(gentle music) >> Good afternoon, cloud community and welcome back to fabulous Las Vegas, Nevada. We are at AWS re:Invent. It's our fourth day, it's in the afternoon. We've got two more segments left. This is a serious marathon, but it's so exciting, it's kept my brain super curious. I'm Savannah Peterson, joined by Paul Gillan today. Paul- >> Hello Savannah. >> Are you as excited about how much we've learned this week as I am? >> I am. It's just taking, my mind is just bursting with all the new information I've absorbed over the last three days. Amazing talking to all these smart people. >> It has really been so cool. >> And learning about all the permutations that we to think about cloud but there are so many businesses that have been built around the cloud, around making the cloud easier to use, supporting cloud as our next guest can talk about, that there's this whole ecosystem element that we don't hear about so much, but it's very much the foundation of the people who are here. >> Speaking of ecosystem, our next guest, please welcome Garrett to the show. Runs Ecosystem for Console Connect. How you doing Eric? >> I'm doing very well. >> Savannah: Garrett, sorry. Excuse me. >> No worries. >> Few names on the show today. >> Garrett: I'm sure. >> I do know your name, my mouth just doesn't want to, just doesn't want to participate today. Have you had a great show so far? >> It's been fantastic. You know, the AWS re:Invent show has always been a fantastic event, so. >> You're a veteran. You're also a CUBE alumni, which is great. >> Yes. Thank you for having me back. Thank you for your time. I most appreciated it. >> Yeah. We love having you. It's going to be great. We'll, we'll try and do even better each time we have you on the show. So just in case those listening are unfamiliar with Console Connect, give us the pitch. >> Okay, so Console Connect is our software defined interconnect platform. We also provide what we call network as a service. This allows our customers and partners to take advantage of our global private network on a pay as you go basis. Scalable and flexible. When you're not using the service, you can turn it off. So you only pay as you go. >> What a novel idea. >> Yes, yes. In the past you would have to have a year or multi-year contract. So we're making our services match cloud offerings around the world. The platform itself is in more than a thousand data centers all around the globe. >> Savannah: Just a couple. >> Yes, just a few. We have about 45 terabits of network behind it. It's all on our private network, so none of it's accessible via the public internet and we have a meeting place which allows our existing customers and partners to reach out across the platform and share services. So one customer needs to subscribe to another customer services, they can do so right across the platform on a pay as to go basis. So it's been very exciting for us. It's been very fast, it seems to me, for the past five or six years that we've had the service. >> At what point in their cloud journey do customers typically realize they need a service like yours? If the bandwidth they're getting, their native bandwidth they're getting is insufficient. >> Yeah, and I think that's a great question. I think the customers themselves have seen a serious disconnect between their direct connections to the cloud service providers where the cloud service providers are billing by the minute. And a traditional telecommunications connection is built by the year or multi years and then you really lose control over your cloud connection when you forget about it, right? Because service is always up. The connection's always up. >> Yeah. >> And a lot of individuals in a company may have access to the cloud, that cloud service, provider service. And next thing you know, you have a runaway group of services that are running that you're paying for and you don't really realize it 'cause the connection's up, you've already paid the connection the cloud service is up, you've already paid for it. >> So how do businesses get better control over that spend or how do you help them? >> Yeah, so how we help them is our service is able to be turned off when it's not in use. So in the event that you don't need the service over a weekend or over a month, you can just turn it off and you're not paying for that. >> It sounds so simple but it actually is kind of revolutionary in the industry which is why I keep coming back to it. It's great. So we've heard a lot about hybrid cloud, multicloud. How is this increasing the complexity for customers? >> Well I think the complexity for customers has increased due to the fact that you have a multicloud requirement or you have multiple teams accessing your cloud service provider and there's no one really managing it from a central perspective. >> Savannah: They can definitely get siloed really easy. >> Yeah, and then it runs away from you and the next thing you know, you start to look at the monthly bills. But generally that happens on an annual basis. If any companies like mine, you're doing your annual reconciliation of your bills and that's when you notice something's not right. >> Yeah, definitely. I can actually see a Slack message I got once, multiple times probably. Is anyone using this service? Why does it cost us that? That's exactly what you're talking about. >> Do you integrate with the Amazon Management Console or is it a separate service? >> It's, our service is a separate service. We are APId in with AWS. You do have a single console from our platform to manage your connections to the cloud. And then once you are connected in, you would still need to use the AWS console to manage your service. They're very, let's just say no one is offering a remote console third party console yet for AWS or any other cloud service for that matter. >> How about for hybrid cloud is obviously the way, you know, the way the industry is going. How do you enable companies to manage their hybrid cloud environments more intelligently? >> Yeah, and that's another great question. We allow that, you know, we're a global company. We have global access around the world. It includes not only traditional telecommunication services but also includes satellite service as well as 5G and LTE capability to the platform. So in the event that someone is in a hyper cloud situation, they have a lot of capability to enable their services. >> You talked about network as a service, and I, we haven't had a chance to dig into it. So tell me a little bit more. How does, how can this help reduce egress charges? How, are people excited when they hear network as a service? Where are we off at on that hype curve? >> Yeah, I think it's low on the excitement scale. >> Savannah: Yeah. >> You know, network has become somewhat of a commodity in the world, like electricity or water, you know, for the most of the world. And so network as a service, what it has enabled is it has enabled the customers more control over what they're doing. 'Cause in the past, you would need weeks, if not months to get services installed. And then if you needed to make a change to that service to increase it or decrease it in accordance to your requirements, that might take a couple of days at the soonest and you know, the Console Connect platform now changed that down to a few minutes. So within a few minutes, you can enable services, turn it up, turn it down, scale up, scale down. >> Savannah: Talk about time to value. >> There's no equipment installation required? >> No, it is our private network and so there must be a direct connection to it. It's not available over the public internet. Generally, a customer will connect to us via a cross connect at a data center or they can bring in a local loop. Or our existing customers, we just flip a little switch, so to speak, software wise, and we give them access to the platform from their existing services. >> Do you work with co-location interconnects as well? >> Exactly, yes. And in fact, you can purchase those services across our platform with a lot of the co-location service providers. >> So if I'm already using a co-lo, I can deploy your service directly from that co-lo. >> Yes. Yes. >> That's very convenient. >> That is very convenient. (laughs) >> You also mentioned the ability interconnect between customers. So your customers can actually connect to each other and conduct transactions or integrate their applications. Talk about how that works. >> Yeah, so for instance, let's say you are a customer that's taking advantage of our platform and you find your network is under a DDoS attack. You can go into our meeting place, connect to one of our cloud service providers who specializes in DDoS mitigation, spin up a connection to them within a few minutes, and immediately, you can start taking care of your DDoS problem. And once it's taken care of, you turn it down. Now those types of services that are subscription based are via API into our platform so we can settle the bill for our customer on behalf of that service provider or the service provider themselves can bill that customer depending on how they want to set it up. So it's very flexible. >> It's really clever, too. I mean, especially in an instance like you just mentioned in that example, that's a moment of panic and high stress and high tension. The last thing you want to be thinking about is what's the right service provider? How quickly can I get this up and running? If I can just couple clicks, couple lines of code perhaps, or even just through the portal, be able to do it, it's pretty powerful. You mentioned that Console Connect, and I want to talk about this 'cause it's clear you care about the user experience, the community and Console Connect came out of LinkedIn DNA and you mentioned there's a social component to the platform as well. Can you tell me a little bit more about that? >> Yes, thank you for that. Yeah, so you can, as a customer or a partner, you can market directly to others on the platform using our meeting place. And you have the ability to reach out directly to people across the platform, send them a message. You have the ability to post articles, blog in one of our sections. And then the other one, you can actually go in and see all the latest activity in the platform. You can see who's the newest companies to join Console Connect. >> Savannah: Oh wow, cool. >> How do I reach out to them? And then that gives you the ability to begin either marketing across the platform or direct marketing to someone or directly just reach out and connect with them and say hey, we want to set a bilateral partnership with you. You know, how do we do that? So it's very flexible. >> Savannah: Yeah. >> Can I connect my systems to others? So if I want to plug into their eCommerce system so I can fulfill orders taken through their eCommerce system, can I enable that kind of connection? >> Oh, we're not there yet. It is coming, but we're just not there yet. >> What are the complexities? >> A lot of that is a trust issue. >> Yeah. >> You know, when you're dealing with across the globe, there are regulations in every location that must be adhered to. A lot of that is security and privacy related. And we must make sure that we are adhering to all the local regulations wherever we are. >> So it's not the technology, it's a problem, really. It's the- >> It's a regulatory issue, yeah. So the technology is there and I would say that the rest is following, it's just, it's slow when you're dealing with permits and with compliance. >> I also want to ask you, our notes here mention egress charges, which are a niggling pain point for a lot of customers. They have to pay to get their data of the cloud. How do you help with that problem? >> So how we help with this is first, we get a discount from our partners, our cloud partners, including AWS, and we pass that on to the customers. The other way is you have a full visibility of which connections you have live into those partners and you can manage that much easier through the single, I would say view. Of all of your connections. >> Savannah: Yeah. >> You can see all of your cloud connections right in the one view. And then you can do a little more digging and say are we using these, you know? Because a lot of times, you have projects that spin up and then someone forgets to spin them back down. So this helps give you that single view. But again, we get the discount that we are happy to pass on as well. >> Which is a win-win for everyone. I've using a tab analogy all show, we all we want it in one place, one tab, not all the tabs. >> Yes. I think network management and service management in any enterprise or partnership company is a real drain on resources. >> Oh yeah. And it's a waste of money. >> Garrett: Yeah. And if you're not managing correctly, yeah, you get the thing on the money. >> Are you an alternative to the direct connect services from the major cloud providers or are you a compliment to them? >> We're not competing with them, we're partnered. And so we don't see ourselves as an alternative. A lot of times, our customers come to us and they want to direct connect in a location where perhaps AWS isn't. >> Paul: Doesn't have a point of presence. >> Exactly. Right. We give them that flexibility of, yes you can directly connect here. And then the other approach that we like to take is we like to give our customers the choice of not only data center, but also region. So a lot of times egress charges are can be calculated across regions as well and that can really add up for our customer. Whereas if you have multiple egress locations, you're not transferring data across a region on the AWS platform or another cloud service platform. You can egress at that location and then take it across your own network or take it across our network and then your egress charges will be more reasonable. >> That's, it's convenient. Smart! You're making people's jobs optimized and easier as well as their stack and all the tools that they're using. It's fantastic. All right Garrett, we've got a new challenge here on theCUBE at re:Invent. >> Garrett: All right. >> It's probably different from the last time you were on theCUBE. We're looking for your 30 second hot take, your thought leadership moment. What's the biggest theme coming out of the show or for you as we look into 2023? >> Well, for in 30 seconds- >> Savannah: Yeah, casual, right? >> No pressure. >> Savannah: No big deal. >> No, so with Console Connect, you know, we are around the globe. I know that a lot of companies at AWS are, some are regional, some are global. And we have the ability to cover both. We can do either regional or global or a hybrid of those. We also have a hybrid approach on different types of services. And so the flexibility, scalability, reliability, and the lowered cost of egress with Console Connect is a win all around. You can't lose with it. >> I love it. You're meeting customers where they are. Garrett, it was fantastic to have you back on theCUBE. We look forward to your third cameo. >> Thank you very much. I appreciate your time. Thank you for having Console Connect on. >> Hey, absolutely. We look forward to continuing to watch and hopefully tell that story as well. And thank all of you for tuning in to day four of AWS's re:Invent coverage in Las Vegas, Nevada. I'm starting to forget my own name. I am with Paul Gilland. I'm Savannah Peterson. This is theCUBE. We are the leading source for high tech coverage. (gentle music)

>> Good afternoon everyone, and welcome back to theCUBE where we're coming to you live from Detroit, Michigan at KubeCon and Cloud Native Con. We're going to keep theCUBE puns coming this afternoon because we have the pleasure of being joined by not one but two guests from Kubiya. John Furrier, my wonderful co-host. You're familiar with these guys. You just chatted with them last week. >> We broke the story of their launch and featured them on theCUBE in our studio conversation. This is a great segment. Real innovative company with lofty goals, and they're really good ones. Looking forward to it. >> If that's not a tease to keep watching I don't know what is. (John laughs) Without further ado, on that note, allow me to introduce Amit and Shaked who are here to tell us all about Kubiya. And I'm going to blow the pitch for you a little bit just because this gets me excited. (all laugh) They're essentially the Siri of DevOps, but that means you can, you can create using voice or chat or any medium. Am I right? Is this? Yeah? >> You're hired. >> Excellent. (all laugh) >> Okay. >> We'll take it. >> Who knows what I'll tell the chat to do or what I'll, what I will control with my voice, but I love where you're. >> Absolutely. I'll just give the high level. Conversational AI for the world of DevOps. Kind of redefining how self-service DevOps is supposed to be essentially accessed, right? As opposed to just having siloed information. You know, having different platforms that require an operator or somebody who's using it to know exactly how they're accessing what they're doing and so forth. Essentially, the ability to express your intent in natural language, English, or any language I use. >> It's quite literally the language barrier sometimes. >> Precisely. >> Both from the spoken as well as code language. And it sounds like you're eliminating that as an obstacle. >> We're essentially saying, turn simple, complex cast into simple conversations. That's, that's really what we're saying here. >> So let's get into the launch. You just launched a fresh startup. >> Yeah, yeah, yeah. >> Yeah. >> So you guys are going to take on the world. Lofty goals if that. I had the briefing. Where's the origination story come from? What, how did you guys get here? Was it a problem that you saw, you were experiencing, an itch you were scratching? What was the motivation and what's the origination story? >> Shaked: So. >> Amit: Okay, go first please. >> Essentially everything started with my experience as being an operator. I used to be a DevOps engineer for a few years for a large (indistinct) company. On later stages I even managed an SRE team. So all of these access requires Q and A staff is something that I experience nonstop on Slack or Teams, all of these communication channels. And usually I find out that everything happens from the chat. So essentially back then I created a chat bot. I connect this chat bot to the different organizational tools, and instead of the developers approaching to me or the team using the on call channel or directly they will just approach the bot. But essentially the bot was very naive, and they still needed to know what they, they want to do inside the bot. But it's still managed to solve 70% of the complexity and the toil on us as a team so we could focus on innovation. So Kubiya's a more advanced version of it. Basically with Kubiya you can define what we call workflows, and we convert all of these complexity of access request into simple conversations that the end users, which could be developers, but not only, are having with a DevOps team. So that's essentially how it works, and we're very excited about it. >> So you were up all night answering the same question over and over again. (all laugh) And you said, Hey, screw it. I'm going to just create a bot, bot myself up. (Shaked laughs) But it gets at something important. I mean, I'm not just joking. It probably happened, right? That was probably the case. You were up all night telling. >> Yeah, I mean it was usually stuff that we didn't need to maintain. It was training requests and questions that just keep on repeating themselves. And actually we were in Israel, but we sell three different time zones of developers. So all of these developers, as soon as the day finishes in Israel, the day in the US started. So they will approach us from the US. So we didn't really sleep. (all laugh) As with these requests non-stop. >> It's that 24 hour. >> Yeah, yeah. 24 hours for a single team. >> So the world clock global (indistinct) catches you a little sometimes. Yeah. >> Yeah, exactly. >> So you basically take all the things that you know that are common and then make a chat bot answering as if you're you. But this brings up the whole question of chat bot utilization. There's been a lot of debate in the AI circles that chat bots really haven't made it. They're not, they haven't been good enough. So 'cause NLP and other trivial, >> Amit: Sure. or things that haven't really clicked. What's different now? How do you guys see your approach cracking the code to go that kind of reasoning level? Bots can reason? Now we're in business. >> Yeah. Most of the chat bots are general purpose, right? We're coming with the domain expertise. We know the pain from the inside. We know how the operators want to define such conversations that users might have with the virtual assistant. So we combined all of the technical tools that are needed in order to get it going. So we have a a DSL, domain specific language, where the operators can define these easy conversations and combine all of the different organizational tools which can be done using DSDK. Besides this fact, we have a no code, for less technical people to create such workflows even with no code interface. And we have a CLI, which you could use to leverage the power of the virtual assist even right from your terminal. So that's how I see the domain expertise coming in that we have different communication channels for everyone that needs to be inside the loop. >> That's awesome. >> And I, and I can add to that. So that's one element, which is the domain expertise. The other one is really our huge differentiator, the ability to let the end users influence the system itself. So essentially. >> John: Like how? Give me an example. >> Sure. We call it teach me feature, but essentially if you have any type of a request and the system hasn't created an automation or hasn't, doesn't recognize it, you can go ahead and bind that into your intent and next time, and you can define the scope for yourself only, for the team, or even for the entire organization that actually has to have permission to access the request and control and so on. >> Savannah: That's something. Yeah, I love that as a knowledge base. I mean a custom tool kit. >> Absolutely. >> And I like that you just said for the individual. So let's say I have some crazy workflows that I don't need anybody else to know about. >> 100 percent. >> I can customize my experience. >> Mm hmm. >> Do you see your, this is really interesting, and I'm, it's surprising to me we haven't seen a lot of players in this space before because what you're doing makes a lot of sense to me, especially as someone who is less technical. >> Yeah. >> Do you view yourselves as a gateway tool for more folks to be involved in more complex technology? >> So, so I'll take that. It's not that we haven't seen advanced virtual assistants. They've existed in different worlds. >> Savannah: Right. >> Up until now they've existed more in CRM tools. >> Savannah: Right. >> Call centers, right? >> Shaked: Yeah. >> You go on to Ralph Lauren, Calvin Klein, you go and chat with. Now imagine you can bring that into a world of dev tools that has high domain expertise, high technical amplitude, and now you can go and combine the domain expertise with the accessibility of conversational AI. That's, that's a unique feature here. >> What's the biggest thing that's surprised you with the launch so far? The reaction to the name, Kubiya, which is Cube in Hebrew. >> Amit: Yes. >> Apparently. >> Savannah: Which I love. >> Which by the way, you know, we have a TM and R on our Cube. (all laugh) So we can talk, you know, license rights. >> Let's drop the trademark rules today, John, here. We're here to share information. Confuse the audience. Sorry about that, by the way. (all laugh) >> We're an open source, inclusive culture. We'll let it slide this time. >> The KubeCon, theCUBE, and Kubiya. (John laughs) In the Hebrew we have this saying, third time we all have ice cream. So. (all laugh) >> I think there's some ice cream over there actually. >> There is. >> Yeah, yeah. There you go. >> All kidding aside, all fun. What's, what's been the reaction? Got some press coverage. We had the launch. You guys launched with theCUBE in here, big reception. What's been the common feedback? >> And really, I think I expected this, but I didn't expect this much. Really, the fact that people really believe in our thesis, really expect great things from us, right? We've starting to working with. >> Savannah: Now the pressure's on. >> Rolling out dozens of POCs, but even that requires obviously a lot of attention to the detail, which we're rolling out. This is effectively what we're seeing. People love the fact that you have a unique and fresh way to approaching the self-service which really has been stalled for a while. And we've recognized that. I think our thesis is where we. >> Okay, so as a startup you have lofty goals, you have investors now. >> Amit: Yeah. >> Congratulations. >> Amit: Thank you. >> They're going to want to keep the traction going, but as a north star, what's your, what are you going to, what are you going to take? What territory are you going to take? Is it new territory? Are you eating someone's lunch? Who are you going to be competing with? What's the target? What's the, what's the? >> Sure, sure. >> I'm sure you guys have it. Who are you takin' over? >> I think the gateway, the entry point to every organization is a bottleneck. You solve the hard problem first. That's where you can go into other directions, and you can imagine where other operational workflows and pains that we can help solve once we have essentially the DevOps. >> John: So you see this as greenfield, new opportunity? >> I believe so. >> Is there any incumbent you see out there? An old stodgy? >> Today we're on internal developer platform service catalog type of, you know, use cases. >> John: Yeah. >> But that's kind of where we can grow from there and have the ecosystem essentially embrace us. >> John: How about the technology platform? >> Amit: Yeah. >> What's the vision for the innovation? >> Essentially want to be able to integrate with all of the different cloud providers, cloud solutions, SaaS platforms, and take the atlas approach that they were using right to the chats from everywhere to anywhere. So essentially we want in the end that users will be able to do anything that they need inside all of these complicated platforms, which some of them are totally complicated, with plain English. >> So what's the biggest challenge for you then on that front leading the technology side of the team? >> So I would say that the conversational AI part is truly complicated because it requires to extract many types of intentions from different types of users and also integrate with so many tools and solutions. >> Savannah: Yeah. So it requires a lot of thinking, a lot of architecture, but we are doing it just fine. >> Awesome. What do you guys think about KubeCon this week? What's, what's the top story that you see emerging out of this? Just generally as an industry observer, what's the most important? >> Savannah: Maybe it's them. Announcement halo. >> What's the cover story that you see? (all laugh) I mean you guys are in the innovation intent-based infrastructure. I get that. >> So obviously everyone's looking to diversify their engineering, diversify their platforms to make sure they're as decoupled from the main CSPs as possible. So being able to build their own, and we're really helping enable a lot of that in there. We're really helping improve upon that open source together with managed platforms can really play a very nice game together. So. >> Awesome. So are you guys hiring, recruiting? Tell us about the team DNA. Now you're in Tel Aviv. You're in the bay. >> Shaked: Check our openings on LinkedIn. (all laugh) >> We have a dozen job postings on our website. Obviously engineering and sales then go to market. >> So when theCUBE comes to Tel Aviv, and we have a location there. >> Yeah. >> Will you be, share some space? >> Savannah: Is this our Tel Aviv office happening right now? I love this. >> Amit: We will be hosting you. >> John: theCube with a C and Kube with a K over there. >> Yeah. >> All one happy family. >> Would love that. >> Get some ice cream. >> Would love that. >> All right, so last question for you all. You just had a very big exciting announcement. It's a bit of a coming out party for you. What do you hope to be able to say in a year that you can't currently say right now? When you join us on theCUBE next time? >> No, no, it's absolutely. I think our thesis that you can turn conversations into operations. It's, it sounds obvious to you when you think about it, but it's not trivial when you look into the workflows, into the operations. The fact that we can actually go a year from today and say we got hundreds of customers, happy customers who've proven the thesis or sharing knowledge between themselves, that would be euphoric for us. >> All right. >> You really are about helping people. >> Absolutely. >> It doesn't seem like it's a lip service from both of you. >> No. (all laugh) >> Is there going to be levels of bot, like level one bot level two, level three, and then finally the SRE gets on the phone? Is that like some point? >> Is there going to be bot singularity? Is that, is that what we're exploring right now? (overlapping chatter) >> Some kind of escalation bot. >> Enlightenment with bots. >> We actually planning a feature we want to call a handoff where a human in the loop is required, which often is needed. Machine cannot do it alone. We'll just. >> Yeah, I think it makes total sense for geos, ops at the same. >> Shaked: Yeah. >> But not exactly the same. Really good, good solution. I love the direction. Congratulations on the launch. >> Shaked: Thank you so much. >> Amit: Thank you very much. >> Yeah, that's very exciting. You can obviously look, check out that news on Silicon Angle since we had the pleasure of breaking it. >> Absolutely. >> If people would like to say hi, stalk you on the internet, where's the best place for them to do that? >> Be on our Twitter and LinkedIn handles of course. So we have kubiya.ai. We also have a free trial until the end of the year, and we also have free forever tier, that people can sign up, play, and come say hi. I mean, we'd love to chat. >> I love it. Well, Amit, Shaked, thank you so much for being with us. >> Shaked: Thank you so much. >> John, thanks for sitting to my left for the entire day. I sincerely appreciate it. >> Just glad I can help out. >> And thank you all for tuning in to this wonderful edition of theCUBE Live from Detroit at KubeCon. Who knows what my voice will be controlling next, but either way, I hope you are there to find out. >> Amit: Love it.

