(calm techno music) >> Hey, welcome to this Cube Conversation. I'm Lisa Martin. I've got two guests here with me. Please Welcome Philipp Niemietz, the intermediate head of the department for the Laboratory of Machine Tools and Production Engineering or WZL. Philipp, welcome to the program. >> Thank you. >> And we have Russ Caldwell here as well, senior product manager at Dell Technologies. Russ, great to see you. >> Thanks for the invite. >> Absolutely. We're going to be talking about how the enhanced video capabilities of Dell EMC's streaming data platform are enabling manufacturing, anomaly detection, and quality control through the use of sensors, cameras, and x-ray cameras. We're going to go ahead, Philipp, and start with you. We're abbreviating the lab as you guys do as WZL. Talk to us about the lab. What types of problems are you solving? >> Yeah, thank you. In the laboratory for machine tools, we are looking at actually all the other problems that arise in production engineering in general. So that's from the actual manufacturing of work pieces and that's getting used in aerospace or automotive industries, and really dig into the specifics of how those metal parts are manufactured, how they are formed, what are the mechanics of this. So this is a very traditional area where we are coming from. We're also looking at like how to manage all those production systems, how to come up with decision-making processes that's moving those engineering environments forward. But in our department, we recently get... 10 years ago... This Industry 4.0 scenario is getting more and more pushed into authentic research. So more and more data is gathered. We have to deal with a lot of data coming from various sources, and how to actually include this in the research, how to derive new findings from this, or even maybe, even physical equations from all the data that we are gathering around this manufacturing technologies. And this is something that we're, from the research perspective, looking at. >> And talk to me about when you were founded. You're based in Germany, but when was the lab founded? >> The lab was founded 100 years ago, about 100 years ago. It's like a very long history. It is the largest institute for production engineering in Germany, or maybe even in Europe. >> Got it. Okay. Well, 100 years. Amazing innovation that I'm sure the lab has seen. Russ, let's go over to you. Talk to us about the Dell EMC streaming data platform or SDP is what referred to it. >> Yeah. Thanks Lisa. So it's interesting that Philipp brings up Industry 4.0 because this is a prime area where the streaming data platform comes into play. Industry 4.0 for manufacturing really kind of encompasses a few things. It's real-time data analysis. It's automation, machine learning. SDP pulls all that together. So it's a software solution from Dell EMC. And one of the ways we make it all happen is we've unified this concept of time in data. Historical data and real-time data are typically analyzed very, very differently. And so we're trying to support Industry 4.0 manufacturing use cases. That's really important, right? Looking at historical data and real-time data, so you can learn from the past, work you've done on the factory floor, and apply that in real-time analytics. And the platform is used to ingest store and analyze data of this real-time and historical data. It leverages a high availability and dynamic scaling with Kubernetes. So that makes it possible to have lot different projects on the platform. And it really offers a lot of methods to automate this high speed and high precision activities that Philipp's talking about here. There's a lot of examples where it comes into play. It's really exciting to work with Philipp and the team there in Germany. But what's great about it is it's a general purpose platform that supports things like construction where they're doing drones with video ingestion, tracking resources on the ground, and things like that. Predictive maintenance and safety for amusement parks, and many other use cases. But with Industry 4.0 and manufacturing, RWTH and Philipp's team has really kind of pushed the boundaries of what's possible to automate and analyze data for the manufacturing process. >> What a great background. So we understand about the lab. We understand about Dell EMC SDP. Philipp, let's go back to you. How was the lab using this technology? >> Yeah, good question. Maybe, going a little bit back to the details of the use case that we are presenting. We started maybe five, six years ago where all this Industry 4.0 was put into research where you wanted to get more data out of the process now. So we started to apply a little census to the machine, starting with the more traditional ones, like energy consumption and some control information that we get from the machine tool itself. But the sensor system are quite like not that complex. And we could deal with the amount of data fairly easy now using just a USB sticks and some local devices, just a storage. But as it's getting more sophisticated, we're getting more sensor data. We're applying new sensor systems with the tool where the extra process is taking place, throughout the year, like delicious information is hidden. So we're getting really close to the process, applying video data, bigger data streams, more sensor data, and even like are not something like an IoT scenarios. We usually have some data points per second, but we're talking here about census that have like maybe a million data points a second now. So every high frequencies that we have to deal with, and of course, then we had to come up with some system that actually have to do this, help to deal with this data. And yeah, use the classic big data stack that we then set up for ourselves in our research facility to deal with