us achieve more efficiencies. >> Less chaos, less complexity. >> That's correct. Let's say when you're in customer conversations, which I know you've had many this week, but you probably do that all the time. Regeneron is a great use case for Rafay. It's so tangible, life sciences. We all get that, especially coming out of the pandemic. What do you say to customers are the top three differentiators of Rafay and why they should go Rafay on top of EKS? >> What's really interesting about these conversations is that, look, we have some pretty cool features in our product. Obviously we must have something interesting otherwise nobody would buy our product. And we have access management and zero trust models and cluster provisioning, all these very nice things. But it always comes down to exactly the same thing, which is every large enterprise that started a journey, independent or Rafay because they didn't know who we were, it's fine. Last year we were a young company, now we are a larger company and they all are basically building towards a roadmap which Rafay truly understands. And in my opinion, and I'm confident when I say this, we understand their life, their journey better than any other company in the market. The reason why we have the flurry of customers we have, the reason why the product has the capacity that it does is because for whatever reason, look, it's scale lock. That's for the history books. But we have complete clarity on what a pharmaceutical company or financial customers company or a high tech company the journey they will take to the cloud and automation for modern infrastructure, we get it. And what I'm selling them is the is the why, not the what. There's a lot of great answers for the what? What do we do? Rakesh doesn't care. I mean, he's trying to solve a bigger problem. He's trying to get his researchers to go faster. So then when they want to run a model, they should be able to do it right now. That's what he cares about. Then he looks for a tool to solve the business problem. And we figured out how to have that conversation and explain why Rafay helps him, essentially multiply the bandwidth that he has in his organization. And of course to that end we have some great technology/ But that's a secondary issue, the first, to me the why is more important than the what. And then we talk about how, which he has to pay us money. That's the how. But yeah, we get there too. But look, this is the important thing. Every enterprise is on exactly the same journey, Lisa. And that if you think about it from just purely economic efficiencies perspective that is not a good investment for our industry. If everybody's solving the same problem that's a waste of resources. Let's find a way to do, what is the point of the cloud? We used to all build data centers. That was not efficient. We all went to the cloud because it's more efficient to have somebody else, AWS, solve this problem for us so we can now focus on the next level problem. And then Rafay solving that problem so that he can focus on his drug discovery, not on Kubernetes. >> That's correct. It's all about efficiencies. Like doing things, learn from each other's experience and build upon it. So the things have been solved. One way you need to leverage that, reuse it. So the principles are the same. >> So then what's next? You had done an amazing job transforming the company. You're facilitating drug discovery faster than ever before. From an infrastructure perspective, what's next on your journey? >> So right now the roadmap what we have is basically talking about making sure that the workload are running more efficient, they're more secure. As we go into these expandable serverless technology, there are more challenging opportunities for us to solve. Those challenges are coming up. We need to make sure that with the new, the world we are living in, we are more securely doing stuff what we were doing previously. More efficiencies is also the key and more distributed. Like if we can leverage the power of cloud in doing more things on demand is on our roadmap. And I think that is where we are all driving. >> And when you said hybrid, you're talking about connecting to your on-prem tools and data? How about cross cloud? >> We are invested in multiple cloud platform itself and we are looking forward to leveraging a technology, which is truly cloud native and we can leverage things together on that. >> And I presume you're helping with that, obviously. >> Last question for both of you. We're making an Instagram reel. Think of this as a sizzle reel, like a 32nd elevator pitch. Question, first one goes to you, Rakesh. If you had a bumper sticker, you put it on, I don't know, say a DeLorean, I hear those are coming back. What would it say about Regeneron as a technology company that's delivering therapeutics? >> It's a tough question, but I would try my best. The bumper sticker would say, discover drug more faster, more efficient. >> Perfect. Haseeb, question about Rafay. What's the bumper sticker? If you had a billboard in on Highway 101 in Redwood City about Rafay and what it's enabling organizations enterprises across the globe to achieve, what would it say? >> I'll tell you what our customers say. So our customers call us the vCenter for Kubernetes and we all know what a vCenter is. We all know why vCenter's so amazingly successful because it takes IT engineers and gives them superpowers. You can run a data center. What is the vCenter for this new world? It us. So vCenter is obviously a trademark with our friends at VMware, so that's why I'm, but our customers truly call us the vCenter for Kubernetes. And I think that's an incredible moniker because that truly codifies our roadmap. It codifies what we are selling today. >> There's nothing more powerful and potent in the voice of the customer. Thank you both for coming on. Thank you for sharing the Regeneron story. Great to have you back on, Haseeb. You need a pin for the number of times you've been on theCUBE. >> At least a gold star. >> We'll work on that. Guys, thank you. We appreciate your time. >> Haseeb: Thank you very much. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Good afternoon, fellow cloud nerds, and welcome back to theCUBE's live coverage of AWS re:Invent, here in a fabulous Sin City, Las Vegas, Nevada. My name is Savannah Peterson, joined by my fabulous co-host, John Furrier. John, how you feeling? >> Great, feeling good Just getting going. Day one of four more, three more days after today. >> Woo! Yeah. >> So much conversation. Talking about business transformation as cloud goes next level- >> Hot topic here for sure. >> Next generation. Data's classic is still around, but the next gen cloud's here, it's changing the game. Lot more AI, machine learning, a lot more business value. I think it's going to be exciting. Next segment's going to be awesome. >> It feels like one of those years where there's just a ton of momentum. I don't think it's just because we're back in person at scale, you can see the literally thousands of people behind us while we're here on set conducting these interviews. Our bold and brave guests, just like the two we have here, combating the noise, the libations, and everything else going on on the show floor. Please help me welcome Mike from Science Logic and Ajay from Zebrium. Gentlemen, welcome to the show floor. >> Thank you. >> Thank you Savannah. It's great to be here. >> How you feeling? Are you feeling the buzz, Mike? Feeling the energy? >> It's tough to not feel and hear the buzz, Savannah >> Savannah: Yeah. (all laughing) >> John: Can you hear me? >> Savannah: Yeah, yeah, yeah. Can you hear me now? What about you, Ajay? How's it feel to be here? >> Yeah, this is high energy. I'm really happy it's bounced back from COVID. I was a little concerned about attendance. This is hopping. >> Yeah, I feel it. It just, you can definitely feel the energy, the sense of community. We're all here for the right reasons. So I know that, I want to set the stage for everyone watching, Zebrium was recently acquired by Science Logic. Mike, can you tell us a little bit about that and what it means for the company? >> Mike: Sure, sure. Well, first of all, science logic, as you may know, has been in the monitoring space for a long time now, and what- >> Savannah: 20 years I believe. >> Yeah. >> Savannah: Just about. >> And what we've seen is a shift from kind of monitoring infrastructure, to monitoring these increasingly complex modern cloud native applications, right? And so this is part of a journey that we've been on at Science Logic to really modernize how enterprises of all sizes manage their IT estate. Okay? So, managing, now workloads that are increasingly in the public cloud, outside the four walls of the enterprise, workloads that are increasingly complex. They're microservices based, they're container based. >> Mhmm. >> Mike: And the rate of change, just because of things like CICD, and agile development has also increased the complexity in the typical IT environment. So all these things have conspired to make the traditional tools and processes of managing IT and IT applications much more difficult. They just don't scale. One of the things that we've seen recently, Savannah is this shift in sort of moving to cloud native applications, right? >> Huge shift. >> Mike: Today it only incorporates about roughly 25% of the typical IT portfolio, but most of the projections we've seen indicate that that's going to invert in about three years. 75% of applications will be what I call cloud native. And so this really requires different technologies to understand what's going on with those applications. And so Zebrium interested us when we were looking at partners at the beginning of this year as they have a super innovative approach to understanding really what's going on with any cloud native application. And they really distill, they separate the complexity out of the equation and they used machine learning to tremendous effect to rapidly understand the root cause of an application failure. And so I was introduced to Ajay, beginning of this year, actually. It feels like it's been a long time now. But we've been on this journey together throughout 2022, and we're thrilled to have Zebrium now, part of the Science Logic family. >> Ajay, Zebrium saves people a lot of time. Obviously, I've worked with developers and seen that struggle when things break, shortening that time to recovery and understanding is so critical. Can you tell us a little bit about what's under the hood and how the ML works to make that happen? >> Ajay: Yeah. So the goal is to figure out not just that something went wrong, but what went wrong. >> Savannah: Right. >> And we took, you know, based on a couple of decades of experience from my co-founders- >> Savannah: Casual couple of decades, came into went into this product just to call that out. Yeah, great. >> Exactly. It took some general learnings about the nature of software and when software breaks, what tends to happen, you tend to see unusual things happen, and they lead to bad things happening. It's very simple. >> Yes. >> It turns out- >> Savannah: Mutations lead to bad things happening, generally speaking. >> So what Zebrium's really good at is identifying those rare things accurately and then figuring out how they connect, or correlate to the bad things, the errors, the warnings, the alerts. So the machine learning has many stages to it, but at its heart it's classifying the event, catalog of any application stack, figuring out what's rare, and when things start to break it's telling you this cluster of events is both unusual, and unlikely to be random, and it's very likely the root cause report for the problem you're trying to solve. We then added some nice enhancements, such as correlation with knowledge spaces in, on the public internet. If someone's ever solved that problem before, we're able to find a match, and pull that back into our platform. But the at the heart, it was a technology that can find rare events and find the connections with other events. >> John: Yeah, and this is the theme of re:Invent this year, data, the role of data, solving end-to-end complexities. One, you mentioned that. Two, I think the Mike, your point about developers and the CICD pipeline is where DevOps is. That is what IT now is. So, if you take digital transformation to its conclusion, or its path and continue it, IT is DevOps. So the developers are actually doing the IT in their coding, hence the shift to autonomous IT. >> Mike: Right, right. Now, those other functions at IT used to be a department, not anymore, or they still are, so, but they'll go away, is security and data teams. You're starting to see the formation of- >> Mike: Yep. >> New replacements to IT as a function to support the developers who are building the applications that will be the company. >> That's right. Yeah. >> John: I mean that's, and do you agree with that statement? >> Yeah, I really do. And you know, collectively independent of whether it's like traditional IT, or it's DevOps, or whatever it is, the enterprise as a whole needs to understand how the infrastructure is deployed, the health of that infrastructure, and more importantly the applications that are hosted in the infrastructure. How are they doing? What's the health? And what we are seeing, and what we're trying to facilitate at Science Logic is really changed the lens of IT, from being low level compute, storage, and networking, to looking at everything through a services lens, looking at the services being delivered by IT, back to the business, and understanding things through a services lens. And Zebrium really compliments that mission that we've been on, by providing, cause a lot of cases, service equal equal application, and they can provide that kind of very real time view of service health in, you know, kind of the IT- >> And automation is beautiful there too, because, as you get into some of the scale- >> Yeah >> Ajay's. understanding how to do this fast is a key component. >> Yeah. So scale, you, you've pinpointed one of the dimensions that makes AI really important when it comes to troubleshooting. The humans just can't scale as fast as data, nor can they keep up with complexity of modern applications. And the third element that we feel is really important is the velocity with which people are now rolling out changes. People develop new features within hours, push them out to production. And in a world like that, the human has just no ability or time to understand what's normal, what's bad, to update their alert rules. And you need a machine, or an AI technology, to go help you with that. And that's basically what we're about. >> So this is where AI Ops comes in, right? Perfectly. Yeah. >> Yeah. You know, and John started to allude to it earlier, but having the insight on what's going on, we believe is only half of the equation, right? Once you understand what's going on, you naturally want to take action to remediate it or optimize it. And we believe automation should not be an exercise that's left to the reader. >> Yeah. >> As a lot of traditional platforms have done. Instead, we have a very robust, no-code, low-code automation built into our platform that allows you to take action in context with what you're seeing right then and there with the service. >> John: Yeah. Essentially monitoring, a term you use observability, some used as a fancy word today, is critical in all operating environments. So if we, if we kind of holistically, hey we're a distributed computing system, aka cloud, you got to track stuff at scale and you got to understand what it, what the impact is from a systems perspective. There's consequences to understanding what goes wrong. So as you look at that, what's the challenge for customers to do that? Because that seems to be the hard part as they lift and shift to the cloud, run their apps on the cloud, now they got to go take it to the next level, which is more developer velocity, faster productivity, and secure. >> Yeah. >> I mean, that seems to be the table stakes now. >> Yeah. >> How are companies forming around that? Are they there yet? Are they halfway there? Are they, where are they in the progression of, one, are they changing? And if so- >> Yeah that's a great question. I mean, I think whether it's an IT use case or a security use case, you can't manage what you don't know about. So visibility, discoverability, understanding what's going on, in a lot of ways that's the really hard problem to solve. And traditionally, we've approached that by like, harvesting data off of all these machines and devices in the infrastructure. But as we've seen with Zebrium and with related machine learning technologies, there's multiple ways of gaining insight as to what's going on. Once you have the insight be it an IT issue, like a service outage, or a security vulnerability, then you can take action. And the idea is you want to make that action as seamless as possible. But I think to answer your question, John, enterprises are still kind of getting their heads around how can we break down all the silos that have built up over the last decade or two, internally, and get visibility across the estate that really matters. And I think that's the real challenge. >> And I mean, and, at the velocity that applications are growing, just looking at our notes here, number of applications scaling from 64 million in 2017 to 147 million in 2021. That goes to what you were talking about, even with those other metrics earlier, 582 million by 2026 is what Morgan Stanley predicts. So, not only do we need to get out of silos we need to be able to see everything all the time, all at once, from the past legacy, as well as as we extend at scale. How are you thinking about that, Ajay? You're now with a big partner as an umbrella. What's next for you all? How, how are you going to help people solve problems faster? >> Yeah, so one of the attractions to the Zebrium team about Science Logic, aside from the team, and the culture, was the product portfolio was so complimentary. As Mike mentioned, you need visibility, you need mapping from low level building blocks to business services. And the end, at the end of the spectrum, once you know something's wrong you need to be able to take action automatically. And again, Science Logic has a very strong product, set of product capabilities and automated actions. What we bring to the table is the middle layer, which is from visibility, understanding what went wrong, figuring out the root cause. So to us, it was really exciting to be a very