>> 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)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante aws is pointing the way to a revolution in system architecture much in the same way that aws defined the cloud operating model last decade we believe it is once again leading in future systems design the secret sauce underpinning these innovations is specialized designs that break the stranglehold of inefficient and bloated centralized processing and allows aws to accommodate a diversity of workloads that span cloud data center as well as the near and far edge hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll dig into the moves that aws has been making which we believe define the future of computing we'll also project what this means for customers partners and aws many competitors now let's take a look at aws's architectural journey the is revolution it started by giving easy access as we all know to virtual machines that could be deployed and decommissioned on demand amazon at the time used a highly customized version of zen that allowed multiple vms to run on one physical machine the hypervisor functions were controlled by x86 now according to werner vogels as much as 30 of the processing was wasted meaning it was supporting hypervisor functions and managing other parts of the system including the storage and networking these overheads led to aws developing custom asics that help to accelerate workloads now in 2013 aws began shipping custom chips and partnered with amd to announce ec2 c3 instances but as the as the aws cloud started to scale they really weren't satisfied with the performance gains that they were getting and they were hitting architectural barriers that prompted aws to start a partnership with anaperta labs this was back in 2014 and they launched then ec2 c4 instances in 2015. the asic in c4 optimized offload functions for storage and networking but still relied on intel xeon as the control point aws aws shelled out a reported 350 million dollars to acquire annapurna in 2015 which is a meager sum to acquire the secret sauce of its future system design this acquisition led to a modern version of project nitro in 2017 nitro nitro offload cards were first introduced in 2013 at this time aws introduced c5 instances and replaced zen with kvm and more tightly coupled the hypervisor with the asic vogels shared last year that this milestone offloaded the remaining components including the control plane the rest of the i o and enabled nearly a hundred percent of the processing to support customer workloads it also enabled a bare metal version of the compute that spawned the partnership the famous partnership with vmware to launch vmware cloud on aws then in 2018 aws took the next step and introduced graviton its custom designed arm-based chip this broke the dependency on x86 and launched a new era of architecture which now supports a wide variety of configurations to support data intensive workloads now these moves preceded other aws innovations including new chips optimized for machine learning and training and inferencing and all kinds of ai the bottom line is aws has architected an approach that offloaded the work currently done by the central processing unit in most general purpose workloads like in the data center it has set the stage in our view for the future allowing shared memory memory disaggregation and independent resources that can be configured to support workloads from the cloud all the way to the edge and nitro is the key to this architecture and to summarize aws nitro think of it as a set of custom hardware and software that runs on an arm-based platform from annapurna aws has moved the hypervisor the network the storage virtualization to dedicated hardware that frees up the cpu to run more efficiently this in our opinion is where the entire industry is headed so let's take a look at that this chart pulls data from the etr data set and lays out key players competing for the future of cloud data center and the edge now we've superimposed nvidia up top and intel they don't show up directly in the etr survey but they clearly are platform players in the mix we covered nvidia extensively in previous breaking analysis and won't go too deep there today but the data shows net scores on the vertical axis that's a measure of spending velocity and then it shows market share in the horizontal axis which is a measure of pervasiveness within the etr data set we're not going to dwell on the relative positions here rather let's comment on the players and start with aws we've laid out aws how they got here and we believe they are setting the direction for the future of the industry and aws is really pushing migration to its arm-based platforms pat morehead at the 6-5 summit spoke to dave brown who heads ec2 at aws and he talked extensively about migrating from x86 to aws's arm-based graviton 2. and he announced a new developer challenge to accelerate that migration to arm instances graviton instances and the end game for customers is a 40 better price performance so a customer running 100 server instances can do the same work with 60 servers now there's some work involved but for the by the customers to actually get there but the payoff if they can get 40 improvement in price performance is quite large imagine this aws currently offers 400 different ec2 instances last year as we reported sorry last year as we reported earlier this year nearly 50 percent of the new ec2 instances so nearly 50 percent of the new ec2 instances shipped in 2020 were arm based and aws is working hard to accelerate this pace it's very clear now let's talk about intel i'll just say it intel is finally responding in earnest and basically it's taking a page out of arm's playbook we're going to dig into that a bit today in 2015 intel paid 16.7 billion dollars for altera a maker of fpgas now also at the 6.5 summit nevin shenoy of intel presented details of what intel is calling an ipu it's infrastructure processing unit this is a departure from intel norms where everything is controlled by a central processing unit ipu's are essentially smart knicks as our dpus so don't get caught up in all the acronym soup as we've reported it's all about offloading work and disaggregating memory and evolving socs system-on-chip and sops system on package but just let this sink in a bit a bit for a moment intel's moves this past week it seems to us anyway are designed to create a platform that is nitro like and the basis of that platform is a 16.7 billion dollar acquisition just compare that to aws's 350 million dollar tuck-in of annapurna that is incredible now chenoy said in his presentation rough quote we've already deployed ipu's using fpgas in a in very high volume at microsoft azure and we've recently announced partnerships with baidu jd cloud and vmware so let's look at vmware vmware is the other you know really big platform player in this race in 2020 vmware announced project monterrey you might recall that it's based on the aforementioned fpgas from intel so vmware is in the mix and it chose to work with intel most likely for a variety of reasons one of the obvious ones is all the software that's running on on on vmware it's been built for x86 and there's a huge install base there the other is pat was heading vmware at the time and and you know when project monterey was conceived so i'll let you connect the dots if you like regardless vmware has a nitro like offering in our view its optionality however is limited by intel but at least it's in the game and appears to be ahead of the competition in this space aws notwithstanding because aws is clearly in the lead now what about microsoft and google suffice it to say that we strongly believe that despite the comments that intel made about shipping fpgas and volume to microsoft that both microsoft and google as well as alibaba will follow aws's lead and develop an arm-based platform like nitro we think they have to in order to keep pace with aws now what about the rest of the data center pack well dell has vmware so despite the split we don't expect any real changes there dell is going to leverage whatever vmware does and do it better than anyone else cisco is interesting in that it just revamped its ucs but we don't see any evidence that it has a nitro like plans in its roadmap same with hpe now both of these companies have history and capabilities around silicon cisco designs its own chips today for carrier class use cases and and hpe as we've reported probably has some remnants of the machine hanging around but both companies are very likely in our view to follow vmware's lead and go with an intel based design what about ibm well we really don't know we think the best thing ibm could do would be to move the ibm cloud of course to an arm-based nitro-like platform we think even the mainframe should move to arm as well i mean it's just too expensive to build a specialized mainframe cpu these days now oracle they're interesting if we were running oracle we would build an arm-based nitro-like database cloud where oracle the database runs cheaper faster and consumes less energy than any other platform that would would dare to run oracle and we'd go one step further and we would optimize for competitive databases in the oracle cloud so we would make oci run the table on all databases and be essentially the database cloud but you know back to sort of fpgas we're not overly excited about about the market amd is acquiring xi links for 35 billion dollars so i guess that's something to get excited about i guess but at least amd is using its inflated stock price to do the deal but we honestly we think that the arm ecosystem will will obliterate the fpga market by making it simpler and faster to move to soc with far better performance flexibility integration and mobility so again we're not too sanguine about intel's acquisition of altera and the moves that amd is making in in the long term now let's take a deeper look at intel's vision of the data center of the future here's a chart that intel showed depicting its vision of the future of the data center what you see is the ipu's which are intelligent nixed and they're embedded in the four blocks shown and they're communicating across a fabric now you have general purpose compute in the upper left and machine intelligent on the bottom left machine intelligence apps and up in the top right you see storage services and then the bottom right variation of alternative processors and this is intel's view of how to share resources and go from a world where everything is controlled by a central processing unit to a more independent set of resources that can work in parallel now gelsinger has talked about all the cool tech that this will allow intel to incorporate including pci and gen 5 and cxl memory interfaces and or cxl memory which are interfaces that enable memory sharing and disaggregation and 5g and 6g connectivity and so forth so that's intel's view of the future of the data center let's look at arm's vision of the future and compare them now there are definite similarities as you can see especially on the right hand side of this chart you've got the blocks of different process processor types these of course are programmable and you notice the high bandwidth memory the hbm3 plus the ddrs on the two sides kind of bookending the blocks that's shared across the entire system and it's connected by pcie gen 5 cxl or ccix multi-die socket so you know you may be looking to say okay two sets of block diagrams big deal well while there are similarities around disaggregation and i guess implied shared memory in the intel diagram and of course the use of advanced standards there are also some notable differences in particular arm is really already at the soc level whereas intel is talking about fpgas neoverse arms architecture is shipping in test mode and we'll have end market product by year end 2022 intel is talking about maybe 2024 we think that's aspirational or 2025 at best arm's road map is much more clear now intel said it will release more details in october so we'll pay attention then maybe we'll recalibrate at that point but it's clear to us that arm is way further along now the other major difference is volume intel is coming at this from a high data center perspective and you know presumably plans to push down market or out to the edge arm is coming at this from the edge low cost low power superior price performance arm is winning at the edge and based on the data that we shared earlier from aws it's clearly gaining ground in the enterprise history strongly suggests that the volume approach will win not only at the low end but eventually at the high end so we want to wrap by looking at what this means for customers and the partner ecosystem the first point we'd like to make is follow the consumer apps this capability the capabilities that we see in consumer apps like image processing and natural language processing and facial recognition and voice translation these inference capabilities that are going on today in mobile will find their way into the enterprise ecosystem ninety percent of the cost associated with machine learning in the cloud is around inference in the future most ai in the enterprise and most certainly at the edge will be inference it's not today because it's too expensive this is why aws is building custom chips for inferencing to drive costs down so it can increase adoption now the second point is we think that customers should start experimenting and see what you can do with arm-based platforms moore's law is accelerating at least the outcome of moore's law the doubling of performance every of the 18 to 24 months it's it's actually much higher than that now when you add up all the different components in these alternative processors just take a look at apple's a5 a15 chip and arm is in the lead in terms of performance price performance cost and energy consumption by moving some workloads onto graviton for example you'll see what types of cost savings you can drive for which applications and possibly generate new applications that you can deliver to your business put a couple engineers in the task and see what they can do in two or three weeks you might be surprised or you might say hey it's too early for us but you'll find out and you may strike gold we would suggest that you talk to your hybrid cloud provider as well and find out if they have a nitro we shared that vmware they've got a clear path as does dell because they're you know vmware cousins what about your other strategic suppliers what's their roadmap what's the time frame to move from where they are today to something that resembles nitro do they even think about that how do they think about that do they think it's important to get there so if if so or if not how are they thinking about reducing your costs and supporting your new workloads at scale now for isvs these consumer capabilities that we discussed earlier all these mobile and and automated systems and cars and and things like that biometrics another example they're going to find their way into your software and your competitors are porting to arm they're embedding these consumer-like capabilities into their apps are you we would strongly recommend that you take a look at that talk to your cloud suppliers and see what they can do to help you innovate run faster and cut costs okay that's it for now thanks to my collaborator david floyer who's been on this topic since early last decade thanks to the community for your comments and insights and hey thanks to patrick morehead and daniel newman for some timely interviews from your event nice job fellas remember i published each week on wikibon.com and siliconangle.com these episodes are all available as podcasts just search for breaking analysis podcasts you can always connect with me on twitter at d vallante or email me at david.velante at siliconangle.com i appreciate the comments on linkedin and clubhouse so follow us if you see us in a room jump in and let's riff on these topics and don't forget to check out etr.plus for all the survey data this is dave vellante for the cube insights powered by etr be well and we'll see you next time

>>From around the globe. It's the cube covering data citizens. 21 brought to you by Colibra >>Welcome to the cubes coverage of Collibra data citizens 21. I'm Lisa Martin. I have three guests with me here today. Colibra customer Freddie Mac, please welcome JAG chief data officer and vice president of single family data and decisions. Jog. Welcome to the cube. >>Thank you, Lisa. Look forward to be, >>Uh, excellent on Kiko LSU as well. Vice president data transformation and analytics solution on Kay. Good to have you on the program. >>Thank you, Lisa. Great to be here and >>A teeth Malik senior director from the single family division at Freddie Mac is here as well. A team welcome. So we have big congratulations in order. Uh, pretty Mac was just announced at data citizens as the winners of the Colibra excellence award for data program of the year. Congratulations on that. We're going to unpack that. Talk about what that means, but I'd love to get familiar with the 3d Jack. Start with you. Talk to me a little bit about your background, your current role as chief data officer. >>Appreciate it, Lisa, thank you for the opportunity to share our story. Uh, my name is Arvind calls me Jack. And as you said, I'm just single-family chief data officer at Freddie Mac, but those that don't know, Freddie Mac is a Garland sponsored entity that supports the U S housing finance system and single family deals with the residential side of the marketplace, as CDO are responsible for our managed content data lineage, data governance, business architecture, which Cleaver plays a integral role, uh, in, in depth, that function as well as, uh, support our shared assets across the enterprise and our data monetization efforts, data, product execution, decision modeling, as well as our business intelligence capabilities, including AI and ML for various use cases as a background, starting my career in New York and then moved to Boston and last 20 years of living in the Northern Virginia DC area and fortunate to have been responsible for business operations, as well as led and, um, executed large transformation efforts. That background has reinforced the power of data and how, how it's so critical to meeting our business objectives. Look forward to our dialogue today, Lisa, once again. >>Excellent. You have a great background and clearly not a dull moment in your job with Freddy, Matt. And tell me a little bit about your background, your role, what you're doing at Freddie >>Mac. Definitely. Um, hi everyone. I'm,, I'm vice president of data transformation and analytics solutions. And I worked for JAG. I'm responsible for many of the things he said, including leading our transformation to the cloud and migrating all our existing data assets front of that transformation journey. I'm also responsible for our business information and business data architecture, decision modeling, business intelligence, and some of the analytics and artificial intelligence. I started my career back in the day as a computer engineer, but I've always been in the financial industry up in New York. And now in the Northern Virginia area, I called myself that bridge between business and technology. And I would say, I think over the last six years with data found that perfect spot where business and technology actually come together to solve real problems and, and really lead, um, you know, businesses to the next stage of, so thank you Lisa for the opportunity today. Excellent. >>And we're going to unpack you call yourself the bridge between business and it that's always such an important bridge. We're going to talk about that in just a minute, but I want to get your background, tell our audience about you. >>Uh, I'm Alec Malek, I'm senior director of business, data architecture, data transformation, and Freddie Mac. Uh, I'm responsible for the overall business data architecture and transformation of the existing data onto the cloud data lake. Uh, my team is responsible for the Kleberg platform and the business analysts that are using and maintaining the data in Libra and also driving the data architecture in close collaboration with our engineering teams. My background is I'm a engineer at heart. I still do a lot of development. This is my first time as of crossing over onto the bridge onto business side of maintaining data and working with data teams. >>Jan, let's talk about digital transformation. Freddie Mac is a 50 year old and growing company. I always love talking with established businesses about digital transformation. It's pretty challenging. Talk to me about your initial plan and what some of the main challenges were that you were looking to solve. >>Uh, great question, Lisa, and, uh, it's definitely pertinent as you say, in our digital world or figuring out how we need to accomplish it. If I look at our data, modernization is it is a major program and, uh, effort, uh, in, in our, in our division, what started as a reducing cost or looking at an infrastructure play, moving from physical data assets to the cloud, as well as enhancing our resiliency as quickly morphed into meeting business demand and objectives, whether it be for sourcing, servicing or securitization of our loan products. So where are we as we think about creating this digital data marketplace, we are, we are basically forming, empowering a new data ecosystem, which Columbia is definitely playing a major role. It's more than just a cloud native data lake, but it's bringing in some of our current assets and capabilities into this new data landscape. >>So as we think about creating an information hub, part of the challenges, as you say, 50 years of having millions of loans and millions of data across multiple assets, it's frigging out that you still have to care and feed legacy while you're building the new highway and figuring out how you best have to transform and translate and move data and assets to this new platform. What we've been striving for is looking at what is the business demand or what is the business use case, and what's the value to help prioritize that transformation. Exciting part is, as you think about new uses of acquiring and distribution of data, as well as news new use cases for prescriptive and predictive analytics, the power of what we're building in our daily, this new data ecosystem, we're feeling comfortable, we'll meet the business demand, but as any CTO will tell you demand is always, uh, outpaces our capacity. And that's why we want to be very diligent in terms of our execution plan. So we're very excited as to what we've accomplished so far this year and looking forward as we offered a remainder year. And as you go into 2022. Excellent, >>Thanks JAG. Uh, two books go to you. As I mentioned in the intro of that Freddie Mac has won the Culebra excellence award for data program of the year. Again, congratulations on that, but I'd love to understand the Kleber center of excellence that you're building at Freddie Mac. First of all, define what a center of excellence is to Freddie Mac and then what you're specifically building. Yeah, sure. >>So the Cleaver center of excellence provides us the overall framework from a people and process standpoint to focus in on our use of Colibra and for adopting best practices. Uh, we can have teams that are focused just on developing best practices and implementing workflows and lineage within Collibra and implementing and adopting a number of different aspects of Libra. It provides the central hub of people being domain experts on the tool that can then be leveraged by different groups within the organization to maintain, uh, the tool. >>Put another follow on question a T for you. How does Freddie Mac define, uh, dated citizens as anybody in finance or sales or marketing or operations? What does that definition of data citizen? >>It's really everyone it's within the organization. They all consume data in different ways and we provide a way of governing data and for them to get a better understanding of data from Collibra itself. So it's really everyone within the organization that way. >>Excellent. Okay. Let's go over to you a big topic at data citizens. 21 is collaboration. That's probably a word that we used a ton in the last 15 plus months or so it was every business really pivoted quickly to figure out how do we best collaborate. But something that you talked about in your intro is being the bridge between business and it, I want to understand from your perspective, how can data teams help to drive improved collaboration between business and it, >>The collaboration between business and technology have been a key focus area for us over the last few years, we actually started an agile transformation journey two years ago that we called modern delivery. And that was about moving away from project teams to persistent product teams that brought business and technology together. And we've really been able to pioneer that in the data space within Freddie Mac, where we have now teams with product owners coming from the data team and then full stack ID developers with them creating these combined teams to meet the business needs. We found that bringing these teams together really remove the barriers that were there in the interaction and the employee satisfaction has been high. And like you said, over the last 16 months with the pandemic, we've actually seen the productivity stay same or even go up because the teams were all working together, they work as a unit and they all have the sense of ownership versus working on a project that has a finite end date to fail. So we've, um, you know, we've been really lucky with having started this two years ago. Well, and >>That's great. And congratulations about either maintaining productivity or having it go up during the last 16 months, which had been incredibly challenging. Jack. I want to ask you what does winning this award from Collibra what does this mean to you and your team and does this signify that you're really establishing a data first culture? >>Great question, Lisa again. Um, I think winning the award, uh, just from a team standpoint, it's a great honor. Uh, Kleber has been a fantastic partner. And when I think about the journey of going from spread sheets, right, that all of us had in the past to now having all our business class returns lineage, and really being at the forefront of our data monetization. So as we think about moving to the cloud Beliebers step in step with us in terms of our integral part of that holistic delivery model, when I ultimately, as a CDO, it's really the team's honor and effort, cause this has been a multi-year journey to get here. And it's great that Libra as a, as a partner has helped us achieve some of these goals, but also recognized, um, where we are in terms of, uh, as looking at data as a product and some of our, um, leading forefront and using that holistic delivery, uh, to, uh, to meet our business objectives. So overall poorly jazzed when, uh, we've been found that we wanted the data program here at Collibra and very honored, um, uh, to, to win this award. That's >>Where we got to bring back I'm jazzed. I liked that jug sticking with you, let's unpack a little bit, some of those positive results, those business outcomes that you've seen so far from the data program. What are those? >>Yeah. So again, if you were thinking about a traditional CDO model, what were the terms that would have been used few years ago? It was around governance and may have been viewed as an oversight. Um, maybe less talking, um, monetization of what it was, the business values that you needed to accomplish collectively. It's really those three building blocks managing content. You got to trust the source, but ultimately it's empowering the business. So the best success that I could say at Freddy, as you're moving to this digital world, it's really empowering the business to figure out the new capabilities and demand and objectives that we're meeting. We're not going to be able to transform the mortgage industry. We're not going to be able or any, any industry, if we're still stuck in old world thinking, and ultimately data is going to be the blood that has to enable those capabilities. >>So if you tell me the business best success, we're no longer talking a okay, I got my data governance, what do we have to do? It's all embedded together. And as I alluded to that partnership between business and it informing that data is a product where you now you're delivering capabilities holistically from program teams all across data. It's no longer an afterthought. As I said, a few minutes ago, you're able to then meet the demand what's current. And how do we want to think about going forward? So it's no longer buzzwords of digital data marketplace. What is the value of that? And that's what the success, I think if our group collectively working across the organization, it's just not one team it's across the organization. Um, and we have our partners, our operations, everyone from business owners, all swimming in the same direction with, and I would say critical management support. So top of the house, our, our head of business, my, my boss was the COO full supportive in terms of how we're trying to execute and I've makes us, um, it's critical because when there is a potential, trade-offs, we're all looking at it collectively as an organization, >>Right. And that's the best viewpoint to have is that sort of centralized unified vision. And as you say, JAG, the support from, from up top, uh, I'd see if I want to ask you, you establish the Culebra center of excellence. What are you focused on now? >>So we really focused in allowing our users to consume data and understand data and really democratizing data so that they can really get a better understanding of that. So that's a lot of our focus and engaging with Collibra and getting them to start to define things in Colibra law form. That's a lot of focus right now. >>Excellent. Want to stay with you one more question and take that I'm gonna ask to all of you, what are you most excited about a lot of success that you've talked about transforming a legacy institution? What are you most excited about and what are the next steps for the data program? Uh, teak what's are your thoughts? >>Yeah, so really modernizing onto, uh, onto a cloud data lake and allowing all of the users and, uh, Freddie Mac to consume data with the level of governance that we need around. It is a exciting proposition for me. >>What would you say is most exciting to you? >>I'm really looking forward to the opportunities that artificial intelligence has to offer, not just in the augmented analytics space, but in the overall data management life cycle. There's still a lot of things that are manual in the data management space. And, uh, I personally believe, uh, artificial intelligence has a huge role to play there. And Jackson >>Question to you, it seems like you have a really strong collaborative team. You have a very collaborative relationship with management and with Collibra, what are you excited about? What's coming down the pipe. >>So Lisa, if I look at it, you know, we sit back here June, 2021, where were we a year ago? And you think about a lot of the capabilities and some of the advancements that we may just in a year sitting virtually using that word jazzed or induced or feeling really great about. We made a lot of accomplishments. I'm excited what we're going to be doing for the next year. So there's other use cases, and I could talk about AIML and OCHA talks about, you know, our new ecosystem. Seeing those use cases come to fruition so that we're, we are contributing to value from a business standpoint. The organization is what really keeps me up. Uh, keeps me up at night. It gets me up in the morning and I'm really feeling dues for the entire division. Excellent. >>Well, thank you. I want to thank all three of you for joining me today. Talking about the successes that Freddie Mac has had transforming in partnership with Colibra again, congratulations on the Culebra excellence award for the data program. It's been a pleasure talking to all three of you. I'm Lisa Martin. You're watching the cubes coverage of Collibra data citizens 21.

