>> Announcer: Live from San Juan, Puerto Rico, it's theCUBE, covering Blockchain Unbound. Brought to you by Blockchain Industries. (upbeat music) >> Hello everyone, welcome back to theCUBE's exclusive coverage in Puerto Rico where we are broadcasting the Blockchain Unbound event. This is a global conference where people from around the world are coming together. From Silicone Valley, from New York, Miami, all around the world. Coming to talk about Blockchain, the disruptive nature of crypto currency and the decentralized applications and how it's changing the world, creating a lot of value. My next guest is Albert Santalo, the founder and CEO of Eight Base, the number Eight Base. Albert, thanks for joining me. >> Thank you, John, it's good to be here. >> So before we get into it, we'll talk on camera a little bit about what you guys are doing. I want you to take a minute to explain what Eight Base is, why, what you guys are doing? What are you disrupting and what's the value proposition? >> So Eight Base is software to build software. So if you've ever, if you're familiar with Wicks or SquareSpace for websites, we essentially do the same thing for this big category called enterprise software. And if you've every been around enterprise software project, it's no fun. It's really expensive, takes a lot of time and it's froth with danger. We make that easy and we empower a group of people called citizen developers. Basically, regular business people to build their own software without having to hire developers. >> You know, cloud computing has done a lot of great things. One of them is this notion of making coding easier. But Blockchain is now a whole new growth phase onto of cloud computing and internet of things, where you have new languages, new key for Ethereum to whatever, yet there's a demand for talent. There's now creative thinking involved. As people rethink business models, re-imagine either sovereignty or a business process, the creativity's in the people, the business model. Not necessarily the technologies, although they're involved. So there's been a challenge for how do you make it easy? So you guys are trying to do that, what's the secret sauce? Is it a tech-play, is it a business-play, cloud-play? How do you guys look at that? >> You're striking at the essence of what we do. So if you think about Blockchain, a lot of work that's been done so far has been sort of protocol level stuff and the applications that most of us see on top of it are things that don't quite look like they're finished products, right. And it has to do with the fact that it's core engineers that are really trying to bring this all to the surface. So what we are is the next layer of infrastructure on top of that protocol level. And we excel at a beautiful user interface that makes it simple for normal people to build these systems quickly and inexpensively without having to have an IQ of 140 plus which is the people that do Blockchain. >> We've seen this similar movie before and I want to get your entrepreneurial background in a separate segment but this is something that's actually happening in cloud computing and in data-science, you've seen the citizen analyst. Cause data-science you have to code python and there's like only a certain population that can do that, but what happened was people were building abstraction layers to make it really easy to wrangle data, use data-science, visualizations, whether it's tableau or whatever, that really changed the nature of what data-science became. And now the benefits in the data-analytics space is multi-fold. You're seeing examples of that. Talk about some use cases that you guys are doing and be specific with some examples of how you see it playing out. How much do they need? Is it a dashboard, how would you envision the product? What's it going to look like? >> This has an enormous democratizing effect, right. So what you're talking about is that data-science was hard to access, expensive to access, only a few people in the world really could do it and then these layers of abstractions have facilitated a much wider group of people being able to do it. So that's exactly what we're doing. We're at the same time bringing the development of software closer to where the requirements live because literally, the people finding the requirements can develop their own software. So what you're going to see is a rollout of Blockchain and non-Blockchain software just accelerated and put into the hands of more people which strikes at the heart of digital transformation. We've all heard about this theme digital transformation. It's businesses that if they don't evolve and adopt Blockchain, AI, all these other things, they have a threat of being put of business. That's where the big opportunity for Eight Base is. >> Digital transformation certainly is going to reshape things, so the idea of having a Blockchain-enabled app, you're going to make it easier for someone to do that. What use cases do you envision being the low-hanging fruit, as you guys go to the market? What are some of the use cases? Because developers still can contribute to your model. Explain how the role of true developer? I get the part of easy to program, because that's natural, leggo-blocked, making