(upbeat music) >> Hello, and welcome back to theCUBE's coverage of Red Hat Summit 2021 Virtual. I'm John Furrier, host of theCUBE. We got a great guest here, Raymond Kok, Senior Vice President Cloud Application Solutions at Siemens Digital Industry Software. Raymond, thanks for remoting in with theCUBE Virtual all the way from the Netherlands. Great to see you. We're in Palo Alto, California. Great to see you. >> All right, thanks for having me. >> Love the international culture of the vibe with virtual, one of the benefits of having remote, which we were in person, but soon the pandemics coming around the corner, but great to see you. Let's get started, let's get into the Digital Industry Software Group that you're involved in, your relationship with Red Hat. But first let's start with, if you could take a minute to give us a brief overview of Siemens and your role there. >> Yeah, so first of all, let me talk a little bit about Siemens because Siemens is obviously a big company. So as you already announced, I'm part of Siemens Digital Industries Software. So Digital Industries is actually the vision at Siemens that is really focused on how to help companies to become a digital enterprise. And so as part of this IoT (faintly speaking) Industrial Internet of Things is obviously an important element of that. And so if you look at my role at Siemens, is really to be the business lead for the cloud part of IoT. And so what I mean with that is specifically a product line called MindSphere. And so Siemens, like I said, is looking at the overall digital transformation of customers, relay product landscape but also how we can support them with new technologies and IoT is very much part of that. >> One of the benefits of doing theCUBE interviews over the years and having the team that we have in the media side, we get to see things early. Industrial IoT, we've been blogging about and reporting for a couple of years now, now it's hard. Because with the pandemic, you still need things to run. And so Industrial IoT, not withstanding, there's still the other edges like consumer edge and other devices, but Industrial IoT is getting all the focus because of security and also because of just critical operations, critical infrastructure and for business and public sector, private sector, everything. This is a huge area. Could you talk about your strategy around Industrial IoT and specifically how you guys are using this analytics, MindSphere as you mentioned, what is that about? How does that help me if I'm a manufacturing organization? >> Yeah, so first of all, maybe it's good to clarify what we mean with Industrial IoT, because there's IoT and there's Industrial IoT. So, when people typically talk about Industrial IoT, it's really three main areas. It's smart grid. So it's really around IoT for energy management and energy usage. There is smart cities. So this is really IoT for smart buildings but also any kind of infrastructure that goes with smart cities. And then the last one is smart factories. And so, we typically, when we say Industrial IoT, we have clients that cover the three main areas that I just mentioned. And so really what it is about is to take advantage of data, right? So IoT is really about how you take advantage of data and how do you actually get insights from this data to run your business better? So maybe to give a specific example, if you look at one of our major customers, like for example, Coke Hellenic, and they just actually presented that (mumbles) last week. They are trying to use IoT to advance how they actually operate the bottling lines of the factories. And so it's really above operational excellence. So, meaning how to get more trooper, how to get more efficiency into how they do production. But in many cases, John, it's also about energy management because data is not just about, okay, operational excellence but also surrounding topics like, how can I better preserve energy as I produce something? And so, yeah. So in many cases, IoT is all about data, getting next levels of insight from the data and then put that to a particular use. So this can be answering the quality of production, getting better performance of your equipment, getting a better use of your equipment when it comes to energy consumption. So there are many use cases typically related to Industrial IoT. >> Yeah, and you got to love the industrial definition to the way you laid it out. That's critical infrastructure and emerging infrastructure and plant and equipment, all those things. But it's also a proxy for (faintly speaking) for business. So this kind of brings me to the kind of connecting the dots. If you don't mind, I'll jump to the convergence question I'd love to bring up, which is the convergence of IT, Information Technology and Operational Technology, OT, which has been discussed before, but you talked about culture clashes, different cultures. Also systems are different, purpose-built, potentially on one side, but they've got to come together, okay? These are both very important software pieces to the puzzle on the platform. How do you see that evolving? What's your take on resolving this dilemma of the priorities, of innovation and security and openness? What's your take on this? >> (Faintly speaking) Topic, John, because the reality is that OT has to ITinice and IT has to OTinice I guess, when we talk about IoT, right? So I think that's why at Siemens, we have kind of a unique viewpoint because Siemens looks at both the OT side of the world through, for example the context of discrete, the process industries look at the automation part of it, so meaning the actual operational automation and then obviously only equipment that comes with it, which is really typically an OT conversation. Then if you look at my business unit, so, Siemens Digital Industries Software, we look at it really from an IT point of view, and so how can we help these customers to become a digital enterprise? And so at Siemens, we're kind of bringing these two views together. And then to your point, we're trying to make the integration as seamless as possible. And to your point actually, it