>>10 years ago, a group of industry storage veterans formed a company called Infinidat. The DNA of the company was steeped in the heritage of its founder, Moshe Yanai, who had a reputation for relentlessly innovating on three main areas, the highest performance, rock solid availability, and the lowest possible cost. Now these elements have historically represented the superpower triumvirate of a successful storage platform. Now, as Infinidat evolved, landed on a fourth vector, that has been a key differentiator and its value proposition, and that is petabyte scale. Hello everyone. And welcome to this Qube conversation. My name is Dave Vellante and I'm pleased to welcome in two longtime friends of theCube. Phil Bullinger is newly minted CEO of Infinidat and of course, Lee Caswell, VMware's VP of Marketing for the cloud platform business unit. Gents, welcome. >>Great to be here. Always good to see you guys. Phil, so you're joining at the 10 year anniversary mark. Congratulations on the appointment. What attracted you to the company? >>You know I spent a long time in my career at enterprise storage and, and enjoying many of the opportunities, you know, through a number of companies. Last fall when I became aware of the Infinidat opportunity and it immediately captured my attention because of frankly my respect for the product through several opportunities I've had with enterprise customers in selling cycles of different products, if they happened to be customers of Infinidat, , they were not bashful about talking about their satisfaction with the product, their level of delight with it. And so I think from, from the sidelines, I've always had a lot of respect for the Infinidat platform, the implementation of the product quality and reliability that it's kind of legendary for. And so when the opportunity came along, it really captured my interest in of course behind a great product is almost always a great team. >>And as I got to know the company and the board, and, you know, some of the leaders, and learned about the momentum and the business, it was just a very, very compelling opportunity for me. And I'll have to say just, you know, 60 days into the job. Everything I hoped for is here, not only a warm welcome to the company, but an exciting opportunity with respect to where Infinidat is at today with the growth of the business. The company has achieved a level of consistent growth through 2020, cashflow positive, EBITDA positive. And now it's a matter of scaling, scaling the business and it's something that I have had success with several times in my career and really, really enjoying the opportunity here at Infinidat to do that. >>That's great. Thanks for that. Now, of course, Lee, VMware was founded nearly a quarter century ago and carved out a major piece of the enterprise pie and predominantly that's been on prem, but the data center's evolving the cloud is evolving, and this universe is expanding. How do you see the future of that on-prem data center? >>No, I think Satya recently said, right, that, that we've reached max consolidation almost right. You pointed that out earlier. I thought that was really interesting, right. You know, we believe in the distributed hybrid cloud and you know, the reasons for that actually turn out to be storage led in there and in, in the real thinking about it, because we're going to have distributed environments and, you know, one of the things that we're doing with Infinidat here today, right, is we're showing how customers can invest intelligently and responsibly on prem and have bridges in across the hybrid cloud. We do that through something called the VMware Cloud Foundation. That's a full stack offering that, uh, an interesting here, right? It started off with a HCI element, but it's expanded into storage and storage at scale, you know, because storage is going to exist... We have very powerful storage value propositions, and you're seeing customers go and deploy both. We're really excited about seeing Infinidat lean into the VMware Cloud Foundation and vVols actually as a way to match the pace of change in today's application world. >>These trends, I mean, building bridges is what we called it. And so that takes a lot of hard work, especially when you're doing from on-prem into hybrid, across clouds, eventually the edge, you know, that's a, that's a non-trivial task. How do you see this playing out in market trends? >>Yeah. You know, we're, we're in the middle of this every day as, as you know, Dave, uh, and certainly Lee, uh, data center architectures ebb and flow from centralized to decentralized, but clearly data locality, I think, is driving a lot of the growth of the distributed data center architecture, the edge data centers, but core is still very significant for, for most enterprise. Uh, and it's, it's, it has, it has a lot to do with the fact that most enterprises want to own their own cloud. You know, when a Fortune 15 or a Fortune 50 or Fortune 100 customer, when they talk about their cloud, they don't want to talk about, you know, the AWS cloud or the GCP cloud or the Azure cloud. They want to talk about their cloud. And almost always, these are hybrid architectures with a large on-prem or colo footprint. >>Uh, the reason for that number of reasons, right? Data sovereignty is a big deal, uh, among the highest priorities for enterprise today. The control of the security, the, the ability to recover quickly from ransomware attacks, et cetera. These, these are the things that are just fundamentally important, uh, to the business continuity and enterprise risk management plan for these companies. But I think one thing that has changed the on prem data center is the fact that it's the core operating characteristics have to take on kind of that public cloud characteristic. It has to be a transparent, seamless scalability. I think the days of, of CIO's  you know, even tolerating people showing up in their data centers with, with disk trays under their arms to add capacity is, is over. Um, they want to seamlessly add capacity. They want nonstop operation, a hundred percent uptime is the bar. >>Now it has to be a consolidation. Massive consolidation is clearly the play for TCO and efficiency. They don't want to have any compromises between scale and availability and performance. You know, the, the very characteristics that you talked about upfront, Dave, that make Infinidat unique, I think are fundamentally the characteristics that enterprises are looking for when they build their cloud on prem. Uh, I, I think our architecture also really does provide a, a set it and forget it, uh, kind of experience. Um, when we install a new Infinidat frame in an enterprise data center, our intentions are we're, we're not going to come back. We don't intend to come back, uh, to, to help fiddle with the bits or, uh, you know, tweak the configuration as applications and, and multitenant users are added. And then of course, flexible economic models. I mean, everybody takes this for granted, but you really, really do have to be completely flexible between the two rails, the CapEx rail and the OpEx rail and every, uh, every step in between. And importantly, when a customer, when an enterprise customer needs to add capacity, they don't have a sales conversation. They just want to have it right. They're already running in their data center. And that's the experience that we provide. >>Yeah. You guys are aligned in that vision, that layer, that abstracts the complexity from the underlying wherever cloud on prem, et cetera. Right. Let's talk about the VMware and Infinidat relationship. I mean, every, every year at VMworld, up until last year, thank you COVID, Infinidat would host this awesome dinner. You'd have the top customers there. Very nice Vegas steak restaurant. I, of course, I always made a point to stop by not just for the food. I mean, I was able to meet some customers and I've talked to many dozens over the years, Phil, and I can echo that sentiment, but, you know, why is the VMware ecosystem so important to Infinidat? And I guess the question there is, is, is petabyte scale that really that prominent in the VMware customer base? >>It's a, it's a very, very important point. VMware is the longest standing Alliance partner of Infinidat. It goes back to really, almost the foundation of the company, certainly starting with the release one, the very first commercial release of Infinidat VMware and a very tight integration with the VMware was a core part of that. Uh, we, we have a capability. We call the Host PowerTools, which drives a consistent best practices implementation around our, our VMware, uh, integration and, and how it's actually used in the data center. And we built on that through the years through just a deep level of integration. And, um, our customers typically are, are at scale petabyte scale or average deployment as a petabyte and up, um, and over 90% of our customers use VMware. So you would say, I, I think I can safely say we're we serve the VMware environment for some of VMware's largest enterprise footprints, uh, in the market. >>I know it's like children, you got, you love all your partners, but is there anything about Infinidat that, that stands out to you a particular area where, where they shine that from your perspective? >>Yeah, I think so. You know, the, the best partnerships, one are ones that are customer driven. It turns out right. And the idea that we have joint customers at large scale and listen storage is a tough business to get, right, right. It takes time to go and mature to harden a code base. Right. And particularly when you're talking about petabyte scale, right now, you've basically got customers buying in for the largest systems. And what we're seeing overall is customers are trying to do more things with fewer component elements, makes sense, right? And so the scale here is important because it's not just scale in terms of like capacity, right. It's scale in terms of performance as well. And so, as you see customers trying to expand the number of different types of applications, this is one of the things we're seeing, right. Is new applications, which could be container-based Kubernetes orchestrated our Tanzu portfolio helps with that. >>Right. If you see what we're doing with Nvidia, for example, we announced some AI work, right. Uh, this week with vSphere. And so what you're starting to see is like the changing nature of applications and the fast pace of applications is really helping customers save us. And I want to go and find solutions that can meet the majority of my needs. And that's one of the things that we're seeing. And particularly with the vVols integration at scale, that we just haven't seen before, uh, and Infinidat has set the bar and is really setting a new, a new record for that. >>Yeah. Let me, let me comment on that a little bit, Dave, we've been a core part of the VMware Cloud Solutions Lab, which is a very, very exciting engaging, investment that VMware has made. A lot of people have contributed to in the industry, but in the, in the VMware Cloud Solutions Lab, we recently demonstrated on a single Infinidat frame over 200,000 vVols on a single system. And I think that not only edges up the bar, I think it completely redefines what, what scale means when you're talking about a vVols implementation. >>So not to geek out here, but vVols, they're kind of a game changer because instead of admins, having to manually allocate storage to performance tiers. An array, that is VASA certified, VASA is VMware, or actually vStorage API for, for storage awareness, VASA, anyway, with vVols, you can dynamically provision storage that matches the way I say it as a match as device attributes to the data and the application requirements of the VM. So Phil,  it seems like so much in VMware land hearkens back to the way mainframes used to solve problems in a modern way. Right. And vVols is a real breakthrough in that regard in terms of storage. So, so how do you guys see it? I, I presume you're, you're sort of vVols certified based on what you just said in the lab. >>Yeah. We recently announced our vVols release and we're not the first to market with the vVols, but from, from the start of the engineering project, we wanted to do it. We wanted to do it the way we think. We think at scale in everything we do, and our customers were very prescriptive about the kind of scale and performance and availability that they wanted to experience in vVols. And we're now seeing quite a bit of customer interest with traction in it. Uh, as I said, we, we redefined the bar for vVols scalability. We support on a single array now, um, a thousand storage containers. Uh, and I think most of our competition is like at one or maybe 10 or 13 or something like that. So, uh, our customers are, again at scale, they said, if you're going to do vVols, we want it... We want it at scale. We want it to embody the characteristics of your, of your platform. We really liked vVols because it, it helps, it helps separate kind of the roles and responsibilities between the VI administrator and the storage system administrator. If you're going to put a majority of your most critical bits on Infinidat in your data center, you're going to want to, you're going to want to have control over how that resource is used, but yet the vVols mplementation and the tools that we provide with that deep level of integration, give the VI, the VI administrator, all of the flexibility they need to manage applications. And vVols of course gives the VI administrator the native use of our snapshot technology. And so it makes it incredibly easy for them to administrate the platform without having to worry about the physical infrastructure, but yet the people worried about the physical infrastructure still have control over that resource. So it's, it's a game changer as far as we're concerned. >>Yeah. Storage has come a long way. Hasn't it, Lee? I'm wondering if you could add some color here, it seems in talking to ... Uh, so that's interesting. You've had, you had a hand in the growth of vSAN and it was very successful product, but he chose Infinidat for that higher end application. It seems like vVols are a key innovation in that regard. How's the vVols uptake going from your perspective. >>Yeah, I think we you know, we're in the second phase of vVols adoption, right? First phase was, Hey, technically interesting, intriguing. Um, but adoption was relatively low, I think because, you know, up until five years ago, um, applications, weren't actually changing that fast. I mean, think about it, right? The applications, ERP systems, CRM systems, you weren't changing those at the pace of what we're doing today. Now what's happening is every business is a software business. Every business, when you work, when you interact with your healthcare provider right now, it's about the apps. Like, can you go and get your schedules online? Can you email your doctors? Right? Can you go and get your labs? Right? The pace of new application development, we have some data showing that there will be more apps developed in the next five years, and then the past 40 years of computing combined. >>And so when you think about that, what's changed now is trying to manage that all from the kind of storage hardware side was just actually getting in the way you want to organize around the fastest beat rate in your infrastructure today. That's the application. So what vVols has helped you do is it allows the vSphere administrator, who's managing VMs and looking at the apps and the changing pace, and be able to basically select storage attributes, including QoS, capacity, IOPS, and do that from the vCenter console, and then be able to rectify things and manage them right from the console right next to the apps. And that provides a really integrated way. So when you have a close interaction, like what we're talking about today, or, you know, integration, um, that the Infinidat has provided now, you've got this ability to have a faster moving activity. And, you know, consolidation is one of the themes you've heard from time to time from VMware, we're consolidating the management so that the vSphere administrator can now go and manage more things. What traditional VMs yes. VMs across HCI. Sure. Plus now, plus storage and into the hybrid cloud and into like containers. It's that consolidated management, which is getting us speed and basically a consumer like experience for infrastructure deployments. >>Yeah. Now Phil mentioned the solutions lab. We've got a huge ecosystem. Several years ago, you launched this, this via the VMware. I think it's called the VMware Cloud Solutions Lab is the official name. What, explain what it does for collaboration and joint solutions development. And then Phil, I want you to go into more detail about what your participation is, but Lee, why don't you explain it? >>Yeah. You know, we don't take just any products that, because listen, there's a mixing. What we take is things that really expand that innovation frontier. And that's what we saw with Infinidat was expanding the frontier on like large capacity for many, many different mixed workloads and a commitment, right. To go and bring in, not just vVols support, of course, all the things we do for just a normal interaction with vSphere. But, uh, bringing vVols in was certainly important in showing how we operate at scale. And then importantly, as we expanded the VCF, VMware Cloud Foundation, to include storagee systems for a customer, for example, right, who has storage and HCI, right? And it looks for how to go and use them. And that's an individual choice at a customer level. We think this is strategically important. Now, as we expand a multicloud experience, that's different from the hyperscalers. Hyperscalers are coming in with two kind of issues, maybe, right? So one is it's single cloud. And the other one is there's a potential competitive aspect or from some right around the ongoing, underlying business and a hyperscaler business model. And so what VMware uniquely is doing is extending a common control plane across storage systems and HCI, and doing that in a way that basically gives customers choice. And we love that the cloud lab is really designed to go and make that a reality for customers strip out perceived and real risk. >>Yeah. To Lee's point of, it's not like there's not dozens and dozens and dozens of logos on the slide for the lab. I think there's like, you know, 10 or 12 from what I saw and Infinidat is one of them. Maybe you could talk a little bit more about your participation in the program and what it does for customers. >>Yeah, absolutely. And I would agree it's I, we liked the lab because it's not just supposed to be one of everything eye candy it's a purpose-built lab to do real things. And we like it because we can really explore, you know, some of the most contemporary, workloads in that environment, as well as solutions to what I considered some of the most contemporary industry problems. We're participating in a couple of ways. I believe we're the only petabyte scale storage solution in the Cloud Solutions Lab at VMware. One of the projects we're working on with VMware is their machine learning platform.  That's one of the first cloud solutions lab projects that we worked on at Infinidat. And we're also a core part of, of what VMware is driving from a data for good initiative. This was inspired by the idea that that tech can be used as a force for good in the world. And right now it's focused on the technology needs of nonprofits. And so we're closely working in, in the cloud solutions lab with, the VMware cloud foundation layers, as well as, their Tanzu and Kubernetes environments and learning a lot and proving a lot. And it's also a great way to demonstrate the capabilities of our platform. >>Yeah. So, yeah, it was just the other day I was on the VMware analyst meeting virtually of course in Zane and Sanjay and a number of other execs were giving the update. And, and just to sort of emphasize what we've been talking about here, this expansion of on-prem the cloud experience, the data from, especially from our survey data, we have a partner UTR that did great surveys on a regular quarterly basis, the VMware cloud on AWS, doing great for sure, but the VMware Cloud Foundation, the on-prem cloud, the hybrid cloud is really exploding and resonating with customers. And that's a good example of this sort of equilibrium that we're seeing between the public and private coming together >>Well on the VMware Cloud Foundation right now with, uh, you know, over a thousand customers, but importantly over 400 of the global 2000, it's the largest customers. And that's actually where the Venn diagram between the work that VMware Cloud Foundation is doing and Infinidat right, you know, this large scale, actually the, you know, interesting crossover, right. And, you know, listen for customers to go and take on a new store system. We always know that it's a high bar, right. So they have to see some really unique value, like how is this going to help? Right. And today that value is I want to spend less time looking down at the storage and more time looking up at the apps, that's how we're working together. Right. And how vVols fits into that, you know, with the VMware Cloud Foundation, it's the hype that hybrid cloud offering really gives customers that future-proofing right. And the degrees of freedom they're most likely to exercise. >>Right. Well, let's close with a, kind of a glimpse of the future. What do you see as the future of the data center specifically, and also your, your collaborations Lee? Why don't you start? >>I think what we hope to be true is turning out to be true. So, you know, if you've looked at the, you know, what's happening in the cloud, not everything is migrating in the cloud, but the public cloud, for example, and I'm talking about public cloud there. The public cloud offers some really interesting, unique value and VMware is doing really interesting things about like DR as a service and other things, right? So we're helping customers tap into that at the same time. Right. We're seeing that the on-prem investment is not stalling at all because of data sovereignty because of bandwidth limitations. Right. And because of really the economics of what it means to rent versus buy. And so, you know, partnering with  leaders on, in storage, right, is a core part of our strategy going forward. And we're looking forward to doing more right with Infinidat, as we see VCF evolve, as we see new applications, including container based applications running on our platform, lots of futures, right. As the pace of application change, you know, doesn't slow down. >>So what do you see for the next 10 years for Infinidat? >>Yeah, well, um, we, I appreciated your introduction because of this speak to sort of the core characteristics of Infinidat. And I think a company like us and at our, at our juncture of evolution, it's important to know exactly who you are. And we clearly are focused in that on-prem hybrid data center environment. We want to be the storage tier that companies use to build their clouds. And, uh, the partnership with VMware, uh, we talked about the Venn diagram. I think it just could not be more complimentary. And so we're certainly going to continue to focus on VMware as our largest and most consequential Alliance partner for our business going forward. Um, I'm excited about, about the data center landscape going forward. I think it's going to continue to ebb and flow. We'll see growth in distributed architectures. We'll see growth at the edge in the core data center. >>I think the, the old, the old days where customers would buy a storage system for a application environment, um, those days are over, it's all about consolidating multiple apps and thousands of users on a single platform. And to do that, you have to be really good at, uh, at a lot of things that we are very good at. Our, our strategy going forward is to evolve as media evolves, but never stray far from what has made Infinidat unique and special and highly differentiated in the marketplace. I think the work that VMware is doing and in Kubernetes >>Is very exciting. We're starting to see that really pick up in our business as well. So as we think about, um, uh, you know, not only staying relevant, but keeping very contemporary with application workloads, you know, we have some very small amount of customers that still do some bare metal, but predominantly as I said, 90% or above is VMware infrastructure. Uh, but we also see, uh, Kubernetes, our CSI driver works well with the VMware suite above it. Uh, so that, that complimentary relationship we see extending forward as, as the application environment evolves. Great, thank you. You know, many years ago when I attended my first, uh, VMworld, the practitioners that were there, you talked to them, half the conversations, they were complaining about storage and how it was so complicated and you needed guys in lab coats to solve problems. And, you know, VMware really has done a great job, publishing the APIs and encouraging the ecosystem. And so if you're a practitioner you're interested in how vVols and Infinidat and VMware were kind of raising the bar and on petabyte scale, there's some good blogs out there. Check out the Virtual Blocks blog for more information, guys. Thanks so much great to have you in the program. Really appreciate it. Thanks so much. Thank you for watching this Cube conversation, Dave Vellante. We'll see you next time.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Okay, >>we're now going to explore the vision of the future of cloud computing From the perspective of one of the leaders in the field, J G >>Share >>a pure off is the vice president of As Your Data ai and Edge at Microsoft G. Welcome to the Cuban cloud. Thanks so much for participating. >>Well, thank you, Dave, and it's a real pleasure to be here with you. And I just wanna welcome the audience as well. >>Well, jg judging from your title, we have a lot of ground to cover, and our audience is definitely interested in all the topics that are implied there. So let's get right into it. You know, we've said many times in the Cube that the new innovation cocktail comprises machine intelligence or a I applied to troves of data. With the scale of the cloud. It's it's no longer, you know, we're driven by Moore's law. It's really those three factors, and those ingredients are gonna power the next wave of value creation and the economy. So, first, do you buy into that premise? >>Yes, absolutely. we do buy into it. And I think, you know, one of the reasons why we put Data Analytics and Ai together is because all of that really begins with the collection of data and managing it and governing it, unlocking analytics in it. And we tend to see things like AI, the value creation that comes from a I as being on that continues off, having started off with really things like analytics and proceeding toe. You know, machine learning and the use of data. Interesting breaks. Yes. >>I'd like to get some more thoughts around a data and how you see the future data and the role of cloud and maybe how >>Microsoft, you >>know, strategy fits in there. I mean, you, your portfolio, you got you got sequel server, Azure, Azure sequel. You got arc, which is kinda azure everywhere for people that aren't familiar with that. You've got synapse. Which course that's all the integration a data warehouse, and get things ready for B I and consumption by the business and and the whole data pipeline and a lot of other services as your data bricks you got You got cosmos in their, uh, Blockchain. You've got open source services like Post Dress and my sequel. So lots of choices there. And I'm wondering, you know, how do you think about the future of Of of Cloud data platforms? It looks like your strategies, right tool for the right job? Is that fair? >>It is fair, but it's also just to step back and look at it. It's fundamentally what we see in this market today is that customer was the Sikh really a comprehensive proposition? And when I say a comprehensive proposition, it is sometimes not just about saying that. Hey, listen way No, you're a sequel server company. We absolutely trust that you have the best Azure sequel database in the cloud, but tell us more. We've got data that's sitting in her group systems. We've got data that's sitting in Post Press in things like mongo DB, right? So that open source proposition today and data and data management and database management has become front and center, so are really sort of push. There is when it comes to migration management, modernization of data to present the broadest possible choice to our customers so we can meet them where they are. However, when it comes to analytics. One of the things they asked for is give us a lot more convergence use. You know it, really, it isn't about having 50 different services. It's really about having that one comprehensive service that is converged. That's where things like synapse Fitzer, where in just land any kind of data in the leg and then use any compute engine on top of it to drive insights from it. So, fundamentally, you know, it is that flexibility that we really sort of focus on to meet our customers where they are and really not pushing our dogma and our beliefs on it. But to meet our customers according to the way they have deployed stuff like this. >>So that's great. I want to stick on this for a minute because, you know, I know when when I have guests on like yourself, do you never want to talk about you know, the competition? But that's all we ever talk about. That's all your customers ever talk about, because because the counter to that right tool for the right job and that I would say, is really kind of Amazon's approach is is that you got the single unified data platform, the mega database that does it all. And that's kind of Oracle's approach. It sounds like you wanna have your cake and eat it, too, so you you got the right tool for the right job approach. But you've got an integration layer that allows you to have that converge database. I wonder if you could add color to that and you confirm or deny what I just said. >>No, that's a That's a very fair observation, but I I say there's a nuance in what I sort of describe when it comes to data management. When it comes to APS, we have them customers with the broadest choice. Even in that, even in that perspective, we also offer convergence. So, case in point, when you think about Cosmos TV under that one sort of service, you get multiple engines, but with the same properties, right global distribution, the five nines availability. It gives customers the ability to basically choose when they have to build that new cloud native AB toe, adopt cosmos Davey and adopted in a way that it's and choose an engine that is most flexible. Tow them, however you know when it comes to say, you know, writing a sequel server, for example from organizing it you know you want. Sometimes you just want to lift and shift it into things. Like I asked In other cases, you want to completely rewrite it, so you need to have the flexibility of choice there that is presented by a legacy off What's its on premises? When it moved into things like analytics, we absolutely believe in convergence, right? So we don't believe that look, you need to have a relation of data warehouse that is separate from a loop system that is separate from, say, a B I system. That is just, you know, it's a bolt on for us. We love the proposition off, really building things that are so integrated that once you land data, once you prep it inside the lake, you can use it for analytics. You can use it for being. You can use it for machine learning. So I think you know, are sort of differentiated. Approach speaks for itself there. Well, >>that's that's interesting, because essentially, again, you're not saying it's an either or, and you're seeing a lot of that in the marketplace. You got some companies say no, it's the Data Lake and others saying No, no put in the data warehouse and that causes confusion and complexity around the data pipeline and a lot of calls. And I'd love to get your thoughts on this. Ah, lot of customers struggled to get value out of data and and specifically data product builders of frustrated that it takes too long to go from. You know, this idea of Hey, I have an idea for a data service and it could drive monetization, but to get there, you gotta go through this complex data lifecycle on pipeline and beg people to add new data sources. And do you do you feel like we have to rethink the way that we approach data architectures? >>Look, I think we do in the cloud, and I think what's happening today and I think the place where I see the most amount of rethink the most amount of push from our customers to really rethink is the area of analytics in a I. It's almost as if what worked in the past will not work going forward. Right? So when you think about analytics on in the Enterprise today, you have relational systems, you have produced systems. You've got data marts. You've got data warehouses. You've got enterprise data warehouses. You know, those large honking databases that you use, uh, to close your books with right? But when you start to modernize it, what deep you are saying is that we don't want to simply take all of that complexity that we've built over say, you know, 34 decades and simply migrated on mass exactly as they are into the cloud. What they really want is a completely different way of looking at things. And I think this is where services like synapse completely provide a differentiated proposition to our customers. What we say there is land the data in any way you see shape or form inside the lake. Once you landed inside the lake, you can essentially use a synapse studio toe. Prep it in the way that you like, use any compute engine of your choice and and operate on this data in any way that you see fit. So, case in point, if you want to hydrate relation all data warehouse, you can do so if you want to do ad hoc analytics using something like spark. You can do so if you want to invoke power. Bi I on that data or b i on that data you can do so if you want to bring in a machine learning model on this breath data you can do so, so inherently. So when customers buy into this proposition, what it solves for them and what it gives them is complete simplicity, right? One way to land the data, multiple ways to use it. And it's all eso. >>Should we think of synapse as an abstraction layer that abstracts away the complexity of the underlying technology? Is that a fair way toe? Think about it. >>Yeah, you can think of it that way. It abstracts away, Dave a couple of things. It takes away the type of data, you know, sort of the complexities related to the type of data. It takes away the complexity related to the size of data. It takes away the complexity related to creating pipelines around all these different types of data and fundamentally puts it in a place where it can be now consumed by any sort of entity inside the actual proposition. And by that token, even data breaks. You know, you can, in fact, use data breaks in in sort off an integrated way with a synapse, Right, >>Well, so that leads me to this notion of and then wonder if you buy into it s Oh, my inference is that a data warehouse or a data lake >>could >>just be a node in inside of a global data >>mesh on. >>Then it's synapses sort of managing, uh, that technology on top. Do you buy into that that global data mesh concept >>we do. And we actually do see our customers using synapse and the value proposition that it brings together in that way. Now it's not where they start. Often times when a customer comes and says, Look, I've got an enterprise data warehouse, I want to migrate it or I have a group system. I want to migrate it. But from there, the evolution is absolutely interesting to see. I give you an example. You know, one of the customers that we're very proud off his FedEx And what FedEx is doing is it's completely reimagining its's logistics system that basically the system that delivers What is it? The three million packages a day on in doing so in this covert times, with the view of basically delivering our covert vaccines. One of the ways they're doing it is basically using synapse. Synapse is essentially that analytic hub where they can get complete view into their logistic processes. Way things are moving, understand things like delays and really put all that together in a way that they can essentially get our packages and these vaccines delivered as quickly as possible. Another example, you know, is one of my favorite, uh, we see once customers buy into it, they essentially can do other things with it. So an example of this is, uh is really my favorite story is Peace Parks Initiative. It is the premier Air White Rhino Conservancy in the world. They essentially are using data that has landed in azure images in particular. So, basically, you know, use drones over the vast area that they patrol and use machine learning on this data to really figure out where is an issue and where there isn't an issue so that this part with about 200 rangers can scramble surgically versus having to read range across the last area that they cover. So What do you see here is you know, the importance is really getting your data in order. Landed consistently. Whatever the kind of data ideas build the right pipelines and then the possibilities of transformation are just endless. >>Yeah, that's very nice how you worked in some of the customer examples. I appreciate that. I wanna ask you, though, that that some people might say that putting in that layer while it clearly adds simplification and e think a great thing that they're begins over time to be be a gap, if you will, between the ability of that layer to integrate all the primitives and all the peace parts on that, that you lose some of that fine grain control and it slows you down. What would you say to that? >>Look, I think that's what we excel at, and that's what we completely sort of buy into on. It's our job to basically provide that level off integration that granularity in the way that so it's an art, absolutely admit it's an art. There are areas where people create simplicity and not a lot of you know, sort of knobs and dials and things like that. But there are areas where customers want flexibility, right? So I think just to give you an example of both of them in landing the data inconsistency in building pipelines, they want simplicity. They don't want complexity. They don't want 50 different places to do this. Just 100 to do it. When it comes to computing and reducing this data analyzing this data, they want flexibility. This is one of the reasons why we say, Hey, listen, you want to use data breaks? If you're you're buying into that proposition and you're absolutely happy with them, you can plug plug it into it. You want to use B I and no, essentially do a small data mart. You can use B I If you say that. Look, I've landed in the lake. I really only want to use em melt, bringing your animal models and party on. So that's where the flexibility comes in. So that's sort of really sort of think about it. Well, >>I like the strategy because, you know, my one of our guest, Jim Octagon, e E. I think one of the foremost thinkers on this notion of off the data mesh and her premises that that that data builders, data product and service builders air frustrated because the the big data system is generic to context. There's no context in there. But by having context in the big data architecture and system, you could get products to market much, much, much faster. So but that seems to be your philosophy. But I'm gonna jump ahead to do my ecosystem question. You've mentioned data breaks a couple of times. There's another partner that you have, which is snowflake. They're kind of trying to build out their own, uh, data cloud, if you will, on global mesh in and the one hand, their partner. On the other hand, there are competitors. How do you sort of balance and square that circle? >>Look, when I see snowflake, I actually see a partner. You know that when we essentially you know, we are. When you think about as you know, this is where I sort of step back and look at Azure as a whole and in azure as a whole. Companies like snowflakes are vital in our ecosystem, right? I mean, there are places we compete, but you know, effectively by helping them build the best snowflake service on Asia. We essentially are able toe, you know, differentiate and offer a differentiated value proposition compared to, say, a Google or on AWS. In fact, that's being our approach with data breaks as well, where you know they are effectively on multiple club, and our opportunity with data breaks is toe essentially integrate them in a way where we offer the best experience. The best integrations on Azure Barna That's always been a focus. >>That's hard to argue with. Strategy. Our data with our data partner eat er, shows Microsoft is both pervasive and impressively having a lot of momentum spending velocity within the budget cycles. I wanna come back thio ai a little bit. It's obviously one of the fastest growing areas in our in our survey data. As I said, clearly, Microsoft is a leader in this space. What's your what's your vision of the future of machine intelligence and how Microsoft will will participate in that opportunity? >>Yeah, so fundamentally, you know, we've built on decades of research around, you know, around, you know, essentially, you know, vision, speech and language that's being the three core building blocks and for the for a really focused period of time we focused on essentially ensuring human parody. So if you ever wondered what the keys to the kingdom are it, czar, it's the most we built in ensuring that the research posture that we've taken there, what we then done is essentially a couple of things we focused on, essentially looking at the spectrum. That is a I both from saying that, Hollis and you know it's gotta work for data. Analysts were looking toe basically use machine learning techniques, toe developers who are essentially, you know, coding and building a machine learning models from scratch. So for that select proposition manifesto us, as you know, really a. I focused on all skill levels. The other court thing we've done is that we've also said, Look, it will only work as long as people trust their data and they can trust their AI models. So there's a tremendous body of work and research we do in things like responsibility. So if you ask me where we sort of push on is fundamentally to make sure that we never lose sight of the fact that the spectrum off a I, and you can sort of come together for any skill level, and we keep that responsibly. I proposition. Absolutely strong now against that canvas, Dave. I'll also tell you that you know, as edge devices get way more capable, right where they can input on the edge, see a camera or a mike or something like that, you will see us pushing a lot more of that capability onto the edge as well. But to me, that's sort of a modality. But the core really is all skill levels and that responsible denia. >>Yeah, So that that brings me to this notion of wanna bring an edge and and hybrid cloud Understand how you're thinking about hybrid cloud multi cloud. Obviously one of your competitors, Amazon won't even say the word multi cloud you guys have, Ah, you know, different approach there. But what's the strategy with regard? Toe, toe hybrid. You know, Do you see the cloud you bringing azure to the edge? Maybe you could talk about that and talk about how you're different from the competition. >>Yeah, I think in the edge from Annette, you know, I live in I'll be the first one to say that the word nge itself is conflated. Okay, It's, uh but I will tell you, just focusing on hybrid. This is one of the places where you know I would say the 2020 if I would have looked back from a corporate perspective. In particular, it has Bean the most informative because we absolutely saw customers digitizing moving to the cloud. And we really saw hybrid in action. 2020 was the year that hybrid sort of really became really from a cloud computing perspective and an example of this is we understood it's not all or nothing. So sometimes customers want azure consistency in their data centers. This is where things like Azure stack comes in. Sometimes they basically come to us and say, We want the flexibility of adopting flexible pattern, you know, platforms like, say, containers orchestra, Cuban Pettis, so that we can essentially deployed wherever you want. And so when we design things like art, it was built for that flexibility in mind. So here is the beauty of what's something like our can do for you. If you have a kubernetes endpoint anywhere we can deploy and as your service onto it, that is the promise, which means if for some reason, the customer says that. Hey, I've got this kubernetes endpoint in AWS and I love as your sequel. You will be able to run as your sequel inside AWS. There's nothing that stops you from doing it so inherently you remember. Our first principle is always to meet our customers where they are. So from that perspective, multi cloud is here to stay. You know, we're never going to be the people that says, I'm sorry, we will never see a But it is a reality for our customers. >>So I wonder if we could close. Thank you for that by looking, looking back and then and then ahead. And I wanna e wanna put forth. Maybe it's, Ah criticism, but maybe not. Maybe it's an art of Microsoft, but But first you know, you get Microsoft an incredible job of transitioning. It's business as your nominee president Azzawi said. Our data shows that so two part question First, Microsoft got there by investing in the cloud, really changing its mind set, I think, in leveraging its huge software state and customer base to put Azure at the center of its strategy, and many have said me included that you got there by creating products that air Good enough. You know, we do a 1.0, it's not that great. And the two Dato, and maybe not the best, but acceptable for your customers. And that's allowed you to grow very rapidly expanding market. >>How >>do you respond to that? Is that is that a fair comment? Ume or than good enough? I wonder if you could share your >>thoughts, gave you? You hurt my feelings with that question. I don't hate me, g getting >>it out there. >>So there was. First of all, thank you for asking me that. You know, I am absolutely the biggest cheerleader. You'll find a Microsoft. I absolutely believe you know that I represent the work off almost 9000 engineers and we wake up every day worrying about our customer and worrying about the customer condition and toe. Absolutely. Make sure we deliver the best in the first time that we do. So when you take the platter off products we've delivered in nausea, be it as your sequel, be it as your cosmos TV synapse as your data breaks, which we did in partnership with data breaks, a za machine learning and recently when we prevail, we sort off, you know, sort of offered the world's first comprehensive data government solution in azure purview. I would humbly submit to you that we're leading the way and we're essentially showing how the future off data ai and the actual work in the cloud. >>I'd be disappointed if you if you had If you didn't, if you capitulated in any way J g So so thank you for that. And the kind of last question is, is looking forward and how you're thinking about the future of cloud last decade. A lot about your cloud migration simplifying infrastructure management, deployment SAS if eyeing my enterprise, lot of simplification and cost savings. And, of course, the redeployment of resource is toward digital transformation. Other other other valuable activities. How >>do >>you think this coming decade will will be defined? Will it be sort of more of the same? Or is there Is there something else out there? >>I think I think that the coming decade will be one where customers start one law outside value out of this. You know what happened in the last decade when people leave the foundation and people essentially looked at the world and said, Look, we've got to make the move, you know, the largely hybrid, but we're going to start making steps to basically digitize and modernize our platforms. I would tell you that with the amount of data that people are moving to the cloud just as an example, you're going to see use of analytics ai for business outcomes explode. You're also going to see a huge sort of focus on things like governance. You know, people need to know where the data is, what the data catalog continues, how to govern it, how to trust this data and given all other privacy and compliance regulations out there. Essentially, they're complying this posture. So I think the unlocking of outcomes versus simply Hey, I've saved money Second, really putting this comprehensive sort off, you know, governance, regime in place. And then, finally, security and trust. It's going to be more paramount than ever before. Yeah, >>nobody's gonna use the data if they don't trust it. I'm glad you brought up your security. It's It's a topic that hits number one on the CEO list. J G. Great conversation. Obviously the strategy is working, and thanks so much for participating in Cuba on cloud. >>Thank you. Thank you, David. I appreciate it and thank you to. Everybody was tuning in today. >>All right? And keep it right there. I'll be back with our next guest right after this short break.

