CUBE Analysis of Day 1 of MWC Barcelona 2023 | MWC Barcelona 2023
>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies creating technologies that drive human progress. (upbeat music) >> Hey everyone, welcome back to theCube's first day of coverage of MWC 23 from Barcelona, Spain. Lisa Martin here with Dave Vellante and Dave Nicholson. I'm literally in between two Daves. We've had a great first day of coverage of the event. There's been lots of conversations, Dave, on disaggregation, on the change of mobility. I want to be able to get your perspectives from both of you on what you saw on the show floor, what you saw and heard from our guests today. So we'll start with you, Dave V. What were some of the things that were our takeaways from day one for you? >> Well, the big takeaway is the event itself. On day one, you get a feel for what this show is like. Now that we're back, face-to-face kind of pretty much full face-to-face. A lot of excitement here. 2000 plus exhibitors, I mean, planes, trains, automobiles, VR, AI, servers, software, I mean everything. I mean, everybody is here. So it's a really comprehensive show. It's not just about mobile. That's why they changed the name from Mobile World Congress. I think the other thing is from the keynotes this morning, I mean, you heard, there's a lot of, you know, action around the telcos and the transformation, but in a lot of ways they're sort of protecting their existing past from the future. And so they have to be careful about how fast they move. But at the same time if they don't move fast, they're going to get disrupted. We heard some complaints, essentially, you know, veiled complaints that the over the top guys aren't paying their fair share and Telco should be able to charge them more. We heard the chairman of Ericsson talk about how we can't let the OTTs do that again. We're going to charge directly for access through APIs to our network, to our data. We heard from Chris Lewis. Yeah. They've only got, or maybe it was San Ji Choha, how they've only got eight APIs. So, you know the developers are the ones who are going to actually build out the innovation at the edge. The telcos are going to provide the connectivity and the infrastructure companies like Dell as well. But it's really to me all about the developers. And that's where the action's going to be. And it's going to be interesting to see how the developers respond to, you know, the gun to the head. If you want access, you're going to have to pay for it. Now maybe there's so much money to be made that they'll go for it, but I feel like there's maybe a different model. And I think some of the emerging telcos are going to say, you know what, here developers, here's a platform, have at it. We're not going to charge you for all the data until you succeed. Then we're going to figure out a monetization model. >> Right. A lot of opportunity for the developer. That skillset is certainly one that's in demand here. And certainly the transformation of the telecom industry is, there's a lot of conundrums that I was hearing going on today, kind of chicken and egg scenarios. But Dave, you had a chance to walk around the show floor. We were here interviewing all day. What were some of the things that you saw that really stuck out to you? >> I think I was struck by how much attention was being paid to private 5G networks. You sort of read between the lines and it appears as though people kind of accept that the big incumbent telecom players are going to be slower to move. And this idea of things like open RAN where you're leveraging open protocols in a stack to deliver more agility and more value. So it sort of goes back to the generalized IT discussion of moving to cloud for agility. It appears as though a lot of players realize that the wild wild west, the real opportunity, is in the private sphere. So it's really interesting to see how that works, how 5G implemented into an environment with wifi how that actually works. It's really interesting. >> So it's, obviously when you talk to companies like Dell, I haven't hit HPE yet. I'm going to go over there and check out their booth. They got an analyst thing going on but it's really early days for them. I mean, they started in this business by taking an X86 box, putting a name on it, you know, that sounded like it was edged, throwing it over, you know, the wall. That's sort of how they all started in this business. And now they're, you know, but they knew they had to form partnerships. They had to build purpose-built systems. Now with 16 G out, you're seeing that. And so it's still really early days, talking about O RAN, open RAN, the open RAN alliance. You know, it's just, I mean, not even, the game hasn't even barely started yet but we heard from Dish today. They're trying to roll out a massive 5G network. Rakuten is really focused on sort of open RAN that's more reliable, you know, or as reliable as the existing networks but not as nearly as huge a scale as Dish. So it's going to take a decade for this to evolve. >> Which is surprising to the average consumer to hear that. Because as far as we know 5G has been around for a long time. We've been talking about 5G, implementing 5G, you sort of assume it's ubiquitous but the reality is it is just the beginning. >> Yeah. And you know, it's got a fake 5G too, right? I mean you see it on your phone and you're like, what's the difference here? And it's, you know, just, >> Dave N.: What does it really mean? >> Right. And so I think your point about private is interesting, the conversation Dave that we had earlier, I had throughout, hey I don't think it's a replacement for wifi. And you said, "well, why not?" I guess it comes down to economics. I mean if you can get the private network priced close enough then you're right. Why wouldn't it replace wifi? Now you got wifi six coming in. So that's a, you know, and WiFi's flexible, it's cheap, it's good for homes, good for offices, but these private networks are going to be like kickass, right? They're going to be designed to run whatever, warehouses and robots, and energy drilling facilities. And so, you know the economics I don't think are there today but maybe they can be at volume. >> Maybe at some point you sort of think of today's science experiment becoming the enterprise-grade solution in the future. I had a chance to have some conversations with folks around the show. And I think, and what I was surprised by was I was reminded, frankly, I wasn't surprised. I was reminded that when we start talking about 5G, we're talking about spectrum that is managed by government entities. Of course all broadcast, all spectrum, is managed in one way or another. But in particular, you can't simply put a SIM in every device now because there are a lot of regulatory hurdles that have to take place. So typically what these things look like today is 5G backhaul to the network, communication from that box to wifi. That's a huge improvement already. So yeah, my question about whether, you know, why not put a SIM in everything? Maybe eventually, but I think, but there are other things that I was not aware of that are standing in the way. >> Your point about spectrum's an interesting one though because private networks, you're going to be able to leverage that spectrum in different ways, and tune it essentially, use different parts of the spectrum, make it programmable so that you can apply it to that specific use case, right? So it's going to be a lot more flexible, you know, because I presume the needs spectrum needs of a hospital are going to be different than, you know, an agribusiness are going to be different than a drilling, you know, unit, offshore drilling unit. And so the ability to have the flexibility to use the spectrum in different ways and apply it to that use case, I think is going to be powerful. But I suspect it's going to be expensive initially. I think the other thing we talked about is public policy and regulation, and it's San Ji Choha brought up the point, is telcos have been highly regulated. They don't just do something and ask for permission, you know, they have to work within the confines of that regulated environment. And there's a lot of these greenfield companies and private networks that don't necessarily have to follow those rules. So that's a potential disruptive force. So at the same time, the telcos are spending what'd we hear, a billion, a trillion and a half over the next seven years? Building out 5G networks. So they got to figure out, you know how to get a payback on that. They'll get it I think on connectivity, 'cause they have a monopoly but they want more. They're greedy. They see the over, they see the Netflixes of the world and the Googles and the Amazons mopping up services and they want a piece of that action but they've never really been good at it. >> Well, I've got a question for both of you. I mean, what do you think the odds are that by the time the Shangri La of fully deployed 5G happens that we have so much data going through it that effectively it feels exactly the same as 3G? What are the odds? >> That's a good point. Well, the thing that gets me about 5G is there's so much of it on, if I go to the consumer side when we're all consumers in our daily lives so much of it's marketing hype. And, you know all the messaging about that, when it's really early innings yet they're talking about 6G. What does actual fully deployed 5G look like? What is that going to enable a hospital to achieve or an oil refinery out in the middle of the ocean? That's something that interests me is what's next for that? Are we going to hear that at this event? >> I mean, walking around, you see a fair amount of discussion of, you know, the internet of things. Edge devices, the increase in connectivity. And again, what I was surprised by was that there's very little talk about a sim card in every one of those devices at this point. It's like, no, no, no, we got wifi to handle all that but aggregating it back into a central network that's leveraging 5G. That's really interesting. That's really interesting. >> I think you, the odds of your, to go back to your question, I think the odds are even money, that by the time it's all built out there's going to be so much data and so much new capability it's going to work similarly at similar speeds as we see in the networks today. You're just going to be able to do so many more things. You know, and your video's going to look better, the graphics are going to look better. But I think over the course of history, this is what's happening. I mean, even when you go back to dial up, if you were in an AOL chat room in 1996, it was, you know, yeah it took a while. You're like, (screeches) (Lisa laughs) the modem and everything else, but once you were in there- >> Once you're there, 2400 baud. >> It was basically real time. And so you could talk to your friends and, you know, little chat room but that's all you could do. You know, if you wanted to watch a video, forget it, right? And then, you know, early days of streaming video, stop, start, stop, start, you know, look at Amazon Prime when it first started, Prime Video was not that great. It's sort of catching up to Netflix. But, so I think your point, that question is really prescient because more data, more capability, more apps means same speed. >> Well, you know, you've used the phrase over the top. And so just just so we're clear so we're talking about the same thing. Typically we're talking about, you've got, you have network providers. Outside of that, you know, Netflix, internet connection, I don't need Comcast, right? Perfect example. Well, what about the over the top that's coming from direct satellite communications with devices. There are times when I don't have a signal on my, happens to be an Apple iPhone, when I get a little SOS satellite logo because I can communicate under very limited circumstances now directly to the satellite for very limited text messaging purposes. Here at the show, I think it might be a Motorola device. It's a dongle that allows any mobile device to leverage direct satellite communication. Again, for texting back to the 2,400 baud modem, you know, days, 1200 even, 300 even, go back far enough. What's that going to look like? Is that too far in the future to think that eventually it's all going to be over the top? It's all going to be handset to satellite and we don't need these RANs anymore. It's all going to be satellite networks. >> Dave V.: I think you're going to see- >> Little too science fiction-y? (laughs) >> No, I, no, I think it's a good question and I think you're going to see fragments. I think you're going to see fragmentation of private networks. I think you're going to see fragmentation of satellites. I think you're going to see legacy incumbents kind of hanging on, you know, the cable companies. I think that's coming. I think by 2030 it'll, the picture will be much more clear. The question is, and I think it's come down to the innovation on top, which platform is going to be the most developer friendly? Right, and you know, I've not heard anything from the big carriers that they're going to be developer friendly. I've heard "we have proprietary data that we're going to charge access for and developers are going to have to pay for that." But I haven't heard them saying "Developers, developers, developers!" You know, Steve Bomber running around, like bend over backwards for developers, they're asking the developers to bend over. And so if a network can, let's say the satellite network is more developer friendly, you know, you're going to see more innovation there potentially. You know, or if a dish network says, "You know what? We're going after developers, we're going after innovation. We're not going to gouge them for all this network data. Rather we're going to make the platform open or maybe we're going to do an app store-like model where we take a piece of the action after they succeed." You know, take it out of the backend, like a Silicon Valley VC as opposed to an East Coast VC. They're not going to get you in the front end. (Lisa laughs) >> Well, you can see the sort of disruptive forces at play between open RAN and the legacy, call it proprietary stack, right? But what is the, you know, if that's sort of a horizontal disruptive model, what's the vertically disruptive model? Is it private networks coming in? Is it a private 5G network that comes in that says, "We're starting from the ground up, everything is containerized. We're going to go find people at KubeCon who are, who understand how to orchestrate with Kubernetes and use containers in microservices, and we're going to have this little 5G network that's going to deliver capabilities that you can't get from the big boys." Is there a way to monetize that? Is there a way for them to be disrupted, be disruptive, or are these private 5G networks that everybody's talking about just relegated to industrial use cases where you're just squeezing better economics out of wireless communication amongst all your devices in your factory? >> That's an interesting question. I mean, there are a lot of those smart factory industrial use cases. I mean, it's basically industry 4.0 use cases. But yeah, I don't count the cloud guys out. You know, everybody says, "oh, the narrative is, well, the latency of the cloud." Well, not if the cloud is at the edge. If you take a local zone and put storage, compute, and data right next to each other and the cloud model with the cloud APIs, and then you got an asynchronous, you know, connection back. I think that's a reasonable model. I think the cloud guys figured out developers, right? Pretty well. Certainly Microsoft and, and Amazon and Google, they know developers. I don't see any reason why they can't bring their model to the edge. So, and that's really disruptive to the legacy telco guys, you know? So they have to be careful. >> One step closer to my dream of eliminating the word "cloud" from IT lexicon. (Lisa laughs) I contend that it has always been IT, and it will always be IT. And this whole idea of cloud, what is cloud? If AWS, for example, is delivering hardware to the edge where it needs to be, is that cloud? Do we go back to the idea that cloud is an operational model and not a question of physical location? I hope we get to that point. >> Well, what's Apex and GreenLake? Apex is, you know, Dell's as a service. GreenLake is- >> HPE. >> HPE's as a service. That's outposts. >> Dave N.: Right. >> Yeah. >> That's their outpost. >> Yeah. >> Well AWS's position used to be, you know, to use them as a proxy for hyperscale cloud. We'll just, we'll grow in a very straight trajectory forever on the back of net new stuff. Forget about the old stuff. As James T. Kirk said of the Klingons, "let them die." (Lisa laughs) As far as the cloud providers were concerned just, yeah, let, let that old stuff go away. Well then they found out, there came a point in time where they realized there's a lot of friction and stickiness associated with that. So they had to deal with the reality of hybridity, if that's the word, the hybrid nature of things. So what are they doing? They're pushing stuff out to the edge, so... >> With the same operating model. >> With the same operating model. >> Similar. I mean, it's limited, right? >> So you see- >> You can't run a lot of database on outpost, you can run RES- >> You see this clash of Titans where some may have written off traditional IT infrastructure vendors, might have been written off as part of the past. Whereas hyperscale cloud providers represent the future. It seems here at this show they're coming head to head and competing evenly. >> And this is where I think a company like Dell or HPE or Cisco has some advantages in that they're not going to compete with the telcos, but the hyperscalers will. >> Lisa: Right. >> Right. You know, and they're already, Google's, how much undersea cable does Google own? A lot. Probably more than anybody. >> Well, we heard from Google and Microsoft this morning in the keynote. It'd be interesting to see if we hear from AWS and then over the next couple of days. But guys, clearly there is, this is a great wrap of day one. And the crazy thing is this is only day one. We've got three more days of coverage, more news, more information to break down and unpack on theCUBE. Look forward to doing that with you guys over the next three days. Thank you for sharing what you saw on the show floor, what you heard from our guests today as we had about 10 interviews. Appreciate your insights and your perspectives and can't wait for tomorrow. >> Right on. >> All right. For Dave Vellante and Dave Nicholson, I'm Lisa Martin. You're watching theCUBE's day one wrap from MWC 23. We'll see you tomorrow. (relaxing music)
SUMMARY :
that drive human progress. of coverage of the event. are going to say, you know what, of the telecom industry is, are going to be slower to move. And now they're, you know, Which is surprising to the I mean you see it on your phone I guess it comes down to economics. I had a chance to have some conversations And so the ability to have the flexibility I mean, what do you think the odds are What is that going to of discussion of, you know, the graphics are going to look better. And then, you know, early the 2,400 baud modem, you know, days, They're not going to get you that you can't get from the big boys." to the legacy telco guys, you know? dream of eliminating the word Apex is, you know, Dell's as a service. That's outposts. So they had to deal with I mean, it's limited, right? they're coming head to going to compete with the telcos, You know, and they're already, Google's, And the crazy thing is We'll see you tomorrow.
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CUBE Insights Day 1 | CloudNativeSecurityCon 23
(upbeat music) >> Hey, everyone. Welcome back to theCUBE's day one coverage of Cloud Native SecurityCon 2023. This has been a great conversation that we've been able to be a part of today. Lisa Martin with John Furrier and Dave Vellante. Dave and John, I want to get your take on the conversations that we had today, starting with the keynote that we were able to see. What are your thoughts? We talked a lot about technology. We also talked a lot about people and culture. John, starting with you, what's the story here with this inaugural event? >> Well, first of all, there's two major threads. One is the breakout of a new event from CloudNativeCon/KubeCon, which is a very successful community and events that they do international and in North America. And that's not stopping. So that's going to be continuing to go great. This event is a breakout with an extreme focus on security and all things security around that ecosystem. And with extensions into the Linux Foundation. We heard Brian Behlendorf was on there from the Linux Foundation. So he was involved in Hyperledger. So not just Cloud Native, all things containers, Kubernetes, all things Linux Foundation as an open source. So, little bit more of a focus. So I like that piece of it. The other big thread on this story is what Dave and Yves were talking about on our panel we had earlier, which was the business model of security is real and that is absolutely happening. It's impacting business today. So you got this, let's build as fast as possible, let's retool, let's replatform, refactor and then the reality of the business imperative. To me, those are the two big high-order bits that are going on and that's the reality of this current situation. >> Dave, what are your top takeaways from today's day one inaugural coverage? >> Yeah, I would add a third leg of the stool to what John said and that's what we were talking about several times today about the security is a do-over. The Pat Gelsinger quote, from what was that, John, 2011, 2012? And that's right around the time that the cloud was hitting this steep part of the S-curve and do-over really has meant in looking back, leveraging cloud native tooling, and cloud native technologies, which are different than traditional security approaches because it has to take into account the unique characteristics of the cloud whether that's dynamic resource allocation, unlimited resources, microservices, containers. And while that has helped solve some problems it also brings new challenges. All these cloud native tools, securing this decentralized infrastructure that people are dealing with and really trying to relearn the security culture. And that's kind of where we are today. >> I think the other thing too that I had Dave is that was we get other guests on with a diverse opinion around foundational models with AI and machine learning. You're going to see a lot more things come in to accelerate the scale and automation piece of it. It is one thing that CloudNativeCon and KubeCon has shown us what the growth of cloud computing is is that containers Kubernetes and these new services are powering scale. And scale you're going to need to have automation and machine learning and AI will be a big part of that. So you start to see the new formation of stacks emerging. So foundational stacks is the machine learning and data apps are coming out. It's going to start to see more apps coming. So I think there's going to be so many new applications and services are going to emerge, and if you don't get your act together on the infrastructure side those apps will not be fully baked. >> And obviously that's a huge risk. Sorry, Dave, go ahead. >> No, that's okay. So there has to be hardware somewhere. You can't get away with no hardware. But increasingly the security architecture like everything else is, is software-defined and makes it a lot more flexible. And to the extent that practitioners and organizations can consolidate this myriad of tools that they have, that means they're going to have less trouble learning new skills, they're going to be able to spend more time focused and become more proficient on the tooling that is being applied. And you're seeing the same thing on the vendor side. You're seeing some of these large vendors, Palo Alto, certainly CrowdStrike and fundamental to their strategy is to pick off more and more and more of these areas in security and begin to consolidate them. And right now, that's a big theme amongst organizations. We know from the survey data that consolidating redundant vendors is the number one cost saving priority today. Along with, at a distant second, optimizing cloud costs, but consolidating redundant vendors there's nowhere where that's more prominent than in security. >> Dave, talk a little bit about that, you mentioned the practitioners and obviously this event bottoms up focused on the practitioners. It seems like they're really in the driver's seat now. With this being the inaugural Cloud Native SecurityCon, first time it's been pulled out of an elevated out of KubeCon as a focus, do you think this is about time that the practitioners are in the driver's seat? >> Well, they're certainly, I mean, we hear about all the tech layoffs. You're not laying off your top security pros and if you are, they're getting picked up very quickly. So I think from that standpoint, anybody who has deep security expertise is in the driver's seat. The problem is that driver's seat is pretty hairy and you got to have the stomach for it. I mean, these are technical heroes, if you will, on the front lines, literally saving the world from criminals and nation-states. And so yes, I think Lisa they have been in the driver's seat for a while, but it it takes a unique person to drive at those speeds. >> I mean, the thing too is that the cloud native world that we are living in comes from cloud computing. And if you look at this, what is a practitioner? There's multiple stakeholders that are being impacted and are vulnerable in the security front at many levels. You have application developers, you got IT market, you got security, infrastructure, and network and whatever. So all that old to new is happening. So if you look at IT, that market is massive. That's still not transformed yet to cloud. So you have companies out there literally fully exposed to ransomware. IT teams that are having practices that are antiquated and outdated. So security patching, I mean the blocking and tackling of the old securities, it's hard to even support that old environment. So in this transition from IT to cloud is changing everything. And so practitioners are impacted from the devs and the ones that get there faster and adopt the ways to make their business better, whether you call it modern technology and architectures, will be alive and hopefully thriving. So that's the challenge. And I think this security focus hits at the heart of the reality of business because like I said, they're under threats. >> I wanted to pick up too on, I thought Brian Behlendorf, he did a forward looking what could become the next problem that we really haven't addressed. He talked about generative AI, automating spearphishing and he flat out said the (indistinct) is not fixed. And so identity access management, again, a lot of different toolings. There's Microsoft, there's Okta, there's dozens of companies with different identity platforms that practitioners have to deal with. And then what he called free riders. So these are folks that go into the repos. They're open source repos, and they find vulnerabilities that developers aren't hopping on quickly. It's like, you remember Patch Tuesday. We still have Patch Tuesday. That meant Hacker Wednesday. It's kind of the same theme there going into these repos and finding areas where the practitioners, the developers aren't responding quickly enough. They just don't necessarily have the resources. And then regulations, public policy being out of alignment with what's really needed, saying, "Oh, you can't ship that fix outside of Germany." Or I'm just making this up, but outside of this region because of a law. And you could be as a developer personally liable for it. So again, while these practitioners are in the driver's seat, it's a hairy place to be. >> Dave, we didn't get the word supercloud in much on this event, did we? >> Well, I'm glad you brought that up because I think security is the big single, biggest challenge for supercloud, securing the supercloud with all the diversity of tooling across clouds and I think you brought something up in the first supercloud, John. You said, "Look, ultimately the cloud, the hyperscalers have to lean in. They are going to be the enablers of supercloud. They already are from an infrastructure standpoint, but they can solve this problem by working together. And I think there needs to be more industry collaboration. >> And I think the point there is that with security the trend will be, in my opinion, you'll see security being reborn in the cloud, around zero trust as structure, and move from an on-premise paradigm to fully cloud native. And you're seeing that in the network side, Dave, where people are going to each cloud and building stacks inside the clouds, hyperscaler clouds that are completely compatible end-to-end with on-premises. Not trying to force the cloud to be working with on-prem. They're completely refactoring as cloud native first. And again, that's developer first, that's data first, that's security first. So to me that's the tell sign. To me is if when you see that, that's good. >> And Lisa, I think the cultural conversation that you've brought into these discussions is super important because I've said many times, bad user behavior is going to trump good security every time. So that idea that the entire organization is responsible for security. You hear that all the time. Well, what does that mean? It doesn't mean I have to be a security expert, it just means I have to be smart. How many people actually use a VPN? >> So I think one of the things that I'm seeing with the cultural change is face-to-face problem solving is one, having remote teams is another. The skillset is big. And I think the culture of having these teams, Dave mentioned something about intramural sports, having the best people on the teams, from putting captains on the jersey of security folks is going to happen. I think you're going to see a lot more of that going on because there's so many areas to work on. You're going to start to see security embedded in all processes. >> Well, it needs to be and that level of shared responsibility is not trivial. That's across the organization. But they're also begs the question of the people problem. People are one of the biggest challenges with respect to security. Everyone has to be on board with this. It has to be coming from the top down, but also the bottom up at the same time. It's challenging to coordinate. >> Well, the training thing I think is going to solve itself in good time. And I think in the fullness of time, if I had to predict, you're going to see managed services being a big driver on the front end, and then as companies realize where their IP will be you'll see those managed service either be a core competency of their business and then still leverage. So I'm a big believer in managed services. So you're seeing Kubernetes, for instance, a lot of managed services. You'll start to see more, get the ball going, get that rolling, then build. So Dave mentioned bottoms up, middle out, that's how transformation happens. So I think managed services will win from here, but ultimately the business model stuff is so critical. >> I'm glad you brought up managed services and I want to add to that managed security service providers, because I saw a stat last year, 50% of organizations in the US don't even have a security operations team. So managed security service providers MSSPs are going to fill the gap, especially for small and midsize companies and for those larger companies that just need to augment and compliment their existing staff. And so those practitioners that we've been talking about, those really hardcore pros, they're going to go into these companies, some large, the big four, all have them. Smaller companies like Arctic Wolf are going to, I think, really play a key role in this decade. >> I want to get your opinion Dave on what you're hoping to see from this event as we've talked about the first inaugural standalone big focus here on security as a standalone. Obviously, it's a huge challenge. What are you hoping for this event to get groundswell from the community? What are you hoping to hear and see as we wrap up day one and go into day two? >> I always say events like this they're about educating, aspiring to action. And so the practitioners that are at this event I think, I used to say they're the technical heroes. So we know there's going to be another Log4j or a another SolarWinds. It's coming. And my hope is that when that happens, it's not an if, it's a when, that the industry, these practitioners are able to respond in a way that's safe and fast and agile and they're able to keep us protected, number one and number two, that they can actually figure out what happened in the long tail of still trying to clean it up is compressed. That's my hope or maybe it's a dream. >> I think day two tomorrow you're going to hear more supply chain, security. You're going to start to see them focus on sessions that target areas if within the CNCF KubeCon + CloudNativeCon area that need support around containers, clusters, around Kubernetes cluster. You're going to start to see them laser focus on cleaning up the house, if you will, if you can call it cleaning up or fixing what needs to get fixed or solved what needs to get solved on the cloud native front. That's going to be urgent. And again, supply chain software as Dave mentioned, free riders too, just using open source. So I think you'll see open source continue to grow, but there'll be an emphasis on verification and certification. And Docker has done a great job with that. You've seen what they've done with their business model over hundreds of millions of dollars in revenue from a pivot. Catch a few years earlier because they verify. So I think we're going to be in this verification blue check mark of code era, of code and software. Super important bill of materials. They call SBOMs, software bill of materials. People want to know what's in their software and that's going to be, again, another opportunity for machine learning and other things. So I'm optimistic that this is going to be a good focus. >> Good. I like that. I think that's one of the things thematically that we've heard today is optimism about what this community can generate in terms of today's point. The next Log4j is coming. We know it's not if, it's when, and all organizations need to be ready to Dave's point to act quickly with agility to dial down and not become the next headline. Nobody wants to be that. Guys, it's been fun working with you on this day one event. Looking forward to day two. Lisa Martin for Dave Vellante and John Furrier. You're watching theCUBE's day one coverage of Cloud Native SecurityCon '23. We'll see you tomorrow. (upbeat music)
SUMMARY :
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Day 1 Keynote Analysis | CloudNativeSecurityCon 23