it easy. How does it grow? How does it evolve? >> So the citizen developer is what we've talked about until now. There's something called the Eight Based server-less chaise which is the heart of the system. In that part of our world, developers or core engineers can work to extend the platform. And in the process of that, they can earn tokens and basically create a business model for themselves. Either one-time payment or a recurring payment. So Eight Base will evolve very, very, rapidly. Not only through Eight Bases' development work and our development team, but through the world at large contributing new capabilities. Think of a Blockchain, a new Blockchain that comes out, that's innovative, all they have to do is create an extension to the Eight Base platform and now that's accessible to all the Eight Base users in the world, right. >> So let me get this right, see if I can unpack this, see if I can un-connect the dots. You're essentially creating software to make people that want to write software really easy. So they essentially invoke some thing and it automatically writes the software for them, so they don't have to. And then you have a development eco-system that can add more to that, much like a marketplace. Is that kind of getting it right? >> Yes, so, when you talk about writing the system, it's a yes and no. >> Okay. >> So one thing we're not, is a code generator. So the software is created but runs inside of our environment because we think the environment is also more than half of the value that we add. We have a fully fault-tolerant, scalable cloud-base environment so that the same people who want to develop don't have to worry about IT. So that's really, really important. >> You've nailed the operational piece. >> That's right and it's fully self-service, so there's no human intervention. So people can try Eight Base before they buy it without having to talk to salespeople, without having to drop a credit card and without having to have implementation people involved. >> That sounds like a great cloud solution to me. And certainly, cloud has proven that a set of services, you know, push-button, kind of capability, Amazon's been very successful, Amazon's Web Service, with their marketplace. Why even provision code, just click on and use it. >> And by the way, in talking about Amazon, what we're doing, in my opinion, wasn't even possible 15 years ago. Even though many of our competitors which date back to those days tried. Things like Amazon Web Services, the Google Cloud, many of the open-source things including Blockchain are what facilitates what we do because we don't have to write it all. We can leverage these incredible underlying technologies and curate them in way that makes it accessible to people. >> So you're tailwind for your business is the open-source software market, you're differentiations, you're running all the operations for them so they don't have to and so you have an extensive, and you're also providing the value of having a Blockchain-enabled capability for someone who's not trained. >> Yes and a visual interface that normal people can understand in terms of building software. A no-code, what we called a no-code. >> Define, normal. >> Well, you know, most of the population. >> Yeah, who want Blockchain, who wants the benefits of it, you guys abstract that away, great. So ICO, you guys doing a fundraising? You guys doing an ICO? What's the plans? >> We have plans for a token sale but I can't talk about it just yet. >> Okay, I respect that, okay cool. So that sounds like it's rocking and rolling. Let's talk about you. So were just joking off camera, big Hurricane's fan from Miami. They're going to get their mojo back. >> Looks that way. >> I love the chain, the turnover chain, fantastic. Love to see the action, energy there. But you also have a lot of success in the industry. Also, you have some scar tissue as us guys, growing up in that era where you have to provision your own stuff. Go to venture capital, get the funding. It was a slog, I mean, on many levels. Some got easier overtime, certainly agile programming helped a lot, but now with cloud and now with this new marketplace where you have almost a global footprint capability. How do you talk to people and say, hey you know, I've been there. I've walked to school with no shoes, back in the day and now it's so much better. How do you talk about this wave? I mean, because it's a bigger wave than anything we've seen before, certainly, a lot of things coming together at once. >> So I love this topic. I've stood up a couple of venture-back technology companies, probably the one I'm best known for is Care Cloud which is backed by Silicone Valley VCs and, you know, I've raised a fare amount of angel investments and venture capital and I appreciate the model, right. It's got its pros and cons and when you talk about scar tissue, you know, all our entreprenuers have scar tissue, whether they were funded or not. I also had a very unique experience because I was at the signing of the Jobs Act. I was standing behind the president at the White House and at the time I was beginning to sort of imagine what could become of that and I did a PBS interview sort of like this. It was actually a