this amount of streaming data to then apply historical analysis. Like Russ just talked about on this classic Hadoop data stack where we used Kafka and Storm for ingestion, and then for streaming processing, and Spark for this traditional historical analysis. And actually, this is exactly where the streaming data platform came into play because we had a meeting with one of the techy account at the university. And we were like talking about this. We were having a chat about this problem. And he's like, "Oh, we have something going on in America, in USA with this a streaming data platform. It was still under a code name or something." And then actually, Russ and I got into contact then talking about the streaming data platform, and how we could actually use it, and get getting part. We were taking part in the alpha program, really working with the system with the developers. And it was really an amazing experience. >> Were you having scale problems with the original kind of traditional big data platform that you talked about with Hadoop, Apache, Kafka, Spark? Was that scale issues, performance issues? Is that why you looked to Dell EMC? >> Yeah. There were several issues, like one is the scaling option now. And when we were not always using all of the sensors, we are just using some of the sensors. We're thinking about account process to different manufacturing technologies, different machines that we have in our laboratory so that we can quickly add sensors. They are shut down sensors. Do not have to take care about setting up new workers or stuff so that the work balance is handled. But that's not the only thing. We also had a lot of issues with administrating this Hadoop stacks. It's quite error prone if you do it yourself, like we are still in the university even though we are very big level laboratory. We still have limited resources. So we spend a lot of time dealing with the dev ops of the system. And actually, this is something where on the streaming data platform actually helped us to reduce the time that we invested into this administration processes. We were able to take more time into the analytics, which is actually what we are interested in. And specifically, the point that Russ talked about this unified concept of time, we now can just apply one and that type of analysis on historical and streaming data, and do not have to separate domains that we have to deal with. Now we dealt with Kafka, and Storm on one side, and Spark on the other side. And now, we can just put it into one model and actually reduce the time now to maintain and handle and implement the code. >> The time reduction is critical for the overall laboratory, the workforce productivity of the folks that are using it. Russ, let's go back to you. Tell us about, first of all, how long has the Dell EMC SDP been around? And what are some of the key features that WZL is leveraging that you're also seeing benefit other industries? >> So the product actually officially launched in early 2020. So in the first quarter of 2020. But what Philipp was just talking about, his organization was actually in the alpha and the beta programs earlier than that in 2019. And that's actually where we had a cross-section of very different kinds of companies in all sorts of industries all over the world; in Japan, and Germany, in the US. And that's where we started to see this pattern of commonality of challenges, and how we could solve those. So one of those things we mentioned that unified concept of time is really powerful because with one line of code, you can actually jump to any point on the timeline of your data, whether it's the real-time data coming off of the sensors right now or something minutes, hours, years ago. And so it's really, really powerful for the developers. But we saw the common challenges that Philipp was just talking about everywhere. So the SDP, one of the great things about it is it's a single piece of software that will install, manage, secure, upgrade, and be supported of all the components that you just heard Philipp talking about. So all the pieces for the ingestion, the storage and the analytics are all in there. And that makes it easier to focus on the problem there. There was other common challenges that our customers were seeing as well. Things like this concept of derived streams, so that you can actually bring in raw streams of data, leave it in its raw form because many times, regulatory reasons, audit reasons, you want to not touch that data. But you can create parallel streams of that data that are called derived streams that are versions that you've altered for some consumption or reporting purposes without affecting the others. And that's powerful when you have multiple teams analyzing different data. And then finally, the thing that Philipp mentioned we saw everywhere, which was a unified way to interact with sensors all the same way because there's sensors for IoT sensors, telemetry log files, video, X-ray, infrared, all sorts of things. But being able to simplify that so that the developers and the data scientists can really build models to solve a business problem was really where we started to focus on how we wanted to bring to market the value of SDP. >> So you launched this, right? And you said early 2020, right before the pandemic and all of the chaos that has- >> Don't recommend that by the way. Don't recommend launching into a pandemic. But yes. >> I'm sure that a lot of lessons learned from silver linings, I'm sure. >> That's right. >> But obviously, big challenges there. I'm curious thought if you thought. One of the things that we've learned from the pandemic is that for so many industries, the access to real-time data is no longer just a nice to have. It is a critical differentiator for those that needed to pivot multiple times to survive in the early days to thrive to continue pivoting. I'm curious, what other industries you saw Russ that came to you saying, "All right, guys. We've got challenges here. Help us figure this out."