(upbeat music) >> Hey everyone and welcome to theCUBE's coverage day one of CloudNativeSecurityCon '23. Lisa Martin here with John Furrier and Dave Vellante. Dave and John, great to have you guys on the program. This is interesting. This is the first inaugural CloudNativeSecurityCon. Formally part of KubeCon, now a separate event here happening in Seattle over the next couple of days. John, I wanted to get your take on, your thoughts on this being a standalone event, the community, the impact. >> Well, this inaugural event, which is great, we love it, we want to cover all inaugural events because you never know, there might not be one next year. So we were here if it happens, we're here at creation. But I think this is a good move for the CNCF and the Linux Foundation as security becomes so important and there's so many issues to resolve that will influence many other things. Developers, machine learning, data as code, supply chain codes. So I think KubeCon, Kubernetes conference and CloudNativeCon, is all about cloud native developers. And it's a huge event and there's so much there. There's containers, there's microservices, all that infrastructure's code, the DevSecOps on that side, there's enough there and it's a huge ecosystem. Pulling it as a separate event is a first move for them. And I think there's a toe in the water kind of vibe here. Testing the waters a little bit on, does this have legs? How is it organized? Looks like they took their time, thought it out extremely well about how to craft it. And so I think this is the beginning of what will probably be a seminal event for the open source community. So let's listen to the clip from Priyanka Sharma who's a CUBE alumni and executive director of the CNCF. This is kind of a teaser- >> We will tackle issues of security together here and further on. We'll share our experiences, successes, perhaps more importantly, failures, and help with the collecting of understanding. We'll create solutions. That's right. The practitioners are leading the way. Having conversations that you need to have. That's all of you. This conference today and tomorrow is packed with 72 sessions for all levels of technologists to reflect the bottoms up, developer first nature of the conference. The co-chairs have selected these sessions and they are true blue practitioners. >> And that's a great clip right there. If you read between the lines, what she's saying there, let's unpack this. Solutions, we're going to fail, we're going to get better. Linux, the culture of iterating. But practitioners, the mention of practitioners, that was very key. Global community, 72 sessions, co-chairs, Liz Rice and experts that are crafting this program. It seems like very similar to what AWS has done with re:Invent as their core show. And then they have re:Inforce which is their cloud native security, Amazon security show. There's enough there, so to me, practitioners, that speaks to the urgency of cloud native security. So to me, I think this is the first move, and again, testing the water. I like the vibe. I think the practitioner angle is relevant. It's very nerdy, so I think this is going to have some legs. >> Yeah, the other key phrase Priyanka mentioned is bottoms up. And John, at our predictions breaking analysis, I asked you to make a prediction about events. And I think you've nailed it. You said, "Look, we're going to have many more events, but they're going to be smaller." Most large events are going to get smaller. AWS is obviously the exception, but a lot of events like this, 500, 700, 1,000 people, that is really targeted. So instead of you take a big giant event and there's events within the event, this is going to be really targeted, really intimate and focused. And that's exactly what this is. I think your prediction nailed it. >> Well, Dave, we'll call to see the event operating system really cohesive events connected together, decoupled, and I think the Linux Foundation does an amazing job of stringing these events together to have community as the focus. And I think the key to these events in the future is having, again, targeted content to distinct user groups in these communities so they can be highly cohesive because they got to be productive. And again, if you try to have a broad, big event, no one's happy. Everyone's underserved. So I think there's an industry concept and then there's pieces tied together. And I think this is going to be a very focused event, but I think it's going to grow very fast. >> 72 sessions, that's a lot of content for this small event that the practitioners are going to have a lot of opportunity to learn from. Do you guys, John, start with you and then Dave, do you think it's about time? You mentioned John, they're dipping their toe in the water. We'll see how this goes. Do you think it's about time that we have this dedicated focus out of this community on cloud native security? >> Well, I think it's definitely time, and I'll tell you there's many reasons why. On the front lines of business, there's a business model for security hackers and breaches. The economics are in favor of the hackers. That's a real reality from ransomware to any kind of breach attacks. There's corporate governance issues that's structural challenges for companies. These are real issues operationally for companies in the enterprise. And at the same time, on the tech stack side, it's been very slow movement, like glaciers in terms of security. Things like DNS, Linux kernel, there are a lot of things in the weeds in the details of the bowels of the tech world, protocol levels that just need to be refactored. And I think you're seeing a lot of that here. It was mentioned from Brian from the Linux Foundation, mentioned Dan Kaminsky who recently passed away who found that vulnerability in BIND which is a DNS construct. That was a critical linchpin. They got to fix these things and Liz Rice is talking about the Linux kernel with the extended Berkeley Packet Filtering thing. And so this is where they're going. This is stuff that needs to be paid attention to because if they don't do it, the train of automation and machine learning is going to run wild with all kinds of automation that the infrastructure just won't be set up for. So I think there's going to be root level changes, and I think ultimately a new security stack will probably be very driven by data will be emerging. So to me, I think this is definitely worth being targeted. And I think you're seeing Amazon doing the same thing. I think this is a playbook out of AWS's event focus and I think that's right. >> Dave, what are you thoughts? >> There was a lot of talk in, again, I go back to the progression here in the last decade about what's the right regime for security? Should the CISO report to the CIO or the board, et cetera, et cetera? We're way beyond that now. I think DevSecOps is being asked to do a lot, particularly DevOps. So we hear a lot about shift left, we're hearing about protecting the runtime and the ops getting much more involved and helping them do their jobs because the cloud itself has brought a lot to the table. It's like the first line of defense, but then you've really got a lot to worry about from a software defined perspective. And it's a complicated situation. Yes, there's less hardware, yes, we can rely on the cloud, but culturally you've got a lot more people that have to work together, have to share data. And you want to remove the blockers, to use an Amazon term. And the way you do that is you really, if we talked about it many times on theCUBE. Do over, you got to really rethink the way in which you approach security and it starts with culture and team. >> Well the thing, I would call it the five C's of security. Culture, you mentioned that's a good C. You got cloud, tons of issues involved in cloud. You've got access issues, identity. you've got clusters, you got Kubernetes clusters. And then you've got containers, the fourth C. And then finally is the code itself, supply chain. So all areas of cloud native, if you take out culture, it's cloud, cluster, container, and code all have levels of security risks and new things in there that need to be addressed. So there's plenty of work to get done for sure. And again, this is developer first, bottoms up, but that's where the change comes in, Dave, from a security standpoint, you always point this out. Bottoms up and then middle out for change. But absolutely, the imperative is today the business impact is real and it's urgent and you got to pedal as fast as you can here, so I think this is going to have legs. We'll see how it goes. >> Really curious to understand the cultural impact that we see being made at this event with the focus on it. John, you mentioned the four C's, five with culture. I often think that culture is probably the leading factor. Without that, without getting those teams aligned, is the rest of it set up to be as successful as possible? I think that's a question that's- >> Well to me, Dave asked Pat Gelsinger in 2014, can security be a do-over at VMWorld when he was the CEO of VMware? He said, "Yes, it has to be." And I think you're seeing that now. And Nick from the co-founder of Palo Alto Networks was quoted on theCUBE by saying, "Zero Trust is some structure to give to security, but cloud allows for the ability to do it over and get some scale going on security." So I think the best people are going to come together in this security world and they're going to work on this. So you're going to start to see more focus around these security events and initiatives. >> So I think that when you go to the, you mentioned re:Inforce a couple times. When you go to re:Inforce, there's a lot of great stuff that Amazon puts forth there. Very positive, it's not that negative. Oh, the world is falling, the sky is falling. And so I like that. However, you don't walk away with an understanding of how they're making the CISOs and the DevOps lives easier once they get beyond the cloud. Of course, it's not Amazon's responsibility. And that's where I think the CNCF really comes in and open source, that's where they pick up. Obviously the cloud's involved, but there's a real opportunity to simplify the lives of the DevSecOps teams and that's what's critical in terms of being able to solve, or at least keep up with this never ending problem. >> Yeah, there's a lot of issues involved. I took some notes here from some of the keynote you heard. Security and education, training and team structure. Detection, incidents that are happening, and how do you respond to that architecture. Identity, isolation, supply chain, and governance and compliance. These are all real things. This is not like hand-waving issues. They're mainstream and they're urgent. Literally the houses are on fire here with the enterprise, so this is going to be very, very important. >> Lisa: That's a great point. >> Some of the other things Priyanka mentioned, exposed edges and nodes. So just when you think we're starting to solve the problem, you got IOT, security's not a one and done task. We've been talking about culture. No person is an island. It's $188 billion business. Cloud native is growing at 27% a year, which just underscores the challenges, and bottom line, practitioners are leading the way. >> Last question for you guys. What are you hoping those practitioners get out of this event, this inaugural event, John? >> Well first of all, I think this inaugural event's going to be for them, but also we at theCUBE are going to be doing a lot more security events. RSA's coming up, we're going to be at re:Inforce, we're obviously going to be covering this event. We've got Black Hat, a variety of other events. We'll probably have our own security events really focused on some key areas. So I think the thing that people are going to walk away from this event is that paying attention to these security events are going to be more than just an industry thing. I think you're going to start to see group gatherings or groups convening virtually and physically around core issues. And I think you're going to start to see a community accelerate around cloud native and open source specifically to help teams get faster and better at what they do. So I think the big walkaway for the customers and the practitioners here is that there's a call to arms happening and this is, again, another signal that it's worth breaking out from the core event, but being tied to it, I think that's a good call and I think it's a well good architecture from a CNCF standpoint and a worthy effort, so I give it a thumbs up. We still don't know what it's going to look like. We'll see what day two looks like, but it seems to be experts, practitioners, deep tech, enabling technologies. These are things that tend to be good things to hear when you're at an event. I'll say the business imperative is obvious. >> The purpose of an event like this, and it aligns with theCUBE's mission, is to educate and inspire business technology pros to action. We do it in theCUBE with free content. Obviously this event is a for-pay event, but they are delivering some real value to the community that they can take back to their organizations to make change. And that's what it's all about. >> Yep, that is what it's all about. I'm looking forward to seeing over as the months unfold, the impact that this event has on the community and the impact the community has on this event going forward, and really the adoption of cloud native security. Guys, great to have you during this keynote analysis. Looking forward to hearing the conversations that we have on theCUBE today. Thanks so much for joining. And for my guests, for my co-hosts, John Furrier and Dave Vellante. I'm Lisa Martin. You're watching theCUBE's day one coverage of CloudNativeSecurityCon '23. Stick around, we got great content on theCUBE coming up. (upbeat music)
SUMMARY :
Dave and John, great to have And so I think this is the beginning nature of the conference. this is going to have some legs. this is going to be really targeted, And I think the key to these a lot of opportunity to learn from. and machine learning is going to run wild Should the CISO report to the CIO think this is going to have legs. is the rest of it set up to And Nick from the co-founder and the DevOps lives easier so this is going to be to solve the problem, you got IOT, of this event, this inaugural event, John? from the core event, but being tied to it, to the community that they can take back Guys, great to have you
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Day 1 Keynote Analysis | Palo Alto Networks Ignite22
>> Narrator: "TheCUBE" presents Ignite 22. Brought to you by Palo Alto Networks. >> Hey everyone. Welcome back to "TheCUBE's" live coverage of Palo Alto Network's Ignite 22 from the MGM Grand in beautiful Las Vegas. I am Lisa Martin here with Dave Vellante. Dave, we just had a great conversa- First of all, we got to hear the keynote, most of it. We also just had a great conversation with the CEO and chairman of Palo Alto Networks, Nikesh Arora. You know, this is a company that was founded back in 2005, he's been there four years, a lot has happened. A lot of growth, a lot of momentum in his tenure. You were saying in your breaking analysis, that they are on track to nearly double revenues from FY 20 to 23. Lots of momentum in this cloud security company. >> Yeah, I'd never met him before. I mean, I've been following a little bit. It's interesting, he came in as, sort of, a security outsider. You know, he joked today that he, the host, I forget the guy's name on the stage, what was his name? Hassan. Hassan, he said "He's the only guy in the room that knows less about security than I do." Because, normally, this is an industry that's steeped in deep expertise. He came in and I think is given a good compliment to the hardcore techies at Palo Alto Network. The company, it's really interesting. The company started out building their own data centers, they called it. Now they look back and call it cloud, but it was their own data centers, kind of like Salesforce did, it's kind of like ServiceNow. Because at the time, you really couldn't do it in the public cloud. The public cloud was a little too unknown. And so they needed that type of control. But Palo Alto's been amazing story since 2020, we wrote about this during the pandemic. So what they did, is they began to pivot to the the true cloud native public cloud, which is kind of immature still. They don't tell you that, but it's kind of still a little bit immature, but it's working. And when they were pivoting, it was around the same time, at Fortinet, who's a competitor there's like, I call 'em a poor man's Palo Alto, and Fortinet probably hates that, but it's kind of true. It's like a value play on a comprehensive platform, and you know Fortinet a little bit. And so, but what was happening is Fortinet was executing on its cloud strategy better than Palo Alto. And there was a real divergence in the valuations of these stocks. And we said at the time, we felt like Palo Alto, being the gold standard, would get through it. And they did. And what's happened is interesting, I wrote about this two weeks ago. If you go back to the pandemic, peak of the pandemic, or just before the peak, kind of in that tech bubble, if you will. Splunk's down 44% from that peak, Okta's down, sorry, not down 44%. 44% of the peak. Okta's 22% of their peak. CrowdStrike, 41%, Zscaler, 36%, Fortinet, 71%. Not so bad. Palo Altos maintained 93% of its peak value, right? So it's a combination of two things. One is, they didn't run up as much during the pandemic, and they're executing through their cloud strategy. And that's provided a sort of softer landing. And I think it's going to be interesting to see where they go from here. And you heard Nikesh, we're going to double, and then double again. So that's 7 billion, 14 billion, heading to 30 billion. >> Lisa: Yeah, yeah. He also talked about one of the things that he's done in his tenure here, as really a workforce transformation. And we talk all the time, it's not just technology and processes, it's people. They've also seemed to have done a pretty good job from a cultural transformation perspective, which is benefiting their customers. And they're also growing- The ecosystem, we talked a little bit about the ecosystem with Nikesh. We've got Google Cloud on, we've got AWS on the program today alone, talking about the partnerships. The ecosystem is expanding, as well. >> Have you ever met Nir Zuk? >> I have not, not yet. >> He's the founder and CTO. I haven't, we've never been on "theCUBE." He was supposed to come on one day down in New York City. Stu and I were going to interview him, and he cut out of the conference early, so we didn't interview him. But he's a very opinionated dude. And you're going to see, he's basically going to come on, and I mean, I hope he is as opinionated on "TheCUBE," but he'll talk about how the industry has screwed it up. And Nikesh sort of talked about that, it's a shiny new toy strategy. Oh, there's another one, here's another one. It's the best in that category. Okay, let's get, and that's how we've gotten to this point. I always use that Optive graphic, which shows the taxonomy, and shows hundreds and hundreds of suppliers in the industry. And again, it's true. Customers have 20, 30, sometimes 40 different tool sets. And so now it's going to be interesting to see. So I guess my point is, it starts at the top. The founder, he's an outspoken, smart, tough Israeli, who's like, "We're going to take this on." We're not afraid to be ambitious. And so, so to your point about people and the culture, it starts there. >> Absolutely. You know, one of the things that you've written about in your breaking analysis over the weekend, Nikesh talked about it, they want to be the consolidator. You see this as they're building out the security supercloud. Talk to me about that. What do you think? What is a security supercloud in your opinion? >> Yeah, so let me start with the consolidator. So Palo Alto obviously is executing on that strategy. CrowdStrike as well, wants to be a consolidator. I would say Zscaler wants to be a consolidator. I would say that Microsoft wants to be a consolidator, so does Cisco. So they're all coming at it from different angles. Cisco coming at it from network security, which is Palo Alto's wheelhouse, with their next gen firewalls, network security. What Palo Alto did was interesting, was they started out with kind of a hardware based firewall, but they didn't try to shove everything into it. They put the other function in there, their cloud. Zscaler. Zscaler is the one running around saying you don't need firewalls anymore. Just run everything through our cloud, our security cloud. I would think that as Zscaler expands its TAM, it's going to start to acquire, and do similar types of things. We'll see how that integrates. CrowdStrike is clearly executing on a similar portfolio strategy, but they're coming at it from endpoint, okay? They have to partner for network security. Cisco is this big and legacy, but they've done a really good job of acquiring and using services to hide some of that complexity. Microsoft is, you know, they probably hate me saying this, but it's the just good enough strategy. And that may have hurt CrowdStrike last quarter, because the SMB was a soft, we'll see. But to specifically answer your question, the opportunity, we think, is to build the security supercloud. What does that mean? That means to have a common security platform across all clouds. So irrespective of whether you're running an Amazon, whether you're running an on-prem, Google, or Azure, the security policies, and the edicts, and the way you secure your enterprise, look the same. There's a PaaS layer, super PaaS layer for developers, so that that the developers can secure their code in a common framework across cloud. So that essentially, Nikesh sort of balked at it, said, "No, no, no, we're not, we're not really building a super cloud." But essentially they kind of are headed in that direction, I think. Although, what I don't know, like CrowdStrike and Microsoft are big competitors. He mentioned AWS and Google. We run on AWS, Google, and in their own data centers. That sounds like they don't currently run a Microsoft. 'Cause Microsoft is much more competitive with the security ecosystem. They got Identity, so they compete with Okta. They got Endpoint, so they compete with CrowdStrike, and Palo Alto. So Microsoft's at war with everybody. So can you build a super cloud on top of the clouds, the hyperscalers, and not do Microsoft? I would say no. >> Right. >> But there's nothing stopping Palo Alto from running in the Microsoft cloud. I don't know if that's a strategy, we should ask them. >> Yeah. They've done a great job in our last few minutes, of really expanding their TAM in the last few years, particularly under Nikesh's leadership. What are some of the things that you heard this morning that you think, really they've done a great job of expanding that TAM. He talked a little bit about, I didn't write the number down, but he talked a little bit about the market opportunity there. What do you see them doing as being best of breed for organizations that have 30 to 50 tools and need to consolidate that? >> Well the market opportunity's enormous. >> Lisa: It is. >> I mean, we're talking about, well north of a hundred billion dollars, I mean 150, 180, depending on whose numerator you use. Gartner, IDC. Dave's, whatever, it's big. Okay, and they've got... Okay, they're headed towards 7 billion out of 180 billion, whatever, again, number you use. So they started with network security, they put most of the network function in the cloud. They moved to Endpoint, Sassy for the edge. They've done acquisitions, the Cortex acquisition, to really bring automated threat intelligence. They just bought Cider Security, which is sort of the shift left, code security, developer, assistance, if you will. That whole shift left, protect right. And so I think a lot of opportunities to continue to acquire best of breed. I liked what Nikesh said. Keep the founders on board, sell them on the mission. Let them help with that integration and putting forth the cultural aspects. And then, sort of, integrate in. So big opportunities, do they get into Endpoint and compete with Okta? I think Okta's probably the one sort of outlier. They want to be the consolidator of identity, right? And they'll probably partner with Okta, just like Okta partners with CrowdStrike. So I think that's part of the challenge of being the consolidator. You're probably not going to be the consolidator for everything, but maybe someday you'll see some kind of mega merger of these companies. CrowdStrike and Okta, or Palo Alto and Okta, or to take on Microsoft, which would be kind of cool to watch. >> That would be. We have a great lineup, Dave. Today and tomorrow, full days, two full days of cube coverage. You mentioned Nir Zuk, we already had the CEO on, founder and CTO. We've got the chief product officer coming on next. We've got chief transformation officer of customers, partners. We're going to have great conversations, and really understand how this organization is helping customers ultimately achieve their SecOps transformation, their digital transformation. And really moved the needle forward to becoming secure data companies. So I'm looking forward to the next two days. >> Yeah, and Wendy Whitmore is coming on. She heads Unit 42, which is, from what I could tell, it's pretty much the competitor to Mandiant, which Google just bought. We had Kevin Mandia on at September at the CrowdStrike event. So that's interesting. That's who I was poking Nikesh a little bit on industry collaboration. You're tight with Google, and then he had an interesting answer. He said "Hey, you start sharing data, you don't know where it's going to go." I think Snowflake could help with that problem, actually. >> Interesting. >> Yeah, little Snowflake and some of the announcements ar Reinvent with the data clean rooms. Data sharing, you know, trusted data. That's one of the other things we didn't talk about, is the real tension in between security and regulation. So the regulators in public policy saying you can't move the data out of the country. And you have to prove to me that you have a chain of custody. That when you say you deleted something, you have to show me that you not only deleted the file, then the data, but also the metadata. That's a really hard problem. So to my point, something that Palo Alto might be able to solve. >> It might be. It'll be an interesting conversation with Unit 42. And like we said, we have a great lineup of guests today and tomorrow with you, so stick around. Lisa Martin and Dave Vellante are covering Palo Alto Networks Ignite 22 for you. We look forward to seeing you in our next segment. Stick around. (light music)
SUMMARY :
Brought to you by Palo Alto Networks. from the MGM Grand in beautiful Las Vegas. Because at the time, you about the ecosystem with Nikesh. and he cut out of the conference early, You know, one of the things and the way you secure your from running in the Microsoft cloud. What are some of the things of being the consolidator. And really moved the needle forward it's pretty much the and some of the announcements We look forward to seeing
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AWS re:Invent 2022 Host Savannah Peterson 1
>>The Cube is live with three different stages here at aws Reinvent in fabulous Las Vegas, Nevada, and wow, is it just buzzing in here? It is absolutely overwhelming, but also thrilling to be here in Las Vegas.
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The Cube is live with three different stages here at aws Reinvent in fabulous Las
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AWS re:Invent DAY 1 Highlights
>>Welcome to Las Vegas. It's the cube live at AWS Reinvent 22. >>The show floor doors just opened people pouring in, and you can certainly feel the excitement here. >>I've heard it's the largest >>Reinvent ever. I call that NextGen Cloud NextGen. It is. It's happening. It's happening right now. >>It is hot. It's a hot >>Show. >>Knowing you in covering your company, that this is not just yesterday, you came up with this idea that now everyone's talking about >>The >>Cube, where we are the leader in high tech coverage. >>It is. It's happening. It's happening right now. >>Wow. That was good. Woo. All right. There we go. Nice job guys.
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Day 1 Keynote Analysis | SuperComputing 22
>>Hello everyone. Welcome to the Cubes Live here in Dallas, Texas. I'm John Ferer, host of the Cube, Three days of wall to wall coverage. Of course, we've got the three fabulous guests here, myself, Savannah, Peterson. S look wonderful. >>Thank you. Jong on. I, I feel lucky to play the part here with my 10 gallon hat. >>Dave Nicholson, who's the analyst uncovering all the Dell Supercomputing, hpe all the technology is changing the game. Dave, you look great. Thanks for coming on. >>Thanks, John. I appreciate >>It. All right, so, so, so you look good. So we're in Dallas, Texas is a trade show conference. I don't know what you'd call this these days, but thousands of booths are here. What's the take here? Why supercomputing 22? What's the big deal? >>Well, the big deal is dramatic incremental progress in terms of supercomputing capability. So what this conference represents is the leading edge in what it can deliver to the world. We're talking about scale that is impossible to comprehend with the human brain, but you can toss out facts and figures like performance measured in ex flops, millions of CPU cores working together, thousands of kilowatts of power required to power these systems. And I think what makes this, what makes this show unique is that it's not just a bunch of vendors, but it's academia. It's PhD candidates coming and looking for companies that they might work with. So it's a very, very different vibe here. >>Savannah, we were talking last night before we were setting up our agenda for it to drill down on this week. And you know, you were, by the way, that looks great. I mean, I wish I had one. >>We'll get you one by the end of the show, >>John. Don't worry. You know, Texas is always big in Texas and that's the, the thing here, but Supercomputing seems like that had a lull for a while. Yeah, it seems like it's gonna explode and you get a chance to review the papers, take a look at it. You, you're a, I won't say closet hardware nerd, but that's your roots. >>Yeah, yeah. Very openly hardware nerd. And, and I'm excited because I, we saw a lot of hype around quantum and around AI five, 10 years ago, but we weren't seeing the application at scale and we also weren't seeing, quite frankly, the hardware wasn't ready to power these types of endeavors at scale. Whereas now, you know, we've got, we've got air cooling, we've got liquid cooling, we've got multiple GPU's. Dell was just showing me all eight of theirs that they put in their beautiful million dollar piece of equipment, which is extremely impressive for folks to run complex calculations. And, but what I'm excited about with all the, I love when we fuse business and academia together, I think that that doesn't happen very often. I've been impressed. I mean, when I walked in today, right away, I'm sure y'all can't see this at home just yet, but we'll try and give you a feel over the course of the next few days. This conference is huge. This >>Is, yeah, it is >>Way bigger than I was expecting, You know, a lot larger than where we just were in Detroit. And, and I love it because we've got the people that are literally inventing the calculations that will determine a lot of our future from sequencing our genome to powering our weather forecasting, as well as all of the companies that create the hardware and the software that's gonna actually support that. Those algorithms and >>Those, and, and the science and the engineering involved has just been going on since 1988. This conference, this trade show going on since 1988, which is, it, it passes the test of time and now the future with all the new use cases emerging from the compute and supercomputing architectures out there, it's from cradle to grave. If you're, if you're in this business, you, you're in school all the way through the industry, it doesn't seem to stop that, that university student side of it. I mean that whole student section here. So you don't see that very often in some of these tech shows, like from students to boardroom. >>Yeah. I actually brought the super computer from 1988 with me in my pocket. And I'm not sure that I'm even joking. I this may have as much processing power, certainly as much storage with one terabyte on board. I sprung for the one terabyte folks. But it is mind boggling the amount of compute power we're, we're talking about. When you dig below the surface, which we'll be doing in the coming days, you see things like leaping from P C I E, you know, gen four to gen five, and the increase that that gives us in, in terms of capabilities for plugging into the motherboard and accessing the CPU complex and on and on and on. But, but you know, something Savannah alluded to, we're talking about the leading edge of what is possible from a humanity perspective. 1%. And, and so I'd like to get into, you know, as we're we're talking to some of the experts that we'll get a chance to talk to, I'd like to get their view on what the future holds and whether we can simply grow through quantitative increases in compute power, or if the real promise is out there in the land of quantum computing, are we all sort of hanging our hats, our large 10 gallon hats? >>If that's yes. Our hats, if we're hanging our hats on that, that that's when truly we'll be able to tease insight out of chaos. I'd like to hear from some of the real experts on that subject. >>I'm glad you brought that up, cuz I'm personally pretty pumped about quantum computing, but I've seen it sit in this hype stage for quite a while and I'm ready for the application. So I'm curious to hear >>What our experts, That's an awesome, that would be, I think that would be an awesome bumper sticker. Frankly. Savannah, I'm pumped, I'm pumped about quantum computing. Who is this person? Who is this person? >>I wanna see it first. Did someone show me it? >>Yeah, yeah. 400 qubits I think was the latest IBM announcement, which, which means something. I'll pretend like I completely understand what it means. >>Tell us what that means, David. >>Well, well, so, so Savannah, let me man explain it to you. Yeah, >>Let's >>Hear it. So, so it's basically, it's, you know, in conventional computing you can either, you can either be on or off zero or one in quantum computing, you can be both, neither or all of the above. That's, that's, that's, that's the depth to which I can go. I >>Like that. That was actually a succinct, as humanly possible >>Really sounds like a Ponzi scheme to me. I, I'm not sure if I, >>Well, let's get into some of the thoughts that you guys have on some of the papers. We saw Savannah and Dave, your perspective on this whole next level kind of expansion with supercomputing and super cloud and super apps will do for this next gen. What use cases are kind of shining out of this, because, you know, it used to be you were limited by how much gear you had stacked up, how big the server could be, the supercomputer. Now you've got large scale cloud computing, you got the ability to have different subsystems like advances in networking. So you're seeing a new architectural, almost bigger. Super computing isn't just a machine, it's a collection of machines, It's a collection of Yeah. Of other stuff. What's your thoughts on these, this architecture and then the use cases that are gonna emerge that were not getable before? >>So in the past, you, you talk about, you know, 1988 and, and you know, let's say a decade ago, the race was to assemble enough compute power to be able to do things quickly enough to be practical. So we knew that if we applied software to hardware, we could get an answer to a problem because we were asking very, very specific questions. And how quickly we got the answer would determine whether it was practical to pursue it or not. So if something took a day instead of a month, okay, fantastic. But now we've reached this critical mass. You could argue when that happened, but definitely I think we're there where things like artificial intelligence and machine learning are the core of what we're doing. We're not just simply asking systems to deliver defined answers. We're asking them to learn from their experiences, starts getting a little spooky, and we're asking them to tease insights out in a way that we haven't figured out. >>So we're saying give us the insight. We're not telling the system specifically how to give us that insight. So I think that's, that's the fundamental difference that's the frontier, is, you know, you're gonna hear a lot about AI and ml and then if you retreat back a bit from Supercomputing, you're in the realm of high performance computing, which is sort of junior version of supercomputing. It's instead of the billion dollar system, it's the system that, you know, schlubs like, like, like, like Facebook or AWS might be able to afford, you know, maybe a hundred million dollars for a system casual, just, just sort of casual kind of thing next to the coffee table in the living room. But I think that's really gonna be the talk. So that's a huge tent when you talk about AI and ml. Yeah, >>I I, I totally agree. We're having some of the conversations that we've had for a long time about AI and bias. I saw a lot of the papers were looking at that. I think that's what's gonna be really interesting to me, what's most exciting about this is how are we pulling together all of this on a global scale. So I'm excited to see how supercomputing impacts climate change, our ability to monitor environmental conditions around the globe and different governments and bodies can all combine. And all of this information can be going into a central brain and learning from it and figuring out how we can make the world a better place. We're learning about the body. There's a lot of people doing molecular biology and sequencing of the genome here. We've got, there's, there's, It's just, it's very, I I don't think a lot of people realize that supercomputing pretty much touches every aspect of our >>Lives. I mean, we've had it, we've had it for a while. I think cloud computing took a lot of the attention, given that that brought in massive capabilities, a lot of agility. And I think what's interesting here at this show, if you look at, you know, what's going on from the guess, like I said, from the dorm room to the boardroom, everyone's here, but you look at what's actually going on above the hardware, CNCF is here. They have a booth, the whole cloud native software business. It's gonna be interesting to see how the software business takes advantage of totally. How these architectures, because let's face it, I've never heard a developer pointer say, I wanna run on slower hardware. So no one wants that. So now if you abstract away the hardware, as we know with, with cloud computing and DevOps cloud on premises and Edge, David, this is like, this is again, nirvana for the industry because you want, it's an exciting thing, the fastest possible compute system for the software. >>Yeah, yeah. >>I I, at the end of the day, that's what we're talking >>About. So I asked, I asked the, the gift question to my Wharton students this morning on a call, and I, you know, I asked specifically if, if I could give you something that was the result of super computing's amazing nature, what would it be? Would it be personalized therapeutics in healthcare? Would it be something related to climate? Being able to figure out exactly what we can do. There's a whole range of possibilities. And what's interesting is >>What were some of the answers? >>So, so, so a lot of the answers, a lot of the answers came down to, to two categories and it was really, it was healthcare and climate. Yeah. A lot of, a lot of understanding and of course, and of course a lot of jokes about how eventually supercomputers will determine that. The problem is people, >>It's people. Yeah, no. So I knew you were headed there, >>But >>Don't people just want custom jeans? Yeah. >>Or, well, so one of the, one of the good ones though was, >>Was also that >>While we're >>Here, a person from a company who shall not be named said, oh, advertising, it was the, it was the what if you could predict with a high degree of certainty that when you sent someone an email saying, Hey, do you wanna buy this? They would say, Well, yeah, I do. Dramatically lowering the cost of acquisition for an individual customer as an example. Those are the kinds of breakthroughs that will transform how we live. Because all of a sudden, industries are completely disrupted, disrupted, not necessarily directly related to supercomputing, but you think about automating the entire fleet of, of, of trucks in, in North America. What does that do to people who currently drive those trucks? Yeah, so there are, there are societal questions at hand that I don't necessarily know the academics are, are, are considering when they're thinking what's possible. >>Well, I think, I think the point about the ad thing brings up the whole cultural shift that's going on from the old generation of, Hey, let's use our best minds in the industry to figure out how to place an ad at the right place in the right pixel, at the right time. Versus solving real problems like climate change our, you know, culture and society and get us getting along as a country and world water sustainability fires in California. Yeah, I mean, come on. >>There's a lot. So I, I gotta say, I was curious when you were playing with your pocket computer there and talking about the terabyte that you have inside. So back in 1988 when Supercomputing started, the first show was in Orlando. It was actually the same four days that we're here right now. I was born in 1988 if we're just talking about how great 1988 is. And so I guess I, >>I was born, So were we Savannah? So were we >>The era of, I think I was in third grade at that time. >>We won't tell, we won't say what you told me earlier about 1988 for you. But that said, so 1988 was when Steve Jobs released the next computer. He was out of Apple at that time. Yeah, that's right. >>Eight >>Megabytes of Ram. >>It's called the Cube. I think >>It's respectable. That's all it was called. It was, it was, it was, it was the cube, which is pretty, pretty exciting. But when we were looking at, yeah, on the supercomputing side, your phone would've been about, is a capable, >>So where will we be in 20 years? It's amazing >>What we gonna, >>Will our holograms be here instead of us physically sitting, sitting at the table? I don't know. >>Well, it's gonna be very interesting to see how the global ecosystem evolves. It used to be very nationalistic culture with computing. I think, I think we're gonna see global, you know, flattening of culture relative to computing. I think space will be a, a massive hopeful, massive discussion. I think software and automation will be at levels we don't even see. So I think software, to me, I'm looking at, that's the enablement of this supercomputing show. In terms of the next five years, what are they gonna do to enable more faster intelligent horsepower? And, and what does that look like? Is it, it used to be simple processor, more processors, more threads, multicores, and then stuff around it. I think this is where I think it's gonna shift to more network computing, network processing, edge latency, physics is involved. I mean, every, everything you can squeeze out of the physics will be Yeah. Interesting to watch. Well, when >>We, when we, when we peel back the cover on the actual pieces of hardware that are driving this revolution, parallelizing, you know, of workloads is critical to this. It's what super computing consists of. There's no such thing as a supercomputer sitting by itself on a table. Even the million dollar system from Dell, which is crazy when you hear Dell and million dollar system. >>And it's still there too, >>Right? Just, just hanging out. Yeah. But, but it's all about the interconnect. When you want to take advantage of parallel processing, you have to have software that can leverage all of the resources and connectivity becomes increasingly important. I think that's gonna be a thread that we're gonna see throughout the next few days with the, with the, you know, the motherboards, for lack of a lack of a better term, allowing faster access to memory, faster access to cpu, gpu, dpu, networking, storage devices, plugging in those all work together. But increasingly it's that connectivity layer that's critically important. Questions of InfiniBand versus ethernet. Our DMA over converged ethernet as an example, a lot of these architectural decisions are gonna be based on power cooling, dead city. So lot of details behind the scenes to make the magic happen. I >>Think the power is gonna be, you know, thinking 20 years out, hopefully everything here is powered sustainably 20 years from now because power pull, I mean these, the more exciting things going on in your supercomputer. The power suck is massive. That when we were talking to Dell, they were saying that's one of the biggest problems, >>Concerns, that's gonna their customers and that's gonna play into sustainability. So a lot of great guests, we got folks from Dell and the industry, a lot of the manufacturers, a lot of the hardware software experts gonna come on and share what's going on. You know, we did a, we did a post why hardware matters a few months ago, Dave. Everyone's like, well it does now more than ever. So we're gonna get into it here at Supercomputing 22, where the hardware matters. Faster power, as we say for the applications. Mr. Cube, moving back with more live coverage. Stay with us back.