debate, talking about it back then. And I never would have imagined, we were talking about things like crowd-funding and stuff like that but never in a million years could I have envisioned what Blockchain could have brought to all this and what ICOs would have looked like and what crowd-funding at a global environment. Up until that time we thought of most of entrepreneurship as a U.S. phenomenon. Now it's a very much global phenomenon. So I'm very excited about what's coming. I think it creates an incredible opportunity for entrepreneurs all over the world to sort of emerge and do what they do. Whether they know VCs personally or not, which is sort of part of the problem. As long as this industry doesn't get too crazy, we can sort of keep that under control and let it grow. >> My personal opinion, having a venture-back company in the past, my current business-looking angle, theCUBE is self-funded, no outside capital. It's interesting because there's three types of funding elements going on in this ICO bubble. The startup and then the other end of the spectrum is that, oh shit, we're going out of business, throw the hail Mary, okay. Pivot, that's what they call it now. We use to call it, shit, we're going out of business! Now it's called, accu-hire and pivoting. And then in the middle is really where the action is. Growth companies that actually have a business model and need growth capital at a scale and technology infrastructure has token economics built in. That's where I see most of the smart money going. On the startup side there's an argument for VCs because that's a good, a lot of my friends are VCs and they've been on theCUBE. They need nurturing, they need advice, they need to have the network effect, and they need to have that service provider. But some can go right to the value faster. So you see the startup category kind of bifurcate into, you know, I really want the VCs and to some, I just want to get to first base, get this thing done and I'll re-evaluate. And there's the holy-grail which is token economics already built in, growth companies. Okay, so that being said, from your perspective, when you look at the Jobs Act, you mentioned that, so I also find that there's new levels of startups coming on, not just the technological entrepreneurs. In Washington D.C. I've covered in great detail with Teresa Carlson, who's the head of Amazon's Web Services global public sector, this tsunami of societal entrepreneurship where NGOs because of the Jobs Act can now invest in mission-driven startups. So what's happening is a level of entrepreneurs coming in, solving stuff that would never get funded by a VC. Talking about a women's abuse app or missing, exploited children or solving world hunger, these used to be philanthropy missions that when there's no more funding, everything's dead. Now there's entrepreneurship going on, there are people doing stuff they know they want to do but need to code. This is kind of where you're targeting. Kind of a data-point to validate what you're doing, right? >> First of all, I love the fact that that's happening. Things that are good for a society obviously is good for everybody. But I would also say that beyond that, you know, people are sort of, if you're lucky enough in life to find out what you're really passionate about, sometimes that always doesn't align itself with profits. So we're giving them an opportunity for people to live a more fulling life by following their dreams and doing good by society, right. But at the end of the day, we have to be able to fund these things and we have to be able to support them. And things like the Jobs Act and crowd-funding and stuff have really given life to this stuff. >> Well the thing about NGOs in these new areas is that they don't have a lot of tech expertise. They have a lot of years of experience in the channels and their relationships and their mission but now there's like, oh damn I got to build something. So who do you turn to? This is kind of where the model of simplicity is really kind of key. >> Eight Base is designed for exactly that. So when we think about where's Eight Base used? First and foremost we think small to mid-sized businesses that are looking to digitally transform, okay. Then we think of large companies where departmentally people don't necessarily want to go to their IT department. They do what's called shadow-IT. They build their own stuff. Eight Base is a much more, it's a much better, much more compliant way to do that, and businesses to be able to cycle faster. But the last thing is entrepreneurs. So imagine, today we have all these platforms to make entrepreneurship easier. Well imagine if you could literally build your product very, very easily without having to hire developers? Think about how we're spawning companies left and right. So part of what we like to do is really be a catalyst for that type of economy overtime. >> Shadow-IT, I've said on theCUBE many times, has been legitimized with the cloud. It used to be kind of a, you know, quiet little secret. You go around, put the credit card down, spin up some servers, get a little prototype and then show the boss and they'll double down on that. Similar kind of concept going on in this world. Get something