 Last decade, the major vectors of power in tech were cloud, mobile, social, and big data. Network computing architectures were heavily influenced by the mobile leg of that stool, with bring your own devices and the classification of the enterprise. The next 10 years are going to see a focus on instrumenting the edge and leveraging architectures that provide a range of capabilities from very small embedded devices to much larger systems that span hybrid IT installations, they move data across clouds and then to the very far edge. And it's so often the case, consumerized IoT technologies, rapidly driving innovations for enterprise IoT. What are the key trends, challenges, and opportunities that this C change brings and how should we think about the expanding networked universe and what will it take to thrive in this new environment? Hello everyone, this is Dave Vellante and welcome back to HPE Discover 2021. You're watching theCUBE's virtual coverage of HPE's annual customer event and with me to discuss the next decade of IoT innovation and enablement is David Logan, who's the vice president and CTO for the Americas for HPE's Aruba Networks. David, welcome to theCUBE, come on in. Thanks so much, it's my pleasure to be here today with you. So if the last decade was all about mobile, and that was legit, it was really driven by the iPhone and Android adoption. And we've been hearing about IoT for a long time. What's the impetus behind the current focus on IoT is it connected cars, connected homes? What's making it real this time from your point of view? You know, it's really almost everything at once. If you look at how IoT systems had been developed over the past 10 years, it was super industry-specific, a lot of niche implementations, a lot of product vendors trying to become an IoT platform play. But with all of that innovation that's taken place, it's been additive over that past 10 years. Now the next 10 years, we're really looking at a phenomenal amount of growth, a phenomenal amount of increased innovation to bring IoT solutions to almost any industry for any purpose, whether it's a horizontal need or a vertical need. So you guys use terms like solutions enablement, IoT solutions, it's a real big focus of HPE's edge to cloud narrative. I wonder if you could add a little color and some details behind that and explain how Aruba fits in? I'll be glad to. So HPE's edge to cloud strategy is a really accurate term. Ultimately, the edge is where IoT solutions are first enabled and it's where data is born. It is where end user experiences live. And Aruba's role in edge to cloud architectures is to provide the connectivity, the performance assurance, the ability to commingle what were once parallel architectures into common infrastructure, common operating platforms and allow this data that's born at the edge to go all the way to the hybrid cloud infrastructure wherever it needs to go, whether it's an IoT end user application, whether it's an IoT subsystem for industry or for a vertical industry or for a vertical enterprise, the Aruba infrastructure really provides this common operating platform at the edge so that the rest of the enterprise can benefit from what's transpiring. When you think about the sort of candidates for IoT at the enterprise level, I mean, the edge obviously is very fragmented and of course the big industrial giants, they're on a path, they're digitizing, they're collecting data, they're driving new monetization initiatives and they got the budgets to do that. Can smaller companies come to this party? Absolutely and it's really the consumerization of IoT that's really driving that. As you mentioned in some of your opening statements, the consumerization of computing with mobile computing architectures, SaaS, cloudification of applications and the extension of the enterprise application environment to the end user with their consumer devices as opposed to their enterprise-issued devices, we're seeing the same effects in IoT now. The consumerization of IoT, the release of the Amazon Echo in 2014, all of the smart TV technology, all of the in-home automation technology that's been developed for individual use cases, for conglomerated use cases, it is this innovation that is now being able to be brought into the enterprise, either in the form of pure consumer technology, just take a look inside your average student dorm room, how much digital technology they brought in, but it's in an enterprise setting in the university. Think about hospitals, healthcare that have brought in technology to facilitate their particular processes. The consumerization will allow digital experiences to be delivered to the patient in their treatment suite, for example. So we're going to see this really drive over the next 10 years quite a significant amount of interesting new use cases. You know, just a quick aside, David, I mean, that Echo example is kind of interesting because when you think about the predominant use cases for AI at the enterprise, it's largely modeling that's taking place in the cloud. But when you think about the predominance of AI on whether it's smartphones or you mentioned things like Echo, that's kind of AI inferencing at the edge, facial recognition is another good example. That's bleeding into the enterprise. And as we've talked about up top, it sort of points the way and informs the enterprise much like the consumerization of IT. Absolutely, you know, organizations