(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

(bright music) >> "Supermetafragilisticexpialadotious." What's in a name? In an homage to the inimitable Charles Fitzgerald, we've chosen this title for today's session because of all the buzz surrounding "supercloud," a term that we introduced last year to signify a major architectural trend and shift that's occurring in the technology industry. Since that time, we've published numerous videos and articles on the topic, and on August 9th, kicked off "Supercloud22," an open industry event designed to advance the supercloud conversation, gathering input from more than 30 experienced technologists and business leaders in "The Cube" and broader technology community. We're talking about individuals like Benoit Dageville, Kit Colbert, Ali Ghodsi, Mohit Aron, David McJannet, and dozens of other experts. And today, we're pleased to welcome David Linthicum, who's a Chief Strategy Officer of Cloud Services at Deloitte Consulting. David is a technology visionary, a technical CTO. He's an author and a frequently sought after keynote speaker at high profile conferences like "VMware Explore" next week. David Linthicum, welcome back to "The Cube." Good to see you again. >> Oh, it's great to be here. Thanks for the invitation. Thanks for having me. >> Yeah, you're very welcome. Okay, so this topic of supercloud, what you call metacloud, has created a lot of interest. VMware calls it cross-cloud services, Snowflake calls it their data cloud, there's a lot of different names, but recently, you published a piece in "InfoWorld" where you said the following. "I really don't care what we call it, "and I really don't care if I put "my own buzzword into the mix. "However, this does not change the fact "that metacloud is perhaps the most important "architectural evolution occurring right now, "and we need to get this right out of the gate. "If we do that, who cares what it's named?" So very cool. And you also mentioned in a recent article that you don't like to put out new terms out in the wild without defining them. So what is a metacloud, or what we call supercloud? What's your definition? >> Yeah, and again, I don't care what people call it. The reality is it's the ability to have a layer of cross-cloud services. It sits above existing public cloud providers. So the idea here is that instead of building different security systems, different governance systems, different operational systems in each specific cloud provider, using whatever native features they provide, we're trying to do that in a cross-cloud way. So in other words, we're pushing out data integration, security, all these other things that we have to take care of as part of deploying a particular cloud provider. And in a multicloud scenario, we're building those in and between the clouds. And so we've been tracking this for about five years. We understood that multicloud is not necessarily about the particular public cloud providers, it's about things that you build in and between the clouds. >> Got it, okay. So I want to come back to that, to the definition, but I want to tie us to the so-called multicloud. You guys did a survey recently. We've said that multicloud was mostly a symptom of multi-vendor, Shadow Cloud, M&A, and only recently has become a strategic imperative. Now, Deloitte published a survey recently entitled "Closing the Cloud Strategy, Technology, Innovation Gap," and I'd like to explore that a little bit. And so in that survey, you showed data. What I liked about it is you went beyond what we all know, right? The old, "Our research shows that on average, "X number of clouds are used at an individual company." I mean, you had that too, but you really went deeper. You identified why companies are using multiple clouds, and you developed different categories of practitioners across 500 survey respondents. But the reasons were very clear for "why multicloud," as this becomes more strategic. Service choice scale, negotiating leverage, improved business resiliency, minimizing lock-in, interoperability of data, et cetera. So my question to you, David, is what's the problem supercloud or metacloud solves, and what's different from multicloud? >> That's a great question. The reality is that if we're... Well, supercloud or metacloud, whatever, is really something that exists above a multicloud, but I kind of view them as the same thing. It's an architectural pattern. We can name it anything. But the reality is that if we're moving to these multicloud environments, we're doing so to leverage best of breed things. In other words, best of breed technology to provide the innovators within the company to take the business to the next level, and we determine that in the survey. And so if we're looking at what a multicloud provides, it's the ability to provide different choices of different services or piece parts that allows us to build anything that we need to do. And so what we found in the survey and what we found in just practice in dealing with our clients is that ultimately, the value of cloud computing is going to be the innovation aspects. In other words, the ability to take the company to the next level from being more innovative and more disruptive in the marketplace that they're in. And the only way to do that, instead of basically leveraging the services of a particular walled garden of a single public cloud provider, is to cast a wider net and get out and leverage all kinds of services to make these happen. So if you think about that, that's basically how multicloud has evolved. In other words, it wasn't planned. They didn't say, "We're going to go do a multicloud." It was different developers and innovators in the company that went off and leveraged these cloud services, sometimes with the consent of IT leadership, sometimes not. And now we have these multitudes of different services that we're leveraging. And so many of these enterprises are going from 1000 to, say, 3000 services under management. That creates a complexity problem. We have a problem of heterogeneity, different platforms, different tools, different services, different AI technology, database technology, things like that. So the metacloud, or the supercloud, or whatever you want to call it, is the ability to deal with that complexity on the complexity's terms. And so instead of building all these various things that we have to do individually in each of the cloud providers, we're trying to do so within a cross-cloud service layer. We're trying to create this layer of technology, which removes us from dealing with the complexity of the underlying multicloud services and makes it manageable. Because right now, I think we're getting to a point of complexity we just can't operate it at the budgetary limits that we are right now. We can't keep the number of skills around, the number of operators around, to keep these things going. We're going to have to get creative in terms of how we manage these things, how we manage a multicloud. And that's where the supercloud, metacloud, whatever they want to call it, comes that. >> Yeah, and as John Furrier likes to say, in IT, we tend to solve complexity with more complexity, and that's not what we're talking about here. We're talking about simplifying, and you talked about the abstraction layer, and then it sounds like I'm inferring more. There's value that's added on top of that. And then you also said the hyperscalers are in a walled garden. So I've been asked, why aren't the hyperscalers superclouds? And I've said, essentially, they want to put your data into their cloud and keep it there. Now, that doesn't mean they won't eventually get into that. We've seen examples a little bit, Outposts, Anthos, Azure Arc, but the hyperscalers really aren't building superclouds or metaclouds, at least today, are they? >> No, they're not. And I always have the predictions for every major cloud conference that this is the conference that the hyperscaler is going to figure out some sort of a multicloud across-cloud strategy. In other words, building services that are able to operate across clouds. That really has never happened. It has happened in dribs and drabs, and you just mentioned a few examples of that, but the ability to own the space, to understand that we're not going to be the center of the universe in how people are going to leverage it, is going to be multiple things, including legacy systems and other cloud providers, and even industry clouds that are emerging these days, and SaaS providers, and all these things. So we're going to assist you in dealing with complexity, and we're going to provide the core services of being there. That hasn't happened yet. And they may be worried about conflicting their market, and the messaging is a bit different, even actively pushing back on the concept of multicloud, but the reality is the market's going to take them there. So in other words, if enough of their customers are asking for this and asking that they take the lead in building these cross-cloud technologies, even if they're participating in the stack and not being the stack, it's too compelling of a market that it's not going to drag a lot of the existing public cloud providers there. >> Well, it's going to be interesting to see how that plays out, David, because I never say never when it comes to a company like AWS, and we've seen how fast they move. And at the same time, they don't want to be commoditized. There's the layer underneath all this infrastructure, and they got this ecosystem that's adding all this tremendous value. But I want to ask you, what are the essential elements of supercloud, coming back to the definition, if you will, and what's different about metacloud, as you call it, from plain old SaaS or PaaS? What are the key elements there? >> Well, the key elements would be holistic management of all of the IT infrastructure. So even though it's sitting above a multicloud, I view metacloud, supercloud as the ability to also manage your existing legacy systems, your existing security stack, your existing network operations, basically everything that exists under the purview of IT. If you think about it, we're moving our infrastructure into the clouds, and we're probably going to hit a saturation point of about 70%. And really, if the supercloud, metacloud, which is going to be expensive to build for most of the enterprises, it needs to support these things holistically. So it needs to have all the services, that is going to be shareable across the different providers, and also existing legacy systems, and also edge computing, and IoT, and all these very diverse systems that we're building there right now. So if complexity is a core challenge to operate these things at scale and the ability to secure these things at scale, we have to have commonality in terms of security architecture and technology, commonality in terms of our directory services, commonality in terms of network operations, commonality in term of cloud operations, commonality in terms of FinOps. All these things should exist in some holistic cross-cloud layer that sits above all this complexity. And you pointed out something very profound. In other words, that is going to mean that we're hiding a lot of the existing cloud providers in terms of their interfaces and dashboards and things like that that we're dealing with today, their APIs. But the reality is that if we're able to manage these things at scale, the public cloud providers are going to benefit greatly from that. They're going to sell more services because people are going to find they're able to leverage them easier. And so in other words, if we're removing the complexity wall, which many in the industry are calling it right now, then suddenly we're moving from, say, the 25 to 30% migrated in the cloud, which most enterprises are today, to 50, 60, 70%. And we're able to do this at scale, and we're doing it at scale because we're providing some architectural optimization through the supercloud, metacloud layer. >> Okay, thanks for that. David, I just want to tap your CTO brain for a minute. At "Supercloud22," we came up with these three deployment models. Kit Colbert put forth the idea that one model would be your control planes running in one cloud, let's say AWS, but it interacts with and can manage and deploy on other clouds, the Kubernetes Cluster Management System. The second one, Mohit Aron from Cohesity laid out, where you instantiate the stack on different clouds and different cloud regions, and then you create a layer, a common interface across those. And then Snowflake was the third deployment model where it's a single global instance, it's one instantiation, and basically building out their own cloud across these regions. Help us parse through that. Do those seem like reasonable deployment models to you? Do you have any thoughts on that? >> Yeah, I mean, that's a distributed computing trick we've been doing, which is, in essence, an agent of the supercloud that's carrying out some of the cloud native functions on that particular cloud, but is, in essence, a slave to the metacloud, or the supercloud, whatever, that's able to run across the various cloud providers. In other words, when it wants to access a service, it may not go directly to that service. It goes directly to the control plane, and that control plane is responsible... Very much like Kubernetes and Docker works, that control plane is responsible for reaching out and leveraging those native services. I think that that's thinking that's a step in the right direction. I think these things unto themselves, at least initially, are going to be a very complex array of technology. Even though we're trying to remove complexity, the supercloud unto itself, in terms of the ability to build this thing that's able to operate at scale across-cloud, is going to be a collection of many different technologies that are interfacing with the public cloud providers in different ways. And so we can start putting these meta architectures together, and I certainly have written and spoke about this for years, but initially, this is going to be something that may escape the detail or the holistic nature of these meta architectures that people are floating around right now. >> Yeah, so I want to stay on this, because anytime I get a CTO brain, I like to... I'm not an engineer, but I've been around a long time, so I know a lot of buzzwords and have absorbed a lot over the years, but so you take those, the second two models, the Mohit instantiate on each cloud and each cloud region versus the Snowflake approach. I asked Benoit Dageville, "Does that mean if I'm in "an AWS east region and I want to do a query on Azure West, "I can do that without moving data?" And he said, "Yes and no." And the answer was really, "No, we actually take a subset of that data," so there's the latency problem. From those deployment model standpoints, what are the trade-offs that you see in terms of instantiating the stack on each individual cloud versus that single instance? Is there a benefit of the single instance for governance and security and simplicity, but a trade-off on latency, or am I overthinking this? >> Yeah, you hit it on the nose. The reality is that the trade-off is going to be latency and performance. If we get wiggy with the distributed nature, like the distributed data example you just provided, we have to basically separate the queries and communicate with the databases on each instance, and then reassemble the result set that goes back to the people who are recording it. And so we can do caching systems and things like that. But the reality is, if it's distributed system, we're going to have latency and bandwidth issues that are going to be limiting us. And also security issues, because if we're removing lots of information over the open internet, or even private circuits, that those are going to be attack vectors that hackers can leverage. You have to keep that in mind. We're trying to reduce those attack vectors. So it would be, in many instances, and I think we have to think about this, that we're going to keep the data in the same physical region for just that. So in other words, it's going to provide the best performance and also the most simplistic access to dealing with security. And so we're not, in essence, thinking about where the data's going, how it's moving across things, things like that. So the challenge is going to be is when you're dealing with a supercloud or metacloud is, when do you make those decisions? And I think, in many instances, even though we're leveraging multiple databases across multiple regions and multiple public cloud providers, and that's the idea of it, we're still going to localize the data for performance reasons. I mean, I just wrote a blog in "InfoWorld" a couple of months ago and talked about, people who are trying to distribute data across different public cloud providers for different reasons, distribute an application development system, things like that, you can do it. With enough time and money, you can do anything. I think the challenge is going to be operating that thing, and also providing a viable business return based on the application. And so why it may look like a good science experiment, and it's cool unto itself as an architect, the reality is the more pragmatic approach is going to be a leavitt in a single region on a single cloud. >> Very interesting. The other reason I like to talk to companies like Deloitte and experienced people like you is 'cause I can get... You're agnostic, right? I mean, you're technology agnostic, vendor agnostic. So I want to come back with another question, which is, how do you deal with what I call the lowest common denominator problem? What I mean by that is if one cloud has, let's say, a superior service... Let's take an example of Nitro and Graviton. AWS seems to be ahead on that, but let's say some other cloud isn't quite quite there yet, and you're building a supercloud or a metacloud. How do you rationalize that? Does it have to be like a caravan in the army where you slow down so all the slowest trucks can keep up, or are the ways to adjudicate that that are advantageous to hide that deficiency? >> Yeah, and that's a great thing about leveraging a supercloud or a metacloud is we're putting that management in a single layer. So as far as a user or even a developer on those systems, they shouldn't worry about the performance that may come back, because we're dealing with the... You hit the nail on the head with that one. The slowest component is the one that dictates performance. And so we have to have some sort of a performance management layer. We're also making dynamic decisions to move data, to move processing, from one server to the other to try to minimize the amount of latency that's coming from a single component. So the great thing about that is we're putting that volatility into a single domain, and it's making architectural decisions in terms of where something will run and where it's getting its data from, things are stored, things like that, based on the performance feedback that's coming back from the various cloud services that are under management. And so if you're running across clouds, it becomes even more interesting, because ultimately, you're going to make some architectural choices on the fly in terms of where that stuff runs based on the active dynamic performance that that public cloud provider is providing. So in other words, we may find that it automatically shut down a database service, say MySQL, on one cloud instance, and moved it to a MySQL instance on another public cloud provider because there was some sort of a performance issue that it couldn't work around. And by the way, it does so dynamically. Away from you making that decision, it's making that decision on your behalf. Again, this is a matter of abstraction, removing complexity, and dealing with complexity through abstraction and automation, and this is... That would be an example of fixing something with automation, self-healing. >> When you meet with some of the public cloud providers and they talk about on-prem private cloud, the general narrative from the hyperscalers is, "Well, that's not a cloud." Should on-prem be inclusive of supercloud, metacloud? >> Absolutely, I mean, and they're selling private cloud instances with the edge cloud that they're selling. The reality is that we're going to have to keep a certain amount of our infrastructure, including private clouds, on premise. It's something that's shrinking as a market share, and it's going to be tougher and tougher to justify as the public cloud providers become better and better at what they do, but we certainly have edge clouds now, and hyperscalers have examples of that where they run a instance of their public cloud infrastructure on premise on physical hardware and software. And the reality is, too, we have data centers and we have systems that just won't go away for another 20 or 30 years. They're just too sticky. They're uneconomically viable to move into the cloud. That's the core thing. It's not that we can't do it. The fact of the matter is we shouldn't do it, because there's not going to be an economic... There's not going to be an economic incentive of making that happen. So if we're going to create this meta layer or this infrastructure which is going to run across clouds, and everybody agrees on, that's what the supercloud is, we have to include the on-premise systems, including private clouds, including legacy systems. And by the way, include the rising number of IoT systems that are out there, and edge-based systems out there. So we're managing it using the same infrastructure into cloud services. So they have metadata systems and they have specialized services, and service finance and retail and things like doing risk analytics. So it gets them further down that path, but not necessarily giving them a SaaS application where they're forced into all of the business processes. We're giving you piece parts. So we'll give you 1000 different parts that are related to the finance industry. You can assemble anything you need, but the thing is, it's not going to be like building it from scratch. We're going to give you risk analytics, we're giving you the financial analytics, all these things that you can leverage within your applications how you want to leverage them. We'll maintain them. So in other words, you don't have to maintain 'em just like a cloud service. And suddenly, we can build applications in a couple of weeks that used to take a couple of months, in some cases, a couple of years. So that seems to be a large take of it moving forward. So get it up in the supercloud. Those become just other services that are under managed... That are under management on the supercloud, the metacloud. So we're able to take those services, abstract them, assemble them, use them in different applications. And the ability to manage where those services are originated versus where they're consumed is going to be managed by the supercloud layer, which, you're dealing with the governance, the service governance, the security systems, the directory systems, identity access management, things like that. They're going to get you further along down the pike, and that comes back as real value. If I'm able to build something in two weeks that used to take me two months, and I'm able to give my creators in the organization the ability to move faster, that's a real advantage. And suddenly, we are going to be valued by our digital footprint, our ability to do things in a creative and innovative way. And so organizations are able to move that fast, leveraging cloud computing for what it should be leveraged, as a true force multiplier for the business. They're going to win the game. They're going to get the most value. They're going to be around in 20 years, the others won't. >> David Linthicum, always love talking. You have a dangerous combination of business and technology expertise. Let's tease. "VMware Explore" next week, you're giving a keynote, if they're going to be there. Which day are you? >> Tuesday. Tuesday, 11 o'clock. >> All right, that's a big day. Tuesday, 11 o'clock. And David, please do stop by "The Cube." We're in Moscone West. Love to get you on and continue this conversation. I got 100 more questions for you. Really appreciate your time. >> I always love talking to people at "The Cube." Thank you very much. >> All right, and thanks for watching our ongoing coverage of "Supercloud22" on "The Cube," your leader in enterprise tech and emerging tech coverage. (bright music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR, This is "Breaking Analysis with Dave Vellante". >> Black Hat 22 was held in Las Vegas last week, the same time as theCUBE Supercloud event. Unlike AWS re:Inforce where words are carefully chosen to put a positive spin on security, Black Hat exposes all the warts of cyber and openly discusses its hard truths. It's a conference that's attended by technical experts who proudly share some of the vulnerabilities they've discovered, and, of course, by numerous vendors marketing their products and services. