[Music] [Applause] [Music] hobb universe and welcome to another cube conversation from our beautiful Studios here in Palo Alto California another great conversation today we're here with leon truffula senior vice president of global customer success at one of my favorite technology companies over the years pega systems leon welcome to the cube glad to be here Peter thank you very much for having me now leon pegas had a great track record over a number of years of helping customers build relatively complex applications and domains like crm etc but where is pega today what have you guys been up to most recently well I think that was some of the most exciting work we're doing is helping customers through their digital transformation journeys and it's where we're seeing our customers generate some incredible value and so that that happens to be the space that I think is most exciting at the at the particular moment especially in terms of how it affects the way our customers are engaging with their customers so I want to build on that because we're pretty passionate about this notion of digital transformation let me throw out a couple concepts I agree where you think this might end up so we believe pretty strongly that the route there is a difference between a business and initial business and that difference is how a business uses its data how it formulates it's at its data into assets and that has significant implications because it suggests that the process of digitally transforming is in fact the process of reinstitution iliza work organizing work organizing engagement around what your data tells you and what your data can do for your customers how does that comport with the way you guys are well I'm going to throw a level of context around that absolutely the data is essential it's essential to understand your customer but that is the point I think I think the point has to be the customer and what the customer is trying to accomplish and of course you need the data to be able to support it but really focusing on the customer instead of focusing on what it is you're trying to do internally is what's key for digital's success so yeah we would agree and by the way when so we would say that it is about applying data to the processes of creating and sustaining your customer yes but you're absolutely right we're not just doing digital transformation on our operation so that's pretty important we're doing digital transformation on anything that's important to how the business engages its marketplace yes yes and and and one of the things that we think is essential though is yes you can assemble the data but if you don't understand from the customer's perspective how that data is going to apply to them as they go from channel to channel what you miss is the important aspect of understanding the true customer journey I mean what is it the what is the outcome the customer is trying to accomplish okay in terms of their interaction with you how do you apply that data so that you ensure that they're getting the right next best action in terms of guiding them through that process and how do you make that next best action contextual with what the customer is a cop trying to try to do so for example you may have an engagement with the customer and through your segmentation have decided wow this is a high net worth customer I want to I want to sell them lots of stuff but if they're on your web page around how to cancel their service with you offering them a cross-sell opportunities inappropriate its leveraging that data as well as the context as well as what is the customer trying to accomplish to ensure that that next best action actually drives to the outcome that you're looking for oh it's in so context matters so let me only run another concept by you then so as for number of years I talked about the difference between what we call offer response for fill marketing where the business is projecting an offer and expecting someone who's respond and then they'll fulfill to need match engage where increasingly you're trying to capture information or insight about again as you said what the customers outcome is and then hopefully find a way to match to their journey there are six their success parameters and then engage them to help them achieve their success is that kind of what we're talking about it is it not to engage where in turn it is except that except that our perspective is is that especially in digital channels you you don't necessarily have to be responsive but actually be proactive be proactive in terms of okay I know this is the outcome the customer is trying to achieve what value can I provide to them as they're going through my process so that they get the most out of my experience one it's going to be simple okay it's got to be quick but it's also going to be value-added to them otherwise they'll fail just as doing that you know you're not really relevant to them and they'll find somebody that is but it speeds important so this so I would say that's part of the matching is the ability to understand the customers need but also provide visibility into their future what how to get to the outcome and what not but that's going to require a new way of thinking about building systems and how those systems get applied to engagement what types of things are your customers doing along those lines to improve the hit rate of matching but also sustaining that throughout a customer's journey so I'm gonna tell you the three biggest mistakes that people make and how pega tries to guide them to avoid it so the first mistake that people make in their digital journeys okay is they think in terms of channels and not the customer journey the second biggest mistake they make okay is that they think in this context of a transaction I'm just doing the transaction but not in terms of the outcome that we're trying to accomplish and then honestly the third biggest mistake is they think in silos instead of the end-to-end relationship that you want to have at the customer so so too often what happens is is that companies take an internal view of what they're trying to accomplish rather than the external view of what's the customer trying to accomplish with me so channel transaction silo those that those those three problems so if we can turn that around what we're basically saying let's start with channel we're focusing first and foremost on the context of the customer and where they are in relation to a journey to an outcome is that the first thing that they're not quite so when you think about channels you almost have to think of this as being a channel agnostic point of view because your customer is going to move from channel to channel to channel as we go through the journey as they go through the journey like if I wanted to open a checking account on a with a digital Bank you know I might start with my mobile device don't have enough time to finish it get into the office want to continue the application on my on your website okay run into a problem want to call you the customer expects that they never have to tell you anything that they've already told you and if you actually end up building the logic for how you open something like a checking account in the channels you will never be able to have that and and fluid seamless experience so let me put that in very specific terms if the context of the engagement is bound inside a particularly then you can't track what the customers doing it's a state you can't track what the customers doing across different channels yes exactly so this is why you've got to think of the customer journey okay this is what a customer has to do to open a checking account with me how do you nuance that experience per channel but essentially okay you end up having to reuse that journey to effectively drive in a successful customer experience and that also leads to this question of silo right because sometimes silos are product silos other times they're channel silos or other times they're customer attributes silos and what you're basically describing is if you're going to truly track where the customer is relative to their outcome and acknowledge that different channels provide different ways of engaging and providing value to the customer different points along that journey then you want to break down those silos so that you can be provide a richer experience to the customer wherever they are on the journey I got that right yeah absolutely so it's another big mistake when I talk about silos people think about what am I gonna push to the customer push to the customer and internally as you think away a lot of you know companies are organized they're organized around products so of course those silos within companies want to push whatever they think the customer should have however the customer is the one that's really in charge and the customer doesn't care about your silos they care about the relationship they have with you all right so and whether achieves the outcome rather than uh facilitates and provides a fidelity or to the outcome that they seek yeah so just imagine how terrible would be if through your segmentation you've decided that you know Peter you're a high-value customer I want to sell you lots of stuff and I want to I want to cross sell you something but if in the context of you being on my page around how you cancel my service with me okay flashing you across that lad that's not going to go over very well that's not going to make you more inclined to stay with me now however you may annoy the hell out of me quite frankly if I understood the context and knew that's the right message for you is a retention proposal well then all of a sudden you start to drive improved relevance to the customer which will in turn drive improve success with the customer I mean we you know we're having our user conference in a couple of days June 36 there's pega world and you know we've got some great mainstage speakers and one of the one of the fabulous stories from last year was around house sprint okay was able to across channels drive improved retention okay why because they actually took that journey approach they understood where their customers were the context of what was happening when a customer might be at risk of leaving okay and be able to provide with the right next best action an offer to ensure that that customer stayed with the organization and they've achieved tremendous success as a result of that and this year we're excited about other customers like anthem telling the story around how they're going to drive customer improvement and customer engagement once again by understanding the customer journey the outcomes the customers are trying to achieve and bringing the right message driven by the data in the right time through the right next action so many years ago I was I have a friend who's a Business School professor and I was discussing the adoption of very complex high-value transaction operational and applications like si P and then as we were having this conversation he kind of stopped and he said so you're telling me your customers were actually willing to pour concrete in their business so hagit none of ecosystems nonetheless provides applications provides a platform provides development tools how are you ensuring that your customers aren't pouring concrete on their business when they adopt peg systems well a lot of it has to deal with with a confluence of a bunch of technologies one core to our product is the ability to build for change so all of our products all of our products are built on a no code platform okay so citizen developers were able to actually take control of their applications make changes of course working with IT ok to ensure that they're well integrated with the systems and and things are well designed but we make it very very easy to build an application and then change that application however what's also critically important is to recognize where it is you need to change so pega has invested very heavily in robotics okay and one of the robots that we bring to market is one that captures the metadata of your users keystrokes as they're engaging okay so this is robotic process automation music no robotic process automation is is is a different type of organism this particular robot we call workforce intelligence and Workforce Intelligence captures the metadata of you users keystrokes throws it up to the cloud where AI engine understands the customer journeys that are happening oh this particular user is opening a new account oh now they're changing an address so on and so forth it sees how your users are engaging with technology and honestly how your technology is engaging with users now today what happens is is that the system will generate report that will show you oh we see this is an area for improved automation because we know what your people learn we can tell you that the ROI from implementing this automation will be X the next one is Sierra next one so we've actually prioritizes for you it gives you a report to prioritize for you the areas where you should change to be able to improve the overall experience now as I turn that into practical things that might be for example suggesting what the next sprint is yes very much so that is what's real today let me take you on a journey of the art of the possible now let me tell you what's around the call no I won't go you won't go well let me take you anyway what's net what's around the corner is the ability for us to generate self optimizing applications so today ok will give you a report telling you what your low-hanging fruit is how about if I also asked you hey do you want us to build test it and deploy it for you do you want us to put an RPA bot here a robotic desktop automation there may be a little DPM automation here that's around the corner and it's actually real today in some of our applications it's real today in our applications around retention upsell cross-sell and end-to-end collections and we're driving it more and more into more of our solutions so this is an incredibly exciting time because not only we able to help customers achieve their digital journey but we're also helping them achieve the incremental improvements that frankly you always have to have to implement because we live in a world with no status quo so you always have to be ready for change no that's very true and the just super clear the whole notion of as you said the citizen programmer means we're not working down in primitives we're working very very close to the way the business thinks about problems right yeah so as we think about building an application it's kind of like the manufacturing of software well the manufacturing of software is the only type of manufacturing yet to benefit from CAD cam so our development environment which we call directly capturing objectives is actually incredibly business friendly using metaphors that are familiar to the business you do not write code in fact if you're writing code when you're delivering a Pegasus you are doing it wrong so the citizen developer the the technically savvy business person is able to very very quickly master the capabilities of how to use a pega system and honestly how to build and maintain their own applications so that's how we make it easy to implement change you we're trying to break out of this paradigm where whenever you want to implement something that's a change you've got to go and hire somebody to come in and do a walk through that write a requirement document okay and then throw it over the fence to IT to translate something in Microsoft Word into a language computers can understand I mean that's been the paradigm for the last 60 years we think there's a better way and and that's what our platform is really focused on driving that better way excellent all right we have to stop there William oh thank you Peter it's been a great conversation went very very very fast all right so Leon trifler global customer success SVP pega systems on Peter Burris this has been another cube conversation Leon great thanks very much thank you Peter [Music]

>>Yeah, yeah. >>Welcome back to session, too. Thoughts about everywhere. Unlock new revenue streams with embedded search and I Today we're joined by our senior director of Global Oh am Rick Dimel, along with speakers from our thoughts about customer Hayes to discuss how thought spot is open for everyone by unlocking unprecedented value through data search in A I, you'll see how thoughts about compound analytics in your applications and hear how industry leaders are creating new revenue streams with embedded search and a I. You'll also learn how to increase app stickiness on how to create an autonomous this experience for your end users. I'm delighted to introduce our senior director of Global OPM from Phillips Spot, Rick DeMARE on then British Ramesh, chief technology officer, and Leon Roof, director of product management, both from Hayes over to you. Rick, >>Thank you so much. I appreciate it. Hi, everybody. We're here to talk to you about Fox Spot everywhere are branded version of our embedded analytics application. It really our analytics application is all about user experience. And in today's world, user experience could mean a lot of things in ux design methodologies. We want to talk about the things that make our product different from an embedded perspective. If you take a look at what product managers and product design people and engineers are doing in this space, they're looking at a couple of key themes when they design applications for us to consume. One of the key things in the marketplace today is about product led growth, where the product is actually the best marketing tool for the business, not even the sales portion or the marketing department. The product, by the word of mouth, is expanding and getting more people onto the system. Why is that important? It's important because within the first few days of any application, regardless of what it is being used binding users, 70% of those users will lose. Interest will stop coming back. Why do they stop coming back? Because there's no ah ha moment through them. To get engaged within the technology, today's technologies need to create a direct relationship with the user. There can't be a gatekeeper between the user and the products, such as marketing or sales or information. In our case. Week to to make this work, we have toe leverage learning models in leverage learning as it's called Thio. Get the user is engaged, and what that means is we have to give them capabilities they already know how to use and understand. There are too many applications on the marketplace today for for users to figure out. So if we can leverage the best of what other APS have, we can increase the usage of our systems. Because in today's world, what we don't want to do from a product perspective is lead the user to a dead end or from a product methodology. Our perspective. It's called an empty state, and in our world we do that all the time. In the embedded market place. If you look at at the embedded marketplace, it's all visualizations and dashboards, or what I call check engine lights in your application's Well, guess what happens when you hit a check engine life. You've got to call the dealer to get more