>>It's my pleasure to be one of the hosts of the cube on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years, the cube has been following the trail of data. And with the relentless March of data growth, this idea of a single version of the truth has become more and more elusive. Moreover data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is many sued as the CTO and co-founder of Reltio Maneesh. Welcome to the program. >>Thank you, Dave. It's a pleasure to be here. >>Okay. Let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with, with data as a source of digital innovation. >>They, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011, there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making, uh, compute capabilities available at scale to solve large data problems was becoming real impossible. The second thing that we saw was, uh, this big trend of, uh, you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone. And, uh, we are seeing more of the best of breed application type of a landscape where even if you look within a specific function, let's say sales or marketing, you have more than a dozen applications that any company is using today. >>And that trend was starting to emerge where we knew very well, that the number of systems that we would have to work with would continue to increase. And, uh, that created a problem of where would you get the single source of truth or the single best version of a customer, a supplier, a product that you're trying to sell those types of critical pieces of information that are core to any business that's out there today. And, um, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of a capability and for us to provide this capability in the cloud as a software, as a service, uh, uh, offering. So that's where, uh, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos and create a unified view of the core critical information that these companies run on. >>Yeah. I mean, the cloud is this giant, you know, hyper distributed system data by its very nature is distributed. It's interesting what you were sort of implying about, you know, the days of the monolithic app are gone by my business partner years ago, John furrier and the cube said data is going to become the new development kit. And we've certainly seen that with the, the pandemic, but tell us more about Reltio and how you help customers deal with that notion of data, silo, data silos, data fragmentation, how do you solve that problem? >>So, data fragmentation is what exists today. And, um, you know, with the Reltio, uh, software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented, siloed, uh, applications or data sources that they have within their enterprise at the same time. Um, there's a lot of dependence on the third party data. You know, when you think about, uh, different problems that you're trying to solve, you have, uh, for B2B type of information that in Bradstreet type of data providers in life sciences, you have IQ via type of data providers. Um, you know, as you look at other verticals, there is a specialized third-party data provider for any, and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know, who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. >>Um, and that's where Reltio fits in as the only platform that can help stitch together, this kind of, uh, information and create a 360 degree view that spans all the data silos and provides that for real-time use for BI and analytics to benefit from, for data science to benefit from. And then this emerging notion of, uh, data in itself is a, um, you know, key starting point that is used by us, uh, in order to make any decisions, just like, uh, we go, you know, if I, they wanted to look at information about you, I would go to places like LinkedIn, look up the information. And then our, my next set of decisions with that information, if somebody wanted to look up information on Reltio, they would go to, let's say Crunchbase as an example, and look up, uh, who are the investors? How much money have we raised all those details that are available? It's not a CRM system by itself, but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide, uh, as a part of the Reltio platform capabilities. >>Awesome. Thank you. And I want to get into the, to the tech, but before we do, maybe we just cut to the chase and maybe you can talk about some of the examples of, of Reltio and action. Some of the customers that you can talk about, maybe the industries that are, that are really adopting this. W what can you tell us there, Maneesh, >>Um, we work across a few different verticals, some of the key verticals that we work in our life sciences, um, and travel and hospitality and financial services, insurance, um, S uh, retail, as an example, those are some of the key verticals for us, but, uh, to give you some examples of, uh, the type of problems that customers are solving with Reltio as the data unification platform, um, let's take CarMax as an example, CarMax is a customer who's in the business of, uh, buying used cars, selling used cars, servicing those used cars. And then, um, you know, you as a customer, don't just transact with them. Once you, you know, you've had a car for three years, you go back and look at what can you trade in that car for, but in order for CarMax to provide a service to you that, uh, goes across all the different touch points, whether you are visiting them at their store location, uh, trying to test drive a car or viewing, uh, information about the various vehicles on their website, or just, uh, you know, punching in the registration number of your car, just to see what is the appraisal from them in terms of how much will they pay for your car? >>This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points and the type of information that they use, uh Reltio for aggregating, unifying, and then making available across all these touch points is all of the information about the customers, all of the information about, uh, the, uh, household, uh, you know, the understanding that they're trying to achieve because, uh, life events can, uh, be buying signals, uh, for, uh, consumers like uni, as well as, uh, who was the, um, associate who helped you either in the selling of a car buying of a car, because business is all about building relationships for the longer term lifetime value that they want to capture. And in that process, um, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, uh, there is a lot of information in order to price it, right, that needs to be gathered, uh, from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio, and then made available, uh, through API APIs or through other methods, and means to the various applications can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run end to end. Well, it sounds like >>That's come along. Sorry. >>I was just going to say it that's one example and, uh, you know, across other verticals that are other similar examples of how companies are leveraging, Reltio >>Just say, can come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and, and, you know, happy to dig into some other examples, but, but I wonder how does it work? I mean, what's the magic behind it? What's the, the tech look like, I mean, obviously you leveraging AWS, maybe you could talk about how so, and maybe some of the services there and some of your unique IP. >>Yeah. Um, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, uh, you know, if you think about, uh, the problem itself, uh, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. Um, you know, for example, I have been in this area was, uh, responsible for creating some of the previous generation capabilities and, uh, most of the friction in those previous generation MDM or master data management type of solutions, um, as the, you know, the technical term that is used to refer to this area, uh, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that, uh, customers want to capture, whether it is, uh, you know, about a patient or a product, or let's say a supplier that you're working well. >>Uh, there is always additional information that you can capture and, uh, you know, use to better inform the decisions for the next engagement and, uh, that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use at scale compute capabilities in the cloud, um, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information, just locking it in a data warehouse has been sort of the problem in the past. And you talked about the clickstream analysis, uh, analytics has a place, but most of the analytics is a rear view mirror picture of the, uh, you know, work that you have to do, versus everybody that we talked to, uh, as a potential customer, wanted to solve the problem