? Give me a snapshot of some of the other industries that were sort of leading Edge last year. >> Sure. There was some surprising ones. I've mentioned it a little bit, but it's interesting you give me a chance to talk about them. 'cause what was also shocking about this was not only that the same problems that I just mentioned happened in multiple industries. It was actually the prevalence of certain kinds of data. So for example, the construction example I gave you where a company was using drones to ingest streaming video as well as Telemetry of all the equipment on the ground. Drones are in all sorts of industries. So it turns out that's a pattern. But even a lower level than just drone data is actually video data or any kind of media data. And so Philipp talked about they're using that kind of data as well in manufacturing. We're seeing video data in every industry combined with other sensor data. And that's what's really surprised us in the beta program. So working with Philipp, we actually altered our roadmap after we launched to realize that we needed to escalate even more features about video analysis and actually be able to take the process even closer to the Edge where the data's being generated. So the other industries, including construction, logistics, medicine, network traffic, all sorts of data, that is a continuous unbounded stream of data falls into the category of being able to be analyzed, stored, playback like a DVR with SDP. >> Playback like a DVR. I like that. Philipp, back over to you. Talk to us about what's next. Obviously, a tremendous amount of innovation in the first 100 years of WZL. Talk to me about what some of the lab's plans are for the future from a streaming data perspective, got a great foundation infrastructure there with Dell EMC. What's next? >> Like we are working together with a large industry consortium, and then we get a lot of information. Not information, but they really want to see that all this big data stuff that's coming into Industry 4.0. And Russ already talked about it. And then, I'm pretty satisfied in having all the data and the data centers that they have, but they want to push it to the Edge. So all the analytics, it's getting more and more to the Edge because they see that the more data you gather, the more data has to be transferred via the network. So we have to come up with ways on, of course, deploy all the model on the Edge, maybe do some analytics on the Edge. I don't know, something like federated learning to see. Maybe you don't even need to transfer the data to the data center. You can start learning approaches on the Edge and combine them with different data sources that are actually sharing the data, which is the specific point in like corporations that want to corporate using the different data sources, but have some privacy issues. So this is something that we are looking into. And also, working like low-code or no-code environments, like different framework that we use here just in our laboratory, but this is also something that we see in the industry. And more and more people have to interact with the data management systems. So they have to somehow get a lower access point than just some pile from script that they need to write. Maybe, they just need drag and drop environment where they can modify some ingestion or some transformation to the data. So they're not always the people and all the data engineers or the computer science experts have to deal with those kind of stuff, and other people can do as well. So this is something that we are looking into this in the next future. But, yeah. But there are a lot of different things, and there's not enough time to talk about all of them. >> So it sounds like an idea to democratize that data to allow more data citizens to leverage that, analyze it and extract value from it because we all know data is oil, it's gold, but only if you can actually get those analysis quickly and make decisions that really affect and drive the business. Russ, last question for you. Talk to us about what you see next coming in the industry. Obviously, launching this technology at a very interesting time, a lot of things have changed in the last year. You've learned a lot. You said you modified the technology based on the WZL implementation. But what are some of the things that you see coming next? >> So it's really interesting 'cause my colleague at Dell constantly reminds me that people develop solutions with the technology they have at the time, right? It's a really obvious statement, but it's really powerful to realize what customers of ours have been doing so far. It's been based on batch tools and storage tools that were available at the time, but weren't necessarily the best match for the problem that we're trying to solve. And the world is moving completely to a real-time view of their data. If you can understand that answer sooner, there's higher value for higher revenue, lower costs, safety, all sorts of reasons, right? To do that, everyone's realizing you can't really count on... Like Philipp, he can't count on moving all the data somewhere else to make that decision, that latency; or sometimes, rules around controlling what data can go. Really, we'll keep it from that. So being able to move code closer to the data is where we see things are really happening. This is actually why the streaming data platform has really focused heavily on Edge implementations. We have SDP Core for the core data center. We also have SDP Edge that runs on single node in three node configurations for a headless environments for all sorts of use cases where you need to