>> Okay, we're now going to explore the vision of the future of cloud computing from the perspective of one of the leaders in the field, JG Chirapurath is the Vice President of Azure Data AI and Edge at Microsoft. JG, welcome to theCUBE on Cloud, thanks so much for participating. >> Well, thank you, Dave. And it's a real pleasure to be here with you and just want to welcome the audience as well. >> Well, JG, judging from your title, we have a lot of ground to cover and our audience is definitely interested in all the topics that are implied there. So let's get right into it. We've said many times in theCUBE that the new innovation cocktail comprises machine intelligence or AI applied to troves of data with the scale of the cloud. It's no longer we're driven by Moore's law. It's really those three factors and those ingredients are going to power the next wave of value creation in the economy. So first, do you buy into that premise? >> Yes, absolutely. We do buy into it and I think one of the reasons why we put data analytics and AI together, is because all of that really begins with the collection of data and managing it and governing it, unlocking analytics in it. And we tend to see things like AI, the value creation that comes from AI as being on that continuum of having started off with really things like analytics and proceeding to be machine learning and the use of data in interesting ways. >> Yes, I'd like to get some more thoughts around data and how you see the future of data and the role of cloud and maybe how Microsoft strategy fits in there. I mean, your portfolio, you've got SQL Server, Azure SQL, you got Arc which is kind of Azure everywhere for people that aren't familiar with that you got Synapse which course does all the integration, the data warehouse and it gets things ready for BI and consumption by the business and the whole data pipeline. And then all the other services, Azure Databricks, you got you got Cosmos in there, you got Blockchain, you've got Open Source services like PostgreSQL and MySQL. So lots of choices there. And I'm wondering, how do you think about the future of cloud data platforms? It looks like your strategy is right tool for the right job. Is that fair? >> It is fair, but it's also just to step back and look at it. It's fundamentally what we see in this market today, is that customers they seek really a comprehensive proposition. And when I say a comprehensive proposition it is sometimes not just about saying that, "Hey, listen "we know you're a sequence of a company, "we absolutely trust that you have the best "Azure SQL database in the cloud. "But tell us more." We've got data that is sitting in Hadoop systems. We've got data that is sitting in PostgreSQL, in things like MongoDB. So that open source proposition today in data and data management and database management has become front and center. So our real sort of push there is when it comes to migration management modernization of data to present the broadest possible choice to our customers, so we can meet them where they are. However, when it comes to analytics, one of the things they ask for is give us lot more convergence use. It really, it isn't about having 50 different services. It's really about having that one comprehensive service that is converged. That's where things like Synapse fits in where you can just land any kind of data in the lake and then use any compute engine on top of it to drive insights from it. So fundamentally, it is that flexibility that we really sort of focus on to meet our customers where they are. And really not pushing our dogma and our beliefs on it but to meet our customers according to the way they've deployed stuff like this. >> So that's great. I want to stick on this for a minute because when I have guests on like yourself they never want to talk about the competition but that's all we ever talk about. And that's all your customers ever talk about. Because the counter to that right tool for the right job and that I would say is really kind of Amazon's approach is that you got the single unified data platform, the mega database. So it does it all. And that's kind of Oracle's approach. It sounds like you want to have your cake and eat it too. So you got the right tool with the right job approach but you've got an integration layer that allows you to have that converged database. I wonder if you could add color to that and confirm or deny what I just said. >> No, that's a very fair observation but I'd say there's a nuance in what I sort of described. When it comes to data management, when it comes to apps, we have then customers with the broadest choice. Even in that perspective, we also offer convergence. So case in point, when you think about cosmos DB under that one sort of service, you get multiple engines but with the same properties. Right, global distribution, the five nines availability. It gives customers the ability to basically choose when they have to build that new cloud native app to adopt cosmos DB and adopt it in a way that is an choose an engine that is most flexible to them. However, when it comes to say, writing a SequenceServer for example, if modernizing it, you want sometimes, you just want to lift and shift it into things like IS. In other cases, you want to completely rewrite it. So you need to have the flexibility of choice there that is presented by a legacy of what sits on premises. When you move into things like analytics, we absolutely believe in convergence. So we don't believe that look, you need to have a relational data warehouse that is separate from a Hadoop system that is separate from say a BI system that is just, it's a bolt-on. For us, we love the proposition of really building things that are so integrated that once you land data, once you prep it inside the Lake you can use it for analytics, you can use it for BI, you can use it for machine learning. So I think, our sort of differentiated approach speaks for itself there. >> Well, that's interesting because essentially again you're not saying it's an either or, and you see a lot of that in the marketplace. You got some companies you say, "No, it's the data lake." And others say "No, no, put it in the data warehouse." And that causes confusion and complexity around the data pipeline and a lot of cutting. And I'd love to get your thoughts on this. A lot of customers struggle to get value out of data and specifically data product builders are frustrated that it takes them too long to go from, this idea of, hey, I have an idea for a data service and it can drive monetization, but to get there you got to go through this complex data life cycle and pipeline and beg people to add new data sources and do you feel like we have to rethink the way that we approach data architecture? >> Look, I think we do in the cloud. And I think what's happening today and I think the place where I see the most amount of rethink and the most amount of push from our customers to really rethink is the area of analytics and AI. It's almost as if what worked in the past will not work going forward. So when you think about analytics only in the enterprise today, you have relational systems, you have Hadoop systems, you've got data marts, you've got data warehouses you've got enterprise data warehouse. So those large honking databases that you use to close your books with. But when you start to modernize it, what people are saying is that we don't want to simply take all of that complexity that we've built over, say three, four decades and simply migrate it en masse exactly as they are into the cloud. What they really want is a completely different way of looking at things. And I think this is where services like Synapse completely provide a differentiated proposition to our customers. What we say there is land the data in any way you see, shape or form inside the lake. Once you landed inside the lake, you can essentially use a Synapse Studio to prep it in the way that you like. Use any compute engine of your choice and operate on this data in any way that you see fit. So case in point, if you want to hydrate a relational data warehouse, you can do so. If you want to do ad hoc analytics using something like Spark, you can do so. If you want to invoke Power BI on that data or BI on that data, you can do so. If you want to bring in a machine learning model on this prep data, you can do so. So inherently, so when customers buy into this proposition, what it solves for them and what it gives to them is complete simplicity. One way to land the data multiple ways to use it. And it's all integrated. >> So should we think of Synapse as an abstraction layer that abstracts away the complexity of the underlying technology? Is that a fair way to think about it? >> Yeah, you can think of it that way. It abstracts away Dave, a couple of things. It takes away that type of data. Sort of complexities related to the type of data. It takes away the complexity related to the size of data. It takes away the complexity related to creating pipelines around all these different types of data. And fundamentally puts it in a place where it can be now consumed by any sort of entity inside the Azure proposition. And by that token, even Databricks. You can in fact use Databricks in sort of an integrated way with the Azure Synapse >> Right, well, so that leads me to this notion of and I wonder if you buy into it. So my inference is that a data warehouse or a data lake could just be a node inside of a global data mesh. And then it's Synapse is sort of managing that technology on top. Do you buy into that? That global data mesh concept? >> We do and we actually do see our customers using Synapse and the value proposition that it brings together in that way. Now it's not where they start, oftentimes when a customer comes and says, "Look, I've got an enterprise data warehouse, "I want to migrate it." Or "I have a Hadoop system, I want to migrate it." But from there, the evolution is absolutely interesting to see. I'll give you an example. One of the customers that we're very proud of is FedEx. And what FedEx is doing is it's completely re-imagining its logistics system. That basically the system that delivers, what is it? The 3 million packages a day. And in doing so, in this COVID times, with the view of basically delivering on COVID vaccines. One of the ways they're doing it, is basically using Synapse. Synapse is essentially that analytic hub where they can get complete view into the logistic processes, way things are moving, understand things like delays and really put all of that together in a way that they can essentially get our packages and these vaccines delivered as quickly as possible. Another example, it's one of my favorite. We see once customers buy into it, they essentially can do other things with it. So an example of this is really my favorite story is Peace Parks initiative. It is the premier of white rhino conservancy in the world. They essentially are using data that has landed in Azure, images in particular to basically use drones over the vast area that they patrol and use machine learning on this data to really figure out where is an issue and where there isn't an issue. So that this part with about 200 radios can scramble surgically versus having to range across the vast area that they cover. So, what you see here is, the importance is really getting your data in order, landing consistently whatever the kind of data it is, build the right pipelines, and then the possibilities of transformation are just endless. >> Yeah, that's very nice how you worked in some of the customer examples and I appreciate that. I want to ask you though that some people might say that putting in that layer while you clearly add simplification and is I think a great thing that there begins over time to be a gap, if you will, between the ability of that layer to integrate all the primitives and all the piece parts, and that you lose some of that fine grain control and it slows you down. What would you say to that? >> Look, I think that's what we excel at and that's what we completely sort of buy into. And it's our job to basically provide that level of integration and that granularity in the way that it's an art. I absolutely admit it's an art. There are areas where people crave simplicity and not a lot of sort of knobs and dials and things like that. But there are areas where customers want flexibility. And so I think just to give you an example of both of them, in landing the data, in consistency in building pipelines, they want simplicity. They don't want complexity. They don't want 50 different places to do this. There's one way to do it. When it comes to computing and reducing this data, analyzing this data, they want flexibility. This is one of the reasons why we say, "Hey, listen you want to use Databricks. "If you're buying into that proposition. "And you're absolutely happy with them, "you can plug it into it." You want to use BI and essentially do a small data model, you can use BI. If you say that, "Look, I've landed into the lake, "I really only want to use ML." Bring in your ML models and party on. So that's where the flexibility comes in. So that's sort of that we sort of think about it. >> Well, I like the strategy because one of our guests, Jumark Dehghani is I think one of the foremost thinkers on this notion of of the data mesh And her premise is that the data builders, data product and service builders are frustrated because the big data system is generic to context. There's no context in there. But by having context in the big data architecture and system you can get products to market much, much, much faster. So, and that seems to be your philosophy but I'm going to jump ahead to my ecosystem question. You've mentioned Databricks a couple of times. There's another partner that you have, which is Snowflake. They're kind of trying to build out their own DataCloud, if you will and GlobalMesh, and the one hand they're a partner on the other hand they're a competitor. How do you sort of balance and square that circle? >> Look, when I see Snowflake, I actually see a partner. When we see essentially we are when you think about Azure now this is where I sort of step back and look at Azure as a whole. And in Azure as a whole, companies like Snowflake are vital in our ecosystem. I mean, there are places we compete, but effectively by helping them build the best Snowflake service on Azure, we essentially are able to differentiate and offer a differentiated value proposition compared to say a Google or an AWS. In fact, that's been our approach with Databricks as well. Where they are effectively on multiple clouds and our opportunity with Databricks is to essentially integrate them in a way where we offer the best experience the best integrations on Azure Berna. That's always been our focus. >> Yeah, it's hard to argue with the strategy or data with our data partner and ETR shows Microsoft is both pervasive and impressively having a lot of momentum spending velocity within the budget cycles. I want to come back to AI a little bit. It's obviously one of the fastest growing areas in our survey data. As I said, clearly Microsoft is a leader in this space. What's your vision of the future of machine intelligence and how Microsoft will participate in that opportunity? >> Yeah, so fundamentally, we've built on decades of research around essentially vision, speech and language. That's been the three core building blocks and for a really focused period of time, we focused on essentially ensuring human parity. So if you ever wonder what the keys to the kingdom are, it's the boat we built in ensuring that the research or posture that we've taken there. What we've then done is essentially a couple of things. We've focused on essentially looking at the spectrum that is AI. Both from saying that, "Hey, listen, "it's got to work for data analysts." We're looking to basically use machine learning techniques to developers who are essentially, coding and building machine learning models from scratch. So for that select proposition manifest to us as really AI focused on all skill levels. The other core thing we've done is that we've also said, "Look, it'll only work as long "as people trust their data "and they can trust their AI models." So there's a tremendous body of work and research we do and things like responsible AI. So if you asked me where we sort of push on is fundamentally to make sure that we never lose sight of the fact that the spectrum of AI can sort of come together for any skill level. And we keep that responsible AI proposition absolutely strong. Now against that canvas Dave, I'll also tell you that as Edge devices get way more capable, where they can input on the Edge, say a camera or a mic or something like that. You will see us pushing a lot more of that capability onto the edge as well. But to me, that's sort of a modality but the core really is all skill levels and that responsibility in AI. >> Yeah, so that brings me to this notion of, I want to bring an Edge and hybrid cloud, understand how you're thinking about hybrid cloud, multicloud obviously one of your competitors Amazon won't even say the word multicloud. You guys have a different approach there but what's the strategy with regard to hybrid? Do you see the cloud, you're bringing Azure to the edge maybe you could talk about that and talk about how you're different from the competition. >> Yeah, I think in the Edge from an Edge and I even I'll be the first one to say that the word Edge itself is conflated. Okay, a little bit it's but I will tell you just focusing on hybrid, this is one of the places where, I would say 2020 if I were to look back from a COVID perspective in particular, it has been the most informative. Because we absolutely saw customers digitizing, moving to the cloud. And we really saw hybrid in action. 2020 was the year that hybrid sort of really became real from a cloud computing perspective. And an example of this is we understood that it's not all or nothing. So sometimes customers want Azure consistency in their data centers. This is where things like Azure Stack comes in. Sometimes they basically come to us and say, "We want the flexibility of adopting "flexible button of platforms let's say containers, "orchestrating Kubernetes "so that we can essentially deploy it wherever you want." And so when we designed things like Arc, it was built for that flexibility in mind. So, here's the beauty of what something like Arc can do for you. If you have a Kubernetes endpoint anywhere, we can deploy an Azure service onto it. That is the promise. Which means, if for some reason the customer says that, "Hey, I've got "this Kubernetes endpoint in AWS. And I love Azure SQL. You will be able to run Azure SQL inside AWS. There's nothing that stops you from doing it. So inherently, remember our first principle is always to meet our customers where they are. So from that perspective, multicloud is here to stay. We are never going to be the people that says, "I'm sorry." We will never say (speaks indistinctly) multicloud but it is a reality for our customers. >> So I wonder if we could close, thank you for that. By looking back and then ahead and I want to put forth, maybe it's a criticism, but maybe not. Maybe it's an art of Microsoft. But first, you did Microsoft an incredible job at transitioning its business. Azure is omnipresent, as we said our data shows that. So two-part question first, Microsoft got there by investing in the cloud, really changing its mindset, I think and leveraging its huge software estate and customer base to put Azure at the center of it's strategy. And many have said, me included, that you got there by creating products that are good enough. We do a one Datto, it's still not that great, then a two Datto and maybe not the best, but acceptable for your customers. And that's allowed you to grow very rapidly expand your market. How do you respond to that? Is that a fair comment? Are you more than good enough? I wonder if you could share your thoughts. >> Dave, you hurt my feelings with that question. >> Don't hate me JG. (both laugh) We're getting it out there all right, so. >> First of all, thank you for asking me that. I am absolutely the biggest cheerleader you'll find at Microsoft. I absolutely believe that I represent the work of almost 9,000 engineers. And we wake up every day worrying about our customer and worrying about the customer condition and to absolutely make sure we deliver the best in the first attempt that we do. So when you take the plethora of products we deliver in Azure, be it Azure SQL, be it Azure Cosmos DB, Synapse, Azure Databricks, which we did in partnership with Databricks, Azure Machine Learning. And recently when we premiered, we sort of offered the world's first comprehensive data governance solution in Azure Purview. I would humbly submit it to you that we are leading the way and we're essentially showing how the future of data, AI and the Edge should work in the cloud. >> Yeah, I'd be disappointed if you capitulated in any way, JG. So, thank you for that. And that's kind of last question is looking forward and how you're thinking about the future of cloud. Last decade, a lot about cloud migration, simplifying infrastructure to management and deployment. SaaSifying My Enterprise, a lot of simplification and cost savings and of course redeployment of resources toward digital transformation, other valuable activities. How do you think this coming decade will be defined? Will it be sort of more of the same or is there something else out there? >> I think that the coming decade will be one where customers start to unlock outsize value out of this. What happened to the last decade where people laid the foundation? And people essentially looked at the world and said, "Look, we've got to make a move. "They're largely hybrid, but you're going to start making "steps to basically digitize and modernize our platforms. I will tell you that with the amount of data that people are moving to the cloud, just as an example, you're going to see use of analytics, AI or business outcomes explode. You're also going to see a huge sort of focus on things like governance. People need to know where the data is, what the data catalog continues, how to govern it, how to trust this data and given all of the privacy and compliance regulations out there essentially their compliance posture. So I think the unlocking of outcomes versus simply, Hey, I've saved money. Second, really putting this comprehensive sort of governance regime in place and then finally security and trust. It's going to be more paramount than ever before. >> Yeah, nobody's going to use the data if they don't trust it, I'm glad you brought up security. It's a topic that is at number one on the CIO list. JG, great conversation. Obviously the strategy is working and thanks so much for participating in Cube on Cloud. >> Thank you, thank you, Dave and I appreciate it and thank you to everybody who's tuning into today. >> All right then keep it right there, I'll be back with our next guest right after this short break.

>>Yeah, yeah. >>Hello and welcome back. I hope you're ready for our next session. Become the analyst of the future. We'll hear the customer's perspective about their increasingly strategic role and the potential career growth that comes with it. Joining us today are Nate Weaver, director of product marketing at Thought Spot. Yasmin Natasa, senior director of national sales strategy and insights over at Comcast and Steve Would Ledge VP of customer and partner initiatives. Oughta Terex. We're so happy to have you all here today. I'll hand things over to meet to kick things off. >>Yeah, thanks, Paula. I'd like to start with a personal story that might resonate with our audience, says an analyst. Early in my career, I was the intermediary between the business and what we called I t right. Basically database administrators. I was responsible for understanding business logic gathering requirements, Ringling data building dashboards for executives and, in my case, 100 plus sales reps. Every request that came through the business intelligence team. We owned everything, right? Indexing databases for speed, S s. I s packages for data transfer maintaining Department of Data Lakes all out cubes, etcetera. We were busy. Now we were constantly building or updating something. The worst part is an analyst, If you ask the business, every request took too long. It was slow. Well, from an analyst perspective, it was slow because it's a complex process with many moving parts. So as an analyst fresh out of grad school often felt overeducated, sometimes underappreciated, like a report writer, we were constantly overwhelmed by never ending ad hoc request, even though we had hundreds of reports and robust dashboards that would answer 90% of the questions. If the end user had an analytical foundation like I did right, if they knew where to look and how to navigate dimensions and hierarchies, etcetera. So anyway, point is, we had to build everything through this complex and slow, um, process. So for the first decade of my career, I had this gut feeling there had to be a better way, and today we're going to talk about how thought SWAT and all tricks are empowering the analysts of the future by reimagining the entire data pipeline. This paradigm shift allows businesses and data teams thio, connect, transform, model and, most importantly, automate what used to be this terribly complex data analysis process. With that, I'd like to hand it over to Steve to describe the all tricks analytic process automation platform and how they help analysts create more robust data sets that enable non technical end users toe ask and answer their own questions, but also more sophisticated business questions. Using Search and AI Analytics in Thoughts Fire Steve over to you. >>Thanks for that really relevant example. Nate and Hi, everyone. I'm Steve. Will it have been in the market for about 20 years, and then Data Analytics and I can completely I can completely appreciate what they was talking about. And what I think is unique about all tricks is how we not only bring people to the data for a self service environment, but I think what's often missed in analytics is the automation and figure out. What is the business process that needs to be repeated and connecting the dots between the date of the process and the people To speed up those insights, uh, to not only give people to self service, access to information, to do data prep and blending, but more advanced analytics, and then driving that into the business in terms of outcomes. And I'll show you what that looks like when you talk about the analytic process automation platform on the next slide. What we've done is we've created this end to end workflow where data is on the left, outcomes around the right and within the ultras environment, we unify data prep and blend analytics, data science and process automation. In this continuous process, so is analysis or an end user. I can go ahead and grab whatever data is made available to me by i t. You have got 80 plus different inputs and a p i s that we connect to. You have this drag and drop environment where you conjoined the data together, apply filters, do some descriptive analytics, even do things like grab text documents and do sentiments analysis through that with text, mining and natural language processing. As people get more used to the platform and want to do more advanced analytics and process automation, we also have things like assisted machine learning and predictive analytics out of the box directly within it as well and typically within organizations. These would be different departments and different tools doing this and we try to bring all this together in one system. So there's 260 different automation building blocks again and drag a drop environment. And then those outcomes could be published into a place where thoughts about visualizes that makes it accessible to the business users to do additional search based B I and analytics directly from their browser. And it's not just the insights that you would get from thought spot, but a lot of automation is also driving unattended, unattended or automated actions within operational systems. If you take an example of one of our customers that's in the telecommunications world, they drive customer insights around likeliness to turn or next best offers, and they deliver that within a salesforce applications. So when you walk into a retail store for your cell phone provider, they will know more about you in terms of what services you might be interested in. And if you're not happy at the time and things like that. So it's about how do we connect all those components within the business process? And what this looks like is on this screen and I won't go through in detail, but it's ah, dragon drop environment, where everything from the input data, whether it's cloud on Prem or even a local file that you might have for a spreadsheet. Uh, I t wants to have this environment where it's governed, and there's sort of components that you're allowed to have access to so that you could do that data crept and blending and not just data within your organization, but also then being able to blend in third party demographic data or firm a graphic information from different third party data providers that we have joined that data together and then do more advanced analytics on it. So you could have a predictive score or something like that being applied and blending that with other information about your customer and then sharing those insights through thought spots and more and more users throughout the organization. And bring that to life. In addition to you, as we know, is gonna talk about her experience of Comcast. Given the world that we're in right now, uh, hospital care and the ability to have enough staff and and take care of all of our people is a really important thing. So one of our customers, a large healthcare network in the South was using all tricks to give not only analyst with the organization, but even nurses were being trained on how to use all tricks and do things like improve observation. Wait time eso that when you come in, the nurse was actually using all tricks to look at the different time stamps out of ethic and create a process for the understands. What are all the causes for weight in three observation room and identify outliers of people that are trying to come in for a certain type of care that may wait much longer than on average. And they're actually able to reduce their wait time by 22%. And the outliers were reduced by about 50% because they did a better job of staffing. And overall staffing is a big issue if you can imagine trying to have a predictive idea of how many staff you need in the different medical facilities around the network, they were bringing in data around the attrition of healthcare workers, the volume of patient load, the scheduled holidays that people have and being able to predict 4 to 6 months out. What are the staff that they need to prepare toe have on on site and ready so they could take care of the patients as they're coming in. In this case, they used in our module within all tricks to do that, planning to give HR and finance a view of what's required, and they could do a drop, a drop down by department and understand between physicians, nurses and different facilities. What is the predicted need in terms of staffing within that organization? So you go to the next slide done, you know, aside from technology, the number one thing for the analysts of the future is being able to focus on higher value business initiatives. So it's not just giving those analysts the ability to do this self service dragon drop data prep and blend and analytics, but also what are the the common problems that we've solved as a community? We have 150,000 people in the alter its community. We've been in business for over 23 years, so you could go toe this gallery and not only get things like the thought spot tools that we have to connect so you can do direct query through T Q l and pushed it into thought spot in Falcon memory and other things. But look at things like the example here is the healthcare District, where we have some of our third party partners that have built out templates and solutions around predictive staffing and tracking the complicating conditions around Cove. It as an example on different KPs that you might have in healthcare, environment and retail, you know, over 150 different solution templates, tens of thousands of different posts across different industries, custom return and other problems that we can solve, and bringing that to the community that help up level, that collective knowledge, that we have this business analyst to solve business problems and not just move data, and then finally, you know, as part of that community, part of my role in all tricks is not only working with partners like thought spot, but I also share our C suite advisory board, which we just happen to have this morning, as a matter of fact, and the number one thing we heard and discussed at that customer advisory board is a round up Skilling, particularly in this virtual world where you can't do in classroom learning how do we game if I and give additional skills to our staff so that they can digitize and automate more and more analytic processes in their organization? I won't go through all this, but we do have learning paths for both beginners. A swell as advanced people that want to get more into the data science world. And we've also given back to our community. There's an initiative called Adapt where we've essentially donated 125 hours of free training free access to our products. Within the first two weeks, we've had over 9000 people participate in that get certified across 100 different companies and then get jobs in this new world where they've got additional skills now around analytics. So I encourage you to check that out, learn what all tricks could do for you in up Skilling your journey becoming that analysts of the future And thanks for having me today thoughts fun looking forward to the rest of conversation with the Azmin. >>Yeah, thanks. I'm gonna jump in real quick here because you just mentioned something that again as an analyst, is incredibly important. That's, you know, empowering Mia's an analyst to answer those more sophisticated business questions. There's a few things that you touched on that would be my personal top three. Right? Is an analyst. You talked about data cleansing because everyone has data quality problems enhancing the data sets. I came from a supply chain analytics background. So things like using Dun and Bradstreet in your examples at risk profiles to my supplier data and, of course, predictive analytics, like creating a forecast to estimate future demand. These are things that I think is an analyst. I could truly provide additional value. I'd like to show you a quick example, if I may, of the type of ad hoc request that I would often get from the business. And it's fairly complex, but with a combination of all tricks and thought spots very easy to answer. Crest. The request would look something like this. I'd like to see my spend this year versus last year to date. Uh, maybe look at that monthly for Onley, my area of responsibility. But I only want to focus on my top five suppliers from this year, right? And that's like an end statement. I saw that in one of your slides and so in thoughts about that's answering or asking a simple question, you're getting the answer in maybe 30 seconds. And that's because behind the scenes, the last part is answering those complexities for you. And if I were to have to write this out in sequel is an analyst, it could take me upwards, maybe oven our because I've got to get into the right environment in the database and think about the filters and the time stamps, and there's a lot going on. So again, thoughts about removes that curiosity tax, which when becoming the analysts of the future again, if I don't have to focus on the small details that allows me to focus on higher value business initiatives, right. And I want to empower the business users to ask and answer their own questions. That does come with up Skilling, the business users as well, by improving data fluency through education and to expand on this idea. I wanna invite Yasmin from Comcast to kind of tell her personal story. A zit relates to analysts of the future inside Comcast. >>Well, thank you for having me. It's such a pleasure. And Steve, thank you so much for starting and setting the groundwork for this amazing conversation. You hit the nail on the head. I mean, data is a Trojan horse off analytics, and our ability to generate that inside is eyes busy is anchored on how well we can understand the data on get the data clean It and tools, like all tricks, are definitely at the forefront off ability to accelerate the I'll speak to incite, which is what hot spot brings to the table. Eso My story with Thought spot started about a year and a half ago as I'm part of the Sales Analytics team that Comcast all group is officially named, uh, compensation strategy and insight. We are part of the Consumer Service, uh, Consumer Service expected Consumer Service group in the cell of Residential Sales Organization, and we were created to provide insight to the Comcast sells channel leaders Thio make sure that they have database insight to drive sales performance, increased revenue. We When we started the function, we were really doing a lot of data wrangling, right? It wasn't just a self performance. It waas understanding who are customers were pulling a data on productivity. Uh, so we were going into HR systems are really going doing the E T l process, but manually sometimes. And we took a pause at one point because we realized that we're spending a good 70% of our time just doing that and maybe 5% of our time storytelling. Now our strength was the storytelling. And so you see how that balance wasn't really there. And eso Jim, my leader pause. It pulls the challenge of Is there a better way of doing this on DSO? We scan the industry, and that's how we came across that spot. And the first time I saw the tool, I fell in love. There's not a way for me to describe it. I fell in love because I love the I love the the innovation that it brought in terms of removing the middleman off, having to create all these layers between the data and me. I want to touch the data. I want to feel it, and I want to ask questions directly to it, and that's what that's what does for us. So when we launched when we launch thoughts about for our team, we immediately saw the difference in our ability to provide our stakeholders with better answers faster. And the combination of the two makes us actually quite dangerous right on. But it has been It has been a great great journey altogether are inter plantation was done on the cloud because at the time, uh, the the we had access to AWS account and I love to be at the edge of technology, So I figured it would be a good excuse for me to learn more about cloud technology on its been things. Video has been a great journey. Um, my, my background, uh, into analytics comes from science. And so, for me, uh, you know, we are really just stretching the surface off. What is possible in terms off the how well remind data to answer business questions on Do you know, tools like thought spot in combination with technologies. Like all trades, eyes really are really the way to go about it. And the up skilling, um the up skilling off the analysts that comes with it is really, really, really exciting because people who love data want to be able to, um want to be efficient about how they spend time with data. Andi and that's what? That's what I spend a lot of my Korea I'd Comcast and before Comcast doing so It gives me a lot of ah, a lot of pleasure to, um to bring that to my organization and to walk with colleagues outside off. We didn't Comcast to do so The way we the way we use stops, that's what we did not seem is varies. One of the things that I'm really excited about is integrating it with all the tools that we have in our analytics portfolio, and and I think about it as the over the top strategy. Right. Uh, group, like many other groups, wouldn't Comcast and with our organizations also used to be I tools. And it is not, um, you choose on a mutually exclusive strategies, right? Eso In our world, we build decision making, uh, decision making tools from the analysis that we generate. When we have the read out with the cells channel leaders, we we talk about the insight, and invariably there's some components off those insight that they want to see on a regular basis. That becomes a reporting activity. We're not in a reporting team. We partner with reporting team for them to think that input and and and put it on and create a regular cadence for it. Uh, the over the top strategy for me is, um, are working with the reporting team to then embed the link to talk spot within the report so that the questions that can be answered by the reports left dashboard are answered within the dashboard. But we make sure that we replicate the data source that feeds that report into thought spot so that the additional questions can then be insert in that spot. It and it works really well because it creates a great collaboration with our partners on the on the reporting side of the house on it also helps of our end the end users do the cell service in along the analytic spectrum, right? You go to the report when you can, when all you need is dropped down the filters and when the questions become more sophisticated, you still have a platform in the place to go to ask the questions directly and do things that are a bit funk here, like, you know, use for like you because you don't know what you're looking for. But you know that there's there's something there to find. >>Yeah, so yeah, I mean, a quick question. Our think would be on this year's analytics meet Cloud open for everyone and your experience. What does that mean to you? Including in the context of the thought spot community inside Comcast? >>Oh yes, it's the Comcast community. The passport commedia Comcast is very vibrant. My peers are actually our colleagues, who I have in my analytics village prior to us getting on board with hot spot and has been a great experience for us. So have thoughts, but as an additional kind of topic Thio to connect on. So my team was the second at Comcast to implement that spot. The first waas, the product team led by Skylar, and he did his instance on Prem. Um, he the way that he brings his data is, is through a sequel server. When I came what, as I mentioned earlier, I went on the cloud because, as I mentioned earlier, I like to be on the edge of technology and at the time thought spot was moving towards towards the cloud. So I wanted to be part of that wave. There's Ah, mobile team has a new instance that is on the cloud thing. The of the compliance team uses all tricks, right? And the S O that that community to me is really how the intellectual capital that we're building, uh, using thought spot is really, really growing on by what happens to me. And the power of being on the cloud is that if we are all using the same tool, right and we are all kind of bringing our data together, um, we are collaborating in ways that make the answer to the business questions that the C suite is asking much better, much richer. They don't always come to us at the same time, right? Each function has his own analytics group, Andi. Sometimes if we are not careful, we're working silo. But the community allows us to know about what each other are working on. And the fact that we're using the same tool creates a common language that translates into opportunities for collaboration, which will translate into, as I mentioned earlier, richer better on what comprehensive answers to the business. So analyst Nick the cloud means better, better business and better business answers and and better experiences for customers at the end of the day, so I'm all for it. >>That's great. Yeah. Comcast is obviously a very large enterprise. Lots of data sources, lots of data movement. It's cool to hear that you have a bit of a hybrid architecture, er thought spot both on premise. Stand in the cloud and you did bring up one other thing that I think is an important question for Steve. Most people may just think of all tricks as an E T l tool, but I know customers like Comcast use it for way more than just that. Can you expand upon the differences between what people think of a detail tool and what all tricks is today? >>Yeah, I think of E. T L tools as sort of production class source to target mapping with transformations and data pipelines that air typically built by I t. To service, you know, major areas within the business, and that's super valuable. One doesn't go away, and in all tricks can provide some of that. But really, it's about the end user empowerment. So going back to some of guys means examples where you know there may be some new information that you receive from a third party or even a spreadsheet that you develop something on. You wanna start to play around that information so you can think of all the tricks as a data lab or data science workbench, in fact, that you know, we're in the Gartner Magic Quadrant for data science and machine learning platforms. Because a lot of that innovation is gonna happen at the individual level we're trying to solve. And over time, you might want to take that learning and then have I t production eyes it within another system. But you know, there's this trade off between the agility that end users need and sort of the governance that I t needs to bring. So we work best in a environment where you have that in user autonomy. You could do E tail workloads, data prep and Glenn bringing your own information on then work with i t. To get that into the right server based environment to scale out in the thought spot and other applications that you develop new insights for the business. So I see it is ah, two sides of the same coin. In many ways, a home. And >>with that we're gonna hand it back over to a Paula. >>Thank you, Nate, Yasmin and Steve for the insights into the journey of the analyst of the future. Next up in a couple minutes, is our third session of today with Ruhollah Benjamin, professor of African American Studies at Princeton University, and our chief data strategy officer, Cindy House, in do a couple of jumping jacks or grab a glass of water and don't miss out on the next important discussion about diversity and data.