SUMMARY :
host of the Cube, Three days of wall to wall coverage. I, I feel lucky to play the part here with my 10 gallon hat. hpe all the technology is changing the game. It. All right, so, so, so you look good. And I think what makes And you know, you were, by the way, that looks great. Yeah, it seems like it's gonna explode and you get a chance to review the papers, Whereas now, you know, we've got, we've got air cooling, that will determine a lot of our future from sequencing our genome to powering our weather forecasting, So you don't see that very often in some of these tech shows, 1%. And, and so I'd like to get into, you know, I'd like to hear from some of the real experts on So I'm curious to hear What our experts, That's an awesome, that would be, I think that would be an awesome bumper sticker. I wanna see it first. 400 qubits I think was the latest IBM announcement, Well, well, so, so Savannah, let me man explain it to you. That's, that's, that's, that's the depth to which I That was actually a succinct, as humanly possible Really sounds like a Ponzi scheme to me. Well, let's get into some of the thoughts that you guys have on some of the papers. So in the past, you, you talk about, you know, 1988 and, and you know, let's say a decade ago, It's instead of the billion dollar system, it's the system that, you know, I saw a lot of the papers were looking at that. So now if you abstract away the hardware, as we know with, and I, you know, I asked specifically if, if I could give you something that was So, so, so a lot of the answers, a lot of the answers came down to, to two categories and it was Yeah, no. So I knew you were headed there, Yeah. oh, advertising, it was the, it was the what if you could predict with a high degree of certainty change our, you know, culture and society and get us getting along as a So I, I gotta say, I was curious when you were playing with your pocket computer there and We won't tell, we won't say what you told me earlier about 1988 for you. That's all it was called. I don't know. So I think software, to me, I'm looking at, that's the enablement of this Even the million dollar system from Dell, which is crazy when you hear Dell and million dollar system. So lot of details behind the scenes to make the magic happen. Think the power is gonna be, you know, thinking 20 years out, hopefully everything here is powered sustainably 20 years So a lot of great guests,
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Day 1 Wrap | KubeCon + CloudNativeCon NA 2022
>>Hello and welcome back to the live coverage of the Cube here. Live in Detroit, Michigan for Cub Con, our seventh year covering all seven years. The cube has been here. M John Fur, host of the Cube, co-founder of the Cube. I'm here with Lisa Mart, my co-host, and our new host, Savannah Peterson. Great to see you guys. We're wrapping up day one of three days of coverage, and our guest analyst is Sario Wall, who's the cube analyst who's gonna give us his report. He's been out all day, ear to the ground in the sessions, peeking in, sneaking in, crashing him, getting all the data. Great to see you, Sarvi. Lisa Savannah, let's wrap this puppy up. >>I am so excited to be here. My first coupon with the cube and being here with you and Lisa has just been a treat. I can't wait to hear what you have to say in on the report side. And I mean, I have just been reflecting, it was last year's coupon that brought me to you, so I feel so lucky. So much can change in a year, folks. You never know where you're be. Wherever you're sitting today, you could be living your dreams in just a few >>Months. Lisa, so much has changed. I mean, just look at the past this year. Events we're back in person. Yeah. Yep. This is a big team here. They're still wearing masks, although we can take 'em off with a cube. But mask requirement. Tech has changed. Conversations are upleveling, skill gaps still there. So much has changed. >>So much has changed. There's so much evolution and so much innovation that we've also seen. You know, we started out the keynote this morning, standing room. Only thousands of people are here. Even though there's a mass requirement, the community that is CNCF Co Con is stronger than I, stronger than I saw it last year. This is only my second co con. But the collaboration, what they've done, their devotion to the maintainers, their devotion to really finding mentors for mentees was really a strong message this morning. And we heard a >>Lot of that today. And it's going beyond Kubernetes, even though it's called co con. I also call it cloud native con, which I think we'll probably end up being the name because at the end of day, the cloud native scaling, you're starting to see the pressure points. You're start to see where things are breaking, where automation's coming in, breaking in a good way. And we're gonna break it all down Again. So much going on again, I've overs gonna be in charge. Digital is transformation. If you take it to its conclusion, then you will see that the developers are running the business. It isn't a department, it's not serving the business, it is the business. If that's the case, everything has to change. And we're, we're happy to have Sarib here with us Cube analysts on the badge. I saw that with the press pass. Well, >>Thank you. Thanks for getting me that badge. So I'm here with you guys and >>Well, you got a rapport. Let's get into it. You, I >>Know. Let's hear what you gotta say. I'm excited. >>Yeah. Went around, actually attend some sessions and, and with the analysts were sitting in, in the media slash press, and I spoke to some people at their booth and the, there are a few, few patterns, you know, which are, some are the exaggeration of existing patterns or some are kind of new patterns emerging. So things are getting complex in open source. The lawn more projects, right. They have, the CNCF has graduated some projects even after graduation, they're, they're exploring, right? Kubernetes is one of those projects which has graduated. And on that front, just a side note, the new projects where, which are entering the cncf, they're the, we, we gotta see that process and the three stages and all that stuff. I tweeted all day long, if you wanna know what it is, you can look at my tweets. But when I will look, actually write right on that actually after, after the show ends, what, what I saw there, these new projects need to be curated properly. >>I think they need to be weed. There's a lot of noise in these projects. There's a lot of overlap. So the, the work is cut out for CNCF folks, by the way. They're sort of managerial committee or whatever you call that. The, the people who are leading it, they're try, I think they're doing their best and they're doing a good job of that. And another thing actually, I really liked in the morning's keynote was that lot of women on the stage and minorities represented. I loved it, to be honest with you. So believe me, I'm a minority even though I'm Indian, but from India, I'm a minority. So people who have Punjab either know that I'm a minority, so I, I understand their pain and how hard it is to, to break through the ceiling and all that. So I love that part as well. Yeah, the >>Activity is clear. Yeah. From day one. It's in the, it's in the dna. I mean, they'll reject anything that the opposite >>Representation too. I mean, it's not just that everyone's invited, it's they're celebrated and that's a very big difference. Yeah. It's, you see conferences offer discounts for women for tickets or minorities, but you don't necessarily see them put them running where their mouth is actually recruit the right women to be on stage. Right. Something you know a little bit about John >>Diversity brings better outcomes, better product perspectives. The product is better with all the perspectives involved. Percent, it might go a little slower, maybe a little debates, but it's all good. I mean, it's, to me, the better product comes when everyone's in. >>I hope you didn't just imply that women would make society. So >>I think John men, like slower means a slower, >>More diversity, more debate, >>The worst. Bringing the diversity into picture >>Wine. That's, that's how good groups, which is, which is >>Great. I mean, yeah, yeah, >>Yeah, yeah. I, I take that mulligan back and say, hey, you knows >>That's >>Just, it's gonna go so much faster and better and cheaper, but that not diversity. Absolutely. >>Yes. Well, you make better products faster because you have a variety >>Of perspectives. The bigger the group, there's more debate. More debate is key. But the key to success is aligning and committing. Absolutely. Once you have that, and that's what open sources has been about for. Oh God, yeah. Generations >>Has been a huge theme in the >>Show generations. All right, so, so, >>So you have to add another, like another important, so observation if you will, is that the security is, is paramount right. Requirement, especially for open source. There was a stat which was presented in the morning that 60% of the projects in under CNCF have more vulnerabilities today than they had last year. So that was, That's shocking actually. It's a big jump. It's a big jump. Like big jump means jump, jump means like it can be from from 40 to 60 or or 50 or 60. But still that percentage is high. What, what that means is that lot more people are contributing. It's very sort of di carmic or ironic that we say like, Oh this project has 10,000 contributors. Is that a good thing? Right. We do. Do we know the quality of that, where they're coming from? Are there any back doors being, you know, open there? How stringent is the process of rolling those things, which are being checked in, into production? You know, who is doing that? I've >>Wondered about that. Yeah. The quantity, quality, efficacy game. Yes. And what a balance that must be for someone like CNCF putting in the structure to try and >>That's >>Hard. Curate and regulate and, and you know, provide some bumpers on the bowling lane, so to speak, of, of all of these projects. Yeah. >>Yeah. We thought if anybody thought that the innovation coming from, or the number of services coming from AWS or Google Cloud or likes of them is overwhelming, look at open source, it's even more >>Overwhelming. What's your take on the supply chain discussion? More code more happening. What are you hearing there? >>The supply chain from the software? Yeah. >>Supply chain software, supply chain security pays. Are people talking about that? What are you >>Seeing? Yeah, actually people are talking about that. The creation, the curation, not creation. Curation of suppliers of software I think is best done in the cloud. Marketplaces Ive call biased or what, you know, but curation of open source is hard. It's hard to know which project to pick. It's hard to know which project will pan out. Many of the good projects don't see the day light of the day, but some decent ones like it becomes >>A marketing problem. Exactly. The more you have out there. Exactly. The more you gotta get above the noise. Exactly. And the noise echo that. And you got, you got GitHub stars, you got contributors, you have vanity metrics now coming in to this that are influencing what's real. But sometimes the best project could have smaller groups. >>Yeah, exactly. And another controversial thing a little bit I will say that is that there's a economics of the practitioner, right? I usually talk about that and economics of the, the enterprise, right? So practitioners in our world, in software world especially right in systems world, practitioners are changing jobs every two to three years. And number of developers doubles every three years. That's the stat I've seen from Uncle Bob. He's authority on that software side of things. Wow. So that means there's a lot more new entrance that means a lot of churn. So who is watching out for the enterprise enterprises economics, You know, like are we creating stable enterprises? How stable are our operations? On a side note to that, most of us see the software as like one band, which is not true. When we talk about all these roles and personas, somebody's writing software for, for core layer, which is the infrastructure part. Somebody's writing business applications, somebody's writing, you know, systems of bracket, some somebody's writing systems of differentiation. We talk about those things. We need to distinguish between those and have principle based technology consumption, which I usually write about in our Oh, >>So bottom line in Europe about it, in your opinion. Yeah. What's the top story here at coupon? >>Top story is >>Headline. Yeah, >>The, the headline. Okay. The open source cannot be ignored. That's a headline. >>And what should people be paying attention to if there's a trend coming out? See any kind of trends coming out or any kind of signal, What, what do you see that people should pay attention to here? The put top >>Two, three things. The signal is that, that if you are a big shop, like you'd need to assess your like capacity to absorb open source. You need to be certain size to absorb the open source. If you are below that threshold, I mean we can talk about that at some other time. Like what is that threshold? I will suggest you to go with the managed services from somebody, whoever is providing those managed services around open source. So manage es, right? So from, take it from aws, Google Cloud or Azure or IBM or anybody, right? So use open source as managed offering rather than doing it yourself. Because doing it yourself is a lot more heavy lifting. >>I I, >>There's so many thoughts coming, right? >>Mind it's, >>So I gotta ask you, what's your rapport? You have some swag, What's the swag look >>Like to you? I do. Just as serious of a report as you do on the to floor, but I do, so you know, I come from a marketing background and as I, I know that Lisa does as well. And one of the things that I think about that we touched on in this is, is you know, canceling the noise or standing out from the noise and, and on a show floor, that's actually a huge challenge for these startups, especially when you're up against a rancher or companies or a Cisco with a very large budget. And let's say you've only got a couple grand for an activation here. Like most of my clients, that's how I ended up in the CU County ecosystem, was here with the A client before. So there actually was a booth over there and I, they didn't quite catch me enough, but they had noise canceling headphones. >>So if you just wanted to take a minute on the show floor and just not hear anything, which I thought was a little bit clever, but gonna take you through some of my favorite swag from today and to all the vendors, you know, this is why you should really put some thought into your swag. You never know when you're gonna end up on the cube. So since most swag is injection molded plastic that's gonna end up in the landfill, I really appreciate that garden has given all of us a potable plant. And even the packaging is plantable, which is very exciting. So most sustainable swag goes to garden. Well done >>Rep replicated, I believe is their name. They do a really good job every year. They had some very funny pins that say a word that, I'm not gonna say live on television, but they have created, they brought two things for us, yet it's replicated little etch sketch for your inner child, which is very nice. And given that we are in Detroit, we are in Motor City, we are in the home of Ford. We had Ford on the show. I love that they have done the custom K eight s key chains in the blue oval logo. Like >>Fords right behind us by the way, and are on you >>Interviewed, we had 'em on earlier GitLab taking it one level more personal and actually giving out digital portraits today. Nice. Cool. Which is quite fun. Get lap house multiple booths here. They actually IPOed while they were on the show floor at CubeCon 2021, which is fun to see that whole gang again. And then last but not least, really embracing the ship wheel logo of a Kubernetes is the robusta accrue that is giving out bucket hats. And if you check out my Twitter at sabba Savvy, you can see me holding the ship wheel that they're letting everyone pose with. So we are all in on Kubernetes. That cove gone 2022, that's for sure. Yeah. >>And this is something, day one guys, we've got three. >>I wanna get one of those >>Hats. We we need to, we need a group photo >>By the end of Friday we will have a beverage and hats on to sign off. That's, that's my word. If I can convince John, >>Don, what's your takeaway? You guys did a great kind of kickoff about last week or so about what you were excited about, what your thoughts were going to be. We're only on day one, There's been thousands of people here, we've had great conversations with contributors, the community. What's your take on day one? What's your, what's your tagline? >>Well, Savannah and I had at we up, we, we were talking about what we might see and I think we, we were right. I think we had it right. There's gonna be a lot more people than there were last year. Okay, check. That's definitely true. We're in >>Person, which >>Is refreshing. I was very surprised about the mask mandate that kind of caught me up guard. I was major. Yeah. Cause I've been comfortable without the mask. I'm not a mask person, but I had to wear it and I was like, ah, mask. But I understand I support that. But whatever. It's >>Corporate travel policy. So you know, that's what it is. >>And then, you know, they, I thought that they did an okay job with the gates, but they wasn't slow like last time. But on the content side, definitely Kubernetes security, top line headline, Kubernetes at scale security, that's, that's to me the bumper sticker top things to pay attention to the supply chain and the role of docker and the web assembly was a surprise. You're starting to see containers ecosystem coming back to, I won't say tension growth in the functionality of containers cuz they have to solve the security problem in the container images. Okay, you got scanning technology so it's a little bit in the weeds, but there's a huge movement going on to fix that problem to scale it so it's not a problem area contain. And then Dr sent a great job with productivity interviews. Scott Johnston over a hundred million in revenue so far. That's my number. They have not publicly said that. That's what I'm reporting from sources extremely well financially. And they, and they love their business model. They make productivity for developers. That's a scoop. That's new >>Information. That's a nice scoop we just dropped there on the co casually. >>You're watching that. Pay attention to that. But that, that's proof. But guess what, Red Hat's got developers too. Yes. Other people have to, So developers gonna go where it's the best. Yeah. Developers are voting with their code, they're voting with their feet. You will see the winners with the developers and that's what we've talked about. >>Well and the companies are catering to the developers. Savannah and I had a great conversation with Ford. Yeah. You saw, you showed their fantastic swag was an E for Ev right behind us. They were talking about the, all the cultural changes that they've really focused on to cater towards the developers. The developers becoming the influencers as you say. But to see a company that is as, as historied as Ford Motor Company and what they're doing to attract and retain developer talent was impressive. And honestly that surprised me. Yeah. >>And their head of deb relations has been working for, for, for 29 years. Which I mean first of all, most companies on the show floor haven't been around for 29 years. Right. But what I love is when you put community first, you get employees to stick around. And I think community is one of the biggest themes here at Cuco. >>Great. My, my favorite story that surprised me and was cool was the Red Hat Lockheed Martin interview where they had edge deployments with micro edge, >>Micro shift, >>Micro >>Shift, new projects under, there's, there are three new projects under, >>Under that was so, so cool because it was an edge story in deployment for the military where lives are on the line, they actually had it working. That is a real world example of Kubernetes and tech orchestrating to deploy the industrial edge. And I think that's proof in my mind that Kubernetes and this ecosystem is gonna move faster through this next wave of growth. Because once things start clicking, you get hybrid on premise to super cloud and edge. That was, that was my favorite cause it was real. That was real >>Story that it can make is literally life and death on the battlefield. Yeah, that was amazing. With what they're doing and what >>They're talking check out the Lockheed Martin Red Hat edge story on Silicon Angle and then a press release all pillar. >>Yeah. Another actually it's impressive, which we knew this which is happening, but I didn't know that it was happening at this scale is the finops. The finops is, I saw your is a discipline which most companies are adopting bigger companies, which are spending like hundreds of millions dollars in cloud average. Si a team size of finops for finops is seven people. And average number of tools is I think 3.5 or around 3.7 or something like that. Average number of tools they use to control the cost. So finops is a very generic term for years. It's not financial operations, it's the financial operations for the cloud cost, you know, containing the cloud costs. So that's a finops that is a very emerging sort of discipline >>To keep an eye on. And well, not only is that important, I talked to, well one of the principles over there, it's growing and they have real big players in that foundation. Their, their events are highly attended. It's super important. It's just, it's the cost side of cloud. And, and of course, you know, everyone wants to know what's going on. No one wants to leave there. Their Amazon on Yeah, you wanna leave the lights on the cloud, as we always say, you never know what the bill's gonna look like. >>The cloud is gonna reach $3 billion in next few years. So we might as well control the cost there. Yeah, >>It was, it was funny to get the reaction I found, I don't know if I was, how I react, I dunno how I felt. But we, we did introduce Super Cloud to a couple of guests and a, there were a couple reactions, a couple drawn. There was a couple, right. There was a couple, couple reactions. And what I love about the super cloud is that some people are like, oh, cringing. And some people are like, yeah, go. So it's a, it's a solid debate. It is solid. I saw more in the segments that I did with you together. People leaning in. Yeah. Super fun. We had a couple sum up, we had a couple, we had a couple cringes, I'll say their names, but I'll go back and make sure I, >>I think people >>Get 'em later. I think people, >>I think people cringe on the, on the term not on the idea. Yeah. You know, so the whole idea is that we are building top of the cloud >>And then so I mean you're gonna like this, I did successfully introduce here on the cube, a new term called architectural list. He did? That's right. Okay. And I wanna thank Charles Fitzgerald for that cuz he called super cloud architectural list. And that's exactly the point of super cloud. If you have a great coding environment, you shouldn't have to do an architecture to do. You should code and let the architecture of the Super cloud make it happen. And of course Brian Gracely, who will be on tomorrow at his cloud cast said Super Cloud enables super services. Super Cloud enables what Super services, super service. The microservices underneath the covers have to be different. High performing, automated. So again, the debate and Susan, the goal is to keep it open. And that's our, that's our goal. But we had a lot of fun with that. It was fun to poke the bear a little bit. So >>What is interesting to see just how people respond to it too, with you throwing it out there so consistently, >>You wanna poke the bear, get a conversation going, you know, let let it go. We'll see, it's been positive so far. >>There, there I had a discussion outside somebody who is from Ford but not attending this conference and they have been there for a while. I, I just some moment hit like me, like I said, people, okay, technologists are horizontal, the codes are horizontal. They will go from four to GM to Chrysler to Bank of America to, you know, GE whatever, you know, like cross vertical within vertical different vendors. So, but the culture of a company is local, right? Right. Ford has been building cars for forever. They sort of democratize it. They commercialize it, right? But they have some intense culture. It's hard to change those cultures. And how do we bring in the new thinking? What is, what approach that should be? Is it a sandbox approach for like putting new sensors on the car? They have to compete with te likes our Tesla, right? Yeah. But they cannot, if they are afraid of deluding their existing market or they're afraid of failure there, right? So it's very >>Tricky. Great stuff. Sorry. Great to have you on as our cube analyst breaking down the stories. We'll document that, that we'll roll out a post on it. Lisa Savannah, let's wrap up the show for day one. We got day two and three. We'll start with you. What's your summary? Quick bumper sticker. What's today's show all about? >>I'm a community first gal and this entire experience is about community and it's really nice to see the community come together, celebrate that, share ideas, and to have our community together on stage. >>Yeah. To me, to me it was all real. It's happening. Kubernetes cloud native at scale, it's happening, it's real. And we see proof points and we're gonna have faster time to value. It's gonna accelerate faster from here. >>The proof points, the impact is real. And we saw that in some amazing stories. And this is just a one of the cubes >>Coverage. Ib final word on this segment was well >>Said Lisa. Yeah, I, I think I, I would repeat what I said. I got eight, nine years back at a rack space conference. Open source is amazing for one biggest reason. It gives the ability to the developing nations to be at somewhat at par where the dev develop nations and, and those people to lift up their masses through the automation. Cuz when automation happens, the corruption goes down and the economy blossoms. And I think it's great and, and we need to do more in it, but we have to be careful about the supply chains around the software so that, so our systems are secure and they are robust. Yeah, >>That's it. Okay. To me for SAR B and my two great co-host, Lisa Martin, Savannah Peterson. I'm John Furry. You're watching the Cube Day one in, in the Books. We'll see you tomorrow, day two Cuban Cloud Native live in Detroit. Thanks for watching.
SUMMARY :
Great to see you guys. I can't wait to hear what you have to say in on the report side. I mean, just look at the past this year. But the collaboration, what they've done, their devotion If that's the case, everything has to change. So I'm here with you guys and Well, you got a rapport. I'm excited. in the media slash press, and I spoke to some people at their I loved it, to be honest with you. that the opposite I mean, it's not just that everyone's invited, it's they're celebrated and I mean, it's, to me, the better product comes when everyone's in. I hope you didn't just imply that women would make society. Bringing the diversity into picture I mean, yeah, yeah, I, I take that mulligan back and say, hey, you knows Just, it's gonna go so much faster and better and cheaper, but that not diversity. But the key to success is aligning So you have to add another, like another important, so observation And what a balance that must be for someone like CNCF putting in the structure to try and of all of these projects. from, or the number of services coming from AWS or Google Cloud or likes of them is What are you hearing there? The supply chain from the software? What are you Many of the And you got, you got GitHub stars, you got the software as like one band, which is not true. What's the top story here Yeah, The, the headline. I will suggest you to And one of the things that I think about that we touched on in this is, to all the vendors, you know, this is why you should really put some thought into your swag. And given that we are in Detroit, we are in Motor City, And if you check out my Twitter at sabba Savvy, By the end of Friday we will have a beverage and hats on to sign off. last week or so about what you were excited about, what your thoughts were going to be. I think we had it right. I was very surprised about the mask mandate that kind of caught me up guard. So you know, that's what it is. And then, you know, they, I thought that they did an okay job with the gates, but they wasn't slow like last time. That's a nice scoop we just dropped there on the co casually. You will see the winners with the developers and that's what we've The developers becoming the influencers as you say. But what I love is when you put community first, you get employees to stick around. My, my favorite story that surprised me and was cool was the Red Hat Lockheed And I think that's proof in my mind that Kubernetes and this ecosystem is Story that it can make is literally life and death on the battlefield. They're talking check out the Lockheed Martin Red Hat edge story on Silicon Angle and for the cloud cost, you know, containing the cloud costs. And, and of course, you know, everyone wants to know what's going on. So we might as well control the I saw more in the segments that I did with you together. I think people, so the whole idea is that we are building top of the cloud So again, the debate and Susan, the goal is to keep it open. You wanna poke the bear, get a conversation going, you know, let let it go. to Chrysler to Bank of America to, you know, GE whatever, Great to have you on as our cube analyst breaking down the stories. I'm a community first gal and this entire experience is about community and it's really nice to see And we see proof points and we're gonna have faster time to value. The proof points, the impact is real. Ib final word on this segment was well It gives the ability to the developing nations We'll see you tomorrow, day two Cuban Cloud Native live in Detroit.
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Day 1 Keynote Analysis | CrowdStrike Fal.Con 2022
(upbeat music) >> Hello everyone, and welcome to Fal.Con 2022, CrowdStrike's big user conference. You're watching the Cube. My name is Dave Vallante. I'm here with my co-host David Nicholson. CrowdStrike is a company that was founded over 10 years ago. This is about 11 years, almost to the day. They're 2 billion company in revenue terms. They're growing at about 60% a year. They've got a path they've committed to wall street. They've got a path to $5 billion by mid decade. They got a $40 billion market cap. They're free, free cash flow positive and trying to build essentially a generational company with a very growing Tam and a modern platform. CrowdStrike has the fundamental belief that the unstoppable breach is a myth. David Nicholson, even though CSOs don't believe that, CrowdStrike is on a mission. Right? >> I didn't hear the phrase. Zero trust mentioned in the keynote >> Right. >> What was mentioned was this idea that CrowdStrike isn't simply a tool, it's a platform. And obviously it takes a platform to get to 5 billion. >> Yeah. So let's talk about the keynote. George Kurtz, the CEO came on. I thought the keynote was, was measured, but very substantive. It was not a lot of hype in there. Most security conferences, the two exceptions are this one and Reinforce, Amazon's big security conference. Steven Schmidt. The first time I was at a Reinforce said "All this narrative about security is such a bad industry" and "We're not doing a great job." And "It's so scary." That doesn't help the industry. George Kurtz sort of took a similar message. And you know what, Dave? When I think of security outside the context of IT I think of like security guards >> Right. >> Like protecting the billionaires. Right? That's a powerful, you know, positive thing. It's not really a defensive movement even though it is defensive but so that was kind of his posture there. But he talked about essentially what I call, not his words permanent changes in the, in the in the cyber defense industry, subsequent to the pandemic. Again, he didn't specifically mention the pandemic but he alluded to, you know, this new world that we live in. Fal.Con is a hundred sessions, eight tracks. And really his contention is we're in the early innings. These guys got 20,000 customers. And I think they got the potential to have hundreds of thousands. >> Yeah. Yeah. So, if I'm working with a security company I want them to be measured. I'm not looking for hype. I don't want those. I don't want those guards to be in disco shirts. I want them in black suits. So, you know, so the, the, the point about measured is is I think a positive one. I was struck by the competence of the people who were on stage today. I have seen very very large companies become kind of bureaucratic. And sometimes you don't get the best of the best up on stage. And we saw a lot of impressive folks. >> Yeah. Michael Santonis get up, but before we get to him. So, a couple points that Kurtz made he said, "digital transformation is needed to bring modern architectures to IT. And that brings modern security." And he laid out that whole sort of old way, new way very Andy Jassy-like old guard, new guard. He didn't hit on it that hard but he basically said "security is all about mitigating risk." And he mentioned that the the CSO I say CSO, he says CSO or CSO has a seat at the board. Now, many CSOs are board level participants. And then he went into the sort of four pillars of, of workload, and the areas that they focus on. So workload to them is end point, identity, and then data. They don't touch network security. That's where they partner with the likes of Cisco, >> Right. >> And Palo Alto networks. But then they went deep into identity threat protection, data, which is their observability platform from an acquisition called Humio. And then they went big time into XDR. We're going to talk about all this stuff. He said, "data is the new digital currency." Talked a lot about how they're now renaming, Humio, Log Scale. That's their Splunk killer. We're going to talk about that all week. And he talked a little bit about the single agent architecture. That is kind of the linchpin of CrowdStrike's architecture. And then Michael Santonis, the CTO came on and did a deep dive into each of those, and really went deep into XDR extended, right? Detection and response. XDR building on EDR. >> Yeah. I think the subject of XDR is something we'll be, we'll be touching on a lot. I think in the next two days. I thought the extension into observability was very, very interesting. When you look at performance metrics, where things are gathering those things in and being able to use a single agent to do so. That speaks to this idea that they are a platform and not just a tool. It's easy to say that you aspire to be a platform. I think that's a proof point. On the subject, by the way of their fundamental architecture. Over the years, there have been times when saying that your infrastructure requires an agent that would've been a deal killer. People say "No agents!" They've stuck to their guns because they know that the best way to deliver what they deliver is to have an agent in the environment. And it has proven to be the right strategy. >> Well, this is one of the things I want to explore with the technical architects that come on here today is, how do you build a lightweight agent that can do everything that you say it's going to do? Because they started out at endpoint, and then they've extended it to all these other modules, you know, identity. They're now into observability. They've got this data platform. They just announced that acquisition of another company they bought Preempt, which is their identity. They announced Responsify, responsify? Reposify, which is sort of extends the observability and gives them visualization or visibility. And I'm like, how do you take? How do you keep an agent lightweight? That's one of the things I want to better understand. And then the other is, as you get into XDR I thought Michael Santonis was pretty interesting. He had black hat last month. He did a little video, you know. >> That was great >> Man in the street, what's XDR what's XDR what's XDR. I thought the best response was, somebody said "a holistic approach to end point security." And so it's really an evolution of, of EDR. So we're going to talk about that. But, how do you keep an agent lightweight and still support all these other capabilities? That's something I really want to dig into, you know, without getting bloated. >> Yeah, Yeah. I think it's all about the TLAs, Dave. It's about the S, it's about SDKs and APIs and having an ecosystem of partners that will look at the lightweight agent and then develop around it. Again, going back to the idea of platform, it's critical. If you're trying to do it all on your own, you get bloat. If you try to be all things to all people with your agent, if you try to reverse engineer every capability that's out there, it doesn't work. >> Well that's one of the things that, again I want to explore because CrowdStrike is trying to be a generational company. In the Breaking Analysis that we published this week. One of the things I said, "In order to be a generational company you have to have a strong ecosystem." Now the ecosystem here is respectable, you know, but it's obviously not AWS class. You know, I think Snowflake is a really good example, ServiceNow. This feels to me like ServiceNow circa 2013. >> Yeah. >> And we've seen how ServiceNow has evolved. You know, Okta, bought Off Zero to give them the developer angle. We heard a little bit about a developer platform today. I want to dig into that some more. And we heard a lot about everybody hates their DLP. I want to get rid of my DLP, data loss prevention. And so, and the same thing with the SIM. One of the ETR round table, Eric Bradley, our colleague at a round table said "If it weren't for the compliance requirements, I would replace my SIM with XDR." And so that's again, another interesting topic. CrowdStrike, cloud native, lightweight agent, you know, some really interesting tuck in acquisitions. Great go-to-market, you know, not super hype just product that works and gets stuff done, you know, seems to have a really good, bright future. >> Yeah, no, I would agree. Definitely. No hype necessary. Just constant execution moving forward. It's clearly something that will be increasingly in demand. Another subject that came up that I thought was interesting, in the keynote, was this idea of security for elections, extending into the realm of misinformation and disinformation which are both very very loaded terms. It'll be very interesting to see how security works its way into that realm in the future. >> Yeah, yeah, >> Yeah. >> Yeah, his guy, Kevin Mandia, who is the CEO of Mandiant, which just got acquired. Google just closed the deal for $5.4 billion. I thought that was kind of light, by the way, I thought Mandiant was worth more than that. Still a good number, but, and Kevin, you know was the founder and, >> Great guy. >> they were self-funded. >> Yeah, yeah impressive. >> So. But I thought he was really impressive. He talked about election security in terms of hardening you know, the election infrastructure, but then, boom he went right to what I see as the biggest issue, disinformation. And so I'm sitting there asking myself, okay how do you deal with that? And what he talked about was mapping network effects and monitoring network effects, >> Right. >> to see who's pumping the disinformation and building career streams to really monitor those network effects, positive, you know, factual or non-factual network or information. Because a lot of times, you know, networks will pump factual information to build credibility. Right? >> Right. >> And get street cred, earn that trust. You know, you talk about zero trust. And then pump disinformation into the network. So they've now got a track. We'll get, we have Kevin Mandia on later with Sean Henry who's the CSO yeah, the the CSO or C S O, chief security officer of CrowdStrike >> more TLA. Well, so, you can think of it as almost the modern equivalent of the political ad where the candidate at the end says I support this ad or I stand behind whatever's in this ad. Forget about trying to define what is dis or misinformation. What is opinion versus fact. Let's have a standard for finding, for exposing where the information is coming from. So if you could see, if you're reading something and there is something that is easily de-code able that says this information is coming from a troll farm of a thousand bots and you can sort of examine the underlying ethos behind where this information is coming from. And you can take that into consideration. Personally, I'm not a believer in trying to filter stuff out. Put the garbage out there, just make sure people know where the garbage is coming from so they can make decisions about it. >> So I got a thought on that because, Kevin Mandia touched on it. Again, I want to ask about this. He said, so this whole idea of these, you know detecting the bots and monitoring the networks. Then he said, you can I think he said something that's to the effect of. "You can go on the offensive." And I'm thinking, okay, what does that mean? So for instance, you see it all the time. Anytime I see some kind of fact put out there, I got to start reading the comments and like cause I like to see both sides, you know. I'm right down the middle. And you'll go down and like 40 comments down, you're like, oh this is, this is fake. This video was edited, >> Right. >> Da, da, da, da, and then a bunch of other people. But then the bots take over and that gets buried. So, maybe going on the offensive is to your point. Go ahead and put it out there. But then the bots, the positive bots say, okay, by the way, this is fake news. This is an edited video FYI. And this is who put it out and here's the bot graph or something like that. And then you attack the bots with more bots and then now everybody can sort of of see it, you know? And it's not like you don't have to, you know email your friend and saying, "Hey dude, this is fake news." >> Right, right. >> You know, Do some research. >> Yeah. >> Put the research out there in volume is what you're saying. >> Yeah. So, it's an, it's just I thought it was an interesting segue into another area of security under the heading of election security. That is fraught with a lot of danger if done wrong, if done incorrectly, you know, you you get into the realm of opinion making. And we should be free to see information, but we also should have access to information about where the information is coming from. >> The other narrative that you hear. So, everything's down today again and I haven't checked lately, but security generally, we wrote about this in our Breaking Analysis. Security, somewhat, has held up in the stock market better than the broad tech market. Why? And the premise is, George Kurt said this on the last conference call, earnings call, that "security is non-discretionary." At the same time he did say that sales cycles are getting a little longer, but we see this as a positive for CrowdStrike. Because CrowdStrike, their mission, or one of their missions is to consolidate all these point tools. We've talked many, many times in the Cube, and in Breaking Analysis and on Silicon Angle, and on Wikibon, how the the security business use too many point tools. You know this as a former CTO. And, now you've got all these stove pipes, the number one challenge the CSOs face is lack of talent. CrowdStrike's premise is they can consolidate that with the Fal.Con platform, and have a single point of control. "Single pane of glass" to use that bromide. So, the question is, is security really non-discretionary? My answer to that is yes and no. It is to a sense, because security is the number one priority. You can't be lax on security. But at the same time the CSO doesn't have an open checkbook, >> Right. >> He or she can't just say, okay, I need this. I need that. I need this. There's other competing initiatives that have to be taken in balance. And so, we've seen in the ETR spending data, you know. By the way, everything's up relative to where it was, pre you know, right at the pandemic, right when, pandemic year everything was flat to down. Everything's up, really up last year, I don't know 8 to 10%. It was expected to be up 8% this year, let's call it 6 to 7% in 21. We were calling for 7 to 8% this year. It's back down to like, you know, 4 or 5% now. It's still healthy, but it's softer. People are being more circumspect. People aren't sure about what the fed's going to do next. Interest rates, you know, loom large. A lot of uncertainty out here. So, in that sense, I would say security is not non-discretionary. Sorry for the double negative. What's your take? >> I think it's less discretionary. >> Okay. >> Food, water, air. Non-discretionary. (David laughing) And then you move away in sort of gradations from that point. I would say that yeah, it is, it falls into the category of less-discretionary. >> Alright. >> Which is a good place to be. >> Dave Nicholson and David Vallante here. Two days of wall to wall coverage of Fal.Con 2022, CrowdStrike's big user conference. We got some great guests. Keep it right there, we'll be right back, right after this short break. (upbeat music)