includes also making sure that we actually drive the standards that are going to make this enable, that are going to make this possible, can be open standards like OPC UA, for example, when you look at discrete manufacturing, but can also be standardizing on certain technologies, right? And so what we're seeing is that, for example, back to my word, talking is really Kubernetes and kind of the container technology that is out there, standard technology is helping this conversation as well. >> Yeah, the integration piece, that's the Kubernetes, containers and micro services. These are bringing cloud native integration points. And that's really going to be key, I'm going to get that in a second, but I want to come back to the MindSphere Analytics piece because data is critical as you mentioned. So integration data security and observability means security, monitoring all these things are evolving. You guys earlier this year, announced you expanding this MindSphere reach in partnership with IBM and Red Hat, so consumers could run on on-prem and cloud. That's the topic of this event. The main theme at Red Hat Summit this year is clearly hybrid cloud, in a distributed kind of computing paradigm which we all love. This is what we're talking about here. We're talking about distributed computing edge, Core Cloud. Why is this important for Siemens and your customers? Why did you decide to work with IBM and Red Hat on this initiative? >> Yeah, it kind of was already somewhat in your question, meaning that if we work with our customers, really the cloud conversation that we have with them is a hybrid cloud conversation. And what we mean with that is, yes, there're elements of public clouds, but especially when you talk about critical factory operations, many of these workloads that we're talking about are actually very close to the shop floor or are at least some what near, and therefore any kind of large enterprise OEM that we work with, so whether it's an automotive OEM, whether it's an aerospace and defense OEM, they all have a hybrid cloud strategy. And so what is interesting about IoT is that this is where hybrid cloud kind of comes together. It kind of goes back to your previous question about IT and OT coming together. As you can imagine OT has always been very on-premise because it's near real time critical factory operations. IT obviously much more comfortable with public cloud. So we're trying to bring this together and therefore, many of these conversations that we have with large enterprise OEMs is really a hybrid cloud conversation. So specifically, what we're doing here together with Red Hat is to enable exactly that. So meaning that we can take MindSphere or solution for IoT Analytics, we can bring that not just to a public cloud or make that available as a public cloud solution, but also on-premise private clouds. And I think it's very interesting because it opens a conversation that allows people to really now start talking about value as opposed to being worried about, okay, where is my data going? Is it secure? Is it actually going to be available when I need it for factory operations? So, yeah, I'm pretty excited about this work that we're doing together, because again, it's about value, making sure that our customers actually can fit what we do at Siemens into a landscape that they feel comfortable with. >> It feels to me, I may be a little bit old school but I feel like this is the innovation that we saw in the eighties and nineties as networks got more expansive and inter networking happened and you start to see that life blood of the action and the value get enabled. And I think your point about hybrid and operating around the environment is critical, because this brings up new challenges and new opportunities. For instance, you don't need to bolt on a caching layer to manage a slow database or you can get real time, and you can get better performance and compute. You don't need to move the data around. So, bringing compute and resource and scale to these edges when they need it, focuses more on the solution architect less on putting point technologies in place to solve. >> Yeah, exactly. Maybe to chime in on that, I think what is also interesting is that it allows the customers to optimize where to best place the workloads that they care about. And so maybe to make that a bit more specific, if you think about a use case like energy management. So let's say that I have a production line, 1500 assets that are consuming energy. If you then think about the data that is involved in analytics, you can imagine that if I start sending all this data to public cloud, maybe, maybe not the most efficient setup, because a first level of filtering and analytics, I can very much close do or do that close to a 2D equipment. And then when I get to aggregation of data, and some further filtering to figure out, okay, what is really happening at the line level? What is really happening at a particular production area level? Again, I think you can do that prior to actually sending some of this data to the cloud, meaning public cloud. Where the public cloud becomes interesting is when you want to aggregate, for example across multiple manufacturing facilities. Now you want to look at the KPIs of one factory versus another, you want to aggregate across multiple factories, you want to figure out, okay, why are certain trends happening just in this factory and it's better in this one? But I think that's why, what we're seeing with clients is that they're expecting from us a layered architecture and to your point, the most efficient way of actually dealing with their use cases across the infrastructure that is available to them. So yeah, if you look at Siemens, we're trying to kind of carefully think about all these layers from fields to edge, to on-premise private cloud, to public clouds, and then make sure that along the way each layer has value and that it's there for a purpose and for a real reason, right? And not just for the sake of having it. >> Yeah, or being limited by the architecture that you're stuck with, constrained by the architecture by what the solutions