 Hello, welcome to this CUBE conversation. I'm John Furrier here in the Palo Alto studios for the CUBE. We had a great conversation around cloud cost optimization, FIN Ops, really important topic in the future of cloud management. We're here featuring N Ops with the founder and CEO, JT Geary, thanks for coming on today. CEO, thanks for coming on. Hey John, thanks for having me, good to see you again. So future cloud management is the topic. You guys were on the showcase before Saddam is on startup showcase. The category just exploded, FIN Ops is huge. Everyone's talking about FIN Ops, not FinTech, FIN Ops. That's cloud costs, everyone's right size and the cloud computing is going next gen. You're seeing the future of AI expanding, more apps are coming, it's not like it's going away, but people are tuning their clouds. You guys are catching the tailwind of this trend. Let's start by giving the audience an overview of what you guys do and your capabilities in managing infrastructure at scale. Yeah, absolutely. So N Ops is a FIN Ops platform. We focus on automation. John, I'm pretty sure you hear that often. One of the hardest thing to do in FIN Ops is like, how do you make it easy so engineers take action? So our focus is on automation. We have a unique pricing model. The platform is completely free like showbacks, chargeback, you know, all that functionality that is just included part of the platform and customers only pay if we save them money. So we just take a percentage of the savings. So that's the model that's like resonating really well because it allows us to, you know, focus on outcomes, focus on optimizing the cost for our customers. One of the things you mentioned, this is like the, you know, this is the thing that's top of people's mind right now. And the reason is because, you know, because the state of the economy, right? In last two, three years, it actually maybe it didn't matter, you know, if the spend was going up because stock was also going up, the revenue was also going up. Now all of a sudden there's this microeconomic, you know, which is really the impacting people to take a step back and see, you know, how can they optimize their cloud spend? Yeah, and I think the so-called recession that people are seeing in the technical market is get to profitability or be more profitable. And I think that is turning in a knob. So at least the queue we've been reporting in, as you know, cloud growth is kind of slowed down, but it's still growing, right? You got the next gen cloud with AI out, with AI coming around the corner, you're seeing people investing more in this kind of the next gen cloud, but they're reigning in their current cloud. I call it, it's like leaving the lights on. You don't want to leave your lights on in your house before you go to bed. You want to turn everything off or optimize it so that it's all policy-based. This is the focus. And this is what we're talking about. This is where the action is, because they're squeezing more profit out of their operations because the cloud's elastic. That's the best part about it. That was the whole idea, right? One of the things actually we do is, you know, we look at all the dev environments and lab environments and we show developers pattern, right? You know, you only need this for Monday to Friday or you need it for only a few days a week. And we, you know, provide this one-click experience so they actually could pause these resources. And in some cases, they're able to save, in many cases, they're able to save a lot of money. And again, John, this is where, this is what cloud was originally intended for, right? But all of a sudden, you know, people that maybe get comfortable, you know, developers have other priorities, right? They have focus to release new features, more revenue generating, you know, work and then optimizing costs, right? So this is where like someone like Anops could come in and help to optimize the cost. But you're right, you know, the whole idea of cloud was you scale up and down based on the need. And somehow, you know, there's not a lot of people who practice that. And when you show the data to the developers and when you provide like a one-click experience, we do see people actually take action and they actually end up taking, saving a lot of money on their dev environments, on the elaborate environments, for example. You know, I read a survey, I can't remember who was the author or what the actual numbers were, but it was pretty high percentage of developers were leaving services on that were not being used or idle, so there's a lot of idle capacity, and or services that are being left on. Now, the nuance point here I want to get your thoughts on is that AWS in particular and all the hyperscalers, they're adding more services all the time. So it's easier to get, I won't say lost in the catalog of services, but like when you're slinging code as a developer, you can sometimes leave services on, if you get to turn them off, write some policy. So this is where the efficiency comes. This is where I think FinOps and like the DevSecOps environments are really seeing that day two operational thing. What are some of the areas that you guys work with? How do you go in and explain the value proposition? What's the pitch to the developers? How easy to get into it? And what's the low hanging fruit savings? And then where's the real action? Yeah, absolutely. So first of all, I think there's this lot of sort of pressure on engineers to reduce cloud cost in general, but