>> Narrator: From around the globe it's theCUBE with digital coverage of Dell Technologies World. Digital experience brought to you by Dell Technologies. >> Welcome back everybody. Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of Dell Technology World. We've been covering Dell Tech World since it started really. It used to just be Dell World and there was EMC World after the merger and this is the all virtual version but we're excited to be here and we've got a great panel coming up. I think you're going to enjoy it. Our first guest is Rajesh Janey. He is the Senior Vice President of Global Alliances for APJ for Dell Technologies. Rajesh, where are you coming in from today? >> I'm speaking to you from Gurgaon, India. >> Awesome. It's the power of the virtual, right? It's not all bad that we don't have to get on planes all the time. >> Absolutely. >> And joining him is Utpal Bakshi. He is the Vice President and Global Vertical Head High Tech for Wipro. Utpal, good to see you. >> Nice to see you. >> And where are you calling us in from? >> I'm from Dallas, Texas. Actually suburb outside of Dallas called South Lake. >> Oh, excellent. Great to see you and again didn't have to get on a plane to do this so not all bad. And also joining us is Satish Yadavalli. He is the Vice President and Global Practice Head, Cloud and Infrastructure Services for Wipro. Satish, where are you joining us from? >> Hi, I'm joining from Bangalore, India. >> Excellent. Welcome. So gentlemen let's just jump into it. Wipro's a huge services firm, does a lot of work with Dell so I wonder Rajesh if you can talk really about the importance of partnerships and the importance of having somebody like Wipro within the Dell ecosystem. >> Absolutely. Thank you for having us on with Wipro. Wipro and we have had a partnership which is over two decades old and we have a multifaceted 360 degree kind of relationship with Wipro. Wipro is a platinum partner and what's more while we bring a lot of technology and products and the depth of product which are relevant to customer's transformation scenarios today, coupled with Wipro's consulting and services and design abilities this becomes an unbeatable power house so to say whereby we can work closely with a customer to help them transform and live in what we are calling the next normal. >> Yeah that's great. Utpal to you there's a lot of interesting trends going on. We've had cloud and big data been going on for a lot but really the talk in social media is what's driving your digital transformation, the CEO, the CIO or COVID and we all know what the answer is. So we've got a lot of new stuff in terms of digital transformation, working from anywhere, workforce transformation. Wonder if you can speak a little bit about how COVID has accelerated some of the priorities that your customers are trying to get done. >> Yeah. I think that's a great point. Wipro has been transforming over the last several years. We were a strong, large scale system integration partner, large IT organization but over the last several years we pivoted hard into the digital transformation world moving into the design side, leading the design, moving to cloud and helping our clients help make that journey and all of that got accelerated with the whole COVID situation. The work from home became all pervasive and the whole virtualization of the workforce really pivoted with some of our key transformational ideas around live workspace and the virtual desk which we've been working very closely with Dell have taken shape. So that has been a big part of our ongoing strategy. Doing the modernization off the network has also accelerated the customer networks and infrastructure was not necessarily set up for enabling these hybrid work environment. A lot of our clients are coming back and saying they want to modernize and actually accelerate. So that has all changed with COVID. Some of it is very positive actually for the business. >> Right. >> From an SI perspective. >> Satish, you've got cloud and infrastructure in your title. Public cloud really changed the game when Amazon kind of came on the scene and now we're seeing this evolution and change over time between a public cloud and hybrid cloud and multi cloud and cloud on cloud. I wonder if you could speak to and then even have an AWS inside of other people's clouds. They're trying to get it out there. The evolution of cloud both as a technology but really more as a way of thinking in terms of rapid deployment of new functionality to support the business and what you're seeing with your customers today. >> So let me share a perspective, right? Enterprises today are looking at options to extract greater value from hybrid cloud investment. It's a brownfield environment today where customers have their existing data centers but the hyperscalers have really come into play now and right cloud is the strategy which most of our customers embrace to address the market demands which are primarily focused on business outcomes today. As Wipro we have invested in developing a holistic extensible platform led approach called Wipro BoundaryLess Enterprise to drive business outcomes to customers. So the BLE construct is all about providing a ready to use plug-and-play platforms making IT easily consumable from multiple stakeholder personas be it admins, be it line of businesses, developers and partners. So basically we have built a holistic solution and our BLE solutions has majorly five building blocks. The first building block would be the BoundaryLess Data Center. The second is the BoundaryLess Container Platform. The third is the BoundaryLess Data Protection Platform. The fourth is the BoundaryLess Cloud Exchange where we get together all the internet connections and define the software defined network part to give access to the workloads across hybrid environments and the BoundaryLess Integration Platform which we call it as BLIP. Basically this is what we have put together to deliver an outcome to the customers powered by BLE. >> So BLE again, you call it the BoundaryLess Enterprise. What's the most important components of BLE? What are the things that most people are missing to actually implement the strategy? >> So if I actually build on you, right? The five building blocks let me elaborate in detail. The first is on the BoundaryLess Data Center. This enables our clients to deliver an infrastructure as a service across data centers and public clouds and enables customers to seamlessly move workloads from Edge to Cloud and manage them in a consistent and efficient model. That's the first building block of our BLE. The second important building block is container, right? We all know today container orchestration is key across hybrid cloud and with micro services and architectures becoming more prominent we see huge search for managing various Kubernetes enrollments with our clients. So our BLCP platform leverages solutions like VMware Tanzu, which is again a Dell company to enable clients manage the multicloud Kubernetes enrollments through a single pane of glass and provide seamless migration and movement of workloads across cloud environments. That's going to be the key in the future with microservices being dominant and every enterprise embracing microservices architectures this becomes very important building block in our overall solution. The third important stuff is BoundaryLess Data Protection. Now that data is all cross in hybrid cloud environment and application actually consume this data it is important to protect the data which is intellectual property and very critical to every business. So with the BLDP platform we ensure that we deliver availability, solidarity, security and reliability of cloud adoption increasingly and rapidly across multicloud platforms. So our solution leverages the DTC of Dell and other existing Dell storages and data production solutions to offer seamless and right cost models which will be very critical for any cloud transformation and schedules as we move forward. The fourth point which I was talking about is BLCE. This is basically a cloud exchange where in a hybrid cloud environment you need to establish connectivities across PaaS and SaaS platforms as well as on-premise networks to provide seamless access to data and the workloads which are in multicloud scenarios. So that's about BLCE. With respect to BLIP it is an integration platform. Today we are in a software defined world and when I talk about providing a single pane of glass solution it is important for us to have an integration platform where I can bring all EPIs together and do northbound and southbound integrations with the architectures of clients and the cloud providers to spin off workloads, to commission, decommission and provide a seamless consumption experience to clients across multiple hyperscalers and on-premise infrastructure. >> Thank you for that summary. I think you hit on all the big trends. I want to go back to you Rajesh 'cause you said that this is a really unique time. You've been in the business for a very long time. You've seen a lot of other transformations and you've seen a lot of big trends. Why is this one different? What makes where we are today such a unique point in time in this IT industry journey? >> Excellent. I think I would say we are in a period of what is called an enforced innovation. While most of the time transformation in IT has been very, very sequential or continuous I think we are seeing an order of shift in the transformation and this whole situation is forcing everyone to accelerate the pace of innovation and transformation. There are two key priorities for every organization in this time. One, build resilient operations and second employee safety. These two parameters have forced the organization to look at their businesses differently, look at their IT infrastructure differently and created a sort of opportunity you can say which is ripe for Wipro's BoundaryLess Enterprise because there are no boundaries. People are working from home. They're no longer in an office confined or boundary. So that's smart. Coming back we are seeing an accelerated innovation. That means our partnership to deliver customer transformation at scale becomes all the more important. Bringing all the good technologies of Dell on one side and combining it Wipro's size, scale and services help us lead in the marketplace for customer transformation. And what's more, we are adding our Dell financial services solutions as Dell Tech on demand to enable all this to be consumed as a service and with flexible payment options which Wipro helps us translate it to customer offerings. >> That's great. Utpal, I want to go to you and get your perspective on how customers, in terms of this boundaryless, how things have changed since March 15th which at least here in the US, I don't know if in India it was on the same date when everything basically got shut down. So it was this light switch moment. Everybody worked from home, no planning, no thought like ready, set, go to now we're six, seven, eight months into this thing and clearly we're it's a marathon not a sprint and even if we go back to some semblance of what was the old normal the new normal is going to be different and everyone is not going to go back to work full time like they did before. So how, from a customer perspective, from a technology implementation perspective and from an initiative and getting this stuff done how has that changed pre-COVID then oh my goodness, it's the light switch moment and now it's, hey, we're in this for the long term. >> Yeah. I think Rajesh did hit upon that a little bit. This is truly that moment where it was a forced innovation. Some of it was happening anyways and it was bound to happen but I think the COVID kind of accelerated all of it. What has impacted is it all started with, okay, how do we enable work from home? And that is when the whole BoundaryLess infrastructure, the virtual desk solutions and all of that started getting impact. I think after that most companies have realized that this is not a short term fix. It is a longterm it's going to be here for staying so they wanted to have a longterm fix so they wanted to come in with innovation but at the same time from a business perspective they've had impact in business so they wanted very creative business models for them to get set with the technology innovation quicker but they didn't want to do it in a traditional way of paying it all upfront and moving it to that. So that is where the creativity in terms of joint innovation which we did with Dell, in flexible payment options, bringing in some kind of an asset lease model and things like that have gained traction. A lot more conversations are around we want to transform help us find a way to make the transformation sooner with maybe less investment upfront and find a way to fund this from the future savings we'll get so that we can be ready for the future without necessarily impacting the bottom line today. All of that has changed, I would say in summary, has accelerated the adoption and the rate of change but it has also led to all of us thinking some creative business models and new approaches to doing business. >> Right, right. Satish back to you. What are the big conflicts that always exist? There's innovation versus security, right? And enabling innovation and giving people more power, more tools, more data to do things at the same time now your tax surface has increased you don't necessarily have everybody locked down on their home infrastructure and they were forced into this. When people are talking about digital transformation, how do they continue to drive forward and how are you helping them on innovation and enabling innovation at the same time as you talked about keeping the data protected and really thinking about business resiliency and continuity in this to increase the tax surface not only because of mobile, but now with the working from home thing? It's increased exponentially. >> Yeah. So I would just take an example of how Wipro handled this pandemic when it hit us and what solutions we get. So let me just give you a perspective. As we all know the current pandemic has disrupted many industries and we were no exception. Basically COVID has brought to the forefront many crucial factors in terms of business continuity process, the quality of employee experience and the automation connected with the employees. So while we enable our employees to connect, collaborate, and communicate with ease from anywhere from any device in a secure way with a consistent user experience powered by Wipro LiVE Workspace platform which actually takes care of delivering a seamless onboarding of user via the Wipro LiVE Workspace platform and consume all the services the way they used to traditionally consume when they were working from office? So this is something which is the power of Wipro LiVe Workspace platform we have implemented to deliver a seamless employee experience access to the workspaces. That's one but also there are some learnings. When we implemented the solutions on the flip side as businesses we must also acknowledge and be cognizant of the fact that employees are trying hard to juggle between frequent interruptions at home and notifications from various applications we receive both on corporate and personal devices. Basically in a nut shell it is difficult to have the culture of corporate to be working from home. Basically that's another big learning. While all of us are adjusting to this new normal we are in constant touch with our employees and trying to improve the overall employee connect and experience. From a solution perspective let me just give you what we actually did. We have close to 175,000 employees across the globe. Suddenly started working from home post lockdown. What does this mean? The traffic pattern suddenly changed the directions which were traditionally moving on a East to West direction started moving North to South. Basically this means a 100% of the workforce in a corporate started coming from the internet to access the corporate infrastructure and then gain access to the customer network. So basically we had to quickly swing in with our solutions and got our engineering teams to re engineer and tweet the infrastructure and security architecture to this new normal. By leveraging our Wipro BLE and video architectures which is powered by Dell VxRail, NSX we were able to spin off and build capacity on on-prem as well as on cloud in less than 24 hours post one got approvals from the client. Lastly we also deployed a back to work IoT solution which helped our employees to get back to work safely. Basically the solution offers various security parameters. Apart from traditional COVID updates it also helps in scanning the employees' temperatures, employee movement within the office premises, bundled with video analytics and enables secure touch less access to the ODCs for employees who are coming back to work. So we are putting all these solutions together and we pretty much seamlessly were able to navigate from the pandemic situation and get our business back to operations in a matter of days. >> 175,000 People. It's really interesting to think about how that network traffic completely changed from inside the firewalls to everything coming from the outside. It's a lot of people to get working from home right away so congratulations on that. As we come to a close Rajesh, I want to come back to you and talk about again, partnership in the age of this rapid acceleration of technology adoption, new technology move. We talked about the work from home. We've talked about cloud. We haven't talked very much about there's this other big thing that's coming down the pike which is 5G and IoT and kind of this entirely new scale of communication that's machine to machine, not person to person and now these connected devices. The amount of traffic continues to go up into the right at an accelerating rate. Tell us a little bit about the meaningfulness of having a partnership like Wipro that you guys can build solutions around new cutting edge technologies and have that real close connection with the customer or with all the supporting services. >> We'd love to. And maybe first I'll give you a perspective on how our employee base started working from home. Some other statistics that they wanted to show maybe add on towards what Satish said. We transitioned 120,000 employees. Twice the normal to work from home within two weeks and every day we are running something like 20,000 meetings and 16 million zoom minutes per day. That's the kind of traffic IT has seen. >> 16 million zoom minutes per day? >> Zoom minutes per day. >> Wow. >> That's the kind of traffic and our VPN traffic user load just tripled. At software or IT we call Dell digital. It was just a smooth and seamless experience. Now coming back, you said rightly. While we have partnered so far to deliver to the solution which are here today and the customers needs which are here today, what are we going to do for the future needs especially ie 5G IoT? We believe as a corporation that Edge is going to be the next wave of innovation. And next way our customers will benefit. Therefore connectivity to Edge via 5G becomes critical. IoT devices and managing the traffic and contain it there itself rather than flowing it back to data center becomes critical. As an example Wipro and Dell technologies are using our hyper converge solutions along with VMware telco and software for a European telco to provide automation and AI to deliver rapid results for the customer. So these are just early parts of it. We are partnering with Wipro to build solutions around 5G as well as telecom related innovation that'll come into the picture. IoT Satish spoke about a simple example of employee attendance. Imagine this is a need which will only accelerate from every organization, multiply it with the automation and AI that needs to be built into machines and feeding all the data back to drive some intelligence and refine the processes, refine the business outcomes. So I think we are working together on many such things and what's important is in all this, when the universe just explodes to devices and millions of devices, security becomes a paramount feature and we are working with Wipro to build what is called an embedded security into each of the solutions that we are designing. Security cannot be an afterthought or a bolt on it's becoming an integral part of the overall solution as we move towards the Edge. >> Yeah, right. And I think as Satish talked about all the distractions and notifications there're a lot of great opportunities for applied AI too to help people know what to do next. It's hard to be context switching all the time, not only on your work, but also the spouses working from home, the kids are doing homeschooling. It's not an optimal environment at all. Gentlemen thank you for your time. Congratulations on your partnership and hope you have a fantastic Dell Tech World. Sorry we can't be in person but this is not too bad. >> Thank you. >> Jeff >> Thank you >> Thank you Utpal, thank you Satish for your partnership. >> All right. Thank you gentlemen. >> Thank you. >> Alright. Stay with us for continuing coverage of Dell Technologies World 2020. I'm Jeff Frick. Thanks for watching. (upbeat music)

(upbeat electronic music) >> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Okay, hello everyone. I'm John Furrier with theCUBE. We're here with Meet the Analysts segment Sunday morning. We've got everyone around the world here to discuss a bit of the news around the EU killing the privacy deal, striking it down, among other topics around, you know, data privacy and global commerce. We got great guests here, Ray Wang, CEO of Constellation Research. Bill Mew, founder and CEO of Cyber Crisis Management from the Firm Crisis Team. And JD, CEO of Spearhead Management. JD, I can let you say your name because I really can't pronounce it. How do I (laughs) pronounce it, doctor? >> I wouldn't even try it unless you are Dutch, otherwise it will seriously hurt your throat. (Ray laughing) So, JD works perfect for me. >> Doctor Drooghaag. >> And Sarbjeet Johal, who's obviously an influencer, a cloud awesome native expert. Great, guys. Great to have you on, appreciate it, thanks for comin' on. And Bill, thank you for initiating this, I appreciate all your tweets. >> Happy Sunday. (Bill laughing) >> You guys have been really tweeting up a storm, I want to get everyone together, kind of as an analyst, Meet the Analyst segment. Let's go through with it. The news is the EU and U.S. Privacy Shield for data struck down by the court, that's the BBC headline. Variety of news, different perspectives, you've got an American perspective and you've got an international perspective. Bill, we'll start with you. What does this news mean? I mean, basically half the people in the world probably don't know what the Privacy Shield means, so why is this ruling so important, and why should it be discussed? >> Well, thanks to sharing between Europe and America, it's based on a two-way promise that when data goes from Europe to America, the Americans promise to respect our privacy, and when data goes form America to Europe, the Europeans promise to respect the American privacy. Unfortunately, there are big cultural differences between the two blocks. The Europeans have a massive orientation around privacy as a human right. And in the U.S., there's somewhat more of a prioritization on national security, and therefore for some time there's been a mismatch here, and it could be argued that the Americans haven't been living up to their promise because they've had various different laws, and look how much talk about FISA and the Cloud Act that actually contravene European privacy and are incompatible with the promise Americans have given. That promise, first of all, was in the form of a treaty called Safe Harbor. This went to court and was struck down. It was replaced by Privacy Shield, which was pretty much the same thing really, and that has recently been to the court as well, and that has been struck down. There now is no other means of legally sharing data between Europe and America other than what are being called standard contractual clauses. This isn't a broad treaty between two nations, these are drawn by each individual country. But also in the ruling, they said that standard contractual clauses could not be used by any companies that were subject to mass surveillance. And actually in the U.S., the FISA courts enforce a level of mass surveillance through all of the major IT firms, of all major U.S. telcos, cloud firms, or indeed, social media firms. So, this means that for all of the companies out there and their clients, business should be carrying on as usual apart from if you're one of those major U.S. IT firms, or one of their clients. >> So, why did this come about? Was there like a major incident? Why now, was it in the court, stuck in the courts? Were people bitchin' and moanin' about it? Why did this go down, what's the real issue? >> For those of us who have been following this attentively, things have been getting more and more precarious for a number of years now. We've had a situation where there are different measures being taken in the U.S., that have continued to erode the different protections that there were for Europeans. FISA is an example that I've given, and that is the sort of secret courts and secret warrants that are issued to seize data without anyone's knowledge. There's the Cloud Act, which is a sort of extrajudicial law that means that warrants can be served in America to U.S. organizations, and they have to hand over data wherever that data resides, anywhere in the world. So, data could exist on a European server, if it was under the control of an American company, they'd have to hand that over. So, whilst FISA is in direct conflict with the promises that the Americans made, things like the Cloud Act are not only in controversion with the promise they've made, there's conflicting law here, because if you're a U.S. subsidiary of a big U.S. firm, and you're based in Europe, who do you obey, the European law that says you can't hand it over because of GDPR, or the American laws that says they've got extrajudicial control, and that you've got to hand it over. So, it's made things a complete mess. And to say has this stuff, hasn't really happened? No, there's been a gradual erosion, and this has been going through the courts for a number of years. And many of us have seen it coming, and now it just hit us. >> So, if I get you right in what you're saying, it's basically all this mishmash of different laws, and there's no coherency, and consistency, is that the core issue? >> On the European side you could argue there's quite a lot of consistency, because we uphold people's privacy, in theory. But there have been incidents which we could talk about with that, but in theory, we hold your rights dear, and also the rights of Europeans, so everyone's data should be safe here from the sort of mass surveillance we're seeing. In the U.S., there's more of a direct conflict between everything, including there's been a, in his first week in the White House, Donald Trump signed an executive order saying that the Privacy Act in the U.S., which had been the main protection for people in the U.S., no longer applied to non-U.S. citizens. Which was, if you wanted try and cause a storm, and if you wanted to try and undermine the treaty, there's no better way of doing it than that. >> A lot of ways, Ray, I mean simplify this for me, because I'm a startup, I'm hustlin', or I'm a big company, I don't even know who runs the servers anymore, and I've got data stored in multiple clouds, I got in regions, and Oracle just announced more regions, you got Amazon, a gazillion regions, I could be on-premise. I mean bottom line, what is this about? I mean, and -- >> Bill's right, I mean when Max Schrems, the Austrian. Bill's right, when Max Schrems the Austrian activist actually filed his case against Facebook for where data was being stored, data residency wasn't as popular. And you know, what it means for companies that are in the cloud is that you have to make sure your data's being stored in the region, and following those specific region rules, you can't skirt those rules anymore. And I think the cloud companies know that this has been coming for some time, and that's why there's been announced in a lot of regions, a lot of areas that are actually happening, so I think that's the important part. But going back to Bill's earlier point, which is important, is America is basically the Canary Islands of privacy, right? Privacy is there, but it isn't there in a very, very explicit sense, and I think we've been skirting the rules for quite some time, because a lot of our economy depends on that data, and the marketing of the data. And so we often confuse privacy with consent, and also with value exchange, and I think that's part of the problem of what's going on here. Companies that have been building their business models on free data, free private data, free personally identifiable data information are the ones that are at risk! And I think that's what's going on here. >> It's the classic Facebook issue, you're the product, and the data is your product. Well, I want to get into what this means, 'cause my personal take away, not knowing the specifics, and just following say, cyber security for instance, one of the tenets there is that data sharing is an invaluable, important ethos in the community. Now, everyone has their own privacy, or security data, they don't want to let everyone know about their exploits but, but it's well known in the security world that sharing data with each other, different companies and countries is actually a good thing. So, the question that comes in my mind, is this really about data sharing or data privacy, or both? >> I think it's about both. And actually what the ruling is saying here is, all we're asking from the European side is please stop spying on us and please give us a level of equal protection that you give to your own citizens. Because data comes from America to Europe, whatever that data belongs to, a U.S. citizen or a European citizen, it's given equal protection. It is only if data goes in the other direction, where you have secret courts, secret warrants, seizure of data on this massive scale, and also a level of lack of equivalence that has been imposed. And we're just asking that once you've sorted out a few of those things, we'd say everything's back on the table, away we go again! >> Why don't we merge the EU with the United States? Wouldn't that solve the problem? (Bill laughing) >> We just left Europe! (laughs heartily) >> Actually I always -- >> A hostile takeover of the UK maybe, the 52nd state. (Bill laughing loudly) >> I always pick on Bill, like Bill, you got all screaming loud and clear about all these concerns, but UKs trying to get out of that economic union. It is a union at the end of the day, and I think the problem is the institutional mismatch between the EU and U.S., U.S. is old democracy, bigger country, population wise, bigger economy. Whereas Europe is several countries trying to put together, band together as one entity, and the institutions are new, like you know, they're 15 years old, right? They're maturing. I think that's where the big mismatch is and -- >> Well, Ray, I want to get your thoughts on this, Ray wrote a book, I forget what year it was, this digital disruption, basically it was digital transformation before it was actually a trend. I mean to me it's like, do you do the process first and then figure out where the value extraction is, and this may be a Silicon Valley or an American thing, but go create value, then figure out how to create process or understand regulations. So, if data and entrepreneurship is going to be a new modern era of value, why wouldn't we want to create a rule based system that's open and enabling, and not restrictive? >> So, that's a great point, right? And the innovation culture means you go do it first, and you figure out the rules later, and that's been a very American way of getting things done, and very Silicon Valley in our perspective, not everyone, but I think in general that's kind of the trend. I think the challenge here is that we are trading privacy for security, privacy for convenience, privacy for personalization, right? And on the security level, it's a very different conversation than what it is on the consumer end, you know, personalization side. On the security side I think most Americans are okay with a little bit of "spying," at least on your own side, you know, to keep the country safe. We're not okay with a China level type of spying, which we're not sure exactly what that means or what's enforceable in the courts. We look like China to the Europeans in the way we treat privacy, and I think that's the perspective we need to understand because Europeans are very explicit about how privacy is being protected. And so this really comes back to a point where we actually have to get to a consent model on privacy, as to knowing what data is being shared, you have the right to say no, and when you have the right to say no. And then if you have a value exchange on that data, then it's really like sometimes it's monetary, sometimes it's non-monetary, sometimes there's other areas around consensus where you can actually put that into place. And I think that's what's missing at this point, saying, you know, "Do we pay for your data? Do we explicitly get your consent first before we use it?" And we haven't had that in place, and I think that's where we're headed towards. And you know sometimes we actually say privacy should be a human right, it is in the UN Charter, but we haven't figured out how to enforce it or talk about it in the digital age. And so I think that's the challenge. >> Okay, people, until they lose it, they don't really understand what it means. I mean, look at Americans. I have to say that we're idiots on this front, (Bill chuckling) but you know, the thing is most people don't even understand how much value's getting sucked out of their digital exhaust. Like, our kids, TikTok and whatnot. So I mean, I get that, I think there's some, there's going to be blow back for America for sure. I just worry it's going to increase the cost of doing business, and take away from the innovation for citizen value, the people, because at the end of the day, it's for the people right? I mean, at the end of the day it's like, what's my privacy mean if I lose value? >> Even before we start talking about the value of the data and the innovation that we can do through data use, you have to understand the European perspective here. For the European there's a level of double standards and an erosion of trust. There's double standards in the fact that in California you have new privacy regulations that are slightly different to GDPR, but they're very much GDPR like. And if the boot was on the other foot, to say if we were spying on Californians and looking at their personal data, and contravening CCPA, the Californians would be up in arms! Likewise if we having promised to have a level of equality, had enacted a local rule in Europe