of what can we do at the point of engagement, how can we influence decisions? >>So, you know, I'll give you an example. I think, uh, everybody's familiar with Quicken loans, um, as the mortgage lender and, uh, in the mortgage lending business, uh, Quicken loans is the customer who's using Reltio as the customer data, um, unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time window, um, you know, anywhere from 10 minutes to about an hour, where if somebody expresses an interest in refinancing or getting a mortgage, they have to close that, uh, business within that, uh, Hart window, the conversion ratios are exponentially better in that hot window versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage, uh, at. And, uh, they've been able to use this notion of real time data, where as soon as you come in through the website, or if you come in through the rocket mortgage app, or you're talking to a broker by calling the one 800 number, they are able to triangulate that it's the same person coming from any of these different channels and respond to that person, whether an offer, uh, ASAP so that, uh, there is no opportunity for the competition to get in and present you with a better offer. >>So those are the types of things where the time to, uh, conversion or the time to action is being looked at. And everybody's trying to shrink that time down, uh, that ability to respond in real time with the capabilities was sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities. And now customers are able to benefit from that. >>That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket, and when you experience that environment, it's totally different than anything you've ever seen before. So it's helpful to hear you explain, like what's behind that because it's, it's truly disruptive. And I, and I'll tell you, the other thing that, that sort of triggered a thought was that we use the word realtime a lot, and we try to develop years ago. We said, what does real-time really mean? And the, the answer we CA we landed on was before you lose the customer, and that's kind of what you just described. Uh, and that is what gives as an example, a quick and a real advantage again, having experienced it firsthand. It's, it's pretty, pretty tremendous. So that's a nice, that's a, that's a nice reference. Um, so, and the other thing that struck me is that what I wanted to ask you, how it's different from sort of legacy master data management solutions, and you sort of described that they've seized to me, they got to take their, their traditional on-prem stack, rip it out, stick it in the cloud is okay, we got our stack in the cloud. >>Now your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a, from an CTO's perspective, what's your, >>Yeah. The clean sheet of paper is the luxury that we have, you know, having seen this movie before having, um, you know, looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, um, you know, across all of our customers, we are today managing, um, uh, about 6.5 billion consolidated profiles of people, organizations, product locations, um, you know, assets, uh, those kinds of details. And these are, these are the types of, uh, crown jewels of the business that every business runs on. You know, for example, if you wanted to, um, let's say you're a large company, like, uh, you know, Ford and you wanted to figure out how much business are you doing, where the, uh, you know, another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. >>It's been a very difficult answer to understand what is the total book of business that they have with that other, um, big, uh, customer and, uh, you know, being able to have the right, uh, unified, uh, relevant, rich clean as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, uh, you know, drive, uh, any kind of, uh, conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. Um, you have to have that foundation of clean data to work with in order to get to those answers. >>Nice. Uh, and then I had questions on just the model is this, it's a SAS model. I presume, how, how is it priced? Do you have a, do you have a freemium? How do I get started? Maybe you could give us some color. >>Yeah, we are a SAS provider. We do everything in the cloud, uh, offer it as a SAS offering, um, for customers to leverage and benefit from our pricing is based on the volume of, uh, uh, consolidated profiles. And the, I use the word profiles because this is not the traditional, uh, data model where you have rows columns, foreign keys. This is a, you know, a profile of a customer, regardless of attribution or any other details that you want to capture. And, um, you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Uh, customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, uh, you know, off these different types of data domains, customer, patient provider, uh, product, uh, asset, those types of details. But, uh, then they grow and some of the customers, uh, HP Inc, as a customer is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use the single source of truth capabilities provided by Reltio. >>And your relationship with AWS you're, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >>Yeah. AWS has been a key partner for us, uh, since the very beginning, uh, we are now on the marketplace. Uh, customers can start with the free version of the product, um, and start to play with the product, understand it better, uh, and then move into the paid tier, um, you know, as they bring in more data, uh, into Reltio. And, uh, you know, we also, uh, have, uh, the partnership with AWS where, uh, you know, customers can benefit from the relationship where they are able to, um, uh, use the, the spend against Reltio to offset the commitment credits that they have for AWS, um, you know, as a cloud provider. So, uh, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >>Nice that love, love, those credits, um, company update, uh, you know, head count funding, revenue trajectory, what kind of metrics are you comfortable sharing? >>So, uh, we are currently, uh, at about, um, you know, slightly North of 300 people, uh, overall at rail queue, we will, uh, grow from 300 to about 400 people this year, uh, itself. Uh, we are, uh, uh, you know, we just put out a press release, uh, where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are, uh, looking at, uh, crossing the a hundred million dollar ARR, um, uh, threshold, uh, later this year. So we're on a great growth trajectory and, uh, the businesses, uh, performing really well. And we are, uh, looking at working with more customers and helping them solve this, uh, uh, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >>That's some impressive growth. Congratulations, w w we're, I'm sure adding a hundred people you're hiring all over the place, but where we get some of your priorities. >>So, um, you know, the, as the business is growing, we are spending equally both on the R and D side of the house, uh, investing more there, but at the same time, also on our go to market, uh, so that we can extend our reach, make sure that, uh, more people know about, uh, Reltio and can start leveraging the benefit of, uh, the technology that we have built on top of, uh, AWS. >>Yeah. I mean, it sounds like you've obviously nailed product market fit, and now you're, you know, scaling and scaling the go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, why, what was prompted that move >>Problems of luxury, uh, you know, as I like to call them, uh, once you know, that you're on a great growth trajectory and, uh, the business is performing well, it's all about, uh, figuring out ways of, uh, you know, making sure that you can drive harder and faster towards that growth, uh, milestones, uh, that you want to achieve. And, uh, you know, for us, uh, the story is no different. Uh, the team has done a wonderful job of, uh, making sure that we can build the right platform, um, you know, work towards this opportunity, that PC, which by the way, um, they just to share with you, uh, MDM or master data management has always been underestimated as a, uh, you know, yes, there is a problem that needs to be solved, but the market sizing was, uh, in a, not as clear, but some of the most recent, uh, estimates from analysts like Gartner, but the, uh, you know, sort of the new incarnation of, uh, data unification and master data management at about a $30 billion, uh, you know, uh, Tam or this market. >>So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, uh, I looked at, uh, you know, how could we scale the business faster and have the right team to work, uh, help us maximize the opportunity. And that's why, uh, you know, we decided, uh, that it was the right point in time for me to bring in somebody who's, uh, worked, uh, at, uh, the stretch of, you know, taking a company from just a a hundred million dollars in ARR to, uh, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, uh, you know, has had that experience and having him take on the CEO role, uh, really puts us on a tremendous, uh, our path to tremendous growth and achieving that, uh, with the right team. >>Yeah. And I think I appreciate your comments on the Tam. I love to look at the Tam and to do a lot of Tam analysis. And I think a lot of times when you define the future Tam based on sort of historical categories, you sometimes under count them. I mean, to me, you guys are in the, the, the digital business business. I mean, the data transformation, the company transformation business, I mean, that could be order of magnitude even bigger. So I think the future is bright for your company. Reltio Maneesh. And thank you so much for coming on the program really appreciate. >>Well, thanks for having me, uh, really enjoyed it. Thank you. >>Okay. Thank you for watching. You're watching the cubes startup showcase. We'll be right back.

