>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome to Las Vegas. It's the cube live on the show floor at HPE discover 2022, the first in person discover in three years, there are about 8,000 people here. The keynote was standing room only Lisa Martin here. I got a powerhouse group joining me for this keynote analysis. Dave ante joins us, Keith Townsend, John farrier, guys. Lot of news. It's all about HPE GreenLake. What were some of the things Dave, that stuck out to you? >>Well, I'll tell you right now, I gotta just quote, Antonio OIR said, Neri said four years ago, I declared that the enterprise of the future would be edge centric, cloud enabled and data driven. As a result, we launched HPE GreenLake. It kind of declared victory. Now I would say that what they're talking about and what they announced, I would consider table stakes. You know, I wish it started in 2014. I wish Antonio took over in 2015 instead of 2018, but I have to give credit, he's brought a focus and uh, and a, he think he's amped it up, John. I mean, if he's really prioritizing, uh, the, as a service they're going on in all in they're burning the boats, uh, and it's good. They got a lot of work to do. They >>Got a lot of work to do three years ago, John Antonio stood on this very stage saying we, and by 2022, we're gonna be delivering our entire portfolio as a service here we are with GreenLake. What I wanna get your thoughts on Keith's as well. >>Yeah. Well, first of all, I think that the crowded house was, uh, and a sign of people wanna come back together. So it's, to me, that was the first good news I saw, which was the HP community, their customer base. They're all here. They're glad to be back and forth. So it shows that they, their customer base it's resonating their value proposition of annual recurring revenue as a service plus the contract values with GreenLake are up. So this resonance with the customers, Dave, on the new operating model, that's a great check the box there. Um, I would say that I don't think HP's, as far along as Antonio had hopes, he'd be the pandemic was a setback. Um, but GreenLake is a real shining star. It's, uh, it's producing some green if you will money for them in terms of contracts, but they still got a lot more work to do because they're in a really interesting zone, Dave, because edge the cloud, although relevant and accurate where the, the shift is going, are they really there with, with the goods? And to me, I'm looking forward to seeing this discover if they have it or not. Certainly the messaging's good, but we're gonna UN UN unpeel that onion back and look at it. But >>Keith they're on the curve, right? At least they're on the cloud curve. >>They're absolutely on the curve. They have APIs, they have consistent developer experience. They announced the developer portal. They're developer centric. You can now consume your three par storage array services via a Terraform, uh, provider. They speak the language of cloud practitioners. You might struggle a little bit if I'm a small startup, you know, why would I look towards HPE? They kind of answered that a little bit. They had evil genius as a customer on stage, not a huge organization. A lot of the pushback they've been given is that if I may startup, I can simply go to a AWS portal, launch, a free trial service and run it. HPE kind of buried the lead. They now have, at least they announced preannounced the capability to, to trial GreenLake. So they're moving in the right direction. But you know, it's, it's it's table states. Well, >>Here's the thing. Here's the dynamic day that's going on. This is something that we've got got we're first of we've been covering HPE HP for now 11 years with the cube and look at Amazon's success and look at where Amazon's struggling. If you can say that they're having crossed overs to the enterprise, uh, cuz the enterprises are now just getting up to speed. You're seeing the rise of lack of talent. It certainly changing, uh, cyber security. You can't find talent. Kubernetes, good luck with that. Try to find someone. So you're seeing the enterprise aren't really geared up or staffed up for doing what I call, you know, high end cloud. So the rise of managed services is, is what we're seeing out there right now. You want Kubernetes clusters is a great set of managed services. You want other services? So that's the tell sign that the enterprises H HP's customers are now walking before they can run. They're crawling, they're now they're walking. So it's they have time to get in the Amazon lane in my opinion. Well, you >>Think about the hallmarks of cloud, obviously there's as a service, there's consumption based pricing. There's a developer, you know, friendliness, uh, there's ecosystem, which is really, really important. I think today, a lot of the ecosystem is partners, resellers and managed service providers. And to your point, Keith table stakes are things like single sign on being able to have, you know, a console being able to do it from a, from a URL to your point about startups is really interesting because that's one of the other hallmarks of cloud is you attract startups. And Lisa, we were at the snowflake summit and I asked the same question, can snowflake attract startups with their own super cloud. And what you saw was ecosystem partners developing in the snowflake cloud and monetizing. And that's something that we're waiting to see here. And I, I think they know >>You're suggesting way you suggesting that HP's gonna attract startups. >>Well, >>I, I think that's a sign if they can do that. That's a sign. And, and right now, I mean, you heard the example that Keith Keith gave. Uh, but, but not, not many. >>Yeah. I'm hoping that H I don't think HP is gonna ever attract startups, but I think the opportunity GreenLake affords the ecosystem is build clouds or purpose driven clouds around GreenLake. Mm-hmm <affirmative> whether it's the agreement with Equinix or all the cos and semi clouds, I think GreenLake gets most small CSPs, a leg up or 80% of the way there, where they can add that 20% of the IP and build services around GreenLake. And then that can attract the, the startup >>Or entrepreneurs. So the, the big question is, okay, where are these developers gonna come from? They could come from incumbents inside of companies. You know, the, the, the DevOps crowd from the enterprise, the really ops dev crowd. Right? I mean, yeah, don't you see that as a sort of a form of innovation startup, even though it's not a true startup. >>Yeah. Even though it's not, >>So Todd's making faces over there, we <laugh> >>Look, it, look it, they have >>Listen, if they don't, if they can't >>Do that, no, this is their focus is not startups. I agree with Keith on this one, they have to take care of business, home Depot. They have big customers and they have a lot of SMBs as well. They've got a great channel. H HP's got amazing infrastructure and, and client action going on. They gotta get the operating model, right job one as a service ARR, and then contract value and, and nail that with GreenLake. >>Who's their ideal customer profile. >>Their ideal is their install base. Look what Microsoft did with 365, they were going down. Their stock price was 26. At one point go to the, they went to the cloud 365, moved everything to the cloud and look at the success they're having. HP has the same kind of installed base. They gotta bring them along. They gotta get the operating model, right. And the developers that they're targeting are the ones inside the company and, or manage services that they're gonna go to the ecosystem for. That's where the cloud native comes in. That's where thing kind of comes together. So to me, I'm bullish on the operating model, but I'm skeptical that HP can get that cloud native developer. I haven't seen it yet. I'm looking for it. We're gonna look for it here. >>A key to that is going to be consistently. I, the, one of the things I'm looking for on the tech side, I, I hate to compare what HPE is doing to what VMware did with vCloud error years ago, but vCloud error on the outside looked >>Wonderful. Yes, >>It did. Once you tried to use it, it was just flaky underneath. And that's the part I'm looking to see customers pounding on it and saying, you know what API call after API I call, can I, uh, provision 10,000 pods a day? Does it scale down? Does it scale? And is it consistent? Is it >>Fragile Al roo she's co seasoned veteran? Uh, she was at V VMware cloud. She saw that movie. She gets a Mulligan, Dave. So I think her leadership is impressive. And I think she could bring a lot to the table to your point about don't make that same mistake and they gotta get this architecture, right. If they get the operating model right with GreenLake, they can double down on that and enable the developers that are driving the digital transformation. That to me is the, the key positions that they have to nail. And they do that. The rest is just fringe work. In my opinion, >>The reason why Alma was brought in, sorry, Lisa, it was, and then you gotta chime in here was to really build out that platform so that internal people at HPE can actually build value on top of it and the ecosystem that's her priority. >>We're gonna hear a lot from the ecosystem in the next couple of days, but I wanna get your perspective on, you've been following HPE a long time, all three of you. What are some of the things that you're hearing right now that are differentiators? We were just at Dell technologies. We talking about apex. We saw the big announcement they had with snowflake. We were at snowflake two weeks ago. I wanna get all three of your opinions on what are you seeing? Where is HP leading? >>I mean, HPE and Dell will, both with Dell, with apex are go, they're both gonna differentiate with their strengths. And, you know, for Dell, that's their breadth and their, their portfolio. And for, for HPE, that's their sort of open posture. I mean, John, you, you know this well, uh, that's their, their ecosystem, which I know has to evolve. And to me, their focus, you know, Antonio laid out some of the key differentiators. I, I, I think some of them were kind of, you know, pushing the envelope a little bit. Uh, but, but I think they're focus on as a service burning the, the, the boats telling wall street, this is our business. I think that's their differentiator. Is that they're, they're all in. >>Yeah. I, I think they, they try to highlight it by re announcing their private cloud service. I don't even know why they needed to announce that they have a private cloud. GreenLake is a cloud it's is a private cloud >>With block storage, hit disaster recovery. It's like good >>With like everything you get. But I think the, the key is, is that all of that is available today and you can get it in all kinds of frame of, of formats and, and frames specifically, if I'm a customer and I wanna get outta the data center and you, you know, Dave, we go back and forth about this all the time, and I wanna repatriate some workloads to Kubernetes on prem. I don't need to spend up another data center. I can go to Equinix, get GreenLake min IO, object storage on the back end, HPE lighthouse, all those services that I need for Kubernetes and repatriate my workloads without buying a new data center. And I get it as a service. I can get that Dave from HPE GreenLake, Dell apex is on the way. The >>Other thing they're differentiating with Aruba, that's something that Dell doesn't have. Yeah. And, and that is their edge play, I think is stronger than >>Of the others. Mean the, to me, the differentiator for HP is their, their history. Their channel's amazing. They got great Salesforce and they have serious customers and they have serious customers that have serious problems, uh, cyber security, uh, infrastructure, the security paradigm's changed. Uh, the deployment is changed how they deploy applications in their customer base. So they gotta step up to that challenge. And I think their differentiator is gonna be their size, their field and their ability to bring that operating model. And the hybrid model is a steady state. That's clear multi-cloud is just hybrids stitched together, but hybrid cloud, which is basically on premises and cloud to edge operating model is the number one thing that they need to nail. And if they nail that right, they will have a poll position that they could accelerate on. And again, I'm really gonna be watching how well they could enable cloud native developers, okay. To build modern agile applications while solving those serious problems with those serious customers. So again, I think hybrids spun in their direction. I'm not gonna say they got lucky, cuz they've always been on the hybrid bandwagon since we've been covering them. But I thought they'd be for a long day, but they're lucky to have hybrid. That's good for them. And I think do what Microsoft did convert their customers over and they do that, right? >>I think the key to that is gonna be ecosystem. Again, the developers need to see, especially the data piece, they talk about the cloud operating model. I think they're really moving that direction. The data piece to me is the weakest. Like they'll, they'll make claims that we can do anything that the cloud can do. You can't run snowflake, can't run data bricks, can't run Mongo Atlas. So they gotta figure out that data layer and that's optionality of, of data stores. And they don't have that today. >>Yeah. They, they, they have an announcement coming and I can't pre-announce it, but they're, they've, I've deemed them against it. They have the vision, Emeral data services, their data fabric multi-protocol access is a great start. They need the data network behind it. They need the ability to build a super cloud, a across multiple cloud providers, bringing some Google infos love inside of, uh, right next to your data. They have the hardware, they have the infrastructure, but they don't have the services. >>That's a key thing. I think one, you just brought up great point, Keith, and that is, is that at the end of the day, Dave, we're in a market now where agility and speed can be accomplished by startups or any company and HP's customers. Okay. Can move fast too. Okay. And so whoever can extend that value. If HPE can enable value creation for their customers, that's gonna be truly their, their task at hand, they got the channel, they got some leverage, but at the end of the day, the customers have alternatives now and they can move faster to get the value that they need to solve their serious problems. Uh, like cyber, like scalable infrastructure, like infrastructures code, like data ops, like AI ops, it's all here. And it's all coming really fast. Can GreenLake carry the day. And >>By the way, everything we just said about GreenLake in terms of table stakes and everything else, it applies for Dell. >>Yeah, absolutely. >>No question. It does guys. We have, and jam packed three days. We're gonna be talking with the ecosystem. We're gonna be talking with HPE leaders with customers. You're gonna hear all of these, uh, all this information unpacked over the next three days. We will be right back with our first guest for Dave ante, Keith Townson and John furrier. I'm Lisa Martin. Our first guest joins us momentarily.