(bright music) >> Welcome back to Supercloud 22. I'm John Furrier, host of "theCUBE" with Dave Vellante, with the opening keynote conversation with Vittorio Viarengo. He's the Vice President of Cross-Cloud at VMware, Cube Alumni. Vittorio, great to see you. Thanks for coming on. >> Ah, my pleasure. >> So you're kicking off the Supercloud event. Again, a pilot. Again, we were texting just a few months ago around some of the momentum. You identified this right away. You saw it, you saw the momentum. What's the reality around supercloud? What's your perspective? >> Well, I think that we have to go back to the history of IT, over the last ever. I feel like in IT, we're always running after the developers. The developers, they're smart. They go for the path of least resistance, and they create innovations, and then the entire stacks moves around, and if you look at developers over the last, you know, 15 years, they've been going to the cloud, right? And the reason they're going for the cloud is, you now, they say software is eating the world. Is really who builds software? Developers, so I think it's developers are eating the world, and so initially, there was one game in town, so they went with AWS, but eventually, we got the multiple clouds, and now, the reality is that the applications there, it's how we make money, how we save money. They're running on multiple cloud, the 75% of the companies running on multiple clouds today, and so, I think that creates the new computing platform for the next, you know, 10 years, 15 years, and I think that that multi-cloud world brings tremendous advantages, as we just talked, but also some challenges, and it's prime to a simplification, and that's where we're trying. >> One of the things we observe is this abstraction layer across clouds to create a consistent experience for customers, and very importantly, as you point out, developers. So when you think about the history of abstractions, we see another one sort of forming in the 2020s, which is really different, as you pointed out, that we had in the 2010s, where there was really, you know, one main cloud. Now, you have all these clouds. What are your thoughts on the history of abstractions? >> Well, if you look at IT, we always needed abstraction to unleash the next level of growth, right? I grew up as a... I started my career as a C++ developer. So initially, you know, on Windows, if you wanted to open a window on the screen, you had to write 200 lines of code. Then the MFC library came in, and now, you still have to be a C++ developer, but now, with a one line of code, you can initiate, open the yellow world and start to build your applications, but it's only when Visual Basic comes along, then now, we get five millions developers building applications that are 20 years later, we're still using, okay? And then the list goes on and on, and in the application integration, we used to look at the bytes on the bus and say, "Okay, this is the customers, and we're going to map it to SAP," and then we went one level higher with SOA and web services and the rest of history, and then unleashed tremendous, you know, growth and look at, you know, how we now, you know, we be able to throw APIs, integrate anything, and so then the ultimate example of abstraction is virtualization. We made all these different servers and networking and storage look like one, and now, you know, and the business never cares if you're running SAP back on-prem on HP or some other piece of hard drive. They care that it runs, right? And so I think that now, we need to bring a level of abstraction in the cloud that not only abstracts the low level APIs at the highest level, but also uniforms and unify the APIs and the way do management and security across multiple cloud. >> Let's unpack that because I think the virtualization angle is interesting 'cause with virtualization enabled AWS. If you look at AWS' success, virtualization, the Hypervisor, got them going, and that established that value. Now, the new structural change is happening. How do you define that specifically? What is supercloud in your mind? >> So in our mind, supercloud is a set of cloud native services that, first of all... Let's unpack that and go back to the virtualization. Virtualization was a great way to do it on-prem and is no wonder that AWS and Azure, they did it on their cloud, right? But the lingo franca of the cloud is not the virtualization layer. That's taken, it's hidden. It's down there, it just does its thing. The lingo franca of cloud is microservices, API, Kubernetes as the orchestration layer, and one would think, "Okay, now, we have Kubernetes, life is good. I just, you know, deploy on- Well, there are six, seven, eight Kubernetes distribution, and so to us, the supercloud is the ability to take, to factor out the common things that you can do across cloud and give you a single pane or glass to manage your application and single pipeline so you can build your application once and deploy it consistently across multiple clouds, and then, basically, factor out the other two important things with the security and observability of the application. >> One of the trade-offs of abstraction, you go back to the mainframe. They had to squeeze out the performance overheads. VMware had to do the same and done a tremendous job of it. So are we going to see that across clouds with multi-cloud or what we call supercloud. Are you going to see a trade-off? What trade-off do you see that the industry, technically, has to attack? >> Abstractions are always about trade-offs, right? You're trading off the speed. You know, I'm writing C++ code goes really fast for scale. You know, now, I have five million developers writing applications, but I think, eventually, what happens is that or you're trading off specialized skills for, you know, more valuable skills, and if I had a dollar every time I heard, "Oh, we cannot run Oracle Databases on virtualization," well, or the JVM is too slow, but guess what? How many Java developers, how many Java application are running out on the JVM? So I think, eventually, there will be trade-offs, but the technology catches up and it's a matter of like how much value are you getting in terms of scales and saving cost versus maybe the performance trade-off you were making on the lower level. >> On the evolution of hybrid cloud, 'cause right now, hybrid cloud is a steady state. People see that clearly, you know, on-premise and Edge, right around the corner. Public native cloud, there's benefits to be in the native cloud. How does multi-cloud fit? 'Cause by default, people have multiple clouds. If they run on Azure, they probably have some sort of productivity software with Microsoft or other Microsoft products, but it's best to breed. It's not yet connected. So multi-cloud has kind of become a default kind of thing. It's not yet a strategy in some people's minds, yet some people are thinking about it. So we think, and I think you might agree, that multi-cloud will happen, multiple clouds in the sense of workloads running seamlessly. Is that a pipe dream or is that near in our future? (men laugh) >> So there is a lot of unpack there. First of all, our definition of multi-cloud is that because most customers are operating their on-prem as the cloud, so the moment you have your on-prem cloud and AWS, your multi-cloud, so 75%, 85% going to 85%- >> You mean Private Cloud on-premise cloud operations? >> Yeah, and then you have another cloud, you're already multi-cloud. >> I'm assuming the experiences is identical, right? That's the assumption you- >> Well, initially, it's not identical, right? That's why you need a supercloud, right? >> Yeah, exactly. >> And most customers though are in denial, meaning that I see them being in five stages of acceptance or adoption of the multi-cloud. One is denial. We are on-prem and maybe we have one cloud. We're standardized. The second one is euphoria. Oh, look, you know, look how fast we go. All these developers are happy to do whatever they want, and then the third one is like, holy crap. They got the first bill. They realize that the security share responsibility model to deal with. They realize that somebody is to deploy this application and manage the application. Nobody does it for them, and then they go into like, (indistinct). Okay, now, we need to do something about this, right? It's a new normal, and then you end up with the enlightment, right? Now, we're really being productive and strategic about how we use multi-cloud. Very, very few customers are in that stage. Most customers are still within the denial and the new normal, and within the spectrum, you see multi-cloud as, "Okay, I have an application here, an application there. Okay, great, big deal." The next level is, "Okay, I have an application here that uses a pieces of a service of an application over there. Okay, now, I'm coordinating application. I'm using microservices," and then the third stage is like, "Okay, I am designing my application to use multiple services or multiple cloud because each uses differentiated features of that particular cloud." >> Is it part of the problem too, Vittorio, that the industry, the technology industry, you guys have not caught up. The cloud vendors aren't solving that problem. What's VMware doing to solve that problem? >> So we have seen this coming four or five years ago, right? That's why we acquired Pivotal, and then we made a number of acquisition around it because we saw that... Well, let's go back. What is VMware DNA? If you look, I've been running engineering, product management in the company then I moved to the dark side, more on the marketing side, but I've seen, and I sweat with those engineers, and when I look at those engineers, these people know how to make stuff that was not designed to work together work together and deliver value, and so if we go back to, you know, on-prem, we did it with virtualization. In the cloud, we did a new level of abstraction, which is, you know, at the APIs at the... And so over the last five years, we built what we believe is very comprehensive portfolio that unified how you build, you run, manage, secure, and access any application across any cloud. No Hypervisor required. >> So that's the game changer right there. So let me ask you a question. How does the choice factor come in because can VMware do all this or do they need to rely on partners? Because most customers have HashiCorp and other companies in there doing services for them as well. So how do you see the multi-partner strategy approach? Can you do it alone or are you going to need help from the ecosystem? >> First of all, if you look at the success of your event today, look how many vendors from multiple backgrounds and multiple level of the stack that are coming together to talk about the supercloud. So that to me is success already, and, of course, there are tremendous companies that are going to deliver fantastic value for, you know, management like HashiCorp or security and the development experience. Our approach is to bring them together as an integrated platform, and I think VMware has both the DNA and the muscles, the investment to be able to pull that off. >> Okay, you saw Keith Townsend. He had that very cool blackboard, and he called, this was maybe eight or nine months ago, he called the supercloud and VMware's multi-cloud vision aspirational. When is this going to be real? >> I think it's absolutely real today in some of the pieces. Right, there's always an aspiration. You have to look at a company like VMware as a company that looks out five, 10 years, right? You know, we have Raghu as our CEO, you know, which is a technical visionary, and so he saw five years ago, the advent of multi-cloud, and we invested in first part of the stack. What is it? How to build applications natively in the cloud using Tanzu. So with Tanzu, you can build application, manage Kubernetes cluster, secure, creating this service match, and so that's the reality today. Then on the next step is security. We recently announced our security approach. We have a very peculiar position in the stack to be able to see security, not just on the endpoint, not just, you know, in the application, but in between, right? By looking at all the Hypervisor, if you're using Hypervisor. You looking at East-West traffic with NSX and cross cloud networks, and so these are the three main places that are in place today, right? And then I cannot spoil our user conference coming in a couple of weeks where we're going to make more announcement around the supercloud, which we called cross-cloud services. >> Vittorio, I remember in 2016, I interviewed Andy Jassy and Raghu when they announced the deal with VMware. VMware and AWS had the relationship, and you're running on the cloud on AWS VMware, and you look at what's happened since, and this is where the supercloud conversation starts to kick in where Amazon's really good at moving bits around and optimizing the power and the silicon of the infrastructure, which means that the higher level services are going to be much more open for people to innovate around. So Dave calls it, the super pass. This area platform is a service to change the SaaS game. So I have to ask you, how do you see the SaaS game changing with supercloud? Because if you have a Private Cloud or Edge, you're now multiple clouds, technically, as you pointed out. How has that changed the SaaS configuration? Because SaaS and IaaS and PaaS had great relationships in native clouds to solve problems. Now, you have the multi-cloud. How do you see this platform as a service area changing or maybe enabling? >> So I think that that's where the innovation, the ability to aggregate common... Because look, there is a reason why people use multiple cloud, right? They choose it because they have differentiated features. So we don't want to ever hide those features, like if you're using Google, because you need AI capabilities, absolutely. We don't want to prevent that, right? But at the PaaS level, you know, when you are orchestrated these microservices, you don't want to do it in five different ways, right? So those are the areas where I think are prime for aggregation and simplification. How you, you know, look at all this Kubernetes environment and being able to monitor your application and force security policies, both from a resource consumption, this group of developers can only use this many resources, but also a run time that you don't run out of like, you know, you get that bill shock, and so those are the areas where I think there's this more ability for us to innovate and deliver value, not at the lower level which is taken by the- >> So you try to have your cake and eat it too, which is if you can pull that off it's game over, right? You have a specific set of cross-cloud services that are unique and value added that are differentiable in the industry, but at the same time, you're trying to give access to developers, if in fact, they want access to those primitives, right? >> Yeah. >> That's a bold aspiration. >> Well, we want to have the cake, eat it, and lose weight. (men laugh) But seriously, I think, going back to your point about the ecosystem, of course, we're not going to do it alone, right? If we were doing it alone, there is not a market, right? And so I think that the market is so big and the area of challenges for IT is so large that there's room for many companies to add value, and I think that, as I said, our approach is to, you know, we're a platform company, right? So you're going to find tremendous companies that will solve one problem for multiple clouds. You're going to find the hyperscaler that have a platform approach for one cloud. We like to think that we can position ourself in that two by two as the company that has a platform approach across multiple clouds. >> You know, it's great. That's where we've known each other for a long time. It's 12 years of "CUBE" coverage. Watching things like the CNCF emerge and do great work, watching cloud native kind of go that next level's been fun to watch, and the developers have had a great run. I mean, open sources booming, developer goodness is out there. People are shifting left, a lot of great stuff going with containers and Kubernetes. So looking good on the developer experience front right now, and I think it's only going to get better, but developers don't think about locking. They just want to get the job done. Move on to the next line of code. It's the ops teams that we're hearing from that are saying, "Hey, we love this, too, but we got to align with the developer." Level up, so to speak. So ops and security teams are saying, "Hey, I got to run this with automation with the higher level services." So there seems to be a focus around the supercloud conversation around ops teams. This is your wheelhouse, VMware. You guys do a lot of IT operations and things of that nature. How do you see that and what's the message cross-cloud brings to and supercloud brings to the development teams and the ops teams who are really going to be doing DevOps together and/or faster? >> I think if you go back to what where we started, right? Developers run the show, and I think there's been a little bit of inertia in IT organization on the op side and the security side in catching up to see how to catch up to where developers are, right? And with the DevOps revolution, if operators don't really understand what the developers need and get ahead of that, they're going to be left behind. So I'll give you an example, like SMB Global, one of our customers, their band runs their operation. Basically, told me I had to sit down and figure out what these developers were doing because I was being left behind and then or Cerner, one of our partners and customers, same thing they say, okay, we sat down. We realized that we needed to get ahead of the developers and set those guard rails, right? These are the Kubernetes environment you want to use? Okay, this is how we're going to set them up. This is want to make sure that we shift left security, that we have a single pipeline that feeds that, and Cerner, using our technology was able to... They made a business decision to move from one hyperscaler, was going to go unnamed to another hyperscaler, It was going to go unnamed, and they managed to change all the deployments in four hours. So that's the power of the supercloud, being able to say, "Hey, developers, do whatever you want, but these are the guard rails, and we're going to be able to like stay ahead of you and give you the flexibility, but also, make sure that operation and security, as a saying." >> Shift left shield right, basically. >> Awesome, awesome stuff. We've got 15 seconds. What is supercloud? What's the bumper sticker? >> The supercloud is a level of abstraction across any of the public clouds that allows developers to go fast, operators to make sense of what's happening, security to enforce security, and end users to access any application with a great user experience and security. >> And it's inclusive of on-prem. I'll just throw that in. (John laughs) >> All right, great stuff. Thanks for coming on. We're going to have a industry panel to talk about and debate Supercloud 22. We'll be right back after this break.

>>Okay. We're back with Ari Basu, who is Cisco's resident philosopher, who also holds a master's in computer science. We're gonna have to unpack that a little bit and Najati chair he who's technical lead at Cisco. Welcome guys. Thanks for coming on the cube. >>Happy to be here. Thanks a >>Lot. All right, let's get into it. We want you to explain how Cisco validated the SBRI technology and the proof points that, that you have, that it actually works as advertised. So first Outre tell first, tell us about Cisco tech. What does Cisco tech do? >>So T is otherwise it's an acronym for technical assistance center is Cisco's support arm, the support organization, and, you know, the risk of sounding like I'm spotting a corporate line. The, the easiest way to summarize what tag does is provide world class support to Cisco customers. What that means is we have about 8,000 engineers worldwide, and any of our Cisco customers can either go on our web portal or call us to open a support request. And we get about 2.2 million of these support requests a year. And what these support requests are, are essentially the customer will describe something that they need done some networking goal that they have, that they wanna accomplish. And then it's tax job to make sure that that goal does get accomplished. Now, it could be something like they're having trouble with an existing network solution, and it's not working as expected, or it could be that they're integrating with a new solution. >>They're, you know, upgrading devices, maybe there's a hardware failure, anything really to do with networking support and, you know, the customer's network goals. If they open up a case for request for help, then tax job is to, is to respond and make sure the customer's, you know, questions and requirements are met about 44% of these support requests are usually trivial and, you know, can be solved within a call or within a day. But the rest of tax cases really involve getting into the network device, looking at logs. It's a very technical role. It's a very technical job. You're look you're, you need to be conversing with network solutions, their designs protocols, et cetera. >>Wow. So 56% non-trivial. And so I would imagine you spend a lot of time digging through through logs. Is that, is that true? Can you quantify that like, you know, every month, how much time you spend digging through logs and is that a pain point? >>Yeah, it's interesting. You asked that because when we started this on this journey to augment our support engineers workflow with zebra solution, one of the things that we did was we went out and asked our engineers what their experience was like doing log analysis. And the anecdotal evidence was that on average, an engineer will spend three out of their eight hours reviewing logs, either online or offline. So what that means is either with the customer live on a WebEx, they're going to be going over logs, network, state information, et cetera, or they're gonna do it offline, where the customer sends them the logs, it's attached to a, you know, a service request and they review it and try to figure out what's going on and provide the customer with information. So it's a very large chunk of our day. You know, I said 8,000 plus engineers, and so three hours a day, that's 24,000 man hours a day spent on long analysis. >>Now the struggle with logs or analyzing logs is there by out of necessity. Logs are very contr contr. They try to pack a lot of information in a very little space. And this is for performance reasons, storage reasons, et cetera, BEC, but the side effect of that is they're very esoteric. So they're hard to read if you're not conversant, if you're not the developer who wrote these logs or you or you, aren't doing code deep dives. And you're looking at where this logs getting printed and things like that, it may not be immediately obvious or even after a low while it may not be obvious what that log line means or how it correlates to whatever problem you're troubleshooting. So it requires tenure. It requires, you know, like I was saying before, it requires a lot of knowledge about the protocol what's expected because when you're doing log analysis, what you're really looking for is a needle in a haystack. You're looking for that one anomalous event, that single thing that tells you this shouldn't have happened. And this was a problem right now doing that kind of anomaly detection requires you to know what is normal. It requires, you know, what the baseline is. And that requires a very in-depth understanding of, you know, the state changes for that network solution or product. So it requires time, tenure and expertise to do well. And it takes a lot of time even when you have that kind of expertise. >>Wow. So thank you, archery. And Najati, that's, that's about, that's almost two days a week for, for a technical resource. That's that's not inexpensive. So what was Cisco looking for to sort of help with this and, and how'd you stumble upon zebra? >>Yeah, so, I mean, we have our internal automation system, which has been running more than a decade now. And what happens is when a customer attaches a log bundle or diagnostic bundle into the service request, we take that from the Sr we analyze it and we represent some kind of information. You know, it can be alert or some tables, some graph to the engineer, so they can, you know, troubleshoot this particular issue. This is an incredible system, but it comes with its own challenges around maintenance to keep it up to date and relevant with Cisco's new products or new version of the product, new defects, new issues, and all kind of things. And when I, what I mean with those challenges are, let's say Cisco comes up with a product today. We need to come together with those engineers. We need to figure out how this bundle works, how it's structured out. >>We need to select individual logs, which are relevant and then start modeling these logs and get some values out of those logs, using pars or some rag access to come to a level that we can consume the logs. And then people start writing rules on top of that abstraction. So people can say in this log, I'm seeing this value together with this other value in another log, maybe I'm hitting this particular defect. So that's how it works. And if you look at it, the abstraction, it can fail the next time. And the next release when the development or the engineer decides to change that log line, which you write that rag X, or we can come up with a new version, which we completely change the services or processes, then whatever you have wrote needs to be re written for that new service. And we see that a lot with products, like for instance, WebEx, where you have a very short release cycle that things can change maybe the next week with a new release. >>So whatever you are writing, especially for that abstraction and for those rules are maybe not relevant with that new release. With that being sake, we have a incredible rule creation process and governance process around it, which starts with maybe a defect. And then it takes it to a level where we have an automation in place. But if you look at it, this really ties to human bandwidth. And our engineers are really busy working on, you know, customer facing, working on issues daily and sometimes creating these rules or these pars are not their biggest priorities, so they can be delayed a bit. So we have this delay between a new issue being identified to a level where we have the automation to detect it next time that some customer faces it. So with all these questions and with all challenges in mind, we start looking into ways of actually how we can automate these automations. >>So these things that we are doing manually, how we can move it a bit further and automate. And we had actually a couple of things in mind that we were looking for and this being one of them being, this has to be product agnostic. Like if Cisco comes up with a product tomorrow, I should be able to take it logs without writing, you know, complex regs, pars, whatever, and deploy it into this system. So it can embrace our logs and make sense of it. And we wanted this platform to be unsupervised. So none of the engineers need to create rules, you know, label logs. This is bad. This is good. Or train the system like which requires a lot of computational power. And the other most important thing for us was we wanted this to be not noisy at all, because what happens with noises when your level of false PE positives really high your engineers start ignoring the good things between that noise. >>So they start the next time, you know, thinking that this thing will not be relevant. So we want something with a lot or less noise. And ultimately we wanted this new platform or new framework to be easily adaptable to our existing workflows. So this is where we started. We start looking into the, you know, first of all, internally, if we can build this thing and also start researching it, and we came up to Zeum actually Larry, one of the co co-founders of Zeum. We came upon his presentation where he clearly explained why this is different, how this works, and it immediately clicked in. And we said, okay, this is exactly what we were looking for. We dived deeper. We checked the block posts where SBRI guys really explained everything very clearly there, they are really open about it. And most importantly, there is a button in their system. >>So what happens usually with AI ML vendors is they have this button where you fill in your details and sales guys call you back. And, you know, we explain the system here. They were like, this is our trial system. We believe in the system, you can just sign up and try it yourself. And that's what we did. We took our, one of our Cisco live DNA center, wireless platforms. We start streaming logs out of it. And then we synthetically, you know, introduce errors, like we broke things. And then we realized that zebra was really catching the errors perfectly. And on top of that, it was really quiet unless you are really breaking something. And the other thing we realized was during that first trial is zebra was actually bringing a lot of context on top of the logs. During those failures, we work with couple of technical leaders and they said, okay, if this failure happens, I I'm expecting this individual log to be there. And we found out with zebra, apart from that individual log, there were a lot of other things which gives a bit more context around the root columns, which was great. And that's where we wanted to take it to the next level. Yeah. >>Okay. So, you know, a couple things to unpack there. I mean, you have the dart board behind you, which is kind of interesting, cuz a lot of times it's like throwing darts at the board to try to figure this stuff out. But to your other point, Cisco actually has some pretty rich tools with AppD and doing observability and you've made acquisitions like thousand eyes. And like you said, I'm, I'm presuming you gotta eat your own dog food or drink your own champagne. And so you've gotta be tools agnostic. And when I first heard about Z zebra, I was like, wait a minute. Really? I was kind of skeptical. I've heard this before. You're telling me all I need is plain text and, and a timestamp. And you got my problem solved. So, and I, I understand that you guys said, okay, let's run a POC. Let's see if we can cut that from, let's say two days a week down to one day, a week. In other words, 50%, let's see if we can automate 50% of the root cause analysis. And, and so you funded a POC. How, how did you test it? You, you put, you know, synthetic, you know, errors and problems in