(upbeat music) >> It's my pleasure, to be one of the hosts of theCUBE on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years theCUBE has been following the trail of data. And with the relentless match of data growth this idea of a single version of the truth has become more and more elusive. Moreover, data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand, the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is Manish Sood the CTO and co-founder of Reltio. Manish, welcome to the program. >> Thank you, Dave. It's a pleasure to be here. >> Okay, let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement, cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with data as a source of digital innovation. >> Dave, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011 there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making compute capabilities available at scale to solve large data problems was becoming real and possible. The second thing that we saw was this big trend of you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone and we are seeing more of the best of breed application type of a landscape where even if you look within a specific function let's say sales or marketing, you have more than a dozen applications that any company is using today. And that trend was starting to emerge where we knew very well that the number of systems that we would have to work with would continue to increase. And that created a problem of where would you get the single source of truth or the single best origin of a customer, a supplier, a product that you're trying to sell, those types of critical pieces of information that are core to any business that's out there today. And, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of capability and for us to provide this capability in the cloud as a software, as a service offering. So that's where, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos, and create a unified view of the core critical information that these companies run on. >> Yeah, the cloud is this giant, you know hyper distributed system, data by its very nature is distributed. It's interesting what you were sort of implying about you know, the days of the monolithic app are gone, but my business partner years ago John Furrier at theCUBE said, data is going to become the new development kit. And we've certainly seen that with the pandemic but tell us more about Reltio and how you help customers deal with that notion of data silos, data fragmentation, how do you solve that problem? >> So data fragmentation is what exists today. And, with the Reltio software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented siloed applications or data sources that they have within their enterprise. At the same time, there's a lot of dependence on the third party data. You know, when you think about different problems that you're trying to solve, you have for B2B type of information that in Bradstreet type of data providers, in life sciences you have IQVIA type of data providers. You know, as you look at other verticals that is a specialized third party data provider for any and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. And that's where Reltio fits in as the only platform that can help stitch together this kind of information and create a 360 degree view that spans all the data silos and provides that for real-time use, for BI and analytics to benefit from, for data science to benefit from, and then this emerging notion of data in itself is a, you know, key starting point that is used by us in order to make any decisions. Just like we go, you know, if I they wanted to look at information about you, I would go to places like LinkedIn, look up the information, and then on my next set of decisions with that information. If somebody wanted to look up information on Reltio they would go to, let's say crunchbase as an example and look up, who are the investors? How much money have we raised? All those details that are available. It's not a CRM system by itself but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide as a part of the Reltio platform capabilities. >> Awesome, thank you. And I want to get into the tech, but before we do maybe we just cut to the chase and maybe you can talk about some of the examples of Reltio and action, some of the customers that you can talk about, maybe the industries that are really adopting this. What can you tell us there Manish? >> We work across a few different verticals some of the key verticals that we work in are life sciences and travel and hospitality and financial services, insurance retail, as an example. Those are some of the key verticals for us. But to give you some examples of the type of problems that customers are solving with Reltio as the data unification platform, let's take CarMax as an example,. CarMax is a customer who's in the business of buying used cars, selling used cars servicing those used cars. And then, you know, you as a customer don't just transact with them once, you know, you've had a car for three years you go back and look at what can you trade in that car for? But in order for CarMax to provide a service to you that goes across all the different touch points whether you are visiting them at their store location trying to test drive a car or viewing information about the various vehicles on their website, or just you know, punching in the registration number of your car just to see what is the appraisal from them in terms of how much will they pay for your car. This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points. And the type of information that they use relative for aggregating, unifying, and then making available across all these touch points, is all of the information about the customers, all of the information about the household, you know, the understanding that they are trying to achieve because life events can be buying signals for consumers like you and I, as well as who was the associate who helped you either in the selling of a car, buying of a car, because their business is all about building relationships for the longer term, lifetime value that they want to capture. And in that process, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, there is a lot of information in order to price it right, that needs to be gathered from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio and then made available through APIs or through other methods and means to the various applications, can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run and to end. >> Well, sounds like we come along, (indistinct). >> I was just going to say that's one example and, you know across other verticals, that are other similar examples of how companies are leveraging, Reltio >> Yeah, so as you say, we've come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and you know happy to dig into some other examples, but I wonder how does it work? I mean, what's the magic behind it? What's the tech look like? I mean, obviously leveraging AWS, maybe you could talk about how, so, and maybe some of the services there and some of your unique IP. >> Yeah, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, you know, if you think about the problem itself, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. You know, for example, I have been in this area was responsible for creating some of the previous generation capabilities and most of the friction in those previous generation MDM or master data management type of solutions as the you know, the technical term that is used to refer to this area, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that