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis", we summarize what we learned from discussions with several people who attended Black Hat and our analysis from reviewing dozens of keynotes, articles, sessions, and data from a recent Black Hat Attendees Survey conducted by Black Hat and Informa, and we'll end with the discussion of what it all means for the challenges around securing the supercloud. Now, I personally did not attend, but as I said at the top, we reviewed a lot of content from the event which is renowned for its hundreds of sessions, breakouts, and strong technical content that is, as they say, unvarnished. Chris Krebs, the former director of Us cybersecurity and infrastructure security agency, CISA, he gave the keynote, and he spoke about the increasing complexity of tech stacks and the ripple effects that that has on organizational risk. Risk was a big theme at the event. Where re:Inforce tends to emphasize, again, the positive state of cybersecurity, it could be said that Black Hat, as the name implies, focuses on the other end of the spectrum. Risk, as a major theme of the event at the show, got a lot of attention. Now, there was a lot of talk, as always, about the expanded threat service, you hear that at any event that's focused on cybersecurity, and tons of emphasis on supply chain risk as a relatively new threat that's come to the CISO's minds. Now, there was also plenty of discussion about hybrid work and how remote work has dramatically increased business risk. According to data from in Intel 471's Mark Arena, the previously mentioned Black Hat Attendee Survey showed that compromise credentials posed the number one source of risk followed by infrastructure vulnerabilities and supply chain risks, so a couple of surveys here that we're citing, and we'll come back to that in a moment. At an MIT cybersecurity conference earlier last decade, theCUBE had a hypothetical conversation with former Boston Globe war correspondent, Charles Sennott, about the future of war and the role of cyber. We had similar discussions with Dr. Robert Gates on theCUBE at a ServiceNow event in 2016. At Black Hat, these discussions went well beyond the theoretical with actual data from the war in Ukraine. It's clear that modern wars are and will be supported by cyber, but the takeaways are that they will be highly situational, targeted, and unpredictable because in combat scenarios, anything can happen. People aren't necessarily at their keyboards. Now, the role of AI was certainly discussed as it is at every conference, and particularly cyber conferences. You know, it was somewhat dissed as over hyped, not surprisingly, but while AI is not a panacea to cyber exposure, automation and machine intelligence can definitely augment, what appear to be and have been stressed out, security teams can do this by recommending actions and taking other helpful types of data and presenting it in a curated form that can streamline the job of the SecOps team. Now, most cyber defenses are still going to be based on tried and true monitoring and telemetry data and log analysis and curating known signatures and analyzing consolidated data, but increasingly, AI will help with the unknowns, i.e. zero-day threats and threat actor behaviors after infiltration. Now, finally, while much lip service was given to collaboration and public-private partnerships, especially after Stuxsnet was revealed early last decade, the real truth is that threat intelligence in the private sector is still evolving. In particular, the industry, mid decade, really tried to commercially exploit proprietary intelligence and, you know, do private things like private reporting and monetize that, but attitudes toward collaboration are trending in a positive direction was one of the sort of outcomes that we heard at Black Hat. Public-private partnerships are being both mandated by government, and there seems to be a willingness to work together to fight an increasingly capable adversary. These things are definitely on the rise. Now, without this type of collaboration, securing the supercloud is going to become much more challenging and confined to narrow solutions. and we're going to talk about that little later in the segment. Okay, let's look at some of the attendees survey data from Black Hat. Just under 200 really serious security pros took the survey, so not enough to slice and dice by hair color, eye color, height, weight, and favorite movie genre, but enough to extract high level takeaways. You know, these strongly agree or disagree survey responses can sometimes give vanilla outputs, but let's look for the ones where very few respondents strongly agree or disagree with a statement or those that overwhelmingly strongly agree or somewhat agree. So it's clear from this that the respondents believe the following, one, your credentials are out there and available to criminals. Very few people thought that that was, you know, unavoidable. Second, remote work is here to stay, and third, nobody was willing to really jinx their firms and say that they strongly disagree that they'll have to respond to a major cybersecurity incident within the next 12 months. Now, as we've reported extensively, COVID has permanently changed the cybersecurity landscape and the CISO's priorities and playbook. Check out this data that queries respondents on the pandemic's impact on cybersecurity, new requirements to secure remote workers, more cloud, more threats from remote systems and remote users, and a shift away from perimeter defenses that are no longer as effective, e.g. firewall appliances. Note, however, the fifth response that's down there highlighted in green. It shows a meaningful drop in the percentage of remote workers that are disregarding corporate security policy, still too many, but 10 percentage points down from 2021 survey. Now, as we've said many times, bad user behavior will trump good security technology virtually every time. Consistent with the commentary from Mark Arena's Intel 471 threat report, fishing for credentials is the number one concern cited in the Black Hat Attendees Survey. This is a people and process problem more than a technology issue. Yes, using multifactor authentication, changing passwords, you know, using unique passwords, using password managers, et cetera, they're all great things, but if it's too hard for users to implement these things, they won't do it, they'll remain exposed, and their organizations will remain exposed. Number two in the graphic, sophisticated attacks that could expose vulnerabilities in the security infrastructure, again, consistent with the Intel 471 data, and three, supply chain risks, again, consistent with Mark Arena's commentary. Ask most CISOs their number one problem, and they'll tell you, "It's a lack of talent." That'll be on the top of their list. So it's no surprise that 63% of survey respondents believe they don't have the security staff necessary to defend against cyber threats. This speaks to the rise of managed security service providers that we've talked about previously on "Breaking Analysis". We've seen estimates that less than 50% of organizations in the US have a SOC, and we see those firms as ripe for MSSP support as well as larger firms augmenting staff with managed service providers. Now, after re:Invent, we put forth this conceptual model that discussed how the cloud was becoming the first line of defense for CISOs, and DevOps was being asked to do more, things like securing the runtime, the containers, the platform, et cetera, and audit was kind of that last line of defense. So a couple things we picked up from Black Hat which are consistent with this shift and some that are somewhat new, first, is getting visibility across the expanded threat surface was a big theme at Black Hat. This makes it even harder to identify risk, of course, this being the expanded threat surface. It's one thing to know that there's a vulnerability somewhere. It's another thing to determine the severity of the risk, but understanding how easy or difficult it is to exploit that vulnerability and how to prioritize action around that. Vulnerability is increasingly complex for CISOs as the security landscape gets complexified. So what's happening is the SOC, if there even is one at the organization, is becoming federated. No longer can there be one ivory tower that's the magic god room of data and threat detection and analysis. Rather, the SOC is becoming distributed following the data, and as we just mentioned, the SOC is being augmented by the cloud provider and the managed service providers, the MSSPs. So there's a lot of critical security data that is decentralized and this will necessitate a new cyber data model where data can be synchronized and shared across a federation of SOCs, if you will, or mini SOCs or SOC capabilities that live in and/or embedded in an organization's ecosystem. Now, to this point about cloud being the first line of defense, let's turn to a story from ETR that came out of our colleague Eric Bradley's insight in a one-on-one he did with a senior IR person at a manufacturing firm. In a piece that ETR published called "Saved by Zscaler", check out this comment. Quote, "As the last layer, we are filtering all the outgoing internet traffic through Zscaler. And when an attacker is already on your network, and they're trying to communicate with the outside to exchange encryption keys, Zscaler is already blocking the traffic. It happened to us. It happened and we were saved by Zscaler." So that's pretty cool. So not only is the cloud the first line of defense, as we sort of depicted in that previous graphic, here's an example where it's also the last line of defense. Now, let's end on what this all means to securing the supercloud. At our Supercloud 22 event last week in our Palo Alto CUBE Studios, we had a session on this topic on supercloud, securing the supercloud. Security, in our view, is going to be one of the most important and difficult challenges for the idea of supercloud to become real. We reviewed in last week's "Breaking Analysis" a detailed discussion with Snowflake co-founder and president of products, Benoit Dageville, how his company approaches security in their data cloud, what we call a superdata cloud. Snowflake doesn't use the term supercloud. They use the term datacloud, but what if you don't have the focus, the engineering depth, and the bank roll that Snowflake has? Does that mean superclouds will only be developed by those companies with deep pockets and enormous resources? Well, that's certainly possible, but on the securing the supercloud panel, we had three technical experts, Gee Rittenhouse of Skyhigh Security, Piyush Sharrma who's the founder of Accurics who sold to Tenable, and Tony Kueh, who's the former Head of Product at VMware. Now, John Furrier asked each of them, "What is missing? What's it going to take to secure the supercloud? What has to happen?" Here's what they said. Play the clip. >> This is the final question. We have one minute left. I wish we had more time. This is a great panel. We'll bring you guys back for sure after the event. What one thing needs to happen to unify or get through the other side of this fragmentation and then the challenges for supercloud? Because remember, the enterprise equation is solve complexity with more complexity. Well, that's not what the market wants. They want simplicity. They want SaaS. They want ease of use. They want infrastructure risk code. What has to happen? What do you think, each of you? >> So I can start, and extending to the previous conversation, I think we need a consortium. We need a framework that defines that if you really want to operate on supercloud, these are the 10 things that you must follow. It doesn't matter whether you take AWS, Slash, or TCP or you have all, and you will have the on-prem also, which means that it has to follow a pattern, and that pattern is what is required for supercloud, in my opinion. Otherwise, security is going everywhere. They're like they have to fix everything, find everything, and so on and so forth. It's not going to be possible. So they need a framework. They need a consortium, and this consortium needs to be, I think, needs to led by the cloud providers because they're the ones who have these foundational infrastructure elements, and the security vendor should contribute on providing more severe detections or severe findings. So that's, in my opinion, should be the model. >> Great, well, thank you, Gee. >> Yeah, I would think it's more along the lines of a business model. We've seen in cloud that the scale matters, and once you're big, you get bigger. We haven't seen that coalesce around either a vendor, a business model, or whatnot to bring all of this and connect it all together yet. So that value proposition in the industry, I think, is missing, but there's elements of it already available. >> I think there needs to be a mindset. If you look, again, history repeating itself. The internet sort of came together around set of IETF, RSC standards. Everybody embraced and extended it, right? But still, there was, at least, a baseline, and I think at that time, the largest and most innovative vendors understood that they couldn't do it by themselves, right? And so I think what we need is a mindset where these big guys, like Google, let's take an example. They're not going to win at all, but they can have a substantial share. So how do they collaborate with the ecosystem around a set of standards so that they can bring their differentiation and then embrace everybody together. >> Okay, so Gee's point about a business model is, you know, business model being missing, it's broadly true, but perhaps Snowflake serves as a business model where they've just gone out and and done it, setting or trying to set a de facto standard by which data can be shared and monetized. They're certainly setting that standard and mandating that standard within the Snowflake ecosystem with its proprietary framework. You know, perhaps that is one answer, but Tony lays out a scenario where there's a collaboration mindset around a set of standards with an ecosystem. You know, intriguing is this idea of a consortium or a framework that Piyush was talking about, and that speaks to the collaboration or lack thereof that we spoke of earlier, and his and Tony's proposal that the cloud providers should lead with the security vendor ecosystem playing a supporting role is pretty compelling, but can you see AWS and Azure and Google in a kumbaya moment getting together to make that happen? It seems unlikely, but maybe a better partnership between the US government and big tech could be a starting point. Okay, that's it for today. I want to thank the many people who attended Black Hat, reported on it, wrote about it, gave talks, did videos, and some that spoke to me that had attended the event, Becky Bracken, who is the EIC at Dark Reading. They do a phenomenal job and the entire team at Dark Reading, the news desk there, Mark Arena, whom I mentioned, Garrett O'Hara, Nash Borges, Kelly Jackson, sorry, Kelly Jackson Higgins, Roya Gordon, Robert Lipovsky, Chris Krebs, and many others, thanks for the great, great commentary and the content that you put out there, and thanks to Alex Myerson, who's on production, and Alex manages the podcasts for us. Ken Schiffman is also in our Marlborough studio as well, outside of Boston. Kristen Martin and Cheryl Knight, they help get the word out on social media and in our newsletters, and Rob Hoff is our Editor-in-Chief at SiliconANGLE and does some great editing and helps with the titles of "Breaking Analysis" quite often. Remember these episodes, they're all available as podcasts, wherever you listen, just search for "Breaking Analysis Podcasts". I publish each on wikibon.com and siliconangle.com, and you could email me, get in touch with me at david.vellante@siliconangle.com or you can DM me @dvellante or comment on my LinkedIn posts, and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis". (upbeat music)

>> Announcer: From around the globe, it's theCube with digital coverage of MIT, Chief Data Officer and Information Quality Symposium brought to you by Silicon Angle Media. >> Hi, I'm Stu Miniman and this is the seventh year of theCubes coverage of the MIT, Chief Data Officer and Information Quality Symposium. We love getting to talk to these chief data officers and the people in this ecosystem, the importance of data, driving data-driven cultures, and really happy to welcome to the program, first time guests Eileen Vitrine, Eileen is the Chief Data Officer for the United States Air Force, Eileen, thank you so much for joining us. >> Thank you Stu really excited about being here today. >> All right, so the United States Air Force, I believe had it first CDO office in 2017, you were put in the CDO role in June of 2018. If you could, bring us back, give us how that was formed inside the Air force and how you came to be in that role. >> Well, Stu I like to say that we are a startup organization and a really mature organization, so it's really about culture change and it began by bringing a group of amazing citizen airman reservists back to the Air Force to bring their skills from industry and bring them into the Air Force. So, I like to say that we're a total force because we have active and reservists working with civilians on a daily basis and one of the first things we did in June was we stood up a data lab, that's based in the Jones building on Andrews Air Force Base. And there, we actually take small use cases that have enterprise focus, and we really try to dig deep to try to drive data insights, to inform senior leaders across the department on really important, what I would call enterprise focused challenges, it's pretty exciting. >> Yeah, it's been fascinating when we've dug into this ecosystem, of course while the data itself is very sensitive and I'm sure for the Air Force, there are some very highest level of security, the practices that are done as to how to leverage data, the line between public and private blurs, because you have people that have come from industry that go into government and people that are from government that have leveraged their experiences there. So, if you could give us a little bit of your background and what it is that your charter has been and what you're looking to build out, as you mentioned that culture of change. >> Well, I like to say I began my data leadership journey as an active duty soldier in the army, and I was originally a transportation officer, today we would use the title condition based maintenance, but back then, it was really about running the numbers so that I could optimize my truck fleet on the road each and every day, so that my soldiers were driving safely. Data has always been part of my leadership journey and so I like to say that one of our challenges is really to make sure that data is part of every airmans core DNA, so that they're using the right data at the right level to drive insights, whether it's tactical, operational or strategic. And so it's really about empowering each and every airman, which I think is pretty exciting. >> There's so many pieces of that data, you talk about data quality, there's obviously the data life cycle. I know your presentation that you're given here at the CDO, IQ talks about the data platform that your team has built, could you explain that? What are the key tenants and what maybe differentiates it from what other organizations might have done? >> So, when we first took the challenge to build our data lab, we really wanted to really come up. Our goal was to have a cross domain solution where we could solve