(upbeat music) >> From Washington, D.C., it's theCUBE, covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> Hi, I'm Stu Miniman, and you're watching theCUBE's exclusive coverage of ScienceLogic Symposium 2019 here at the Ritz Carlton in Washington, D.C. Happy to welcome to the program first-time guest but a long-time customer of ScienceLogic, Karl Fosburg, who's the senior director of systems integration at Hughes. Thanks so much for joining us. >> Thanks for having me. >> Alright, so we're here in D.C., and that's important 'cause first of all, you're based down here, and ScienceLogic is based down here. >> Yup. Bring us back a little bit. You said you'd been a customer a long time as to... maybe give us a little bit of the before picture, if you could. >> Sure, so yeah, we've been a customer for 12 years now, and we picked ScienceLogic for a big list of reasons, actually wrote the RFI itself, and probably 20 pages long. Lots of people came back and gave us responses. ScienceLogic was one of the short-listed candidates that we picked out. We did a bake-off with a couple other vendors, and ScienceLogic was the clear winner. >> All right. So Karl, lets zoom out for a second here >> Okay. and just give us a level set on Hughes, what Hughes is today. You know, I'm familiar with what Hughes was back in the day and there's certain pieces that are no longer there so give us a level set on the company in the business. >> Yeah, sure. So, Hughes is formally known as Hughes Network Systems, were owned by EchoStar Corporation and we're a managed service provider. We have a consumer business where we provide broadband internet to folks that live really out in the countryside and can't get cable, or DSL, or FIOS, things like that. We have about 1.4 million subscribers in our consumer business. We've also launched consumer services in South America, Brazil, Ecuador, Columbia, places like that. Really serving under-served areas for giving them broadband. We also have an enterprise business where we sell to credit card processing, gas and oil, pipelines, fast foods, places like that. >> Okay. So Karl, is it safe to say you use satellites but no longer put them into space? >> We use satellites, that's correct. We contract that out now. Yeah, we are the last remaining Hughes company. >> Yeah. So, service providers are always fascinating to me because we talk about enterprise IT and how fast things are changing. At least for my entire career, when I talk to service providers, change and growth is really just baked into the DNA. >> Yep. I need to move fast. When you talk about scale, it means something very different and living in that complex world, and just give us a little bit about what things are like in 2019 for you. >> Sure, yeah. The scale is always our challenge. Like I like to say, we have sales people too and they're out there selling new products and services constantly. So we needed to be able to grow with those sales. We started out with a couple thousand devices that needed monitor in applications. Now we're up to almost 30 thousand Nox systems that we monitor. Also, we're keeping track of nearly 2 million terminals and the status of them and things like that. So, yeah, scale is super important to us. >> Okay. So, bring us inside, where ScienceLogic fits into your equation. >> Sure. So when we put out our FI to industry years ago, we were trying to replace a whole bunch of different tools. We had other vendor products and things like that. We really wanted to consolidate tools as much as possible into a single platform. Traditional ICNP, SNMP monitoring is how we originally started. Now we have lots and lots of integration with other tools, APM products, different streaming media products. We're integrating more and more with streaming services now in terms of getting data into the platform. So, yeah ... >> Yeah. Karl, I'd love to get your viewpoint. Something that came through to me in the keynote is on the one hand the years like, oh, well AIOps is going to replace things like some of the traditional players here, but then you see onto the stage it's like, oh okay, we're actually going to have integrations with a number of these tools. So yes, there's overlap but it needs to be integrated. How do you look at that as, is this the primary product? Is this a piece of the product? How do data collection between all these various tools go together? Well, that's a great question 'cause that's exactly what we and lots of other folks are grappling with right now. We've got data producers all over the place now, and we're really focused on the data production and high quality data back at the source into a real pub-sub type of architecture of which we believe that ScienceLogic will be both a producer and consumer of that pub-sub architecture, and whether it's the one tool to rule them all or not? Probably not, no ones going to be that, and we've got lots of vendors that purport to be the one tool to rule them all. But really, we're focused on ScienceLogic at this point to be really the focus, especially for our operations folks. We've got 24/7 staff. They use ScienceLogic as their main tool that they go to. So that's really where we want the data to end. That's where we want as much intelligence to end as possible. >> So, I'd be curious... You've been using the tool for a dozen years now. 12 years ago the discussion of data wasn't no where near what it was today. >> Correct. Can you bring us through a little bit of that journey, and you mentioned data a bunch, but how important is that? Where are you in your journey for... There was that maturity model that was put up there, the role of data today, and where do you see it going? >> Well, data is everything today. 12 years ago we were grappling with things like naming conventions and simple firewall rules and whatnot. Those days are long, long past. Now, the data quality and the pipeline is what we're focused on right now 'cause like Dave said in the keynote, "Garbage in, garbage out". We're really really focused on trying to get good quality data by focusing on the source of the data. As opposed to fixing it after it's been moved into whatever platform it ends up in. So we're using proper scheme of management and trying to bake-day the governance into the actual engineered products, and if it's not governed data then you don't get to look at it. And that's really our focus. We're an engineering company at heart so we actually write most of our own software. So we're kind of in control of our own destiny there, and we're really focused on pushing that back because we think the benefits in the long run are going to be worth that investment to get clean data all the way back to the source. >> Yeah. So Karl, one of the big shifts I've seen in the last few years... When you talked about managing and monitoring, I used to as the administrator or controller, used to be able to go and touch all of those pieces. Today, there's more and more some of those pieces I need to manage not just the stuff that's in my environment or my hosted environment, but outside of my environment and doing public clouds. >> Yep. >> Bring us up to speed as to where does Cloud fit? What's your Cloud strategy? >> Sure. We're actually launching some of our first applications in GCP right now. So we're working with our Google partners in this particular case to integrate the data that they can collect natively in their systems, bring it back in as actionable events into ScienceLogic platform, while keeping the vast majority of the data native to their platform. No need to bring back application specific data unless we're actually going to do something with it, or if we need to cross-correlate it with other information. The data sources live in our data centers, not in GCP. So we need to combine it with information we know about, our on-prem equipment, plus the applications running there. So that's the data we'll bring back to cross correlate. >> How do you decide what lives where, and where does ScienceLogic fit in the whole discussion? >> Yeah, that's a good question. What lives where... We kind of go back to license models and cost models. We're pretty good sticklers about focus on doing proper upfront analysis to make sure we don't end up with some six or seven figure bill at the end of the year from a Cloud provider. We also tend to do a lot of stuff on-prem because a lot of our systems have to run in one of our data centers. If you've ever driven past our building you'll see these large large dish's antennas outside. A lot of our equipment has to be within milliseconds or microseconds even of those dishes. So we actually have a large data center presence kind of scattered around the country and around the world. So, we have the compute resources to do it ourselves. >> Yeah, and even I would think edge computing something that plays into what you're doing. What do you see as some of the main challenges as the kind of footprint for what you're doing and things to spread out more? >> Yeah. Keeping, let's say pet projects, and shadow IP projects, keeping them in check is a really big focus right now, and also with DevOps sort of the "I'll do everything, I'm going to be my own IP department" philosophy is a new challenge that we're facing. So integrating with what the DevOps guys are building into our overall monitoring strategy, that's when a new challenge has really creeped up or it last, lets say six months or a year. >> Okay. Is there an intersection between your use of the ScienceLogic in the DevOps team yet? >> Not a big one yet. I think we're still learning DevOps at this point. I consider it a lifestyle change, not really a thing that you go get. So, I think we're still kind of early adoption for DevOps, and really only greenfield projects at this point in time. >> Okay. How about the term of the show is AIOps, so what's your act in the AIOps? Where do things like machine learning and automation fit into your environment? >> Yeah. We actually have quite a few used cases where we really think that machine learning is going to help us a lot. Cross-correlation is a big area for us. We have lots of information, but figuring it out, feeding like the APMs and Cisco ACI software defined networking, and those bits of information all into one product, we've been challenging ScienceLogic on this for quite a while. It's like, okay, you guys know about everything now. Tell us something that we didn't know before, and that's kind of where we're at, and seeing the announcements from this morning was really encouraging that we're finally see the horizon at this point. >> Yeah. If you can, (mumble), but how has ScienceLogic been doing on the roadmap? What helps between ScienceLogic and your vendor ecosystem out there? What more could they be doing to make your life easier? >> Yeah, that's a good question. So, if you would ask me that a year ago I probably wouldn't have been as encouraged as I am today. It was a challenge and they're engineering company, we're an engineering company. Sometimes you have to focus on foundation, and it's not cool, it's not sexy, it's not shiny, but you have to do it. And I think they've been focused a lot on their foundational aspects of the product which will actually enable doing things like machine learning. There's no point in doing machine learning if you have bad data or if you have a platform that doesn't support very very fast queries, and the graph QL database. We think that we're going to use that extensively and through the API, not even through the UIs. So, I think foundation is important. I think they focused on it for the last couple of years. I think we're finally going to start to see the benefits of it. Both single factor sort of machine learning, anomaly detection, but we really want to see it on a cross domain. I want to be able to see in ScienceLogic impacted by in our full stack environment. >> Yeah. I'd expect you probably had some visibility into what was coming up in the Big Ben release. Is there anything that jumped out at you, or that you're ready to use day one? >> The automations, for sure. We'll use that definitely day one. The way they've gone through and really made it a lot easier to use. You don't have to be a python developer anymore to actually get a lot of benefits out of the product. So I can turn that over to some of our junior engineers to actually handle those things, and we get a lot more sophisticated with them now. Primarily we used to focus on, "oh, let's send an email" type of thing. Now we can actually execute back-end actions without having to have a programmer to do it. So that right away we're going to use out of box. >> Okay. And in that forward looking piece, without breaking any visibility you have into their roadmap, what would you like to see more? >> I'd like to see more getting performance data into their real scalable, laterally scalable back end. And that's certainly an area that I'd love to see as much progress as fast as possible on. Also the Pub-Sub subscribing to streams coming out of our Kafka cluster. We want that to be in the product as soon as possible 'cause we really believe that that's where the majority of our data of the future is going to come from. Also, new applications, they come and go. Docker containers spin up, spin down. So the state of something is no longer fixed and we need to be able to integrate with Kubernetes and our open shift platform to be able to know, "Well what should be running right now?" So, those are the things that are on our roadmap that we need out of the product as soon as possible. >> Yeah. So it definitely came to me that ScienceLogic's listening. Are they moving fast enough for you? >> No. No ones ever moved fast enough. So, yeah, they're moving so that's good, but yeah, I could use it today if they had it. >> All right. Karl, last thing, you've been to a few of the ScienceLogic events in the past. You've been to other industry shows, what's special about the show? What brings you and your team to ScienceLogic symposiums? >> One of the things that ScienceLogic does a really good job is they bring a lot of resources here, and actual resources that actually know stuff. It's not just telling me, "Oh, that shiny new object is going to be in the platform at some indeterminate time in the future." It's the actual engineers, people writing code, product managers, things like that. So having access directly to the people who actually do the platform updates and changes is super valuable. The new sensor where we can touch and feel, take attires on new things has been excellent this year. So I think that's probably the thing, just quick access to all the resources. We have a bit of an advantage, we're only 45 minutes up the road. We can come down here as need be to visit their headquarters but having everyone here at one time is great. >> All right. Well Karl Forsberb, really appreciate you sharing your history and experience in future direction as to where things are going on your end. >> All right. >> I'm Stu Miniman. We'll be back with lots more coverage here from ScienceLogic 2019. Thanks for watching theCube. (upbeat music)

(energetic music) >> From Washington D.C., It's theCUBE! Covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> Welcome back to TheCUBE's coverage of ScienceLogic Symposium 2019, I'm Stu Miniman, and we're here at the Ritz-Carlton in Washington, D.C. Happy to welcome to the program two first-time guests from ScienceLogic, to my left is Leslie Minnix-Wolfe, who is the Senior Director of Product Marketing. And to her left, is Russ Elsner, who's the Senior Director of Product Strategy. Thank you so much for joining us. >> Thank you sir. >> Good, good to be here. >> All right, so Leslie let's start with you. Talk a lot about the product, a whole lot of announcements, Big Ben on the keynote this morning. Everybody's in, getting a little bit more of injection in the keynote today. Tell us a little bit about your roll, what you work on inside of ScienceLogic. >> Okay, so I am basically responsible for enterprise product marketing. So my job is to spin the story and help our sales guys successfully sell the product. >> All right, and Russ. >> I'm part of the product strategy team. So, I have product management responsibilities. I work a lot with the analytics and applications. And I spend a lot of time in the field with our customers. >> All right so, Leslie let's start with enterprise, the keynote this morning. The themes that I hear at many of the shows, you know we talk about things like digital transformation. But, we know the only constant in our environment is change. You know, it's good. I've actually talked to a couple of your customers and one of them this morning he's like "Look, most people don't like change. "I do, I'm embracing it I'm digging in, It's good." But, you know, we have arguments sometimes in analyst circles. And it's like are customers moving any faster. My peers that have been in the industry longer, they're like, Hogwash Stu. They never move faster they don't want change, we can't get them to move anything. I'm like, come on, if they don't the alternative is often, You're going to be... You know, you're competitors are going to take advantage of data and do things better. So, bring us a little bit of insight as what you're hearing from your customers both here and in your day to day. >> Sure, yeah, change is constant now and so one of the big challenges that our customers are facing is how do I keep up with it. The traditional manual processes that they've had in place for years are just not sufficient anymore. So they're looking for ways to move faster, to automate some of the processes that they've been doing manually. To find ways to free up resources to focus on things that do require a human to be involved. But they really need to have more automation in their day to day operations. >> All right, so Russ when I look at this space you know, tooling, monitoring has been something that in my career, has been a little bit messy. (laughter) Guess a little bit of an understatement even. It's an interesting... When I look at, kind of, that balance between what's happening in the infrastructure space and the application space. I went through, one of your partners over here is like "from legacy to server lists and how many weeks." (laughter) And I'm like okay that sounds good on a slide but, these things take awhile. >> Absolutely. Bring us inside a little bit, kind of the the application space an how that marries with the underlying pieces and monitoring. >> Yeah, you have a lot of transformations happening. There's a lot of new technologies and trends happening. You hear about server lists or containers or microservices. And that does represent a part of the application world. There are applications being written with those technologies. But, one of the things is that those applications don't live in isolation. It's that there part of broader business services and we're not rewriting everything and so the new shiny application and the new framework has to work with the old legacy application. So, a big piece of what we see is how do we collapse those different silos of information? How do we merge that data into something meaningful? You can have the greatest Kubernetes based microservice application but, if it requires a SAP instance it's on PRIM it's on Bare Metal. Those things need to work together. So, how do you work with an environment that's like that? Enterprise, just by it's nature is incredibly heterogeneous, lot's of different technologies and that's not going to change. >> Yeah. It's going to be that way. >> You're preaching to the choir, here. You know, IT it always seems additive the answer is always and. And, unfortunately, nothing ever dies. By the way you want to run that wonderful Kubernetes Docker stuff and everything. I could do it on a mainframe with Z Linux. So, from that environment to the latest greatest hypercloud environment >> Right. Talk a little bit about your customers. Most of them probably have hundreds of applications. They're working through that portfolio. What goes where, how do I manage all of those various pieces, and not kill my staff? (laughter) One of the things we're spending a lot of time with this, is that obviously, we come from a background of infrastructure management. So, we understand the different technologies different layers and the heterogeneous nature and on top of that runs application. So they have their own data and there's APM space. So we're seeing a lot of interest in the work we're doing with taking our view of the infrastructure and marrying it to the application view that we're getting from tools like Appdynamics or Dynatrace or New Relic. And so, we're able to take that data and leverage it on top of the infrastructure to give you a single view which aids in root cause analysis, capacity planning and all the different things that people want to do. Which lead us to automation. So, this idea of merging data from lots of sources is a big theme for us. >> All right so, Leslie who are some of the key constituents that you're talking to, to messaging to. In the industry we talked about silos for so many time. And now it's like oh, we're going to get architects and generalists. And you know cloud changes everything, yes and no. (laughter) We understand where budgets sit for most CIO's today. So, bring us inside what you're seeing. >> Sure. Yeah, we're seeing a tremendous change. Where before we use to talk more to the infrastructure team, to the folks managing the servers, the storage the network. We're really seeing a broader audience. And a multiple constituent. We're looking at directors, VP's, CIO's, CEO's, architects. We're starting to see more people that are tools managers, folks that are involved in the application side of the house. So, it's really diverged. So, you're not going in and talking to one person you're talking to lots of different teams, lots of different organizations that need to work together. To Russ's point in about being able to bring all this data together. As you bring it together, those different stakeholders have more visibility into each others areas. And they also have a better understanding of what the impact is when something goes down in the infrastructure, how it effects the app and vice versa. >> Leslie, the other thing I'm wondering if you can help me squint through, when I looked at the landscape, it's, you know, my ITSM's I've got my logging, I've got all my various tools and silos. When I hear something like, actually, your CEO Dave just said "Oh, we just had a customer that replaced 50 tools." with there it's like, How do you target that? How does a customer know that they have a solution that they have a challenge that you fit, Because, you understand, you can't be all things to all people. You've got certain partners that might claim that kind of thing. >> Right But, where you fit in the marketplace how do you balance that? >> Well, so I think what we're seeing now is that there have been some big players for a long time. What we refer to fondly as the Big Four. And those companies really haven't evolved to the extent that they can support the latest technology. Certainly at the speed with which organizations are adopting them. So, they might be able to support some of the legacy but they've really become so cumbersome, so complicated and difficult to maintain people are wanting to move away from them. I would say five years ago, most organizations weren't willing to move down that path. But with some of the recent acquisitions, The Broadcom acquisition, Microfocus acquisition. You're seeing that more organizations are looking to replace those tools in their entirety. And as a result of that they're looking at how can I minimize my tool set. I'm not going to get rid of everything and only have one vendor. But, how do I pick the right tools and bring them together. And this is one of the areas where we do extremely well in that we can bring in data, we can integrate in other tools, we can give you the full picture. But, we're kind of that hub, that central. And I think we heard that earlier today from Bailey at Cisco, where he talked about ScienceLogic is really the core to their monitoring and management environment, because we're bringing the data and we're feeding the data in to other systems as well as managing it within ScienceLogic. >> Russ, I actually heard, data was emphasized more that I expect. I know enough about the management and monitoring space. We understand data was important to that, I'm a networking guy by background, we've been talking about leveraging the data for network and using some automation and things like that but it's a little bit different. Can you talk some about those relationships to data? We understand data's going to be everywhere and customers actually wrapping my arms around it make sure I can manage it, compliance and to hopefully get value out of that is one of the most important things in today. >> Absolutely, so one of the things we stress a lot when we talk about data, it use to be that data was hard to come by. We were data poor and so how do we get... We don't have a probe there so how do we get this data, Do we need agent? That's different now, data is... We are drowning in data, we have so much data. So, really the key is to give that data context. And so for us that means a lot of structure, and topology and dependencies across the layers of abstraction, across the application. And we think that's really the key to taking this, just vast unstructured mess of data that isn't useful to the business and actually be able to take... Apply analytics, and actually take action, and ultimately drive automation by learning and maintaining that structure in real time automatically, because that's something a human can't do. So, you need machine help, you need to automate that. >> So, Leslie, there was in the keynote this morning that to start discussion of the AI Ops maturity model >> Right >> And one of the things struck me is there was not a single person in the poll that said, yes I've gone fully automated. And first, there's the maturity of the technology, the term and where we are. But, there's also that, let's put it on the table. That fear sometimes, is to "Oh my gosh, the machines are taking our jobs" (laughter) You know, we laugh, but it is something that needs to be addressed. How are you addressing that, Where are your customers with at least that willingness, because I use to run operations for a number of years, and I told my team, look you're going to have more work next year, and you're going to have more things change, so if you can't simplify, automate. Get rid of things, I've got to have somebody helping me, and boy those robots would be a good help there. >> What we're seeing is, I mean let's be real, people don't like to do the mundane tasks, right. So you think about, When you report an issue to the service desk. Do you really want to open that ticket? Do you want to enter in all that information yourself? Do you want to provide all the details that they need in order to help you? No. People don't do it they put in the bare minimum and then what ends up happening is there's this back and forth, as they try collect more information. It's things like that, that you want to automate. You want to be able to take that burden off of the individuals And do the things, or at least allow them to do the things that they really need to do. The things that require their intelligence. So, we can do things like clean up storage disk space when your starting to run out of disk space. Or we can restart a service, or we might apply a configuration change that we know that is inconsistent in environment. So, there's lots of things like that that you can automate without actually replacing the individual. You're just freeing them up to do more high level thinking. >> Russ, anything else along the automation line. Great customer examples or any successes that you've seen that are worth sharing? >> Yeah, automation also comes in the form of connecting the breadcrumbs. So, we have a great example. A customer we worked with, they had an EPM tool, one of the great ones, you know, top of the magic quadrant kind of thing, and it kept on reporting code problems. The applications going down, affecting revenue, huge visibility. And it's saying code problem, code problem ,code problem. But the problem is jumping around. Sometimes it's here, sometimes it's there. So, it seemed like a ghost. So, when we connected that data, the APN data with the V center data and the network data what it turned out was, there was a packet loss in the hypervisor. So, it was actually network outage that was manifesting itself as a code problem, and as soon as they saw that, they said what's causing that network problem? They immediately found a big spike of traffic and were able to solve it. They always had the data. They had the network data, they had the VMware data they had the JVM data. They didn't know to connect the dots. And so, by us putting it right next to each other we connected the dots, and it was a human ultimately that said I know what's wrong, I can fix that. But it took them 30 seconds to solve a problem that they had been chasing after for months. That's a form of automation too is get the information to the human, so that they can make a smart decision. That's automation just as much as rebooting a >> Exactly server or cleaning a disk >> Well right, It's The Hitchhikers Guide to the Galaxy. Sometimes, the answers are easy if I know what question to ask. >> Exactly, yes. (laughter) >> And that's something we've seen from data scientists too. That's what their expertise is, is to help find that. All right, Leslie give us a little view forward. We heard a little bit, so many integrations, the AI ops journey. What should customers be looking for forward? What are they asking you, to help bring them along that journey? >> Oh gosh. They're asking us to make it easier on all counts. Whether it's easier to collect the data, easier to add the context to the data, easier to analyze the data. So, we're putting more and more analytics into our platform. So that their not having to do a lot of the analysis themselves. There's, as you said earlier, there's the folks that are afraid they're going to lose their job because the robots or the machines are taking over. That's not really where I see it. It's just that we're bringing the automation in ways and the analytics in ways that they don't want to have to do, so that they can look at it and solve the really gnarly problems and start focusing on areas that are not necessarily going to be automatable or predictable. It's the things that are unusual that their going to have to get involved in as opposed to the things that are traditional and constant. So, Russ, I'd love for you to comment on the same question. And just a little bit of feedback I got talking to some of the customers is they like directionally where it's going, but the term they through out was dynamic. Because, if you talk about cloud you talk about containers. Down the road things like serverless. It's if it pulls every five minutes it's probably out of date. >> oh, Absolutely. I remember back when we talked big data, real time was one of those misnomers that got thrown out there. Really, what we always said is what real time needs to mean is the data in the right place to the right people to solve the issue >> Absolutely. >> Exactly. So, where do you guys see this directionally, and how do you get more dynamic? >> Well see, dynamic exists in a bunch of different ways. How immediate is the data? How accurate is the dependency map, and that's changing and shifting all the time. So, we have to keep that up to date automatically in our product. It's also the analytics that get applied the recommendations you make. And one of the things you can talk to data scientists and they can build a model, train a model, test a model and find something. But if they find something that was true three weeks ago it's irrelevant. So, we need to build systems that can do this in real time. That they can in real time, meaning, gather data in real time, understand the context in real time, recognize the behavior and make a recommendation or take an action. There's a lot of stuff that we have to do to get there. We have a lot of the pieces in place, it's a really cool time in the industry right now because, we have the tools we have the technology. And it's a need that needs to be filled. That's really where we're spending our energy is completing that loop. Closed loop system that can help humans do their jobs better and in a more automated way. >> Awesome. Well, Leslie and Russ, thanks so much for sharing your visibility into what customers are doing and the progress with your platforms. >> All right, thank you Stu. >> And we'll be back with more coverage here from ScienceLogic Symposium 2019. I'm Stu Miniman, and thank you for watching theCUBE. (energetic music)