there, but how did you test that? It actually works Najati >>Yeah. So we, we wanted to take it to the next level, which is meaning that we wanted to back test is with existing SARS. And we decided, you know, we, we chose four different products from four different verticals, data center, security, collaboration, and enterprise networking. And we find out SARS where the engineer put some kind of log in the resolution summary. So they closed the case. And in the summary of the Sr, they put, I identified these log lines and they led me to the roots and we, we ingested those log bundles. And we, we tried to see if Zeum can surface that exact same log line in their analysis. So we initially did it with archery ourself and after 50 tests or so we were really happy with the results. I mean, almost most of them, we saw the log line that we were looking for, but that was not enough. >>And we brought it of course, to our management and they said, okay, let's, let's try this with real users because the log being there is one thing, but the engineer reaching to that log is another take. So we wanted to make sure that when we put it in front of our users, our engineers, they can actually come to that log themselves because, you know, we, we know this platform so we can, you know, make searches and find whatever we are looking for, but we wanted to do that. So we extended our pilots to some selected engineers and they tested with their own SRSS. Also do some back testing for some SARS, which are closed in the past or recently. And with, with a sample set of, I guess, close to 200 SARS, we find out like majority of the time, almost 95% of the time the engineer could find the log they were looking for in zebra analysis. >>Yeah. Okay. So you were looking for 50%, you got to 95%. And my understanding is you actually did it with four pretty well known Cisco products, WebEx client DNA center, identity services, engine ISE, and then, then UCS. Yes. Unified pursuit. So you use actual real data and, and that was kind of your proof proof point, but Ari. So that's sounds pretty impressive. And, and you've have you put this into production now and what have you found? >>Well, yes, we're, we've launched this with the four products that you mentioned. We're providing our tech engineers with the ability, whenever a, whenever a support bundle for that product gets attached to the support request. We are processing it, using sense and then providing that sense analysis to the tech engineer for their review. >>So are you seeing the results in production? I mean, are you actually able to, to, to reclaim that time that people are spending? I mean, it was literally almost two days a week down to, you know, a part of a day, is that what you're seeing in production and what are you able to do with that extra time and people getting their weekends back? Are you putting 'em on more strategic tasks? How are you handling that? >>Yeah. So, so what we're seeing is, and I can tell you from my own personal experience using this tool, that troubleshooting any one of the cases, I don't take more than 15 to 20 minutes to go through the zebra report. And I know within that time either what the root causes or I know that zebra doesn't have the information that I need to solve this particular case. So we've definitely seen, well, it's been very hard to measure exactly how much time we've saved per engineer, right? What we, again, anecdotally, what we've heard from our users is that out of those three hours that they were spending per day, we're definitely able to reclaim at least one of those hours and, and what, even more importantly, you know, what the kind of feedback that we've gotten in terms of, I think one statement that really summarizes how Zebra's impacted our workflow was from one of our users. >>And they said, well, you know, until you provide us with this tool, log analysis was a very black and white affair, but now it's become really colorful. And I mean, if you think about it, log analysis is indeed black and white. You're looking at it on a terminal screen where the background is black and the text is white, or you're looking at it as a text where the background is white and the text is black, but what's what they're really trying to say. Is there hardly any visual cues that help you navigate these logs, which are so esoteric, so dense, et cetera. But what XRM does is it provides a lot of color and context to the whole process. So now you're able to quickly get to, you know, using their word cloud, using their interactive histogram, using the summaries of every incident. You're very quickly able to summarize what might be happening and what you need to look into. >>Like, what are the important aspects of this particular log bundle that might be relevant to you? So we've definitely seen that a really great use case that kind of encapsulates all of this was very early on in our experiment. There was, there was this support request that had been escalated to the business unit or the development team. And the tech engineer had really, they, they had an intuition about what was going wrong because of their experience because of, you know, the symptoms that they'd seen. They kind of had an idea, but they weren't able to convince the development team because they weren't able to find any evidence to back up what they thought was happening. And we, it was entirely happenstance that I happened to pick up that case and did an analysis using Seebri. And then I sat down with the attack engineer and we were very quickly within 15 minutes, we were able to get down to the exact sequence of events that highlighted what the customer thought was happening, evidence of what the, so not the customer, what the attack engineer thought was the, was a root cause. It was a rude pause. And then we were able to share that evidence with our business unit and, you know, redirect their resources so that we could change down what the problem was. And that really has been, that that really shows you how that color and context helps in log analysis. >>Interesting. You know, we do a fair amount of work in the cube in the RPA space, the robotic process automation and the narrative in the press when our RPA first started taking off was, oh, it's, you know, machines replacing humans, or we're gonna lose jobs. And, and what actually happened was people were just eliminating mundane tasks and, and the, the employee's actually very happy about it. But my question to you is, was there ever a reticence amongst your team? Like, oh, wow, I'm gonna, I'm gonna lose my job if the machine's gonna replace me, or have you found that people were excited about this and what what's been the reaction amongst the team? >>Well, I think, you know, every automation and AI project has that immediate gut reaction of you're automating away our jobs and so forth. And there is initially there's a little bit of reticence, but I mean, it's like you said, once you start using the tool, you realize that it's not your job, that's getting automated away. It's just that your job's becoming a little easier to do, and it's faster and more efficient. And you're able to get more done in less time. That's really what we're trying to accomplish here at the end of the day, rim will identify these incidents. They'll do the correlation, et cetera. But if you don't understand what you're reading, then that information's useless to you. So you need the human, you need the network expert to actually look at these incidents, but what we are able to skin away or get rid of is all of the fat that's involved in our, you know, in our process, like without having to download the bundle, which, you know, when it's many gigabytes in size, and now we're working from home with the pandemic and everything, you're, you know, pulling massive amounts of logs from the corporate network onto your local device that takes time and then opening it up, loading it in a text editor that takes time. >>All of these things are we're trying to get rid of. And instead we're trying to make it easier and quicker for you to find what you're looking for. So it's like you said, you take away the mundane, you take away the, the difficulties and the slog, but you don't really take away the work, the work still needs to be done. >>Yeah. Great guys. Thanks so much. Appreciate you sharing your story. It's quite, quite fascinating. Really. Thank you for coming on. >>Thanks for having us. >>You're very welcome. Okay. In a moment, I'll be back to wrap up with some final thoughts. This is Dave Valante and you're watching the, >>So today we talked about the need, not only to gain end to end visibility, but why there's a need to automate the identification of root cause problems and doing so with modern technology and machine intelligence can dramatically speed up the process and identify the vast majority of issues right out of the box. If you will. And this technology, it can work with log bundles in batches, or with real time data, as long as there's plain text and a timestamp, it seems Zebra's technology will get you the outcome of automating root cause analysis with very high degrees of accuracy. Zebra is available on Preem or in the cloud. Now this is important for some companies on Preem because there's really some sensitive data inside logs that for compliance and governance reasons, companies have to keep inside their four walls. Now SBRI has a free trial. Of course they better, right? So check it out@zebra.com. You can book a live demo and sign up for a free trial. Thanks for watching this special presentation on the cube, the leader in enterprise and emerging tech coverage on Dave Valante and.

>>From the cube studios in Palo Alto, in Boston, bringing you data driven insights from the cube and ETR. This is breaking analysis with Dave ante. >>When Frank sluman took service, now public many people undervalued the company, positioning it as just a better help desk tool. You know, it turns out that the firm actually had a massive Tam expansion opportunity in it. SM customer service, HR, logistics, security marketing, and service management. Generally now stock price followed over the years, the stellar execution under Slootman and CFO, Mike scar Kelly's leadership. Now, when they took the reins at snowflake expectations were already set that they'd repeat the feet, but this time, if anything, the company was overvalued out of the gate, the thing is people didn't really better understand the market opportunity this time around, other than that, it was a bet on Salman's track record of execution and on data, pretty good bets, but folks really didn't appreciate that snowflake. Wasn't just a better data warehouse that it was building what they call a data cloud, and we've turned a data super cloud. >>Hello and welcome to this. Week's Wikibon cube insights powered by ETR in this breaking analysis, we'll do four things. First. We're gonna review the recent narrative and concerns about snowflake and its value. Second, we're gonna share survey data from ETR that will confirm precisely what the company's CFO has been telling anyone who will listen. And third, we're gonna share our view of what snowflake is building IE, trying to become the defacto standard data platform, and four convey our expectations for the upcoming snowflake summit. Next week at Caesar's palace in Las Vegas, Snowflake's most recent quarterly results they've been well covered and well documented. It basically hit its targets, which for snowflake investors was bad news wall street piled on expressing concerns about Snowflake's consumption, pricing model, slowing growth rates, lack of profitability and valuation. Given the, given the current macro market conditions, the stock dropped below its IPO offering price, which you couldn't touch on day one, by the way, as the stock opened well above that and, and certainly closed well above that price of one 20 and folks express concerns about some pretty massive insider selling throughout 2021 and early 2022, all this caused the stock price to drop quite substantially. >>And today it's down around 63% or more year to date, but the only real substantive change in the company's business is that some of its largest consumer facing companies, while still growing dialed back, their consumption this past quarter, the tone of the call was I wouldn't say contentious the earnings call, but Scarelli, I think was getting somewhat annoyed with the implication from some analyst questions that something is fundamentally wrong with Snowflake's business. So let's unpack this a bit first. I wanna talk about the consumption pricing on the earnings call. One of the analysts asked if snowflake would consider more of a subscription based model so that they could better weather such fluctuations and demand before the analyst could even finish the question, CFO Scarelli emphatically interrupted and said, no, <laugh> the analyst might as well have asked, Hey Mike, have you ever considered changing your pricing model and screwing your customers the same way most legacy SaaS companies lock their customers in? >>So you could squeeze more revenue out of them and make my forecasting life a little bit easier. <laugh> consumption pricing is one of the things that makes a company like snowflake so attractive because customers is especially large customers facing fluctuating demand can dial and their end demand can dial down usage for certain workloads that are maybe not yet revenue producing or critical. Now let's jump to insider trading. There were a lot of insider selling going on last year and into 2022 now, I mean a lot sloop and Scarelli Christine Kleinman. Mike SP several board members. They sold stock worth, you know, many, many hundreds of millions of dollars or, or more at prices in the two hundreds and three hundreds and even four hundreds. You remember the company at one point was valued at a hundred billion dollars, surpassing the value of service now, which is this stupid at this point in the company's tenure and the insider's cost basis was very often in the single digit. >>So on the one hand, I can't blame them. You know what a gift the market gave them last year. Now also famed investor, Peter Linsey famously said, insiders sell for many reasons, but they only buy for one. But I have to say there wasn't a lot of insider buying of the stock when it was in the three hundreds and above. And so yeah, this pattern is something to watch our insiders buying. Now, I'm not sure we'll keep watching snowflake. It's pretty generous with stock based compensation and insiders still own plenty of stock. So, you know, maybe not, but we'll see in future disclosures, but the bottom line is Snowflake's business. Hasn't dramatically changed with the exception of these large consumer facing companies. Now, another analyst pointed out that companies like snap, he pointed to company snap, Peloton, Netflix, and face Facebook have been cutting back. >>And Scarelli said, and what was a bit of a surprise to me? Well, I'm not gonna name the customers, but it's not the ones you mentioned. So I, I thought I would've, you know, if I were the analyst I would've follow up with, how about Walmart target visa, Amex, Expedia price line, or Uber? Any of those Mike? I, I doubt he would've answered me anything. Anyway, the one thing that Scarelli did do is update Snowflake's fiscal year 2029 outlook to emphasize the long term opportunity that the company sees. This chart shows a financial snapshot of Snowflake's current business using a combination of quarterly and full year numbers in a model of what the business will look like. According to Scarelli in Dave ante with a little bit of judgment in 2029. So this is essentially based on the company's framework. Snowflake this year will surpass 2 billion in revenues and targeting 10 billion by 2029. >>Its current growth rate is 84% and its target is 30% in the out years, which is pretty impressive. Gross margins are gonna tick up a bit, but remember Snowflake's cost a good sold they're dominated by its cloud cost. So it's got a governor. There has to pay AWS Azure and Google for its infrastructure. But high seventies is a, is a good target. It's not like the historical Microsoft, you know, 80, 90% gross margin. Not that Microsoft is there anymore, but, but snowflake, you know, was gonna be limited by how far it can, how much it can push gross margin because of that factor. It's got a tiny operating margin today and it's targeting 20% in 2029. So that would be 2 billion. And you would certainly expect it's operating leverage in the out years to enable much, much, much lower SGNA than the current 54%. I'm guessing R and D's gonna stay healthy, you know, coming in at 15% or so. >>But the real interesting number to watch is free cash flow, 16% this year for the full fiscal year growing to 25% by 2029. So 2.5 billion in free cash flow in the out years, which I believe is up from previous Scarelli forecast in that 10, you know, out year view 2029 view and expect the net revenue retention, the NRR, it's gonna moderate. It's gonna come down, but it's still gonna be well over a hundred percent. We pegged it at 130% based on some of Mike's guidance. Now today, snowflake and every other stock is well off this morning. The company had a 40 billion value would drop well below that midday, but let's stick with the 40 billion on this, this sad Friday on the stock market, we'll go to 40 billion and who knows what the stock is gonna be valued in 2029? No idea, but let's say between 40 and 200 billion and look, it could get even ugly in the market as interest rates rise. >>And if inflation stays high, you know, until we get a Paul Voker like action, which is gonna be painful from the fed share, you know, let's hope we don't have a repeat of the long drawn out 1970s stagflation, but that is a concern among investors. We're gonna try to keep it positive here and we'll do a little sensitivity analysis of snowflake based on Scarelli and Ante's 2029 projections. What we've done here is we've calculated in this chart. Today's current valuation at about 40 billion and run a CAGR through 2029 with our estimates of valuation at that time. So if it stays at 40 billion valuation, can you imagine snowflake grow into a 10 billion company with no increase in valuation by the end, by by 2029 fiscal 2029, that would be a major bummer and investors would get a, a 0% return at 50 billion, 4% Kager 60 billion, 7%. >>Kegar now 7% market return is historically not bad relative to say the S and P 500, but with that kind of revenue and profitability growth projected by snowflake combined with inflation, that would again be a, a kind of a buzzkill for investors. The picture at 75 billion valuation, isn't much brighter, but it picks up at, at a hundred billion, even with inflation that should outperform the market. And as you get to 200 billion, which would track by the way, revenue growth, you get a 30% plus return, which would be pretty good. Could snowflake beat these projections. Absolutely. Could the market perform at the optimistic end of the spectrum? Sure. It could. It could outperform these levels. Could it not perform at these levels? You bet, but hopefully this gives a little context and framework to what Scarelli was talking about and his framework, not with notwithstanding the market's unpredictability you're you're on your own. >>There. I can't help snowflake looks like it's going to continue either way in amazing run compared to other software companies historically, and whether that's reflected in the stock price. Again, I, I, I can't predict, okay. Let's look at some ETR survey data, which aligns really well with what snowflake is telling the street. This chart shows the breakdown of Snowflake's net score and net score. Remember is ETS proprietary methodology that measures the percent of customers in their survey that are adding the platform new. That's the lime green at 19% existing snowflake customers that are ex spending 6% or more on the platform relative to last year. That's the forest green that's 55%. That's a big number flat spend. That's the gray at 21% decreasing spending. That's the pinkish at 5% and churning that's the red only 1% or, or moving off the platform, tiny, tiny churn, subtract the red from the greens and you get a net score that, that, that nets out to 68%. >>That's an, a very impressive net score by ETR standards. But it's down from the highs of the seventies and mid eighties, where high seventies and mid eighties, where snowflake has been since January of 2019 note that this survey of 1500 or so organizations includes 155 snowflake customers. What was really interesting is when we cut the data by industry sector, two of Snowflake's most important verticals, our finance and healthcare, both of those sectors are holding a net score in the ETR survey at its historic range. 83%. Hasn't really moved off that, you know, 80% plus number really encouraging, but retail consumer showed a dramatic decline. This past survey from 73% in the previous quarter down to 54%, 54% in just three months time. So this data aligns almost perfectly with what CFO Scarelli has been telling the street. So I give a lot of credibility to that narrative. >>Now here's a time series chart for the net score and the provision in the data set, meaning how penetrated snowflake is in the survey. Again, net score measures, spending velocity and a specific platform and provision measures the presence in the data set. You can see the steep downward trend in net score this past quarter. Now for context note, the red dotted line on the vertical axis at 40%, that's a bit of a magic number. Anything above that is best in class in our view, snowflake still a well, well above that line, but the April survey as we reported on May 7th in quite a bit of detail shows a meaningful break in the snowflake trend as shown by ETRS call out on the bottom line. You can see a steady rise in the survey, which is a proxy for Snowflake's overall market penetration. So steadily moving up and up. >>Here's a bit of a different view on that data bringing in some of Snowflake's peers and other data platforms. This XY graph shows net score on the vertical axis and provision on the horizontal with the red dotted line. At 40%, you can see from the ETR callouts again, that snowflake while declining in net score still holds the highest net score in the survey. So of course the highest data platforms while the spending velocity on AWS and Microsoft, uh, data platforms, outperforms that have, uh, sorry, while they're spending velocity on snowflake outperforms, that of AWS and, and Microsoft data platforms, those two are still well above the 40% line with a stronger market presence in the category. That's impressive because of their size. And you can see Google cloud and Mongo DB right around the 40% line. Now we reported on Mongo last week and discussed the commentary on consumption models. >>And we referenced Ray Lenchos what we thought was, was quite thoughtful research, uh, that rewarded Mongo DB for its forecasting transparency and, and accuracy and, and less likelihood of facing consumption headwinds. And, and I'll reiterate what I said last week, that snowflake, while seeing demand fluctuations this past quarter from those large customers is, is not like a data lake where you're just gonna shove data in and figure it out later, no schema on, right. Just throw it into the pond. That's gonna be more discretionary and you can turn that stuff off. More likely. Now you, you bring data into the snowflake data cloud with the intent of driving insights, which leads to actions, which leads to value creation. And as snowflake adds capabilities and expands its platform features and innovations and its ecosystem more and more data products are gonna be developed in the snowflake data cloud and by data products. >>We mean products and services that are conceived by business users. And that can be directly monetized, not just via analytics, but through governed data sharing and direct monetization. Here's a picture of that opportunity as we see it, this is our spin on our snowflake total available market chart that we've published many, many times. The key point here goes back to our opening statements. The snowflake data cloud is evolving well beyond just being a simpler and easier to use and more elastic cloud database snowflake is building what we often refer to as a super cloud. That is an abstraction layer that companies that, that comprises rich features and leverages the underlying primitives and APIs of the cloud providers, but hides all that complexity and adds new value beyond that infrastructure that value is seen in the left example in terms of compressed cycle time, snowflake often uses the example of pharmaceutical companies compressing time to discover a drug by years. >>Great example, there are many others this, and, and then through organic development and ecosystem expansion, snowflake will accelerate feature delivery. Snowflake's data cloud vision is not about vertically integrating all the functionality into its platform. Rather it's about creating a platform and delivering secure governed and facile and powerful analytics and data sharing capabilities to its customers, partners in a broad ecosystem so they can create additional value. On top of that ecosystem is how snowflake fills the gaps in its platform by building the best cloud data platform in the world, in terms of collaboration, security, governance, developer, friendliness, machine intelligence, etcetera, snowflake believes and plans to create a defacto standard. In our view in data platforms, get your data into the data cloud and all these native capabilities will be available to you. Now, is that a walled garden? Some might say it is. It's an interesting question and <laugh>, it's a moving target. >>It's definitely proprietary in the sense that snowflake is building something that is highly differentiatable and is building a moat around it. But the more open snowflake can make its platform. The more open source it uses, the more developer friendly and the great greater likelihood people will gravitate toward snowflake. Now, my new friend Tani, she's the creator of the data mesh concept. She might bristle at this narrative in favor, a more open source version of what snowflake is trying to build, but practically speaking, I think she'd recognize that we're a long ways off from that. And I also think that the benefits of a platform that despite requiring data to be inside of the data cloud can distribute data globally, enable facile governed, and computational data sharing, and to a large degree be a self-service platform for data, product builders. So this is how we see snow, the snowflake data cloud vision evolving question is edge part of that vision on the right hand side. >>Well, again, we think that is going to be a future challenge where the ecosystem is gonna have to come to play to fill those gaps. If snowflake can tap the edge, it'll bring even more clarity as to how it can expand into what we believe is a massive 200 billion Tam. Okay, let's close on next. Week's snowflake summit in Las Vegas. The cube is very excited to be there. I'll be hosting with Lisa Martin and we'll have Frank son as well as Christian Kleinman and several other snowflake experts. Analysts are gonna be there, uh, customers. And we're gonna have a number of ecosystem partners on as well. Here's what we'll be looking for. At least some of the things, evidence that our view of Snowflake's data cloud is actually taking shape and evolving in the way that we showed on the previous chart, where we also wanna figure out where snowflake is with it. >>Streamlet acquisition. Remember streamlet is a data science play and an expansion into data, bricks, territory, data, bricks, and snowflake have been going at it for a while. Streamlet brings an open source Python library and machine learning and kind of developer friendly data science environment. We also expect to hear some discussion, hopefully a lot of discussion about developers. Snowflake has a dedicated developer conference in November. So we expect to hear more about that and how it's gonna be leveraging further leveraging snow park, which it has previously announced, including a public preview of programming for unstructured data and data monetization along the lines of what we suggested earlier that is building data products that have the bells and whistles of native snowflake and can be directly monetized by Snowflake's customers. Snowflake's already announced a new workload this past week in security, and we'll be watching for others. >>And finally, what's happening in the all important ecosystem. One of the things we noted when we covered service now, cause we use service now as, as an example because Frank Lupin and Mike Scarelli and others, you know, DNA were there and they're improving on that service. Now in his post IPO, early adult years had a very slow pace. In our view was often one of our criticism of ecosystem development, you know, ServiceNow. They had some niche SI uh, like cloud Sherpa, and eventually the big guys came in and, and, and began to really lean in. And you had some other innovators kind of circling the mothership, some smaller companies, but generally we see sluman emphasizing the ecosystem growth much, much more than with this previous company. And that is a fundamental requirement in our view of any cloud or modern cloud company now to paraphrase the crazy man, Steve bomber developers, developers, developers, cause he screamed it and ranted and ran around the stage and was sweating <laugh> ecosystem ecosystem ecosystem equals optionality for developers and that's what they want. >>And that's how we see the current and future state of snowflake. Thanks today. If you're in Vegas next week, please stop by and say hello with the cube. Thanks to my colleagues, Stephanie Chan, who sometimes helps research breaking analysis topics. Alex, my is, and OS Myerson is on production. And today Andrew Frick, Sarah hiney, Steven Conti Anderson hill Chuck all and the entire team in Palo Alto, including Christian. Sorry, didn't mean to forget you Christian writer, of course, Kristin Martin and Cheryl Knight, they helped get the word out. And Rob ho is our E IIC over at Silicon angle. Remember, all these episodes are available as podcast, wherever you listen to search breaking analysis podcast, I publish each week on wikibon.com and Silicon angle.com. You can email me directly anytime David dot Valante Silicon angle.com. If you got something interesting, I'll respond. If not, I won't or DM me@deteorcommentonmylinkedinpostsandpleasedocheckoutetr.ai for the best survey data in the enterprise tech business. This is Dave Valante for the insights powered by ETR. Thanks for watching. And we'll see you next week. I hope if not, we'll see you next time on breaking analysis.