information about what just took place. The same thing happens in the analytic space where we provide visualizations to users. They get an indicator, but they have to go through your gatekeepers to get access to the real value of that data. What am I looking at? Why is it important the best user experiences out on the marketplace today? They are autonomous. If we wanna leverage the true value of digital transformation, we have to allow our developers to develop, not have them, the gatekeepers to the rial, content to users want. And in today's world, with data growing at much larger and faster levels than we've ever seen. And with that shelf life or value of that data being much shorter and that data itself being much more fragmented, there's no developer or analysts that can create enough visualizations or dashboards in the world to keep the consumption or desire for these users to get access to information up to speed. Clients today require the ability to sift through this information on their own to customize their own content. And if we don't support this methodology, our users are gonna end up feeling powerless and frustrated and coming back to us. The gatekeepers of that information for more information. Loyalty, conversely, can be created when we give the users the ability toe access this information on their own. That is what product like growth is all about in thought spot, as you know we're all about search. It's simple. It's guided as we type. It gives a super fast responses, but it's also smart on the back end handling complexities, and it's really safe from a governance and as well as who gets access to what perspective it's unknown learned environment. Equally important in that learned environment is this expectation that it's not just search on music. It's actually gonna recommend content to me on the fly instantly as I try content I might not even thought of before. Just the way Spotify recommends music to us or Netflix recommends a movie. This is a expected learned behavior, and we don't want to support that so that they can get benefit and get to the ah ha moments much quicker. In the end, which consumption layer do you want to use, the one that leads you to the Dead End Street or the one that gets you to the ah ha moment quickly and easily and does it in an autonomous fashion. Needless to say, the benefits of autonomous user access are well documented today. Natural language search is the wave of the future. It is today. By 2004 75% of organizations are going to be using it. The dashboard is dead. It's no longer going to be utilized through search today, I if we can improve customer satisfaction and customer productivity, we're going to increase pretensions of our retention of our applications. And if we do that just a little bit, it's gonna have a tremendous impact to our bottom line. The way we deploy hotspots. As you know, from today's conversations in the cloud, it could be a manage class, not offering or could be software that runs in your own VPC. We've talked about that at length at this conference. We've also talked about the transformation of application delivery from a Cloud Analytics perspective at length here it beyond. But we apply those same principles to your product development. The benefits are astronomical because not only do you get architectural flexibility to scale up and scale down and right size, but your engineers will increase their productivity because their offerings, because their time and effort is not going to be spent on delivering analytics but delivering their offerings. The speed of innovation isn't gonna be released twice a year or four times a year. It's gonna It can happen on a weekly basis, so your time to market in your margins should increase significantly. At this point, I want a hand. The microphone over to Revert. Tesche was going to tell you a little bit about what they're doing. It hes for cash. >>Thanks, Rick. I just want to introduce myself to the audience. My name is Rotational. Mention the CTO Europe ace. I'm joined my today by my colleague Gillian Ruffles or doctor of product management will be demoing what we have built with thoughts about, >>um but >>just to my introduction, I'm going to talk about five key things. Talk about what we do. What hes, uh we have Really, um what we went through the select that spot with other competitors What we have built with that spot very quickly and last but not least, some lessons learned during the implementation. So just to start with what we do, uh, we're age. We are health care compliance and revenue integrity platform were a saas platform voter on AWS were very short of l A. That's it. Use it on these around 1 50 customers across the U. S. On these include large academic Medical Insight on. We have been in the compliant space for the last 30 plus years, and we were traditionally consulting company. But very recently we have people did more towards software platform model, uh, in terms off why we chose that spot. There were three business problems that I faced when I took this job last year. At age number one is, uh, should be really rapidly deliver new functionality, nor platform, and he agile because some of our product development cycles are in weeks and not months. Hey had a lot of data, which we collected traditionally from the SAS platform, and all should be really create inside stretch experience for our customers. And then the third Big one is what we saw Waas large for customers but really demanding self service capabilities. But they were really not going for the static dash boats and and curated content, but instead they wanted to really use the cell service capabilities. Thio mind the data and get some interesting answers during their questions. So they elevated around three products around these problems statements, and there were 14 reasons why we just start spot number one wars off course. The performance and speed to insights. Uh, we had around 800 to a billion robot of data and we wanted to really kind of mind the data and set up the data in seconds on not minutes and hours. We had a lot of out of the box capabilities with that spot, be it natural language search, predictive algorithms. And also the interactive visualization, which, which was which, Which gave us the agility Thio deliver these products very quickly. And then, uh, the end user experience. We just wanted to make sure that I would users can use this interface s so that they can very quickly, um, do some discovery of data and get some insights very quickly. On last but not least, talksport add a lot of robust AP ice around the platform which helped us embed tot spot into are offering. But those are the four key reasons which we went for thoughts part which we thought was, uh, missing in in the other products we evaluated performance and search, uh, the interactive visualization, the end user experience, and last but not least flexible AP ice, which we could customize into our platform in terms of what we built. We were trying to solve to $50 billion problem in health care, which is around denials. Um so every year, around 2, 50 to $300 billion are denied by players thes air claims which are submitted by providers. And we built offering, which we called it US revenue optimizer. But in plain English, what revenue optimizer does is it gives the capability tow our customers to mind that denials data s so that they can really understand why the claims were being denied. And under what category? Recent reasons. We're all the providers and quarters who are responsible for these claims, Um, that were dryland denials, how they could really do some, uh, prediction off. It is trending based on their historical denial reasons. And then last but not least, we also build some functionality in the platform where we could close the loop between insights, action and outcome that Leon will be showing where we could detect some compliance and revenue risks in the platform. On more importantly, we could, uh, take those risks, put it in a I would say, shopping card and and push it to the stakeholders to take corrective action so the revenue optimizer is something which we built in three months from concept to lunch and and that that pretty much prove the value proposition of thoughts. But while we could kind of take it the market within a short period of time Next leopard >>in terms >>off lessons learned during the implementation thes air, some of the things that came to my mind asses, we're going through this journey. The first one is, uh, focus on the use case formulation, outcomes and wishful story boarding. And that is something that hot spot that's really balance. Now you can you can focus on your business problem formulation and not really focus on your custom dash boarding and technology track, etcetera. So I think it really helped our team to focus on the versus problem, to focus on the outcomes from the problem and more importantly, really spend some time on visualizing What story are we say? Are we trying to say to our customers through revenue optimizer The second lesson learned first When we started this implementation, we did not dualistic data volume and capacity planning exercise and we learned it our way. When we are we loaded a lot of our data sets into that spot. And then Aziz were doing performance optimization. XYZ. We figured out that we had to go back and shot the infrastructure because the data volumes are growing exponentially and we did not account for it. So the biggest lesson learned This is part of your architectural er planning, exercise, always future proof your infrastructure and make sure that you work very closely with the transport engineering team. Um, to make sure that the platform can scale. Uh, the last two points are passport as a robust set of AP Ice and we were able to plug into those AP ice to seamlessly ended the top spot software into a platform. And last but not least, one thing I would like to closest as we start these projects, it's very common that the solution design we run into a lot of surprises. The one thing I should say is, along those 12 weeks, we very closely work with the thoughts, part architecture and accounting, and they were a great partner to work with us to really understand our business problem, and they were along the way to kind of government suggested, recommends and workarounds and more importantly, also, helpers put some other features and functionality which you requested in their engineering roadmap. So it's been a very successful partnership. Um, So I think the biggest take of it is please make sure that you set up your project and operating model value ember thoughts what resources and your team to make sure that they can help you as you. It's some obstacles in the projects so that you can meet your time ones. Uh, those are the key lessons learned from the implementation. And with that, I would pass this to my colleague Leon Rough was going to show you a demo off what we go. >>Thanks for Tesh. So when we were looking Thio provide this to our customer base, we knew that not everyone needed do you access or have available to them the same types of information or at the same particular level of information. And we do have different roles within RMD auto Enterprise platform. So we did, uh, minimize some roles to certain information. We drew upon a persona centric approach because we knew that those different personas had different goals and different reasons for wanting to drive into these insights, and those different personas were on three different levels. So we're looking at the executive level, which is more on the C suite. Chief Compliance Officer. We have a denial trending analyses pin board, which is more for the upper, uh, managers and also exact relatives if they're interested. And then really, um, the targeted denial analysis is more for the day to day analysts, um, the usage so that they could go in and they can really see where the trends are going and how they need to take action and launch into the auditing workflow so within the executive or review, Um, and not to mention that we were integrating and implementing this when everyone was we were focused on co vid. So as you can imagine, just without covert in the picture, our customers are concentrated on denials, and that's why they utilize our platform so they could minimize those risks and then throw in the covert factor. Um, you know, those denial dollars increase substantially over the course of spring and the summer, and we wanted to be able to give them ah, good view of the denials in aggregate as well as's we focus some curated pin boards specific to those areas that were accounting for those high developed denials. So on the Executive Overview Board, we created some banner tiles. The banner tiles are pretty much a blast of information for executives thes air, particular areas where there concentrating and their look looking at those numbers consistently so it provides them away to take a good look at that and have that quick snapshot. Um, more importantly, we did offer as I mentioned some curated pin boards so that it would give customers this turnkey access. They wouldn't necessarily have to wonder, You know, what should I be doing now on Day one, but the day one that we're providing to them these curated insights leads the curiosity and increases that curiosity so that they can go in and start creating their own. But the base curated set is a good overview of their denial dollars and those risks, and we used, um, a subject matter expert within our organization who worked in the field. So it's important to know you know what you're targeting and why you're targeting it and what's important to these personas. Um, not everyone is necessarily interests in all the same information, and you want to really hit on those critical key point to draw them and, um, and allowed them that quick access and answer those questions they may have. So in this particular example, the curated insight that we created was a monthly denial amount by functional area. And as I was mentioning being uber focused on co vid, you know, a lot of scrutiny goes back to those organizations, especially those coding and H i M departments, um, to ensure that their coding correctly, making sure that players aren't sitting on, um, those payments or denying those payments. So if I were in executive and I came in here and this was interesting to me and I want to drill down a little bit, I might say, You know, let me focus more on the functional area than I know probably is our main concern. And that's coating and h i M. And because of it hit in about the early winter. I know that those claims came in and they weren't getting paid until springtime. So that's where I start to see a spike. And what's nice is that the executive can drill down, they may have a hunch, or they can utilize any of the data attributes we made available to them from the Remittance file. So all of these data, um, attributes are related to what's being sent on the 8 35 fear familiar with the anti 8 35 file. So in particular, if I was curious and had a suspicion that these were co vid related or just want to concentrate in that area, um, we have particular flag set up. So the confirmed and suspected cases are pulling in certain diagnosis and procedure codes. And I might say 1.27 million is pretty high. Um, toe look at for that particular month, and then they have the ability to drill down even further. Maybe they want to look at a facility level or where that where that's coming from. Furthermore, on the executive level, we did take advantage of Let me stop here where, um also provided some lagged a so leg. This is important to organizations in this area because they wanna know how long does it take before they re submit a claim that was originally denied before they get paid industry benchmark is about 10 days of 10 days is a fairly good, good, um, basis to look at. And then, obviously anything over that they're going to take a little bit more scrutiny on and want to drill in and understand why that is. And again, they have that capabilities in order to drill down and really get it. Those answers that they're looking for, we also for this particular pin board. And these users thought it would be helpful to utilize the time Siri's forecasting that's made available. So again, thes executives need thio need to keep track and forecast where they're trends were going or what those numbers may look like in the future. And we thought by providing the prediction pins and we have a few prediction pins, um would give them that capability to take a look at that and be able to drill down and use that within, um, certain reporting and such for their organization. Another person, a level that I will go to is, um, Mawr on the analyst side, where those folks are utilizing, um, are auditing workflow and being in our platform, creating audits, completing audits, we have it segregated by two different areas. And this is by claim types so professional or institutional, I'm going to jump in here. And then I am going to go to present mode. So in this particular, um, in this particular view or insight, we're providing that analysts view with something that's really key and critical in their organization is denials related Thio HCC s andi. That's a condition category that kind of forecast, the risk of treatment. And, you know, if that particular patient is probably going to be seen again and have more conditions and higher costs, higher health care spending. So in this example, we're looking at the top 15 attending providers that had those HCC denials. And this is, um, critical because at this point, it really peaks in analyst curiosity. Especially, You know, they'll see providers here and then see the top 15 on the top is generating Ah, hide denial rate. Hi, denial. The dollars for those HCC's and that's a that's a real risk to the organization, because if that behavior continues, um, then those those dollars won't go down. That number won't go down so that analysts then can go in and they can drill down um, I'm going to drill down on diagnosis and then look at the diagnosis name because I have a suspicion, but I'm not exactly sure. And what's great is that they can easily do this. Change the view. Um, you know, it's showing a lot of diagnoses, but what's important is the first one is sepsis and substance is a big one. Substances something that those organizations see a lot of. And if they hover, they can see that 49.57 million, um, is attributed to that. So they may want to look further into that. They'd probably be interested in closing that loop and creating an audit. And so what allowed us to be able to do that for them is we're launching directly into our auditing workflow. So they noticed something in the carried insight. It sparked some investigation, and then they don't have to leave that insight to be able to jump into the auditing workflow and complete that. Answer that question. Okay, so now they're at the point where we've pulled back all the cases that attributed to that dollar amount that we saw on the Insight and the users launching into their auditing workflow. They have the ability Thio select be selective about what cases they wanna pull into the audit or if they were looking, um, as we saw with sepsis, they could pull in their 1600 rose, but they could take a sampling size, which is primarily what they would do. They went audit all 1600 cases, and then from this point in they're into, they're auditing workflow and they'd continue down the path. Looking at those cases they just pulled in and being able Thio finalized the audit and determine, you know, if further, um, education with that provider is needed. So that concludes the demo of how we integrated thought spot into our platform. >>Thank you, LeAnn. And thank you. Re test for taking the time to walk us through. Not only your company, but how Thought spot is helping you Power analytics for your clients. At this point, we want to open this up for a little Q and A, but we want to leave you with the fact that thought spot everywhere. Specifically, it cannot only do this for Hayes, but could do it for any company anywhere they need. Analytical applications providing these applications for their customers, their partners, providers or anybody within their network for more about this, you can see that the website attached below >>Thanks, Rick and thanks for tests and Leon that I find it just fascinating hearing what our customers are doing with our technology. And I certainly have learned 100% more about sepsis than I ever knew before this session. So thank you so much for sharing that it's really is great to see how you're taking our software and putting it into your application. So that's it for this session. But do stay tuned for the next session, which is all about getting the most out of your data and amplifying your insights. With the help of A, I will be joined by two thought spot leaders who will share their first hand experiences. So take a quick breather and come right back