John, you have to realize that engineers were never trained to optimize cloud spend, right? They were trained to solve like business problem or liability performance, right? This is like a new sort of problem that we're trying to solve and put more responsibility on them, right? Again, I think once you provide them tooling, where cost optimization is just as easy as provisioning resources, we do see engineers taking action. So how we're able to kind of have great impact is two ways. Number one, what we do is we make sure that customers are paying less for what they have provisioned. So when they provision resources, we are automatically like making the right commitments and if as they downscale or upscale we're actually adjusting their commitments. And that John could be a full-time job, right? Again, engineers are good at building stuff. Maybe they're not good at understanding AWS pricing plans. So our idea is to free them up so they don't have to manage these commitments on day-to-day basis. The second thing is after you're paying less, can you use less, right? Are there resources that you don't need? And this is where we provide automation to find resources. Again, the future of cloud management is AI and automation, right? So far the cloud management has been like, here's a recommendation, take action, no one does it, right? If we keep doing things like that, I don't think we're going anywhere. So the whole idea of ANOPS is we actually take actions because honestly, this is how we get paid. We only take percentage of the savings. So our motto is pay less. And then we constantly provide recommendations where customers could easily take action and they consume less, they use less and that's how they're able to optimize their overall cloud spend. Okay, so don't bury the lead story there. You just kind of smung by that little statement of you don't get paid until you get, they get savings. Is that true? Is there a retainer at all or is there any up front? Or is it all on the back end with the customer? You're aligning with their savings. Is that, take a minute to explain that key piece there. It's all based on the impact. So we take percentage of the savings. If we're optimizing your commitments, then we take savings compared to the on demand. And if we're pausing your resources, we're taking percentage of the amount of money we save. And if we run your workloads on spot, we obviously take a percentage of the savings compared to on demand. It's a powerful model, John. And we have a lot of happy customers. Again, what it really does, it drives focus on our end on one thing. One thing is like, how can we optimize costs for our customers? And I do believe that is the future of cloud management. I do believe this is how we can bring some automation and deliver a bigger impact in cost optimization on cloud. Yeah, I just read a survey and we've actually pulled some of our CUBE alumni database on this question. How many times has a DevOps engineer been called into the office of executive costs? And 60% have been pulled in. Okay, so that's one. The other thing that you've brought up is interesting about the DevOps developer is that if the security shift left, that trend is about guardrails and security. Here, it's the same thing. The developers want to have the operationally covered. So it's the same concept that's shifting leftist for security you're doing for operations and cloud management, right? And that's kind of the same concept, right? That's right. So we have to provide an experience to developers. So we get closer to how they work, right? So how do developers work? Most of their time is spent writing code, reviewing pull requests. So at DevOps, we do send pull requests and with cost optimization opportunities. So it's very, very easy for developers to kind of accept those recommendations. If we don't do that, yeah, it is hard to kind of meet where developers are actually, spending most of their time. So we will see a lot of that happening over next, hopefully five years. There will be a lot more tooling and that's where we focus on. How can we make it easy for developers to just take action with one click? As I've said, at least in KubeCon in many years on theCUBE, developers are going to drive the standards and drive the change. You see it happening in real time. They adopted a tool or a platform. It drives in the standard amount of what the feature is. If it drives it, drives it. I can see the advantage you guys have. Developers adopting, there's no risk, almost no risk. But at some point you have to sit down with the organization and say, here's how we're going to benchmark how we get paid. I'm sure they probably have some glaring problems. Could you give some examples of how you guys help do this with organizations and tie that to Amazon's best practices and benefits that they have? How do you, how does that all work? Take us through how the sausage is made. Yeah, many of our customers were actually saving them like 20 to 30% of their cloud spend. One of the things that we realized, John, once you free developers up, as you mentioned, there's 60% of the time they're getting called in to optimize the costs. And normally what happens if CTO is like, let's reduce costs, you bring in a developer, developers spend some time Googling and in addition to whatever else they're doing, right? That's how, this is like one more thing they have to work on now, right? What we noticed when people are leveraging Ennobs, we're able to reduce like in many cases