data problems at the appropriate classification level. And so we built the VAULT data platform, VAULT stands for visible, accessible, understandable, linked, and trustworthy. And if you look at the DOD data strategy, they will also add the tenants of interoperability and secure. So, the first steps that we have really focused on is making data visible and accessible to airmen, to empower them, to drive insights from available data to solve their problems. So, it's really about that data empowerment, we like to use the hashtag built by airmen because it's really about each and every airman being part of the solution. And I think it's really an exciting time to be in the Air Force because any airman can solve a really hard challenge and it can very quickly wrap it up rapidly, escalate up with great velocity to senior leadership, to be an enterprise solution. >> Is there some basic training that goes on from a data standpoint? For any of those that have lived in data, oftentimes you can get lost in numbers, you have to have context, you need to understand how do I separate good from bad data, or when is data still valid? So, how does someone in the Air Force get some of that beta data competency? >> Well, we have taken a multitenant approach because each and every airman has different needs. So, we have quite a few pathfinders across the Air Force today, to help what I call, upscale our total force. And so I developed a partnership with the Air Force Institute of Technology and they now have a online graduate level data science certificate program. So, individuals studying at AFIT or remotely have the opportunity to really focus on building up their data touchpoints. Just recently, we have been working on a pathfinder to allow our data officers to get their ICCP Federal Data Sector Governance Certificate Program. So, we've been running what I would call short boot camps to prep data officers to be ready for that. And I think the one that I'm most excited about is that this year, this fall, new cadets at the U.S Air Force Academy will be able to have an undergraduate degree in data science and so it's not about a one prong approach, it's about having short courses as well as academe solutions to up skill our total force moving forward. >> Well, information absolutely is such an important differentiator(laughs) in general business and absolutely the military aspects are there. You mentioned the DOD talks about interoperability in their platform, can you speak a little bit to how you make sure that data is secure? Yet, I'm sure there's opportunities for other organizations, for there to be collaboration between them. >> Well, I like to say, that we don't fight alone. So, I work on a daily basis with my peers, Tom Cecila at the Department of Navy and Greg Garcia at the Department of Army, as well as Mr. David Berg in the DOD level. It's really important that we have an integrated approach moving forward and in the DOD we partner with our security experts, so it's not about us doing security individually, it's really about, in the Air Force we use a term called digital air force, and it's about optimizing and building a trusted partnership with our CIO colleagues, as well as our chief management colleagues because it's really about that trusted partnership to make sure that we're working collaboratively across the enterprise and whatever we do in the department, we also have to reach across our services so that we're all working together. >> Eileen, I'm curious if there's been much impact from the global pandemic. When I talk to enterprise companies, that they had to rapidly make sure that while they needed to protect data, when it was in their four walls and maybe for VPN, now everyone is accessing data, much more work from home and the like. I have to imagine some of those security measures you've already taken, but have there anything along those lines or anything else that this shift in where people are, and a little bit more dispersed has impacted your work? >> Well, the story that I like to say is, that this has given us velocity. So, prior to COVID, we built our VAULT data platform as a multitenancy platform that is also cross-domain solution, so it allows people to develop and do their problem solving in an appropriate classification level. And it allows us to connect or pushup if we need to into higher classification levels. The other thing that it has helped us really work smart because we do as much as we can in that unclassified environment and then using our cloud based solution in our gateways, it allows us to bring people in at a very scheduled component so that we maximize, or we optimize their time on site. And so I really think that it's really given us great velocity because it has really allowed people to work on the right problem set, on the right class of patient level at a specific time. And plus the other pieces, we look at what we're doing is that the problem set that we've had has really allowed people to become more data focused. I think that it's personal for folks moving forward, so it has increased understanding in terms of the need for data insights, as we move forward to drive decision making. It's not that data makes the decision, but it's using the insight to make the decision. >> And one of the interesting conversations we've been having about how to get to those data insights is the use of things like machine learning, artificial intelligence, anything you can share about, how you're looking at that journey, where you are along that discovery. >> Well, I love to say that in order to do AI and machine learning, you have to have great volumes of high quality data. And so really step one was visible, accessible data, but we in the Department of the Air Force stood up an accelerator at MIT. And so we have a group of amazing airmen that are actually working with MIT on a daily basis to solve some of those, what I would call opportunities for us to move forward. My office collaborates with them on a consistent basis, because they're doing additional use cases in that academic environment, which I'm pretty excited about because I think it gives us access to some of the smartest minds. >> All right, Eileen also I understand it's your first year doing the event. Unfortunately, we don't get, all come together in Cambridge, walking those hallways and being able to listen to some of those conversations and follow up is something we've very much enjoyed over the years. What excites you about being interact with your peers and participating in the event this year? >> Well, I really think it's about helping each other leverage the amazing lessons learned. I think that if we look collaboratively, both across industry and in the federal sector, there have been amazing lessons learned and it gives us a great forum for us to really share and leverage those lessons learned as we move forward so that we're not hitting the reboot button, but we actually are starting faster. So, it comes back to the velocity component, it all helps us go faster and at a higher quality level and I think that's really exciting. >> So, final question I have for you, we've talked for years about digital transformation, we've really said that having that data strategy and that culture of leveraging data is one of the most critical pieces of having gone through that transformation. For people that are maybe early on their journey, any advice that you'd give them, having worked through a couple of years of this and the experience you've had with your peers. >> I think that the first thing is that you have to really start with a blank slate and really look at the art of the possible. Don't think about what you've always done, think about where you want to go because there are many different paths to get there. And if you look at what the target goal is, it's really about making sure that you do that backward tracking to get to that goal. And the other piece that I tell my colleagues is celebrate the wins. My team of airmen, they are amazing, it's an honor to serve them and the reality is that they are doing great things and sometimes you want more. And it's really important to celebrate the victories because it's a very long journey and we keep moving the goalposts because we're always striving for excellence. >> Absolutely, it is always a journey that we're on, it's not about the destination. Eileen, thank you so much for sharing all that you've learned and glad you could participate. >> Thank you, STU, I appreciate being included today. Have a great day. >> Thanks and thank you for watching theCube. I'm Stu Miniman stay tuned for more from the MIT, CDO IQ event. (lively upbeat music)

>> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards brought to you by Amazon web services. >> Hi, and welcome back. I'm Stu Miniman. This is theCUBE coverage of the AWS Public Sector Partner Awards. We going to be talking about the Customer Obsession Mission award winner. So happy to welcome to the program. First of all, welcoming back Joel Lipkin. He is the chief operating officer of Four Points Technologies, which is the winner of the aforementioned award and joining him one of his customers, Ryan Hillard, who is a assistant developer with the United States, Small Business Administration, and of course the SBA, an organization that a lot of people in the United States have gotten more familiar with this year. Joel and Ryan, thanks so much for joining us. >> Hi Stu? >> Hey Stu; Thank you. >> All right, so Ryan, I'm sorry, Joel, as I mentioned, you've been on the program, but maybe just give us a sketch if you would, Four Points, your role, your partnership with AWS. >> Sure, I'm Joel Lipkin. I'm the chief operating officer at Four Points Technology, Four Points is a value added technology reseller focused on the federal government and we've been working with federal customer since 2002. We're a service disabled veteran owned small business, and we've been in a Amazon partner since 2012. >> Wonderful; Ryan, if you could, obviously, as I mentioned, the SBA, a lot of people know for the PPP in 2020, if you could tell us a little bit about your role in your organization and tee up for us, if you would, the project that Four Points was involved with that you worked on. >> Sure; so I worked for the chief information officer and I don't have this official title, but I am the de facto manager of our Amazon Web Services presence. This year, we've had a very exciting time with what's been happening in the world, the Paycheck Protection Program, and the SBA have been kind of leveraged to help the US economy recover in the face of the pandemic. And a key part of that has been using Amazon Web Services and our partnership with Four Points Technology to launch new applications to address those requirements. >> Wonderful; Joel, maybe a connect for us. How long has Four Points been working with the SBA and start to give us a little bit more about the projects that you're working together, which I understand was predated the COVID incidents. >> Sure; we've been with SBA for several years now. And SBA was one of the earlier federal agencies that really saw the value in separating their procurement for cloud capacity, from the development implementation and managed services that they either did internally or use third party contractors for. So, Four Points came in as a true value added reseller of cloud to SBA providing cloud capacity and also Amazon professionals services. >> All right; so Ryan bring us in a little bit, the project that we're talking about here, what was the challenge? What were the goals you were looking to accomplish? Help flush out a little bit, what you're doing there? >> Yeah, so most recently Four Points partnered with us to deliver Lender Gateway. Lender Gateway is an application for small community oriented lenders to submit Paycheck Protection loans. So some of these lenders don't have giant established IT departments like big banks do, and they needed an easier way to help their customers. We built that application in six days and I called the Four Points cloud manager on a Saturday, and I said, help, help, I need two accounts by three o'clock and Four Points was there for us. We got new accounts set up. We were able to build the application and deploy it literally in a week and meet the requirements set for us. And that system has now moved billions of dollars of loans. I don't know the exact amount, but has done an incredible amount of work and it wouldn't have been possible without our partnership with Four Points. So we're really excited about that. >> Yeah, If I could drill in there for a second. Absolutely it's been an unprecedented, how fast that amount of money move through the legislature to out to the end user. Help us understand a little bit, how much were you using AWS technologies and solutions that Four Points had helped you with, and how much of this was kind of a net new, you said you built a new application, you had to activate some things fast, help us understand a little bit more. >> Yeah, that's so that's a great question. So we have five major systems in AWS today. And so we're very comfortable with AWS service offerings. What's interesting about Lender Gateway is that it's the first application we've built from scratch in a totally serverless capacity. So one of the hard technical requirements of the Paycheck Protection Program is that, it has huge amounts of demand. So when we're launching a system, we need to know that that system will not go down no matter how much traffic it receives or how many requests it has to handle. So we leaned on services like AWS Lambda, S3, dynamoDB, all of their serverless offerings to make sure that under no circumstances could this application fail. And it never did. We never even actually saw a performance degradation. So a massive success from my perspective as the program manager. >> well, that's wonderful. Joel, of course, you talk about scalability, you talk about uptime. Those are really the promise the public cloud has brought. Ryan did a good job of teeing out some of the services from AWS, but help us understand architecturally how you help put that together, and, the various pieces underneath. >> Yes Stu, it's interesting. Four Points is really focused on delivering capacity. Our delivery model is very much built around giving our customers like Ryan full control over their cloud environments so that they can use it as transparently as though they were working with Amazon directly. They have access to all of the 200+ services that AWS has. They also have a direct access to billing and usage information that lets them really optimize things. So this is sort of a perfect example of how well that works because SBA and Ryan knew their requirements better than anyone. And they were able to leverage exactly the right AWS tools without having to apply to use them. It was as though they were working directly with AWS and the AWS environment on the technology side. And I will say SBA has been really a leader in using of variety of AWS services beyond standard compute and storage, not just in a tested environment, but in a live very, very robust, really large environment. >> Yeah, right, and I was excited to hear about your Lambda usage, how you're building with the serverless architecture there. Could you just bring us through a little bit, how you ramped up on that, any tools or community solutions that you were leveraging to make sure you understood that and any lessons you learned along the way as you were building that application and rolling it out? >> Yeah, that's a great question. So I think one of the mistakes that I see program managers make all the time is thinking that they can migrate a workload to the cloud and keep it architecturally the same way it was. And what they quickly find out is that their old architecture that ran in their on premise data center might actually be more expensive in the cloud than it was in their data center. And so when you're thinking about migrating a workload, you really need to come in with the assumption that you will actually be redesigning that workload and building the system in cloud native technology. You know, the concept of Lambda is so powerful, but it didn't exist for, you know, it didn't exist 20 years ago when some of these systems and applications were being written and now being able to leverage Lambda to only use exactly the compute you need, means you can literally pay pennies on the dollar. One of the interesting things about the PPP program and everything happening in the world is that our main website, sba.gov is now serving a a hundred or a thousand times more traffic daily than it was used to doing. But because we lean on serverless technology like Lambda, we have scaled non-linearly in terms of costs. So we're only paying like two or three times more than we used to pay per month, but we're doing a hundred or a thousand times more work. That's a win, that's a huge victory for cloud technology, in my opinion. >> Yeah, and on that point, I think the other thing that SBA did really amazingly well was take advantage of first reserved instances. But I think it was the day that Amazon announced savings plans as a cost control mechanism. Ryan and SBA were on them. They were our first customer to use savings plans. And I think there were probably the first customer in the federal space to use them. So it's not just using the technology smart, it's using the cost control tools really well also. >> Yeah, so Stu, I wanted to jump in here just because I'm so glad Joel brought that up. I was describing how workloads need to morph and transform as they move from legacy setups into more cloud native ones. Well, we were the first federal agency to buy savings plans. And for folks who don't know savings plans essentially make your reserved instances fungible across services. So if you had a workload that was running on EC2 before, now instead of buying a reserved instance at a certain instant size, a certain family, you can instead buy a savings plan. And when your workload is ready to be moved from EC2 to something a little bit more containerized or cloud native, like Fargate or Lambda, then you don't actually forego your reserved instance. I see program managers get into this weird spot where they bought reserved instances, so they feel like they need to use them for a whole year. So they don't upgrade their system until their reserved instances expire. And that's really the tail wagging the dog. We were very excited about savings plans. I think we bought them four days after they came out and they have enabled us to do things like, be very ambitious with how we rethink our systems and how we rebuild them. And I'm so glad you brought that up to all because it's been such a key thing over this last year. >> Yeah, it's been a really interesting discussion point I've been having the last few years, is that the role between developers and that, that finance piece. So, Ryan, who is it that advises you on this? Is there somebody on the finance team from the SBA? is it Four Points? You know, being aware of savings plan, it was something that was announced at Reinvent, but it takes a while for that to trickle and oftentimes developers don't need to think about or think that they don't need to think about the financial implications of how they're architecting things. So how, how does that communication and decision making happen? >> That's such a great question. I think it goes back to how Four Points is customer obsessed. One of our favorite things about using a small business reseller like Four Points instead of dealing directly with our cloud service provider is that Four Points provides us a service where every quarter they do an independent assessment of our systems, how much we're spending and what that looks like from a service breakdown. And then we get that perspective and that opinion, and we enrich it with our conversation with our AWS account manager, with our finance people. But having that third party independent person come in and say, "Hey, this is what we think" has been so powerful because Joel and Dana and team have always had observations that nobody else has had. And those kinds of insights are nice to have, when you have people who are suspicious of a vendor telling you to buy more things with them, because they're the vendor >> From the lessons you've learned there, any final advice that you'd give to your peers out there, and how will you take what you've learned working on this project to other things, either in the SBA or in talking with your peers in other organizations. >> So I have two big things. So one is go use a small business reseller. I would be remiss if I didn't use this opportunity to tell you as a member of the US Small Business Administration, that there are some really, really great service providers out there. They are part of our programs like Four Points, and they can help you achieve that balance between trusting your cloud service provider and having that a third party entity that can come in and, call bowl and also call Yahtzee. So recognize good things and recognize bad things. So that would be number one. And then number two is moving to the cloud is so often sold as a technology project. And it's like 20% technology and 80% culture and workforce change. And so be honest with yourselves and your executive teams that this isn't a technology project. This is, we going to change how we do business project, and we going to change the culture of this organization kind of project. >> All right; and Joel, I'll let you have the final word on lessons learned here and also about Four Points and congratulations again, the Customer Obsession Mission award winner. >> Great, thanks Stu, we're so appreciative to Amazon for their recognition and to Ryan and SBA for giving us the opportunity to support such an important program. We are a small business, we are very much focused on delivering what our customers need in the cloud. And it's just such a tremendous feeling to be able to work on a program like this that has such, such payoff for the whole country. >> All right, Well, Joel and Ryan, thank you so much for sharing your updates, such an important project this year. Thanks so much. >> Thank you Stu. >> Thanks >> Stay with us for more covered from the AWS Public Sector Partner awards. I'm Stu Miniman, and thank you for watching theCUBE.

>> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards brought to you by Amazon web services. >> Hi, and welcome back, I'm Stu Miniman and we're here at the AWS Public Sector. Their Partner Awards, really enjoying this. We get to talk to some of the diverse ecosystem as well as they've all brought on their customers, some really phenomenal case studies. Happy to welcome to the program two first time guests. First of all, we have Jared Bell, he's the Chief Engineer of self response, operational readiness at T-Rex Solutions and T-Rex is the award winner for the most customer obsessed mission-based in Fed Civ. So Jared, congratulations to you and the T-Rex team and also joining him, his customer Michael Thieme, he's the Assistant Director for the Decennial Census Program systems and contracts for the US Census Bureau, thank you so much both for joining us. >> Good to be here. >> All right, Jared, if we could start with you, as I said, you're an award winner, you sit in the Fed Civ space, you've brought us to the Census Bureau, which most people understand the importance of that government program coming up on that, you know, every 10 year we've been hearing, you know, TV and radio ads talking about it, but Jared, if you could just give us a thumbnail of T-Rex and what you do in the AWS ecosystem. >> So yeah again, my name's Jared Bell and I work for T-Rex Solutions. T-Rex is a mid tier IT federal contracting company in Southern Maryland, recently graduated from hubs on status, and so T-Rex really focuses on four key areas, infrastructure in Cloud modernization, cybersecurity, and active cyber defense, big data management and analytics, and then overall enterprise system integration. And so we've been, you know, AWS partner for quite some time now and with decennial, you know, we got to really exercise a lot of the bells and whistles that are out there and really put it all to the test. >> All right, well, Michael, you know, so many people in IT, we talk about the peaks and valleys that we have, not too many companies in our organization say, well, we know exactly, you know, that 10 year spike of activity that we're going to have, I know there's lots of work that goes on beyond that, but it tells a little bit , your role inside the Census Bureau and what's under your purview. >> Yes, the Census Bureau, is actually does hundreds of surveys every year, but the decennial census is our sort of our main flagship activity. And I am the Assistant Director under our Associate Director for the IT and for the contracts for the decennial census. >> Wonderful and if you could tell us a little bit the project that you're working on, that eventually pulled T-Rex in. >> Sure. This is the 2020 census and the challenge of the 2020 census is we've done the census since 1790 in the United States. It's a pillar, a foundation of our democracy, and this was the most technologically advanced census we've ever done. Actually up until 2020, we have done our censuses mostly by pen, paper, and pencil. And this is a census where we opened up the internet for people to respond from home. We can have people respond on the phone, people can respond with an iPhone or an Android device. We tried to make it as easy as possible and as secure as possible for people to respond to the census where they were and we wanted to meet the respondent where they were. >> All right. So Jared, I'd love you to chime in here 'cause I'm here and talking about, you know, the technology adoption, you know, how much was already in plans there, where did T-Rex intersect with this census activity? >> Yeah. So, you know, census deserves a lot of credit for their kind of innovative approach with this technical integrator contract, which T-Rex was fortunate enough to win. When we came in, you know, we were just wrapping up the 2018 test. we really only had 18 months to go from start to, you know, a live operational tests to prepare for 2020. And it was really exciting to be brought in on such a large mission critical project and this is one of the largest federal IT products in the Cloud to date. And so, you know, when we came in, we had to really, you know, bring together a whole lot of solutions. I mean, the internet self response, which is what we're going to to talk about today was one of the major components. But we really had a lot of other activities that we had to engage in. You know, we had to design and prepare an IT solution to support 260 field offices, 16,000 field staff, 400,000 mobile devices and users that were going to go out and knock on doors for a numeration. So it was real6ly a big effort that we were honored to be a part of, you know, and on top of that, T-Rex actually brought to the table, a lot of its past experience with cybersecurity and active cyber defense, also, you know, because of the importance of all this data, you know, we had the role in security all throughout, and I think T-Rex was prepared for that and did a great job. And then, you know, overall I think that, not necessarily directly to your question, but I think, y6ou know, one of the things that we were able to do to make ourselves successful and to really engage with the census Bureau and be effective with our stakeholders was that we really build a culture of decennial within the technical integrator, you know, we had brown bags and working sessions to really teach the team the importance of the decennial, you know, not just as a career move, but also as a important activity for our country. And so I think that that really helped the team, you know, internalize that mission and really drove kind of our dedication to the census mission and really made us effective and again, a lot of the T-Rex leadership had a lot of experience there from past decennials and so they really brought that mindset to the team and I think it really paid off. >> Michael, if you could bring us inside a little a bit the project, you know, 18 months, obviously you have a specific deadline you need to hit, for that help us understand kind of the architectural considerations that you had there, any concerns that you had and I have to imagine that just the global activities, the impacts of COVID-19 has impacted some of the end stage, if you will, activities here in 2020. >> Absolutely. Yeah. The decennial census is, I believe a very unique IT problem. We have essentially 10 months out of the decade that we have to scale up to gigantic and then scale back down to run the rest of the Census Bureau's activities. But our project, you know, every year ending in zero, April 1st is census day. Now April 1st continued to be census day in 2020, but we also had COVID essentially taking over virtually everything in this country and in fact in the world. So, the way that we set up to do the census with the Cloud and with the IT approach and modernization that we took, actually, frankly, very luckily enabled us to kind of get through this whole thing. Now, we haven't had, Jared discussed a little bit the fact that we're here to talk about our internet self response, we haven't had one second of downtime for our response. We've taken 77 million. I think even more than 78 million responses from households, out of the 140 million households in the United States, we've gotten 77 million people to respond on our internet site without one second of downtime, a good user experience, a good supportability, but the project has always been the same. It's just this time, we're actually doing it with much more technology and hopefully the way that the Cloud has supported us will prove to be really effective for the COVID-19 situation. Because we've had changes in our plans, difference in timeframes, we are actually not even going into the field, or we're just starting to go into the field these next few weeks where we would have almost been coming out of the field at this time. So that flexibility, that expandability, that elasticity, that being in the Cloud gives all of our IT capabilities was really valuable this time. >> Well, Jared, I'm wondering if you can comment on that. All of the things that Michael just said, you know, seem like, you know, they are just the spotlight pieces that I looked at Cloud for. You know, being able to scale on demand, being able to use what I need when I need it, and then dial things down when I don't, and especially, you know, I don't want to have to, you know, I want to limit how much people actually need to get involved. So help understand a little bit, you know, what AWS services underneath, we're supporting this and anything else around the Cloud deployment. >> Sure, yeah. Michael is spot on. I mean, the cloud is tailor made for our operation and activity here. You know, I think all told, we use over 30 of the AWS FedRAMP solutions in standing up our environment across all those 52 system of systems that we were working with. You know, just to name a few, I mean, internet self response alone, you're relying heavily on auto scaling groups, elastic load balancers, you know, we relied a lot on Lambda Functions, DynamoDB. We're one of the first adopters through DynamoDB global tables, which we use for a session persistence across regions. And then on top of that, you know, the data was all flowing down into RDS databases and then from there to, you know, the census data Lake, which was built on EMR and Elasticsearch capabilities, and that's just to name a couple. I mean, you know, we had, we ran the gamut of AWS services to make all this work and they really helped us accelerate. And as Michael said, you know, we stood this up expecting to be working together in a war room, watching everything hand in hand, and because of the way we, were able to architect it in partnership with AWS, we all had to go out and stay at home, you know, the infrastructure remain rock solid. We can have to worry about, you know, being hands on with the equipment and, you know, again, the ability to automate and integrate with those solutions Cloud formation and things like that really let us keep a small agile team of, you know, DevSecOps there to handle the deployments. And we were doing full scale deployments with, you know, one or two people in the middle of the night without any problems. So it really streamlined things for us and helped us keep a tight natural, sure. >> Michael, I'm curious about what kind of training your team need to go through to take advantage of this solution. So from bringing it up to the ripple effect, as you said, you're only now starting to look at who would go into the field who uses devices and the like, so help us understand really the human aspect of undergoing this technology. >> Sure. Now, the census always has to ramp up this sort of immediate workforce. We hire, we actually process over 3 million people through, I think, 3.9 million people applied to work for the Census Bureau. And each decade we have to come up with a training program and actually training sites all over the country and the IT to support those. Now, again, modernization for the 2020 census, didn't only involve the things like our internet self response, it also involves our training. We have all online training now, we used to have what we called verbatim training, where we had individual teachers all over the country in places like libraries, essentially reading text exactly the same way to exactly over and over again to our, to the people that we trained. But now it's all electronic, it allows us to, and this goes to the COVID situation as well, it allows us to bring only three people in at a time to do training. Essentially get them started with our device that we have them use when they're knocking on doors and then go home and do the training, and then come back to work with us all with a minimal contact, human contact, sort of a model. And that, even though we designed it differently, the way that we set the technology of this time allowed us to change that design very quickly, get people trained, not essentially stop the census. We essentially had to slow it down because we weren't sure exactly when it was going to be safe to go knocking on door to door, but we were able to do the training and all of that worked and continues to work phenomenally. >> Wonderful. Jared, I wonder if you've got any lessons learned from working with the census group that might be applicable to kind of, the broader customers out there? >> Oh, sure. Well, working with the census, you know, it was really a great group to work with. I mean, one of the few groups I worked with who have such a clear vision and understanding of what they want their final outcome to be, I think again, you know, for us the internalization of the decennial mission, right? It's so big, it's so important. I think that because we adopted it early on we felt that we were true partners with census, we had a lot of credibility with our counterparts and I think that they understood that we were in it with them together and that was really important. I would also say that, you know, because we're talking about the go Cloud solutions that we worked, you know, we also engage heavily with the AWS engineering group and in partnership with them, you know, we relied on the infrastructure event management services they offer and was able to give us a lot of great insight into our architecture and our systems and monitoring to really make us feel like we were ready for the big show when the time came. So, you know, I think for me, another lesson learned there was that, you know, the Cloud providers like AWS, they're not just a vendor, they're a partner and I think that now going forward, we'll continue to engage with those partners early and often. >> Michael the question I have for you is, you know, what would you say to your peers? What lessons did you have learned and how much of what you've done for the census, do you think it will be applicable to all those other surveys that you do in between the big 10 year surveys? >> All right. I think we have actually set a good milestone for the rest of the Census Bureau, that the modernization that the 2020 census has allowed since it is our flagship really is something that we hope we can continue through the decade and into the next census, as a matter of fact. But I think one of the big lessons learned I wanted to talk about was we have always struggled with disaster recovery. And one of the things that having the Cloud and our partners in the Cloud has helped us do is essentially take advantage of the resilience of the Cloud. So there are data centers all over the country. If ever had a downtime somewhere, we knew that we were going to be able to stay up. For the decennial census, we've never had the budget to pay for a persistent disaster recovery. And the Cloud essentially gives us that kind of capability. Jared talked a lot about security. I think we have taken our security posture to a whole different level, something that allowed us to essentially, as I said before, keep our internet self response free of hacks and breaches through this whole process and through a much longer process than we even intended to keep it open. So, there's a lot here that I think we want to bring into the next decade, a lot that we want to continue, and we want the census to essentially stay as modern as it has become for 2020. >> Well, I will tell you personally Michael, I did take the census online, it was really easy to do, and I'll definitely recommend if they haven't already, everybody listening out there so important that you participate in the census so that they have complete data. So, Michael, Jared, thank you so much. Jared, congratulations to your team for winning the award and you know, such a great customer. Michael, thank you so much for what you and your team are doing. We Appreciate all that's being done, especially in these challenging times. >> Thank you and thanks for doing the census. >> All right and stay tuned for more coverage of the AWS public sector partner award I'm Stu Miniman and thank you for watching theCUBE. (upbeat music)

I met with some CIOs yesterday from the state local government now that has been a super surprising market for me where I'm seeing them actually 2018 was a true change of the year for them massive workloads in the state Medicaid systems that are moving off of legacy systems on AWS justice and public safety systems moving off on AWS so that's where you're seeing news but you know what they shared with me yesterday and my theme as you saw today was removing barriers but they talked about acquisition barriers still that states still don't know how to buy cloud and they were asking for help can you help kind of educate and work with our acquisition officials so it's nice when they're asking us for help in areas that they see their own lockers Cyber Command cannot see today attacks on our country so they're left to try to go after the offense but all the offense has to do is hit over here they're looking at these sets of targets there you don't see the attacks so they wouldn't have seen the attack on Sony they don't see these devastating attacks they don't see the thefts so the real solution to what you bring up is make it visible make it so our nation can defend itself in cyber by seeing the attacks that are hitting us that should help us protect companies and sectors and help us share that information it has to be at speed so we talk about sharing but it's senseless for me to send you for air traffic control a letter that a plane is located at overhead you get it in the mail seven days later you think fighting blindfolded that's right I mean you can't do either and so what it gets you to is we have to create the new norm for visibility in cyberspace this does a whole host of things and you were good to bring out it's also fake news it's also deception it's all these other things that are going on we have to make that visible so what ground station is is it's a service that you can use like any other cloud service just pay for what you use on demand you can scale up you can scale down and we think that we're in the early stages of opening up innovations in this industry where an AWS announced a partnership in October 2016 and it really was the coming together of the best in the public cloud with the best of the private cloud for what we describe as the hybrid cloud opportunity in the past two and a half years coming up on three years pretty soon has been incredibly exciting we started off with some of the key industries that we fell for us public sectors are among our top three industries by financial services telco public sector healthcare manufacturing all the key industries technology we're looking for ways by which they could take their applique into the cloud without having to refactor Andry platform those applications that's a big deal because it's wasted work if you could lift and shift and then innovate and that's the value we brought to the public sector and some of our earliest customers were customers in the public sector like MIT schools about both of the regulated industries in the on-premise world were very strong in almost every civilian military the legislative branch the judicial branch the federal agencies all of them use us millions and millions of workloads the question really is how is they think about modernization and yet they get the best benefits of the public cloud while leveraging their VMware footprint at FINRA we have a very deliberate technology strategy and we constantly keep pace with technology in order to affect our business in the best possible way we always are looking for means to get more efficient and more effective and use our funding for the best possible business value so to that end we are completely in the cloud for a lot of our market regulation operations all the applications are in the cloud we in fact we were one of the early adopters of the cloud from that perspective all of our big data operations were fully operational in the cloud by 2016 itself that was itself a two-year project that we started in 2014 then from 2016 we have been working with machine language and recently over the past six months or so we've been working with neural networks so this was an opportunity for us to share what where we have been where we are coming from where we are going with the intent that whatever we do by way of principles can be adopted by any other enterprise we are looking to share our journey and to encourage others to adopt technology that's really I mean the problems that could be solved with technology now for good will I think will outweigh the technology for hill as Jay Carney calls it so right now when everyone's talking about Facebook and all this nonsense that happened with the elections I think is that's pretty visible that's painful for people to kind of deal with but then the reality is that never should have happened I think you're gonna see a resurgence of people that are going to solve problems and if you look at the software developer persona over the past 10 to 15 years it went from hire some developers build a product ship it market and make some money to developers being the front lines power players in software companies they're on the front lines they're making changes they're moving fast creating value I see that kind of paradigm hitting normal people where they can impact change like a developer would for an application in society I think you're gonna have younger people solving all kinds of crisis around whether it's hopefully crisis healthcare these problems will be solved at a-- will be a big catalyst a great example it would be when you think about all these siloed organizations within our community care you're unable to track any one one record and the record could be an individual or an organization so well what they're doing is they're moving all those disparate data silos into an opportunity to say let's do how many constituents do we have what type of services do they need how do we become proactive so when you take a look at someone who's moved into the community and their health record comes in what are the services that they need because right now they have to go find those services and if the county were to do things more proactively say hey these are the services that you need here's where you can actually go and get them and it's it's those individual personalized engagements that once you pull all that data together through all the different organizations from the beginning of a 911 for whatever reason through their health record to say this is the care that they need they these are the cares that they have and these are the services that they need and oh by the way they might be allergic to something or they might have missed a doctor's appointment let's go ensure that they're getting the health care there's one state that's actually even thinking about their senior care why don't we go put an Alexa in their house to remind them that these are the medications that you need you have a doctor's appointment at 2:00 o'clock do you want me to order a ride for you to get to your doctor's appointment on time that is proactive you walk around the expo floor here the booths are much smaller and I didn't understand that at first and then it quit for me if you want to sell services to government you don't buy a bigger booth you buy a congressperson and it turns out those are less expensive many technologies can be used for for good or for ill we we have a service at AWS a facial recognition service we're certainly not the only company that provides that service to customers thus far since Amazon recognition has been around we've had reports of thousands of positive uses - you know finding missing children breaking up human sex trafficking human trafficking rings assisting law enforcement in positive ways we haven't heard yet any cases of abuse by law enforcement but we certainly understand that that potential exists and we we encourage regulators and lawmakers to look closely at that we've put forth publicly guidelines that we think would be useful as they build a legislative or regulatory framework you

yeah I probably would use a sort of ever-changing I would say ever-expanding you know but you have to write because what we saw when we started off is roll around how to automate my datacenter how do I get a cloud experience in my data center what we see changing and okay Frank is driven by this whole app refactoring process that customers want to deploy apps maybe in the cloud maybe develop in the cloud and so they need an extension to the automated data center into the cloud and so really what you see from us is an expansion of that ACA concept you rangas point we actually really didn't change we just we're just extending it to container development platforms two different cloud environments what's the same area automate end-to-end network reach as well as the segmentation what is the right there right sorry security regime in this you know cloud era how is it evolving well I mean what we're doing is we're bringing tools like tetration which now runs on Prem and in the cloud things like stealthWatch which runs on from in the cloud and simply bringing them security frameworks that are very effective we're I think a very capable of well known security vendor but bringing them the capability to run the same capabilities in their on-prem environments and their data centers as well as in multiple public clouds and that just eliminates the seams that hackers could maybe get into it makes common policy Possible's they can define policy around an application once and have that apply across the vault environments which not only it's easier for them but it eliminates potential mistakes that they might make that might leave things open to a hacker so for us it's that simple bringing very effective common frameworks for security across all these cisco has embraced the idea of being a platform and not a siloed individual product line and so for a service provider like CenturyLink for us to be able to embrace that same philosophy of the platform of services what that means is that our engineering and field ops folks our Operations teams do all the hard work on the back end to make sure that we have established all of the right security the right network the reliability the global scalability of our specific platform of services and being that leader in telecommunications and then we're able to lay that cisco platform on top of it and what happens then from a product management level is once you've established that foundation it's really plug-and-play the customer calls and says I need calling I need meetings I need you know whatever it is they need and we build that solution and very quickly can put those components into play and get them to use the service right away so what we've done across the portfolio even in primary storage is made sure that we've done all sorts of things that help you against a ransomware a malware attack keep the data encrypted I think the key point and actually I think Silicon angle wrote about this is like some like 98% of all enterprises getting a broke it in two anyway so it's great that you've got security software on the edge with at the IBM or RSA or blue coat or checkpoint oh who cares who you buy the software from but when they're in there stealing and sometimes you know some accounts have told us they can track them down in a day but if you're a giant global fortune 500 datacenter look it may take you like a week so they can be stealing stuff right and left so we've done everything from we have right once technology right so it's immutable data you can't change it we've got encryption so if they steal it guess what they can't use it but the other thing we've done is real protection against ransomware now that's a great question in terms of modernization of infrastructure and there's some really interesting trends that I think are occurring and I think the one that's getting a lot of us is really edge computing and what we're finding is depending on the use case it can be an enterprise application where you're trying to get localization of your data it could be an IOT application where it's it's really critical for latency or bandwidth to keep compute and data close to the thing if you will or it could be mobile edge computing where you want to do thing like analytics and AI on a video stream before you tax the the bandwidth of the cellular infrastructure with that data stream so across the board I think edge is super exciting and you can't talk about edge with like I said talking about artificial intelligence another big trend whether it's running native running with an accelerator an FPGA I think we're seeing a myriad of use cases in that space but Security's in the end to your point right I've got software to find access I've got mobile access points I've got you know tetration I've got you know all of these products that are helping people that in the past they were just patching holes in the dike you know hey this happened let's put this software product here this happened let's put this in and we actually built the security practice like the last three or four years ago it's growing you know the number of people that are whether it's regulation compliance you know I got some real problem I think I've got a problem and I don't know what it