(soft music) >> From around the globe, it's theCUBE. Presenting, Accelerating Automation with DevNet, brought to you by Cisco. >> And welcome back everybody, Jeff Frick here with theCUBE. We have our ongoing coverage of the Cisco DevNet event. It's really Accelerating with Automation and Programmability in the new normal. And we know the new normal is definitely continuing to go. We've been doing this since the middle of March and now we're in October. So, we're excited to have our next guest. He's Thomas Scheibe, he is the vice president of product management for data center for Cisco, Thomas, great to see you. >> Hey, good to see you too. >> Yeah. >> Yeah, and truly run it in normal as everybody can see on our background. >> Exactly, so, I mean, I'm curious, we've talked to a lot of people. We talked to a lot of leaders, you know, especially like back in March and April with this light switch moment, which was, you know, no time to prep, and suddenly everybody has to work from home. Teachers got to teach from home. And so you got the kids home, you got the spouse home, everybody's home trying to get on the network and do their zoom calls and their classes. I'm curious from your perspective, you guys are right there on the network, you're right in the infrastructure. What did you hear and see kind of from your customers when suddenly, you know, March 16th hit and everybody had to go home? >> Well, (laughs) good point, hey, I do think we all appreciate the network much more than we used to do before. And then the only other difference is I'm really more on WebEx calls and zoom calls, but, you know, otherwise yes. What I do see actually is that as I said network becomes much more operas as a critical piece. And so before we really talked a lot about agility and flexibility, these days we talk much more about resiliency quite frankly, and what do I need to have in place with respect to network to get my things from left to right. And you know, north to south and east to west, as we see in the data center. >> Right. >> And touches as for most of my customers, a very, very important topic at this point. >> Right, you know, it's amazing to think, you know, had this happened, you know, five years ago, 10 years ago, you know, the ability for so many people in the information industry to be able to actually make that transition relatively seamlessly is actually pretty amazing. I'm sure there was (chuckles) some excitement and some kudos in terms of, you know, it is all based on the network and it is kind of this quiet thing in the background that nobody pays attention to. It's like a ref in the football game until they make a bad play. So, you know, it is pretty fascinating that you and your colleagues have put this infrastructure and that enabled us to really make that move with really no prep, no planning and actually have a whole lot of services delivered into our homes that we're used to getting at the office or are used to getting at school. >> Yeah, and I mean, to your point, I mean, some of us did some planning. We clearly talking about some of these trends and the way I look at this trend as being distributed data centers and having the ability to move your workloads and access for users to wherever you want to be. And so I think that clearly went on for a while. And so, in a sense we prep was our normal we're prepping for. But as I said, resiliency just became so much more important. And, you know, one of the things I actually do a little preview for a blog I put out end of August around resiliency. If you didn't put this in place, you better put it in place. Because I think as we all know, we saw it in March this is like maybe two or three months, we're now in October. And I think this is the new normal for some time being. >> Yeah, I think so. So, let's stick on that theme in terms of trends, right? The other great trend is public cloud and hybrid cloud and multi cloud. There's all types of variants on that theme, you had in that blog post about resiliency in data center cloud networking, data center cloud. You know, some people think, wait, it's kind of an either or I either got my data center or I've got my stuff in the cloud and I've got public cloud. And then as I said, hybrid cloud, you're talking really specifically about enabling both inner data center resiliency within multi data center resiliency within the same enterprise as well as connecting to the cloud. That's probably counterintuitive for some people to think that that's something that Cisco is excited about and supporting. So, I wonder if you can share, you know, kind of how the market is changing, how you guys are reacting and really putting the things in place to deliver customer choice. >> Yeah, no, it's actually, to me, it's really not counterintuitive because in the end, what I'm focusing on and the company is focusing on is what our customers want to do and need to do. And that's really, you know, most people call hybrid cloud or multicloud. In the end, what it is is really the ability to have the flexibility, to move your workloads where you want them to be. And there are different reasons why you want to place them, right? You might've placed them for security reason. You might played some compliance reasons depending on which customer segment you're after. If you're in the United States or in Europe or in Asia, there are a lot of different reasons where you're going to put your syncs. And so I think in the end what an enterprise looks for is that agility, flexibility, and resiliency. And so really what you want to put in place is what we call like a cloud on ramp, right? You need to have an ability to move syncs as needed. But the logic context section which we see in the last couple of months accelerating is really this whole theme around digital transformation, which goes hand in hand than was the requirement on the IT side really do. And IT operations transformation, right? How IT operates. And I think that's really exciting to see, and this was excellent. Well, a lot of my discussions I was customized. What does it actually mean with respect to the IT organization? And what are the operational changes there's a lot of our customers are going through quite frankly accelerated going through? >> Right, and automation is in the title of the event. So, automation is an increasingly important thing, you know, as we know, and we hear all the time, you know, the flows of data, the complexity of the data. Either on the security or the way the network's moving, or as you said, shifting workloads around, based on the dynamic situations, whether that's business security, et cetera. And a software defined networking has been around for a while. How are you seeing kind of this evolution in adding more automation, you know, to more and more processes to free up those you know, kind of limited resources in terms of really skilled people to focus on the things that they should be focused on and not stuff that hopefully you can, you know, get a machine to run with some level of automation. >> Yeah, that's a good point. And I said, TechLine, I have, you know, sometimes when my mind is really going from CloudReady, which is in most of our infrastructure is today to cloud-native. And so let me a little expand on those, right? It's like the CloudReady is basically what we have put in place over the last five to six years, all the infrastructure that our customers have, network infrastructure or the Nexus 9000, they're all CloudReady, right? And what this really means, you have APIs everywhere, right? Whether this is on the box, whether it's on the controller, whether this is on the operations tools, all of these are API enabled. And that's just the foundation for automation, right? You have to have that. Now, the next step really is what do you do with that capability, right? And this is the integration with a lot of automation tools and that's the whole range, right? This is where the IT operation transformation kicks in different customers at different speed, right? Some just, you know, I use these APIs and use normal tools that they have on a network world just to pull information. Some customers go for further saying, "I want to integrate this with some CMDB tools." Some go even further and saying, "This is like the cloud-native (indistinct), "Oh, I want to use, let's say, Red Hat Ansible, or I want to use (indistinct) Terraform and use those things to actually drive how I managed my infrastructure. And so that's really the combination of the automation capability plus the integration was relevant cloud-native enabling tools that really is happening at this point. We're seeing customers accelerating in that motion. Which really then drives us how they run their IT operations. >> Right. >> And so that's a pretty exciting area to see. given as I said, we have the infrastructure in place. There's no need for customers to actually do change something. Most of them have already the infrastructures that can do this. It's just not doing the operational change the process change is to actually get there. >> Right, and it's funny, we recently covered, you know, PagerDuty and they highlight what you just talked about, the cloud-native, which is, you know, all of these applications now are so interdependent on all these different API, you know, pulling data from all these technical applications. So, hey, when they work great, it's terrific. But if there's a problem, you know, there's a whole lot of potential throats to choke out there and find those issues. And it's all being connected via the network. So, you know, it's even more critically important, not only for the application, but for all these little tiny components within the application to deliver, you know, ultimately a customer experience within very small units of time. So, that you don't lose that customer. You complete that transaction. They check out of their shopping cart. You know, all these things that are now created with cloud-native applications that just couldn't really do before. >> Now, you're absolutely right. And this is like, just as I said, I'm actually very excited because it opens up a lot of abilities for our customers. How they want to actually structure the operation, right? One of the nice things around this whole automation plus cloud network tool integration is you actually opened us up not a sole automation training, not just to the network operations personnel, right? You also open it up and can use those for the SecOps person or for the DevOps person or for the CloudOps engineering team, right? Because the way it's structured, the way we built this, it's literally as an API interface and you can now decide, what is your process? Do you want to have a more traditional process, you have to request, a network operation teams executes the request using these tools and then hands it back over. Or do you say, "Hey, maybe some of these security things, "I can hand over the SecOps team and they can "directly call these APIs, right?" Or even one step further, you can have the opportunity that the DevOps or the application team actually says, "Hey, I going to write a whole infrastructure as code "kind of a script or template, and I just execute, right?" And it's really just using what the infrastructure provides. And so that whole range of different user roles in our customer base, what they can do with the automation capability that's available. It's just very, very exciting way because it literally unleashes a lot of flexibility. How they want to structure and how they want to rebuild the IT operations processes. >> That's interesting, you know, 'cause the, you know, the DevOps culture has taken over a lot, right? Obviously changed software programming for the last 20 years. And I think, you know, there's a lot of just kind of the concept of DevOps versus necessarily, you know, the actual things that you do to execute that technique. And I don't think most people would think of, you know, NetworkOps or, NetOps, whatever the equivalent is in the networking world to have kind of a fast changing dynamic kind of point of view versus a stick it in, spec it, stick it in, lock it down. So, I wonder if you can, you can share how, kind of that DevOps attitude point of view, workflow, whatever the right verb is has impacted things at Cisco in the way you guys think about networking and flexibility within the networking world. >> Yeah, literally, absolutely. And again, it's all customer driven, right? It's none of these is really actually, you know, a little bit of credit, maybe some of us where we have a vision, but a lot of it is just customer driven feedback. And yeah, we do have EU Network Operations Teams come to you saying, "Hey, we use Ansible heavily on the compute, "so, we might use this for Alpha Seven. "We want to use the same for networking." And so we made available all these integrations with sobriety as a state, whether these are the switches, whether these are ACI and dc network controller or our multi site orchestration capabilities, all of these has Ansible integration the way to the right. The other one as I mentioned that how she formed Tarco Terraform, we have integrations available and they see the requests for these tools to use that. And so that is the motion we're in for over a year now. And another blog actually is out there we just posted saying, Yeah, all set what you can do. And then a parallel to this, right? Just making the integration available. We also have a very, very heavy focus on definite and enablement and training. And, you know, a little plucking I know probably part of the segment, the whole definite community that Cisco has is very, very vibrant. And the beauty of this is right. If you look at us, whether you're a NetOps person or a DevOps person or a SecOps person, it doesn't really matter. There's a lot of like capability available to just help you get going or go from one level to the next level, right? And there's simple things like sandbox environments where you can, you know, without stress try things out, snippets of code are there, you can do all of these things. And so we do see it's a kind of a push and pull a tremendous amount of interest and a tremendous time people spend to learn. Quite frankly then, that's another side product of the suggestion when people say, "Oh man, and say, okay, online learning is the thing." So, these tools are used very heavily. >> Right. That's awesome 'cause you know, we've had Susie Leon a number of times and I know he and Mandy and the team, right? Really built this DevNet thing. And it really follows along this other theme that we see consistently across other pieces of tech, which is democratization, right? Democratization is the access tool, taking it out of just a mahogany row with, again, a really limited number of people that know how to make it work. And it can make the changes in an opening up to a software defined world where now it's application centric point of view, where the people that are building the apps to go create competitive advantage now don't have to wait for, you know, the one network person to help them out in and out of these environments really interesting. And I wonder if, you know, when you look at what's happened with public cloud and how they kind of changed the buying parameter, how they kind of changed the degree of difficulty to get project started, you know, how you guys have kind of integrated that type of thought process to make it easier for app developers to get their job done. >> Yeah, I mean, again, I typically look at this more from a customer lens, right? It's the transformation process and it always starts as I want agility, I want flexibility and I want resiliency, right? This is where we talk to a business owner what they're looking for. And then that translates into an IT operations process, right? Your strategy needs to map then how you actually do this. And that just drives then what tools do you want to have available to actually enable this, right? And the enablement again is for different roles, right? You need to give sync services to the app developer and the platform team and the security team, right? To your point so the network can act at the same speed. But you also give tools to the network operations teams because they need to adjust then, they have the ability to react to some of these requirements, right? And it's not just automation, I said we focused on that, but there's also to your point, the need, how do I extend between data centers? You know, just for backup and recovery, and how do I extend into public clouds, right? And in the end that's a network connectivity problem, and we have solved as, we have meters available, we have integrations into AWS. We have integrations into Ajua to actually make this very easy from a network perspective to extend your private domains, private networks into which have private networks on these public clouds. So, from an app developer perspective, now it looks like it's on the same network. It's a protective enterprise network. Some of it might sit here, some of it might sit here. But it's really looking the same. And that's really in the end I said what a business looks at, right? They don't necessarily want to say, I need you to have something separate for this deployment or separate for that deployment. What they want is I need you to deploy something. I need to do this resilience. And the resilient way and an agile way gives me the tools. And so that's really where we focused and what