(upbeat music) >> Okay, we're back with Atri Basu who is Cisco's resident philosopher who also holds a master's in computer science. We're going to have to unpack that a little bit. And Necati Cehreli, who's technical lead at Cisco. Welcome, guys. Thanks for coming on theCUBE. >> Happy to be here. >> Thanks a lot. >> All right, let's get into it. We want you to explain how Cisco validated the Zebrium technology and the proof points that you have that it actually works as advertised. So first Atri, first tell us about Cisco TAC. What does Cisco TAC do? >> So TAC is otherwise it's an acronym for Technical Assistance Center, is Cisco's support arm, the support organization. And the risk of sounding like I'm spouting a corporate line. The easiest way to summarize what TAC does is provide world class support to Cisco customers. What that means is we have about 8,000 engineers worldwide and any of our Cisco customers can either go on our web portal or call us to open a support request. And we get about 2.2 million of these support requests a year. And what these support requests are, are essentially the customer will describe something that they need done some networking goal that they have that they want to accomplish. And then it's TACs job to make sure that that goal does get accomplished. Now, it could be something like they're having trouble with an existing network solution and it's not working as expected or it could be that they're integrating with a new solution. They're, you know, upgrading devices maybe there's a hardware failure anything really to do with networking support and, you know the customer's network goals. If they open up a case for testing for help then TACs job is to respond and make sure the customer's, you know questions and requirements are met. About 44% of these support requests are usually trivial and, you know can be solved within a call or within a day. But the rest of TAC cases really involve getting into the network device, looking at logs. It's a very technical role. It's a very technical job. You need to be conversed with network solutions, their designs, protocols, et cetera. >> Wow. So 56% non-trivial. And so I would imagine you spend a lot of time digging through logs. Is that true? Can you quantify that like, you know, every month how much time you spend digging through logs and is that a pain point? >> Yeah, it's interesting you asked that because when we started on this journey to augment our support engineers workflow with Zebrium solution, one of the things that we did was we went out and asked our engineers what their experience was like doing log analysis. And the anecdotal evidence was that on average an engineer will spend three out of their eight hours reviewing logs either online or offline. So what that means is either with the customer live on a WebEx, they're going to be going over logs, network, state information, et cetera or they're going to do it offline where the customer sends them the logs it's attached to a, you know, a service request and they review it and try to figure out what's going on and provide the customer with information. So it's a very large chunk of our day. You know, I said 8,000 plus engineers and so three hours a day that's 24,000 man hours a day spent on log analysis. Now the struggle with logs or analyzing logs is there by out of necessity, logs are very contrite. They try to pack a lot of information in a very little space. And this is for performance reasons, storage reasons, et cetera, but the side effect of that is they're very esoteric. So they're hard to read if you're not conversant if you're not the developer who wrote these logs or you aren't doing code deep dives. And you're looking at where this logs getting printed and things like that, it may not be immediately obvious or even after a little while it may not be obvious what that log line means or how it correlates to whatever problem you're troubleshooting. So it requires tenure. It requires, you know, like I was saying before it requires a lot of knowledge about the protocol what's expected because when you're doing log analysis what you're really looking for is a needle in a haystack. You're looking for that one anomalous event, that single thing that tells you this shouldn't have happened, and this was a problem right. Now doing that kind of anomaly detection requires you to know what is normal. It requires, you know, what the baseline is. And that requires a very in depth understanding of, you know the state changes for that network solution or product. So it requires time to near and expertise to do well. And it takes a lot of time even when you have that kind of expertise. >> Wow. So thank you, Atri. And Necati, that's almost two days a week for a technical resource. That's not inexpensive. So what was Cisco looking for to sort of help with this and how'd you stumble upon Zebrium? >> Yeah, so, we have our internal automation system which has been running more than a decade now. And what happens is when a customer attach log bundle or diagnostic bundle into the service request we take that from the Sr we analyze it and we represent some kind of information. You know, it can be alerts or some tables, some graph, to the engineer, so they can, you know troubleshoot this particular issue. This is an incredible system, but it comes with its own challenges around maintenance to keep it up to date and relevant with Cisco's new products or a new version of a product, new defects, new issues and all kind of things. And when I mean with those challenges are let's say Cisco comes up with a product today. We need to come together with those engineers. We need to figure out how this bundle works, how it's structured out. We need to select individual logs, which are relevant and then start modeling these logs and get some values out of those logs, using PaaS or some rag access to come to a level that we can consume the logs. And then people start writing rules on top of that abstraction. So people can say in this log I'm seeing this value together with this other value in another log, maybe I'm hitting this particular defect. So that's how it works. And if you look at it, the abstraction it can fail the next time. And the next release when the development or engineer decides to change that log line which you write that rag X or we can come up with a new version which we completely change the services or processes then whatever you have wrote needs to be re-written for the new service. And we see that a lot with products, like for instance, WebEx where you have a very short release cycle that things can change maybe the next week with a new release. So whatever you are writing, especially for that abstraction and for those rules are maybe not relevant with that new release. With that being said we have a incredible rule creation process and governance process around it which starts with maybe a defect. And then it takes it to a level where we have an automation in place. But if you look at it, this really ties to human bandwidth. And our engineers are really busy working on you know, customer facing, working on issues daily and sometimes creating news rules or these PaaS are not their biggest priorities so they can be delayed a bit. So we have this delay between a new issue being identified to a level where we have the automation to detect it next time that some customer faces it. So with all these questions and with all challenges in mind we start looking into ways of actually how we can automate these automation. So these things that we are doing manually how we can move it a bit further and automate. And we had actually a couple of things in mind that we were looking for and this being one of them being this has to be product agnostic. Like if Cisco comes up with a product tomorrow I should be able to take it logs without writing, you know, complex regs, PaaS, whatever and deploy it into this system. So it can embrace our logs and make sense of it. And we wanted this platform to be unsupervised. So none of the engineers need to create rules, you know, label logs, this is bad, this is good. Or train the system like which requires a lot of computational power. And the other most important thing for us was we wanted this to be not noisy at all because what happens with noises when your level of false positives really high your engineers start ignoring the good things between that noise. So they start the next time, you know thinking that this thing will not be relevant. So we want something with a lot more less noise. And ultimately we wanted this new platform or new framework to be easily adaptable to our existing workflow. So this is where we started. We start looking into the, you know first of all, internally, if we can build this thing and also start researching it, and we came up to Zebrium actually Larry, one of the co-founders of Zebrium. We came upon his presentation where he clearly explained why this is different, how this works and it immediately clicked in and we said, okay, this is exactly what we were looking for. We dive deeper. We checked the block posts where Zebrium guys really explain everything very clearly there. They're really open about it. And most importantly, there is a button in their system. And so what happens usually with AI ML vendors is they have this button where you fill in your details and a sales guys call you back and you know, explains the system here. They were like, this is our trial system. We believe in the system you can just sign up and try it yourself. And that's what we did. We took one of our Cisco live DNA Center, wireless platforms. We start streaming logs out of it. And then we synthetically, you know, introduce errors like we broke things. And then we realized that Zebrium was really catching the errors perfectly. And on top of that, it was really quiet unless you are really breaking something. And the other thing we realized was during that first trial is Zebrium was actually bringing a lot of context on top of the logs. During those failures, we worked with couple of technical leaders and they said, "Okay if this failure happens I'm expecting this individual log to be there." And we found out with Zebrium apart from that individual log there were a lot of other things which gives a bit more context around the root cause, which was great. And that's where we wanted to take it to the next level. Yeah. >> Okay. So, you know, a couple things to unpack there. I mean, you have the dart board behind you which is kind of interesting, 'cause a lot of times it's like throwing darts at the board to try to figure this stuff out. But to your other point, Cisco actually has some pretty rich tools with AppD and doing observability and you've made acquisitions like thousand eyes. And like you said, I'm presuming you got to eat your own dog food or drink your own champagne. And so you've got to be tools agnostic. And when I first heard about Zebrium, I was like wait a minute. Really? I was kind of skeptical. I've heard this before. You're telling me all I need is plain text and a timestamp. And you got my problem solved. So, and I understand that you guys said, okay let's run a POC. Let's see if we can cut that from, let's say two days a week down to one day, a week. In other words, 50%, let's see if we can automate 50% of the root cause analysis. And so you funded a POC. How did you test it? You put, you know, synthetic, you know errors and problems in there, but how did you test that, it actually works Necati? >> Yeah. So we wanted to take it to the next level which is meaning that we wanted to back test is with existing SaaS. And we decided, you know, we chose four different products from four different verticals, data center security, collaboration, and enterprise networking. And we find out SaaS where the engineer put some kind of log in the resolution summary. So they closed the case. And in the summary of the SR, they put "I identified these log lines and they led me to the root cause" and we ingested those log bundles. And we tried to see if Zebrium can surface that exact same log line in their analysis. So we initially did it with archery ourself and after 50 tests or so we were really happy with the results. I mean, almost most of them we saw the log line that we were looking for but that was not enough. And we brought it of course to our management and they said, "Okay, let's try this with real users" because the log being there is one thing but the engineer reaching to that log is another take. So we wanted to make sure that when we put it in front of our users, our engineers, they can actually come to that log themselves because, you know, we know this platform so we can, you know make searches and find whatever we are looking for but we wanted to do that. So we extended our pilots to some selected engineers and they tested with their own SaaS. Also due some back testing for some SaaS which are closed in the past or recently. And with a sample set of, I guess, close to 200 SaaS we find out like majority of the time, almost 95% of the time the engineer could find the log they were looking for in Zebrium's analysis. >> Yeah. Okay. So you were looking for 50%, you got the 95%. And my understanding is you actually did it with four pretty well known Cisco products, WebEx client, DNA Center Identity services, engine ISE, and then UCS. Unified pursuit. So you use actual real data and that was kind of your proof point, but Atri, so that sounds pretty impressive. And have you put this into production now and what have you found? >> Well, yes, we've launched this with the four products that you mentioned. We're providing our TAC engineers with the ability, whenever a support bundle for that product gets attached to the support request. We are processing it, using sense and then providing that sense analysis to the TAC engineer for their review. >> So are you seeing the results in production? I mean, are you actually able to reclaim that time that people are spending? I mean, it was literally almost two days a week down to you know, a part of a day, is that what you're seeing in production and what are you able to do with that extra time and people getting their weekends back? Are you putting 'em on more strategic tasks? How are you handling that? >> Yeah. So what we're seeing is, and I can tell you from my own personal experience using this tool that troubleshooting any one of the cases, I don't take more than 15 to 20 minutes to go through the Zebrium report. And I know within that time either what the root causes or I know that Zebrium doesn't have the information that I need to solve this particular case. So we've definitely seen, well it's been very hard to measure exactly how much time we've saved per engineer, right? Again, anecdotally, what we've heard from our users is that out of those three hours that they were spending per day, we're definitely able to reclaim at least one of those hours and what even more importantly, you know, what the kind of feedback that we've gotten in terms of I think one statement that really summarizes how Zebrium's impacted our workflow was from one of our users. And they said, "Well, you know, until you provide us with this tool, log analysis was a very black and white affair, but now it's become really colorful." And I mean, if you think about it log analysis is indeed black and white. You're looking at it on a terminal screen where the background is black and the text is white, or you're looking at it as a text where the background is white and the text is black, but what they're really trying to say is there are hardly any visual cues that help you navigate these logs which are so esoteric, so dense, et cetera. But what Zebrium does is it provides a lot of color and context to the whole process. So now you're able to quickly get to, you know using their Word Cloud, using their interactive histogram, using the summaries of every incident. You're very quickly able to summarize what might be happening and what you need to look into. Like, what are the important aspects of this particular log bundle that might be relevant to you? So we've definitely seen that. A really great use case that kind of encapsulates all of this was very early on in our experiment. There was this support request that had been escalated to the business unit or the development team. And the TAC engineer had really, they had an intuition about what was going wrong because of their experience because of, you know the symptoms that they'd seen. They kind of had an idea but they weren't able to convince the development team because they weren't able to find any evidence to back up what they thought was happening. And it was entirely happenstance that I happened to pick up that case and did an analysis using Zebrium. And then I sat down with a TAC engineer and we were very quickly within 15 minutes we were able to get down to the exact sequence of events that highlighted what the customer thought was happening, evidence of what the sorry not the customer what the TAC engineer thought was a root cause. And then we were able to share that evidence with our business unit and, you know redirect their resources so that we could chase down what the problem was. And that that really shows you how that color and context helps in log analysis. >> Interesting. You know, we do a fair amount of work in theCUBE in the RPA space, the robotic process automation and the narrative in the press when our RPA first started taking off was, oh, it's, you know machines replacing humans, or we're going to lose jobs. And what actually happened was people were just eliminating mundane tasks and the employees actually very happy about it. But what my question to you is was there ever a reticence amongst your team? Like, oh, wow, I'm going to lose my job if the machine's going to replace me or have you found that people were excited about this and what's been the reaction amongst the team? >> Well, I think, you know, every automation and AI project has that immediate gut reaction of you're automating away our jobs and so forth. And there is initially there's a little bit of reticence but I mean, it's like you said once you start using the tool, you realize that it's not your job, that's getting automated away. It's just that your job's becoming a little easier to do and it's faster and more efficient. And you're able to get more done in less time. That's really what we're trying to accomplish here. At the end of the day, Zebrium will identify these incidents. They'll do the correlation, et cetera. But if you don't understand what you're reading then that information's useless to you. So you need the human you need the network expert to actually look at these incidents, but what we are able to skin away or get rid of is all of is all the fat that's involved in our process like without having to download the bundle, which, you know when it's many gigabytes in size and now we're working from home with the pandemic and everything, you're, you know pulling massive amounts of logs from the corporate network onto your local device that takes time and then opening it up, loading it in a text editor that takes time. All of these things are we're trying to get rid of. And instead we're trying to make it easier and quicker for you to find what you're looking for. So it's like you said, you take away the mundane you take away the difficulties and the slog but you don't really take away the work the work still needs to be done. >> Yeah, great. Guys, thanks so much appreciate you sharing your story. It's quite, quite fascinating. Really. Thank you for coming on. >> Thanks for having us. >> You're very welcome. >> Excellent. >> Okay. In a moment, I'll be back to wrap up with some final thoughts. This is Dave Vellante and you're watching theCUBE. (upbeat music)

>> Announcer: TheCUBE presents Dell Technologies World brought to you by Dell. >> Welcome back to theCUBE's coverage, day one, Dell Technologies World live from Las Vegas at the Venetian. Lisa Martin here with Dave Vellante and John Furrier. Guys let's talk, first of all, first time back in person since Dell Tech World 2019. Lots going on, lots of news today. I'm going to start with you, Dave, since you're closest to me. What are some of the things that have impressed you at this first in-person event in three years? >> Well, the first thing I want to say is, so John and I, we started theCUBE in 2010, John, right? In Boston, EMC World. Now of course, Dell owns EMC, so wow. It's good to be back here. Dell's built this beautiful set. I'd say the number one thing that's surprised me was how many people were here. Airport was packed, cab lines, the line at the Palazzo, the hotel, to get in was, you know, probably an hour long. And there's, I thought there'd be maybe 5,000 people here. I would say it's closer to eight. So the hall was packed today and everybody was pumped. Michael Dell was so happy to be up on stage. He talked, I dunno if you guys saw his keynote. He basically talked, obviously how great it is to be back, but he talked about their mission, building technologies that enable that better human condition. There was a big, you know, chewy words, right? And then they got into, you know, all the cool stuff they're doing so we can get into it. But they had CVS up on stage, they had USAA on stage. A big theme was trust. Which of course, if you're Dell, you know, you want people to trust you. I guess the other thing is this is the first live event they've had since the VMware spin. >> Right. >> So in 2019 they owned VMware. VMware's no longer a part of the income statement. Dell had a ton of debt back then. Now Dell's balance sheet looks actually better than VMware's because they restructured everything. And so it's a world without VMware where now with VMware their gross margins were in the 30-plus percent range. Now they're down to 20%. So we're now asking what's next for Dell? And they stood up on stage, we can talk about it some more, but a lot of multi-cloud, a lot of cyber resilience, obviously big themes around APEX, you know, hybrid work, John. So, well let's get into that. >> What are some of the key things that you heard today? >> Well, first of all, the customers on stage are always great. Dell's Technologies, 10 years for theCUBE and their history. I saw something back here, 25 years with celebrating precision, the history of Michael Dell's journey and the current Dell Technologies with EMC folded in and a little bit of VMware DNA still in there even though they're separated out. Just has a loyal set of customers. And you roam the hallways here, you see a lot of people know Dell, love Dell. Michael Dell himself was proud to talk before the event about he's number one, Dave, in PC market share. That's been his goal to beat HP for years. (laughing) And so he's got that done. But they're transforming their business cause they have to, the data center is now cloud. Cloud is now the distributed computing. Dell has all the piece parts today. We've covered this three years ago. Now it's turned into multi-cloud, which is multi-vendor, as a service is how the consumers consume, innovate with data, that's kind of the raw material. Future of work, and obviously the partners that they have. So I think Dell is going to continue to maintain the news of being the great in the front lines as a data-center-slash-enterprise, now cloud, Edge player. So, you know, I'm impressed with their constant reinvention of the company and the news hits all the cards: Snowflake partnership, cutting edge company in the cloud, partnership with Snowflake, APEX, their product that's innovating at the Edge, this new kind of product that's going to bring it together. Unifying, all those themes, Dave, are all hitting the marks. >> Chuck Whitten up on stage, obviously he was the multicloud, you know, conversation. And I think the vision that they they're laying out and Jeff Clarke talked about it as well, is a term that John and I coined. We can't remember who coined it, John or me, "supercloud." >> Yeah. (laughing) >> And they're talking about building an abstraction layer, building on top of the clouds, connecting on-prem to the clouds, across clouds, out to the Edge, hiding the underlying complexity, Dell managing all that. That's their vision. It's aspirational today but that really is supercloud. And it's more than multi-cloud. >> You coined the term supercloud. >> Did I? >> We riffed together. I called it sub-cloud. >> Oh, that's right. And then I said, no, it's got to float over. Super! Superman flies. (John laughs) Right, that's right. >> Sub-cloud, not really a good name. Nobody wants to be sub of anything. >> I think my kid gave it to me, John, actually. (laughing) >> Well if we do know that Michael Dell watches theCUBE, he's been on theCUBE many times. He watches theCUBE, clearly he's paying attention! >> Yeah, well I hope so. I mean, we write a lot about this and we talk to a lot of customers and talk to a lot of people. But let's talk about the announcements if we can. So... The APEX cyber recovery service, you know, ransomware recovery. They're now also running that on AWS and Azure. So that's big. We heard Presidio, they was super thrilled about that. So they're... The thing I'd say about that is, you know, Dell used to be really defensive about cloud. Now I think they're leaning in. They're saying, "Hey we're not going to spend, you know, Charles Fitzgerald, the snarky guy, does some good work on CAPEX. I mean, you look at how much the cloud guys are spending on CAPEX a year, $30, $40 billion. >> They can't compete. >> On cloud CAPEX. Dell doesn't want compete. >> John: You can't compete. >> Build on top of that, so that's a gift. So that's cool. You mentioned the Snowflake announcement. I thought that was big. What that is... It's very interesting, so Frank Slootman has always said, "We're not doing a half-way house, we're in the cloud." Okay, so square that circle for me. Now Snowflake's coming on-prem. Well, yeah, what they're doing is allowing customers to keep data in a Dell object store, ECS or other object stores. But use Snowflake. So non-native Snowflake data on-prem. So that expands Snowflake cloud. What it also does is give Dell a little sizzle, a little better partner and there's a path to cloud migration if that's where the customers want to go. >> Well, I mean, I would say that that's a