>>Welcome back to Boston. We're down in the Seaport. This is the Cube's coverage of red hat summit, 2022. I'm Dave ante with my co-host Paul Gillon, Sebastian Moes. Here he is a senior enterprise architect at bit mark Sebastian. Thanks for coming to the queue. Welcome to the United States. Good to have you in Boston. >>Thank you. Thank you for the invitation. It's uh, good to be on a live summit again after, uh, those, uh, testing two years >>Strange, isn't it? I mean, people kind of don't know what to do. Shake, bump this bump, >>And >>It's like, but where everybody wants to get out of the, the home, the lockdown and, you know, there's a real pent up demand. Tell us about bit mark. >>Um, bit mark is a managed service, uh, provider for, um, German statutory health insurance companies. Um, we manage about our software that we develop, um, is for about 85% of the, uh, German health insurance companies. Um, we have, uh, not only do we build the software, we also have data centers where we run software for, for our customers. Um, and it's everything that a health insurance company is, uh, mandatory to have to run their business, so to >>Speak what, what's the life of an enterprise architect like these days and how, how has it evolved? How has it changed? Uh, I mean, independent of the pandemic, will we get to that, but, but, you know, technology changes, organizational objectives of, of changed the public policy changes. How, how was your, the life of an enterprise architect changed? >>Um, well we, we have this, uh, big monolith JG E application that is, uh, run on JBO. Um, and now we want to, we want to change that into a more modern environment and using, uh, OpenShift to do that. Um, and yeah, there's, uh, there's a lot of reg regulatory things that come up that need to be, um, need to be figured in. Uh, there is new demands that our customers have that we need to figure out how to get to market, uh, and to be able to deliver software more faster and, you know, make the turnaround, uh, or have the turnaround be less. >>So kind of following the technology trends of going from big monolith to microservices and containerization and distributed data, the, the, >>The whole, the scalability, uh, you know, and quick turnaround, that is, that is the main focus. >>So the application that you're here talking about this pace to face in application, kind of a new market for you, a new direction, is this part of that overall shift to a more modular microservices based, uh, >>Structure? Um, well, we, we, we had applications like this before, but this is a new branch of it because, um, there's a strong drive in Germany too, for more digital digitalization. Um, and to have a new interacting model with the customer from basic things to more advanced features like medication services, vaccination status, um, managing your allergies, and that's an edit value that we want to give, uh, for our customers. So they can, their customers can benefit. >>I dunno what it's like in Germany, but in the United States used to call up the doctor and say, Hey, can I just, can we do this over the phone? No, you gotta come into the office. Mm-hmm <affirmative> and then of course, with the pandemic, it was like, you can't come into the office. It was just total flipping, cuz you could get 80% of what you needed done, and this is what your app enabled essentially. Right? >>Yeah. And, and some that and some added value as well, uh, to, to give, um, yeah, a benefit for using this, uh, online interaction for, um, the insured people, the, the patients, >>Essentially a digital gateway, including your data. Well, that's the other thing you can't get right. As a patient, you can't ever get through your data, it's like right. You >>Get it, but nobody else can >>Get it. <laugh> sometimes it's hard for you to get it cuz of again, in the United States, HIPAA and the, and the, and the requirements for privacy restrict often access to, to data, you have to go through hoops to get it. So, uh, so, so that experience is what you codified in your application. Yes. >>Um, yes, we have this, uh, unique data set of all health related information that people have to, uh, interact with in, in when they're sick or when they deal with their healthcare company. Um, and yeah, we wanna provide that data to the customers. So they're able to look at it. Um, there's also the, uh, electronic patient folder. You can say, um, where there's data like medical exams and stuff in there that they have access to. We provide that as well for, for our customers. Um, but, uh, yeah, it is about the interaction and that I can see when I put something in to my insurance company via email or the doctor put something in that I have the interaction on my phone and see when it was delivered, um, to them when it's active, when I get the money, stuff like that. >>Now this application is built on OpenShift, it's cloud native, uh, has all the constructs. How different was that for your development team from building something like you mentioned, the monolithic Jbos application that you already have, how different was building the cloud native, uh, >>Constructs. Um, it is quite different. I mean, it's building software, there's a lot of the same things involved. We've been, we've done agile and scrum, uh, before and so on, but we now have a, um, we're trying to be, or no, we're actually achieved to be faster in bringing this to market, um, deploying it in different data centers, doing it all automatically doing automatic tested, uh, right as part of the pipeline. Um, there's, there's a lot of huge steps that we can, we're able to take because of the technology. And that's why we did go there in the first place. That's why we said, okay, this is, it needs to be, uh, cloud native. >>You found that red, red hat had the full suite of tools that you needed. >>Um, yeah, I mean, we, there's some open source stuff that we've also integrated into the pipeline and everything, but there's a lot of, for example, we are using the, uh, three scale, uh, the API management from, from red hat, um, just to be able to, um, use the functionality that we build, that the customers can use the functionality in other products that they use that serve partner people, uh, uh, certain partner companies can, are able to use the services as well. >>Okay. So the, the, the dumb question is, but I'll ask it anyway is you could get this stuff for free Kubernetes, open source, you know, you get E Ks for free. Why didn't you just use the freebie? >>Why? Um, well, we're, we're on a scale with so many, um, uh, customers and data centers that we have to take that we do need support in, in a way. Um, and I usually say, so if we take software from whoever, whatever company it is, we're gonna break it. Yeah. <laugh> um, the, the, the transaction load that we have is, is quite, uh, intense and the performance that we need, uh, especially in the, in the business to business, um, market is, is so big that we do need the interaction with, with a vendor and that they're able to help us, uh, with certain escalations >>German Germans play rough. So <laugh>, um, you know, when a, when a vendor announces an innovation lab, I always go, okay, that's an EBC, like an executive briefing center. It's all gonna be used for sales. But my understanding is you actually leveraged the innovation labs. It was actually helpful in building this application. Is that true? >>I, I, I actually, uh, to part in the open innovation that we did with RA hat, and we knew we knew what we wanted to do. We, we knew the technology, we knew what we wanted to have done, um, but they helped us to, to get there step by step with the, with the tools they have, the, um, uh, you know, the ways of working and how this is, this is built. It really lends itself to, to build that step by step and worry about some stuff later and just do it. Um, yeah, piecemeal, >>This is Al is also a new market for you. It's your first real business to consumer facing application. That's that implies a very different approach to experience design, uh, to how you >>And performance yeah, >>Yeah. Perform exactly. Uh, how did your development team adapt to that? >>Um, well, there's, there's, you know, certain things that you build into the process, like integration, testing, automated integration testing, where the application just gets checked right after you check in your software. Um, we built in low testing to, you know, we have an idea of how many transactions per second, there will be. And so the low testing takes care of that as well. Um, and that is easier if you have a small piece of software instead of the whole monolith that we usually have. And so you, we are able to, to build it quicker and get it out quick in, in hours. >>How, how have you, um, accessed customer feedback, you do your, you know, net promoter score surveys, what, what's the been the customer reaction, your, your consumer >>Reaction? Um, they, they, I mean, I'm kind of the wrong guy to talk to, to, uh, about <laugh> to >>Talk about, come on the architected, the thing. >>Yeah, I, I did. And, and then the feedback has been, it's been very good so far, uh, and we are pretty happy with it. Uh, it's it's running, uh, very well. Um, I don't quite know how they got there. Our customer does, uh, you know, uh, questionnaires and, and stuff like that. Yeah. We have a, a different depart, uh, department to, to solicit feedback on that. But from what I hear, uh, it's, it's received very well. >>One of the cloud native features, I understand you used extensively with APIs, uh, for integrations. How are you making this application accessible to partners? What, I mean, what are you exposing? How will you use those APIs to enhance the value through, through an ecosystem of >>Partners? Um, well, we document them, um, and so they're out there to use. And as long as there's a, um, a security process within, um, em that we have in front of it, um, they're open source, um, APIs. So, uh, as I said, they have other programs that they wrote themselves or that they bought that are able to use those APIs, um, from an open API document. Uh, and, and just interact with that as long as the user is, uh, authenticated, they're able to, to get this data and show it in a different context and use it in a different context. >>Did you play golf? >>Um, I used to time ago, not anymore. >>Now, do you know what a Mulligan is? Yes, I did. Okay. If you had a Mulligan, you'd do this all over again. What, what would you do differently? >>Um, an interesting question. I, don't not sure. Um, you, you say you're smarter after, after you've done that. Yeah. And, and of course there's, uh, there's, there, there there's certainly were things that I didn't expect that would happen. Um, like how, how really you need to go modular and on, on everything and need your own resource and infrastructure. Um, because we came from a very centralized, um, uh, scope. We had a database that is a big DB database, um, and now we're going into smaller database and not decentralized a lot. Um, and that was something that the extent of it, I didn't expect, I, I wanted to use more smaller things. And, and that was something that we very quickly learned that no, we need really need to separate stuff out. >>Was that an organizational sort of mindset shift? Um, are you, are you rethinking or rearchitecting your data, um, your data architecture as part of that, or is that more, or is this more just sort of tactical for this app? >>Um, no, we're definitely need to need to do this because, uh, it really gets, um, or it really is a, um, something to handle a, a big pool of data is, is really a challenge or can be a challenge at times >>To scale, >>To, to, to scale that up. Right. Yeah. Um, and so, yeah, we are going to, to separate that out and double some data. That's, that's gonna be a thing it's gonna be more data at the end, but since it's scaled out and, and decentralized, that will >>Help a lot of organizations would say, well, we wanna keep it centralized monolithic, which is kind of a negative term, but I think it's true, uh, because it's more cost effective. We're not gonna duplicate things as much. We're gonna have roles that are dedicated, but it sounds like you're seeing a business advantage of distributing those functions, decentralizing those functions to a >>Extent, right, right. Because if you, if you have a centralized Mon monolith, then it, I, yeah, it might be negative, but it really is. It's a good working software. Um, but to have that, it's, um, it's really hard to release new features and new, new, you know, even buck fixes it, it just takes time. It, it is, uh, uh, a time consuming process. And if you have it decentralized and in smaller packages, you can just do, Afix run it through the pipeline, have the testing done and just put that out within hours. >>How important was it to bit more to build this application on an open source platform? >>Um, the open source didn't come so much in our perspective of things, or we didn't consider it that much. It was just, this is there. This works. We have a good support behind that. Um, we are, our, our coach is not open sourced, then we're not going to anytime soon tell about it. Um, we're actually thinking about having parts that might be, uh, a kind of open source dish, uh, just in the healthcare community kind of thing. Um, but, uh, yeah, no, that didn't F factor in as much. Um, it was just something that we had >>Experienced another architecture question. So you've got the application stack, right. If I can use that term, although application development tools that you build use to build the application, and then you've got the data that the application needs, how are those architected, are they sort of separate entities? Are they coming together? >>Um, we used to have, we used to have, uh, uh, data, um, net a, a, um, an MDA approach, a J hue. Um, so they're very strong connected. That is, there's just in the database. There are models and entities that we use in the, in the JBO. Um, and well, we're still gonna use hibernate to, to, uh, to do the G GPA, but it's, uh, yeah, it's something that needs to be restructured because it just takes a lot of resources to manage data from different parts of the application, bringing them together, um, that will, will need to change. >>And what about new data sources? If I came to and say, Sebastian, I need to inject new data into the, the app. I need to get this to how, how, how difficult or, or fast easy is that, >>Uh, now in the, in the world now, or actually we wanna >>Compare, can you compare before and now, I mean, it wouldn' have to happen before would be >>Like, in the time in the timeframe it's, it's, it's not, it's hard to say. I mean, but if you have a project right now, we're talking, uh, months, um, like a year to, to get it done, get it tested, and then it even takes, um, up to a month to before it's out to every customer. Yeah. The rollout process takes some time. Yeah. Um, and we're planning on, or we, we developed the new, uh, the new software we developed in a couple of months. Uh, and then it is deployed and then it's in production and it's in production for all the customers that wanted to use it for now. I mean, it's not deployed to all customers yet, uh, because they need to adapt it and in their way. Um, but they have it, you know, it's, it's right there. It's deployed. Yeah. When we fix it, it's in a, you know, hours, couple days it's out and it's out in production, in different data centers for different customers. >>And we've come full circle the life of a, of an architect. It's, uh, it sounds like it's much better today. Sebastian, thanks so much for coming to the cube. Appreciate your time and your insights. And thank you for watching. Keep it right there that you watching the Cube's coverage of red hat summit, 2022 from Boston, Dave Valante for Paul Gillon, we'll be right back.

