 Welcome back, everyone, to theCUBE's live coverage of SuperCloud 5, the Battle for AI Supremacy. I'm your host, Rebecca Knight. We've got two great guests for this segment. We are welcoming Hasib Moudani. He is the CEO of RefA Systems. Back to theCUBE. He's like, he's a CUBE alum. Welcome back to theCUBE, Hasib. Thanks for having me. Good to see you again. And Michael Quail. He is the AABG Global Container Lead at Accenture. Thanks so much for coming on theCUBE, Michael. Hey, thanks for having me. Appreciate being here. So I want to start with you, Hasib. I know you were just here on theCUBE talking to our analyst, John Furrier. But tell our viewers a little bit about RefA Systems. Familiarize us with your company. Happy to do it. So we are essentially the cloud automation business. We help enterprises as they move to the cloud, make it easy for their developers and their data scientists to consume computer. Fundamentally, that's the job. Today, that job revolves around a few technologies, Kubernetes being one of them, which is why John and I spoke at CUBE last week. And of course, yeah, the generative AI thing that we're going to talk about today. And essentially what we build is a platform that makes it easy for platform teams in enterprises to deliver these new capabilities to internal users, developers, data scientists, in a controlled fashion. So developers get the autonomy to do what they want. But then platform, IT, gets the control and the efficiencies is that everybody keeps moving fast with all the governance that they want in place. You told John Furrier that it is repeatedly flexible automation. I like that concept. I should remember that. Did I say that? Awesome. Michael, tell us a little bit about your role at Accenture as a global container lead. Sure, I'd be happy to. So I've been with Accenture for close to five years. I work in the exclusive AWS field. I work with some of the smartest people in Accenture. We are kind of what was considered the elite. We work closely with AWS in developing offers and products and go-to-market solutions with AWS for a vast number of the large Fortune 100 enterprise customers in the Accenture portfolio. My role as a global container lead is to help define strategy. And a big focus of that is around day two operations where Rafay fits into the enterprise and can help our organizations, no matter where they are in their Kubernetes journey, do more with less resources. And that's the approach that I've kind of fine-tuned over the last year as I've worked with Rafay. We've done a lot of thought leadership. We've done a lot of connecting with clients and our go-to-market teams to help bring this solution out into the wild and out to the enterprise ecosystem. And when you step back and look at it, you know, Docker's been around since about 2013. But it's now 2023 and enterprises are just now starting to see that the benefits of container to help them lower costs and move quickly and give them a developer-friendly experience with Kubernetes. So Rafay really fits the needs very well. And that's why we have this wonderful relationship we're building together. So both of you in your roles at your different organizations are really all about helping enterprises do things, do more of what they need to do. But there is this gap between companies doing projects here and there, one-offs, teams getting special dispensation to try stuff out, and then introducing things at scale. Haseeb, can you talk a little bit about this challenge and what you hear from customers about how this plays out? I'll share a relevant example. We are very strong partners with AWS, as is Michael here, part of AAPG at Accenture, which is focused on AWS. We've been working closely with AWS to make it easy for enterprises to consume a platform called Petro, which is essentially a platform to try out different types of business models. So what happens to enterprises is somebody gets excited and they try some technology, because it's new, they want to explore it, and it's great. It's a good thing to do. But then eventually the second thing comes in, the third thing comes in, the fourth thing comes. And the CIO organization, they have a charter to control the consumption of these things. Particularly in this economy, people want to be careful about costs. They want to be careful about exposure to data, et cetera. There's a lot of reasons why IT wants to be involved in these functions. So as one example, as it relates to Bedrock, what we did was we built a template so that any of our customers, IT is our fundamental customer, can deliver in a self-sufficient fashion the consumption of Bedrock to their developers and data scientists. Now, how that happens, that's a platform problem, IT problem. But the point is developers get to do what they want, but IT gets to deliver. And we find that to be our job. So look, we sell a really cool product. It does a lot of things. But to what end? The end is the gap or the chasm that you described. How do we bridge that chasm so that the things that developers want to try, they continue to try, but with essentially let's call it transparent oversight by IT. And if you can sort of meld it together, don't slow