dangerous game because we've seen that movie before, VMware and AWS. >> Yeah but that we've talked about this. Don't you think that was the right move for VMware? >> At the time, but if you don't nurture the relationship AWS will take all those customers, ultimately, from VMware. >> But that product's still doing very well. We'll see with NetApp is another one. NetApp on AWS. I forget what they call it, but yeah, file and AWS. So that was, go ahead. >> I was just going to say, what's the impact of Snowflake? Why do you think Snowflake chose Dell? >> Because Dell's a $101 billion company and they have a huge distribution channel and a lot of common customers. >> They own storage on the premise. >> Yep. And so Snowflake's looking for, you know, storage options on which they can, you know, bring data into their cloud. Snowflake wants the data to go from on-prem into the cloud. There's no question about that. >> And I would add another thing, is that Snowflake can't do what Dell Technologies does on-premises with storage and Dell can't do what Snowflake's doing. So I think it's a mutual short-term and medium-term benefit to say, "Hey you want to run on Snowflake? You need some services there? Great, but come back and use Dell." So that to me, I think that's a win-win for Snowflake. Just the dangerous game is, whoever can develop the higher-level services in the cloud will ultimately be the winner. >> But I think the thing I would say there is, as I said, Snowflake would love for the migration to occur, but they realize it's not always going to happen. And so why not partner with a company like Dell, you know, start that pipeline. And for Dell, hey, you know, why fight fashion, as Jeremy Burton would say. The other thing was Project Alpine, which is file, block and object across cloud. That's again setting up this supercloud. And then APEX. I mean, APEX is the discussion. We had a one-on-one session, a bunch of analysts with Jeff Woodrow who runs ISG. We were supposed to be talking about ISG, all we talked about is APEX. Then we had another session with APEX and all we talked about, of course, is APEX. So, they're still figuring that out, I would say, at this point. They don't quite have product market fit and I think they'd admit that, but they're working hard on scaling engineering, trying to figure out the channel model, the compensation. You know, taking their time even, but moving fast if you know what I mean. >> I mean, Dave, I think the big trend that's jumping out of me here is that, something that we've been covering, the headless cloud, meaning if you can do as a service, which is one of Dell's major points today, that to me, everyone is a PaaS layer. I think everyone that's building digital transformation apps has to be their own SaaS. So they either do that with somebody, a man in service, which fits beautifully into that trend, or do it own. Now e-commerce has this nailed down. Shopify or build your own on top of the cloud. So headless retail's a hot trend. You're going to start to see that come into the enterprise where the enterprise can have their cake and eat it too and take advantage of managed services where they don't have expertise. So those two things right there I think is going to drive a lot of growth for Dell. >> So essentially Lisa, what Dell is doing is saying, "Okay, the timing's good with the VMware spin." They say, "Now we're going to build our own cloud as a service, APEX." And they're starting with infrastructure as a service, you know, storage as a service. Obviously cyber recovery is a service. So you're going to get compute and storage and data protection. Eventually they'll move into other areas. And it's really important for them to do that to have their own cloud, but they've got to build up the ecosystem. Snowflake is a small example. My view, they need hundreds and hundreds of Snowflakes to fill the gaps, you know, move up the stack in middleware and database and DevOps. I mean, they should be partnering with HashiCorp. They should be partnering with all these companies that do DevOps stuff. They should be... I'd like to see them, frankly, partner with competitors to their data protection group. Why, you know, sounds crazy, but if you're going to build a cloud, look at AWS. They partner with everybody, right? And so that's what a true cloud experience looks like. You've got this huge menu. And so I think Dell's going to have to try to differentiate from HP. HPE was first, right, and they're all in. Dell's saying we're going to let the customers tell us where to go. And so they, I think one differentiation is their ecosystem, their ability to build that ecosystem. Yeah, but HP's got a good distribution channel too. Just not as big as Dell's. >> They all got the assets in it, but they're transforming. So I think at the end of the day, as Dell and even HPE transforms, they got to solve the customer problems and reduce the complexity. So again, the managed services piece with APEX is huge. I think having the building blocks for multi hybrid cloud at the Edge, just, you can't go wrong with that. If the customers can deploy it and consume it. >> What were some of the messages that you heard from, you mentioned CVS on stage, USAA on stage. Dell's always been very, very customer-focused. They've got some great brands. What did you hear from that customer's voice that shows you they're going in the right direction? >> Well first of all, the customers are longstanding customers of Dell Technologies, so that's one recognition of the ongoing partnerships. But they're also messaged up with Dell's messaging, right? They're telling the Dell story. And what I heard from the Dell story was moving fast and reducing complexity is their number one goal. They see the cloud option has to be there. Cloud native, Edge came up a little bit and the role of data. So I think all the new application development today that's relevant has a data as code kind of concept. Data engineering is the hottest skillset on the planet right now. And data engineering is not data science. So you start to see top-level CSOs and CIOs saying the new modern applications have to have data embedded in. It's just too hard. It's too hard to find that engineering team. So I heard the customer saying, we love the direction, we love the managed services. And by the way, we want to have that supply chain and cyber risk reduced. So yeah, big endorsement for Dell. >> You know, the biggest transformation in Dell, the two biggest transformations. One was the financials. You know, the income statement is totaled at a $101 billion company, growing at 17% a year. That's actually quite remarkable. But the flip side of that, the other big transformation was the customer. And with the acquisition of EMC but specifically VMware, it changed the whole conversation for Dell with customers. I think pre-2015, you wouldn't have had that type of narrative up on stage with customers. Cause it was, you know, compellant and it was equal logic and it was small businesses. Now you're talking about really deep strategic relationships that were enabled by that transformation. So my point is, to answer your question, it's going to be really interesting to see what happens post-VMware because when VMware came together with Dell, the industry didn't like it. The VMware ecosystem was like (growls) Dell. Okay, but customers loved it, right? And that's one of the things I heard on stage today. They didn't say, oh, well we love the VMware. But he mentioned VMware, the CTO from USAA. So Dell configured this commercial agreement with VMware, Michael Dell's the chairman of both companies. So that was part of the incentive. The other incentive is Dell is the number one distribution channel for VMware. So I think they now have that muscle memory in place where they've earned that trust. And I think that will continue on past the spin. It was actually quite brilliant the way they've orchestrated that. >> Yeah, Lisa, one more thing I want to add to that is that what I heard also was, you got the classic "here's how you be a leader in the modern era." It's a big leadership message. But then when you heard some of the notes, software-defined, multi-cloud with an emphasis on operations, Dave. So, okay, if you're a good leader, stay with Dell in operations. So you see strategy and operations kind of coming together around cloud. But big software defined multi-cloud data operational story. And I think those customers are kind of on that. You know, you got to maintain your operations. DevOps is operations, DevSecOps is operations. So big, like, don't get too greedy on the modern, shiny new toy, you know, in the cloud. >> Yeah, it's a safe bet, right? For infrastructure. I mean, HPE is a good bet too, but I mean Dell's got a way broader portfolio, bigger supply chain. It's got the end-to-end with the desktop, laptop, you know, the client side business, you know, a bigger services organization. And now the big challenge in my mind for Dell is okay, what's next? And I think they got to get into data management, obviously build up as a service, build up their cloud. They need software in their portfolio. I mean, you know, 20% gross margin company, it just, Wall Street's not as interested. You know, if they want to build more value, which they do, they've got to get more into software and I think you're going to see that. Again, I think you're going to see more M&A. I'd love to see more organic R&D instead of stock buybacks but I get why they have to do that. >> Well one of the things I'm looking at, Dave, in terms of what I think the future impact's going to be is the generational shift with the gen-Z and millennials running IT in the modern era. Not your old school rack-and-stack data center mentality. And then ultimately the scoreboard will determine, in my mind, the winner in their race is, where are the workloads running? Right? The workloads, and then also what's the application development scene look like? What do the apps look like? What are they building on? What's scaling them, what's running them? And the Edge is going to be a big part of that. So to me, operations, Edge, workloads and the development and then the workforce shift. >> And I do think Edge, I'm glad you brought up Edge. Edge is, you know, so fragmented but I think there's going to be a massive opportunity in Edge. There's going to be so much compute at the Edge. Dell talked about it, so much data. It's unclear to me right now how they go after that other than in pockets, like we heard from Gill. I believe they're going to do really well in retail. No question there. >> Yeah. >> But there's so much other industrial aisle IT- >> The telco space of towers, Edge. >> And Dell's, you know, Dell's server business, eh okay, it's got Intel and AMD inside, okay great. Their high margins come from storage, not from compute. Not the case with AWS. AWS had 35% operating margins last quarter. Oracle and Microsoft, that's the level that they're at. And I'd love to see Dell figure out a way to get paid more for their compute expertise. And that's going to take some R&D. >> John: Yeah, yeah. >> Last question guys, as we wrap up our wrap of day one. Given everything that we've all been through the last couple of years, what is your overall summary of what Dell announced today? The vibe of the show? How well have they fared the last two years? >> Well, I mean, they had a remarkable last two years. In a large part thanks to the client business. I think today you're seeing, you know, them lift the veil on what's next. And I think their story is coherent. There's, again, financially, they're a much more sound company, much better balance sheet. Not the most attractive income statement from a margin standpoint and they got work to do there. But wow, as far as driving revenue, they know how to sell. >> Yeah, I mean to me, I think looking back to before the pandemic, when we were here on the stage last, we were talking end-to-end, Dell leadership. And I say the biggest thing is Dell's catching up fast, faster than I thought. And I think they got, they're skating to where the puck is going, Dave, and I'll tell you why. The end-to-end I thought wouldn't be a total flyer if the Edge got too dynamic, but the fact that the Edge is growing so fast, it's more complex, that's actually given Dell more time. So to me, what I see happening is Dell having that extra time to nail the Edge piece, cause if they get there, if they get there, then they'll have their core competency. And why do I say that? Cause hardware is back. Server god boxes are going to be back. You're going to see servers at the Edge. And look at the failure of Amazon's Outpost, okay? Amazon's Outpost was essentially hardware. That's Dell's business. So you talk about like compute as a cloud but they really didn't do well with deploying compute like Dell does with servers. EKS is kicking ass at the Edge. So serverless with hardware, I think, is going to be the killer solution at the Edge. A combination of cloud and Edge hardware. And the Edge looks more like a data center than the cloud looks like the data center, so- >> So you're saying hardware matters? >> HardwareMatters.com. >> I think that's what I heard. >> HardwareMatters.com, check out that site, coming soon. (all laughing) >> I think it matters more than ever, you know- >> Blockchain, silicon advances. >> I think reason hardware matters is cause it's barbelling. It's going from the box to the silicon and it's going, you know, upstream into software defined. >> Horizontally, scalability means good silicon at the Edge, under the cover, scaling all the stuff and machine learning and AI in the application. So we've said this on theCUBE now, what, five years now? >> Dave: Yeah, yep. >> Guys, we've got an action packed night tonight. Two days tomorrow and Wednesday. Michael Dell is on tomorrow. Chuck Whitten is on, Jeff Clarke, et cetera, et cetera. Caitlin Gordon is on Wednesday. >> All the heavy hitters are coming on. >> They're coming on, they're going to be... >> Dave: Allison Dew's coming on. >> Allison Dew's coming on. >> We're going to talk about the Matthew McConaughey interview, which was, I thought, fantastic. J.J. Davis is coming on. So we're going to have a great channel discussion, as well, with Cheryl Cook. >> That's right. >> A lot of the product people are coming on. We're going to be talking APEX, it's going to be good. With cyber recovery, the Storage Alchemist is coming on, John! (all laughing) >> Boy, I can't wait to see that one. >> Well stick around guys for our coverage all day tomorrow, Tuesday and Wednesday. Lisa Martin with Dave Vellante and John Furrier coming to you live from the Venetian in Las Vegas. This is Dell Technologies World 2022. We look forward to seeing you tomorrow and the next day. (bouncy, upbeat music)

>> As to the adoption challenges, I wasn't clear on where that should go. I mean, I'm happy to just throw it out there. >> You'll again punch it back to me, right? >> Okay. >> Question comes to me and I'm going to pass the ball to Greg to connect the thread on one backbone is needed. Emphasizing Cat 9K that we just talked about. >> And same thing for the last question. The routes to market? >> Yes. >> Okay. >> Yes. >> Great. So we'll use that program for everything. Perfect. >> Masum, could you... Yeah, right there. So mark your place and try not to move that seat. That's it. Now, come forward just a tad, just a tad. There we go. Yeah. Okay, that's fine. Okay Alex, we're good. >> Okay. So Leonard don't leave after this 'Cause I'm going to do my outro. I'm going to do that as a separate asset, okay? >> You bet. >> Okay, great. So guys just it'll be five, four, three, silent, two, one. And then just follow my lead, okay? All right, Alex, you're ready? Masum and Greg, you're ready? >> Ready. >> Ready. >> Okay, here we go on me. On Dave in five, four, three, (beep). Okay, we're back. Digging into the infrastructure to make hybrid work possible. High performance, cost effective, scalable, and secure. That's what it's all about. And so far, we've covered the rapid migration to Wi-Fi 6E technology, and the role that switching is going to play. And now we're going to get into Private 5G and to do that, let's welcome Masum Mir, who is Vice President, and General Manager of Mobile, Cable and IoT business at Cisco. And Greg Dorai who is the Vice President of Product Management for the networking experiences group at Cisco. He's responsible for Catalyst access, that whole portfolio, Enterprise 5G, Cisco DNA Spaces, Cisco ISE, a lot of stuff there Greg. And gentlemen, welcome. >> Dave thank you for having us. >> Yeah, our pleasure. Masum let's start with you on the topic of Private 5G. What do we need to know about that? And more specifically, what's unique about Cisco's Private 5G? >> So most importantly, delivering Private 5G in enterprise terms, that's super important to look at 5G. Many of our peer groups might have got it wrong. We're looking at Private 5G with the lens of enterprise, what enterprise really needs. Is 5G going to come and displace a lot of existing technology, or is it going to help augment the technology that enterprise. It has an excellent the digitization journey. I wanted to start Dave with the basic premise of hybrid work. And what hybrid work really means. Is it only for knowledge worker, or is it for all workers? So we strongly believe hybrid work needs to empower all workers. It's not only connecting remote workers but also bringing people, things and space together. And we strongly believe the combination of Wi-Fi 6 and 5G for private network is going to accelerate that journey bringing people, things and space together in a very, very cohesive way. Why our offer is so unique? We are going to create a continuum. Enterprises don't have to make a hard choice. They will be using Wi-Fi technology and 5G technology hand in hand without creating a disruption on their policy and identity systems. They don't have to rethink, "Do I have to go and build a new backbone?" Is a common backbone that will support both Wi-Fi as well as 5G. Most importantly, delivering this entire offer as a service with the ease of consumption, ease of operation, and a trusted environment that they can put their mission critical workload on. >> Now, I like it. So a couple takeaways there. I mean, it's inclusive of all workers not just knowledge workers, non disruptive, everybody loves to hear that. And of course, it has service model as key Masum, let me stay with you. I mean, we can't wait for 5G, right? It's lightning fast, it got super low latency, very high bandwidth. So that's what everybody's excited about. The question though is, 5G gets introduced, yeah it's going to power things like IoT networks. Is that going to replace Wi-Fi and legacy wired broadband? >> Absolutely not. So we see Private 5G as an augmentation to the enterprise on top of Wi-Fi. Wi-Fi as you heard in the previous conversation, Wi-Fi is bringing more capability with Wi-Fi 6 and Wi-Fi 6E. And 5G is going to be yet another augmentation. Wi-Fi and 5G will coexist within enterprise for many years to come. I would like my friend, Greg to talk a little bit about this continuum. Greg? >> Yeah, I think it's sort of like, I like to say it's an and not an or. Because there's enough use cases out there which require spectrum. And you know, spectrum is a constraint. So you have Private 5G, your Wi-Fi 6, and both offer opportunities. So for example, in an indoor carpeted setting where you're basically connecting your phone for basic browsing, or connecting your laptop, Wi-Fi is sufficient. But if it's a process automation factory where you need seven nines of reliability, Private 5G is the better technology. Similarly outdoor, large areas, it's probably Private 5G, right? 'Cause you can have easy handoff between public and private. So it's use case driven. And once it's use case driven, it's going to be an or because there's so many next-gen use cases. Whether it's AR VR, drones, you know, self-driving cars you name it, right? And so I think these two technologies, 5G and Wi-Fi 6E is going to work hand in hand to deliver awesome outcomes for our customers. >> Yeah. And just the data volumes are going to be incredible. We always talk about the data volumes. You ain't seen nothing yet is what I always say. But the thing is every new tech that's introduced into the enterprise, you can almost be certain that it's going to bring adoption challenges. And not only that, it also is going to bring changes in the way you do things. And that brings new complexities from an operational standpoint. So my question is, how are you addressing this with the introduction of 5G? >> Dave, this is a fantastic question. And this is why we have spent, me and Greg have spent tremendous amount of time to create continuum. I'll start with the foundation first, backbone. So we have been building this enterprise backbone supported with wired connection as well as Wi-Fi connection. We wanted to make sure that as Private 5G comes within enterprise, you don't have to rethink and reimagine your backbone. It's the common backbone that will support what Wi-Fi, Wi-Fi 6, Wi-Fi 6E, as well as Private 5G. You're rest assured that it is the same backbone that we have heard in the previous section on the Cat 9K that will also support a Private 5G access. The second aspect of Private 5G is as you build any new technology into enterprise often time we get into this trap. To get to an outcome, we move fast and we create a silo. And then that silo operation creates barriers to mainstream it. So upfront, we have to think about not creating another silo. And how we are doing it. Number one, is a device that can connect into Wi-Fi network or a Private 5G network. You don't have to reimagine or rethink how I'm going to manage the identity. We'll create continuum with a common identity across the Wi-Fi access or 5G access in the same environment. The second aspect of that is how are we going to retain all our staff? Our enterprise staff is well trained with Wi-Fi technology and wired technology. Now 5G comes with tremendous amount of value and benefit. But it also comes with inherent technology complexity, learning curve problem. This is where our simple to consume, simple to operate model of SaaS comes to play. That we're going to take all those complexity away. It is a cloud delivered service. So enterprise don't have to go through this massive learning curve adopting this technology. Last but not least, on how we are going to manage your capital. Any new technology and enterprise often time, you need huge amount of upfront investment to adopt the technology to get to the other side of getting the outcome. So again, our business model of SaaS will allow enterprise to adopt this new technology and pay as your grow model to meet with enterprise needs. Finally, I also wanted to pass to Greg to touch a little bit more on how we are thinking about this common identity across any access in the enterprise. Greg, to you. >> So we thought about it in two different ways. One is, a lot of enterprises today use our identity and secure management platform. We call it ISE, Cisco ISE platform. And so, years and years of policy and identities, and which access servers, radio servers they use et cetera, are plugged in already into our ISE, right? So, if you can share that with this Private 5G as a service infrastructure that Masum's been building, we think we'll be able to create that bridge. Because we are not forcing enterprises to create new identities or new policies. So that's sort of step one to make it easier. We also thought through so something where in the case of a public 5G network, for example. It's very convenient because you take your phone out of your pocket and it's connected to the network, right? Versus for wifi, you have to log into an SSID in your hotel, or in your home, and in home, it's automatic. But that's that login process that creates friction. And that's a problem because then you can't be seamless. So we initiated what we call as open roaming, right? Like that's a identity federation that we first created between identity owners. Could be carriers, could be anything, right? Anyone who owns an identity. And they will share with venues. And so if the sharing happens, then that onboarding can be automatic. And once onboarding is automatic, then it's easy to pass off between Wi-Fi and 5G. And so that's again, another way in which you can lower the adoption barriers 'cause you share across public Private 5G and Wi-Fi networks. So these are two concrete examples of how we thought about lowering the barriers of adoption as we enter into this heterogeneous world. >> Nice, I can't wait. Let's talk about how this thing, scales in the go to market. What are the most likely, or maybe preferred, or obvious routes to market for Private 5G from Cisco? >> So Dave stay tuned right when they announce more about it. But I can also assure you that access to this spectrum is a challenge for many enterprises when it comes to cellular technology. In some countries there are more spectrum accessible by enterprise. In many countries, that's not the case. So we have thought through very carefully that how do we bring this offer to the market partnering with many service providers and mobile operators. Where in countries where you don't have direct access to the spectrum, our partnership with mobile operators, that you will hear more about as we come to Mobile World Congress, is going to allow our enterprise to consume this technology. even if they don't have the spectrum. In the places where the enterprise might have spectrum access, we'll also in our manage service providers to hide the complexity of the new technology on top of our SaaS services, or cloud delivered services. This is the augmentation with the partnership with manage service providers and mobile operators that will ease this journey for enterprises. Our most important primitive in this journey is to keep it simple for enterprise, make it intuitive, and trust it from day one. >> Outstanding. Okay, Masum, Greg, thanks so much. It was great to have you guys on. I really appreciate your time. >> Thank you. >> Thank you. >> In a moment, I'll be back with some closing thoughts and an opportunity for you to actually see this technology in action and talk to the experts directly. Keep it right there.