customers want to capture, whether it is, you know, about a patient or a product or let's say a supplier that you're working with, there is always additional information that you can capture and you know use to better inform the decisions for the next engagement. And that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use add scale compute capabilities in the cloud, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information just locking it in a data warehouse has been sort of the problem in the past, and you talked about the clickstream analysis. Analytics has a place, but most of the analytics is a real view mirror picture of the, you know, work that you have to do versus everybody that we talk to as a potential customer wanted to solve the problem of what can we do at the point of engagement? How can we influence decisions? So, you know, I'll give you an example. I think everybody's familiar with Quicken loans as the mortgage lender, and in the mortgage lending business, Quicken loans is the customer who's using Reltio as the customer data unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time vendor, you know anywhere from 10 minutes to about an hour where if somebody expresses an interest in refinancing or getting a mortgage they have to close that business within that hot vendor. The conversion ratios are exponentially better in that hot vendor versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage at? And they've been able to use this notion of real time data where as soon as you come in through the website or if you come in through the rocket mortgage app or you're talking to a broker by calling the 1800 number they are able to triangulate that it's the same person coming from any of these different channels and respond to that person with an offer ASAP so that there is no opportunity for the competition to get in and present you with a better offer. So those are the types of things where the time to conversion or the time to action is being looked at, and everybody's trying to shrink that time down. That ability to respond in real time with the capabilities were sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities, and now customers are able to benefit from that. >> That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket when you experience that environment, it's totally different, than anything you've ever seen before. So it's helpful to hear you explain like what's behind that because, it's truly disruptive and I'll tell you the other thing that sort of triggered a thought was that we use the word realtime a lot and we try to develop years ago. We said, what does real-time really mean? And the answer we landed on was, before you lose the customer, and that's kind of what you just described. And that is what gives as an example a quick and a real advantage again, having experienced it firsthand. It's pretty, pretty tremendous. So that's a nice reference. So, and the other thing that struck me is, I wanted to ask you how it's different from sort of legacy Master Data Management solutions and you sort of described that they've since to me they've got to take their traditional on-prime stack, rip it out, stick it in the iCloud, it's okay we got our stack in the cloud now. Your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a CTO's perspective, what's your take? >> Yeah, the clean sheet of paper is the luxury that we have. You know, having seen this movie before having, you know looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, you know, across all of our customers, we are today managing about 6.5 billion consolidated profiles of people, organizations, product, locations, you know, assets, those kinds of details. And these are the types of crown jewels of the business that every business runs on. You know, for example, if you wanted to let's say you're a large company, like, you know, Ford and you wanted to figure out how much business are you doing, whether, you know another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. It's been a very difficult to answer to understand what is the total book of business that they have with that other big customer. And, you know, being able to have the right, unified, relevant, ready clean information as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, you know drive any kind of conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. You have to have that foundation of clean data to work with in order to get to those answers. >> Nice, and then I had questions on just analysis, it's a SAS model I presume, how is it priced? Do you have a freemium? How do I get started? Maybe you could give us some color on that. >> Yeah, we are a SAS provider. We do everything in the cloud, offer it as a SAS offering for customers to leverage and benefit from. Our pricing is based on the volume of consolidated profiles, and I use the word profiles because this is not the traditional data model, where you have rows, columns, foreign keys. This is a profile of a customer, regardless of attribution or any other details that you want to capture. And you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, you know, off these different types of data domains, customer, patient, provider, product, asset, those types of details, but then they grow and some of the customers HPInc, as a customer, is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use, the single source of truth capabilities provided by Reltio. >> And, and your relationship with AWS, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >> Yeah, AWS has been a key partner for us since the very beginning. We are now on the marketplace. Customers can start with the free version of the product and start to play with the product, understand it better and then move into the paid tier, you know as they bring in more data into Reltio and, you know be also have the partnership with AWS where, you know customers can benefit from the relationship where they are able to use the spend against Reltio to offset the commitment credits that they have for AWS, you know, as a cloud provider. So, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >> Nice, love those credits. Company update, you know, head count, funding, revenue trajectory what kind of metrics are you comfortable sharing? >> So we are currently at about, you know, slightly not at 300 people overall at Reltio. We will grow from 300 to about 400 people this year itself we are, you know, we just put out a press release where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are looking at crossing the hundred million dollar ARR threshold later this year. So we are on a great growth trajectory and the business is performing really well. And we are looking at working with more customers and helping them solve this, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >> That's some impressive growth, congratulations. We're, I'm sure adding hundred people you're hiring all over the place, but where we are some of your priorities? >> So, you know, the, as the business is growing we are spending equally, both on the R and D side of the house investing more there, but at the same time also on our go to market so that we can extend our reach, make sure that more people know about Reltio and can start leveraging the benefit of the technology that we have built on top of AWS. >> Yeah, I mean it sounds like you've obviously nailed product market fit and now you're, you know, scaling the grip, go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, what was prompted that move? >> Problems of luxury, you know, as I like to call them once you know that you're in a great growth trajectory, and the business is performing well, it's all about figuring out ways of, you know making sure that you can drive harder and faster towards that growth milestones that you want to achieve. And, you know, for us, the story is no different. The team has done a wonderful job of making sure that we can build the right platform, you know work towards this opportunity that we see, which by the way they've just to share with you, MDM or Master Data Management has always been underestimated as a, you know, yes there is a problem that needs to be solved but the market sizing was in a, not as clear but some of the most recent estimates from analysts like Gartner, but the, you know, sort of the new incarnation of data unification and Master Data Management at about a $30 billion, yeah, TAM for this market. So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, I looked at, you know how could we scale the business faster and have the right team to work help us maximize the opportunity. And that's why, you know, we decided that it was the right point in time for me to bring in somebody who's worked at the stretch of, you know taking a company from just a hundred million dollars in ARR to, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, you know, has had that experience and having him take on the CEO role really puts us on a tremendous path or path to tremendous growth and achieving that with the right team. >> Yeah, and I think I appreciate your comments on the TAM. I love to look at the TAM and to do a lot of TAM analysis. And I think a lot of times when you define the the future TAM based on sort of historical categories, you sometimes under count them. I mean, to me you guys are in the digital business. I mean, the data transformation the company transformation business, I mean that could be order of magnitude even bigger. So I think the future is bright for your company Reltio, Manish and thank you so much for coming on the program. Really appreciate it. >> Well, thanks for having me, really enjoyed it. Thank you. >> Okay, thank you for watching. You're watching theCUBEs Startup Showcase. We'll be right back. (upbeat music)