SUMMARY :
that the unstoppable breach is a myth. I didn't hear the phrase. platform to get to 5 billion. And you know what, Dave? in the cyber defense industry, of the people who were on stage today. And he mentioned that the That is kind of the linchpin that the best way to deliver And then the other is, as you get into XDR Man in the street, It's about the S, it's about SDKs and APIs One of the things I said, And so, and the same thing with the SIM. into that realm in the future. of light, by the way, Yeah, as the biggest issue, disinformation. Because a lot of times, you know, into the network. And you can take that into consideration. cause I like to see both sides, you know. And then you attack the You know, Put the research out there in volume I thought it was an interesting And the premise is, George Kurt said this the fed's going to do next. And then you move away Two days of wall to wall coverage
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Day 1 Keynote Analysis and Wrap Up | VMware Explore 2022
>>Hi there. Welcome back to the cubes day. One coverage of VMware Explorer, 2022 from San Francisco, Lisa Martin and Dave Nicholson. Dave, we've been here all day, having some great conversations with the VMware partner ecosystem >>With real live people >>Within in 3d. Yeah. People actually sitting down next to us still >>Appreciated, even though, you know, we've, we've done a few of these events, but yeah, it feels like things are getting back to normal. >>It does. You and I were both in the keynote starting this morning, standing room only. We're hearing somewhere between 7,000 and 10,000 attendees. Yeah. We're in Moscoe west. So we're kind of away from a little bit of the, the main action. But talk to me about some of the things that you heard this morning in the keynote, some of the announcements from VMware, did it meet your expectations? >>Yes. And because I didn't expect, you know, this is very, very different than going to say an AWS event where they're going to launch 300 new shiny objects. This was very much in my mind so far about VMware focusing on its core value proposition and an aspect of its core value proposition that is the cloud stack and how they are shoring up places in that strategy that needed shoring up like addressing issues with licensing. So you don't have to have separate licensing for on premises, VMware things. You're doing separate licenses in hyperscale cloud providers for doing those very same things that looks like something that's going to roll out over time. That's very, very interesting. Something that wasn't really wasn't mentioned directly, but, but, but actually one of our guests mentioned it. It's this idea that if you take the VMware cloud provider partner, community VCP P is the inside term for it. >>There are thousands of VMware partners that deliver VMware cloud software on top of infrastructure, all around the globe. If you take that VCP P community as an entity, you can argue that it is the third or fourth largest cloud on earth. If you look at that as a core value proposition and you look at Broadcom, acquiring VMware, assuming everything goes through it, isn't just vSphere. That is exciting to Broadcom, or it shouldn't be at least because you have the entire cloud stack when you look at it from that perspective. And I think they were trying to get some of that across today. >>So they address the Broadcom acquisition obviously is the elephant in the room. It was right. Impossible. >>Well, well, they have OC 10 stand up in wave. OC >>Tanon stood up. Did, did a wave, just >>Crowd because he can't say anything. And you know, I've got European approval still pending, right. You know, all sorts of stuff. But >>What we are, what we heard today from, I'll say the partner ecosystem, we talked with NetApp, we talked with pure storage. We talked with Phoenix, snap, others. I I'd have to look through my notes. Everyone's actually quite positive. Yeah. On the acquisition and what it can mean for the future of VMware. Did you hear the same? >>Yes, absolutely. And I think partially that's because the partners that we talk to are really close to the core of VMware's value proposition. That's never going to go away. So if you're talking about NetApp and AWS partnering with VMware to deliver NetApp storage services into that environment, that's core VMware proposition, it's nowhere near the bleeding edge of what, of, what, of what VMware has been doing. So they're going to be bullish. The other thing that's interesting from some of the partners that we've talked to, if you had asked us five or 10 years ago, would those partners be successful today? We might have predicted that they'd all be gone, right? NetApp what's gonna happen. Well, all storage is going to cloud. Guess what NetApp's doing? Pretty darn well with its partner, with its cloud partnerships and card and, and cloud strategy, VMware old school virtualization on premises. Ah, what are they gonna do? I'll tell you. I was skeptical when pat Gelsinger first pursued the VMC strategy with AWS. Hey, it's worked out pretty well and now they have the same capabilities everywhere. So I think that it's, it's interesting to see how solidly positioned some traditional good old fashioned blue gene technologies are how well positioned they are in this era of cloud and how VMware is such a, such a core part of that. So of course they're happy. Yeah. >>Yeah. We talked, we had AWS, NetApp and VMware on, on set for a segment and talked about, and you and I were talking about that segment before it went live. Just the power of look what AWS is doing, how you know, how, how many years ago, 10 years ago would they have been, I'm not gonna partner with NetApp and VMware and now look, it's a core to their business unit. >>Yeah, no, they wouldn't have acknowledged it. They, in fact, there was a time when AWS thought that they could maintain their stratospheric rise at the level they needed to while just letting all legacy existing stuff, just sort of fade away, you know, they'll just do it on the backs of everything new. They ran headlong into something. We call stickiness specifically around the area. VMware, they found that application environments for a variety of really good reasons belong in this context. And it's hard to rip them out by the roots. It's, you know, AWS might have told you five or 10 years ago. Well, if people don't move to cloud immediately, it's because of one reason they're stupid. The reality is there are a lot of really good reasons to maintain that VMware context. They embrace that with VMC. And now I think the it's really interesting. The NetApp announcement is another indication that the world of hyperscale cloud sees VMware as something that is part of the future. That is a very, very long tail. That very, very long tail is clearly what Broadcom is interested in. They don't see this as a flash in the pan. Let's make revenue really quickly. This is about a long ti a long time of future long future >>Long future. Well, VMware's coming off solid quarter earnings that just announced speeding estimates growing the top line by up to 6%. So there's, there's momentum that they're bringing with them into this acquisition. >>Yeah, definitely momentum big argument over what the strategy might be moving forward in terms of growth versus efficiency. I think that virtualization that includes the traditional VM with a resident full blown OS is definitely something that is behind us, but that we're carrying forward for good reason. The transition in, from a VMware perspective into the world of Zu critically important, it's critically important that they get that right as they move forward. So that net new cloud native applications could be, can be created in the VMware context that way. So it's, it's really gonna be interesting to watch over the next couple of years, the direction that this goes, but, but it's easy to get immersed in the Kool-Aid when you're at an event like this, I try to be as skeptical as possible. And I'm actually feeling pretty, I'm feeling better about VMware's future than I did before I arrived today. So that's >>Interesting. Yeah. >>Yeah, no question about it. I think, I mean, there, there, there is such a large core that I think it's gonna take it into the future a long way. >>Well, they definitely have a lot of tailwind behind them. The, the one thing that I, that we didn't get to do today was talk to any customers. We will get to do that tomorrow. When I always love hearing from the voice of the customer, we heard voice of the customer stories from the vendors, from VMware, from NetApp, from >>Little skewed, eat a little skewed. Exactly. They're all happy. All the customers are happy >>They're and very >>Successful and very successful. >>But tomorrow we get to actually rack open and talk with some VMware customers, obviously, right. Customers in the ecosystem as well. And I want to hear from them what their thoughts are on the acquisition. Yeah. >>We know they're, they're not bringing their disgruntled customers. Right. You know, this is my, this is my ex-wife's my, my ex-mother-in-law. And she's here to tell you that she didn't have a good experience. Yeah, no, that's not >>Gonna happen. We're gonna hear good stories tomorrow, but it's always nice to, to hear the stories from the customers themselves. Yeah. I always like doing that. >>No, it's always, it is informative. It's all, it's interesting from the perspective that you, you hone in on what they care about, because even if they have sort of an idea of, of, of the message that they want to get across in terms of what they're doing, still build default to that core of what they really care about. And that's interesting because what the customers really care about is part of that core. And as VMware becomes part of Broadcom, potentially, it's gonna be all about those things that are important, that you know, that customers find important. >>And that's exactly what it should be about. You know, of course we, every conversation that we had today, probably every conversation was inclusive of customer outcomes. What outcomes are you helping businesses achieve regardless of industry, especially as we're hopefully coming out of the pandemic, still in a, in a dynamic, remote hybrid work environment, but it's all about enabling businesses to, to achieve their goals. So I always wanna understand from, from VMware's perspective or AWS or NetApp procure, what are the goals that your customers are coming to you with and who are you having those conversations with? We also heard today a number of probably almost everyone that during the pandemic, the conversations are going up the stack. And maybe they've been talking with the director of it. Now it's the VP of engineering. Maybe it's the CFO. Yep. We're seeing much more strategic initiatives and focus here as customers in every industry have to pivot and have gotta get to the cloud. >>Yeah. I think that's why we work together. Well, Lisa, because you have the virtual leash and you can yank me back from diving into the technical stuff because, because I just, I, I get a pit in my stomach when someone says, oh, technology doesn't matter. It's all about outcomes. Yeah, yeah, yeah. Okay. Try doing this on technology that doesn't work. Your outcomes are gonna suck both Arely but no, no, no, they are. I know. And, and, and, and it's important that we focus on those things cuz that's what customers really care about. They do, they really care about the business outcomes >>They do. And, and on the cube, we care about those as well. And we wanna get that message across. >>I wish they would care more about speeds and feeds though. It's super interesting. It's like horsepower and torque and it's all >>He does. He gets really excited about that. But the good thing is tomorrow we have more opportunities. Yes. Got a great guest line up tomorrow. Dave and I are gonna be talking to them from right here on this set. So we encourage you to come check in for day two of our coverage of VMware Explorer live from San Francisco. We hope you have a great rest of your day and we'll see you tomorrow.
SUMMARY :
Welcome back to the cubes day. Within in 3d. Appreciated, even though, you know, we've, we've done a few of these events, but yeah, But talk to me about some of the things that you heard this morning in that is the cloud stack and how they are at least because you have the entire cloud stack when you look at it from that perspective. So they address the Broadcom acquisition obviously is the elephant in the room. Well, well, they have OC 10 stand up in wave. And you know, I've got European approval still pending, On the acquisition and what it can mean for the future of VMware. So I think that it's, it's interesting to see how solidly Just the power of look what AWS is doing, how you know, And it's hard to rip them out by the roots. estimates growing the top line by up to 6%. it's critically important that they get that right as they move forward. Yeah. that I think it's gonna take it into the future a long way. the voice of the customer, we heard voice of the customer stories from the vendors, from VMware, All the customers are happy And I want to hear from them what their thoughts are on the And she's here to tell you that she didn't have a good experience. I always like doing that. of, of the message that they want to get across in terms of what they're doing, still build default to that Now it's the VP of engineering. and, and, and it's important that we focus on those things cuz that's what customers really And, and on the cube, we care about those as well. I wish they would care more about speeds and feeds though. So we encourage you to come check in for day two of our coverage of VMware
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Lie 1, The Most Effective Data Architecture Is Centralized | Starburst
(bright upbeat music) >> In 2011, early Facebook employee and Cloudera co-founder Jeff Hammerbacher famously said, "The best minds of my generation are thinking about how to get people to click on ads, and that sucks!" Let's face it. More than a decade later, organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile and data-driven enterprise. What does that even mean, you ask? Well, it means that everyone in the organization has the data they need when they need it in a context that's relevant to advance the mission of an organization. Now, that could mean cutting costs, could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data warehouses, data marts, data hubs, and yes even data lakes were broken and left us wanting for more. Welcome to The Data Doesn't Lie... Or Does It? A series of conversations produced by theCUBE and made possible by Starburst Data. I'm your host, Dave Vellante, and joining me today are three industry experts. Justin Borgman is the co-founder and CEO of Starburst, Richard Jarvis is the CTO at EMIS Health, and Teresa Tung is cloud first technologist at Accenture. Today, we're going to have a candid discussion that will expose the unfulfilled, and yes, broken promises of a data past. We'll expose data lies: big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth inevitable? Will the data warehouse ever have feature parity with the data lake or vice versa? Is the so-called modern data stack simply centralization in the cloud, AKA the old guards model in new cloud close? How can organizations rethink their data architectures and regimes to realize the true promises of data? Can and will an open ecosystem deliver on these promises in our lifetimes? We're spanning much of the Western world today. Richard is in the UK, Teresa is on the West Coast, and Justin is in Massachusetts with me. I'm in theCUBE studios, about 30 miles outside of Boston. Folks, welcome to the program. Thanks for coming on. >> Thanks for having us. >> Okay, let's get right into it. You're very welcome. Now, here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >> Yeah, definitely a lie. My first startup was a company called Hadapt, which was an early SQL engine for IDU that was acquired by Teradata. And when I got to Teradata, of course, Teradata is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on prem, data in the cloud. Those companies were acquiring other companies and inheriting their data architecture. So despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >> So Richard, from a practitioner's point of view, what are your thoughts? I mean, there's a lot of pressure to cut cost, keep things centralized, serve the business as best as possible from that standpoint. What does your experience show? >> Yeah, I mean, I think I would echo Justin's experience really that we as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in a platform that's close to data experts people who really understand healthcare data from pharmacies or from doctors. And so, although if you were starting from a greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that businesses just don't grow up like that. And it's just really impossible to get that academic perfection of storing everything in one place. >> Teresa, I feel like Sarbanes-Oxley have kind of saved the data warehouse, right? (laughs) You actually did have to have a single version of the truth for certain financial data, but really for some of those other use cases I mentioned, I do feel like the industry has kind of let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralize? >> I think you got to have centralized governance, right? So from the central team, for things like Sarbanes-Oxley, for things like security, for certain very core data sets having a centralized set of roles, responsibilities to really QA, right? To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise, you're not going to be able to scale, right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately, you're going to collaborate with your partners. So partners that are not within the company, right? External partners. We're going to see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >> So Justin, you guys last, jeez, I think it was about a year ago, had a session on data mesh. It was a great program. You invited Zhamak Dehghani. Of course, she's the creator of the data mesh. One of our fundamental premises is that you've got this hyper specialized team that you've got to go through if you want anything. But at the same time, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess, a question for you Richard. How do you deal with that? Do you organize so that there are a few sort of rock stars that build cubes and the like or have you had any success in sort of decentralizing with your constituencies that data model? >> Yeah. So we absolutely have got rockstar data scientists and data guardians, if you like. People who understand what it means to use this data, particularly the data that we use at EMIS is very private, it's healthcare information. And some of the rules and regulations around using the data are very complex and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a consulting type experience from a set of rock stars to help a more decentralized business who needs to understand the data and to generate some valuable output. >> Justin, what do you say to a customer or prospect that says, "Look, Justin. I got a centralized team and that's the most cost effective way to serve the business. Otherwise, I got duplication." What do you say to that? >> Well, I would argue it's probably not the most cost effective, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you for many, many years to come. I think that's the story at Oracle or Teradata or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams, as much as they are experts in the technology, they don't necessarily understand the data itself. And this is one of the core tenets of data mesh that Zhamak writes about is this idea of the domain owners actually know the data the best. And so by not only acknowledging that data is generally decentralized, and to your earlier point about Sarbanes-Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for those laws to be compliant. But I think the reality is the data mesh model basically says data's decentralized and we're going to turn that into an asset rather than a liability. And we're going to turn that into an asset by empowering the people that know the data the best to participate in the process of curating and creating data products for consumption. So I think when you think about it that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two models comparing and contrasting. >> So do you think the demise of the data warehouse is inevitable? Teresa, you work with a lot of clients. They're not just going to rip and replace their existing infrastructure. Maybe they're going to build on top of it, but what does that mean? Does that mean the EDW just becomes less and less valuable over time or it's maybe just isolated to specific use cases? What's your take on that? >> Listen, I still would love all my data within a data warehouse. I would love it mastered, would love it owned by a central team, right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date, I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's going to be a new technology that's going to emerge that we're going to want to tap into. There's going to be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this new mesh layer that still takes advantage of the things I mentioned: the data products in the systems that are meaningful today, and the data products that actually might span a number of systems. Maybe either those that either source systems with the domains that know it best, or the consumer-based systems or products that need to be packaged in a way that'd be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to use all of them. >> So, Richard, let me ask you. Take Zhamak's principles back to those. You got the domain ownership and data as product. Okay, great. Sounds good. But it creates what I would argue are two challenges: self-serve infrastructure, let's park that for a second, and then in your industry, one of the most regulated, most sensitive, computational governance. How do you automate and ensure federated governance in that mesh model that Teresa was just talking about? >> Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to centralize the security and the governance of the data. And I think although a data warehouse makes that very simple 'cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at EMIS is we have a single security layer that sits on top of our data mesh, which means that no matter which user is accessing which data source, we go through a well audited, well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is audited in a very kind of standard way regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible, understanding where your source of truth is and securing that in a common way is still a valuable approach, and you can do it without having to bring all that data into a single bucket so that it's all in one place. And so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform, and ensuring that only data that's available under GDPR and other regulations is being used by the data users. >> Yeah. So Justin, we always talk about data democratization, and up until recently, they really haven't been line of sight as to how to get there, but do you have anything to add to this because you're essentially doing analytic queries with data that's all dispersed all over. How are you seeing your customers handle this challenge? >> Yeah, I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, the people who know the data the best, to create data as a product ultimately to be consumed. And we try to represent that in our product as effectively, almost eCommerce like experience where you go and discover and look for the data products that have been created in your organization, and then you can start to consume them as you'd like. And so really trying to build on that notion of data democratization and self-service, and making it very easy to discover and start to use with whatever BI tool you may like or even just running SQL queries yourself. >> Okay guys, grab a sip of water. After the short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence. Keep it right there. (bright upbeat music)
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Day 1 Keynote Analysis | Snowflake Summit 2022
>>Good morning live from Las Vegas, Lisa Martin and Dave Lanta here covering snowflake summit 22. Dave, it's great to be here in person. The keynote we just came from was standing room only. In fact, there was overflow. People are excited to be back and to hear from the company in person the first time, since the IPO, >>Lots of stuff, lots of deep technical dives, uh, you know, they took the high end of the pyramid and then dove down deep in the keynotes. It >>Was good. They did. And we've got Doug Hench with us to break this down in the next eight to 10 minutes, VP and principle analyst at constellation research. Doug, welcome to the cube. >>Great to be here. >>All right, so guys, I was telling Dave, as we were walking back from the keynote, this was probably the most technical keynote I've seen in a very long time. Obviously in person let's break down some of the key announcements. What were some of the things Dave that stood out to you and what they announced just in the last hour and a half alone? >>Well, I, you know, we had a leave before they did it, but the unit store piece was really interesting to me cuz you know, the big criticism is, oh, say snowflake, that doesn't do transaction data. It's just a data warehouse. And now they're sort of reaching out. We're seeing the evolution of the ecosystem. Uh, sluman said it was by design. It was one of the questions I had for them. Is this just kind of happen or is it by design? So that's one of many things that, that we can unpack. I mean the security workload, uh, the, the Apache tables, we were just talking about thatt, which not a lot of hands went up when they said, who uses Apache tables, but, but a lot of the things they're doing seem to me anyway, to be trying to counteract the narrative, that snow, I mean that data bricks is put out there about you guys. Aren't open, you're a walled garden and now they're saying, Hey, we're we're as open as anybody, but what are your thoughts, Doug? >>Well, that's the, the iceberg announcement, uh, also, uh, the announcement of, of uni store being able to reach out to, to any source. Uh, you know, I think the big theme here was this, this contrast you constantly see with snowflake between their effort to democratize and simplify and disrupt the market by bringing in a great big tent. And you saw that great big tent here today, 7,000 people, 2,007,000 plus I'm told 2000 just three years ago. So this company is growing hugely quickly, >>Unprecedented everybody. >>Yeah. Uh, fastest company to a billion in revenue is Frank Salman said in his keynote today. Um, you know, and I think that there's, there's that great big tent. And then there's the innovations they're delivering. And a lot of their announcements are way ahead of the J general availability. A lot of the things they talked about today, Python support and some, some other aspects they're just getting into public preview. And many of the things that they're announcing today are in private preview. So it could be six, 12 months be before they're generally available. So they're here educating a lot of these customers. What is iceberg? You know, they're letting them know about, Hey, we're not just the data warehouse. We're not just letting you migrate your old workloads into the cloud. We're helping you innovate with things like the data marketplace. I see the data marketplace is really crucial to a lot of the announcements they're making today. Particularly the native apps, >>You know, what was interesting sluman in his keynote said we don't use the term data mesh, cuz that means has meaning to the people, lady from Geico stood up and said, we're building a data mesh. And when you think about, you know, the, those Gemma Dani's definition of data mesh, Snowflake's actually ticking a lot of boxes. I mean, it's it's is it a decentralized architecture? You could argue that it's sort of their own wall garden, but things like data as product we heard about building data products, uh, uh, self-serve infrastructure, uh, computational governance, automated governance. So those are all principles of Gemma's data mesh. So I there's close as anybody that, that I've seen with the exception of it's all in the data cloud. >>Why do you think he was very particular in saying we're not gonna call it a data mesh? I, >>I think he's respecting the principles that have been put forth by the data mesh community generally and specifically Jamma Dani. Uh, and they don't want to, you know, they don't want to data mesh wash. I mean, I, I, I think that's a good call. >>Yeah, that's it's a little bit out there and, and it, they didn't talk about data mesh so much as Geico, uh, the keynote or mentioned their building one. So again, they have this mix of the great big tent of customers and then very forward looking very sophisticated customers. And that's who they're speaking to with some of these announcements, like the native apps and the uni store to bring transactional data, bring more data in and innovate, create new apps. And the key to the apps is that they're made available through the marketplace. Things like data sharing. That's pretty simple. A lot of, uh, of their competitors are talking about, Hey, we can data share, but they don't have the things that make it easy, like the way to distribute the data, the way to monetize the data. So now they're looking forward monetizing apps, they changed the name from the data marketplace to the, to the snowflake marketplace. So it'll be apps. It will be data. It'll be all sorts of innovative products. >>We talk about Geico, uh, JPMC is speaking at this conference, uh, and the lead technical person of their data mesh initiative. So it's like, they're some of their customers that they're putting forth. So it's kind of interesting. And then Doug, something else that you and I have talked about on the, some of the panels that we've done is you've got an application development stack, you got the database over there and then you have the data analytics stack and we've, I've said, well, those things come together. Then people have said, yeah, they have to. And this is what snowflake seems to be driving towards. >>Well with uni store, they're reaching out and trying to bring transactional data in, right? Hey, don't limit this to analytical information. And there's other ways to do that, like CDC and streaming, but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So a, another reach to a broader play across a big community that they're >>Building different than what we saw last week at Mongo, different than what you know, Oracle does with, with heat wave. A lot of ways to skin a cat. >>That was gonna be my next question to both of you is talk to me about all the announcements that we saw. And, and like we said, we didn't actually get to see the entire keynote had come back here. Where are they from a differentiation perspective in terms of the competitive market? You mentioned Doug, a lot of the announcements in either private preview or soon to be public preview early. Talk to me about your thoughts where they are from a competitive standpoint. >>Again, it's that dichotomy between their very forward looking announcements. They're just coming on with things like Python support. That's just becoming generally available. They're just introducing, uh, uh, machine learning algorithms, like time series built into the database. So in some ways they're catching up while painting this vision of future capabilities and talking about things that are in development or in private preview that won't be here for a year or two, but they're so they're out there, uh, talking about a BLE bleeding edge story yet the reality is the product sometimes are lagging behind. Yeah, >>It's interesting. I mean, they' a lot of companies choose not to announce anything until it's ready to ship. Yeah. Typically that's a technique used by the big whales to try to freeze the market, but I think it's different here. And the strategy is to educate customers on what's possible because snowflake really does have, you know, they're trying to differentiate from, Hey, we're not just a data warehouse. We have a highly differentiatable strategy from whether it's Oracle or certainly, you know, Mongo is more transactional, but, but you know, whether it's couch base or Redis or all the other databases out there, they're saying we're not a database, we're a data cloud. <laugh> right. Right. Okay. What is that? Well, look at all the things that you can do with the data cloud, but to me, the most interesting is you can actually build data products and you can monetize that. And their, the emphasis on ecosystem, you, they look at Salman's previous company would ServiceNow took a long time for them to build an ecosystem. It was a lot of SI in smaller SI and they finally kind of took off, but this is exceeding my expectations and ecosystem is critical because they can't do it all. You know, they're gonna O otherwise they're gonna spread themselves to >>That. That's what I think some competitors just don't get about snowflake. They don't get that. It's all about the community, about their network that they're building and the relationships between these customers. And that they're facilitating that with distribution, with monetization, things that are hard. So you can't just add sharing, or you can share data from one of their, uh, legacy competitors, uh, in, in somebody else's marketplace that doesn't facilitate the transaction that doesn't, you know, build on the community. Well, >>And you know, one of the criticisms too, of the criticism on snowflake goes, they don't, you know, they can't do complex joins. They don't do workload management. And I think their answer to that is, well, we're gonna look to the ecosystem to do that. Or you, you saw some kind of, um, cost governance today in the, in the keynote, we're gonna help you optimize your spend, um, a little different than workload management, but related >>Part of their governance was having a, a, a node, uh, for every workload. So workload isolation in that way, but that led to the cost problems, you know, like too many nodes with not enough optimization. So here too, you saw a lot of, uh, announcements around cost controls, budgets, new features, uh, user groups that you could bring, uh, caps and guardrails around those costs. >>In the last couple minutes, guys talk about their momentum. Franks Lutman showed a slide today that showed over 5,900 customers. I was looking at some stats, uh, in the last couple of days that showed that there is an over 1200% increase in the number of customers with a million plus ARR. Talk about their momentum, what you expect to see here. A lot of people here, people are ready to hear what they're doing in person. >>Well, I think this, the stats say it all, uh, fastest company to a, to a billion in revenue. Uh, you see the land and expand experience that many companies have and in the cost control, uh, announcements they were making, they showed the typical curve like, and he talked about it being a roller coaster, and we wanna help you level that out. Uh, so that's, uh, a matter of maturation. Uh, that's one of the downsides of this rapid growth. You know, you have customers adding new users, adding new clusters, multi clusters, and the costs get outta control. They want to help customers even that out, uh, with reporting with these budget and cost control measures. So, uh, one of the growing pains that comes with, uh, adding so many customers so quickly, and those customers adding so many users and new, uh, workloads quickly, >>I know we gotta break, but last point I'll make about the key. Uh, keynote is SL alluded to the fact that they're not taking the foot off the gas. They don't see any reason to, despite the narrative in the press, they have inherent profitability. If they want to be more profitable, they could be, but they're going for growth >>Going for growth. There is so much to unpack in the next three days. You won't wanna miss it. The Cube's wall to oil coverage, Lisa Martin for Dave Valenti, Doug hen joined us in our keynote analysis. Thanks so much for walking, watching stick around. Our first guest is up in just a few minutes.
SUMMARY :
22. Dave, it's great to be here in person. Lots of stuff, lots of deep technical dives, uh, you know, they took the high end of the pyramid and then dove down deep And we've got Doug Hench with us to break this down in the next eight to 10 minutes, stood out to you and what they announced just in the last hour and a half alone? but, but a lot of the things they're doing seem to me anyway, to be trying to counteract the narrative, Uh, you know, I think the big theme here was this, And many of the things that they're announcing today are in private preview. And when you think about, you know, the, those Gemma Dani's definition of data mesh, Uh, and they don't want to, you know, And the key to the apps is that they're made available through the marketplace. And then Doug, something else that you and I have talked about on the, some of the panels that we've done is you've So a, another reach to a broader play across a big community that Building different than what we saw last week at Mongo, different than what you know, Oracle does with, That was gonna be my next question to both of you is talk to me about all the announcements that we saw. into the database. Well, look at all the things that you can do with the data cloud, but to me, the most interesting is you So you can't just add sharing, or you can share data from one of their, And you know, one of the criticisms too, of the criticism on snowflake goes, they don't, you know, they can't do complex joins. new features, uh, user groups that you could bring, uh, A lot of people here, people are ready to hear what they're doing they showed the typical curve like, and he talked about it being a roller coaster, and we wanna help you level that Uh, keynote is SL alluded to the fact that they're There is so much to unpack in the next three days.