is our ability to come back and sit down and say let's evaluate what your situation is so I was talking to the networking guys and so Wow enterprise networking it's up way up what's driving that the need to transform or is that you know what is it they're like a lot of times it's something are long security that's making them step back and reevaluate and then sometimes that transfer translates into an entire network refresh there are tools that people use and everybody's environments a little different so some might want to integrate in and use ansible terraform you know tools like that and so then you need code that will help integrate into that other people are using ServiceNow for tickets so if something happens integrate into that people are using different types of devices hopefully mostly Cisco but they may be other using others as well we can extend code that goes into that so it really helps to go in different areas and what's kind of cool is that our there's an amount of code that where people have the same problems you know and you know you start doing something everyone has to make the first few kind of same things in software let's get that into exchange and so let's share that there's places where partners are gonna want to differentiate keep that to yourselves like use that as your differentiated offer and then there's areas where people want to solve in communities of interest so we have we have someone who does networking and he wants to do automation he does it for power management in the utilities industry so he wants a community that will help write code that'll help for that area you know so people have different interests and you know we're hoping to help facilitate that because Cisco actually has a great community we have a great community that we've been building over the last 30 years there the network experts they're solving the real problems around the world they work for partners they work for customers and we're hoping that this will be a tool to get them to band together and contribute in a in a software kinda way they have the right reason to be afraid because so many automation was created a once user exactly was right and then you have the cost of traditional automation you have the complexity to create a network automation you guys realize that middle coordination you cannot have little automation only work on a portion of your needle you have to work on majority if not all of your needle right so that's became very complex just like a you wanna a self-driving car you can go buy a Tesla a new car you can drive on its own but if you wanna your 10 year order Toyota driving on its own richer feared that's a very complex well let's today Network automation how to deal with it you have to deal with multi vendor technology Marty years of technology so people spend a lot of money the return are very small they so they have a right to affair afraid of it but the challenge is there is what's alternative yeah I think that is one of the things that's very unique about the definite community is within the community we have technical stakeholders from small startups to really large partners or huge enterprises and when we're all here in the demo soon we're all engineers and we're all exchanging ideas kind of no matter what the scale so it becomes this great mixing of you know shared experiences and ideas and that is some of the most interesting conversations that I've actually heard this week is people talking about how maybe they're using one Cisco platform in these two very different environments and exchanging ideas about how they do that or maybe how they're using a Cisco platform with an open-source tool and then people finding value in thinking oh maybe I can do that in my environment so that part of the ecosystem and community is very interesting and then we're also helping partners find each other so we do a lot of work around you know here's a partner in the Cisco ecosystem who goes and installs Meraki networks right here's a software partner who builds mapping technology on top of indoor Wi-Fi networks and getting those two together because the software partner is not going to install the network and the network person may not write that application in that way and so bringing them together we've had a lot of really good information coming back from the community around kind of finding each other and being able to deliver those outcomes what are you guys doing Tom we'll start with you how are you guys working together to infuse and integrate security into the technologies and that from a customer's perspective those risks that dial down yeah so so we're in Cisco's integrating security across all of our product portfolio right and and that includes our data center portfolio all the way through our campus our when all those portfolios so we continue to look for opportunities to to integrate you know whether it's dual factor authentication or things like secure data center with a fire you know of highly scalable multi instance firewall in front of a data center things like that so we're we're definitely looking for areas and angles and opportunities for us to not only integrate it from a product standpoint but also ensure that we are talking that story with our customers so that they know they can they can leverage Cisco for the full architecture from a security standing on the storage of the data from an encryption perspective and as it gets moved or his mobile you know that that level of security and policy follows it you know wherever the data is secure of course enemy everybody always wants more performance they want lower cost security in many ways has begun to trump those other two attributes they've they've become table stakes security as well but security is really number one now ya talk about that talk about the major trends that you're seeing well of course of course security now is top of mine for everyone board level conversations executive level conversations all the time I think what ends up happening is in the past we would think about it as Network performance cost etc security as a tangent kind of side conversation now of course it's built into everything that we do [Music]

>> Announcer: Live from San Francisco, celebrating 10 years of high tech coverage, it's theCUBE. Covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> Welcome back to bright and sunny San Francisco. Gorgeous day here in the City on the Bay. Dave Vellante, John Walls. We continue our coverage here on theCUBE VMworld 2019 with Doc D'Errico from Infodant, CMO. Doc, good to see you again, sir! >> Infinidat. >> Oh Infinidat! Sorry, sorry, sorry. (Doc laughs) But, good to see you! >> I missed my opportunity but thanks, Dave, yeah, it's good to be back. >> John: You bet. Marc Creviere, who is principle systems engineer at US Signal. Good to see you again, Marc here. You were here just last year, right? >> Yeah, I'm an alumni now. >> We'll touch base on that in just a little bit. Doc, first off, let's just talk about the show from your perspective. What you're doing here, explain to our viewers at home what it's all about and what you find the vibe that's going on this year. What kind of sense do you get? >> The vibe is fantastic The sense is great. Coming back to San Francisco, I'm not sure what we were really expecting but it's a really good tempo, a lot of great people, lot of great feedback on our recent launch. A lot of people looking at what're we doing, especially with VMware and availability. Lots of new use cases for snapshot technologies which is fantastic. The 100% availability, it's great getting people come up to you who say "Hey, this is incredible. "You guys actually put some teeth behind your guarantees," "you know, you're not just promising "some future discounts or something. "In the VMworld environment where I've got my VMs, "I need that kind of guarantee, I need that support. "I need to know that my systems "are going to be there when I need them, "because that's my business," right? It's just an incredible vibe. >> And had your party last night? >> We had our party last night. And guess who was there? (laughs) >> I did stop by, it was a very cool venue. The San Francisco Mint, which is, it was kind of awesome. >> Yeah, it was a great, great environment. It was great having people like Dave there, and some of the other industry luminaries talk to our customers. >> I didn't get the tour of the Vault. >> Doc: I'll get you a picture. (laughing) >> So, Marc, I mentioned in the intro, we had you on last year. So, let's look back at the last 12 months for you. US Signal, and what's been going on with you, and what are you seeing here and kind of feeling here in terms of business? >> Yeah, thanks for having me back. It's been another great year at US Signal. We are planning on opening a new data center in the Detroit Metro area, coming up online Q1 of 2020, so that's exciting for us. Purpose built, wholly owned and operated by us, so that's great. It's going to add to our capabilities in that region. We've had a heavy focus on DR technologies, DR as a Service technologies in the past year. Seeing a lot of success, a lot of really good conversations with customers and developing their plans, and bringing our new capabilities to be able to service those needs. >> So, tell us more about the DR as a Service. I mean, that's obviously one of the early sort of cloud-use cases? >> Marc: Yeah. >> Add some color, what is it all about, how does it relate to some of the other DR solutions that are out there and what role do these guys play? >> Yeah, well we conducted a survey of a little over 100 of companies in our region, a little over 100 respondents, and three out of four respondents told us that their biggest concerns were either distributed denial of service or ransomware. Obviously, we've got these bad actors out there. And it doesn't necessarily have to be a bad actor, it could be something force of nature making data unavailable, right? It doesn't matter how great the equipment is if either a bad actor or nature takes it out for you. So, having that protection, we're able to have replication technology. We actually have three separate technologies that we use now. We enhanced our Zerto-based offering to include multi-cloud so we can now have customers replicate to either multiple cloud destinations, us being one of them, or they can replicate to one of their sites and us as a tertiary site, so that's new. They're able to bring their existing licensing. One thing that's exciting to me, near and dear to my heart, is drafts for VMware based on the vCloud availability platform. So, we're a big VM, vCloud shop, big consumer of VMware technologies, that's why we're out here, and that's really exciting to me because it uses built in VMware replication technologies. There's not a lot of learning curve, there's not a lot of extra components. Super simple to get up and running and get RPOs as low as 5 minutes, and it's easy, and it's relatively cheap on an OPX-type platform, where you're paying for storage and per VM and that's it. And then we've also spun up a replication for Veeam, Cloud replication for Veeam based on that ecosystem. So, we've got a lot of entry points, a lot of different ways that we can protect that data and bring it in and get a copy in our data center, so in the event that it becomes unavailable at the source, it's either managed or customer managed. We can get it up and running in a short time frame on our infrastructure. >> And Infinidat is the primary storage underneath all this? >> Marc: Yeah. >> So, explain more about... So, Doc, you and I have had these conversations. The state of the art, whatever, 15 years ago, was three-site data centers, very complex, extremely expensive. I'm interested in how we're attacking that problem today. You obviously, with multi cloud, it's multi-site, but how are we attacking the cost problem, the complexity problem, the "I can't test because I can fail over "but I'm afraid to fail back" problem? >> Well, you know, there's so many different ways to cover all of these. We're talking just about ransomware, you know, ransomware are immutable snaps, become an important play and we have Snap Rotator which will allow you to build a certain number of snaps and have them just rotate through so you're not just creating an infinite number, you're not wasting time and space. And, by the way, time and space, our snapshots are zero-overhead. There's zero performance penalty, unless you want to crash consistent copy, and there's really zero data overhead because it's only the incremental data that you write. So, by creating this, you can do it every couple seconds, and then create some immutable copies of that. You know, make them time out, so they can't be modified, 30 days, 60 days, whatever you decide administratively. So that's great. If you're looking for the DRaaS, the DR as a Service-type capabilities, whether it's single site or multi site, going to cloud service providers makes a lot of sense. 'Cause now, even if it's on premises to a cloud service provider, now you're not having to worry about that second set of infrastructure, you're not having to worry about the management of it, you're not having to worry about the systems integration of it, or even go CSP to CSP, right? Go from one data center within your favorite cloud service provider, hopefully US Signal, to another or any one of our great partners would be super, too. And then, of course, InfiniSync, where if you really want that longer distance capability, why bother with a bunker site? Why bother with all that complexity and that cost and overhead? Put in an InfiniSync appliance in with a VM, and you've got the recoverability. You can go asynchronous distances, and have a zero RPO. >> For way, way less. >> Oh, a fraction of the cost. It'll cost you less for the InfiniSync appliance than it'll cost you for the telecoms equipment that you need for a bunker site. >> If I don't want to build another data center... Go ahead. >> What I'm curious about; I heard a number yesterday in one of the interviews we had, about ransomware. The number kind of blew me away, and I thought about one out of every three companies will be a victim of, or at least a ransomware attack within the next two years, which means everyone, over the next six, if you extrapolate that out. Does that sound about right from what you're seeing? That the intrusions are reaching that kind of frequency? >> I'm surprised it's that low, but I'll let Marc try and answer that. >> We've done some events where we actually demo how easy it is, like, through a phishing attack, to get that in there. So, it's not just about having those protections in place, it's your user training; that's a huge area, training those users what to look for in those emails to avoid that sort of thing, but it's not perfect. People are imperfect. >> Dave: And yeah, you got to have both the protection on the front end, the training for the people, and those recovery options in the event it does get in. In our survey, the average monetary damage was over $150,000 per incident. And that means that some people got off a little lighter and some people paid a lot more, if that was the average. >> Should you pay the ransom? >> Uh, not if you've got a good plan in place that can test it. (laughs) >> But it is, it's a reasonable question. >> Huge quandary. Some are, some aren't, right? Atlanta says "no, we're going to pay a boatload "to protect against it, but we're not going to pay that," what was it, 55,000 or whatever it was? >> Let's negotiate. >> Yeah, I think I said last time I was here that until you've tested your plan, you don't really have one. You know, it rings just as true today. >> What's your business worth? I mean, it's a great question, really. What is your business worth to you? Your business is probably worth a lot more, and they probably throw these numbers out there, thinking "Well...", then becomes a no-brainer for you to pay, and that's the whole point. Because what is ransomware? It's malware that's recoverable, maybe. You're not even sure of that. >> Is it usually, is it operator error? Is it human error that allows that to work more often than not? Or, is it a mixture of technical chops, or just...? >> It's a mixture; you've got to know what vulnerabilities are out there on your infrastructure, you got to make sure you're staying up to date on patching those vulnerabilities, paying attention to any compliance practices, if you're a compliant organization. You know, HIPAA, PCI, our entire infrastructure footprint is actually HIPAA and PCI compliant at the levels that we control. So, it's a heavy lift. You got to stick with it. >> But just to kind of bring it full circle to the comment about the ransom and paying it, you know Marc said something really important, "Have a good plan." I would argue, have a good partner. If you don't have a CISO who's got the chops to be dealing with these types of problems, that's when you need a partner like US Signal to really step in and take you through what's involved in a realistic plan, something that's not going to break the bank, something that's really going to protect your business going forward, because these things are very real. >> One of the concerns I have in this topic is that things happen really fast these days. So, if there are problems, they replicate very, very quickly. How do you address that problem? Is it architecture, analytics, I'm sure process, maybe you could add some color to that. >> All of the above. Having those controls in place, those segregations, we've got, obviously, clear segregation between our management and customer data plans. And each of our customer data plans are separate from each other. It's secure multi-tenancy, not just multi-tenancy. So yeah, it's important to keep those delineations, user access, making sure that people only have access to what they need, and a lot of that, again, is covered by those compliance practices and paying close attention to what they have. There are reasons they have these guidelines and these rules and these audits. It's to help, in large part to protect against that. >> You mentioned before, Marc, you're a heavy VMware user, Infinidat, it's kind of the new kid on the block. People said "Oh, they'll never be--" >> Marc: Not for us. >> What's that? >> Not for us. >> Not for you, right, but for the storage industry. Doc and I have been in the storage industry a while. But, I'm curious as to what you want from a supplier like Infinidat, why you chose Infinidat? How're they doing with regard to VMware affinity, all those things people tend to talk about as important. >> Marc: All right, well-- >> What do you think is important? >> Well, in the Infinidat experience, the company experience, the support experience, it is the benchmark by which we judge all other vendors now. It's that good. The working with us whenever we need equipment, obviously they've got, the price per terabyte is hard to beat with the way they're able to leverage that technology. The responsiveness, if we've needed something in a hurry they've been able to get it to us in a hurry, It ties in extremely well with our infrastructure because we scale so quickly, right? Trends are very hard with us, because there's all these hockey sticks. It's going, going, going, we get a big order and it goes up really fast. I think the theme right now is scale to win? >> Yep. >> So that resonates with us because by having that in place and having that scale ready to go, we don't even need to anticipate those hockey sticks because it's already there. >> Great. Well, gentlemen, thanks for the time. We appreciate that. Doc, Infinidat. (laughs) >> Thank you very much it's great to see you both again. >> John: Look forward to see you in 2020, right? >> I'll be back. >> Yeah, it's become an annual thing. >> Michael said we'll be celebrating our 20th year, so I'm looking forward to seeing-- >> And this is our 10th year here, so anniversaries all across the board. >> Congratulations. >> Congratulations. >> Have a good rest of the show, we appreciate the time. >> Thank you very much. >> Thank you. >> Back with more VMworld 2019, we continue our coverage live here on theCUBE. We're at Moscone Center North in San Francisco. (upbeat electronic music)

>> from Cambridge, Massachusetts. It's the Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to Cambridge, Massachusetts. Everybody watching the Cuban leader live tech coverage. We here covering the M I t CDO conference M I t CEO Day to wrapping up. Bob Parr is here. He's a partner in principle at KPMG, and he's joined by Streetcar Krishna, who is the managing director of data science. Aye, aye. And innovation at KPMG. Gents, welcome to the Cube. Thank >> thank you. Let's start with your >> roles. So, Bob, where do you focus >> my focus? Ah, within KPMG, we've got three main business lines audit tax, an advisory. And so I'm the advisory chief date officer. So I'm more focused on how we use data competitively in the market. More the offense side of our focus. So, you know, how do we make sure that our teams have the data they need to deliver value? Uh, much as possible working concert with the enterprise? CDO uh, who's more focused on our infrastructure, Our standards, security, privacy and those >> you've focused on making KPMG better A >> supposed exactly clients. OK, >> I also have a second hat, and I also serve financial service is si Dios as well. So Okay, so >> get her out of a dual role. I got sales guys in >> streetcar. What was your role? >> Yeah, You know, I focus a lot on data science, artificial intelligence and overall innovation s o my reaction. I actually represent a centre of >> excellence within KPMG that focuses on the I machine learning natural language processing. And I work with Bob's Division to actually advance the data site off the store because all the eye needs data. And without data, there's no algorithms, So we're focusing a lot on How do we use a I to make data Better think about their equality. Think about data lineage. Think about all of the problems that data has. How can we make it better using algorithms? And I focused a lot on that working with Bob, But no, it's it's customers and internal. I mean, you know, I were a horizontal within the form, So we help customers. We help internal, we focus a lot on the market. >> So, Bob, you mentioned used data offensively. So 10 12 years ago, it was data was a liability. You had to get rid of it. Keep it no longer than you had to, because you're gonna get soon. So email archives came in and obviously thinks flipped after the big data. But so what do you What are you seeing in terms of that shift from From the defense data to the offensive? >> Yeah, and it's it's really you know, when you think about it and let me define sort of offense versus defense. Who on the defense side, historically, that's where most of CEOs have played. That's risk regulatory reporting, privacy, um, even litigation support those types of activities today. Uh, and really, until about a year and 1/2 ago, we really saw most CEOs still really anchored in that I run a forum with a number of studios and financial service is, and every year we get them together and asked him the same set of questions. This was the first year where they said that you know what my primary focus now is. Growth. It's bringing efficiency is trying to generate value on the offensive side. It's not like the regulatory work's going away, certainly in the face of some of the pending privacy regulation. But you know, it's It's a sign that the volume of use cases as the investments in their digital transformations are starting to kick out, as well as the volumes of data that are available. The raw material that's available to them in terms of third party data in terms of the the just the general volumes that that exist that are streaming into the organization and the overall literacy in the business units are creating this, this massive demand. And so they're having to >> respond because of getting a handle on the data they're actually finding. Word is, they're categorizing it there, there, >> yeah, organizing that. That is still still a challenge. Um, I think it's better with when you have a very narrow scope of critical data elements going back to the structure data that we're talking it with the regulatory reporting when you start to get into the three offense, the generating value, getting the customer experience, you know, really exploring. You know that side of it. There's there's a ton of new muscle that has to be built new muscle in terms of data quality, new muscle in terms of um, really more scalable operating model. I think that's a big issue right now with Si Dios is, you know, we've got ah, we're used to that limited swath of CDs and they've got Stewardship Network. That's very labor intensive. A lot of manual processes still, um, and and they have some good basic technology, but it's a lot of its rules based. And when you do you think about those how that constraints going to scale when you have all of this demand. You know, when you look at the customer experience analytics that they want to do when you look at, you know, just a I applied to things like operations. The demand on the focus there is is is gonna start to create a fundamental shift >> this week are one of things that I >> have scene, and maybe it's just my small observation space. But I wonder, if you could comment Is that seems like many CBO's air not directly involved in the aye aye initiatives. Clearly, the chief digital officer is involved, but the CDO zehr kind of, you know, in the background still, you see that? >> That's a fantastic question, and I think this is where we're seeing some off the cutting it change that is happening in the industry. And when Barbara presenter idea that we can often civilly look at data, this is what it is that studios for a long time have become more reactive in their roles. And that is that is starting to come forefront now. So a lot of institutions were working with are asking What's the next generation Roll off a CDO and why are they in the background and why are they not in the foreground? And this is when you become more often they were proactive with data and the digital officers are obviously focused on, you know, the transformation that has to happen. But the studios are their backbone in order to make the transformation. Really. And if the CDO started, think about their data as an asset did as a product did us a service. The judicial officers are right there because those are the real, you know, like the data data they're living so CDO can really become from my back office to really become a business line. We've >> seen taking the reins in machine learning in machine learning projects and cos you work with. Who >> was driving that? Yeah. Great question. So we are seeing, like, you know, different. I would put them in buckets, right? There is no one mortal fits all. We're seeing different generations within the company's. Some off. The ones were just testing out the market. There's two keeping it in their technology space in their back office. Take idea and, you know, in in forward I d let me call them where they are starting to experiment with this. But you see, the mature organizations on the other end of the spectrum, they are integrating action, learning and a I right into the business line because they want to see ex souls having the technology right by their side so they can lead leverage. Aye, aye. And machine learning spot right for the business right there. And that is where we're seeing know some of the new models. Come on. >> I think the big shift from a CDO perspective is using a i to prep data for a That's that's fundamentally where you know, where the data science was distributed. Some of that data science has to come back and free the integration for equality for data prepping because you've got all this data third party and other from customer streaming into the organization. And you know, the work that you're doing around, um, anomaly detection is it transcends developing the rules, doing the profiling, doing the rules. You know, the very manual, the very labor intensive process you've got to get away from that >> is used in order for this to be scale goes and a I to figure out which out goes to apply t >> clean to prepare the data toe, see what algorithms we can use. So it's basically what we're calling a eye for data rather than just data leading into a I. So it's I mean, you know, you developed a technology for one off our clients and pretty large financial service. They were getting closer, like 1,000,000,000 data points every day. And there was no way manually, you could go through the same quality controls and all of those processes. So we automated it through algorithms, and these algorithms are learning the behavior of data as they flow into the organization, and they're able to proactively tell their problems are starting very much. And this is the new face that we see in in the industry, you cannot scale the traditional data governance using manual processes, we have to go to the next generation where a i natural language processing and think about on structure data, right? I mean, that is, like 90% off. The organization is unstructured