>> From Washington DC, it's theCUBE. Covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> I'm Stu Miniman and this is theCUBE's coverage of ScienceLogic Symposium 2019 here at The Ritz-Carlton in Washington DC. Really excited to welcome back to the program. It's the co-founder CEO and the Headmaster of Wizarding school, >> Wizarding school, yes. >> Dave Link, thank you so much for joining us. Great to be here Steve. >> All right, so Dave first of all congratulations, really been enjoying the event you know you you kicked it off in the keynote this morning great energy, really I think capturing you know where we are in you know IT in business today. We understand how things are changing so much and it's a complex world and ScienceLogic is trying to do Its part to help simplify and make it easier for IT to you know run at the speed of business and machines. >> That's exactly right. What's happening in the world right now is you've got a confluence of cloud apps, traditional legacy apps and they're colliding together and as they collide together you need new tools to manage that in a way that's different than what we've seen in the past. You're looking at lots of sources coming together to contextualize, not just seeing what's happening, understanding how systems relate to one another but acting upon them. Machine at machine speed means that automation is king and the wizard hat actually relates to a storyline we had earlier today when we think about how to educate the marketplace and the customers we realized that we needed a very new way of communicating. So videos E-Learning The Wizard of learning has been a theme of the show to help our customers to get up to speed and actually take full advantage of the application that we provide to help them deliver great service quality. >> Yeah well and we appreciate you bringing theCUBE to help with that video education of the community overall. >> That's right >> Yeah so you know look Dave you know wanted... let's step back for a second and you know we want to going to get to the business update but first you know the company is founded in 2003. You know cloud wasn't a term, some of the underlying foundations of what became cloud, you know existed back there. Those of us in the industry understand some of the waves that have happened there but you know to talk about cloud and micro services and all of these changes that have... So give us a little bit about that evolution about the original premise of the company, as we move now to you know the world of today and how you manage to keep the company moving and relevant >> I love telling this story Stu because it never gets old >> Yeah >> A lot of the original feces that we had about where service business service analysis was going, the application analysis connected to the infrastructure. Our belief was we were going to move to a world where it wasn't based on devices or nodes or systems. It was really based on this service and what we're seeing with cloud has accentuated that tenfold because services now are made up of compound things, technologies, service delivery mechanisms as a service platforms and they all have to work with one another The platform we built had an architecture that was very open that could take data streams from lots of different sources, create a common information model contextualize that and then act upon it. So now more than ever before, we really built the right platform with multi-tenancy, with role based access control with all the things that were really hard problems to solve code day one and now the thesis that we had that it was more about the service view is as important as it as it's ever been with ephemeral systems that are coming and going, with really containerized systems on top of virtual machines on top of their metal. All these abstraction layers require a different mindset but an open architecture is really at the heart of pulling lots of data streams together contextualizing it and then acting upon it >> Yeah, so I'm a sucker for Venn diagrams. so you heard that the analyst in the keynote this morning talked about AI ops and he said to the inner structure intersection of IT operations data science and machine learning >> Yes >> Data at the center of everything, it's something we've had a couple of waves of trying on intelligence and automation, are things we've been talking about for decades in IT. Give us a little bit as why some of those waves are coming together so that now and what you're doing is the right moment to really help accelerate. You've been having great growth for a number of years and project out some really strong growth for the next few. >> We have over the last five years the company has grown over five hundred and forty percent from a revenue perspective and I think that's the underpinnings of that relates to do we have the right market fit. Are we solving a problem that's material to customers that it's hard for them to solve without our product. But I really envision a future we've been working on this for a couple decades, right? The future is one I hope where from a artificial intelligence at machine speed where we're getting so predictive and understanding, through really smart scalable algorithms the future faults that may occur for you know we've both been at this for a long time. we've been talking about event correlation for many years. I envision a world where you're not doing event correlation when you've had an event, it's actually too late. Usually that's caused by a system telling you that there is a problem. So what we're really working on what we've talked a lot about here at the show is not just predictive analytics but really understanding what's abnormal and getting in front of a problem before there is a problem with the system with really super smart algorithms that help customers understand, many different data sets converge together and what they really mean so that you can get ahead of a service outage rather than have the fault that you're then working on correlating to infrastructure to application layers. >> You know the other thing that's been interesting for me to watch is, the core of where you started was really working with the service Fighters. I've had a chance to talk to a number of your service fighters >> Yes and Hughes has been with you since the early days up to you know one that just bought a couple of weeks ago and you know they're happy very. Talked about kind of the compare/contrast of the service riders and the enterprise because you know cloud is impacting you know the big hybrid hyper scale clouds are impacting both of those and the rate of change is affecting both of those in a lot of ways. So I'm curious as you see you know what what what's similar and what's different between going into those markets. >> When we thought about the problem for service providers there were two axes that we were looking at. Number one was from one instance of our platform you had to serve many customers that all had their own tenancy. But on top of that, you had to layer in a role based access control who could see what the customer had their view, the internal ops teams had their view. So building out a really complicated foundational model and an architecture that would support tenancy on steroids with one instance of our product was a really important linchpin of what's now, incredibly important to enterprises, because enterprises are getting into a moment where they're having to really act as service bureau's, service brokers and that means that all the different teams that support different technology silos, really have to work together as one and... but yet they still need their own views.So a lot of the foundational highly differentiated capabilities we built for service providers, for large scale globally distributed enterprises, actually meets a need profile that is very hard to find solutions that fit that profile and can give them that consolidated view but yet the deep dive view for the practitioner and we're finding that more and more enterprises, have follow-the-sun operations, follow-the-sun architecture teams, follow-the-sun engineering teams that need different views that is really hard to get most products that were built in this space were built for a single tenant enterprise view and that never gives you the granularity for each consumer and each persona to get the view that they need. So it's interesting that although we kind of over engineered those capabilities for the service provider needs it's becoming involved with the enterprises as they're looking at how do they need to do things as really a converged team, working as one team across many silo disciplines and that requires a very different way of thinking, a different tool space a different solution to the problem that we built kind of from the ground up. It's now really appropriate for the DevOps teams the teams that are really having to break down the silos and work as one team. >> Yeah the, the the the term that often gets misused and misunderstood is scale. But if you truly can build something that's distributed architecture for scale, It really opens up a lot of opportunities. One of the things you highlight it also is that, ScienceLogic puts a lot of investment into you know R&D and keep working on things big announcement of Big Ben, seemed I've had a chance to hear what everybody likes and the best. Talk a little bit about you know how you keep the development efforts going how you put that strong and effort on it and you know boy you know you said you worked on the UI for three years and now it sounds you know it's a bold statement to be like okay and everybody you're using this, you know you can't have the safety blanket of old away in new way for a while, >> You're constantly reinventing and refactoring code base to get to new outcomes for customers. we're spending between 35 and 40 percent of revenues on R&D. That's generally almost twice as much as many of our competitors and we're doing that because there is so much still to do. At times we have really thought carefully, could we scale back should we scale back our R&D spend but fortunately we've had a very supportive board of directors that believes in our vision. Believes in the vision that this is a unique moment in time the whole market is transitioning to a new tool set, because of all of the crosswinds of public cloud refactoring of applications containerization abstraction of the network, a storage, compute. All of these things combining together require a very different way of solving this problem We've, we've actually seen this play out in the past which again is why we're over investing in engineering. When you look at the mainframes and the compute architecture of mainframes and then we went to client-server, the tools that managed the mainframe really didn't manage the client-server. we've now gone from client-server to cloud the same things happening again. Because the needs are so different and we're going to see a very different generation of tools rule this next gen of requirements the customers have when they have a multitude of clouds that all work together to deliver an outcome to an application that you as a user are benefiting from. >> Alright so talked about the growth, talked about the investment, it's a strong industry validation today also. Gartner up on stage talked about the definition of AI ops they might not be fully in sync as to how mature the market is but it's still important that they are you know this is a trend and something to watch and it's on their hype cycle and Forrester released the wave which had congratulations ScienceLogic as the the top scorer up in the leaders category. So congratulations on that and what does that mean. >> Well we're thrilled about that because that external validation is what customers look at. It helps them with their analysis and that the talk tracks that everybody's on in our industry sometimes it's hard to discern who does what and how well each company does it to some degree from a marketing perspective many people use the same words so the good words are already used up. So sometimes it's hard to understand how each product is differentiated in the marketplace the Forrester wave report was so thorough so comprehensive, put us through over 30 use case scenarios where we had to demonstrate to get the qualifications for that ranking. So it wasn't just us responding in writing and waving our arms and throwing out a few powerpoints to get to that result we had to prove it and it feels the satisfaction of actually proving it for our team for our engineering team for everybody here at the company I'm so proud of everybody because that's really from a product perspective. We love those product recognition awards are actually sometimes more enjoyable than the growth recognition awards because that means you're really delivering a value to the customer where they're going to when they deploy the product they're going to have a good outcome. So that's what we're focused on and having Forrester put us at the top of the wave report is a special moment in the history of the company. >> Alright so Dave this is your user conference, so what I want to end on... Let's talk about the customers and here's here's my observation as you know, my first time coming to your event and I've talked to a number of seen some of the interactions there. There are certain products that customers love the relationship is an interesting and I would say a really good one the customers are really engaged and enjoying and liking it and it's almost like that friend that you can be like I really like you and your friends in their car I can be like this is how I want you to get better in ScienceLogic this is what you've done and I'm excited once on the roadmap and this is where I want you to go even more. So it's it's like you know that that friend that you can kind of hang out with and joke with and I've seen some of those relationships it's a good robust relationship and strong partnerships. It seems that you build with your customers am I getting the right vibe how do you look at your relationships with your customers. >> From a simple business perspective, I look at a couple things this is just as a run the business metric. On average our customers buy about twenty four, twenty five percent more capacity each year. On average our customers stay with us for 7-10 years. On average our customers pay us within 59 days. So I look at are we getting paid on time, do our customers buy more capacity each and every year and do we retain our customers. We retain about ninety five percent of our customers. So those metrics are really best-in-class, net subscription retention, DSO. All of those things are really good foundational indicators of we're doing a great job for our customers but what I love is this interaction that we have with them where they're they're never ending pressure on us to do better to strive for something that makes a day in their life a better day. I love that pressure it's uncomfortable many days of the week as I mentioned in my opening presentation but it makes us a better company and everybody in the company embodies this sense of how do we capture that synthesize it and then deliver against their needs and wants as quick as we can. So our innovation rates now are as high as they've ever been the throughput our of our development team this last quarter was the best we've ever seen in the history of the company, not just because we have more people but we're getting more done in the same amount of time. So all the KPIs that I look at are pointing in a really positive direction of great momentum for the business and really good alignment with customer needs and wants. We have probably the best market fit I've ever seen with the needs and wants of a net new customer and how our product fits against that. The Forrester wave report was yet another independent validation of how good our market fit in our strategy is right now to solve real problems that are very painful for customers to solve without our product >> Alright, Dave I can't let the head wizard gone without looking a little bit into the future. So as you look down the road what should we be looking as industry watchers to seem from ScienceLogic, seen from the industry you know I asked customers if they had a magic wand you know what would they do to make things better. You had a magic wand up on stage what will you be doing to make the industry better for all of us. >> There's so many things that when we think about making the industry better, it's a community and that means that among the key things that everybody's focused on right now for AI OPS is automation. So sharing those lessons learned cauterizing, validating the automation opportunities whether it's with provisioning systems, with end devices for capacity planning. All the things that we're doing we're starting to work with our customers to publish that broadly so that they can benefit from one another as quick as possible to take those best practices and throughout our community put them into production. If we do that each and every day and really focus on delivering that value across the customer base even for competitive customers. They compete with one another what we've seen is the spirit of cooperation and that to me is among the most satisfying parts of our customer and user community that it's a community that wants to help each other get better every day of the week and that's really hard mission as well. So from a trend line for the entire industry, I think we're all moving towards a moment in time where we have this autonomic capability where we know the applications are infrastructure, we're the tools that help us keep those applications running are getting smarter and smarter by the day and basically move us away from a fault and event correlation storyline to a predictive automation storyline >> Alright well Dave actually I said it on theCUBE a couple of years ago data holds the potential be that flywheel of growth for many years to come. Really appreciate you sharing the story and thanks again for having theCUBE at the event. >> Thanks too great to be here with you. Alright we'll be back with more coverage here from ScienceLogic Symposium 2019, I'm Stu Miniman and thank you for watching theCUBE.

>> from Washington, D. C. It's the queue covering science logic. Symposium twenty nineteen. Brought to you by Science Logic. >> Hi, I'm student men and this is the Cubes coverage of Science Logic. Symposium twenty nineteen here at the Ritz Carlton in Washington, D. C. Been four hundred sixty. People here just finished the afternoon Kino, and they've actually gone off to the evening event. It's thie yet to be finished. Spy Museum. They get a good three sixty view of Washington D. C. So the hallways are a little echoing in quiet but really excited to have on the final guest of the day. Eric Gordon, who's the vice president of business development and alliances as science logic. Erik, thanks so much for joining me, >> thanks to you. Great to be here. >> All right, so busy. Dev and Alliances. I've talked to a number of your partner's. I've gone through a lot of things, but you wear, I think, just like your CEO. A few different hats. Ah, and your old let's let's get into what your role is that the company? >> Yeah, it's actually changed over time, but for the most part I've to court responsibilities. One is I'm looking after our ecosystem of technology partners. And so we have from key strategic CE that we work with in the marketplace, in the cloud space on the data center, all across the ecosystem, a lot of different technologies. But we also have products that we resell input on our priceless that combined to create a solution for our customers in the second half of what my responsible is really focused on. What is our product strategy around integration? Automation? Because those Air Corps components to our platform and I look after that with several different teams. >> So let's talk about that the ecosystem pit person, the alliances. Because I got a lot of shows. I talked to a lot of companies, and it's all too easy for companies to be like, Oh, we're we're the best and we do so many different things. And when I first heard about the space in a ops, it's like, Oh, well, I I Ops is replacing a lot of waves and, you know, your average customer replaces fourteen tools. I heard there's one customer who replaces fifty tools, but at the same time, there was a strong focus about integrations in deeper even some of the products that you say, Yeah, there's overlap in that competitive, you know, you're working with those environments, so give us a little bit of the philosophy, how you balance that, you know, we want to do it all and help our customers to do lots of different things. And especially when you get to big customers and service providers, we understand that it's a big world and there never is that, you know, mythical single pane of glass. >> Yeah, no, totally agree. And we hear this a lot. You know, I've got a tool for this. I got a tool for that and or I had to Vendor come in and say that they could do it all. And you know, really, At the end of the day, if there's there's no one vendor on DH, you know the Venn diagrams of functionalities, air overlapping. That's the nature of the industry. And when we saw this on the early days of it with the big monopolies. But I think right now it's it's around. How do we saw the customer problem? Mohr effectively, From our perspective, we look at the combination of things. First is is what solutions out there give us good data data that we can use data that we can enrich, how we can leverage that to help drive better insights from other types of data that we collect so that theirs is where integration is a keep part of this on DH. What we know is that ultimately in our space, we're doing about monitoring a core collection. We're goingto have to click with everybody, so we're gonna have to integrate with any partner that might have some form of I. P are connected through an I p address to some sort of a p I. We need that data. So we have partnerships on that side. I think really, what's interesting is when we think about things like workflow or orchestration or types of mediation, we might integrate with other technologies to enrich that data further. So we look for partners that ultimately our customers air using things that we can do consolidation and drive better outcome with that enrich date experience. >> Yes, so let's drill down one little bit if you talk about like, you know a PM and SM tools out there some recent announcements and and you digging deeper on there. What what are some of the highlights? So one >> thing is, if you already have, like, agents are often come up, Our customs says, Well, I've got an A P M. Agent that's already doing some things. Well, that's great. We can leverage that, that there's some good insight that we can gather from either to apologies or other metrics or like in user experience. But we also go deeper on other aspects, like on the network side or on the infrastructure side, or on the the cloud service aside. So, you know, ultimately, it's a conversation of say, what? What can we leverage? What, what's accurate, what's in real time? And if there's things that we can, you know, gather, then that's our primary strategy. So I you know, I do think the ecosystem plays a key role in a i ops, but really, to do that, it's run automation because anything that we do, we have to do with scale and we have to do with security. We have to do it with the intent of driving some form of outcome. And so, you know, those are the key principles behind selecting technology partners. >> Okay, Let's talk some about that automation. It was a big discussion in the keynote this morning. Really talking about the maturity model. One of the analysts up there says you really want to make sure you separate things like, you know, the machine learning piece of it with the automation. The observation I've made a couple of times is, you know, yes. We all know you can automate a really bad process. And so I need toe, you know, make sure, you know, do I have good data And, you know, how am I making automation make me better Not just, you know, to change things. >> Yeah, well, I think it's Science Lodge that we look at. Automation is in every part of what we do within the product. From the from the collection of how we automate it scale how we consolidate that data. And then we're doing a lot of the data preparation using automation technologies. And then when we start to analyze and enrich that data, we're also using it Other algorithmic approaches, for example, topology and context. So if we know that some things connected weaken Dr An automation to make an inference and that data then feeds into the final step, which is around how we action on that. So we drive automation in the classic sense to say trigger workflow or, let's say, update another system of record or system of truth like a C M G B or a notification. And so one of things that we did hear from Garden this morning is engaging in an SM process. Is a core part of AI ai ops as muchas data collection and driving other forms of automation. >> All right, Do you have some examples of you know how automation you're helping your customers love any customer stories you've got along that line? >> Well, >> really. You know, there's so many stories we're hearing the halls of Symposium, and so it's it's it's hard to pick one, but, you know, I think all ten times what we say is, what what's driving your service desk time like you've got people you know, looking at all of these different dispirit systems, and we can look at it. Let's say a top end of your most sort of frequented events or alerts, or even look at your top service desk incidents and say, How could we automate that, you know. And some of that automation could be at the technology level, you know, simplest as restarting a service or prove you re provisioning of'Em. Or it could be clearing a log or even maybe shutting down an event because it's irrelevant. So there's There's several different examples in the cloud as well. Terms of how things air provisioning attached. And if we see something out of a policy, we can alarm that say, hey, maybe my storage costs are going to accelerate because someone made a bad change. So there's different ways that we can apply automation during the life cycle. But I think enhancing the service management component perhaps is one of the most impactful ones, >> you know. So, Eric, we azan industry automation been something we've been talking about for quite a while now, and they're they're sometimes pushback of, you know, from the end, users especially, you know, some of the practitioners out there as you know. Well, I could do it better. You know, the fear that you're going to lose your job. How are you seeing that progressing and you know, how were things different today? Both from a technology standpoint, as well as from your customers. Can't wait. >> I think if you asked any enterprise CIA already service provider, service delivery manager, they'd always say, I'd love to operate as much as I can when you get down on the practitioner level. You know, obviously I think there's some sort. Like I I do my job, Thank you very much. I have my favorite wit, my process. So I think there's a conversation depending on. You know, if we're saying hey from the practitioner side, is there set of data that you need or set of scripts? Or are things that you're doing manually that we can put into a workflow? And at the at the business layer, it's like, Do you feel like you're getting the value from some of the investments you've made? And is, how is automation? Help you realize that an example there is. We see oftentimes is around the quality of data that's going into the C, M. D. B and from AA AA. Lot of times we see that their investment in technology is like service now, and other platforms is fairly high expense, and they want to optimize that, and they want to realize the power of automation at the at the service level. So if we can, if we can convince, if you will, through a set of really concrete use cases that the data coming from science logic at the speed and the quality can actually improve the seemed to be to >> the level of >> really efficient automation. All of a sudden, people start to see that as a change as an opportunity. And that's where I think a I Ops is helping change the narrative, to say how automation Khun B really, really applied rather than just being this mystical concept that is hard to do. And, you know, people don't liketo think that a robot's taking their job. I think what's gonna happen is that machine learning algorithms are going to make jobs easier and, you know, ultimately were far, far from the point where a ized doing something and some sort of, you know, crazy automata way. But I think it's the deep learning, moving a machine learning to you. No good quality data sets that dr meaningful insights that's giving us a lot better view until where automation could play in the >> future. Yeah, absolutely. It's our belief that you know, automation. There's certain things that you probably don't want to do because repetitive, it's boring or mistake prone on DH. Therefore, you know automation can really help those environments move forward. You could move up the stack. You can manage those environment. There's definitely some retraining that that needs to happen often. But you know that the danger is if you're if you're doing now what you were doing five years ago, chances are your competition is moving along and, you know, finding a better way to do it. >> You know, just a point on this soup is really around the velocity of data that's coming in. So we're seeing, you know, we talked about the three bees. You know, the volume of data. You have to use automation to be able to manage that huge amount of different data sources, the variety. There's no human that can process the amount of machine information from the amount of technologies that you have on DH that you know. Obviously it's speed, right. The velocity and that is that is clearly not going to be something that any human could be capable of doing. And so there's a relationship here between technology and human processes and science logics and a really interesting position right now to really kind of help with that process. But more importantly, accelerate the value by being all to process it and make it intelligent. >> Wait, Erica, you're saying I'm not neo from the Matrix and I can't, you know, read through everything and be able to move faster than physics allows. Give >> yourself maybe fifteen, twenty years. We might be. You know that that you know, I don't think that that many people can really predict the impact of the you know, we'LL say machinery, evolving toe, artificial intelligence and there's it's going to be very used, case specific. But we do know one thing is that algorithms? Air helping. But algorithms are dependent on that clean data stack, right? And And if you can't handle the scale, then obviously there's going. It's going to be minimized in terms. Is total utility >> alright? Well, Eric, I get the good to let you give us that the final word from science logic from Symposium twenty nineteen on the Cube. >> So you know, the first thing is is this is there's two things that we learned from this event. The first thing is, is how our customers you're evolving in this dynamic space. And what we know is that if if you don't change, it's going to be a problem. Because the only consistent thing is change and change is happening faster on it. And we call that disruption. And so what we want to do is we want to understand how science AJ is a technology company. I can really help that customer go through that transition with confidence. And then, more importantly, is what could we do? Delivering better, more enrich solutions to our customers that actually are changing the way the game is played. And so we feel like we're a disrupter in the A ops market. We are. Certainly Forrester has helped us recognize that. But But we're not done work. We're continuing on this journey. >> All right, Well, Eric, routine. Thank you so much for sharing your insights and the journey towards Aye, Aye, Ops. Thanks so much to. All right. Well, that comes to an end of what we're doing here at science Logic. Symposium twenty nineteen. I know. I learned a lot. I hope you did too. I'm stew Minutemen. Thanks so much from our whole crew. Here it's Silicon Angle Media's The Cube. Check out the cube dot net for all the videos from this show, as well as where we'LL be in the future. Reach out if you have any questions and once again, thanks for joining us.