going, show some momentum. >> And get some money. >> You guys take care of that for everybody. Okay, so what's going on in Puerto Rico? Let's shift gears. We're here in Puerto Rico, what's your observation, what's the vibe? Obviously, they're trying to bid themselves out like they want to be a haven for entrepreneurship, bring the local culture together. What are you hearing here in the hallways here? What are you talking about? What's some of the observations? >> First of all I'm a big fan of Puerto Rico. I live in Miami so I've been to Puerto Rico many, many times and the place has been hard hit by the hurricane. I love the fact that the government was able to reform the tax situation five years ago and I think it's exactly that type of thing that will bring, sort of, that will spawn the type of innovation that we need here. All communities need to evolve, in my opinion, to technology communities. You've seen it obviously Silicone Valley is the exaggerated example but you've seen it in places like Detroit, New York, Austin, and even Miami is very important. A big, big part of the message I carry. When you live on a island, it's sort of has an even different dynamic, but there's no reason why that can't emerge here in Puerto Rico. I'm hopeful that these incentives, et cetera, will attract that kind of-- >> It's a short flight to the mainland. It's entrepreneurial center. >> It's the United States. >> It's the United States. With digital, there's no boundaries with digital cultural. Opportunity for them. >> That's right. >> Albert, thanks for spending the time. What's next for you, what are you going to do? Obviously, you've got your business you're building, can't talk about your token sale. >> Well we haven't literally launched the company yet but we're anticipating that next week or the following we're actually going to make our announcement and then they'll be lots of announcements after that. >> Come on, give us a little bit more, you're teasing us here. >> By the way, today is our birthday so we were incorporated in ides of March 2017. >> Let's hope that's good luck. (Albert laughs) Albert Santalo, founder and CEO of Eight Base, look for him. We'll be watching the news, trying to get some scoop here but he's not giving in. Good job, well done, seasoned pro. >> Thank you, John. >> We'll be back with more live coverage here in Puerto Rico for theCUBE's coverage of Blockchain Unbound. Thanks for watching, we'll be right back. (lively music)

>> Hi, I'm Peter Burris and welcome to another Wikibon Action Item. (upbeat digital music) >> Cameraman: Three, two, one. >> Hi. Once again, we're broadcasting from our beautiful Palo Alto studios, theCUBE studios, and this week we've got another great group. David Floyer in the studio with me along with George Gilbert. And on the phone we've got Jim Kobielus and Ralph Finos. Hey, guys. >> Hi there. >> So we're going to talk about something that's going to become a big issue. It's only now starting to emerge. And that is, what will be the roadmap to automation? Automation is going to be absolutely crucial for the success of IT in the future and the success of any digital business. At its core, many people have presumed that automation was about reducing labor. So introducing software and other technologies, we would effectively be able to substitute for administrative, operator, and related labor. And while that is absolutely a feature of what we're talking about, the bigger issue is ultimately is that we cannot conceive of more complex workloads that are capable of providing better customer experience, superior operations, all the other things a digital business ultimately wants to achieve. If we don't have a capability for simplifying how those underlying resources get put together, configured, or organized, orchestrated, and ultimately sustained delivery of. So the other part of automation is to allow for much more work that can be performed on the same resources much faster. It's a basis for how we think about plasticity and the ability to reconfigure resources very quickly. Now, the challenge is this industry, the IT industry has always used standards as a weapon. We use standards as a basis of creating eco systems or scale, or mass for even something as, like mainframes. Where there weren't hundreds of millions of potential users. But IBM was successful at using that as a basis for driving their costs down and approving a superior product. That's clearly what Microsoft and Intel did many years ago, was achieve that kind of scale through the driving more, and more, and more, ultimately, volume of the technology, and they won. But along the way though, each time, each generation has featured a significant amount of competition at how those interfaces came together and how they worked. And this is going to be the mother of all standard-oriented competition. How does one automation framework and another automation framework fit together? One being able to create value in a way that serves another automation framework, but ultimately as a, for many companies, a way of creating more scale onto their platform. More volume onto that platform. So this notion of how automation is going to evolve is going to be crucially important. David