data, and we have not talked about data quality. We have not talked about data governance. For a lot of these sources of information, now is the time. Hey, I can do it. >> And I think that raised a great question. If you look at unstructured and a lot of the data sources, as you start to take more of an offensive stance will be unstructured. And the data quality, what it means to apply data quality isn't the the profiling and the rules generation the way you would with standard data. So the teams, the skills that CEOs have in their organizations, have to change. You have to start to, and, you know, it's a great example where, you know, you guys were ingesting documents and there was handwriting all over the documents, you know, and >> yeah, you know, you're a great example, Bob. Like you no way would ask the client, like, you know, is this document gonna scanned into the system so my algorithm can run and they're like, Yeah, everything is good. I mean, the deal is there, but when you then start scanning it, you realize there's handwriting and the information is in the handwriting. So all the algorithms breakdown now >> tribal knowledge striving Exactly. >> Exactly. So that's what we're seeing. You know, if I if we talk about the digital transformation in data in the city organization, it is this idea dart. Nothing is left unseen. Some algorithm or some technology, has seen everything that is coming into. The organization has has has a para 500. So you can tell you where the problems are. And this is what algorithms do. This scale beautifully. >> So the data quality approaches are evolving, sort of changing. So rather than heavy, heavy emphasis on masking or duplication and things like that, you would traditionally think of participating the difficult not that that goes away. But it's got to evolve to use machine >> intelligence. Exactly what kind of >> skill sets people need thio achieve that Is it Is it the same people or do we need to retrain them or bring in new skills. >> Yeah, great question. And I can talk from the inspector off. Where is disrupting every industry now that we know, right? But we knew when you look at what skills are >> required, all of the eye, including natural language processing, machine learning, still require human in the loop. And >> that is the training that goes in there. And who do you who are the >> people who have that knowledge? It is the business analyst. It's the data analyst who are the knowledge betters the C suite and the studios. They are able to make decisions. But the day today is still with the data analyst. >> Those s Emmys. Those sm >> means So we have to obscure them to really start >> interacting with these new technologies where they are the leaders, rather than just waiting for answers to come through. And >> when that happens now being as a data scientist, my job is easy because they're Siamese, are there? I deploy the technology. They're semi's trained algorithms on a regular basis. Then it is a fully fungible model which is evolving with the business. And no longer am I spending time re architect ing my rules. And like my, you know, what are the masking capabilities I need to have? It is evolving us. >> Does that change the >> number one problem that you hear from data scientists, which is the 80% of the time >> spent on wrangling cleaning data 10 15 20% run into sm. He's being concerned that they're gonna be replaced by the machine. Their training. >> I actually see them being really enabled now where they're spending 80% of the time doing boring job off, looking at data. Now they're spending 90% of their time looking at the elements future creative in which requires human intelligence to say, Hey, this is different because off X, >> y and Z so let's let's go out. It sounds like a lot of what machine learning is being used for now in your domain is clean things up its plumbing. It's basic foundation work. So go out. Three years after all that work has been done and the data is clean. Where are your clients talking about going next with machine learning? Bob, did you want? >> I mean, it's a whole. It varies by by industry, obviously, but, um but it covers the gamut from, you know, and it's generally tied to what's driving their strategies. So if you look at a financial service is organization as an example today, you're gonna have, you know, really a I driving a lot of the behind the scenes on the customer experience. It's, you know, today with your credit card company. It's behind the scenes doing fraud detection. You know, that's that's going to continue. So it's take the critical functions that were more data. It makes better models that, you know, that that's just going to explode. And I think they're really you can look across all the functions, from finance to to marketing to operations. I mean, it's it's gonna be pervasive across, you know all of that. >> So if I may, I don't top award. While Bob was saying, I think what's gonna what What our clients are asking is, how can I exhilarate the decision making? Because at the end of the day on Lee, all our leaders are focused on making decisions, and all of this data science is leading up to their decision, and today you see like you know what you brought up, like 80% of the time is wasted in cleaning the data. So only 20% time was spent in riel experimentation and analytics. So your decision making time was reduced to 20% off the effort that I put in the pipeline. What if now I can make it 80% of the time? They're I put in the pipeline, better decisions are gonna come on the train. So when I go into a meeting and I'm saying like, Hey, can you show me what happened in this particular region or in this particular part of the country? Previously, it would have been like, Oh, can you come back in two weeks? I will have the data ready, and I will tell you the answer. But in two weeks, the business has ran away and the CDO know or the C Street doesn't require the same answer. But where we're headed as as the data quality improves, you can get to really time questions and decisions. >> So decision, sport, business, intelligence. Well, we're getting better. Isn't interesting to me. Six months to build a cube, we'd still still not good enough. Moving too fast. As the saying goes, data is plentiful. Insights aren't Yes, you know, in your view, well, machine intelligence. Finally, close that gap. Get us closer to real time decision >> making. It will eventually. But there's there's so much that we need to. Our industry needs to understand first, and it really ingrained. And, you know, today there is still a fundamental trust issues with a I you know, it's we've done a lot of work >> watch Black box or a part of >> it. Part of it. I think you know, the research we've done. And some of this is nine countries, 2400 senior executives. And we asked some, ah, a lot of questions around their data and trusted analytics, and 92% of them came back with. They have some fundamental trust issues with their data and their analytics and and they feel like there's reputational risk material reputational risk. This isn't getting one little number wrong on one of the >> reports about some more of an >> issue, you know, we also do a CEO study, and we've done this many years in a row going back to 2017. We started asked them okay, making a lot of companies their data driven right. When it comes to >> what they say they're doing well, They say they're day driven. That's the >> point. At the end of the day, they making strategic decisions where you have an insight that's not intuitive. Do you trust your gut? Go with the analytics back then. You know, 67% said they go with their gut, So okay, this is 2017. This industry's moving quickly. There's tons and tons of investment. Look at it. 2018 go down. No, went up 78%. So it's not aware this issue there is something We're fundamentally wrong and you hit it on. It's a part of its black box, and part of it's the date equality and part of its bias. And there's there's all of these things flowing around it. And so when we dug into that, we said, Well, okay, if that exists, how are we going to help organizations get their arms around this issue and start digging into that that trust issue and really it's the front part is, is exactly what we're talking about in terms of data quality, both structured more traditional approaches and unstructured, using the handwriting example in those types of techniques. But then you get into the models themselves, and it's, you know, the critical thing she had to worry about is, you know, lineage. So from an integrity perspective, where's the data coming from? Whether the sources for the change controls on some of that, they need to look at explain ability, gain at the black box part where you can you tell me the inferences decisions are those documented. And this is important for this me, the human in the loop to get confidence in the algorithm as well as you know, that executive group. So they understand there's a structure set of processes around >> Moneyball. Problem is actually pretty confined. It's pretty straightforward. Dono 32 teams are throwing minor leagues, but the data models pretty consistent through the problem with organizations is I didn't know data model is consistent with the organization you mentioned, Risk Bob. The >> other problem is organizational inertia. If they don't trust it, what is it? What is a P and l manage to do when he or she wants to preserve? Yeah, you know, their exit position. They attacked the data. You know, I don't believe that well, which which is >> a fundamental point, which is culture. Yes. I mean, you can you can have all the data, science and all the governance that you want. But if you don't work culture in parallel with all this, it's it's not gonna stick. And and that's, I think the lot of the leading organisations, they're starting to really dig into this. We hear a lot of it literacy. We hear a lot about, you know, top down support. What does that really mean? It means, you know, senior executives are placing bats around and linking demonstrably linking the data and the role of data days an asset into their strategies and then messaging it out and being specific around the types of investments that are going to reinforce that business strategy. So that's absolutely critical. And then literacy absolutely fundamental is well, because it's not just the executives and the data scientists that have to get this. It's the guy in ops that you're trying to get you. They need to understand, you know, not only tools, but it's less about the tools. But it's the techniques, so it's not. The approach is being used, are more transparent and and that you know they're starting to also understand, you know, the issues of privacy and data usage rights. That's that's also something that we can't leave it the curb. With all this >> innovation, it's also believing that there's an imperative. I mean, there's a lot of for all the talk about digital transformation hear it everywhere. Everybody's trying to get digital, right? But there's still a lot of complacency in the organization in the lines of business in operation to save. We're actually doing really well. You know, we're in financial service is health care really hasn't been disrupted. This is Oh, it's coming, it's coming. But there's still a lot of I'll be retired by then or hanging. Actually, it's >> also it's also the fact that, you know, like in the previous generation, like, you know, if I had to go to a shopping, I would go into a shop and if I wanted by an insurance product, I would call my insurance agent. But today the New world, it's just a top off my screen. I have to go from Amazon, so some other some other app, and this is really this is what is happening to all of our kind. Previously that they start their customers, pocketed them in different experience. Buckets. It's not anymore that's real in front of them. So if you don't get into their digital transformation, a customer is not going to discount you by saying, Oh, you're not Amazon. So I'm not going to expect that you're still on my phone and you're only two types of here, so you have to become really digital >> little surprises that you said you see the next. The next stage is being decision support rather than customer experience, because we hear that for CEOs, customer experience is top of mind right now. >> No natural profile. There are two differences, right? One is external facing is absolutely the customer internal facing. It's absolutely the decision making, because that's how they're separating. The internal were, says the external, and you know most of the meetings that we goto Customer insight is the first place where analytics is starting where data is being cleaned up. Their questions are being asked about. Can I master my customer records? Can I do a good master off my vendor list? That is where they start. But all of that leads to good decision making to support the customers. So it's like that external towards internal view well, back >> to the offense versus defense and the shift. I mean, it absolutely is on the offense side. So it is with the customer, and that's a more directly to the business strategy. So it's get That's the area that's getting the money, the support and people feel like it's they're making an impact with it there. When it's it's down here in some admin area, it's below the water line, and, you know, even though it's important and it flows up here, it doesn't get the VIN visibility. So >> that's great conversation. You coming on? You got to leave it there. Thank you for watching right back with our next guest, Dave Lot. Paul Gillen from M I t CDO I Q Right back. You're watching the Cube

>> From Cambridge, Massachusetts, it's The Cube, covering MIT Chief data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. >> Welcome back to Cambridge, everybody. We're here at Tang building at MIT for the MIT CDOIQ Conference. This is the 13th annual MIT CDOIQ. It started as a information quality conference and grew through the big data era, the Chief Data Officer emerged and now it's sort of a combination of those roles. That governance role, the Chief Data Officer role. Critical for organizations for quality and data initiatives, leading digital transformations ans the like. I'm Dave Vallante with my cohost Paul Gillin, you're watching The Cube, the leader in tech coverage. Mark Chrisco is here, the deputy, sorry, Principle Deputy Director for Enterprise Information at the Department of Defense. Good to see you again, thanks for coming on. >> Oh, thank you for having me. >> So, Principle Deputy Director Enterprise Information, what do you do? >> I do data. I do acquisition data. I'm the person in charge of lining the acquisition data for the programs for the Under Secretary and the components so a strong partnership with the army, navy, and air force to enable the department and the services to execute their programs better, more efficiently, and be efficient in the data management. >> What is acquisition data? >> So acquisition data generally can be considered best in the shorthand of cost schedule performance data. When a program is born, you have to manage, you have to be sure it's resourced, you're reporting up to congress, you need to be sure you have insight into the programs. And finally, sometimes you have to make decisions on those programs. So, cost schedule performance is a good shorthand for it. >> So kind of the key metrics and performance metrics around those initiatives. And how much of that is how you present that data? The visualization of it. Is that part of your role or is that, sort of, another part of the organization you partner with, or? >> Well, if you think about it, the visualization can take many forms beyond that. So a good part of the role is finding the authoritative trusted source of that data, making sure it's accurate so we don't spend time disagreeing on different data sets on cost schedule performance. The major programs are tremendously complex and large and involve and awful lot of data in the a buildup to a point where you can look at that. It's just not about visualizing, it's about having governed authoritative data that is, frankly, trustworthy that you can can go operate in. >> What are some of the challenges of getting good quality data? >> Well, I think part of the challenge was having a common lexicon across the department and the services. And as I said, the partnership with the services had been key in helping define and creating a semantic data model for the department that we can use. So we can have agreement on what it would mean when we were using it and collecting it. The services have thrown all in and, in their perspective, have extended that data model down through their components to their programs so they can better manage the programs because the programs are executed at a service level, not at an OSD level. >> Can you make that real? I mean, is there an example you can give us of what you mean by a common semantic model? >> So for cost schedule, let's take a very simple one, program identification. Having a key number for that, having a long name, a short name, and having just the general description of that, were in various states amongst the systems. We've had decades where, however the system was configured, configured it the way they wanted to. It was largely not governed and then trying to bring those data sets together were just impossible to do. So even with just program identification. Since the majority of the programs and numbers are executed at a service level, we worked really hard to get the common words and meanings across all the programs. >> So it's a governance exercise the? >> Yeah. It is certainly a governance exercise. I think about it as not so much as, in the IT world or the data world will call it governance, it's leadership. Let's settle on some common semantics here that we can all live with and go forward and do that. Because clearly there's needs for other pieces of data that we may or may not have but establishing a core set of common meanings across the department has proven very valuable. >> What are some of the key data challenges that the DOD faces? And how is your role helping address them? >> Well in our case, and I'm certain there's a myriad of data choices across the department. In our place it was clarity in and the governance of this. Many of the pieces of data were required by statute, law, police, or regulation. We came out of eras where data was the piece of a report and not really considered data. And we had to lead our ways to beyond the report to saying, "No, we're really "talking about key data management." So we've been at this for a few years and working with the services, that has been a challenge. I think we're at the part where we've established the common semantics for the department to go forward with that. And one of the challenges that I think is the access and dissemination of knowing what you can share and when you can share it. Because Michael Candolim said earlier that the data in mosaic, sometimes you really need to worry about it from our perspective. Is too much publicly available or should we protect on behalf of the government? >> That's a challenge. Is the are challenge in terms of, I'm sure there is but I wonder if you can describe it or maybe talk about how you might have solved it, maybe it's not a big deal, but you got to serve the mission of the organization. >> Absolutely. >> That's, like, number one. But at the same time, you've got stakeholders and they're powerful politicians and they have needs and there's transparency requirements, there are laws. They're not always aligned, those two directives, are they? >> No, thank goodness I don't have to deal with misalignments of those. We try to speak in the truth of here's the data and the decisions across the organization of our reports still go to congress, they go to congress on an annual basis through the selected acquisition report. And, you know, we are better understanding what we need to protect and how to advice congress on what should be protected and why. I would not say that's an easy proposition. The demands for those data come from the GAO, come from congress, come from the Inspector General and having to navigate that requires good access and dissemination controls and knowing why. We've sponsored some research though the RAND organization to help us look and understand why you have got to protect it and what policies, rules, and regulations are. And all those reports have been public so we could be sure that people would understand what it is. We're coming out of an era where data was not considered as it is today where reports were easily stamped with a little rubber stamp but data now moves at the velocities of milliseconds not as the velocity of reports. So we really took a comprehensive look at that. How do you manage data in a world where it is data and it is on infrastructures like data models. >> So, the future of war. Everybody talks about cyber as the future of war. There's a lot of data associated with that. How does that change what you guys do? Or does it? >> Well, I think from an acquisition perspective, you would think, you know. In that discussion that you just presented us, we're micro in that. We're equipping and acquiring through acquisitions. What we've done is we make sure that our data is shareable, you know? Open I, API structures. Having our data models. Letting the war fighters have our data so they could better understand where information is here. Letting other communities to better help that. By us doing our jobs where we sit, we can contribute to their missions and we've aways been every sharing in that. >> Is technology evolving to the point where, let's assume you could dial back 10 or 15 years and you had the nirvana of data quality. We know how fast technology is changing but is it changing as an enabler to really leverage that quality of data in ways that you might not have even envision 10 or 15 years ago? >> I think technology is. I think a lot of this is not in tools, it's now in technique and management practices. I think many of us find ourselves rethinking of how to do this now that you have data, now that you have tools that you can get them. How can you adopt better and faster? That requires a cultural change to organization. In some cases it requires more advanced skills, in other cases it requires you to think differently about the problems. I always like to consider that we, at some point, thought about it as a process-driven organization. Step one to step two to step three. Now process is ubiquitous because data becomes ubiquitous and you could refactor your processes and decisions much more efficiently and effectively. >> What are some of the information quality problems you have to wrestle with? >> Well, in our case, by setting a definite semantic meaning, we kicked the quality problems to those who provide the authoritative data. And if they had a quality problem, we said, "Here's your data. "We're going to now use it." So it spurs, it changes the model of them ensuring the quality of those who own the data. And by working with the services, they've worked down through their data issues and have used us a bit as the foil for cleaning up their data errors that they have from different inputs. And I like to think about it as flipping the model of saying, "It's not my job to drive quality, "it's my job to drive clarity, "it's their job to drive the quality into the system." >> Let's talk about this event. So, you guys are long-time contributors to the event. Mark, have you been here since the beginning? Or close to it? >> Um... About halfway through I think. >> When the focus was primarily on information quality? >> Yes. >> Was it CDOIQ at the time or was it IQ? >> It was the very beginnings of CDOIQ. It was right before it became CDOIQ. >> Early part of this decade? >> Yes. >> Okay. >> It was Information Quality Symposium originally, is that was attracted you to it? >> Well, yes, I was interested in it because I think there were two things that drew my interest. One, a colleague had told me about it and we were just starting the data journey at that point. And it was talking about information quality and it was out of a business school in the MIT slenton side of the house. And coming from a business perspective, it was not just the providence of IT, I wanted to learn form others because I sit on the business side of the equation. Not a pure IT-ist or technology. And I came here to learn. I've never stopped learning through my entire journey here. >> What have you learned this week? >> Well, there's an awful lot I learned. I think it's been... This space is evolving so rapidly with the law, policy, and regulation. Establishing the CDOs, establishing the roles, getting hear from the CDOs, getting to hear from visions, hear from Michael Conlan and hear from others in the federal agencies. Having them up here and being able to collaborate and talk to them. Also hearing from the technology people, the people that're bringing solutions to the table. And then, I always say this is a bit like group therapy here because many of us have similar problems, we have different start and end points and learning from each other has proven to be very valuable. From the hallway conversations to hearing somebody and seeing how they thought about the products, seeing how commercial industry has implemented data management. And you have a lot of similarity of focus of people dealing with trying to bring data to bring value to the organizations and understanding their transformations, it's proven invaluable. >> Well, what did the appointment of the DOD's first CDO last year, what statement did that make to the organization? >> That data's important. Data are important. And having a CDO in that and, when Micheal came on board, we shared some lessons learned and we were thinking about how to do that, you know? As I said, I function in a, arguably a silo of the institution is the acquisition data. But we were copying CDO homework so it helped in my mind that we can go across to somebody else that would understand and could understand what we're trying to do and help us. And I think it becomes, the CDO community has always been very sharing and collaborative and I hold that true with Micheal today. >> It's kind of the ethos of this event. I mean, obviously you guys have been heavily involved. We've always been thrilled to cover this. I think we started in 2013 and we've seen it grow, it's kind of fire marshal full now. We got to get to a new facility, I understand. >> Fire marshal full. >> Next year. So that's congratulations to all the success. >> Yeah, I think it's important and we've now seen, you know, you hear it, you can read it in every newspaper, every channel out there, that data are important. And what's more important than the factor of governance and the factor of bringing safety and security to the nation? >> I do feel like a lot in, certainly in commercial world, I don't know if it applies in the government, but a lot of these AI projects are moving really fast. Especially in Silicon Valley, there's this move fast and break things mentality. And I think that's part of why you're seeing some of these big tech companies struggle right now because they're moving fast and they're breaking things without the governance injected and many CDOs are not heavily involved in some of these skunk works projects and it's almost like they're bolting on governance which has never been a great formula for success in areas like governance and compliance and security. You know, the philosophy of designing it in has tangible benefits. I wonder if you could comment on that? >> Yeah, I can talk about it as we think about it in our space and it may be limited. AI is a bit high on the hype curve as you might imagine right now, and the question would be is can it solve a problem that you have? Well, you just can't buy a piece of software or a methodology and have it solve a problem if you don't know what problem you're trying to solve and you wouldn't understand the answer when it gave it to you. And I think we have to raise our data intellectualism across the organization to better work with these products because they certainly represent utility but it's not like you give it with no fences on either side or you open up your aperture to find basic solution on this. How you move forward with it is your workforce has got to be in tune with that, you have to understand some of the data, at least the basics, and particularly with products when you get the machine learning AI deep learning, the models are going to be moving so fast that you have to intellectually understand them because you'll never be able to go all the way back and stubby pencil back to an answer. And if you don't have the skills and the math and the understanding of how these things are put together, it may not bring the value that they can bring to us. >> Mark, thanks very much for coming on The Cube. >> Thank you very much. >> Great to see you again and appreciate all the work you guys both do for the community. All right. And thank you for watching. We'll be right back with our next guest right after this short break. You're watching The Cube from MIT CDOIQ.