>> from Washington, D. C. It's the queue covering science logic. Symposium twenty nineteen. Brought to you by Science Logic >> Hi, I'm student men and this is the Cubes coverage of Science Logic. Symposium twenty nineteen here at the Ritz Carlton in Washington, D. C. First of all, want Welcome back to the program. Roger Putnam, Who's the vice president of Global Solutions? That science logic Thanks for coming back and what with programme A first time Rob Gruner listed is this loosened architect from Telstra. But >> Rob, I actually had >> a chance to talk to some of your co ords there, they said. Arav robs a wizard. He's an engineer that does everything. So you know, solutions. Architect. Of course, we know that they're out there. They do a lot of different things and asleep, leased. Your peers say you're somebody that does quite a lot of different >> things. Did Jack of All trades master of none unfortunate >> way? It's all right, don't you know it is in vogue now to be, you know, a generalist. It's, you know, we've gone from specialties to well, oh no, it's it's platforms and everything's going to be everything, so I have plenty of background with Telstra, but maybe talk a little bit about you know, your role in the organization and what what kind of things you're involved in. Since you know some of those trades that you >> are jack of all, >> probably our spies have come into Telstra's an acquisition. So, you know, working for small company, you tend to do everything on. For some reason, I've been allowed to continue to do that on developing expertise around science logic. And that means I've been involved across a lot of areas of the business as we've been adopting science logic more widely, and it's been quite interesting. Process means eye contact, that expertise and then see how it's applied across the organization. So it's been quite interesting, >> awesome. One of things that's been interested in me and in talking to service Friday is talking to the enterprise customers is two. You know how many tools they had, how many they replaced with science logic, but also what things it's integrating with and working with. It was a big focus on the keynote this morning is, you know, integrations with Sam and you know all these various pieces, so maybe give us a little bit of kind of the scope. You know how long's tells me you've been using science logic, How broads the deployment and you know what? What? What does it do in? What does it tie into >> a tte? The mammoth is more enterprise focused. So on. That's the area. Tell Stur I come from so it's really around delivering services to her customers. Quite recently, we've seen then looking in deploying science logic across their carriage spokes and managing services there. That's quite a large deployment. You know, we're quite happy with that in terms of what is going to be doing for the business on the integrations, their endless. So Telstra, like a lot of large organizations, has a lot of different systems to talk to. A lot of different service dis, depending on the operational areas. So in service now is one of those. But it's a hollow of other stuff on, so that's a very challenging process. And sounds objects being pretty good at, you know, spreading itself around. Those >> give us a little insight as to you know, how fast things are changing. You know, hear Kafka and Streams and, you know, constantly moving I've been looking at the, you know, communities and container stuff that's happening, which is which is fast moving. So >> are definitely say it. And Telstra's trying as hard as akin to move as quickly as the market can allowed. So definitely it's virtual izing. ITT's automating II ops is a big component of what we're doing. It is extremely important for the business. >> Okay, so Alps is something you're doing have to We're not as mature as we'd like to video. I'm not sure if you saw the keynote this morning, but they put out a maturity models So would love for you to, you know, where are you when you look at that? They kind of had the three criterias there is. There's kind of the the machine learning, there's the automation and I'm trying to remember the third piece that was there, but you know where where are you today? You know, how'd you get there? And you know what? What's what's a little bit of the road map going forward? >> I think it might be probably our ambitions to be in that the upper end of the spectrum and into remediation, But that's an ambition and I think we've got a while to go with that. So, uh, more than that, I can't coming off >> its interests. So they have that The keynote tomorrow they're going. Jean Kim speaking on the deaf ops. And, you know, I'm a big fan of the Phoenix project and they talked about, you know, the jack of all trades that does it all. He could sometimes be the bottleneck in the system. Absolutely. Because you can't be up. I need something fixed. Well, we'LL go to Rob Rob all fix it. That's great. That fire floating mode. I know I've done that in my career, and it's one of those things. Oh, jeez, you're never going to move at this job because you're replaceable. It's like that's a dangerous place to be. >> It is s >> o. You know, we talk a little bit about, you know, you said, you know, science logic. You know that they position themselves as this is going to help you move that, you know, machine speed and keep up with that. Give us a little bit the reality of what you're seeing. How what does that impact your job? Your organization? >> Look, I think sounds logic has done a wonderful job within the organization. It's it's the legacy infrastructure within any organization, particularly tells her scale. That's really holding you back on. There's a lot of Well, I think people level with Intel Street. Move as quickly as we can, but we have such a large number of legacy systems to deal with. You know, we're looking at one deployment of Sands object. We were looking at IDing systems to kill, So it's a big task >> the wonderful technical death that we've all inherited. So So you know, Roger, you know, this something we hear from all customers. It'd be lovely if I had the mythical, you know, unicorn that, you know, start from the ground up and you know, he can start afresh. But we always have to have that mix and give it a little bit about what you're seeing. You know, about the Telstra in a little bit broader, You know, >> I think what tell us she has done really well with taking advantage of our technology was they didn't come in with this attitude of would rip out everything that we have and just have a magic easy bun. Software doesn't work that way. I think we've all learned the lessons of tough deployments when you try to stay out of fix everything. So they came in with a really gradual, phased approach of Get a couple pieces done where they had gaps. You start to fill those gaps. What's happening during the last few years as we've seen the shift greater change and they've taken advantage of the platforms, nationalities a hole as they go through their digitization efforts. And so as they digitize, they taking this step by step by step approach to you know what you were saying earlier with Rob does. He doesn't answer the question of being the one man band, but they did was they build it all process wise, using software to drive the automation. So once it's done one time, you're not stuck on the person anymore. And so I think when we look at our most successful customers like Telstra, it's because they've had this gradual, phased approach where they're using software rather than single person bottlenecks. And rather than having these tiger teams to try to solve problems and moving towards a better process to take advantage of the world, we're in today. So how >> do you measure success? You know, what are some of the business outcomes or, you know, k p I's that you understand how you're moving from kind of where you were to where you want to be. >> Uh, that's a difficult one to answer because particularly sounds, logic was used in so many different context. So for a certain part of the business, we might say, Are we monitoring the full stack? I were giving customers real value invisibility through the whole dynamic of the business. And then, in another context, we using sound subject. We were just saying, We just need to deploy its scale. We need two one board as quickly as possible. We need to keep the cost down to a minimum. We need to keep events that's allow as possible. Okay, so it's more about the efficiency argument, so it's really depends and way we're trying to use it and how we're deploying it. So >> how do you have visibility across how everybody is doing and getting trained on the latest things and keeping up to date and sharing best practices? How do you manage that internally, and how do you how do you do you network with your peers on some of that? >> Well, we've tried Teo really within. Tell us we have a concept of centre of excellence. So it's really about, you know, being recognizes the business experts in particular area and allowing the business to understand. That's that. That's where the expertise sits on a certain we've done a very good job with that and then allowing and communicating that after the business as well. So it's a very tough asked. It's a big business. We have thirty thousand people so often one person doesn't know about another person, another floor on the buildings, you know, to try and spread it across the biz, since we have fifty officers worldwide. So it's a process, you >> know? I mean, Roger just want one of things that here is, you know, science logic. It's not a widget, and it's, you know, can fit in a lot of different environments and a lot of different uses. You know, I heard of, you know, strong emphasis in into training had your CEO on where in his wizard tat for for for the that the learning knowledge that was gonna happen. So you know you talk a little bit about how science logic is looking to address this, especially for some you know, large customers like Telstra. >> You know, I think there's a general skills gap in is a whole beyond our technology beyond what's taking place in the world today. And you know, I've been in the business for quite a while, and we've long focused on training the operator on how to utilize the technology to solve their specific problems. And while that those aspects really powerful, some of the things we've done recently to go a step further is when we hear similar questions. We started record all of those so our customers could watch videos of how to solve problems instead of just going onto some form and let me type some question and hope somebody responds to in the future. You have read it for that. So we've got a look at a better mechanism and video based training handheld handling the customers we can build out these use cases drives the platform value, and what Telstra does it's really unique is they use the platform less so from a perspective of can I manage X y Z technology. But what can I build on top of it? How can I break the platform to some extend? And Rob is a mad scientist for us here. I mean, could jump into this more. But they've broken the platform to solve those business needs by addressing them individually. And what we've done is we've taken his best practices, and we rolled them back out to the rest of our customers. So with Robin, tell Hsia and a couple of other really great customers were driving a better community and sense of community so less question, answer form, less traditional support, more video, more community, more share ability. And that's where you're going to get additional quality. Coming out from the products are being delivered. Makes sense to you, Robert. Absolutely. >> Yeah, Rob. I mean, I love any commentary on that. You know, the network effect of software especially would talk about Sasser as a service type things, you know, that's what sales force really came out. It was like a weight one customer. Ask for something and wake everybody. You can take advantage of that or something similar. So are you seeing that kind of dynamics today with science logic and with others >> well, perfectly within the Telstra business. Absolutely so by building a capital into one area, you can share it across. And we found that we've been able to then sell the system internally, your internal stakeholders, so they appreciate the value of it and we can build on that. And then our customers, whilst we don't necessarily lady with the product they can. They see what's going on, and they basically then take it on as a service as well. So it's very, very interesting process. >> So one thing we haven't talked about yet, but you talk about data, you know, what's the role of data in your environment is something that you know key to the platform from science logic. How you leveraging it? How's that changing in your environment? One of the opportunities there. >> It's interesting questions. So as the telco, we collect a lot of data on DA. Obviously we have federal agencies who make that a requirement as well. So we have an existing data like initiative on that's very full of moment, and science logic is where we're looking at how we can add to that the value, valuable information and provides, but like everyone else, is a lot of data to collect, and it's an interesting process to try and make sense out of it and react accordingly. I mean, as a business, we were responding to millions and millions events of a day. So it's, you know, it's a difficult thing. >> Yeah, one of things. When we look at things like you know, anything that requires training like machine learning or the like, There's the balance between I want to learn from everybody. But you know, you're in a competitive marketplace. I don't want my competitors necessarily to get things. So you know the software products usually Well, I can isolate, and it doesn't have specific information. But how do you look at that dynamic of making sure that you gain from what the industry is doing, but that, you know, you could still stay competitive in ahead of your competition? >> Uh, >> no. I don't have a necessary can answer that. I suppose my head's tied into really what I could do with a platform and how I can then bring new technologies into the company's. So that's really are spies remind spaces on, Really, it's what I'm focused on. So you know what we do with the daughter probably is. He's not necessarily big concerns. How >> about that? There was quite a lot of announcements this week. The number of integrations as well as you know, update to the product. Anything specifically that you've been waiting for or that has caught your eye, >> the service now integration. I think it is far more advanced than has been in the past. On we have aspect of the business used thinks over quite heavily. So the fact that that's now matured and much more robust and you know which sort of offering that'LL have a lot of impact on the business. So I definitely mean the machine learning is another great thing on the question of then how that develops over time. So we'LL see how that goes. You >> know, Roger loves you know what? When I've been digging into some is the feedback you've been getting from customers and what's been leading toe, you know, some of the enhancement. So I would love, love your take on what you're saying. >> You know, I think one of the things that tell Sharpe pushed us towards a few years back was we're going to build. We already have a data like we don't need you to function. Is there Data Lake? So its multiple different Veda lakes And this concept of how do I move later From one day to lake to a different data Lake lakes within lakes ponds. Whatever the terminology is today the data ocean, our family perfect. And I'm getting to that data ocean from our lake. We have to go get streaming data. So now I'm going to extremes against really geographic here. But, you know, Rob really pushed us to make sure we could go right to Kaka buses and pushed data out. So what do you do with the data? And so tell Strip has been a, you know, an early adopter of a lot of our technology. And by being an early adopter, they've pushed us in a number of directions. So I think when you see a lot of the functionality that we've released this week and we've announced, it's been because of our customer base because of our partners like Telstra, that need to drive the business for further and forward, especially the industry like Telco World, where everything is mobile everything's moving so fast and aggressively. They're really like a good sounding board for where we need to go and how do we get there and and that drive And that partnership is What I think I'm most excited about working with tell sure is they demand from us to be excellent, and that gets great product coming out. And we see the results this week with all of our customers excitingly looking at stream treating capability that Rob was pushing us for well in advance of anyone else. >> Yeah, Robin, I want to give you the final word. You know, I can't help but notice you actually co branded shirts you've got tell star on your arm wither with science logic there. So, obviously, more than just a vendor relationship there, maybe close us out with you know how important science logic is. Two to your business >> job, Critical part of the business. I mean, particularly where we're looking at the commodity aspect of many services, you know, we can't survive unless we can provide quality, invaluable information where customers and really sounds. Logic has been the key platform for that. So in some respects, we're resting, you know, an aspect of the business entirely and Scientology's hands and we're hoping they'LL deliver >> well, Robin Raj, Thank you so much for joining us. Just sharing all the progress that you've made in. You know where things were going? Thanks so much, thanks to all right. And I'm student men. This is the Cube at Science Logic Symposium twenty nineteen. Thanks for watching.