nice tuck in into this broader platform where we helped complete the story. >> Savannah: Yeah, that's, that's exciting. >> John: Should we do the Insta challenge? >> I was just getting ready to do that. You go for it John. You go ahead and kick it off. >> So we have this little tradition now, Instagram real, short and sweet. If you were going to see yourself on Instagram, what would be the Instagram reel of why this year's re:Invent is so important, and why people should pay attention to what's going on right now in the industry, or your company? >> Well, I think partly what Ajay was saying it's good to be back, right? So seeing just the energy and being back in 3D, you know en mass, is awesome again. It really is. >> Yeah. >> Mike: But, you know, I think this is where it's happening. We are at an inflection point of our industry and we're seeing a sea change in the way that applications and software delivered to businesses, to enterprises. And it's happening right here. This is the nexus of it. And so we're thrilled to be here as a part of all this, and excited about the future. >> All right, Ajay- >> Well done. He passes >> Your Instagram reel. >> Knowing what's happening in the broader economy, in the business context, it's, it feels even more important that companies like us are working on technologies that empower the same number of people to do more. Because it may not be realistic to just add on more headcount given what's going on in the world. But your deliverables and your roadmaps aren't slowing down. So, still the same amount of complexity, the same growth rates, but you're going to have to deal with all of that with fewer resources and be smarter about it. So, the approaches we're taking feel very much off the moment, you know, given what's going on in the real world. >> I love it. I love it. I've got, I've got kind of a finger to the wind, potentially hardball question for you here to close it out. But, given that you both have your finger really on the pulse right here, what percentage of current IT operations do you think will eventually be automated by AI and ML? Or AI ops? >> Well, I think a large percentage of traditional IT operations, and I'm talking about, you know, network operating center type of, you know, checking heartbeat monitors of compute storage and networking health. I think a lot of those things are going to be automated, right? Machine learning, just because of the scale. You can't scale, you can't hire enough NOC engineers to scale that kind of complexity. But I think IT talents, and what they're going to be focusing on is going shift, and they're going to be focusing on different parts. And I believe a lot of IT is going to be a much more of an enabler for the business, versus just managing things when they go wrong. So that's- >> All right. >> That's what I believe is part of the change. >> That's your, all right Ajay what about your hot take? >> Knowing how error-prone predictions are, (all laughing) I'll caveat my with- >> Savannah: We're allowing for human error here. >> I could be wildly wrong, but if I had to guess, you know, in 10 years you know, as much as 50% of the tasks will be automated. >> Mike: Oh, you- >> I love it. >> Mike: You threw a number out there. >> I love it. I love that he put his finger out- >> You got to see, you got to say the matrix. We're all going to be part of the matrix. >> Well, you know- >> And Star Trek- >> Skynet >> We can only turn back to this footage in a few years and quote you exactly when you have the, you know Mackenzie Research or the Morgan Stanley research that we've been mentioning here tonight and say that you've called it accurately. So I appreciate that. Ajay, it was wonderful to have you here. Congratulations on the acquisition. Thank you. Mike, thank you so much for being here on the Science Logic side, and congratulations to the team on 20 years. That's very exciting. John. Thank you. >> I try, I tried. Thank you. >> You try, you succeed. And thank you to all of our fabulous viewers out there at home. Be sure and tweet us at theCUBE. Say hello, Furrier, Sav is savvy. Let us know what you're thinking of AWS re:Invent where we are live from Las Vegas all week. You're watching theCUBE, the leader in high tech coverage. My name's Savannah Peterson, and we'll see you soon. (upbeat music)

>>Hey everyone. Welcome back to Las Vegas. This is the Cube's live coverage of day. One of snowflake summit 22 fourth annual. We're very happy to be here. A lot of people here, Lisa Martin with Dave Valante, David's always great to be at these events with you, but me. This one is shot out of the cannon from day one, data, data, data, data. That's what you heard of here. First, we have two guests joining us next, please. Welcome Matthew Scalian. Who's an alumni of the cube CEO and founder of Matillion and Jer staying chief data architect and global head of data engineering from Western union. Welcome gentlemen. Thank >>You. Great to be here. >>We're gonna unpack the Western union story in a second. I love that, but Matthew, I wanted to start with you, give the audience who might not be familiar with Matillion an overview, your vision, your differentiators, your joint value statement with snowflake, >>Of course. Well, first of all, thank you for having me on the cube. Again, Matillion S mission is to make the world's data useful, and we do that by providing a technology platform that allows our customers to load transform, synchronize, and orchestrate data on the snowflake data cloud. And on, on the cloud in general, we've been doing that for a number of years. We're co headquartered in the UK and the us, hence my dat accents. And we work with all sorts of companies, commercial scale, large end enterprises, particularly including of course, I'm delighted to say our friends at Western union. So that's why we're here today. >>And we're gonna talk about that in a second, but I wanna understand what's new with the data integration platform from Matillion perspective, lots of stuff coming out, give us an overview. >>Yeah, of course, it's been a really busy year and it's great to be here at snowflake summit to be able to share some of what we've been working on. You know, the Matillion platform is all about making our customers as productive as possible in terms of time to value insight on that analytics, data science, AI projects, like get you to value faster. And so the more technology we can put in the platform and the easier we can make it to use, the better we can achieve that goal. So this year we've, we've shipped a product that we call MDL 2.0, that's enterprise focused, exquisitely, easy to use batch data pipelines. So customers can load data even more simply into the snowflake data cloud, very excitingly we've also launched Matillion CDC. And so this is an industry first cloud native writer, head log based change data capture. >>I haven't come up with a shorter way of saying that, but, and surprise customers need this technology and it's been around for years, but mostly pre-cloud technology. That's been repurposed for the cloud. And so Matillion has rebuilt that concept for the cloud. And we launched that earlier this year. And of course we've continued to build out the core Matillion ETL platform that today over a thousand joint snowflake Matillion customers use, including Western union, of course we've been adding features there such as universal connectivity. And so a challenge that all data integration vendors have is having the right connectors for their source systems. Universal connectivity allows you to connect to any source system without writing code point and click. We shape that as well. So it's been a busy year, >>Was really simple. Sorry. I love that. He said that and it also sounded great with your accent. I didn't wanna >>Thank you. Excellent. Javier, talk about your role at Western union in, in what you've seen in terms of the evolution of the, the data stack. >>So in the last few years, well, a little bit of Western union, a 70 or 170 year old company, pretty much everybody knows what Western union is, right? Driving an interesting synergy from what Matthew says, when data moves money moves, that's what we do when he moves the da, he moves the data. We move the money. That's the synergy between, you know, us and the organization that support us from data move perspective. So what I've seen in the last few years is obviously a shift towards the cloud, but, you know, within the cloud itself, obviously there's a lot of players as well. And we as customers have always been wishing to have a short, smaller footprint of data so that the movement becomes a little lesser. You know, interestingly enough, in this conference, I've heard some very interesting stuff, which kind of helping me to bring that footprint down to a manageable number, to be more governed, to be more, you know, effective in terms of delivering more end results for my customers as well. >>So Matillion has been a great partner for us from our cloud adoption perspective. During the COVID times, we were a re we are a, you know, multi-channel organization. We have retail stores as well, our digital presence, but people just couldn't go to the retail stores. So we had to find ways to accelerate our adoption, make sure our systems are scaling and making sure that we are delivering the same experience to our customers. And that's where, you know, tools like Matillion came in and really, really partnered up with us to kind of bring it up to the level. >>So talk specifically about the stack evolution. Cause I have this sort of theory that everybody talks about injecting data and, and machine intelligence and AI and machine learning into apps. But the application development stack is like totally separate from the, the data analytics and the data pipeline stack. And the database is somewhere over here as well. How is that evolving? Are those worlds coming together? >>Some part of those words are coming together, but where I still see the difference is your heavy lifting will still happen on the data stack. You cannot have that heavy lifting on the app because if once the apps becomes heavy, you'll have trouble communicating with, with, with the organizations. You know, you need to be as lean as possible in the front end and make sure things are curated. Things are available on demand as soon as possible. And that's why you see all these API driven applications are doing really, really well because they're delivering those results back to the, the leaner applications much faster. So I'm a big proponent of, yes, it can be hybrid, but the majority of the heavy lifting still needs to happen down at the data layer, which is where I think snowflake plays a really good role >>In APIs are the connective tissue >>APIs connections. Yes. >>Also I think, you know, in terms of the, the data stack, there's another parallel that you can draw from applications, right? So technology is when they're new, we tend to do things in a granular way. We write a lot of code. We do a lot of sticking of things together with plasters and sticky tape. And it's the purview of high end engineers and people enthusiastic about that to get started. Then the business starts to see the value in this stuff, and we need to move a lot faster. And technology solutions come in and this is what the, the data cloud is all about, right? The technology getting out of the way and allowing people to focus on higher order problems of innovating around analytics, data applications, AI, machine learning, you know, that's also where Matillion sit as well as other companies in this modern enterprise data stack is technology vendors are coming in allowing organizations to move faster and have high levels of productivity. So I think that's a good parallel to application development. >>And's just follow up on that. When you think about data prep and you know, all the focus on data quality, you've got a data team, you know, in the data pipeline, a very specialized, maybe even hyper specialized data engineers, quality engineers, data, quality engineers, data analysts, data scientist, but they, and they serve a lot of different business lines. They don't necessarily have the business, they don't have the business context typically. So it's kind of this back and forth. Do you see that changing in your organization or, or the are the lines of business taking more responsibility for the data and, and addressing that problem? It's, >>It's like you die by thousand paper cuts or you just die. Right? That's the kind >>Of, right, >>Because if I say it's, it's good to be federated, it comes with its own flaws. But if I say, if it's good to be decentralized, then I'm the, the guy to choke, right? And in my role, I'm the guy to choke. So I've selectively tried to be a pseudo federated organization, where do I do have folks reporting into our organization, but they sit close to the line of business because the business understands data better. We are working with them hand in glove. We have dedicated teams that support them. And our problem is we are also regional. We are 200 countries. So the regional needs are very different than our us needs. Majority of the organizations that you probably end up talking to have like very us focused, 50 per more than 50% of our revenue is international. So we do, we are dealing with people who are international, their needs for data, their needs for quality and their needs for the, the delivery of those analytics and the data is completely different. And so we have to be a little bit more closer to the business than traditionally. Some, some organizations feel that they need >>To, is there need for the underlying infrastructure and the operational details that as diverse, or is that something that you bring standardization to the, >>So the best part about this, the cloud that happened to us is exactly that, because at one point of time, I had infrastructure in one country. I had another infrastructure sitting in another country, regional teams, making different different decisions of bringing in different tools. Now I can standardize. I will say, Matillion is our standard for doing ETL work. If this is the use case, but then it gets deployed across the geographies because the cloud helps us or the cloud platform helps us to manage it. Sitting down here. I have three centers around the world, you know, Costa Rica, India, and the us. I can manage 24 7 sitting here. No >>Problem. So the underlying our infrastructure is, is global, but the data needs are dealt with locally. Yep. >>One of the pav question, I was just thinking JVE is super well positioned funds for you, which is around that business domain knowledge versus technical expertise. Cause again, early in technology journeys tend, things tend to be very technical and therefore only high end engineers can do it, but high end engineers are scar. Right? Right. And, and also, I mean, we survey our hundreds of large enterprise customers and they tell us they spend two thirds of their time doing stuff they don't really want to do like reinventing the wheel, basic data movement and the low order staff. And so if you can make those people more productive and allow them to focus on higher value problems, but also bring pseudo technical people into it. Overall, the business can go a lot faster. And the way you do that is by making it easier. That's why Matillion is a low code NOCO platform, but Jer and Western union are doing this right. I >>Mean, I can't compete with AWS and Google to hire people. So I need to find people who are smart to figure the products that we have to make them work. I don't want them to spend time on infrastructure, Adam, I don't want them to spend time on trying to manage platforms. I want them to deliver the data, deliver the results to the business so that they can build and serve their customers better. So it's a little bit of a different approach, different mindset. I used to be in consulting for 17 years. I thought I knew it all, but it changed overnight when I own all of these systems. And I'm like, I need to be a little bit more smarter than this. I need to be more proactive and figure out what my business needs rather than what just from a technology needs. It's more what the business needs and how I can deliver that needs to them. So simple analogy, you know, I can build the best architecture in the world. It's gonna cost me an arm and leg, but I can't drive it because the pipeline is not there. So I can have a Ferrari, but I can't drive it. It's still capped at 80, 80 miles an hour. So rather than spend, rather than building one Ferrari, let me have 10 Toyotas or 10 Fs, which will go further along and do better for my cus my, for my customers. >>So how do you see this whole, we hearing about the data cloud. We hear about the marketplace, data products now, application development inside the data cloud. How do you see that affecting not so much the productivity of the data teams. I don't wanna necessarily say, but the product, the value that, that customers like you can get out >>Data. So data is moving closer to the business. That's the value I see, because you are injecting the business and you're injecting the application much more closer to the data because it, in the past, it was days and days of, you know, churn the data to actually clear results. Now the data has moved much closer. So I have a much faster turnaround time. The business can adapt and actually react much, much faster. It took us like 16 to 30 days to deliver, you know, data for marketing. Now I can turn it down in four hours. If I see something happening, I'll give you an example. The war in Ukraine happened. Let is shut down operations in Russia. Ukraine is cash swamp. There's no cash in Ukraine. We have cash. We roll out campaign, $0 money, transferred to Ukraine within four hours of the world going on. That's the impact that we have >>Massive impact. That's huge, especially with such a macro challenge going on, on the, in, in the world. Thank you so much for sharing the Matillion snowflake partnership story, how it's helping Western union really transform into a data company. We love hearing stories of organizations that are 170 years old that have always really been technology focused, but to see it come to life so quickly is pretty powerful. Guys. Thank you so much for your time. Thanks >>Guys. Thank you, having it. Thank >>You >>For Dave Velante and our guests. I'm Lisa Martin. You're watching the cubes live coverage of snowflake summit 22 live from Las Vegas. Stick around. We'll be back after a short break.