like Microsoft, Google, Amazon, they're really leading the charge from both a consumerization perspective, but also a developer enablement perspective, bringing the ability for AI machine learning, very specific capabilities, like you mentioned, video recognition, to be able to be brought into enterprise application environments by a developer, so that they don't necessarily need to know how to develop that full AI ML stack, but can incorporate that capability into their end user applications. And then it's going to lead to brand new productivity innovations that an enterprise can benefit from. It's going to lead to certainly new business models. It's going to lead to the ability to integrate federated systems together, whether it's a business model between two enterprises or whether it's the, you know, how a particular enterprise operates their own business. It's going to be really fascinating. I was reading about hand recognition, you know, for security, you go beyond fingerprint recognition. It should now be hacked. Let's talk about the market. Everybody talks about the TAM, you know, pick your trillion, one billion, one trillion, two trillion. It's a huge total available market, as they said, very fragmented. So how do you think about segmenting the market? How should we think about the different categories of IoT and solutions and architectures? Well, you know, every organization is easily categorized by their industry, healthcare, higher education, industrial, retail. They all have their particular operating models that generally speaking have a lot of similarities. And so when we think about market and market segmentation, I think it's first important to think about the particular vertical that an enterprise organization belongs to. And then, you know, innovators like us here at Aruba, we think about how do these particular industries need solutions, and then we look across them for horizontal opportunities. For example, within Aruba's solution set, the ability to go through rapid IoT device onboarding and security policy process and procedures, that's pretty universally applicable across many different industries. But at the same time, when you look inside a particular vertical like a heavily industrialized setting, they want to collapse their OT infrastructure and their IoT and IT infrastructures altogether. And they're going to need some very specific solutions to do that, whether it's the ability to guarantee data flow from the edge to the cloud, whether it's security, performance assurance, whatever their needs are, they're going to be very unique to them too. And so looking at it by vertical first is important. And then I think setting by size makes sense. And then as we were talking about earlier, the consumerization of IoT systems is really going to bring the ability for medium and smaller organizations to benefit from a lot of these innovations. Another aside, maybe it's not a quick aside, but you get the OT and the IT, you got OT engineers that are pretty hardcore about the way they do things. And you got IT folks, they have security edicts and compliance and so forth. How are they working together? Like who's driving the bus and that convergence? You know, every organization has their own operating culture. They have their prior way of doing things and then they have the future. And the real key here for leadership, honestly, the real key here for organizational leadership, solution technology leadership in these organizations is to figure out how to bring everybody together. The OT responsible part of the organization, the folks that are in the line of business, the folks that are in biomedical engineering and a healthcare organization, they know what the end application is. They know what the systems behaviors are going to be from an end users perspective or from a technologies perspective as it's applied at the edge. The IT team knows how to build and operate and maintain a robust infrastructure that is all co-mingled together, that is all integrated together. They're going to have to work together so that they understand the end user applications, the experiences that need to be delivered, the systems architecture and then how it needs to be operated. But the reason they need to come together is it needs to be using a common enterprise architecture to do so. Common network infrastructure, common computing, storage, data platforms, at least from a standards perspective so that the enterprise can get operational efficiency. And so they can really have the one plus one equals three value proposition moments when multiple systems come together. So a couple of things we just hit there, the organizational challenges, the architectural challenges. You don't want to have more stovepipes. Everybody talks about stovepipes and data silos. Are there any other challenges that you'd note that an organization faces in planning and implementing an IOT solutions architecture from your perspective or the organizational, we talked about that. We talked about some technical, any others that we might have missed. It's interesting when you look inside an enterprise that has some decent best practices or some good best practices for implementing their enterprise IOT frameworks. As I mentioned, bringing the organization together from the end user perspective and the experiences that they need from the operational perspective and the operational technology bleeding into