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Day 1 Wrap | Kubecon + Cloudnativecon Europe 2022
>> Narrator: theCUBE presents KubeCon and Cloud NativeCon Europe, 2022 brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain. A coverage of KubeCon, Cloud NativeCon, Europe, 2022. I'm Keith Townsend. Your host of theCUBE, along with Paul Gillum, Senior Editor Enterprise Architecture for Silicon Angle, Enrico, Senior IT Analyst for GigaOm . This has been a full day, 7,500 attendees. I might have seen them run out of food, this is just unexpected. I mean, it escalated from what I understand, it went from capping it off at 4,000 gold, 5,000 gold in it off finally at 7,500 people. I'm super excited for... Today's been a great dead coverage. I'm super excited for tomorrow's coverage from theCUBE, but first off, we'll let the the new person on stage take the first question of the wrap up of the day of coverage, Enrico, what's different about this year versus other KubeCons or Cloud Native conversations. >> I think in general, it's the maturity. So we talk a lot about day two operations, observability, monitoring, going deeper and deeper in the security aspects of the application. So this means that for many enterprises, Kubernetes is becoming real critical. They want to get more control of it. And of course you have the discussion around FinOps, around cost control, because we are deploying Kubernetes everywhere. And if you don't have everything optimized, control, monitored, costs go to the roof and think about deploying the Public Cloud . If your application is not optimized, you're paying more. But also in that, on-premises if you are not optimized, you don't have any clear idea what is going to happen. So capacity planning become the nightmare, that we know from the past. So there is a lot of going on around these topics, really exciting actually, less infrastructure, more application. That is what Kubernetes is in here. >> Paul help me separate some of the signal from the noise. There is a lot going on a lot of overlap. What are some of the big themes of takeaways for day one that Enterprise Architects, Executives, need to take home and really chew on? >> Well, the Kubernetes was a turning point. Docker was introduced nine years ago, and for the first three or four years it was an interesting technology that was not very widely adopted. Kubernetes came along and gave developers a reason to use containers. What strikes me about this conference is that this is a developer event, ordinarily you go to conferences and it's geared toward IT Managers, towards CIOs, this is very much geared toward developers. When you have the hearts and minds of developers the rest of the industry is sort of pulled along with it. So this is ground zero for the hottest area of the entire computing industry right now, is in this area building Distributed services, Microservices based, Cloud Native applications. And it's the developers who are leading the way. I think that's a significant shift. I don't see the Managers here, the CIOs here. These are the people who are pulling this industry into the next generation. >> One of the interesting things that I've seen when we've always said, Kubernetes is for the developers, but we talk with an icon from MoneyGram, who's a end user, he's an enterprise architect, and he brought Kubernetes to his front end developers, and they rejected it. They said, what is this? I just want to develop code. So when we say Kubernetes is for developers or the developers are here, how do we reconcile that mismatch of experience? We have Enterprise Architect here. I hear constantly that the Kubernetes is for developers, but is it a certain kind of developer that Kubernetes is for? >> Well, yes and no. I mean, so the paradigm is changing. Okay. So, and maybe a few years back, it was tough to understand how make your application different. So microservices, everything was new for everybody, but actually, everything has changed to a point and now the developer understands, is neural. So, going through the application, APIs, automation, because the complexity of this application is huge, and you have, 724 kind of development sort of deployment. So you have to stay always on, et cetera, et cetera. And actually, to the point of developers bringing this new generation of decision makers in there. So they are actually decision, they are adopting technology. Maybe it's a sort of shadow IT at the very beginning. So they're adopting it, they're using it. And they're starting to use a lot of open source stuff. And then somebody upper in the stack, the Executive, says what are... They discover that the technology is already in place is a critical component, and then it's transformed in something enterprise, meaning paying enterprise services on top of it to be sure support contract and so on. So it's a real journey. And these guys are the real decision makers, or they are at the base of the decision making process, at least >> Cloud Native is something we're going to learn to take for granted. When you remember back, remember the Fail Whale in the early days of Twitter, when periodically the service would just crash from traffic, or Amazon went through the same thing. Facebook went through the same thing. We don't see that anymore because we are now learning to take Cloud Native for granted. We assume applications are going to be available. They're going to be performant. They're going to scale. They're going to handle anything we throw at them. That is Cloud Native at work. And I think we forget sometimes how refreshing it is to have an internet that really works for you. >> Yeah, I think we're much earlier in the journey. We had Microsoft on, the Xbox team talked about 22,000 pods running Linkerd some of the initial problems and pain points around those challenges. Much of my hallway track conversation has been centered around as we talk about the decision makers, the platform teams. And this is what I'm getting excited to talk about in tomorrow's coverage. Who's on the ground doing this stuff. Is it developers as we see or hear or told? Or is it what we're seeing from the Microsoft example, the MoneyGram example, where central IT is getting it. And not only are they getting it, they're enabling developers to simply write code, build it, and Kubernetes is invisible. It seems like that's become the Holy Grail to make Kubernetes invisible and Cloud Native invisible, and the experience is much closer to Cloud. >> So I think that, it's an interesting, I mean, I had a lot of conversation in the past year is that it's not that the original traditional IT operations are disappearing. So it's just that traditional IT operation are giving resources to these new developers. Okay, so it's a sort of walled garden, you don't see the wall, but it's a walled garden. So they are giving you resources and you use these resources like an internal Cloud. So a few years back, we were talking about private Cloud, the private Cloud as let's say the same identical paradigm of the Public Cloud is not possible, because there are no infinite resources or well, whatever we think are infinite resources. So what you're doing today is giving these developers enough resources to think that they are unlimited and they can do automatic operationing and do all these kind of things. So they don't think about infrastructure at all, but actually it's there. So IT operation are still there providing resources to let developers be more free and agile and everything. So we are still in a, I think an interesting time for all of it. >> Kubernetes and Cloud Native in general, I think are blurring the lines, traditional lines development and operations always were separate entities. Obviously with DevOps, those two are emerging. But now we're moving when you add in shift left testing, shift right testing, DevSecOps, you see the developers become much more involved in the infrastructure and they want to be involved in infrastructure because that's what makes their applications perform. So this is going to cause, I think IT organizations to have to do some rethinking about what those traditional lines are, maybe break down those walls and have these teams work much closer together. And that should be a good thing because the people who are developing applications should also have intimate knowledge of the infrastructure they're going to run on. >> So Paul, another recurring theme that we've heard here is the impact of funding on resources. What have your discussions been around founders and creators when it comes to sourcing talent and the impact of the markets on just their day to day? >> Well, the sourcing talent has been a huge issue for the last year, of course, really, ever since the pandemic started. Interestingly, one of our guests earlier today said that with the meltdown in the tech stock market, actually talent has become more available, because people who were tied to their companies because of their stock options are now seeing those options are underwater and suddenly they're not as loyal to the companies they joined. So that's certainly for the startups, there are many small startups here, they're seeing a bit of a windfall now from the tech stock bust. Nevertheless, skills are a long term problem. The US educational system is turning out about 10% of the skilled people that the industry needs every year. And no one I know, sees an end to that issue anytime soon. >> So Enrico, last question to you. Let's talk about what that means to the practitioner. There's a lot of opportunity out there. 200 plus sponsors I hear, I think is worth the projects is 200 plus, where are the big opportunities as a practitioner, as I'm thinking about the next thing that I'm going to learn to help me survive the next 10 or 15 years of my career? Where you think the focus should be? Should it be that low level Cloud builder? Or should it be at those levels of extraction that we're seeing and reading about? >> I think that it's a good question. The answer is not that easy. I mean, being a developer today, for sure, grants you a salary at the end of the month. I mean, there is high demand, but actually there are a lot of other technical figures in the data center, in the Cloud, that could really find easily a job today. So, developers is the first in my mind also because they are more, they can serve multiple roles. It means you can be a developer, but actually you can be also with the new roles that we have, especially now with the DevOps, you can be somebody that supports operation because you know automation, you know a few other things. So you can be a sysadmin of the next generation even if you are a developer, even if when you start as a developer. >> KubeCon 2022, is exciting. I don't care if you're a developer, practitioner, a investor, IT decision maker, CIO, CXO, there's so much to learn and absorb here and we're going to be covering it for the next two days. Me and Paul will be shoulder to shoulder, I'm not going to say you're going to get sick of this because it's just, it's all great information, we'll help sort all of this. From Valencia, Spain. I'm Keith Townsend, along with my host Enrico Signoretti, Paul Gillum, and you're watching theCUBE, the leader in high tech coverage. (upbeat music)
SUMMARY :
the Cloud Native Computing Foundation of the wrap up of the day of coverage, of the application. of the signal from the noise. and for the first three or four years I hear constantly that the and now the developer understands, the early days of Twitter, and the experience is is that it's not that the of the infrastructure and the impact of the markets So that's certainly for the startups, So Enrico, last question to you. of the next generation it for the next two days.
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Day 1 Wrap Up | Kubecon + Cloudnativecon Europe 2022
>>The cube presents, Coon and cloud native con Europe 22, brought to you by the cloud native computing foundation. >>Welcome to Valencia Spain and coverage of Q con cloud native con Europe, 2022. I'm Keith Townsend. You're a host of the cube along with Paul Gillum, senior editor, enterprise architecture for Silicon angle, ENCO, senior ready, senior it analyst for giga own. Uh, this has been a full day, 7,500 attendees. I might have seen them run out of food. This is just unexpected. I mean, they, the, it escalated from what understand it went from four, capping it off to 4,000 gold, 5,000 gold in and off. Finally at 7,500 people. I'm super excited for, you know, today's been a great day of coverage. I'm super excited for tomorrow's coverage, uh, from the cube. But first off, we'll let the, the new person on stage take the, the first question of, of the wrap up of the day of coverage, UN Rico on Rico. What's different about this year versus other Q coupons or cloud native conversations. >>I, I think in general, it's the maturity. So we talk it a lot about day two operations, uh, observability monitoring, uh, going deeper and deeper in the security aspects of the application. So this means that for many enterprises, Kubernetes is becoming real critical. They want to, to get more control of it. And of course you have the discussion around Phen op around, you know, uh, cost control because we are deploying Kubernetes everywhere. And, and if you don't have everything optimized control, monitor it, you know, uh, cost to the roof and think about, uh, deploying the public cloud. If your application is not optimized, you're paying more, but also in the on premises, if you are not optimiz, you don't have the clear idea of what is going to happen. So capacity planning become the nightmare that we know from the past. So there is a lot of going on around these topics, uh, really exciting, actually less infrastructure, more replication. That is what Kubernetes is India. >>Paul help me separate some of the signal from the noise. Uh, there is a lot going on a lot of overlap. What are some of the big themes of takeaways for day one that enterprise architects executives need to take home and really chew >>On? Well, the Kubernetes was a turning point. You know, Docker was introduced nine years ago and for the first three or four years, it was an interesting technology that was not very widely adopted. Kubernetes came along and gave developers a reason to use containers. What strikes me about this conference is that this is a developer event, you know, ordinarily you go to conferences and it's geared toward it managers towards CIOs. This is very much geared toward developers when you have the hearts and minds of developers, the rest of the industry is sort of pulled along with it. So this is ground zero for the hottest, uh, the, the hottest area of the entire computing industry. Right now, I is in this area building distributed services, BA microservices based cloud native applications. And it's the developers who are leading the way. I think that's, that's a significant shift. I don't see the managers here, the CIOs here, these are the people who are, uh, who are pulling this industry into the next generation. >>Um, one of the interesting things that I've seen when we, you know, we've always said, Kubernetes is for the developers, but we talk with, uh, an icon from, uh, MoneyGram. Who's a end user, he's an enterprise architect. And he brought Kubernetes to his front end developers and they, they, they kind of rejected it. They said, what is this? I just wanna develop cold. So when we say Kubernetes is for developers, or the developers are here, where, how do we reconcile that mismatch of experience? We have enterprise architecture. I hear constantly that, that the, uh, Kubernetes is for developers, but is it a certain kind of developer that Kubernetes is for? >>Well, yes and no. I mean, so the paradigm is changing. Okay. So, and maybe a few years back, it was tough to understand how, you know, uh, uh, make your application different. So microservices, everything was new for everybody, but actually, so everything is changed to a point. Now, the developer understands, you know, it is neural. So, you know, going through the application APIs automation, because the complexity of this application is, is huge. And you have, you know, 7 24 kind of development, uh, sort of deployment. So you have to stay always on cetera, et cetera. And actually to the point of, you know, developers, uh, you know, bringing this new generation of, uh, decision makers in India. So they are actually decision, they are adopting technology. Maybe it's a sort of shadow it at the very beginning. So they're adopting it, they're using it. And they're starting to use a lot of open source stuff. And then somebody upper in the stack, the executive says, what are, yeah, they, they discover that the technology is already in place is, uh, is a critical component. And then it's, uh, you know, uh, transformed in something enterprise, meaning, you know, paying enterprise services on top of it to be sure con uh, contract and so on. So it's a real journey. And these are, these guys are the real decision makers. Oh, they are at the base of the decision making process. At least >>Cloud native is something we're gonna learn to take for granted. You know, when you remember back, remember the fail whale in the early days of Twitter, when periodically the service would just would just, uh, um, crash from, uh, from, uh, traffic or Amazon went through the same thing. Facebook went through the same thing. We don't see that anymore because we are now learning to take cloud native for granted. We assume applications are gonna be available. They're gonna be performant. They're gonna scale. They're gonna handle anything. We throw at them that is cloud native at work. And I think we, we forget sometimes how refreshing it is to have, uh, an internet that really works for you. >>Yeah. I, I think we're much earlier in the journey. You know, we have Microsoft, uh, on the Xbox team talked about 22,000 pods running ni D some of the initial problems and pain points of, uh, around those challenges. Uh, much of my hallway track conversation has been centered around as we talk about kind of the decision makers, the platform teams. And this is what I'm getting excited to talk about in tomorrow's coverage. Who's on the ground doing this stuff. Is it developers as we are, as, as we see or hear or told, or is it what we're seeing from the Microsoft example, the MoneyGram example where central it is kind of getting it, and not only are they getting it, they're enabling developers to, to simply write code, build it. And Kubernetes is invisible. It seems like that's become the holy grill to make Kubernetes invisible cloud native invisible, and the experience is much closer to cloud. >>So I, I think that, uh, um, it's an interesting, I mean, I had a lot of conversation in the past year is that it's not that the original, you know, traditional it operations are disappearing. So it's just that, uh, traditional it operation are giving resources to these new developers. Okay. So it's a, it's a sort of walled garden. You don't see the wall, but it's a walled garden. So they are giving you resources and you use these resources like an internal cloud. So a few years back, we were talking about private cloud, the private cloud, as, you know, as a, let's say, uh, the same identical paradigm of, of the public cloud. This is not possible because there are no infinite resources or, well, whatever we, we think are infinite resources. So what you're doing today is giving these developers enough resources to think that they are unlimited and they can, uh, do automatic provisioning and do all these kind of things. So they don't think about infrastructure at all, but actually it's there. So it operation are still there providing resources to let developers be more free and agile and everything. So we are still in a, I think in an interesting time for all of it, >>Kubernetes and cloud native in general, I think are blurring the lines, traditional lines development and operations always were separate entities, obviously through with DevOps. Those two are emerging, but now we're moving. When you add in shift left testing shift, right? Testing, uh, dev SecOps, you see the developers become much more involved in the infrastructure and they want to be involved in infrastructure because that's what makes their applications perform. So this is gonna, cause I think it organizations to have, do some rethinking about what those traditional lines are, maybe break down those walls and have these teams work, work much closer together. And that should be a good thing because the people who are developing applications should also have intimate knowledge of the infrastructure they're gonna run on. >>So Paul, another recurring theme that we've heard here is the impact of funding on resources. What have you, what have your discussions been around founders and creators when it comes to sourcing talent and the impact of the markets on just their day to day? >>Well, the sourcing talent has been a huge issue for the last year. Of course, really ever since the pandemic started interesting. We, uh, one of our, our guests earlier today said that with the meltdown in the tech stock market, actually talent has become more available because people who were tied to their companies because of their, their stock options are now seeing those options are underwater. And suddenly they're not as loyal to the companies they joined. So that's certainly for the, for the startups. Uh, there are many small startups here. Um, they're seeing a bit of a windfall now from the, uh, from the tech stock, uh, bust, um, nevertheless skills are a long term problem. The us, uh, educational system is turning out about 10% of the skilled people that the industry needs every year. And no one I know, sees an end to that issue anytime soon. >>So ENGO, last question to you, let's talk about what that means to the practitioner. There's a lot of opportunity out >>There. >>200 plus sponsors I hear here I think is, or the projects is 200 plus, where are the big opportunities as a practitioner, as I'm thinking about the next thing that I'm going to learn to help me survive the next 10 or 15 years of my career? Where, where do you think the focus should be? Should it be that low level, uh, cloud builder, or should it be at those Le levels of extraction that we're seeing and reading about? >>I, I think, I think that, uh, you know, it's, uh, it's a good question. The, the answer is not that easy. I mean, uh, being a developer today, for sure grants, you, you know, uh, a salary at the end of the month, I mean, there is high demand, but actually there are a lot of other technical, uh, figures in, in the, in, uh, in the data center in the cloud that could, you know, really find easily a job today. So developers is the first in my mind also because they are more, uh, they, they can serve multiple roles. It means you can be a developer, but actually you can be also, you know, with the new roles that we have, especially now with the DevOps, you can be, uh, somebody that supports operation because, you know, automation, you know, a few other things. So you can be a C admin of the next generation, even if you're a developer, even if when you start as a developer, >>Cuan 20, 22 is exciting. I don't care if you're a developer practitioner, a investor, a, uh, it decision maker is CIO CXO. They're so much to learn and absorb here and we're going to be covering it for the next two days. Me and Paul will be shoulder to shoulder. We will, you, I'm not gonna say you're gonna get sick of this because it's just, you know, it's all great information. We'll, we'll, we'll help sort all of this from Valencia Spain. I'm Keith Townsend, along with my host ENCO senior, the Paul Gillon. And you're watching the, you, the leader in high tech coverage.
SUMMARY :
brought to you by the cloud native computing foundation. You're a host of the cube along with Paul So capacity planning become the nightmare that we know from the past. Paul help me separate some of the signal from the noise. And it's the developers who are leading the way. Um, one of the interesting things that I've seen when we, you know, we've always said, Now, the developer understands, you know, it is the early days of Twitter, when periodically the service would just would just, uh, um, Who's on the ground doing this stuff. So they are giving you resources and you use these resources like an internal cloud. So this is gonna, cause I think it organizations to have, do some rethinking about what those traditional and the impact of the markets on just their day to day? 10% of the skilled people that the industry needs every year. So ENGO, last question to you, let's talk about what that means to the practitioner. is the first in my mind also because they are more, uh, they, they can serve multiple roles. the Paul Gillon.
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Richard Hummel, Netscout | Threat Report Episode 1
>>Kicking things off for Netscout's latest threat intelligence reports. I'm Lisa Martin with Richard Hummel manager of threat intelligence at NetScout. We're going to be talking about DDoSs for hire. It's a free for all Richard, welcome to the program. >>Thanks for having me. At least that's always a pleasure to do interviews with you here on acuity. >>Likewise. So, which are the dark web is a dangerous place. We know that we're adversaries own and operate DDoS for hire platforms and botnets to launch everything from free tests to high powered multi-vector attacks. What did you find? What kind of attacks are being launched on the dark web, >>Sadly, any and every type of attack you. And I think you put it eloquently that it's free a little while ago. I got a question come in from a media journalists that I was talking to and they asked me what is the average cost of a DDoS attack? And my gut reaction was mad, 10, 20 USD. I even asked another reporter later on, what do you think it costs? And he came out with two or 300 USD. And so that was kinda my expectations. Well, just because of that question, I broke up my lab and I said, you know what? I'm just going to kind of sleuth a little bit. And so I started logging in, I started looking at these underground platforms and I spend time on 19 of hundreds. There's a website out there that lists all with like three or 400 of these things, but I just chose the top 19. >>And when I started looking at these, every platform that I evaluated had some form of free attacks during launch. And these are the typical for your five attacks like NTP, cl doubt, DNS amplification. These are the, the rope or routine types of attacks we see in the DDoS threat landscape and it's free. And then it scales from there. You have $5 entry fees to do trials. You have a week trial, you can go all the way up to 6,500 USD. And the adversary reports to launch one terabit per second attack with that costs. There's another one that says, Hey, we have 150,000 button-up nodes. He has $2,500, and then you can launch it from this platform. And they also have customization. They have these little sliders on there. You can go in and say, you know what? I have five targets. I want to launch 10 attacks at once. I want it to last this many minutes. These are the vectors I want to use. And then it just tells you here's what you got to pay. Now, it used to be, you needed to have a crypto wallet to even launch a DDoS attack. Well, that's no longer the case. Second. It used to be crypto currency. Well, now they take PayPal. They take wire transfers. They do Western union transfers. And so yeah, this barrier to entry, it doesn't exist anymore. >>Wow. The evolution of data also attacks the low barrier to entry. The customization. You mentioned that you researched the top 19 validated DDoS for hire services. You guys captured the types of attacks, reported number of users and the costs to launch what you went through. What are some of the things that really stuck out to you that you found? >>I think the biggest thing, the biggest outlier that I saw with a lot of these things is that this, the sheer amount of attacks or tech types that they purport to launch that combined with one other metric that I'll, I'll tell you in just a minute. But when I started adding all of these out, I came out with a list of something like 450 different line items. This is taking the attack types from all 19 of these platforms and putting it into a spreadsheet. And then when I actually got rid of the duplicates and I started looking at each one of these to see, did they call it this? And then this one called it, this, there was still 200 different types of attacks. And these attacks are not just your typical volume metric things or your typical like botnet net related things. I mean, they're going after applications. >>They're going after capture pages. They're going after some website based anti DDoSs stuff. They're going after specific games, grand theft, auto Counter-Strike, all of these things. And they have specific attacks designed to overwhelm those layers. And you can actually see in some of the, the, the news or the update boxes they have on their platforms that they put rolling updates similar to like what you would see with Microsoft update. Here's what changed. And so they'll list, oh, we added this capture bypass, or we tweak this bypass, or guess what? We added a new server. And now you have this, this more power to launch bigger attacks. The other thing that really surprised me was the sheer number of users and attacks that they put for it to have and have launched. So across these 19 platforms, I counted over 1 million registered users. Now it could be that multiple users are registered across multiple platforms. >>And so maybe that's a little redundant, but a million or 19. And then the attacks, just whatever they showed in their platform. Now, I don't know what time segment that says it could be all time. It could be a certain snapshot, whatever, 19 of several hundred of these things, more than 10 million attacks. Now, if we look at 2020, we saw 10 million attacks on the whole year, 2021, we saw 9.7 million. So you can just see it. I mean, we're not seeing the whole breadth of the threat landscape. We see about a third probably of the world's internet traffic. And so if what they say is true, there's a lot more attacks out there than even. We talk about >>A lot more attacks than, than are even uncovered. That's shocking. The evolution of DDoSs is, is also quite shocking. One of the things I noticed in the first half 2021 threat intelligence report that NetScout published was some of the underground services offer blacklists or delisting services to prevent attacks. And I thought that sounds like a good thing, but what does that really mean? >>So actually, when we were writing the last chart report, a colleague of mine role in Dobbins had actually talked about this and he's like, Hey, I saw this thing where it's this quasi illegal organization. And they were talking about listing you as this. And they actually turn around and sell these lists. And so I started researching that a little bit. And what it turns out is these organizations, they report to be VPN services. Yeah. And they also say, you know what, we're offer these kinds of lists or block lists. We offer this VPN service, but we are also collecting your IP address. And so if you don't want us to basically resell that to somebody else, or if you want us to add that so that people can attack you based on what they're seeing on the VPN, then you can pay us money and you can do like different tiers of this. >>You can say, block me for a week or a block me for a lifetime and all of these different platforms. I wouldn't say all of them, probably four of the 19 that I looked at had this service. Now as a user, I'm not going to go to every single DDoS for hire platform. I'm not going to purchase the VPN from every single one of these. I'm not going to go and add myself to their denialist across all of these things. That's, that's kind of way too much work for one. And the cost is going to be in the thousands, if not tens of thousands, as you start to add all of these things together. And so they, they report to do something good and in turn, take your information and sell it. And what's worse is they actually assign your username or your handle or your gamer tag to that IP address. >>And so now you have this full list of IPS with gamer tags. And so an adversary Alto that has no qualms or scruples about launching DDoS attacks can then purchase that list. And guess what, Hey, this, this gamer over here who has this gamer tag, he always tells me I don't, I don't want to face them anymore. So anytime I see him in a match, I'm going to go over here to this DDoS for hire platform. And I'm going to just launch attack against him, try to knock them off of them. And so that's the kind of shady business practices that we're seeing here in the underground forums. >>Well, I knew that wasn't a good, I knew that you would actually give me the skinny on what that was. So another thing that I was wondering if it was a good, you know, despite this, you talked about the incredible diversity of these platforms, the majority of attack types that you sign are recognized and mitigated by standard defensive practices. Is that another good, bad disguise as good? >>No, in this case, it is very much good. So I, as far as I've seen, there's not a single DDoS attack type from a Google stressor service to date that you can't mitigate using preparation and your, your typical DDoSs platforms, mitigation protection systems. And even, even the bandwidth, the throughput, what some people call the size or the speed of attacks. We don't really see anything in the terabit per second range from these services. Now they'll, they'll boast about having the capability to do X number of packets per second, or this size of an attack. And so some of them will even say that, Hey, you pay us this money and we're going to give you a one terabit per second attack to date in the four years that I've been here on NetScout. And even some of my colleagues who've been around the space for decades. >>They have yet to see an attack source from one of these details for higher platforms that exceed one terabit per second in bandwidth or volume. And so they might talk a big game. They might boast about these things, but oftentimes it's, it's smoke and mirrors. It's a way to get people into their platforms to purchase things. If I had to pick kind of an average volume or size of attacks for these beer stressors on the high-end, I would say around the 150 to 200 gigabit per second. Now they're a small organization that might seem huge, but to a service provider, that's, that's probably a drop in the bucket and they can easily saturate that across their network, or observe, absorb that even without the top of the line mitigation services. So just being able to have something in place, understand how adversaries are launching these attacks, what attack vectors they are, you know, do some research. >>We have this portal called ominous threat horizon, where you can actually go in there and into your industry segment and your country. And you can just look to see, are there attacks against people like me in my country? And so, but understanding if you are the target of attacks, which it's not, if it's a win, then you can understand, okay, I need to probably have provisions in place for up to this threshold and ensure there's a tax that will exceed that. But at least you're doing due diligence to have some measure of protection, understanding that these are the typical kinds of attacks that you can expect. >>Yeah. That due diligence is key. Richard, thanks for joining me talking about DDoSs for hire a lot of interesting things there that was uncovered in a moment. Richard and I are going to be back to talk about the rise of server class bot net armies.