Floyer, are APIs going to be enough to solve this problem? >> No. That's a short answer to that. This is a very complex problem, and I think it's worthwhile spending a minute just on what are the component parts that need to be brought together. We're going to have a multi-cloud environment. Multiple private clouds, multiple public clouds, and they've got to work together in some way. And the automation is about, and you've got the Edge as well. So you've got a huge amount of data all across all of these different areas. And automation and orchestration across that, are as you said, not just about efficiency, they're about making it work. Making it able to be, to work and to be available. So all of the issues of availability, of security, of compliance, all of these difficult issues are a subject to getting this whole environment to be able to work together through a set of APIs, yes, but a lot lot more than that. And in particular, when you think about it, to me, volume of data is critical. Is who has access to that data. >> Peter: Now, why is that? >> Because if you're dealing with AI and you're dealing with any form of automation like this, the more data you have, the better your models are. And if you can increase that amount of data, as Google show every day, you will maintain that handle on all that control over that area. >> So you said something really important, because the implied assumption, and obviously, it's a major feature of what's going on, is that we've been talking about doing more automation for a long time. But what's different this time is the availability of AI and machine learning, for example, >> Right. as a basis for recognizing patterns, taking remedial action or taking predictive action to avoid the need for remedial action. And it's the availability of that data that's going to improve the quality of those models. >> Yes. Now, George, you've done a lot of work around this a whole notion of ML for ITOM. What are the kind of different approaches? If there's two ways that we're looking at it right now, what are the two ways? >> So there are two ends of the extreme. One is I want to see end to end what's going on across my private cloud or clouds. As well as if I have different applications in different public clouds. But that's very difficult. You get end-to-end visibility but you have to relax a lot of assumptions about what's where. >> And that's called the-- >> Breadth first. So the pro is end-to-end visibility. Con is you don't know how all the pieces fit together quite as well, so you get less fidelity in terms of diagnosing root causes. >> So you're trying to optimize at a macro level while recognizing that you can't optimize at a micro level. >> Right. Now the other approach, the other end of the spectrum, is depth first. Where you constrain the set of workloads and services that you're building and that you know about, and how they fit together. And then the models, based on the data you collect there, can become so rich that you have very very high fidelity root cause determination which allows you to do very precise recommendations or even automated remediation. What we haven't figured out hot to do yet is marry the depth first with the breadth first. So that you have multiple focus depth first. That's very tricky. >> Now, if you think about how the industry has evolved, we wrote some stuff about what we call, what I call the iron triangle. Which is basically a very tight relationship between specialists in technology. So the people who were responsible for a particular asset, be it storage, or the system, or the network. The vendors, who provided a lot of the knowledge about how that worked, and therefore made that specialist more or less successful and competent. And then the automation technology that that vendor ultimately provided. Now, that was not automation technology that was associated with AI or anything along those lines. It was kind of out of the box, buy our tool, and this is how you're going to automate various workflows or scripts, or whatever else it might be. And every effort to try to break that has been met with screaming because, well, you're now breaking my automation routines. So the depth-first approach, even without ML, has been the way that we've done it historically. But, David, you're talking about something different. It's the availability of the data that starts to change that. >> Yeah. >> So are we going to start seeing new compacts put in place between users and vendors and OEMs and a lot of these other folks? And it sounds like it's going to be about access to the data. >> Absolutely. So you're going to start. let's start at the bottom. You've got people who have a particular component, whatever that component is. It might be storage. It might be networking. Whatever that component is. They have products in that area which will be collecting data. And they will need for their particular area to provide a degree of automation. A degree of capability. And they need to do two things. They need to do that optimization and also provide data to other people. So they have to have an OEM agreement not just for the equipment that they provide, but for the data that they're going to give and the data they're going to