(Soft music playing) >> Narrator: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a CUBE Conversation. >> Hello, this is Dave Vellante. Welcome to this CUBE Conversation. We're here with Scott Strickland. Who's the executive vice president and CIO of Wyndham Hotels & Resorts. Scott, great to talk to CIO's, thanks so much for coming on theCUBE. >> Thanks for inviting me, Dave. >> You're very welcome. All right, let's let me, let's get into it. You guys, Wyndham Hotels & Resorts, obviously that industry hard hit by the COVID pandemic. Uh, I got to say though, your executives doing a great job, you guys just had your earnings call. Your stock is more than doubled since the March low. So obviously hanging in there, well-run company, but how did the, how did you respond to the, to the, and adapt to the COVID impact? What was your first move? >> Our first move, um, when we looked at COVID, we're on the sharp end of that proverbial hospitality spear. You know, we're in an industry where people are going to see this first and COVID is going to be very apparent as people stop traveling. So the first thing we saw is actually in China, because we're a worldwide company. We saw obviously the impact of COVID there. So we had a little bit of a head start in terms of planning here in North America. And we were already planning for possible hotel closures and for different work environments. The very first thing we did was actually take our corporate staff, roughly 1400 people off campus in a 36 hour period. And we're really, really proud of that. The second thing we did was, we looked at how do we help our franchisees as they consider possibly closing their hotels? Or how do they react to a much lower occupancy type environment? >> Yeah. So, okay. So you had like a canary in a coal mine with visibility in China. You didn't, you didn't wait, you acted. I want to bring up a chart guys, if, if you would. Um, this is data from our data partner ETR, and every quarter they go out and ask customers, you you going to adopt new, you going to spend more, that's the green, are you flat spending? Are you going to decrease spending, or are you going to kind of replace the platform? This is specific to Zscaler and you can see, and this was taken, Scott, right at the height of the US lockdown. And so what impressed me is that well over half, well, 52% of the customers that they talked to said, they're going to spend more on Zscaler. Now of course, part of that was the work from home pivot the investment in security. But I wonder Scott, if you could tell us, what does this picture look like for Wyndham? >> So as we were migrating off site, we realized that we needed a different set of security solutions for us. We had implemented Zscaler from an end point security. They have additional security in terms of putting applications behind them. So they can serve almost as a VPN and you don't have to leverage VPN to get to some of your apps in the future. And we're going to be spending more with them actually to implement that solution. So for us, we're going to be in that box, in that eye area there, where we will be spending more with Zscaler in the next six months than we did in the prior year. >> So what, what do you think happens with this kind of work from home? Um, basically you saw, I just saw Twitter said, "Hey, we're going to make it permanent." Other companies said, "Hey, we're going to make it through the end of the year." What's your thinking in terms of that work from home, you know, hybrid, how are we, how was Wyndham going to respond going forward? >> On a go-forward basis, we're going to go to a hybrid model. So what that'll mean for us is we're going to be looking at the equivalent of shifts, almost, so two days on, a deep cleaning, two days on and rotate that through so that you have different shifts of people who necessarily aren't, aren't interacting with each other. We also, before we even went off site, we were looking at a work-from-home model and what COVID did, is it really accelerated it for us. So when we go back into the offices, we're going to have roughly 20% of our staff, that's going to remain as Twitter referred to them as "permanent work from home." These are roles that only need to be in the office once every two to three weeks. And then we're going to go to that rotational schedule for the rest of the folks for that phase one. >> So one of the other things that our friends at ETR looking into is sort of what CIOs are expecting, in terms of the shape of the recovery. People talk about a V-shape, uh, which, you know, some people expect, but not most, most people expect some kind of U shape recovery down for maybe a couple of quarters and then come back over the next several quarters. Or an L shape down for three or more quarters. And then very slowly coming back, you know, maybe into the late '20, '21, some of the harder-hit industries like airlines, you would expect that. What's your thinking in terms of the shape of the recovery. >> As we look at the recovery, we try to make it a database decision right now. And so we work a lot with Smith Travel. They provide most of the data actually for the hospitality industry. Looking at occupancy and guests preconceptions, are they willing to come back in? Are they willing to check into a hotel? And what Smith is forecasting right now is a very gradual U over the next year and a half or so. Now that said, we believe that we're well positioned in the industry because as people do start to travel again, we believe they're going to want to go to "drive-to" hotels. And with 9,000 plus hotels worldwide, and the top economy brands around such as Super 8 and Days Inn, those are classic drive-to hotels. You know, you're going to go drive and visit your parents, who you haven't seen in a while. You need to stay somewhere overnight off the highway. You're going to check into a Days Inn, we believe we're going to be well positioned to capture some of the initial market share when it does return. >> Well, true. I think people, I mean, people have cabin fever and young people I think are going to be more receptive, you know, people with a lot of disposable income. So I think that could actually bode well, and it'd be some upside for industries like yours. I want to talk about, you know, get into the security aspect, the cloud. Um, you obviously have a CSO. Um, We'll talk about that. You, you, you were, uh, your CSO was a peer, uh, is that right? How, what's your relationship to your CSO? >> Sure. So at Wyndham hotels and resorts, the CSO reports into me, he reports into IT. He's a group vice president level reporting into me as an EVP. However, really when we think about it, I, I treat him as a peer. And what I love about having him in my group, is he can be part of those technology decisions and the development cycle from the beginning. So what that enables us to do is we're not coming along later and putting security into one of our products. He's part of the security decisions as we develop our products. Whether it's an application, whether it's an infrastructure, whether it's even a new networking solution. He's part of those decisions from the beginning, which has been great. And he's the type of guy actually, that the rest of my teams want to work with. And they want to work with his security teams and ask them questions. So he serves as a trusted advisor for us. >> So that's an interesting model. And I think it's one that's going to gain traction because, you know, if the, if the security team is sort of an isolated island, you know, it's sort of all falls on them. You've got a seat at the table. Security, of course, as we know is a board-level topic right now. So let's, let's talk about your environment. I kind of want to talk about, you know, pre- and post-COVID, but also pre- and post-Zscaler. So let me, let's paint a picture. You know, a lot of organizations, you've got the corporate headquarters, you've got a lot of appliances. Um, You've got, maybe got people working from home, tunneling through and a VPN. You got your data center somewhere, but you've got all these cloud apps as well. Um, So it's a changing environment. You've got to bring your own devices. What did you know, go back a little bit, however much is appropriate. What did Wyndham look like in the pre-mode? >> So in the pre-mode we had seven global offices scattered throughout the world. And our main office on the Parsippany campus was roughly 1400 people across two buildings. We used a classic, uh, Cisco sort of infrastructure with multiple redundant data lines brought in, and then the heavy duty switches that didn't turn off, loaded it into a wifi network as well. We then had a dedicated line out to our co-location facility and that in turn, then served out into our public cloud, such as an AWS or Google. So that was our pre picture. We were in process. Even prior to this, we were in the process of saying, okay, we have some of this legacy hardware in it and the Cisco-type environment, how do we deploy that so that it can be cloud first? So we were halfway through a Meraki implementation all the way from the switch level and the wifi level so that we could administer that remotely. And what this has done for us is we've actually accelerated that implementation. Uh, the good thing about everybody being out of the office is it's pretty easy to send one or two people in, to complete some of that work in the closets and get our backbone adjusted. So what we've been doing is we've been working at fixing that backbone, replacing it with the Meraki switch and wifi equipment so that we can remote administer it from anywhere in the world, which is, is suddenly has opened up a whole new level of ability to follow the sun, ability to possibly even outsource that or leverage lower cost resources to do some of that. They don't have to be based here in the New York, New Jersey area. >> So maybe the big sort of challenges that you face. A lot of organizations will tell us, you've got different users coming in from different apps. They've got different security policies, uh, different standards, you got shadow IT, um, with, with, you know, not really enforcing our corporate edicts. Uh, what were some of the challenges that you faced that maybe the objectives of bringing in Zscaler? >> Sure. So the last part that I didn't really cover, that it'll help play into some of these challenges is our co-location facility. Originally we had three data centers and we migrated those three data centers largely into the cloud, into an AWS or into a SaaS-based environment. But for some of those applications that just you can't, we put it into a co-location facility and then paid a third party to manage that, so that we're out of the administration and data center business. So that's, that's part of that pre so when this came along and we suddenly said, okay, how do we lock everything down? How do we ensure that we understand how people are going to access this? Um, we only had two or three applications that had a significant user base where we needed to invest in VPN, where we needed to ramp up our VPN licenses because suddenly everybody's going to be at home. >> For example, the beautiful part is, is what we had our, our biggest applications. Those were already cloud-based. So those were already being accessed by people who just had a network connection. And that was why originally we chose, we chose Zscaler because we wanted our folks no matter where they were. And the classic example, our CSO was working there at Starbucks and they need to access our HR, uh, SaaS-based application. We can do that with confidence, from a Starbucks or from a coffee shop, you know, any coffee shop in the world, because we know we have Zscaler installed on their end point because we know it's going to go through that level of scrutiny and we'll have that protection. So even if the network is being sniffed or there's something weird going on, there we'll be protected. So Zscaler has been a partner for us on that for about a year or so. And then I spoke earlier a little bit about us, uh, looking at their VPN-like solution where you put the applications behind Zscaler so that you no longer have to go in with VPN and double-click and get a token from a company like RSA or something of that nature. You can just make it, you know, a virtual application that you can access via Zscaler as well. >> And let me just understand Scott, that would be essentially like a security cloud that you would be putting in front of all applications or just your private applications. >> That's a great way to think about it, Dave. Yes, is it would be a security cloud that we would put in front of all of our applications. So we have it in front of our applications that are SaaS-based, and then we would start putting it in front of our applications that are based in our co-location facility. >> So Scott, when I talk to CSOs and I ask them, what's their number one challenge, they'll tell me "lack of talent." "We've got all these devices and we're running around and we just can't find the talent." So I'm wondering, is that a main challenge of you and what is the business impact of this sort of new security regime that you're putting in place? >> So what's really worked well for us is we've been able to recruit some of the best and the brightest and keep them here because we're continuing to implement these cloud-based security tools. So Zscaler's, one of them, we have others in our suite there, and that's what excites security guys and gals is that they get to play with some of the new toys and we get to migrate from something that was legacy to something that's brand new and they continue to get to improve their resume. Yes, but they also get to play with play with the new toys and some of the shiny new objects. Our retention rate in our security team is unheard of in the industry. We are single digit turnover, voluntary turnover a year over year on our security team. And again, these are guys and girls that could go into the city and make more and they purposely chosen not to because we let them be at the front edge of, of security. >> Well, that's, that's a pretty interesting metric. Because a lot of times you guys don't, like air traffic controllers, you know, the eyes bleeding, staring at screens all day and it's, you know, you got to, you got to win every day. You know, the bad guys only have to win once. But, but so, okay. So what has been the business impact of sort of this new approach that you've been taking, this sort of cloud-first approach? >> What it's allowed us to do is to look at the threats that are actually most important. So if you look at security, you know, you have your traditional DDOS attacks, you have SQL injections, you have some of these lower-level type attacks by automating a lot even. And by putting it into the cloud, we're not worried about most of that anymore. What we can really focus on now is the state-sponsored agencies or the criminal agencies that are coming after us with very, very sophisticated phishing attacks or mail. We had some physical mail attacks recently that are trying to penetrate us in ways that we've never seen before. And again, that's exciting for the security team because they get to focus and they get to almost think like one of these hackers and say, okay, if they're trying to get in here, where, where do we believe we're not protected? How do we go on the offensive a little bit here? We have, we have a threat-hunting organization as well. >> And I'm actually, if you had a Mulligan, I don't know if you golf of, if you do, hopefully. >> I do, I do every time Dave, >> Yeah, yeah, you know, my, my golf, my golf club went out of business. I got to find another one. But, but if you had a mulligan, what would you do over again? What kind of advice would you give to your peers? >> My mulligan on this would have been to have moved faster. When we started, our original migration of the cloud back then even then there was concerns about, can the cloud be as secure as your physical data center? And the answer there is absolutely yes. If you've ever toured one of these Tier Ones, you know, such as an Amazon or a Google and you take a look at their security versus our physical security, tear off that band-aid, execute the migration, and wherever possible as you do that migration, don't go a legacy-for-legacy. Don't do a lift-and-shift. Instead, take the opportunity to transform, do a lift-and-transform while you're doing that. Not a lift-and-shift. So my mulligan would be go faster. And if I got a bonus mulligan, then I'd say a lift-and-transform, not lift-and-shift. >> Yeah. That's great advice. I mean, I tend to agree with you. I think that the work that we've done in the research that we've done really underscores what you've just said. There is a shared-responsibility model, uh, but shared responsibility is great. Uh, when you, when you're working with a, like you say, an Amazon or an Azure or Google. Um, so last question is, you know, when you look forward, we've been so tactical early putting out fires, but as you start to come out of this thing, how do you see, you know, some of the things that you're going to preserve from the past maybe, but what does the future look like? I mean, it's kind of ironic. This whole thing hit at the start of a new decade. So I think we all agree. And maybe, maybe you do too. Maybe you don't, I'd love your thoughts. We're just not going to go back to 2019. So as you start to think of the, the midterm and the longer term, what's your, what are your, some of your planning, assumptions, and some of your thinking? >> They say, Dave, "never to waste a good crisis." And we've learned a lot out of this crisis. Uh, one is that we don't need a traditional work-from-home model, and we're going to be able to collapse actually our, our campus down into a single building, and then go with that shift, uh, approach that I spoke to earlier. If I look forward into the medium and the longer term, what we're seeing is we're seeing that our franchisees and our guests, things are going to change. When you check into a hotel, you're going to want to have that as contact-less an experience as possible. So how do we offer the technology at scale to our guests and franchisees to enable that? That's beyond just mobile check in, and that's beyond mobile checkout. You know, that's keyless entry, that's mobile payments. That's the ability to choose my room, perhaps on my mobile device. You know, there's, there's a whole new world. I believe that's coming, ordering my, my room service on my mobile device from my room without leaving my room. You can start to see it in this brave new world, you know, post-, post-COVID that we're going to be able to leverage a lot more contact-less, a lot less face-to-face technologies, but still enable a good guest experience when they're at our hotels. >> Well, I'm excited about that because I mean, as, as theCUBE, you know, our businesses do go into events. I mean, mostly because we're all in the studio now, but we do a lot of travel. And this notion of accelerating the digital transformation and leaders like yourself, Scott, really driving that, I'm excited about the new experiences. So I really want to thank you for coming on theCUBE and sharing with us the best practice and, and your journey. Appreciate it. >> Hey, thanks for reaching out, Dave. Good to be here. >> All right. And I thank you for watching everybody. This is Dave Vellante for theCUBE. We'll see you next time. (soft music playing)