we're driving, right? It's that combination of automation consistently, and then definite tools available that we support, but they're all open. They're all standard tools as the ones I mentioned, right? That everybody's using. So, you're not getting into this, "Oh, this is specific to Cisco, right? It's really democratization, I actually liked your term. >> Yeah, it's a great term and it's really interesting, especially with the APIs and the way everything is so tied together. That everyone kind of has to enable this because that's what the customer is demanding. And it is all about the applications and the workloads and where those things are moving, but they don't really want to manage that. They just want to, you know, deliver business benefit to their customers in respond to, you know, competitive threats in the marketplace, et cetera. So, it's really an interesting time for the infrastructure to really support kind of this app first point of view, versus the other way around is kind of what it used to be. And enable this hyper fast development, hyper fast change in the competitive landscape or else you will be left behind. So, super important stuff. >> Yeah, no, I totally agree. And as I said, I mean, it's kind of interesting because we started on the Cisco data center. It's where we started this probably six or seven years ago. When we named the application-centric, clearly a lot of these concepts evolved. But in a sense it is that reversal of the role from the network provides something and you use to, this is what I want to do. And I need a service thinking on the networking side to expose services that can be consumed. And so that clearly is playing out. And as I said, automation is a key foundation that we put in place. And our customers most of our customers at this point are on these products. They have all the capabilities there are. They can literally take advantage. There's really nothing that stops them at this point. >> Well, it's good times for you because I'm sure you've seen all the memes in social media, right? What's driving your digital transformation is the CEO, the CMO or COVID. And we all know the answer to the question. So, I don't think the pace of change is going to slow down anytime soon. So, (indistinct) keeping the network up and enabling us all to get done what we have to get done and all the little magic that happens behind the scenes. >> Yeah, I know, thanks for having me and again, yeah, if you're listening and you're wondering, how do I get started? Cisco definitely is the place to go. It's, you know, fantastic, fantastic environment. And I highly recommend everybody, roll up the sleeves and you know, the best reasons you can have. >> Yeah, and we know once the physical events come back, we've been to DevNet Create a bunch of times, and it's a super vibrant, super excited, really engaged community, sharing lots of information. It's still kind of that early vibe, you know, where everyone is still really enthusiastic and really about learning and sharing information. So, like Susie and the team have really built a great thing and we're happy to continue to cover it and eventually we'll be back face to face. >> Okay, (chuckles) look forward to that as well. >> All right, thanks. He's Thomas and I'm Jeff you're watching continuing coverage of CiscoDevNet Accelerating With Automation and Programmability. Thanks for watching, we'll see you next time. (upbeat music)

>>Hi, Maya. Mr England. And I am an associate professor of electrical engineering and computer science at M I T. It's been fantastic to be part of this team that Professor Yamamoto put together, uh, for the entity Fire program. It's a great pleasure to report to you are update from the first year I will talk to you today about our recent work in photonic accelerators for machine intelligence. You can already get a flavor of the kind of work that I'll be presenting from the photonic integrated circuit that services a platonic matrix processor that we are developing to try toe break some of the bottle next that we encounter in inference, machine learning tasks in particular tasks like vision, games control or language processing. This work is jointly led with Dr Ryan heavily, uh, scientists at NTT Research, and he will have a poster that you should check out. Uh, in this conference should also say that there are postdoc positions available. Um, just take a look at announcements on Q P lab at m i t dot eu. So if you look at these machine learning applications, look under the hood. You see that a common feature is that they used these artificial neural networks or a and ends where you have an input layer of, let's say, and neurons and values that is connected to the first layer of, let's Say, also and neurons and connecting the first to the second layer would, if you represented it biomatrix requiring and biomatrix that has of order and squared free parameters. >>Okay, now, in traditional machine learning inference, you would have to grab these n squared values from memory. And every time you do that, it costs quite a lot of energy. Maybe you can match, but it's still quite costly in energy, and moreover, each of the input values >>has to be multiplied by that matrix. And if you multiply an end by one vector by an end square matrix, you have to do a border and squared multiplication. Okay, now, on a digital computer, you therefore have to do a voter in secret operations and memory access, which could be quite costly. But the proposition is that on a photonic integrated circuits, perhaps we could do that matrix vector multiplication directly on the P. I C itself by encoding optical fields on sending them through a programmed program into parameter and the output them would be a product of the matrix multiplied by the input vector. And that is actually the experiment. We did, uh, demonstrating that That this is, you know, in principle, possible back in 2017 and a collaboration with Professor Marine Soldier Judge. Now, if we look a little bit more closely at the device is shown here, this consists of a silicon layer that is pattern into wave guides. We do this with foundry. This was fabricated with the opposite foundry, and many thanks to our collaborators who helped make that possible. And and this thing guides light, uh, on about of these wave guides to make these two by two transformations Maxine and the kilometers, as they called >>input to input wave guides coming in to input to output wave guides going out. And by having to phase settings here data and five, we can control any arbitrary, uh, s U two rotation. Now, if I wanna have any modes coming in and modes coming out that could be represented by an S u N unitary transformation, and that's what this kind of trip allows you to dio and That's the key ingredient that really launched us in in my group. I should at this point, acknowledge the people who have made this possible and in particular point out Leon Bernstein and Alex lots as well as, uh, Ryan heavily once more. Also, these other collaborators problems important immigrant soldier dish and, of course, to a funding in particular now three entity research funding. So why optics optics has failed many times before in building computers. But why is this different? And I think the difference is that we now you know, we're not trying to build an entirely new computer out of optics were selective in how we apply optics. We should use optics for what it's good at. And that's probably not so much from non linearity, unnecessarily I mean, not memory, um, communication and fan out great in optics. And as we just said, linear algebra, you can do in optics. Fantastic. Okay, so you should make use of these things and then combine it judiciously with electronic processing to see if you can get an advantage in the entire system out of it, okay. And eso before I move on. Actually, based on the 2017 paper, uh, to startups were created, like intelligence and like, matter and the two students from my group, Nick Harris. And they responded, uh, co started this this this jointly founded by matter. And just after, you know, after, like, about two years, they've been able to create their first, uh, device >>the first metrics. Large scale processor. This is this device has called Mars has 64 input mode. 64 Promodes and the full program ability under the hood. Okay. So because they're integrating wave guides directly with Seamus Electron ICS, they were able to get all the wiring complexity, dealt with all the feedback and so forth. And this device is now able to just process a 64 or 64 unitary majors on the sly. Okay, parameters are three wants total power consumption. Um, it has ah, late and see how long it takes for a matrix to be multiplied by a factor of less than a nanosecond. And because this device works well over a pretty large 20 gigahertz, you could put many channels that are individually at one big hurts, so you can have tens of S U two s u 65 or 64 rotations simultaneously that you could do the sort of back in the envelope. Physics gives you that per multiply accumulate. You have just tens of Tempted jewels. Attn. A moment. So that's very, very competitive. That's that's awesome. Okay, so you see, plan and potentially the breakthroughs that are enabled by photonics here And actually, more recently, they actually one thing that made it possible is very cool Eyes thes My face shifters actually have no hold power, whereas our face shifters studios double modulation. These use, uh, nano scale mechanical modulators that have no hold power. So once you program a unitary, you could just hold it there. No energy consumption added over >>time. So photonics really is on the rise in computing on demand. But once again, you have to be. You have to be careful in how you compare against a chance to find where is the game to be had. So what I've talked so far about is wait stationary photonic processing. Okay, up until here. Now what tronics has that also, but it doesn't have the benefits of the coherence of optical fields transitioning through this, uh, to this to this matrix nor the bandwidth. Okay, Eso So that's Ah, that is, I think a really exciting direction. And these companies are off and they're they're building these trips and we'll see the next couple of months how well this works. Uh, on the A different direction is to have an output stationary matrix vector multiplication. And for this I want to point to this paper we wrote with Ryan, Emily and the other team members that projects the activation functions together with the weight terms onto a detector array and by the interference of the activation function and the weight term by Hamad and >>Affection. It's possible if you think about Hamad and affection that it actually automatically produces the multiplication interference turn between two optical fields gives you the multiplication between them. And so that's what that is making use of. I wanna talk a little bit more about that approach. So we actually did a careful analysis in the P R X paper that was cited in the last >>page and that analysis of the energy consumption show that this device and principal, uh, can compute at at an energy poor multiply accumulate that is below what you could theoretically dio at room temperature using irreversible computer like like our digital computers that we use in everyday life. Um, so I want to illustrate that you can see that from this plot here, but this is showing. It's the number of neurons that you have per layer. And on the vertical axis is the energy per multiply accumulate in terms of jewels. And when we make use of the massive fan out together with this photo electric multiplication by career detection, we estimate that >>we're on this curve here. So the more right. So since our energy consumption scales us and whereas for a for a digital computer it skills and squared, we, um we gain mawr as you go to a larger matrices. So for largest matrices like matrices of >>scale 1,005,000, even with present day technology, we estimate that we would hit and energy per multiply accumulate of about a center draw. Okay, But if we look at if we imagine a photonic device that >>uses a photonic system that uses devices that have already been demonstrated individually but not packaged in large system, you know, individually in research papers, we would be on this curve here where you would very quickly dip underneath the lander, a limit which corresponds to the thermodynamic limit for doing as many bit operations that you would have to do to do the same depth of neural network as we do here. And I should say that all of these numbers were computed for this simulated >>optical neural network, um, for having the equivalent, our rate that a fully digital computer that a digital computer would have and eso equivalent in the error rate. So it's limited in the error by the model itself rather than the imperfections of the devices. Okay. And we benchmark that on the amnesty data set. So that was a theoretical work that looked at the scaling limits and show that there's great, great hope to to really gain tremendously in the energy per bit, but also in the overall latency and throughput. But you shouldn't celebrate too early. You have to really do a careful system level study comparing, uh, electronic approaches, which oftentimes happened analogous approach to the optical approaches. And we did that in the first major step in this digital optical neural network. Uh, study here, which was done together with the PNG who is an electron ICS designer who actually works on, uh, tronics based on c'mon specifically made for machine on an acceleration. And Professor Joel, member of M I t. Who is also a fellow at video And what we studied there in particular, is what if we just replaced on Lee the communication part with optics, Okay. And we looked at, you know, getting the same equivalent error rates that you would have with electronic computer. And that showed that that way should have a benefit for large neural networks, because large neural networks will require lots of communication that eventually do not fit on a single Elektronik trip anymore. At that point, you have to go longer distances, and that's where the optical connections start to win out. So for details, I would like to point to that system level study. But we're now applying more sophisticated studies like this, uh, like that simulate full system simulation to our other optical networks to really see where the benefits that we might have, where we can exploit thes now. Lastly, I want to just say What if we had known nominee Garrity's that >>were actually reversible. There were quantum coherent, in fact, and we looked at that. So supposed to have the same architectural layout. But rather than having like a sexual absorption absorption or photo detection and the electronic non linearity, which is what we've done so far, you have all optical non linearity, okay? Based, for example, on a curve medium. So suppose that we had, like, a strong enough current medium so that the output from one of these transformations can pass through it, get an intensity dependent face shift and then passes into the next layer. Okay, What we did in this case is we said okay. Suppose that you have this. You have multiple layers of these, Uh um accent of the parameter measures. Okay. These air, just like the ones that we had before. >>Um, and you want to train this to do something? So suppose that training is, for example, quantum optical state compression. Okay, you have an optical quantum optical state you'd like to see How much can I compress that to have the same quantum information in it? Okay. And we trained that to discover a efficient algorithm for that. We also trained it for reinforcement, learning for black box, quantum simulation and what? You know what is particularly interesting? Perhaps in new term for one way corner repeaters. So we said if we have a communication network that has these quantum optical neural networks stationed some distance away, you come in with an optical encoded pulse that encodes an optical cubit into many individual photons. How do I repair that multi foot on state to send them the corrected optical state out the other side? This is a one way error correcting scheme. We didn't know how to build it, but we put it as a challenge to the neural network. And we trained in, you know, in simulation we trained the neural network. How toe apply the >>weights in the Matrix transformations to perform that Andi answering actually a challenge in the field of optical quantum networks. So that gives us motivation to try to build these kinds of nonlinear narratives. And we've done a fair amount of work. Uh, in this you can see references five through seven. Here I've talked about thes programmable photonics already for the the benchmark analysis and some of the other related work. Please see Ryan's poster we have? Where? As I mentioned we where we have ongoing work in benchmarking >>optical computing assed part of the NTT program with our collaborators. Um And I think that's the main thing that I want to stay here, you know, at the end is that the exciting thing, really is that the physics tells us that there are many orders of magnitude of efficiency gains, uh, that are to be had, Uh, if we you know, if we can develop the technology to realize it. I was being conservative here with three orders of magnitude. This could be six >>orders of magnitude for larger neural networks that we may have to use and that we may want to use in the future. So the physics tells us there are there is, like, a tremendous amount of gap between where we are and where we could be and that, I think, makes this tremendously exciting >>and makes the NTT five projects so very timely. So with that, you know, thank you for your attention and I'll be happy. Thio talk about any of these topics