SUMMARY :
We're going to be talking about DDoSs for At least that's always a pleasure to do interviews with you here on acuity. What did you find? And I think you put it eloquently that it's And the adversary reports to launch one terabit per second attack with that costs. What are some of the things that really stuck out to you that you found? And then this one called it, this, there was still 200 different And you can actually see in some of the, the, the news or the update boxes they have on their And so if what they say is And I thought that sounds like a good thing, And so if you don't want us to basically resell that to somebody else, or if you want us And the cost is going to be in the thousands, if not tens of thousands, as you start to add all of these things together. And so now you have this full list of IPS with gamer tags. the majority of attack types that you sign are recognized and mitigated by standard And so some of them will even say that, Hey, you pay us this money and we're going to give you a one terabit per second attack to date And so they might And you can just look to see, are there attacks against people like me in my country? Richard and I are going to be back to talk
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Loris Degioanni | AWS Startup Showcase S2 Ep 1 | Open Cloud Innovations
>>Welcoming into the cubes presentation of AWS startup showcase open cloud innovations. This is season two episode one of the ongoing series covering exciting hot startups from the AWS ecosystem. Today's episode. One of season two theme is open source community and the open cloud innovations. I'm your host, John farrier of the cube. And today we're excited to be joined by Loris Dajani who is the C T O chief technology officer and founder of cystic found that in his backyard with some wine and beer. Great to see you. We're here to talk about Falco finding cloud threats in real time. Thank you for joining us, Laura. Thanks. Good to see you >>Love that your company was founded in your backyard. Classic startup story. You have been growing very, very fast. And the key point of the showcase is to talk about the startups that are making a difference and, and that are winning and doing well. You guys have done extremely well with your business. Congratulations, but thank you. The big theme is security and as organizations have moved their business critical applications to the cloud, the attackers have followed. This is Billy important in the industry. You guys are in the middle of this. What's your view on this? What's your take? What's your reaction? >>Yeah. As we, as a end ecosystem are moving to the cloud as more and more, we are developing cloud native applications. We relying on CACD. We are relying on orchestrations in containers. Security is becoming more and more important. And I would say more and more complex. I mean, we're reading every day in the news about attacks about data leaks and so on. There's rarely a day when there's nothing major happening and that we can see the press from this point of view. And definitely things are evolving. Things are changing in the cloud. In for example, Cisco just released a cloud native security and usage report a few days ago. And the mundane things that we found among our user base, for example, 60, 66% of containers are running as rude. So still many organizations adopting a relatively relaxed way to deploy their applications. Not because they like doing it, but because it tends to be, you know, easier and a little bit with a little bit less ration. >>We also found that that 27% of users unnecessary route access in the 73% of the cloud accounts, public has three buckets. This is all stuff that is all good, but can generate consequences when you make a mistake, like typically, you know, your data leaks, no, because of super sophisticated attacks, but because somebody in your organization forgets maybe some data on it on a public history bucket, or because some credentials that are not restrictive enough, maybe are leaked to another team member or, or, or a Gita, you know, repository or something like that. So is infrastructures and the software becomes a let's a more sophisticated and more automated. There's also at the same time, more risks and opportunities for misconfigurations that then tend to be, you know, very often the sewers of, of issues in the cloud. >>Yeah, those self-inflicted wounds definitely come up. We've seen people leaving S3 buckets open, you know, it's user error, but, you know, w w those are small little things that get taken care of pretty quickly. That's just hygiene. It's just discipline. You know, most of the sophisticated enterprises are moving way past that, but now they're adopting more cloud native, right. And as they get into the critical apps, securing them has been challenging. We've talked to many CEOs and CSOs, and they say that to us. Yeah. It's very challenging, but we're on it. I have to ask you, what should people worry about when secure in the cloud, because they know is challenging, then they'll have the opportunity on the other side, what are they worried about? What do you see people scared of or addressing, or what should I be worried about when securing the cloud? >>Yeah, definitely. Sometimes when I'm talking about the security, I like to compare, you know, the old data center in that the old monolithic applications to a castle, you know, in middle aged castle. So what, what did you do to protect your castle? You used to build very thick walls around it, and then a small entrance and be very careful about the entrance, you know, protect the entrance very well. So what we used to doing that, that data center was protect everything, you know, the, the whole perimeter in a very aggressive way with firewalls and making sure that there was only a very narrow entrance to our data center. And, you know, as much as possible, like active security there, like firewalls or this kind of stuff. Now we're in the cloud. Now, it's everything. Everything is much more diffused, right? Our users, our customers are coming from all over the planet, every country, every geography, every time, but also our internal team is coming from everywhere because they're all accessing a cloud environment. >>You know, they often from home for different offices, again, from every different geography, every different country. So in this configuration, the metaphor data that they like to use is an amusement park, right? You have a big area with many important things inside in the users and operators that are coming from different dangerous is that you cannot really block, you know, you need to let everything come in and in operate together in these kinds of environment, the traditional protection is not really effective. It's overwhelming. And it doesn't really serve the purpose that we need. We cannot build a giant water under our amusement park. We need people to come in. So what we're finding is that understanding, getting visibility and doing, if you Rheodyne is much more important. So it's more like we need to replace the big walls with a granular network of security cameras that allow us to see what's happening in the, in the different areas of our amusement park. And we need to be able to do that in a way that is real time and allows us to react in a smart way as things happen because in the modern world of cloud five minutes of delay in understanding that something is wrong, mean that you're ready being, you know, attacked and your data's already being >>Well. I also love the analogy of the amusement park. And of course, certain rides, you need to be a certain height to ride the rollercoaster that I guess, that's it credentials or security credentials, as we say, but in all seriousness, the perimeter is dead. We all know that also moats were relied upon as well in the old days, you know, you secure the firewall, nothing comes in, goes out, and then once you're in, you don't know what's going on. Now that's flipped. There's no walls, there's no moats everyone's in. And so you're saying this kind of security camera kind of model is key. So again, this topic here is securing real time. Yeah. How do you do that? Because it's happening so fast. It's moving. There's a lot of movement. It's not at rest there's data moving around fast. What's the secret sauce to making real identifying real-time threats in an enterprise. >>Yeah. And in, in our opinion, there are some key ingredients. One is a granularity, right? You cannot really understand the threats in your amusement park. If you're just watching these from, from a satellite picture. So you need to be there. You need to be granular. You need to be located in the, in the areas where stuff happens. This means, for example, in, in security for the clowning in runtime, security is important to whoever your sensors that are distributed, that are able to observe every single end point. Not only that, but you also need to look at the infrastructure, right? From this point of view, cloud providers like Amazon, for example, offer nice facilities. Like for example, there's CloudTrail in AWS that collects in a nice opinionated consistent way, the data that is coming from multiple cloud services. So it's important from one point of view, to go deep into, into the endpoint, into the processes, into what's executing, but also collect his information like the cultural information and being able to correlate it to there's no full security without covering all of the basics. >>So a security is a matter of both granularity and being able to go deep and understanding what every single item does, but also being able to go abroad and collect the right data, the right data sources and correlated. And then the real time is really critical. So decisions need to be taken as the data comes in. So the streaming nature of security engines is becoming more and more important. So the step one of course, security, especially cost security, posture management was very much let's ball. Once in a while, let's, let's involve the API and see what's happening. This is still important. Of course, you know, you need to have the basics covered, but more and more, the paradigm needs to change to, okay, the data is coming in second by second, instead of asking for the data manually, once in a while, second by second, there's the moment it arrives. You need to be able to detect, correlate, take decisions. And so, you know, machine learning is very important. Automation is very important. The rules that are coming from the community on a daily basis are, are very important. >>Let me ask you a question, cause I love this topic because it's a data problem at the same time. There's some network action going on. I love this idea of no perimeter. You're going to be monitoring anything, but there's been trade offs in the past, overhead involved, whether you're monitoring or putting probes in the network or the different, there's all kinds of different approaches. How does the new technology with cloud and machine learning change the dynamics of the kinds of approaches? Because it's kind of not old tech, but you the same similar concepts to network management, other things, what what's going on now that's different and what makes this possible today? >>Yeah, I think from the friction point of view, which is one very important topic here. So this needs to be deployed efficiently and easily in this transparency, transparent as possible, everywhere, everywhere to avoid blind spots and making sure that everything is scheduled in front. His point of view, it's very important to integrate with the orchestration is very important to make use of all of the facilities that Amazon provides in the it's very important to have a system that is deployed automatically and not manually. That is in particular, the only to avoid blind spots because it's manual deployment is employed. Somebody would forget, you know, to deploy where somewhere where it's important. And then from the performance point of view, very much, for example, with Falco, you know, our open source front-end security engine, we really took key design decisions at the beginning to make sure that the engine would be able to support in Paris, millions of events per second, with minimal overhead. >>You know, they're barely measure measurable overhead. When you want to design something like that, you know, that you need to accept some kind of trade-offs. You need to know that you need to maybe limit a little bit this expressiveness, you know, or what can be done, but ease of deployment and performance were more important goals here. And you know, it's not uncommon for us is Dave to have users of Farco or commercial customers that they have tens of thousands, hundreds of thousands of machines. You know, I said two machines and sometimes millions of containers. And in these environments, lightweight is key. You want death, but you want overhead to be really meaningful and >>Okay, so a amusement park, a lot of diverse applications. So integration, I get that orchestration brings back the Kubernetes angle a little bit and Falco and per overhead and performance cloud scale. So all these things are working in favor. If I get that right, is that, am I getting that right? You get the cloud scale, you get the integration and open. >>Yeah, exactly. Any like ingredients over SEP, you know, and that, and with these ingredients, it's possible to bake a, a recipe to, to have a plate better, can be more usable, more effective and more efficient. That may be the place that we're doing in the previous direction. >>Oh, so I've got to ask you about Falco because it's come up a lot. We talked about it on our cube conversations already on the internet. Check that out. And a great conversation there. You guys have close to 40 million plus million downloads of, of this. You have also 80 was far gate integration, so six, some significant traction. What does this mean? I mean, what is it telling us? Why is this successful? What are people doing with Falco? I see this as a leading indicator, and I know you guys were sponsoring the project, so congratulations and propelled your business, but there's something going on here. What does this as a leading indicator of? >>Yeah. And for, for the audience, Falco is the runtime security tool of the cloud native generation such. And so when we, the Falco, we were inspired by previous generation, for example, network intrusion detection, system tools, and a post protection tools and so on. But we created essentially a unique tool that would really be designed for the modern paradigm of containers, cloud CIC, and salt and Falco essentially is able to collect a bunch of brainer information from your applications that are running in the cloud and is a religion that is based on policies that are driven by the community, essentially that allow you to detect misconfigurations attacks and normals conditions in your cloud, in your cloud applications. Recently, we announced that the extension of Falco to support a cloud infrastructure and time security by parsing cloud logs, like cloud trail and so on. So now Falba can be used at the same time to protect the workloads that are running in virtual machines or containers. >>And also the cloud infrastructure to give the audience a couple of examples, focused, able to detect if somebody is running a shelf in a radius container, or if somebody is downloading a sensitive by, from an S3 bucket, all of these in real time with Falco, we decided to go really with CR study. This is Degas was one of the team members that started it, but we decided to go to the community right away, because this is one other ingredient. We are talking about the ingredients before, and there's not a successful modern security tool without being able to leverage the community and empower the community to contribute to it, to use it, to validate and so on. And that's also why we contributed Falco to the cloud native computing foundation. So that Falco is a CNCF tool and is blessed by many organizations. We are also partnering with many companies, including Amazon. Last year, we released that far gate support for Falco. And that was done is a project that was done in cooperation with Amazon, so that we could have strong runtime security for the containers that are running in. >>Well, I've got to say, first of all, congratulations. And I think that's a bold move to donate or not donate contribute to the open source community because you're enabling a lot of people to do great things. And some people might be scared. They think they might be foreclosing and beneficial in the future, but in the reality, that is the new business model open source. So I think that's worth calling out and congratulations. This is the new commercial open source paradigm. And it kind of leads into my last question, which is why is security well-positioned to benefit from open source besides the fact that the new model of getting people enabled and getting scale and getting standards like you're doing, makes everybody win. And again, that's a community model. That's not a proprietary approach. So again, source again, big part of this. Why was security benefit from opensource? >>I am a strong believer. I mean, we are in a better, we could say we are in a war, right? The good guys versus the bad guys. The internet is full of bad guys. And these bad guys are coordinated, are motivated, are sometimes we'll find it. And we'll equip. We win only if we fight this war as a community. So the old paradigm of vendors building their own Eva towers, you know, their own self-contained ecosystems and that the us as users as, as, as customers, every many different, you know, environments that don't communicate with each other, just doesn't take advantage of our capabilities. Our strength is as a community. So we are much stronger against the big guys and we have a much better chance doing when this war, if we adopt a paradigm that allows us to work together. Think only about for example, I don't know, companies any to train, you know, the workforce on the security best practices on the security tools. >>It's much better to standardize on something, build the stack that is accepted by everybody and tell it can focus on learning the stack and becoming a master of the steak rounded rather than every single organization naming the different tool. And, and then B it's very hard to attract talent and to have the right, you know, people that can help you with, with your issues in, in, in, in, in, with your goals. So the future of security is going to be open source. I'm a strong believer in that, and we'll see more and more examples like Falco of initiatives that really start with, with the community and for the community. >>Like we always say an open, open winds, always turn the lights on, put the code out there. And I think, I think the community model is winning. Congratulations, Loris Dajani CTO and founder of SIS dig congratulatory success. And thank you for coming on the cube for the ADB startup showcase open cloud innovations. Thanks for coming on. Okay. Is the cube stay with us all day long every day with the cube, check us out the cube.net. I'm John furrier. Thanks for watching.
SUMMARY :
Good to see you And the key point of the showcase is to talk about the startups that are making a difference and, but because it tends to be, you know, easier and a little bit with a little bit less ration. for misconfigurations that then tend to be, you know, very often the sewers You know, most of the sophisticated enterprises I like to compare, you know, the old data center in that the metaphor data that they like to use is an amusement park, right? What's the secret sauce to making real identifying real-time threats in the cultural information and being able to correlate it to there's no full security the paradigm needs to change to, okay, the data is coming in second by second, How does the new technology with cloud and machine learning change And then from the performance point of view, very much, for example, with Falco, you know, You need to know that you need to maybe limit a little bit this expressiveness, you know, You get the cloud scale, you get the integration and open. over SEP, you know, and that, and with these ingredients, it's possible to bake Oh, so I've got to ask you about Falco because it's come up a lot. on policies that are driven by the community, essentially that allow you to detect And also the cloud infrastructure to give the audience a couple of examples, And I think that's a bold move to donate or not donate contribute that the us as users as, as, as customers, to attract talent and to have the right, you know, people that can help you with, And thank you for coming
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InfiniGuard Cyber Resilience New Cybercrime Solutions 1
(gentle music) >> High profile cyber attacks like the SolarWinds hack, the JBS meat and the Florida municipality breach, have heightened awareness of how exposed, critical infrastructure has become. Because the pandemic has shifted employees to remote modes of work, hackers now have a much easier target to fish for credentials and exploit less secure home networks. Take the recent Log4j vulnerability, that's yet another example, of how hackers can take advantage of weak links in the chain. Now data storage companies have an important role to play in fighting cyber crime. Ultimately, they provide the equivalent of a bank vault if you will, and are responsible for storing and protecting the data that cyber criminals are targeting to steal or encrypt, in an effort to hold companies hostage, in a ransomware attack. Now in an effort to help customers understand how to protect themselves from such vulnerabilities, and how one storage company is addressing these challenges, the Cube is hosting this special presentation InfiniGuard Cyber Resilience: New Cybercrime Solutions. And we're going to speak with Eric Herzog, who's the Chief Marketing Officer of Infinidat, and then we'll bring in Stan Wysocki who is the president of Mark III Systems who is either an expert in IT infrastructure and artificial intelligence. First, let me welcome Eric Herzog back to the Cube, hello, Eric. >> Great, Dave, thank you very much, always love talking to you and the Cube, about leading edge technology solutions for end users. >> Alright let's do it. So, first we want to address the transformation and big business progress of Infinidat. New CEO, he's injected new management, new head of marketing obviously, Phil Bullinger is really been focused on accelerating the company's original vision, and doing so, Eric, in the typically unconventional style of Infinidat, you just put out a press release, capping 2021, can you set the stage for us, and give us the business update? >> Sure, so of course we summarized our 2021 results. What a very, very strong year. What a very, very strong year. We increased our bookings over 40% year to year. Even in Q4, we increased our bookings over 68%. And over 25% of the fortune 50 use an Infinidat solution, either our InfiniBox, or InfiniBox SSA, all flash array, or our Infiniguard, which is the focus of the launch we're doing today, on February 9th. >> Yeah, so I always said that Infinidat is one of the best kept secrets in the storage business. So let's talk about that hard news, what you launched on February 9th, and why it's important. >> Well, what we've done is we've got a high end enterprise purpose-built backup appliance, the InfiniGuard. We made some substantial advances in that. The key is focused on cyber resilience with what we call our infinisafe technology. Infinisafe incorporates a number of subsets, of cyber resilience from immutable snapshots, to logical air gapping, to fenced isolated networks, to almost instantaneous recovery for your backup data sets. In addition, we also dramatically improved the performance of the backup and recovery, which means, for example, if a backup window was taking three hours, now the backup window on that primary backup dataset could take only an hour and a half, which of course, as we all know backup dramatically impacts the performance of your primary applications, your primary servers, and your primary storage. So we've done both the cyber resilience aspect and then, on modern data protection, making sure that the backup and recovery are faster, for a traditional backup workload. >> So tell us a little bit more about Infinisafe, and specifically, Eric I'm interested in how it's different from other solutions, don't make me a liar, I had said, you guys always kind of take nonconventional approaches so tell us, add a little color to Infinisafe and how is it really unique from competitors? >> Sure, well Infinisafe incorporates as I mentioned, several different aspects. First of all, the immutable snapshots. So immutable snapshots can not be deleted, they cannot be altered, you cannot accelerate the rate, you can set the rate of immutable stuff, do I want to do it once a day? Do I want to do it twice a day? And obviously if a hacker could get in, you could accelerate that. Our immutable snaps are physically separated from the management schema. So the inside of an Infiniguard, we have what we call a data dedupe appliance, and that data dedupe engine, it goes ahead and it applies data reduction technology, to that back up data set. But we've divorced the immutable snapshots from the management of what we now call a DDE. So the DDE has kind of access of giving you that gap, that logical gap between the management schema of a DDE, and of course the immutable snapshot. We also combine that with this air gap technology, you've got the immutability and the air gap, which is local in that instance, but we also can do it remotely. So we can replicate from one Infiniguard in data center A, to a different Infiniguard in data center B. You then can configure that backup data set with the same immutable snapshot, and the same length, one day, half a day, six hours, whatever you choose, and then of course it'll have that same capability. The third thing we've done is very unique. We have a fenced isolated network to perform forensics. So, if the Cube has a cyber or malware attack, you need to make sure that once you've cleaned it up, off the primary storage, the primary servers, that you recover, a known good data set. So we set up this isolated fence network in which to perform that forensic analysis, to give you the appropriate good recover point. However, unlike many of our competitors, we can do it with a single InfiniBox. Some of our competitors, right on their websites say, you need two of their purpose-built backup appliances, to do cyber resilience. Meaning, twice the CapEx and twice the OpEx, which we can do with a single Infiniguard solution. And then lastly is our near instantaneous recovery. As you know, we're recovering backup data sets. We can make between 15 and 30 minutes time, the backup data set fully accessible to the backup admin or the storage admin to use their Commvault, their Veeam, their Veritas, their IBM Spectrum Protect, or whatever their backup software is, to do recovery from the InfiniGuard box, back to the primary storage using of course the backup software that they created the original dataset with. That is very unique. When you look out in the industry and look at, whether it be purpose-built backup competitors, or whether you look at primary storage competitors, almost no one talks about the speed of their recovery, and the one or two that do, talk about recovering the data set. We recover the entire environment. We are ready to go, and the backup admin, if they were, for example, Commvault, Veeam or Veritas, they could immediately start the backup, as soon as we did our recovery, which again, takes between 15 and 30 minutes, independent of the data set size. That could be 50 terabytes, it could be a petabyte, it could be two petabytes. And even two petabytes of data can be available in 15 to 30 minutes. And then of course, the backup admin can restore from that backup dataset. Very powerful and very unique in those aspects. >> Whilst the reason why this is so important is like I said, it's like the bank vault, because hackers are going to go after that backup corpus that's where the gold is, that's where all the data is. So this all really sounds good. But there's more than Infinisafe in this launch. What else should we know? >> Well, the other thing we've done is dramatically improved the performance of the purpose-built backup plants at the core. So for example, the last time we publicly announced our numbers, we were at 74 terabytes an hour, now we're 180 terabytes an hour. So of course, as we all know, when you do a backup, it impacts the performance of the primary applications, the primary servers and the primary storage. So if that backup window was taking three hours, now that we've more than doubled the performance, you could be up to 50% better. So a three hour backup window, if that's what the dataset took to be backed up, now we can get that down to an hour and a half or even faster. So that of course minimizes the impact on primary storage, primary applications, and of course your primary storage, making it much, much more efficient, from a backup perspective, and of course less impact on the primary applications, the primary servers, and primary storage. >> So I've talked to a number of Infinidat customers, they're very loyal and kind of passionate. So I wonder if you could kind of put that perspective on this discussion. The impact that InfiniGuard, this announcement, that's going to have for your customers, paint a picture as to how it's going to change their business. >> Sure, so let me give you an example. One of our customers is a cloud service buyer, in North America, they focus only on healthcare. So here's a couple of key benefits that they got. First of all, they use our integration with two different backup vendors. They don't have one, they have two. So we're tightly integrated with our backup software partners. They got a 40% cost savings on CapEX, compared to the previous vendor that they had. And, they used to be able to do 30,000 backup per day, now they can do 90,000 backup a day. And by the way, that's all with the previous version of InfiniGuard, not the version we just announced on the 9th. One of our other customers, which is in AMEA and they happened to be an energy company, they were using purpose-built backup from the other vendor, and they had 14 of them, seven in data center one, and seven in data center two. With InfiniGuard, they've got one in data center one, and one in data center two. So 14 purpose-built backup appliances consolidated down into two. And on top of that, those purpose-built backup appliances from the other vendor actually had a couple recovery failures, where they were not able to recover the data. They've been installed for a year now, they've had zero recovers, zero recovery failures, whereas the previous vendor had some. And lastly, let's talk about a large global fortune financial services. So, one of the biggest in the industry, their cost savings from their previous vendor was 46%. In addition, when you look at their cyber resilience design, they were using one of those vendors that probably talks about needing two system products to do their cyber resiliency. They again were able to take those two systems out, and use one InfiniGuard solution. Again, reducing both their capital expenditure, two going to one. And then the operational expenditure, they only have to manage one InfiniGuard versus two of the other guys appliances. Those are just three examples all over the world. One in cloud service providing, one in the energy space, and one a global fortune 500 financial services company. Just some real world examples. And all those by the way, Dave, were before the enhancements of Infinisafe, and before the additional performance we've added in the launch of InfiniGuard on February 9th. >> So like I'm just kind of sketching out the business case, you know, put my CFO hat on. So you're lowering costs cause you're consolidating, so that means I need less hardware and software. But also there's probably labor costs associated with that. If I could do it faster with less resources, I got less stuff to manage. You're accelerating the backup time, so that frees up resources that I can apply elsewhere, recovery, you know, is really important. So I'm inferring faster recovery, all this lowers my risk, and then I can sort of calculate the probability of having data loss, and then what that means to my business. Am I getting that right? >> Yeah, yeah. And in fact, the other impact is on your primary service and your primary storage. If the backup window shrinks, then you're not slowing down that SAP app, that Oracle app, you know, that SQL app, whatever you're running, whether that be the financials, whether that be your logistics, whether it be your manufacturing system, every time you turn on that backup, to do that backup, that backup window slows you down. So cutting that in half has an impact on the real-world application side, which obviously most storage guys, you know, it's hard for us to quantify. But you are taking the impact of backup, and basically reducing it, if you will shrinking the backup window, so their primary applications don't get hammered as much by the backup while they're still trying to run that SAP, that Oracle or that SQL workload. >> And you're not a backup software vendor, so I have optionality there. I can pretty much choose all the popular, you know. >> Absolutely, so Veeam, Veritas, Commvault, IBM Spectrum Protect, all the majors. And in fact, one of the players I mentioned, as you were talking about the end-users, they use two different backup packages, two of 'em. So, two of the major vendors that I named, we work with them just within one account. So, we're very flexible, the user picks what they want from a backup software perspective, and we can work with anything. So, whatever they want to use, is fine with us. We integrate with all of them, we have integration, for example, also with VMware, for vVols and other aspects in container integration, so you know, whether it be our purpose-built backup appliance, InfiniGuard, or what we do with the InfiniBox, we always make sure we integrate with the surrounding environment. 'Cause storage is not an island, storage needs to exist in your data center, or your hybrid cloud data center, or what you're doing for containers. So we make sure we have integration with our InfiniBox, our InfiniBox SSA, all flash. And of course the product we're enhancing today, the InfiniGuard. >> Yeah, integration is super important in the enterprise. Enterprises want solutions, they're busy. (laughs) They don't have unlimited budget to go, you know, plugging stuff together. So, okay Eric, we got to leave it there. Thank you so much. >> Great, thank you very much Dave. Always love talking to the Cube. >> Okay, in a moment Stan Wysocki is coming in. He's the president of Mark III Systems. He's going to join us for a drill down on how InfiniGuard is impacting customers. You're watching the Cube, your global leader, in enterprise tech coverage. (gentle music)
SUMMARY :
the Cube is hosting this always love talking to you and the Cube, and doing so, Eric, in the And over 25% of the fortune 50 in the storage business. that the backup and recovery are faster, and of course the immutable snapshot. it's like the bank vault, of the primary applications, So I've talked to a number and before the additional You're accelerating the backup time, And in fact, the other impact all the popular, you know. And in fact, one of the important in the enterprise. Always love talking to the Cube. He's the president of Mark III Systems.
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David Lehanski, NHL & Rob Smedley, Formula 1 | AWS re:Invent 2021
(tubular bells chiming) >> Welcome back to theCUBE's coverage, AWS re:Invent 2021. I'm John Furrier your host of theCUBE. We're here, get all the action wall-to-wall coverage. The keynotes with the new CEO, Adam Leschi just happened. A lot of action wall-to-wall coverage for days, and we'd love cloud computing because it impacts business. We love all that, but when it impact sports, we love it even more because it can relate to it. You can see the two great guests here from the NHL Formula 1. We got David Lehanski the EVP of business development and innovation at the NHL, Rob Smedley, director of data systems at Formula 1. Gentlemen, thanks for joining me today in theCUBE. >> Thanks for having us. >> So obviously formula one we know is very data driven. Pun intended, NHL has a lot of action going on as well with innovation streaming, et cetera. Let's get into it. You're both Amazon customers, right? We'll start with you. Formula 1, big partnership with AWS. What's that about? how you guys look at this cloud as you guys go to the next level? Cause you're under a lot of pressure with the data, from the cars and standards and all that good stuff. What's up. >> What's going on? >> Well, I mean, you know, it started probably four or five years ago with the acquisition of Liberty media and formula 1, and there was a real drive towards data. There was a real drive towards, you know, unearthing all of the data that we've got, you know, formula 1, arguably probably generates the most data, this most sports data of any sport on the planet. You know, we have car telemetry data, timing data, metadata, image data, you know, we own all the video data, and the audio data of driver radio, tire data, weather data, you put all that together. You got to, you know, a real massive data. And it was just about trying to unearth that and, and engage the fans more. And that's where the partnership with AWS come from. >> And the competitiveness in formula one I know is really high. You got a lot of smart people on these teams looking for an edge. And I know it's like, it's a whole new world with data as things get exposed. So I got to ask you, what is your job? Are you there to like to corral the data that kind of set standards? What's your role? >> Well, my role is essentially, to use the data at central league level, if you want, for all the franchises, that's all 20 drivers, within the 10 teams to try to, you know, use that data in whatever way possible, whether it's the new car or whether it's the F1 insights powered by AWS to try to engage the fans more. You know, we've understood that data, is really important to tell the story of Formula 1. And it's really important to reach different demographics as well. The younger demographics, the young, the gen Zedders is, you know, those types of guys, it's really important to get to them, because you can condense and at one hour 45 race down to five minutes, right. Which is what they want. So this has been a really important step for us. And a really important part of that journey has been the enablement. >> And I can see the whole e-sports thing I could see after a race. Okay. Now the fans race amongst themselves, as the technology simulation gets better, only headroom there. So to speak. >> Yeah, yeah, absolutely. I mean, that's what we're, you know, that's probably the next generation of what we want to do with the data is we want to make it much more interactive. We're already giving, you know, through the insights and through, you know, the way that, we're trying to tell stories with the different data assets we're already trying to do that, in a much more proactive way of telling the story. The next level of that. is completely immersive, is interactive. And that's what we call the 21st drivers. So there's 20, formula 1 drivers. Right. But, we want to build systems using the data and gamification where you can embed yourself and immerse yourself in that, in the races, the 21st driver and race against the other guys on a Sunday afternoon. >> Awesome. Dave, let's get to the NHL National Hockey League. You guys are doing a lot of good stuff. You're the EVP of innovation and what's going on over there. How do you see the cloud helping you guys innovate. what's on your agenda and what's your role? >> Wow. I don't know if we have enough time, but at the highest level, you know, we're trying to expand and enhance the way we produce and present our game to the world. You know, our sport, we have some similarities, but there's a lot of differences based on the uniqueness of the sport. Statistics, hadn't really been a big part of the National Hockey League in the way people consume the game. I always say, you know, goaltenders have two statistics that have been used to evaluate them. And they were the same ones that were used to evaluate them back in 1917. So almost again a hundred years where it hasn't really evolved that much, but we think there's so much there that can really enrich and transform the game. So we're trying to partner with AWS and the best technology companies in the world to figure out how we can start to capture that data and turn it into meaningful content and experiences that allow fans to go a little bit deeper and a little bit broader. >> Yeah, I can see the data being used for also seeing what the NFL is doing a lot with the safety. Hits are getting harder and faster in the NHL. I mean, the collisions, the equipment, everyone is going faster. That's a big safety issue too. Isn't it? >> There is a safety component too. And it, look, that is one of the unique things about our sports. Both of us are speed involved. The speed though, for us, it's not just on the ice, it's also the pace of play, right? So when you have a stoppage, it's typically 10 or 15 seconds long. So there's not a lot of time to integrate data, to tell stories, to build and graphics and visualizations. So the first phase for us was to build the tracking system that could capture the positional, the positions of the puck and the players throughout the course of every game. And that's generating a massive amount of new data. Now we're trying to add video to that data so we could start to use it to create entirely new experiences. >> What are you guys thinking about from a fan experience as you look at the analytics. Are they interested in more like the, where the puck is, how fast people are going, what are some of the analytics sharing? >> So it depends, Right? So from a fan standpoint, you know, avid fans really want to, they want to go deep and they want understand controlled zone entries and like, you know, things that are really inherent to, you know, the core factors for determining outcome. Casual fans, they like just on knowing speed, right? How fast is the puck moving? How fast are the players moving. Before we had the system, we weren't able to produce it. Before we had AWS, you won't be able to produce that in real time and overlay it onto a game. So we could go even deeper when it comes to players and coaches and media partners, but the ability to build a solution that works in real time to give them the data and the video that they can use to tell those stories is born from AWS. >> And that brings up a great point. I'd love to ask both of you, if you can answer this question about the fan expectations. One of the big trends coming out of this re-invent this year as cloud is creating more capabilities, but the users and the consumers have new expectations. They want it on mobile, they want the highlights, they want everything. They want the data, there are data junkies. They want everything, cause they're immersing, into the experience with multiple touchpoints. TV, app. Whatever. >> I think that's right. And I think that it's up to, you know, as David's just saying that the two sports here with a lot of similarities and you can see that we're both on the same journey and that's because it's been driven in the end by the consumers, it's been driven by our customers. And, I think that now we're on, you know, what I would call the data flywheel, where there's a lot of inertia and it's just getting stronger and stronger and stronger. And this was, if we go back say three, four years when we started the partnership with AWS and we started to get really deep into the data and understand, you know, what the objectives of this whole exercise were, we always knew that there'd be a point where it started to build a lot of momentum and have a lot of inertia and that's, what's happening now. There's a real thirst for it, right? And it's not just, you know, even the naysayers, you know, even the people that kind of looked at it and went, well, why are you filling my screen with data exactly the same as what Dave says, you know, since you know, the goaltender since 1917, you've used the same two stats to evaluate that particular player. In formula 1 it's been exactly the same. So we started to introduce stuff which had been the same state as core for 70 years. And they say, well, what's all this about. Now, those people can't live without that. Right? It's become, a key part of the broadcast. >> And it creates new products, like things like Netflix, who would've thought a series would be on Formula 1, a soap opera for formula 1 in behind the scenes, driving to survive has been quite an acceleration for fan base. I mean, techies in Silicon valley and all around the world have told us like, hey, you know what? That exposes the nerdiness of Formula 1. Kind of cool. So who would have thought, I mean, there's going to be shows on this whole other level. >> I think, another point to add it is about increasing your distribution points and getting your content out to as many people as possible through as many platforms as possible. But I think in addition to that, it's really about, Rob started to touch on this personalization and customization. What can you do within those platforms to give fans the ability to sort of create their own experience? Right? So data highlights, huge, huge, huge level of importance. >> I think community is going to be a big part of this too. As you start to see the data creates more interactions and more progression, if you will. Community, I'm a Bruins fan in California. There's not a lot of Bruins fans, mostly sharks fans, but I got to get online. Where am I? Where's my tribe. I want to hang, that's not just on Twitter. >> Yeah >> So there's a whole another level coming. How do you guys see community developing in your sports? >> I think the community is the biggest factor in all of this. Right? And it's kind of bringing together. It's a global sports community, first and foremost, but then you've got these pockets. So you've got NHL, NFL, you've got formula 1 and they're all gaining popularity, but it's all through really everybody being on this same journey. Everybody's on this same journey of involving tech in the sport of revolutionizing their particular sport. And it's building this global community. I mean, In formula 1, we've got a billion fans worldwide, but that's growing, it's growing every single year, but it's only growing because we're starting now to get to that younger demographic, formerly one could never get to the demographic, you know, formula 1 fans looked like us, but now it's starting to really improve our system. >> The virtualization of this hybrid world we're living in opens up the doors for more access. >> Absolutely. Yeah. And I think that's the key point here. And again, they've touched on it. It's the personalization. It's using data and platforms and packages to personalize somebody's engagement with their particular sport. >> I got a couple of questions from the fan base, I knew you guys were coming on. I want to get to you , first, Rob, how has F1 been using Amazon and the cloud to develop the new 2022 race car? >> Well, I mean, it, I would say it's no exaggeration to say Amazon technology enabled, was the key enabler in as being able to design that 2022 car, you know, we designed it in a virtual environment called computational fluid dynamics. You know, the simulations, when we were first running design iterations, were taking something like 40 hours with when we started running it on the EC2, you know, spinning up 7,000 calls, something like that. We got that down to seven hours, manageable. We designed the whole new car. >> Awesome. On the NHL, the question here for you, is that okay, how is the young generation coming into the game? What's changed with the innovation that's impacting, how the games played and how the young guns are coming up? Is there any in technology enabling that? >> Sure. You know, so we're looking at the type of content that younger fans are gravitating to, obviously highlights and dance games, but we talked about it before the ability to see what they want to see with regard to that. So, you know, where we're trying to get to is where you could watch a game and ultimately decide whether or not you want to turn on a right rail of real-time statistics for your favorite player, for your favorite team, for a specific event, whether or not you want to turn on the ability to network with your friends across social platforms, whether or not you want to turn on the betting functionality, whether or not you want to turn on the game functionality. Right? So this is how the younger generation really wants to consume the data, like sort of, they want to see what they want to see, when and how they want to see it. So we're working on that. And then there's everything that goes beyond that. The world of NFTs and VR and AR and alternate forms of content distribution, none of that would be capable or available if not for the ability to capture process and distribute data and video in an aggregate in real time. >> You know, I really think we're onto something so new here. And if you guys are really kind of illustrating the whole point of how being in person, the old model of physical, I don't have to go into arena to watch hockey or go watch formula 1, and hopefully it's on TV. Maybe it's got coverage here and there, but now with hybrid, you can integrate the experiences from the physical in-person where the asset is. >> Absolutely. >> And to virtual and just open up completely new hybrid use cases. I mean, this is brand new. There's no standards. >> Not, exactly. And that's something that we're really starting to look at, which is the event of the future. You know? So how would you bring, how do you mismatch? How would you bring that whole data experience and that whole broadcast experience to the actual event, the live event, and how would you bring the live event to somebody's front room? It's the hybrid model, right? And this is definitely next generation of how we're using the data. We're working with AWS. We're calling it event of the future. It's really, really exciting. I mean, you can imagine going there, to a formula 1 race, you're sat in the stands. You're no longer, you know, watching a car pass every few seconds and wondering what's going on. You've now got AR, VR that you can kind of put up and lay-up across what's going on the track. >> Well, a lot of people would love to get you guys' reaction to this comment online. Cause this is big, I see a lot of naysayers out there because they're so locked into the business model of the physical location. There's a lot of investment in events like this, wants me to buy tickets and show up. So they call it a one-way door here in the industry, they don't want to go through that one way door, but I'm saying that door has already been passed. It's like you're in this hybrid world is here. If you don't get out in front of it, you're going to be toast. So the question is, how do you guys think about this when you talk about the business model of experience? Cause you have to get in there and it's not super great right now on virtual. It could be better. It has to get better. So it's a balance. How do you guys talk about that in your respective fields to educate the potential? I won't say naysayers, but yeah. >> Yeah no, no, no. So we believe it wholeheartedly. You know, when you think about the inner arena experience, there's a lot of infrastructure that needs to be in place to be able to deliver those types of experiences to fans, while they're in the building, we wholeheartedly believe that the people who are paying the most to see our games should get the best possible experience. So there should be no replay, they don't get, there should be no game that they can't access, no application that they couldn't have on their phone, but you need to have, you know, fairly advanced wireless in the arena infrastructures in place. You need to have a lot of cloud infrastructure and services there. So, you know, that's why we're leveraging Kinesis and SageMaker and AWS elemental services to get all of it condensed, operating in the cloud and distributed. So if you're a fan at a game, they're 18,000 other people, like you trying to access a mobile phone to place a bet on a real-time event that just happened, you can actually do it, but a lot needs to go into that. >> Yeah, that's really good insight because what you're pointing out is is that the physical location is the first party asset. That's the key. You build on that, invest in that and then feed it out into the next world and then figure that out. Do you agree with that. >> Absolutely. 100 percent correct. Well, 100 percent agree with everything that David just said. And we've got probably, you know, an even bigger challenge because we've got these 20 sites where we lift and shift 20, 23 races, you know, all round the world where we lift and shift every couple of weeks, and they're not arenas either. They're, you know, these are huge sites. These are you know, five, six kilometer by five, six kilometer square sites. So trying to do everything that David just said in that space, we can open it. >> Yeah, we just turn the lights off, it's over, he's got to pack it all up. >> The private 5G is going to totally help. You can run drones and have full blanket coverage over the location. That's good. That's good stuff. Final question for you guys on data, because I think this is something that we've been kind of talking about on theCUBE over the past year, we see open source software has become a huge success. Do you guys see opening up the data to your fan base and seeing e-sports races in formula 1, is just going crazy. Everyone loves it. It's not there yet but the equipment having your own car in your living room, but it's close, pretty close, it's there. Opening up the data, how do you see that potential? Because there are people who want to maybe code on top of it. How do you guys view that? >> Well, I think it, has to, I mean, Dave, again, touched on this earlier when he talked about, you know, the difference between the casual and the avid. The avid, you'll never, ever satisfy the average thirst for data, right. They want to do what I did and sit on a pit wall and manage a grand Prix team. And that's great, you know, it shouldn't just be for a privilege, you know, 10, 20 people in the world to do that. We should be able to give everybody that experience because we have the technology and the ability and the know how to be able to do that. And that's where, you know, again, partnership with AWS, where we're talking about something called the virtual pit wall. So, you know, the pit stands where it's kind of like the mission control. We want to be able to bring that to the average. And it's just getting deeper and deeper layers where you can set up your bespoke environment. You can set it up just as if you were a race engineer or a team strategist, one of those guys, and you can just get deeper and deeper. And then you start to lay over that. You start to build your own models. We bring in simulation into that whole area. And, you know, it's exactly the same as what you have in the teams. You just go deeper and deeper and deeper. >> What's it like to be on the pit wall there, managing teams. what's it. (men laughing) >> Hmm scary sometimes >> Nerve wrecking. >> Nerve-wracking, I mean, I talked about, you know, the gen Zedders who want the, you know, a two hour race to pass in five minutes, it passes in five minutes. Cause there's so much going on. You know, it's kind of like being the coach or the, you know, the football manager, you know, you're under a lot of pressure. You've got to make the right decisions. You've got to, you know, you've got to make decisions in split seconds. Everybody's an expert 10 seconds after the decision has been made. It's that type of thing, but it's great fun, you know. >> I can see virtual Formula 1 being a hot total hit because with all the data and now autonomous vehicles, you can almost have a collective kind of team approach, like swapping out AI in the cars in real time from the virtual pit. >> Yeah. And again, you know, I'm just going to name check deep racer because you know, AWS deep racer, you know, we formula 1, and AWS deep racer. We did an activation about a year back in the first lockdown, in the first COVID lockdown. So we took a couple of formula 1 drivers, Daniel Ricardo being one of them. And then we built out this deep racer platform and we're trying to look at how we can bring that more, you know, more together. So you've got this virtual, sorry, this AI car, this autonomous car, and you've got formula 1. And how do we merge those two worlds together? And again, that's just trying to immerse people more in the experience. >> Alright, final question. What's the coolest thing you got going on in each of your respective innovation fields with AWS? What would you highlight your favorite innovation or coolest thing you're doing? >> Well, I can't tell you about the coolest, right. That's for sure. Look, I just think what we're doing with AWS with regard to AIML around data and statistics analytics, based on what I said earlier, the evolution of statistics and analytics and hockey really hasn't taken hold, we're there now. The ability to really take a game that's has so much volatility, and we're the only professional teams sport that has personnel changes occurring in life play. So you never really know who's on the ice and the ability now to deliver real-time graphics and visualizations in the broadcast based on movements that had just played within milliseconds. And, we're starting to do that today with shot and save analytics with AWS. So where that can go in the future is really, what's probably the most exciting because it'll totally transform the way fans consumer our game. >> The NHS has always been on the cutting edge on the tech. Been following you guys for years, congratulations. Rob, the coolest thing you're working on, from Amazon, that's cool, and in formula 1 that's in your plate right now. >> Do you know what, I mean, there's so much going on at the minute. It's really difficult to choose any one thing. I think the whole partnership it's everything that we wanted it to be that, you know, the whole way that we're moving data forward and where we're revolutionizing this sport in a lot of ways, you know, sport has sat still for a long time. And to go through that digital transformation, you know, with Amazon and you know, in all the various areas that we're working on, I just think it's all, you know, it's all really, really cool. I mean, it's just moving forward at such a pace. Now. >> If you don't mind me asking why I got you here on the whole data thing, I'm just thinking about if I was on a team, I'd be like, okay, there's a whole new wild west. It's this arbitrage of data, we'll get over on the other team. Do you have to watch out, do you guys talk about like watching teams actually, I mean, it's actually innovative that they can get an edge, but an unfair advantage if they actually had used the data, is there like discussion around, like who can use the data, which teams? >> Of course. I mean, you know, when you get down to the franchises, each team can only use its individual data. You know, that's where we have key insight up at the league level because we've got, you know, a subset of all of the teams data. So we can kind of see everything that's going on. >> And watch out for the hackers coming in and get that data. >> Oh, well, alright, we've got pretty good security. >> Guys, thanks for coming on. I love the sports angle on this. It's really awesome. I think this is a great example of how cloud and digital lifestyle is coming together. The tech integration with the fan experience and the business models are super compelling, and I think that's illustration to just every other business. Thanks for coming on theCUBE. Appreciate it. >> Awesome. >> Thank you. >> Okay so theCUBE's coverage here at AWS re:Invent. I'm John furrier, your host in theCUBE. You're watching the leader in event tech covers theCUBE. Thanks for watching. (soul music)
SUMMARY :
and innovation at the NHL, as you guys go to the next level? that we've got, you know, And the competitiveness to try to, you know, And I can see the whole e-sports thing I mean, that's what we're, you know, How do you see the cloud but at the highest level, you know, and faster in the NHL. it's not just on the ice, What are you guys thinking but the ability to build a One of the big trends coming even the naysayers, you know, in behind the scenes, driving to survive the ability to sort of create and more progression, if you will. How do you guys see community to the demographic, you know, The virtualization of this It's the personalization. I want to get to you , it on the EC2, you know, how is the young generation the ability to see what they want to see And if you guys are really And to virtual and just open up and how would you bring the live event love to get you guys' reaction the most to see our games it out into the next world And we've got probably, you know, he's got to pack it all up. the data to your fan base and the know how to be able to do that. on the pit wall there, the gen Zedders who want the, you know, from the virtual pit. deep racer because you know, What's the coolest thing you got going on and the ability now to been on the cutting edge that we wanted it to be that, you know, the whole data thing, I mean, you know, and get that data. alright, we've got pretty good security. and the business models I'm John furrier, your host in theCUBE.