that said that when data from America's over here, actually the privacy of Americans counts for nothing, we're only going to prioritize the privacy of Europeans. Again, the Americans would be up in arms! And therefore you can see that there are real double standards here that are a massive issue, and until those addressed, we're not going to trust the Americans. And likewise, the very fact that on a number of occasions Americans have signed up to treaties and promised to protect our data as they did with Safe Harbor, as they did with Privacy Shield, and then have blatantly, blatantly failed to do so means that actually to get back to even a level playing field, where we were, you have a great deal of trust to overcome! And the thing from the perspective of the big IT firms, they've seen this coming for a long time, as Ray was saying, and they sought to try and have a presence in Europe and other things. But the way this ruling has gone is that, I'm sorry, that isn't going to be sufficient! These big IT firms based in the U.S. that have been happy to hand over data, well some of them maybe more happy than others, but they all need to hand over data to the NSA or the CIA. They've been doing this for some time now without actually respecting this data privacy agreement that has existed between the two trading blocks. And now they've been called out, and the position now is that the U.S. is no longer trusted, and neither are any of these large American technology firms. And until the snooping stops and equality is introduced, they can now no longer, even from their European operations, they can no longer use standard contractual clauses to transfer data, which is going to be a massive restriction on their business. And if they had any sense, they'd be lobbying very, very hard right now to the Senate, to the House, to try and persuade U.S. lawmakers actually to stick to some these treaties! To stop introducing really mad laws that ride roughshod over other people's privacy, and have a certain amount of respect. >> Let's let JD weigh in, 'cause he just got in, sorry on the video, I made him back on a host 'cause he dropped off. Just, Bill, real quick, I mean I think it's like when, you know, I go to Europe there's the line for Americans, there's the line for EU. Or EU and everybody else. I mean we might be there, but ultimately this has to be solved. So, JD, I want to let you weigh in, Germany has been at the beginning forefront of privacy, and they've been hardcore, and how's this all playing out in your perspective? >> Well, the first thing that we have to understand is that in Germany, there is a very strong law for regulation. Germans panic as soon as they know regulation, so they need to understand what am I allowed to do, and what am I not allowed to do. And they expect the same from the others. For the record I'm not German, but I live in Germany for some 20 years, so I got a bit of a feeling for them. And that sense of need for regulation has spread very fast throughout the European Union, because most of the European member states of the European Union consider this, that it makes sense, and then we found that Britain had already a very good framework for privacy, so GDPR itself is very largely based on what the United Kingdom already had in place with their privacy act. Moving forward, we try to find agreement and consensus with other countries, especially the United States because that's where most of the tech providers are, only to find out, and that is where it started to go really, really bad, 2014, when the mass production by Edward Snowden came out, to find out it's not data from citizens, it's surveillance programs which include companies. I joined a purchasing conference a few weeks ago where the purchase of a large European multinational, where the purchasing director explicitly stated that usage of U.S. based tech providers for sensitive data is prohibited as a result of them finding out that they have been under surveillance. So, it's not just the citizens, there's mass -- >> There you have it, guys! We did trust you! We did have agreements there that you could have abided by, but you chose not to, you chose to abuse our trust! And you're now in a position where you are no longer trusted, and unless you can lobby your own elected representatives to actually recreate a level playing field, we're not going to continue trusting you. >> So, I think really I -- >> Well I mean that, you know, innovation has to come from somewhere, and you know, has to come from America if that's the case, you guys have to get on board, right? Is that what it -- >> Innovation without trust? >> Is that the perspective? >> I don't think it's a country thing, I mean like, it's not you or them, I think everybody -- >> I'm just bustin' Bill's chops there. >> No, but I think everybody, everybody is looking for what the privacy rules are, and that's important. And you can have that innovation with consent, and I think that's really where we're going to get to. And this is why I keep pushing that issue. I mean, privacy should be a fundamental right, and how you get paid for that privacy is interesting, or how you get compensated for that privacy if you know what the explicit value exchange is. What you're talking about here is the surveillance that's going on by companies, which shouldn't be happening, right? That shouldn't be happening at the company level. At the government level I can understand that that is happening, and I think those are treaties that the governments have to agree upon as to how much they're going to impinge on our personal privacy for the trade off for security, and I don't think they've had those discussions either. Or they decided and didn't tell any of their citizens, and I think that's probably more likely the case. >> I mean, I think what's happening here, Bill, you guys were pointing out, and Ray, you articulated there on the other side, and my kind of colorful joke aside, is that we're living a first generation modern sociology problem. I mean, this is a policy challenge that extends across multiple industries, cyber security, citizen's rights, geopolitical. I mean when would look, and even when we were doing CUBE events overseas in Europe, in North American companies we'd call it abroad, we'd just recycle the American program, and we found there's so much localization value. So, Ray, this is the digital disruption, it's the virtualization of physical for digital worlds, and it's a lot of network theory, which is computer science, a lot of sociology. This is a modern challenge, and I don't think it so much has a silver bullet, it's just that we need smart people working on this. That's my take away! >> I think we can describe the ideal endpoint being somewhere we have meaningful protection alongside the maximization of economic and social value through innovation. So, that should be what we would all agree would be the ideal endpoint. But we need both, we need meaningful protection, and we need the maximization of economic and social value through innovation! >> Can I add another axis? Another axis, security as well. >> Well, I could -- >> I put meaningful protection as becoming both security and privacy. >> Well, I'll speak for the American perspective here, and I won't speak, 'cause I'm not the President of the United States, but I will say as someone who's been from Silicon Valley and the east coast as a technical person, not a political person, our lawmakers are idiots when it comes to tech, just generally. (Ray laughing) They're not really -- (Bill laughing loudly) >> They really don't understand. They really don't understand the tech at all! >> So, the problem is -- >> I'm not claiming ours are a great deal better. (laughs) >> Well, this is why I think this is a modern problem. Like, the young people I talk to are like, "Why do we have this rules?" They're all lawyers that got into these positions of Congress on the American side, and so with the American JEDI Contract you guys have been following very closely is, it's been like the old school Oracle, IBM, and then Amazon is leading with an innovative solution, and Microsoft has come in and re-pivoted. And so what you have is a fight for the digital future of citizenship! And I think what's happening is that we're in a massive societal transition, where the people in charge don't know what the hell they're talkin' about, technically. And they don't know who to tap to solve the problems, or even shape or frame the problems. Now, there's pockets of people that are workin' on it, but to me as someone who looks at this saying, it's a pretty simple solution, no one's ever seen this before. So, there's a metaphor you can draw, but it's a completely different problem space because it's, this is all digital, data's involved. >> We've got a lobbyists out there, and we've got some tech firms spending an enormous amount of lobbying. If those lobbyists aren't trying to steer their representatives in the right direction to come up with law that aren't going to massively undermine trade and data sharing between Europe and America, then they're making a big mistake, because we got here through some really dumb lawmaking in the U.S., I mean, there are none of the laws in Europe that are a problem here. 'Cause GDPR isn't a great difference, a great deal different from some of the laws that we have already in California and elsewhere. >> Bill, Bill. >> The laws that are at issue here -- >> Bill, Bill! You have to like, back up a little bit from that rhetoric that EU is perfect and U.S. is not, that's not true actually. >> I'm not saying we're perfect! >> No, no, you say that all the time. >> But I'm saying there's a massive lack of innovation. Yeah, yeah. >> I don't, I've never said it! >> Arm wrestle! >> Yes, yes. >> When I'm being critical of some of the dumb laws in the U.S, (Sarbjeet laughing) I'm not saying Europe is perfect. What we're trying to say is that in this particular instance, I said there was an equal balance here between meaningful protection and the maximization of economic and social value. On the meaningful protection side, America's got it very wrong in terms of the meaningful protection it provides to civil European data. On the maximization of economic and social value, I think Europe's got it wrong. I think there are a lot of things we could do in Europe to actually have far more innovation. >> Yeah. >> It's a cultural issue. The Germans want rules, that's what they crave for. America's the other way, we don't want rules, I mean, pretty much is a rebel society. And that's kind of the ethos of most tech companies. But I think you know, to me the media, there's two things that go on with this tech business. The company's themselves have to be checked by say, government, and I believe in not a lot of regulation, but enough to check the power of bad actors. Media so called "checking power", both of these major roles, they don't really know what they're talking about, and this is back to the education piece. The people who are in the media so called "checking power" and the government checking power assume that the companies are bad. Right, so yeah, because eight out of ten companies like Amazon, actually try to do good things. If you don't know what good is, you don't really, (laughs) you know, you're in the wrong game. So, I think media and government have a huge education opportunity to look at this because they don't even know what they're measuring. >> I support the level of innovation -- >> I think we're unreeling from the globalization. Like, we are undoing the globalization, and that these are the side effects, these conflicts are a side effect of that. >> Yeah, so all I'm saying is I support the focus on innovation in America, and that has driven an enormous amount of wealth and value. What I'm questioning here is do you really need to spy on us, your allies, in order to help that innovation? And I'm starting to, I mean, do you need mass surveillance of your allies? I mean, I can see you may want to have some surveillance of people who are a threat to you, but wait, guys, we're meant to be on your side, and you haven't been treating our privacy with a great deal of respect! >> You know, Saudi Arabia was our ally. You know, 9/11 happened because of them, their people, right? There is no ally here, and there is no enemy, in a way. We don't know where the rogue actors are sitting, like they don't know, they can be within the walls -- >> It's well understood I think, I agree, sorry. it's well understood that nation states are enabling terrorist groups to take out cyber attacks. That's well known, the source enables it. So, I think there's the privacy versus -- >> I'm not sure it's true in your case that it's Europeans that's doing this though. >> No, no, well you know, they share -- >> I'm a former officer in the Royal Navy, I've stood shoulder to shoulder with my U.S. counterparts. I put my life on the line on NATO exercises in real war zones, and I'm now a disabled ex-serviceman as a result of that. I mean, if I put my line on the line shoulder to shoulder with Americans, why is my privacy not respected? >> Hold on -- >> I feel it's, I was going to say actually that it's not that, like even the U.S., right? Part of the spying internally is we have internal actors that are behaving poorly. >> Yeah. >> Right, we have Marxist organizations posing as, you know, whatever it is, I'll leave it at that. But my point being is we've got a lot of that, every country has that, every country has actors and citizens and people in the system that are destined to try to overthrow the system. And I think that's what that surveillance is about. The question is, we don't have treaties, or we didn't have your explicit agreements. And that's why I'm pushing really hard here, like, they're separating privacy versus security, which is the national security, and privacy versus us as citizens in terms of our data being basically taken over for free, being used for free. >> John: I agree with that. >> That I think we have some agreement on. I just think that our governments haven't really had that conversation about what surveillance means. Maybe someone agreed and said, "Okay, that's fine. You guys can go do that, we won't tell anybody." And that's what it feels like. And I don't think we deliberately are saying, "Hey, we wanted to spy on your citizens." I think someone said, "Hey, there's a benefit here too." Otherwise I don't think the EU would have let this happen for that long unless Max had made that case and started this ball rolling, so, and Edward Snowden and other folks. >> Yeah, and I totally support the need for security. >> I want to enter the -- >> I mean we need to, where there are domestic terrorists, we need to stop them, and we need to have local action in UK to stop it happening here, and in America to stop it happening there. But if we're doing that, there is absolutely no need for the Americans to be spying on us. And there's absolutely no need for the Americans to say that privacy applies to U.S. citizens only, and not to Europeans, these are daft, it's just daft! >> That's a fair point. I'm sure GCHQ and everyone else has this covered, I mean I'm sure they do. (laughs) >> Oh, Bill, I know, I've been involved, I've been involved, and I know for a fact the U.S. and the UK are discussing I know a company called IronNet, which is run by General Keith Alexander, funded by C5 Capital. There's a lot of collaboration, because again, they're tryin' to get their arms around how to frame it. And they all agree that sharing data for the security side is super important, right? And I think IronNet has this thing called Iron Dome, which is essentially like they're saying, hey, we'll just consistency around the rules of shared data, and we can both, everyone can have their own little data. So, I think there's recognition at the highest levels of some smart people on both countries. (laughs) "Hey, let's work together!" The issue I have is just policy, and I think there's a lot of clustering going on. Clustered here around just getting out of their own way. That's my take on that. >> Are we a PG show? Wait, are we a PG show? I just got to remember that. (laughs) (Bill laughing) >> It's the internet, there's no regulation, there's no rules! >> There's no regulation! >> The European rules or is it the American rules? (Ray laughing) >> I would like to jump back quickly to the purpose of the surveillance, and especially when mass surveillance is done under the cover of national security and terror prevention. I worked with five clients in the past decade who all have been targeted under mass surveillance, which was revealed by Edward Snowden, and when they did their own investigation, and partially was confirmed by Edward Snowden in person, they found out that their purchasing department, their engineering department, big parts of their pricing data was targeted in mass surveillance. There's no way that anyone can explain me that that has anything to do with preventing terror attacks, or finding the bad guys. That is economical espionage, you cannot call it in any other way. And that was authorized by the same legislation that authorizes the surveillance for the right purposes. I'm all for fighting terror, and anything that can help us prevent terror from happening, I would be the first person to welcome it. But I do not welcome when that regulation is abused for a lot of other things under the cover of national interest. I understand -- >> Back to the lawmakers again. And again, America's been victim to the Chinese some of the individual properties, well documented, well known in tech circles. >> Yeah, but just 'cause the Chinese have targeted you doesn't give you free right to target us. >> I'm not saying that, but its abuse of power -- >> If the U.S. can sort out a little bit of reform, in the Senate and the House, I think that would go a long way to solving the issues that Europeans have right now, and a long way to sort of reaching a far better place from which we can all innovate and cooperate. >> Here's the challenge that I see. If you want to be instrumenting everything, you need a closed society, because if you have a free country like America and the UK, a democracy, you're open. If you're open, you can't stop everything, right? So, there has to be a trust, to your point, Bill. As to me that I'm just, I just can't get my arms around that idea of complete lockdown and data surveillance because I don't think it's gettable in the United States, like it's a free world, it's like, open. It should be open. But here we've got the grids, and we've got the critical infrastructure that should be protected. So, that's one hand. I just can't get around that, 'cause once you start getting to locking down stuff and measuring everything, that's just a series of walled gardens. >> So, to JD's point on the procurement data and pricing data, I have been involved in some of those kind of operations, and I think it's financial espionage that they're looking at, financial security, trying to figure out a way to track down capital flows and what was purchased. I hope that was it in your client's case, but I think it's trying to figure out where the money flow is going, more so than trying to understand the pricing data from competitive purposes. If it is the latter, where they're stealing the competitive information on pricing, and data's getting back to a competitor, that is definitely a no-no! But if it's really to figure out where the money trail went, which is what I think most of those financial analysts are doing, especially in the CIA, or in the FBI, that's really what that probably would have been. >> Yeah, I don't think that the CIA is selling the data to your competitors, as a company, to Microsoft or to Google, they're not selling it to each other, right? They're not giving it to each other, right? So, I think the one big problem I studied with FISA is that they get the data, but how long they can keep the data and how long they can mine the data. So, they should use that data as exhaust. Means like, they use it and just throw it away. But they don't, they keep mining that data at a later date, and FISA is only good for five years. Like, I learned that every five years we revisit that, and that's what happened this time, that we renewed it for six years this time, not five, for some reason one extra year. So, I think we revisit all these laws -- >> Could be an election cycle. >> Huh? >> Could be an election cycle maybe. (laughs) >> Yes, exactly! So, we revisit all these laws with Congress and Senate here periodically just to make sure that they are up to date, and that they're not infringing on human rights, or citizen's rights, or stuff like that. >> When you say you update to check they're not conflicting with anything, did you not support that it was conflicting with Privacy Shield and some of the promises you made to Europeans? At what point did that fail to become obvious? >> It does, because there's heightened urgency. Every big incident happens, 9/11 caused a lot of new sort of like regulations and laws coming into the picture. And then the last time, that the Russian interference in our election, that created some sort of heightened urgency. Like, "We need to do something guys here, like if some country can topple our elections, right, that's not acceptable." So, yeah -- >> And what was it that your allies did that caused you to spy on us and to downgrade our privacy? >> I'm not expert on the political systems here. I think our allies are, okay, loose on their, okay, I call it village politics. Like, world is like a village. Like it's so only few countries, it's not millions of countries, right? That's how I see it, a city versus a village, and that's how I see the countries, like village politics. Like there are two camps, like there's Russia and China camp, and then there's U.S. camp on the other side. Like, we used to have Russia and U.S., two forces, big guys, and they managed the whole world balance somehow, right? Like some people with one camp, the other with the other, right? That's how they used to work. Now that Russia has gone, hold on, let me finish, let me finish. >> Yeah. >> Russia's gone, there's this void, right? And China's trying to fill the void. Chinese are not like, acting diplomatic enough to fill that void, and there's, it's all like we're on this imbalance, I believe. And then Russia becomes a rogue actor kind of in a way, that's how I see it, and then they are funding all these bad people. You see that all along, like what happened in the Middle East and all that stuff. >> You said there are different camps. We thought we were in your camp! We didn't expect to be spied on by you, or to have our rights downgraded by you. >> No, I understand but -- >> We thought we were on your side! >> But, but you have to guys to trust us also, like in a village. Let me tell you, I come from a village, that's why I use the villager as a hashtag in my twitter also. Like in village, there are usually one or two families which keep the village intact, that's our roles. >> Right. >> Like, I don't know if you have lived in a village or not -- >> Well, Bill, you're making some great statements. Where's the evidence on the surveillance, where can people find more information on this? Can you share? >> I think there's plenty of evidence, and I can send some stuff on, and I'm a little bit shocked given the awareness of the FISA Act, the Cloud Act, the fact that these things are in existence and they're not exactly unknown. And many people have been complaining about them for years. I mean, we've had Safe Harbor overturned, we've had Privacy Shield overturned, and these weren't just on a whim! >> Yeah, what does JD have in his hand? I want to know. >> The Edward Snowden book! (laughs) >> By Edward Snowden, which gives you plenty. But it wasn't enough, and it's something that we have to keep in mind, because we can always claim that whatever Edward Snowden wrote, that he made it up. Every publication by Edward Snowden is an avalanche of technical confirmation. One of the things that he described about the Cisco switches, which Bill prefers to quote every time, which is a proven case, there were bundles of researchers saying, "I told you guys!" Nobody paid attention to those researchers, and Edward Snowden was smart enough to get the mass media representation in there. But there's one thing, a question I have for Sabjeet, because in the two parties strategy, it is interesting that you always take out the European Union as part. And the European Union is a big player, and it will continue to grow. It has a growing amount of trade agreements with a growing amount of countries, and I still hope, and I think think Bill -- >> Well, I think the number of countries is reducing, you've just lost one! >> Only one. (Bill laughing loudly) Actually though, those are four countries under one kingdom, but that's another point. (Bill chortling heartily) >> Guys, final topic, 5G impact, 'cause you mentioned Cisco, couldn't help think about -- >> Let me finish please my question, John. >> Okay, go ahead. How would you the United States respond if the European Union would now legalize to spy on everybody and every company, and every governmental institution within the United States and say, "No, no, it's our privilege, we need that." How would the United States respond? >> You can try that and see economically what happens to you, that's how the village politics work, you have to listen to the mightier than you, and we are economically mightier, that's the fact. Actually it's hard to swallow fact for, even for anybody else. >> If you guys built a great app, I would use it, and surveil all you want. >> Yeah, but so this is going to be driven by the economics. (John laughing) But the -- >> That's exactly what John said. >> This is going to be driven by the economics here. The big U.S. cloud firms are got to find this ruling enormously difficult for them, and they are inevitably going to lobby for a level of reform. And I think a level of a reform is needed. Nobody on your side is actually arguing very vociferously that the Cloud Act and the discrimination against Europeans is actually a particularly good idea. The problem is that once you've done the reform, are we going to believe you when you say, "Oh, it's all good now, we've stopped it!" Because with Crypto AG scandal in Switzerland you weren't exactly honest about what you were doing. With the FISA courts, so I mean FISA secret courts, the secret warrants, how do we know and what proof can we have that you've stopped doing all these bad things? And I think one of the challenges, A, going to be the reform, and then B, got to be able to show that you actually got your act together and you're now clean. And until you can solve those two, many of your big tech companies are going to be at a competitive disadvantage, and they're going to be screaming for this reform. >> Well, I think that, you know, General Mattis said in his book about Trump and the United states, is that you need alliances, and I think your point about trust and executing together, without alliances, it really doesn't work. So, unless there's some sort of real alliance, (laughs) like understanding that there's going to be some teamwork here, (Bill laughing) I don't think it's going to go anywhere. So, otherwise it'll continue to be siloed and network based, right? So to the village point, if TikTok can become a massively successful app, and they're surveilling, so and then we have to decide that we're going to put up with that, I mean, that's not my decision, but that's what's goin' on here. It's like, what is TikTok, is it good or bad? Amazon sent out an email, and they've retracted it, that's because it went public. I guarantee you that they're talkin' about that at Amazon, like, "Why would we want infiltration by the Chinese?" And I'm speculating, I have no data, I'm just saying, you know. They email those out, then they pull it back, "Oh, we didn't mean to send that." Really, hmm? (laughs) You know, so this kind of -- >> But the TRA Balin's good, you always want to get TRA Balin out there. >> Yeah, exactly. There's some spying going on! So, this is the reality. >> So, John, you were talking about 5G, and I think you know, the role of 5G, you know, the battle between Cisco and Huawei, you just have to look at it this way, would you rather have the U.S. spy on you, or would you rather have China? And that's really your binary choice at this moment. And you know both is happening, and so the question is which one is better. Like, the one that you're in alliance with? The one that you're not in alliance with, the one that wants to bury you, and decimate your country, and steal all your secrets and then commercialize 'em? Or the one kind of does it, but doesn't really do it explicitly? So, you've got to choose. (laughs) >> It's supposed to be -- >> Or you can say no, we're going to create our own standard for 5G and kick both out, that's an option. >> It's probably not as straightforward a question as, or an answer to that question as you say, because if we were to fast-forward 50 years, I would argue that China is going to be the largest trading nation in the world. I believe that China is going to have the upper hand on many of these technologies, and therefore why would we not want to use some of their innovation, some of their technology, why would we not actually be more orientated around trading with them than we might be with the U.S.? I think the U.S. is throwing its weight around at this moment in time, but if we were to fast-forward I think looking in the longterm, if I had to put my money on Huawei or some of its competitors, I think given its level of investments in research and whatever, I think the better longterm bet is Huawei. >> No, no, actually you guys need to pick a camp. It's a village again. You have to pick a camp, you can't be with both guys. >> Global village. >> Oh, right, so we have to go with the guys that have been spying on us? >> How do you know the Chinese haven't been spying on you? (Ray and John laughing loudly) >> I think I'm very happy, you find a backdoor in the Huawei equipment and you show it to us, we'll take them to task on it. But don't start bullying us into making decisions based on what-ifs. >> I don't think I'm, I'm not qualified to represent the U.S., but what we would want to say is that if you look at the dynamics of what's going on, China, we've been studying that as well in terms of the geopolitical aspects of what happens in technology, they have to do what they're doing right now. Because in 20 years our population dynamics go like this, right? You've got the one child policy, and they won't have the ability to go out and fight for those same resources where they are, so what they're doing makes sense from a country perspective and country policy. But I think they're going to look like Japan in 20 years, right? Because the xenophobia, the lack of immigration, the lack of inside stuff coming in, an aging population. I mean, those are all factors that slow down your economy in the long run. And the lack of bringing new people in for ideas, I mean that's part of it, they're a closed system. And so I think the longterm dynamics of every closed system is that they tend to fail versus open systems. So, I'm not sure, they may have better technology along the way. But I think a lot of us are probably in the camp now thinking that we're not going to aid and abet them, in that sense to get there. >> You're competing a country with a company, I didn't say that China had necessarily everything rosy in its future, it'll be a bigger economy, and it'll be a bigger trading partner, but it's got its problems, the one child policy and the repercussions of that. But that is not one of the things, Huawei, I think Huawei's a massively unlimited company that has got a massive lead, certainly in 5G technology, and may continue to maintain a lead into 6G and beyond. >> Oh yeah, yeah, Huawei's done a great job on the 5G side, and I don't disagree with that. And they're ahead in many aspects compared to the U.S., and they're already working on the 6G technologies as well, and the roll outs have been further ahead. So, that's definitely -- >> And they've got a great backer too, the financer, the country China. Okay guys, (Ray laughing) let's wrap up the segment. Thanks for everyone's time. Final thoughts, just each of you on this core issue of the news that we discussed and the impact that was the conversation. What's the core issue? What should people think about? What's your solution? What's your opinion of how this plays out? Just final statements. We'll start with Bill, Ray, Sarbjeet and JD. >> All I'm going to ask you is stop spying on us, treat us equally, treat us like the allies that we are, and then I think we've got to a bright future together! >> John: Ray? >> I would say that Bill's right in that aspect in terms of how security agreements work, I think that we've needed to be more explicit about those. I can't represent the U.S. government, but I think the larger issue is really how do we view privacy, and how we do trade offs between security and convenience, and you know, what's required for personalization, and companies that are built on data. So, the sooner we get to those kind of rules, an understanding of what's possible, what's a consensus between different countries and companies, I think the better off we will all be a society. >> Yeah, I believe the most important kind of independence is the economic independence. Like, economically sound parties dictate the terms, that's what U.S. is doing. And the smaller countries have to live with it or pick the other bigger player, number two in this case is China. John said earlier, I think, also what JD said is the fine balance between national security and the privacy. You can't have, you have to strike that balance, because the rogue actors are sitting in your country, and across the boundaries of the countries, right? So, it's not that FISA is being fought by Europeans only. Our internal people are fighting that too, like how when you are mining our data, like what are you using it for? Like, I get concerned too, when you can use that data against me, that you have some data against me, right? So, I think it's the fine balance between security and privacy, we have to strike that. Awesome. JD? I'll include a little fake check, fact check, at the moment China is the largest economy, the European Union is the second largest economy, followed directly by the USA, it's a very small difference, and I recommend that these two big parties behind the largest economy start to collaborate and start to do that eye to eye, because if you want to balance the economical and manufacturing power of China, you cannot do that as being number two and number three. You have to join up forces, and that starts with sticking with the treaties that you signed, and that has not happened in the past, almost four years. So, let's go back to the table, let's work on rules where from both sides the rights and the privileges are properly reflected, and then do the most important thing, stick to them! >> Yep, I think that's awesome. I think I would say that these young kids in high school and college, they need to come up and solve the problems, this is going to be a new generational shift where the geopolitical landscape will change radically, you mentioned the top three there. And new alliances, new kinds of re-imagination has to be there, and from America's standpoint I'll just say that I'd like to see lawmakers have, instead of a LinkedIn handle, a GitHub handle. You know, when they all go out on campaign talk about what code they've written. So, I think having a technical background or some sort of knowledge of computer science and how the internet works with sociology and societal impact will be critical for our citizenships to advance. So, you know rather a lawyer, right so? (laughs) Maybe get some law involved in that, I mean the critical lawyers, but today most people are lawyers in American politics, but show me a GitHub handle of that congressman, that senator, I'd be impressed. So, that's what we need. >> Thanks, good night! >> Ray, you want to say something? >> I wanted to say something, because I thought the U.S. economy was 21 trillion, the EU is sittin' at about 16, and China was sitting about 14, but okay, I don't know. >> You need to do math man. >> Hey, we went over our 30 minutes time, we can do an hour with you guys, so you're still good. (laughs) >> Can't take anymore. >> No go on, get in there, go at it when you've got something to say. >> I don't think it's immaterial the exact size of the economy, I think that we're better off collaborating on even and fair terms, we are -- >> We're all better off collaborating. >> Yeah. >> Gentlemen -- >> But the collaboration has to be on equal and fair terms, you know. (laughs) >> How do you define fair, good point. Fair and balanced, you know, we've got the new -- >> We did define fair, we struck a treaty! We absolutely defined it, absolutely! >> Yeah. >> And then one side didn't stick to it. >> We will leave it right there, and we'll follow up (Bill laughing) in a later conversation. Gentlemen, you guys are good. Thank you. (relaxing electronic music)