(upbeat music) >> Announcer: From New York, it's theCUBE. Covering ESCAPE/19. >> Everyone, welcome to theCUBE coverage here in New York City for the ESCAPE Conference 19. This is the inaugural event for multicloud, I think it's the first industry event for, really talking about multicloud and the impact to enterprises and public cloud. My next guest is Steve Mullaney, President and CEO of Aviatrix, storied career in tech, been there done that, seen many waves of innovation. Nicira, Palo Alto Networks, and now Aviatrix. You retired for a while, welcome back! >> I did, yeah, five years, yeah, yeah, yeah. >> Welcome to theCUBE. >> Thank you, thanks for having me. >> It's nice to have you on because I think you have a good perspective on the multicloud because you've been in the industry since the 80s. We've both been broke in at the same time. And we've seen the waves. >> Oh, yeah. >> This wave is bigger than, I think, most of the other waves combined because it brings together so many things, infrastructure, software, cloud scale, and a new modern application environment. And then you complicate everything by throwing IoT out there, edges being pushed to their boundaries, securities equations changed, all this is going on right now, all at the same time. >> No, and that's why I was basically retired for five years, and I was at Nicira, we got bought by VMware, I stayed there for a couple years, and I just said, "Okay, that's it!" I've had a good career and I'm done. And about a year ago, the world changed. And it felt like on a Tuesday morning, I noticed enterprises really, we'd been talking about cloud for 12 years. And five years ago they said, "We're coming in, we're going to do it," but they didn't really mean it. But about a year ago, all in the same day, every enterprise said, "No, now we actually mean it." And I don't know why, I don't know if it was just people retired or just five years of talking about it, they all decided, we're comin' in, and enterprises all moved together. And this wave, as you said, is bigger than, I was around in 1992, in the early 90s, in the movement from mainframe to client server. This is 10 times bigger than that. And more importantly, it's going to happen 10,000 times faster. Because (fingers tapping). What's that? I just deployed 62 data centers around the world. Because if I can leverage the greatest infrastructure built, basic infrastructure of the hyperscalers, AWS, Azure, Google, Alibaba, Oracle, you name it. It's unbelievable the velocity at which you can now start deploying. >> Steve, I think you're onto something big here, and this is why I'm here at this event and why I'm excited, that a lot of the industry thought leaders and practitioners and leaders are doing this event. Small events, inaugural, but I think it has a lot of links. Because there's a lot of tell signs that I like to look at, one is cloud. I've been covering Amazon eight years now, with theCUBE, I've known AWS since it started, and I've done many startups in its launch using AWS. But I've had many conversations with Andy Jassy, one on ones, privately, I got an exclusive coming up for re:Invent with him. I've gotten to know him. It started out, "Everyone's moving to the cloud. "Every data center's not going to exist." And then, you know-- >> Oh, maybe not, yeah, yeah. >> Maybe not, we'll do an output. So I challenged him last year, I said, "Andy, come on, dude, like you were saying like a year ago that." >> Steve: Yeah, it's all AWS or nothing. >> And he said, "John, look I'm not, "I just listen to the customers." And I interviewed him when he did the VMware deal. And he's very customer focused. And when they make these moves with outpost, and I think it's going to be a hybrid message this year at re:Invent, you know it's real. >> Steve: Oh, yeah. >> I think this validates your point, so I got to ask you, what specifically do you see the formula being for multicloud, because certainly everyone's recognized that there's a huge benefit for AWS. But from a scale standpoint, so why not use that? What's going on on the Enterprise on-premise that's making this new thing work? >> I think it all starts with architecture, like anything else. I think right now, enterprises have said, "Okay, we've burned a boat, right? "Now, we're not going to get rid of our data centers, "but in terms of our strategic investment, "we are moving into the cloud. "We are going to leverage "the infrastructure of the hyperscalers. "And whether that is just one hyperscaler, or multiple." And I have not met an enterprise who thinks there only going to be one, right, every single one of them. Now, I don't think they're moving workloads across, I don't think that. I think they see that, I'm going to use Google for AI, I'm going to use AWS because it started there. I'm going to use Azure, for Office 365, and other different things, and everything in infrastructure is always multi. It's never homogeneous, right, it's always that. So I think is going to happen, and I think what people are begging for right now, is, I want to build an architecture that gives me the optionality to be able to deliver a common set of services whether I'm on AWS or multiple clouds. And I want them to be my services and I don't want to have understand the low level abstractions and constructs of each of those clouds, because their all different. One's metric, one's U.S., one's some other weird thing. And I don't have the time, the people, or the resources to be able to do that. Give me a common set of services, that are my services, that I can deploy and abstract away the details of those public clouds. >> Yeah, it's an interesting point there, in fact, I called BS on multicloud last year when it started to kind of rear it's head, I'm like, "Come on, multicloud is bullshit." And I said that on theCUBE. And here's what I meant. Multicloud as an operating model is directionally correct, but the architecture hasn't shown where there's true multicloud. Now, the fact of the matter is, people have Amazon, people have Office and Office 365, that's technically two clouds, >> They're siloed, yeah. >> If they give us Google, that's three clouds. >> I use two or three clouds. >> So, if he have three clouds, I guess they have multiple clouds. But you bring up an interesting point, and going back as a student of the history of tech industry, multi-vendor has been a big deal. >> It is a big deal. >> And like you said, there will be a multi-vendor world, that will happen. The question is how. How do you guys see it happening? >> Well I think what's-- >> Your company is attacking this Aviatrix. >> What's interesting is, so now you think about from a customer perspective which, I do the same thing, same thing with AWS. It's always outside in. Okay, I'm thinking as a enterprise IT person. I'm making the move. Do you believe that your basic infrastructure will lever the hyperscalers, or will you build an on-prem? Everyone says, "I believe that's the way I'm going to go." Great, how do I do that? So, I'm a IT architect, who do I go to to help me? Do I go to CISCO? No. The most shocking thing for me, of the six months I've been at Aviatrix, is that word's never used. It's like it was DEC or IBM in the conversation, when you were talking about client-server, no, why would you? CISCO, Juniper, Arista, any of the networking people, not even in the conversation. VMware, not really in the conversation. So, I don't have any incumbent vendor that I can go to that I used to go to. >> Why aren't they in the conversation? 'Cause of the commodity, they've been extracted away? >> I think it's just because it's the innovation of dilemma. Right, once you're selling a lot of stuff into on-prem, to then go and say, I mean you look at Palo Alto Networks, they're trying to make that transition. Acquiring a bunch of companies, VMware acquiring a bunch of companies. Why are they doing that? Because they know, I got to get off on-prem, everything's going in the cloud. >> So it's a legacy. >> It's a legacy thing, and I think what happens is, there is only one reason, and one reason only, an enterprise customer is not using Aviatrix. 'Cause they never heard of us. That's why, that's the only reason. Once they hear about what they're doing, my God. >> Well, give the plug, talk about the company, what do you guys do-- >> So we deliver, I mean it sounds like I made it up for this conference, but actually this conference was perfect for this. It's networking and security services for the multicloud enterprise. And we're building an architecture, that people can deploy, that will give them this common architecture across all the different clouds. So whether you're just using one cloud or multiple, it doesn't matter, it's the same set of security and networking services. And we do that by embracing and extending the basic constructs that AWS, Google, Azure, and Oracle, and all the other clouds will give you, and to deliver that real enterprise class. Because the other thing we've found is, everyone thinks that the cloud gives you everything and anything you will ever need from networking and security. Let's say AWS, they're going to do everything I need. What the enterprises are figuring out, is once they start going in, what they realize is, it's created for the low-level common basic constructs. And the enterprise starts at, well, I need these BGP feature because guess what, the data center is not going away. And I need more than a hundred route limitations, and I need, all of a sudden there's fifty different limitations AWS will give me. Well, they didn't talk about that! Well, of course they're not going to talk about that. They are just going to go check, check, check, we solve all your problems. As enterprises now move in, with mission critical applications, they're realizing, I need the same level of networking and security services that I had on-prem. I can't get that with the native constructs. So where do I go? That's what we do, so we fill in, we embrace what we can of those constructs, we fill in holes where there are fill in holes. And then we give you the mechanism to be able to orchestrate that across the global network. >> So you operationalize the hyperscale clouds for enterprise, >> Yes. >> that's basically what you do. >> Steve: Exactly, for the enterprise. >> Yeah, exactly. >> On the level that they need. >> So you get the benefits of the cloud, but all those nuances under the cover details like networking and other features you abstract that away and provide an operating model for enterprise compliments. >> And the beautiful thing about it is the velocity, at which we can, we're over the top, effectively over the top. We're integrated into the Cloud Suite, understand what cloud native, we understand all the constructs of accounts, and all the things we need to do. But what we expose to the customer, to the enterprise, is a set of over-the-top services that just work. >> Okay Steve, so I got to ask you, since we are at The Multi-Cloud Conference. What is multicloud, I mean how do you define it, you laid out a pretty compelling architecture of what needs are, levers in the cloud, and on-prem is what Aviatrix does. But what is the definition, how should people understand what is multicloud? >> I think for us, for networking and security in that base, so we're basic infrastructure. We get out there first, right? So, if you're going to build a city, you don't start putting people there first the first thing, if you do it right, is you get sewers, you get electricity, gas, roads, all that. Networking and security, infrastructure, is basic infrastructure goes out first. And you want to create an architecture that's going to live with you for twenty years. You don't want to have to rip up the roads and put the sewers in later. And that architecture needs to be multicloud because, even though you think maybe, most of our customers are 90% AWS right now. But every single one of them say, "But I'm moving to Azure, I'm moving to Google, "I've got retail customers that won't allow me "to put my infrastructure on AWS." Or, "I have machine learning, AI type apps on Google." They all say that same thing. But what they all then say to us, is, "You're going to be the mechanism "upon which I'm going to be able to deploy "this common set of services." So they don't need to know that. >> All right, give an example of a customer you guys have, name a name, we had a customer on stage here-- >> Steve: So, Jefferies. >> John: They did this for a use case. >> Yeah so, Jefferies. Financial Services Institution, lots of requirements, Mark Leon Soon is going to be on stage with me tomorrow. We started working with them about nine months ago. Exactly the same thing, they said, "Okay, you know what? "We need to start moving to the cloud, "we've got to start leveraging the cloud. "But, it's too complicated, right? "Even AWS, says 'Go Build.' "I don't want to go build, I want to consume services. "But they don't have all the service that I needed, "they're too low a level. "They're very high function, high enterprise requirements." So they start using us to orchestrate things, to provide transit networking, to provide egress filtering out to the Internet, we have high performance encryption, AWS will only offer it one gig. We can offer it to 10, 20, 30, 40 gig. So they start deploying, they start realizing all the things we do. Then they go and say, "I want to bring my Palo Alto Networks firewall "into the cloud." When you start looking at that, 'cause then guess what? All my policies, I want the same level that I have on-prem when I'm in the cloud. If I go try to bring in my VM series into AWS the construct that AWS give you, they cause you limitations in performance, in visibility, It's integration hassles, there's performance, sustainability, visibility issues, they force you to use SNAT. And there's all these issues, and they go, "Oh my God, this is a pain in the ass." We solved all that for them. We basically cloudify the VM series for them, so all those limitations go away. So that's just another use case that they use. Now they start looking, and they say, "Okay, now I'm going to start extending into other clouds and I want to use you as the common frame point, the common pane of glass. >> Well Steve, good luck in your venture, you're back in the saddle again. >> Steve: Yeah. >> Another ride here, you feel good about it? >> This is going to be the best, the biggest that I've been, and I was at Palo Alto Networks and VMware Nicira. And this one's going to be bigger than both of those. >> What's your vision for where this is going to be for you, where do you see the company in a few years, what are some of the outcomes you expect to happen? >> Our opportunity, and I look at it as, someone's going to take this opportunity, and the reason I came back is, why not us, someone's going to take it. And the opportunity, honestly, is to become, effectively, what Cisco was in the early 90's. To define the architecture, the networking and the security infrastructure architecture for enterprise customers. They are begging for that right now, that's our opportunity. >> Cloud Interoperability. >> Interoperability, yeah. And so there's so many things that we need to go and do. When you look at also the thing that people are going to say, the operations. So many people think, I want it the same as it was on-prem. I think with the cloud, and across multicloud you can do it right with us, and actually better. Because the visibility that you get is more, than what you get on-prem. >> Well, and the thing that's interesting that's different about this new world that we're talking about is that there is going to be constant improvements in new things which means that the functionality game is going to increase, which means the agility is even more important because the apps are going to have more things to do. >> Yeah. I mean in the end, why do you want to go to cloud? I want to go to cloud 'cause I want it to be self-service and I want agility. I want my developers, I want everybody to be able to do things quicker because all of the sudden they say, "Let's go roll this out", and you want to be able to do it. >> Well, good luck on the new venture, Aviatrix, check 'em out, hot multicloud startup, growing, how many people do you have, put the plug in, >> 100. >> what are you guys looking for, are you hiring, give me a quick plug. >> We just hired a new VP at World Wide Sales, James Winebrenner, who was Viptela CEO, VP Sales in Cisco, hiring a tremendous amount of sales guys right now, we're closing on a $40 million Series C round next week, and we're hiring a lot of people. >> Good luck, we'll be following you Steve, thanks for coming on and sharing your insights. Again, multicloud, this is a shift that's happening, multicloud is just another word for multi-vendor, in a new modern era, this is what it has been in the technology industry, but a whole new world. This is theCUBE coverage here in New York City, ESCAPE/19, I'm John Furrier, thanks for watching. (upbeat music)

(upbeat music) >> Announcer: From New York, it's theCUBE. Covering ESCAPE/19. >> Everyone, welcome to theCUBE coverage here in New York City for the ESCAPE Conference 19. This is the inaugural event for multicloud, I think it's the first industry event for, really talking about multicloud and the impact to enterprises and public cloud. My next guest is Steve Mullaney, President and CEO of Aviatrix, storied career in tech, been there done that, seen many waves of innovation. Nicira, Palo Alto Networks, and now Aviatrix. You retired for a while, welcome back! >> I did, yeah, five years, yeah, yeah, yeah. >> Welcome to theCUBE. >> Thank you, thanks for having me. >> It's nice to have you on because I think you have a good perspective on the multicloud because you've been in the industry since the 80s. We've both been broke in at the same time. And we've seen the waves. >> Oh, yeah. >> This wave is bigger than, I think, most of the other waves combined because it brings together so many things, infrastructure, software, cloud scale, and a new modern application environment. And then you complicate everything by throwing IoT out there, edges being pushed to their boundaries, securities equations changed, all this is going on right now, all at the same time. >> No, and that's why I was basically retired for five years, and I was at Nicira, we got bought by VMware, I stayed there for a couple years, and I just said, "Okay, that's it!" I've had a good career and I'm done. And about a year ago, the world changed. And it felt like on a Tuesday morning, I noticed enterprises really, we'd been talking about cloud for 12 years. And five years ago they said, "We're coming in, we're going to do it," but they didn't really mean it. But about a year ago, all in the same day, every enterprise said, "No, now we actually mean it." And I don't know why, I don't know if it was just people retired or just five years of talking about it, they all decided, we're comin' in, and enterprises all moved together. And this wave, as you said, is bigger than, I was around in 1992, in the early 90s, in the movement from mainframe to client server. This is 10 times bigger than that. And more importantly, it's going to happen 10,000 times faster. Because (fingers tapping). What's that? I just deployed 62 data centers around the world. Because if I can leverage the greatest infrastructure built, basic infrastructure of the hyperscalers, AWS, Azure, Google, Alibaba, Oracle, you name it. It's unbelievable the velocity at which you can now start deploying. >> Steve, I think you're onto something big here, and this is why I'm here at this event and why I'm excited, that a lot of the industry thought leaders and practitioners and leaders are doing this event. Small events, inaugural, but I think it has a lot of links. Because there's a lot of tell signs that I like to look at, one is cloud. I've been covering Amazon eight years now, with theCUBE, I've known AWS since it started, and I've done many startups in its launch using AWS. But I've had many conversations with Andy Jassy, one on ones, privately, I got an exclusive coming up for re:Invent with him. I've gotten to know him. It started out, "Everyone's moving to the cloud. "Every data center's not going to exist." And then, you know-- >> Oh, maybe not, yeah, yeah. >> Maybe not, we'll do an output. So I challenged him last year, I said, "Andy, come on, dude, like you were saying like a year ago that." >> Steve: Yeah, it's all AWS or nothing. >> And he said, "John, look I'm not, "I just listen to the customers." And I interviewed him when he did the VMware deal. And he's very customer