 Hey, everyone. Welcome to the Q's presentation of the AWS Startup Showcase, Analytics and Cost Optimization. This is season three, episode two of our ongoing series that covers very exciting startups from the AWS ecosystem. I'm your host, Lisa Martin. Today, excited to be joined by one of our CUBE alum, Aran Khanna, the CEO and co-founder of Archera. And Steve Baer joins as well, Senior Site Reliability Engineer at Archera's customer Chemit Trading. Guys, great to have you here. Thank you so much for joining me on the program. Thank you. Thank you so much for having us. We're going to be talking about Archera Free Automated Cloud Management. We're also going to be talking about Chemit's Trading's use case. So Aran, you and your co-founder brother, Nikhil, you guys were on the CUBE just a month or so ago talking with our co-founder, John Furrier. Great story. As you guys talked about with John, there's a lot of ways to save on the cloud. There's a lot of vendors that are saying to customers, hey, we can get you cloud savings. But Archera is different. I know that you have a different model. Talk to me about that. Yeah, absolutely. So to go back a little bit to really the founding story of Archera, one of our key experiences from our team is actually a lot of us former Amazonians. I, myself, was actually part of the launch of the SageMaker program at AWS, which includes the SageMaker platform and a lot of the managed inference APIs around things like recognition and Lex and Pauley. And one of the big issues that we saw in customers adopting these, as everyone has learned now, very expensive AI and ML services based on deep learning was cost. And what I kept finding with my customers was that while AWS and cloud providers like Azure have native tools that were free or low cost to try and help them address some of these problems and adopt these new services in a cost-conscious way, they were fairly hard to use, not really integrated with each other. And it actually cost a lot of engineering time to string these things together. And on the other side, there were a lot of vendors I would work with who were promising to accelerate the process of putting a cost optimization of FinOps practice, if you will, in place, but they would come into my customer and say, hey, we can save you X dollars, but we won't tell you how until you lock into a few annual contracts or a strategy that obligates you to basically give up some ongoing percentage of spend and savings. So it left a lot of my customers between a rock and a hard place. And that's really what precipitated us starting our chair up. We wanted to create a bit of a new model, as you referenced, with a free single platform that acts as a replacement for those native AWS and other cloud providers, free tools and fills the gaps in their offerings with a low floor, high ceiling type of approach with the ability for a customer who really wants to get at something in place, but doesn't have the time to come in and click a button and basically get 60% of the way there from a savings perspective or really advanced FinOps teams to come in and dig down and figure out what are the individual resources and commitments they want to be covering and using going forward. So that's really the model that we've pioneered. And one of the key ways that we've tried to go to market is to be really customer obsessed. There's no one way doors. It's all two way doors. That's actually one of the key innovations we're bringing to this market in filling the gaps in the AWS ecosystem, particularly around commitments. And there's never a hidden savings tax. There's no surprise bills. So we're really trying to pioneer this customer obsessed model. And one of the key things that we found that customers really like is the fact that we actually have a new solution that fills the gaps between on demand one year and three year commitments with a flexible offering that allows customers to commit to any AWS service, not just compute, but things like SageMaker as well for as short as 30 days and then have the option at any point after that to click a button and send that commitment right off their books. And that's been able to unlock a lot of new use cases for customers. And the beautiful thing is customers can use our platform and opt into that and pay us money as part of adopting those commitments, or they can just use our platform to automate and plan native AWS commitments, save millions of dollars and never pay us a penny. And that's really the model that we're trying to bring into the ecosystem to be very customer obsessed. Very customer obsessed. Also very transparent, it sounds like. So you did a great job, Aron, of talking about the catalysts that were there to start our chair, the gaps that you're filling in the market. We talked about use cases. We've got Steve here from Clement Trading. We're going to be talking about his use case in a minute. But Aron, our chair of focus is on automating commitment management. Excuse me. Can you dig into what that category of optimization really entails and what it is that our chair delivers in that category? Yeah, absolutely. So when you think about commitments at AWS, there are, as an example, their commitments on all the different clouds, but we'll talk about AWS because it has the largest number of different commitment types. There are 36 plus ways to commit to any given workload. And depending on how long that workload will be up, what the actual savings rate is, and