>> Narrator: From around the globe, it's theCUBE with digital coverage of AnsibleFest 2020, brought to you by Red Hat. >> The ascendancy of massive clouds underscored the limits of human labor. People, they simply don't scale at the pace of today's technology. And this trend created an automation mandate for IT which has been further accentuated by the pandemic. The world is witnessing the build-out of a massively distributed system that comprises on-prem apps, public clouds and edge computing. The challenge we face is how to go from managing things you can see and touch to cost effectively managing, securing and scaling these vast systems. It requires an automation first mindset. Hello, everyone. This is Dave Vellante and welcome back to AnsibleFest 2020. We have a great panel to wrap up this show. With me are our three excellent guests and CUBE alums. Ashesh Badani is the Senior Vice President of Cloud Platforms at Red Hat. Ashesh, good to see you again. Thanks for coming on. >> Yeah, likewise. Thanks for having me on again, Dave. >> Stefanie Chiras is Vice President and General Manager of the RHEL Business Unit and my sports buddy. Stefanie, glad to see you back in the New England area. I knew you'd be back. >> Yeah, good to see you, Dave. Thanks for having us today. >> You're very welcome. And then finally, Joe Fitzgerald, longtime CUBE alum, Vice President and General Manager of the Management Business Unit at Red Hat. Joe, good to see you. >> Hey, Dave, good to be here with you. >> Ashesh, I'm going to start with you. Lay out the big picture for us. So how do you see this evolution to what we sometimes talk about as hybrid cloud, but really truly a hybrid cloud environment across these three platforms that I just talked about? >> Yeah, let me start off by echoing something that most of your viewers have probably heard in the past. There's always this notion about developers, developers, developers. And you know, that still holds true. We aren't going away from that anymore. Developers are the new kingmakers. But increasingly, as the scope and complexity of applications and services that are deployed in this heterogeneous environment increases, it's more and more about automation, automation, automation. In the times we live in today, even, you know, before dealing with the crises that, you know, we have, just the sheer magnitude of requirements that are being placed on enterprises and expectations from customers require us to be more and more focused on automating tasks which humans just can't keep up with. So you know, as we look forward, this conversation here today, you know, what Ansible's doing, you know, is squarely aimed at dealing with this complexity that we all face. >> So Stefanie, I wonder if you could talk about what it's going to take to implement what I call this true hybrid cloud, this connection and management of this environment. RHEL is obviously a key piece of that. That's going to be your business unit, but take us through your thoughts there. >> Yeah, so I'm kind of building on what Ashesh said. When we look at this hybrid cloud world, right, which now hybrid is much more than it was considered five years ago. It used to be hybrid was on-prem versus off-prem. Now, hybrid translates to many layers in the stack. It can be VMs hybrid with containers. It can be on-prem with off-prem and clearly with edge involved, as well. Whenever you start to require the ability to bridge across these, that's where we focus on having a platform that allows you to access sort of all of those and be able to deploy your applications in a simple way. When I look at what customers require, it's all about speed of deploying applications, right, build, deploy and run your applications. It's about stability, which is clearly where we're focused on RHEL being able to provide that stability across multiple types of hybrid deployment models. And third is all about scale. It is absolutely all about scale and that's across multiple ranges in hybrid, be it on-prem, off-prem, edge and that's where all of this automation comes in, so to me, it's really about where do you make those strategic decisions that allow you to choose, right, for the flexibility that you need and still be able to deploy applications with speed, have that stability, resiliency, and be able to scale. >> So Joe, let's talk about your swim lane and it's weird to even use that term, right? 'Cause as Stefanie just said, we're kind of breaking down all these silos that we talk in terms of platform, but how do you see this evolving, and specifically, what's the contribution from a management perspective? >> Right, so Stefanie and Ashesh talked about sort of speed, scale and complexity. Right, people are trying to deploy things faster or larger scale, and oh, by the way, keep everything highly available and secure. That's a challenge, right? And so, you know, interestingly enough, Red Hat, about five years ago, we recognized that automation was going to be a problem as people were moving into open hybrid clouds, which we've been working with our customers for years on. And so we acquired this small company called Ansible, which had some really early emerging technology, all open source, right, to do automation. And what we've done over the past five years is we've really amplified that automation and amplified the innovation in that community to be able to provide automation across a wide array of domains that you need to automate, right, and to be able to plug that in to all the different processes that people need in order to be able to go faster, but to track, manage, secure and govern these kind of environments. So we made this bet years ago and it's paying off for Red Hat in very big ways. >> I mean, no doubt about it. I mean, when you guys bought Ansible, so it wasn't clear that it was going to be the clear leader. It is now. I mean, it's pulled ahead of Chef, Puppet. You saw, you know, VMware bought Salt, but I mean, Ansible very clearly has, based on our surveys, the greatest market momentum. We're going to talk about that. I know some of the other analysts have chimed in on this, but let me come back to this notion of on-prem and cloud and edge and this is complicated. I mean, the edge, it's kind of its own island, isn't it? I mean, you got the IT and the OT schism, so maybe you could talk a little bit about how you see those worlds coming together, the cloud, the on-prem, the edge. Maybe Stefanie, you can start. >> Yeah, I think the magic, Dave, is going to happen when it's not its own island, right, as we start to see this world driven by data cause the spread of a data center to be really dis-aggregated and allow that compute to move out closer to the data, the magic happens when it doesn't feel like an island, right, that's the beauty and the promise of hybrid. So when you start to look at what can you provide that is consistent that serves as a single language that you can talk to from on-prem, off-prem and edge, you know, it all comes down to, for us, having a platform that you can build once and deploy across all of those, but the real delicacy with edge is there are some different deployment models. I think that comes into deployment space and we're clearly getting feedback from customers. We're working on some capabilities where edge requires some different deployment models in the ways you update, et cetera, and thanks to all of you out there who are working with us upstream in order to deliver that. And I think the second place where it's unique is in this ability to manage and automate out at the edge, but our goal is certainly at our platform levels, whether it be on RHEL, whether it be on OpenShift to