>> From Washington D.C. it's theCUBE covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> Hi, I'm Stu Miniman and this is theCUBE's coverage of ScienceLogic Symposium 2019 here at The Ritz-Carlton in Washington D.C. About 460 people here, the events' grown about 50%, been digging in with a lot of the practitioners, the technical people as well as some of the partners. And for this session I'm happy to welcome to the program for the first time guest, Surendra who is the vice president and CTO for automation in IBM's global technology services. And joining us also is Dave Link who is the co-founder and CEO of ScienceLogic. Gentlemen, thank you so much for joining us. >> Thank you for having us. >> Thanks for having us. >> Alright, so Surendra let's start with you. Anybody that knows IBM services at the core of your business, primary driver, large number of the presented to the employees at IBM are there. You've got automation in your title so, let's flush out a little bit for us, your part of the organization and your role there. >> Alright, so as you pointed out, IBM, a big part of IBM is services; it's a large component. And that two major parts of that and though we come together as one in terms of IBM services, one is much more focused on infrastructure services and the other one on business services. So, the automation I'm dealing with primarily is in the infrastructure services area which means all the way from resources you have in a persons data center going into now much more of course in a hybrid environment, hybrid multi-cloud, with different clouds out there including our own and providing the automation around that. And when we mean automation we mean the things that we have to do to keep our clients' environments healthy from a availability and performance standpoint; making sure that our environment then we respond to the changes that they need to the environment because it obviously evolves over time, we do that effectively and correctly and certainly another very important part is to make sure that they're secure and compliant. So, if you think of Maslow's hierarchy of the things that IT operations has to do that in a nutshell sums it up. That's what we do for our clients. >> Yeah, so Dave luckily we've got a one on one with you today to dig out lots of nuggets from the kino and talk a bit about the company but, you talk about IT operations and one of the pieces I've got infrastructure, I've got applications, ScienceLogic sits at an interesting place in this heterogeneous ever-changing world that we live in today. >> It does and the world's changing quickly because the clouds transforming the way people build applications. And that is causing a lot of applications to be refactored to take advantage of some of these technologies. The especially focused global scale we've seen them, we've used them, applications that we use on our phone. They require a different footprint and that requires then a different set of tools to manage an application that lives in the cloud and it also might live in a multi-cloud environment with some data coming from private clouds that populate information on public clouds. What we found is the tools industry is at a bit of a crossroads because the applications now need to be infrastructure aware, but the infrastructure could be served from a lot of different places, meaning they've got lots of data sources to sort together and contextualize to understand how they relate to one another real time. And that's the challenge that we've been focused on solving for our customers. >> Alright, Surendra I want to know if we can get a little bit more to automation and we talk automation, >> There's also IBM use for a number of years, the cognitive and there was the analyst that spoke in the kino this morning. He put cognitive as this overarching umbrella and underneath that you had the AI and underneath that you had that machine learning and deep learning pieces there. Can you help tease out a little bit for IBM global services in your customers? How do they think of the relationship between the MLAI cognitive piece in automation? >> So I think the way you laid it out, the way it was talked about this morning absolutely makes sense, so cognitive is a broad definition and then within that of course AI and the different techniques within AI, machine learning being one, natural language processing, national languages understanding which not as much statistically driven as being another type of AI. And we use all of these techniques to make our automation smarter. So, often times when we're trying to automate something, there can be very prescriptive type of automation, say a particular event comes in and then you take a response to it. But then often times you have situations where you have events especially what Dave was talking about; when an application is distributed not just a classic of distributed application, but now distributed of infrastructure you may have. Some of it may be running on the main frame, some of it actually running in different clouds. And all of this comes together, you have events and signals coming from all of this and trying to reason over where a problem may be originating from because now you have a slow performance. What's the reason for the slow performance? Trying to do some degree of root cause determination, problem determination; that's where some of the smarts comes in in terms of how we actually want to be able to diagnose a problem and then actually kick off maybe more diagnostics and eventually kick off actions to automatically fix that or give the practitioner the ability to fix that in a effective fashion. So that's one place. The other areas that one type of machine learning I shouldn't say one type, but deadly machine learning techniques lend themselves to that. There's another arena of causes a lot of knowledge and information buried in tickets and knowledge documents and things like that. And to be able to extract from that, the things that are most meaningful and that's where the natural language understanding comes in and now you marry that with the information that's coming from machines, which is far more contextualized. And to be able to reason over these two together and be able to make decisions, so that's where the automation. >> Wonder if we can actually, let's some of those terms I want to up level a little bit. I hear knowledge I hear information; the core of everything that people are doing these today, it's data. And what I heard, and was really illuminated to me listening to what I've seen of ScienceLogic is that data collection and leveraging and unlocking value of data is such an important piece of what they're doing. From an IBM standpoint and your customers, where does data fit into that whole discussion? How do things like ScienceLogic fit in the overall portfolio of solutions that you're helping customers through either manager, deploying and services? >> So definitely in the IT Ops arena, a big part of IT Ops, at the heart of it really is monitoring and keeping track of systems. So, all sets of systems throw off a lot of data whether it's log data, real time performance data, events that are happening, monitoring of the performance of the application and that's tons and tons of data. And that's where a platform like ScienceLogic comes in, as a monitoring system with capabilities to do what we call also event management. And in the old days, actually probably would have thought about monitoring event management and logs as somewhat different things; these worlds are collapsing together a bit more. And so this is where ScienceLogic has a platform that lends itself to a marriage of these faces in that sense. And then that would feed a downstream automation system of informing it what actions to take. Dave, thoughts on that? >> Dave, if you want to comment on that I've got some follow ups too, but. >> Yeah, there's many areas of automation. There's layers of automation and I think Surendra's worked with customers over a story career to help them through the different layered cakes of automation. You have automation related to provisioning systems, the provision and in some case provision based on capacity analytics. There's automation based on analysis of a root cause and then once you know it, conducting other layers of automation to augment the root cause with other insights so that when you send up a case or a ticket, it's not just the event but other information that somebody would have to go and do, after they get the event to figure out what's going on. So you do that at time of event that's another automation layer and then the final automation layer, is if you know predictively about how to solve the problem just going ahead if you have 99% confidence that you can solve it based on these use case conditions just solve it. So when you look at the different layers of automation, ScienceLogic is in some cases a data engine, to get accurate clean data to make the right decisions. In other cases, we'll kick off automations in other tools. In some cases we'll automate into ecosystem platforms whether it's a ticketing system, a service desk system, a notifications systems, that augment our platform. So, all those layers really have to work together real time to create service assurance that IBM's customers expect. They expect perfection they expect that excellence the brand that IBM presents means it just works. And so you got to have the right tooling in place and the right automation layers to deliver that kind of service quality. >> Yeah, Dave I actually been, one of the things that really impressed me is that the balance between on the one hand, we've talked to customers that take many many tools and replace it with ScienceLogic. But, we understand that there is no one single pane of glass or one tool to rule them all, the theme of the shows; you get the superheros together because it takes a team. You give a little bit of a history lesson which resonated me. I remember SNMP was going to solve everything for us, right? But, the lot of focus on all the integrations that works, so if you've got your APM tools, your ITSM tools or things you're doing in the cloud. It's the API economy today, so balancing that you want to provide the solutions for your customers, but you're going to work with many of the things that they have; it's been an interesting balance to watch. >> Yeah, I think that's the one thing we've realized over the years; you can't rip and replace years and years of work that's been done for good reason. I did hear today that one of our new customers is replacing a record 51 tools with our product. But a lot of these might be shadow IT tools that they've built on top of special instrumentation they might have for a specific use cases or applications or a reason that a subject matter expert would apply another tool, another automation. So, the thing that we've realized is that you've got to pull data from so many sources today to get machine learning, artificial intelligence is only as good as the data that it's making those decisions upon. >> Absolutely. >> So you've got to pull data from many different sources, understand how they relate to one another and then make the right recommendations so that you get that smooth service assurance that everybody's shooting for. And in a time where systems are ephemeral where they're coming and going and moving around a lot, that's compounding the challenge that operations has not just in all the different technologies that make up the service; where those technologies are being delivered from, but the data sources that need to be mashed together in a common format to make intelligent decisions and that's really the problem we've been tackling. >> Alright, Surendra I wonder if you can bring us inside your, you talked to a lot of enterprise customers and it helped share their voices to in this space, not sure if they're probably not calling it AI ops there, but some of the big challenges that they're facing where you're helping them to meet those challenges and where ScienceLogic fits in. >> So certainly the, yes, they probably don't want to talk about it that. They want to make sure that their applications are always up and performing the way they expect them to be and at the same time, being responsive to changes because they need to respond to their business demands where the applications and what they have out there continually has to evolve, but at the same time be very available. So, all the way from even if you think about something that is traditional and is batch jobs which they have large processing of batch jobs; sometimes those things slow down and because now they're running through multiple systems and trying to understand the precedence and actions you take when a batch job is not running properly; as just one example, right? Then what actions we want, first diagnosing why it's not working well. Is it because some upstream system is not providing it the data it needs? Is it clogged up because it's waiting on instructions from some downstream system? And then how do you recover from this? Do you stop the thing? Just kill it or do you have to then understand what downstream further subsequent batch jobs needs to or other jobs will be impacted because you killed this one? And all of that planning needs to be done in some fashion and the actions taken such that if we have to take an action because something has failed, we take the right kind of action. So that's one type of thing where it matters for clients. Certainly, performance is one that matters a lot and even on the most modern of applications because it may be an application that's entirely sitting on the cloud, but it's using five or 10 different SAS providers. Understanding which of those interactions may be causing a performance issue is a challenge because you need to be able to diagnose that and take some actions against that. Maybe it's a log in or the IDN management service that you getting from somewhere else and understanding if they have any issues and whether that provider is providing the right kind of monitoring or information about their system such that you can reason over it and understand; okay my service which is dependent on this other service is actually being impacted. And all these kind of things, it's a lot of data and these need to come together. That's where the platform something like ScienceLogic would come into play. And then taking actions on top of that is now where a platform also starts to matter because you start to develop different types of what we call content. So we distinguish the space between an automation platform or a framework plus and the content you need to have that. And ScienceLogic they talk about power packs and these things you need to have that essentially call out the work flows of the kind of actions you need to take when you have the falling signature of a certain bundle of events that have come together. Can you reason over it to say okay, this is what I need to do? And that's where a lot of our focus is to make sure that we have the right content to make sure that our clients applications stay healthy. Did that get to, I think build on what you were talking about a bit? >> Absolutely. Yes, you've got, it's this confluence of a know how an intelligence from working with customers, solving problems for them and being proactive against the applications that really run their business; and that means you're constantly adjusting. These networks I think Surendra's said it before, they're like living organisms. Based on load, based on so many factors; they're not stagnant, they're changing all the time, unless you need the right tools to understand not just anomaly's what's different, but the new technologies that come in to augmenting solutions and enhancing them and how that effects the whole service delivery cadence. >> Mr. Surendra, I want to give you the final word. One of the things I found heartening when I look at this big wave of AI that's been coming is, there's been good focus on what kind of business outcomes customers are having. >> Okay. >> Because back in the big data wave I remember we did the survey's and it was like what was the most common use case? And it was custom. And what you don't want to have is a science project, right? >> Right. >> Yes. >> You actually want to get things done. So any kinds you can give as to, I know you understand we're still early in a lot of these deployments and rollouts but what do you seeing out there? What are some of the lighthouse use cases? >> So, certainly for us, right? We've been at using data for a while now to improve the service assurance for our clients and I'll be talking about this tomorrow, but one of the things we have done is we found that now in terms of the events and incidents that we deal with, we can automatically respond with essentially no human interference or involvement I should say about 55% of them. And a lot of this is because we have an engine behind it where we get data from multiple different sources. So, monitoring event data, configuration data of the systems that matter, tickets; not just incident tickets but change tickets and all of these things and a lot of that's unstructured information and you essentially make decisions over this and say okay, I know I have seen this kind of event before in these other situations and I can identify an automation whether it's a power pack, an automotor, an Ansible module, playbook. that has worked in the situation before in another client and these two situations are similar enough such that I can now say with these kind of events coming in, or group events I can respond to it in this particular fashion; that's how we keep pushing the envelope in terms of driving more and more automation and automated response such that the I would say certainly the easy or the trivial kinds of I shouldn't say trivial, but the easy kinds of events and monitoring things we see in monitoring are being taken care of even the more somewhat moderate ones where file systems are filling out for some unknown reasons we know how to act on them. Some services are going down in some strange ways we know how to act on them to getting to even more complex things like the batch job type of thing. Example I gave you because those can be some really pernicious things can be happening in a broad network and we have to be able to diagnose that problem, hopefully with smarts to be able to fix that. And into this we bring in lots of different techniques. When you have the incident tickets, change tickets and all of that, that's unstructured information; we need to reason over that using natural language understanding to pick out the right I'm getting a bit technical here, verp no pas that matter that say okay this probably led to these kind of incidents downstream from typical changes. In another client in a similar environment. Can we see that? And can we then do something proactively in this case. So those are all the different places that we're bringing in AI, call it whatever you want, AIML into a very practical environment of improving certainly how we respond to the incidents that we have in our clients environments. Understanding when I talked about the next level changes when people are making changes to systems, understanding the risks associated with that change; based on all the learning that we have because we are very large service provider with essentially, approximately 1,000 clients. We get learning over a very diverse and heterogeneous experience and we reason over that to understand okay, how risky is this change? And all the way into the compliance arena, understanding how much risk there is in the environment that our clients facing because they're not keeping up with patches or configurations for security parameters that are not as optimal as they could be. >> Alright, well Surendra we really appreciate you sharing a glimpse into some of your customers and the opportunities that they're facing. >> Thank you. >> Thanks so much for joining us. Alright and Dave, we'll be talking to you a little bit more later. >> Great, thanks for having me. >> All right. >> Thank you. >> And thank you as always for watching. I'm Stu Miniman and thanks for watching theCUBE. >> Thank you Dave. >> Thank you. (upbeat techno music)

(upbeat music) >> From Washington D.C. it's theCUBE. Covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> I'm Stu Miniman and you're watching theCUBE's exclusive coverage of ScienceLogic Symposium 2019 here at the Ritz-Carlton in Washington D.C. Happy to welcome to the program a first time guest off the keynote stage this morning Bailey Szeto who is the Vice President of Customer and Seller Experience IT at Cisco. Thanks for coming and joining us. >> My pleasure. >> All right so Bailey, I've actually, you know I've watched, and partnered, and worked with Cisco my entire career but you actually changed my view of something about Cisco in your keynote this morning. And that's, you know, you said that 99% of Cisco's 50 billion dollars plus is transacted online so I should be thinking of you more as like Amazon.com you know, than as, you know the networking giant I've know my entire career. >> Well You know it's certainly true that most of our revenue comes through our online presence but it's perhaps in a different manner than what you're thinking right? So obviously we do do some business direct and we might have some stragglers selling, buying something with a credit card, but that's not the bulk of our business. The bulk of our business is through primarily partners, resellers and when I say online I meant B to B transactions. >> No no. I totally understand Bailey and what I love is you're in Cisco IT. >> That's right. >> And therefore we're not going to talk about a lot of the networking pieces. We're going to talk about what runs Cisco's business and you have the pieces and you know client success and support and all those run, and even, I didn't even realize the employee engagement all runs through you know Cisco.com >> That's right. >> And I love you did a nice little video. Gave all of those that have been in the industry. You kind of go through and look at the history of like oh okay there's the HTML stuff I used to code. >> That's right, that's right. >> Back in the 90s through all of the updates and yeah we definitely-- >> I was just expecting the little triangle with the guy like shoveling dirt under construction. You know the shovel right? >> Yeah the 404 not found. >> That's right, that's right. >> I know if I go to Cisco.com/go/product name that usually was a short cut to get me to some of the things I care about but for those people who weren't here for the key note or who might not know as much give us a little bit about you know your purview and kind of the scale and scope of what you do. >> Yeah so at Cisco I'm in Cisco IT. But I'm responsible for supporting all of the revenue generation portions of the company. So that's specifically marketing and what they do, sales and what sales does. Cisco services is a very big part of our company so I support the services organization. And most recently Cisco's been on a journey to really kind of move from a once and done hardware sales motion to a full reoccurring revenue type of stream. So we've stood up the whole customer success motion. And so I run the IT portions of that as well. And last but not least you heard me mention that 85% of our revenue actually comes through our partners. So I support all the systems that are partners interact with as well. >> Yeah it's interesting so we've done theCUBE at Cisco Live the last two years. >> Sure. >> And there's a observation I made a year ago when I started going to that show. And it was you know, if I'm a networking person but this applies to you know most people in IT, I used to manage stuff I could touch and go, I understand where it is and how I touch it and everything. Now a lot of what I have to deal with is outside of my purview and therefore I need to get into that environment kind of pair that with you know companies like yourself that are inquisitive. And so you have lots of change going on and lots of things that are in your environment there so we know change is the only constant in our industry. >> Without a doubt. >> So maybe give us a little bit of those dynamics and how that impact what's happening in your world. >> Yeah so I mean we talked a bit about my responsibilities and one of this is Cisco.com It's probably one of the more important platforms that I'm responsible for from an IT perspective. But I also mentioned that Cisco's a very, we grow through acquisitions a lot. It's one of our basic business strategies. And so every time we buy a company it's a big rush to kind of take that acquired company and integrate their online presence into Cisco.com right? So once a company is acquired we don't want people to think of it as a separate company both from a kind of marketing perspective but more importantly we're actually integrating that product into our Cisco ecosystem as well. So just having to move all that technology into Cisco.com is certainly a big job. But I think you are maybe asking this from a different perspective as well which is to say okay you know new technology is being introduced all the time and while it makes sense from a company portfolio perspective I think as a former IT person you're going to agree with me it makes our jobs a little bit more difficult. It's both a blessing and a curse right? From the perspective it's a blessing in that we get this great new technology to incorporate and use in our running of the business but it also adds a lot of complexity and so it's pretty important that we have both the systems and processes to be able to manage all that complexity in our infrastructure really. >> All right so infrastructure monitoring. >> Yes. >> Something you spent a lot of time talking about. I guess I'll set it up when I talked to my friends in the networking space these days or a lot of it, the joke is if you say single pane of glass they are going to spell it P-A-I-N because we understand that there's not one tool to rule them all. >> Right. >> Yes that I might have a primary piece but in the virtualization world I had to plug in to V Center and you know Cisco has you know you laid out a broad portfolio of various tools up and down and across the stack from you know security down to physical and upper layer and plus all the acquisitions. So can you lay out a little bit as to you know where ScienceLogic fits and there's a number of Cisco's tooling that that integrates in with. >> Yeah so when I talked about our journey with ScienceLogic you know Cisco of course has a number of tool and capabilities to take care of the pieces that we are known for. For example Application Dynamics is a great company that we bought and provides great insight into application health. But obviously in a network perspective right we have Cloud Management software, security software that type of thing and so I think what we realized in Cisco IT what my team realized is that it really isn't about a single system to rule them all it's about trying to find multiple platforms that can work together and really share data so as to drive richer insights. And so I think maybe the industry has been on a bit of a wrong path think it's you know it's not Lord of The Rings, one ring to rule them all or whatever right? It's about being able to use multiple applications but having the right data insides move around as needed so that depending on your lens or your role in IT whether you're a network guy or an application guy that you're going to use the tool that's more most natural to yourself but pulling in the right amount of data from those other parts to be able to get the right insight. >> Yeah I saw your closing slide mirrored the theme we've seen at the show of superheroes. So the super power everybody needs in IT today is how do I leverage my data and we understand that it probably takes more like the Avengers to be able to put those together because data is everywhere. >> Yeah the funny thing is that that wasn't actually a set theme. I think we must all have Avengers on our mind because everyone independently came up with the super hero concept. >> Yeah no spoilers on End Game either way though. >> That's right, that's right. >> Excellent so you know can you just bring us inside of some of that ScienceLogic journey? My understanding you're probably the largest enterprised employment of it so you know we always love to talk about scale and what that means and how it's been in your viewpoint. >> Yeah you know we actually before ScienceLogic we actually had our own system that Cisco IT wrote right and so you know as IT professionals we always think we can do it better than anyone else but we've reached a point where just so much technology and so much complexity came to the market that we really wanted to find a solution that would really kind of enable us to grow into the future with all the things that are happening right whether you're talking about Virtualization with Containers or you know Cloud native applications or Multicloud, these are all technology trends that have made our jobs in IT incredibly complex. And so we started to look for what could we replace our home grown monitoring platform with and ultimately we decided that ScienceLogic was the best fit for us. And since we've deployed it we as with most things we tend to stretch the scale especially with our vendors and so I think we are the largest ScienceLogic enterprise customer at this point. But we are seeing incredible benefits in terms of being able to connect ScienceLogic's Infrastructure Monitoring with our own Application Dynamics and really marry the two for those insightful bits that we get from both. >> All right so one of the big themed discussion here is that journey toward AI Ops. >> Yes. >> While we speak actually I've got a team in Mountainview that is at the DevNet Create Show which Cisco helped organize. >> Sure. >> We're doing two days of interviews there and DevSecOps is probably one of the key topics their going to be talking about. In your keynote this morning I heard IT Ops in a discussion there so bring us inside a little bit organizationally you know what you're seeing you know your viewpoint on these various trends that are you know helping to modernize you know transform operations. >> Yeah I think from a operations organization standpoint you're going to see the applications team and the infrastructure team work even closer together. Maybe one of the things that didn't really make super clear in my keynote this morning is I actually work on kind of the app side of the house right? I'm the direct interface to the business. And as such I actually don't interface with ScienceLogic directly but I'm a strong partner with my infrastructure team who are I think they are all sitting over there that do run ScienceLogic right and so in today's world you really can't just say oh this is infa problem they are going to deal with it. Because of that really big mix of well is it an infrastructure problem, is it an application health problem? And a lot of times it's both. And so organizationally it might be two separate organizations but the need to work together is you know even greater today than ever before. >> You're preaching to the choir. I mean when we launched Virtualization and then later when Containers came around there was the nirvana that oh I'm going to have some unit of infrastructure where the application people just don't need to worry about it. >> Right. >> You know serverless from it's name seems to imply that but we understand that eventually you know there's networking, there's storage, there's compute all underneath these kind of things. >> That's right. >> It's just repackaging so you know the applications important you know I'm long time infrastructure guy. >> That's right >> But, the number one rule is the reason we are here is to run that application and make sure your data you know gets where it needs to be otherwise you know we're not here just to power things. >> That's right. And I just realized I probably would get in trouble if I said it's actually the application, infrastructure, and of course the network all has to work together. >> Yeah well that's a given. Can you just we talked a little bit about App Dynamics you know when I think about Cisco you know broad