give back. The automatization of the data, for example, going up and the availability of data to help themselves. >> So contracts effectively mean that you're going to have to negotiate value capture on the data side as well as the revenue side. >> Absolutely. >> The ability to do contracting historically has been around individual products. And so we're pretty good at that. So we can say, you will buy this product. I'm delivering you the value. And then the utility of that product is up to you. When we start going to service contracts, we get a little bit different kind of an arrangement. Now, it's an ongoing continuous delivery. But for the most part, a lot of those service contracts have been predicated to known in advance classes of functions, like Salesforce, for example. Or the SASS business where you're able to write a contract that says over time you will have access to this service. When we start talking about some of this automation though, now we're talking about ongoing, but highly bespoke, and potentially highly divergent, over a relatively short period of time, that you have a hard time writing contracts that will prescribe the range of behaviors and the promise about how those behaviors are actually going to perform. I don't think we're there yet. What do you guys think? >> Well, >> No, no way. I mean, >> Especially when you think about realtime. (laughing) >> Yeah. It has to be realtime to get to the end point of automating the actual reply than the actual action that you take. That's where you have to get to. You can't, It won't be sufficient in realtime. I think it's a very interesting area, this contracts area. If you think about solutions for it, I would be going straight towards blockchain type architectures and dynamic blockchain contracts that would have to be put in place. >> Peter: But they're not realtime. >> The contracts aren't realtime. The contracts will never be realtime, but the >> Accessed? access to the data and the understanding of what data is required. Those will be realtime. >> Well, we'll see. I mean, the theorem's what? Every 12 seconds? >> Well. That's >> Everything gets updated? >> That's To me, that's good enough. >> Okay. >> That's realtime enough. It's not going to solve the problem of somebody >> Peter: It's not going to solve the problem at the edge. >> At the very edge, but it's certainly sufficient to solve the problem of contracts. >> Okay. >> But, and I would add to that and say, in addition to having all this data available. Let's go back like 10, 20 years and look at Cisco. A lot of their differentiation and what entrenched them was sort of universal familiarity with their admin interfaces and they might not expose APIs in a way that would make it common across their competitors. But if you had data from them and a constrained number of other providers for around which you would build let's say, these modern big data applications. It's if you constrain the problem, you can get to the depth first. >> Yeah, but Cisco is a great example of it's an archetype for what I said earlier, that notion of an iron triangle. You had Cisco admins >> Yeah. that were certified to run Cisco gear and therefore had a strong incentive to ensure that more Cisco gear was purchased utilizing a Cisco command line interface that did incorporate a fair amount of automation for that Cisco gear and it was almost impossible for a lot of companies to penetrate that tight arrangement between the Cisco admin that was certified, the Cisco gear, and the COI. >> And the exact same thing happened with Oracle. The Oracle admin skillset was pervasive within large >> Peter: Happened with everybody. >> Yes, absolutely >> But, >> Peter: The only reason it didn't happen in the IBM mainframe, David, was because of a >> It did happen, yeah, >> Well, but it did happen, but governments stepped in and said, this violates antitrust. And IBM was forced by law, by court decree, to open up those interfaces. >> Yes. That's true. >> But are we going to see the same type of thing >> I think it's very interesting to see the shape of this market. When we look a little bit ahead. People like Amazon are going to have IAS, they're going to be running applications. They are going to go for the depth way of doing things across, or what which way around is it? >> Peter: The breadth. They're going to be end to end. >> But they will go depth in individual-- >> Components. Or show of, but they will put together their own type of things for their services. >> Right. >> Equally, other players like Dell, for example, have a lot of different products. A lot of different components in a lot of different areas. They have to go piece by piece and put together a consortium of suppliers to them. Storage suppliers, chip suppliers, and put together that outside and it's going to have to be a different type of solution that they put together. HP will have the same issue there. And as of people like CA, for example, who we'll see an opportunity for them to be come in again with great products and overlooking the whole of all of this data coming in. >> Peter: Oh, sure. Absolutely. >> So there's a lot of players who could be in this area. Microsoft, I missed out, of course they will have the two ends