>>from around the globe. It's the Cube with digital coverage of next level network experience event brought to >>you by info blocks. Okay, welcome back, everyone. This is the Cube's coverage of the next level networking experience. Virtual event within four blocks. I'm John Furrow, your host of the Cube. We're here in our Palo Alto, Calif. Studios as part of our remote access during Covic, getting the interviews and the stories and sharing that with you. We got a great guest here, then savages the network operations manager at Morgan School District in Utah. A customer of info blocks to share a story. Then thanks for coming on. >>Thanks for having >>me. First of all, the Red Sox had a plus interview. I would say right now is gonna go great. Go Sox. Which baseball was in season. Great to have you on. Um, >>we'll get there. We'll >>get there. Um, my Yankee fans say when I say that. But anyway, Miss baseball, um, you know. But that brings up covert 19 baseball season sports. Life has been impacted. Your district. Like many school districts around the world, we're told to shut down, send workers home. That meant sending kids home, too. So we got the educators, get the administration, and you've got the kids all going home. >>Yeah. >>What did you do to keep things going? Because then stop. They had to do the remote learning and new things were emerging. New patterns, new traffic, new kinds of experiences. What did you learn? What's going on? >>Well, first we tried to lock the doors and pretend we weren't there, but they found us. Um, really? I mean, real quickly in our school district, we're not a 1 to 1 operation, so the, uh that caused a big change for us. Um, we had to quickly adapt. And we chose to use chromebooks because that's what we have for the students to use in their classes. So getting that, uh, squared away and send out into the family's was was a big challenge. But then on top of that being the school district, we then had to decide. Okay, how do we protect and filter provide the filtering that the students are gonna need even though they're at home? So there's some relative safety there when they're online and and accessing your email and things like that. So those were. Our two are probably our two. Biggest hurdles was, you know, ramping up the devices and then and then providing, making sure, you know, the network access from a filtering and consistency standpoint was going to work. >>You know, I got to ask you because I see this kind of disruption you don't You don't read about this in the i t. Manual around disaster recovery and, you know, disruption to operations. But essentially, the whole thing changes, but you still got to connect to the network, DNS. You gotta get the access to the content. You got content, you get systems. You got security all to be managed while in flight of dealing with connection points that remote. So you've got the disruption and the craziness of that, and then you've got this big I o t experiment basically edge of the network, you know, in all over the place. You know, on one hand, you kind of geek out and say, Wow, this is really kind of a challenge is an opportunity to solve the problem at the same time, you know, What do you do? So take us through that because that's a is a challenge of locking down the security in a borderless environment. People are everywhere. The students business has to get done. You got to resolve to. The resource is >>so thankfully, we had migrated If it blocks several years ago. Um and just this last, I would say in October, I finally got us on. Ah, cloud the blocks. One threat defense Cloud portion of it too. So from a security standpoint, we already had a really good, um foundation in place from both the DNs aspect and the DNS security aspect. Um so that was to be honest, most users. It was seamless transition. In many regards, both users didn't even realize they were being, You know, pushed through the info blocks is cloud DNs server, you know, which was providing security and filtering. So that was a big plus for us because it it was less man hours. We had to spend troubleshooting people's DNS resolutions. Why sites Wouldn't you know? Maybe they weren't being filtered correctly. All that was was to be honest, perfect. Where other platforms we had previously were just a nightmare to manage, >>like, for example, of the old way versus the new way here and marital, is it? What files configuration will take us through? What? You >>know, it was like a separate. It was a separate product content filter that works in conjunction with the firewall. Um, and I'm not going to name the company's name. I don't want, you know, even though many company but it seemed with that product we were spending, on average about 3 to 4 hours a day fixing false positives just from a filtering aspect because it would interfere with the DNS. And it does. It didn't really do it. I mean, how it filters is not based on DNS. Totally right. So by migrating temple blocks are DNS and the filtering the security is all handling at the DNs level. And it was just much more, um, to be I mean, frankly, honestly, is much more invisible to the end user. So >>more efficient. You decouple filtering from DNs resolution. Got it. All right, this is the big topic. I've been talking with info blocks people on this program in this event is on how this new d d I layer DNs d XP and I p address management kind of altogether super important. It's critical infrastructure Yeah. No spoilers, Enterprise. You're borderless institution. Same thing you go to school as a customer. How does the d I lay out this foundational security play for delivering this next level experience? What's your take on that? >>Well, for our like, for a school platform, we we use it in a number of ways. Besides, I mean, the filtering is huge, but just for the ability, like, for example, one of the components is is response policy zones or DNS firewalls what they call it, and that allows you one to manage, um, traditional, like DNS names, right? P addresses you can. You can manage those by creating essentially a zone that is like a white list of blacklist rewrite. So you've got a lot of control, and again it's filtering at the DNs level, so it's looking based on DNS responses inquiry. The other aspect of that is, is the feeds that you receive from info blocks. So by subscribing to those, we, um we have access to a lot of information that info Blocks and their partners have created identifying, you know, bad actors, malware attack vectors based on again DNs, uh, traffic, if you will, and so that takes a load office. Not having to worry. I'm trying to do all that on our own. I mean, we've seen a lot of attacks minimized because of the feeds themselves. So that again frees us up. We're a very small school district. In some regards, there's a I am the only network person in the district, and there's like, a total of four of us that manage, you know, kind of the support aspect. And so, being able to not have to spend time researching or tracking down, you know, breaches and attacks as much because of the DNS. Security frees me up to do other things, you know, like in the more standard networking realm, from a design and implementation. >>Great. Thanks for sharing that. I want to ask about security as a very competitive space security here and everyone promising it different things at different security things. You know, by I gotta ask you, why did you guys decide to use info blocks and what's the reason behind it? >>Well, to be frankly honest, I'm actually in info blocks trainer and I've been training for 15 years, so I kind of had an agenda when I first took this job to help out the school district. In my experience, I've been doing working in networking for over 20 years. And in my experience, I ever boxes one of the most easy and in best managed DNS solutions that I've come across. So, um, you know, I might be a little biased, but I'm okay with that. And so I I pushed us to be honest, to get there and then from the security aspect has all that has evolved. It just makes to me it makes sense. Why not wrap the more things you can maybe wrapped together. And so you know, when you're talking about attacks, over 90% of attacks use DNS. So if I have a solution that is already providing my DNS and then wraps the security into it, it just makes the most sense for me. >>Yeah. I mean, go back. The info box is DNA. You got cricket. Liu Stuart Bailey, the founder, was this is zero. This didn't just wake up one day and decided to start up these air practitioners early days of the Internet. They know DNS cold and DNS is we've been evolved. I mean, and when it needs that when you get into the DNS. Hacks and then you realize Okay, let's build an abstraction layer. You've seen Internet navigation discovery, all the stuff that's been proven. It is a critical infrastructure. >>Well, and to be honest, it's It's one of those services that you can't can't filter the firewall right. You have to have it. You have to. It's that foundation layer. And so it makes sense that Attackers air leveraging it because the fire will has to let it through in and out. And so it's a natural, almost a natural path for them to break in. So having something that speaks native DNS as part of your security platform makes more sense because it it can understand and see those attacks, the more sophisticated they become as well. >>So I gotta ask you, since you're very familiar info blocks and you're actually deploying its great solution. But I got this new DD I Layer, which is an abstraction, is always a great evolution. Take away complexity and more functionality. Cloud certainly cloud natives everywhere. That's but if it's for what is the update, if if I'm watching this month, you know I've been running DNS and I know it's out there. It's been running everything. And I got a update, my foundation of my business. I got to make my DNS rock solid. What's the new update? What's info blocks doing now? I know they got DNS chops seeing that on it. What's new about info blocks? What do you say? >>Well, it's, you know, they have a couple things that they've been trying to modify over the last several years. In my opinion, making more DNS like a you know, like software as a service, you know, service on demand, type of approach. That's a yes. So you have the cloud components to where you can take a lot of the heavy lifting, maybe off of your network team's shoulders. Because it is, it is. Um, I think people will be surprised how many customers out there. I have, ah, teams that are managing the DNS and even the D HCP aspect that that's not really what their experiences and then they don't They don't have, ah, true, maybe background Indians, and so having something that can help make that easier. It's almost, you know, hey, maybe used this term it almost sounds like it's too simple, but it's almost like a plug and play approached for some. For some environments, you know you're able to pop that in, and a lot of probably the problems they've been dealing with and not realizing what the root cause was will be fixed. So that's always a huge component with with info blocks. But their security is really what's come about in the last several years, Um, and and back as a school district, you know, our besides securing traffic, which every customer has to do, um, we have our you know, we're We have a lot of laws and regulations around filtering with with students and teachers. So anyone that's using a campus own device And so for us this I don't think people realized that the maturity that the filtering aspect of the blocks one defence now it's it's really evolved over the last couple of years. It's become a really, really good product and, like I said earlier, just work seamlessly with the data security. So it is going to be using >>an SD Wan unpacked everything. You go regular root level DNs is it? So I gotta ask you. How is the info blocks helping you keep network services running in system secure? >>Well, I think I think we're more on just the DNs d It does R d eight DNS and DCP. So from that standpoint, you know, in the five years almost we've been running that aspect. We have had very little if if maybe one or two incidents of problems with, you know from a DNS TCP so so are our users are able to connect, you know, when they turn on their computer To them, the Internet's up. You know, there's no there's no bumps in the road stopping them from from being able to connect. So that's a huge thing. You know, you don't have to deal with those Those constant issues again is a small team that just takes time away from the big projects. You're trying to, um, and then to the being able to now combine things. Security filtering solution. Uh, that alone has probably saved us. Oh, we'll probably you know, upwards of 500 man hours in the last eight months. So where normally we would be spending those hours again, troubleshooting issues that false positives, things like that. And there's a small team that just sucks the life out of you when you have to. You always spend time on that. >>I mean, you always chasing your tails. Almost. You want to be productive. Automation plays >>a >>key role in that, >>right? Yeah. >>So I got to ask you, you know, just a general question. I'm curious. You know, one of the things I see is sprawling of devices. WiFi was a great example that put an access point up a rogue access point, you know, as you get more connections. De HCP was amazing about this is awesome. But also, you had also de HCP problem. You got the the key Management is not just around slinging more d HDP around. So you got the trend? Is more connections on the eyepiece? Not how does info blocks make that easier? Because for people who may not know, the DNS ends announcing TCP and IP address management. They're all kind of tied together. Right? So this >>is the >>magic of DD I in my head. I want to get your thoughts on how you see that. Evolving. >>Yeah, I think that's another kind of back twice. It's kind of almost like a plug and play for a lot of customer environments. They're getting, you know, you're getting the DSP, DNs and eye Pam all wrapped in once you have this product that speaks, well, those languages, if you will and that And, um along with some of the reporting services and things of that nature. Um, when I look for, like, a Mac address in my influx database, I'm not just going to get ah, Mac address and what the i p addresses. I'm not just going to get the DNs like the host name. Maybe you know, the beauty and fully qualified domain name. Either I have the ability to bring in all this information that one. The client is communicating with the DCP DNS server on top of things like metadata that you can configure in the database to help really color in the picture of your network. So when you're looking at what device is using this I p when we talk about rogue devices or things like that, uh, I can get so much more information out of info blocks that almost almost to the point where you're almost being able to nail down the location of where the devices that even if it's a wireless client because it works in conjunction with some of our wireless appointments, too. So within, you know, a matter of minutes we have almost all the information we would need to take whatever action is appropriate for something like that, that getting used to take us hours and hours to troubleshoot. >>Appreciate a lot of the other interviews I've done with the info blocks, folks. One of the things that came out of them is the trailing. You can see the trail they're getting. They got to get in somewhere. DNS is the footprints of there you got? That's the traffic, and that's been helping on a potential attacks in D DOS is, for example, no one knows what that is, but DNS is what he said. A lot of the surface areas, DNS. With the hackers are makes it easier to find things. >>Well, you know, by integrating with the cloud I've I've got, you know, that the cloud based with the blocks one, it added a advanced DNS security, which helps protect skins Adidas as well as any cast to help provide more availability because I'm pushing on my DNs traffic through those cloud servers. It's like I've I'm almost equivalent of a very large organization that would normally spend millions of millions of dollars trying to do this on their own. So I'm getting the benefits and kind of the equivalent from that cloud hybrid approach that normally we would never have have. The resource is, >>Well, then I really appreciate you taking the time out of your busy day to remote into the Cube studios. Talk about next level networking experience, so I want to just ask you, just put your experience hat on. You've been You've seen some waves. You've seen the technology evolve when you hear next level networking and when you hear next level networking experience almost two separate meetings. But next level networking means next level. Next level networking experience means is some experience behind it. One of those two phrases mean to you next level networking and next level networking experience. >>Well, to me, I always look at it as the evolution of being able to have a user experience that's consistent no matter where you're located, with your home in your office and special with in today's environment. We have to be able to provide that consistent experience. But what I think what a lot of people may not think about or my overlook if you're just, you know, more of an end user is along with that experience, it has to be a consistent excess security approach. So if I'm an end user, um, I should be able to have the access the, um and the security, which, you know, you know, filtering all that fun stuff to not just allow me the connectivity, but to bring me, you know, that to keep the secure wherever I met. And ah, um, I think schools, you know, obviously with code and in the one the one that everyone was forced to do. But I think businesses And generally I think that's, you know, years ago, Cisco when I worked with Cisco, we talked about, you know, the remote user of the mobile user and how Cisco is kind of leading, uh, the way on that. And I think, you know, with the nature of things like this pandemic, I think being able to have your your users again have that consistent experience, no matter where they're at is going to be key. And so that's how I see when I think of the network evolution, I think that's how it it has to go. >>Well, we appreciate your your time sharing your insights Has a lot of a lot of people are learning that you've got to pour the concrete to build the building. DNS becoming kind of critical infrastructure. But final question for you. I got you here, you know? How you doing? Actually, schools looks like they're gonna have some either fully virtual for the next semester or some sort of time or set schedule. There's all kinds of different approaches. This is the end of the day. It's still is this big i o t experiment from a traffic standpoint. So new expectations create new solutions. What do you see on the horizon? What challenges do you see as you ride this way? Because you've got a hold down the fort, their school district for 3000 students. And you got the administration and the faculty. So you know What are you expecting? And what do you hope to see Evolve Or what do you want to stay away from? What's your opinion? >>I think? I think my my biggest concern is, you know, making sure our like, our students and staff don't, uh, you know, run into trouble on by say that more from, you know, you know, by being, you know, being exposed to attacks, you know, their data with Delta becomes, you know, comes back to our data as a district. But, you know, the student data, I think I think, you know, with anything kids are very vulnerable. Ah, very role, vulnerable targets for many reasons. You know, they're quick to use technology that quick to use, like social media, things like that. But they're they're probably the first ones to do security Does not, you know, across their mind. So I think my big my big concern is as we're moving this, you know, hybrid, hybrid approach where kids can be in school where they're going to be at home. Maybe they'll change from the days of the week. It'll fluctuate, uh, keeping them secure, you know, protecting them from themselves. Maybe in a way, if I have to be the guy is kind of the grumpy old dad it looked at. I'm okay with wearing that hat. I think that's my biggest. Our concern is providing that type of, uh, stability and security. So parents at the end of that could be, you know, I have more peace of mind that their kids you know, our online even more. It's great >>that you can bring that experience because, you know, new new environments, like whether it zooming or using, try and get the different software tools that are out there that were built for on premise premises. You have now potentially a click here. Click there. They could be a target. So, you know, being safe and getting the job done to make sure they have up time. So the remote access it again. If you've got a new edge now, right? So the edge of the network is the home. Exactly. Yeah. Your service area just got bigger. >>Yeah. Yeah, we're in. You know, I'm everybody's guest, whether they like it or not. >>I appreciate that. Appreciate your time and good luck. And let's stay in touch. Thanks for your time. >>Hey, thanks for having me. You guys have a good rest of your weekend? Day two. State State. >>Thank you very much. It's the Cube's coverage with info blocks for a special next level networking experience. Pop up event. I'm John for the Cube. Your host. Thanks for watching. Yeah, yeah, yeah.

>>from around the globe. It's the Cube with digital coverage of next level network experience event brought to you by Info blocks Hi ups to Minuteman and welcome to the Cube's coverage of the info blocks virtual event. Digging into the next level networking experience. I'm here with John Furrier, who is the host of the event. John. We've been talking about next level networking for for a few years now. Everything's multi cloud cloud native SAS adoption, really transforming the way that we have to think about networking. Tell us a little bit about this event. >>So as you know, yeah, again go back years from when member VM Ware bought in a sexual like Okay, you know that's going to change the game software to find networking. And we love that. We were all riffing on program ability. You saw the Dev Ops trajectory hitting networking. We would say that's where the action is on this event really kind of speaks to Info Blocks as a company which is really well known for DNS. I mean, they had cricket. Liu Stuart Bailey, that really kind of the pioneers in DNS and security have constantly been adding innovation to it, but DNS is one of those things where it's kind of like not thought about, but it runs everywhere, runs the web. It is critical infrastructure and, you know D HCP. We all know what that is. We have a home router, and then he got I p address management. These have been traditionally different things for enterprises, and everyone has it. They got to deal with it. And it's really, ultimately the location and how things resolved and connect. So you know, it really becomes a foundational opportunity to figure out where the access is not only a remote access, but security. So we had a great bunch of guests looking at looking at the info blocks. Next level networking, because they bought, had an acquisition, a Cube alumni snap route recently, and this caught our attention because they were doing Cloud Native. And one of the guests we had was Glenn Sullivan. He was the founder of Snap Route. He was the the guy who did all the Siri work for Apple. So this guy knows large scale of those cloud native We had kuna Sunni, who's the runs? Corporate development in all of the products for info blocks. He kind of went into the strategy of how they're taking the I won't say boring DNs, but the critical infrastructure of DNS and how they're extending the functionality with an abstraction layer around D D I, which is DNS DCP and management. And then we had some great guests on there. We had a Craig Sanderson from info blocks. He's on there. You'll hear from him. He talked about the security and then finally a customer who's running a big school district who, with Covert 19 exposes all these challenges around what has been called the borderless enterprise. So really, next level is that, you know, how do you deal with all this stuff? And that's been a big issue. So we're gonna unpack all that in this virtual event. We have four great interviews, and so it's going to be a great program. >>Yeah, John, as you said it to some of those foundational pieces of how network is done, a lot of times runs, you know, under the radar, something you don't need to think about. But all of these changes, as we said, you know my data. My network is now highly distributed, especially I would expect that the impact of the global pandemic and work from home are really causing even more of these challenges and to think about distributed infrastructure even more. So what are some of the themes we should be looking for here? How much of them kind of tie into what we've been talking about the last couple of years in some of these cloud native worlds? >>That's great questions to I'll get into some of the themes of the program, but you brought up the covert 19 again. We've been talking about this in our reporting. You've been doing a ton of interviews following all your your stuff as well as well as all of our team. Covert 19 really exposes the aspect of critical infrastructure, and to me it's like it's the It's the great I o T experiment happening in real time. It's forcing companies saying, Hey, the work. The future of work is about workplace. The location is now home workforce. Are the people emotional? They want ease of use. They want a different experience. They're all not in the office workloads and work flows. All of them have the common word working it so I think over 19 exposes this what I call I o t experiment because everyone is now borderless. It changes the game and really puts the pressure on security network access. And ultimately, you know, the bad guys are out there so you could have someone a teacher at home or a worker at home, and they get some malware attack and they're not sophisticated, zoom or whatever they're using for tools. All that's changed and they're vulnerable. So this brings up a huge networking challenge from whether even VP ends or even relevant or not to everything. So, to me, that is a huge point. You're gonna hear that throughout the commentary that that's kind of teased out. But the real things about innovation around the cloud you're gonna hear info blocks and they're experts talk about what they're doing and how they see cloud scale and cloud native integrating into an older paradigm like DNS. And to me, that's the That's the evolution of this DD I concept. That's an abstraction layer that creates innovation opportunities but also takes away a lot of the complexities around managing all the DNS things out there and again, that's the access of the network. It's a it's a place of truth is really kind of low level, but it's really foundational. So to me, that's the main theme. And customers want ease of use into it, whether they're at home or not, and replacing the old ways to putting a box out there. That's the way it was, DNs DNs. People would manage it all. Now they want to have it provisioned, managed a manage service cloud Native Cloud operations because it's only gonna get has to get that way. >>Yeah, it's interesting, John. You know, we watched the whole wave of software defined impact networking. I think of a company like Info blocks. They've been around for decades. They're dominant in the space is that they play in. Traditionally, it would have been an appliance that you thought of for their environment you talked about. They now have the snapper out acquisition as part of what they're doing. So it just what should we be looking for? What are they really the main point? That Info Box wants to bring people together for this next level networking experience? >>Well, Glenn Sullivan was one of my favorite discussions, and he's been on. He's a cube alumni and he's so smart. He came again from Apple. He knows that he knows what large scale looks like. Snap route was really early and was one of those technologies that just, you know, it has the core DNs built in kubernetes built in. They were doing some pretty aggressive, I would call it for lack of a better word kubernetes on bare metal. They were doing stuff, but really super cool kubernetes you combine that with DNS and info blocks actually has the core DNs that's actually in every kubernetes of in the CN CF. So everything that comes out of the CN CF from a core DNS standpoint is info blocks. So yeah, they're definitely relevant in the whole CNC of Cloud Native foundation, effort around cloud native. And as that scales just micro services, you're gonna have to have this new abstraction layer and also be compatible with automation. So that's, um, we didn't go into the weeds on that, but that was essentially the head room for all the different conversations roles of cloud native and open source technologies enabling borderless enterprises because you got to have the operation side and you got to have the program ability. So you start to get into the true dev ops that we used to riff on all the time. You know, move fast, break stuff to don't break anything. Right? So ops, ops and Dev have to come together. This is where the winners and losers of networking will be determined. You gotta provide the enablement for developers, but you gotta provide the stability of an operational checklist. >>Yeah, John, I guess the last question I want to ask you before we get to the guests, You know, that operational change, You know, we saw for so many years it was, Oh, all the networking people, they're going to have to learn to code up weight. Dev ops is actually gonna spreading the information around. And maybe I won't need a particular networking team. But we understand when things go wrong, you've gotta have somebody with the expertise that could be able to dig in. What are you know, who should be listening to this? What are some of those organizational implications for what you're talking about with info blocks? >>That's a great point. I mean, the biggest challenge that I see in all this entire digital transformation as it starts to get down into the cloud native world is, most people are asking the wrong questions. They don't even know what they're talking about When it comes down to trying to compare an apple to an orange, they're really kind of disconnected on language. You got server people in networking. We know that they have different languages, and working together is key. When you think about something like DNS, that's a technical. That's an operator that's an I t person, that someone who's running critical infrastructure. But when you start to think about the security aspect of it, it's a CSO conversation. So what I'm seeing come out of this that's critical, is when you start to get into this cloud native world. You have more stakeholders in the value proposition of all this and with covert 19. As I pointed out, you know you got hacks and you got security. So when you talk with security, that's up and down the organization. That's the CSO down to the teams themselves. We have about automation horizontally scaling with Dev ops. That's multiple teams, so you have an integration kind of stakeholders. You know DNS servers, all networking. All these people have to kind of come together. So the people who should watch this are the people who are concerned about scaling the modern enterprise, which is borderless, which is code word for multiple access points and multiple connection points. R i o t um, how do you make that work? And that's the real challenge. So it's kind of like an I t a person who wants to figure out where the puck will be so they could be there when it's there and skate to where the puck is, as we say, and and the CSO of the senior people have to understand that DNS cannot be overlooked because whether it's a managed service. So So Cloudflare had a huge out into the DNS. Setting DNS takes down everything. So it's ah, it's the most fertile ground and the most targeted ground for attacks, and that is well understood. So getting the right questions in place foundational we had to set up the modern enterprise, and then that's going to be a construct for the cloud native architecture and ultimately the developer environment. So yeah, it's a topic that's kind of nerdy with DNS, But it has implications across digital transformation. >>Jonah expecting lots of conversations around security and automation how they tie into all of the modern and modernization themes. Absolutely some pieces that shouldn't be left behind. All right, John Ferrier, Thanks so much for helping us kick off. Really interested. Make sure to stick with us off to listen to all the guest interviews here that John has done the info blocks. Next level networking experience. Instrument, man. And thank you for watching the Cube. Yeah, yeah, yeah, yeah, yeah, yeah.