>> Announcer: "theCUBE" presents KubeCon and CloudNativeCon Europe 2022 brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain and KubeCon and CloudNativeCon Europe 2022. I'm Keith Townsend, my co-host, Paul Gillin, Senior Editor Enterprise Architecture for SiliconANGLE. We're going to talk, or continue to talk to amazing people. The coverage has been amazing, but also the city of Valencia is beautiful. I have to eat a little crow, I landed and I saw the convention center, Paul, have you got out and explored the city at all? >> Absolutely, my first reaction to Valencia when we were out in this industrial section was, "This looks like Cincinnati." >> Yes. >> But then I got on the bus second day here, 10 minutes to downtown, another world, it's almost a middle ages flavor down there with these little winding streets and just absolutely gorgeous city. >> Beautiful city. I compared it to Charlotte, no disrespect to Charlotte, but this is an amazing city. Naina Singh, Principal Product Manager at Red Hat, and Roland Huss, also Principal Product Manager at Red Hat. We're going to talk a little serverless. I'm going to get this right off the bat. People get kind of feisty when we call things like Knative serverless. What's the difference between something like a Lambda and Knative? >> Okay, so I'll start. Lambda is, like a function as a server, right? Which is one of the definitions of serverless. Serverless is a deployment platform now. When we introduced serverless to containers through Knative, that's when the serverless got revolutionized, it democratized serverless. Lambda was proprietary-based, you write small snippets of code, run for a short duration of time on demand, and done. And then Knative which brought serverless to containers, where all those benefits of easy, practical, event-driven, running on demand, going up and down, all those came to containers. So that's where Knative comes into picture. >> Yeah, I would also say that Knative is based on containers from the very beginning, and so, it really allows you to run arbitrary workloads in your container, whereas with Lambda you have only a limited set of language that you can use and you have a runtime contract there which is much easier with Knative to run your applications, for example, if it's coming in a language that is not supported by Lambda. And of course the most important benefit of Knative is it's run on top of Kubernetes, which allows you- >> Yes. >> To run your serverless platform on any other Kubernetes installation, so I think this is one of the biggest thing. >> I think we saw about three years ago there was a burst of interest around serverless computing and really some very compelling cost arguments for using it, and then it seemed to die down, we haven't heard a lot about serverless, and maybe I'm just not listening to the right people, but what is it going to take for serverless to kind of break out and achieve its potential? >> Yeah, I would say that really the big advantage of course of Knative in that case is that you can scale down to zero. I think this is one of the big things that will really bring more people onto board because you really save a lot of money with that if your applications are not running when they're not used. Yeah, I think also that, because you don't have this vendor log in part thing, when people realize that you can run really on every Kubernete platform, then I think that the journey of serverless will continue. >> And I will add that the event-driven applications, there hasn't been enough buzz around them yet. There is, but serverless is going to bring a new lease on life on them, right? The other thing is the ease of use for developers. With Knative, we are introducing a new programming model, the functions, where you don't even have to create containers, it would do create containers for you. >> So you create the servers, but not the containers? >> Right now, you create the containers and then you deploy them in a serverless fashion using Knative. But the container creation was on the developers, and functions is going to be the third component of Knative that we are developing upstream, and Red Hat donated that project, is going to be where code to cloud capability. So you bring your code and everything else will be taken care of, so. >> So, I'd call a function or, it's funny, we're kind of circular with this. What used to be, I'd write a function and put it into a container, this server will provide that function not just call that function as if I'm developing kind of a low code no code, not no code, but a low code effort. So if there's a repetitive thing that the community wants to do, you'll provide that as a predefined function or as a server. >> Yeah, exactly. So functions really helps the developer to bring their code into the container, so it's really kind of a new (indistinct) on top of Knative- >> on top op. >> And of course, it's also a more opinionated approach. It's really more closer coming to Lambda now because it also comes with a programming model, which means that you have certain signature that you have to implement and other stuff. But you can also create your own templates, because at the end what matters is that you have a container at the end that you can run on Knative. >> What kind of applications is serverless really the ideal platform? >> Yeah, of course the ideal application is a HTTP-based web application that has no state and that has a very non-uniform traffic shape, which means that, for example, if you have a business where you only have spikes at certain times, like maybe for Super Bowl or Christmas, when selling some merchandise like that, then you can scale up from zero very quickly at a arbitrary high depending on the load. And this is, I think, the big benefit over, for example, Kubernetes Horizontal Pod Autoscaling where it's more like indirect measures of value scaling based on CPR memory, but here, it directly relates one to one to the traffic that is coming in to concurrent request. Yeah, so this helps a lot for non-uniform traffic shapes that I think this has become one of the ideal use case. >> Yeah. But I think that is one of the most used or defined one, but I do believe that you can write almost all applications. There are some, of course, that would not be the right load, but as long as you are handling state through external mechanism. Let's say, for example you're using database to save the state, or you're using physical volume amount to save the state, it increases the density of your cluster because when they're running, the containers would pop up, when your application is not running, the container would go down, and the resources can be used to run any other application that you want to us, right? >> So, when I'm thinking about Lambda, I kind of get the event-driven nature of Lambda. I have a S3 bucket, and if a S3 event is driven, then my functions as the server will start, and that's kind of the listening servers. How does that work with Knative or a Kubernetes-based thing? 'Cause I don't have an event-driven thing that I can think of that kicks off, like, how can I do that in Kubernetes? >> So I'll start. So it is exactly the same thing. In Knative world, it's the container that's going to come up and your servers in the container, that will do the processing of that same event that you are talking. So let's say the notification came from S3 server when the object got dropped, that would trigger an application. And in world of Kubernetes, Knative, it's the container that's going to come up with the servers in it, do the processing, either find another servers or whatever it needs to do. >> So Knative is listening for the event, and when the event happens, then Knative executes the container. >> Exactly. >> Basically. >> So the concept of Knative source which is kind of adapted to the external world, for example, for the S3 bucket. And as soon as there is an event coming in, Knative will wake up that server, will transmit this event as a cloud event, which is another standard from the CNCF, and then when the server is done, then the server spins down again to zero so that the server is only running when there are events, which is very cost effective and which people really actually like to have this kind of way of dynamic scaling up from zero to one and even higher like that. >> Lambda has been sort of synonymous with serverless in the early going here, is Knative a competitor to Lambda, is it complimentary? Would you use the two together? >> Yeah, I would say that Lambda is a offering from AWS, so it's a cloud server there. Knative itself is a platform, so you can run it in the cloud, and there are other cloud offerings like from IBM, but you can also run it on-premise for example, that's the alternative. So you can also have hybrid set scenarios where you really can put one part into the cloud, the other part on-prem, and I think there's a big difference in that you have a much more flexibility and you can avoid this kind of Windows login compared to AWS Lambda. >> Because Knative provides specifications and performance tests, so you can move from one server to another. If you are on IBM offering that's using Knative, and if you go to a Google offering- >> A google offering. >> That's on Knative, or a Red Hat offering on Knative, it should be seamless because they're both conforming to the same specifications of Knative. Whereas if you are in Lambda, there are custom deployments, so you are only going to be able to run those workloads only on AWS. >> So KnativeCon, co-located event as part of KubeCon, I'm curious as to the level of effort in the user interaction for deploying Knative. 'Cause when I think about Lambda or cloud-run or one of the other functions as a servers, there is no backend that I have to worry about. And I think this is where some of the debate becomes over serverless versus some other definition. What's the level of lifting that needs to be done to deploy Knative in my Kubernetes environment? >> So if you like... >> Is this something that comes as based part of the OpenShift install or do I have to like, you know, I have to... >> Go ahead, you answer first. >> Okay, so actually for OpenShift, it's a code layer product. So you have this catalog of operator that you can choose from, and OpenShift Serverless is one part of that. So it's really kind of a one click install where you have also get a default configuration, you can flexibly configure it as you like. Yeah, we think that's a good user experience and of course you can go to these cloud offerings like Google Cloud one or IBM Code Engine, they just have everything set up for you. And the idea of other different alternatives, you have (indistinct) charts, you can install Knative in different ways, you also have options for the backend systems. For example, we mentioned that when an event comes in, then there's a broker in the middle of something which dispatches all the events to the servers, and there you can have a different backend system like Kafka or AMQ. So you can have very production grade messaging system which really is responsible for delivering your events to your servers. >> Now, Knative has recently, I'm sorry, did I interrupt you? >> No, I was just going to say that Knative, when we talk about, we generally just talk about the serverless deployment model, right? And the Eventing gets eclipsed in. That Eventing which provides this infrastructure for producing and consuming event is inherent part of Knative, right? So you install Knative, you install Eventing, and then you are ready to connect all your disparate systems through Events. With CloudEvents, that's the specification we use for consistent and portable events. >> So Knative recently admitted to the, or accepted by the Cloud Native Computing Foundation, incubating there. Congratulations, it's a big step. >> Thank you. >> Thanks. >> How does that change the outlook for Knative adoption? >> So we get a lot of support now from the CNCF which is really great, so we could be part of this conference, for example which was not so easy before that. And we see really a lot of interest and we also heard before the move that many contributors were not, started into looking into Knative because of this kind of non being part of a mutual foundation, so they were kind of afraid that the project would go away anytime like that. And we see the adoption really increases, but slowly at the moment. So we are still ramping up there and we really hope for more contributors. Yeah, that's where we are. >> CNCF is almost synonymous with open source and trust. So, being in CNCF and then having this first KnativeCon event as part of KubeCon, we are hoping, and it's a recent addition to CNCF as well, right? So we are hoping that this events and these interviews, this will catapult more interest into serverless. So I'm really, really hopeful and I only see positive from here on out for Knative. >> Well, I can sense the excitement. KnativeCon sold out, congratulations on that. >> Thank you. >> I can talk about serverless all day, it's a topic that I really love, it's a fascinating way to build applications and manage applications, but we have a lot more coverage to do today on "theCUBE" from Spain. From Valencia, Spain, I'm Keith Townsend along with Paul Gillin, and you're watching "theCUBE," the leader in high-tech coverage. (gentle upbeat music)

>>Well, hi everybody, John Walls here on the cube. And thank you for joining us here for this cube conversation today. And we're talking about data. Of course, it's a blessing and the respect that it's become such a valuable asset. So many companies around the world, it's also a curse, obviously, because it is certainly can be vulnerable. It is under attack and Druva is all about protecting your data and preventing those attacks. And with us to talk about that a little bit more in depth as Jaspreet Singh, who is the founder and CEO at Druva and Steven Manley, who was the company's CTO. Gentlemen, thanks for being with us here on the queue. Good to see you. >>Thank you. Thank you, John. >>So Jaspreet, let me just begin with you. Let's, let's talk about the larger picture of data these days. And, and we read, it seems as though every day about some kind of invasion, you know, where some ransomware attack it's become all too commonplace. So if you wouldn't maybe just set the stage a little bit for the state of ransomware here in 2021. >>That's right. John, I think Lansing has now a new national security threat and at the scene, uh, all around us, this, uh, almost every single day, we hear about businesses getting hit with a, a new ransomware attack, uh, ransomware 1.0 was more a malware situation impacting our data. And as you know, the pandemic transformed the entire data landscape, like the application, the terror, the entire supply chain delivery model as to be more online, more connected, which, you know, for this mortar stores, this whole approach towards a malware coming in, we're also seeing ransomware 2.0, it is all about like insider techs or, or, or in general security misconfiguration, which could lead to data being exfiltrated or traded off in the market. So in general, as data is far more connected, far more expected to be online security techs from either malware or human oriented security issues are becoming more and more dominant threat to, to our, our entire data landscape. Right? >>Yeah. So, so Steven, if you would, I'd like you to just to follow up on this, this, uh, uh, will the landscape to take one of Jaspreet's terms here about what you're seeing in terms of, of kind of these evolving threats now, um, used to be probably, I don't know, five, six years ago, it was a very different, uh, set of problems and challenges and companies maybe weren't as laser focused as they are now. Um, maybe take us through that, that process, what has happened with regard to the client base that you see and you're working with in terms of their recognition and other steps that they need to take going forward as they modernize their operations? >>Yeah. You know, I th I think there's, there's two things we see from, uh, from sort of a technical perspective. The first one is in just pre-call that ransomware 1.0, ransomware 1.0, uh, is mainstream at this point, you know, so, so you, you can go out there and you don't have to be an expert hacker there's ransomware as a service. You know, your average, your average teenager can basically download a ransomware attack kit, uh, you know, get, get a pretty lightweight cloud account and attack school districts, hospitals, municipal organizations, whatever it is, you know, with what we would consider the traditional ransomware and, and that's become ubiquitous. And that's why we see all these reports of, there are multiple ransomware attacks every minute, you know, in the United States and around the world. So, so that's, that's, that's one part which is you're going to get hit. >>Now you'll probably get heading in with the more traditional ransomware, but, you know, like any industry, the ransomware people have evolved. And so it's as just breed said, they are constantly innovating. And so what we're seeing now from, uh, from sort of a marketplace standpoint is, you know, getting smarter about the ransomware attack. So, so laying low, longer, uh, you know, sort of corrupting or attacking data a little bit more slowly. So it's harder to detect specifically attacking backup infrastructure so that you won't be able to recover exfiltrating data. So that, so that now you can have sort of two types of threats, one that your data is encrypted, and the other is if you don't pay us, we're just going to post it on the internet. So, so you've got stage one, which is ubiquitous, and you've got to protect yourself against that because anyone can be attacked at any time. And then you've got stage two where it's getting smarter and that's where organizations then have to step up their game and say, I've got to keep my backup safer. Uh, I've got to be able to detect things a little bit more easily, and I need to start really understanding my data footprint. So I understand what can be exfiltrated and what that's going to mean to me as a business. >>So, Jess, um, to that point, that Steven was just talking about how the organizations need to get smarter in terms of your communications that you're having with the folks in the C-suite, um, is that point, is that you, if they readily identified today, I mean, are, do they get it, um, are the, is the communication going out to their stakeholders, are the business priorities being aligned appropriately? I mean, what, what are organizations and specifically on that executive level, what are they doing right now? Um, in terms of, of preparation in terms of protections that, that, uh, again, are so necessary, I would think. >>Yeah, absolutely. So I think we do see customers truly making strides to solving the problem. There's not a one facet that, you know, one solution fits all problem either, right? So there's, there's, there's, there's a whole productive nature of preventing ransomware detection and response. There's a readiness aspect of it, but what happens when you do get here now that recovery element to it, how do I recover in time in shape from a attack like this, the customers are evolving. They're understanding at the same time, they actually deploying appropriate technologies to, to put all the three aspects of solving the solution. What does Stickney like any of the security challenge? This is, uh, you know, there's not a one application solve all problems. Typically the OLAP and controls built by a multiple group and multiple parties to make sure you're ready to response towards a tech like this. >>And just to jump in, because one of the things I find fascinating as we go through this, the customer conversations I have, I've I've been doing, you know, sort of data protection for a long time. We won't get into that, but, but most of my time I'd spent talking to, you know, VPs of it. Maybe I'd see a CIO. It's fascinating. Now we will have conversations with boards of directors because it becomes such a big issue. And the focus is, is, is so different, right? Because they understand that this isn't just like a usual backup and recovery, or even the traditional disaster recovery that you might do from a natural disaster or some sort of hardware outage. They're seeing that there are so many stages now to an orchestrator recovery. These customers we work with where it's, it's, it's not just about, I need a little bit to technology. They're really looking for how do I operationalize all of this? You know, because once you're up at the board of directors, this is no longer a which product is better than X, Y, or Z. It's a discussion about who can really insulate me from the risk, because these, these can be business sending events. If you're not careful, >>Right? I mean, you're ready. This is a great point. And actually, Steven, I hadn't really thought about these fiduciary responsibilities that boards have. And obviously we think about operations. We think about PNL, right? We think about all, but I hadn't really thought about how also data protection. And I want to talk about data resiliency, how those come into play, as well as those board decisions are made. So let's talk about resiliency. I want you guys to explain this concept to me. Um, so the, you know, what, what's the distinction between protection and resiliency because to me, they're, they're maybe not exactly synonymous, but they're kind of cousins in some respects. So a Jaspreet, if you will talk about resiliency and how you define that. >>Sure. So I just see what I mentioned, right? The prediction was more about how do I actually save guard my data to actually, you know, recover from an incident right there, didn't say residency is all about being ready to respond in time, right? The forward-leaning pusher of making sure, you know, am I ready to not just recover from a very, uh, you know, age, old problem of application failure or, or human errors, but also a cyber attack or a, you know, a true age incident or a cyber recovery or security incident, which I'm prepared to respond in a appropriate SLA across the board. Right. Uh, and resiliency also goes beyond, you know, just the nature of data itself, right? You're, you're talking about applications, environments ecosystem to truly understand that the enterprise operation needs it. Data needs to be holistic. We talked through how do I get my business online, faster. Right. And that's the two nature of differentiation between, uh, protection going towards resiliency. >>And then as obviously driving a lot of your product development. Right. And, and, and I know you've got the data resilience, resiliency, cloud, um, service that you're offering now. So Steven blitz blitz, let's dive into that a little bit. Um, what was the Genesis of that offering and, and what do you see as its primary advantages to your clients? >>Yeah, so, so I think, I think there's, there's really those, those tier two key words there it's resiliency and it's cloud. So just brief, kind of walked about how your resiliency is that step forward. It's that shift left, whatever term you want to use. To me, the best part about the cloud is, and like I said, I've been doing this for a long time and I've yet to meet a customer. Who's come to me and said, I really wish I could spend more money and more time on my data protection infrastructure. I love sticking together, multiple separate products. It's just a great use of my time. Right? Nobody says that what they really say is, could you just solve this problem for me? This is, this is hard capacity planning and patching and upgrades and tying together all the different components from up to seven different vendors. >>This is hard work. And I just need this to work. I need this to work seamlessly. And so we, we, we looked at that cloud part and we said, well, when you think of cloud, you think of something that's flexible. You think of something that's on demand. You think of something that does the job for you. And so, you know, when we talk about this data resiliency cloud, it's about, you know, moving onto your front foot, getting aggressive, being ready for what's coming, but having, you know, frankly, Druva do it for you as opposed to saying here's some technology, good luck. You know, Mr. And Mrs. Customer, you know, we've got this solved for you, it's our job to take care of it. >>And to add to it, you know, this entire resiliency question cannot be solved to a simple, a software is approach is a fundamental belief because the same network, the same principles of operation, the same people involved, you know, what, what those are involved around the primary application that the resiliency aspect has to be air gap appropriately, not just at the data level, but ID and operations limit as well. Right? So a notion of a cloud, almost a social distancing for your data, right? And you're in your ego to the enterprise that, Hey, if anything happens to my primary network application stack data, my second Bree cloud, my redundancy cloud is ready to respond inappropriate, define SNDs to recover my Buddhist business holistically as a combination of integrating with SecOps as a combination of truly integrating disaster recovery elements with cyber recovery elements, truly understanding application recovery from a backup and recovery point of view. So holistically understanding the notion of resiliency and simplifying it to the elements of public cloud. Yes, sir. >>How do you bend that for your clients? Because as you both pointed out, they have different needs, right? And they have, they have different obviously different that they're involved in different sectors of different operations with different priorities and all that. How is the data resiliency cloud, uh, providing them with the kind of flexibility and aid, the kind of adaptability that you need in order to conform it for what you need and not necessarily, you know, what someone else in another sector is, is all about. >>So, so for me, there's a couple of things that, that is great about, about being the data resiliency cloud. One is that we've got well over 3,500 customers, which means that no matter what segment you're looking in, you're not going to be alone, right? If you're, if you're healthcare, if you're finance, if you're a manufacturing, Druva, Druva understands, you know, what you, and many of, of your similar sort of companies look like, which enables us to work in a lot of ways and enables us to understand what trends are happening across your industry, whether it's, you know, ransomware attacks that are coming across, you know, say manufacturing space and how those look or what data growth looks like, or what type of applications are important in those industries. So it's, it's really useful for us to be able to say, we understand these different verticals because we've got such a broad customer base. >>I think the second thing that comes in then is every customer. I meet the number one question they asked me, and Amanda might not be the first one, but it's the one they want to ask. It's always, how am I doing compared to everybody else? And so it's really useful to, to be able to sit down and say, look in your industry. This is what we see as the standards right now. So this is where you fall. You're sort of maybe a stage two, everybody else's at stage three will help you move forward. You, our industry as a whole is actually ahead of many of the other industries, but this is what's coming next for it for others. And so it's really useful for those customers to understand where they sit in respect to, to sort of the broader marketplace. And so that's one of the values I think we bring is that we do have such a broad understanding of our customers because we are a service as opposed to just selling software. >>Yeah. And those customers too, um, as you've talked about, they're looking maybe at their, their, their competitive landscape and trying to decide, okay, are we keeping up with the Joneses, so to speak? Um, but all of you, all of us, we're all trying to, we're trying to keep up with the bad guys. And so in terms of that going forward, what does that challenge for you at Druva in terms of being anticipatory in terms of trying to recognize, uh, their trends and their movements and, and therefore we're thinking so that you can be that, that great, uh, protective mechanism, you can be that prophylactic measure that stands between a company and something bad from happening. >>So I I'll start. And then, uh, it's funny cause, uh, you know, just breed and I had just this morning, we were actually talking about some of the future of ransomware protection and one of the things that we are using a lot in driven, and I get every company says they're doing it is the use of AIML, especially in detecting, uh, sort of unusual trends. Um, but, but you know, but I think we're different than most because the AIML we use is again, across, you know, two and a half billion backups every year, right? Because we, we get, we get visibility across everybody. So it's not just isolated, but we're looking at things like, you know, unusual access patterns in the data and usual access patterns based on administrators, because like Jaspreet said, said at the beginning, one of the things we see the ransomware attackers doing is they're trying to get entire control of your environment because if I control your environment, if I control your phone system, your email, I can get control of your backup application and delete everything. >>So we're even doing things to sort of prevent, oh, you know, we were getting unusual administrative access patterns. Let's stop that. We're getting unusual recovery patterns. Maybe that's somebody trying to steal data out. Let's track that. So our use of AIML is across a much broader data set than anybody else. And it's looking at a lot more than just, you know, sort of data, data pattern changes took to a much broader set of things. And, and basically, again, it's, it's sort of a, a bi-weekly meeting we have where Jaspreet comes in with more ideas that basically for our, for, for our team to start to go, what else can we do? Because the landscape keeps changing. >>And on top of it, I think also if you think about data protection or even data storage was never designed from a security point of view, it was always designed from a point of view of recoverability of data tool. Application issues are basically not corruption, but security or the thinking help us also fundamentally understand how do we think about elements of zero trust all around the platform and how do you make sure to what Steven mentioned, if your IDP gets compromised, if you do have a bad actor, enter a data protection solution, make us, how do you still make sure levels of automatization immutability like multiple levels of control that it plays to make sure no bad actor take construct control and true recoverability resiliency is possible across a variety of scenarios and Trudy customer driven SLA. So both foundationally, uh, we've, we've truly built something which is now, uh, it's very deep in and focused on security. The same time as Steven mentioned to understanding of customer landscape really helps us understand bad actors thought more, better, and more faster than many of our, uh, in the industry competition. >>Well, the need is great. That's for sure. And gentlemen, I want to thank you for the time today to talk about, uh, what Druva is doing and wish you continued success down the road. Thanks to you both. >>Thank >>You. All right. We've been talking about data, keeping it safe, keeping your data safe. That's what Druva is all about. And I'm John Walls and you've been watching the cube.