a number of different factors, you actually need to navigate this as an end user. That's really, really difficult to do, especially if you're not an expert in cloud pricing, which, of course, no one wants to become an expert in. They want to go and build software and deliver value to end users. So what we do at our chair is provide the tools to not only look at all the different commitment types and build an AI driven forecast of our customers' workloads, but then come up with a set of blended default strategies, blending all the different commitment types, all the term lengths, all the different contract types, including our 30 day GRIs are guaranteed buyback insured instances to really give customers a set of options that in one click they can apply to their infrastructure or they can actually dig in, build a really customized automation strategy and deploy that. So again, that's that low floor and high ceiling approach, but generally what we're trying to do is make sure that customers are able to, instead of taking weeks to do this, take hours or even minutes to do this, no matter how deep down the stack they want to go. And one of the other very unique things that we're doing is taking that next step after purchasing commitments where you're actually reselling them or exchanging them and making that entirely free to customers. That's something that, again, a lot of customers are on things like convertible or reserve instances are used to paying some ungodly percentage of ongoing savings or spend. They're coming to us and getting it for free. So really trying to hone in on where we're providing value, where we take a cost on our books with this guaranteed buyback and trying to give the rest of that universal weight of the customers for free to get them into the motion of actually automating this process without that downside risk of having an ongoing tax on your total spend or savings. You get to keep as much of that as makes sense for your organization. Well, the value prop is quite clear as well. Let's dig into an actual use case. We've got Steve Bear here as we introduced in the beginning of the show from Kemet Trading. Steve, welcome. Talk about what the company does and also tell us a little bit about your role. I understand you are a jack of all trades. Sure. So Kemet Trading is a financial technology provider to institutions on the buy side. So if you're doing trading specifically for us, we service digital asset derivatives. So a very niche space in a nascent market, small team moving fast, hopefully not breaking anything. It's kind of the vibe we have going. As you mentioned, title is Senior SRE, but that pretty much means everything at the platform on down. So if it's dealing with colos to managing our whole cloud infrared to self-service platform engineering and then of course, operational excellence and the SRE practices. So lots to do there. On your plate. Go ahead. Sorry. Yes. Oh, sure. So we found our chair through the AWS network, actually through our AWS startup. So it was a wonderful, easy way to get access. We got it installed through the marketplace, dropped in some cloud formation, and we were in, as Arun kind of mentioned, the barrier to entry, the initial onboarding was easy and it was a no-brainer for us. As you might imagine, in general, AWS billing is notorious for being difficult. It was just to begin to understand even what was going on. We had tons of greenfield development moving rapidly and needed to bring some maturation to how we were handling our spin. What were some of the key technical requirements, Steve, that you and Kevin had, that when you saw our chair, the light just, the light bulb went off? What were some of those key capabilities that it had to deliver? Sure. Well, I mean, for us, in the space that we work and being a early-stage company, we try to balance as much as possible the uniqueness of the regulatory things that our customers and therefore us may have to deal with. So the long-term commitment of a zonal or regional RI was a non-starter for us. And as Arun mentioned, the GRI really hit that sweet spot where we could begin to take advantage of the cost benefit of some of these commitments without any of the risk that some jurisdiction may change how things operate and we have to then move. Talk a little bit more about the use case and are there some cool outcomes? Arun did a great job of describing some of the significant cost benefits that organizations can get. It also sounds like the time to value as well. What are some of the big outcomes that you guys are achieving so far? Sure. Well, I mean, we get initial price breaks on our ECS-based workloads in Fargate. So just getting a baseline. Don't have to manage that. Don't have to deal with any of that turnkey out the box as we are driving that product maturity as we are moving to dedicated ECS-backed EC2 hosts. We can then move to GRIs for those. So whether we move further into cloud-native technologies or more into the host-based, more traditional VM-based technologies, no matter which way we grow and mature our architecture, we can keep cost at the front of our consideration. Which is critical. Arun, talk a little bit about what Steve shared in terms of the Kemet Trading use case. I imagine there's a lot of similarities with what you see with other companies in different industries. Yeah, absolutely. One of the key things that we try and put in place from a process perspective for all of our customers, no matter