 Live, from Las Vegas, it's theCUBE! Covering AWS re-invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. Welcome back to theCUBE. We are in Las Vegas, Lisa Martin with John Walls. I'm very excited that we're kind of color coordinated. Well, we didn't compare notes to begin with, but certainly the pink thing, it's working today. I feel like you complete me. Yeah, oh, thank you. I really do. I don't hear that very often. My wife even says that. Can you tell that we're at the end of day one of theCUBE's coverage of AWS re-invent? Good day, though. Yes, it has been. We're very excited. We have a couple of guests joining us for our final segment on this. Please welcome, we have Bill Gerard, CTO of Digital Transformation and Scale Solutions at Intel. Bill, welcome to our show. Thank you very much, happy to be here. And one of our friends, it's no stranger to theCUBE, one of our former hosts, Bobby Allen, the CTO of Cloud General. Hey, Bobby. Thank you, thank you for having us. So guys, here we are. This, there has not been a lull in the background noise all day at re-invent day one. But Bobby, I want to start with you. Talk to our audience about Cloud General. Who are you guys? What do you do? And what's different about what you're delivering? So one of the first things that's different about Cloud General is where we're located. So we're in Charlotte, which I call Silicon South. So we're kind of representing the East Coast. And we're a company that focuses on helping with workload placement and transformation. So where you don't know whether something should go on-prem, off-prem. If you put it in Amazon, what services should it consume? Licensing models, pricing models. We help you make data-driven decisions, right? So you're not just going based on opinion. You're going based on facts. And that's challenging because, you know, in the, as John Furrier would say, you know, Cloud 1.0, which was compute network storage. It was the easy, I shouldn't say easy, but the lift and shift applications that enterprises do. All right, these workloads should go to the cloud. Now we have, you know, what's left over and that's challenging for organizations. Some of the legacy ones can't move. How do you help from a consultative standpoint that customers evaluate the workloads? What data are they running? What the value that data has? And if they are able to move some of those more challenging applications. So part of the framework for us, Lisa, is we want to make sure we understand what people are willing and able to change. Right, because sometimes it's not just about lower costs. Sometimes it's about agility, flexibility, deploying to different regions. So what we often start with is what does better look like to you? What does success look like for your organization? And so then based on that, we analyze the applications with an objective data-driven framework and then make sure the apps land where they're supposed to go. We're not selling any skewer product. We're selling advice to give you insight about what you should do. You know, but Bobby, I think, and maybe Bill too, you could chime in here on this. If you give people a choice, what does this look like? What do you want to, I don't want to do anything. I want to stay put, right? But that obviously, that's not an option. But I'm sure you do get pushed back quite a bit from these, you know, almost a legacy mindset. And we've talked a lot about this whole transformation versus transition. Some people don't want to go, period. So how do you cajole them, persuade them, bring them along on this journey because it's going to be a long trip. Yeah, I think it's a good- And you've got to pack a lunch. It's a good point. I think what we've seen, most of them have, you know, data experience. As I said, they tried an element, didn't get the results that they expected. This is where, you know, the partnership that we have with Cloud Genre, really, you know, that data-driven, intelligent-based planning is super important, right? We want to really fundamentally help organizations move the right workloads, make sure they've got the right results, and not have to redo it, right? And so, part of that, you know, is to move when you're either at past scars or, you know, not used to what you're doing, given the data and the information to be able to do that intelligently and make that as fast as they can, and, you know, at the right, you know, experience and performance, you know, from a capability perspective. So, so many businesses these days, if they're not, let's put it legacy, if they're not looking in the rear-view mirror, what does the slide mirror say, objects are closer than they appear? Even for Amazon, right? For all of these companies, there are smaller organizations that might be born in the cloud, compared to the legacies who aren't, and if they're not looking at we have to transform from the top down, and digitally, truly transform, their business may not be here in a year or two. So, the choice, and I think they need to pack a lunch and a hip flask for this, because it's quite the journey, but I'm curious, with the opportunity that cloud provides, when you have these consultative conversations, what are, this can be so transformative, not just to a business, but to an entire industry? Bill, talk to us from your perspective about some of the things that you've seen, and how this next generation of cloud with AI and machine learning, for example, can really transfer, like, what's the next industry that you think is primed to be really flipped upside down? Well, I mean, the good news is, I think most of the industries and the segments that we talk to have realized they need some level of transformation. So, doing the business as usual, really isn't an option to really grow and drive in the future, but I do think the next evolution really does center on what's happening in AI and analytics, whether it's, you know, moving manufacturing from, you know, video-based defect detection, you know, supply chain integrity, you know, what's happening from a retail was really the first in that evolution, but we see it in healthcare, in federal data center modernization, and it's really moving at a faster pace and adopting those cloud technologies wherever they need it, both in their data center, in the public cloud, out at the edge, and we'll start to see a real shift from, you