(upbeat music) >> The Cloud essentially turned the data center into an API and ushered in the era of programmable infrastructure, no longer do we think about deploying infrastructure in rigid silos with a hardened, outer shell, rather infrastructure has to facilitate digital business strategies. And what this means is putting data at the core of your organization, irrespective of its physical location. It also means infrastructure generally and storage specifically must be accessed as sets of services that can be discovered, deployed, managed, secured, and governed in a DevOps model or OpsDev, if you prefer. Now, this has specific implications as to how vendor product strategies will evolve and how they'll meet modern data requirements. Welcome to this Cube conversation, everybody. This is Dave Vellante. And with me to discuss these sea changes is Ajay Singh, the Chief Product Officer of Pure Storage, Ajay welcome. >> Thank you, David, gald to be on. >> Yeah, great to have you, so let's talk about your role at Pure. I think you're the first CPO, what's the vision there? >> That's right, I just joined up Pure about eight months ago from VMware as the chief product officer and you're right, I'm the first our chief product officer at Pure. And at VMware I ran the Cloud management business unit, which was a lot about automation and infrastructure as code. And it's just great to join Pure, which has a phenomenal all flash product set. I kind of call it the iPhone or flash story super easy to use. And how do we take that same ease of use, which is a heart of a Cloud operating principle, and how do we actually take it up to really deliver a modern data experience, which includes infrastructure and storage as code, but then even more beyond that and how do you do modern operations and then modern data services. So super excited to be at Pure. And the vision, if you may, at the end of the day, is to provide, leveraging this moderate experience, a connected and effortless experience data experience, which allows customers to ultimately focus on what matters for them, their business, and by really leveraging and managing and winning with their data, because ultimately data is the new oil, if you may, and if you can mine it, get insights from it and really drive a competitive edge in the digital transformation in your head, and that's what be intended to help our customers to. >> So you joined earlier this year kind of, I guess, middle of the pandemic really I'm interested in kind of your first 100 days, what that was like, what key milestones you set and now you're into your second a 100 plus days. How's that all going? What can you share with us in and that's interesting timing because the effects of the pandemic you came in in a kind of post that, so you had experience from VMware and then you had to apply that to the product organization. So tell us about that sort of first a 100 days and the sort of mission now. >> Absolutely, so as we talked about the vision, around the modern data experience, kind of have three components to it, modernizing the infrastructure and really it's kudos to the team out of the work we've been doing, a ton of work in modernizing the infrastructure, I'll briefly talk to that, then modernizing the data, much more than modernizing the operations. I'll talk to that as well. And then of course, down the pike, modernizing data services. So if you think about it from modernizing the infrastructure, if you think about Pure for a minute, Pure is the first company that took flash to mainstream, essentially bringing what we call consumer simplicity to enterprise storage. The manual for the products with the front and back of a business card, that's it, you plug it in, boom, it's up and running, and then you get proactive AI driven support, right? So that was kind of the heart of Pure. Now you think about Pure again, what's unique about Pure has been a lot of our competition, has dealt with flash at the SSD level, hey, because guess what? All this software was built for hard drive. And so if I can treat NAND as a solid state drive SSD, then my software would easily work on it. But with Pure, because we started with flash, we released went straight to the NAND level, and as opposed to kind of the SSD layer, and what that does is it gives you greater efficiency, greater reliability and create a performance compared to an SSD, because you can optimize at the chip level as opposed to at the SSD module level. That's one big advantage that Pure has going for itself. And if you look at the physics, in the industry for a minute, there's recent data put out by Wikibon early this year, effectively showing that by the year 2026, flash on a dollar per terabyte basis, just the economics of the semiconductor versus the hard disk is going to be cheaper than hard disk. So this big inflection point is slowly but surely coming that's going to disrupt the hardest industry, already the high end has been taken over by flash, but hybrid is next and then even the long tail is coming up over there. And so to end to that extent our lead, if you may, the introduction of QLC NAND, QLC NAND powerful competition is barely introducing, we've been at it for a while. We just recently this year in my first a 100 days, we introduced the flasher AC, C40 and C60 drives, which really start to open up our ability to go after the hybrid story market in a big way. It opens up a big new market for us. So great work there by the team,. Also at the heart of it. If you think about it in the NAND side, we have our flash array, which is a scale-up latency centric architecture and FlashBlade which is a scale-out throughput architecture, all operating with NAND. And what that does is it allows us to cover both structured data, unstructured data, tier one apps and tier two apps. So pretty broad data coverage in that journey to the all flash data center, slowly but surely we're heading over there to the all flash data center based on demand economics that we just talked about, and we've done a bunch of releases. And then the team has done a bunch of things around introducing and NVME or fabric, the kind of thing that you expect them to do. A lot of recognition in the industry for the team or from the likes of TrustRadius, Gartner, named FlashRay, the Carton Peer Insights, the customer choice award and primary storage in the MQ. We were the leader. So a lot of kudos and recognition coming to the team as a result, Flash Blade just hit a billion dollars in cumulative revenue, kind of a leader by far in kind of the unstructured data, fast file an object marketplace. And then of course, all the work we're doing around what we say, ESG, environmental, social and governance, around reducing carbon footprint, reducing waste, our whole notion of evergreen and non-disruptive upgrades. We also kind of did a lot of work in that where we actually announced that over 2,700 customers have actually done non-disruptive upgrades over the technology. >> Yeah a lot to unpack there. And a lot of this sometimes you people say, oh, it's the plumbing, but the plumbing is actually very important too. 'Cause we're in a major inflection point, when we went from spinning disk to NAND. And it's all about volumes, you're seeing this all over the industry now, you see your old boss, Pat Gelsinger, is dealing with this at Intel. And it's all about consumer volumes in my view anyway, because thanks to Steve Jobs, NAND volumes are enormous and what two hard disk drive makers left in the planet. I don't know, maybe there's two and a half, but so those volumes drive costs down. And so you're on that curve and you can debate as to when it's going to happen, but it's not an if it's a when. Let me, shift gears a little bit. Because Cloud, as I was saying, it's ushered in this API economy, this as a service model, a lot of infrastructure companies have responded. How are you thinking at Pure about the as a service model for your customers? What's the strategy? How is it evolving and how does it differentiate from the competition? >> Absolutely, a great question. It's kind of segues into the second part of the moderate experience, which is how do you modernize the operations? And that's where automation as a service, because ultimately, the Cloud has validated and the address of this model, right? People are looking for outcomes. They care less about how you get there. They just want the outcome. And the as a service model actually delivers these outcomes. And this whole notion of infrastructure as code is kind of the start of it. Imagine if my infrastructure for a developer is just a line of code, in a Git repository in a program that goes through a CICD process and automatically kind of is configured and set up, fits in with the Terraform, the Ansibles, all that different automation frameworks. And so what we've done is we've gone down the path of really building out what I think is modern operations with this ability to have storage as code, disability, in addition modern operations is not just storage scored, but also we've got recently introduced some comprehensive ransomware protection, that's part of modern operations. There's all the threat you hear in the news or ransomware. We introduced what we call safe mode snapshots that allow you to recover in literally seconds. When you have a ransomware attack, we also have in the modern operations Pure one, which is maybe the leader in AI driven support to prevent downtime. We actually call you 80% of the time and fix the problems without you knowing about it. That's what modern operations is all about. And then also Martin operations says, okay, you've got flash on your on-prem side, but even maybe using flash in the public Cloud, how can I have seamless multi-Cloud experience in our Cloud block store we've introduced around Amazon, AWS and Azure allows one to do that. And then finally, for modern applications, if you think about it, this whole notion of infrastructure's code, as a service, software driven storage, the Kubernetes infrastructure enables one to really deliver a great automation framework that enables to reduce the labor required to manage the storage infrastructure and deliver it as code. And we have, kudos to Charlie and the Pure storage team before my time with the acquisition of Portworx, Portworx today is truly delivers true storage as code orchestrated entirely through Kubernetes and in a multi-Cloud hybrid situation. So it can run on EKS, GKE, OpenShift rancher, Tansu, recently announced as the leader by giggle home for enterprise Kubernetes storage. We were really proud about that asset. And then finally, the last piece are Pure as a service. That's also all outcome oriented, SLS. What matters is you sign up for SLS, and then you get those SLS, very different from our competition, right? Our competition tends to be a lot more around financial engineering, hey, you can buy it OPEX versus CapEx. And, but you get the same thing with a lot of professional services, we've really got, I'd say a couple of years and lead on, actually delivering and managing with SRE engineers for the SLA. So a lot of great work there. We recently also introduced Cisco FlashStack, again, flash stack as a service, again, as a service, a validation of that. And then finally, we also recently did a announcement with Aquaponics, with their bare metal as a service where we are a key part of their bare metal as a service offering, again, pushing the kind of the added service strategy. So yes, big for us, that's where the buck is skating, half the enterprises, even on prem, wanting to consume things in the Cloud operating model. And so that's where we're putting it lot. >> I see, so your contention is, it's not just this CapEx to OPEX, that's kind of the, during the economic downturn of 2007, 2008, the economic crisis, that was the big thing for CFOs. So that's kind of yesterday's news. What you're saying is you're creating a Cloud, like operating model, as I was saying upfront, irrespective of physical location. And I see that as your challenge, the industry's challenge, be, if I'm going to effect the digital transformation, I don't want to deal with the Cloud primitives. I want you to hide the underlying complexity of that Cloud. I want to deal with higher level problems, but so that brings me to digital transformation, which is kind of the now initiative, or I even sometimes call it the mandate. There's not a one size fits all for digital transformation, but I'm interested in your thoughts on the must take steps, universal steps that everybody needs to think about in a digital transformation journey. >> Yeah, so ultimately the digital transformation is all about how companies are gain a competitive edge in this new digital world or that the company are, and the competition are changing the game on, right? So you want to make sure that you can rapidly try new things, fail fast, innovate and invest, but speed is of the essence, agility and the Cloud operating model enables that agility. And so what we're also doing is not only are we driving agility in a multicloud kind of data, infrastructure, data operation fashion, but we also taking it a step further. We were also on the journey to deliver modern data services. Imagine on a Pure on-prem infrastructure, along with your different public Clouds that you're working on with the Kubernetes infrastructures, you could, with a few clicks run Kakfa as a service, TensorFlow as a service, Mongo as a service. So me as a technology team can truly become a service provider and not just an on-prem service provider, but a multi-Cloud service provider. Such that these services can be used to analyze the data that you have, not only your data, your partner data, third party public data, and how you can marry those different data sets, analyze it to deliver new insights that ultimately give you a competitive edge in the digital transformation. So you can see data plays a big role there. The data is what generates those insights. Your ability to match that data with partner data, public data, your data, the analysis on it services ready to go, as you get the digital, as you can do the insights. You can really start to separate yourself from your competition and get on the leaderboard a decade from now when this digital transformation settles down. >> All right, so bring us home, Ajay, summarize what does a modern data strategy look like and how does it fit into a digital business or a digital organization? >> So look, at the end of the day, data and analysis, both of them play a big role in the digital transformation. And it really comes down to how do I leverage this data, my data, partner data, public data, to really get that edge. And that links back to a vision. How do we provide that connected and effortless, modern data experience that allows our customers to focus on their business? How do I get the edge in the digital transformation? But easily leveraging, managing and winning with their data. And that's the heart of where Pure is headed. >> Ajay Singh, thanks so much for coming inside theCube and sharing your vision. >> Thank you, Dave, it was a real pleasure. >> And thank you for watching this Cube conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave a lot and you're watching the cube. We're here with Omar assad is the vice president, GM of H P S H C I and primary storage and data management business. And Sandeep Singh was the vice president of marketing for HP storage division. Welcome gents. Great to see you. >>Great to be here. Dave, >>it's a pleasure to be here today. >>Hey, so uh, last month you guys, you made a big announcement and and now you're, you know, shining the spotlight on that here at discover Cindy. Maybe you can give us a quick recap, what do we need to know? >>Yeah, Dave. We announced that we're expanding HB Green Lake by transforming HB storage to a cloud native software defined data services business. We unveiled a new vision for data that accelerates data dream of transformation for our customers. Uh and it introduced a and we introduced the data services platform that consists of two game changing innovations are first announcement was data services cloud console. It's a SAS based console that delivers the cut operational agility and it's designed to unify data operations through a suite of cloud data services. Our second announcement is H P E electra. It's cloud native data infrastructure to power your data edge to cloud. And it's managed natively with data services cloud console to bring that cloud operational model to our customers wherever their data lives. Together with the data services >>platform. >>Hp Green Green Lake brings that cloud experience to our customers data across edge and on premises environment and lays the foundation for our customers to shift from managing storage to managing data. >>Well, I think it lays the foundation for the next decade. You know, when we entered this past decade, we we we we keep we use terms like software led that that sort of morphed into. So the software defined data center containers with kubernetes, let's zoom out for a minute. If we can homer, maybe you could describe the problems that you're trying to address with this announcement. >>Thanks dave. It's always a pleasure talking to you on these topics. So in my role as general manager for primary storage, I speak with the hundreds of customers across the board and I consistently hear that data is at the heart of what our customers are doing and they're looking for a data driven transformative approach to their business. But as they engage on these things, there are two challenges that they consistently faced. The first one is that managing storage at scale Is rife with complexity. So while storage has gotten faster in the last 20 years, managing a single array or maybe two or three arrays has gotten simpler over time. But managing storage at scale when you deploy fleet, so storage as customers continue to gather, store and life cycle of that data. This process is extremely frustrating for customers. Still I. T. Administrators are firefighting, they're unable to innovate for their business because now data spans all the way from edge to corridor cloud. And then with the advent of public cloud there's another dimension of multi cloud that has been added to their data sprawl. And then secondly what what we what we consistently hear is that idea administrators need to shift from managing storage to managing data. What this basically means is that I. T. Has a desire to mobilize, protect and provision data seamlessly across its lifecycle and across the locations that it is stored at. This ensures that I. D. Leaders uh and also people within the organization understand the context of the data that they store and they operate upon. Yet data management is an extremely big challenge and it is a web of fragmented data silos across processes across infrastructure all the way from test and dev to administration uh to production uh to back up to lifecycle data advantage. Uh And so up till now data management was tied up with storage management and this needs to change for our customers especially with the diversity of the application workloads as they're growing and as customers are expanding their footprint across a multi cloud environment, >>just had to almost um response there. We recently conducted a survey that was actually done by E. S. She. Um and that was a survey of IT. decision makers. And it's interesting what it showcased, 93% of the respondents indicated that storage and data management complexity is impeding their digital transformation. 