>>Yeah, >>from The Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Everybody welcome back to the Cube's coverage of the IBM think 2020 digital event experience. My name is Dave Volante. Manish Gupta is here. He's the global managing director for chemicals, petroleum and industrial products that IBM Manish. Thanks so much for coming on The Cube. How you doing out there in Saratoga, California? All good. >>I'm doing great. I'm doing great, given, considering everything. The role of all of this. >>I mean, right, it's tough times, but look it, We can still, you know, have a smile every now and then, right? I mean, you know, it's very nice for a lot of people in our hearts. Go out. Everybody there. So I I want to start off one of the areas that you're steeped in is the energy sector. You know, generally, people are very much concerned about oil. Price of oil drop below, you know, zero went negative. People have been paying people take oil and understand that was a technical, but still the prices of depressed >>I >>learned about credit risk and the like. But what's your take on what's going on in the energy sector right now? >>Yes. So I think the companies that, uh, that have taken on a lot of debt and don't have a stable operating conditions will naturally suffer through this in the oil industry. Clearly, until the prices come back with will be as demand picks up, that would be several months to more than that. As we can imagine, we'll see the The more stable companies, the more I'll say companies that have ah longer balance sheets survived for sure. In addition, you know, the the other aspect of it is of course, they're all double down on making sure your companies and your free services companies or double down on productivity conserving cash as well as considering how they accelerate. In my view, there transition are more more profitable areas of growth as demand comes back, >>is there? Is there a silver lining here? I mean, in normal times, you know, of the oil price drops and the like, a tax cut. Um, I know the government. The United States government, anyway, has been beefing up its strategic reserves that has a history of buying low Is there any good that you see coming out of this? So >>So I think the good that'll come out is is surely that the stronger companies will come through more successfully. The company that have taken less risk, the companies that have that have invested in more more stable operating platforms and and at the end of the day, I think, the companies that have taken a more future proof strategy for their business portfolio. So whether you take a B B, for example or a shell, they're actively working the words deporting the energy transition. I think that will be the You'll see an acceleration of companies starting the thinker off where they need to go in the future. You support the energy transition. I think the silver lining of the end of the day will be, Ah, that as is, sometimes you just said oil is very precious. Resource, therefore, should not be burned. And and so the question at hand is, you know, what do you do with with all the oil that's available? What do you build out of it? Whether it's petrochemicals, I think that transition to more future proof product portfolio on business model will be will be truly the silver lining. >>How about the broader industrial companies that you follow? I mean, they were sort of moving down a path of digital transformation. I o t obviously is the big theme within many industrial sectors. What are you seeing in the broader? >>So I think in the broader base clearly, you know, supply chains and the spread of barely, you know, demand demand dropping prior demand signals which were sometimes ignored for historical reporting. Ah, that that is now becoming more important. I your sense and response by then. So as you step back and look that that they need to maintain business continuity is, of course, the highest priority. But as they come out off this, we expect that we're thinking of this is as the future for industrial sector will be. What we would call is hybrid. I you know, supply chains will need to be local and global manufacturing will need to be both traditional. A swell is additive. I you know, you you produce more, more locally and in addition of products and services will need to be a combination of digital and and physical. And at the end of the day if you step back. I saw something recently that said, Ah, you know who's leading the digital transformation in your company Now the multiple choices were the CEO, the CDO CIO, or is it? And this option was circled over 19. If you think of it in simple terms, covered, 19 is creating the acceleration of digital transformation because the only valid response in in my mind as you look at these ah as these different hybrid models is a consideration of technology being being a fulcrum off, getting a future proof of black mom. >>So it would seem to me that the financial framework are going to change. The The notion of how you made money for the last 10 years is not going to be the way you make money going forward. Yeah, there's there's likely to be some share shifts. In other words, those that figure out how to be profitable with this sort of new model perhaps could gain share efficiently. And and maybe you're going to see some share shifts in the industrial zone. What are your thoughts on that? >>Yes. So companies that are in what we would call essential of vertical industries will definitely be the ones that they continue to grow. You take a simple example, or for spectral chemicals companies, companies that make make plastics as well as chemical, they're going to a variety of other applications. Plastics. Interestingly enough, it's now a resurgence, and the reason it's resurgent is it's really it's a boarding, you know, hygiene, packaging, medical packaging, etcetera, etcetera. We'll see industries that shift that way if we step back and look at a broader and broader ah study that was done actually about 10 years ago by Harvard. With that, the companies that survive a recession, I think it said about 9% of the company's actually flourish coming out of a recession, about 75% take three years to recover and on the remainder was. I think if you do the math about 17 18% Ah, do not survive. But to do such a recession now, the ones that drive through >>I >>had a dual focus on both the customer experience and customer engagement and shifting to areas of higher value by thinking of what they should be doing and how they should be doing doing those things and Secondly, they also focused a lot on on operational improvements. And whether that's obliging, that's manufacturing. It's whether it's outsourcing non core functions. Automating that's a problem that you're focused on customer on operations is the hallmark of a successful outcome. Was what the study studied determined putting that that that your focus is what will be the the prime hallmark as we come through this >>interesting it Now, of course, biology sort of got us into this problem in technology. Deal with some of these issues on Help us get out of this problem. And what specifically is IBM doing? >>Yes, So we've We've identified seven areas off focus as we think of off coming out of this crisis, and we have referred to those 78 years of off focus as being our emerge. Stronger areas of focus the ones that I think are relevant, are including new ways of working. Ah, cyber resilience. Thinking of extreme motivation, automation. An intelligent work flows thinking off, making sure that we are eating our clients with having more in a more system that are available on demand, helping them create platforms and applications that can work regardless of the location At the end of the day, we step back for a brief three areas of focus that we see will be new. It new ways of working and supporting work. They're working or remote working. Ah, extreme automation. When industrial companies come back to work safe, distancing, he's going to be the norm as well as allowing for but the fact that you want to be you want to be prepared for the next crisis. Therefore, extreme automation, whether that implementing robots and factories or or implementing solutions that guide you in the worker safety or workers being close together as well as supporting customer engagement or the customer experience is being done. Putting that extreme automation layer through so that so that the reliance and the ability to cooperate with out the workforce becomes more important. I think it's really the acceleration that we expect. We'll be able to support our clients with, uh, as as they come out of there soon, as they as they had after the next normal. >>You see software robots as being a part of that sort of automation friends, you know, r p A and the like >>for sure that that's an important part, especially in the back office functions that will be software robots and, I think, layered on top of that when you buy AI. Then you have AI augmenting a lot of professionals, whether it's chat bots in customer call centers or technical service centers or or it far greater increasing in automation processes that could be automated. But then the AI would would support for the rest that can't be simply automated but need intelligence support as well. >>So if I go back to your CEO of a Harvard study, last thing I want to be I'm on the board just feels, is in your 17%. I either want to be in the 90% if I'm well positioned right now, and maybe you have an opportunity to do so. But if not, I'm in that fat middle. And I really wanna be ableto come out of this stronger, even if it may might take a couple of years. So my question is, it seems like companies, they're gonna have to, at least in the near term, potentially sacrifice profitability in order to gain that business continuance, business resiliency that you talked about. Can they can They have their cake and eat it, too. In other words, can they maybe take a near term hit on profitability? But they ultimately become more successful and more profitable? Maybe using data >>the data would be one thing. I think the other part of this will will using data, for example, to predict demand forecast where where the puck is going and the use of data on on a monthly basis is going to be inadequate. Clearly right. Getting more more capability for real time demand sensing to create platforms that allow us to allow companies to understand where needs are emerging so that they can pivot there. Ah, their product portfolio accordingly, Collaborating with customers in in a far more I'll call it CO create crowd source way Ah would create more resilient customer relationship that come out in the future as well. And at the end, I think they'll be also an element around asset like strategies, which requires partnering with IBM suppliers etcetera, which then allow data to be the foundation where you can essentially say I'm using this much of this capability our forces, I'm investing in insignificant of capital a place. >>So when I talk to executives. I'm hearing the consistent themes We very much are concerned about the health and well of our of our employees getting remote home infrastructure going once we ensure that they're healthy, we want to make sure that they're productive getting staying close to customers for sure. Making Short Foster are in line because there's so much uncertainty. But not a lot of time right now is being spent on sort of the long term strategic aspect of the organization that maybe will come back slowly. So what advice are you giving the organizations right now in this situation? >>Yeah. So I think the biggest focus would be, as I think, Winston Churchill said, this never based a good crisis. Eso So considering considering that as being the backdrop Ah, these are the times when, when recognizing what would be the sources of value, like I said before making sure the dual focus is kept in mind, apart from of course, ah, employee health and safety and engagement. Ah, then then, in addition to that, keeping in mind that the localization off supply chains will need to be a big topic keeping your ah, as they say, powder dry for but the opportunity of buyer and march. I would also be an element start considering how you re configure your supply chain. And at the end of the day, another important element would be making sure that you are Ah, you. As you come out of this, don't lose sight off sustainable development. No as well as you go back to the things off the fact that since digital will be an important fulcrum come out the other end apart from the other elements we talked about that you start prioritized those digital transformation programs that focus on both operations and supply chain as well as customer engagement. And that becomes a key focus and no longer just driven by, Let's say, the straight business case, but also persisting and ending. The resilience will come out and deal with people prices as well. >>So many of those things that you just mentioned might have been culturally challenging for a lot of organizations prior to over it. But in a way, organization's going to get covert Mulligan or the CEO. You know, the boards of directors might have felt like okay, we had to make some changes, but we got to be careful now with Covic being such a disruptor. Uh huh. Organizations been really drive forward and set up for the next decade. Bring us home. What do your final thought? >>Yeah, I think boards and see years have Do you have to really think of this in stages and and start to Of course, the initially the start of this crisis was not not planned, but recognizing that this recovery will appear in stages, so we think of it is respond, which is where most companies are the next day being ah you know, being being recover, which is getting started back up or dealing with demand and so on. And the third stage being green went I think boards and see years need to start putting perhaps three work streams in place around these three different time horizons. And keep that they're planning in place so that they can effectively work to recovery while they have a separate stream. That's focusing on the reinvent, but they're more resilient and more prepared, and they are able to take and take advantage of both the opportunities as well as of getting more resilient company for the future, >>great insight and an awesome advice. Thanks so much for coming on The Cube. Really appreciate your time. >>Appreciate it. Thank you for the opportunity. >>You're very welcome. And thank you for watching everybody. We're seeing the pattern emerged where? We're not just gonna go back the last decade. We're really gonna have toe prepare for the next decade. Business resiliency and business continuance and flexibility. It's a whole new world, folks. This is the Cube covering IBM. Think 2020 the digital event. We'll be right back right after this short break. >>Yeah, yeah, yeah, yeah, yeah, yeah.

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all >>around the world. This is a cube conversation, Everyone. Welcome to this week's Cube insights, powered by ET are My name is Dave Volante, and we've been reporting every week really on the code. 19. Impact on Budgets Docker Korakia is back in with me soccer. It's great to see you really >>again for having >>your very welcome. Soccer is, of course, the director of research, that we are our data partner and man. I mean, you guys have just been digging into the data or a court reiterate We're down, you know, roughly around minus 5% for the year. The thing about what we're doing here and where they want to stress in the audience that that's going to change. The key point is we don't just do ah, placeholder and update you in December. Every time we get new information, we're going to convey it to you. So let's get right into it. What we want to do today is you kind of part two from the takeaways that we did last week. So let's start with the macro guys. If you bring up the first chart, take us through kind of the top three takeaways. And just to reiterate where we're at >>Yeah, no problem. And look, as you mentioned, uh, what we're doing right now is we're collecting the pulse of CIOs. And so things change on and we continue to expect them to change, you know, in the next few weeks, in the next few months, as things change with it. So just kind of give a recap of the survey and then kind of going through some of our top macro takeaways. So in March mid March, we launched our Technology Spending Intention Survey. We had 1250 CIOs approximately. Take that survey. They provided their updated 2020 verse 2019 spending intentions, right? So effectively, they first Davis, those 20 21st 19 spending intentions in January. And then they went ahead and up state of those based on what happened with move it and then in tandem with that, we did this kind of over 19 drill down survey where we asked CEOs to estimate the budget impact off overnight in versus what they originally forecast in the year. And so that leads us to our first take away here, where we essentially aggregated the data from all these CIOs in that Logan 19 drill down survey. And we saw a revision of 900 basis points so down to a decline of 5%. And so coming into the year, the consensus was about 4% growth. Ah, and now you can see we're down about 5% for the year. And again, that's subject to change. And we're going again re measure that a Z kind of get into June July and we have a couple of months under our belt with the folks at night. The second big take away here is, you know, the industries that are really indicating those declines and spend retail, consumer airlines, financials, telco I key services in consulting. Those are the verticals, as we mentioned last week, that we're really seeing some of the largest Pullbacks and spend from consumers and businesses. So it makes sense that they are revising their budgets downwards the most. And then finally, the last thing we captured that we spoke about last week as well as a few weeks before that, and I think that's really been playing out the last kind of week in 1/2 earnings is CIOs are continuing to press the pedal on digital transformation. Right? We saw that with Microsoft, with service now last night, right, those companies continued the post good numbers and you see good demand, what we're seeing and where those declines that we just mentioned earlier are coming from. It's it's the legacy that's the on premise that your place there's such a concentration of loss and deceleration within some of those companies. And we'll kind of get into that more a Z go through more slides. But that's really what kind of here, you know, that's really what we need to focus on is the declines are coming from very select vendors. >>Yeah, and of course you know where we were in earning season now, and we're paying close attention to that. A lot of people say I just ignore the earnings here, you know, you got the over 19 Mulligan, but But that's really not right. I mean, obviously you want to look at balance sheets, you want to look at cash flows, but also we're squinting through some of the data your point about I t services and insulting is interesting. I saw another research firm put out that you know, services and consulting was going to be OK. Our data does, you know, different. Uh, and we're watching. For instance, Jim Kavanaugh on IBM's earnings call was very specific about the metrics that they're watching. They're obviously very concerned about pricing and their ability. The book business. There we saw the cloud guys announced Google was up in the strong fifties. The estimate is DCP was even higher up in the 80% range. Azure, you know, we'll talk about this killing it. I mean, you guys have been all over of Microsoft and its presence, you know, high fifties aws solid at around 34% growth from a larger base. But as we've been reporting, you know, downturns. They've been they've been good to cloud. >>That's right. And I think, you know, based on the data that we've captured, um, you know, it's