move the code and make the decisions right when the data is generated at the sensors. The other things we see happening in the industry that are really important is everything's moving to a fully software-defined solution. This idea of being able to have software-defined stream ingestion, analytics and storage. You can deploy the solution you want in the form factor that you have available at your location is important, right? And so, fully software-defined solutions is really going to be where things are at, and which gives you this kind of cloud-like experience, but you can deploy it anywhere at the Edge, Core or cloud, right? And that's really, really powerful. Philipp picked up on the one that we see a lot of this idea of low-code, no-code whether it's things like node red in the IoT world, where you're being able to stitch together a sequence of functions to answer questions in real time or other more sophisticated tools. That ability to, like you said, democratize what people can do with the data in real time is going to be extremely valuable as things move forward. And then the biggest thing we see that we're really focused on is we need to make it as easy as possible to ingest any kind of data. The more data types that you can bring in, the more problems you can solve. And so bringing on as many on-ramps and connectivity into other solutions is really, really important. And for all that, SDP's team is really focused on trying to prioritize the customers like Philipp's team in the RWTH WZL labs there. But finding those common patterns everywhere so that we can actually kind of make it the norm to be analyzing streaming data, not just historical batch data. >> Right. That's outstanding. As you said, the world is moving to real-time analytics. Real-time data ingestion is absolutely critical on there. Just think of the problems that we don't even know about that we could solve. Guys, thank you for joining me today, talking about what WZL is doing with the Dell EMC streaming data platform, and all the innovations you've done so far, and what's coming in the future. We'll have to catch up in the next six months or so, and see what great progress you've made. Thank you for your time. >> Thanks, Lisa. >> Thank you. >> For my guests, I'm Lisa Martin. You're watching a Cube Conversation. (calm techno music)

>> Announcer: From downtown San Francisco, it's theCUBE, covering RSA North America 2018. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're at the RSA conference in San Francisco 40,000 plus people talking about security, gets bigger and bigger every year. Soon it's going to eclipse Oracle Open World and Sales Force to be the biggest conference in all of San Francisco. But we've got somebody who's been coming here he said for 16 years, Ricardo Villidiego, the EDP and GM Security and Fraud for Cyxtera. Did I get that right, Cyxtera? >> Cyxtera. >> Jeff: Cyxtera Technologies, great to see you. >> Thank you Jeff, it's glad to be here. >> So you said you've been coming here for 16 years. How has it changed? >> Yeah, that's exactly right. You know it's becoming bigger, and bigger, and bigger I believe this is a representation of the size of the prowling out there. >> But are we getting better at it, or is it just the tax service is getting better? Why are there so many, why is it getting bigger and bigger? Are we going to get this thing solved or? >> I think it is that combination within we have the unique solution that is going to help significantly organizations to get better in the security landscape I think the issue that we have is there's just so many now use in general and I think that now is a representation of the disconnection that exists between the way technologies are deploying security and the way technologies are consuming IT. I think IT is completely, has a evolved significantly and is completely hybrid today and organizations are continuing to deploy security in a way like if we were in the 90s. >> Right. >> And that's the biggest connection that exists between the attacks and the protection. >> But in the 90s we still like, or you can correct me, and we can actually build some big brick walls and a moat and a couple crocodiles and we can keep the bad guys out. That's not the way anymore. >> It is not a way. And look, I believe we're up there every protection creates a reaction on the adversary. And that is absolutely true in security and it is absolutely true in the fraud landscape. Every protection measure will push the adversary to innovate and that innovation is what, for good and for bad, has created this big market which we can't complain. >> Right, right. So for folks that aren't familiar with Cyxtera give them the quick update on what you guys are all about. >> So see, I think Cyxtera is here to conquer the cyber security space. I think what we did is we put together technologies from the companies that we acquire. >> Right. >> With a combination of the call center facilities that we also acquired from Centurylink to build this vision of the secure infrastructure company and what we're launching here at the RSA conference 2018 is AppGate 4.0 which is the flagship offering around secure access. Secure access is that anchor up on which organizations can deploy a secure way to enable their workforce and their party relationships to get access the critical assets within the network in a secure way. >> Okay, and you said 4.0 so that implies that there was a three and a two and probably a one. >> Actually you're right. >> So what are some of the new things in 4.0? >> Well, it's great it gives it an evolution of the current platform we lounge what we call life entitlements which is an innovative concept upon which we can dynamically adjust the permitter of an an end point. And the user that is behind that end point. I think, you