portfolio, you know the SD-WAN, the ACI how do some of those fit into this discussion are there tie ins with what ScienceLogic is doing? >> It absolutely does. So as I talked about it when we talked about that collection of super heroes it's not a single super hero it's not a duo either it's really a big team. It's The Avengers right? And so when you think about Cisco's portfolio we have a lot of additional components needed to provide that modern operating IT operating platform right? So we talked about a lot about Application Dynamics we talked about ScienceLogic but what Cisco brings to the mix is things like ACI, Tetration, Policy Enforcement, Multicloud Management. So all those things again have to work together like The Avengers do to provide that modern platform. >> Yeah you mentioned multicloud and I know in your keynote you talked about AWS and GCP. >> That's right. >> How's Cloud changing things in your world? >> It absolutely is again it's I'll go back to the it's both a blessing and a curse right? The blessing is enormous capability that we get from the Cloud, enormous flexibility. As and example using Cisco.com as an example we host a lot of you know a lot of public information about our products and websites and data sheets and that type of thing on Cisco.com. And then a couple years ago we decided we're going to refresh the engagement of Cisco.com We wanted to make it much more personalized. We wanted to incorporate video. Those are all great things but the moment you try to throw video and guess what? Native video whether it be in English or French or Chinese or Japanese depending on where you are well that put an enormous strain on our infrastructure and if you had to travel if the packets had to travel from Japan to the United States to our data center that would slow things down. So we took advantage of Public Cloud to really kind of push out the content to the edges so that we could get localized content as close to the customer as possible. That's the great thing about it. But again the management of that increasing complexity right so both a blessing and a curse. AWS, GCP, we are using for doing a lot of video streaming work. And so again great capabilities from that platform as well. >> All right so we saw this week a lot of announcements of some of the integrations Service Now and App Dynamics were two of the ones that highlighted that I think impacted you. Anything from the announcements that is particularly excited you and I guess final on that is there anything roadmap wise that you know you'd be looking directionally for this phase to evolve towards? >> Yeah I think I was excited to see in fact that's one of the main reasons why we chose ScienceLogic in the first place was the quality and the amount of integrations that they have right? And so we're also a big Service Now customer and we see the benefits of automatically open cases in Service Now when ScienceLogic detects an issue as an example right? And I would say going forward we'll be looking to either have out of the box or if needed you know Cisco IT will build something even more integrations with the Cisco products. We already have App Dynamics but as I mentioned we have a lot of other components that are critical to the network and so we'll be looking for tighter integration and all this to drive really drive data together so that we can get to what I think what most people at this conference are hoping to achieve which is really driving towards automation and AI Ops right? So that's really the desire for I think for everyone attending this conference. It's certainly our desire in Cisco IT. And you know I'm looking forward to working with ScienceLogic to building out that roadmap. >> You know so I guess final question for you you talked about that automation, where are you when it comes to we look at you know things like machine learning and automation which if you listen to the analyst that spoke this morning is like you want to make sure you separate those things. >> That's right. >> We understand you know any of us that have done process and operations is you know you can automate a really bad process and it's not a good thing. >> That's right, that's right. >> So where are you on that journey? What do you see? You know what are the barriers that keep us from kind of the nirvana where you know oh geez I can actually just seal off the data center and let everything run? >> Right I think it's funny you mentioned Cisco Live so actually I present on a topic of AI at Cisco Live as well. So what this other speaker talked about really hit home with me understanding what is AI really. Because I think there's a general perception in the press that it's like this magical fairy dust you can just sprinkle on everything and it like makes everything perfect right? AI is really good at pattern recognition but you still need to put some check points and really have human beings kind of check the work of AI right? And so you know we actually have seen data center outages not Cisco but in the press when AI runs amok right? And so I think the first step of automation that's a given. We want to do that but that involves a lot of human beings kind of looking at the data and deciding okay these sequence of events can be cured by this set of automation. AI Ops is a something that's a whole different thing if you followed the definition of AI to say okay let the computer do it all on its own. I don't think we're there yet. I think we have a ways to go. And I certainly wouldn't trust want to trust our you know multi billion dollar business to AI Ops at this point in time. >> Well Bailey there's an event we did a couple years ago with a couple professors from MIT that are really forward looking on this and they say it's racing with the machines because people plus machines will always do better >> Yes. >> Than people alone or machines alone and hopefully that keeps some of us that are a little bit worried about the Skynets of the world taking over from getting a little bit too paranoid all of a sudden. >> I totally agree with that statement. In fact the quote that jumps in my head is "Better together". And I'll close with ScienceLogic App Dynamics better together. People AI better together. >> All right well Bailey since you ended on a perfect quote there thank you so much for joining and I hope to see you at Cisco Live San Diego. >> Fantastic, my pleasure. >> All right and thank you so much for watching theCUBE as always, I'm Stu Miniman here at ScienceLogic 2019 in Washington D.C. (upbeat music)

(upbeat music) >> From Washington, DC, it's theCUBE, covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> I'm Stu Miniman, and this is theCUBE's coverage of ScienceLogic Symposium 2019, here at the Ritz-Carlton, in Washington, DC. Have about 460 people, it's a good mix of enterprise users, of course there's government agencies, as well as a lot of service providers, which is really where ScienceLogic started and has, many of their customers are in that space. And happy to welcome to the program, coming to us from Europe, a first time guest on the program, Luc Horee, who's RCloud and innovation Manager at Realdolmen, who's, as I said, a service provider. Thanks so much for joining me. >> Thank you, no problem. >> So, you're based in Belgium, you're a service provider, tell us a little bit about Realdolmen, a little bit about the size, scope, number of users, and we'll take it from there. >> Realdolmen is an Belgium company, around 1,500 people in an country that is small compared to the U.S. So we have an total of 11 million people. One of the biggest service providers in Belgium, but we also do reselling, and we also do service integration. Our customers it's Belgium, it's what we call SMB market. But we have around, in total, I think three thousand customers in Belgium. Some only are buying products or licenses, others are in fact in full manage service operations. >> Okay great, yeah, the SMB market, as you call it, we understand, especially for service providers, really important market, help them, I don't want to have to manage my IT, I want to be able to go to experts that can do this. >> That's one of the reasons, yeah. >> RCloud and Innovation Manager, it's an interesting title, tell us a little bit about your role inside the company. >> I already worked for more than 36 years in the company, so I had a lot of jobs within the company. In the previous job I was a Operations Manager, and now I am RCloud and Innovation Manager. RCloud is our private cloud that we are using for hosting customers and serving customers. It's and active-active data center where we can do disaster recovery, set up, and so on. So for customers that are no longer interested in building their own data centers, that's what we doing. And it's for some of them also an in between on-premise data center and public clouds. So we have customers moving to Azure and AWS, and sometimes they just stay for specific reasons in our RCloud. Innovation Manger is about how do we set up, how do we improve our tooling, and how do we improve our processes in helping and unburdening our customers. >> You mentioned the public clouds like Azure and AWS, do you have relationships with them, do you have connections into some of those public clouds? >> We are Microsoft partner, so most of our customers are going to Azure, but it's also building up in Amazon, and we did receive some questions also about Google. >> Okay, great. So when we talk about operations, service providers, very rapid change environment, typically you have a lot of customers to be able to deal with, give us a little bit about what's changing in your business, the infrastructure management and the tooling space. >> In the tooling space, IT is moving, IT in motion is what we heard in the keynote this morning. Customers are expecting a lot, about dashboarding, they want to see how their business is behaving not about what is a device doing. We need to monitor more and more applications, and the business lines. So that's why we are implementing ScienceLogic, or had an implementation of ScienceLogic, and now we doing the second phase in building more runbook automations, more dashboarding, more experience levels instead of SLS or XLS. >> Great, I want to get to the automation, but first, you've only been using ScienceLogic for a couple of years now, bring us back to, was it a bunch of in-house tooling that you had created for managing before that drove us there, paint us a picture of kind of the before and how you ended up with ScienceLogic. >> We had Microsoft Systems Center Operations Manager, we had Nagios, we had some plugs-in on this tooling, so it was I think in total six or seven tools, and we did some interfacing about it. But yeah, seven tools interfacing, not easy to run, a lot of management, a lot of people involved, a lot of skills required, so the reason was simplify it. >> So did you completely eliminate those seven previous tools? >> Yup, as of the 1st of April this year they are gone. >> All right, so there was a little bit of a journey, can you walk us through a little bit about there, was it prying it away from certain people, was it maturity from your side or from a product standpoint, what were some of those points that took a little while to get there. >> It took a while just to convince everybody in the company, set up an organization, it's not only the tooling it's also the organization need to be involved, a lot of communication, there's a change process going on, and we implemented, the first customers were in November 2017 on the system, and since then every month we added sometimes two, sometimes five, sometimes seven, sometimes one, as customer, so the people internally and externally need to get used to the product, so that's step-by-step, keep it simple, do it slowly but fast, and with a deadline. >> So, you talk a little bit about your organization operationally, what's the impact then to your ultimate end user, do they see anything, has it changed how, has it improved cost? >> It's changed certainly for the customers, because the old tools, there was no multi tenancy, there was not easy logon, so they had no access to the dashboards, they were just waiting for the monthly reporting and say, okay, it was up, okay we were, now they can have access, we use single sign-on to do that, so the customers are happy that they can see, they can see line of business dashboarding, and so on. And certainly internally it did improve a lot of cost savings, because a lot of the things we are doing now is automation, and we started the integration with our ITSM tool, and that will go live, normally next week. >> Okay, what ITSM tool are you-- >> It's a German tool, it's from a company called OMNINET, and the tool is called OMNITRACKER. >> Great, talk now about that automation, where have you come so far, where do you see it progressing in the future? >> We started first with some task automation, we have an 24/7 operation team, first-line, and they were doing a lot of manual tasks, so where we can, and what we first did was automate some manual tasks. And now we are progressing with ITSM integration, bi-directional integration, and then we will start with removing from old mailboxes, where we can do some restart automatically, so we will take a look at the incidents, see what we can do, see if we can do some automation with that, and we will certainly progress very far, as far as possible to do more and more automation and less manual work. >> Great, tell us, you've attended this event before, what brings you back to the event? >> First of all I want to see a lot of the demos, what's coming, because we are today, 8.12 version was announced, we are on 8.9, we will move next week to 8.10, so what is coming, so I have to talk internally to people, okay, what's coming, I need to convince all program managers, service delivery managers, I can talk to customers what is coming, what they can expect, so that's one of the reasons. The other reason is to talk to other customers of ScienceLogic, what are you doing, what's helping you, what's not, and so on. >> Yeah, I noticed one of the things they talked about is making it easier to upgrade from versions, when you think about the cloud world, as we talk about it, is, if your customers are in Azure, you don't ask them what version of Azure they're running, you're running whatever version Microsoft has it, they patch it, they update it, if security fix happens it goes there, when you talk about moving from 8.9 to 10 to 12, that process of when do I do it, how do I do it, how's ScienceLogic doing it, keeping things easy to upgrade, were there things in the keynote that you were ready to jump on? >> We started with, the first version 8.3 or 4 I think, and we always try to be in good shape in the newer releases. So we already had some experience with upgrading, and it's going smooth. And whatever I heard from the system engineers, it's going better and better and better. So normally we have only a very small outage to do that, in fact it should be minimal, sometimes they switch over or something like that, when a database is changed, but normally operations is always running 24/7, and there is no interruption for operations. >> Has there been anything at the show that you've seen so far, either through the demos, talking to some of the experts, or in the keynote, that you want to highlight? >> One of the things that I have seen is the connection with the application, with the APM tools, that's what our customers also are requesting more and more, the integration of infrastructure and application, and the multi cloud of course. >> Yeah, that's definitely something we've heard. All right Luc, I want to give you the final word, things to take away, for people that haven't come to a ScienceLogic event, what you think that they should take away from an event like this. >> For me the greatest take-away is come here to learn. Come here to see what is possible, what the future is, what AIOps will mean in the future, prepare yourself for the next three to five years, that's the main reason. >> Great, well thank you so much, preparing for the next three to five years, we know the pace of change isn't slowing down at all, so it's great to be able to talk to a practitioner that's helping to manage and deal with so many of those environments, thanks so much for joining me. >> Thank you. >> All right, and we'll be back with more coverage here, be sure to check out thecube.net for all interviews, I'm Stu Miniman, and thanks so much for watching. (upbeat music)

>> From Washington DC, it's theCUBE. Covering the ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> Hi, I'm Stu Miniman, and this is theCUBE's special coverage of ScienceLogic symposium 2019 here at the Ritz-Carlton, in Washington DC, about 460 people here, I'm told over 50% growth, from last year's event, the first time we've had theCUBE here, really excited to be able to dig in, with a number of the executives, customers and partners, and no better way, to kick off than one of the users, here at the event, actually coming here from across the pond, here to the district, happy to welcome to the program first-time guest, Nigel Wilks who's the Head of Global Tooling at Computacenter, based in the UK, Nigel, thanks so much for joinin' us. >> Hey, a pleasure. >> And joining him from ScienceLogic we have Clive Spanswick, who's the Vice President of Sales from EMEA, Clive thanks so much for joinin' us. >> Pleasure to be here. >> All right, so Nigel, set the stage for us, coming to the event here, tell me what brings you here, and tell us a little bit about Computacenter. >> Yeah sure, so, we're a relatively new customer to ScienceLogic so, I think, what, we signed two, three weeks ago? So, not deployed yet, but got great expectations. So, there's a lot of background research in the sessions. Finding about more what the additional capabilities that we can unlock, which will help drive our business further forward. So, Computacenter is a large IT provider, global. Based in the UK, as headquarters. My area of the business is in the Managed Services sector. So realistically, we're looking to reduce our cost to serve. Be more proactive for our customers, and, we've got great expectations of what ScienceLogic can do around those areas. Unlocking more automation, and eventually leading down the AI path. >> So Nigel, what I heard in the keynote is, some of the same themes I've been hearing around the industry, we are unparalleled as to how fast things are changing in the industry, there's just more complexity, there's more heterogeneous environments, for companies like yours, usually agility is one of those things that's coming to the top of the environment and oh my gosh, when I became an analyst about nine years ago, it was the tooling and management options out there where usually some of the things that customers would say are weak in their environment, and something I think I've heard for my entire career, so, maybe give us a little bit as to some of what you're hearing from the business side and how it makes sure that you can run your services faster and ultimately serve your customers better and how your look at, I don't know whether you call it AI Ops, but this whole space, fits into that environment. >> Sure, so-- >> Yeah. >> We've with probably a lot of organic growth within Computacenter over quite a short period of time. Also through acquisitions, we've got quite a fragmented tooling landscape globally. So, nearly two years ago, we kind of set on the journey to become more of a global entity, and certainly from my perspective a tooling landscape. Looking to consolidate those down, simplify our services, again helping reduce our cost base, and then leverage the automation stuff I talked about earlier. So, just going to ScienceLogic, we're moving away from some of the big names. And consolidating over 50 tools into the one ScienceLogic solution. >> Wow. That's great, let's bring ya into the discussion Clive, yeah, I heard in the keynote this morning, it was, the typical customer, it's at least 14 tools. >> Yes. >> That get consolidated down. I think back about five years ago, frictionless and simplicity were the terms that I heard. I talked to a lot of companies, it's like "Oh okay, yes I've got integrations I need to do "if I'm doing acquisitions, whether I be in, "if I'm in services of course that's there" But, you know, financial industries, and, heck, Cisco IT who I'm going to be talking to later, does an acquisition a month, what are you seeing, give us a little bit of the EMEA flavor and-- >> Sure. >> How what Nigel's saying, how is that resonating with your customer base? >> Yeah, absolutely Stu. So we see this a lot with the leading service providers now that are really being challenged by their customers to really extend their portfolio of services, over an ever more diverse range of technologies, and this is one of the big challenges that has driven tool sprawl over the course of the last seven to ten years, so simplification of the toolset, is really one of the key drivers to really deliver outcomes for efficiency, so a lot of the way we see modern service providers operating today really is all about automation, to get to better automation at a lower cost you have to drive simplification into the tool chain. So, we see this a lot with our customers across the region and indeed worldwide, that taking the tools landscape and really collapsing that into a much more simplified model is an essential ingredient to drive efficiencies that then in turn can be delivered to the customer as lower-cost services, so that's the real driving force that we see for customers today. >> Alright. Nigel, we'd love to hear, I know you've just gone through the process of choosing but, what are you looking for, are there specific business drivers, how will success be measured in your environment? >> Part of the process was, to look at what our business requirements were. And map those on through an RFI process. Of which ScienceLogic were one of the vendors that took part. So I think at the benchmark of everything we did, at the heart of the whole process, was that business requirements. Just making sure that whichever toolsets we selected, would go down that route. We never expected to have a single-vendor solution, which, fortunately we've got ScienceLogic which covers the majority, but with the partner ecosystem, some of those guys are here today. It kind of rounds it up for us. But moving away from our current providers, some of those, they present challenges to us as well. Tryin' to unlock data that's within the platforms, some of those tools are through acquisitions. So as much as you've got a brand name as part of a whole stable of tools, they don't inter-operate very well. And the beauty of going to ScienceLogic was, everything comes in together, even the partner tools, which allows us to really look at what we can do in the future. >> Alright, so, Nigel I've got the tough question for you. When I came into the show, one of the things that really struck me, is how data's at the center of what's important here, you know, when we look at companies, digital transformation often is a buzzword, but, we've really defined the difference between the old way and the modern environment is, how is data something that can actually drive your business, are you data-driven in your decisions, can you monetize data, what I heard in the keynote discussion is, data's such an important, not just the collecting but leveraging, and that's driving the intelligence, the automation. How much did that focus on data play into your decision, and can you give us a little bit of insight as to how your company looks at the role of data in the IT world today? >> Well, it's very important, that's quite a simple solution to that one. So for me, an infrastructure tooling perspective, being able to bring all the data into one place but contextualize it as well, means that we can then do some good stuff. Again, driving us down that automation path but from an end-user point of view we've got end-user analytics, that can open up a lot of different worlds for us, predicting what issues users have, rather than calling a service desk, theoretically, going further down the future, we'll be calling them to say, "I can see you've got a problem, "I can fix it for you remotely." Those kind of decisions that we can make from that data. But in my kind of space, the infrastructure tooling side, we need to go onto that AI Ops journey, and as you heard this morning, now, or at least a few weeks ago, to get there, it's like getting the data into a good shape, knowing what we want to do with the AI Ops moving forward. So, automation's a good candidate, that helps up achieve some of our objectives, reduces customers' downtime as well but, we've also got to be careful that we're not tryin' to automate resolution to poor behavior. >> Yeah >> Yeah, so, rather than fixing the root cause, we need to actually look at things and say, "Is this an incident-worthy event, "is this something that "we need to actually do something with, "or is it just an automation candidate?" And it's going to drive some of those behaviors for us. >> Clive, I'd love to get your viewpoint as to what you're hearing from customers, when I listened to the analyst this morning, he's like "You need to really differentiate "between that machine learning piece, "and the automation." Because any of us that've worked in operations environment, you can automate a bad process. >> Yeah. >> And data doesn't necessarily mean good information, so we need to manage those things a little bit separately, and that maturation of where customers are for both automation and intelligence, is a tough one, when they did a poll when your CEO was up on stage, nobody's fully, turn things over to the computers. >> Yep, yep. >> So, where are your customers, how are they thinking through the AIML, the use of data, and those pieces? >> So see, I think to be fair, a lot of customers today, AI Ops as we know is a relatively new term to the market, so I think a lot of businesses are struggling to recognize their own maturity, and I think, what we learned from this morning from Dave Link, our CEO, about how you characterize yourself on the journey to AI Ops maturity I think is a very valuable thing, and I think as I look at a lot of the customers and we saw from the poll earlier in the main session, that a lot of businesses today are fairly in the middle of maturity, so they're really at about the point of consolidating all the data in one place, the next big step of that of course is to clean that data up and contextualize it, so that you can start to leverage that data for the meaningful outcomes, and that's really where the smarts of machine learning and early-stage AI really start to play. We still, to be fair, still a long way off from the realization of full AI, but there are many pragmatic things that you can do, to get you very well level set, to take full advantage when those opportunities start to present themselves. >> Alright. So, Nigel, you're goin' through this process to really modernize your toolset you said you're replacing a whole bunch of things with the new one, what ultimately will this mean to your end-user customers? >> I think a more proactive service. Just dialing it back down to the simple things. If we simplify our service, we can have, from a business point of view, we can be consistent in how we deliver service globally. But from an end-user point of view. At the end of the day, most of the stuff is event-driven. End users typically find those out before systems do. Just from whole new cycles, reducing false positives and things. But it also means that, again, automation is being at the heart of what we want to try and achieve. We can automatically fix these things, so it's less downtime. And then hopefully we can just kind of prevent. Automation's great, but prevention's better. >> Yeah. How do you see your journey going forward, when you look at that automation, I mean I can't imagine you at a day one, your desk, putting everything in and everything's there, do you have a roadmap out there as to how you look at your deployment and how you're going to change things internally? Yeah. This, realistically, is going to be a catalyst to how we do things. So what starts off as a tooling replacement project, becomes that overall, we can do things global process. Working a little bit smarter than we have been before, doing things on a larger scale, but using common processes. That's quite a big shift in how we work now. But also means from our sales forces perspective, they're selling the same thing, it doesn't matter which country they're in. It becomes more about delivery location, and a language. >> Great. Clive, give us a little bit as to, what are customers like Nigel, what should they expect once they've made the deployment, how long does that transformation take-- >> Sure. >> And what's the day one and then, three months, six months out? >> Sure, great questions. So the whole journey that we're exploring, with all of our customers, is this move to AI Ops and they've done really the support of the resilient digital experience for their customers. The journey itself is continuous. So, one of the big challenges that we know to be true in the space that we operate in, is the demand for constant change. So the idea and the process that we're going on with, with computer sensor is that, we will take you through a series of maturity stages, of crawl, walk and run. And then once we get them to run, it will be a case of continuous improvement and continuous development. We expect to get to the first break of that within the first quarter, we're going to be delivering instant value from the platform pretty much from the word go, but once we get into the process of business as usual, running the operation, it really becomes about the improvement of moving, from really the stages of helping them react better to incidents, and then moving into a much more proactive and predictive state, and then finally, the endgame of this of course, is to really get to the point of, automate to avoid the incidents happening altogether, and that really, I guess, is where we start to step towards the ultimate vision of AI Ops and the things that that can bring to bear. >> Alright, so, Nigel, I want you to take me inside your team, 'cause on the one hand we say, "I have a whole bunch of tools, "I'm going to simplify and I'm going to unify "and that's going to be great." And I'm sure there's many on your team they're like, "Ah, I hate this tool, and this one's a pain "and this and that. "But we kind of know how "to do everything that I'm doing today." So, one, give us a little insight as to, is there some of that clinging to the past, and, on the other hand, are there some things that, like, "Oh my gosh, I'm glad I will never have to do "one two or three ever again, "once I've gone through this process"? >> Great, great question, so, everyone has their favorite tool, or favorite bit of software. I think, internally, we've clearly got that challenge as well. But it's fair to say, the reverse is true, there's a lot of tools out there that the user base are more than happy to get rid of. But ultimately, I think as we've gone through the cycle with ScienceLogic, and certainly we've had some good workshops with the various user base, highlighting what's possible, we've had some really really positive feedback. I still expect challenges, change, change is a big thing, most people don't like change but, I think there's a great opportunity for people to, at the end of the day learn a new tool. Something different, something fresh. And also then, they can think about what the tool can do, how can we exploit it more, so, we're not locked into the model that we were in before, the tools that we'd use for years and we've worked in the same way. We've got an exciting journey to start looking at how we can derive better services, how we can simplify our services. How we can let customers self-serve, to a degree as well. So you know, I think it's an exciting journey that we're on. And I think it'll be good to come back next year and demonstrate where we are. >> I love that, I definitely want to talk about that, Clive, give you the final word on this. What final advice to you give him, he's made the decision, he's goin' onboard. Tell him, I'm sure, unicorns and rainbows and everything's going to be phenomenal, but, what are some of the things you hear from your customers as they roll things out, give him a little bit of the "Yay" and a little bit of the-- >> Sure >> Just "Hey make sure "we've educated everybody on this." >> Yeah, again, great question Stu. So, from working with our customer base, the big thing that we see is that this is a continuous journey. The journey doesn't stop. What we do is we make things progressively easier, and the opportunities to scale and standardize are almost limitless. I guess the one word of counsel I would give is that, one of the big things that we see, with any major transformation, we're talking about the automations we can deliver around monitoring but, with any transformation it is really how you start to shift the culture of the organization to work a way around the new ways of operating, and really winning the hearts and minds of the guys that this stuff is going to make the biggest difference to. So, we're talking in the first instance of course about the operational stakeholders and the key users, having them engaged, and really working that process to get the maximum benefit out of the platform. From there, really is about the improvements that they can achieve in customer experience and of course, as Nigel has already said, a lot of that is really centered around the opportunities it's going to present them to show real innovations, around their service portfolio and my guidance there would be, don't be shy to show the world of the possible, to your enterprise customers, because they are demanding more, and there is so much that they can do with the platform to really unleash super value to their customer base. >> Yeah I love that, the world of the possible, we understand all the stresses and strains put on business and IT today so, Clive, Nigel, thank you so much for joining us, Nigel we look forward to hearin' how things go, catch up with you in a year maybe. >> Pleasure. >> Of course, thank you. >> Alright, so we'll be here all day at the Ritz-Carlton in Washington DC, ScienceLogic Symposium 2019, I'm Stu Miniman and as always, thank you for watchin' theCUBE. 