95% of the respondents indicated that solving storage and data management complexity is a top 10 business initiative for them And 94% want to bring the cloud experience on premises. >>You know, I'll chime in. I think as you guys move to the sort of software world and container world affinity to developers homer. You talked about, you know, things like data protection and we talk about security being bolted on all the time. Now. It's designed in it's it's done at sort of the point of creation, not as an afterthought and that's a big change that we see coming. Uh Let's talk about, you know what also needs to change as customers make the move from this idea of managing storage to to managing data or maybe you can take that one. >>That's a that's a very interesting problem. Right. What are the things that have to be true in order for us to move into this new data management model? So, dave one of the things that the public cloud got right is the cloud operational model which sets the standard for agility and a fast pace for our customers in a classic I. T. On prime model. If you ever wanted to stand up an application or if you were thinking about standing up a particular workload, uh you're going to file a series of I. T. Tickets uh And then you are at the mercy of whatever complex processes exist within organization and and depending on what the level of approvals are within a particular organization, standing up a workload can take days, weeks or even months in certain cases. So what cloud did was a rock that level of simplicity for someone that wanted to instead she ate an app. This means that the provision of underlying infrastructure that makes that workload possible needs to be reduced to minutes from days and weeks. But so what we are intending to do over here is to bring the best of both worlds together so that the cloud experience can be experienced everywhere with ease and simplicity and the customers don't need to change their operating model. So it's blending the two together. And that's what we are trying to usher in into this new era where we start to differentiate between data management and storage management as two independent. Yes, >>Great. Thank you for that. Omer. So deep. I wonder if you could share with the audience, you know, the vision that you guys unveiled, What does it look like? How are you making it actually substantive and and real? >>Yeah. David, That's also great question. Um across the board it's time to reimagine data management. Everything that homer shared. Those challenges are leading to customers needing to break down the silos and complexity that plagues these distributed data environments. And our vision is to deliver a new data experience that helps customers unleash the power of data. We call this vision unified data obs Unified Data Ops integrates data centric policies to streamline data management cloud native control to bring the cloud operational model to where customers data labs and a I driven insights to make the infrastructure invisible. It delivers a new data experience to simplify and bring that agility of cloud to data infrastructure. Streamline data management and help customers innovate faster than ever before. We're making the promise of unified Data Ops Real by transforming H P E storage to a cloud native software defined data services business and introducing a data services platform that expands Hve Green Lake. >>I mean, you know, you talk about the complexity, I see, I look at it as you kind of almost embracing the complexity saying, look, it's gonna keep getting more complex as the cloud expands to the edge on prem Cross cloud, it gets more complex underneath. What you're doing is you're almost embracing that complexity, putting a layer over it and hiding that complexity from from the end customer that and so they can spend their time doing other things over. I wonder if you can maybe talk a little bit more about the data services console, is it sort of another, you know, software layer to manage infrastructure? What exactly is it? >>It's a lot more than that dave and you're you're 100% right. It's basically we're attempting in this release to attack that complexity. Head on. So simply put data services. Cloud console is a SAS based console that delivers cloud operational model and cloud operational agility uh to our customers, it unifies data operations through a series of cloud data services that are delivered on top of this console to our customers in a continuous innovation stream. Uh And what we have done is going back to the point that I made earlier separating storage and data management and putting the strong suites of each of those together into the SAS delivered console for our customers. So what we have done is we have separated data and infrastructure management away from physical hardware to provide a comprehensive and a unified approach to managing data and infrastructure wherever it lives from a customer's perspective, it could be at the edge, it could be in a coal. Oh, it could be in their data center or it could be a bunch of data services that are deployed within the public cloud. So now our customers with data services, cloud console can manage the entire life cycle of their data from all the way from deployment, upgrading and optimizing it uh from a single console from anywhere in the world. Uh This console is designed to streamline data management with cloud data services that enable access to data, It allows for policy-based data protection, it allows for an organizational wide search on top of your storage assets. And we deliver basically a 360° visibility to all your data from a single console that the customer can experience from anywhere. So, so if you look at the journey, the way we're deciding to deliver this. So the first in its first incarnation, uh data services, cloud console gives you infrastructure and cloud data services to start to do data management along with that. But this is that foundation that we are placing in front of our customers, the SAS console through which we get touch our customers on a daily basis. And now as our customers get access to the SAAS platform on the back end, we will continue to roll in additional services throughout the years on a true SAS based innovation base for our customers. And and these services can will be will be ranging all the way from data protection to multiple out data management, all the way to visibility all the way to understanding the context of your data as it's stored across your enterprise. And in addition to that, we're offering a consistent, revised, unified API which allows for our customers to build automation against their storage infrastructure without ever worrying about that. As infrastructure changes. Uh the A P I proof points are going to break for them. That is never going to happen because they are going to be programming to a single SAS based aPI interface from now on. >>Right. And that brings in this idea of infrastructures coding because you talk about as a service to talk about Green Lake and and my question is always okay. Tell me what's behind that. And if and if and if and if you're talking about boxes and and widgets, that's a it's a problem. And you're not you're talking about services and A P. I. S and microservices and that's really the future model. And infrastructure is code and ultimately data as code is really part of that. So, All right. So you guys, I know some of your branding folks, you guys give deep thought uh, to this. So the second part of the announcement is the new product brands and deep maybe you can talk about that a little bit. >>Sure. Ultimately delivering the cloud operational model requires cognitive data infrastructure and that has been engineered to be natively managed from the cloud. And that's why we have also introduced H. P. E. Electra. Omar. Can you perhaps described HB electro even more? >>Absolutely. Thank you. Sandy. Uh, so with with HB Electoral we're launching a new brand of cloud native hardware infrastructure to power our customers data all the way from edge to the core to the cloud. The releases are smaller models for the edge then at the same time having models for the data center and then expanding those services into the public cloud as well. Right. All these hardware devices, Electoral hardware devices are cloud native. Empowered by our Data services. Cloud Council. We're announcing two models with this launch H. P. E. Electra 9000. Uh, this is for our mission critical workloads. It has its history and bases in H P E primera. It comes with 100% availability guarantee. Uh It's the first of its type in the industry. It comes with standard support contract, No special verb is required. And then we're also launching HB electoral 6000. Uh These are based in our history of uh nimble storage systems. Uh These these are for business critical applications, especially for that mid range of the storage market, optimizing price, performance and efficiency. Both of these systems are full envy, any storage powered by our timeless capabilities with data in place upgrades. And then they both deliver a unified infrastructure and data management experience through the data services, cloud console. Uh and and and at the back end, unified ai Ops experience with H P E info site is seamlessly blended in along with the offering for our customers. >>So this is what I was talking about before. It's sort of not your grandfather's storage business anymore. Is this is this is this is something that is part of that, that unified vision, that layer that I talked about. The AP is the program ability. So you're you're reaching into new territory here. Maybe you can give us an example of how the customers experience what that looks like. >>Excellent, loved her Dave. So essentially what we're doing is we're changing the storage experience to a true cloud operational model for our customers. These recent announcements that we just went through along with, indeed they expand the cloud experience that our customers get with storage as a service with HPD Green Lake. So a couple of examples to make this real. So the first of all is simplified deployment. Uh, so I t no longer has to go through complex startup and deployment processes. Now, all you need to do is these systems shipped and delivered to the customer's data center. Operational staff just need to rack and stack and then leave, connect the power cable, connect the network cable. And the job is done from that point onwards, data services console takes over where you can onboard these systems, you can provision these systems if you have a pre existing organization wide security as well as standard profile setup in data services console, we can automatically apply those on your behalf and bring these systems online. From a customer's perspective, they can be anywhere in the world to onboard these systems, they could be driving in a car, they could be sitting on a beach uh And and you know, these systems are automatically on boarded through this cloud operational model which is delivered through the SAAS application for our customers. Another big example. All that I'd like to shed light on is intent based provisioning. Uh So Dave typically provisioning a workload within a data center is an extremely spreadsheet driven trial and error kind of a task. Which system do I land it on? Uh Is my existing sl is going to be affected which systems that loaded, which systems are loaded enough that I put this additional workload on it and the performance doesn't take. All of these decisions are trial and error on a constant basis with cloud data services console along with the electron new systems that are constantly in a loop back information feeding uh Typical analytics to the console. All you need to do is to describe the type of the workload and the intent of the workload in terms of block size S. L. A. That you would like to experience at that point. Data services console consults with intra site at the back end. We run through thousands of data points that are constantly being given to us by your fleet and we come back with a few recommendations. You can accept the recommendation and at that time we go ahead and fully deploy this workload on your behalf or you can specify a particular system and then we will try to enforce the S. L. A. On that system. So it completely eliminates the guesswork and the planning that you have to do in this regard. Uh And last but not the least. Uh you know, one of the most important things is, you know, upgrades has been a huge problem for our customers. Uh And typically oftentimes when you're not in this constant, you know, loop back communication with your customers. It often is a big challenge to identify which release or which bug fix or which update goes on to which particular machine. All of that has been completely taken away from our customers and fully automated. Uh we run thousands of signatures across are installed base. We identify which upgrades need to be curated for which machines in a fleet for a particular customer. And then if it applies to that customer we presented, and if the customer accepts it, we automatically go ahead and upgrade the system and and and last, but not the least from a global management perspective. Now, a customer has an independent data view of their data estate, independent from a storage estate. And data services. Council can blend the two to give a consistent view or you can just look at the fleet view or the data view. >>It's kind of the Holy Grail. I mean I've been in this business a long time and I think I t. People have dreamt about you know this kind of capability for for a long long time. I wonder if we could sort of stay on the customers for a moment here and and talk about what's enabled. Now everybody's talking digital transformation that I joke about the joke. Not funny. The force marched to digital with Covid uh and we really wasn't planned for but the customers really want to drive now that digital transfer some of them are on the back burner and now they're moving to the front burner. What are the outcomes that are that are enabled here? Omar. >>Excellent. So so on on a typical basis for a traditional I. T. Customer, this cloud operational model means that you know information technology staff can move a lot faster and they can be a lot more productive on the things that are directly relevant to their business. They can get up to 99% of the savings back to spend more time on strategic projects or best of all spend time with their families rather than managing and upgrading infrastructure and fleets of infrastructure. Right. For line of business owners, the new experience means that their data infrastructure can be presented can be provision where the self service on demand type of capability. Uh They necessarily don't have to be in the data center to be able to make those decisions. Capacity management, performance management, all of that is died in and presented to them wherever they are easy to consume SAS based models and especially for data innovators, whether it's D B A s, uh whether it's data analysts, they can start to consume infrastructure and ultimately data as a code to speed up their app development because again, the context that we're bringing forward is the context of data decoupling it from. Actually, storage management, storage management and data management are now two separate domains that can be presented through a single console to tie the end to end picture for a customer. But at the end of the day, what we have felt is that customers really really want to rely and move forward with the data management and leave infrastructure management to machine oriented task, which we have completely automated on their behalf. >>So I'm sure you've heard you got the memo about, you know, H H P going all in on as a service. Uh it's clear that the companies all in. How does this announcement fit in to that overall mission, Sandeep >>Dave. We believe the future is edge to cloud and our mission is to be the edge to cloud platform as a service company and as as HB transforms HP Green Lake is our unified cloud platform. Hp Green Link is how we deliver cloud services and agile cloud experiences to customers, applications and data across the edge to cloud. With the storage announcement that we made recently, we announced that we're expanding HB Green Lake with as a service transformation of the HPV storage business to a cloud native software defined data services business. And this expands storage as a service delivering full cloud experience to our customers data across edge and on prem environment across the board were committed to being a strategic partner for every one of our customers and helping them accelerate their digital transformation. >>Yeah, that's where the puck is going guys. Hey as always great conversation with with our friends from HP storage. Thanks so much for the collaboration and congratulations on the announcements and I know you're not done yet. >>Thanks. Dave. Thanks. Dave. All right. Dave. It's a pleasure to be here. >>You're very welcome. And thank you for being with us for hp. You discovered 2021. You're watching the cube, the leader digital check coverage. Keep it right there, but right back. >>Mhm. Mhm.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cube. We're here with Omar assad is the vice president GM of H P S H C I and primary storage and data management business. And Sandeep Singh was the vice president of marketing for HP storage division. Welcome gents. Great to see you. >>Great to be here. Dave, >>It's a pleasure to be here today. >>Hey, so uh, last month you guys, you made a big announcement and and now you're, you know, shining the spotlight on that here at discover Cindy. Maybe you can give us a quick recap, what do we need to know? >>Yeah, Dave. We announced that we're expanding HB Green Lake by transforming HB storage to a cloud native software defined data services business. We unveiled a new vision for data that accelerates data, dream of transformation for our customers. Uh and it introduced a and we introduced the data services platform that consists of two game changing innovations are first announcement was Data services cloud console. It's a SAS based console that delivers the cut operational agility and it's designed to unify data operations through a suite of cloud data services. Our 2nd announcement is HPE. Electra. It's cloud native data infrastructure to power your data edge to cloud. And it's managed natively with data services cloud console to bring that cloud operational model to our customers wherever their data lives together with the data services platform. Hp Green Green Lake brings that cloud experience to our customers data across edge and on premises environment and lays the foundation for our customers to shift from managing storage to managing data. >>Well, I think it lays the foundation for the next decade. You know, when we entered this past decade, we we were Ricky bobby's terms like software led that that sort of morphed into. So the software defined data center containers with kubernetes, Let's zoom out for a minute. If we can homer maybe you could describe the problems that you're trying to address with this announcement. >>Thanks dave. It's always a pleasure talking to you on these topics. So in my role as general manager for primary storage, I speak with the hundreds of customers across the board and I consistently hear that data is at the heart of what our customers are doing and they're looking for a data driven transformative approach to their business. But as they engage on these things, there are two challenges that they consistently faced. The first one is that managing storage at scale Is rife with complexity. So while storage has gotten faster in the last 20 years, managing a single array or maybe two or three arrays has gotten simpler over time. But managing storage at scale when you deploy fleet. So storage as customers continue to gather, store and lifecycle that data. This process is extremely frustrating for customers. Still I. T. Administrators are firefighting, they're unable to innovate for their business because now data spans all the way from edge to corridor cloud. And then with the advent of public cloud there's another dimension of multi cloud that has been added to their data sprawl. And then secondly what what we what we consistently hear is that idea administrators need to shift from managing storage to managing data. What this basically means is that I. D. Has a desire to mobilize, protect and provision data seamlessly across its lifecycle and across the locations that it is stored at. Uh This ensures that I. D. Leaders uh and also people within the organization understand the context of the data that they store and they operate upon. Yet data management is an extremely big challenge and it is a web of fragmented data silos across processes across infrastructure all the way from test and dev to administration uh to production uh to back up to lifecycle data management. Uh And so up till now data management was tied up with storage management and this needs to change for our customers especially with the diversity of the application workloads as they're growing and as customers are expanding their footprint across a multi cloud environment >>just to add to almost uh response there. We recently conducted a survey that was actually done by E. S. She. Um and that was a survey of IT. decision makers. And it's interesting what it showcased, 93% of the respondents indicated that storage and data management complexity is impeding their digital transformation. 