them down. The developers let them go as fast as they want. But at the same time, have all the requisite controls, all the governance list, but it doesn't get in their way. That's the nirvana that every IT team wants, right? And that's what we've sort of enabled with our product. And particularly when we sort of take our product and apply that, you know, to the sort of the Accenture machinery, we're able to solve really big problems for really large companies. Michael, are IT teams pretty much the same in the sense of, are they all dealing with the same problems? Doesn't matter if it's healthcare or financial services or manufacturing. Is there sort of a plug and play element here? What would you say? I'd say there is a common play element. IT teams typically aren't all the same, but they do have the same set of problems they try to address, which is the governance and the oversight, which is also to getting where they need to be to manage these environments effectively. You would step back and look at it, how long it takes to set up the controls, the tooling, the automation, the governance, the only different aspects that teams need in their environments. It takes them a long time to get there. There's a lot of decisions that need to be made on what tools they need to run, what patterns and procedures they need to follow. When we look at what Rafay offers, this accelerates that process drastically. There's just a lot of good that comes out of Rafay. Our teams want to be able to do more with less resources, so they look to automation, they look to things that handle the audit capabilities, the compliance capabilities that can standardize these environments and ensure that things are deployed in a manner that is consistent with their patterns and their architectural board-approved methods of deploying workloads. Michael, walk me through how this partnership works. How do you and Rafay team up to deliver these solutions to companies? That's a wonderful question. We look at a list of clients where we have established relationships, whether that's Accenture, whether that's Rafay. We come to them with a power of three kind of methodology where we partner with AWS, we partner with Rafay, we partner with Accenture's vast experience and deep expertise in many different fields of technologies. We look at this as an opportunity, we look at this as a way to solve problems for our clients. We have this thing where Accenture likes to become the trusted advisor to our clients so they come to us when they need something. That's how we sell more work, that's how we get more revenue, that's how we are able to invest in these partnerships and bring and deliver excellence for our clients. Okay, so we are still such early days. AI, of course, has been around for a good long time, but the pretty early days in having AI being adopted by the masses, can you talk a little, Haseeb, about what you're seeing, how you view the landscape right now in terms of all the small startups that are trying to make sure that they have a stake in some land here. And of course, there are big players. How are you viewing what's going on right now in terms of the AI landscape? Yeah, so there's a bunch of fun called middle ventures. They published a state-of-the-art generated AI report a few days ago and actually fascinating information. They've done a really good job and I was actually reading this this morning so it had the following kind of data points. The total cloud spend 23 was $400 billion, $400 billion, off which the AI spend was about $70 billion, off which Gen AI spend was $2.5 billion, a lot less, right? And that's actually not surprising because it's early days, right? Of course, right? And I would view that it's going to grow and grow because more and more people are heading up GPUs which is really cloud spend and on from there. Look, it's common in our industry that a new technology comes about and of course we all get excited, right? And some people who are so close to that industry, they sort of do the force for the trees and we all forget that it takes time for enterprises to do these things. And you know what the classic example of that is Kubernetes, right? Many of us have been going to KubeCon for years, right? Michael, how long have we been involved in going to KubeCon, right? It feels like 10 years. But it's now... It feels like forever. It feels like forever, right? But now it's actually a thing. In fact, last week when I was talking to John on the same show, we were talking about how finally Kubernetes is becoming essentially boring, right? It's a standard now, right? Everybody's got it. But it took that many years. So the question is how long does it take for Gen AI to get there? Will it be faster? Probably because it delivers so much impact and people will go faster. But what I know and what Michael knows is that if enterprises don't do this right, we will hit that sort of... What's the phrase Gartner uses? The kind of go from the high point all the way to the low point in their sort of progression of technologies. I think that's going to come very fast, right? It is a great technology. And with the right tooling, it can be applied well, right? And that's the