people are really pressing the pedal on cloud and SAS with this much remote work, you need to have you know, that structure in place to maintain productivity. >>Okay, let's bring up the next slide. Now. We've been reporting a lot on this sort of next generation work loads Bob one Dato all about storage and infrastructures of service. Compute. There's an obviously some database, but there's a new analytics workload emerging. Uh, and it's kind of replacing, or at least disinter mediating or disrupting the traditional e d ws. I've said for years. CDW is failed to live up to its expectations of 360 degree insights and real time data, and that's really what we're showing here is some of the traditional CDW guys are getting hit on Some of the emerging guys, um, are looking pretty good. So take us through what we're looking at here. Soccer. >>Yeah, no problem. So we're looking at the database data warehousing sector. What you're looking at here is replacement rates. Um And so, as example, if you see up in with roughly 20% replacement, what that means is one out of five people who took the survey for that particular sector for that vendor indicated that they were replacing, and so you can see here for their data. Cloudera, IBM, Oracle. They have very elevated and accelerating replacement rates. And so when we kind of think about this space. You can really see the bifurcation, right? Look how well positioned the Microsoft AWS is. Google Mongo, Snowflake, low replacements, right low, consistent replacements. And then, of course, on the left hand side of the screen, you're really seeing elevated, accelerating. And so this space is It kind of goes with that theme that we've been talking about that we covered last week by application, right when you think about the declines that you're seeing and spend again, it's very targeted for a lot of these kind of legacy legacy vendors. And we're again. We're seeing a lot of the next gen players that Microsoft AWS in your post very strong data. And so here, looking within database, it's very clear as to which vendors are well positioned for 2020 and which ones look like they're being ripped out and swapped out in the next few months. >>So this to me, is really interesting. So you know, you you've certainly reported on the impact that snowflake is having on Terra data. And in some of IBM's business, the old man, he's a business. You can see that here. You know, it's interesting. During the Hadoop days, Cloudera Horton works when they realize that it didn't really make money on Hadoop. They sort of getting the data management and data database and you're seeing that is under pressure. It's kind of interesting to me. Oracle, you know, is still not what we're seeing with terror data, right, Because they've got a stranglehold on the marketplace That's right, hanging in there. Right? But that snowflake would no replacements is very impressive. Mongo consistent performer. And in Google aws, Microsoft AWS supports with Red Shift. They did a one time license with Park Cell, which was an MPP database. They totally retooled a thing. And now they're sort of interestingly copycatting snowflake separating compute from storage and doing some other moves. And yet they're really strong partners. So interesting >>is going on and even, you know, red shift dynamodb all. They all look good. All these all these AWS products continue screen Very well. Ah, in the data warehousing space, So yeah, to your point, there's a clear divergence of which products CIOs want to use and which ones they no longer want in their stack. >>Yeah, the database market is very much now fragment that it used to be in an Oracle db two sequel server. As you mentioned, you got a lot of choices. The Amazon. I think I counted, you know, 10 data stores, maybe more. Dynamodb Aurora, Red shift on and on and on. So a really interesting space, a lot of activity in that new workload that I'm talking about taking, Ah, analytic databases, bringing data science, pooling into that space and really driving these real time insights that we've been reporting on. So that's that's quite an exciting space. Let's talk about this whole workflow. I t s m a service now. Just just announced, uh, we've been consistently crushing it. The Cube has been following them for many, many years, whether, you know, from the early days of Fred Luddy, Bruce Lukman, the short time John Donahoe. And now Bill McDermott is the CEO, but consistent performance since the AIPO. But what are we actually showing here? Saga? Yeah, You bring up that slot. Thank you. >>So our key take away on kind of the i t m m i t s m i t workflow spaces. Look, it's best in breed, which is service now, or some of the lower cost providers. Right There's really no room for middle of the pack, so >>this is an >>interesting charts. And so what you're looking at here, there's a few directives, so kind of walk you through it and then I'll walk through. The actual results is we're looking within service now accounts. And so we're seeing how these companies are doing within or among customers that are using service. Now, today, where you're looking at on the ex, access is essentially shared market share our shared customers, and then on the Y axis you're seeing essentially the spend velocity off those vendors within service. Now's outs, right? So if the vendor was doing well, you would see them moving up into the right, right? That means they're having more customer overlap with service now, and they're also accelerating Spend, but you can see if you will get zendesk. If you look at BMC, it's a managed right. You can see there either losing market share and spend within service now accounts or they're losing spend right and zendesk is another example Here, Um, and what's actually interesting is, and we've had a lot of anecdotal evidence from CIOs is that look they start with service. Now it's best in breed, but a few of them have said, Look, it's got expensive, Um, and so they would move over Rezendes. And then they would look at it versus a conference that last year, and we had a few CEO say, Look at last quarter of the price of zendesk. Andi moved away from Zendesk and subsequently well, with last year. And so it's just it's interesting that, you know, during these times where you know CIOs are reducing their budgets on that look, it's either best of breed or low cost. There's really no room in the middle, and so it's actually kind of interesting. In this space, it's It's an interesting dynamic and being usually it's best of breed or low cost. Rarely do you kind of see both win, and I think that's what kind of makes the space interesting. >>I've been following service now for a number of years. I just make a few comments there. First of all, you know, workday was the gold standard in enterprise software for the longest time and, you know, company and and and I I always considered service now to be kind of part of that you know Silicon Valley Mafia with Frank's Loop. But what's happened is, you know, Sluman did a masterful job of identifying the total available market and executing with demand, and now you know, his successors have picking it beyond there. You know, service now has a market cap that's not quite double, but I mean, I think workday last I checked was in the mid thirties. Service now is market valuation is up in the 60 billion range. I mean, they announced, um uh, just recently, very interestingly, they be expectations. They lowered their guidance relative to consensus guide, but I think the street hose, first of all, they beat their numbers and they've got that SAS model, that very predictable model. And I think people are saying, Look there, just leaving meat on the bone so they can continue to be because that's been their sort of m o these last several years. So you got to like their positioning and you get to talk to customers. They are pricey. You do hear complaints about that, and they've got a strong lock spec. But generally I got my experiences. If people can identify business value and clear productivity, they work through the lock in, you know, they'll just fight it out in the negotiations with procurement. >>That's right, and two things on that. So with service now and and even Salesforce, right, they are a platform like approach type of vendors right where you build on them. And that's what makes them such break companies, right? Even if they have, you know, little nicks and knacks here and there. When they report people see past that right, they understand their best of breed. You build your companies on the service now's and the sales forces of the world. And to the second point, you're exactly right. Businesses want to maintain consistent productivity on, and I think that, you know, is it kind of resonates with the theme, right, doubling down on Cloud and sas. Um, as as you have all this remote work, as you have kind of, you know, questionable are curating marquee a macro environment organizations want to make sure that their employees continue to execute that they're generating consistent productivity. And using these kind of best of breed tools is the way to go. >>It's interesting you mentioned, uh, salesforce and service now for years I've been saying they're on a collision course we haven't seen yet because they're both platforms. I still, uh I'm waiting for that to happen. Let's bring up the next card and let's get into networking way talk. Um Ah. Couple of weeks ago, about the whole shift from traditional Mpls moving to SD win. And this sort of really lays it out. Take us through the data here, please. >>Yeah, no problem. So we're just looking at a handful of vendors here. Really? We're looking at networking vendors that have the highest adoption rates within cloud accounts. And so what we did was we looked inside of aws azure GCC, right. We essentially isolated just those customers. And then we said which networking vendors are seeing the best spend data and the most adoptions within those cloud accounts. And so you get you can kind of see some, uh, some themes here, right? SD lan. Right. You can see Iraqi their VM. Where nsx. You see some next gen load balance saying are they're on the cdn side right then. And so you're seeing a theme here of more next gen players on You're not really seeing a lot of the mpls vendors here, right? They're the ones that have more flattening, decreasing and replacing data. And so the reason just kind of going on this slide is you know, when you kind of think about the networking space as a whole, this is where adoptions are going. This is this is where spends billing and expanded, arise it. And what we just talked about >>your networking such a fascinating space to me because you got you got the leader and Cisco That has helped 2/3 of the market for the longest time, despite competitors like Arista, Juniper and others trying to get in the Air Force and NSX. And the big Neisseria acquisition, you know, kind of potentially disrupted that. But you can see, you know, Cisco, they don't go down without a fight. And ah, there, let's take a look at the next card on Cdn. You know, this is interesting. Uh, you know, you think with all this activity around work from home and remote offices, there's a hot area, But what are we looking at here? >>Yeah, no problem. And that's right, right? You would think. And so we're looking at Cdn players here you would think with the uptake in traffic, you would see fantastic. That scores right for all the cdn vendor. So what you're looking at here and again there's a few lenses on here, so I kind of walk. You kind of walk the audience through here is first we isolated only those individuals that were accelerating their budgets due to work from home. Right. So we've had this conversation now for a few weeks where support employees working from home. You did see a decent number of organizations. I think it was 20 or 30% of organizations at the per server that indicated they're actually accelerate instead. So we're looking at those individuals. And then what we're doing is we're seeing how are how's Cloudflare and aka my performing within those accounts, right? And so we're looking at those specific customers and you could just see within Cloudflare and we practice and security and networking which by more the Cdn piece, How consistent elevated the date is right? This is spend in density, right? Not overall market share is obviously aka my you know, their brand father CD ends. They have the most market share and if you look at optimized to the right. Now you can see the spend velocity is not very good. It's actually negative across boats sector. So you know it's not. We're not saying that. Look, there's a changing of the guard that's occurring right now. We're still relatively small compared talk my But there's just such a start on trust here and again, it kind of goes to what we're talking about. Our macro themes, right? CIOs are continuing to invest in next gen Technologies, and better technologies on that is having an impact on some of these legacy. And, you know, grandfather providers. >>Well, I mean, I think as we enter this again, I've said a number of times. It's ironic overhead coming into a new decade. And you're seeing this throughout the I T. Stack, where you've got a lot of disruptors and you've got companies with large install bases, lot of on Prem or a lot of historical legacy. Yeah, and it's very hard for them to show growth. They often times squeeze R and D because they gotta serve Wall Street. And this is the kind of dilemma they're in, and the only good news with a comma here is there is less bad security go from negative 20% to a negative 8% net score. Um, but wow, what a what a contrast, but to your point, much, much smaller base, but still very relevant. We've seen this movie before. Let's let's wrap with another area that we've talked about. What is virtualization? Desktop virtualization? Beady eye again. A beneficiary of the work from home pivot. Um, And we're focused here, right on Fortune 500 net scores. But give us the low down on this start. >>Yeah, So this is something that look, I think it's it's pretty obvious to into the market you're seeing an uptake and spend across the board versus three months ago in a year ago and spending, etc. Among your desktop virtualization players, there's FBI, right? So that's gonna be your VPN right now. Obviously, they reported pretty good numbers there, so this is an obvious slide, but we wanted to kind of throw it in there. Just say, look, you know, these organizations are seeing nice upticks incent, you know, within the virtualization sectors, specifically within Fortune 500 again, that's kind of, you know, work from home spend that we're seeing here, >>right? So, I mean, this is really a 100% net score in the Fortune 500 for workspaces is pretty amazing. And I think the shared in on this that the end was actually quite large. It wasn't like single digits, Many dozens. I remember when Workspaces first came out, it maybe wasn't ready for prime time. But clearly there's momentum there, and we're seeing this across the board saga. Thanks so much for coming in this week. Really appreciate it. We're gonna be in touch with with you with the TR. We're gonna continue to report on this, but start Dr stay safe. And thanks again. >>Thanks again. Appreciate it. Looking for to do another one. >>All right. Thank you. Everybody for watching this Cube insights Powered by ET are this is Dave Volante for Dr Sadaaki. Remember, all these episodes are available as podcasts. I published weekly on wiki bond dot com Uh, and also on silicon angle dot com Don't forget tr dot Plus, Check out all the action there. Thanks for watching everybody. We'll see you next time. Yeah, yeah, yeah, yeah, yeah

>>Live from Las Vegas. It's the cube covering UI path forward Americas 2019 brought to you by UI path. >>Welcome back to Las Vegas. Everybody, you watching the cube, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. Ahmed Zion, he is here, he's the chief automation officer at accelerate a specialist service provider in this area of RPA in Armando Lambert is the vice president of enterprise optimization governance and risk guys. Oh sorry. At Bayview asset management in Miami. Welcome to the cube criminal. Thank you for that. So Bayview, you've got a good view of the Bay and Miami, is that kinda where the name comes from or the beautiful place to work happening with UI path forward to was in Miami at the Fontainebleau back here in Vegas. But um, so let's get into it. I met um, chief automation officer. That's kind of a cool title. I don't see that a lot. What's that entail? And tell us about accelerate. >>So accelerate at accelerated where one of the largest nice providers is the only thing that we do a process automation and AI company. And our sole focus has been process automation since our inception and our past lives were generalists. We did well and wanted to do it again. Uh, so when we started accelerate, we wanted to make sure that we focused on a very specific vertical niche and process automation was just starting up the uptick about mid 2016 ish. >> So there's gonna be some interesting conversations around process automation is like had an analyst on yesterday, they predicted RPA is dead, you know, process automation lives. You know, it's kind of a tongue in cheek thing. So maybe we can talk about that a little bit, but Amando tell us about your role and a little bit about Bayview. So Bayview is an asset management company, primarily whole loans, mortgage back securities, mortgage servicing rights. >>We offer service advisory as well as investment vehicles. My role basically is to strategize, innovate, look at new technologies, new ways of streamlining the business. Um, and you know, about in 2016, you know, we were faced with the challenge and the challenge was we have a lot of road swiveled to chair type work, back office, operational work. Um, and I went in there just trying to look at people, processes and systems and trying to figure out a way to make things more efficient. And you know, RPA is one of those vehicles. Okay. So smart. You started with people in process, you didn't start with the technology. Yeah, absolutely. Right. So what did you learn? I mean, take us back to 2016 when you started to do the investigation, you started unpack the processes and the people. What did you see and then what led you to RPA? >>Yeah, I mean, I think inherently you're, you're, there's a lot of business processes that are just brought down through years of just being kind of entrepreneurial and doing a lot of business. So a, of these prices of processes early on we felt like we can just go in and automate and we realized that just needed a level of process optimization first. Um, so in doing that, it just kind of directs the vehicle right into what type of automation you need to do. It's not always RPA. RPA is big, a big component for us. Um, it works for us. Early on we wanted to put a strong governance structure. I strongly believe that, you know, and it's worked out so far for us. >> So you, you brought in accelerate, you brought in an outside firm to help you with that process automation, is that right? Absolutely. >>So tell us more about how that all went down. So that was, that was an interesting, um, interesting time, right? The, these products were coming up. Nobody really knew how well they work. And so we went in and we actually did proof of value, right? We said, Hey, this is all well and good. Let's do a proof of concept that a proof of value at that time, proof of concepts really were a thing. I don't, I don't think we should do them anymore. We should only do proof of values. But we went in, looked at the various systems they had, tried it out so he could demonstrate it to his management that this