provide that consistent platform that allows you that ease of deployment, then you got to manage and automate it and that's where the whole Ansible and the ecosystem really plays in. You need that ecosystem and that's always what I love about AnsibleFest is this community comes together and it's a vibrant community, for sure. >> Well, I mean, Ashesh, you guys are betting big on this and I often think of the cloud is just this one big cloud. You got the on-prem cloud, you got the public clouds. Edge becomes just an extension of that cloud. Is that how you think about it and what is it actually going to take to make that edge not an island? >> Yeah, great point, Dave, and that's exactly how we think about it. We've always thought about our vision of the cloud as being a platform and abstraction that spans all the underlying infrastructure that the user can take advantage of, so if it happens to reside in a data center, some in a private cloud running off a data center, more increasingly in the public cloud setting, and as Stefanie called out, we're also starting to see edge deployments come in. We're seeing, you know, big build-outs in the work we're doing with telecom providers from a 5G perspective that's helping drive that. We're seeing, if you will, IOT-like opportunities with, let's say, the automotive sector or some in the retail sector, as well. And so this fabric, if you will, needs to span this entire set of deployment that a customer will take advantage of. And Joe started touching on this a little bit, right, with this notion of the speed, scale and complexity, so we see this platform needing to expand to all these footprints that customers are using. At the same time, the requirements that they have, even when they're going out the edge, is the same with regard to what they see in the data center and the public cloud, so putting all that together really is our sweet spot. That's our focus. And to the point you're making, Dave, that's where we're making a huge bet across all of Red Hat. >> So I mentioned, you know, some of our research and I do these breaking analysis segments every week and recently I was digging into cloud and specifically was interested in hybrid and multi. And you know, hybrid been I think pretty well understood for awhile. Multi I think was a lot of, you know, a lot of talk, but it's becoming real and the data really shows that. It shows OpenShift and Ansible have momentum. I mentioned that before. Yeah, you know, obviously VMware is there, but clearly Red Hat is well positioned specifically in multicloud and hybrid. And I know some of the other analyst firms have picked up on this. What are you guys seeing in the market? Maybe Joe, you can chime in and Ashesh, you can maybe add some color. >> Yeah, so you know, there's a lot of fashion, right, around hybrid and multicloud today, so every vendor is jumping on with multicloud storing. And you know, a lot of the vendors' strategies are, pick my solution and vertically use my stuff in the public cloud on-premise, maybe even at the edge, right, and you'll be fine. And you know, obviously customers don't like lock-in. They like to be able to take advantage of the best services, availability, security, different things that are available in each of these different clouds, right? So there is a strong preference for hybrid and multicloud. Red Hat is sort of the Switzerland of hybrid and multicloud because we enable you to run your workloads across all these different substrates, whether it's in public clouds, multiple, right, into the data center and physical, virtual, bare metal, out to the edge and edge is not a single homogeneous, you know, set of hardware or even implementation. It varies a lot by vertical, so you have a lot of diversity, right? And so Red Hat is really good at helping provide the platforms like OpenShift and RHEL that are going to provide that consistency across those different environments or also in the case of Ansible to provide automation that's going to match the physics of management and automation that are required across each of those different environments. Trust me, managing or automating something at the edge and with very small footprint of some device across the constraint network is very, very different than managing things in a public cloud or in a data center and that's where I think Red Hat is really focused and that's our sweet spot, helping people manage those environments. >> And Ashesh, you guys have obviously put a lot of effort there. If you could maybe comment. >> Yeah, I was just going to say, Dave, I'll add just really quickly to what Joe said. He said it well. But the thing I will add is the way for us to succeed here is to follow the user, follow the customer. Right, instead of us just coming out with regard to what we believe the path to be, you know, we're really kind of working closely with the actual customers that we have. So for example, recently been working with a large water utility in Italy, but they're thinking about, you know, the world that they live in and how can they go off and, you know, have kiosks that are spread throughout Italy, able to provide reports with regard to the quality of the water that's available, as well as other services to all their citizens. But it's really interesting use case for us to go off and pursue because in some sense, you can ask yourself, well, is that public cloud? Are they going to take advantage of those services? Is that, you know, private cloud? Is that data center, is that IOT, is that edge? At a certain point in time, what you've got to think about is, well, we've got to provide integrated end-to-end solution that spans all of these different worlds, and so as long as I think we keep that focus, as long as we make sure our North Star is really what the user's trying to do, what problem they're trying to solve, I think we'll come out just fine on the other side of this. >> So I'd love to get all your thoughts, all three of you, on just what's going on in containers, generally, Kubernetes, specifically. I mean, everybody knows it's a hot space and the data shows that it is maturing, but it's amazing to me how much momentum it still has. I mean, it's like the new shiny toy, but it's everywhere and so it's able to sort of maintain that velocity and it's really becoming the go-to cloud native development platform, so the question is how is Red Hat, you know, helping your customers connect OpenShift to the rest of their IT infrastructure, platforms, their processes, the tools. I mean, who wants to start? I'd love to hear from all three of you. Ashesh, why don't you kick it off and then we'll just go left to right. >> So Dave, we've spoken to you and to folks the CUBE, as well, other for many years on this. We've made a huge investment in the Kubernetes market and been one of the earliest to do that and we continue to believe in the promise that it delivers to users, this notion of being able to have an environment that customers can use regardless of the underlying choices that they make. Here's an extremely powerful one, it's truly an open source, right? This is key to, you know, what we do. Increasingly, what we're working on is to ensure that one, if you make a commitment to Kubernetes and increasingly we see lots of customers around the world doing that, that we ensure that we're working closely, that our entire portfolio helps support that. So if you're going to make a choice with regard to Kubernetes base deployment, we help support you running it yourself wherever it is that you choose to run it, we help support you whether you choose to have us manage on your behalf and then also make sure we're providing an entire portfolio of services, both within Red Hat as well as from third parties so that you have the most productive, integrated experience possible. >> Okay, and Stefanie, loved your point of view on this, and Joe, I'd love to understand how you're bridging kind of the Ansible and Kubernetes communities, but Stefanie, why don't you chime in first? >> Yeah, I'll quickly add to what Ashesh said and talked about well on really the promise and the value of containers, but particularly from a RHEL perspective, we have taken all our capabilities and knowledge in the Linux space and we have taken that to apply it to OpenShift, right, because Kubernetes and containers is just another way to deploy Linux, so making sure that that underpinning is stable, secure and resilient and tied to an ecosystem, right? An ecosystem of various architectures, an ecosystem of ISVs and tooling, right? We've pulled that together and everything we've done in Linux for, you know, over decades now at Red Hat and we've put that into that customer experience around OpenShift to deploy