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[Music] live from cambridge massachusetts extracting the signal from the noise it's the cube covering the MIT chief data officer and information quality symposium now your host dave Volante and paul Gillett hi buddy welcome back to Cambridge Massachusetts we're at MIT Paul Gillan and myself are here for two days and we're really pleased to have sandy Pentland on he's the director of MIT Media labs entrepreneurship program just coming off a keynote mr. Alex sandy Pentland Spellman thanks for coming with you how'd you get that name sandy was that the color you know my dad was named Alex too so I had to get the diminutive so Alexander turns into Zander or Sasha or sandy ah excellent so man it's stuck so we learned from your keynote today that like your mom said hey if every other kid jumps off the bridge do you and the answer should be yes why is that well if your other friends or presumably as rational as you and have same sort of values as you and if they're doing something that looks crazy they must have a piece of information you don't like maybe Godzilla is coming bridges come and it really is time to get off but and so so while it's used as a metaphor for doing the irrational things it's actually shows that using your social context can be most rational because it's a way of getting information that you don't otherwise have so you broke down your talk to chief data officers and new types of analysis smarter organizations smarter networks and then really interesting new new architecture if we could sort of break those down sure you talked about sort of networks not individual nodes as really should be the focus to understand behavior can you unpack that a little well it's a little bit like the bridge or metaphor you know a lot of what we learn a lot of our behavior comes from watching other people we're not even conscious of it but you know if everybody else starts you know wearing a certain sort of shoe or or you know acting in a certain or using a phrase in business like all these new sort of buzz phrases like oh you have to - because it's to fit in it means something it's it's part of being hyper formants and being part of your group but that's not in data analytics today today what they look at is just your personal properties not what you're exposed to and the group that you're part of so they would look at the guy on the bridge and they say he's not going to jump because he doesn't have that information but on the other hand if all of other people who like him are making a different decision he probably is going to jump and your research has been you dig into organizations and you've found the relationship between productivity and this type of analysis has been pretty substantial very substantive offenses a ssin and outside of the organization dealing with customers so people focus on things like personality history various sort of training things like that what we find is compared to the pattern of interaction with other people so who do you talk to when and what situations those other factors are tiny they're often a whole order of magnitude less important than just do you talk to all the people in your group do you talk outside of your group do if you violate the org chart and talk to other people if you do you're almost certainly one of the high productivity high innovation people so what what impact does this have or were the implications of this on organizations which historically have been have been highly Madonn hierarchies reporting structures all of these institutions that we evolved in the post-world War two ERA is this working against their productivity well what they did is is they set some simple rules in that they could deal with and wrap their head around but what we find is that those simple rules are exactly the opposite of what you need for innovation and because really what they're doing is they're enforcing silos they're enforcing atomization of the work and everybody talks about we need to be more fluid we need to be more innovative we need to be able to move faster and what that requires is better communication habits and so what we find when we measure the communication habits is that that's exactly right better communication habits lead to more innovative organizations what's really amazing is almost no organization does it so people don't know does everybody talk to everybody in this group do they talk outside of the group there's no graphic there's no visualization and when you give a group a visualization of their pattern of organization of communication they change it and they become more innovative they become more productive I'm sure you're familiar with holacracy this idea that of doing away with with organizational boundaries and sort of do titles and sure everybody talks to everyone is that in your view a better way to structure an organization think that's too extreme but it's headed in the right direction I mean so what we're talking first of all people try to do this without any data so you know everybody's the same well everybody really isn't the same and how would you know if you're behaving as well as the same as other people or I mean there's no data so so what I'm suggesting is something that's sort of halfway between the two yeah you can have leaders you can have organization in there but you also have to have good flow of ideas and what that means is you have to make talking outside your org chart a value it's something you're rewarded for it means that including everybody in the loop in your organization is something you ought to be rewarded for and of course that requires data so the sorts of things we do with peoples we make displays could just be piece of paper that shows the patterns of communication and we give it to everybody and you know what people actually know what to do with it when you give it to them they say well gee you know this group of people is all talking to each other but they're not talking to that group maybe they ought to talk to each other it's that simple but in the lack of data you can't feel so you instrumented people essentially with let's badges and you could measure conversations at the watercooler yeah they're their frequency their duration not the content not the content just that's the activity just is it happening right and is it happening between groups just just people from this group go to that other groups water cooler stuff like that and that actually is enough to really make a substantial difference in the corporation and you gave an example of you were able to predict trending stories on Twitter better than the internal mechanism and Twitter did I understand that Kerina so what we've done by studying organizations like this and coming up with these sort of rules of how people behave so the notion that people learn from each other and that it's the patterns of communication that matter you can encode that along with machine learning and suddenly you get something that looks like machine learning but in many ways it's more powerful and more reliable and so we have a spin-out called Endor and what that does is it lets your average guy who can use a spreadsheet do something that's really competitive with the best machine learning groups in the world and that's pretty exciting because everybody has these reams of data but what they don't have is a whole bunch of PhDs who can study it for six months and and come up with a machine learning algorithm to do it they have a bunch of guys that are smart know the business but they don't know the machine learning so it endured doesn't supply something like a spreadsheet to be able to allow the normal guy to do as good as the machine learning guys there's a lot of focus right now on anticipating predicting customer behavior better a lot of us been focused on on individuals understanding individuals better is that wrongheaded I mean should marketers be looking more at this group theory and treating customers more as buckets of similar behaviors it's not it's not buckets but treating people as individuals is is a mistake because while people do have individual preferences most of those preferences are learned from other people it's keeping up with the Jones it's fitting in its it's learning what the best practice is so you can predict people better from the company they keep than you can from their demographics always virtually every single time you can do better from the company they keep than from the standard sort of data so what that means is when you do analysis you need to look at the relationships between people and at one level it's sort of obvious you analyze somebody personally without knowing something about their relationships right about you know the type of things they do the places they go those are important but they're usually not in the data and what I find is I do this with a lot of big organizations and what I find is you look at their data analytics it's all based on individuals and it's not based on the context to those individuals absolutely I want to ask you further about that because when I think of the surveys that I fill out they're always about my personal preference Yahoo I want to do I can't remember ever filling out a survey that asked me about what my peer group does are you saying that those are the questions we should be asking yeah exactly right and of course you want to get data about that you want to know if if you go to these locations all the time to go to that restaurant you go to this sort of entertainment who else goes there what are they by what's trending in your group because it's not the general population and these not necessary people I know but they're people I identify with Yammer haps that's why I go to certain restaurants not because my friends go there but because people who I aspire to be like yeah there yeah and and the other way around you go there and you say well gosh these other people are like me because they go here too and I see that they're you know wearing different sort of clothes or they're by or the simplest thing you go to restaurants you see other people all buying the mushi yes maybe I should try the mushi I usually don't like it but seems to work well and this is I like this restaurant and everybody else who comes here likes it so I'll try it right it's that simple so it's important to point out we're talking about the predictive analytics Capas they're probably people watching might say this Sandi's crazy we mean we don't want it personalized we want to personalize the customer experience still I'm presuming sure but when we're talking about predictive analytics you're saying the the community the peer group is a much better predictor than the individual that's right yeah okay so I want to come back to the the org chart these are you saying that org charts shouldn't necessarily change but the incentives should or your previous thing to do is you have an org chart but the incentives that are across the entire organization is good communication within the box you're in and good communication outside of the box and to put those incentives in place you need to have data you need to be able to have some way of estimating does everybody talk to each other do they talk to the rest of the organization and there's a variety of ways you can do that we do it with little badges we do it by analyzing phone call data email is not so good because email is not really a social relationship it's just this this little formal thing you do often but by using things like the badges like the phone calls surveys for that matter right you can give people feedback about are they communicating in the right way are they communicating with other parts of the organization and by visualizing that to people they'll begin to do the right thing you had this notion of network tuning oh you don't want an insufficiently diverse network but you don't want a network that's too dense you might find the sweet spot in the middle desert how do you actually implement that that tuning well the first thing is is you have to measure okay you have to know how dense is the social interaction the communication pattern because if you don't know that there's nothing to - right and then what you want to ask is you want to ask the signal property of something being two dances the same ideas go around then around and around so you look at the graph that you get from this data and you ask you know this Joe talked to Bob talk to Mary talk to Joe talk to you know is it full of cycles like that and if it's too full of cycles then that's a problem right because it's the same people talking to each other same ideas going around and there's some nice mathematical formulas for major in it they're sort of hard to put into English but it has to do with if you look at the flow of ideas are you getting a sufficiently diverse set of ideas coming to you or is it just the same people all talking to each other so are you sort of cut off from the rest of the world in your book social physics you talk about rewards and incentives isms and one of the things that struck me as you say that that rewards that people are actually more motivated by rewards for others than for themselves correct me if I'm wrong if paraphrasing you wrong there but but there's but but rewarding the group or or doing something good for somebody else is actually a powerful incentive is it is that the true the case well you said it almost right so so if you want to change behavior these social incentives are more powerful than financial incentives so if you have everybody in a group let's say and people are rewarded by the behavior of the other people in the group what will they do well they'll talk to the other people about doing the right thing because their reward my reward depends on your behavior so I'm gonna talk to you about it okay and your reward depends on it you'll talk and I don't know so what we're doing is we're creating much more communication around this problem and social pressure because you know if you don't do it you're screwing me and and you know I may not be a big thing but you're gonna think twice about that whereas some small financial award usually it's not such a big thing for people so if you think people talk a lot about you know persona persona marketing when I first met John Fourier he had this idea of affinity rank which was his version of you know peer group PageRank hmm do you do you hear a lot about you know get a lot of questions about persona persona marketing and and what does your research show in terms of how we should be appealing to that persona so sorry good questions about that some time and I don't know what he really originally intended but the way people often imply it is very static you have a particular persona that's fixed for all parts of your life well that's not true I mean you could be a baseball coach for your kid and a banker during the day and a member of a church and those are three different personas and what defines those personas it's the group that you're interacting with it's it's the the people you learn with and try and fit in so your persona is a variable thing and the thing that's the key to it is what are the groups that you're you're interacting with so if I analyzed your groups of interactions I'd see three different clusters I'd see the baseball one I'd say the banking one I'd see the church group one and then I would know that you have three personas and I could tell which one you're in typically by seeing who you're spending time with right now is the risk of applying this idea of behaviors influenced by groups is there the risk of falling over into profiling and essentially treating people anticipating behaviors based upon characteristics that may not be indicative of how any individual might act back credit alcoholics as you example right I don't get a job because people like people who are similar to me tend to be alcoholics let's say this is different though so this is not people who are similar to you if you hang out with alcoholics all the time then they're really eyes are good on that you're an alcoholic it may not be yes and there is a risk of over identifying or or extrapolating but it's different than people like me I mean if you go to the you know the dingy bars were beers or a buck and everybody gets wasted and you do that repeatedly you're talking about behaviors rather than characteristics behaviors rather than characteristics right I mean you know if you drink a lot maybe you drink a lot so we have a question from the crowd so it says real time makes persona very difficult yeah so it was come back to furriers premise was I was Twitter data you know such is changing very rapidly so are there social platforms that you see that can inform in real time to help us sort of get a better understanding of persona and affinity group affinity well there are data sources that do that right so first as if I look at telephone data or credit card data even for that matter sure this geo-located I can ask but what sort of people buy here or what sort of people are in this bar or restaurant and I can look at their demographics and where they go to I showed an example of that in San Francisco using data from San Francisco so there is this data which means that any app that's interested in it that has sufficient breadth and although sufficient adoption can do these sorts of analyses can you give an example of how you're working with the many organizations now I'm sure you can't name them but can you give an example of how you're applying these principles practically now whether it's in law enforcement or in consumer marketing how are you putting these to work well there's a bunch of different things that that go together with this view of you know it's the flow of ideas that's the important thing not the demographics so talk about behavior change and we're working with a small country to change their traffic safety by enrolling people in small groups where you know the benefit I get for driving right depends on your safety and we're good buddies we know that that's how you sign up sign up with your buddies and what that means is I'm going to talk to you about your driving if you're driving in a dangerous way and that we've seen in small experiments is a lot more effective than giving you points on your driver's license or discount on your insurance the social relationships so so that's an example another example is we're beginning a project to look at unemployment and what we see is is that people have a hard time getting re-employed don't have diverse enough social networks and it sounds kind of common sense but they don't physically get out enough compared to the people that do get jobs so what's the obvious thing well you encouraged them to get out more you make it easier for them to get out more so those are some examples when you talk about health care what you can do is you can say well look you know I don't know particular things you're doing but based on the behavior that you show right and the behavior of the people you hang with you may be at much higher risk of diabetes and it's not any particular behavior this is the way medical stuff is always pitched is you know it's this behavior that beer every combination of things all right and so you're not really aware that you're doing anything bad but if all your buds are at risk of it then you probably are too because you're probably doing a lot of the same sort of behaviors and medicine is a place where people are willing to give up some of the privacy because the consequences are so important so we're looking at people who are interested in personalized medicine and are willing to you know share their data about where they go and what they spend time doing in order to get statistics back from the people they spend time with about what are the risk factors they pick up from the people around them and the behaviors they engage in um your message this to the cdos today was you know you were sort of joking you're measuring that right and a lot of times they weren't a lot of the non-intuitive things your research has found so I wanna talk about the data and access to the data and how the CBO can you know affect change in their organization a lot of the data lives in silos I mean if they certainly think of social data Facebook LinkedIn yeah Twitter you mentioned credit card data is that a problem or is data becoming more accessible through api's or is it still just sort of a battle to get that data architecture running well it's a it's a battle and in fact actually it's a political and very passionate battle and it revolves around who controls the data and privacy is a big part of that so one of the messages is that to be able to get really ditch data sources you have to engage with the customer a lot so people are more than willing our research we've set up you know entire cities where we've changed the rules and we've found that people are more than willing to volunteer very detailed personal data under two conditions one is they have to know that it's safe so you're not reselling it you're handling it in a secure way it's not going to get out in some way and the other is that they get value for it and they can see the value so it's not spreading out and they're part of the discussion so you know you want more personalized medicine people are willing to share right because it's important to them or for their family you know if you want to share we're willing to share very personal stuff about their kids they would never do that but if it results in the kid getting a better education more opportunity yeah they're absolutely willing so that leads to a great segue into enigma yeah you talked about enigma as a potential security layer for the internet but also potential privacy yeah solution so talk about enigma where it's at yeah what it is where it's at and how it potentially could permeate yeah so we've been building architectures and working with this sort of problem this conundrum basically datas and silos people feel paranoid and probably correctly about their data leaky now companies don't have access to data don't know what to do with it and a lot of it has to do with safe sharing another aspect of this problem is cybersecurity you're getting increasing the amount of attacks done stuff bad for companies bad for people it's just going to get worse and we actually know what the answers to these things are the answers our data is encrypted all the time everywhere you do the computation on encrypted data you never transmit it you never unencrypted it to be able to do things we also know that in terms of control of the data is possible to build fairly simple permission mechanisms so that you know the computer just won't share it in the wrong places and if it does you know skyrockets go up and the cop scum you can build systems like that today but the part that's never been able never allowed that to happen is you need to keep track of a lot of things in a way that's not hackable you need to know that somebody doesn't just short-circuit it or take it out the back and what's interesting is the mechanisms that are in Bitcoin give you exactly that power so you whatever you feel about Bitcoin you know it's speculative bubble or whatever the blockchain which is part of it is this open ledger that is unhackable and and has the following characteristics that's amazing it's called trustless what that means is you can work with a bunch of crooks and still know that the ledger that you're keeping is correct because it doesn't require trusting people to work with them it's something where everybody has to agree to be able to get things and it works it works in Bitcoin at scale over the whole world and so what we've done is adapted that technology to be able to build a system called enigma which takes data in an encrypted form computes on it in an encrypted form transmits it according to the person's permissions and only that way in an encrypted form and you know it provides this layer of security and privacy that we've never had before there have been some projects that come close to this but know we're pretty excited about this and and what I think you're going to see is you're going to see some of the big financial institutions trying to use it among themselves some of the big logistics some of the big medical things trying to use it in in hotspots where they have real problems but the hope is is that it gets spread among the general population so it becomes quite literally the privacy and security level that doesn't have Warren Buffett might be right that it might fail as a currency but the technology has really inspired some new innovations that's right so so it's essentially a distributed it's not a walled garden it's a distributed black box that's what you're describing you never exposed the data that's right you don't need a trusted third party that's getting attacked that's right nobody has to stamp that this is correct because the moment you do that first of all other people are controlling you and the second thing is is there a point of attack so it gets rid of that trusted third party centralization makes it distributed you can have again a bunch of bad actors in the system it doesn't hurt it's peer-to-peer where you have to have 51% of the people being bad before things really go bad how do you solve the problem of performing calculations on encrypted data because they're classic techniques actually it's been known for over 20 years how to do that but there are two pieces missing one piece is it wasn't efficient it scaled really poorly and what we did is came up with a way of solving that by making it essentially multi scale so it's it's a distributed solution for this that brings the cost down to something that's linear in the number of elements which is a real change and the second is keeping track of all of the stuff in a way that's secure it's fine to have an addition that's secure you know but if that isn't better than a whole system that secure it doesn't do you any good and so that's where the blockchain comes in it gives you this accounting mechanism for knowing which computations are being done who has access to them what the keys are things like that so Google glass was sort of incubated in MIT Media labs and well before yeah my group you go right in your group and yeah it didn't take off me because it's just not cool it looks kind of goofy but now enigma has a lot of potential solving a huge problem are you can open-source it what do you yeah it's an open-source system we hope to get more people involved in it and right now we're looking for some test beds to show how well it works and make sure that all the things are dotted and crossed and so forth and where can people learn more about it oh go to a nygma dot media dot mit.edu all right sandy we're way over our time so obviously you were interesting so thanks keep right there buddy Paul and I we right back with our next guest we're live from see this is the cube right back [Music]