know, really consolidation into large hyper-converged data centers to, you know, distributed computing wherever they can get, and that's where we're excited about the work we're doing with Amazon, the work we're doing with, you know, ISV partners to be at the capability where they need it, but I think it will be really the next evolution of services everywhere. So, but we talk us through an example or a use case of a customer that you're working with at Cloud Genera, with Intel and AWS. What does that trifecta look like for, say, a retailer or a financial services organization? Yeah, so that looks like this. So Lisa, when we talk about workload placement, we think that most companies look at that as a single question, it's at least a five-fold question. Right, there's the venue, there's the service, there's the configuration, the licensing model, and the pricing model. You need to look at all five of those things. So even if you've decided on AWS as your strategic partner, we're not done yet. So we have a very large financial services customer that I can't name publicly, but we've collaborated with them to analyze tens of thousands of workloads, some that go best off-prem, some that go best on-prem, and they need guidance and coaching on things like, are you paying for Red Hat twice? You're paying for licensing on-prem, are you also paying for that in the cloud? There are things that maybe should be running in RDS, database as a service. Here's your opportunity to cut down on labor and shift some of the relationships to have to, re-indexing databases is not glamorous or a differentiated value for your business. Let's take advantage of what AWS does well and make this better for your company. One of the things that I want to kind of introduce to piggyback on your question, we lean on people process technology as kind of the three-legged horse in enterprise. I want to change that. People process product or people process problem. We're falling in love with the tech and getting lazy. The technology should be almost ubiquitous or under the covers to make a product better or to solve a problem for the customer. Well, maybe on that, I mean, automation can certainly come in and make a big play here because we're taking all these new tasks. If you can automate them, then you free up your people, your developers to do their thing, right? Yeah. So you raise an interesting point on that about being lazy and relying on things, but yet you do want to off-put or off-load some of these tasks. Do you not to free up that creativity and free up the people to do what they're supposed to be doing? That's a delicate balance, though, isn't it? It is. It is. This is where I think the data-driven informed decision is important. We did a lot of research with Cloud Genre and our customers, and there's really four key technical characteristics when evaluating workload. The first one, of course, is the size of the data. Where is the data created? Where is it used? Where is it consumed? The second one is the performance, right? Either performance not only to other systems around it or the end user, but the performance of the infrastructure. What do you need out of the capability? The level of integration with other systems. And then, of course, security. We hear that time and again, right? Regulatory needs. What are we having from top-secret data to company-sensitive data? And really getting that type of information to drive those workload placement decision becomes at the forefront of that. And then getting, you know, using Cloud Genre to help understand the number of interfaces in and out, the size of the data, the performance utilization of the systems really helps customers understand how to move the right workload, what's involved, and then how to put that in the right AWS instance and use the right AWS capabilities. You know, and you both have hit on something here because the complexity of this decision, because it's multi-dimensionally, you talked about the five points a little bit ago, now you've talked about four other factors. So this is not a static environment. No, it's not. And to me, that, as you're making a decision, that point is what's very difficult for, I would assume, for the people that you're interfacing with on the company level, because it's a moving target for them, right? They just, you know, it's dynamic, it's changing, your data flows exponentially increasing, capabilities are changing. So how do you keep them from just breaking down? I want to jump in on that, because again, I'm going to repeat this again. My thesis is often technology's the easy part. We need to have conversations about what we want to do. And so I had a conversation earlier today, think of Amazon like a chef. They can make anything I want, but I need to decide what I want to eat. If I'm a vegan and he wants steak, that's not Amazon's fault, if they can't cook something that's a mismatch of a bad conversation. We need to communicate. So what I'm finding is, a lot of executives are worried about this. They're worried that you're going to give me the right, the wrong answer to the right question. The reality is, you may have the wrong question first of all, right? The question is usually further upstream. So the worry that you're going to give me the wrong answer to the right question, but often you need to worry that you're getting, you're starting with the wrong question and you're going to get the right answer. Ask the right question first and then you got a chance to get to the final destination better. Wow. And then in this multi-cloud world, that many organizations live in, mostly not by strategy. It could be by M&A, it could be by developer preference for different solutions. A lot of CEOs are telling us, we've inherited a lot of this multi-cloud mess. And technical debt, exactly. So doesn't that just compound the problem? Because to your point, I mean, you think of what are the, we hear so many different stats about the number of clouds that an average enterprise is using is like five to nine. That whole world, that's a reality for organizations. So in terms of how the business can be transformed by what you guys are doing together, it seems like there's a tremendous opportunity there. But to your point, Bobby, where do you start? How do you help them understand what that right first question is at the executive level? So that