95% of the respondents indicated that solving storage and data management complexity is a top 10 business initiative for them and 94% want to bring the cloud experience on premises, >>you know, al china. And I think as you guys move to the sort of software world and container world affinity to developers homer, you talked about, you know, things like data protection and we talk about security being bolted on all the time. Now. It's designed in it's it's done at sort of the point of creation, not as an afterthought. And that's a big change that we see coming. Uh But let's talk about, you know, what also needs to change as customers make the move from this idea of managing storage to to managing data or maybe you can take that one. >>That's a that's a that's a very interesting problem. Right. What are the things that have to be true in order for us to move into this new data management model? So, dave one of the things that the public cloud got right is the cloud operational model uh which sets the standard for agility and a fast pace for our customers in a classic I. T. On prime model, if you ever wanted to stand up an application or if you were thinking about standing up a particular workload, uh you're going to file a series of I. T. Tickets and then you're at the mercy of whatever complex processes exist within organization and and depending on what the level of approvals are within a particular organization, standing up a workload can take days, weeks or even months in certain cases. So what cloud did was they brought that level of simplicity for someone that wanted to instead she ate an app. This means that the provisioning of underlying infrastructure that makes that workload possible needs to be reduced to minutes from days and weeks. But so what we are intending to do over here is to bring the best of both worlds together so that the cloud experience can be experienced everywhere with ease and simplicity and the customers don't need to change their operating model. So it's blending the two together. And that's what we are trying to usher in into this new era where we start to differentiate between data management and storage management as two independent things. >>Great, thank you for that. Omer sometimes I wonder if you could share with the audience, you know, the vision that you guys unveiled, What does it look like? How are you making it actually substantive and and real? >>Yeah. Dave. That's also great question. Um across the board it's time to reimagine data management. Everything that homer shared. Those challenges are leading to customers needing to break down the silos and complexity that plagues these distributed data environments. And our vision is to deliver a new data experience that helps customers unleash the power of data. We call this vision unified data jobs, Unified Data Ops integrates data centric policies to streamline data management, cloud native control to bring the cloud operational model to where customers data labs and a I driven insights to make the infrastructure invisible. It delivers a new data experience to simplify and bring that agility of cloud to data infrastructure. Streamline data management and help customers innovate faster than ever before. We're making the promise of Unified Data Ops Real by transforming Hve storage to a cloud native software defined data services business and introducing a data services platform that expands Hve Green Lake. >>I mean, you know, you talk about the complexity, I see, I look at it as you kind of almost embracing the complexity saying, look, it's gonna keep getting more complex as the cloud expands to the edge on prem Cross cloud, it gets more complex underneath. What you're doing is you're almost embracing that complexity and putting a layer over it and hiding that complexity from from the end customer that and so they can spend their time doing other things over. I wonder if you can maybe talk a little bit more about the data services console, Is it sort of another software layer to manage infrastructure? What exactly is it? >>It's a lot more than that, Dave and you're you're 100% right. It's basically we're attempting in this release to attack that complexity head on. So simply put data services. Cloud console is a SAS based console that delivers cloud operational model and cloud operational agility uh to our customers. It unifies data operations through a series of cloud data services that are delivered on top of this console to our customers in a continuous innovation stream. Uh And what we have done is going back to the point that I made earlier separating storage and data management and putting the strong suites of each of those together into the SAS delivered console for our customers. So what we have done is we have separated data and infrastructure management away from physical hardware to provide a comprehensive and a unified approach to managing data and infrastructure wherever it lives. From a customer's perspective, it could be at the edge, it could be in a coal. Oh, it could be in their data center or it could be a bunch of data services that are deployed within the public cloud. So now our customers with data services. Cloud console can manage the entire life cycle of their data from all the way from deployment, upgrading and optimizing it uh from a single console from anywhere in the world. Uh This console is designed to streamline data management with cloud data services that enable access to data. It allows for policy-based data protection, it allows for an organizational wide search on top of your storage assets. And we deliver basically a 360° visibility to all your data from a single console that the customer can experience from anywhere. So, so if you look at the journey the way we're deciding to deliver this. So the first, in its first incarnation, uh Data services, Cloud console gives you infrastructure and cloud data services to start to do data management along with that. But this is that foundation that we are placing in front of our customers, the SAS console, through which we get touch our customers on a daily basis. And now as our customers get access to the SAAS platform on the back end, we will continue to roll in additional services throughout the years on a true SAS based innovation base for our customers. And and these services can will be will be ranging all the way from data protection to multiple out data management, all the way to visibility all the way to understanding the context of your data as it's stored across your enterprise. And in addition to that, we're offering a consistent revised unified Api which allows for our customers to build automation against their storage infrastructure. Without ever worrying about that. As infrastructure changes, uh, the A. P I proof points are going to break for them. That is never going to happen because they are going to be programming to a single SAS based aPI interface from now on. >>Right. And that brings in this idea of infrastructure as code because you talk about as a service to talk about Green Lake and and my question is always okay. Tell me what's behind that. And if and if and if and if you're talking about boxes and and widgets, that's a it's a problem. And you're not, you're talking about services and A P. I. S and microservices and that's really the future model and infrastructure is code and ultimately data as code is really part of that. So, All right. So you guys, I know some of your branding folks, you guys give deep thought to this. So the second part of the announcement is the new product brands and deep maybe you can talk about that a little bit. >>Sure. Ultimately delivering the cloud operational model requires cognitive data infrastructure and that has been engineered to be natively managed from the cloud. And that's why we have also introduced H. P. E. Electra. Omar, Can you perhaps described HB electro even more. >>Absolutely. Thank you. Sandy. Uh, so with with HB Electoral we're launching a new brand of cloud native hardware infrastructure to power our customers data all the way from edge to the core to the cloud. The releases are smaller models for the edge then at the same time having models for the data center and then expanding those services into the public cloud as well. Right. All these hardware devices, Electoral hardware devices are cloud native and powered by our data services. Cloud Council, we're announcing two models with this launch H. P. E Electoral 9000. Uh, this is for our mission critical workloads. It has its history and bases in H P E. Primera. It comes with 100% availability guarantee. Uh It's the first of its type in the industry. It comes with standard support contract, no special verb is required. And then we're also launching HB Electoral 6000. Uh These are based in our history of uh nimble storage systems. Uh These these are for business critical applications, especially for that mid range of the storage market, optimizing price, performance and efficiency. Both of these systems are full envy any storage powered by our timeless capabilities with data in place upgrades. And then they both deliver a unified infrastructure and data management experience through the data services, cloud console. Uh And and and at the back end unified Ai Ops experience with H P. E. Info site is seamlessly blended in along with the offering for our >>customers. So this is what I was talking about before. It's sort of not your grandfather's storage business anymore. This is this is this is something that is part of that, that unified vision, that layer that I talked about, the A. P. I. Is the program ability. So you're you're reaching into new territory here. Maybe you can give us an example of how the customers experience what that looks like. >>Excellent. Love to Dave. So essentially what we're doing is we're changing the storage experience to a true cloud operational model for our customers. These recent announcements that we just went through along with, indeed they expand the cloud experience that our customers get with storage as a service with HP Green Lake. So a couple of examples to make this real. So the first of all is simplified deployment. Uh So I t no longer has to go through complex startup and deployment processes. Now all you need to do is these systems shipped and delivered to the customer's data center. Operational staff just need to rack and stack and then leave connect the power cable, connect the network cable. And the job is done. From that point onwards, data services console takes over where you can onboard these systems, you can provision these systems if you have a pre existing organization wide security as well as standard profile setup in data services console, we can automatically apply those on your behalf and bring these systems online. From a customer's perspective, they can be anywhere in the world to onboard these systems, they could be driving in a car, they could be sitting on a beach. Uh And and you know, these systems are automatically on boarded through this cloud operational model which is delivered through the SAAS application for our customers. Another big example. All that I'd like to shed light on is intent based provisioning. Uh So Dave typically provisioning a workload within a data center is an extremely spreadsheet driven trial and error kind of a task. Which system do I land it on? Uh Is my existing sl is going to be affected which systems that loaded which systems are loaded enough that I put this additional workload on it and the performance doesn't take. All of these decisions are trial and error on a constant basis with cloud Data services console along with the electron new systems that are constantly in a loop back information feeding uh Typical analytics to the console. All you need to do is to describe the type of the workload and the intent of the workload in terms of block size S. L. A. That you would like to experience at that point. Data services console consults with intra site at the back end. We run through thousands of data points that are constantly being given to us by your fleet and we come back with a few recommendations. You can accept the recommendation and at that time we go ahead and fully deploy this workload on your behalf or you can specify a particular system and then people try to enforce the S. L. A. On that system. So it completely eliminates the guesswork and the planning that you have to do in this regard. Uh And last but not the least. Uh You know, one of the most important things is, you know, upgrades has been a huge problem for our customers. Uh And typically oftentimes when you're not in this constant, you know, loop back communication with your customers. It often is a big challenge to identify which release or which bug fix or which update goes on to which particular machine, all of that has been completely taken away from our customers and fully automated. Uh We run thousands of signatures across are installed base. We identify which upgrades need to be curated for which machines in a fleet for a particular customer. And then if it applies to that customer we presented, and if the customer accepts it, we automatically go ahead and upgrade the system and and and last, but not the least from a global management perspective. Now, a customer has an independent data view of their data estate, independent from a storage estate and data services. Council can blend the two to give a consistent view or you can just look at the fleet view or the data view. >>It's kind of the holy Grail. I mean I've been in this business a long time and I think I. T. People have dreamt about you know this kind of capability for for a long long time. I wonder if we could sort of stay on the customers for a moment here and and talk about what's enabled. Now. Everybody's talking digital transformation. I joke about the joke. Not funny. The force marched to digital with Covid. Uh and we really wasn't planned for but the customers really want to drive now that digital transfer some of them are on the back burner and now they're moving to the front burner. What are the outcomes that are that are enabled here? Omar. >>Excellent. So so on on a typical basis for a traditional I. T. Customer this cloud operational model means that you know information technology staff can move a lot faster and they can be a lot more productive on the things that are directly relevant to their business. They can get up to 99% of the savings back to spend more time on strategic projects or best of all spend time with their families rather than managing and upgrading infrastructure and fleets of infrastructure. Right for line of business owners, the new experience means that their data infrastructure can be presented can be provision where the self service on demand type of capability. Uh They necessarily don't have to be in the data center to be able to make those decisions. Capacity management, performance management, all of that is died in and presented to them wherever they are easy to consume. SaS based models and especially for data innovators, whether it's D B A s, whether it's data analysts, they can start to consume infrastructure and ultimately data as a code to speed up their app development because again, the context that we're bringing forward is the context of data decoupling it from. Actually, storage management, storage management and data management are now two separate domains that can be presented through a single console to tie the end to end picture for a customer. But at the end of the day, what we have felt is that customers really, really want to rely and move forward with the data management and leave infrastructure management to machine oriented task, which we have completely automated on their behalf. >>So I'm sure you've heard you got the memo about, you know, H H p going all in on as a service. Uh it is clear that the companies all in. How does this announcement fit in to that overall mission? Cindy >>dave We believe the future is edge to cloud and our mission is to be the edge to cloud platform as a service company and as as HB transforms HP Green Lake is our unified cloud platform. Hp Green Link is how we deliver cloud services and agile cloud experiences to customers applications and data across the edge to cloud. With the storage announcement that we made recently, we announced that we're expanding HB Green Lake with as a service transformation of the HPV storage business to a cloud native software defined data services business. And this expands storage as a service, delivering full cloud experience to our customers data across edge and on prem environment across the board were committed to being a strategic partner for every one of our customers and helping them accelerate their digital transformation. >>Yeah, that's where the puck is going guys. Hey as always great conversation with with our friends from HP storage. Thanks so much for the collaboration and congratulations on the announcements and and I know you're not done yet. >>Thanks. Dave. Thanks. Dave. >>Thanks. Dave. It's a pleasure to be here. >>You're very welcome. And thank you for being with us for hp. You discovered 2021 you're watching the cube, the leader digital check coverage. Keep it right there, but right back. >>Yeah. Yeah.

>>mhm Yes, everyone, welcome back to the cubes coverage of dr khan 2021. I'm john for your host of the cube. Got a great segment here. One of the big supporters and open source amazon web services returning back second year. Dr khan virtual Deepak Singh, vice president of the compute services at AWS Deepak, Great to see you. Thanks for coming back on remotely again soon. We'll be in real life. Reinvent is going to be in person, we'll be there. Good to see you. >>Good to see you too, john it's always good to do these. I don't know how how often I've been at the cube now, but it's great every single time your >>legend and getting on there, a lot of important things to discuss your in one of the most important areas in the technology industry right now and that is at the confluence of cloud scale and modern development applications as they shift towards as Andy Jassy says, the new guard, right. It's been happening. You guys have been a big proponent of open source and enabling open source is a service creating business models for companies. But more importantly, you guys are powering, making it easier for folks to use software. And doctor has been a big relationship for you. Could you take a minute to first talk about the doctor, a W S relationship and your involvement and what you're doing? >>Yeah, actually it goes back a long way. Uh you know, Justin, we announced PCS had reinvented 2014 and PCS at that time was very much managed orchestration service on top of DACA at that time. I think it was the first really big one out there from a cloud provider. And since then, of course, the world has evolved quite a bit and relationship with DR has evolved a lot. The thing I'd like to talk to is something that we announced that Dr last year, I don't remember if I talked about it on the cube at that time. But last year we started working with DR on how can we go from doctor Run, which customers love or DR desktop, which customers love and make it easy for people to run containers on pcs and Fergie. Uh so most new customers running containers and AWS today start with this Yes and party or half of them and we wanted to make it very easy for them to start with where they are on the laptop which is often bucket to stop and have running services the native US. So we started working with DR and that that collaboration has been very successful. We want to keep you look forward to continuing to work on evolving that where you can use Docker compose doctor, desktop, doctor run the fuel that darker customers used and the labour grand production services on the end of your side, which is the part that we've got that on. So I think that's one area where we work really well together. Uh, the other area where I think the two companies continue to work well together. It's open source in general as some of, you know, AWS has a very strong commitment to contain a. D uh, EKS our community service is moving towards community. Forget it actually runs all on community today and uh, we collaborate dr Rhonda on the Ocr specification because, you know, the Oc I am expect is becoming the de facto packaging format idea. W S. This morning we launched yesterday, we launched a service called Opera. And the main expected input for opera is an Ocr image are being in this Atlanta as well, where those ci images now a way of packaging for lambda. And I think the last one I like to call out and it has been an amazing partnership and it's an area where most people don't pay attention is amid signing. Uh, there's a project called Notary. We do the second version of the Notary Spec for remit signing and AWS Docker and a couple of other companies have been working very closely together on bringing that uh, you know, finalizing no tv too, so that at least in our case we can start building services for our customers on top of that. You know, it's it's a great relationship and I expect to see it continue. >>Well, I think one of the themes this year is developer experience. So good. Good call out there in the new announcements on the tools you have and software because that seems to be a great developer integration with Docker question I have for you is how should the customers think about things like E C. S and versus E K. S. App, Runner lambda uh for kind of running their containers. How do they understand the difference is, what's there? What's the, what's the thought process there? What's >>that? It's a good question actually been announced after. And I think there was one of the questions I started getting on twitter. You know, let's start at the very beginning. Anyone can pick up a Docker container and run it on easy to today. You can run it on easy to, we can run a light sail, but doc around works just fine. It's the limits machine. Then people want to do more complex things. They want to run large scale orchestrated services. They won't run their entire business and containers. We have customers will do that today. Uh, you know, you have people like Vanguard who runs a significant portion of the infrastructure on pcs frg or you have to elope with the heavy user of chaos, our community service. So in general, if you're running large scale systems, you're building your platforms, you're most likely to use the csny Chaos. Um, if you come from a community's background, you're, you're running communities on prem or you want the flexibility and control the communities gives you, you're gonna end up with the chaos. That's what we see our customers doing. If you just want to run containers, you want to use AWS to its fullest extent where you want the continue a P I to be part of the W A S A P. I said then you pick is yes. And I think one of the reasons you see so many customers start with the CSN, Forget is with forget to get the significant ease of use from an operational standpoint. And we see many start ups and you know, enterprises, especially security focus enterprises leaning towards farming. But there's a class of customers that doesn't want to think about orchestration that just wants. Here's my code, here's my container image just run my service for me and that's when things like happen, I can come and that's one of the reasons we launched it. Land is a little bit different. Lambda is a unique service. You buy into an event driven architecture. If you do that, then you can figure our application into this. That's they should start its magic. Uh, the container part, there is what land announced agreement where they now support containers, packaging. So instead of zip files, you can package up your functions as containers. Then lambda will run them for you. The advantage it gives you with all the tooling that you built, that you have to build your containers now works the land as well. So I won't call and a container orchestration service in the same sense of the CSC cso Afrin are but it definitely allows