(bright upbeat music) >> Reporter: From theCUBE Studios in Palo Alto in Boston. Connecting with thought leaders all around the world. This is theCUBE conversation. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're coming to you today from our Palo Alto studios, talking about a really important topic. And that's data. And as we hear over and over and over, right data is the oil. Data is the new currency. Data is driving business decisions. Data drives AI. Data drives machine learning. Data is increasingly important. And we're still kind of waiting for it, to show up on balance sheets. Which is kind of implied in a lot of the big iterations, that we see in companies that are built on data. But one of the important things about data, is taking care of it. And we're excited to have our next guest here to talk about, some of the things you need to think about, and best practices in securing your data. Backing up your data, protecting your data. We're joined today by Tim Burlowski. He is the senior director, Product Management from Veritas. Joining us from remote. I believe you're in Minnesota. Tim, great to see you. >> Yep, thanks for having me. >> Absolutely, so let's just jump into it. So all we hear about is data these days. It's such an important topic, that is growing exponentially. And it's structured and it's unstructured. And it's so core to the business. And are you making database decisions? And are you getting enough data to drive your AI? And your machine learning algorithms? I mean, data is only exploding. You've been in this business for a long, a long, long time. I wonder if you can share your perspective, when you hear these things. more data is going to be created in the next 15 minutes. And wasn't the entire history of men before us? I'm making that up, but it's been quite an explosion. >> I know yeah, I know where you're coming from. And frankly, I don't even put that, in my presentation anymore. Because it's a lot like saying gravity exists, And things that you drop out, of a window will fall to the ground. Everyone's heard it. Everyone's aware of it. The numbers are just so staggering. You don't even know what to do with it. Like how many iPhones could you stack to the moon and back and then to Saturn? Doesn't make sense. But the truth is, we are seeing an explosion. Everyone knows it. We have to manage it better. Now for us, a lot of what we do, is in this data protection space. Where we want to make sure, that data is protected and always available. All of the data that's been created, and the growth in mission-critical applications. It's no longer seven to 20 mission-critical applications. It's hundreds and hundreds of mission-critical applications. Means you have to be ready, with a recent recovery if necessary. And you need to provide that data back to the consumer, as quickly as you possibly can. Because you've got people waiting on it. We've all got our apps on our phone, where we're looking at our bank account 24 seven. We don't wait until a teller appears at nine a.m anymore. It's not the world we live in. >> Right, I'm just curious if you've got some tailwinds, in terms of you're kind of, you've been in this market for a very long time. In terms of people finally realizing that their data, is really more of an asset and a liability. In the investments, to gather it, protect it, analyze it, have it ready for refresh it, If there's some problem. It's a positive investment towards, kind of revenue and strategic importance to the company, as opposed to kind of a back-office IT function, that we're kind of taking care of business because we have to. >> But that one really varies a lot by company. I see companies taking shortcuts and outsourcing, and then suddenly you'll see them in the news. And they discover that they had a major outage for a couple of days. And suddenly practices change very, very quickly. The relative comprehensive, sturdy and reliable infrastructure that people run today, sometimes lulls people into false security. And then you see a major airlines with a multi-day outage. And you go hmm, I think we missed a few steps in the process. So it sometimes takes those rude awakenings. But the companies who are really taking it seriously, and starting to practice pruning their data, examining their data for PII. So they meet various compliance regimes, and other in various states and countries. And starting to think about their backup stream, really being, how do we get a fast recovery? Instead of how do I make a copy, which I will never use again? Are really starting to drive a more efficient IT operation, when it comes to data protection. >> No, it's an interesting take, in reference to having some issue. Because we do a lot of stuff around security. Which is related to but not equal to this conversation. And one of the topics in security is that, most people have already been breached. It's just a function of how fast can you find out, and how fast can you minimize the damage? And how fast can you move on? Why are they breaching? They're breaching to get the data. So I would imagine, with this constant reading in the newspaper, of who was breached here there and everywhere, pretty much every day. That's got to be a huge driver, in terms of people kind of upping their game, and the sophistication, of the way they really think about data protection. >> It is and I'll tell you, I've had the misfortune, I would say. Of talking to customers who are in the middle of recovering, from a major ransomware malware attack. And it's a very difficult proposition. And what customers often discover is, they haven't practiced enough, they don't have enough of a DR plan present. We are certainly rising the occasion. Our products are sort of the last thing, that often stands between the customer, losing their data completely. And so we're looking at a number of technology innovations, that will enable them to store their data on immutable devices. And for the backup infrastructure, to be completely aware of that. Which we'll be announcing later this summer. Which we're very excited about. Of course, from our perspective of our appliance portfolio, we've always provided a couple of extra layers of security against intrusion detection, and intrusion prevention right out of the box. Because we know the backup infrastructure becomes this collection of the very most important data in your infrastructure. Because that's the thing you back up. And you want to restore. If there's ever any sort of manmade disaster or otherwise. >> Right. So I want to shift gears a little bit, and talk about kind of the evolution of the infrastructure kind of scene. If you will. With the rise of public clouds, with Amazon and Google and Microsoft, is sure. And then obviously, you tried into a data center. Lot of talk about HP discover, this week kind of going from edge to cloud and data center in the middle. So the environment in which these applications live, and these applications run, and where the data is, relative to those applications. Is evolved dramatically over the last, you probably have a much better time perspective than I do. Five years, 10 years. But it continues to accelerate, in this kind of Application-Centric World versus, kind of an Infrastructure Centric World. Just curious to get your take on, The kind of the challenges that presents to your company, and what you guys are trying to do to accomplish. And how do you see that continuing to evolve and get, not simpler but more complex over time? >> That is a very astute acknowledgement of what's going on in the industry. And I often call it the industry's getting weirder. I would have thought at some point, we'd sort of have Linux and Windows, and a couple of database vendors. And the truth is that database vendors exploded. And it's not just Linux anymore. It's containers. And it might be a container based on CentOS. And it might be container running in the cloud. Or it might be a simple function, like a lambda function running on nothing in AWS. And so this whole world has gotten a lot stranger. From my perspective, I think the biggest change for Veritas, has been a renewed focus on API's that we make public to customers, in ways that we can glue and stitch these systems together. Now, of course, it doesn't replace the deep integration, we do with companies like VMware, with Docker, as well as the the container ecosystem around. Open shift and some of those technologies. But from our perspective, we've had to be a little bit more prolific, in what we support. And the truth is, it's all files, it's all objects, it's all things we've done before. But they just keep bubbling up in new and different ways. >> Right, but what's interesting though, is you touch on all kinds of stuff there with Kubernetes and clouds and in containers. Is a lot of it's kind of ethereal, right? The whole idea of of a cloud-based infrastructure, is that you can bring it up and bring it down as you need it. You can adjust it as you go. And literally turn it off when you don't need it. And bring it back up. And then you add to that serverless. And this kind of increasing atomization, of all the different parts of compute. Kind of an interesting thing for you guys, to try to back up as these things are created and destructed. We hear these crazy stories of, automating Kubernetes to spin up tons of these things at a time and then bring them back back down. And then I'm curious too. Within that is also the open source. kind of challenge in continuing to have evolution in open source technologies, API's, et cetera. So it is getting weirder and weirder, on a number of fronts as you guys continue to evolve with the market. >> Absolutely, and all I'll tell you, you have to think about all technologies as being on a bridge. As I remind people, we have washing machines. They work really well but washboards still exist, even though it's a technology from 18th century, or beforehand. Now, they may be used as still do exist. Now, my point in this is, people need a bridge. Most enterprises run on an amazing amount of technology, they've developed as a stack over the last 10 to 15 years. And they can't immediately rewrite that, and put it all in a cloud container. So we're actually seeing a lot of use of containers, and Kubernetes with fairly heavy application stacks. When you think about something as heavy as, all have Oracle inside of a container. You can understand that, that's a big lift for container. And it's not ephemeral at all. Then it reaches out to storage, that has that persistence value. And that's where we come in. 'Cause we want to make sure that persistent storage, is always protected. And easily available to the customer for any recovery needs. >> Is great, so I want to shift gears a little bit Tim, to talk about regulations and compliance. 'Cause, regulatory requirements drive a lot of behavior and activity, and really oftentimes, are ahead of maybe the business prerogative to do things like provide backups, provide quick and dirty, quick and easy access. Because you needed it for, a public Freedom of Information Act request. Or you need it for some type of court type of activity. So I wonder if you can kind of talk about, how the regulatory environment, continues to evolve over time. And how does that impact, what you guys are doing in the marketplace? >> Great question. The biggest place is It's affected us, is customers are starting to think about privacy. And where do I have data which relates to, personally identifying information. And that's really driven a lot, by the European regulations around GDPR. Then we're seeing the California Privacy Act come in. And a number of other states are considering legislation in this area. In some ways, it's actually been a good news story for data protection and data management. Because people are starting to say, I should identify where the data is, I should figure out where the PII is. And I should make sure, I'm actually using my backups for the right purposes. Which is something we've always believed in. We've always thought, Hey, Mr. Customer, I see you're backing up an Oracle database for 10 years. What are you going to do with it in 10 years? Are you going to install Oracle seven and reboot it? It doesn't really add up to me. So, how can you get to a true archive, for that data you really need archive? And then for your backup set, how can you keep it lean and mean. And just keep it for the length of time you actually need it? Which for many customers, could be as little as 14, 15 days, maybe six months, maybe a year. But it's often not those extreme retentions people were thinking of, when they were building their tape based infrastructure 10 years ago. >> Right, that's funny. 'Cause as you mentioned, also I'm thinking of, is big data. Right in this constant kind of conversation. In the Big Data world is they keep everything forever, with the hopes that at some point in time, there may be a different algorithm or a different kind of process, you might run on that, but you didn't think about. Right kind of scheme on read versus scheme on right. But to your point, is that necessarily something that has to be backed up, but it sounds like a lot of, kind of policy driven activity. Than to drive the software to define what to back up, what you don't back up, how you back it up, how long you back it up? And a lot of kind of business decisions as opposed to technology decisions. >> Absolutely, that's been on the back of, the price of storing a bit of data, has declined over the last 10 years. An average 15 percent year over year. For a very long time. So people have ignored the problem. But the truth is, when you're really working at scale, there's a tremendous amount of waste. And we've identified for customers, using our data analytics technology. Millions of dollars of cost savings, where they were, both had storing files on, expensive primary tier one storage. And they were backing up those same, that same bit of information every single week. Even though it hadn't changed, or hadn't been read in seven plus years, and they couldn't find an owner for the information in the company. They literally didn't know why they had it. And I think people are starting to consider that. Especially in budget constraint times. >> Right, it's so funny, right? Sometimes it's such a simple answer, a friend one time had a startup, and he was doing contract management. This is 20 years ago. And I was like, how do you manage the complexity of contracts inside software. Again 20 years ago. And he said, Jeff, that's not it at all. We just need to know like, where is the contract? who signed it and when does it expire? And they built the business, on answering simple questions like that. It's sometimes the simple stuff that's the hard stuff. I want to shift gears a little bit Tim, on what bear toss dude in the market in terms of still having appliances? I'm sure a lot of people like weight appliances. Why are we still using appliances? This is a software defined world. And everything just runs on x86 architecture. You guys still have appliances, tell us a little bit about the why. And some of the benefits of having, kind of a dedicated hardware, software piece of equipment, versus just a pure software solution that sits on anybody's box. >> That's a great question. Thanks for asking. When I think about that world, you have to understand Veritas at its core is absolutely a software company. We build software and we preserve the choice and how the customer implements. When I say we preserve choice. We obviously still support old school Unix. We certainly have enormous investment in the x86 world, both on Windows and various Linux flavors. And of course, you can run those same That same software in the cloud. And of course, you can run it inside of a virtualized infrastructure. So we always like to preserve choice. Now why did we create the appliance business, it's frankly because customers asked us to. The thing that made storing backups on disk affordable, was this technology known as deduplication. Which at its heart is just a fancy kind of compression, That's very, very good at copies of data, where there's a lot of blocks that are have been seen before. And so we don't store them if we've seen them before. We simply store the ones that are new and fresh. So from our perspective, customers said, "we want this technology." And the market really moved away, from general purpose solutions on servers to do that. Because it was very hard to build something, that could have a very high throughput, very high memory, and at the same time, could give excellent support for random access reads, when the customer actually needed to read that data. And so we created a purpose built appliances as a result. And what we discovered in the the process was, there were a lot of pieces that were actually fairly hard in the enterprise. So when a customer would describe, the purchasing process of their typical solution before appliances, they would talk about, filing tickets with the server team. Filing tickets with the storage team. Filing tickets with security team. And sometimes taking six or nine months, to get a piece of equipment ready to install the backup software on the floor. Whereas with ours, they placed an order, it showed up on the dock, as soon as it when it was in the rack, they were ready to go and working independently. Now while we have a great and thriving appliance business, we're very, very proud of, we always preserve choice at Veritas. And even though that's the business I represent, I would make sure our customers always understand, that we're interested in the best platform for the customer. So that's our basic perspective. If you want to go deeper, let me know where you have questions. (chuckles) >> Well, I'm curious on the process, when there's a fail, when there's attack, when there's ransomware, whatever. When you need to go back to your backup. What are some of the things that your approach enables, or what are kind of the typical stumbling blocks that are the hardest things to overcome. That people miss when they're planning for that. Or thinking about it. That kind of rear their ugly heads, when the time comes that, oh, I guess we need to go back to a backup version. >> Yeah, and I'll break that input into this disaster recovery or restore process. And then also the process of backup. So when you think about that disaster recovery, and I'll use ransomware as that piece of it. Because that's the real kind of disaster, when you're looking at equipment in the infrastructure, which has been wiped clean. That's a worst case scenario for most IT managers. When you think about that situation, we've built into our appliances first of all, a hardened Linux OS. Meaning we've shrank down that OS as much as we possibly could. Second, we've added role-based access protection. To make sure that you simply can't log in and perform activities which you're not privileged to perform. And then we have intrusion protection software, intrusion detection software. To ensure that even for those zero day attacks, that we may not even be aware of when we release our software, that the system is hardened. Of course, you have firewalls and STIG rules, STIG or rules are DoD standard, for hardening Linux based devices. So we've got a hardened device. And I was talking to a customer, in a different part of the world this week. Where they described having a data center, where everything had been wiped. And there's one thing left there, their NetBackup appliances. And they were then able to then take that, and use that for the restore. Because that was a real vault for their data. Now, the flipside is, that's a rare day. So that is truly a black swan event. When you think about day to day, and we're running a data protection operation, really think about speed of backup. And for us being able to take something that's neatly tuned for the hardware, the operating system, the tuning, the net backup software is all configured out of the box and ready to go. And the data protection folks, can be independently able to drive that is a great value. Because essentially, you have Lego style building blocks. Where you can order device, it always performs the same. And three years from now, you don't have to redesign it. And take your expensive IT staff and ask them to figure out what's the best solution. We've just got another one off the shelf for you, another series in the model. >> Right >> Now, as you said earlier, the world's getting weirder. It definitely is. So we'll be branching off into what kind of appliances we offer. And you'll see some announcements later, in the year where we'll be offering some reference architecture approaches, which will be a little different than what we offer today. Just to meet the customer demand that's out there. >> Yeah, that's great. I mean, 'cause as you said, it's all about customer choice. And meeting the customer where they want to meet. But before I let you go, this is pretty interesting conversation. I want to get your perspective, as someone who's been in the business, for a really long time. And as you look at opportunities around, machine learning and artificial intelligence, and you look at kind of the I'm going to steal your line about things getting weirder. And use over and over. But as they continue to get weirder and weirder, where do you see kind of the evolution is, you kind of sit back, not necessarily in the next six months or so. But where do you see growth opportunities and places you want to go? That better still out in front of you, even though you've been doing this for many, many years? >> Well, that's a great question. So this is yet another wave. And that's often how I look at it. Meaning, there's a wave of Unix. There's a wave of windows. There's wave of virtualization. And each of these technologies, brought some real shifts to our environment. I think, from my perspective, the next big wave is dealing with ransomware. And some of these compliance requirements we talked about earlier. And then I can't get away from this big data, AI piece and my son's studying computer science in college. And that's a weekly conversation for us. What's new in that front? Because I think we're going to see, a lot more technology developed there. We are just truly on the beginning of that curve. And frankly, when I think about the companies I work with, they have a tremendous amount of data. But that's really only going to increase, as they realize they can actually develop value from it. And as you mentioned, first thing once it shows up on the balance sheet, suddenly everyone's going to get very excited about that. >> Yeah, it's so funny, right? 'Cause it basically does show up on the balance sheet of Facebook, and it shows up on the balance sheet of Google. But it's just not a line item. And I keep waiting for the tipping point, to happen where that becomes, a line item on the balance sheet. Because increasingly, that is arguably, the most important asset. 0r certainly the information and learning that goes around that data. >> You're right. And frankly, it's an insurable asset at this point. You can go to a company in a number of commercial settings and get ransomware insurance, for instance. So people are definitely recognizing the value of it if they're willing to insure it. >> Right, right. All right, Tim. Well, thank you very much for stopping by. And giving us an update really interesting times in, kind of taking care of business and really the core of the business, which is the data inside the business. So, important work. And thanks for taking a few minutes. >> All right, thanks. I'll be glad to be back anytime you want me. >> Alright, He's Tim. I'm Jeff. You're watching theCUBE. Thanks for watching. We'll see you next time. (upbeat music)

>> Announcer: From around the globe, it's theCUBE, with coverage of SUSECON Digital, brought you by SUSE. (upbeat music) >> Welcome back. I'm Stu Miniman and this is theCUBE's coverage of SUSECON Digital. And really excited to welcome to the program a first time guest, and he's relatively fresh off the keynote, Alexander Kocher, who is the President and Managing Director of Elektrobit, talking about autonomous vehicles. Alex, thanks so much or joinin' us. >> Thank you, Stu, for inviting me. >> All right, so you know, definitely really interesting technologies, and a lot of talent. So many of the ways we talk about in the IT industry, to talk about cloud computing, edge impacting things, how AI fits into the world, and the balance between people and technology. Well, your company's living it. So why don't we start a little bit. Elektrobit, at least from the research I've done and from the keynote, you are a software company if I have it right. And autonomous vehicles is really what you're driving for. But give our audience a little bit of Elektrobit where you fit in the market today. >> Yeah, Elektrobit, so you can say we are software creatrs unlocking the future of mobility. We are pioneering software in the automotive industry since more than 30 years, empowering already now more than 1 billion devices, in hundreds of millions of cars, and serving since more than 30 years the automotive industry. So as software is becoming the second biggest enabler of the innovation in the car, we are driving this with our technologies. We are focusing on software infrastructure solutions, so coming from the deep, deep layers in the car, up to the HMI, up to the user interface, and providing there specific technologies for really building the basis, and able our customers to focus on their innovations. So this is car infrastructure software. This is software for autonomous driving, as you said. And this is application software mainly in the tooling to create fancy and good-looking user interfaces in modern vehicles. >> Yeah, wow, 30 years. You know most people don't think about software that long in the automotive industry. Of course anybody that owned a car understands that a lot of times it no longer, ya know, people going under the hood, but they're plugging something in and going on a computer, understand what that is. If you could, give us a little bit, what are the trends going on? We've been talking for the last couple a years, if you talk from an autonomous vehicle stand point. Probably people have seen the five stages model that's been put out there, everything from some driver-assist technologies, to a fully autonomous vehicle. But what are you seeing, your software, the companies you supply to and the users, what's happening there? >> So, I would class the trends at the moment in our industry in three blocks. There is electrification, where software is for sure playing a role, but is more used as a supporting technology. Here dominating innovation is coming from other technologies like battery, fuel cells, charging mechanisms, and so on. But then the second trend and the third trend, automated driving and connectivity, to really make the car part of the internet, these are two mega trends where software is dominating the scene, and really also dominating the value of the car as well. And I think these are the trends. We need for all of those to develop new car connectors, similar to server infrastructures already, so that you can seamlessly integrate applications, services from the cloud into the car. And I think these are the trends. And the partnership we are the moment working with SUSE is really coming into play as well to combine experiences from other industries, from other technologies, open source technologies with the embedded world. And create added value for our customer. >> Yeah so let's dig into that SUSE partnership a little bit. Obviously community is a big thing that's talked about there, at the show and from SUSE's customers. There's what can we learn, what is the role of open source, and how do we really enable innovation? So what's important about the partnership with SUSE? >> I think, let me give a little bit of a background. So when becoming an IT device, the amount of software, the complexity is increasing like hell. What he have at the moment, round about 10% created by software in the car, we will see 30% value created by software in 10 years from now. And this is done by a disruptive change in the development model. At the moment we stopped developing functions and features at the point when we introduce the car into the market. This will completely change. Just think about a mobile device like I have it here in my hand. During the whole life cycle of this device, which is of course much shorter than the life cycle of a car, you will innovate and update functions here. This will also be introduced in the next generation, which is under development at the moment, of cars. So that you can update applications, new services during the whole life cycle of the car. And this requires new platforms. It doesn't stop at the introduction of the car. It will continue over a real, real long period of time, years it takes, even. We have a long maintenance cycles. And therefore you need to have new partnership models, and also other technologies where this is already applied with other technologies in other industries. And here our partnership really comes into play, where we need to even get other talent pools. other pools of creativity, other pools of and forces of innovation, so that we really enable with existing methods, new methods, our customers to focus on their differentiating functions to compete against their competitor. And here exactly our partnership is targeting it. >> Okay so it sounds like we're talking specifically Linux means that there's a common underlying programming model, and that there's a skill set pool out there. Am I getting that right? >> Yes, correct. At the moment, so the automotive industry stands for reliable, high performance, high quality of cars and maintaining these features and essential functions over a long, long period of time. But when using embedded technologies, you are endangered always to re-implement it again and again and reuse is not necessarily that what is implemented here from one generation to the other, completely innovated sometimes, And here with other technologies, like you're doing with Linux for example, an open source, you open up a complete new field of innovation and creativity, and of course also access to talent pools, which is very much limited at the very moment in the embedded world as well. >> Alex, I'm curious how Elektrobit thinks about data. Number one, all the training data, how AI is done. Is there any industry sharing going on with that discussion? Let's start there and then maybe we'll talk a little bit about security when we get through the basic data points. >> (laughs) Yeah so, indeed, just think about cars. One of the most accurate sensor in our environment, with all the sensors you have, camera sensors, radio sensors, liter sensors, and so on and so forth, which create a hell lot amount of data, a terabyte by day. And of course this is something which needs to be shared, because the road infrastructure, we talked about this beforehand, is the same independent, whether it's a BMW car, whether it's a GM car, whether it's a Ford car, or a Daimler car, or a Toyota. So it's for all the cars the same car infrastructure. And of course there's a lot of discussion ongoing to share this data. Although now when making business out of that, the business model needs to, as you mentioned, for sure recognize and respect the privacy of the data in order to make business out of that. >> Excellent-- >> So then--Sorry >> Please, please continue. >> So yes, I think there is discussion ongoing. And already in, for example, in map data and traffic control, there is already ongoing the share of the data amongst the manufacturers as well. >> Excellent. And of course, security is paramount. When I look at Elektrobit, cyber security is prominent in the automotive discussion. How does that play in? What's the experience that you've had there from the security side. >> Yeah, so Elektrobit, so we built up our security, but really coming from inside the car. Now three years ago we acquired a company with out mother company together which is now integrated and consolidated within Elektrobit. It's called Argus Cyber Security from Tel Aviv in Israel. And with that we are now able to really provide solutions, end to end solutions from deep inside the car up to the cloud, so that the data stream is secure to the highest standards of security, of course. And this is, on the long side, really securing remote control, maintenance of the car, but also then privacy in terms when you download new services, when you provide information into the cloud where you are. For example we talked abut this data as new currency from the sensors existing in the car. So for that reason exactly we acquired this company with their technologies we are able to provide end to end solutions also for the existing software we are providing to our customers. >> Right, Alex, I'm curious just when you talk about autonomous vehicles, anything distinct about Europe? I think about the challenge and the opportunity. Number one, you're in Germany. You've got some of the best highways in the world. Well thought-out, really well architected. But throughout Europe you also have some the oldest cities where it could be really challenging to traverse. So anything different you might be able to share with our audience about what we should look for for that journey of autonomous vehicle in Europe? >> So... basically your question, already lined it out. So yes, I think autonomous driving and it's starting with functions like hybrid pilot so that you really create a kind of a clean room, where you have a very well-defined environment, where you can start to drive autonomous, and really hands off, eyes off, so level three, level four. In old cities, the structure is yeah, grown, grown over hundreds of years. So it's for sure not foreseen for autonomous driving, at that point in time. Or let's say at that point in time you had an autonomous vehicular horse which found all the time the stable. But nowadays it's a little bit different. So the more difficult environment is for sure the center of cities. And there it will take a while. But we are on the go by going really step by step from a very well-defined environment like a highway, where you can define certain use cases. And with the evolution of sensors, with the evolution of algorithms, with the evolution of processing power, then go step by step to a more complex environment like inner cities. >> Excellent. What should people be looking for when it comes to autonomous vehicles? What can you give us on the next 12 to 24 months, what you're expecting in the industry? >> So I think at the moment, I think in the 12 to, we're still in the face when it comes to autonomous driving, we have driver assistance functions evolving from there. A level two, level two plus. Level three functions where you really then have hands off, will probably come in two, three, four years. Here it's not only the industry by itself who is the limiting factor, but also the regulations on the outside. We just recently saw the announcement of Audi that homologation related to topics at the moment not clear. This is also to be considered. Technology is already prepared, ie, I'm now, even with driver-assistance functions, able to drive. I had an experience with my car by 200km/hr around the curve, and pulling the steers a little bit off So it's still in the face. You have to be aware that you can control. So the function itself is already existing. But homologation that you really can do this for more than 10 seconds, this is the critical thing. And really be prepared techonology for all the eventual things. So here we have limiting factors also from the regulations around that. And this is basically what we have to deal with. So just recently announced by Audi A8 in the introduction. >> Excellent stuff. All right, Alex, I want to give you the final word. Just share with the audience at SUSECON, what it means for Elektrobit to participate in this partnership. >> Yeah, I think the main thing of this partnership is really that we... We are enabled to really provide and infrastructure which fulfills the complete requirements of the car industry. So long-term maintenance, enablement of secure downloads during the whole life cycle of the car, and reusabilty, backward compatibility which is very important thing as well, when you produce technologies for products which have a very long product life cycle. And with the experience SUSE brings into play from other industries, with their solutions, with their Linux distributions and container technologies, with our experience from the automotive industry, I'm really sure that with that partnership, we enable our customers to focus on their innovations, and we enable ourselves to provide the basic solutions for the industry, and for... new future intelligent vehicles. >> All right, well, thank you so much for sharing all of the updates. Fascinating stuff. Thank you so much for joining. >> Thank you, Stu, for inviting me. >> All right, lots more coverage from SUSECON Digital '20. I'm Stu Miniman and thank you for watching theCUBE. (upbeat music)