containers, so we've really built, it has been a portfolio-wide effort, as Ashesh alluded to, and of course, it passes over to Ansible as well with Joe's portfolio. >> Yeah, we talked about this upfront, Joe. The communities are so crucial, so how are you bridging those Ansible and Kubernetes communities? What's your thought on that? >> Well, a quick note about those communities. So you know, OpenShift is built on Kubernetes and a number of other projects. Kubernetes is number seven in the top 10 open source projects based on the number of contributors. Turns out Ansible is number nine, right? So if you think about it, these are two incredibly robust communities, right? On the one hand, building the container platform in Kubernetes and in the other around Ansible and automation. It turns out that as the need for this digital acceleration and building these container-based applications comes along, there's a lot of other things that have to be done when you deploy container-based applications, whether it's infrastructure automation, right, to expand and manage and automate the infrastructure that you're running your container-based applications on, creating more clusters, you know, configuring storage, network, you know, counts, things like that, but also connecting to other systems in the environment that need to be integrated with around, you know, ITSM or systems of record, change management, inventory, cost, things like that, so what we've done is we've integrated Ansible, right, in a very powerful way with OpenShift through our advanced cluster management capability, which allows us to provide an easy way to instrument Ansible during critical points, whether it's you're deploying new clusters out there or you're deploying a new version of an application or a new application for the first time, whether you're checking policy, right, to ensure that, you know, the thing is secure and that, you know, you can govern these environments, right, that you're relying on. So we've really now tied together two sort of de facto standards, OpenShift built on Kubernetes and a number of other projects and then Ansible, or Red Hat, has taken this innovation in the community and created these certified content collections, platforms and capabilities that people can actually build and rely on and know that it's going to work. >> Ashesh, I mean, Red Hat has earned the right, really, to play in both the cloud native world and of course the traditional infrastructure world, but I'm interested in what you're seeing there, how you're bringing those two worlds together. Are they still, you know, largely separate? Are you seeing traditional IT? I mean, you're certainly seeing them lean in to more and more cloud native, but what are you guys doing specifically to kind of bring those worlds together? >> Yeah, increasingly it's really hard to be able to separate out those worlds, right? So in the past, we used to call it shadow IT. There really is no shadow IT anymore, right? This is IT. So we've embraced that completely. You know, our take on that is to say there are certain applications that are going to be appropriate for being run in a data center a certain way. There are certain other workloads that'll find their way appropriate for the public cloud. We want to make sure we're meeting them across, but what we want to do is constantly introduce technologies to help support the choices customers make. What do I mean by that? Let me give a couple examples. One is, you know, we can say customers have VMs that are based out in specific environments and they can only run as VMs. That code can't be containerized for a variety of reasons, right? You know, hard to re-architect that, don't have the funds, you know, have certain security compliance reasons. Well, what if we could take those VMs and then have them be run in containers in a native fashion? Wouldn't that be extremely powerful value proposition to run containers and then VMs as containers sort of side by side with Kubernetes orchestrating them all. So that's a capability we call open source virtualization. We've introduced that and made that generally available within our platform. Another one, which I think Joe starting to touch on a little bit here, is both around this notion of Ansible, as well as advanced cluster management. And say, once technologies like Ansible are familiar to our customers, how about if we find ways to introduce things like the operator framework to help support people's use of Ansible and introduce technologies like advanced cluster management, which allows for us to say, well, regardless of where you run your clusters, whether you run your Kubernetes clusters on premise, you run them in the cloud, right, we can imagine a consistent fashion and manage, you know, health and policy and compliance of applications across that entire state. So David, question's extremely good one, right, but what we are trying to do is try to be able to say, you know, we are going to just span those two worlds and provide as many tools as possible to ensure that customers feel like, you know, the shift, if you will, or the move between traditional enterprise software application development and the more modern cloud native can be bridged as seamlessly as possible. >> Yeah, Joe, we heard a lot of this at AnsibleFest, so the ACM as a key component of your innovation, and frankly, your competitive posture. Anything you would add to what Ashesh just shared? >> Well, I think that one of the things that Red Hat is really good at is we take management and automation as sort of an intrinsic part of what needs to go on. It's not an afterthought. You just don't go build something, go, "Oh I need management," go out and, you know, go get something, right, so we've been working on, sort of automation and management for many, many years, right, so we build it in concert with these platforms, right, and we understand the physics of these different environments, so we're very focused on that from inception, as opposed to an afterthought when people sort of paint themselves into a corner or have management challenges they can't deal with. >> There's a lot of analogs in our business, isn't there? Management is a bolt-on and security is a bolt-on. It just doesn't work that well and certainly doesn't scale. Stefanie, I want to come back to you and I want to come back to the edge. We hear a lot of people talking about extending their deployments to the edge in the future. I mean, you look at what IBM's doing. They're essentially betting its business on RHEL and OpenShift and betting that its customers are going to do the same as well are you. Maybe talk about, you know, what you're doing to specifically extend RHEL to the edge. >> Yeah, Dave, so we've been looking at this space consistent with our strategy, as Ashesh talked about, right? Our goal is to make sure that it all looks and feels the same and provides one single Linux experience. We've been building on a number of those aspects for quite some time, things like being able to deal with heterogeneous architectures, as an example, being able to deal with, you know, having Arm components and x86 components and power components and being able to leverage all of that from multiple vendors and being able to deploy. Those are things we've been focused on for a long time and now when you move into the space of the edge, certainly we're seeing, you know, essentially data center level hardware move out to be dis-aggregated and dispersed as they move it closer to the data and where that's coming in and where the analysis needs to be done, but some of those foundational things that we've been working on for years starts to pay off because the edge tends to be more heterogeneous all the way from an architecture level to an application level, so now we're seeing some asks. We've been working upstream in order to pull in some features that drive capabilities around specifically updating, deploying those updates, doing rollbacks and things like that, so we're focused on that. But really, it's about pulling together the capabilities of having multiple architectures, dealing with heterogeneous infrastructure out there at the edge, being able to reliably deploy it even when, for example, we have customers who they deploy their hardware and they can't touch it for years. How do they make sure that that's out there in a stable environment that they can count on? And then, you know, adding in things like containerization. We talked about the magic of that, being able to deploy an application consistently and being able to deploy a single container out there to the edge. We're thinking about it all the way from the architecture up to how the application gets deployed and it's going