focused. And when they make these moves with outpost, and I think it's going to be a hybrid message this year at re:Invent, you know it's real. >> Steve: Oh, yeah. >> I think this validates your point, so I got to ask you, what specifically do you see the formula being for multicloud, because certainly everyone's recognized that there's a huge benefit for AWS. But from a scale standpoint, so why not use that? What's going on on the Enterprise on-premise that's making this new thing work? >> I think it all starts with architecture, like anything else. I think right now, enterprises have said, "Okay, we've burned a boat, right? "Now, we're not going to get rid of our data centers, "but in terms of our strategic investment, "we are moving into the cloud. "We are going to leverage "the infrastructure of the hyperscalers. "And whether that is just one hyperscaler, or multiple." And I have not met an enterprise who thinks there only going to be one, right, every single one of them. Now, I don't think they're moving workloads across, I don't think that. I think they see that, I'm going to use Google for AI, I'm going to use AWS because it started there. I'm going to use Azure, for Office 365, and other different things, and everything in infrastructure is always multi. It's never homogeneous, right, it's always that. So I think is going to happen, and I think what people are begging for right now, is, I want to build an architecture that gives me the optionality to be able to deliver a common set of services whether I'm on AWS or multiple clouds. And I want them to be my services and I don't want to have understand the low level abstractions and constructs of each of those clouds, because their all different. One's metric, one's U.S., one's some other weird thing. And I don't have the time, the people, or the resources to be able to do that. Give me a common set of services, that are my services, that I can deploy and abstract away the details of those public clouds. >> Yeah, it's an interesting point there, in fact, I called BS on multicloud last year when it started to kind of rear it's head, I'm like, "Come on, multicloud is bullshit." And I said that on theCUBE. And here's what I meant. Multicloud as an operating model is directionally correct, but the architecture hasn't shown where there's true multicloud. Now, the fact of the matter is, people have Amazon, people have Office and Office 365, that's technically two clouds, >> They're siloed, yeah. >> If they give us Google, that's three clouds. >> I use two or three clouds. >> So, if he have three clouds, I guess they have multiple clouds. But you bring up an interesting point, and going back as a student of the history of tech industry, multi-vendor has been a big deal. >> It is a big deal. >> And like you said, there will be a multi-vendor world, that will happen. The question is how. How do you guys see it happening? >> Well I think what's-- >> Your company is attacking this Aviatrix. >> What's interesting is, so now you think about from a customer perspective which, I do the same thing, same thing with AWS. It's always outside in. Okay, I'm thinking as a enterprise IT person. I'm making the move. Do you believe that your basic infrastructure will lever the hyperscalers, or will you build an on-prem? Everyone says, "I believe that's the way I'm going to go." Great, how do I do that? So, I'm a IT architect, who do I go to to help me? Do I go to CISCO? No. The most shocking thing for me, of the six months I've been at Aviatrix, is that word's never used. It's like it was DEC or IBM in the conversation, when you were talking about client-server, no, why would you? CISCO, Juniper, Arista, any of the networking people, not even in the conversation. VMware, not really in the conversation. So, I don't have any incumbent vendor that I can go to that I used to go to. >> Why aren't they in the conversation? 'Cause of the commodity, they've been extracted away? >> I think it's just because it's the innovation of dilemma. Right, once you're selling a lot of stuff into on-prem, to then go and say, I mean you look at Palo Alto Networks, they're trying to make that transition. Acquiring a bunch of companies, VMware acquiring a bunch of companies. Why are they doing that? Because they know, I got to get off on-prem, everything's going in the cloud. >> So it's a legacy. >> It's a legacy thing, and I think what happens is, there is only one reason, and one reason only, an enterprise customer is not using Aviatrix. 'Cause they never heard of us. That's why, that's the only reason. Once they hear about what they're doing, my God. >> Well, give the plug, talk about the company, what do you guys do-- >> So we deliver, I mean it sounds like I made it up for this conference, but actually this conference was perfect for this. It's networking and security services for the multicloud enterprise. And we're building an architecture, that people can deploy, that will give them this common architecture across all the different clouds. So whether you're just using one cloud or multiple, it doesn't matter, it's the same set of security and networking services. And we do that by embracing and extending the basic constructs that AWS, Google, Azure, and Oracle, and all the other clouds will give you, and to deliver that real enterprise class. Because the other thing we've found is, everyone thinks that the cloud gives you everything and anything you will ever need from networking and security. Let's say AWS, they're going to do everything I need. What the enterprises are figuring out, is once they stop going in, what they realize is, it's created for the low-level common basic constructs. And the enterprise starts at, well, I need these BGP feature because guess what, the data center is not going away. And I need more than a hundred route limitations, and I need, all of a sudden there's fifty different limitations AWS will give me. Well, they didn't talk about that! Well, of course they're not going to talk about that. They are just going to go check, check, check, we solve all your problems. As enterprises now move in, with mission critical applications, they're realizing, I need the same level of networking and security services that I had on-prem. I can't get that with the native constructs. So where do I go? That's what we do, so we fill in, we embrace what we can of those constructs, we fill in holes where there are fill in holes. And then we give you the mechanism to be able to orchestrate that across the global network. >> So you operationalize the hyperscale clouds for enterprise, >> Yes. >> that's basically what you do. >> Steve: Exactly, for the enterprise. >> Yeah, exactly. >> On the level that they need. >> So you get the benefits of the cloud, but all those nuances under the cover details like networking and other features you abstract that away and provide an operating model for enterprise compliments. >> And the beautiful thing about it is the velocity, at which we can, we're over the top, effectively over the top. We're integrated into the Cloud Suite, understand what cloud native, we understand all the constructs of accounts, and all the things we need to do. But what we expose to the customer, to the enterprise, is a set of over-the-top services that just work. >> Okay Steve, so I got to ask you, since we are at The Multi-Cloud Conference. What is multicloud, I mean how do you define it, you laid out a pretty compelling architecture of what needs are, levers in the cloud, and on-prem is what Aviatrix does. But what is the definition, how should people understand what is multicloud? >> I think for us, for networking and security in that base, so we're basic infrastructure. We get out there first, right? So, if you're going to build a city, you don't start putting people there first the first thing, if you do it right, is you get sewers, you get electricity, gas, roads, all that. Networking and security, infrastructure, is basic infrastructure goes out first. And you want to create an architecture that's going to live with you for twenty years. You don't want to have to rip up the roads and put the sewers in later. And that architecture needs to be multicloud because, even though you think maybe, most of our customers are 90% AWS right now. But every single one of them say, "But I'm moving to Azure, I'm moving to Google, "I've got retail customers that won't allow me "to put my infrastructure on AWS." Or, "I have machine learning, AI type apps on Google." They all say that same thing. But what they all then say to us, is, "You're going to be the mechanism "upon which I'm going to be able to deploy "this common set of services." So they don't need to know that. >> All right, give an example of a customer you guys have, name a name, we had a customer on stage here-- >> Steve: So, Jefferies. >> John: They did this for a use case. >> Yeah so, Jefferies. Financial Services Institution, lots of requirements, Mark Leon Soon is going to be on stage with me tomorrow. We started working with them about nine months ago. Exactly the same thing, they said, "Okay, you know what? "We need to start moving to the cloud, "we've got to start leveraging the cloud. "But, it's too complicated, right? "Even AWS, says 'Go Build.' "I don't want to go build, I want to consume services. "But they don't have all the service that I needed, "they're too low a level. "They're very high function, high enterprise requirements." So they start using us to orchestrate things, to provide transit networking, to provide egress filtering out to the Internet, we have high performance encryption, AWS will only offer it one gig. We can offer it to 10, 20, 30, 40 gig. So they start deploying, they start realizing all the things we do. Then they go and say, "I want to bring my Palo Alto Networks firewall "into the cloud." When you start looking at that, 'cause then guess what? All my policies, I want the same level that I have on-prem when I'm in the cloud. If I go try to bring in my VM series into AWS the construct that AWS give you, they cause you limitations in performance, in visibility, It's integration hassles, there's performance, sustainability, visibility issues, they force you to use SNAT. And there's all these issues, and they go, "Oh my God, this is a pain in the ass." We solved all that for them. We basically cloudify the VM series for them, so all those limitations go away. So that's just another use case that they use. Now they start looking, and they say, "Okay, now I'm going to start extending into other clouds and I want to use you as the common frame point, the common pane of glass. >> Well Steve, good luck in your venture, you're back in the saddle again. >> Steve: Yeah. >> Another ride here, you feel good about it? >> This is going to be the best, the biggest that I've been, and I was at Palo Alto Networks and VMware Nicira. And this one's going to be bigger than both of those. >> What's your vision for where this is going to be for you, where do you see the company in a few years, what are some of the outcomes you expect to happen? >> Our opportunity, and I look at it as, someone's going to take this opportunity, and the reason I came back is, why not us, someone's going to take it. And the opportunity, honestly, is to become, effectively, what Cisco was in the early 90's. To define the architecture, the networking and the security infrastructure architecture for enterprise customers. They are begging for that right now, that's our opportunity. >> Cloud Interoperability. >> Interoperability, yeah. And so there's so many things that we need to go and do. When you look at also the thing that people are going to say, the operations. So many people think, I want it the same as it was on-prem. I think with the cloud, and across multicloud you can do it right with us, and actually better. Because the visibility that you get is more, than what you get on-prem. >> Well, and the thing that's interesting that's different about this new world that we're talking about is that there is going to be constant improvements in new things which means that the functionality game is going to increase, which means the agility is even more important because the apps are going to have more things to do. >> Yeah. I mean in the end, why do you want to go to cloud? I want to go to cloud 'cause I want it to be self-service and I want agility. I want my developers, I want everybody to be able to do things quicker because all of the sudden they say, "Let's go roll this out", and you want to be able to do it. >> Well, good luck on the new venture, Aviatrix, check 'em out, hot multicloud startup, growing, how many people do you have, put the plug in, >> 100. >> what are you guys looking for, are you hiring, give me a quick plug. >> We just hired a new VP at World Wide Sales, James Winebrenner, who was Viptela CEO, VP Sales in Cisco, hiring a tremendous amount of sales guys right now, we're closing on a $40 million Series C round next week, and we're hiring a lot of people. >> Good luck, we'll be following you Steve, thanks for coming on and sharing your insights. Again, multicloud, this is a shift that's happening, multicloud is just another word for multi-vendor, in a new modern era, this is what it has been in the technology industry, but a whole new world. This is theCUBE coverage here in New York City, ESCAPE/19, I'm John Furrier, thanks for watching. (upbeat music)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody welcome to this special cube in size powered by ET our enterprise Technology Research our partner who's got this database to solve the spending data and what we're gonna do is a braking analysis on the analytic database market we're seeing that cloud and cloud players are disrupting that marketplace and that marketplace really traditionally has been known as the enterprise data warehouse market so Alex if you wouldn't mind bringing up the first slide I want to talk about some of the trends in the traditional EDW market I almost don't like to use that term anymore because it's sort of a pejorative but let's look at it's a very large market it's about twenty billion dollars today growing it you know high single digits low double digits it's expected to be in the 30 to 35 billion dollar size by mid next decade now historically this is dominated by teradata who started this market really back in the 1980s with the first appliance the first converged appliance or coal with Exadata you know IBM I'll talk about IBM a little bit they bought a company called mateesah back in the day and they've basically this month just basically killed the t's and killed the brand Microsoft has entered the fray and so it's it's been a fairly large market but I say it's failed to really live up to the promises that we heard about in the late 90s early parts of the 2000 namely that you were going to be able to get a 360 degree view of your data and you're gonna have this flexible easy access to the data you know the reality is data warehouses were really expensive they were slow you had to go through a few experts to to get data it took a long time I'll tell you I've done a lot of research on this space and when you talked to the the data warehouse practitioners they would tell you we always had to chase the chips anytime Intel would come out with a new chip we forced it in there because we just didn't have the performance to really run the analytics as we need to it's took so long one practitioner described it as a snake swallowing a basketball so you've got all those data which is the sort of metaphor for the basketball just really practitioners had a hard time standing up infrastructure and what happened as a spate of new players came into the marketplace these these MPP players trying to disrupt the market you had Vertica who was eventually purchased by HP and then they sold them to Micro Focus greenplum was buy bought by EMC and really you know company is de-emphasized greenplum Netezza 1.7 billion dollar acquisition by IBM IBM just this month month killed the brand they're kind of you know refactoring everything par Excel was interesting was it was a company based on an open-source platform that Amazon AWS did a one-time license with and created a redshift it ever actually put a lot of innovation redshift this is really doing well well show you some data on that we've also at the time saw a major shift toward unstructured data and read much much greater emphasis on analytics it coincided with Hadoop which also disrupted the market economics I often joked it the ROI of a dupe was reduction on investment and so you saw all these data lakes being built and of course they turned into the data swamps and you had dozens of companies come into the database space which used to be rather boring but Mike Amazon with dynamodb s AP with HANA data stacks Redis Mongo you know snowflake is another one that I'm going to talk about in detail today so you're starting to see the blurring of lines between relational and non relational and what was was what once thought of is no sequel became not only sequel sequel became the killer app for Hadoop and so at any rate you saw this new class of data stores emerging and snowflake was one of the more interesting and and I want to share some of that data with you some of the spending intentions so over the last several weeks and months we've shared spending intentions from ETR enterprise technology research they're a company that that the manages of the spending data and has a panel of about 4,500 end-users they go out and do spending in tension surveys periodically so Alex if you bring up this survey data I want to show you this so this is spending intentions and and what it shows is that the public cloud vendors in snowflake who really is a database as a service offering so cloud like are really leading the pack here so the sector that I'm showing is the enterprise data warehouse and I've added in the the analytics business intelligence and Big Data section so what this chart shows is the vendor on the left-hand side and then this bar chart has colors the the red is we're leaving the platform the gray is our spending will be flat so this is from the July survey expect to expectations for the second half of 2019 so gray is flat the the dark green is increase and the lime green is we are a new customer coming on to the platform so if you take the the greens and subtract out the red and there's two Reds the dark red is leaving the lighter red is spending less so if you subtract the Reds from the greens you get what's called a net score so the higher the net score the better so you can see here the net score of snowflake is 81% so that very very high you can also see AWS in Microsoft a very high and Google so the cloud vendors of which I would consider a snowflake at cloud vendor like at the cloud model all kicking butt now look at Oracle look at the the incumbents Oracle IBM and Tara data Oracle and IBM are in the single digits for a net score and the Terra data is in a negative 10% so that's obviously not a good sign for those guys so you're seeing share gains from the cloud company snowflake AWS Microsoft and Google at the expense of certainly of teradata but likely IBM and Oracle Oracle's little for animal they got Exadata