the container image format as a standard packaging format. I think that's the sort of universal common theme that you find across AWS at this point of time. >>You know, one of the things that we're observing at this at this event here is a lot of developers Coop con and Lennox foundations. A lot of operators to kubernetes hits that. But here's developers. And the thing is I want to ease of use, simplicity experience, but also I want the innovation. Yeah, I want all of it. When I ask you what is amazon bring to the table for the new equation, what would you say? >>Yeah, I mean for me it's always you've probably heard me say this 100 times. Many 1000 times. It's foggy fog. It's unique to us. It takes a lot of what we have learned about operating infrastructure scale. The question we asked ourselves, you know, in many ways we talk about forget even before belong pcs but we have to learn on what it meant and what customers really wanted. But the idea was when you are running clusters of instances of machines to run containers on, you have to start thinking about a lot of things that in some ways VMS but BMS in the car were taken away capacity. What kind of infrastructure to run it on? Should have been touched. Should have not been back. You know, where is my container running? Those are things. They suddenly started having to think about those kind of backwards almost. So the idea was how can we make your containerized bundles? So TCS task or community is part of the thing that you talk to and that is the main unit that you operate on. That is the unit that you get built on and meet it on. That's where Forget comes in and it allows us to do many interesting things. We've effectively changed the engine of forget since we've launched it. Uh, we run it on ec two instances and we run it on fire cracker. Uh, we have changed the forget agent architecture. We've made a lot of underneath the hood, uh, changes that even take the take advantage of the broader innovation, the rate of us, We did a whole bunch more to launch acronym trans on top of family customers don't have to think about it. They don't have to worry about it. It happens underneath the hood. It's always your engine as as you go along and it takes away all the operational pain of managing clusters of running into picking which instances to use to getting out, trying to figure out how to bend back and get efficiency. That becomes our problem. So, you know, that is an area where you should expect to see a Stuart done more. It's becoming the fabric of so many things that eight of us now. Uh, it's, you know, in some ways we're just talking a lot more to do. >>Yeah. And it's a really good time. A lot more wave of developers coming in. One of the things that we've been reporting on on Silicon England cube with our cute videos is more developers keep on coming on, more people coming in and contributing to the open source community. Even end users, not just the normal awesome hyper scholars you're talking about like classic, I call main street enterprises. So two things I want to ask you on the customer side because you have kind of to customers, you have the community that open source community and you have enterprise customers that want to make it easier. What are you seeing and hearing from customers? I know you guys work backwards from the customer. So I got to ask you work backwards from the community and work backwards from the enterprise customer. What's going on in their environment? What's the key trends that they're riding? What's the big challenges? What's the big opportunities that they're facing and saying for the community? >>Yeah, I start with the enterprise. That's almost an easier answer. Which is, you know, we're seeing increasingly enterprises moving into the cloud wholesale. Like in some ways you could argue that the pandemic has just accelerated it, but we have started seeing that before. Uh they want to move to the cloud and adult modern best practices. Uh If you see my talk agreement last few years, I've talked about modernization and all the aspects of modernization, and that's 90% of our conversation with enterprises, I've walked into a meeting supposedly to talk about containers, whatever half a conversation is spent on. How does an organization modernize? What does an organization need to do to modernize and containers and serverless play a pretty important part in it, because it gives them an opportunity to step away from the shackles of sort of fixed infrastructure and the methods and approaches that built in. But equally, we are talking about C I C. D, you know, fully automated deployments. What does it mean for developers to run their own services? What are the child, how do you monitor and uh, instrument uh, your services? How do you do observe ability in the modern world? So those are the challenges that enterprises are going towards, and you're spending a ton of time helping them there. But many of them are still running infrastructure on premises. So, you know, we have outpost for them. Uh, you know, just last week, you're talking to a bunch of our customers and they have lots of interesting ideas and things that they want to do without both, but many of them also have their own infrastructure and that's where something like UCS anywhere came from, which is hey, you like using Pcs in the cloud, You like having the safety i that just orchestrates containers for you. It does it on on his in an AWS region. It will do it in an outpost. It'll do it on wavelength, it'll do it on local zone. How about we allow you to do it on whatever infrastructure you bring to us. Uh you want to bring a raspberry pi, you can do that. You want to bring your on premises data center infrastructure, we can do that or a point of sale device, as long as you can get the agent running and you can connect to an AWS region, even though it's okay to lose connectivity every now and then. We can orchestrate a container for you over there and, you know, the same customer that likes the ease of use of Vcs. And the simplicity really resonated with that message really resonates with them. So I think where we are today with the enterprise is we've got some really good solutions for you in eight of us and we are now allowing you to take those a. P. I. S and then launch containers wherever you want to run them, whether it's the edge or whether it's your own data center. I think that's a big part of where the enterprise is going. But by and large, I think yes, a lot of them are still making that change from running infrastructure and applications the way they used to do a modern sort of, if you want to use the word cloud native way and we're helping them a lot. We've done, the community is interesting. They want to be more participatory. Uh that's where things like co pilot comes from. God, honestly, the best thing we've ever done in my order is probably are open road maps where the community can go into the road map and engage with us over there, whether it's an open source project or just trying to tell us what the feature is and how they would like to see it. It's a great engagement and you know, it's not us a lot. It's helped us prioritize correctly and think about what we want to do next. So yeah, I think that's, that >>must be very hard to do for opening up the kimono on the road map because normally that's the crown jewels and its secretive and you know, and um, now it's all out in the open. I think that is a really interesting, um, experiment and what's your reaction to that? What's been the feedback on the road map peace? Because I mean, I definitely want to see, uh, >>we do it pretty much for every service in my organization and we've been doing it now for three years. So years forget, I think about three years and it's been great. Now we are very we are very upfront, which is security and availability. Our job 000 and you know, 100 times out of 100 at altitudes between a new feature and helping our customers be available and safe. We'll do that. And this is why we don't put dates in that we just tell you directionally where we are and what we are prioritizing Uh, there every now and then we'll put something in there that, you know, well not choose not to put a feature in there because we want to keep it secret until it launches. But for the most part, 99% of our own myself there and people engaged with it. And it's not proven to be a problem because you've also been very responsible with how we manage and be very transparent on whether we can commit to something or not. And I think that's not. >>I gotta ask you on as a leader uh threaded leader on this group. Open source is super important, as you know, and you continue to do it from under years. How are you investing in the future? What's your plan? Uh plans for your team, the industry actually very inclusive, Which is very cool. It's gonna resonate well, what's the plans? Give us some details on what you're investing in, what your priorities? What's your first principles? >>Yeah, So it goes in many ways, one when I I also have the luxury also on the amazon open source program office. So, you know, I get the chance to my team, rather not me help amazon engineers participate in open source. That that's the team that helps create the tools for them, makes it easy for them to contribute, creates, you know, manages all the licenses, etcetera. I'll give you a simple example, you know, in there, just think of the cr credential helper that was written by one of our engineers and he kind of distorted because he felt it was something that we needed to do. And we made it open source in general, in in many of our teams. The first question we asked is should something the open why is this thing not open source, especially if it's a utility or some piece of software that runs along with services. So they'll step one. But we've done some big things also, I, you know, a couple of years ago we launched Lennox operating system called bottle Rocket. And right from the beginning it was very clear to us that bottle Rocket was two things. It was both in AWS product. But first it was an open source project. We've already learned a little bit from what we've done at Firecracker. But making bottle rocket and open source operating system is very important. Anyone can take part of Rocket the open source to build tooling. You can run it whatever you want. If you want to take part of Rocket and build a version and manage it for another provider. For another provider wants to do it, go for it. There's nothing stopping you from doing that. So you'll see us do a lot there. Obviously there's multiple areas. You've seen WS investing on the open source side. But to me, the winds come from when engineers can participate in small things, released little helpers or get contributions from outside. I think that's where we're still, we can always have that. We're going to continue to strive to make it better and easier. And uh, you know, I said, I have, you know, me and my team, we have an opportunity to help their inside the company and we continue to do so. But that's what gets me excited. >>Yeah, that's great stuff. And congratulations on investing in the community, really enjoys it and I know it moves the needle for the industry. Deepak, I gotta ask you why I got you here. Dr khan obviously, developers, what's the most important story that they should be paying attention to as a developer because of what's going on shift left for security day two operations also known as a I ops getups, whatever you wanna call it, you know, ongoing, you get server lists, you got land. I mean, all kinds of great things are going on. You mentioned Fargate, >>um >>what should they be paying attention to that's going to really help their life, both innovation wise and just the quality of life. >>Yeah, I would say look at, you know, in the end it is very easy developers in particular, I want to build the buildings and it's very easy to get tempted to try and get learn everything about something. You have access to all the bells and whistles and knobs, but in reality, if you want to run things you want to, you want to focus on what's important, the business application, that and you the application. And I think a lot of what I'll tell developers and I think it's a lot of where the industry is going is we have built a really solid foundation, whether it's humanity, so you CSN forget or you know, continue industries out there. We have very solid foundation that, you know, our customers and develop a goal of the world can use to build upon. But increasingly, and you know, they are going to provide tools that sort of take that wrap them up and providing a nice package solution After another great example, our collaboration, the doctor around Dr desktop are a great example where we get all the mark focus on the application and build on top of that and you can get so much done. I think that's one trend. You'll see more and more. Those things are no longer toys, their production grade systems that you can build real world applications on, even though they're so easy to use. The second thing I would add to that is uh, get uh, it is, you know, you can give it whatever name you want. There's uh, there's nuances there, but I actually think get up is the way people should be running the infrastructure, my virus in my personal, you know, it's something that we believe a lot in homicide as hard as you go towards immutable infrastructure, infrastructure, automation, we can get off plays a significant role. I think developers naturally gravitate towards it. And if you want to live in a world where development and operations are tightly linked, I think it after the huge role to play in that it's actually a big part of how we're planning to do things like yes, anywhere, for example, a significant player and that it would be a proton. I think get up will be a significant in the future of proton as well. So I think that's the other trend. If you wanted to pick a trend that people should pay attention. That's what I believe in a lot. >>Well you're an expert. So I want to get you a quick definition. What is get Ops, how would you define it? Because that's a big trend. What does it, what does that mean? >>Electricity will probably shoot me for getting this wrong. I tell you how I think about it. Which is, you know, in many cases, um, you when you're doing deployments are pushing a deployment getups is more of a full deployment. When you are pushing code to get depository, you have a system that knows that the event has happened and then pulls from there and triggers the thing as opposed to you telling it take I have this new piece of code now go deployed everywhere. So to me, the biggest changes that Two parts one is it's more for full mechanism where you're pulling because something has changed. So it needs systems like container orchestrators to keep them, you know, to keep them in sync. And the second part of the natural natural evolution of infrastructure score, which is basically everything is called the figures code. Infrastructure as code, code is code and everything is getting stored in that software repo and the software repo becomes your store of record and drives everything. Uh So for a glass of customers, that's going to be a pretty big deal. >>Yeah, when you're checking in code, that's again, it's like a compiler for the compiler, a container for the container, you've got things for each other. Automation is ultimately what we're talking about here. And that's to me where machine learning kicks in. So again, having this open source foundational fabric, as you said, forget out the muck or the undifferentiated heavy lifting. This is what we're talking about automation, isn't it? Deepak? >>Yes. I mean I said uh one thing where we hang our hat on is there's such good stuff out there in the world which we like to contribute to, but the thing we like to hang our hat on is how do you run this? How do you do it this in ways that you can uniquely bring capabilities to customers where there's things like nitro or things are nitro open stuff. Well, the fact that we have built up this operational infrastructure over the last in a decade plus or in the container space over the last seven years where we really really know how to run these things at scale and have made all the investments to make it easy to do. So that's that's where we have hanger hard keeping people safe, helping them only available applications, their new startup, that just completely takes off in over the weekend. For whatever reason, because, you know, you're the next hot thing on twitter and our goal is to support you whether you are, you know, uh enterprise that's moving from the main train or you are the next hot startup, that's you know, growing virally and uh, you know, we've done a lot to build systems help both sides and yeah, it's >>interesting if you sing about open source where it's come from, I mean I remember that base wouldn't open source wasn't open, I would be peddling software, there's a free copy of Linux, UNIX um in college and now it's all free. But I mean just what's changed now. It used to be just free software, download software. You got it now, it's a service. Service now can be monetized quickly. And what you guys are offering with AWS and cloud scale is you've done all these things as I don't have to have a developer. I get the benefits of the scale, I can bring my open source code to the table, make it a service integrated in with other services and be the next snowflake, be the next, you know, a company that could scale. And that is that's the that's the innovation, right? That's the this is a new phenomenon. So it also changes the business model. >>Yeah, actually you're you're quite right. Actually, I I like one more thing to it. But you look at how a lot of enterprises use containers today. Most of them are using something like this year, Symphony or GS to build an internal developer platform and internal developer portal. And then the question then becomes this hard to scale this modern and development practices to an entire organization. What is your big bank that's been around as thousands and thousands of ID stuff That may not all be experts are running communities running container is when you scale it out different systems that proton come into play. That was actually the inspiration is how do you help an organization where they're building these developer Portholes and developer infrastructure, developer platforms, How do you make it easy for them to build it? Be almost use it as a way to get these modern practices into the hands of all the business units, where they may not have the time to become experts at the modern ways of running infrastructure because they're busy doing other things. And I think you'll see the a lot more happening that space that's not happening in the open source community. There's proton, there's a bunch of interesting things happening here and be interesting to see how that evolves. >>And also, you know, the communal, communal aspect of not just writing code together, but succeeding, right, building something. I mean, that's when you start to see the commercial meets open kind of ethos of communal activity of working together and sharing a big part of this year's. Dakar Con is sharing not just running and shipping code but sharing. >>Yeah, I mean if you think about it uh Dockers original value was you build run and shit right? You use the same code to build it, you use the same code to ship it, the same sort of infrastructure interface and then you run it and that, you know, the fact that the doctor images such a wonderfully shareable entity uh that can run every girl is such a powerful and it's called the Ci Image. Now I still call him Dr images because it's just easier. But that to me like that is a big deal and I think it's becoming and become an even bigger deal over the years. I came from something before, Amazon has to work in The sciences and bioinformatics and you know, the ability to share codeshare dependencies, package all of that up in a container image is a big deal. It's what got me one of the reasons I got fascinated with container 78 years ago. So it will be interesting to see where all of systems. >>It's great, great stuff. Great success. And congratulations. Deepak, Great to always talk to you got a great finger on the pulse. You lead a really important organizations at AWS and you know, doctor has such a huge success with developers, even though the company has gone through kind of a uh change over and a pivot to what they're doing now. They're back to their open source roots, but they have millions and millions of developers use Docker and new developers are coming in dot net developers are coming in. Windows developers are coming in and and so it's no longer about Lennox anymore. It's about just coding. >>Yeah. And it's it's part of this big trend towards infrastructure, automation and and you know development and deployment practices that I think everyone is going to adopt faster than we think they will. But you know, companies like Doctor and opens those projects that they involved are critical in making that a lot easier for them. And then you know, folks like us get to build on top of that orbit them and make it even easier. >>Well, great testimony the doctor that you guys based your E C. S on Docker Doctor has a critical role in developing community. I run composed in their hub with dr desktop and we'll be watching amazon and and the community activity and see what kind of experiences you guys can bring to the table and continue that momentum. Thank you Deepak for coming on the >>cube. Thank you, john. That's always a pleasure. >>Okay. Mr cubes. Dr khan 2021 virtual coverage. I'm john for your host of the cube. Thanks for watching.