(upbeat music) >> Welcome back, everyone, to theCUBE's live coverage, day one wrap-up. I'm John Furrier, with Dave Vellante. We have Jerry Chen, special guest who's been with us every year on theCUBE since inception. Certainly every AWS re:Invent, nine years straight. Jerry Chen, great to see you for our guest analyst's wrap up VC general partner, Greylock partners, good to see you. >> John, Dave, it's great to see you guys. Thanks for having me again. It wouldn't be re:Invent without the three of us sitting here and we missed last year, right, because of COVID. So we have to make up for lost time. >> John: We did a virtual one- >> Dave: we did virtual stuff= >> John: wasn't the same as in-person. >> Dave: Definitely not the same. >> Jerry: Not the same thing. So, it's good to see you guys again in person, and less than 6 feet apart. >> Cheers, yeah. >> And 7,000 people here, showing that the event's still relevant. >> Jerry: Yeah. >> Some people would kill for those numbers, it's a bad year for Amazon, down from 60,000. >> Jerry: Yeah. >> So, ecosystem's booming. Okay, let's get to it. Day one in the books, new CEO, new sheriff in town, his name's Adam Selipsky. Your take? >> Well, Adam's new, but he's old, right? Something, you know, like something new, something old, something blue, right? It's so, Adam was early Amazon, so he had that founding DNA. Left, you know, CEO of Tableau, acquired by Salesforce, came back few months ago. So I think it was a great move, because one, he's got the history and culture under Jassy, so he's definitely the Bezos Jassy tree of leadership, but yet he's been outside the bubble. Right? So he actually knows what it means to run a company not on the Amazon platform. So, I think Adam's a great choice to lead AWS for what we call it, like maybe act two, right? Act one, the first X years with Jassy, and maybe this is the second act under Adam. >> Yeah. And he's got- and he was very technical, hung around all the techies, James Hamilton, DeSantis, all the engineers, built that core primitives. Now, as they say, this cloud next gen's here, act two, it's about applications. >> Jerry: Yeah. >> Infrastructure as code is in place. Interesting area. Where's the growth come from? So, look, you know, the ecosystem has got to build these super clouds, or as you say, Castles on the Cloud, which you coined, but you brought this up years ago, that the moats and the value has to be in there somewhere. Do you want to revise that prediction now that you see what's coming from Selipsky? >> Okay, well, so let's refresh. Greylock.com/castles has worked out, like we did, but a lot of thought leadership and the two of you, have informed my thinking at Castles in the Cloud, how to compete against Amazon in the cloud. So you'd argue act one, the startup phase, the first, you know, X years at Amazon was from 2008 to, you know, 2021, the first X years, building the platform, digging the moats. Right? So what did you have? You have castle the platform business, economies of scale, which means decreasing marginal costs and natural network effects. So once the moat's in place and you had huge market share, what do you for act two, right? Now the moats are in place, you can start exploring the moats for I think, Adam talked about in your article, horizontal and verticals, right? Horizontal solutions up the stack, like Amazon Connect, CRM solutions, right? Horizontal apps, maybe the app layer, and verticals, industrials, financials, healthcare, et cetera. So, I think Jassy did a foundation of the castle and now we're seeing, you know, what Adam and his generation would do for act two. >> So he's, so there's almost like an act one A, because if you take the four hyperscalers, they're about, maybe do 120 billion this year, out of, I don't know, pick a number, it's many hundreds of billions, at least in infrastructure. >> Jerry: Correct. >> And those four hyperscalers growing at 35% collectively, right? So there's some growth there, but I feel like there's got to be deeper business integration, right? It's not just about IT transformation, it's about deeper- So that's maybe where this Connect like stuff comes, but are there enough of those? You know, I didn't, I haven't, I didn't hear a lot of that this morning. I heard a little bit, ML- >> Jerry: Sure. >> AI into Connect, but where's the next Connect, right? They've got to do dozens of those in order to go deeper. >> Either, Dave, dozens of those Connects or more of those premise, so the ML announcement was today. So you look at what Twilio did by buying Segment, right? Deconstruct a CRM to compete against Adam Selipsky's old acquire of Salesforce.com. They bought Segment, so Twilio now has communicates, like texting, messaging, email, but all the data come from Segment. >> Dave: With consumption-based pricing. >> With consumption-based pricing. So, right? So that's an example of kind of what the second act of cloud looks like. It may not look like full SaaS apps like Salesforce.com, but these primitives, both horizontally vertically, because again, what does Amazon have as an asset that other guys don't? Install based developers. Developers aren't going to necessarily build or consume SaaS apps, but they're going to consume things like these API's and primitives. And so you look around, what's cloud act two look like? It may not be VM's or containers. It may be API's like Stripe and Billing, Twilio messaging, right? Concepts like that. So, we'll see what the next act at cloud looks like. And they announced a bunch of stuff today, serverless for the data analytics, right? So serverless is this move towards not consuming raw compute and storage, but APIs. >> What about competition? Microsoft is nipping at the heels of AWS. >> Dave: John put them out of business earlier today. [John and Dave Laugh] >> No, I said, quote, I'll just- let me rephrase. I said, if Amazon goes unchecked- >> Jerry: Sure. >> They'll annihilate Microsoft's ecosystem. Because if you're an ISV, why wouldn't you want to run on the best platform? >> Jerry: Sure. >> Speeds and feeds matter when you have these shifts of software development. >> Jerry: You want them both. >> So, you know, I mean, you thought about the 80's, if you were at database, you wanted the best processor. So I think this Annapurna vertical integrated stacks are interesting because if my app runs better and I have a platform, prefabricated or purpose-built platform, to be there for me, I'm going to build a great SaaS app. If it runs faster and it cost less, I'm going to flop to Amazon. That's just, that's my prediction. >> So I think better changes, right? And so I think if you're Amazon, you say cheaper, better, faster, and they're investing in chips, proprietary silicon to run better, faster, their machine learning training chips, but if you're Azure or Google, you got to redefine what better is. And as a startup investor, we're always trying to do category definition, right? Like here's a category by spin. So now, if you're Azure or Google, there are things you can say that are better, and Google argued their chips, their TensorFlow, are better. Azure say our regions, our security, our enterprise readiness is better. And so all of a sudden, the criteria "what's better" changes. So from faster and cheaper to maybe better compliance, better visibility, better manageability, different colors, I don't know, right? You have to change the game , because if you play the same game on Amazon's turf, to your point, John, it- it's game over because they have economies of scale. But I think Azure and Google and other clouds, the superclouds, or subclouds are changing the game, what it means to compete. And so I think what's going on, just two more seconds, from decentralized cloud, being Web 3 and crypto, that's a whole 'nother can of worms, to Edge compute, what Cloudflare are doing with R2 and storage, they're trying to change the name of the game. >> Well, that's right. If you go frontal against Amazon, you're got to get decimated. You got to move the goalposts for better. And I think that's a good way to look at it, Dave. What does better mean? So that's the question that's on the table. What does that look like? And I think that's an unknown, that's coming. Okay, back to the start-ups. Category definition. That's an awesome term. That to me is a key thing. How do you look at what a category is on your sub- on your Castles of the Cloud, you brought up how many categories of- >> Jerry: 33 markets and a bunch of submarkets, yeah. >> Yeah. Explain that concept. >> So, we did Castle in the Clouds where my team looked at all the services offered at Azure, Google, and Amazon. We downloaded the services and recategorized them to like, 30 plus markets and a bunch of submarkets. Because, the reason why is apples to apples, you know, Amazon, Google, Azure all have databases, but they might call them different things. And so I think first things first is, let's give developers and customers kind of apples to apples comparisons. So I think those are known markets. The key in investing in the cloud, or investing in general, is you're either investing in budget replacement, replacing a known market, cheaper, better database, to your point, or a net new market, right? Which is always tricky. So I think the biggest threat to a lot of the startups and incumbents, the biggest threat by startups and incumbents, is either one, do something cheaper, better in a current market, or find a net new market that they haven't thought about yet. And if you can win that net new market before the rest, then that's unbelievable. We call it the, you know, the blue ocean strategy, >> Dave: Is that essentially what Snowflake has done, started with cheaper, better, and now they're building the data cloud? >> Jerry: I think there's- it's evolution, correct. So they said cheaper, better. And the Castle in the Cloud, we talked about, they actually built deep IP. So they went a known category, data warehouses, right? You had Teradata, Redshift, Snowflake cheaper, better, faster. And now let's say, okay, once you have the customers, let's change the name of the game and create a data cloud. And it's TBD whether or not Snowflake can win data cloud. Like we talked about Rockset, one of my investments that's actually move the goalpost saying, oh, data cloud is nice, but real time data is where it's at, and Snowflake and those guys can't play in real time. >> Dave: No, they're not in a position to play in real time data. >> Jerry: Right. >> Dave: I mean, that's right. >> So again, so that's an example of a startup moving the goalpost on what previously was a startup that moved the goalpost on an incumbent. >> Dave: And when you think about Edge, it's going to be real-time AI inferencing at the Edge, and you're right, Snowflake's not set up well at all for that. >> John: So competition wise, how do the people compete? Because this is what Databricks did the same exact thing. I have Ali on the record going back years, "Well, we love Amazon. We're only on Amazon." Now he's talking multicloud. >> So, you know, once you get there, you kind of change your tune cause you've got some scale, but then you got new potential entrants coming in, like Rockset. >> Jerry: Correct. >> So. >> Dave: But then, and if you add up the market caps of just those two companies, Databricks and Snowflake, it's much larger than the database market. So this, we're defining new markets now. >> Jerry: I think there's market cap, especially Snowflake that's in the public market, Databricks is still private, is optimism that there's a second or third act in the database space left to be unlocked. And you look at what's going on in that space, these real-time analytics or real-time apps, for sure there's optimism there. But, but to John's point, you're right, like you earn the right to play the next act, but it's tricky because startups disrupt incumbents and become incumbents, and they're also victims their own success, right? So you're- there's technical debt, there's also business model debt. So you're victims of your own business model, victims of your own success. And so what got you here may not get you to the next phase. And so I think for Amazon, that's a question. For Databricks and Snowflake, that's a question, is what got them here? Can they play to the next act? And look, Apple did it, multiple acts. >> John: Well, I mean, I think I- [Crosstalk] >> John: I think it's whether you take shortcuts or not, if you have debt, you make it a little bit of a shortcut bet. >> Jerry: Yeah. >> Okay. That's cool. But ultimately what you're getting at here is beachhead thinking. Get a beachhead- >> Jerry: Correct. >> Get in the market, and then sequence to a different position. Classic competitive strategy, 101. That's hard to do because you want to win the beachhead- >> I know. >> John: And take a little technical debt and business model debt, cheat a little bit, and then, is it not fortified yet? So beachhead to expansion is the question. >> Jerry: That's every board meeting, John and Dave, that we're in, right? It's called you need a narrow enough wedge to land. And it is like, I don't want the tip of the spear, I want the poison on the tip of a spear, right? [Dave and John Laugh] >> You want, especially in this cloud market, a super focused wedge to land. And the problem is, as a founder, as investor, you're always thinking about the global max, right? Like the ultimate platform winner, but you don't get the right to play the early- the late innings if you don't make it out of the early innings. And so narrow beachhead, sharp wedge, but you got to land in a space, a place of real estate with adjacent tan, adjacent markets, right? Like Uber, black cars, taxi's, food, whatever, right? Snowflake, data warehouse, data cloud. And so I think the key with all startups is you'll hit some ceiling of market size. Is there a second ramp? >> Dave: So it's- the art is when to scale and how fast to scale. >> Right. Picking when, how fast, in which- which best place, it was tough. And so, the best companies are always thinking about their second or third act while the first act's still going. >> John: Yeah. And leveraging cloud to refactor, I think that's the key to Snowflake, was they had the wedge with data warehouse, they saw the position, but refactored and in the cloud with services that they knew Teradata wouldn't use. >> Jerry: Correct. >> And they're in. From there, it's just competitive IP, crank, go to market. >> And then you have the other unnatural things. You have channel, you have installed base of customers, right? And then you start selling more stuff to the same channel, to the same customers. That's what Amazon's doing. All the incumbent's do that. Amazon's got, you know, 300 services now, launching more this week, so now they have channel distribution, right? Every credit card for all the developers, and they have installed base of customers. And so they will just launch new things and serve the customers. So the startups had to disrupt them somehow. >> Well, it's always great to chat with Jerry. Every year we discover and we riff and we identify, in real time, new stuff. We were talking about this whole vertical, horizontal scale and kind of castles early on, years ago. And now it's happened. You were right. Congratulations. That's a great thesis. There's real advantages to build on a cloud. You can get the- you can build a business there. >> Jerry: Right. >> John: That's your thesis. And by the way, these markets are changing. So if you're smart, you can actually compete. >> Jerry: I think you beat, and to Dave's earlier point, you have to adapt, right? And so what's the Darwin thing, it's not the strongest, but the most adaptable. So both- Amazon's adapt and the startups who are the most adaptable will win. >> Dave: Where are you, you guys might've talked about this, where do you stand on the cost of goods sold issue? >> Jerry: Oh, I think everything's true, right? I think you can save money at some scale to repatriate your cloud, but again, Wall Street rewards growth versus COGS, right? So I think you've got a choice between a dollar of growth versus a dollar reducing COGS, people choose growth right now. That may not always be the case, but at some point, if you're a company at some scale and the dollars of growth is slowing down, you definitely have to reduce the dollars in cost. And so you start optimizing cloud costs, and that could be going to Amazon, Azure, or Google, reducing COGS. >> Dave: Negotiate, yeah. >> John: Or, you have no visibility on new net new opportunities. So growth is about new opportunities. >> Correct. >> If you repatriating things, there's no growth. >> Jerry: It's not either, or- >> That's my opinion. >> Jerry: COGS or growth, right? But they're both valid, definitely, so you can do both. And so I don't think- it's what's your priorities, you can't do everything at once. So if I'm a founder or CEO or in this case investor, and I said, "Hey, Dave, and John, if you said I can either save you 25 basis points in gross margin, or I can increase another 10% top line this year", I'm going to say increase the top line, we'll deal with the gross margin later. Not that it's not important, but right now the early phase- >> Priorities. >> Jerry: It's growth. >> Yeah. All right, Jerry Chen, great to see you. Great to have you on, great CUBE alumni, great guest analyst. Thanks for breaking it down. CUBE coverage here in Las Vegas for re:Invent, back in person. Of course, it's a virtual event, we've got a hybrid event for Amazon, as well as theCUBE. I'm John Furrier, you're watching the leader in worldwide tech coverage. Thanks for watching. (Gentle music)

>>Yeah, yeah. >>Welcome back to our final session in cultivating a data fluent culture track earlier today, we heard from experts like Valerie from the Data Lodge who shared best practices that you can apply to build that data flew into culture in your organization and tips on how to become the next analyst of the future from Yasmin at Comcast and Steve at all Terex. Then we heard from a captivating session with Cindy Hausen and Ruhollah Benjamin, professor at Princeton, on how now is our chance to change the patterns of injustice that we see have been woven into the fabric of society. If you do not have a chance to see today's content, I highly recommend that you check it out on demand. There's a lot of great information that you could start applying today. Now I'm excited to introduce our next session, which will take a look at how the democratization of data is powering digital transformation in the insurance industry. We have two prestigious guests joining us today. First Jim Bramblett, managing director of North America insurance practice, lead at its center. Throughout Jim's career, he's been focused on large scale transformation from large to midsize insurance carriers. His direct experience with clients has traditionally been in the intersection of technology, platform transformation and operating remodel redesign. We also have Michael cast Onus, executive VP and chief operating officer at DNA. He's responsible for all information technology, analytics and operating functions across the organization. Michael has led major initiatives to launch digital programs and incorporating modern AP I architectures ER, which was primarily deployed in the cloud. Jim, please take it away. >>Great. Thanks, Paula E thought we'd cover a few things today around around data. This is some of the trends we see in data within the insurance sector. And then I'll hand it over to Michael Teoh, take you through his story. You know, I think at the macro level, as we think about data and we think about data in the context of the insurance sector, it's interesting because the entire history of the insurance sector has been built on data and yet, at the same time, the entire future of it relies on that same data or similar similar themes for data. But but different. Right? So we think about the history, what has existed in an insurance companies. Four walls was often very enough, very enough to compete, right? So if you think about your customer data, claims, data, CRM, data, digital data, all all the data that was yeah, contained within the four walls of your company was enough to compete on. And you're able to do that for hundreds of years. But as we we think about now as we think about the future and the ability to kind of compete on data, this data comes from many more places just than inside your four walls. It comes from every device, every human, every vehicle, every property, every every digital interaction. Um in upon this data is what we believe insurers need to pivot to. To compete right. They need to be able to consume this data at scale. They need to be able to turn through this data to drive analytics, and they serve up insights based on those analytics really at the desktop of insurance professionals. And by the way, that has to be in the natural transition of national transaction. Of that employees work day. So an underwriter at a desktop claim him on the desktop, the sales associate of desktop. Those insights need to be served up at that point in time when most relevant. And you know. So if we think about how insurance companies are leveraging data, we see this really on kind of three horizons and starting from the left hand side of the page here, this is really brilliant basics. So how my leveraging core core data and core applied intelligence to monetize your existing strategy? And I think this brilliant based, brilliant basics concept is where most of most of my clients, at least within insurance are are today. You know, how are we leveraging data in the most effective way and putting it in the hands of business decision makers to make decisions largely through reporting and some applied intelligence? Um, Horizon two. We see, you know, definitely other industries blazing a trail here, and this is really about How do we integrate ecosystems and partners Now? I think within insurance, you know, we've had data providers forever, right? Whether it's NPR data, credit data risk data, you know, data aggregators and data providers have been a critical part of the insurance sector for for decades. I think what's different about this this ecosystem and partnership model is that it's much more Oneto one and it's much more, you know, kind of. How do we integrate more tightly and how do we become more embedded in each other's transactions? I think that we see some emergence of this, um, in insurance with automotive manufacturers with building management systems. But I think in the grand scheme of things, this is really very, very nascent for us as a sector. And I think the third horizon is is, you know, how do we fundamentally think about data differently to drive new business models? And I, you know, I don't know that we haven't ensure here in North America that's really doing this at any sort of scale. We certainly see pilots and proofs of concepts. We see some carriers in Europe farther down this path, but it's really it's really very new for us. A Z Think about these three horizons for insurance. So you know what's what's behind all this and what's behind. You know, the next powering of digital transformation and and we think at the end of the exercise, its data data will be the next engine that powers digital transformation. So in this exhibit, you know we see the three horizons across the top. You know, data is activated and activating digital transformation. And this, you know, this purple 3rd, 3rd road here is we think some of the foundational building blocks required to kind of get this right. But I think what's most important about about this this purple third bar here is the far right box, which is business adoption. Because you can build this infrastructure, you can have. You know, this great scalable cloud capability. Um, you can create a bunch of applications and intelligence, but unless it's adopted by the business, unless it's democratized, unless those insights and decisions air served up in the natural course of business, you're gonna have trouble really driving value. So that way, I think this is a really interesting time for data. We think this is kind of the next horizon to power the next age of digital transformation for insurance companies. With that brief prelude, I am, I'm honored. Thio, turn it over to Michael Stone Is the Cielo at CNN Insurance? >>Thanks, Jim, for that intro and very exciting Thio be here is part of part of beyond when I think a digital transformation within the context of insurance, actually look at it through the lens of competing in an era of near perfect information. So in order to be able to deliver all of the potential value that we talked about with regard to data and changing ecosystem and changing demands, the question becomes, How do you actually harness the information that's available to everybody to fundamentally change the business? So if you'll indulge me a bit here, let me tell you just a little bit more for those that don't know about insurance, what it really is. And I use a very long run on sentence to do that. It's a business model where capital is placed against risk in the form of products and associated services sold the customers through channels two companies to generate a return. Now, this sounds like a lot of other businesses in across multiple industries that were there watching today. But the difference within insurance is that every major word in that long run on sentence is changing sources of capital that we could draw on to be able to underwrite risk of going away. The nature of risk itself is changing from the perspective of policies that live six months to a year, the policies that could last six minutes. The products that we're creating are changing every day for our ability to actually put a satellite up in the air or ensure against the next pandemic. Our customers are not just companies or individuals, but they could be governments completely different entities than we would have been in sharing in the past and channels were changing. We sell direct, we sell through brokers and products are actually being embedded in other products. So you may buy something and not even know that insurance is a part of it. And what's most interesting here is the last word which is around return In the old world. Insurance was a cash flow business in which we could bring the premium in and get a level of interest income and being able to use that money to be able thio buffer the underwriting results that we would have. But those returns or dramatically reduced because of the interest income scenario, So we have to generate a higher rate of return. So what do we need to do? Is an insurance company in through this digital transformation to be able to get there? Well, fundamentally, we need to rethink how we're using information, and this is where thought spot and the cloud coming for us. We have two basic problems that we're looking to solve with information. The first one is information veracity. Do we believe it? When we get it? Can we actually trust it? Do we know what it means when we say that this is a policy in force or this is a new customer where this is the amount of attention or rate that we're going to get? Do we actually believe in that piece of data? The second is information velocity. Can we get it fast enough to be able to capitalize upon it? So in other words, we're We're working in a situation where the feedback loop is closing quickly and it's operating at a speed that we've never worked in before. So if we can't solve veracity and velocity, then we're never going to be able to get to where we need to go. So when we think of something like hot spot, what do we use it for? We use it to be able to put it in the hands of our business years so that they could ask the key questions about how the business is running. How much profit of my generating this month? What brokers do I need to talk? Thio. What is my rate retention? Look like what? The trends that I'm seeing. And we're using that mechanism not just to present nice visualizations, but to enable that really quick, dynamic question and answer and social, socially enabled search, which completely puts us in a different position of being able to respond to the market conditions. In addition, we're using it for pattern recognition. Were using it for artificial intelligence. We're gonna be capitalizing on the social aspect of of search that's that's enabled through thought spot and also connecting it into our advanced machine learning models and other capabilities that we currently have. But without it solving the two fundamental problems of veracity and velocity, we would be handicapped. So let me give you some advice about if I were in your position and you don't need to be in sleepy old industry like insurance to be able to do this, I'll leave you with three things. The first one is picking water holes so What are the things that you really want to be good at? What are the pieces of information that you really need to know more about? I mean, in insurance, its customers, it's businesses, locations, it's behavior. There are only a few water also really understand and pick those water holes that you're going to be really good at. The second is stand on the shoulders of giants. You know, in the world of technology, there's often a philosophy that says, Well, I can build it something better than somebody else create if I have it in house. But I'm happy to stand on the shoulders of giants like Thought Spot and Google and others to be able to create this capability because guess what? They're gonna out innovate any of the internal shops all day and every day. So don't be afraid. Thio. Stand side by side on the shoulders of giants as part of your journey. Unless you've got to build these organizations not just the technology for rapid experimentation and learning, because guess what? The moment you deliver insight, it begs another question, which also could change the business process, which could change the business model and If your organization the broader organization of business technology, analytics, customer service operations, etcetera is not built in a way that could be dynamic and flexible based on where the market is or is going, then you're gonna miss out on the opportunity. So again, I'm proud to be part of the fast black community. Really love the technology. And if if you look too, have the same kind of issues with your given industry about how you can actually speed up decision making, deliver insights and deliver this kind of search and recommended to use it. And with that, let's go to some questions. >>Awesome. Thank you so much, Michael and Jim for that in depth perspective and those tangible takeaways for our audience. We have a few minutes left and would love to ask a few questions. So here's the first one for Michael Michael. What are some of the most important things that you know now that you didn't know before you started this process? I think one of >>the things that's a great question. I think one of the things that really struck me is that, you know, traditional thinking would be very use case centric or pain point centric Show me, uh, this particular model or a particular question you want me to answer that can build your own analytics to do that or show me a deficiency in the system and I can go and develop a quick head that will do well, then you know, wallpaper over that particular issue. But what we've really learned is the foundation matters. So when we think about building things is building the things that are below the waterline, the pipes and plumbing about how you move data around how the engines work and how it all connects together gives you the above the waterline features that you could deliver to. You know, your employees into your customers much faster chasing use cases across the top above the waterline and ignoring what's below the water line to me. Is it really, uh, easy recipe too quick? Get your way to nothing. So again, focus on the foundation bill below the water line and then iterated above the water line that z what the lessons we've learned. It has been very effective for us. >>I think that's a very great advice for all those watching today on. But Here's one for Jim. Jim. What skills would you say are required for teams to truly adopt this digital transformation process? >>Yeah, well, I think that's a really good question, and I think I'd start with it's It's never one. Well, our experience has shown us number a one person show, right? So So we think to kind of drive some of the value that that that Michael spoke about. We really looked across disciplinary teams, which is a an amalgamation of skills and and team members, right? So if you think about the data science skills required, just kinda under under understand how toe toe work with data and drive insights, Sometimes that's high end analytic skills. Um, where you gonna find value? So some value architectural skills Thio really articulate, you know, Is this gonna move the needle for my business? I think there's a couple of critical critical components of this team. One is, you know, the operation. Whatever. That operation maybe has to be embedded, right, because they designed this is gonna look at a piece of data that seems interesting in the business Leader is going to say that that actually means nothing to me in my operation. So and then I think the last the last type of skill would be would be a data translator. Um, sitting between sometimes the technology in the business so that this amalgamation of skills is important. You know, something that Michael talked about briefly that I think is critical is You know, once you deliver insight, it leads to 10 more questions. So just in a intellectual curiosity and an understanding of, you know, if I find something here, here, the implications downstream from my business are really important. So in an environment of experimenting and learning thes thes cross discipline teams, we have found to be most effective. And I think we thought spot, you know, the platform is wired to support that type of analysis and wired to support that type of teaming. >>Definitely. I think that's though there's some really great skills. That's for people to keep in mind while they are going through this process. Okay, Michael, we have another question for you. What are some of the key changes you've had to make in your environment to make this digital transformation happen? >>That's a great question. I think if you look at our environment. We've got a mixture of, you know, space agent Stone age. We've got old legacy systems. We have all sorts of different storage. We have, you know, smatterings of things that were in cloud. The first thing that we needed to do was make a strong commitment to the cloud. So Google is our partner for for the cloud platform on unabashedly. The second thing that we needed to dio was really rethink the interplay between analytics systems in operational systems. So traditionally, you've got a large data warehouses that sit out over here that, you know, we've got some kind of extract and low that occurs, and we've got transactional operational systems that run the business, and we're thinking about them very differently from the perspective of bringing them together. How Doe I actually take advantage of data emotion that's in the cloud. So then I can actually serve up analytics, and I can also change business process as it's happening for the people that are transacting business. And in the meantime, I can also serve the multiple masters of total cost and consumption. So again, I didn't applications are two ships that pass in the night and never be in the world of Sienna. When you look at them is very much interrelated, especially as we want to get our analytics right. We want to get our A i m all right, and we want to get operational systems right By capturing that dated motion force across that architecture er that was an important point. Commit to the cloud, rethink the way we think analytics systems, work and operational systems work and then move them in tandem, as opposed to doing one without the other one in the vacuum. >>That's that's great advice, Michael. I think it's very important those key elements you just hit one question that we have final question we have for Jim. Jim, how do you see your client sustain the benefits that they've gained through this process? >>Yeah, it's a really good question. Um, you know, I think about some of the major themes around around beyond right, data fluency is one of them, right? And as I think about fluency, you only attain fluency through using the language every single day. They were day, week, over week, month over month. So you know, I think that applies to this. This problem too. You know, we see a lot of clients have to change probably two things at the same time. Number one is mindset, and number two is is structure. So if you want to turn these data projects from projects into processes, right, so so move away from spinning up teams, getting getting results and winding down. You wanna move away from that Teoh process, which is this is just the way working for these teams. Um, you have to change the mindset and often times you have to marry that with orb structure change. So So I'm gonna spin up these teams, but this team is going to deliver a set of insights on day. Then we're gonna be continuous improvement teams that that persist over time. So I think this shifting from project teams to persistent teams coupled with mindset coupled with with or structure changed, you know, a lot of times has to be in place for a period of time to get to get the fluency and achieve the fluency that that most organizations need. >>Thanks, Jim, for that well thought out answer. It really goes to show that the transformation process really varies when it comes to organizations, but I think this is a great way to close out today's track. I like to think Jim, Michael, as well as all the experts that you heard earlier today for sharing. There's best practice as to how you all can start transforming your organization's by building a data fluent culture, Um, and really empowering your employees to understand what data means and how to take actions with it. As we wrap up and get ready for the next session, I'd like to leave you all with just a couple of things. Number one if you miss anything or would like to watch any of the other tracks. Don't worry. We have everything available after this event on demand number two. If you want to ask more questions from the experts that you heard earlier today, you have a chance to do so. At the Meet The Experts Roundtable, make sure to attend the one for track four in cultivating a data fluent culture. Now, as we get ready for the product roadmap, go take a sip of water. This is something you do not want to miss. If you love what you heard yesterday, you're gonna like what you hear today. I hear there's some type of Indiana Jones theme to it all, so I won't say anything else, but I'll see you there.