know, a permitter that's today doesn't exist as they were in the 90s. >> Right, right. >> That concept of a unique permitter that is protected by the firewall that is implemented by Enact Technology doesn't exist anymore. >> Right. >> Today is about agility, today is about mobility, today is about enabling the end user to securely access their... >> Their applications, >> The inevitable actions, >> They may need, right. >> And what AppGate does is exactly that. Is to identify what the security processor of the end point and the user behind the end point and deploy a security of one that's unique to the specific conditions of an end point and the user behind that end point when they're trying to access critical assets within the network. >> Okay, so if I heard you right, so instead of just a traditional wall it's a combination of identity, >> Ricardo: It's identity. >> The end point how their access is, and then the context within the application. >> That's exactly right. >> Oh, awesome so that's very significant change than probably when you started out years ago. >> Absolutely, and look Jeff, I think you know to some extent the way enterprises are deploying security is delusional. And I say that because there is a reality and it looks like we're ignoring ignoring the reality but the reality is the way organizations are consuming IT is totally different than what it was in the 90s and the early 2000s. >> Right. >> The way organizations are deploying security today doesn't match with the way they're consuming IT today. That's where AppGate SDP can breach that gap and enable organizations to deploy security strategies that match with the reality of IT obstacles today. >> Right. If they don't get it, they better get it quick 'cause else not, you know we see them in the Wall Street Journal tomorrow morning and that's not a happy place to be. >> Absolutely not, absolute not and we're trying to help them to stay aware of that. >> Right. Alright, Ricardo we'll have to leave it there we're crammed for time but thanks for taking a few minutes out of your day. >> Alright Jeff, thank you very much I love to be here. >> Alright. He's Ricardo I'm Jeff you're watching theCUBE from RSAC 2018 San Francisco. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Welcome back to AWS re:Invent 2017. I am Lisa Martin with theCUBE, our day two of continuing coverage of this event that has attracted 44,000 people. Keith Townsend is my cohost, and we are very excited to welcome to theCUBE family Simon West, the CMO of Cyxtera. Welcome, Simon. >> Thank you, great to be here. >> Cyxtera, a six-month-old company. Tell us about it, what do you guys do? >> Sure, so as you said we are just six months old. It feels longer than that now, born at the intersection of five simultaneous acquisitions. One part of that was the acquisition of 57 data centers and a global co-location business that was formerly owned and operated by Century Link. Into that we've added the security and analytics capabilities of four modern startup software companies, and the vision is to provide a secure infrastructure solution both within our data centers, but interestingly even though I've got 57 data centers around the world, I want to be location agnostic. We recognize that today's enterprises are running multi-clouds, running hybrid environments, so we extend our security solutions on prem and into public clouds which is why we are here at AWS re:Invent. >> Fantastic. >> One of the big challenges that we hear from the enterprise perspective, hybrid IT is that the control that we have internally are very different from the controls that exist in AWS. How do you guys help even that out? >> You are exactly right, we would go so far as to gently suggest that the core method by which we protect access to infrastructure and applications which is still predicated on a physical perimeter is just fundamentally flawed in a 2017 world where your applications are everywhere, your users are everywhere connecting on a myriad of devices. You can't build a wall around that which doesn't exist. You have also obviously, as you say, you've got that problem of hydrogenous platforms, each with their own method of control. Our flagship product in that area is a product called AppGate SDP. SDP stands for software defined perimeter which is an emerging specification born out of the US government's disarm. Now a number of companies are offering software defined perimeter solutions. The basic premise that we hold is that security should be user centric rather than IP centric. A firewall is still predicated on granting access from one IP block to another IP block. The VPN may capture who is coming in, but once you are in, we give you basically unfettered access to flat corporate internal networks and we track you as an IP address rather than as a user. We think we should get more user centric. The user should be at the center of our policy. We think it should be more like cloud in the way we run security so rather than these hardware-based static central chokepoints, we think security should be real-time, it should be adaptive and intelligent, and it should be as agile as the cloud. You build cloud applications that are capable of spawning multiple copies of themselves, auto scaling up and down, moving from availability zone to availability zone yet our typical network security posture is still highly static. When you have some of the high profile attacks that we have seen over the last few months, our ability to change policy, immediately we recognize a problem. A particular operating system, apps in a particular service pack, is incredibly out of step with how agile the rest of our IT is. So more like cloud in terms of the way it operates, and finally we think, and so does the software defined perimeter spec, we think