(upbeat music) >> Announcer: Live from San Francisco, celebrating 10 years of high-tech coverage, it's theCUBE, covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> Welcome back to theCUBE. Two sets, wall-to-wall coverage, our 10th year. We actually call this one the Valley set, over on the other side, it's in the middle of a meadow, and this was in the valley. I'm Stu Miniman. My cohost for this segment is, of course, John Furrier, the founder of SiliconANGLE. And joining us, the quintessential Valley guest that we have, Jerry Chen. Long time participant in the program, climbing up the leaderboard here of theCUBE Times at VMworld. Jerry, thank you so much for joining us. >> Stu, John, thanks for having me back. >> All right, so we knew you back when you worked for VMware. >> Jerry: Right. >> You're now a partner at Greylock. We watched some of your amazing startups, we've had many of them on our program. Just a little bit going on in your world this day, maybe we'll start there. >> Sure, it amazes me, both being at VMworld 10 years since you guys started covering. For me, I joined VMware back in 2003. So I was at the first Vmworld, through every single one of them, and seeing this ecosystem reinvent itself, and juxtapose that with every other conference at Moscone. So Dreamforce, Oracle OpenWorld, VMworld. And I would say five years ago, no one would have thought Dreamforce itself, or Salesforce as an ecosystem big enough for investors. But yes, now they can invest in startups. All they do is sell to the Salesforce ecosystem. You can always invest in a startup. All they sell to is the VMware ecosystem. And for sure, when, you and I, three of us go to Amazon or an event, that ecosystem just continues to grow exponentially year over year. >> And this some of the highlights of Datadog, we were talking before we came on camera. They always had a big booth, they bet on the AWS ecosystem, not a lot of Datadog here, but monitoring turns into observability, a key component, which basically was a white space. I mean, monitoring was boring. A little sector, but because of the nature of the data security auditing, this has become kind of a killer category. >> I think last week you saw SignalFX get acquired by Splunk, which is another huge enterprise company, and Datadog filed their S-1. No one thought monitoring would be a big enough market to support multiple billion plus companies, and what we've learned is making a bet on just cloud-native companies like Datadog did, purely in the Amazon Ecosystem, was a great bet because they've grown super fast, and that market turned out to be very big. In addition, it could be Splunk, and they could bet on logging for mostly on-premise companies. That turned out to be a large market. So I think five, 10 years ago, no one thought that these markets would be so big and so gigantic. The cloud itself, you can have a multi-billion dollar company like Datadog purely on a cloud-native application and cloud-native companies, if you will. >> You know, it's interesting, you're a VC and the enterprise specialist at Greylock. Consumer used to be all the rage in venture. "Oh, we're going to consumer against Facebook," Facebook breaks democracy, all kinds of problems. Being regulated. But enterprise became really hot with the cloud, and then you have an interesting dynamic. Now a thousand flowers are blooming on the startup side, so yes, there's a lot of action in startups, but the buyers of startups and the IPO markets is where the liquidity happens, which you care about, right? So now you have liquidity options for IPO for fast-growing flit scalers as you guys call it, and then the M and A market are buying the companies. So I got to ask you, with seeing Splunk as a great example, where they own the log market, log files, bring SignalFX in, former VMware guys and Facebook guys, comes in, they add some servability piece to it. Splunk's got more power now because of the acquisition. It's not just token acquisition. This is the market, product market slash M and A market. What's your thoughts on that? Because that's a key exit opportunity, and the numbers are pretty sizable when you think about it. >> I think just going back to the opportunity, the market's so big that you have multiple multi-billion dollar companies, so like Splunk's a huge company, great company. We're investors in a company called Sumo Logic. That's going to also be a successful company, and also a big-- >> John: And filed for IPO. >> And a big company that's OZA, Amazon, and Vmworld. So I think what you have here is each of these markets are monitoring, APM, the log, infrastructure, are turning out to be multi multi-billion, and larger than we anticipated. So I think before, to your analogy in the consumer, we always knew consumer markets had huge TAMs. Like how many billion in people are on Facebook? How many billion people are on Twitter? What we're learning now is the market and the TAM for these enterprise software companies, be it SAAS, be it LOG, be it Metrics, be it security, those TAMs are actually bigger than we thought beforehand as well. >> And the driver of that is what? Cloud, transformation, just replatforming, modernization? The businesses are businesses still. >> I think the move to cloud is accelerate, I think your last line, "businesses are businesses," is what's key. Like every business now is being touched by software. They all got to go cloud so I'm an investor in a company called Blend that does mortgage software. So the entire financial services industry, from mortgages to car loans and consumer lending, that's all going digital. That's all going online. Jobs that were like mortgage brokers are going to be an app on your phone now. So finance, retail, healthcare, construction, so all these markets now are going to the cloud, going digital, so these TAMs are expanding exponentially. >> Yeah, Jerry, want to get your take on the ecosystem. You know, we look at VMware, they built a big ecosystem, the end user computing space, you know. You've coined the term Virtual Desktop Infrastructure, from that environment there was an ecosystem around there. I see VMware at a lot of shows, and they have a good presence there, and there's some overlap between the public cloud space. Like when I go to this show, and I walk through the expo hall, oh my gosh. Data protection is everywhere, and all of those companies are at a all of the cloud environment, but do you see a transition from, you know, where VMware is in kind of the cloud-native space? Is there a lot of overlap, or what's your thinking on those kind of dynamics? >> I think all above. I think VMware at Vwworld, and like all these tech companies are constantly reinventing themselves and expanding. So you have, as a VC, say it's this company I'm looking at, when it's two individuals, and a dog, and PowerPoint. Is it a feature, is it a product, or is it a company? It's a feature, it's okay. You know, it's probably not worth the investment, but it's worthwhile. It'll get acquired for something. Is it a product? Some companies are just one killer product, right? And you can ride that product for the arc of the company. But then some startups turn out be companies, multi-product companies. And there always have one or two great products, and then you start adding new things as the market evolves, and VMware has done that. And so, as a result of adding server virtualization, desktop virtualization, Cloud Foundry which I helped build, out in the Kubernetes stuff. So they're adding multiple products to their company. I think the great companies can do that. Look at Amazon. They keep launching 10 new products every single month. Microsoft has done a great job reinventing themselves. So I think the great companies can reinvent, but not transform, they just add to what they have, and just to be a multi-product family. >> Stu: All right, so you mentioned Cloud Foundry. >> Yeah. >> Pivotal, of course, is now back in the mothership where it started there. When Cloud Foundry first started it was, "Well, we're not going to take the hypervisor "and put it all of these places." We needed a slightly different footprint. Well, five years later, we're talking about Kubernetes is going to be baked into Vsphere, and Vsphere is going to be a main piece of VMware's cloud-native strategy. Has the market changed or some of those technology pieces, you know, still a challenge? What's your take there? >> You know, it's a great question because I think what we're seeing is there's never ever in technology as you guys know, on platforms, it's a zero-sum game. It's never always going to all mainframe, all client server, all VMs, all microservers, all Serverless, right? And I think we're seeing is it's also never going to be all Amazon, it's never going to be all Google, it's never going to be all Azure, right? I think we talked about early days, it's not a winner take all. It may be, you know, what one-third, two-thirds, or something, 25-40% market share, but it's not going to be all or nothing. And so we're seeing companies now have architectures on multiple clouds, multiple technologies, and so just like 10 years ago, you had a mainframe team, you had a Windows team, you had a Solaris team. Remember Sun and Spark? And a Linux team. Now you have a Google team, and Azure team, an Amazon team, and an on-prem team. And so you just had these different stacks evolve, and I think what's interesting to see is like, we've kind of had this swing of momentum around Docker, Containers, Kubernetes, Serverless, but at the same time you see a bunch of folks realize, okay, what's happening is I'm choosing how much I want to consume. Like an API, a container, or a whole VM, right? And people realizing, yes, maybe consuming the APIs is our right level of consumption, but quite frankly, Stu, John, buying whole VMs also what I want. So you see a bunch of companies say, I'm just going to build better monolithic applications around VMware, I'm going to build better microservices around Docker and Kubernetes, and then we'll use Serverless where I think I need to use Serverless. >> Yeah, that's a good point. One of the things we hear from customers we talk to, and there's two types of enterprise customers, at least in the enterprise infrastructure side, classic CIOs and then CISOs. Two different spectrums. CIOs, old, traditional, multi-vendor means a good thing, no lock in, I know how to deal with that world. CISOs, they want to build their own stacks, manage their own technology, then push APIs out to the suppliers, and rechange the supplier relationship because security is so important they're forced to the cutting edge. So I look at that a kind of canary in the coal mine, and want to get your thought on that, because we're seeing a trend where enterprises are building software. They're saying, hey, you know, I want a stack internally that we're going to do for a variety of different reasons, security or whatever, and that doesn't really blend well for the multi-cloud team approach, because not everyone can have three killer teams building stacks, so you're seeing some people saying, you know, I'm going to pick a cloud here and go all in on certain things, build the stack, and then have a backup cloud there. And then some CIOs say, hey, you know what? I want all the cloud guys in there negotiating their best price maybe, or whatever. >> I think it's great nuance you pointed out. Even just like we had a Windows team and a Linux team, you still had a single database team that ran across both, or storage teams are ran across both. So I think the nuance here is certain parts of the stack should be Azure, Amazon, VMware. Certain parts of the stack should be, I think that the ultimate expression is just an API with service errors. So one of the companies you guys are familiar with, Roxette, it's a search and Serverless analytics company. It's basically an API in the cloud, multi-cloud, to do search and analytics. And just like you had a database team that's independent across all these stacks, for certain parts of the architecture, you're going to want something like Roxette, that's going to be independent of the architecture stacks. And so it's not all isolated, it's not siloed, it's not all horizontal, depending on the part of the stack, you're going to either want a horizontal cross-cloud solution, or a team that's going to go deep on one. >> So it's really a contextual decision based on what the environment looks like, or business. >> And there's certain areas of technology that we know from history that lends themself to either full stacks versus horizontals. Just like I said, there was a storage team and a database team, right? That's Oracle, or something that ran across Windows and Linux and Sun, you're going to see someone like Roxette become this search and Serverless analytics team across multiple cloud stacks. >> This is why the investment is such a great opportunity for the enterprise VCs right now because, I mean, there's so many dimensions of opportunities for companies to grow and become pretty large, and the markets are shifting so the TAM is pretty big. Michael Dell was just on the other side, I interviewed him. He says, you know, he was getting kind of in Dave's grill saying, "Well, the TAM for enterprise is bigger than cloud TAM." I go, "Well that TAM is going to be replatformized, so like that's going away and moving, shifting, so the numbers are big but they're shifting so tons of opportunities. >> It depends if you're a big company like Dell versus a small startup. Oftentimes, this true that the TAM for enterprise is still much larger than cloud, but your point is what's shifting were the dollars growing fast. >> The TAM for horses was huge at one point, and then, you know, cars came along, right? So you know. >> Every startup, what you want to do, you want to attach to a growing budget. You don't want to attach to a flat to shrinking budget. And so right now, if you're a founder, and say, "Okay, where are the budget dollars flowing to?" Everyone's got a kind of a cloud strategy, just like they had a VMware virtualization strategy, so if I'm like a startup G, metrics, or data analytics, I'm going to try to attach to where the dollars are flowing. That's a cloud strategy, that's an AI application strategy, security strategy. >> So let me ask you one question. So if I'm going to start up, this is a hypothetical startup, startups got an opportunity. It's a SaaS-based startup, they say, "You know what? "This is a feature in the market "that's part of a bigger system, "but I'm going to innovate on that." I think that with the markets shifting, that could evolve into a large TAM to your point about Datadog. What's the strategy, from an investment standpoint, that you would take? Would you say go all in on the single product? Do you want to have one or two features? What's the makeup of that approach, because you want to have some maybe defensibility, is it go all in on the one thing and hope that you return into like a Salesforce, then you bolt stuff on, or do you go in and try to do a little platform play underneath? >> It depends where you are in the startup world. We're in lifecycle. Look, startups succeed because they do one thing better, right? And so focus, focus, focus. And you have to have something that's like 10 times faster, 10 times better, 10 times cheaper, or something different. Something the world hasn't seen before. But if you do that one thing well, either A, you're taking budget dollars from incumbents, or B, you're something net new, the world hasn't seen, people will come to you when they see utility. As an investor I like to see that focus, I like to see, you know, some founders you get say, hey, Stu, think bigger. Some founders like John think smaller. Like what's your wedge? What's that initial entry point to the customer you're going to hit? Because once you land that, you get the right to do the next product, the next feature. >> That's the land, adopt, expand, like Xoom did. Or they picked video, >> Correct, voice, et cetera. >> I mean who the hell thought that was going to be a big market? It's a legacy market but they innovated with the cloud. >> Absolutely. I have all these sayings that I try to say like, "You don't get to play the late innings, "if you don't make it out the early innings," right? You know, and so if you want and have this strategy for this large platform, that's great, and every VC wants to see a path there. But they want to see execute from we're going to land, and we're expand. Now, startups fail because either where they land, they picked incorrectly. Like you decided to storm the wrong beach, right? Or it's either to small, or it's too big. The initial landing spot is too big, and they can't hold that ground. And so part of the art of navigating from Point A to Point B, or where I say, Act one, Act two, Act three of a lifecycle is make sure that you land correctly, earn your keep, show a lot of value, win that first battle, if you will, Act one, and then they move to Act two, Act three, and you can see a company like VMware clearly on their second, third act, right? And they've done a nice job of owning one product category, server virtualization, desktop virtualization, now expanding to other adjacent categories, buying companies like Carbon Black, right? In terms of security. So it doesn't happen overnight. I mean, VMware started in 1998. I was there when there was about 200 employees. People forget Amazon's been, gosh 27, 1998, when Bezos started selling books. Now they're selling books, movies, food, groceries, video, right? >> When did you first use AWS? Was it when the EC2 launched? I mean, everyone kicked the tires on that puppy. >> We all kicked the tires. I was at VMware as a Product Manager, I think it was '06 when they launched, right? And we all kind of kicked the tires on it. And it was a classic innoverse dilemna. We saw this thing that you thought was small and a very narrow surface area. Amazon started with an EC2, >> Two building blocks, storage and EC2. >> S-3, right, that's it. And then they said, "Okay, we're going to give a focus, focus on basic compute and basic object storage," and people were like, "What can you do with S-3? "Nothing," right? It's not a Sand, it's an availability. It's going to fail all the time, but people just started innovating and working their way through it. >> All right, so Jerry, when you look at the overall marketscape out there today, it seems like you still feel pretty confident that it's a good time for startups. Would you say that's true? >> Absolutely. >> All right, I want to get your final word here. 10 years in theCUBE at Vmworld, you know, you've known John for a long time. Did you think we'd make it? Any big memories as to what you've seen as we've changed over the years. >> I've plenty, let's go back to, >> John: Okay, now you can embarrass us. >> 10 year anniversary of VMworld. For your first Vmworld 10 years ago, I was like a Product Manager, and John Furrier, I think I met at a Press dinner, and he's like, "Hey, Chen," walking by, "come here, sit down," and they turn the camera on, and we had no idea what was going on, and he just started asking a bunch of random questions. I'm like, sure, I haven't cleared this with marketing or anyone else, but why not? >> John: Hijack interview, we call that. >> Hijack interview, and then it's been amazing to watch the two of you, Dave, John, everybody, grow SiliconANGLE and theCUBE in particular, and to this, the immediate franchise, in terms of both having a presence at all these shows, like Amazon, Oracle World, DreamForce, Vmworld, etc. But also the content you guys have, right? So now you have 10 years of deep content, and embarrassingly enough, 10 years, I guess, of videos of yours truly, which is always painful to watch, like either what I was saying, or you know, what my hair looked like back then. >> Stu: Jerry, you still have hair though, so. (laughing) >> Well, the beautiful thing is that we can look at the reputation trajectory of what people say and what actually happens. You always had good picks, loved the post you did on MOATs. That turned out to be very timeless content, and yeah, sometimes you miss it, we sometimes cringe. >> We miss a bunch. >> I remember starting one time with no headset on. Lot of great memories, Jerry. Great to have you in the community. Thanks for all your contribution. >> I look forward to the next 10 years of theCUBE, so I got to be here for the 20th anniversary, and now if I walk away, come back on right away, do I get another notch on my CUBE attending list so I can go up and catch Hared in the best? >> If you come on the other set, that counts as another interview. >> Perfect, so I got to catch up with Steve and the rest of the guys. >> Steve just lost it to Eric Herzog just a minute ago. We had a ceremony. It was like a walk through the supermarket, the doors thing, and the confetti came down. 11th time so you got to get to 11 now. So 12 is the high water mark. >> Done, we need t-shirts. (laughing) >> Well Jerry, thanks so much for joining us again. For John Furrier, I'm Stu Miniman, and you can go to theCUBE.net, if you search for Jerry Chen, there's over 16 interviews on there. I know I've gone back and watched some of them. Some great discussions we've had over the years. Thanks so much, and stay tuned for lots more coverage here at Vmworld 2019. Thanks for watching theCUBE. (upbeat music)

from San Mateo its the cube covering scaler innovation day brought to you by scaler Livan welcome to the special innovation day with the cube here in San Mateo California heart of Silicon Valley John for the cube our next guest as Steve Newman the co-founder scaler congratulations thanks for having us you guys got a great company here Thanks yeah go ahead glad to have you here so tell the story what's the backstory you guys found it interesting pedigree of founders all tech entrepreneurs tech tech savvy tech athletes as we say tell the backstory how'd it all start and had it all come together so I also traced the story back to I was part of the team that built the original Google Docs and a lot of the early people here at scaler either were part of that Google Docs team or you know they're people we met while we were at Google and really scaler is an outgrowth of the it's a solution to problems we were having trying to run that system at Google you know Google Docs of course became part of a whole ecosystem with Google Drive and Google sheets and there's that you know all these applications working together it's a very complicated system and keeping that humming behind the scenes became a very complicated problem well congratulate ago Google Docs is used by a lot of people so been great success scale is different though you guys are taking a different approach than the competition what's unique about it can you share kind of like the history of where it's going and where it came from and where it's going yeah so you know maybe it'd be helpful like just to kind of set the context a little bit to the blackboard yeah so you know I you know I talked about it's kind of probably put a little flesh on what I was saying about you know there's a very complicated system that we're trying to run in the whole Google Drive ecosystem too there are all these trends in the industry nowadays you know the move to the cloud and micro services and kubernetes and serverless and can use deployment is all everything like these are all great innovations makes you know people are building more complex applications they're evolving faster but it's making things a lot more complicated and to make that concrete imagine that you're running an e-commerce site back in the calm web 1.0 era so you're gonna have a web server maybe a patchy you've got a MySQL database behind that with your inventory and your shopping carts you may be an email gateway and some kind of payment gateway and that's about it that's your that's your system each one of these pieces involved you know going to Fry's buying a computer driving it over the data center slotting it into a rack you know a lot of sweat went into every one of those boxes but there's only about four boxes it's your whole system if you wanted to go faster you threw more hardware at it more ram exactly and like and you know not literally through but literally carried you literally brought in more hardware and so you know took a lot of work just to do the you know that simple system fast forward a couple of decades if you're running uh running an e-commerce site today well you know you're certainly not seeing the inside of a data center you know stripe will run the payments for you you know somebody's on will run the database server and say you know like this is much much you know you know one guy can get this going in an afternoon literally but nobody's running this today this is not a competitive operation today if you're an e-commerce today you also have personalization and advertising based on the surf service history or purchase history and you know there's a separate flow for gifts and you know then printing the you know interfacing to your delivery service and and you know you've got 150 blocks on this diagram and maybe your engineering team doesn't have to be so much larger because each one of those box is so much easier to run but it's still a complicated system and trying to actually understand what's working what's not working why isn't it working and and tracking that down and fixing it this is the challenge day and this and this is where we come in and that's the main focus for today is that you can figure it out but the complexity of the moving parts is the problem exactly so you know and so you see oh you know 10% of the time that somebody comes in to open their shopping cart it fails well you know the problem pops out here but the the root cause turns out to be a problem with your database system back here and and figuring that out you know that's that's the challenge okay so with cloud technology economics has changed how is cloud changing the game so it's interesting you know changes changes the game for our customers and it changes the game for us so for a customer you know kind of we touched on this a little bit like things are a lot easier people run stuff for you you know you're not running your own hardware you're not you know you're often you're not even running your own software you're just consuming a service it's a lot easier to scale up and down so you can do much more ambitious things and you can move a lot faster but you have these complexity problems for us what it presents an an economy of scale opportunity so to you know we step in to help you on the telemetry side what's happening in my system why is it happening when did it start happening what's causing it to happen that all takes a lot of data log data other kinds of data so every one of those components is generating data and by the way for our customers know that they're running a hundred and 50 services instead of four they are generating a lot more data and so traditionally if you're trying to manage that yourself running your own log management cluster or whatever solution you know it's a real challenge to you as you scale up as your system gets more complex you've got so much data to manage we've taken an approach where we're able to service all of our customers out of a single centralized cluster meaning we get an economy of scale each one of our customers gets to work with a basically log management engine that's to scale to our scale rather than the individual customers scale so the older versions of log management had the same kind of complexity challenges you just drew a lot ecommerce as the data types increase so does their complexity is that so the complexity increases and but you also get into just a data scale problem you know suddenly you're generating terabytes of data but you don't you know the you only want to devote a certain budget to the computing resources that are gonna process that data because we can share our processing across all of our customers we we fundamentally changed economics it's a little bit like when you go and run a search and Google thousands literally thousands of servers in that tenth of a second that Google is processing the query 3,000 servers on the Google site may have been involved those aren't your 3,000 servers you know you're sharing those with you know 50 million other people in your data center region but but for a millisecond there those 3,000 servers are all for you and that's that's a big part of how Google is able to give such amazing results so quickly but in still economically yeah economically for them and that's basically on a smaller scale that's what we're doing is you know taking the same hardware and making it all of it available to all of the customers people talk about metrics as the solution to scaling problems is that correct so this is a really interesting question so you know metrics are great you know basically the you know if you look up the definition of a metric it's basically just a measurement on number and you know and it's a great way to boil down you know so I've had 83 million people visit my website today and they did 163 million things in this add mirror and that's you can't make sense of that you can boil it down to you know this is the amount of traffic on the site this was the error rate this was the average response time so these you know these are great it's a great summarization to give you an overall flavor of what's going on the challenge with metrics is that they tend to measure they can be a great way to measure your problems your symptoms sites up it's down it's fast its slow when you want to get to then to the cause of that problem all right exactly why is the site now and I know something's wrong with the database but what's the error message and what you know what's the exact detail here and a metric isn't going to give that to you and in particular when people talk about metrics they tend to have in mind a specific approach to metrics where this flood of events and data very early is distilled down let's count the number of requests measure the average time and then throw away the data and keep the metric that's efficient you know throwing away data means you don't have to pay to manage the data and it gives you this summary but then as soon as you want to drill down you don't have any more data so if you want to look at a different metric one that you didn't set up in advance you can't do it and if you need to go into the the details you can't do an interesting story about that you know when you were at Google you mentioned you the problem statements came from Google but one of things I love about Google is they really kind of nailed the sre model and they clearly decoupled roles you know developers and site reliability engineers who are essentially one-to-many relationship with all the massive hardware and that's a nice operating model it's had a lot of efficiencies was tied together but you guys are kind of saying in a way that does developers use the cloud they become their own sres in a way because this cloud can give them that kind of Google like scale and in smaller ways not like Google size but but that's similar dynamic where there's a lot of compute and a lot of things happening on behalf of the application or the engineers developer as developers become the operator through their role what challenges do they have and what do you see that happening because that's interesting trim because as applications become larger cloud can service them at scale they then become their own sres what yeah well how does that roll out most how do you see that yes I mean and so this is something we see happening at more and more of our customers and one of the implications of that is you have all these people these developers who are now responsible for operations but but they're not special you know they're not that specialist SRE team they're specialists in developing code not in operations they're you know they they minor in operations and and they don't think of it as their real job you know that's the distraction something goes wrong all right they're they're called upon to help fix it they want to get it done as quickly as possible so they can get back to their real job so they're not gonna make the same mental investment in becoming an expert at operations and an expert at the operations tools and the telemetry tools you know they're not gonna be a log management expert on metrics expert um and so they need they need tools that have a gentle learning Kurt have a gentle learning curve and are gonna make it easy for them to get Ian's not really know what they're doing on this side of things but find an answer solve the problem and get back out and that's kind of a concept you guys have of speed to truth exactly so and we mean a couple of things by that sort of most literally we our tool is it's a high performance solution you you hand us your terabytes of log data you ask some question you know what's the trend on this error in this service over the last day and we you know we give you a quick answer Big Data scan through a give you a quick answer but really it's you know that's just part of the overall chain of events which goes from the you know the developer with a problem until they have a solution so they they have to figure out even how to approach the problem what question to ask us you know they have to pose the query and in our interface and so we've done a lot of work to to simplify that learning curve where instead of a complicated query language you can click a button get a graph and then start breaking down that just visually break that down which okay here's the error rate but how does that break down by server or user or whatever dimension and be able to drill down and explore in a you know very kind of straightforward way how would you describe the culture at scaler I mean you guys been around for a while you still growing fast growing startup you haven't done the B round yet got any you guys self-funded it got customers early they pushed you again now 300 plus customers what's the culture like here so you know it's been this has been a fun company to build in part because you know we're into you know the the heart of this company is the engineering team our customers our engineers so you know we're kind of the kind of the same group and that keeps the you know it kind of keeps the inside in the outside very close together and I think that's been a part of the culture we've built is you know we all know why we're building this what it's for you know we use scalar extensively internally but you but even you know even if we weren't we're it's the kind of thing we've used in the past and we're gonna use in the future and so you know I think people are really excited here because you know we understand why and you have an opinion of the future on how it should roll out what's the big problem statement you guys are solving as a company what's it how would you boil that down if asked so by a customer and engineer out there what real problem are you solving that's core problem big problem that's gonna be helping me you know at the end of the day it's giving people the confidence to keep you know building these kind of complicated systems and move quickly because because and this is the business pressure everyone is under you know whatever business you're in it has a digital element and your competitors are in the same you know doing the same thing and they are building these sophisticated systems and they're adding functionality and they're moving quickly you need to be able to do the same thing but it's easy then to get tangled up in this complexity so at the end of the day you know we're giving people the ability to understand those systems and and and the functionality and the software's getting stronger and stronger more complicated with service meshes and micro services as applications start to have these the ability to stand up and tear down services on the fly that's so annoying and they'll even wield more data exact you get more data it gets more complicated actually if you don't mind there's a little story I'd like to tell so hold on just will I clear this out this is going back back to Google and again you know kind of part of the inspiration of you know how he came to build scalar and this doesn't be a story of frustration of you know probably get ourselves into that operation and motivation yep so we were we were working on this project it was building a file system that could tie together Google Docs Google sheets Google Drive Google photos and the black diagram looks kind of like the thing I just erased but there was one particular problem we had that took us months and literally months and months and months to track down you know you'd like to solve a problem in a few minutes or a few hours but this one took months and it had to do with the the indexing system so you have all these files in Google Drive you wanna be able to search and so we had modeled out how we were gonna build this or this search engine you'd think you know Google searches a solve problem but actually so Google web search is four things the whole world can see there's also like Gmail search which is four things that only one person can see so it's lots of separate little indexes those are both solve problems at Google Google Drive is for things a few people can see you share it with your coworker or your whoever and it's actually a very different problem and but we looked at the statistics and we found that the average document our average file was shared with about 1.1 people in other words things were mostly private or maybe you share with one or two people so we said we're just gonna make if something's shared to three people we're just gonna make three copies of it and then now we have just the Gmail problem each copy is for one person and we did the math on how how much work is this going to be to build these indexes and in round numbers we were looking at something like at the time this would be so much larger now but at the time we had maybe one billion documents and files in the system each one was shared to about 1.1 people maybe it was a thousand words long on average and maybe it would change be edited once per day on average so we had about a trillion word updates per day if you multiply all that together and so we allocate it we put in a request and purchase machines to handle that much traffic and we started bringing up the system and immediately collapsed it was completely overloaded and we checked our numbers and we check them again yeah 1.1 about a billion whatever and but then work into the system with just way beyond them and we looked at our metrics so you know measuring the number documents measuring each of these things all the metrics looked right to make a month's long story short these metrics and averages were hiding some funny business there turned out there was this type of use case read of occasional documents that were shared to thousands of people and one of there was a specific example it was the signup sheet for the Google company picnic this is a spreadsheet it was shared to about 5,000 people so it wasn't the whole company but you know a big chunk of Mountain View which meant it was I don't know let's say 20 thousand words long because it had you know the name and a couple other things for each person this is one document but shared to 5,000 people and you know during the period people were signing up maybe it was changing a couple thousand times per day so you multiply out just this document and you get 200 billion word updates for that one document in a day where we're estimating a trillion for the whole earth and so there was something like a hundred documents in this kid Google was hamstringing your own thing we were hamstrung our own thing there were about a hundred examples like this so now we're up to 20 trillion and like that was the whole problem these hundred files and we would have never found that until we got way down into the details of the the logs which in this two months just took month so because we didn't have the tools because we didn't have scaler yeah and I think this is the kind of anomaly you might see with Web Services evolving with micro services which someone has an API interface with some other SAS as apps start to rely on each other this is a new dynamic we're seeing as SLA s are also tied together so the question is whose fault is it exactly you have to whose fault is it and also things get so much more varied now you know again web 1.0 e-commerce you buy a thing you buy a thing that's all the same now you're building a social media site or whatever you've got 8 followers you've got 8 million followers this person has three movies rented on Netflix this person has three thousand movies everything's different and so then you get these funny things hiding yeah you're flying blind if you don't get all the data exposed it's like it's like you know blind person trying to read Braille as we heard earlier see if thanks so much for sharing the insight great story I'm John furry you're here for the q4 innovation day at scalers headquarters thanks for watching