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Day 1 Keynote Analysis | UiPath FORWARD IV
>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by, >>Hey, welcome to the cubes coverage of forward for UI path forward for live from the Bellagio in Las Vegas. I'm Lisa Martin with David. David's great to be back sitting at an anchor desk. >>Yeah, good to see. This is my first show. Since June, we were at mobile world Congress and I've been, I've been doing a number of shows where they'll they'll the host myself would be there with some guests as a pre-record to some simulive show, but this is real live awesome to be working with you again. So we did live last week at a DC public sector summit for AWS next week's cube con. So it's three in a row. So maybe it's a trend. It we'll see. >>Well, the thing that was really surprising was that we were in the keynote briefly this morning. It was standing room only. There are a lot of people at this conference. They think they were expecting about 2000. And to me it looked like there were at least out, if not more >>Funny leases, most companies, if not virtually all of them, except for a handful are canceling physical events. And because they're saying their customers aren't traveling, but I've talked to over a dozen customers here. I just got here yesterday afternoon. I've talked about 10 or 12 customers who are here. They're flying, they're traveling. And we're going to dig into a lot of that. Today. We have Uber coming on the program. We have applied materials coming on, blue cross blue shield. I'm really happy that UI path decided to, to put a number of customers on the cubes so we can test what we're hearing, you know, in the marketing. >>Well, one of the first things that they said in the keynote this morning was we want to hear from our customers, what are we doing? Right? What are we not doing enough of? What do you want more? They've got eight over 8,000 customers. You mentioned some of the ones that are going to be on the program this week, including Chevron and Merck who are on today. And 70% of their revenue comes from existing customers. This is a company that has, is really kind of a use case in land and expand. Yeah. >>And I think you're going to see this trend. You know what it's like with COVID it's day to day, month to month, quarter to quarter, you're trying to figure out, okay, what's the right model. Clearly hybrid is the, is the new abnormal, if you will. And I think we're going to see is, is you're going to have VIP events and this is kind of a VIP event. It's not, you know, 5,000 people, it's kind of 1500, 2000, but there are a lot of VIP customers here. Obviously the partners here. So what they did before the show is they had a partner summit. It was packed. You talk about standing room only. They had a healthcare summit, it was packed. And so they have these little VIP sections, little events within the event, and then they broadcast it out to a wider audience. And I think that's going to be the normal one. I think you're going to see CEO's in a room, maybe in a hotel and in wherever in Manhattan or, or San Francisco. And then they'll broadcast out to that wider audience. I think people are learning how to build better hybrid events, but by the way, this is all new. As I said, hybrid events, I meant virtual events. And now they're learning to learn how to build hybrid events. And that's a nother new process. >>It is, but it's also exciting to see the traction, the momentum that is here from, uh, you know, they, and they IPO at about what six months ago, you covered that your breaking analysis that you did right before the IPO and the breaking analysis that you did last last week, I believe really fascinating. Interesting acceleration is, is a theme. We're going to talk about the acceleration of automation and the momentum that the pandemic is driving. But this is a company that's accelerated everything. As you said on your breaking analysis, lightning in a bottle, this is a company that went global very quickly. We're seeing them as some of the leading companies. We can probably count on one hand who are actually coming back to these hybrid events and say, we want to be with our customers again and learn from you what you're doing, what's going on. And we've got a lot of news to share. >>Yeah, we've been covering UI path since 2015. And the piece we wrote back at IPO was, uh, you, you bypass long, strange trip to IPO and it, and it was strange. And that they kind of hung out as a software development shop for the better part of a decade. And then just listening and learning, writing code, they were kind of geeks writing code and loved it. And then they realized, wow, we have something here we can. And they, their uniqueness is they have a computer vision technology. They have the ability to sort of infer what a form looks like and then actually populated. And the thing that UI path did that was different was they made sound, sounds crazy. They made the product really simple to use, right? And we know simplicity works. We see that with best example in storage, storage, complicated business, pure storage, right? >>They pop it in. You kind of Veeam is another one. It just works. And so they, they created a freemium model that made it easy for departments to start small, you know, maybe for 15, 20, 20 $5,000, you could get a software robot and then it would do things like whatever it, it would pull data out of one spreadsheet, put it into another pull date out of one, SAS populated and people then realize, wow, I am saving a ton of time. I can do some other things. I'm more productive. And other people looking over her shoulder would say, Hey, what is that you're using? Can I get that? And then all of a sudden, like you said, lightning in a bottle and it exploded, not a conventional Silicon valley, you know, funded company, even though they got a lot of funding, they got, they raised close to a billion dollars before they went public. Um, and now they're public went public in April. The stock has been sort of trending downward for the last four or five months, a little bit off on sympathy, but you know, >>What do you think that is? They had such momentum going into it. They clearly have a lot of momentum here. 8,000 plus customers. They've got over 1200 customers with an ARR above a hundred thousand. Why do you think the stock is? >>So I think a couple of things, at least, I think first of all, the street doesn't fully understand this company. You know, Daniel DNAs has never been the CEO of a public company. He's not from Silicon valley. He's, you know, from, from, uh, Eastern Europe and they don't know him that well, uh, they've got, you know, the very, very capable, and so they're educating the streets. So there's a comfort level there. They're looking at their growth and they're inferring from their billings that their growth is, is declining. The new growth from new customers in particular. But there, the ARR is still growing at 60% annually. They also guided a little bit conservatively for the street. And the other thing is they've been profitable. I'm not if a cashflow basis. And then they guided that they would actually be, be somewhat unprofitable in the coming quarter. >>People didn't like that. They don't care about profits until you're somewhat profitable. And then you say, Hey, we're going to be a little less profitable, but of course they get events like this. So that I think it's just a matter of the street, getting to understand them. And I will say this, and you know, this, they're getting a lot of business from their existing customers. We saw this with snowflake, uh, Cleveland research, put out a note saying, oh, Snowflake's new customer growth is slowing. We published research from our friends at ETR that showed well, they're getting a lot of business from existing customers that sort of fat middle is really where they're starting to mind. And you can see this with UI path. The lifetime value of the customers is just growing and growing and growing. And so I'm not as concerned. The stocks, you know, we don't, we don't, we're not the stock advisors, but the stock is just over 50. >>Now it wasn't 90 at one point. So it's got a valuation of somewhere around 26 billion, which was closer to 50 billion. So who knows, maybe this is a buying opportunity. There's not a lot of data. So the technical analyst are saying, well, we really don't know where it's going to cook it down to 30. It could go, could go rock it up from here. I think the point Lisa is, this is a marathon. It's not a sprint, it's a long-term play. And these guys are the leaders. And they're, I think moving away from the pack. And the last thing is this concern about competition from Microsoft who bought a company last year to really in earnest, get into this business. And everybody's afraid of Microsoft. >>Well, one thing that we know that's growing considerably is the total addressable market pre pandemic. It was about 30 billion. It's now north of 60 billion. We've seen the pandemic accelerate a lot of things. Talk to me a little bit about automation as its role in digital transformation from your side. >>Yeah, I think, you know, this is again, it's a really good question because when you look at these total available market numbers, the way that companies virtually all companies, whether it's Dell or Cisco or UI path or anybody, they take data from like Gartner and IDC and they say, okay, these are the markets that we kind of play in, and this is how it's growing. What's really happening. Lisa's all these markets are converging because of digital. So to your question, it's a di what's a digital business. A digital business is a data business and they differentiate by the way in which they use data. And if you're not a digital business during the pandemic, you're out of business. So all of these markets, cloud machine intelligence, AI automation, orchestra, uh, container orchestration, container platforms, they're all coming together as one, it's all being built in as one. >>So 60 billion up from 30 billion, I think it could be a hundred billion. I think, you know, they threw out a stat today that 2% of processes are automated, uh, says to me that, I mean, anything digital is going to be automated. So that is hundreds of billions of dollars of, of market opportunity, right? And so there's no shortage of market opportunity for this company. And that's why, by the way, everybody's entering it. We saw SAP make some acquisitions. We S we see in for talking about it, uh, uh, Salesforce service now, and these SAS companies are all saying, Hey, we can own the automation piece within our stack, what UI path is doing. And the reason why I liked their strategy better is they're a specialist in automation horizontally across all these software stacks. And that's really why their Tam I think is, >>And that gives them quite a big differentiator that horizontal play >>It does. I think I see. So I don't see, I think there's a continuum and I think you got Microsoft over here with Azure and personal productivity in their cloud. And then you've got the pure plays, which are really focusing on a broader automation agenda. That's UI path, that's automation, anywhere I would put blue prism in that category, the blueprints, and by the way, is getting, getting acquired by Vista. And they're gonna merge them with Tipco company that, you know, quite a bit about, and that's an integration play. So that's kind of interesting. I would put them as more of a horizontal play. And then in the fat middle, you've got SAP and in four, and, and, you know, IBM's getting into the game, although they, I think they OEM from a lot of different companies and all those other companies I mentioned before, they're kind of the walled gardens. >>And so I think that UI path is less of a head-to-head competitor with Microsoft today anyway, than it is for instance, with automation anywhere. And it's, and it's growing faster than automation, anywhere from what we can tell. And it's, it's still leader in that horizontal play. You know, you never discount Microsoft, but I think just like for instance, Okta is a specialist in, in, in access identity, access management and privileged, privileged access management and access government, they compete with Microsoft's single sign on, right. But they're a horizontal play. So there's plenty of room for, for both in my view. Anyway, >>Some of the things that you can you think that we're going to hear, you know, seem to be at this inflection point where UI path wants to move away from being an RPA point solution to an enterprise automation platform they made, they made some announcements about vision a couple of years ago at the last in-person event. What are some of the things you think that are going to be announced in the next couple? >>That's a really good question. I'm glad you picked up on that because they started as a point tool essentially. And then they realized, wow, if we're really going to grow as a company, we have to expand that. So they made acquisite, they've been making acquisitions. One of the key acquisitions they made was a company called process gold. So it's funny when we've done previous, uh, RPA events, I've said RPA in its early days was kind of scripts paving the cow path, meaning you're taking existing processes of saying, okay, we're just going to automate them where UI path is headed in others is they're looking across the enterprise and how do we go end to end? How do we take a broader automation agenda and drive automation throughout the entire organization? And I think that's a lot of what we're going to hear from today. We heard that from executives, APAR co co Kaylon, and, um, and, and, and Ted Kumar talked about their engineering and their product vision. And I think you iPad test to show that that's actually what's happening with customers and they have the portfolio to deliver >>Well, those two executives that you just mentioned, and a lot of others are going to be on the program. The next couple of days jam packed. Dave, I'm looking forward to unpacking what UI path is doing. The acceleration in the automation markets. We're going to have a fun couple of days. >>Thanks for coming on here for David >>Lente. I'm Lisa Martin. We're going to be back live from Las Vegas at UI path forward for in just a minute.
SUMMARY :
the Bellagio in Las Vegas. but this is real live awesome to be working with you again. And to me it looked like there were at least out, if not more And because they're saying their customers aren't You mentioned some of the ones that are going to be on the program this week, including Chevron and Merck who And I think that's going to be the normal one. events and say, we want to be with our customers again and learn from you what you're doing, And the thing that UI path did that was different was And then all of a sudden, like you said, lightning in a bottle and What do you think that is? And the other thing is they've been profitable. And I will say this, and you know, this, they're getting a lot of business And the last thing is this concern about competition We've seen the pandemic accelerate a lot And if you're not a digital business during the pandemic, you're out of business. And the reason why I liked their So I don't see, I think there's a continuum and I think you got And so I think that UI path is less of a head-to-head competitor with Some of the things that you can you think that we're going to hear, you know, seem to be at this inflection point where UI And I think you iPad test to show that Well, those two executives that you just mentioned, and a lot of others are going to be on the program. We're going to be back live from Las Vegas at UI path forward for in just a minute.
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Day 1 Keynote Analysis | UiPath FORWARD IV
>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by, >>Hey, welcome to the cubes coverage of forward for UI path forward for live from the Bellagio in Las Vegas. I'm Lisa Martin with David. David's great to be back sitting at an anchor desk. >>Yeah, good to see. This is my first show. Since June, we were at mobile world Congress and I've been, I've been doing a number of shows where they'll they'll the host myself would be there with some guests as a pre-record to some simulive show, but this is real live awesome to be working with you again. So we did live last week at a DC public sector summit for AWS next week's cube con. So it's three in a row. So maybe it's a trend. It we'll see. >>Well, the thing that was really surprising was that we were in the keynote briefly this morning. It was standing room only. There are a lot of people at this conference. They think they were expecting about 2000. And to me it looked like there were at least out, if not more >>Funny leases, most companies, if not virtually all of them, except for a handful are canceling physical events. And because they're saying their customers aren't traveling, but I've talked to over a dozen customers. I just got here yesterday afternoon. I've talked about 10 or 12 customers who are here. They're flying, they're traveling. And we're going to dig into a lot of that. Today. We have Uber coming on the program. We have applied materials coming on, blue cross blue shield. I'm really happy that you AIPAC decided to, to put a number of customers on the cubes so we can test what we're hearing, you know, in the marketing. >>Well, one of the first things that they said in the keynote this morning was we want to hear from our customers, what are we doing? Right? What are we not doing enough of? What do you want more? They've got eight over 8,000 customers. You mentioned some of the ones that are going to be on the program this week, including Chevron and Merck who are on today. And 70% of their revenue comes from existing customers. This is a company that has, is really kind of a use case in land and expand. Yeah. >>And I think you're going to see this trend. You know what it's like with COVID it's day to day, month to month, quarter to quarter, you're trying to figure out, okay, what's the right model. Clearly hybrid is the, is the new abnormal, if you will. And I think we're going to see is, is you're going to have VIP events. And this is kind of a VIP event. It's not, you know, 5,000 people, it's kind of 1500, 2000, but there are a lot of VIP customers here. Obviously the partners here. So what they did before the show is they had a partner summit. It was packed. You talked about standing room only. They had a healthcare summit, it was packed. And so they have these little VIP sections, little events within the event, and then they broadcast it out to a wider audience. And I think that's going to be the normal one. I think you're going to see CEO's in a room, maybe in a hotel and wherever in Manhattan or, or San Francisco. And then they'll broadcast out to that wider audience. I think people are learning how to build better hybrid events, but by the way, this is all new. As I said, hybrid events, I meant virtual events. And now they're learning to learn how to build hybrid events. And that's a whole nother new process. >>It is. But it's also exciting to see the traction, the momentum that is here from, you know, they and they IPO at about what six months ago, you covered that your breaking analysis that you did right before the IPO and the breaking analysis that you did last last week, I believe really fascinating. Interesting acceleration is a theme. We're going to talk about the acceleration of automation and the momentum that the pandemic is driving. But this is a company that's accelerated everything. As you said on your breaking analysis, lightning in a bottle, this is a company that went global very quickly. We're seeing them as some of the leading companies. We can probably count on one hand who are actually coming back to these hybrid events and say, we want to be with our customers again and learn from you what you're doing, what's going on. And we've got a lot of news to share. >>Yeah, we've been covering UI path since 2015. And the piece we wrote back at IPO was, uh, you, you bypass long, strange trip to IPO and it, and it was strange. And that they kind of hung out as a software development shop for the better part of a decade. And then just listening and learning, writing code, they were kind of gigs writing code and loved it. And then they realized, wow, we have something here we can. And they, their uniqueness is they have a computer vision technology. They have the ability to sort of infer what a form looks like and then actually populated. And the thing that UI path did that was different was they made it sound, sounds crazy. They made the product really simple to use, and we know simplicity works. We see that with best example in storage storage, a complicated business, pure storage, right? >>They pop it in. You kind of Veeam is another one. It just works. And so they, they created a freemium model. It made it easy for departments to start small, you know, maybe for 15, 20, 20 $5,000, you could get a software robot and then it would do things like whatever it, it would pull data out of one spreadsheet, put it into another pull date out of one, SAS populated and people then realize, wow, I am saving a ton of time. I can do some other things I'm more productive. And then other people looking over her shoulder would say, Hey, what is that you're using? Can I get that? And then all of a sudden, like you said, lightning in a bottle and it exploded, not a conventional Silicon valley, you know, funded company, even though they got a lot of funding, they got, they raised, I think, close to a billion dollars before they went public. Um, and now they're public went public in April. The stock has been sort of trending downward for the last four or five months, a little bit off on sympathy, but you know, >>What do you think that is? They had such momentum going into it. They clearly have a lot of momentum here. 8,000 plus customers. They've got over 1200 customers with an ARR above a hundred thousand. Why do you think the stock is? >>So I think a couple of things, at least, I think first of all, the street doesn't fully understand this company. You know, Daniel DNAs has never been the CEO of a public company. He's not from Silicon valley. He's, you know, from, from, uh, Eastern Europe and they don't know him that well, uh, they've got, you know, the very, very capable, and so they're educating the streets. So there's a comfort level there. They're looking at their growth and they're inferring from their billings that their growth is, is declining. The new growth from new customers in particular. But there, the ARR is still growing at 60% annually. They also guided a little bit conservatively for the street. And the other thing is they've been profitable. I'm not if a cashflow basis. And then they guided that they would actually be, be somewhat unprofitable in the coming quarter. >>People didn't like that. They don't care about profits until you're somewhat profitable. And then you say, Hey, we're going to be a little less profitable, but of course they get events like this. So that, that, I think it's just a matter of the street getting to understand them. And I will say this, and you know, this, they're getting a lot of business from their existing customers. We saw this with snowflake, uh, Cleveland research, put out a note saying, oh, Snowflake's new customer growth is slowing. We published research from our friends at ETR that showed well, they're getting a lot of business from existing customers that sort of fat middle is really where they're starting to mind. And you can see this with UI path. The lifetime value of the customers is just growing and growing and growing. And so I'm not as concerned. The stocks, you know, we don't, we don't, we're not the stock advisors, but the stock is just over 50. >>Now it wasn't 90 at one point. So it's got a valuation of somewhere around 26 billion, which was closer to 50 billion. So who knows, maybe this is a buying opportunity. There's not a lot of data. So the technical analyst are saying, well, we really don't know where it's going to cook it down to 30. It could go, could go rock it up from here. I think the point Lisa is, this is a marathon. It's not a sprint, it's a long-term play. And these guys are the leaders. And they're, I think moving away from the pack. And the last thing is this concern about competition from Microsoft who bought a company last year to really in earnest, get into this business. And everybody's afraid of Microsoft. >>Well, one thing that we know that's growing considerably is the total addressable market pre pandemic. It was about 30 billion. It's now north of 60 billion. We've seen the pandemic accelerate a lot of things. Talk to me a little bit about automation as its role in digital transformation from your side. >>Yeah, I think, you know, this is again, it's a really good question because when you look at these total available market numbers, the way that companies virtually all companies, whether it's Dell or Cisco or UI path or anybody, they take data from like Gartner and IDC and they say, okay, these are the markets that we kind of play in, and this is how it's growing. What's really happening leases. All these markets are converging because of digital. So to your question, it's a di what's a digital business. A digital business is a data business and they differentiate by the way in which they use data. And if you're not a digital business during the pandemic, you're out of business. So all of these markets, cloud machine intelligence, AI automation, orchestra, uh, container orchestration, container platforms, they're all coming together as one, it's all being built in as one. >>So 60 billion, you know, up from 30 billion, I think it could be a hundred billion. I think, you know, they threw out a stat today that 2% of processes are automated says to me that, I mean, anything digital is going to be automated. So that is hundreds of billions of dollars of, of market opportunity, right? And so there's no shortage of market opportunity for this company. And that's why, by the way, everybody's entering it. We saw SAP make some acquisitions. We S we see in for talking about it, uh, uh, Salesforce, uh, service now, and these SAS companies are all saying, Hey, we can own the automation piece within our stack, what UI path is doing. And the reason why I liked their strategy better is they're a specialist in automation horizontally across all these software stacks. And that's really why they're Tam, I think is, >>And that gives them quite a big differentiator that horizontal play >>It does. I think I see. So I don't see, I think there's a continuum and I think you got Microsoft over here with Azure and personal productivity in their cloud. And then you've got the pure plays, which are really focusing on a broader automation agenda. That's UI path, that's automation, anywhere I would put blue prism in that category blueprints. And by the way, he's getting, getting acquired by Vista, and they're gonna merge them with TIBCO company that, you know, quite a bit about, and that's an integration play. So that's kind of interesting. I would put them as more of a horizontal play. And then in the fat middle, you've got SAP and in four and, you know, IBM is getting to the game. Although they, I think they OEM from a lot of different companies and all those other companies I mentioned before, they're kind of the walled gardens. >>And so I think that UI path is less of a head-to-head competitor with, with Microsoft today anyway, than it is for instance, with automation anywhere. And it's, and it's growing faster than automation, anywhere from what we can tell. And it's, it's still a leader in that horizontal play. You know, you never discount Microsoft, but I think just like for instance, Okta is a specialist in, in, in access identity, access management and privileged, privileged access management and access government, they compete with Microsoft's single sign on, right. But they're a horizontal play. So there's plenty of room for, for both in my view. Anyway, >>Some of the things that you can you think that we're going to hear, you know, seem to be at this inflection point where UI path wants to move away from being an RPA point solution to an enterprise automation platform they made, they made some announcements about vision a couple of years ago at the last in-person event. What are some of the things you think that are going to be announced in the next couple? >>That's a really good question. I'm glad you picked up on that because they started as a point tool essentially. And then they realized, wow, if we're really going to grow as a company, we have to expand that. So they made acquisite, they've been making acquisitions. One of the key acquisitions they made was a company called process gold. So it's funny when we've done previous, uh, RPA events, I've said RPA in its early days was kind of scripts paving the cow path, meaning you're taking existing processes of saying, okay, we're just going to automate them where UI path is headed in others is they're looking across the enterprise and how do we go end to end? How do we take a broader automation agenda and drive automation throughout the entire organization? And I think that's a lot of what we're going to hear from today. We heard that from executives, APAR, co Kaylon, and, um, and, and, and Ted Coomer talked about their engineering and their product vision. And I think you iPad has to show that that's actually what's happening with customers and they have the portfolio to deliver >>Well, those two executives that you just mentioned, and a lot of others are going to be on the program. The next couple of days jam packed. Dave, I'm looking forward to unpacking what UI path is doing. The acceleration in the automation market. We're going to have a fun >>Couple of days. Thanks for coming on here for David >>Lante. I'm Lisa Martin. We're going to be back live from Las Vegas at UI path forward for in just a minute.
SUMMARY :
the Bellagio in Las Vegas. but this is real live awesome to be working with you again. And to me it looked like there were at least out, if not more And we're going to dig into a lot of that. You mentioned some of the ones that are going to be on the program this week, including Chevron and Merck who And I think that's going to be the normal one. hybrid events and say, we want to be with our customers again and learn from you what you're doing, And the thing that UI path did that was different was And then all of a sudden, like you said, lightning in a bottle and What do you think that is? And the other thing is they've been profitable. And I will say this, and you know, And the last thing is this concern about competition Well, one thing that we know that's growing considerably is the total addressable market pre pandemic. Yeah, I think, you know, this is again, it's a really good question because when you look And the reason why I liked their strategy better is they're And by the way, he's getting, getting acquired by Vista, and they're gonna merge them with TIBCO company that, And so I think that UI path is less of a head-to-head competitor with, Some of the things that you can you think that we're going to hear, you know, seem to be at this inflection point where UI And I think you iPad has to show that Well, those two executives that you just mentioned, and a lot of others are going to be on the program. Couple of days. We're going to be back live from Las Vegas at UI path forward for in just a minute.
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MAIN STAGE INDUSTRY EVENT 1
>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.