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Hi everyone. Welcome back to the cubes. Live coverage cube live program for re:Invent 2020. This is our Q virtual. We're not in person like we normally are. Today is the AWS public sector. Worldwide celebration day. A lot of content coming from Teresa Carlson and her team and highlighting everything. Of course, the cube channel on the re:Invent events site. Well, the content we streaming there, if you go to the description, you can click on the link and check out all the on-demand interviews. We've done hundreds of videos live before the event pre recorded as well as here live today for public sector day, I'm showing Lisa Martin co-hosts of the cube. Who's been involved in a lot of those interviews. Uh, Lisa, great to see you before we good to see you. Thanks for coming on. >>Likewise. Good to see you too, John. Glad that you're staying safe. >>Well, a lot of good action. And before we get started, I do want to put a plug out for, um, some Salesforce, big party virtual event. Uh, Salesforce is having a big party at re:Invent 2020 a virtual house party with chance the rapper performing an exclusive set with surprise celebrities and DJ in residence December 10th that's tomorrow at 5:00 PM Pacific, go to salesforce.com/big party to check out chance the rapper. Uh, I'm a big fan. Of course my kids are more fans than, uh, check out the sales report. Okay. Back to cube virtual Lisa. Great to see you. >>Likewise John. So public sector day, a lot of transformation mean re:Invent being reinvented, being virtual 500,000 registered. And so, so much has changed, but a lot also that Teresa Carlson spoke about in her keynote and this morning about the transformation across the public sector, that's really been driven by necessity with COVID. It was really impressive to hear and see all of the good things that AWS is facilitating across healthcare, government, education, state, and local. You name it. >>Yeah. The thing I love about Theresa is she's always been ever since I've known her now she's been on the cube every year, since 2013, since we've been covering re:Invent, she's always had a big, bold vision, and she's always kind of stayed on that track. And this year that was really clear out of the box on her, her leadership session. You got to think big and you got to look at the value of the data. That was the key message from her, her and her group public sector, by the way, has been highly active with the COVID pandemic. A lot of public services have been leveraging Amazon cloud to serve, uh, their, their, their people, whether it's getting them the checks for entitlements or getting them, you know, pharmacy drugs and whatnot, and helping them with the pandemic. But clearly Amazon has stepped up and helped education with, with, uh, remotes. So Theresa's team has been pretty busy. So I think that they had more time to prepare for the virtual keynote. I should've gotten chock full of more announcements. >>Yeah. And also some great examples. As you mentioned, we heard from UK biobank, some of the interviews also that have already happened on the kid that you've done showed some amazing work that AWS has helped to facilitate for school districts in Los Angeles, for example, the government of Rhode Island. And those are some of the great things cabbage, what they were able to enable Kevin's to do, to deliver small business loans of so quickly. A lot of that, I thought, I wish we're hearing more about how technology is facilitating so much. Goodness, in COVID on the news. Of course, we're hearing a lot of the challenges with online learning, but there's a lot of amazing things that AWS has been able to facilitate incredibly quickly. >>You know, one of the concerns I have with Theresa and her team years and years ago was this idea of national parks, right? You know, we have spaces where we can go visit and why isn't there a cyber version of that. And so you S you saw that progression and she'd been doing a lot of deals where they're using the cloud and donating their technology for the betterment of society. And one of the things that was, um, news today was an advancement of their open data registry, which has been kind of this open commons of, you know, health data and whatnot. And now they have all the sequencing data that's searchable, readable, uh, from the national Institute of health for DNA sequencing. So this is going to be, again, more commons, like approach is starting to see that I think this is going to be a real big trend lease. >>I think you're going to start to see the big companies have to really contribute to society in a way that we've never seen before, because they have the large scale. You can donate large compute to say research projects. So you starting to see, uh, from Teresa's team, the bubbling up of these new shared experiences around technology for the betterment of society. I think that sequencing was one, the renewable energy project. Another one, again, they're investing in women owned businesses and underrepresented minorities, and at small, medium size businesses to fund them, we saw a guy launching stuff in space that can create, you know, synthetic satellites. So you can look through clouds. This is new. I mean, this is interesting. >>It is interesting. And it actually, to your point is impactful at every level across the globe, going from when they talked about we farm creating this network of small scale of farmers, connectivity was their biggest problem. And now there's over a million. I'm sure that number it's probably even bigger. I've connected farmers due to AWS. You talked about also it's the cord 19 search, which is the expansion of their open research dataset. COVID open research data set that is only possible because of cloud computing and AWS hundreds of thousands of assets in there. Um, 200 plus open data sets for genomic research. She talked about how that's been at the of some of the things that we've seen go on so quickly with operation work speed, uh, with respect to the vaccine. So a lot of acceleration when we know public sector kind of traditionally not necessarily fast movers, but of course, as we've all said, a number of times recently necessity is the mother of invention and the speed element and the connectivity element were things that really spoke loudly to me with what Teresa said today, about the importance of extracting value from data. >>You know, when I talked to Andy Jassy and he talked about this in his keynote, the digital transformation is on full display. And the necessity being the mother of invention is a great phrase, the system and sticking because you can't hide. I mean, you have to deliver these services in the public sector, or, you know, people's lives are going to be impacted in certainly this there's death involved, right? So you have that and then you've got education. I mean, people want to see that changed quicker. There's always been conscious, Oh, education has got to be re-imagined well, guess what? There's no school open. So we got to re-imagine it now. So you get a lot of pressure, unprecedented demand. She said, Theresa said, three's a crosswind actually set onstage for education change. Um, so that's huge. Right? And then the other thing that she mentioned, I think that's going to be a big focus. >>It's not as, um, you know, headline news oriented is this whole jobs training piece. Um, that's a huge deal because the, the tsunami that hits so fast on this digital transformation, because the COVID, we're going to have a post COVID era of rapid acceleration of new skills. So people gotta get trained. So this ain't going to be the boring training programs, the guy who get kind of get better. So I think you're going to see some innovation Lisa, around how people think about delivering and constructing training programs to be much more real world thinking outside the box, you're going to start to see new things. Otherwise it's just going to be too slowly, the training right now. It's just, you know, sign up for the courseware and get a certification. Yeah, you got to do those things, but how can you get sort of cases done faster? How do you get people with the skills in their hands and virtual hands, if you will, to stand up more cloud, more AI, the pressure's there. So we can, that's going to be a huge thing to watch. >>Okay. The pressure is there. You're right. And a need is there. She talked about a lot of the demand that their customers are driving for some of the services and the education services as well that they're offering. But I'd like to point about upskilling focusing on the people, not just the people, but also the diversity inclusion. And we all know how impactful thought diversity is. So their, their dedication, their in their focus there, and also her recommendation to be bold. And I think in the education, respect was really critical. There is no time like now to move digital transformation. If education systems aren't there, then you know, it's a huge challenge and it impacts every person, every element of every family. So what they're able to do there, by focusing on the people and enabling folks to get trained faster, more resources online can only be a good, you know, Theresa >>Has always, um, has her own flare to style to her. She's incredible business woman and have such respect for her. She's been so successful. Um, but she always sends her presentations with the, kind of the, the kind of her to dues. Um, and you kind of pointed that out. So just review them with you. And I want to get your reaction. Number one, she said, you got to re-imagine and enable a digital, a digitally enabled business. Number two, identify data has an realized value and then increase your diversity. And she pointed to avis.training. Um, and that's kind of her kind of get out there and do those things so digitally enabled business, get that unrealized day to get it into work and increase your diversity. And then she had had a big party every year just said, instead of a party go out and do a random act of kindness act. So, yeah, typical, three's a flare, you know, she kind of ended it with a random act of kindness, but, but her bold vision, those are practical, uh, mandates. What's your reaction to, to that? >>I bold vision. I absolutely 100% I think right now is the time that no business can afford to be hiding under the covers. We have to be, they have to be very thoughtful and very prescriptive, but be bold. There's so much opportunity right now. We're seeing a ton of invention and innovation, John, that we've seen over the last nine months. There's a lot of COVID catalysts that we've been talking about on the cube that are really fantastic. So I think that recommendation to set a bold vision is absolutely imperative, not easy to achieve, but I think right now more than ever, it could really be what sets apart, the winners and losers of tomorrow. >>Yeah. I love it. I just say that on this final note, um, cloud and AI is really in play cloud-scale machine learning, which essentially feeds AI is all about data compute going down to the chip level, AI and software and data is critical for cloud. So really awesome keynote again, leadership session by Teresa Carlson, and there's a whole site of content available. Checkout the cube page, click down on the main page. You'll see that description. You'll see a link to the re:Invent page and check on public sector. A lot of great content. Lisa final question for us to kind of close out this keynote leadership session analysis here on all sector day. I want to get your take on, um, the interviews you've done with the Amazon folks and partners and customers. What are the themes that have been boiling out of those? What have you have been hearing? What's your take and observation of the common pattern? >>You know, given the fact that we haven't all been able to be together at my last cube event in person was reinvent 2019. And we're so used to having, you know, three, four days of wall-to-wall coverage, two sides, being able to have those close personal conversations with our guests this year really did a phenomenal job of recreating that same experience, digitally there's tremendous amount of innovation happening. I think that was the one thing that really jumped out at me, the speed with which it's happening, how so many different types businesses have pivoted, not once, but again and again, and again, as times are changing and how even I yesterday I interviewed Boone, supersonic CEO, some of the things that they're facilitating to get commercial supersonic flight back that fully cloud and AI machine learning can do that. There was no stoppage of innovation this year. In fact, that actually got faster. And I think that was a resounding theme and a lot of positivity from the guests. >>You know, the cue, his business was to go to events and extract the signal from the noise. Guess what? There's no physical events. We have the cube virtual. We have pivoted. We are now in our eighth, ninth month of cube virtual. It's been a new model. We've gotten more interviews, more people can just click into the cube virtual. We have more virtual sets, the Cuban virtualized Lisa. Although I miss them in real life as a whole new ballgame for us, >>It is a whole new ball game. And it also provides a lot of opportunities for businesses to get their messaging out and connect and engage with their audience, which is important. >>Well, I miss real life. I miss everybody out there. I wish we could be there in person. Uh, the world will stay hybrid. I think with virtual, I think this has been a great format. There's been some great benefits, but we want to be in person. I want you on the desk with us. So, and all the folks out there I wish we could see. And then we'll see you next year. Thanks everyone for watching the key. This is our keynote analysis and leadership analysis of the worldwide public sector. Teresa Carlson, Kenya. I'm John from Lisa Martin. Thanks for watching.

>> Announcer: From around the globe, it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Worldwide Public Sector. >> Welcome to theCUBE Virtual and our coverage of AWS re:Invent 2020, the specialized programming for Worldwide Public Sector. I'm Lisa Martin. I'm joined by Nick Speece the chief federal technologist for Snowflake. Nick, welcome to theCUBE. >> Thank you, Lisa. It's great to be here. >> Likewise, chief federal technologist, that's the first time I've ever heard of that title. Tell me a little bit about that. >> It's probably the last time you'll hear it. So chief federal technologist is really somebody in the company who is focused on bringing the needs of the federal government back to our corporate headquarters, making sure that the product as it's developed and evolves has the federal requirements in mind. >> Excellent. So the last couple of months for Snowflake big, biggest software IPO and software history your market cap right now is at 66 billion 515 data workloads running on Snowflake's platform every day 250 petabytes of data under management, a lot is going on. Let's talk about Snowflake. You guys operate only in the cloud, why was that decision made and how does that impact businesses analysis of data? >> Yeah, so great question and the answer is actually in the opening that you gave for us and thank you for that reinforcement. Snowflake can't exist anywhere, but the cloud. Technology over the last five to 10 years has really seen a move from what the cloud originally was, which was I have a virtual machine in my data center, I'm going to run it on your stuff not mine, into more comprehensive service offerings like Snowflake. We can't reach the kind of scale that Snowflake operates at every day and that our customers demand without the technology of clouds like AWS. The technology has to be there, the underlying and underpinning architecture has to be there, otherwise our customers get left in the dark and we can't can't have that. >> And especially today as data volumes are massively increasing and we know that that's only going to go up. We know that IT is only going to be more complex but when we talk to businesses in any industry the value of the data is in the insights the ability to extract that data in real time glean insights from it so that businesses can make data-based decisions that pivot their business, especially critical during the year that we have now known as 2020. Talk to me a little bit about though digging into your marketing material, everyone, there's all these terms, right, that everyone uses and you guys use single source of truth. What does it actually mean for single source, for stuff like? >> Yeah, so we talk about cloud, we talk about single source of truth and when you're looking at data problems, the problem and the solution are the same thing. A massive amount of data is a raw resource, that's all it is. And trying to refine that raw resource into something that is insightful or something that is useful to a business process is a challenge that every customer in every market, in every region undergoes. And how you overcome that is critical. And one of the primary focuses of Snowflake is to evolve the data cloud. Snowflake platform is the underlying technology for the data cloud but the data cloud is where we're going. And what I mean by data cloud. If you have a data set, your internal data, that is your truth, but it might not be the truth. So in Snowflake we encourage our customers to collaborate on data sets. For example, if you want to know how many people are living in a certain borough in New York City you could go around with a clicker and count everyone, or you could just ask the Census Bureau. That's the nature of the data cloud and what we're talking about here. Going to the subject matter experts who have the data that you need, using our marketplace, using our private exchanges, using our data sharing to build your own data cloud and become part of the next gen architecture for data sharing and collaboration, to get to the source of the truth, to make better decisions, to gain better insights. It's great to combine your data with enrich data from other sources, especially when it comes to making federal decisions and governance decisions. >> Absolutely that's critical. That the biggest challenge customers have is being able to sort through all that and find. I like how you put this as their single source of truth. Can you give us some examples of some federal agencies maybe even just anonymously that are using the power of Snowflake to do just that? >> Absolutely. We've got customers in the healthcare space and in some of the law enforcement spaces and especially in public education that are trying to increase the awareness of the folks that are subscribing to their services, for example, folks that are looking for healthcare help. If you're filing claims for a certain healthcare providers or certain care facilities, we want to make sure that those claims that are forwarded to those entities are legitimate, first of all, for example, if you're filing a claim for knee surgery in Florida, you probably didn't have one in California, three hours later. So those kinds of enforcement activities, and not just trying to do audits but also to benefit everybody who's receiving care. There's a lot of push now about genetic sequencing, DNA and RNA vaccination is huge with COVID-19, getting access to massive amounts of data to do analysis against and figure out the best approach, that's critical for where we go in the next 10 to 15 years in healthcare. Snowflake is very, very honored and happy to be propelling that move in the healthcare space. >> It is that's going to be absolutely critical but we're also seeing it, you know, everywhere else, such as for universities and education, suddenly this need, the last few months for real-time learning. Talk to me about data analysis. Can Snowflake help companies, you talked about enriching data sets so not just companies sources of data but additional data sets that they can add in and evaluate and analyze to make great decisions, but from a historical real-time perspective, talk to me how Snowflake helps with that data analysis. >> Yeah, sure. Right. So Snowflake in and of itself can do some analysis work. We've got some great visualization tools in our new UI that was released recently on public preview. So there's some analysis tools built into Snowflake but really where the value comes from is in taking your tools that you already use today and connecting it to a data source or platform that can wrangle that data, that can move that data through automated pipelines to give you a model view of that data that's beneficial. For example, data scientists and data engineers spend 80% of their time, and I know a lot of statistics are made up on the spot, that was not a promise, but trying to move this data through and refine it and build features to get to the point where you can ask a question is 80% of these very valuable professionals time. Shortening those timelines is what Snowflake really aims to do in the analysis space. We're not trying to replace the analysis tools that you use today, we work fine with all of them. The big difference is presenting them with enough data volume to give you real insights and eliminate bias as much as we can in data sets. >> What are some of the things that differentiates Snowflake from data warehouses and other folks in the market? >> Yeah. Great question. The big difference is Snowflake was built natively for the cloud. We weren't adapted to the cloud, we didn't adopt the cloud at some point in the future, Snowflake was built from scratch to be in the cloud. And since this is the appropriate show to mention it the primary difference between us is we were built to use object storage foundationally underneath our technology. And I know that sounds really nerdy and it is, but it adds a tremendous amount of value. If you think about how we used to collaborate 10 years ago we'd have a spreadsheet that if I open that spreadsheet for my share drive and you tried to open it at the same time, you'd get locked out. You're told you couldn't have it. And if tradition stays true I would probably be on vacation for two weeks. Contrast that now with the massive Google Doc platform and Office 365, object storage has changed the way that we collaborate on the same kinds of documents. Multiple people interacting with one thing at one time without contention, that's the reason why Snowflake has to operate in the cloud. We bring that same paradigm, multiple actors on a single object and give you that source of truth the truth that you absolutely need to make decisions. >> And that's critical these days as we know. We're in living in uncertain times and one of the things I think we can expect is the uncertainty to continue, but also for many industries people to stay remote or some big percentage for quite a while. So the ability to have those collaboration tools and be able to collaborate in real time is table stakes for so many companies. But when we're talking about some of the things going on this year, security, we can't not talk about security. You know, all these folks from home accessing corporate networks, you know, maybe not through VPNs or behind firewalls, the cloud is paramount to that. How does Snowflake address the security issue? >> Absolutely. So I'll start by saying our security is inherited from the wonderful security platform that AWS has underneath it. So we inherit all the security around data storage the EC Compute, all of the different entities and end points that AWS already secures Snowflake takes the same precautions. More than that, we've also built and rolled this access control to ensure that people are getting access only to the data that they should be getting access to, we recently implemented data masking as well, so certain roles are not able to see unmasked data, but they can still do queries that use the underlying data to filter. So there's a lot of different capabilities built in, encryption at rest, encryption in flight, AES-256 encryption keys used in a hierarchial model. These are phenomenal security architectures that are paramount to the security of the folks that are using our platform. Because we know at the end of the day the first day we have a leak in Snowflake is probably our last day in business. We got to be good at that which is why it's our top priority. >> I didn't, to ever talk about security as an inherited, I must be a dominant trait if we're going to be talking about, you know, genetics and chromosomes and mRNA and things like that. So walk me through last question, a government organization, or say they're an AWS customer or they want to start using Snowflake, what's that process? How do they go about doing that to leverage those inherited security capabilities that you talked about? >> Well, thankfully AWS has helped us put a FedRAMP moderate certified Snowflake region together in AWS, East commercial, so we're very happy to have a FedRAMP moderate region. They can access Snowflake through the AWS Marketplace or from Snowflake.com, you can start a trial in just a couple of minutes. Our security is built into all of our regions although the FedRAMP regions are specialized in some of the encryption technology we use, but we always, always always protect our users' data, regardless of where it is. >> You make it sound easy, I got to say. (laughing) >> That's because it is. (laughing) Thank you cloud. >> That's good. And well, that's good and it should be, especially because there's so much complexity and uncertainty everywhere else in the world right now. Last question for you. As I mentioned in the beginning, the biggest IPO in software history, just a couple of months ago during probably one of the most strangest time of any of us have ever, and our relatives ever witnessed, what can we expect from Snowflake in 2021? Are you going to bring all the good vibes that we all need? (laughing) >> Well, good vibes is our business model. You know, Snowflake is a phenomenal platform. We've had a ton of success driven by the success of our cloud provider partners, driven by the success of our wonderful customers. We have over 4,000 people using Snowflake now to great effect. You can look for more features, you can look for more functions, but really the evolution of the data cloud, our big push is to help our customers get into the data cloud, get the truth out of their data and make better decisions every day. And you'll see more of that from us as time continues. >> One more question I wanted to sneak in, how did you work with those customers to evolve the data cloud? What's that feedback loop like? >> It's, a lot of it comes down to silos that the customers have built up over years and years and years of operation. That's the first step. In Snowflake there isn't such thing really as a data silo there's data put into Snowflake, everything is unified, you can do queries across databases, that's the first thing. The second thing is browsing our data marketplace. It's just like an App Store for your phone but instead it's data sets and the data sets are published by the experts who know that material better than anyone. I mentioned earlier bringing in everything from housing evaluation data to COVID-19 data from California and Boston, bringing World Health Organization data, John Hopkins University data, joining that with the data that you already use today along with weather and population counts, the main thing here, the strategy is almost endless. More and more data sets are being published over every day. We have over a hundred contributors in the marketplace now. >> That's exciting that we have the technology and the power like this to help the world re, you know, recover from such a crazy time. It's nice to know that, that there was the power of that behind that, and the smart folks like you chief federal technologists, helping to fine tune that and really ensure that organizations across the government can maximize the value of data and find their single source of truth. Nick, it's been a blast having you on theCUBE. Thank you for joining me. >> Thank you for having me. >> For next piece, I'm Lisa Martin. You're watching theCUBE Virtual. (upbeat music)