and they're putting a lot of investments in there maybe talk about that a little bit more now you see on the right hand side this black says shared accounts so the N in this survey this July survey that ETR did is a thousand sixty eight so of a thousand sixty eight customers each er is asking them okay what's your spending going to be on enterprise data warehouse and analytics big data platforms and you can see the number of accounts out of that thousand sixty eight that are being cited so snowflake only had 52 and I'll show you some other data from from past surveys AWS 319 Microsoft the big you know whale here trillion dollar valuation 851 going down the line you see Oracle a number you know very large number and in Tara data and IBM pretty large as well certainly enough to get statistically valid results so takeaway here is snowflake you know very very strong and the other cloud vendors the hyper scale is AWS Microsoft and Google and their data stores doing very well in the marketplace and challenging the incumbents now the next slide that I want to show you is a time series for selected suppliers that can only show five on this chart but it's the spending intentions again in that EDW and analytics bi big data segment and it shows the spending intentions from January 17 survey all the way through July 19 so you can see the the period the periods that ETR takes this the snapshots and again the latest July survey is over a thousand n the other ones are very very large too so you can see here at the very top snowflake is that yellow line and they just showed up in the January 19 a survey and so you're seeing now actually you go back one yeah January 19 survey and then you see them in July you see the net score is the July next net score that I'm showing that's 35 that's the number of accounts out of the corpus of data that snowflake had in the survey back in January and now it's up to 52 you can see they lead the packet just in terms of the spending intention in terms of mentions AWS and Microsoft also up there very strong you see big gap down to Oracle and Terra data I didn't show I BM didn't show Google Google actually would be quite high to just around where Microsoft is but you can see the pressure that the cloud is placing on the incumbents so what are the incumbents going to do about it well certainly you're gonna see you know in the case of Oracle spending a lot of money trying to maybe rethink the the architecture refactor the architecture Oracle open worlds coming up shortly I'm sure you're gonna see a lot of new announcements around Exadata they're putting a lot of wood behind the the exadata arrow so you know we'll keep in touch with that and stay tuned but you can see again the big takeaways here is that cloud guys are really disrupting the traditional edw marketplace alright let's talk a little bit about snowflakes so I'm gonna highlight those guys and maybe give a little bit of inside baseball here but what you need to know about snowflakes so I've put some some points here just some quick points on the slide Alex if you want to bring that up very fast-growing cloud and SAS based data warehousing player growing that couple hundred percent annually their annual recurring revenue very high these guys are getting ready to do an IPO talk about that a little bit they were founded in 2012 and it kind of came out of stealth and hiding in 2014 after bringing Bob Moog Leon from Microsoft as the CEO it was really the background on these guys is they're three engineers from Oracle will probably bored out of their mind like you know what we got this great idea why should we give it to Oracle let's go pop out and start a company and that NIN's and as such they started a snowflake they really are disrupting the incumbents they've raised over 900 million dollars in venture and they've got almost a four billion dollar valuation last May they brought on Frank salute Minh and this is really a pivot point I think for the company and they're getting ready to do an IPO so and so let's talk a little bit about that in a moment but before we do that I want to bring up just this really simple picture of Alex if you if you'd bring this this slide up this block diagram it's like a kindergarten so that you know people like you know I can even understand it but basically the innovation around the snowflake architecture was that they they separated their claim is that they separated the storage from the compute and they've got this other layer called cloud services so let me talk about that for a minute snowflake fundamentally rethought the architecture of the data warehouse to really try to take advantage of the cloud so traditionally enterprise data warehouses are static you've got infrastructure that kind of dictates what you can do with the data warehouse and you got to predict you know your peak needs and you bring in a bunch of storage and compute and you say okay here's the infrastructure and this is what I got it's static if your workload grows or some new compliance regulation comes out or some new data set has to be analyzed well this is what you got you you got your infrastructure and yeah you can add to it in chunks of compute and storage together or you can forklift out and put in new infrastructure or you can chase more chips as I said it's that snake swallowing a basketball was not pretty so very static situation and you have to over provision whereas the cloud is all about you know pay buy the drink and it's about elasticity and on demand resources you got cheap storage and cheap compute and you can just pay for it as you use it so the innovation from snowflake was to separate the compute from storage so that you could independently scale those and decoupling those in a way that allowed you to sort of tune the knobs oh I need more compute dial it up I need more storage dial it up or dial it down and pay for only what you need now another nuance here is traditionally the computing and data warehousing happens on one cluster so you got contention for the resources of that cluster what snowflake does is you can spin up a warehouse on the fly you can size it up you can size it down based on the needs of the workload so that workload is what dictates the infrastructure also in snowflakes architecture you can access the same data from many many different houses so you got again that three layers that I'm showing you the storage the compute and the cloud services so let me go through some examples so you can really better understand this so you've got storage data you got customer data you got you know order data you got log files you might have parts data you know what's an inventory kind of thing and you want to build warehouses based on that data you might have marketing a warehouse you might have a sales warehouse you might have a finance warehouse maybe there's a supply chain warehouse so again by separating the compute from that sort of virtualized compute from the from the storage layer you can access any data leave the data where it is and I'll talk about this in more and bring the compute to the data so this is what in part the cloud layer does they've got security and governance they got data warehouse management in that cloud layer and and resource optimization but the key in in my opinion is this metadata management I think that's part of snowflakes secret sauce is the ability to leave data where it is and have the smarts and the algorithms to really efficiently bring the compute to the data so that you're not moving data around if you think about how traditional data warehouses work you put all the data into a central location so you can you know operate on it well that data movement takes a long long time it's very very complicated so that's part of the secret sauce is knowing what data lives where and efficiently bringing that compute to the data this dramatically improves performance it's a game changer and it's much much less expensive now when I come back to Frank's Luqman this is somebody that I've is a career that I've followed I've known had him on the cube of a number of times I first met Frank Sloot when he was at data domain he took that company took it public and then sold it originally NetApp made a bid for the company EMC Joe Tucci in the defensive play said no we're not gonna let Ned afgan it there was a little auction he ended up selling the company for I think two and a half billion dollars sloop and came in he helped clean up the the data protection business of EMC and then left did a stint as a VC and then took over service now when snoop and took over ServiceNow and a lot of people know this the ServiceNow is the the shiny toy on Wall Street today service that was a mess when saluteth took it over it's about 100 120 million dollar company he and his team took it to 1.2 billion dramatically increased the the valuation and one of the ways they did that was by thinking about the Tam and expanding that Tim that's part of a CEOs job as Tam expansion Steuben is also a great operational guy and he brought in an amazing team to do that I'll talk a little bit about that team effect uh well he just brought in Mike Scarpelli he was the CFO was the CFO of ServiceNow brought him in to run finance for snowflake so you've seen that playbook emerge you know be interesting Beth white was the CMO at data domain she was the CMO at ServiceNow helped take that company she's an amazing resource she kind of you know and in retirement she's young but she's kind of in retirement doing some advisory roles wonder if slooping will bring her back I wonder if Dan Magee who was ServiceNow is operational you know guru wonder if he'll come out of retirement how about Dave Schneider who runs the sales team at at ServiceNow well he you know be be lord over we'll see the kinds of things that Sluman looks for just in my view of observing his playbook over the years he looks for great product he looks for a big market he looks for disruption and he looks for off-the-chart ROI so his sales teams can go in and really make a strong business case to disrupt the existing legacy players so I one of the things I said that snoopin looks for is a large market so let's look at this market and this is the thing that people missed around ServiceNow and to credit Pat myself and David for in the back you know we saw the Tam potential of ServiceNow is to be many many tens of billions you know Gartner when they when ServiceNow first came out said hey helpdesk it's a small market couple billion dollars we saw the potential to transform not only IT operations but go beyond helpdesk change management at cetera IT Service Management into lines of business and we wrote a piece on wiki Vaughn back then it's showing the potential Tam and we think something similar could happen here so the market today let's call 20 billion growing to 30 Billy big first of all but a lot of players in here what if so one of the things that we see snowflake potentially being able to do with its architecture and its vision is able to bring enterprise search you know to the marketplace 80% of the data that's out there today sits behind firewalls it's not searchable by Google what if you could unlock that data and access it in query at anytime anywhere put the power in the hands of the line of business users to do that maybe think Google search for enterprises but with provenance and security and governance and compliance and the ability to run analytics for a line of business users it's think of it as citizens data analytics we think that tam could be 70 plus billion dollars so just think about that in terms of how this company might this company snowflake might go to market you by the time they do their IPO you know it could be they could be you know three four five hundred billion dollar company so we'll see we'll keep an eye on that now because the markets so big this is not like the ITSM the the market that ServiceNow was going after they crushed BMC HP was there but really not paying attention to it IBM had a product it had all these products that were old legacy products they weren't designed for the cloud and so you know ServiceNow was able to really crush that market and caught everybody by surprise and just really blew it out there's a similar dynamic here in that these guys are disrupting the legacy players with a cloud like model but at the same time so the Amazon with redshift so is Microsoft with its analytics platform you know teradata is trying to figure it out they you know they've got an inertia of a large install base but it's a big on-prem install base I think they struggle a little bit but their their advantages they've got customers locked in or go with exudate is very interesting Oracle has burned the boats and in gone to cloud first in Oracle mark my words is is reacting everything for the cloud now you can say Oh Oracle they're old school they're old guard that's fine but one of the things about Oracle and Larry Ellison they spend money on R&D they're very very heavy investor in Rd and and I think that you know you can see the exadata as it's actually been a very successful product they will react attacked exadata believe you me to to bring compute to the data they understand you can't just move all this the InfiniBand is not gonna solve their problem in terms of moving data around their architecture so you know watch Oracle you've got other competitors like Google who shows up well in the ETR survey so they got bigquery and BigTable and you got a you know a lot of other players here you know guys like data stacks are in there and you've got you've got Amazon with dynamo DB you've got couch base you've got all kinds of database players that are sort of blurring the lines as I said between sequel no sequel but the real takeaway here from the ETR data is you've got cloud again is winning it's driving the discussion and the spending discussion with an IT watch this company snowflake they're gonna do an IPO I guarantee it hopefully they will see if they'll get in before the booth before the market turns down but we've seen this play by Frank Sluman before and his team and and and the spending data shows that this company is hot you see them all over Silicon Valley you're seeing them show up in the in the spending data so we'll keep an eye on this it's an exciting market database market used to be kind of boring now it's red-hot so there you have it folks thanks for listening is a Dave Volante cube insights we'll see you next time

(upbeat techno music) >> Live from San Francisco, celebrating 10 years of high-tech coverage, it's theCUBE. Covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> And we are back at VMworld 2019, here in San Francisco, along with Stu Miniman. I'm John Walls. Welcome to theCUBE here, continuing our coverage here at Moscone. And we're now joined by Don Murawski, who is the manager of Servers and Storage at Wendy's. Don, glad to have you on theCUBE. >> Glad to be here. >> Before we leave, you're going to have to settle this with Stu. He's very upset about the change in menu. That number eight is no longer number eight. >> I can't do anything about that-- >> Well, perhaps we're going to look into that a little bit later on. And what you can do something about is is tell us about your portfolio of services. What you do in terms of, what you are managing in terms of storage, in terms of servers at Wendy's. >> Right, right, yeah. As you know, IT has, especially in the food industry, has become huge, especially mobile app, mobile ordering. You know, DoorDash. Order your food and have it delivered to you. You know, massive business. Massive financial for the company too. How that plays for me is, managing the infrastructure that it runs on. Whether it's an AWS or Azure. A lot of that stuff is on-prem still. So we have to manage a huge amount of volume with a very dense environment. For a hyper-converged shop, Nutanix is part of that. Cohesity is a huge part of our system now. Two data centers. One in Atlanta, one in Dublin, Ohio. So, it's quite quite a big effort. >> You mentioned on-prem, off-prem. About what's your split right now, and are you-- >> I'd say 30:70. >> Okay. >> Yeah, 30 off, 70 on. >> And how is that going to change, you think, over the next three, four, or five years? >> Oh it's changing, drastically. Cost. You know, CapEx, OpEx. It depends where our model's going to be at. Right now, we're more CapEx. So when that goes to OpEx, you'll see a lot more cloud. So right now, 70:30. 70 on-prems, 30 off. >> All right, Don, we talked to so many companies today, and what is that digital transformation they're going through? You talk about app and mobile. It's like boy, I'm reading articles about, how do we make sure that your food delivery person, doesn't eat a lot of french fries, before it gets to you? Maybe speak a little about the ripple effect that has to, your group and IT, as to, you know, we always say fast food. What's faster than walking up to the counter and you know... You guys don't have it sitting under the warmers, of course. They put that together and make it. But it's now transforming that fast food business. >> Yeah, it was touching the back-end servers So it's important that those are properly tuned, properly functioning, on legacy, sometimes legacy hardware. So between cloud and on-prem, it's been a challenge. And we're still working through that challenge. A lot of our developers are in-house. We actually have a big presence for developing right now for our own app. We actually develop our own app and websites. So a lot of that is tied into the movement of, more into cloud technology, than on-prem technology. So right now, like I said, it's 70:30. But it's still a challenge. >> And what is it about that when you say it's a challenge, I mean. So we've drilled down on that a little bit. >> It's just dealing with, not (mumbles) With on-prem you can't scale like you can with AWS or Azure. You can scale 100 times down an Azure bot, auto-scaling. On-prem we can't do that quite yet. We're getting there. So that's still a challenge, because a lot of the information still hasn't touched, on-prem. On-prem databases, which are getting older too, so to speak. So it's still a challenge. >> Don, when you talk to companies, you talk about that whole modernization. And the keynote this morning. We're talking about hybrid-cloud. We talked about multi-cloud. HCI is often a piece of that modernization, but how do you look at how you scale and change things in your data center, versus the public cloud. Is it making progress? Is it limiting at all? >> It's slow progress, slower than we want. More like into, getting rid of the VMs, go containerization. That's a lot of containerization that's happening now with Kubernetes. We have a DevOps apartment we actually just created internally to do that type of work. It's just taking a little bit longer than we anticipated. >> Yeah, and (mumbles) obviously Kubernetes is big discussion here. >> Right. >> How long has your group been using it? >> Not a year. >> Why do you use it? What is it? What's the value to your organization? >> Click a button and you've got a server. It's auto-scaling. So instead of taking two hours to build a server, or three, it's taking two minutes. I think we actually timed a Linux server build in two and a half minutes. The fact that you've got a small workforce too. I mean, we're advertising jobs. Things are what they are. They're pretty stagnant. So we have to make do with the technology that's out there. And Kubernetes is a big part of our future, infrastructure. >> But oftentimes Kubernetes is something that will help me if I want to move something from my data center to the cloud or between clouds or like, do you use that use case yet? Or -- >> Not yet, not yet, we're getting there. >> Okay. >> Yes. Slower progress than we'd want, but yeah, we're getting there. >> All right, when you're living in this multifaceted environment, bring us inside your data management. What's that like today, what's working, what challenges do you have? >> I'll tell you what it was like. It was a nightmare.