thing works. And as soon as that was over, I think I'd given to her, Armando, here we went all in, right? We said, all right, let's look at the highest value things. >>Let's deliver this. Um, let's figure out a governance model. Let's, let's not, let's not hold it back like we, like we have done in the past. It project spinning up. So let's get the infrastructure up and running very quickly. Let's get, let's get a few automations out there. Some of the business sees the value right away, right? Crawl, walk, run. We can do this. You know, what are we going to automate and what do we need from it and how are we going to govern this? These are the three pillars that I see that I suggest everybody look at it. And we did that in parallel parallel streams and all three of them. And within a few months he was able to return a significant value back to the business, which has led to adoption. I think, I think that has been a very big reason why he's been able to scale because he was able to show early value back to the business very quickly focusing on value rather than the technology or the underlying solution. >>Right? It's um, a lot of times we see folks going into RPA saying, what can RPA do for me? I think that is the wrong question. Um, the question really is what do you do? Let's classify what you do in manual mechanical work, intelligent work and wasteful work, right? And then look at your toolbox. I have RPA, I have AI, I have other technologies that within an enterprise folks are working on, and then apply those to it. RPA becomes the glue for most of these things. You have API as SDKs. You have AI technologies, be it cloud or on prem. RPA becomes the glue and it becomes easy to deploy once you figured out what all the different pieces are. But it's important to look at the process first and say, what? What do you do? So when the business comes back and say, what can you do for me with RPA? >>I said, no, I don't know. What can you do for, with the, I don't know. Tell me what you do and then I'll tell you what the solution is. So mono, given that you started with the value, did that ease some of those potential friction that you sometimes see with change management or change in general? Or did you still see that resistance? And I'm interested in where you started, what were some of those high value areas that you attack but, but the cultural piece first if you will. Yeah, I mean a lot of marketing, you know, it's really what it comes down to trying to prove to the Csuite and managing director areas. Like this is a value proposition. You know, early on, you know, we did a lot of presenting roundtables, luncheon learns with the business. You know, because there is some resistance early on. >>I think everybody has a misconception that it's going to take their jobs where I believe it's gonna create a lot more jobs in the future. Um, for me it was always a scalability play. You know, how can our business do more for less? And that's really what we really wanted to get to. Throughout that journey. We realized there's a lot of benefit, especially for companies that have a heavy back office operations. Um, and we just started, like I mentioned there, we started slow. I didn't want to boil the ocean. I knew I needed to prove to leadership that this works. And I think about three years ago, we all kind of felt, is this going to stick? You know, we've seen technology, I've been in technology for over 20 years and you know, some things fly, some things don't. Right? So we wanted to prove that it worked. >>And you know, the industry just kind of surrounded itself around that. And look where we are now. I think everybody's putting a lot of money in their budgets for, you know, intelligent automation, not just RPA. So the initiative was kind of middle up to the C suite and then top down. Is that how it, absolutely. I'm a firm believer the tone needs to come from the top. It has to come from the top. And you know, luckily for me, I have great leaders in our company. Um, they understood the vision, they understand what, what it could potentially mean for their business. They just needed someone to help execute it. So what kinds of things did you start with? There was a lot of sort of manual form filling out or some of that, uh, you know, data extraction from PDFs using, utilizing OCR, you know, RPAs great to gather and collect data so that they can put it in their models and make more informed decisions. >>Uh, claims processes, you know, dealing with different agencies. So, you know, early on in adopting UI path, there were some limitations. We worked around that. Now it's pretty much limitless and they could touch any system, any technology, any process. So yeah, it's growing tremendously. And in terms of just ensuring governance and compliance as you scale, you have robots doing that. Um, how do you tell me what we're working more and more. I mean, I think regulators now realize, okay, you're removing the human element, right? So, you know, that's a big value as well. Or sampling. Now you're not limited to what you can sample. You can sample 100%, you know, so those are big values and when you speak to regulators, they really understand that I would say five years ago, I'm not so sure. Um, but now they welcome it. And I think a lot of the government agencies now are, are adopting RPA. >>Uh, so it's, it's a good story. Well, automation kill sampling is that I think it is absolutely right. The point actually interesting point that you made, right? Uh, the regulators or the auditors or for that matter, the security and the compliance guys inside the enterprise have this. So this term of the bot, right has this connotation of Terminator and I keep telling him, no, this is that thing. You buy a target that does this. I press the right button, it goes right up, press the left button, mil goes left. It just doesn't think on its own. And I think that conversation is very important, right? Once you have that conversation with the security and the compliance guys to say, this is a bot, it only does what you ask it to do. You could put a social security number in front of this guy all day long in front of this user ID all day long. >>It just doesn't know what to do with it. Won't ever read it. And once they realize that they, the, the conversation changes, um, you know, especially when it in compliance and audit, right? Uh, the compliance officers would love this. Once you tell them there's a lot of decision making that happened in people's heads or Excel spreadsheets that never made it to systems and was never logged. So you'd get something in you massage that, you did that, and you put that in the system. That decision making is now auditable. So you can go back and say, here was the input, here was the massaging of it. Here's what went into the system of record after it came in. So that I think, I think those conversations early on really helped this scale in an age old problem and tribal knowledge. Exactly. You know, Joe has his spreadsheet and Fred knows the Joe has the spreadsheet. >>So when Joe leaves, he has to get the spreadsheet back. And that's kind of this perpetual thing. How much of what you guys did, Armando was processed re-engineering versus just applying automation at some low hanging fruit. Um, I think looking back now it's about a 50, 50 split. Um, you know, there are some areas that have robust processes and that makes our life easier. We can just kind of go in, map it out, look at the automation future state and deploy, develop and deployed. Uh, you know, some areas, you know, they inherit processes and they don't always just so busy doing their day jobs and they don't always realize there's, there's room for efficiency in their process. So, you know, early on when we priced out how much this would cost, how much development it would be, we didn't always factor in that it would be a 50, 50 split and doing a lot more process improvement in the beginning. >>Um, we've now counted for that. So absolutely. It's about a 50, 50 split. Craig LeClaire this morning said something that, you know, I was an analyst and he says, very, you know, very analyst's sort of savings. You've got to stop worrying about the ROI, you know, focus on the more strategic stuff. Every analyst sort of says that. But yeah, there weren't a lot of CFOs too. And they're like, where's the ROI? So you know, you're in the services business, you know, you have to have ROI dollars matter. Absolutely. So you obviously measure ROI. How do you look at it? You know what you said earlier, you're not cutting jobs, right? But so what do you tick? How do you measure kind of the, the value, the ROI? I mean, you know, giving the end user a little more to think about, right? Giving them the opportunity to, you know, do more, be more thoughtful in what their day to day job is rather than doing the swivel chair type work. >>So, you know, the measurement, the beauty around RPA is it's very quantifiable. You know, unlike some traditional it systems, you really can, the data doesn't always kick back. You know, all our, our, our own bots, all our processes kickback, they give us data that we can quantify, um, metrics on, on, on volume versus man hours. This is all information you capture early on. You need to do this at the discovery stage and we train. We have a robust training program for our business analysts and program managers and developers and they're always, that's the question they ask every time. It's not just about what is your process, your cute future, current state, future state, and it's like, how many limit? Let me look at your historical trending. What are their volumes look like? You know, our business is very cyclical. It goes up and down, and when I mentioned I want them to be scalable and have more capacity, that's really the play for me. >>For me, it's never been an FTE. I get it. It may come from the Csuite, but like I said, the tone from the top has been solid. Their vision is more about, Hey, when it's cyclical and it goes up and down, we need to be able to do more. We need to be able to scale. Have you been able to measure productivity improvement? Absolutely. Absolutely we have. If you had a Mulligan, what would you do differently? A good question. I mean, I think we factored early on, I mentioned this early on how much process improvement was needed. I think we undervalued that. And um, you know, every business faces the same challenges, right? They, you know, everyone feels like they're doing the right thing. These processes are inherited. You know, regulations change, investors change. There's new business rules every day, you know, and you kind of need to sit back as a business user every now and then and refresh that. >>And um, you know, we didn't account for that early on. We're helping the business do that. Our business is fantastic. They bought into the program and it's like having additional workforce working on your side. You know, Daniel Dienes in his keynote last night, basically sending them pick up on something you guys said is, is, um, he really appreciates those customers who took a chance early on. He goes, because frankly, our product wasn't, you know, fully, fully baked out. And I was like, wow, what an honest statement from a CEO. You don't usually hear that. My sense is that they got it right. You path. And I'd love your comments. In the sense that they attack, they went after simplicity and said, okay, make it easy to adopt and then we'll figure it out. And then, you know, bringing in the functionality is that, is that kind of what happened or picking up on Daniel? >>And by the way it was, it's amazing. Humility really comes through, right? So I saw him 2016 standing on stage and when my partner came to us for the idea of saying, Hey, we're going to do, we should do this RPA thing. Now I'm giving away my age. But 1998, my first job, I was sitting in front of the computer and Prudential and they put this software in front of me. It was called SQA robot. It was a test automation tool. It was called SQL robot. Uh, why that relates to Daniel is he's had a, came on the stage in the IRPA conference in 2016 if remember, I love this presentation just to blues black thing and few words on it. He goes, let's not kid ourselves. We have this very traditional, you know, QA automation technology that we think can do something really super. >>And I have built a product on top of that, but there's, there's not a lot of magic in here yet. Right. So that's, but, but I think the, the, the great thing about you I've had has been the vision, right? The vision has been, and if you saw yesterday they started with the core and unlike some of the other vendors, they said, we're just going to do RPA really well. We're not going to go into the OCR market. We're not going to try to build AI things. Let's make sure that our core RPA, so you know, you want to go, you're an enterprise, you want to do OCR, you're not going to buy it from an RPA company. You want to buy it from somebody who's been doing it for 30 years or we just has that sole focus. I think you'll have had had that sole focus. >>But as I've seen in the past three, four years, they've just done a great job with the, with the full vision, right. Starting from, they started with the middle of the core of the product and they said, okay, let's go towards the business and see what the business needs with, you know, planning of their, um, of their automations on and so forth and going further to the right to say, let us enable the technology guys who actually implement this to give them the tools and the integrations they need to, to actually make this routed to full product. Um, I think it's a very good question when people say, what can you do with RPA for me? So I said that answer was very different three years ago than it is today. Right? Some of the things are coming out of the box with these. So I, I, I predict that in the next few years, document understanding and natural language and all of that will just be built in today's still very sort of clunky in terms of how you do it. >>But I think those things are coming, coming together. So looking at processes that way is really important. It's a lot of runway for this. Margaret, Armando, I'll give you the last word. Where do you see are RPA or intelligent automation going in, in your organization? Is it still early days you had a lot more adoption or you're pretty much, you know, settled? No, definitely not settled. Um, I think it's, you know, RPA is just one of the tools in the spectrum of intelligent automation. So more integration, more API APIs, a lot of machine learning, uh, eventually some AI. Um, so yeah, we are not slowing down. There's a lot of opportunity. My mandate as I mentioned before, is just scale, scale, scale. So you know, the process is working. We have a good program in place. We'll continue marching forward. Great guys, thanks so much for coming. Thank you for sharing your story. Thank you for watching. From right back with the cube. Live from UI path forward three in Las Vegas. Right back.

(techno music) >> Hello and welcome to the special Cube presentation here in the Palo Alto studios of TheCube. I'm here with the Extend SD-Wan to the Wireless LAN segment here at Riverbed. I'm John Furrier. Our next guest is Bruce Miller, Vice President of Product Marketing at Riverbed Xirrus. Welcome to the segment: Extend the SD-Wann to the Wireless Lan Wi-Fi. [Production Man] No Wi-Fi. (sharp clap) >> Production Man: (mumbles) let's try it again. Let's get that good solid intro. >> Okay, good call. (laughing) >> Production Man: Reset please. >> Been a long day. >> Production Man: Yeah, that's okay. >> That's how long? >> Production Man: Well let's see. >> It's a tongue-twister on extend the wireless LAN. (laughing) Doesn't just roll off the tongue. (laughing) I got flustered, hold on. I got to make my font bigger. >> Production Man: You only get one mulligan. >> John: I buy mulligans when I play, or use lifesavers. (techno music) >> Hello and welcome to the special Cube presentation here in the studios in Palo Alto, California. I'm John Furrier, co-host of TheCube. This special segment: Experiencing the Future of Networking With the Extend the SD-WAN to Wireless LAN segment conversation with Bruce Miller, Vice President of Product Marketing at Riverbed Xirrus. Thanks for joining me today. Thanks for coming in. >> Great. Thanks for having me. >> So we had a whole segment on experiencing the future of networking with SD-WAN in action, but this is a dedicated segment really addressing the hottest area in the planet right now, relative to networking, that's wireless. Known as wireless LAN, local area networking or Wi-Fi. It's pervasive. It's everywhere. Most everyone knows about Wi-Fi if they have a device. They've had connections at large stadiums, large events, lot of use cases for it. But there's also the use case of internet of things. So this certainly is a topic of conversation for the future -- >> Absolutely. >> John: Of networking. >> Yeah and Wi-Fi is pervasive like you said. It's the connection to the internet for most people. In fact, a lot of people equate that; Wi-Fi equals the internet for a lot of teenagers for example. And as you mentioned, the IoT and where we are moving forward, you know it's all about growth and scale. And we only had maybe one or two Wi-Fi devices five or six years ago and now we're walking around with three, sometimes four. We have college students showing up with 15 sometimes, to their dorm. So it's very pervasive and the IoT, as you mentioned, billions and billions of devices coming online. So what we've seen is very much a scale and the need to scale these Wi-Fi networks. >> Yeah and then folks watching that are in the business of IT, you know we're all consumers too. So we've all been to stadiums or places where there's plenty of Wi-Fi, but you just can't get -- >> Bruce: Right. >> The (mumbles) to load. That's a backhaul issue, or in some cases there's not enough Wi-Fi frequency around. So there's been a dense challenge, there's been scale challenges. And then on the IoT side, for large enterprises, they have requirements that have to meet the network-- >> Right. >> Configuration. So there's complexity and scale on many fronts. This is the top priority companies. >> Yeah. >> How do you see that evolving? Because Wi-Fi wasn't really kind of built for that in the old days? >> Yeah. >> How has it evolved today? >> And it is actually a topic that Xirrus kind of saw very early on. And so if you go back 10, 12 years when we first put the company together, it was foreshadowing or foreseeing that this was going to happen. There was a lot of money going into the Wi-Fi devices, if you actually think about it, the Wi-Fi devices we're carrying around, but not the infrastructure itself. So we set out to solve that problem. And really the market then eventually kind of came to us in the sense of; hey, how do I get 10,000 people online at a convention center for example, or 20,000 people, 80,000 people in a stadium. Those are the extreme examples. But in general, it's just pervasive everywhere. You know you need Wi-Fi indoors, outdoors, in the elevator shafts, in the bathrooms. I mean we're called to cover any kind of scenario from that perspective. And so Xirrus, you know that was a challenge that we took on. And today I believe we solved it very, very well, because we can scale into these scenarios. And it keeps on going up into the right. I mean there's more traffic. There's more devices on the network every single day. Millions of devices in fact are provisioned to connect to Wi-Fi every single day that are new. And that keeps on, like I said, going up, and up. >> So scale and density has been your forte at Xirrus, now part of Riverbed