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Have you ever wondered how we sequence the human genome, One of the things that, you know, both Cloudera and Claire sensor very and really honestly have a technological advantage over some of the larger organizations. A lot of the data you find or research you find health is usually based on white men. One of the things that we're concerned about in healthcare is that there's bias in treatment already. So you can make the treatments in the long run. Researchers are now able to use these technologies and really take those you know, underserved environments, um, in healthcare. provide the foundation to develop service center applications, sales reports, It's the era of smart but also the condition of those goods. biggest automotive customers are Volkswagen for the NPSA. And the real-time data collection is key, and this is something we cannot achieve in a classical data Finally, a data platform that lets you say yes, and digital business, but you think about it. And as such the way we use insights is also rapidly evolving. the full results they desire. Great to see you as well, Dave, Hey, so I call it the new abnormal, I finally managed to get some bag and to be able to show up dressed appropriately for you today. events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. What, what do you mean by hybrid data? So how in the heck do you get both the freedom and security You talked about security, the data flows are going to change. in the office and are not, I know our plans, Dave, uh, involve us kind of mint control of payment systems in manufacturing, you know, the pandemic highlighted America's we, uh, you know, at Cloudera I happened to be leading our own digital transformation of that type of work and the financial services industry you pointed out. You've got to ensure that you can see who just touched, perhaps by the humans, perhaps by the machines that may have led to a particular outcome. You bring it into the discussion, the hybrid data, uh, sort of new, I think, you know, for every industry transformation, uh, change in general is And they begin to deploy that on-prem and then they start Uh, w what, what do you want people to leave Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. Really thank you for your time. You bet Dave pleasure being with you. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the a data first strategy and accelerating the path to value and hybrid environments. And the reason we're talking about speed and why speed Thank you for joining us over the unit. chip company focused on graphics, but as you know, over the last decade, that data exists in different places and the compute needs to follow the data. And that's the kind of success we're looking forward to with all customers. the infrastructure to support all the ideas that the subject matter experts are coming up with in terms And just to give you context, know how the platforms to run them on just kind of the close out. the work they did with you guys and Chev, obviously also. Is it primarily go to market or you do an engineering work? and take advantage of invidious platform to drive better price performance, lower cost, purpose platforms that are, that are running all this ERP and CRM and HCM and you So that regardless of the technique, So the good news, the reason this is important is because when you think about these data intensive workloads, maybe these consumer examples and Rob, how are you thinking about enterprise AI in The opportunity is huge here, but you know, 90% of the cost of AI Maybe you could add something to that. You know, the way we see this at Nvidia, this journey is in three phases or three steps, And you still come home and assemble it, but all the parts are there. uh, you know, garbage in, garbage out. perform at much greater speed and efficiency, you know, and that's allowing us as an industry That is really the value layer that you guys are building out on top of that, And that's what keeps us moving forward. this partnership started, uh, with data analytics, um, as you know, So let's talk a little bit about, you know, you've been in this game So having the data to know where, you know, And I think for companies just getting started in this, the thing to think about is one of It just ha you know, I think with COVID, you know, we were working with, um, a retailer where they had 12,000 the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount the big opportunity is, you know, you can apply AI in areas where some kind of normalcy and predictability, uh, what do you see in that regard? and they'll select an industry to say, you know what, I'm a restaurant business. And it's that that's able to accurately So where do you see things like They've got to move, you know, more involved in, in the data pipeline, if you will, the data process, and really getting them to, you know, kind of unlock the data because they do where you can have a very product mindset to delivering your data, I think is very important data is a product going to sell my data and that's not necessarily what you mean, thinking about products or that are able to agily, you know, think about how can we collect this data, Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected So the telematics, you know, um, in order to realize something you know, financial services and insurance, they were some of the early adopters, weren't they? this elevator is going to need maintenance, you know, before a critical accident could happen. So ultimately you can take action. Thanks Dave. Maybe you could talk about your foundational core principles. are the signals that are occurring that are going to help them with decisions, create stronger value And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody um, uh, you know, just getting better insights into what customers need and when do they need it? I mean, where does, where do things like hybrid fit in? whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're to how you think about balancing practices and processes while at the same time activity and the way that you can affect that either in, you know, near time or Can I also get intelligence about the data to know that it's actually satisfying guidance as to where customers should start, where, you know, where can we find some of the quick wins a decision at that current point in the process, or are you collecting and technology and the roles they play in creating a data strategy. and I hate to use the phrase almost, but you know, the fuel behind the process, Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, ready to come, not just, you know, one month, two months, three months or a year from now, And you also have a chief digital officer who is participating the early, you know, beginners, the sort of fat middle, And I think, you know, also being data where, and, you know, trying to actually become, any advice that you have around creating and defining a data strategy. How do you maintain that memory of your business? Um, the gap between when you see you know, spreadsheets and PowerPoint presentations and lots of mapping to to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout
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Collibra Day 1 Felix Zhamak
>>Hi, Felix. Great to be here. >>Likewise. Um, so when I started reading about data mesh, I think about a year ago, I found myself the more I read about it, the more I find myself agreeing with other principles behind data mesh, it actually took me back to almost the starting of Colibra 13 years ago, based on the research we were doing on semantic technologies, even personally my own master thesis, which was about domain driven ontologies. And we'll talk about domain-driven as it's a key principle behind data mesh, but before we get into that, let's not assume that everybody knows what data measures about. Although we've seen a lot of traction and momentum, which is fantastic to see, but maybe if you could start by talking about some of the key principles and, and a brief overview of what data mesh, uh, Isabella of >>Course, well, they're happy to, uh, so Dana mesh is an approach is a new approach. It's a decentralized, decentralized approach to managing and accessing data and particularly analytical data at scale. So we can break that down a little bit. What is analytical data? Well, analytical data is the data that fuels our reporting as a business intelligence. Most importantly, the machine learning training, right? So it's the data, that's, it's an aggregate view of historical events that happens across organizations, many domains within organizations, or even beyond one organization, right? Um, and today we manage, uh, this analytical data through very centralized solutions. So whether it's a data lake or data warehouse or combinations of the two, and, uh, to be honest, we have kind of outsource the accountability for it, to the data team, right? It doesn't happen within the domains. Uh, what we have found ourselves with is, uh, central button next. >>So as we see the growth in the scale of organizations, in terms of the origins of the data and in terms of the great expectations for the data, all of these wonderful use cases that are, that requires access to that, unless we're data, uh, we find ourselves kind of constraints and limited in agility to respond, you know, because we have a centralized bottleneck from team to technology, to architecture. So there's a mesh kind of is that looks at the past what we've done, accidental complexity that we've kind of created and tries to reimagine a different way of, uh, managing and accessing data that can truly scale as this origins of the data grows. As they become available within one organization, we didn't want a cloud or another, and it links down really the approach based on four principles. Uh, so I so far, I haven't tried to be prescriptive as exactly how you implement it. >>I leave that to Elizabeth, to the imaginations of the users. Um, of course I have my opinions, but, but without being prescriptive, I think there are full shifts that needs to happen. One is, uh, we need to start breaking down the, kind of this complex problem of accessing to data around boundaries that can allow this to scale out a solution. So boundaries that are, that naturally fits into that model or domains, right. Our business domain. So, so there's a first principle is the domain ownership of the data. So analytical data will be shared and served and accountable, uh, by the domains where they come from. And then the second dimension of that is, okay. So once we break down this, the ownership of the database on domains, how can we prevent this data siloing? So the second principle is really treating data as a product. >>So considering the success of that data based on the access and usability and the lifelong experience of data analysts, data scientists. So we talk about data as a product and that the third principle is to really make it possible feasible. We need to really rethink our data platforms, our infrastructure capabilities, and create a new set ourselves of capabilities that allows domain in fact, to own their data in fact, to manage the life cycle of their analytical data. So then self-serve daytime frustration and platform is the fourth principle. And the last principle is really around governance because we have to think about governance. In fact, when I first wrote it down, this was like a little kind of concern in, in embedded in what some of my texts and I thought about, okay, now to make this real, we need to think about securing and quality of the data accessibility of the data at scale, in a fashion that embraces this autonomous domain ownership. So we have to think about how can we make this real with competition of governance? How can we make those domains be part of the governance, federated governance, federally, the competition of governance is the fourth principle. So at insurance it's a organizational shift, it's an architectural change. And of course technology needs to change to get us to decentralize access and management of Emily's school data. >>Yeah, I think that makes a ton of sense. If you want to scale, typically you have to think much more distributed versus centralized at we've seen it in other practices as well, that domain-driven thinking as well. I think, especially around engineering, right? We've seen a lot of the same principles and best practices in order to scale engineering teams and not make the same mistakes again, but maybe we can start there with kind of the core principles around that domain driven thinking. Can you elaborate a little bit on that? Why that is so important than the kind of data organizations, data functions as well? >>Absolutely. I mean, if you look at your organizations, organizations are complex systems, right? There are eight made of parts, which are basically domains functions of the business, your automation and your customer management, yourselves marketing. And then the behavior of the organization is the result of an intuitive, you know, network of dependencies and interactions with these domains. So if we just overlay data on this complex system, it does make sense to really, to scale, to bring the ownership and, um, really access to data right at the domain where it originates, right. But to the people who know that data best and most capable of providing that data. So to optimize response, to change, to optimize creating new features, new services, new machine learning models, we've got to kind of think about your call optimization, but not that the cost of global good. Right. Uh, so the domain ownership really talks about giving autonomy to the domains and accountability to provide their data and model the data, um, in a responsible way, be accountable for its quality. >>So no collect some of the empower them and localize some of those responsibilities, but at the same time, you know, thinking about the global goods, so what are they, how that domain needs to be accountable against the other domains on the mission? That's the governance piece covers that. And that leads to some interesting kind of architectural shifts, because when you think about not submission of the data, then you think about, okay, if I have a machine learning model that needs, you know, three pieces of the data from the different domains, I ended up actually distributing the computer also back to those domains. So it actually starts shifting kind of architectural as well. We start with ownership. Yeah, >>No, I think that makes a ton of sense, but I can imagine people thinking, well, if you're organizing, according to these domains, aren't gonna be going to grades different silos, even more silos. And I think that's where it second principle that's, um, think of data as a product and it comes in, I think that's incredibly powerful in my mind. It's powerful because it helps us think about usability. It helps us think about the consumer of that data and really packaging it in the right way. And as one sentence that I've heard you use that I think is incredibly powerful, it's less collecting, more connecting. Um, and can you elaborate on that a little bit? >>Absolutely. I mean the power and the value of the data is not enhanced, which we have got and stored on this, right. It's really about connecting that data to other data sets to aluminate new insights. The higher order information is connecting that data to the users, right. Then they want to use it. So that's why I think, uh, if we shift that thinking from just collecting more in one place, like whatever, and ability to connect datasets, then, then arrive at a different solution. So, uh, I think data as a product, as you said, exactly, was a kind of a response to the challenges that domain-driven siloing could create. And the idea is that the data that now these domains own needs to be shared with some accountability and incentive structure as a product. So if you bring product thinking to data, what does that mean? >>That means delighting the experience that there are users who are they, they're the data analysts, data scientists. So, you know, how can we delight their experience of their journey starts with a hypothesis. I have a question. Do I have right data to answer this question with a particular model? Let me discover it, let me find it if it's useful. Do I trust it? So really fascinated in that journey? I think we have two choices in that we have the choice of source of that data. The people who are really shouldn't be accountable for it, shrug off the responsibility and say, you know, I dumped this data on some event streaming and somebody downstream, the governance or data team will take care of a terror again. So it usable piece of information. And that's what we have done for, you know, half century almost. And, or let's say let's bring intention of providing quality data back to the source and make the folks both empower them and make them accountable for providing that data right at the source as a product. And I think by being intentional about that, um, w we're going to remove a lot of accidental complexity that we have created with, you know, labyrinth pipelines of moving data from one place to another, and try to build quality back into it. Um, and that requires, you know, architectural shifts, organizational shifts, incentive models, and the whole package, >>The hope is absolutely. And we'll talk about that. Federated computational governance is going to be a really an important aspect, but the other part of kind of data as a product next to usability is whole trust. Right? If you, if you want to use it, why is also trusts so important if you think about data as a product? >>Well, uh, I mean, maybe we turn this question back to you. Would you buy the shiniest product if you don't trust it, if you, if you don't trust where it comes from, can I use it? Is it, does it have integrity? I wouldn't. I think, I think it's almost irresponsible to use the data that you can trust, right. And the, really the meaning of the trust is that, do I know enough about this data to, to, for it, to be useful for the purpose that I'm using it for? So, um, I think trust is absolutely fundamental to, as a fundamental characteristics of a data as a product. And again, it comes back to breaching the gap between what the data user knows needs to know to really trust them, use that data, to find it, whether it's suitable and what they know today. So we can bridge that gap with, uh, you know, adding documentation, adding SLRs, adding lineage, like all of these additional information, but not only that, but also having people that are accountable for providing that integrity and those silos and guaranteeing. So it's really those product owners. So I think, um, it's just, for me, it's a non trust is a non-negotiable characteristic of the data as a product, like any other consumer product. >>Exactly. Like you said, if you think about consumer product, consumer marketplace is almost Uber of Amazon, of Airbnb. You have the simple rating as a very simple way of showing trust and those two and those different stakeholders and that almost. And we also say, okay, how do we actually get there? And I think data measure also talks a little bit about the roles responsibilities. And I think the importance overall of a, of a data product owner probably is aligned with that, that importance and trust. Yeah, >>Absolutely. I think we can't just wish for these good things happens without putting the accountability and the right roles in place. And the data product owner is just the starting point for us to stop playing hot potato. When it comes to, you know, who owns the data will be accountable for not so much. Who's the actual owner of that data because the owner of the data is you and me where the data comes really from, but it's the data product owner who's going to be responsible for the life cycle of this. They know when the data gets changed with consumers, meaning you feel as a new information, make sure that that gets carried out and maybe one day retire that data. So that long term ownership with intimate understanding of the needs of the user for that data, as well as the data itself and the domain itself and managing the life cycle of that, uh, I think that's a, that's a necessary role. >>Um, and then we have to think about why would anybody want to be a data product owner, right? What are the incentives we have to set up in the infrastructure, you know, in the organization. Um, and it really comes down to, I think, adopting prior art that exists in the product ownership landscape and bring it really to the data and assume the data users as the, as the customers, right. To make them happy. So our incentives on KPIs for these people before they get product on it needs to be aligned with the happiness of their data users. >>Yep. I love that. The alignment again, to the consumer using things like we know from product management, product owner of these roles and reusing that for data, I think that makes it makes a ton of sense. And it's a good leeway to talk a little about governance, right? We mentioned already federated governance, computational governance at we seeing that challenge often with our customers centralizing versus decentralizing. How do we find the right balance? Can you talk a little bit about that in the context of data mesh? How do we, how do we do this? >>Yeah, absolutely. I think the, I was hoping to pack three concepts in the title of the governance, but I thought that would be quite mouthful. So, uh, as you mentioned, uh, the kind of that federated aspects, the competition aspects, and I think embedded governance, I would, if I could add another kind of phrasing there and really it's about, um, as we talked about to how to make it happen. So I think the Federation matters because the people who are really in a position listed this, their product owners in a position to provide data in a trustworthy, with integrity and secure way, they have to have a stake in doing that, right. They have to be accountable, not just for their little domain or a big domain, but also they have to have an accountability for the mesh. So some of the concerns that are applied to all of the data front, I've seen fluid, how we secure them are consistently really secure them. >>How do we model the data or the schema language or the SLO metrics, or that allows this, uh, data to be interoperable so we can join multiple data products. So we have to have, I think, a set of policies that are really minimum set of policies that we have to apply globally to all the data products and then in a federated fashion, incentivize the data product owners. So have a stake in that and make that happen because there's always going to be a challenge in prioritizing. Would I add another few attributes? So my data sets to make my customers happy, or would I adopt that this standardized modeling language, right? They have to make that kind of continuous, um, kind of prioritization. Um, and they have to be incentivized to do both. Right. Uh, and then the other piece of it is okay, if we want to apply these consistent policies, across many data products and the mesh, how would it be physically possible? >>And the only way I can see, and I have seen it done in service mesh would be possible is by embedding those policies as competition, as code into every single data product. And how do we do that again, platform has a big part of it. So be able to have this embedded policy engines and whatever those things are into the data products, uh, and to, to be able to competition. So by default, when you become a data product, as part of the scaffolding of that data product, you get all of these, um, kind of computational capabilities to configure your, your policies according to the global policies. >>No, that makes sense. That makes, that makes it on a sense. That makes sense. >>I'm just curious. Really. So you've been at this for a while. You've built this system for the 13 years came from kind of academic background. So, uh, to be honest, we run into your products, lots of our clients, and there's always like a chat conversation within ThoughtWorks that, uh, do you guys know about this product then? So and so, oh, I should have curious, well, how do you think data governance tehcnology then skip and you need to shift with data mesh, right. And, and if, if I would ask, how would your roadmap changes with database? >>Yeah, I think it's a really good question. Um, what I don't want to do is to make, make the mistake that Venice often make and think of data mesh as a product. I think it's a much more holistic mindset change, right? That that's organization. Yes. It needs to be a kind of a platform enablement component there. And we've actually, I think authentically what, how we think about governance, that's very aligned with some of the principles and data measures that federate their thinking or customers know about going to communities domains or operating model. We really support that flexibility. I think from a roadmap perspective, I think making that even easier, uh, as always kind of a, a focus focus area for us, um, specifically around data measures are a few things that come to mind. Uh, one, I think is connectivity, right? If you, if you give different teams more ownership and accountability, we're not going to live in a world where all of the data is going to be stored on one location, right? >>You want to give people themes the opportunity and the accountability to make their own technology decisions so that they are fit for purpose. So I think whatever platform being able to really provide out of the box connectivity to a very wide, um, area or a range of technologies, I think is absolutely critical, um, on the, on the product as a or data as a product, thinking that usability, I think that's top of mind, uh, that's part of our roadmap. You're going to hear us, uh, stock about that tomorrow as well. Um, that data consumer, how do we make it as easy as possible for people to discover data that they can trust that they can access? Um, and in that thinking is a big part of our roadmap. So again, making that as easy as possible, uh, is a, is a big part of it. >>And, and also on the, I think the computation aspect that you mentioned, I think we believe in as well, if, if it's just documentation is going to be really hard to keep that alive, right? And so you have to make an active, we have to get close to the actual data. So if you think about a policy enforcement, for example, some things we're talking about, it's not just definition is the enforcement data quality. That's why we are so excited about our or data quality, um, acquisition as well. Um, so these are a couple of the things that we're thinking of, again, your, your, um, your, your, uh, message around from collecting to connecting. We talk about unity. I think that that works really, really well with our mission and vision as well. So mark, thank you so much. I wish we had more time to continue the conversation, uh, but it's been great to have a conversation here. Thank you so much for being here today and, uh, let's continue to work on that on data. Hello. I'm excited >>To see it. Just come to like.
SUMMARY :
Great to be here. I found myself the more I read about it, the more I find myself agreeing with other principles So it's the data, that's, it's an aggregate view of historical events that happens in agility to respond, you know, because we have a centralized bottleneck from team to technology, I leave that to Elizabeth, to the imaginations of the users. some of my texts and I thought about, okay, now to make this real, we need to think about securing in order to scale engineering teams and not make the same mistakes again, but maybe we can start there with kind Uh, so the domain ownership really talks about giving autonomy to the domains and And that leads to some interesting kind of architectural shifts, because when you think about not And as one sentence that I've heard you use that I think is incredibly powerful, it's less collecting, data that now these domains own needs to be shared with some accountability shouldn't be accountable for it, shrug off the responsibility and say, you know, I dumped this data on some event streaming aspect, but the other part of kind of data as a product next to usability is whole So we can bridge that gap with, uh, you know, adding documentation, And I think data measure also talks a little bit about the roles responsibilities. of the data is you and me where the data comes really from, but it's the data product owner who's What are the incentives we have to set up in the infrastructure, you know, in the organization. The alignment again, to the consumer using things like we know from product management, So some of the concerns that are applied to all of the data front, Um, and they have to be incentivized to do both. So be able to have this embedded policy engines That makes, that makes it on a sense. So and so, oh, I should have curious, the principles and data measures that federate their thinking or customers know about going to communities domains or operating of the box connectivity to a very wide, um, area or a range of technologies, And, and also on the, I think the computation aspect that you mentioned, I think we believe in as well, Just come to like.
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Intermission 1 | DockerCon 2021
>>Hey, everyone. I want to welcome you back. This is our intermission. And let me tell you what a morning we've had for those of you that don't know. I'm, Hayma Ganapati, I'm in product marketing at Docker. And I would just want to quote, actually someone who was in one of the chat rooms and this, I think encapsulates exactly how I feel today, because this is my first Docker con and the quote was from. And he said, I feel like a kid in an ice cream store where I don't know which flavor to choose. I want to go to all of the sessions and I got to tell you that's how I felt. And, you know, um, I want to just do some specific call-ups. Um, first of all, Dana way to keep it real in your interview. I love the cube interview. If you miss that, um, it was really great. >>She talks a lot about, uh, CI CD pipeline and you know, what to do with GoodHub. It was great. Um, I also want to say that I was, uh, slipping back and forth between the community rooms and way to go Brazil obrigado until all of the people who participate in the Brazil room, we had about 250 plus people in that room. And the, the chat window was just going crazy and in the French community room, Vive left hall. So if you've a uncle funny, uh, we had about 150 plus people in that room. So I just want to say that, you know, we've been seeing a lot of participation and I just want to thank everyone for attending and for participating on people have been so kind in the chat rooms, we just want to remind you to stay kind, you know, presenters put a lot of effort into their presentations, so just, you know, offer some positive and supportive critique to them. >>And the other thing I want to mention is all of the countries that we're seeing, all of the participation. So I'm just going to call out a few. We have people from the Netherlands, from Canada, from South Africa, Akron, Ohio, Belgium, Austria, yeah, Ecuador, New Zealand. And he cut up Westchester. Like, I mean, it just goes list goes on and on and on. And I think this really speaks to the power of Docker community. And it's a real testimony to how people from all over the world are in love with Docker technology and are excited to be here. And so I just wanted to thank everyone again and want to remind you that we want to leverage the power of community. And we have a fundraising campaign going on to help, uh, people who are affected by COVID. And you know, some of our big communities, especially in India and Brazil are, have been really affected by COVID. >>So we're asking you to contribute and we'd really like you to participate. Um, we have, uh, the, the link you can see here, Docker donates, you can tweet about it and would love to see the numbers go up for those donations, because, you know, I've personally been affected, had some family members pass away from COVID in India, and I'm sure other people may have stories that firsthand or secondhand. So please do that and let's show what the power of Docker community can do. And before I hand over to, to Peter, I'm just going to read out some of the tweets we've been getting, okay, this Brett and Peter, these are great. Uh, one of the, one of the tweets said dev environments is one of the most exciting features in the past few years. Super excited to try this out. Great, great, great tweet. Yeah. >>I agree to, um, another loving the content that was not your tweets. You can, you can slip me the 20 bucks later. Um, there's another tweet that says loving the content from hashtag Docker con so far fascinating use cases and interesting progress and future directions love that. And then there's another one I'm trying to find it here. Uh, I've been waiting for this so long Docker builds now work on Intel and M one. So keep those tweets coming. We love getting this kind of feedback and we love reading the chat room. So, um, Peter, you know, I attended your, your panel and I love that we were talking about a security and that moving, moving it left. So how did that go for you? >>Uh, it was, it was, uh, it was extremely fun. And for those that are, uh, I think my parents might be watching, so they probably watched it and were like, w this is the most boring thing I've ever seen, but, um, you know, you get a bunch of geeks and, uh, Brett has told me I should use geek instead of nerd, but I, I liked, uh, geek. So you get a bunch of geeks talking about security and coding and, um, what, what, what containers actually are, what vulnerabilities are. Yeah, it was, it was extremely fun. The panel was fantastic. They were very engaging the chat. I mean, I couldn't keep up with the chat. Right. It would just kept flying by, uh, luckily I had a helper to pull off questions, but, um, yeah, it's super exciting. You can, I know we're all remote, but you can just feel that energy, right. It was, it was great. It was great. Yeah. Yeah, for sure. It's super >>Connected. I felt that with your panel to Brett as well, sorry to talk over you there, but yeah. How did, how did it go for you? I, there was a lot of engagement in your session. >>Uh, ditto, like it was just, uh, there was so many questions. We only got to get a fraction of them. I tried to pick themes because, uh, when you talk about continuous testing and integration and all the things that take a part of that, um, you, you end up with lots of, well, what I like is the discussion around opinions, because so much of these pipelines from code on your machine, into production and everything in between, it's really, uh, it's a culture. It turns out to be the description of your culture and how you all perceive testing, how you, what you value in testing. And so that really started to come out as a theme, um, throughout that show. And we, we ran at a time. I was also watching Peters and it was fantastic, but like you think an hour is enough time to cover a topic, but it's just tipping tip of the iceberg kind of stuff. So I think it was super helpful. I learned some things, um, I really enjoyed watching Peters and, uh, yeah, can't wait for the next one. There's >>More than that. And likewise, great. I mean, I know, I know we're w maybe we pat chose it, but it, it was, it was super exciting to watch your panel. They were very Nikos, one of my favorite people in the world, uh, a fellow Austinite, but, um, yeah, I love that too. How you, uh, you were talking about opinions right. And playing off each other. It's, it's always interesting to hear smart people, uh, how they think, right. Yeah. I learned from how they think, right. Yeah. A hundred percent. >>So, all right. So we're, we're, um, what's next? Like, we, we gotta keep this thing going, so I've got to remember that. >>I want to, so I want to talk a bit about some of the panels that are, or the sessions that are coming up and just want to remind people that happened this afternoon. I'm all about use cases. You know, I was a developer for many decades, and it's great to hear how other developers are using the tools. But, uh, as a developer, I always wanted to know how are, what are the end user applications? And so we have two exciting sessions at 1:00 PM. We have sneak and red ventures, and they're going to be talking about how they used Docker containers. The title of the, uh, uh, session is great. An ounce of prevention, curing, insecure, container images. So check that out. And we also have another one at one 30 with Massimo, from AWS and Dexter Legaspi from Sirius XM. And they're going to be talking about a real world application using Docker containers. So I really want you to, to encourage you to attend those. >>Yeah. Um, can I say one really quick? Cause I'm Sue and a shout out to Eric Smalling. He's giving the red ventures talk with our partners. He's awesome. Go check out his, uh, but I'm really excited about Matt. Jarvis's sneak talk around. Uh, I think we might've talked about it earlier. My container image has 500 vulnerabilities vulnerabilities now what, right. I mean, I think as developers, as we're coming into this and dev ops and everybody right. You scan and then you see all these vulnerabilities just shoot by. And you're like, well, what do I do? So Matt, Matt will be addressing that. And he is fantastic. I can go on. There's a bunch of them. >>Yeah. There's a whole bunch of coming up and right up after this, I'm on a live stream with a bunch of panels on get ops. And then after that, Peter will be back. And so stay tuned and thanks for watching during the intermission. And we'll see you soon. >>I'm also leading the women in tech panel attend that. Don't forget to do that. >>Absolutely. Yep. All right. Ciao. Ciao >>For me like my first, oh, I get it about Docker was when I used a SQL server container on my neck book for the first time >>Being able to install Docker desktop, which was the first thing that I did and be able to build this without worrying about any of my software versions that I currently had on my machine. It was >>Awesome. One of the things, because I love the most about Docker is because I write books and I do video training courses to help a lot of people take their first steps with Docker and containers and to get a connection with those people and for them to come back to me and say, do you know what this is so cool, so easy, and it's going to change both my job. And, but also my organization, my team, all of that kind of stuff, change the experience that our customers have with our applications and what our business really puts a smile on my face. If >>You want to use containers, then Docker is the first toys, especially with tools like the mark Docker, compose, you can, uh, easily do your day-to-day job as a developer, or even if you're an ops person, then there are the books of the cloud and other things. So yeah, the idea is that we can go the simplicity one simple task, uh, to, uh, Daugherty mate and make that reuse as many times. Uh, that is one of the cool things I like about my >>Favorite part about Docker is using it as a developer tool. I using Docker desktop, really easy to install, really easy to run. >>Every time I come back to DACA, I love the simplicity of the way that it works, especially on things like security, which I find frustrating and hard. It's just done so seamlessly. And so my favorite thing about DACA is not just that it changed the world in the way that we develop in and ship and build applications and put that. It's just so easy that even the guy, like, I think >>It really is all about finding that aha moment, that hook where Docker really makes sense to you because once you have that moment, then all of a sudden, you, you know, you are on your way to being a Docker power user. >>We need for people to understand this technology better before they can, uh, actually dive deep into that. And Docker makes it easier to explain things, to explain the concept of containers, to explain how containers will work, how you can split your environments, how you can, uh, standardize all your pipelines and so on. It's important that we also take the time to help other people. And I think it's very important that we also give back and that's part of the motto of open sources. How do we give back to other people and how we help other people learn? And I think that's what I'm really passionate about. This whole thing is continuing, uh, giving back to the community. I just >>Hope and has fun at Docker con. And I know that there's a lot of great speakers coming and I will be watching the talks, even though they're happening at 3:00 AM and in my local time zone, um, I'm pretty excited to watch and, uh, hopefully watch more than later on streaming or YouTube or wherever they're going to be. So I hope everyone has fun and learn something and yeah, I don't see how you couldn't have fun.
SUMMARY :
I want to welcome you back. She talks a lot about, uh, CI CD pipeline and you know, what to do with GoodHub. And I think this really speaks to So we're asking you to contribute and we'd really like you to participate. I agree to, um, another loving the content that was not your tweets. thing I've ever seen, but, um, you know, you get a bunch of geeks and, I felt that with your panel to Brett as well, sorry to talk over you there, And so that really started to come out as a theme, um, throughout that show. And likewise, great. So we're, we're, um, what's next? So I really want you to, to encourage you to attend those. You scan and then you see all these vulnerabilities just shoot by. And we'll see you soon. I'm also leading the women in tech panel attend that. Being able to install Docker desktop, which was the first thing that I did and be able to to get a connection with those people and for them to come back to me and say, do you know what this the mark Docker, compose, you can, uh, easily do your day-to-day job as a developer, really easy to install, really easy to run. It's just so easy that even the guy, like, I think really makes sense to you because once you have that moment, And I think it's very important that we also give back and that's part of the motto of open sources. And I know that there's a lot of great speakers coming and I
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Io-Tahoe Episode 6: ActiveDQ™ Intelligent Automation for Data Quality Management promo 1
>>The data Lake concept was intriguing when first introduced in 2010, but people quickly realized that shoving data into a data Lake may data Lake stagnant, repositories that were essentially storage bins that were less expensive than traditional data warehouses. This is Dave Vellante joined me for IO. Tahoe's latest installment of the data automation series, active DQ, intelligent automation for data quality management. We'll talk to experts from snowflake about their data assessment utility from within the snowflake platform and how it scales to the demands of business. While also controlling costs. I have Tahoe CEO, AIG Hora will explain how IO Tahoe and snowflake together are bringing active DQ to market. And what the customers are saying about it. Save the date Thursday, April 29th for IO Tahoes data automation series active DQ, intelligent automation for data quality show streams promptly at 11:00 AM Eastern on the cube, the >>In high tech coverage.
SUMMARY :
the snowflake platform and how it scales to the demands of business.
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CoC Promo 1 11
>> It took a global pandemic for the world to realize an inescapable truth about cloud computing. It's a journey, not a destination. It's a mental model and a mindset. This is Dave Vellante, inviting you to join me on Thursday June 21st for "theCUBE" on cloud. Look if 2020 was about jumping onto the cloud, bandwagon for many firms, 2021 will be about navigating through the cloud landscape and exploring the opportunities presented by edge computing, AI, multi-cloud and serverless along the way. On January 21st "theCUBE" will bring together CXOs, practitioners, technologists, CIOs, analysts, to understand the future of cloud. Tapping the expertise, knowledge, and independent voices from "theCUBE" community. Registration is free. Mark your calendars for "theCUBE" on cloud January 21st. You're watching "theCUBE," the global leader in digital high-tech coverage.
SUMMARY :
for the world to realize
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