are. You're saying, the script is flipped upside down where you can optimize your business, which by the way will flow up more data to evaluate. So there's a new post analysis mode of post configuration, and you could align your resources best way you see fit to maximize your business model. This is the beautiful thing about this distributed edge concept is the software enablement of the business is there. So the data is critical. So, as more controlled data comes in, it's not just set it up and watch it run. Yeah, there's automation involved in a lot of software but you're getting new data coming in. If you have this new observation space, of new horizontally scalable data, this new data coming in. >> Yeah, exactly, exactly. And I think you said a key point there. We don't want our architecture to constrain. I guess, what kind of value the customer can actually get out of these use cases and therefore, I think it's kind of exciting that in this ecosystem, especially also the interplay between Red Hat and Siemens, that we kind of take it one step further and think about, okay, what is actually truly the most optimal way for customers to go do this? And that we've formed these kinds of partnerships to really help the customer even take another step forward. So I think it's pretty, pretty nice. >> Well, Raymond, I really appreciate it. That's a masterclass, a commentary, nice gems you're dropping here on theCUBE, I appreciate it. The way I look at it, I'd love to get your final reaction to kind of the world we're living in. Just my take on it is that, we have a new operating system of business, and we're kind of getting at, is that you guys now can have an operating model for your customers and software. It's not just another (faintly speaking) For a server and the server is the business, it's the world now. >> Yeah, exactly. And I think from my point of view, I think it's exciting to see us again in this world of complex technology always to find new ways to help the customer to kind of advance their use cases, right? Because the imperatives that, for example discreet manufacturing doesn't really change. They've been there for many, many years. And I think for us to be able to bring out technology closer together and then solve, and I do use use cases in an even more efficient way. I think that's pretty interesting. And yeah, so I see good things and I think ultimately IoT, I think those that can actually bring real value are going to be able to deal like we just talked about, the hybrid scenarios, but the people that are going to matter is the people that can bring the most insights out of this data, right? Because what I always say about IoT is, it's yet more a messy data. So it's only worth actually collecting all this data if you actually get next to levels and new levels of insight from it. And I think, yeah, it has to kind of fit that kind of a mantra, and I think together that we're really trying to figure that out, so- >> I know some people as well would agree with that statement, I do as well, but the other side of that question is, if you don't architect the edge properly or the IoT edge, the data costs could be compelling. You could get hit with some charges because most people have been burned by the idea of moving data around versus say, moving compute. So, back to this value, where's the edge? What're you optimizing for? That's kind of the big question. How do you react to that when someone says, Raymond, what should I be optimizing for as I lay out my architecture for the core to edge, data center cloud edge scenario, what am I optimizing for? >> Yeah, I think you kind of work backwards from what you're trying to achieve. I think it may sound kind of obvious, but quite often I get in discussions with customers where we first start talking technology, obviously it's exciting. I'll be kind of attacking myself. So it's exciting to talk about technology but they forget to start from, okay, what's the return of the invest and what's the use case, right? And so, what are we trying to solve? Who is trying to benefit from it? And what benefit are they looking for? And then if you carefully work backwards from there, you will actually see that as we just talk about data and insights into data are in many cases, leading some elements of the value that a particular person is looking for. And then working backwards from there, you will actually figure out that back to the layer of discussion that we just had, this data doesn't have to be available at every level, right? Every layer adds some value, and so therefore you have to have kind of an open discussion and that's meaning an open discussion about what layers to use. And that's why at Siemens, we kind of follow that approach. So meaning that we work backwards from the use case, then we think about, okay, what is most appropriate at the field and control level? Then what to your point, is the most appropriate at the edge level? Then what is the most appropriate at the cloud level? And then from there, you actually figure out, okay, where do I deploy? What kind of acquisition of data? What kind of insights am I interested in at that level? And then basically, what kind of machine learning am I going to deploy there? And then work all the way from there. And it seems to work. And that's why to your point, it's all about making sure that at every level data is there for a reason and you process it for a reason, because otherwise it's just acknowledging it, interesting still, but it doesn't have any value, right? >> Awesome. Raymond, great insight there. And this is all about engineering. You guys are doing a great job. Engineering, the solutions, this is DevOps, DevSecOps, it's some hybrid cloud, really bringing those that value to the edge, industrial edge. Congratulations for all the great work. Raymond Kok, Senior Vice President, Cloud Application Solutions at Siemens Digital Industries Software. Thanks for coming on theCUBE. >> Okay, yeah. Thanks for having me. >> Okay. >> Thank you. >> I'm John Furrier with theCUBE, Red Hat Summit 2021 Virtual. 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