though the acquisition. >> Bruce: Right. >> Translate that to the end-user or customer for you, which is the person either in IT or someone in operational technologies that has to deploy network fast. >> Bruce: Right. >> And they're going to use wireless Wi-Fi for that. What's in it for them? >> Yeah, and that's a very key part of it is deploying and getting this out there very simply and at scale. And you know provisioning the Wi-Fi network, deploying something that is now basically utility. You think about it, gas, water, electric, all these things are utilities. Wi-Fi's basically the same thing. In fact, I was just visiting a higher-ed customer of ours who made that statement. If the power goes out, the students are asking for Wi-Fi. They expect it to still work, right? It's more important, in fact, almost to them if they don't have that. So -- >> God forbid they lose the internet, but they're happy to live without power. >> Yeah, yeah, or water or whatever. So we see it that way. Wi-Fi is a utility. You need to make it utility-grade. You need to make it enterprise-grade, so we can scale and support those things. So you hit on a couple of those key things. How do you do it at scale? And then how do you provision and make that very ubiquitous and be able to role that out in a broad fashion? And that's key to what we do. >> I know you got a demo, we're going to get to that shortly. So stay tuned. Stay with us for the demo. We'll walk through a use case. Let's talk about the integration with Riverbed. Why is now important? Because I think we all can imagine and see how Wi-Fi is relevant. No doubt about it. Scale is a huge thing happening as more devices come online; people and machines. But when it has to connect into the network, that's a big conversation point with IT practitioners and people in these large companies. They want more Wi-Fi. They want it secure. They want it at scale. They want it with all the policies. Where's that integration with Riverbed? Can you explain how that works? >> Right. And that's key to where the acquisition came from. So we kind of talked about scale and then complexity, and how you deploy these things. The integration with Riverbed is really focused on the second one where there's the SD-WAN story that we've been talking about and the vision for running common policies across the WAN, the LAN, the WLAN into the data center, all managed though the cloud. And Xirrus fulfills that WLAN piece of that equation where it can be deployed at the wireless edge, connecting all those devices in an enterprise, or in whatever deployment you're talking about. And now the policies that are actually deployed are common with what is being put into the SD-WAN portion of it. So in the Riverbed side of things, that's a SteelConnect solution. So we're integrating in, as part of the SteelConnect solution, to support the software to find LAN, so to speak, at the edge of the network with switches and Wi-Fi access points that will support that. And so the synergies are very much there in terms of providing that vision across the entire network. >> So full integration of the SteelConnect from a management and provisioning standpoint -- demo perspective. >> Right. Yeah, configuration and the policies. Especially the application layer policies where you can say, hey I have a new CRN application I'm rolling out, or database application. And then that policy to prioritize that and insure a good user experience could be rolled out across the entire network. >> Give some quick use cases of customer industries that you guys are successful in. >> Sure. Probably the one we're best known for is what we call large public venues or LPVs. So this could be, for example, Liverpool Football Club which is a great name for us. Microsoft is another customer. So these are places where you have literally 10,000 and 20,000 people connecting at once, or 80,000 people in the stadium for example, a portion of those are connected to Wi-Fi. That is a very, very difficult scenario to actually solve. So we did some things that are very unique in the industry to support those kind of situations. Another big one for us is education. That is actually the biggest Wi-Fi market in general if you look at how many people are buying it or what kind of organizations are buying Wi-Fi. And we have some very large customers there; Brigham Young University for example and Idaho, Columbus State University. These are scenarios where they've rolled out ubiquitous Wi-Fi across campus, you know, stadiums, basketball arenas, all the way to the dorms, to the offices, to the auditoriums, to the libraries, indoor, outdoor, I mean it's very broad-use cases. And that's what you see in higher ed. >> I mean the Wi-Fi really kind of redefines, doesn't reimagine, but it redefines what a campus is. I mean in college -- >> Bruce: Yeah. >> You know what a campus is; hospitals, large venues like public flash mob contained campus. >> Yeah. >> The problem there's different. >> Yeah. >> There's 28 people trying to get into the -- >> All at the same time. >> Spectrum. >> Yeah, we call that flash traffic when you see, like at halftime maybe of a game, or some event happens. >> John: Touchdown, and all the videos. >> Yeah and everybody wants do do it at the same time. And those are very challenging to support those kind of scenarios. And that's something that we have really defined a solution that can handle very well. >> Well congratulations. Thank you for building that, because I love to get my Wi-Fi at Stanford Stadium and all the other places that need to have that. >> Bruce: Sure. >> And when I go to Liverpool to watch a soccer game-- >> Bruce: Yeah. I'll be kind of thinking about you guys. >> Bruce: Next time you're there. >> Okay, let's get into the demo. Let's take the real life, in action of extending SD-WAN to wireless LANs with Wi-Fi. >> Right. >> Show us what you got here. >> Bruce: Sure. So the first thing I want to talk about is provisioning the network. We have solution called CommandCenter that makes that very fast and easy. And this is actually a view of a dashboard that shows multiple tenants in a cloud management system. Okay, so imagine each of these as a separate customer. Or if I'm a large organization, this could be separate sites or locations. So I'm going to just do an example here and say let's create a new customer, and say TheCube is that customer. >> John: All right, I like that. >> Bruce: I will say that we're enabling you with Wi-Fi. So I'll create TheCube. And what this is actually doing is just with literally a few mouse clicks I've actually created a new cloud instance that is TheCube. And then what I can come down here and do is edit that location. And let's just say that, well let's see here, Joe is going to be the administrator of that. So he's going to have access to manage that network. And then I have identified a couple access points here. I'm just going to drag and drop those in there. And these are now provisioned to TheCube. And then the last thing I'm going to do is, let's take a profile. So let's say, I have a configuration template, or whatever, maybe I'll just call you. You have a business profile and I'm going to deploy that to your location as well. Hit deploy. And basically, just that quickly what I've done is actually spun up a new customer. So you can imagine if you're a service provider in fact, then that means you're quicker to revenue. I'm actually able to turn on a customer and start charging him for Wi-Fi. >> John: Let's stay on this example with TheCube. Because I think this is really important to the dense qua problem. So we go to Moscone Center all the time. >> Bruce: Sure. >> And they have Wi-Fi. They have large crowds come in. And we're used to doing a live broadcast there. >> Right, sure. >> So I'd love to have my own Wi-Fi provisioned. Is that what happened there? Could they potentially say, you know, dedicate this access point or this subnet of the network to TheCube? >> They could, I mean it would be a variation on this, but absolutely. I mean one of the things that we do very well is taking a Wi-Fi device or an AP and segment it out for use cases like that. >> John: AP being access point. >> Access point, exactly. So in a convention environment like that, those are actually quite challenging 'cause you have so many people on the network. And what you need to do is carve out a resource that might be dedicated to that. So if you can't get good Wi-Fi-- >> John: Like good video, like we do video production-- >> We can do that. >> and so we want to-- >> Yeah. >> Actually prioritize the video traffic. >> Bruce: Absolutely. And we'll show that a little bit later in the demo. >> The recreational. >> Bruce: Yeah, you separate it out, right. And make sure that-- >> So continue, so that on-ramping there-- >> Bruce: Yeah, so basically this was just showing you how quickly you can create TheCube. This is the environment that I basically set up. It's got a couple APs. It's ready to go. I can now start. I can plug in those access points, and that side is up and running. So that's the provisioning aspect. The second aspect of Wi-Fi that we don't talk about is access to the network itself. This is actually a challenge with a lot of environments that's how do I get all of these people onto the network at the same time and do that very easily without IT getting a phone call saying, hey help me I dunno what the password is or -- >> John: Are we onboarding users and stuff like that? >> Bruce: Yeah, onboarding. Well we have a solution there, it's called EasyPass. And that solution allows you to create the portals that you see when you log into -- >> John: Like (mumbles) tollbooths? >> Bruce: Yeah, and it basically provides a very easy way of doing that. So let's just say this is TheCube guest, and I'll create a new portal. And this is a guest network right, so I know when I came in here today, I connected to the Wi-Fi network and I had to figure out how to do that, and what was the password. So let's just say we're creating a Wi-Fi network here. This just shows how easy and quick that interface is. I can customize the page. Let's select an image. We'll select a background image here. And then actually use Facebook and Google can be optionally used to log in. So just that quickly I've created a portal that says, this is what you're going to see when you log in. Now obviously if it's TheCube you put your own logos and data there. But the idea here is that a user can come in here and either register with his email or use Facebook or Google for example to get on the network. >> John: Is that (mumbles) thing in through the preexisting credentials? >> Bruce: This is used, in this case, yeah with Facebook you're using the credential that they have to get onto their system. And You're basically using that for Wi-Fi as well, so that the user name and password is now providing access. >> John: So it's seamless to the user what their choice is. >> Bruce: Yeah. And some people use Facebook, others will just connect with their email. >> John: Some people want to register, but most people just want to connect with either Twitter, LinkedIn, or whatever they have. >> Bruce: Yeah, yeah. And so this basically just shows how quick and easy it is to set up a guest page that gets somebody on the network. Very simple to use. And so IT administers love this because it simplifies their job significantly. The other thing I wanted to show here real quick is just the Microsoft Azure to Google integration. We actually have integration directly with these two ecosystems where if you already are in a Office 365 shop or a Google App shop as a lot of schools are, they can just use those credentials. The user logs in with their laptop, with their username, password, and it gets them access to Wi-Fi at the same time. Kill two birds with one stone. >> John: So if it's active directory, you got your Microsoft. If it's Google and what they use you can do that. >> Bruce: Right, yeah. So it's all in the cloud. So now this is again, moving everything into the cloud as opposed to using some local resource to do authentication and maintaining those resources. >> John: That seems to be the theme with Riverbed; simplify. >> Bruce: Right, absolutely. And this is the two big things here. We're scaling the Wi-Fi network to support these broad use cases. And then we're simplifying it with the tools to enable that to roll out very smoothly. >> Well all the research points to, that manual task that don't add value will be automated away. And those tasks will be shifted to more value activities. >> Right. >> Okay, so take us through monitoring. Now what happens when, you know I'm doing my Snapchats or Instagram, or my Facebook Lives, and you go, whoa, whoa, whoa. >> Bruce: Right. >> John: Or I'm interested in knowing if someone's downloading the latest movie on BitTorrent. >> Bruce: Yeah, yeah and that's very key. So if I go back to our solution here. The dashboard actually shows what's going on in the network. So this is actually a very flexible interface. You can move things around, create widgets, do different things. And in fact we have a map function where you would lay all the stuff out on a map and then I can actually show what the coverage is, for example that Wi-Fi and a floorplan. This happens to be my house. >> John: That's an RF metric? >> Bruce: That is actually RF coverage within this location of these access points. >> John: That is very cool. >> Bruce: Then I can jump in here and troubleshoot from there. But to your point in terms of what's going on -- >> John: So it shows overlaying clouds and channels and all those deep, deep configuration stuff. >> Bruce: All the information if you need to go there. >> John: And you just don't need to get involved in that. >> Bruce: Most of this stuff is automated. There's the auto button for a lot of this when you hook up the Wi-Fi the first time. You don't want to have to tweek all of those things. So we have the auto button that 90% of the users would use or more. And then if you needed to tune it we can go from there. But yeah, to your point in terms of application policies and controls. Here's an example of what we do here. For example, I can see what types of traffic is on this network here. So let's look at for example, YouTube. And we see that there's actually a couple users here that are using a lot of YouTube traffic. I can click on any of these applications and see what the amount of traffic is associated with that. But what's more interesting then is doing something about it. So what we have is a policy engine that recognizes 1,600 different applications and allows me to create policies on them. I can create rules and say, okay let's look at YouTube specifically, which is a streaming media application. And you can see we have hundreds in here, in fact 1,600 total. And I can block YouTube if I so desire from the network. Or maybe I allow it in there, but I limit that traffic per user to say 500 K or something like that so they maybe can't watch a 4 K video or something like that. So Enterprise is-- >> John: Make it crawl for them. >> Bruce: Yeah, you can do it, but you can't overload the network. So Enterprise is hospitals. You know schools love this because they can get that granular control of the network. And maybe this happens to be instead of Enterprise that's using a database, maybe they're an Oracle shop, and so they want to raise the quality of service on that and put that high priority. So you could do that just the same. >> John: And so whatever the priority is, they can get bandwidth through it. So if it's live gaming, and you want to have that game be, that's what I want. >> Bruce: Exactly. >> John: Or minimize it. >> Bruce: So this really, what this map ends up doing is mapping the wireless to the business needs of the organization that's deploying it. >> John: So the optimization of the network, you can look at much more clearly with the visualization, and make decisions. On the network map there with the RF. Is that for placement of access points? Or is that more for understanding propagation or -- >> Bruce: It's, yeah we have a separate design tool that allows you to design those heat maps. And then when you actually have a live network what you were looking at was actually the coverage estimation based on what's actually deployed. >> John: So it's kind of -- >> Bruce: So if an AP goes down, it turns red and then you'll see a hole in your coverage and you'll know that you have a problem that you have to go and solve. >> Okay, great. So it's (mumbles) gives you a hand. >> Yeah. >> Okay, analytics. What other analytics do you have in the demo that you could share? >> Bruce: Right, so analytics is an interesting one. We have a lot of data that we pull into the network from the Wi-Fi. So if you think about it, we know who is on the network. We know what they're doing. What applications they're going to. We know where they are, 'cause we actually calculate the location of those users. And that information is all pulled into this central location here. So if I pull in a couple of these analytics charts you actually see now what is going on in that location over time. So here we have users and how long they're actually in the network. >> John: Can you see the URL path they're using? >> Bruce: That's in the application portion. This is just kind of showing bulk, like how many users are showing in the network and how long are they there. And then how many are there, and how many are actually repeat or new. So a retail customer may be interested that, if it's like I'm getting 40% existing customers coming back, but maybe there's 60% on a given day. And then that can change over time depending on location. So the bottom line is Wi-Fi is turning, for us, into a big data challenge or solution to where I can take all that data on who, what, where, why that they're doing and then turn that into business intelligence that the retailer, that's a big one, can use for making more intelligent decisions about how they run their business. >> Okay, so bottom line for the folks watching, with respect to wireless; what's the future state that they need to be thinking about in terms of planning for Wi-Fi and to experience the future of networking by extending SD-WAN to the wireless LAN? >> Right, so there's a lot of things to consider when you look at Wi-Fi. What you're doing today is probably not going to be the same as what you do next year, and certainly not five years from now. So this is actually a big challenge for a lot of our customers to kind of get that future view of what's going to happen, because they're making a purchase decision today that's going to last them for awhile. So what we look at is solving the problems that those users might run into, which can be scale, you might be using and seeing double or triple the number of users in traffic in the next few years, so you have to solve that. You have to solve the security problems, which we didn't talk about too much today, but EasyPass is one of the solutions for that. I want to ensure those users can get on, but make sure that they're secure, my corporate data is going to be protected. And then finally the simplicity of doing that. So I know Wi-Fi is going to change. I know the network requirements are going to change. How can I simply go into an interface, though this cloud management solution we provide and make those changes that are needed and adapt to that dynamic that we're talking about. And then all of that then folds into the broader picture of the SD-WAN story that we talk about with Riverbed, where now I can do some of those things across the LAN and WAN holistically through a common control point. >> And the common control point is key because the users don't view things as LAN and WAN. They just want their stuff. >> Bruce: Yeah, right. >> Wherever they are. >> Yeah, they don't care. So they might be connected into the Wi-Fi, so that's pretty visible, but in the end the Wi-Fi could work fine, but if that WAN connection is down or compromised, or anywhere in between the data center, all these things have to be working. >> And the tools to make the integration easier, whether it's Microsoft 365, and Google, On-Premise or GoogleLogin or Facebook. >> Right, right, all those ecosystems. I mean this is the big part of what we're trying to do is tap into those systems that everybody is using anyway and make it all seamless. >> John: And easy. >> So everyone knows how to log into their Google or Facebook account, so now let's just make that part of the Wi-Fi experience. >> And security's all solid? >> Yeah, security is solid if you use it. And that's the big thing about Wi-Fi is there's a lot of open guest network still out there. And little by little you're seeing those become secure, but what tends to happen is that complexity and security are kind of at odds with each other. The more secure you make a network, the more complex. >> John: And here you're making it easier. >> That's why EasyPass and the name, that's what we do to make that as simple as possible because security is very important. >> Bruce Miller: Extending the SD-WAN to the Wireless LAN in our segment experiencing the future of networking. Thanks so much for sharing. I'm John Furrier. 