opportunity we're seeing selfishly for Rafi that we can help our customers templatize some of this new technology so that they can consume it much easier inside the enterprise with the right control and governance. And this is what us in Accenture are spending a lot of time thinking about together. How do we build these well thought-through templates so that if a developer wants to try Lama 2 on OCI, okay, fine, or Bedrock on AWS, or Gen AI with Azure, whatever the stable diffusion on Open AI. Any of these technologies that are relevant in this new screen-generated space, we want to help them get there faster, but with the right control like this. Because if the controls are not in place, that the solution will come. Because of AWS. If those controls and standardization is not in place and we've seen this in the enterprise, it becomes a wild west where teams are doing things one way and other teams doing things a different way. There's no mesh, there's no cohesiveness. And then the CTO is going, what's going on over here? Why is this going on over here? Why do we have this huge disconnect? And where is our standardization? Where's our governance? And where's the audit trail? Like especially in financial services, this is a huge thing to be able to hand to your regulators and your compliance auditors to make sure things are being done correctly. And Rafay just hits it out of the home. It's a home run with us right out of the park. Absolutely. Yeah, so Michael, I mean there's so many different startups moving in this direction. So many companies trying to work out their AI strategies. Can you let us in on some of the conversations you're having in the room where it happens at Accenture in terms of how you're helping companies figure out what that seemed called, you need to get this right. You need to have the right approach here. You do, right. And that's where we formulate the planning, the strategy that initial discussion takes shape and we, first we have to assess their needs. Where are they going? Why do they need this technology? And how's it going to fit into your organization and how can it be consumed properly by the, you know, the customers of the organization, the developers? There's a lot to consider there. Letting in on what Accenture is doing, that's a kind of a challenging situation because we keep everything very tightly to the chest and we don't share what we're doing with our clients with a lot of people. That's, you know, our confidentiality agreement kind of prohibits that. Fair enough. But yeah, yeah, for sure. So, I see Michael obviously is such a fan of Rafay's systems. One of the things we talk about so much on theCUBE is innovation and this need to really stay ahead of the curve. How in your company are you making sure that you are ahead of competitors here and sort of maintaining that competitive edge and staying to use the buzzword innovative? So, we have a continuous learning environment. That's one of the things that's stressed to us. You don't just do your job. You contribute back to the company by learning more, by contributing thought leadership, by providing insight into what the recommended and best products on the market are and that's where Rafay fits in. That's why I'm very much leaning in heavily on this relationship. The future of us managing Kubernetes clusters for our customer is now. We see a lot of this where they're asking us to build teams around supporting these Kubernetes environments because Enterprise just doesn't have the resources to do this effectively. When clients come to you wanting to know where they should start, how do you start to help them formulate their approach and how are you helping to make sure that they have the right strategy and that that strategy has integrity and has the controls that are necessary and while they of course want to be innovative, they still need to have the boundaries of what Rafay and Accenture can do for them. Yeah, we've learned a lot from our friends at Accenture about how they do business, right? So in fact, the most interesting innovation we've done in terms of our field process, technology is one thing, right? We've done some fun things, but in terms of how we could engage is this idea of service delivery, right? So that's something definitely we've learned from our team. Like, how do you, like, you know, as quickly as possible really understand what is the customer actually trying to do, right? So I guess as an example, people call us and say, hey, we saw this one feature on your ref side. We want to talk about it. Okay, that's very nice. What are you trying to solve for? What is the real goal here, right? How will you make your internal team successful and pushing ourselves and the customer to think about that as quickly as possible is something that certainly is not common practice for product companies. It just isn't because we all get excited about our technologies, but this is the beauty of the relationship where we've learned a lot from our friends. And now we're trying to sort of even tailor our sales to that end. And for the most part, our expectation is we'd be doing a bunch of these sales in any case through our partners, right? It's kind of