joined by satya nadella no tell us what about about your your your thoughts on this event in general you know last year was about Big Data this year it's a little bit more focused a little bit broader focus on the modern enterprise as they say what's your take on kind of >> this event it's a great event on this is my first time here as well and having a chance to even see a couple of panels and just participate i think this notion of a modern enterprise is for real i think that it is re-imagination of what does infrastructure mean what do applications mean inside of the enterprise and we're going through this kak tonic shift which we participate in and so to have a forum like this to >> discuss that was just great so let's dig into that a little bit what you know what makes the what makes the moderate enterprise it's it's certainly a cloud and virtualization you've got the Big Data piece kind of the DevOps model of application development how do you kind of define what all bring to bringing together all these different elements >> what makes a modern enterprise yeah one of the things that I like to sort of make sure we focus on I work on the infrastructure business at Microsoft so >> if you're in the infrastructure business the key thing is to be in touch with the applications and it turns out in our own case today we are building a pretty diverse set of applications both consumer and enterprise so we're building vein which is an applied machine learning application real in building office 365 which is an enterprise focus collaboration communication application we're building dynamics and another enterprise crm ERP in the cloud application and what have you so that diversity of applications makes you rethink what is the infrastructure needed from storage compute as well as the network and so we are building a new operating system for the modern enterprise to be able to deploy these modern applications so that's kind of how I conceptualize I would say there are four major elements to it the first one is it's inside of the data center you have much more of a software driven by descent where you're orchestrating your compute storage and network in support of your applications either at the data center or multi data center scale because there's not a single atom rise that's not using some public cloud provider or another service provider in addition to what they already are virtualizing inside their own private cloud so that is all a software control plane and so we are really thinking about what is the modern operating system that enables you to manage the data center a second dimension would be the what is driven through consumerization of IT I like to describe it as transforming IT to be much more people century so you want end-users to adopt the devices they want and still have access to all their applications and data and yet aighty needs to be able to set compliance and policy so how do you really reimagine that is another dimension big data is something you reference there's not going to be a single application that's not a big data application and so those are the major major teams and the last thing I would say is this DevOps so not only have you built the application but it's even the life cycle around the applications being reimagined how developers and operations professionals come together in support of an ongoing improvement and continuous integration these four megatrends I think constitute a modern enterprise >> infrastructure interesting so let's dig into a little bit about what you mentioned about the use of kind of public cloud infrastructure as well as your internal data center so you've got these hybrid environments they're starting to emerge again pretty much software lead a software led infrastructure is what we're calling it a wiki bond how do you go about actually making it possible for for CIOs and their teams and to actually manage those environments in as efficient way as possible you know making decisions about which applications are deployed in the public cloud which it deployed in your data center how they interact potentially applications that are drawing on data from both spots it's obviously can get very complex so you know Microsoft is one of those public cloud providers with windows so how do you approach that product so >> if you sort of take what you just described which is if you you sort of start with the design point that there will be a public cloud there will be a private cloud and a service provider cloud then how you think about the software control is going to be defined by that design so it's not going to be narrowly defined as bring everything into my data center and I'll help you manage it but it is actually distributed so I think of this is the true fruition of distributed computing and we believe in that so then what are the things that matter first is identity so anything whenever things get distributed the most important thing that brings back things together is actually identity of users and identity for resources so active directory was a great resource for many enterprises in terms of how they came the complexity of the previous generation of client server now we have replumbed and reimagined active directory with Azure Active Directory so this consistency in directories helps IT administrators manage this complexity the next one is virtualization so not only would you be able to virtualize on your private cloud you should be able to move the same work cloud workload which is virtualized to any of these other clouds so you need a degree of guarantee that the performance characteristics of a virtualized workload get maintained across all so that's another thing that with our hyper-v investments and our add your investments we are in a making sure that happens the other one would be management so with if you can be sitting on the system center management console in the orchestrator and looking at a workload which could be in fact in 11 of these clouds or in fact the tears of a single app could be split which is the front end is on azure the back end is back in on premise and so that's also very very important to have a management tier which is the control plane that allows you to manage this complexity and lastly it's the consistency of the application platform Excel so if you're building and development you never want to be in the state where you build a great app but you can never check out so if you build it in the public cloud in the case of azure you should be able to take it and run it on a private cloud or on a service provider so these four things are on identity management virtualization and application platform I think is the core investment you've got to make to help enterprises truly adopt the cloud while you know it's >> complex but you gotta tame the complexity and then of course be what you're talking about it really is a lot of data being generated companies of course want to want to start taking an end of that data they want to analyze it they want to actually take those insights and turn them into either applications or perhaps convey them to executives and others in terms of visualization and of course one of those underlying platforms is to do talk about Microsoft's approach to Hadoop I know you're working with Hortonworks you actually kind of discontinued working on your own Big Data technology when you realize I think that you know who Duke was gonna is going to become the de facto standard so talk about how you're making it possible to bring the dip into this environment where more and more companies are looking to ring that it may be as a big data hub kind of store a lot of data and then feeds out to applications different workloads what is your approach to actually making that I guess enterprise ready yep and making it easy to get it get started and then term you know maybe science projects into really production whether the quantity I >> mean this notion of being able to take data and convert it into insights in support of enterprise goals is sort of the holy grail of this moment and so one of the things that we are actively doing is to bring a lot of the traditional value we've always had if you think about the momentum we have with our self-service bi capabilities on the edge of data which is Excel SharePoint sequel analysis services is where all data goes to in order to be able to drive in sites within and you know with it with end users because at the end of the day humans will be involved to be able to drive inside out of all of this data so now the question is how do we take that edge loop and connected with the information production which is upstream and that is where we are completing the story with having HD inside haven't even a relational interface on top of HT insight for in-memory ad-hoc query analysis like a data warehouse on top of it which i think the Hadoop community itself is adopting which is a sequel interface on Hadoop is probably one of the more talked about things nowadays and so this notion of having a complete data platform everything from MapReduce to stream processing to sequel like query interactively and then empowering end-users and workflows with data around their users which share for in Excel where we've invested in things like a power pivot and Power View which are actually powerful in-memory databases in fact I would say the most powerful in-memory database now is power view inside of Excel from where you can issue a sequel I mean basically a hive query to HD inside and populate millions of rows in a tabular column form that you're very familiar with we think that that democratization of big data is going to be very very important to acceptance of it as you said it from science projects or just being in the data science department to bring ubiquitous so we've only got time for >> one more question so just love to get your kind of future outlook what are some of the key priorities for you and your group over the next day 6 to 12 >> months I mean the key thing for us is really bootstrapping our cloud business we've got some fantastic traction with office 365 it's really doing very well in the q3 earnings we talked about how we have known a run rate basis a billion dollars in revenue going to office 365 and many customers who are to office 365 never bought an exchange server from so we're even it's not even zero something really in the short run it please and so we're very glad with that and there is a sure is just a natural complement to any customer who's already got office 365 sharepoint extensions the end user bi Active Directory administration all of these are sort of very natural extensions but agile itself now has got very very significant momentum yesterday we talked about how as urine as your services with all of our service provider partners has also got a billion dollars in revenue so that means when it comes to the core of the enterprise and their move to the cloud which is going to be complimenting a lot of what they're already doing in on premise is something that we're a pretty major player on and if anything we want to be solving the here and now practical problems with a forward-looking vision around identity around consistency of the management plane around virtualization compatibility around the application platforms and I think that that's what we're really up to in the immediate future all right yeah I think you really hit on something there with these gonna be high route deployments they're going to you know just much like in big data you know dupe isn't going to come in and replace your database your relational database and neither is the cloud whenever place your internal data center they've got to work together it sounds like you guys are working hard to kind of make that as seamless of the proposal as possible for your clients so I slept in Delaware Microsoft appreciate you coming on the cube thanks very much well hope you come back and join us about 39 thank you so much we'll be right back from the excel at Stanford symposium with our next guest writing for this

hi everybody welcome back to the Q we're here live at the Stanford accel partners summit I should say event here at Stanford University I am joined by Satya Nadella who is the president of server and tools baby Scholars Program with the Q I thanks so much for coming on appreciate it I think first time here on the cube we've had of course lots of folks on Microsoft on in the past and always a great to get your your take so tell us a little bit about your your your thoughts on this event in general you know last year was about big data this year it's a little bit more focused a little bit broader focus on the modern enterprise as they say what's your take on kind of this events it's a great event down this is my first time here as well and um having a chance to even see a couple of panels and just participate I think this notion of a modern enterprise is for real I think that it is a reimagining of what does infrastructure mean what do applications mean inside of the enterprise and we're going through this tectonic shift which we participate in and so to have a forum like this to discuss that was just great so let's dig into that a little bit what you know what makes the what makes the modern enterprise it's it's certainly a cloud and virtualization you've got the big data piece kind of the DevOps model of application development how do you kind of define what all bring to bringing together all these different elements what makes a modern enterprise yeah one of the things that I like to sort of make sure we focus on I work on the infrastructure business at Microsoft so you're in the infrastructure business the key thing is to be in touch with the applique and it turns out in our own case today we are building a pretty diverse set of applications both consumer and enterprise so they're building Bane which is an applied machine learning application we learn building office 365 which is an enterprise focused collaboration communication application we're building dynamics and another Enterprise CRM ERP in the cloud application and what have you so that diversity of applications makes you rethink what is the infrastructure needed from storage compute as well as the network and so we are building a new operating system for the modern enterprise to be able to deploy these modern applications so that's kind of how I conceptualize I would say there are four major elements to it the first one is it's inside of the data center you have much more of a software driven data set where you're orchestrating your compute storage and network in support of your applications either at the data center or multi data center scale because there's not a single enterprise that's not using some public cloud provider or another service provider in addition to what they already are virtualizing inside their own private cloud so that is all a software control plane and so we are really thinking about what is the modern operating system that enables you to manage the data center a second dimension would be the what is driven through consumerization of IT I like to describe it as transforming IT to be much more people central so you want end-users to adopt the devices they want and still have access to all their applications and data and yet IT needs to be able to set compliance and policy so how do you really arean that is in another dimension big data is something you referenced there's not going to be a single application that's not a big data application and so those are the major Keane's and the last thing I would say is this DevOps so not only have you built the application but it's even the lifecycle around the application is being reimagined how developers and operations professionals come together in support of an ongoing improvement and continuous integration these four mega trends I think constitute a modern enterprise infrastructure matrix so let's dig into a little bit about what you mentioned about the use of kind of public cloud infrastructure as well as your internal data center so you've got these hybrid environments that are starting to emerge again pretty much software lead a software led infrastructure is what we're calling it a wiki bond how do you go about actually making it possible for for CIOs and their teams and to actually manage those environments in an efficient way as possible you know making decisions about which applications are deployed in the public cloud which are deployed in your data center how they interact potentially applications that are drawing on data from both spots it's obviously can get very complex so you know Microsoft is one of those public cloud providers with Windows Azure so how do you approach that problem so if you sort of take what you just described which is if you you sort of start with the design point that there will be a public cloud there will be a private cloud and a service provider cloud then how you think about the software control is going to be defined by that design so it's not going to be narrowly defined as bring everything into my data center and I'll help you manage it but it is actually distributed so if I think of this is the true fruition of distributed computing and we believe in that so then what are the things that matter first is identity so anything whenever things get distributed the most important thing that brings back things together is actually identity of users and identity for resources so Active Directory was a great resource for many enterprises in terms of how they came the complexity of the previous generation of client server now we've replumbed and we my Active Directory with Azure Active Directory so this consistency in directories helps IT administrators manage this complexity the next one is virtualization so not only will you be able to virtualize on your private cloud you should be able to move the same work cloud workload which is virtualized to any of these other clouds so you need a degree of guarantee that the performance characteristics of a virtualized workload get maintained across all so that's another thing that with our hyper-v investments and our agile investments we are making sure that happens the other one would be management so with if you can be sitting on the system center management console and the orchestrator and looking at a workload which could be in fact in one one of these clouds or in fact the tears of a single application could be split which is the front end is on Azure the back end is back in on-premise and so that's also very very important to have a management tier which is the control plane that allows you to manage this complexity and lastly it's the consistency of the application platform itself so if you're building a development you never want to be in the state where you build a great app but you can never check out so you if you build it in the public cloud in the case of azure you should be able to take it and run it on a private cloud or on a service provider cloud so these four things are on identity management virtualization and application platform I think is the core investment you've got to make to help enterprises truly adopt the cloud while you know it's complex but you gotta tame the complexity and then of course what you're talking about it really is a lot of data being generated companies of course want to want to start taking advantage of that data they want to analyze it they want to actually take those insights and turn them into either applications or perhaps convey them to executives and others in terms of visualization and of course one of those underlying platforms is to do talk about Microsoft's approach to Hadoop I know you're working with Hortonworks you actually kind of discontinued working on your own big data technology when you as I think that you know Hadoop was given is going to become the de facto standard so talk about how you're making it possible to bring the dupe into this environment where more and more companies are looking to bring that in maybe as a big data hub kind of store a lot of data and then feeds out to applications different workloads what is your approach actually making that I guess Enterprise ready yeah and making it easy to get and get started and then turn you know maybe science projects into really production whether the point is right I mean this notion of being able to take data and convert it into insights in support of enterprise goals is sort of the holy grail of this moment and so one of the things that we are actively doing is to bring a lot of the traditional value we've always had if you think about the momentum we have with our self-service bi capabilities on the edge of data which is Excel sharepoint sequel analysis services is where all data goes to in order to be able to drive insights within and you know with it with end users because at the end of the day humans will be involved to be able to drive inside out of all of this data so now the question is how do we take that edge loop and connected with the information production which is upstream and that is where we are completing the story with having HD inside having even a relational interface on top of HD insight for in-memory ad hoc query analysis like a data warehouse on top of it which I think the Hadoop community itself is adopting which is a sequel interface on Hadoop is probably one of the more talked about things nowadays and so this notion of having a complete data platform everything from MapReduce to stream processing to sequel like query interactively and then empowering end-users and workflows with data around end users which share or in Excel where we've invested in things like a power pivot and Power View which are actually powerful in-memory databases in fact I would say the most powerful in-memory database now is Power View inside of Excel from where you can issue a sequel I mean basically a hive query to HD inside and populate millions of in a tabular column form that you're very familiar with we think that that democratization of big data is going to be very very important to acceptance of it as you said it from science projects or just being in the data science department to bring ubiquitous so we've only got time for one more question so just love to get your kind of future outlook what are some of the key priorities for you and your group over the next say six to twelve months I mean the key thing for us is really bootstrapping our cloud business we've got some fantastic traction with office 365 it's really doing very well in the q3 earnings we talked about how we have a moving on a run rate basis of billion dollars a revenue going to office 365 and many customers who are coming to office 365 never bought an exchange server from so we're even it's not even 0 some really in the short run at least and so we're very glad with that and there is a j''r is just a natural complement to any customer who's already got office 365 SharePoint extensions the end user bi Active Directory administration all of these are sort of very natural extensions but Azure itself now has got very very significant momentum yesterday we talked about how Azure and Azure services with all of our service provider partners has also got a billion dollars of revenue so that means when it comes to the core of the enterprise and their move to the cloud which is going to be complementing a lot of what they're already doing in on-premise is something that we're a pretty major player on and if anything we want to be solving the here and now practical problems with a forward-looking vision around identity around consistency of the management plane around virtualization compatibility around the application platforms and I think that that's what we are up to in the immediate future alright yeah I think you really hit on something there with these gonna be hybrid deployments they're going to you know just much like in big data you know doop isn't going to come in and replace your database your relational database and neither is the cloud going to replace your internal data center they've got to work together it sounds like you guys are working hard to kind of make that as seamless of the proposal as possible for your clients so Satya Nadella for Microsoft we appreciate you coming on the queue thanks very much well hope you come back and join us about three thank you so much we'll be right back from the Excel Stanford symposium with our next guests ready for this

>> Wait. Okay, We're back. Live here at Stanford University Alumni Center. What a great day. Stanford loved this place. A lot of brilliant minds here. And this is the Stanford Excel Seventeenth annual symposium called Excel Enterprise. That's the hashtag falls on Twitter here with Jeff Kelly. Silicon angles. Exclusive coverage is too cute. Our flagship program about the events extract the signal from the noise. And our next guest is Amanda Richardson, the head of product. That president. Welcome to the Cube. >> Thank you. Awesome. >> So really amazing event. I'LL see a lot of big minds here, and we're also live in San Francisco at the age of us somewhere all the developers air geeking out with Amazon and all the tools you the head of product President, tell us what is President. Tell us what you're doing here. >> So, President, a collaborative presentations will. So we look forward, Teo, helping our users create idea, share ideas and really have a platform for uh, putting. Their message is out there and better sharing with the audience is So we're here because we love excel. I'm here because I'm a GSP alum and any reason to get back to the farm is a good one, and we just think it's a great place to meet people piers and share ideas and hopefully learn from each other's mistakes. >> So what? You're the new business school president? >> So I got you a job before the new business school. It's pretty awesome, but I kind of want to go back. I was joking with my husband this morning. I think it may be time for a phD. >> Yeah, Sanford's Grace, but as the head of product, you can. You still get the geek out? >> Yeah, >> And look at also the market side. You gotta look into engineering also product. So in this whole enterprise two point Oh, thank you just never happened. It's still happening. It's like going and going. But now with cloud with mobile, it's all happening right? So I got that cloud mobile social thing going on. We've been covering. So knowing it's looking angle. What are you seeing now as the market drivers for those two forces cloud and mobile and social is all that coming together? >> Um, it is all coming together, and I think you know, we call it like the consumerism ation of enterprise. Right. So, um people have one phone, one device, one presence. I think five years ago you probably tried to keep your world separated between your enterprise, professional life and your personal life, and now it really all comes together. So you've gotta solve the problems for the enterprise users in the same way you solve problems for consumers, right? What are their big needs? What are their pain points? Where do they find value, focus on those areas and make it easy to use on DH? I think that's what's finally accelerating on bringing really cool, sexy problems to the enterprise users. You just bring a consumer approach. One >> of the biggest barriers that you see in that adopts House of consumer ization of consideration of the enterprise has been talked about for many, many years and finally was seeing a ray of hope. >> Yeah, wave and making the lives the end of the tunnel >> sunrise a face. So it's there, it's there. So one of the key drivers that are helping this go faster now versus years before Oh yes, next two years next year. >> Um so I think I think mobile is actually a great point, so you can't keep pieces like Evernote, Dropbox President out of your users hands. I mean, I remember being in meetings with manager meetings five, seven years ago, talking about how we're gonna ban Facebook, and that just seems quaint now because it's all in your phone and you can't tell people not to bring their phones to work. So I think Mobil's had a huge impact and getting more of these products and tools into the hands of the consumers and out of really this kind of big brother control type situation, Thie Other thing I think that's happening is just worlds are blending together and the availability of of tools on the Internet. It sounds silly to say, but, you know, you can remember five, ten years ago, you couldn't access your perhaps it's near p program. Or perhaps this even productivity tools from home. There was a time when we all had to remote in and yeah, I mean, I'm dating myself and showing why I color my hair. But it really is. You know, the world is changing, and I think, thank goodness for the Internet, thanking us for the Web and thank goodness for >> Mo. It's interesting you mention the dating yourselves first. You look fabulous, you know, you know world. I mean, I'm older, I know how old I am. And I just had the twenty seven year old kid on drop box. So you know, that's young. But, you know, it's a lot of senior folks now. This enterprise market is shifting from consumer. You seeing some of the leaders are those experienced managers because they've lived through the right client server that lived through the that first wave. So is that just because we're more, there's more people that know that market more amusing? You're seeing a lot more cos they're not not the twenty something. It's over thirty five over forty. >> Yeah, eso no comment on age. But Thea, I think what excites me about the space I can just talk about myself is you know, I have a consumer background. So it was super fun to be in consumer five ten years ago when you know Internet was taking off. He finally have a platform on which you have millions of users to test and learn and grow. And now that you can apply that to enterprise, I mean, I think it's new challenges but similar challenges. And I really think one of the more interesting things is that it's actually solving really compelling problems. One of the you know, um, I think there are a lot of opportunities out there around photo sharing and, um, Geo location and, you know, putting together your social graph. But you know, where I find passion and energy is actually providing value and solving problems and really being a key part of someone's someone's life, That's what gets me here. Hope that keeps others here. >> So let's talk about you're solving really interesting problem. What is the mean? What is your wife? What is president about? Why are you doing what you're doing? Is it simply, you know, we've talked. We hear a lot about the concerns around power point and right death by the PowerPoint slide and that kind of thing is that really, uh, the issue you've set out to overcome our tell us a little about what you do and why you do it. >> So, um, we certainly get compared to power point a lot, but where we, uh problem we really like to solve on on a more grand scale is that we believe ideas are best shared and best collaborated about. So if you think of ideas like jeans, they can come together. They can be built on each other. A great example of president uses. There is an organization in Syria rebel organization that used President to really be the platform to explain their ideas and what the issues really were in a quick, meaningful, impactful way. I think having a platform by which you can share ideas and better understand each other can apply Teo making the world a better place but can also apply Teo helping scientists share their information around the globe, building on ideas and I know even within president, we use the tool. Teo better communicate product road maps to engineering so that we can better align. I think it's all about communication. Helping ideas grow faster and helping the world to be a more understanding place. I mean, it's a little peace, love and happiness, but it it is why we get out of bed every morning. We really think because he's a great tool for people to be the platform for them to share their ideas. And >> so I'm actually president User. I've started using recently. Actually, I downloaded. You can see here about the kind of downloaded the desktop version, and I were working on the plane that was coming out here from Boston. But, you know, it's certainly a very interesting platform. It's very different from Power. Point certainly creates much, much more compelling type of way to present information. Uh, what are some of the design principles that's had a product? What are some of the things that you really kind of court your philosophy in terms of design, find it and and implementing our should say, creating the kind of user interface and the way people interact with information? >> Yes. So I'm really proud of President of the co founders have really doubled down, if you will, on our design effort. So we have a full time user research staff. We have a full time data research that we have a full time design staff, all three different roles, all three big teams. I'm really focused on understanding our users. So we saw for key user problems in terms of design principles, specifically that we focus on, we like to, uh, help users understand structure of their ideas. So one of the challenges of President. For those who come from a power point model is everything should be linear. And one of our principles is that not all ideas are linear. There may be areas where we consume into different pieces. So helping to communicate that that is particularly important for us and how to provide simple structure. Um, I think the other ideas, uh, helping to make it beautiful. We believe that words are better. What are? Excuse me? Pictures are better. Way to communicate in words. Um, you know, death by bullet point >> thing is a common affliction, >> eh? So how can you, uh, say something with a picture that would have taken a hundred words? And that's what we try to do. >> So you know what? Your problem is? Both kind of software service, but also down with stop version. Right? Mentioned. But you know what? The software service Mom, you're able, I assume, to collect data on the way people are using your product, right. How does kind of that type of information do you incorporate that into the design process and making changes to the product come to talk about how you used data analysis really >> product. Yeah. So, you know, I believe the role of product managers to understand the user intimately have a point of view on a strategy, but then early validate through data. So not to Pripyat. We do have data about your desktop PC, which is what >> I covered. Big data for what? You have no problem with that. >> So we focus a lot on one or user stew. Do what makes them successful way try toe. Have measurable outcomes for all of our initiatives, whether its user behavior or defining what a good presidents are really helping users to solve their problems. We use data tio, on the small level, optimized and on a big level really define an objective and a goal. So how can we really push things through the funnel to get to the user to their success point, which we measure is giving a presentation. >> So both find ten of tactical issues, but also a kind of inform your larger >> are big company KP eyes. They're all based on data. >> Okay, thanks for coming on The tears. We gotta break that. Their next guest coming in lining up all of the crowd's breaking up the Silicon Angles Exclusive coverage of Stanford Excel seventeen Annual symposium. Hashtag Excel Enterprise Where it sells Doing a lot of great enterprises is Cuba's looking angles. Coverage of Stanford Excel Symposium right back with our next guest after this short break.