the industry, is to firstly try and get them a win upfront because we offer this unique 30-day discount that really doesn't have any alternative in the AWS ecosystem. It unlocks net new ways to commit to the cloud. That means that as soon as we install with the customer within the first few hours, we're able to actually click a button, cover resources with commitments, and get them immediate wins from a savings perspective because there are usually workloads like seasonality or short-term projects that are just not being covered today with commitments. That 30-day GRI that Steve was talking about unlocks. That's a pretty universal thing. But then as our customers mature and Steve is talking about the evolution of their architecture over time, one of the other key things we do from a commitment perspective is help them actually build very granular long-term forecasts with what we call our scenario planner. That allows them not only to figure out, all right, how do I save money today by covering stuff that I'm uncertain about, but then how do I actually plan out and get more certain about the future, figure out what those future workloads could be, and then start to evolve my commitment strategy so I can commit to more things for longer, use GRIs where it makes sense, use native AWS commitments where it makes sense, but overall find the lowest total cost of ownership for my workloads over the long term given my engineering plans. That's where we get with particularly some of our larger customers into things like helping them negotiate the enterprise deal with their cloud vendor like AWS or Azure. That actually encompasses not just thinking about the commitments, but thinking about the infrastructure. That's where we start to work more with engineering themes. Now our platform is entirely free and we give a ton of visibility, charge back, show back out of the box for free to those engineering themes. They can see what they're using, but additionally we have this scenario forecasting tool that will house engineers before they spin things up or as they're spinning things up and growing to model out what does that future spend going to be and contribute that upstream into a real global forecast for a customer that really drives what is that top level, CIO level bill or check rather, that they're going to write for the next one to three to five years to their cloud provider. So really going from the granular resource commitment at the beginning of our engagement all the way to that top level enterprise commitment as we kind of go through the circle and really help customers mature their FinOps process. So really a very complete almost visibility tool that you're enabling organizations to be able to see from those prioritization of resources to the top line which is key. You talked about FinOps. Steve, I know a little bit about Kemet, you described a little bit about it. I'm running an extensive cloud environment. Talk about from your seat, what are some of the major drivers for building a successful FinOps practice in a company that is really fast growing and that it's cloud native. What Aron talked about getting you know in sync with the engineers. What do engineers need to do to help make FinOps successful? Oh man, I mean just starting with your your spend OpEx and mine from day zero. We oftentimes think of cost management in our cost control in these sort of restrictive ways as a optimization after the fact and really especially in the current macro being mindful of your of your spend as you're trying to grow and trying to move fast and deliver a successful product that is engaging with customers and meeting their expectations a lot can go wrong. With the benefit of greenfield development, we employ certain technologies as much as possible. I mentioned how Fargate might be moving some of this workloads to host based. But due to the nature of our workloads with dedicated hosts, the overhead they bring, it's kind of unavoidable and being quickly required. Now, default on demand but everything across the board, you very quickly are spending far more than you would have otherwise and with something as simple as our chair in these offerings, GRIs really hit that sweet spot to allow us to make that consideration and take that consideration and take action on that consideration from day one. And that's the key really is to be able to take action on that. Aron, talk a little bit about from a cultural perspective bringing engineering folks together, DevOps folks together who may not be as familiar with cloud pricing and optimization or speak the language or to your point earlier really need should they be spending their resources there. How does our chair help bridge the engineering folks, the DevOps folks so that they can achieve those big savings that you're talking about? Yeah, so one of the key things that we're trying to do with our DevOps users specifically is give them one really, really easy interface much simpler than the AWS Cost Explorer to see just default what their individual infrastructure, what their individual piece of the overall AWS Pi is costing on a near real-time basis of giving them smart alerting and smart reporting around that. So I think really starts with the visibility piece that again we're providing for free for our customers but then it goes into kind of longer term things like custom dashboards where you can actually bring in the actual units that you're serving and look at unit economics and cost of