that they can combine together. >> Well, they may have an advantage that nobody else has-- >> Exactly. Yeah. because they're strong in both places. But I have Jim Kobielus. Let me check, are you there now? Do we got Jim back? >> Can you hear me? >> Peter: I can barely hear you, Jim. Could we bring Jim's volume up a little bit? So, Jim, I asked the question earlier, about we have the tooling for AI. We know how to get data. How to build models and how to apply the models in a broad brush way. And we're certainly starting to see that happen within the IT operations management world. The ITOM world, but we don't yet know how we're going to write these contracts that are capable of better anticipating, putting in place a regime that really describes how the, what are the limits of data sharing? What are the limits of derivative use? Et cetera. I argued, and here in the studio we generally agreed, that's we still haven't figured that out and that this is going to be one of the places where the tension between, at least in the B2B world, data availability and derivative use and where you capture value and where those profitables go, is going to be significant. But I want to get your take. Has the AI community >> Yeah. started figuring out how we're going to contractually handle obligations around data, data use, data sharing, data derivative use. >> The short answer is, no they have not. The longer answer is, that can you hear me, first of all? >> Peter: Barely. >> Okay. Should I keep talking? >> Yeah. Go ahead. >> Okay. The short answer is, no that the AI community has not addressed those, those IP protection issues. But there is a growing push in the AI community to leverage blockchain for such requirements in terms of block chains to store smart contracts where related to downstream utilization of data and derivative models. But that's extraordinarily early on in its development in terms of insight in the AI community and in the blockchain community as well. In other words, in fact, in one of the posts that I'm working on right now, is looking at a company called 8base that's actually using blockchain to store all of those assets, those artifacts for the development and lifecycle along with the smart contracts to drive those downstream uses. So what I'm saying is that there's lots of smart people like yourselves are thinking about these problems, but there's no consensus, definitely, in the AI community for how to manage all those rights downstream. >> All right. So very quickly, Ralph Finos, if you're there. I want to get your perspective >> Yeah. on what this means from markets, market leadership. What do you think? How's this going to impact who are the leaders, who's likely to continue to grow and gain even more strength? What're your thoughts on this? >> Yeah. I think, my perspective on this thing in the near term is to focus on simplification. And to focus on depth, because you can get return, you can get payback for that kind of work and it simplifies the overall picture so when you're going broad, you've got less of a problem to deal with. To link all these things together. So I'm going to go with the Shaker kind of perspective on the world is to make things simple. And to focus there. And I think the complexity of what we're talking about for breadth is too difficult to handle at this point in time. I don't see it happening any time in the near future. >> Although there are some companies, like Splunk, for example, that are doing a decent job of presenting a more of a breadth approach, but they're not going deep into the various elements. So, George, really quick. Let's talk to you. >> I beg to disagree on that one. >> Peter: Oh! >> They're actually, they built a platform, originally that was breadth first. They built all these, essentially, forwarders which could understand the formats of the output of all sorts of different devices and services. But then they started building what they called curated experiences which is the equivalent of what we call depth first. They're doing it for IT service management. They're doing it for what's called user behavior. Analytics, which is it's a way of tracking bad actors or bad devices on a network. And they're going to be pumping out more of those. What's not clear yet, is how they're going to integrate those so that IT service management understands security and vice versa. >> And I think that's one of the key things, George, is that ultimately, the real question will be or not the real question, but when we think about the roadmap, it's probably that security is going to be early on one of the things that gets addressed here. And again, it's not just security from a perimeter standpoint. Some people are calling it a software-based perimeter. Our perspective is the data's going to go everywhere and ultimately how do you sustain a zero trust world where you know your data is going to be out in the clear so what are you going to do about it? All right. So look. Let's wrap this one up. Jim Kobielus, let's give you the first Action Item. Jim, Action Item. >> Action Item. Wow. Action Item Automation is just to follow the stack of assets that drive automation and figure out your overall sharing architecture for sharing out these