(upbeat music) >> From Cambridge, Massachusetts, it's the CUBE. Covering MIT Chief Data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. (upbeat music) >> Welcome back to MIT in Cambridge Massachusetts everybody you're watching the CUBE the leader in live tech coverage. We go out to the events and extract the signal from the noise we hear at the MIT CDOIQ. It's the MIT Chief Data Officer event the 13th annual event. The CUBE started covering this show in 2013. I'm Dave Vellante with Paul Gillin, my co-host, and Michael Conlin is here as the chief data officer of the Department of Defense, Michael welcome, thank you for coming on. >> Thank you, it's a pleasure to be here. >> So the DoD is, I think it's the largest organization in the world, what does the chief data officer of the DoD do on a day to day basis? >> A range of things because we have a range of challenges at the Department of Defense. We are the single largest organization on the planet. We have the greatest scope and scale and complexity. We have the most dangerous competitors of anybody on the planet, it's not a trivial issue for us. So, I've a range of challenges. Challenges around, how do I lift the overall performance of the department using data effectively? How do I help executives make better decisions faster, using more recent, more common data? More common enterprise data is the expression we use. How do I help them become more sophisticated consumers of data and especially data analytics? And, how do we get to the point where, I can compare performance over here with performance over there, on a common basis? And compared to commercial benchmark? Which is now an expectation for us, and ask are we doing this as well as we should, right across the patch? Knowing, that all that data comes from multiple different places to start with. So we have to overcome all those differences and provide that department wide view. That's the essence of the role. And now with the recent passage of the Foundations for Evidenced-Based Policymaking Act, there are a number of additional expectations that go on top of that, but this is ultimately about improving affordability and performance of the department. >> So overall performance of the organization... >> Overall performance. >> ...as well, and maybe that comes from supporting various initiatives, and making sure you're driving performance on that basis as well. >> It does, but our litmus test is are we enabling the National Defense Strategy to succeed? Only reason to touch data is to enable the National Defense Strategy to be more successful than without it. And so we're always measuring ourselves against that. But it is, can we objectively say we're performing better? Can we objectively say that we are more affordable? In terms of the way we support the National Defense Strategy. >> I'm curious about your motivations for taking on this assignment because your background, as I see, is primarily in the private sector. A year ago you joined the US Department of Defense. A huge set of issues that you're tackling now, why'd you do it? >> So I am a capitalist, like most Americans, and I'm a serial entrepreneur. This was my first opportunity to serve government. And when I looked at it, knowing that I could directly support national defense, knowing that I could make a direct meaningful contribution, let me exercise that spirit of patriotism that many of us have, but we just not found ourselves an opportunity. When this opportunity came along I just couldn't say no to it. There's so much to be done and so much appetite for improvement that I just couldn't walk away for this. Now I've to tell you, when you start you take an oath of office to protect and defend the constitution. I don't know, it's maybe a paragraph or maybe it's two paragraphs. It felt like it took an hour to choke it out, because I was suddenly struck with all of this emotion. >> The gravity of what you were doing. >> Yeah, the gravity of what I'm doing. And that was just a reinforcement of the choice I'd already made, obviously right. But the chance to be the first chief data officer of the entire Department of Defense, just an enormous privilege. The chance to bring commercial sector best practices in and really lift the game of the department, again enormous privilege. There's so many people who could do this, probably better than me. The fact that I got the opportunity I just couldn't say no. Just too important, to many places I could see that we could make things better. I think anybody with a patriotic bone in their body would of jumped at the opportunity. >> That's awesome, I love that congratulations on getting that role and seemingly thrive in it. A big part of preserving that capitalist belief, defending the constitution and the American way, it sounds corny, but... >> It's real. >> I'm a patriot as well, is security. And security and data are intertwined. And just the whole future of warfare is dramatically changing. Can you talk about in a format like this, security, you're thinking on that, the department's thinking on that from a CDO's perspective? >> So as you know we have a number of swimlanes within the department and security is very clear swimlane, it's aligned under our chief information officer, but security is everybody's responsibility, of course. Now the longstanding criticism of security people is that they think they best way to secure anything is to permit nobody to touch it. The clear expectation for me as chief data officer is to make sure that information is shared to the right people as rapidly as possible. And, that's a different philosophy. Now I'm really lucky. Lieutenant General Denis Crall our principal cyber advisor, Dana Deasy our CIO, these people understand how important it is to get information in the right place at the right time, make it rapidly available and secure it every step along the way. We embrace the zero trust mantra. And because we embrace the zero trust mantra we're directly concerned with defending the data itself. And as long as we defend the data and the same mechanisms are the mechanisms we use to let people share it, suddenly the tension goes away. Suddenly we all have the same goal. Because the goal is not to prevent use of data, it's to enable use of data in a secure way. So the traditional tension that might be in that place doesn't exist in the department. Very productive, very professional level of collaboration with those folks in this space. Very sophisticated people. >> When we were talking before we went live you mentioned that the DoD has 10,000 plus operational systems... >> That's correct. >> A portfolio of that magnitude just overwhelming, I mean how did you know what to do first when you moved into this job, or did you have a clear mandate when you were hired? >> So I did have a clear mandate when I was hired and luckily that was spelled out. We knew what to do first because we sat down with actual leaders of the department and asked them what their goals were for improving the performance of the department. And everything starts from that conversation. You find those executives that what to improve performance, you understand what those goals are, and what data they need to manage that improvement. And you capture all the critical business questions they need answers to. From that point on they're bought in to everything that happens, right. Because they want those answers to those critical business questions. They have performance targets of their own, this is now aligned with. And so you have the support you need to go down the rest of the path of finding the data, standardizing it, et cetera. In order to deliver the answers to those questions. But it all starts which either the business mission leaders or the warfighting mission leaders who define the steps they're taking to implement the National Defense Strategy. Everything gets lined up against that, you get instant support and you know you're going after the right thing. This is not, an if you build it they will come. This is not, a driftnet the organization try to gather up all the data. This is spear fishing for specific answers to materially important questions, and everything we do is done on that basis. >> We hear Mark Ramsey this morning talk about the... He showed a picture of stove pipes and then he complicated that picture by showing multiple copies within each of those stove pipes, and says this is organizations that we've all lived in. >> That's my organization too. >> So talk about some of those data challenges at the DoD and how you're addressing those, specifically how you're enabling soldiers in the field to get the right data to the field when they need it. >> So what we'll be delicate when we talk about what we do for soldiers in the field. >> Understood, yeah. >> That tends to be sensitive. >> Understand why, sure. >> But all of those dynamics that Mark described in that presentation are present in every large cooperation I've ever served. And that includes the Department of Defense. That heterogeneity and sprawl of IT that what I would refer to, he showed us a hair ball of IT. Every large organization has a hair ball of IT. And data scattered all over the place. We took many of the same steps that he described in terms of organizing and presenting meaningful answers to questions, in almost exactly the same sequence. The challenge as you heard me use the statistics that our CIO's published digital monetization strategies, which calls out that we have roughly 10,000 operational systems. Well, every one of them is different. Every one's put in place by a different group of people at a different time, with a different set of requirements, and a different budget, and a different focus. You know organizational scope. We're just like he showed. We're trying to blend all that in to a common view. So we have to find what's the real authoritative piece of data, cause it's not all of those systems. It's only a subset of those systems. And you have to do all of the mapping and translations, to make the result add up. Otherwise you double count or you miss something. This is work in progress. This will always be a work in progress to any large organization. So I don't want to give you impression it's all sorted. Definitely not all sorted. But, the reality is we're trying to get to the point where people can see the data that's available and that's a requirement by the way under the Foundations Act that we have a data catalog, an authoritative data catalog so people can see it and they have the ability to then request access to that through automation. This is what's critical, you need to be able to request access and have it arbitraged on the basis of whether you should directly have access based on your role, your workflow, et cetera, but it should happen in real time. You don't want to wait weeks, or months, or however long for some paperwork to move around. So this all has to become highly automated. So, what's the data, who can access it under what policy, for what purpose? Our roles and responsibilities? Identity management? All this is a combined set of solutions that we have to put in place. I'm mostly worried about a subset of that. My colleagues in these other swimlanes are working to do the rest. Most people in the department have access to data they need in their space. That hasn't been a problem. The problem is you go from space to space, you have to learn a new set of systems and a new set of techniques for a new set of data formats which means you have to be retrained. That really limits our freedom of maneuver of human beings. In the ideal world you'd be able to move from any job in any part of the department to the same job in another part of the department with no retraining whatsoever. You'd be instantly able to make a contribution. That's what we're trying to get to. So that's a different kind of a challenge, right. How do we get that level of consistency in the user experience, a modern user experience. So that if I'm a real estate manager, or I'm a medical business manager, or I'm a clinical professional, or I'm whatever, I can go from this location in this part of the department to that location in that part and my experience is the same. It's completely modern, and it's completely consistent. No retraining. >> How much of that challenge pie is people, process and technology? How would you split that opportunity? >> Well everything starts for a process perspective. Because if you automate a bad process, you just make more mistakes in less time at greater costs. Obviously that's not the ideal. But the biggest single challenge is people. It's talent, it's culture. Both on the demand side and on the supply side. If fact a lot of what I talked about in my remarks, was the additional changes we need to put in place to bring people into a more modern approach to data, more modern consumption. And look, we have pockets of excellence. And they can hold their own against any team, any place on the planet. But they are pockets of excellence. And what we're trying to do is raise the entire organization's performance. So it's people, people, and people and then the other stuff. But the products, don't care about (laughs). >> We often here about... >> They're going to change in 12 to 18 months. I'm a technologist, I'm hands on. The products are going to change rapidly, I make no emotional commitment to products. But the people that's a different story. >> Well we know that in the commercial world we often hear that cultural resistance is what sabotages modernization efforts. The DoD is sort of the ultimate top-down organization. It is any easier to get buy-in because the culture is sort of command and control oriented? >> It's hard in the DoD, it's not easier in the DoD. Ultimately people respond to their performance incentives. That's the dirty secrets performance incentives, they work every time. So unless you restructure performance measures and incentives for people their behavior's never going to change. They need to see their personal future in the future you're prescribing. And if they don't see it, you're going to get resistance every time. They're going to do what they believe they're incented to do. Making those changes, cascading those performance measures down, has been difficult because much of the decision-making processes in the department have been based on slow-moving systems and slow-moving data. I mean think about it, our budget planning process was created by Robert McNamara, as the Secretary of Defense. It requires you to plan everything for five years. And it takes more than a year to plan a single year's worth of activities, it's slow-moving. And we have regulation, we have legislation, we're a law-abiding organization, we do what we have to do. All of those things slow things down. And there's a culture of expecting macro-level consensus building. Which means everybody feels they can say no. If everybody can say no, then change becomes peanut butter spread across an organization. When you peanut butter spread across something our size and scale, the layer's pretty thin. So we have the same problem that other organizations have. There is clearly a perception of top-down change and if the Secretary or the Deputy Secretary issue an instruction people will obey it. It just takes some time to work it's way down into all the detailed combinations and permutations. Cause you have to make sophisticated decisions now. How am I going to change for my performance measures for that group to that group? And that takes time and energy and thought. There's a natural sort of pipeline effect in this. So there's real tension I think in between this perception of top-down and people will obey the orders their given. But when you're trying to integrate those changes into a board set of policy and process and people, that takes time and energy. >> And as a result the leaders have to be circumspect about the orders they give because they want to see success. They want to make sure that what they say is actually implemented or it reflects poorly on the organization. >> I think that out leaders are absolutely concerned about accomplishing the outcomes that they set out. And I think that they are rightfully determined to get the change as rapidly as possible. I would not expect them to be circumspect. I would anticipate that they would be firm and clear in the direction that they set and they would set aggressive targets because you need aggressive targets to get aggressively changed outcomes. Now. >> But they would have to choose wisely, they can't just fire off orders and expect everything to be done. I would think that they got to really think about what they want to get done, and put all the wood behind the arrow as you... >> I think that they constantly balance all those considerations. I must say, I did not appreciate before I joined the department the extraordinary caliber of leadership we enjoy. We have people with real insight and experience, and high intellectual horsepower making the decisions in the department. We've been blessed with the continuing stream of them at all of the senior ranks. These people could go anywhere, or do anything that they wanted in the economy and they've chosen to be in the department. And they bring enormous intellectual firepower to bear on challenges. >> Well you mentioned the motivation at the top of the segment, that's largely pretty powerful. >> Yeah, oh absolutely. >> I want to ask you, we have to break, but the organizational structure, you talked about the CIO, actually the responsibility for security within the CIO. >> Sure. >> To whom do you report. What's the organization look like? >> So I report to the Chief Management Officer of the Department of Defense. So if you think about the order of precedents, there's the Secretary of Defense, the Deputy Secretary of Defense and third in order is the Chief Management Officer. I report to the Chief Management Officer. >> As does the CIO, is that right? >> As does the CIO, as does the CIO. And actually this is quite typical in large organizations, that you don't have the CDO and the CIO in the same space because the concerns are very different. They have to collaborate but very different concerns. We used to see CDOs reporting to CIOs that's fallen dramatically in terms of the frequency you see that. Cause we now recognize that's just a failure mode. So you don't want to go down that path. The number one most common reporting relationship is actually to a CEO, the chief executive officer, of an organization. It's all about, what executive is driving performance for the organization? That's the person the CDO should report to. And I'm blessed in that I do find myself reporting to the executive driving organizational improvement. For me, that's a critical thing. That would make the difference between whether I could succeed or whether I'm doomed to fail. >> COO would be common too in a commercial organization. >> Yeah, in certain commercial organizations, it's a COO. It just depends on the nature of the business and their maturity with data. But if you're in the... If data's the business, CDO will report to the CEO. There are other organizations where it'll be the COO or CFO, it just depends on the nature of that business. And in our case I'm quite fortunate. >> Well Michael, thank you for, not only the coming to the CUBE but the service you're providing to the country, we really appreciate your insights and... >> It's a pleasure meeting you. >> It's a pleasure meeting you. All right, keep it right there everybody we'll be right back with our next guest. You're watching the CUBE live from MIT CDOIQ, be right back. (upbeat music)