that access needs to be thought of as conditional rather than just a X, Y, yes or no. Jim has access to sensitive financial systems should be dependent on what operating system Jim is using whether Jim is on a coffee shop Wi-Fi network or on a structured corporate network, the time of day, the day of week, our overall security posture. The way AppGate works is when a user tries to access a system, the policy can ingest any one of these different conditional items. It can interrogate the device the user is using for the right software revisions. You can look at environmental variables. It can even look at internal business systems and check anything it can get to via an API, and only if those conditions are met will it provide access to a specific system, and then it can monitor that real time, so if your context changes, you move from a trusted network to an untested network, we can alter access. We can prime for a one time multifactor authentication or take any other steps the user wants. We offer that in cloud, on premise, integrated into our data centers to provide one central policy mechanism no matter what platform you are running on. In the case of AWS, we integrate with features like security groups, like AMI machine tagging, so you can build policy natively out of those Amazon features as well. >> Talk about that transition to this user based approach. I would imagine that a user can migrate their legacy systems into one of your 56, 57 data centers, and then as they start to expand out to the cloud, they have to change their operating model from they may migrate their traditional big firewall into your data center. What does that migration process look like? Is that an application by application spec, network by network? How do I transition? >> You know, it really varies. It feels a lot like I'm an old cloud guy, so it feels a lot like cloud did in the late 00s, in 2008, 2009. We think the software defined perimeter is going to have that big of an impact, a cloudlike impact on network and application security, but the way in which organizations will choose to implement it is going to vary. One of the things we did very early on was to integrate AppGate as a service into the data centers. If you think about co-location environments, when you bring new gear into a data center, you racket and stack it, the very next thing you do after that is drag a VPN back to the corporate office so you can access it remotely, which we would respectfully suggest is not necessarily the best way to do it in 2017 out of the chute. We've then integrated AppGate so organizations can just avail themselves of that as a service, and instantly have a kind of easy on-ramp. One of the big areas we see, and we've seen with customers here at re:Invent is customers who are moving workloads to cloud, and want to make sure that they can have that same sense of fine-grained access control common to those on premises and off premises environments, whether that's at migration or that's just an extension of an app into cloud environments, so it's kind of all over the place. >> Sorry Simon, what differentiates Cyxtera's approach to the software defined perimeter from your competitors? >> A couple of things, it's extremely robust in terms of one, being able to run in multiple environments, so a native AWS version, versions that run natively in other public cloud environments. Obviously we think the ability to offer it deeply integrated into the data centers is important. It's also capable of granting access to more than just web applications. You've got some solutions out there that are really web proxies and that are built for SAS apps and born on the cloud apps. This is more of a fundamental network platform by which you can gain access to any system or application you choose, and finally was introduced the concept of what we call scriptable entitlements which is the ability to interrogate third-party systems via API, and bring back those results as part of the building policy. An example there is we've got service provider customers who are running large multitenant environments. You then have a technical support organization who needs to support a huge multi thousands of servers environment with multiple customers running in multiple VLANs and typically the way you have to do that is a jam box in the middle and then giving these technical support folks access to that entire backend management network which is a security risk. With AppGate, you can actually integrate into a ticketing system and when John in support asks for access to a customer database server, at runtime, we can find out whether there is a trouble ticket open on that box assigned to that rep, and only then will we grant access. We don't grant level network access. We grant access to that specific application. We call it a segment of one, secure and cryptic connection between the user's device and the application or the applications they have access to but to nothing else. Everything else on the network is literally dark. It cannot be port scanned. It doesn't show up at all, so it's a much narrower sense of control, a much narrower sense of access, and again it's dynamic. If that trouble ticket that shut off, the access goes away automatically. We think the integration into business systems is a critical piece of the puzzle and an area where I think we have innovated with AppGate. >> Let's talk about security in depth. Obviously you guys are putting the software security perimeter around the data center, what we would classify as the data center which is kind of disappearing in a sense, and the edge. You talked about end-user protection. Where do you guys pickup and drop off when it comes to MDM, mobile device management, which is much more important now with mobile, and then laptops, desktops, et