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>> [Announcer] Live from Boston Massachusetts. This is theCUBE. Covering Sparks Summit East 2017. Brought to you by Databricks. Now here are your hosts, Dave Vellante and George Gilbert. >> [Dave] Welcome back to Boston everybody, this is Spark Summit East #SparkSummit And this is theCUBE. Ion Stoica is here. He's Executive Chairman of Databricks and Professor of Computer Science at UCal Berkeley. The smarts is rubbing off on me. I always feel smart when I co-host with George. And now having you on is just a pleasure, so thanks very much for taking the time. >> [Ion] Thank you for having me. >> So loved the talk this morning, we learned about RISELabs, we're going to talk about that. Which is the son of AMP. You may be the father of those two, so. Again welcome. Give us the update, great keynote this morning. How's the vibe, how are you feeling? >> [Ion] I think it's great, you know, thank you and thank everyone for attending the summit. It's a lot of energy, a lot of interesting discussions, and a lot of ideas around. So I'm very happy about how things are going. >> [Dave] So let's start with RISELabs. Maybe take us back, to those who don't understand, so the birth of AMP and what you were trying to achieve there and what's next. >> Yeah, so the AMP was a six-year Project at Berkeley, and it involved around eight faculties and over the duration of the lab around 60 students and postdocs, And the mission of the AMPLab was to make sense of big data. AMPLab started in 2009, at the end of 2009, and the premise is that in order to make sense of this big data, we need a holistic approach, which involves algorithms, in particular machine-learning algorithms, machines, means systems, large-scale systems, and people, crowd sourcing. And more precisely the goal was to build a stack, a data analytic stack for interactive analytics, to be used across industry and academia. And, of course, being at Berkeley, it has to be open source. (laugh) So that's basically what was AMPLab and it was a birthplace for Apache Spark that's why you are all here today. And a few other open-source systems like Mesos, Apache Mesos, and Alluxio which was previously called Tachyon. And so AMPLab ended in December last year and in January, this January, we started a new lab which is called RISE. RISE stands for Real-time Intelligent Secure Execution. And the premise of the new lab is that actually the real value in the data is the decision you can make on the data. And you can see this more and more at almost every organization. They want to use their data to make some decision to improve their business processes, applications, services, or come up with new applications and services. But then if you think about that, what does it mean that the emphasis is on the decision? Then it means that you want the decision to be fast, because fast decisions are better than slower decisions. You want decisions to be on fresh data, on live data, because decisions on the data I have right now are original but those are decisions on the data from yesterday, or last week. And then you also want to make targeted, personalized decisions. Because the decisions on personal information are better than aggregate information. So that's the fundamental premise. So therefore you want to be on platforms, tools and algorithms to enable intelligent real-time decisions on live data with strong security. And the security is a big emphasis of the lab because it means to provide privacy, confidentiality and integrity, and as you hear about data breaches or things like that every day. So for an organization, it is extremely important to provide privacy and confidentiality to their users and it's not only because the users want that, but it also indirectly can help them to improve their service. Because if I guarantee your data is confidential with me, you are probably much more willing to share some of your data with me. And if you share some of the data with me, I can build and provide better services. So that's basically in a nutshell what the lab is and what the focus is. >> [Dave] Okay, so you said three things: fast, live and targeted. So fast means you can affect the outcome. >> Yes. Live data means it's better quality. And then targeted means it's relevant. >> Yes. >> Okay, and then my question on security, I felt like when cloud and Big Data came to fore, security became a do-over. (laughter) Is that a fair assessment? Are you doing it over? >> [George] Or as Bill Clinton would call it, a Mulligan. >> Yeah, if you get a Mulligan on security. >> I think security is, it's always a difficult topic because it means so many things for so many people. >> Hmm-mmm. >> So there are instances and actually cloud is quite secure. It's actually cloud can be more secure than some on-prem deployments. In fact, if you hear about these data leaks or security breaches, you don't hear them happening in the cloud. And there is some reason for that, right? It is because they have trained people, you know, they are paranoid about this, they do a specification maybe much more often and things like that. But still, you know, the state of security is not that great. Right? For instance, if I compromise your operating system, whether it's in cloud or in not in the cloud, I can't do anything. Right? Or your VM, right? On all this cloud you run on a VM. And now you are going to allow on some containers. Right? So it's a lot of attacks, or there are attacks, sophisticated attacks, which means your data is encrypted, but if I can look at the access patterns, how much data you transferred, or how much data you access from memory, then I can infer something about what you are doing about your queries, right? If it's more data, maybe it's a query on New York. If it's less data it's probably maybe something smaller, like maybe something at Berkeley. So you can infer from multiple queries just looking at the access. So it's a difficult problem. But fortunately again, there are some new technologies which are developed and some new algorithms which gives us some hope. One of the most interesting technologies which is happening today is hardware enclaves. So with hardware enclaves you can execute the code within this enclave which is hardware protected. And even if your operating system or VM is compromised, you cannot access your code which runs into this enclave. And Intel has Intell SGX and we are working and collaborating with them actively. ARM has TrustZone and AMB also announced they are going to have a similar technology in their chips. So that's kind of a very interesting and very promising development. I think the other aspect, it's a focus of the lab, is that even if you have the enclaves, it doesn't automatically solve the problem. Because the code itself has a vulnerability. Yes, I can run the code in hardware enclave, but the code can send out >> Right. >> data outside. >> Right, the enclave is a more granular perimeter. Right? >> Yeah. So yeah, so you are looking and the security expert is in your lab looking at this, maybe how to split the application so you run only a small part in the enclave, which is a critical part, and you can make sure that also the code is secure, and the rest of the code you run outside. But the rest of the code, it's only going to work on data which is encrypted. Right? So there is a lot of interesting research but that's good. >> And does Blockchain fit in there as well? >> Yeah, I think Blockchain it's a very interesting technology. And again it's real-time and the area is also very interesting directions. >> Yeah, right. >> Absolutely. >> So you guys, I want George, you've shared with me sort of what you were calling a new workload. So you had batch and you have interactive and now you've got continuous- >> Continuous, yes. >> And I know that's a topic that you want to discuss and I'd love to hear more about that. But George, tee it up. >> Well, okay. So we were talking earlier and the objective of RISE is fast and continuous-type decisions. And this is different from the traditional, you either do it batch or you do it interactive. So maybe tell us about some applications where that is one workload among the other traditional workloads. And then let's unpack that a little more. >> Yeah, so I'll give you a few applications. So it's more than continuously interacting with the environment continuously, but you also learn continuously. I'll give you some examples. So for instance in one example, think about you want to detect a network security attack, and respond and diagnose and defend in the real time. So what this means is that you need to continuously get logs from the network and from the more endpoints you can get the better. Right? Because more data will help you to detect things faster. But then you need to detect the new pattern and you need to learn the new patterns. Because new security attacks, which are the ones that are effective, are slightly different from the past one because you hope that you already have the defense in place for the past ones. So now you are going to learn that and then you are going to react. You may push patches in real time. You may push filters, installing new filters to firewalls. So that's kind of one application that's going in real time. Another application can be about self driving. Now self driving has made tremendous strides. And a lot of algorithms you know, very smart algorithms now they are implemented on the cars. Right? All the system is on the cars. But imagine now that you want to continuously get the information from this car, aggregate and learn and then send back the information you learned to the cars. Like for instance if it's an accident or a roadblock an object which is dropped on the highway, so you can learn from the other cars what they've done in that situation. It may mean in some cases the driver took an evasive action, right? Maybe you can monitor also the cars which are not self-driving, but driven by the humans. And then you learn that in real time and then the other cars which follow through the same, confronted with the same situation, they now know what to do. Right? So this is again, I want to emphasize this. Not only continuous sensing environment, and making the decisions, but a very important components about learning. >> Let me take you back to the security example as I sort of process the auto one. >> Yeah, yeah. >> So in the security example, it doesn't sound like, I mean if you have a vast network, you know, end points, software, infrastructure, you're not going to have one God model looking out at everything. >> Yes. >> So I assume that means there are models distributed everywhere and they don't know what a new, necessarily but an entirely new attack pattern looks like. So in other words, for that isolated model, it doesn't know what it doesn't know. I don't know if that's what Rumsfeld called it. >> Yes (laughs). >> How does it know what to pass back for retraining? >> Yes. Yes. Yes. So there are many aspects and there are many things you can look at. And it's again, it's a research problem, so I cannot give you the solution now, I can hypothesize and I give you some examples. But for instance, you can look about, and you correlate by observing the affect. Some of the affects of the attack are visible. In some cases, denial of service attack. That's pretty clear. Even the And so forth, they maybe cause computers to crash, right? So once you see some of this kind of anomaly, right, anomalies on the end devices, end host and things like that. Maybe reported by humans, right? Then you can try to correlate with what kind of traffic you've got. Right? And from there, from that correlation, probably you can, and hopefully, you can develop some models to identify what kind of traffic. Where it comes from. What is the content, and so forth, which causes behavior, anomalous behavior. >> And where is that correlation happening? >> I think it will happen everywhere, right? Because- >> At the edge and at the center. >> Absolutely. >> And then I assume that it sounds like the models both at the edge and at the center are ensemble models. >> Yes. >> Because you're tracking different behavior. >> Yes. You are going to track different behavior and you are going to, I think that's a good hypothesis. And then you are going to assemble them, assemble to come up with the best decision. >> Okay, so now let's wind forward to the car example. >> Yeah. >> So it sound like there's a mesh network, at least, Peter Levine's sort of talk was there's near-local compute resources and you can use bitcoin to pay for it or Blockchain or however it works. But that sort of topology, we haven't really encountered before in computing, have we? And how imminent is that sort of ... >> I think that some of the stuff you can do today in the cloud. I think if you're on super-low latency probably you need to have more computation towards the edges, but if I'm thinking that I want kind of reactions on tens, hundreds of milliseconds, in theory you can do it today with the cloud infrastructure we have. And if you think about in many cases, if you can't do it within a few hundredths of milliseconds, it's still super useful. Right? To avoid this object which has dropped on the highway. You know, if I have a few hundred milliseconds, many cars will effectively avoid that having that information. >> Let's have that conversation about the edge a little further. The one we were having off camera. So there's a debate in our community about how much data will stay at the edge, how much will go into the cloud, David Flores said 90% of it will stay at the edge. Your comment was, it depends on the value. What do you mean by that? >> I think that that depends who am I and how I perceive the value of the data. And, you know, what can be the value of the data? This is what I was saying. I think that value of the data is fundamentally what kind of decisions, what kind of actions it will enable me to take. Right? So here I'm not just talking about you know, credit card information or things like that, even exactly there is an action somebody's going to take on that. So if I do believe that the data can provide me with ability to take better actions or make better decisions I think that I want to keep it. And it's not, because why I want to keep it, because also it's not only the decision it enables me now, but everyone is going to continuously improve their algorithms. Develop new algorithms. And when you do that, how do you test them? You test on the old data. Right? So I think that for all these reasons, a lot of data, valuable data in this sense, is going to go to the cloud. Now, is there a lot of data that should remain on the edges? And I think that's fair. But it's, again, if a cloud provider, or someone who provides a service in the cloud, believes that the data is valuable. I do believe that eventually it is going to get to the cloud. >> So if it's valuable, it will be persisted and will eventually get to the cloud? And we talked about latency, but latency, the example of evasive action. You can't send the back to the cloud and make the decision, you have to make it real time. But eventually that data, if it's important, will go back to the cloud. The other question of all this data that we are now processing on a continuous basis, how much actually will get persisted, most of it, much of it probably does not get persisted. Right? Is that a fair assumption? >> Yeah, I think so. And probably all the data is not equal. All right? It's like you want to maybe, even if you take a continuous video, all right? On the cars, they continuously have videos from multiple cameras and radar and lidar, all of this stuff. This continuous. And if you think about this one, I would assume that you don't want to send all the data to the cloud. But the data around the interesting events, you may want to do, right? So before and after the car has a near-accident, or took an evasive action, or the human had to intervene. So in all these cases, probably I want to send the data to the cloud. But for the most cases, probably not. >> That's good. We have to leave it there, but I'll give you the last word on things that are exciting you, things you're working on, interesting projects. >> Yeah, so I think this is what really excites me is about how we are going to have this continuous application, you are going to continuously interact with the environment. You are going to continuously learn and improve. And here there are many challenges. And I just want to say a few more there, and which we haven't discussed. One, in general it's about explainability. Right? If these systems augment the human decision process, if these systems are going to make decisions which impact you as a human, you want to know why. Right? Like I gave this example, assuming you have machine-learning algorithms, you're making a diagnosis on your MRI, or x-ray. You want to know why. What is in this x-ray causes that decision? If you go to the doctor, they are going to point and show you. Okay, this is why you have this condition. So I think this is very important. Because as a human you want to understand. And you want to understand not only why the decision happens, but you want also to understand what you have to do, you want to understand what you need to do to do better in the future, right? Like if your mortgage application is turned down, I want to know why is that? Because next time when I apply to the mortgage, I want to have a higher chance to get it through. So I think that's a very important aspect. And the last thing I will say is that this is super important and information is about having algorithms which can say I don't know. Right? It's like, okay I never have seen this situation in the past. So I don't know what to do. This is much better than giving you just the wrong decision. Right? >> Right, or a low probability that you don't know what to do with. (laughs) >> Yeah. >> Excellent. Ion, thanks again for coming in theCUBE. It was really a pleasure having you. >> Thanks for having me. >> You're welcome. All right, keep it right there everybody. George and I will be back to do our wrap right after this short break. This is theCUBE. We're live from Spark Summit East. Right back. (techno music)