(digital music) >> Hello everyone. And welcome to theCUBE where we're covering the recent news from Hewlett Packard Enterprise Making Moves and Storage. And with me are Omer Asad, Vice President and General Manager for Primary Storage, HCI and Data Management at HPE and Sandeep Singh who's the Vice President of Storage Marketing at Hewlett Packard Enterprise. Gentlemen, welcome back to theCUBE. Great to see you both. >> Dave its a pleasure to be here. >> Always a pleasure talking to you Dave thank you so much. >> Oh, it's my pleasure. Hey, so we just watched HPE make a big announcement and I wonder Sandeep, if you could give us a quick recap. >> Yeah, of course Dave. In the world of enterprise storage there hasn't been a moment like this in decades, a point at which everything is changing for data and infrastructure and it's really coming at the nexus of data, cloud and AI that's opening up the opportunity for customers across industries to accelerate their data-driven transformation. Building on that we just unveiled a new vision for data that accelerates the data driving transformation for customers edge to cloud. And to pay that off we introduce a new data services platform that consists of two game-changing innovations. First it's a data services cloud console which is a SaaS based console that delivers cloud operational agility for customers. And it's designed to unify data operations through a suite of cloud services. Though our second announcement is HPE Electra. HPE Electra is a cloud native data infrastructure portfolio to power your data edge to cloud. It's managed natively with data services cloud console and it brings that cloud operational model to customers wherever their data lives. These innovations are really combined with our industry leading AIOPS platform which is HPE InfoSight and combine these innovations radically simplify and bring that cloud operational model to customers our data and infrastructure management. And it gives the opportunity for streamlining data management across the life cycle. These innovations are making it possible for organizations across the industries to unleash the power of data. >> That's kind of cool. There're a lot of the stuff we've been talking about for all these years is sort of this unified layer across all clouds on-prem, AI injected in I could tell you're excited and it sounds like you you can't wait to get these offerings in the hands of customers, but I wonder we get back up a minute. Omer, maybe you could describe the problem statement that you're addressing with this announcement. What are customers really pain points? >> Excellent question, Dave. So in my role, as the General Manager for Data Management and Storage here at HPE I get the wonderful opportunity to talk to hundreds of customers in a year. And, you know, as time has progressed as the amount of data under organizations' management has continued to increase, what I have noticed is that recently there are three main themes that are continuously emerging and are now bubbling at the top. The first one is storage infrastructure management itself is extremely complex for customers. While there have been lots of leaps and down progress in managing a single array or managing two arrays with a lot of simplification of the UI and maybe some modern UIs are present but as the problem starts to get at scale as customers acquire more and more assets to store and manage their data on premise the management at scale is extremely complex. Yes, storage has gotten faster, yes, flash has had a profound effect on performance availability and latency access to the data but infrastructure management and storage management as a whole has become a pain for customers and it's a constant theme as storage lifecycle management comes up storage refresh has come up and deploying and managing storage infrastructure at scale comes up. So that's one of the main problems that I've been seeing as I talk to customers. Now, secondly, a lot of customers are now talking about two different elements. One is storage and storage deployment and life cycle management. And the second is the management of data that is stored on those storage devices. As the amount of data grows the silos continue to grow a single view of life cycle management of data doesn't, you know, customers don't get to see it. And lastly, one of the biggest things that we see is a lot of customers are now asking, how can I extract a value from this data under my management because they can't seem to parse through the silos. So there is an incredible amount of productivity lost when it comes to data management as a whole, which is just fragmented into silos, and then from a storage management. And when you put these two together and especially add two more elements to it which is hybrid management of data or a multicloud management of data the silos and the sprawl just continues and there is nothing that is stitching together this thing at scale. So these are the three main themes that constantly appear in these discussions. Although in spite of these a lot of modern enhancements in storage >> Well, I wonder if I could comment guys 'cause I've been following this industry for a number of years and you're absolutely right, Omer. I mean, if you look at the amount of money and time and energy that's spent into or put into the data architectures people are frustrated they're not getting enough out of it. And I'd note that, you know, the prevailing way in which we've attacked complexity historically is you build a better box. And well, while that system was maybe easier to manage than the predecessor systems all it did is create another silo and then the cloud, despite its impaired simplicity that was another disconnected siloed. So then we threw siloed management solutions at the problem and we're left with this collection of point solutions with data sort of trapped inside. So I wonder if you could give us your thoughts on that and you know, do you agree, what data do you have around this problem statement? >> Yeah, Dave that's a great point. And actually ESG just recently conducted a survey of over 250 IT decision makers. And that actually brings one of the perfect validations of the problems that Omer and you just articulated. What it showed is that 93% of the respondents indicated that storage and data management, that complexity is impeding their digital transformation. On average, the organizations have over 23 different data management tools which just typifies and is a perfect showcase of the fragmentation and the complexity that exists in that data management. And 95% of the respondents indicated that solving storage and data management that complexity is a top 10 business initiative for them. And actually top five for 67% of the respondents. So it's a great validation across the board. >> Well, its fresh in their minds too, because pre pandemic there was probably, you know, a mixed picture, right. It was probably well there's complacency or we're not moving fast enough, we have other priorities, but they were forced into this. Now they know what the real problem is it's front and center. Yeah, I liked that you're putting out there in your announcement this sort of future state that you're envisioning for customers. And I wonder if we could sort of summarize that and share with our listeners that vision that you unveiled what does it look like and how are you making it real? >> Yeah, overall, we feel very strongly that it's time for our customers to reimagine data management. And our vision is that customers need to break down the silos and complexity that plagues the distributed data environments. And they need to experience a new data experience across the board that's going to help them accelerate their data-driven transformation and we call this vision Unified DataOps. Unified DataOps integrates data-centric policies across the board to streamline data management, cloud-native control and operations to bring that agility of cloud and the operational model to wherever data lives. And AI driven insights and intelligence to make the infrastructure invisible. It delivers a whole new experience to customers to radically simplify and bring the agility of cloud to data and data infrastructure, streamlined data management and really help customers innovate faster than ever before. And we're making the promise of Unified DataOps real by transforming the entire HPE storage business to a cloud native software defined data services and that's through introducing a data services platform that expands HPE GreenLake. >> I mean, the key word I take away there Sandeep, is invisible. I mean, as a customer I want you to abstract that complexity away that underlying infrastructure complexity I just don't want to see it anymore. Omer, I wonder if we could start with the first part of the announcement maybe you can help us unpack data services, cloud console. I mean, you know, people are immediately going to think it's just another software product to manage infrastructure. But to really innovate, I'm hoping that it's more than that. >> Absolutely, Dave, it's a lot more than that. What we have done fundamentally at the root of the problem is we have taken the data and infrastructure control away from the hardware and through that, we provided a unified approach to manage the data wherever it lives. It's a full blown SaaS console which our customers get onto and from there they can deploy appliances, manage appliances, lifecycle appliances and then they not only stop at that but then go ahead and start to get context around their data. But all of that (indistinct) available through a SaaS platform, a SaaS console as every customer onboards themselves and their equipment and their storage infrastructure onto this console then they can go ahead and define role-based access for different parts of their organization. They can also apply role-based access to HPE GreenLake management personnel so they can come in and do and perform all the operations for the customers via the same console by just being another access control methodology in that. And then in addition to that, as you know, data mobility is extremely important to our customers. How do you make data available in different hyperscaler clouds if the customer's digital transformation requires that? So again, from that single cloud console from that single data console, which we are naming here as data services console customers are able to curate the data, maneuver the data, pre-positioned the data into different hyperscalers. But the beautiful thing is that the entire view of the storage infrastructure, the data with its context that is stored on top of that access control methodologies and management framework is operational from a single SaaS console which the customer can decide to give access to whichever management entity or authority comes into help them. And then what this leads us into is then combining these things into a northbound API. So anybody that wants to streamline operational manageability can then use these APIs to program against a single API which will then control the entire infrastructure on behalf of the customer. So if somebody dare what this is it is bringing that cloud operational model that was so desired by each one of our customers into their data centers and this is what I call an in-place transformation of a management experience for our customer by making them seamlessly available on a cloud operational model for their infrastructure. >> Yeah, and you've turned that into essentially an API with a lot of automation, that's great. So, okay. So that's kind of how you're trying to change the game here you're charting new territory. I want you to talk, you talked to hundreds and hundreds of customers every year I wonder if you could paint a picture from the customer perspective how does their experience actually change? >> Right, that's a wonderful question, Dave. This allows me to break it down into bits and bytes further for you and I love that, right. So the way you look at it is, you know, recently if you look at the storage management, as we talked about earlier, from an array perspective or maybe two arrays perspective has been simplified I mean, it's a solved problem. But when you start to imagine deploying hundreds of arrays and these are large customers, they have massive amounts of data assets, storage management hasn't scaled along as the infrastructure scales. But if you look at the consumer world you can have hundreds of devices but the ownership model is completely (indistinct). So the inspiration for solving this problem for us actually was inspired from consumerization of IT and that's a big trend over here. So now we're changing the customer's ownership model, the customer's deployment model and the customer's data management model into a true cloud first model. So let me give some of the examples of that, right. So first of all, let's talk about deployment. So previously deployment has been a massive challenge for our customers. What does deployment in this new data services console world looks like? Devices show up, you rack them up and then you plug in the power cable, you plug in the network cable and then you walk out of the data center. Data center administrator or the storage of administrator they will be on their iPad, on their data services console, or iPhone or whatever the device of their choice is and from that console, from that point on the device will be registered, onboarded, its initial state will be given to it from the cloud. And if the customer has some predefined States for their previous deployment model already saved with the data console they don't even need to do that we'll just take that and apply that state and induct the device into the fleet that's just one example. It's extremely simple plug in the power cable, plug in the network cable and the data center operational manager just walks out. After that you could be on the beach, you could be at your home, you could be driving in a car and this don't, I advise people not to fiddle with their iPhones when they're driving in a car, but still you could do it if you want to, right. So that's just one part from a deployment methodology perspective. Now, the second thing that, you know, Sandeep and I often bounce ideas on is provisioning of a workload. It's like a science these days. And is this array going to be able to absorb my workload, is the latency going to go South does this workload latency profile match this particular piece of device in my data center? All of this is extremely manual and it literally takes, I mean, if you talk to any of the customers or even analysts, deploying a workload is a massive challenge. It's a guesswork that you have to model and, you know basically see how it works out. I think based on HPE InfoSight, we're collecting hundreds and millions of data points from all these devices. So now to harness that and present that back to a customer in a very simple manner so that we can model on their behalf to the data services console, which is now workload of it, you just describe your workload, hey, I'm going to need these many IOPS and by the way, this happens to be my application. And that's it. On the backend because we're managing your infrastructure the cloud console understands your entire fleet. We are seeing the statistics and the telemetric coming off of your systems and because now you've described the workload for us we can do that matching for you. And what intent based provisioning does is describe your workloads in two or three clicks or maybe two or three API construct formats and we'll do the provisioning, the deployment and bringing it up for you on your behalf on the right pieces of infrastructure that matched it. And if you don't like our choices you can manually change it as well. But from a provisioning perspective I think that took days can now come down to a couple of minutes of the description. And lastly, then, you know, global data management distributed infrastructure from edge to cloud, invisible upgrades, only upgrading the right amount of infrastructure that needs the upgrade. All of that just comes rolling along with it, right. So those are some of the things that this data services console as a SaaS management and scale allows you to. >> And actually, if I can just jump in and add a little bit of what Omer described, especially with intent-based provisioning, that's really bringing a paradigm shift to provisioning. It's shifting it from a LAN-centric to app-center provisioning. And when you combine it with identity management and role-based access what it means is that you're enabling self-service on demand provisioning of the underlying data infrastructure to accelerate the app workload deployments. And you're eliminating guesswork and providing the ability to be able to optimize service level objectives. >> Yeah, it sounds like you've really nailed that in an elegant way that provisioning challenge. I've been saying for years if your primary expertise is deploying logical unit numbers you better find some other scales because the day is coming that that's just going to get automated away. So that's cool. There's another issue that I'm sure you've thought about but I wonder if you could address, I mean, you've got the cloud, the definition of cloud is changing that the cloud is expanding to on-prem on-prem expand to the cloud. It's going out to the edge, it's going across clouds and so, you know, security becomes a big issue that threat surface is expanding, the operating model is changing. So how are you thinking about addressing those security concerns? >> Excellent question, Dave. So, you know, most of the organizations that we talked to in today's modern world, you know almost every customer that I talk to has deployed either some sort of a cloud console where they're either one of the customers were the hyperscalers or you know, buy in for SaaS-based applications or pervasive across the customer base. And as you know, we were the first ones to introduce the automatic telemeter management through HPE InfoSight that's one of the largest storage SaaS services in production today that we operate on behalf of our customers, which has, you know, Dave, about 85% connectivity rate. So from that perspective, keeping customer's data secure, keeping customer's telemetry information secure we're no stranger to that. Again, we follow all security protocols that any cloud operational SaaS service would do. So a reverse handling, the firewall compliancy security audit logs that are published to our customers and published to customers' chief information security officers. So all of those, you know what I call crossing the T's and dotted the I's we do that with security expert and security policies for which each of our customers has a different set of rules. And we have a proper engagement model that we go through that particular audit process for our customers. Then secondly, Dave the data services cloud console is actually built on a fundamental cloud deployment technology that is not sort of that new. Aruba Central which is an Aruba management console which is also an HPE company it's been deployed and it's managing millions of access points in a SaaS framework for our customers. So the fundamental building blocks of the data storage console from a basic enablement perspective come from the Aruba Central console. And what we've taken is we've taken those generic cloud-based SaaS services and then built data and storage centric SaaS services on top of that and made them available to our customers. >> Yeah, I really like the Aruba. You picked that up several years ago and it's same thing with InfoSight the way that you bring it to other parts of the portfolio those are really good signs to watch of successful acquisitions. All right, there's a lot here. I want to talk about the second part of the announcement. I know you're a branding team you guys are serious about branding that new product brand. Maybe you could talk about that. >> So again, so delivering the cloud operational model is just the first piece, right. And now the second part of the announcement is delivering the cloud native hardware infrastructure which is extremely performing to go along with this cloud operational model. So what we have done Dave, in this announcement is we've announced HPE Electra. This is our new brand for our cloud native infrastructure to power your data and its appliances from core to the edge, to the cloud, right. And what it does is it takes the cloud operational model and this hardware is powered by that, it's completely wrapped around data. And so HPE Electra is available in two models right now, the HB electron 9,000 which is available for mission critical workloads for those high intensity workloads with a hundred percent availability guarantee where no failure is ever an option. And then it's also available as HPE Electra, 6,000 which is available for general purpose, business critical workloads generally trying to address that mid range of the storage market. And both of these systems are full 100% NBME front and back. And they're powered by the same unified cloud management operational experience that the data cloud console provides. And what it does is it allows our customers to simplify the deployment model, it simplifies their management model and really really allows them to focus on the context, the data and their app diversity whereas data mobility, data connectivity, data management in a multicloud world is then completely obstructed from them. >> Dave: Yeah. >> Sandeep: And Dave. >> Dave: Go ahead, please. >> Just to jump in HPE Electra combined with data services cloud console is delivering a cloud experience that makes deploying and scaling the application workloads as simple as flipping a switch. >> Dave: Nice. >> It really does. And you know, I'm very comfortable in saying this you know, like HPE InfoSight, we were the first in the industry to bring AI-based elementary and support enabled metrics (indistinct). And then here with data services console and the hardware that goes with it we're just completely transforming the storage ownership and a storage management model. And for our customers, it's a seamless non-disruptive upgrade with fully data in place upgrade. And they transform to a cloud operational model where they can manage their infrastructure better where they are through a complete consumer grade SaaS console is again the first of its kind when you look at storage management and storage management at scale. >> And I like how you're emphasizing that management layer, but underneath you got all the modern hardware technologies too which is important because it's a performance got to be, you know, a good price performance. >> Absolutely. >> So now can we bring this back again to the customers what are the outcomes that this is going to enable for them? >> So I think Dave, the first and the foremost thing is as they scale their storage infrastructures they don't have to think it's really as simple as yeah, just send it to the data center, plug in the power cable, plug in the network cable and up it comes. And from that point onwards the life cycle and the device management aspect are completely abstracted by the data services console. All they have to focus is I just have new capacity available to me and when I have an application the system will figure it out for me where they need to deploy. So no more needing the guesswork, the Excel sheets of capacity management, you know the chargeback models, none of that stuff is needed. And for customers that are looking to transform their applications customers looking to refactor their applications into a hyperscaler model or maybe transform from VM to containers, all they need to think about and focus is on that the data will just follow these workloads from that perspective. >> And Dave, just to almost response here as I speak with customers one of the things I'm hearing from IT is that line of business really wants IT to deliver that agility of cloud yet IT also has to deliver all of the enterprise reliability, availability, all of the data services. And what's fantastic here is that through this cloud operational model IT can deliver that agility, that line of business owners are looking for at the same time they've been under pressure to do a lot more with less. And through this agility, IT is able to get time back be able to focus more on the strategic projects at the same time, be able to get time back to spend more time with their families that's incredibly important. >> Omer: Right >> Well, I love the sort of mindset shift that I'm seeing from HPE we're not talking about how much the box weighs (laughing) we're talking about the customer experience. And I wonder, you know, that kind of leads me, Sandeep to how this kind of fits in to this new really, to me, I'm seeing the transformation before our eyes but how does it fit into HPE's overall mission? >> Well, Dave, our mission overall is to be the edge to cloud platform as a service company with HPE GreenLake, being the key to delivering that cloud experience. And as Omer put it, be able to deliver that cloud experience wherever the customer's data lives. And today we're advancing HPE GreenLake as a service transformation of the HPE storage business to a software defined cloud data services business overall. And for our customers, this translates to how to operational and ownership experience that unleashes their agility, their data and their innovation. So we're super excited >> Guys, I can tell you're excited. Thanks so much for coming to theCUBE and summarizing the announcements, congratulations and best of luck to both of you and to HPE and your customers. >> Thank you Dave. It was a pleasure. (digital music)