>> Narrator: From Las Vegas, it's theCUBE. Covering Qualys Security Conference 2019. Brought to you by Qualys. >> Hey, welcome back, you ready with Jeff Frick here with theCUBE. We are at the Qualys Security Conference in Las Vegas. This show's been going on, I think, 19 years. This is our first time here. We're excited to be here, and we've got, there's always these people that go between the vendor and the customer and back and forth. We've had it go one way, now we've got somebody who was at Qualys and now is out implementing the technology. We're excited to welcome Grant Johnson. He is the director of Risk and Compliance for Ancestry. Grant, great to see you. >> Thank you for having me, great to be here. >> Yeah, it is always interesting to me and there's always a lot of people at these shows that go back and forth between, and their creating the technology and delivering the technology versus implementing the technology and executing at the customer side. So, you saw an opportunity at Ancestry, what opportunity did you see and why did you make that move? >> Well it's a good question, I was really happy where I was at, I worked for here at Qualys for a long time. But, I had a good colleague of mine from way back just say, hey look, he took over as the chief information security officer at Ancestry and said, "they've got an opportunity here, do you want it?" I said, "hey sure." I mean, it was really kind of a green field. It was the ability to get in on the ground floor, designing the processes, the environment, the people and everything to, what I saw is really a really cool opportunity, they were moving to the cloud. Complete cloud infrastructure which was a few years ago, you know, a little uncommon so it was just and opportunity to learn a lot of different things and kind of be thinking through some different processes and the way to fix it. >> Right, right, so you've been there for a little while now. Over three years, what was the current state and then what was the opportunity to really make some of those changes, as kind of this new initiative with this new see, so? >> No, yeah, we were traditional. You know, a server data center kind of background and everything like that. But with the way the company was starting to go as we were growing it, really just crazy, just at a crazy clip, to where we really couldn't sustain. We wanted to go global, we wanted to move Ancertry out to Europe and to other environments and just see the growth that was going to happen there, and there just wasn't a way that we could do it with the traditional data center model. We're plugging those in all over the place, so the ideas is, we're going to go to a cloud and with going to the cloud, we could really rethink the way that we do security and vulnerability management, and as we went from a more traditional bottle which is, where you scan and tell people to patch and do things like that, to where we can try to start to bake vulnerability management into the process and do a lot of different things. And you know, we've done some pretty cool things that way, I think as a company and, always evolving, always trying to be better and better every day but it was a lot of fun and it's been really kind of a neat ride. >> So, was there a lot of app redesign and a whole bunch of your core infrastructure. Not boxes, but really kind of software infrastructure that had to be redone around a cloud focus so you can scale? >> Yeah. There absolutely was. We really couldn't lift and shift. We really had to take, because we were taking advantage of the cloud environment, if we just lifted and shifted our old infrastructure in there, it wasn't going to take advantage of that cloud expansion like we needed it to. >> Right. >> We needed it to be able to handle it tide, of high tide, low tide, versus those traffic times when we're high and low. So it really took a rewrite. And it was a lot of really neat people coming together. We basically, at the onset of this right when I started in 2016, our chief technology officer got up and said, "we're going to burn the ships." We have not signed the contract for our data center to renew at 18 months. So we have to go to the cloud. And it was really neat to see hundreds of people really come together and really make that happen. I've been involved in the corporate world for a long time in IT. And a lot of those projects fail. And it was really neat to see a big project like that actually get off the ground. >> Right, right. It's funny, the burning the ship analogy is always an interesting one. (grant laughs) Which you know, Arnold Schwarzenegger never had a plan B. (grant laughs) Because if you have plan B, you're going to fall back. So just commit and go forward. >> A lot of truth to that. Right, you're flying without a net, whatever kind of metaphor you want to use on that one. Yeah, but you have to succeed and there is a lot that'll get it done I think, if you just don't have that plan B like you said. >> Right, so talk about kind of where Ancestry now is in terms of being able to roll out apps quicker, in terms of being able to scale much larger, in terms of being able to take advantages of a lot more attack surface area, which probably in the old model was probably not good. Now those are actually new touch points for customers. >> It's a brave new world on a lot of aspects. I mean, to the first part of that, we're just a few days away from cyber Monday. Which is you know, our normal rate clip of transactions is about 10 to 12 transactions a second. >> So still a bump, is cyber Monday still a bump? >> It's still huge for us. >> We have internet at home now. We don't have to go to work to get on the internet to shop. >> You know, crazy enough, it still is. You know, over the course of the week, and kind of starting on Thanksgiving, we scale to have about 250 transactions a second. So that was one of the good parts of the cloud, do you invest and the big iron and in the big piping for your peak times of the year. Or and it sits, your 7-10% utilization during the rest of the year, but you can handle those peaks well. So I mean, we're just getting into the time of year, so that's where our cloud expansion, where a lot of the value for that has come. In terms, of attack surface, yeah, absolutely. Five years ago, I didn't even know what a container was. And we're taking advantage a lot of that technology to be able to move nimbly. You can't spin up a server fast enough to meet the demands of user online clicking things. You really have to go with containers and that also increases what you really need to be able to secure with people and the process and technology and everything like that. >> Right. >> So it's been a challenge. It's been really revitalizing and really, really neat to me to get in there and learn some new things and new stuff like that. >> That's great. So I want to ask you. It may be a little sensitive, not too sensitive but kind of sensitive right. Is with 23 and Me and Ancestry, and DNA registries, et cetera, it's opened up this whole new conversation around cold case and privacy and blah blah blah. I don't want to get into that. That's a whole different conversation, but in terms of your world and in terms of risking compliance, that's a whole different type of a data set I think that probably existed in the early days of Ancestry.com >> Yeah >> Where you're just trying to put your family tree together. So, how does that increased value, increased sensitivity, increased potential opportunity for problems impact the way that you do your job and the way that you structure your compliance systems? >> Boy. Honestly, that is part of the reason why I joined the company. Is that I really kind of saw this opportunity. Kind of be a part of really a new technology that's coming online. I'd have to say. >> Or is it no different than everyone else's personal information and those types of things? Maybe it's just higher profile in the news today. >> Not it all, no. It kind of inherent within our company. We realized that our ability to grow and stay affable or just alive as a business, we pivot on security. And security for us and privacy is at the fore front. And I think one of the key changes that's done for maybe in other companies that I get is, people from our development teams, to our operations teams, to our security department, to our executives. We don't have to sell security to em. They really get it. It's our customer privacy and their data that we're asking people to share their most personal data with us. We can give you a new credit card. Or, you can get a new credit card number issued. We can't give you a new DNA sequence. >> Right. >> So once that's out there, it's out there and it is the utmost to us. And like I said, we don't have to sell security internally, and with that we've gotten a lot of support internally to be able to implement the kind of things that we needed to implement to keep that data as secure as we can. >> Right, well that's nice to hear and probably really nice for you to be able to execute your job that you don't have to sell securities. It is important, important stuff. >> Grant: Yes, that's absolutely true. >> All right, good. So we are jamming through digital transformation. If we talk a year from now, what's on your plate for the next year? >> We just continue to evolve. We're trying to still continue the build in some of those processes that make us better, stronger, faster, as we go through, to respond to threats. And just really kind of handle the global expansion that our company's undergoing right now. Just want to keep the lights on and make sure that nobody even thinks about security when they can do this. I can't speak for them, but I think we really want to lead the world in terms of privacy and customer trust and things like that. So there are a lot of things that I think we've got coming up that we really want to kind of lead the way on. >> Good, good. I think that is a great objective and I think you guys are in a good position to be the shining light to be, kind of guiding in that direction 'cause it's important stuff, really important stuff. >> Yeah, we hope so, we really do. >> Well Grant, nothing but the best to you. Good luck and keep all that stuff locked down. >> Thank you, thank you so much! Thanks for having me. >> He's Grant, I'm Jeff. You're watching theCube. We're at the Qualys Security Conference at the Bellagio in La Vegas. Thanks for watching. We'll see you next time. (upbeat music)

>> Announcer: Live from San Diego, California. It's the Cube. Covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Welcome back. We're here in San Diego Convention Center for Cisco Live 2019. I'm Stu Miniman and my co-hosts Dave volante. Lisa Martin's also been here for our three days, wall to wall coverage with about 28 to 30,000 here in attendance for the 30th anniversary of the user and partner show for Cisco. Happy to welcome to the program our first time guest, Jeff Scheaffer, who's Vice President of Product Management Strategy inside of Cisco. Thanks so much for joining us. >> Thank you Stu, glad to be here. >> Alright, so Jeff DNA center, some of the environments that you have. There were some announcements on Monday, why don't we start there? Walk us through the updates to the product line. >> Thanks Stu. So we're really excited, right. >> So as you know, with Cisco, we're really building out the intent based network, in support of digital transformation for all of our customers. And one of the key aspects of the intent based network is that we have incredible programability in the network, all supported through the DNA see controller. And this week, we're really excited. We announced two new innovations in the controller. One was incorporating a new set of analytics and machine learning capabilities as part of our assurance package so that we can more quickly troubleshoot network issues. And the third is being able to connect together the multi dev environments. So how do we stitch together, the software defined access to the Software defined WAN, to the software defined data center so that we can lay digital services across the entire network. >> Stu: Yeah, it's a story we've been watching the last couple of years at Cisco is that this move to software in many ways as a unifying factor. >> Yes. >> Used to be I had all these product lines, and I need to learn the interfaces, as my friends that come to the show for many years, when you said single pane of glass, there's like, come on that's spelt P-A-I-N. Today's world, it's an API economy. And what's been really interesting to watch the last... Recently, a lot of times, it's that ml and AI underneath that spans and helps automate a lot of those pieces underneath the covers now. >> Yes, absolutely, it does. So the thing we're excited AI is a broad topic as you know. And underneath that umbrella we have built in new capabilities around the machine learning, the ability to do deep learning, as we look at anonymized data sets in the cloud on deduce patterns that people don't know yet. And then thirdly, we're looking at machine reasoning. So how do we take that the analytics to pinpoint or identify anomalies in the fabric of the network in these new IBM fabrics and then be able to couple that with a set of orchestrated automation so that we can we can emulate the behavior that a network engineer would normally do in order to troubleshoot and diagnose problems and so we're that much faster at identifying them, pinpointing the root cause and then actually being able to give recommendations if not automatically fixing it, the recommendations to resolve the issues. >> So the programability aspect, of course, we're here in the DevNet zone. So, can we dig into that a little bit? I mean I'm imagining by that, it allows me to provision, bandwidth performance, certain levels, all through API calls and it's through software. And I can set thresholds, I can talk more about what that does for me as a customer. >> Sure. So in general, within DNA center, we have a kind of very rich programability capability. It's very much an API first developed controller. So everything that we can do within the controller is a setup of published and curated API's. And those API's come in different categories. So we have API's that are around the automatic configuration and the provisioning of the network infrastructure. Very much, Dave as you're suggesting that you can run as a headless entity inside of a if somebody like a lot of service providers and partners are using this to offer a service to their end customers. And so they can automatically provision out the network and they can do that in support of new applications. We're really actually excited with that in our partnership with Red Hat, we just introduced a new set of answerable plugins as an example, to support a DevOps process by which software developers build new applications as part of that DevOps code pipeline. By using the answerable plugins, we can actually drive automation into the network to provision the networking in support of those apps. So a lot of capabilities there. >> So is the uniqueness of that you can actually do that or is the uniqueness that you're Cisco. >> I know. So to a large part of it... In terms of the way things have been done historically, and this is that most of the time, if you were to look at how do you configure a network, it was device by device and it was through command line interfaces. >> Right. >> And it's error prone, it's complex, it's cumbersome, it takes a lot of time. And so what we've done with the network controllers, is by moving above the top of the intent based network, we're actually able to automatically configure and provision either policy through policies, either QoS or segmentation for security and do that in a very automated way. And to be able to do it in a scalable way. So that is an amusing new kind of configuration mechanisms we're very proud of the work we're doing around NetComp and YANG Models and that's something that's very unique in the way we're approaching that in the market today. >> Yeah, Jeff, historically, one of the concerns was the network. It's tied to the application wasn't as tight there. It's like you talked about networking people, it's just the water that runs through the pipes that we watched with first with ACI now with intent based networking. We're getting closer and closer to that application, especially you talk about multi domain what's going on at ties right with the microservices architectures that are coming on there. So as the applications get more complicated, the network needs to be able to understand what's happening there and respond to what's needed and give back the services that they need. >> Yeah. So I think building on where you're taking that conversation, one of the really kind of key or anchor points of the whole idea around the multi domain integrations that we provided, when we bring together Software Defined access, the software defined when and the software defined data center. We're using the the rich API's that exists in all of our controllers, whether its DNA see for software defined access, whether it's vManaged for the software defined WAN, or whether it's ACI around the software defined data center. And we're integrating all three of these controllers so that they can do a couple of really important things for customers. So in the context of the application. So the very first thing is how do we provide for segmentation? So segmentation is about how do we provide access policy and drive that into the network so that the right users have access to the right applications and other people don't. And then being able to use the programability. If the user moves from say the campus to the branch, we can automatically have the policy follow the user. If the application moves from the data center to the cloud, We can have the policy automatically follow the application and that way we always ensure that the right people have access to the right applications at the right time. The other use case around the around the API's and the multi domain segmentation is that to the extent an application needs quality of service. We think about an 82% of the US we move forward in time or roughly 82% of the traffic on the internet is starting to become video on the networks and like an 8k video is 7.29 terabits per second. So how do you ensure that there's enough bandwidth and enough quality of service to ensure the latency of like virtual reality or augmented reality where latency matters. And so the other thing we're doing with policy is provisioning up the Qos, so that as you configure it in the data center, it's honored in the software defined WAN and it's honored it all the way to the end user in the software defined access. >> Stu you were saying earlier how traditional is like don't touch my network, right, okay. So Jeff, my question is if you look over the last 10 years, as you bring in the software design defined data center and infrastructure programmable and infrastructure, infrastructures code. How is that change? And is it changing the relationship between infrastructure pros and application developers and application development heads? >> Yeah, absolutely, absolutely. So kind of comes from two different angles. So number one, from the extent that every software development organization becomes more and more of a DevOps organization and they want to be able to deliver value, the experience, the velocity around the applications to production, as they go through those code pipelines through the DevOps practices, they need to be able to automatically provision out test environments, they need to be able to automatically provision out the pre stage and then automatically promote the applications into production environments. And that's what why it's so important, for example, as we as we mentioned earlier about the answerable plugins that allow the configuration of the network in support of application DevOps teams. The second thing that we find with the network engineers themselves, to the extent we've defined everything as software defined. We have this rich set of digital services that we're starting to manage in these infrastructures and through the controller that programability, the controller, network engineers are having to evolve their capability. And so, you know, we're really excited that the show that Susie Wee, who leads our DevNet program introduced a whole new category of offerings in support of how you start to become both not only a network engineer, but also development aware through for example, the DevNet automation exchange, by making DevNet certifications available through Cisco certifications. And by hosting these curated communities, where we're able to contribute new applications that run on top of our controllers. We're able to contribute new integrations, new automation, logic, new AI, ml logic, everything that's possible. And by curating it, it means it's curated code, but then it's stored in very common repositories like GitHub. It's still really excited with everything she's doing. If Cisco is going to prime the pump with initially right with apps and code started-- >> We've been priming the pump. But we've actually over the last little bit, we've developed a number of partnerships. So we have over 25 partners that have built value added applications and integrations for example, DNA center, we have a number of partners that have actually taken DNA center and wrapped it with a new kind of a new service offering a solution offering to the network. I'll give you a great example. So one of our partner that Tall tale. So what they've done is they've taken DNA Center at the core and our ability to quickly provision wireless infrastructure. And they've wrapped it with a hook telling solution for Convention Center. So think about a convention center, you have a large space, multiple concurrent shows, every one of them setting up their own wireless network with their own SSID. And so the ability to set these up, tear these down, resolve problems quickly in these high density spaces. And they built out completely as a solution on top of the programability of DNA center and our IBM infrastructure. So it's a very exciting time. >> Alright, so Jeff, some new things announced but I also want you to touch on I believe, about a year ago, API and programability was launched. What lessons learned? What feedback from the customers? Give us the update. >> Yeah, so we launched the programability. And as we mentioned before, it's a kind of a very broad ecosystem of capability. Now, the first thing about, programability is really meant to do a couple of key things. One, and probably most important, is to enable all of our customers to be able to make sure that everything's fit for purpose. So how do we integrate into their existing enterprise ecosystems. And so we know we're API first, we have SDK sample apps, we have a bunch of out of the box integrations that use all these SDK for example, integrations with service now and others. And so that's new. The second thing that we're doing with all of the program abilities, we're using it to enable the community. So the challenges we all know, in technology spaces, is that the rate of innovation continues to expand. It's like innovation is on the sphere. You know, it's the surface area of the sphere. And as every year progresses, that surface area gets bigger. The rate of innovation gets bigger and the ability to keep up with that, exceeds the capacity of most organizations. So the best way to harness that is a community based approach. And if you don't have communities, if you don't have programability, if you don't take that strategic approach, it's very hard to stay current and relevant to the market of the future. So that's another big thing that we're really excited by is being able to track that community and then an ecosystem of partners in development. >> Great, Jeff, want to just give you the final word, a lot going on in your space, any final customer takeaways or things you want people to walk away from your team from Cisco Live 2019. >> Yeah, so the present thing that I'm most excited by is that as we look at the transformation of networks, from kind of the device centricity to how do we manage segmentation in these multi domain fabrics. And do that in support of ensuring quality of experience, so the bandwidth and the latency and support of the applications. Ensuring the segmentation and the secure, being able to minimize the attack surface on these new infrastructures by driving segmentation through the fabric. It really takes kind of a systems approach to this, which is how we bring the intent based network together with, for example, the new Cat9K family from Cisco and then bringing DNA centered the controller together. By bringing those two things together. We're really helping to change the entire architecture of the industry for the next 20 years. So very excited to be here. Thank you guys. >> Excellent. >> Dave: You are welcome. >> Well, Jeff Schafer, really appreciate all the updates. Congratulations on what's going there. For Dave volante, Dave, you have a final word to say. >> Well go Bruins is the only thing I can think about right now Stu. >> That's what I was expecting you to say. So Dave Volante I'm Stu Miniman. We back, getting towards the end of three days wall to wall coverage here from San Diego, for Cisco Live 2019. Thanks for watching the Cube (techy music)

>> What are you? This's and who we are today? A za country as a university. Congratulations, Reggie Jackson. You are Cube alumni? >> No. >> Live from San Diego, California. It's the queue covering Sisqo live US 2019 Tio by Cisco and its ecosystem barkers. >> Welcome back to San Diego. Everybody who went to the Cube, the leader in live tech coverage. My name is Dave Volante, and I'm here with my co host Student of the day. One of our wall to wall coverage of Sisqo Live 2019 behind us is the definite zone. A lot of action here. A lot of the C c e E. Folks learning howto code infrastructure. A big trend in the business G written houses here is the senior vice president and general manager of the security business group Francisco. Gee, thanks for coming on the Cube. My pleasure. Thank you for inviting me. So we've been talking on the cube a lot about Cisco coming at it. Multi cloud, for example, from a position of strength, try to convince your customers that your networks air higher performance, more cost effective and very importantly, more secure, of course. And I mean everybody always wants more performance. They want lower costs. Security in many ways has begun to trump those other two attributes. They they become table stakes, security as well. But security is really number one. Now talk about that. Talk about the major trends that you're seeing. >> Well, of course, of course, security now is top of mind for everyone. Board level conversations, executive level conversations all the time. I think what ends up happening is in the past. We would think about it as network performance cost, etcetera security as a tangent kind of side conversation. Now, of course, it's built into everything that we do in the conversations that we have. And it's equally around performance, but also round simplicity, because security tends to be a little bit hard and lots of process. And how do you go through with compliance? Regulations were also folk. He's in a lot of effort on making it simple. >> Okay, so the big trendy, obviously, here's people talk about what you used to put all the money in the perimeter, hardened the perimeter. Now you can't dig a moat anymore. The queen leaves your castle. Yeah, it's a whole new paradigm. Yeah, So customers are realizing that it's a board level topic. Now, how is Cisco responding to that trend specifically? >> Well, quite frankly, what we're doing is taking that old perimeter and moving that perimeter to the appropriate spots Could be your branch. Now doing direct Internet access will move the perimeter to the branch. Could be your users. Your local mobile workforce will move the perimeter to surround those users and, of course, those applications that are sitting in the data center. Now, as they moved to and from the public cloud, we put segmentation, micro segmentation and follow them as well, to those perimeters are breaking down from one giant moat with the queen. Now we have lots and lots of little ones. >> So it's like the cubes do. You could bring it in exactly everywhere, everywhere built in. >> So you know what we know. It's a multi cloud world for customers today. One of the important pieces to help pull together the multi cloud is the SD land piece. Francisco, as a few diff different solutions in that space, an area. I was hoping you could explain that security piece of S t win, because people think of it so It's kind of like the old way, an opt or some of these other things. But security is such an important piece of that, you know, ever growing landscape. >> So you know, it's funny because people are adopting Ston for simplicity as well as lower costs, and the last thing we want to have forced people to do is to have tto bolt on various security solutions. Right then also, you know, the next day your network operations is complex again. So what we did last year was we took part of the security portfolio and built it directly into our on premises ston appliances so that you could take that ston deploy it. And so security is built in. That is a huge, huge market opportunity. And of course, since we also have a secure cloud platform, we're moving that same feature functionality into the clouds. So whether our customers want to secure their ston with technologies on Prem or in the cloud, Cisco has both ends >> covered wound. It ties into the whole development dev ops mentality and Christians appropriate here in the definite soon. But do you want to ask you how have organizations? However, there was security regimes or how are they evolving? How are they changing? It used to be okay. SEC ops. That's your problem, guys. It's your problem. And we know that doesn't work. Yes, a team effort. But talk about the organizational evolution that you're saying. >> We'll not only so the organizational effort. You were seeing a lot of the technology emerge and from an organization perspective, whether it's it's under a CEO or see. So that's a separate conversation. But from a technology perspective, they're getting heavily, heavily integrated. And that is now forcing network people to actually think about policy segmentation security muchmore than they were in the past and, conversely, security people starting to think about mobile devices and networking and things like that. So we're seeing this big blur across the organization, both from an operational perspective as well as processes and work flows. >> What about the role of data and analytics in terms of Howard informs you how that's evolving machine intelligence coming into play? How Cisco exploiting that? What's it going to >> mean for your customers? Well, as the industry leader in terms of security, we consume massive amounts of data. For example, we block 6,000,000,000 events per day. That's more than Google queries, right? We do 185,000,000,000 DNA s queries. That's 5% of the global Internet traffic. Of course, Ria's humans can't like calculate what's the good in the bad? So we rely heavily on machine learning, artificial intelligence and whatnot. We have the largest non government threat research group in the industry, and that's what they do day after day, looking for those needles in a haystack, thes threats in the sea of normal. >> And you can't do that with with alerts. I mean, just that way you've gotta have automation. So in his world of cloud, so so talk a little bit about the automation principles that you guys are done designing into your products. >> Well, security is one of the fields where not only do we have to calculate the alert, but we operate in the environment of false positives. You could turn on like we're going to protect you and block everything. But then also a lot of things that appear as threats actually weren't threats, those air, false positives. So our goal is to protect the enterprise and get zero false positive go all the way to the edge and the way we do that, of course, is not only tow, automate and say these are all your events, but we have to rank. Stack them in terms of importance. There's only a certain amount of time in the day, so you want to go to the most important, most critical event. Automate that, then go next the neck. So we automate but also ranks stack in the presence >> of false and do you see the day? Or maybe you're starting to get their ready where the machine actually acts as an agent for you and certainly, I'm sure a plugs, holes and things like that, but actually takes it one step further and makes decisions about what to go after. So >> in many cases, yes, particularly riel time around files and things like that in other cases? No, because there's a work floor flow there that says I'm actually not going to deploy those firewall >> rules >> until I test them and evaluate them and whatnot. So everything from rial time into probably >> aware you need a human and that you do, in the end, the Yeah, yeah, >> So in an ever 10 changing threat landscape. But, you know, how do you make sure you keep up? Cisco's made a number of acquisitions. How do you make it a seamless, you know, security environment for them, despite all of these various threats and attacks. >> So welcome to my day job studio. So essentially, we've done two things. We've taken all these assets, and we do accumulate and acquire the market leaders in the space. And the first thing that we do is integrate the back end. Though all those events I was telling you about, they're coming from all of these technologies, so we bring them all back so that we can focus on the efficacy. That is a big step, but that's what we do first. Then the second step, once that's done, is to integrate the front end so that the user, the customer, can sit there and go. Oh, I'm tracking an event. It came in through our email. It came in through a firewall, came through our end point and unify the front and experience. But the first thing we do is always on the back, >> so you get a lot of pressure from customers, obviously, because you are the network. You get a lot of pressure for them. But you in a position now, toe, actually lead the transformation with your customers. I mean, the whole paradigm shift, the mind, this shift. And what do you doing along those lines? >> So we are absolutely leading our customers were leading it and secure D A direct Internet access and SD win. The other thing that we've been investing heavily is in zero trust. So instead of just allowing everyone on the network and follow the threats we acquired Duo last year the leader in M F A. A and zero Trust. And now we're integrating that into the network so that we can also establish trust. But then block and verify. >> Craigie, I know you gotta jump, so thanks so much for your time. I recognize you. Thank you so much for coming. You're welcome. Great to have you. All right, keep it right to everybody. We'll be back with her next guess right after this short break, David, want a student at Lisa? Martin is also here. You watching the Cube from Cisco Live? San Diego back? >> No,