worked out very naturally. But now that, you know, we're doing it this way, really, we're talking about, you know, it's customer first. It's about understanding their goals and their aspirations and then helping them understand where Rafa fits very essentially. And then everybody else. Michael, we're nearing the end of 2023, which is pretty, pretty, pretty unfathomable. How are you looking ahead to next year? I mean, the economy is starting to look a little iffy or maybe it's actually been looking iffy for years, depending on which forecast you're looking at. Technology is in a lot of flux right now. What are you expecting for 2024 and what are you thinking is going to be sort of the dominant conversations that we'll be having on the Cube as it relates to generative AI? Shaving costs. Absolutely. Our enterprise customers are not looking to spend those $100 million, $200 million transformation deals. They're looking to shave costs internally to accelerate their developers' abilities by using automation as much as possible or generative AI where it makes sense. They are definitely, you know, pulling back at those big spending numbers. We're seeing smaller projects. We're seeing numerous projects around helping us with AI and figuring out where it fits into our business. There's going to be a big push, I think, in 2024 for optimizing those technologies that support these things like AI and Kubernetes and the things that Refe is doing. It's going to be an exciting year. I think we're out of the woods for the economic downturn. We're seeing a little bit more activity in the segment where people are actively hiring again. There's some recruiting activities. I'm very much plugged into that scene being married to a recruiter, so I see that kind of command to play a little bit, and that's good news. It's still questionable that we're hoping for the best, but we have to deal with the cars that we've been dealt. Well, let's see. He brings up a really good point about the... We know that there is an enduring labor shortage just based on the numbers. There's also a skills gap when it comes to these new technologies, and it seems as though with automation you can, in fact... And also at a time when companies are trying to shave costs, your technologies do present a really promising opportunity for companies to sort of kill many birds with one stone. You know, it's foundationally responsible for making the human situation better, and the one way it does that is by taking people away from something that are incredibly repetitive and unnecessary, and this applies to the industrial revolution. It applies to factories burning out furniture, I guess, and there's no difference. At the end of the day, resolving an age-old problem, which is, hey, a bunch of people are solving this problem. Can we do it faster if you want? That's entirely a business, and the interesting thing in our business is every customer you talk to, they just don't have enough people to solve the problem that they need to be solved. So it's an easier conversation because, okay, you have this backlog of things that need to be done. You don't have enough people, and even with unlimited capital, you can't find them because they don't exist. There is a skills gap. How are you going to get there? Well, let's address that gap with technology, with automation, right? And that's the pitch. What we do is a secondary issue, right? And look, all these things kind of tie together very nicely because if you first start with, customer, what is the big problem you're going to solve for, right, what is the goal? How would you get there? Well, wow, to get there, you need to hire another 30 people. Well, that's not going to happen. Fortunately, we bring technology that will address that gap and your existing talent can now fill these gaps, right? So enabling existing talent to be able to now do way more than to do today is the value, right? Because look, of course, we end up quote-unquote spending money that they don't have to hire more people and our product perhaps doesn't cost as much as 20, 30 people. But the real value at that point is time, right? I get to get there faster, right? I get to deliver on the promise that I made to my developers, but at a lower cost, right? This is what people want, right? Just if you want to reduce cost, doing with the project, by the way, that's a great way to reduce cost, right? But of course, we have a goal in mind, right? We have to solve a problem. I'm going to solve it. I'm going to solve it in a shorter time frame, and I'm going to do it at a lower price point. That's collectively what we are selling through automation. And by the way, those people that existing talent are going to have more interesting, fulfilling, meaningful jobs because they're not being burned out by those repetitive and boring tasks. Indeed, indeed. Yep. Excellent. Well, Asif and Michael, this has been a really fascinating conversation. Thank you both so much for coming on theCUBE. Our pleasure. If you're having us, please hit it. Thanks for having us. I'm Rebecca Knight. Stay tuned for more of theCUBE's coverage of SuperCloud 5. You are watching theCUBE, your leader in enterprise technology coverage.