or merging into IT technology. Clearly there's that organizational component, but that then needs to map into a newly refined enterprise architecture. Last decade, the 90s, the 2000s, 2010s, we talked about an enterprise architecture a lot. It was a lot about client server and it was a lot about migrating from legacy application architectures into Next Gen and Web 2.0. And now it's all about machine to machine and mobile and post-mobile. And that means the enterprise architecture that maybe got dusty on the shelf needs to be pulled off and re-implemented. And interestingly, as a networking vendor, what we've seen as a best practice is these enterprise organizations recognize that with cloud and mobile and IOT and vendors playing such an important role that a lot of control and a lot of visibility has been pulled away from the classic enterprise IT organization. And now looking at the network as the place where experiences come to at the places as to where instrumentation of the overall end-to-end architecture can come together. And so they're really now starting to look at the network as a far more important component than perhaps they did four or five years ago where it might have just been, four bars of Wi-Fi or connectivity from branch to headquarters. When I think about enterprise architectures, I definitely go to workloads and they go, okay, how is work that's being done in the enterprise changing? And you obviously have a lot of general purpose ERP and financials and CRM and HCM, et cetera. You've got this emerging set of workloads that's data intensive, whether it's AI or whatever you call it. Some people call it matrix workloads, all the kind of new interesting data intensive workloads. And then there's a ton of work being done that's just don't even supporting applications directly. It's making storage run better or networks run better. And so it's kind of wasted cycles, if you will. So I talked to a lot of people who are kind of rethinking that architecture to your point based upon the type of work that's being done. And obviously things like inferencing at the edge that we talked about a little bit earlier are going to drive that in the enterprise. And that's really going to put new requirements on the architectures, is it not? Absolutely. In fact, this is core to the HPE edge to cloud strategy and architecture. Ultimately, every organization is going to be different. They're going to have different use cases, different business requirements. But we are going to find over the next 10 years that a significant amount of the data that is born at the edge and the experiences that are delivered at the edge need a local presence of compute and communications to enable what needs to take place locally from an operations perspective. Let me give you a concrete example. I've mentioned healthcare a couple of times. Imagine a healthcare environment of a large healthcare network organization and they need to consume patient telemetry information from all of their patient bedside monitoring systems at the point of patient care. Well, what if the point of patient care is in a hospital tower? What if the point of patient care is in the patient's home? That's a completely different set of circumstances physically and logically from an enterprise architecture perspective. And so it's particularly important to think through how data will be born at the edge, consumed locally, processed locally and then forwarded to hybrid cloud computing environments for continued processing after the fact. So you might need to react immediately to some patient telemetry that's collected locally but then also collect that information, process it in a metadata, store it somewhere else, maybe have it diverge into multiple streams. And in all of this, the computing architecture at the edge, the hybrid cloud architecture, the network architecture from edge to cloud all matters because this involves security and involves availability involves performance. It involves how the data itself is used, the experience of the end users that are responsible for the delivery of the experience itself. So the ultimate enterprise architecture here is going to evolve yet again. And just as we've seen over 30 years, the centralization, the decentralization, the centralization, the distribution of various functions, we're just seeing that again because we continue to reinvent how we operate with better and better architectural models. Right, and pendulum's definitely swinging. When I think about the compute at the local level, I think it's got to be super high performance and dirt cheap and low power. And I want to ask you a question about something you said earlier about your strategy is really to look for those horizontal opportunities. So am I right to infer, you're not going after the deep edge with specialized capabilities or are you? I think Tesla, right? I mean, designing their own chips for their cars. You're not going there, I presume, but you also reference, hey, there's going to be some data that's coming back. That's kind of your role, but maybe you could help clarify that for me. Yeah, so interesting we are in a way going after those special edge cases, but that's through the creation of an architecture that is malleable enough where you can define an enterprise network architecture, an enterprise network experience that will address the horizontal, easy to understand use cases like mobile devices that need