cetera, and you mentioned third parties, pieces of data center equipment that's not in your data center, like a wind farm. >> Sure, so you are right. We are absolutely moving to the edge. I think we continue to think that the data center will be as important as it ever was. The more cloud we have, the more data centers it needs to run in. The more public cloud we have the more people want to move some of their machines that might have historically run on prem to cloud data centers with low latency direct connect to public cloud environments. If you look at our data center footprint with regard to the edge, we are not just in the major markets, although in major metropolitan markets I've got half a dozen data centers all linked together, but I'm also in markets started across the country, so I've got half a dozen in New York and New Jersey, half a dozen in DC, half a dozen in the Bay Area, but I'm in Tampa, I'm in Columbus Ohio, I'm in Dallas, I'm in Denver, and so that distribution becomes particularly important as more customers move data to the edge. From a security perspective, again, we think of that data center as the nexus of enterprise at IT and the cloud. The data center is where our conversation about security in terms of access control starts. It's a physical security message of biometrics, and ID checks, and so forth, but there, we think is the missing piece of the puzzle. The principal point of ingress and egress into a data center today is not to the front door, the back door, or the loading dock. It's the massively clustered multicarrier network core, so if you are not providing some level of access control in and out of the network, I'd offer you are not providing a truly secure infrastructure solution. We start there. We are focused mainly at this point with AppGate at controlling the conversation between the user device and the system applications themselves. One of our other acquisitions, a company called Cat Bird has done some innovative work in terms of east/west segmentation in virtual environments, which is notoriously difficult otherwise to see, to stop the spread of how machines can talk to each other in a large virtualized forms as well, and so it's the infrastructure where we principally focus. >> Where are we, or maybe where are you guys in this revolution of information security? Are we at the forefront of massive change? What is Cyxtera's view on that? >> I think we are at the beginnings of a revolution that's about 20 years late. If you can kind of carbon date year zero of modern IT at around 1996, which is the advent of the Internet as a commercial and consumer force, that was the revolution for enterprise IT. That was the moment that we had to move IT outside the four walls of the machine room on the corporate campus. Prior to that, the applications all ran on big beige boxes in one room. The users were largely tethered to them by smaller beige boxes in other rooms, and the notion of perimeter security worked. It was a valid construct. As soon as enterprises had to start thinking about an increasingly global user base, as soon as users started to connect from all over the place, the concept of this perimeter goes away. Over the last 20 years, you've seen revolution after revolution and the way in which we design, provision, deploy, manage and operate our business applications, our development frameworks, and our infrastructure. We've revolutionized for availability. We've revolutionized agility. We've turned IT into a real-time API driven motion, and we've revolutionized for scalability with platforms like AWS just industrializing this real time IT on a global scale, and if you took a systems administrator from '96, and you showed them IT today, I think you have some explaining to do. If you took a security administrator from 1996 and showed him 2017, I think the construct would be familiar. We are still hardware driven in a software defined world. We are still assuming that access is static, that it's never changing, that it's predicated on the users being someplace, the applications being another, and again, in a world of real time IT, a world in which our underlying application footprint changes without any human intervention whatsoever, and I think you see with WannaCry, with NotPetya, with all of these attacks, the commonalities that they have in the terms of the reason they were so devastating is one, they take advantage of lateral spread. They take advantage of riding an authorized access into a corporate network where port scans show up 10,000s of ports where you can rattle the handles, break the locks, and spread like wildfire, and two, in the case of something like WannaCry, days after we realized what the problem was, we were unable to simply alter as an institution, as an industry, or as an enterprise access policy at the press of a button until we could get things patched. We had to sit, and wait, and watch the fires continue to burn, so it's a question of security being insufficiently agile, insufficiently automated and adaptive, and insufficiently software driven. We think that is just starting. I think on the SDP side, we've noticed in the last six months the conversation changing. We've noticed customers who now have SDP mandates internally who are seriously starting to evaluate these technologies. >> Wow, it sounds like Cyxtera is at the beginning of being potentially a great leader in this security revolution. We wish you, Simon, and the entire company the best of luck. We thank you so much for joining us on theCUBE, and we look forward to hearing great things from you guys down the road. >> Much appreciated, thank you both. >> Absolutely, for my cohost, Keith Townsend, I'm Lisa Martin. You are watching theCUBE's continuous coverage of AWS re:Invent 2017. Stick around guys, we will be right back.