there's four technical points that Bill talked about. The executive staff is all on board with yes. This is the question we're asking. Then we'll understand if the technology is right to solve it. It's got to start with really what the company's business imperative is. It can't start with an IT objective. It's, are we moving into new markets? Do we need to deploy capabilities faster? Are we doing a digital customer experience transformation? Are we deploying new factories, new products into new regions? And so really the first area is what's the core company strategy and imperatives of the business objective? And then how does IT really help them achieve that? In some cases it may be we have to shift and reduce our data center footprints. We have to move capabilities to where we have a new region deployments. We've got to get them over to Europe. We don't have capabilities in Europe. We're going to Asia. I've got a mobile sales force now where I need to get that customer, meet the customer where they're doing in the retail store. And that really then leads quite simply to what are the capabilities that we have in-house that we're using? How are they being utilized and who's using them? And then how do we get them to where they need to be? Some cases it's a cost imperative. Some cases an agility, time to market. And in others, and we're seeing this more often, is really what are the new sets of technologies, AI services, training, inferencing that we're not experienced to do and set up and we don't want to spend the time to go train our infrastructure teams on the technology. So we'll put our data scientists in there figuring out the right set of workloads, the right set of technology that we can then transform and move our applications to utilize. And so it really starts, I think, with the business conversation or what's the key inflection point that they're experiencing. And have you both seen that change in the last few years that now it's where, you know, cloud, not cloud, what goes on cloud was an IT conversation to your point, Bill, and then the CAO got involved with me a little bit later. But now we're seeing and hearing the CEO has got to be involved from a business imperative perspective. Yeah, share some data, right? So a couple of years ago, everybody was pursuing cloud largely for cost, agility started to become primary, and that's still very important. A lot of the internal enterprise data modernizations were essentially stalled a bit because they were trying to figure how much do we move to the public cloud, right? We want to take advantage of those modern services. At that time, we did a lot of research with our partners. Roughly, you know, 56% of enterprise workloads were in their own data center. You know, the rest of them were public cloud. And then we saw really the work, the intelligent workload discussion that says we've had some false starts. Organizations now really consistently realize they need both, you know, their own infrastructure and public cloud. And we've actually seen an increase of infrastructure modernization while they're moving more and more stuff to the cloud, they're actually growing their on-center. It's now roughly 59% on-prem today for that same business. And that's largely because they're using more cloud services, but they're also even using more on-premise. And they're realizing it's a balance and not stalling one or starving one and then committing to the other. They're committing to both and really just growing the business where it needs to go. There's strategic reasons though, right? Yes. Well, there should be for strategic reasons. There aren't always, back to your question, about which question to ask. One of the questions I often ask is what do you think the benefits will be if you go to cloud? And part of what happens is it's not a cloud capability problem, it's an expectation problem. You're not going to put your ERP system in the cloud and drop 30% cost in a month. And so that's where we need to have a conversation on, you know, let's iterate on what this is actually going to look like, let's evolve the organization, let's change our thinking. And then the other part of this, and this is where Cloud Generation and Intel come in, let's model what simulation looks like. So we're going to take those legacy workloads and let's model containers, let's model microservices. So before you have to invest in transformation, that may not make sense, let's see what the outcomes look like through simulation, through AI, through ML, and understand where does it make sense to apply the resources, you know, to double click on that solution that will help the business. I was going to finish my last question, Bobby, with you saying why cloud genera, but I think you just answered that. So last question for you though, from an expectation perspective, give me one of your favorite examples of customer, whatever kind of industry they're in that you've come in and helped them really level set their expectations and kick that door wide open. That's tough. Too many to choose from? Yeah. That's a good one to have. Let me try to tackle that one quickly. Storage, compute, databases, those are all things that people look at. I think what people are struggling with the most in terms of kind of expectations is what they're willing and able to change. And so this is kind of what I'll leave on. Bill and I talked about this earlier today. A product is good, a plan is better, a partnership is best. Because what the enterprises are saying is we're overwhelmed, either fix it for me or get in there with me and do it, right? Being this together. And so what we've learned is it's not about workloads applications, it's all kind of the same. We need help, we're overwhelmed. I want to partner in telling cloud genera to get in this thing with me, help me figure this out because I told Stu this, cloud is the best of teenagers that just learn how to drive. It's very capable but it needs some guard rails. I love that. Thanks you guys so much for explaining to John and me what you guys are doing together and how you're really flipping the model for what customers need to be evaluated and what they need to be asking. We appreciate your time. Thank you for having us. Our pleasure. Thank you. For John Walls, I'm Lisa Martin. You've been watching theCUBE at ReInvent 19 from Vegas. We'll see you tomorrow.