up to 50% of their cloud costs and depending on how optimized they were before we got in. And all of a sudden, they don't have to think about this at all. This is totally on autopilot. We're constantly reaching out on resources that could be paused. We are maximizing their all right coverage. We're finding resources that could be run on spot and make it easy for them to move those workloads on spot. And all of a sudden this is on autopilot, you know? And now they can focus their energy on building, you know, stuff and, you know, focus on revenue generating activities pretty much. I'm sure this is a fun model. You optimize someone to a nice equilibrium. It's like, okay, you can't squeeze any more profit out of that, but it's still growing their cloud over here. You can just point the software over there. So great stuff. My final question for you is really more about, you know, this is a great solution. It's in line with what people are doing. It's certainly relevant and very cool right now to be turn those knobs to drive more profit, more cash flow and also take your developers off the mundane tasks and have them coding. Critical. I mean, this is like top of the top of the mind. How do organizations who are starting their FinOps journey, so to speak? What guidance can you provide? How do they get started with NOps? What benefits? How do they see out of the gate? Take us through that onboarding or prospect watching, thinking, hey, you know what? This is exactly my board conversation, my executive meetings, my team meetings are talking about this. Let's jump in and do some NOps. What's the story? Yeah. The first step is, you know, if you sign up for a free platform, we can look at your cloud data and kind of show you how we can save you money. By the way, John, we process like close to billion dollars in cloud spend. So this is all we do every day. So we're really good at figuring out ways to optimize, you know, cloud spend for customers. Step one, where I see a lot of success, once they see the data in NOps, we build a lot of functionality around like, how do you build showbacks? How do you distribute costs around, you know, across multiple teams and business units? We leverage machine learning for that. And, you know, most of the time, what I see like customers don't even have that kind of understanding. So once they do this like showbacks and cost allocation, then they develop this baseline. And then on top of that, we show, you know, what are the areas where we can, you know, optimize the spend for the customers. And normally it's one click where we can say, you know, just click here and we can literally save you, you know, $5,000 in month of May and maybe $20,000 next month, right? It literally requires our engineering effort. And we do this every week, you know, we're constantly sending like new recommendations and customers just have to do like one click to implement those. In many cases, you know, once you set policies, we take actions automatically. So it's really as simple as that. And just feel like there's nothing to lose here. You know, just- Hey, JT, you're making people's lives easier, more productive and you're giving them cash. Right to the bottom line. Yeah, exactly. They got nothing to lose. Sign up, you know, I'm pretty sure we can save you some money. I definitely, definitely love your business model. I mean, Phenom, I've always been a big fan and Phenos more than ever is going to be continually be tuning in. Final question for you, well, we got you here. Obviously, AI is a big part of the conversation. In that same survey, 55% are using AI today, just starting to put in place, you know, baby steps to get using AI with guardrails in ops. You're focused right now with AI. What's your view? Yeah, that's what we do, what we do, right? We're like, rather than managing commitments on spreadsheets, we have a model that automatically learns, you know, how we can maximize the commitments for customers. We find resources, patterns, depending on that. The model adopts to your workloads. And then we make those recommendations. Then obviously we use AWS event bridge to take action. But yeah, there's, we cannot do what we are doing without AI and machine learning, John. It's like, you know, I was just tapping to one of our developers, like we process like $20 trillion AWS billing rows at like every hour. So there's no one like, you know, there's no like a single person sitting there and making these decisions, you know? I mean, that's, there's no way to do that, right? I'd be smiling if I was you too. What a great business model. And again, you got that data. And again, the data is a treasure trove too. That's going to give you more insights and signaling. Yes, yeah. And singular focus, right? Like how do we use this data to optimize customer spend? Because if we're able to do that, then we get paid. So we're like, we're focused on that. This is an example of the future of the clouds, a super application, great in line with developers. This is the future JT. Thank you for coming on this CUBE conversation. Looking forward to hosting you on the AWS startup showcase coming up and looking forward to second return for you. Thanks for coming on. Thanks, appreciate it. Okay. I'm John Furrier here. The Palo Alto students with CUBE conversation. Talk about the future of cloud spend. This is where AI is going scale and the data are key. And this is what, what tuning up the internet is all about and cloud. I'm your host, John Furrier. Thanks for watching.