goods sold as sort of the next level metric and we really allow engineers to go through that whole process from just seeing what is being spent to understanding what are they getting for what is being spent and what is that kind of as the product goes into maturity and actually is being served to end customers what is that metric that they really want to optimize around because often if you're spending more it could be a good thing because you're serving more users right. So that's one of the key things from a visibility perspective we're trying to bring to engineers and we have an enterprise ready sort of BI solution that's very customizable to really help customers go from the simple free product that we provide to something much more sophisticated and then on the other side we essentially will help customers on the engineering side integrate things like the scenario forecasting into their workflows and part of that key part of our scenario forecasting tool is helping customers understand on the dev outside what is actually as I'm spinning something up what is actually the alternative that I have here is there a cheaper region could I be running on graviton or is you know AWS compute optimizer saying that this thing is way too oversized I should be running you know two two instance sizes smaller all of that data is in you know 1015 disparate places between the AWS simple pricing calculator and trusted advisor and compute optimizer we bring it all into one place and increasingly are putting it into the engineering workflow where they're working in github you know in their infrastructure as code environment etc so that's really the way that we think about bringing that kind of disparate set of information at the fingertips of dev ops users and they always want to do the right thing the engineers the dev ops users so it's just about making it easy for them. Yeah really streamlining their productivity as well it sounds like Steve my last question for you is if you are talking to a prospect if Veronica says hey Steve you got this this hot prospect they want to talk to a customer who's really successful with our technology what would you say if someone said Steve why our chair why Steve what do you think? For us it was the easy onboarding and the no cost to get started I think it with the ease of the onboarding process getting up and just bringing visibility of these things the the value prop for the the initial input is is extreme and that's even if it's just a free that's a free offering at that point so even if you aren't taking advantage of the whole suite of things that our chair is bringing to the table just beginning to frame and have that single pane of glass that you can begin to interrogate these things throughout your cloud of state that's it's critical. So strong value prop and Steve you did a great job of really articulating our chair's value prop through the Kemet trading use case. Aron I want to leave you with the final words here what are some of the final kind of takeaways that you want our audience to know about our chair the approach this unique approach that you're bringing to cloud cost management. Well you know to Steve's point I think one of the things that we're pioneering is a true two-way door in the cost management space from a vendor perspective. Again we want to be really customer obsessed and the two things we wanted to do in starting this customer and this company was one reset essentially the price floor so it's no longer based on a percentage of savings or spend but it can be completely free for the customers to go and use native tools and then it gives them access to more advanced strategies like using GRIs or our you know custom BI and reporting dashboards that then they can opt in to pay a flat sort of SaaS rate for based on our costs not based on their spend or savings. So that was sort of one piece of it the other piece was actually to really revolutionize in a way the way that people work instead of providing just visibility we want to provide automation we want to provide more integration with DevOps workflows and eventually have this 24-7 you know FinOps AI co-pilot that's really helping you not just by giving you great default plans when you log into the platform that you can go and play with and implement and the click but really going deeper into the engineering workflow to help you and your teams choose the right resources up front and plan out for those long-term three to five-year enterprise sort of roadmap discussions that you have with your cloud vendor when you start getting to scale and you know I'd say that one of the key things that I want to leave folks with is just to echo what Steve said there's really no risk in trying us we're never going to charge a percentage of spend or savings we like to say we compete with AWS cost explorer because we're a free tool and we're about as easy to turn on and use and you know that's the way that we think cost management for any platform should exist in the future and that's the world that we're trying to build for customers awesome work guys revolutionize the way people work cost optimization no risk who could say no to that aron steve thank you so much for coming on the cube for the AWS startup showcase analytics and cost optimization we really enjoyed the time with you thank you thank you thank you my pleasure we want to thank you for watching and remind you to keep it right here for more action on the cube your leader in tech coverage