assets. I think the core asset will remain orchestration models. I don't think predictive models in AI are a huge piece of the overall automation pie in terms of the logic. So just focus on building out and protecting and sharing and reusing your orchestration models. Those are critically important. In any domain. End to end or in specific automation domains. >> Peter: David Floyer, Action Item. >> So my Action Item is to acknowledge that the world of building your own automation yourself around a whole lot of piece parts that you put together are over. You won't have access to a sufficient data. So enterprises must take a broad view of getting data, of getting components that have data be giving them data. Make contracts with people to give them data, masking or whatever it is and become part of a broader scheme that will allow them to meet the automation requirements of the 21st century. >> Ralph Finos, Action Item. >> Yeah. Again, I would reiterate the importance of keeping it simple. Taking care of the depth questions and moving forward from there. The complexity is enormous, and-- >> Peter: George Gilbert, Action Item. >> I say, start with what customers always start with with a new technology, which is a constrained environment like a pilot and there's two areas that are potentially high return. One is big data, where it's been a multi vendor or multi-vendor component mix, and a mess. And so you take that and you constrain that and make that a depth-first approach in the cloud where there is data to manage that. And the second one is security, where we have now a more and more trained applications just for that. I say, don't start with a platform. Start with those solutions and then start adding more solutions around that. >> All right. Great. So here's our overall Action Item. The question of automation or roadmap to automation is crucial for multiple reasons. But one of the most important ones is it's inconceivable to us to envision how a business can institute even more complex applications if we don't have a way of improving the degree of automation on the underlying infrastructure. How this is going to play out, we're not exactly sure. But we do think that there are a few principals that are going to be important that users have to focus on. Number one is data. Be very clear that there is value in your data, both to you as well as to your suppliers and as you think about writing contracts, don't write contracts that are focused on a product now. Focus on even that product as a service over time where you are sharing data back and forth in addition to getting some return out of whatever assets you've put in place. And make sure that the negotiations specifically acknowledge the value of that data to your suppliers as well. Number two, that there is certainly going to be a scale here. There's certainly going to be a volume question here. And as we think about where a lot of the new approaches to doing these or this notion of automation, is going to come out of the cloud vendors. Once again, the cloud vendors are articulating what the overall model is going to look like. What that cloud experience is going to look like. And it's going to be a challenge to other suppliers who are providing an on-premises true private cloud and Edge orientation where the data must live sometimes it is not something that they just want to do because they want to do it. Because that data requires it to be able to reflect that cloud operating model. And expect, ultimately, that your suppliers also are going to have to have very clear contractual relationships with the cloud players and each other for how that data gets shared. Ultimately, however, we think it's crucially important that any CIO recognized that the existing environment that they have right now is not converged. The existing environment today remains operators, suppliers of technology, and suppliers of automation capabilities and breaking that up is going to be crucial. Not only to achieving automation objectives, but to achieve a converged infrastructure, hyper converged infrastructure, multi-cloud arrangements, including private cloud, true private cloud, and the cloud itself. And this is going to be a management challenge, goes way beyond just products and technology, to actually incorporating how you think about your shopping, organized, how you institutionalize the work that the business requires, and therefore what you identify as a tasks that will be first to be automated. Our expectation, security's going to be early on. Why? Because your CEO and your board of directors are going to demand it. So think about how automation can be improved and enhanced through a security lens, but do so in a way that ensures that over time you can bring new capabilities on with a depth-first approach at least, to the breadth that you need within your shop and within your business, your digital business, to achieve the success and the results that you want. Okay. Once again, I want to thank David Floyer and George Gilbert here in the studio with us. On the phone, Ralph Finos and Jim Kobielus. Couldn't get Neil Raiden in today, sorry Neil. And I am Peter Burris, and this has been an Action Item. Talk to you again soon. (upbeat digital music)