WiFi connectivity or mobile devices that need Bluetooth connectivity or ZigBee or what have you. But also we have found that through, again, through consumerization of IoT systems that IoT specific technologies for very specific edge use cases are still embedding common access technologies, common networking technologies, common security protocols, common orchestration capabilities for compute as some examples. And so what we are building is the ability for an enterprise architect or an enterprise network architect to define a single network architecture physically that can co-mingle lots of different, perhaps parallel network architectures into a single common platform and then operate it, even though that it might consume multiple many parallel types of systems, ultimately operated as one single entity. Honestly, that's the power of the Aruba architecture is even though we have to physically deploy access points and switches and SD-WAN gateways to create whatever the enterprise network architecture looks like, it's all driven by software and it's all driven by common interfaces that at some point get down to, okay, I can actually connect that kind of strange device because it has enough commonality so that I can plug in this USB adapter into this access point. And all of a sudden I've got this connectivity for this very specialized thing, transporting a specialized protocol across an IP network. So it's really the blend of looking for horizontal opportunities so that we attack the market effectively, but also make sure we don't leave anybody behind in the process just because they've got a specialized need. Yeah, thank you for that clarification. So Aruba is going to participate in the entire value chain that we've sort of laid out here and visualized. What do you think's going on? Maybe we could talk about the vendor landscape, the pretenders from the contenders. What are the keys in your view to the product solutions, the right clarity of vision, maybe some things that haven't been invented yet? How do you think about that? Yeah, so a lot of lessons learned over the past 10 years, I would say. There've been a number of very prominent enterprise technology companies, facilities tech, vertical oriented solutions for healthcare for industrial settings, and they've all at one point or another tried to build a platform strategy. They have decided to self-annoint or anoint themselves with we're going to be the platform for some particular horizontal function inside the enterprise that involves IoT, because we want to be the centerpiece where all this data from all these IoT systems concerning this particular environment flows through and we want to help democratize data access. Unfortunately, most of them still took a very vendor specific point of view about it, even by layering standards on top of what they've built, even forming industry consortiums. They haven't necessarily achieved critical mass of what we would all like to see, which is full democratization of IoT solution architectures and IoT data access. And I think we're going to see that over the next 10 years. It's going to take a while, but I think to your question of what are some interesting products or technologies to be developed? I think industries working together, vendors working together, like Microsoft, like Google, like Amazon, like Aruba, HPE, like InOcean, which is an industry consortium. These places where we come together and decide to achieve the greater good, to achieve greater benefits for our enterprise customers and build a platform capabilities using standards, using open source, using consumerized tech, using really critical functions in orchestration, configuration management, API architectures, standard object models for how information is communicated. I think that we will be able to democratize IoT data access. I think we'll be able to democratize how IoT systems are deployed and dramatically expand the market opportunity for the benefit of everybody. We've certainly seen those types of collaborations before. I'm not sure it's ever been this large. Yeah, maybe the internet was this large, but that was more government driven than it was vendor driven, which is what you're laying out. Give us the bumper sticker for why HPE and Aruba. Well, HPE is in a really interesting position. We really are enabling the entire edge-to-cloud architecture, as we've mentioned a few times, and the ability to lay out the foundation of the infrastructure for communications, for compute, for storage, regardless of how an enterprise organization wants to consume it, whether it's all at the edge or all in private data centers or in hybrid architecture, whether they wanna control the entire architecture top to bottom, whether they want us to help them deploy and manage the architecture on their behalf with our industry partners. Ultimately, we are giving them a set of building blocks end-to-end that will coexist with whatever they've already built, help them build a malleable architecture going forward in the future, and really help them achieve economy of scale. David, very interesting discussion. Thank you so much for your perspectives. Really appreciate you coming on theCUBE. Thank you so much, Dave. I really appreciate the time and I'm really excited to be a part of Discover. Awesome, and thank you for watching this segment of HPE Discover 2021. You're watching theCUBE. This is Dave Vellante. Keep it right there.