>>text, you know, consumer opens up their iphone and says, oh my gosh, I love the technology behind my eyes. What's it been like being on the shark tank? You know, filming is fun, hang out, just fun and it's fun to be a celebrity at first your head gets really big and you get a good tables at restaurants who says texas has got a little possess more skin in the game today in charge of his destiny robert Hirschbeck, No stars. Here is CUBA alumni. Yeah, okay. >>Hi. I'm john Ferry, the co founder of silicon angle Media and co host of the cube. I've been in the tech business since I was 19 1st programming on many computers in a large enterprise and then worked at IBM and Hewlett Packard total of nine years in the enterprise brian's jobs from programming, Training, consulting and ultimately as an executive salesperson and then started my first company with 1997 and moved to Silicon Valley in 1999. I've been here ever since. I've always loved technology and I love covering you know, emerging technology as trained as a software developer and love business and I love the impact of software and technology to business to me creating technology that starts the company and creates value and jobs is probably the most rewarding things I've ever been involved in. And I bring that energy to the queue because the Cubans were all the ideas are and what the experts are, where the people are and I think what's most exciting about the cube is that we get to talk to people who are making things happen, entrepreneur ceo of companies, venture capitalists, people who are really on a day in and day out basis, building great companies and the technology business is just not a lot of real time live tv coverage and, and the cube is a non linear tv operation. We do everything that the T. V guys on cable don't do. We do longer interviews. We asked tougher questions, we ask sometimes some light questions. We talked about the person and what they feel about. It's not prompted and scripted. It's a conversation authentic And for shows that have the Cube coverage and makes the show buzz. That creates excitement. More importantly, it creates great content, great digital assets that can be shared instantaneously to the world. Over 31 million people have viewed the cube and that is the result. Great content, great conversations and I'm so proud to be part of you with great team. Hi, I'm john ferrier. Thanks for watching the cube. >>Hello and welcome to the cube. We are here live on the ground in the expo floor of a live event. The AWS public sector summit. I'm john for your host of the cube. We're here for the next two days. Wall to wall coverage. I'm here with Sandy carter to kick off the event. Vice president partner as partners on AWS public sector. Great to see you Sandy, >>so great to see you john live and in person, right? >>I'm excited. I'm jumping out of my chair because I did a, I did a twitter periscope yesterday and said a live event and all the comments are, oh my God, an expo floor a real events. Congratulations. >>True. Yeah. We're so excited yesterday. We had our partner day and we sold out the event. It was rock them and pack them and we had to turn people away. So what a great experience. Right, >>Well, I'm excited. People are actually happy. We tried, we tried covering mobile world congress in Barcelona. Still, people were there, people felt good here at same vibe. People are excited to be in person. You get all your partners here. You guys have had had an amazing year. Congratulations. We did a couple awards show with you guys. But I think the big story is the amazon services for the partners. Public sector has been a real game changer. I mean we talked about it before, but again, it continues to happen. What's the update? >>Yeah, well we had, so there's lots of announcements. So let me start out with some really cool growth things because I know you're a big growth guy. So we announced here at the conference yesterday that our government competency program for partners is now the number one industry in AWS for are the competency. That's a huge deal. Government is growing so fast. We saw that during the pandemic, everybody was moving to the cloud and it's just affirmation with the government competency now taking that number one position across AWS. So not across public sector across AWS and then one of our fastest growing areas as well as health care. So we now have an A. T. O. Authority to operate for HIPPA and Hi trust and that's now our fastest growing area with 85% growth. So I love that new news about the growth that we're seeing in public sector and all the energy that's going into the cloud and beyond. >>You know, one of the things that we talked about before and another Cuban of you. But I want to get your reaction now current state of the art now in the moment the pandemic has highlighted the antiquated outdated systems and highlighted help inadequate. They are cloud. You guys have done an amazing job to stand up value quickly now we're in a hybrid world. So you've got hybrid automation ai driving a complete change and it's happening pretty quick. What's the new things that you guys are seeing that's emerging? Obviously a steady state of more growth. But what's the big success programs that you're seeing right now? >>Well, there's a few new programs that we're seeing that have really taken off. So one is called proserve ready. We announced yesterday that it's now G. A. And the U. S. And a media and why that's so important is that our proserve team a lot of times when they're doing contracts, they run out of resources and so they need to tap on the shoulder some partners to come and help them. And the customers told us that they wanted them to be pro served ready so to have that badge of honor if you would that they're using the same template, the same best practices that we use as well. And so we're seeing that as a big value creator for our partners, but also for our customers because now those partners are being trained by us and really helping to be mentored on the job training as they go. Very powerful program. >>Well, one of the things that really impressed by and I've talked to some of your MSP partners on the floor here as they walk by, they see the cube, they're all doing well. They're all happy. They got a spring in their step. And the thing is that this public private partnerships is a real trend we've been talking about for a while. More people in the public sector saying, hey, I want I need a commercial relationship, not the old school, you know, we're public. We have all these rules. There's more collaboration. Can you share your thoughts on how you see that evolving? Because now the partners in the public sector are partnering closer than ever before. >>Yeah, it's really um, I think it's really fascinating because a lot of our new partners are actually commercial partners that are now choosing to add a public sector practice with them. And I think a lot of that is because of these public and private partnerships. So let me give you an example space. So we were at the space symposium our first time ever for a W. S at the space symposium and what we found was there were partners, they're like orbital insight who's bringing data from satellites, There are public sector partner, but that data is being used for insurance companies being used for agriculture being used to impact environment. So I think a lot of those public private partnerships are strengthening as we go through Covid or have like getting alec of it. And we do see a lot of push in that area. >>Talk about health care because health care is again changing radically. We talked to customers all the time. They're like, they have a lot of legacy systems but they can't just throw them away. So cloud native aligns well with health care. >>It does. And in fact, you know, if you think about health care, most health care, they don't build solutions themselves, they depend on partners to build them. So they do the customer doesn't buy and the partner does the build. So it's a great and exciting area for our partners. We just launched a new program called the mission accelerator program. It's in beta and that program is really fascinating because our healthcare partners, our government partners and more now can use these accelerators that maybe isolate a common area like um digital analytics for health care and they can reuse those. So it's pretty, I think it's really exciting today as we think about the potential health care and beyond. >>You know, one of the challenge that I always thought you had that you guys do a good job on, I'd love to get your reaction to now is there's more and more people who want to partner with you than ever before. And sometimes it hasn't always been easy in the old days like to get fed ramp certified or even deal with public sector. If you were a commercial vendor, you guys have done a lot with accelerating certifications. Where are you on that spectrum now, what's next? What's the next wave of partner onboarding or what's the partner trends around the opportunities in public sector? >>Well, one of the new things that we announced, we have tested out in the U. S. You know, that's the amazon way, right, Andy's way, you tested your experiment. If it works, you roll it out, we have a concierge program now to help a lot of those new partners get inundated into public sector. And so it's basically, I'm gonna hold your hand just like at a hotel. I would go up and say, hey, can you direct me to the right restaurant or to the right museum, we do the same thing, we hand hold people through that process. Um, if you don't want to do that, we also have a new program called navigate which is built for brand new partners. And what that enables our partners to do is to kind of be guided through that process. So you are right. We have so many partners now who want to come and grow with us that it's really essential that we provide a great partner, experienced a how to on board. >>Yeah. And the A. P. M. Was the amazon partner network also has a lot of crossover. You see a lot a lot of that going on because the cloud, it's you can do both. >>Absolutely. And I think it's really, you know, we leverage all of the ap in programs that exist today. So for example, there was just a new program that was put out for a growth rebate and that was driven by the A. P. N. And we're leveraging and using that in public sector too. So there's a lot of prosecutes going on to make it easier for our partners to do business with us. >>So I have to ask you on a personal note, I know we've talked about before, your very comfortable the virtual now hybrid space. How's your team doing? How's the structure looks like, what are your goals, what are you excited about? >>Well, I think I have the greatest team ever. So of course I'm excited about our team and we are working in this new hybrid world. So it is a change for everybody uh the other day we had some people in the office and some people calling in virtually so how to manage that, right was really quite interesting. Our goals that we align our whole team around and we talked a little bit about this yesterday are around mission which are the solution areas migration, so getting everything to the cloud and then in the cloud, we talk about modernization, are you gonna use Ai Ml or I O T? And we actually just announced a new program around that to to help out IOT partners to really build and understand that data that's coming in from I O T I D C says that that idea that IOT data has increased by four times uh in the, during the covid period. So there's so many more partners who need help. >>There's a huge shift going on and you know, we always try to explain on the cube. Dave and I talked about a lot and it's re platform with the cloud, which is not just lift and shift you kind of move and then re platform then re factoring your business and there's a nuance there between re platform in which is great. Take advantage of cloud scale. But the re factoring allows for this unique advantage of these high level services. >>That's right >>and this is where people are winning. What's your reaction to that? >>Oh, I completely agree. I think this whole area of modernizing your application, like we have a lot of folks who are doing mainframe migrations and to your point if they just lift what they had in COBOL and they move it to a W S, there's really not a lot of value there, but when they rewrite the code, when they re factor the code, that's where we're seeing tremendous breakthrough momentum with our partner community, you know, Deloitte is one of our top partners with our mainframe migration. They have both our technology and our consulting um, mainframe migration competency there to one of the other things I think you would be interested in is in our session yesterday we just completed some research with r C T O s and we talked about the next mega trends that are coming around Web three dato. And I'm sure you've been hearing a lot about web www dot right? Yeah, >>0.04.0, it's all moving too fast. I mean it's moving >>fast. And so some of the things we talked to our partners about yesterday are like the metaverse that's coming. So you talked about health care yesterday electronic caregiver announced an entire application for virtual caregivers in the metaverse. We talked about Blockchain, you know, and the rise of Blockchain yesterday, we had a whole set of meetings, everybody was talking about Blockchain because now you've got El Salvador Panama Ukraine who have all adopted Bitcoin which is built on the Blockchain. So there are some really exciting things going on in technology and public sector. >>It's a societal shift and I think the confluence of tech user experience data, new, decentralized ways of changing society. You're in the middle of it. >>We are and our partners are in the middle of it and data data, data data, that's what I would say. Everybody is using data. You and I even talked about how you guys are using data. Data is really a hot topic and we we're really trying to help our partners figure out just how to migrate the data to the cloud but also to use that analytics and machine learning on it too. Well, >>thanks for sharing the data here on our opening segment. The insights we will be getting out of the Great Sandy. Great to see you got a couple more interviews with you. Thanks for coming on. I appreciate you And thanks for all your support. You guys are doing great. Your partners are happy you're on a great wave. Congratulations. Thank you, john appreciate more coverage from the queue here. Neither is public sector summit. We'll be right back. Mhm Yeah. >>Mhm. Mhm robert Herjavec. People obviously know you from shark tank

(radio calls) >> Announcer: From around the globe, its theCUBE covering Space & Cybersecurity Symposium 2020, hosted by Cal poly. Hello, welcome back to theCUBE virtual coverage with Cal Poly for the Space and Cybersecurity Symposium, a day four and the wrap up session, keynote session with the Lieutenant Governor of California, Eleni Kounalakis. She's here to deliver her keynote speech on the topic of California's role in supporting America's Cybersecurity future. Eleni, take it away. >> Thank you, John, for the introduction. I am Lieutenant Governor Eleni Kounalakis. It is an honor to be part of Cal Poly Space and Cybersecurity Symposium. As I speak kind of Pierre with the governor's office of business and economic development is available on the chat, too ready to answer any questions you might have. California and indeed the world are facing significant challenges right now. Every day we are faced with the ongoing COVID-19 pandemic and the economic downturn that is ensued. We have flattened the curve in California and are moving in the right direction but it is clear that we're not out of the woods yet. It is also impossible right now to escape the reality of climate change from the fire sparked by exceptionally rare, dry lightening events to extreme heat waves threatening public health and putting a strain on our electricity grid. We see that climate change is here now. And of course we've been recently confronted with a series of brutal examples of institutionalized racism that have created an awakening among people of all walks of life and compelled us into the streets to march and protest. In the context of all this, we cannot forget that we continue to be faced with other less visible but still very serious challenges. Cybersecurity threats are one of these. We have seen cities, companies and individuals paralyzed by attacks costing time and money and creating an atmosphere of uncertainty and insecurity. Our state agencies, local governments, police departments, utilities, news outlets and private companies from all industries are target. The threats around cybersecurity are serious but not unlike all the challenges we face in California. We have the tools and fortitude to address them. That is why this symposium is so important. Thank you, Cal Poly and all the participants for being here and for the important contributions you bring to this conference. I'd like to also say a few words about California's role in America's future in space. California has been at the forefront of the aerospace industry for more than a century through all the major innovations in aerospace from wooden aircraft, to World War II Bombers, to rockets and Mars rovers. California has played a pivotal role. Today, California is the number one state in total defense spending, defense contract spending and total number of personnel. It is estimated the Aerospace and Defense Industry, provides $168 billion in economic impact to our state. And America's best trained and most experienced aerospace and technology workforce lives here in California. The fact that the aerospace and defense sector, has had a strong history in California is no accident. California has always had strong innovation ecosystem and robust infrastructure that puts many sectors in a position to thrive. Of course, a big part of that infrastructure is a skilled workforce. And at the foundation of a skilled workforce is education. California has the strongest system of public higher education in the world. We're home to 10 university of California campuses, 23 California State university campuses and 116 California Community Colleges. All told nearly 3 million students are enrolled in public higher education. We also have world renowned private universities including the California Institute of Technology and Stanford University numbers one and three in the country for aerospace engineering. California also has four national laboratories and several NASA facilities. California possesses a strong spirit of innovation, risk taking and entrepreneurship. Half of all venture capital funding in the United States, goes to companies here in California. Lastly, but certainly no less critical to our success, California is a diverse state. 27% of all Californians are foreign born, 27% more than one in four of our population of 40 million people are immigrants from another country, Europe central and South America, India, Asia, everywhere. Our rich cultural diversity is our strength and helps drive our economy. As I look to the future of industries like cybersecurity and the growing commercial space industry, I know our state will need to work with those industries to make sure we continue to train our workforce for the demands of an evolving industry. The office of the lieutenant governor has a unique perspective on higher education and workforce development. I'm on the UC Board of Regents, the CSU Board of Trustees. And as of about two weeks ago, the Community Colleges Board of Governors. The office of the lieutenant governor is now the only office that is a member of every governing board, overseeing our public higher education system. Earlier in the symposium, we heard a rich discussion with Undersecretary Stewart Knox from the California Labor and Workforce Development Agency about what the state is doing to meet the needs of space and cybersecurity industries. As he mentioned, there are over 37,000 job vacancies in cybersecurity in our state. We need to address that gap. To do so, I see an important role for public private partnerships. We need input from industry and curriculum development. Some companies like Lockheed Martin, have very productive partnerships with universities and community colleges that train students with skills they need to enter aerospace and cyber industries. That type of collaboration will be key. We also need help from the industry to make sure students know that fields like cybersecurity even exist. People's early career interests are so often shaped by the jobs that members of their family have or what they see in popular culture. With such a young and evolving field like cybersecurity, many students are unaware of the job opportunities. I know for my visits to university campuses that students are hungry for STEM career paths where they see opportunities for good paying jobs. When I spoke with students at UC Merced, many of them were first generation college students who went through community college system before enrolling in a UC and they gravitated to STEM majors. With so many job opportunities available to STEM students, cybersecurity ought to be one that they are aware of and consider. Since this symposium is being hosted by Cal Poly, I wanted to highlight the tremendous work they're doing as leaders in the space and cybersecurity industry. Cal Poly California Cybersecurity Institute, does incredible work bringing together academia, industry and government training the next generation of cyber experts and researching emerging cybersecurity issues. As we heard from the President of Cal Poly, Jeff Armstrong the university is in the perfect location to contribute to a thriving space industry. It's close to Vandenberg Air Force Base and UC Santa Barbara and could be home to the future permanent headquarters of US Space Command. The state is also committed to supporting this space industry in the Central Coast. In July, the State of California, Cal poly US-based force and the others signed a memorandum of understanding to develop a commercial space port at Vandenberg Air Force Base and to develop a master plan to grow the commercial space industry in the region. Governor Newsom has made a commitment to lift up all regions of the state. And this strategy will position the Central Coast to be a global leader in the future of the space industry. I'd like to leave you with a few final thoughts, with everything we're facing. Fires, climate change, pandemic. It is easy to feel overwhelmed but I remain optimistic because I know that the people of the State of California are resilient, persistent, and determined to address our challenges and show a path toward a better future for ourselves and our families. The growth of the space industry and the economic development potential of projects like the Spaceport at Vandenberg Air Force Base, our great example of what we can look forward to. The potential for the commercial space industry to become a $3 trillion industry by mid century, as many experts predict is another. There are so many opportunities, new companies are going to emerge doing things we never could have dreamed of today. As Lieutenant General John Thompson said in the first session, the next few years of space and cyber innovation are not going to be a pony ride at the state fair, they're going to be a rodeo. We should all saddle up. Thank you. >> Okay, thank you very much, Eleni. I really appreciate it. Thank you for your participation and all your support to you and your staff. You guys doing a lot of work, a lot going on in California but cybersecurity and space as it comes together, California's playing a pivotal role in leading the world and the community. Thank you very much for your time. >> Okay, this session is going to continue with Bill Britton. Who's the vice president of technology and CIO at Cal Poly but more importantly, he's the director of the cyber institute located at Cal Poly. It's a global organization looking at the intersection of space and cybersecurity. Bill, let's wrap this up. Eleni had a great talk, talking about the future of cybersecurity in America and its future. The role California is playing, Cal Poly is right in the Central Coast. You're in the epicenter of it. We've had a great lineup here. Thanks for coming on. Let's put a capstone on this event. >> Thank you, John. But most importantly, thanks for being a great partner helping us get this to move forward and really changing the dynamic of this conversation. What an amazing time we're at, we had quite an unusual group but it's really kind of the focus and we've moved a lot of space around ourselves. And we've gone from Lieutenant General Thompson and the discussion of the opposition and space force and what things are going on in the future, the importance of cyber in space. And then we went on and moved on to the operations. And we had a private company who builds, we had the DOD, Department Of Defense and their context and NASA and theirs. And then we talked about public private partnerships from President Armstrong, Mr. Bhangu Mahad from the DOD and Mr. Steve Jacques from the National Security Space Association. It's been an amazing conference for one thing, I've heard repeatedly over and over and over, the reference to digital, the reference to cloud, the reference to the need for cybersecurity to be involved and really how important that is to start earlier than just at the employment level. To really go down into the system, the K through 12 and start there. And what an amazing time to be able to start there because we're returning to space in a larger capacity and it's now all around us. And the lieutenant governor really highlighted for us that California is intimately involved and we have to find a way to get our students involved at that same level. >> I want to ask you about this inflection point that was a big theme of this conference and symposium. It was throughout the interviews and throughout the conversations, both on the chat and also kind of on Twitter as well in the social web. Is that this new generation, it wasn't just space and government DOD, all the normal stuff you see, you saw JPL, the Hewlett Foundation, the Defense Innovation Unit, Amazon Web Services, NASA. Then you saw entrepreneurs come in, who were doing some stuff. And so you had this confluence of community. Of course, Cal Poly had participated in space. You guys does some great job, but it's not just the physical face-to-face show up, gets to hear some academic papers. This was a virtual event. We had over 300 organizations attend, different organizations around the world. Being a virtual event you had more range to get more people. This isn't digital. This symposium isn't about Central California anymore. It's global. >> No, it really has gone. >> What really happened to that? >> It's really kind of interesting because at first all of this was word of mouth for this symposium to take place. And it just started growing and growing and the more that we talk to organizations for support, the more we found how interconnected they were on an international scale. So much so that we've decided to take our cyber competition next year and take it globally as well. So if in fact as Major General Shaw said, this is about a multinational support force. Maybe it's time our students started interacting on that level to start with and not have to grow into it as they get older, but do it now and around space and around cybersecurity and around that digital environment and really kind of reduce the digital dividing space. >> Yeah, General Thompson mentioned this, 80 countries with programs. This is like the Olympics for space and we want to have these competitions. So I got great vision and I love that vision, but I know you have the number... Not number, the scores and from the competition this year that happened earlier in the week. Could you share the results of that challenge? >> Yeah, absolutely. We had 83 teams participate this year in the California Cyber Innovation Challenge. And again, it was based around a spacecraft scenario where a spacecraft, a commercial spacecraft was hacked and returned to earth. And the students had to do the forensics on the payload. And then they had to do downstream network analysis, using things like Wireshark and autopsy and other systems. It was a really tough competition. The students had to work hard and we had middle school and high school students participate. We had an intermediate league, new schools who had never done it before or even some who didn't even have STEM programs but were just signing up to really get involved in the experience. And we had our ultimate division which was those who had competed in several times before. And the winner of that competition was North Hollywood. They've been the winning team for four years in a row. Now it's a phenomenal program, they have their hats off to them for competing and winning again. Now what's really cool is not only did they have to show their technical prowess in the game but they also have to then brief and out-brief what they've learned to a panel of judges. And these are not pushovers. These are experts in the field of cybersecurity in space. We even had a couple of goons participating from DefCon and the teams present their findings. So not only are we talking technical, we're talking about presentation skills. The ability to speak and understand. And let me tell you, after reading all of their texts to each other over the weekend adds a whole new language they're using to interact with each other. It's amazing. And they are so more advanced and ready to understand space problems and virtual problems than we are. We have to challenge them even more. >> Well, it sounds like North Hollywood got the franchise. It's likethe Patriots, the Lakers, they've got a dynasty developing down there in North Hollywood. >> Well, what happens when there's a dynasty you have to look for other talent. So next year we're going global and we're going to have multiple states involved in the challenge and we're going to go international. So if North Hollywood pulls it off again next year, it's going to be because they've met the best in the world than defeated >> Okay, the gauntlet has been thrown down, got to take down North Hollywood from winning again next year. We'll be following that. Bill, great to get those results on the cyber challenge we'll keep track and we'll put a plug for it on our site. So we got to get some press on that. My question to you is now as we're going digital, other theme was that they want to hire digital natives into the space force. Okay, the DOD is looking at new skills. This was a big theme throughout the conference not just the commercial partnerships with government which I believe they had kind of put more research and personally, that's my personal opinion. They should be putting in way more research into academic and these environments to get more creative. But the skill sets was a big theme. What's your thoughts on how you saw some of the highlight moments there around skill sets? >> John, it's really interesting 'cause what we've noticed is in the past, everybody thinks skill sets for the engineering students. And it's way beyond that. It's all the students, it's all of them understanding what we call cyber cognizance. Understanding how cybersecurity works whatever career field they choose to be in. Space, there is no facet of supporting space that doesn't need that cyber cognizance. If you're in the back room doing the operations, you're doing the billing, you're doing the contracting. Those are still avenues by which cybersecurity attacks can be successful and disrupt your space mission. The fact that it's international, the connectivities, all of those things means that everyone in that system digitally has to be aware of what's going on around them. That's a whole new thought process. It's a whole new way of addressing a problem and dealing with space. And again it's virtual to everyone. >> That's awesome. Bill, great to have you on. Thank you for including theCUBE virtual, our CUBE event software platform that we're rolling out. We've been using it for the event and thank you for your partnership in this co-creation opening up your community, your symposium to the world, and we're so glad to be part of it. I want to thank you and Dustin and the team and the President of Cal Poly for including us. Thank you very much. >> Thank you, John. It's been an amazing partnership. We look forward to it in the future. >> Okay, that's it. That concludes the Space and Cybersecurity Symposium 2020. I'm John Furrier with theCUBE, your host with Cal Poly, who put on an amazing virtual presentation, brought all the guests together. And again, shout out to Bill Britton and Dustin DeBrum who did a great job as well as the President of Cal poly who endorsed and let them do it all. Great event. See you soon. (flash light sound)