(laughs) >> Yeah. That'd be awful. (laughing) >> It was a complete nightmare. Multiple vendors. Very complex. Now we're trying to simplify things, make it more dense with (mumbles) Cohesity. It's been a big part for the past year. We moved all our backups at Cohesity. So Cohesity is basically backup and DR now. I don't use it like secondary storage. I have other storage for that, smaller storage units. So it's... Two years ago, we had lost our primary storage and basically took down the company. And living through trying to get your data back for hours and hours and hours, and working. I had guys working 100 hours a week for two, three weeks. And (mumbles) didn't see their families. So making something that is easy to use, manageable, and recoverable, was huge. So take the complexity out and add the ease administration. And that's what we did with Cohesity. >> Yeah, and you're painting really maybe not a worst-case scenario but an awful-case scenario. >> It was an awful case scenario. >> Yeah. So I mean, disaster recovery was a disaster for you. It sounds like that. >> It was. >> So is that what drove you to the Cohesity decision? >> It was, that was a big factor. The fact that I need to be able replicate this stuff to another location, that's one thing. That's what everybody says. But can you actually recover it if it's in the other location. No, we couldn't. Now we can, and I actually prove that through a POC. So yeah, it was a big factor. The fact that people had to sacrifice weekends and I mean literally, work all night, multiple nights, to get things back up, to get the business back up. >> So what do you say to your colleagues or counterparts out there, maybe who haven't, maybe done this kind of spadework that you guys from -- >> I'd try to turn down your critical servers and see if you can recover 'em. You know, take them down and see if you can get 'em back up. Test your DR, because if you don't, it's going to come back to bite ya, and it did. We got most of our data back, but there's some things we didn't get back. We had to recover, I think we had to retire a couple systems that were homegrown systems that were written by a developer back in the day, that's no longer there, we couldn't get it back. We had to send whole departments home, because of this. So I would say, test it. Make sure it works. And make sure your vendor, whoever you pick, is standing by you too. That's a big thing, it's that relationship with the vendor. We don't pick it because it works, we do. But we also pick it because of the relationship with the vendor. Are they going to be there when all, you know what, breaks loose. >> Right. >> Some do, some don't. >> Who's your friend right? >> Who's your friend. >> So Don, you've gotten your title. It's Server and Storage. But you're talking about the Kubernetes, and modern multi-cloud environment-- >> Don: We're small shop. We're small IT shop. So out of my group, DevOps actually spun out. So now we're kind of a infrastructure DevOps team That DevOps is a whole separate thing now because of my team. >> Yeah but (mumbles) what I guess I wanted to get it right is that, was that mostly internally training and going through the model. >> Yeah, it was. >> Bring us through some of those, what worked well, what was a little bit of a pain point. >> Pain points, It took a year to get one application working. But now it's working, you see the value in it. Because I was like, this is a waste of time. We don't scale that much. But however when you do, it sure is nice to build a server like I said, two minutes, that's a huge factor. You know, it was coming, that seemed to be the trend. DevOps, I mean, we wouldn't have DevOps jobs three, four years ago. Well now there's DevOps admin jobs. So it was coming, it was just a matter of time. >> You've been using Cohesity for about a year now, you said. >> A year. >> You talked about where you're using it. Give us a little bit looking forward. Where do you go with Cohesity. What would you like to see them do. >> Yeah, I think a big point is going to be, especially from a (mumble) infrastructure platform, will be more of an Azure footprint. Shrinking the on-prem data center. So Cohesity is going to play a huge role. We still have a lot of 2008 servers. And 2008 goes out of, end of life, in a few months. There's no way I'm going to retire 200+ servers by January. It's not going to be humanly possible. So a lot of that stuff I had to get moved to Azure for support, and Cohesity's going to play a big role in moving that and protecting it. So yeah, I'd say a good path for Cohesity in the future for us. >> So when I brought you on and we talked about the menu, item number eight, that you said you can't help Stu with, is that right? What is menu item number eight? >> It was one of the chicken specialties (mumbles) they have. >> So however, if that, we are very supportive. >> Don: I like that. >> We have our $2 Frosty donation for the year. >> Don: It's good. >> So a Frosty a day right? A free Frosty a day. >> That's right. >> So, we are supportive. >> That's good. >> If you can work on that number eight, maybe-- >> Don: I'll work on it. >> Maybe we can be even more supportive. >> All right John. >> Thanks Don. >> I appreciate it. >> Absolutely, this belongs to Gabe Leon, by the way, on our crew. Just got to give Gabe a shout-out there, for helping us out. Back with more here on theCUBE. You're watching this live, VMworld San Francisco here, 2019.

>> live from Mountain View, California It's the queue covering definite create twenty nineteen. Brought to you by Cisco. >> Hi. Lisa Martin for the Cube, Live at Cisco Definite. Create twenty nineteen. This is Day two of our coverage here. We're excited to welcome Taylor Barnett, a speaker tech talk speaker for this event. Lead community engineer at Stoplight Taylor. It's great to have you on the Cube. I'm glad to be here. So first, inform us before we talk about your tech talk that you can yesterday here, adept that create tell us a little bit about Stop like, >> yeah, So stoplight is a platform. Teo, build test and design web ap eyes specifically, we focus right now on recipe eyes, but we're really encouraging design first principles when people are building out there a prize for very much preproduction And what we have found was so many guys out there are not documented. They're not tested, they're not designed well And so we wanted to build tooling the help users be able to do that. >> So that documentation we've heard yeah, yesterday and today is absolutely >> essential. Yeah, And so a lot of what we're doing is we're actually using the Open A P I specifications, which a lot of teams at Cisco are now using. And so we can auto generate documentation from that. But also, we can auto generate instant mock >> servers. >> Um, do different types of testing all from that, because it's both human and machine readable. You're taking advantage of that. >> So you gave a tech talk yesterday, so I like the title going to Infinity and beyond Documentation with open FBI. Tell us our audience, like basically kind of an overview of what you presented in the three takeaways that your audience left with. >> Yeah, so historically open a P I specification has been known to be an auto generating reference documentation. So what people are like, Yeah, I know it for documentation, but they don't know it for all the other things. So the things that helped them do design first principles, the things that helped them mock and get feedback about their AP eyes and also how to test. And so I say, the three takeaways, that's what I focus on, was, how does this design first really benefit us? And why is it worth spending that time? Because a lot of engineers. It kind of feels like a friction point. Like you're making me do something else before I can start coding on DSO helping them see those benefits and then also being ableto use the feedback through They get through mach ap eyes so that they don't have tio code all the p I and then get the feedback. They could do it before that process. So much, master. Yeah, totally. And just better testing to actually make sure that we once we designed the A that we actually implementing it to what the design says. Uh, >> so I'm not design front. You mentioned design first telling you before we met. Lied that we've heard that. Yeah, I did what I had yesterday and today. This's design first approach and it sounds like from what you're saying for developers, it's not necessarily the first thing they want to do. They want to get their hands on start coding. So yeah, tell may tell us what design first means and actually how it can really make the developers job better. >> Yeah, Yes. Oh, Design First is really just being able to take a step back before that code and like describe what the is on a lower like endpoint level for us that's doing it in a visual editor at Stoplight. We actually have a visual editor to help people do that so that it's not like writing things from scratch. So even then, that makes it faster than having to write on a blank document that nobody wants to like right in. And it might be a mess. And decisions are hard to make around that document because it's a mess and all this stuff and then being able to take that and then start doing the mocking and all the other things. So for developers, it's a lot about getting to see what those other benefits are to convince them that it's worth it. And that's going to save some time overall versus like having toe wait. One great example of that is actually with being ableto Ma K P IIs friend and engineers could go ahead and start implementing the guy before the development process of actually implement thing is even done so that traditional, like waterfall development process. You just cut that out because they can start doing in a parallel on DH so it can really make teams a lot more efficient. >> Did you Were you happy with the reaction yesterday? This is a This is the definite communities. God. Five hundred eighty five thousand plus people. There's been about four hundred here in person. What was the reaction? Especially from developers who may have been around a while and are very used to the waterfall upload where they like. Taylor. This is amazing. Or girl, this is like a whole cultural change. Yeah, you know, I mean, we we work well, >> actually, a lot of enterprise companies that stoplight. And it is it is a little bit of a cultural change. You talk, there's this whole bigger idea of, like, a P I transformation. Even just moving to having a pee ice first is a bigger change. And then, you know, then the design part. But I have found that once, if you're introducing somebody to a prize first, it's easy to sneak in design. So then you don't have to Then teach Oh, let's design the first and do decide. It's all part of the same package s o. A lot of enterprises what They're like transformations to moving toe, like in a very FBI focused infrastructures. They then are just more receptacle to design >> first. That's good. Especially if you're able to show them that the obvious benefits. Yeah, there getting things done faster like this is actually taking this new approach. Is that going to be better for you? And do you find that that developers are adjusting quickly to this new? Yeah. I mean, there's definitely >> pain points. The tooling is still catching up. Uh, so the industry is for recipe eyes has kind of centered around open FBI specifications. But there were others before that Ramel for a specifically and I'd use it for anybody. Also open a p. I used to be called swagger specification. Some people might know it by that, but a lot of it is like, Yeah, the tooling is still maturing, but it's in a lot better place than it used to be. So when I was a back end FBI engineer about four five years ago, I was introduced through a P I blueprint, which is another justification, and it was very painful tohave to document in a p I with it. And now it's just gotten so much better with the tooling mature >> you can see massive differences alone just by asking. >> Totally. Yeah, just like the last four years, actually. >> So this is your first definite create and your speaker at your very first one. That's pretty cool, Taylor. Yeah? Yeah. How long have you been involved in the definite community? And how is it impacted what you do for stuff like, >> Yeah. So I was kind of introduced through it. I knew people that worked on definite and like Mandy. And And so then I kind of got introduced that that, you know, it's been really interesting to see how they built up this community of people sharing code. And it's different then, like, get hub type community. And so it's kind of interesting. It was just like it's ah, you know, you don't see a lot of communities that are run by companies that necessarily >> there they're >> not in the code repository business, but they see the value in people sharing things and collaborating and stuff like that. And so it's kind of different of a community, but also very interesting tow. Have watching grab >> the sharing in the collaboration you walk in yesterday. People are eager to do that Yeah, and other types of conferences that we covered the Cube, especially if there's cooperative Shin Partners there. It's a different vibe has been very, very much one that's been refreshing on and to your point. The difference between what Cisco's built here in the lost, very organically bio away in the last five years with Suzie and Mandy have done that opened nous and that excitability to share things and learn from each other, even though there's got to be developers here from competing companies. Yeah, that's a very cool spirit. Yeah, and something that I think they've done a very good job fostering that they also I kind of wonder if it's chicken and egg. How much has definite. And this, you know, over half a million strong community been sort of forcing function or an accelerator of Cisco's evolution? If you look at Cisco's been around for such a long time, not on a P I first company Yeah, big enterprise. This is a big all of their products and with GPS ***, been really >> awesome to see all the talks that are focused on Cisco's a prize being designed first like I don't see a lot of enterprises that feel like they've really taken it toe heart as much. I've talked to some people and they say, Yeah, I mean, you know, there's been some pain points, but I'm like, Yeah, but there's companies that are envious of the Y .'All done this. Yes, and they've really, like, probably improved the developer experience that they're a piece so much because of having that design first >> approach. So one other thing that I think it's very cool about definite and create is that yesterday morning it was kicked off by two really strong technologists. You don't mention we had Mandy really on yesterday is a senior director of developer experience. Right after you. I've got Susie Leon, the SPP in CTO, and I go to a lot of events. The Cube covers a lot of events every year, and it's very important to us to be able to highlight women and technology because it's still an unresolved, you know, gap there. But it's also really unusual to see an event kicked off both days. No females. You've been a stem since you were a kid. How does that impact you? Do you see that is inspiring. You that is. I wish it wasn't an issue. >> Yeah, no. Yeah. I wish it was an issue, but no, but it's really awesome. So, like, when I was trying to decide if I accept my when they asked me to come speak, I totally looked at that. That was something when I saw their faces on them that they were going to be key notes and stuff, you know, it gave me already, like, a whole different feeling of how the conference >> was going to be >> so it was really exciting to see that. Yeah, >> that's good. And when I first got into tech a long time ago, I was just not aware of what was not monitor in a technical role. But I didn't notice. I mean, they noticed the difference and the disparity, but I didn't feel it. Yeah, And so it wasn't until I started going to more and more events where I sell >> theirs. So, yeah, sometimes you're at events where it's just the sea of people that don't look like you. And it's a lot different here. >> Yeah, until I imagine I appreciated it this morning. I'm sure. Well, when Susie called onto stage the young girls from Verizon and those from Presidio that are Cisco's clearly making a concerted effort to recognize and help this diversity in thought. I mean, imagine designing AP eyes with, you know, many different perspective is better products and services and company, and will be we just have more thought divers in and of itself. >> Oh, yeah, I think about it a lot with developer experience. So one of the things is there's this idea of beginner's mind failure that sometimes if if you think you're a p, I is like, great. But you don't approach it with the beginner's mind, you might actually be failing a lot of your users. So, you know, your, uh, your veteran developer, you're, you know, super skilled and you you don't fail in the somewhere areas that someone who's newer to development might fail. And so then you just lost a bunch of customers and right up front without even them getting deeper into the FBI. And so being ableto have, like more diverse perspectives around, designing a prize could definitely help prevent that. That's a >> really important point so that you make there because it's like if this is really everything that's designed these days. Whatever it is a on iPad. But sticker a piece of clothing. It's all designed for a consumer. Yeah, to consume whatever the product of services. And, you know, in technology, so much conversation goes around delivering an outstanding customer experience. And you're saying, you know, we have to think about that. Probably worked design, thinking, coming play right about designing with that sort of a day bers perspective of approach. That paper you gonna lose customers here were >> actually gets to the bottom line. Yeah, versus just being like a nice benefit kinds. >> Yeah, well, Taylor has been so fun having you on the Cube. Thank you so much. Now you have a flight to catch back in Austin. So thank you so much for doing this afternoon and rats on being a speaker at first. And it will seem Thanks for having me. My pleasure. I'm Lisa Martin. You're watching to keep live from Cisco. Definite. Create twenty nineteen. Thanks for watching