>> Live from San Diego, California, it's theCUBE, covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Welcome back to theCUBE. Our coverage of Cisco Live day three is in full effect. I am Lisa Martin with Dave Vellante and we have a couple of guests joining us. We've got Mike Bundy, head of Cisco Strategic Alliances from, guess where? The jacket should give it away, Pure Storage. And Tom Koppelman, the VP of Architecture Sales America for Cisco, hi guys! >> Hi. >> Hi. >> How ya doing? >> Thanks for bringing more brightness to our set. >> Yeah I forgot my sunglasses. >> I know, we're in the buzzy, bright DevNet Zone. We've been here all week. Great event, massive event, my goodness. 28,000 folks or so, Mike let's start with you. Give us a status of the Pure-Cisco relationship, the evolution of that, where you guys are now. What is exciting? >> Sure, so the relationship, it's unbelievable in terms of the amount of synergies and energy we have together. In fact, Tom at Cisco was really involved in the early genesis of this relationship, prior to me joining the company. And, in the last couple years, we've probably doubled in terms of our go-to-market and sell to customers together. So, tremendous growth. Partnership brings a value to us because of the strong heritage that we have from a DevNet tie-in, in terms of all the automation that we have on the platform, so. It's just a tremendous, tremendous, great partnership. >> And Tom, Cisco has a massive partner ecosystem, a lot of choice. What is it about Pure Storage that is providing advantages to Cisco? Where it's helping customers really kind of bridge this gap between hyper-converged, multi-cloud hybrid, all that jazz? >> Right, so Pure was a first mover in terms of flash storage, right. We saw demand from our customers wanting that technology to improve their data center environments. And when we partnered up early, we were able to kind of capture that momentum, right. And, when I think about our go-to-market with Pure, which is really where I kind of focus, there's very little friction in that relationship, right. There's not competitive overlap. There's not things like that. It's technology that the customers want, that they ask for, and a good field go-to-market in leadership on both sides that are willing to invest and get engaged and move the relationship forward. >> So what else are you guys doing besides just the go-to-market partnership because I got a hold of this timeline of Cisco Validated Designs that Pure and Cisco have put out over the last five years, four years. >> Right. >> And there's like 13 milestones on there. So that's roughly three a year. Of course, it started with Pure's IPO. So that's when Cisco said, all right, these guys are real. Start working with them. And in the early days, of course, you started with FlashStack. That was the flagship product. And then VDI, everybody does VDI, analysts are like, yeah, yeah, everybody does VDI. But then it started really accelerating the cadence. So it's more than just go-to-market. What's beneath that go-to-market? >> Yeah, good question. >> You want to? >> You hit the highlights of the CVD's and whatnot. >> I would say that Pure, this is our number one partnership that we have from an alliance perspective. The investment is far exceeding other partnerships we have. So, the amount of product integration that we're doing is tremendous, as you see there. We've focused on ACI and multi data centers the last couple years. We've focusing on AI and machine learning, most recently. And beyond that, we just signed an agreement and have released resell of Cisco SAN switches in the marketplace. It's the resell agreement we've ever done as a company and it just further shows the commitment in resources that we're willing to put into making sure the partnership is successful and continues to grow and evolve. >> And on top of that the investment in Cisco Intersight, in integrating with Cisco Intersight, the management platform, which is very important to us, it just shows commitment of the partnership. >> Let's talk more about that. So, how does that work? What problems is that solving for customers? >> Well, Cisco Intersight is our cloud based management offering for compute and Pure has integrated their storage platform as part of that solution. So allowing customers, whether it's a converged solution, just raw compute, a hyper-converged solution, but allowing them to manage those pools and deliver that via a cloud solution. >> So Pure plugs into the Cisco API. Now you're part of that stack, essentially. So it's transparent to the customer. And, Cisco's management plane takes care of all that. >> That's exactly right, correct, yes. >> Its' a big deal for us because it was the first integration with Intersight from any storage partner that Cisco has, right. So first to market. We want to embrace hyper-convergence, which is a big important priority for Cisco, and also bridging that gap. So as we compete against single vendor stacks, we have the right solution that customers are looking for. And ultimately, that's why it's so important for us. >> Yeah, Pure is big on firsts. First to flash, you just mentioned another first, you were the first with NVMe, before that you were with the evergreen. I mean, you like being first. >> First orange sport coat. >> That's definitely first there. (laughing) >> Let's talk about customer value though. Obviously, that's what it's all about. As we look at, not just the tremendous amount of choice that customer have when it comes to technology partners, but also the amount of data that's being generated, that's growing astronomically. Yet, organizations are getting so little value out of that because they can't extract the insights. What are you guys doing together leveraging the superpowers of AI and machine learning to help customers in any industry search a really, not just monetize that data, but really accelerate their businesses. Tom you're smiling so let's start with you. >> Yeah, so we came out with an AI server, right, our ML 480, and we've integrated that. Pure has invested, we've both invested and done an integration between FlashBlade, and I'll let Mike talk a little about FlashBlade and the value proposition of FlashBlade, but integrated that with our AI server. And our AI server is an Nvidia powered server, so it essentially gives you scale of processing and capabilities to allow you capitalize on all that data so the customers can get the information they need out of that. If you want to take a second on FlashBlade. >> And you know, AI is the buzz. It's the hot two letter acronym in the industry these days. $13 billion infrastructure opportunity, et cetera, et cetera. So, what Pure is really focused on is, data is the new oil of commodities for customers and clients. What we've built is a platform called FlashBlade, an architecture called the Data Hub, that allows you to not have to copy data and move it around and create silos in data warehouses. So, you can much easier execute a data strategy with the Data Hub architecture, using FlashBlade. When you look at machine learning in terms of how you build a data pipeline so that you can then get to quicker results from a business application standpoint with AI. That's what we've built together with Cisco. We're uber, uber, super excited a number of customers already in the last couple months. >> So I'm going to push a little on that, AI server, AI storage, people don't associate storage and server guys with AI. But if I hear you correctly, there's a $13 billion opportunity for workloads. To manage workloads running on your servers and your storage. >> Correct. >> And so you're optimizing them for AI workloads. >> Absolutely, exactly right. >> So you're not necessarily inventing AI. You're providing infrastructure so that people can leverage AI, is that right? >> Yes. >> Yeah, and the same way that we've built APIs together to work with Intersight, we do that in a way that allows our customers to leverage Cafe, other applications that can help build that data pipeline. We build the platform from the infrastructure level, it makes the management easy and we partner with all of the applications at the top end, but also the middleware and that software prepackage layer that connects via APIs to us. So, it's easy, it's agile, it's manageable, it's a cloud-like experience for the customers, right. >> Easy, agile, all awesome but security. Absolutely critical today. What are you guys doing, Tom I'll start with you, how are you guys working together infuse and integrate security into the technology so that from a customer's perspective, those risks dial down. >> So, Cisco is integrating security across all of our product portfolio, right. And, that includes our data center portfolio, all the way through our campus, our WAN, all those portfolios. We continue to look for opportunities to integrate, whether it's dual-factor authentication or things like secure data center where the highly scalable, multi-instance firewall in front of a data center, things like that. So we're definitely looking for areas and angles and opportunities for us to, not only integrate it from a product standpoint, but also ensure that we are talking that story with our customers so that they know they can leverage Cisco for the full architecture from a security standpoint. >> And the same thing on the storage of the data from an encryption perspective, and as the data gets moved or is mobile, that level of security and policy follows it wherever the data is moved. >> So, what should we expect, what's next in the time? What's 14 going to look like? You don't have top give us specifics but are we going to see blockchain CVDs? What should observers think about the partnership going forward? What could we look forward to? >> Yeah, I mean, the adoption of Container capability is tremendous in our customers environment. Cisco has a cloud Container platform available today. We're integrating that into FlashStack in the very near future. Embracing the cloud. Disaster recovery and data protection it's very hot for customers. Improving that experience so that you have faster restoration times, you're able to look at multi-tier strategy that's very easy to manage from a storage perspective, leveraging S3 with Amazon, Azure, et cetera. So, that's a couple things that are on the short term building block together. >> Yeah, I was going to comment on certainly multi cloud and Containers, those would be two of the big ones that I'd hit on, right. And, in the event of multi cloud leveraging, converged and hyper-converged together to better solve a customer's problems. >> So I was going to ask you. So hyper-converged now becomes a bridge to the cloud if, in fact, that's where customers want to go. >> Yes, it can be. >> Absolutely. >> Yeah, it can be, yes. >> Absolutely. >> Well guys thank you so much for joining Dave and me on the program, sharing with us the momentum that the Pure-Cisco relationship has and what excites you for the future. We appreciate your time. >> Thank you. >> Thank guys. >> For Dave Vellante, I'm Lisa Martin, you're watching theCUBE live from Cisco Live San Diego. Thanks for watching. (electronic music)

>> Live from San Diego, California It's the queue covering Sisqo live US 2019 Tio by Cisco and its ecosystem. Barker's >> Welcome Back to San Diego. The Cube has been live here at Cisco Life for the last three days. Student a man with meat, Lisa Martin wrapping things up and we're pleased to welcome to the Cube for the first time James Slay me, the cofounder and had a product for Double James. Welcome to the Cube >> very much. >> All right, So, Deborah, before we get into who you guys are, why you started this company stew. Thought maybe this had to do with your love of dub. Step the name >> way do like that step. But it really wasn't the reason May my co founders were involved with telecommunications and the industry, and we thought the cloud was coming quite fast. And we thought, you know, we started an opportunity that as much as the telcos we're trying to move service. It's a cloud that was value weds they need to provide. And there wasn't really a quality solution for recording for uncle's. >> So came from dubbing tape to tape back in the day. For those here is can remember when we had >> the tapes the name came from. That's how I remember we came, came about The name is that we're thinking, you know, I like to set because it was dubbing and then, you know, double came out of that was available. >> So tell us our audience about call cloud based call recording tell us a little bit about that. But why? What was the impetus for you saying? You know what? There's a gap in the market. We gotta solve it. >> Yeah, So everything think traditional providers were all in on premise Catholics based servers licensing all that traditionally no software model with the transition to cloud for telephony. So unified communications or anything like that Theo ability to have a platform that could record content. Really, By switching it on where that was, we partnered with Toko. So I say, I say tacos and Australian Server that Carrie is also provided tell they want to hear about what they called connect to their network and then offer it at scale so they could switch on one user or actually switch on 100,000 users instantly. And we managed the back into that and they get to go to the service. >> Yeah, it's interesting. So Lisa and I were at the Enterprise Connect show this year, and one of the themes we got out of the week of doing that show is Well, there's always the cool new technologies were doing video, and you know, there's the E R. And you know, people use Chatbots Airways do their voices still critical. Yeah, So maybe talk about you know, your customer base and you know, the role that you're playing to help them. And, you know, still, that that voice is is such an important decent of how we communicate. Yeah, it's really interesting, >> Like way still. Look at that. The important things that I done via voice. If you've got an important customer, you know, discussion, we have you going to send him an email you're probably gonna have followed up with a phone call or initiate with a phone call on most of time. That daughter is is lost. So you know things we discuss and you don't get them back. And, you know, generally call recording. If you're looking at that, people think contact center and regulatory reasons like financial services and that's our bread and butter. But now we're seeing with exposed the more cloud based options. That is, this is a study talk to expand that used case across outside of that traditional reason and not just call recording, you know, eyes that you know, becoming more prevalent as well. >> So how are you guys infusing a I into what you're doing? And also with Sisko to not only be able to apply intelligence to the data that you're gathered from reported calls, but also Dustan, the way that also facilitates security and privacy? >> Yeah, so Security's calling way couldn't have a platform that's use it is connected. Tio, You know, 18 See's Network way got over 100 telco or carrying their ways connected globally at the moment. That's all across Europe, America, Canada and then Asia as well. And now you know, we've been chosen by Sisko for their broad cloud platform, which I recently acquired way. What we see is that because we can capture content at scale way, then can actually easily then produce transcriptions, sentiment tone from the best of the three providers around the world with my be asked. But, you know, we could use any other third party provider that customer might want to use. Use case. Then Khun B. Go towards a small business in my you know, I'll say it's more reasonable and I'll explain on enterprise in a small business, theirselves person might be speeding, made the main customer 1,000,000 customer brings up. It is not happy, and we're going to tell the boss or the team leader they could automate, literally as easy automation, saying notifications Conor, a team leader. You should call this customer back. Without that, they lose the potential of retaining that customer now that previously that's only really the large business or the only has the technology to do that, all the ability to actually get it to market with us and because we connected to the network or even on, you know easily on ah, call manager solution through Cisco, that's any size of business. Large business. We're seeing also a bank as an example there, looking to capture everything across their whole business, not just contact center and start looking for key words that I said it's a credit card or home loan, and they make sure that their agent or their employee is disclosing that product correctly to the customer to make sure they're compliant Now that they're not talking about that across the of the whole business, not just always example. 4,000 seats in a context enter but 40,000 across their whole business on any phone, they using the moment without a mobile cellular or a despondent. >> Okay, so bring us inside your customers. Is that you know you mentioned call centers? Is that the primary use case? Do you go into different verticals? You know what? What does your customer base look like? >> Way definitely go like a safe contact centers for sure on DH. That's it's it's been there for a long time. That requirement to record phone calls and do it well, uh, financial services knock. It's throughout throughout the world, in the U. S. As well in the Europe because of me fit and all those requirements compliant. But as said way are now expanding that use case because of a A and requirement access data. Also, our platform is an open, open platform if that makes sense, but everything we record or capture is encrypted. But it isn't a format that Thean customer can use a CZ that won't apply themselves. They're all looking at using a I. You know, there are other other data sources in the company because it's available. They can use it with other. Well, >> yeah, actually, I just wanted to poke it that because one of the challenges we have out there is there's a lot of data, but how do I actually extract value out of that? So is this now a way for your customers to really unlock something that historically you just you you might have kept it for compliance. Reason to work, you know, to review some kind of training. But it was a little bit tough to get in and leverage the information that was in >> there. Yeah, you know, cos today I really they're they're assessing, You know, anything in a written format today they already losing. I want to do that Previously has been really hard to do that with voice now, because we can capture again captured at scale there. Now I can look at it and say, Can we use the same tools? Were looking for everything else in our business. I looked down and saw that the voice >> so walk us through an example of where double is integrated into an organization. If we think of a bank and you mentioned, you know, use case is one of them piqued my interest about Okay, sentiment. If there is an issue that needs to be escalated and somebody in the organization needs to call a customer, what's been recorded is indicating that is never able to integrate with, like marketing automation serum tools that that data is then pulled in a map back to that account and how it's being managed. >> Yeah, correct. Good, really good question, probably explained that way are a global platform. So we deployed everywhere in the world. So Australia's I'm from a trailer again, but U S Canada, Singapore, Japan, London, Ireland and the UK way recording that in that country we store in the country. But it is a scale. Little platform is a service, which means that way run a product, eyes a p I to open a p I, whether we've integrated with their application or the customer then can say we never want to log into doubles applications. Were you present all the daughter and our own complications already? That's already practiced today. It's available today is in ample. If they wanted to use South forces a serum looking today. Look at the contacts. You can see all the holes, All the transcriptions directly in South Force. >> That's cool. So they get that visibility in a way that that works for them? >> Yeah. Yeah, not precious. We look at ourselves a platform first, and we provide applications. We know users. Did you call recording as they expect to use it, like with permission based access team management. But in reality, we're trying to make it fit in the way that you they'll write their own business and more insights. >> Alright. So, James, we're here at Cisco Live. So explain to us how you tie into what's going on here at the show. You know, we're here in the definite zone. Curious If you talked about being an open platform, Do you know I did in the development pieces here? Yeah, >> we've We've had some really good conversations in the last three days. It's interesting to see people talk about, you know, they come up and they start talking about cool recording and way Explain what we just discussed. Relations open and they can access via Pio, and they start thinking they can see their mind. Figure out how they could apply that their own business. We've always wave always work the Cisco Way Boys work with broad Soft, which they've now acquired, and they now make that part of the business. But you know where that's called Manager. Wait. Have now announced they're doing whether it's calling, you know, we're talking to customers about cool recording through double on whether it's calling now. So if businesses you know, having a plan, Teo moved there from the UN Prem to cloud that Cisco way, make a second unified solution for them and they could make a road map for that with him. So it's a really good conversation we're having here. >> So in the development of the go to market strategy, or so I already have an established Francisco. >> Now where do you have a stress ready? We're day of Ah, we're partners, Cisco. Already we've got over 100 carries who used this go in. Their networks were really connected to them. I'm already recording in capturing content on those networks were pretty tight with this guy for sure, but you look at the enterprise that its president, although cloud yet they're really moving to that. So if they want to have a core recording solution or a solution on for him, and they might want to move to cloud future in the future, we have that in the future. So I'm doing it now is probably maintain the same service right through. >> So can you give us an example, a customer success that is leveraging Debra with Cisco whether you, you, Khun Anonymous eyes it or if you can name it? Great. But I would love to see how it's really working in action to drug business results. >> Yeah, it's going Good question. I'm trying to be the best one to give you. At the moment, I could think of a customer of ours with, you know, in the UK they're spread it costs. I think around 100 locations they're currently recording with double and using transcription to transcribe their calls are looking for patterns across the whole business and the using Cisco for the late telephony on then, looking at that and I've actually found things that just decided to save money, they've been losing some money in certain locations, and they've used the transcription. Seem patents actually implemented changes to actually sell a say that >> Awesome. So in terms of the last three days of Sisqo live, some of the announcements that have come out Cisco has been on this transition here on the hardware company network here, back in the day to now introducing AP eyes across the product portfolio, which he'd been two years ago. They didn't have to this pivot towards a software focus for a company like double born in the cloud. What does that signify to you guys? >> Uh, so you see what a sight it was. >> Yeah, what does that signify to double >> wellit's great for us, and it's really important for us to make sure we're along into that. We've already have always been an A P I first company on, you know, accessing the contents. But it's a challenge may, sometimes for businesses to embrace that way, need to make sure that we're way we're looking at Cisco and understand how they want to use Ap eyes and aligning ourselves on DH. Hopefully push him along because we're doing it for a while, eh? So we released, you know five years ago. It was cloud based, and it's good for everyone. Started talking about a pee eyes and employing them. >> Awesome. Well, James Splint. Pleasure to have you on the Cube this afternoon with stew in me. Thanks for stopping Mind sharing what Debra's doing with Cisco and to really help transform enterprises from any industry. We appreciate your time, all right. And we can't close the queue. But Sisqo live in San Diego without saying this one thing, which we're all going to do together. You ready, guys? On my count. 321 Classy. San Diego for soon. Minuteman II. Lisa. Bart, you've been watching the Cube. Thanks so much for watching. We'll see you next time.

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