to take the whole portfolio to do that as you need to manage it, as you need to deploy containers, so it's a focus across the company for how we deal with that. >> And as we were talking about before, you know, it takes a village. You know that bromide, but it does, requires an ecosystem of jobs. I mean, there's some real technical challenges in R&D that has to happen. I mean, you've got to be, you know, you're talking about cloud native in all three different clouds, and you know, and not just the big three, but other clouds and then bringing that to the edge, so there's some clear technical challenges, but there's also some business challenges out there. So you know, what are you seeing in that regard? You know, what are some of those things that you hope to solve by bridging that gap? >> Well, I think one of the things we're trying to do and I'm focused on the management and automation side is to provide a common set of management tooling of automation, right, and I think Ansible fits that quite well. So for the past five years since Ansible's been part of Red Hat, we've expanded from, you know, they started off initially doing configuration management, right? We've expanded to include, you know, network and storage and security, now edge. At AnsibleFest, we demonstrated things like serverless event-driven automation, right, building an OpenShift serverless in Knative. We're trying to expand the use cases for Ansible so that there's a simplicity, there's a tool reduction, right, across all these environments and you don't have to go deal with nine vendors, and you know, 17 different tools to try to manage each element here to be able to provide a common set. It reduces complexity, cost and allows skills to be able to be reused across these different areas. It's going to all be about digital acceleration, right, and reducing that complexity. And one last comment. One of the reasons we bought Ansible years ago is the architecture, it's agent-less. Many of our competitors that you hear, the first thing they want to do is go deploy an agent somewhere and that creates its own ongoing burden of, do I have the latest version of the agent? Is it secure? Does it fit on the device? As Stefanie mentioned, is there a version that fits on the architecture the device is running on? It starts getting really, really complicated. So Ansible is just simple, elegant, agent-less. We've expanded the domains we can automate with it and we've expanded sort of the modality. How can I call it? User, driven by an event, as part of some life cycle management, app deployment, Ansible plugs right in. >> Well, Joe, you can tell you're a management guy, right? Agents, another thing that has to be managed. You just laundry list of stuff. (laughs) I want to come back to this notion Joe just touched on, this digital transformation. They say, "If it ain't broke, don't fix it." Well, COVID broke everything. And I got to say, I mean, all the talk about digital transformation over the last, you know, several years, yes, it was certainly happening, but there was also a lot of lip service going on and now if you're not digital, you're out of business. And so, you know, given everything that we've seen in the last, you know, whatever, 150, 200 days or so, what's the impact that you're seeing on customers' digital transformation initiatives, and you know, what is Red Hat doing to respond? Maybe Ashesh, you could start and we can get feedback from the others. >> Yeah, David, it's an unfortunate thing to say, right, but there's that meme going around with regard to who's responsible for digital transformation and it's a little bit of I guess gallows humor to call it COVID, but we're increasingly seeing that customers and the journey that they're on is one that they haven't really gotten off, even with this, if you will, change of environment that's come about. So projects that we've seen in play, you know, are still underway. We've seen acceleration, actually, in some places with regard to making services more easily accessible. Anyone who's invested in hybrid cloud or public cloud is seeing huge value with regard to being able to consume services remotely, being able to do this on demand and that's a big part of the value proposition, you know, that comes forward. And increasingly what we're trying to do is try to say, how can we engage and assist you in these times, right? So our services team, for example, has transformed to be able to help customers remotely. Our support team has gone off and work more and more with customers. For a company like Red Hat, that hasn't been completely, if you will, difficult thing to do mostly because we've been so used to working in a distributed fashion, working remotely with our customers, so that's not a challenge in itself, but making sure customers understand that this is really a critical journey for them to go on and how we can kind of help them, you know, walk through that has been good and we're finding that that message really resonates. Right, so both Stefanie and Joe talked a little bit about, you know, how essentially our entire portfolio is now built around, you know, ensuring that if you'd like to consume on demand, we can help support you, if you'd like to consume in a traditional fashion, we can help you. That amount of flexibility that we provide to customers is really coming to bear at this point in time. >> So maybe we could wrap with, we haven't really dropped any customer names. Stefanie and Joe and Ashesh, I wonder if you have any stories you can share or, you know, customer examples that we could close on that are exciting to you this year. >> So I can start, if that's okay. >> Please. >> So an area that I find super interesting from a customer perspective that we're increasingly seeing more and more customers go down is sheer interest in, if you will, kind of diversity of use cases that we're seeing, right? So we see this, for example, in automotive, right? So whether it's a BMW or a Volkswagen, we see this now in health care with the ACA, in we'll say a little bit more traditional industries like energy with Exxon or Schlumberger around increasingly embrace of AIML, right? So artificial machine learning, if you will, advanced analytics being much more proactive with regard to how they can take data that's coming in, adjust it, be able to make sense of the patterns and then be able to, you know, have some action that has real business impact. So this whole trend towards, you know, AIML workloads that they can run is extremely powerful. We work very closely with Nvidia, as well, and we're seeing a lot of interest, for example, in being able to run a Kubernetes-based platform, support Nvidia GPUs for specific class workloads. There's a whole bunch of customers, people in financial services that, you know, this is a rich area of interest. You know, we've seen great use cases for example around grid with Deutsche Bank. And so, to me, I'm personally really excited to see kind of that embrace the PC from our customers regard to saying there's a whole lot of data that's out there. You know, how can we essentially use all of these tools that we have in place? You know, we talk about containers, microservices, DevOps, you know, all of this and then put it to bear to really put to work and get business value. >> Great, thank you for that, Ashesh. Stefanie, Joe, Stefanie, anything you want to add or final thoughts? >> Yeah, just one thing to add and I think Ashesh talked to a whole number across industry verticals and customers. But I think the one thing that I've seen through COVID is that if nothing else, it's taught us that change is the only constant and I think, you know, our whole vision of open hybrid cloud is how to enable customers to be flexible and do what they need to do when they need to do it, wherever they want to deploy, however they want to build. We provide them some consistency, right, across that as they make those changes and I think as I've worked with customers here through since the beginning of COVID, it's been amazing to me the diversity of how they've had to respond. Some have doubled down in the data center, some have doubled down on going public cloud and to me, this is the proof of the strategy that we're on, right, that open hybrid cloud is about delivering flexibility, and boy, nothing's taught us the need for flexibility like COVID has recently, so I think there's a lot more to do. I think pulling together the platforms and the automation is what is going to enable the ability to do that in a simple fashion. >> So Joe, you get the final word. I mean, AnsibleFest 2020, I mean, it's weird, right? But that's the way these events are, all virtual. Hopefully, next year we got a shot at being face to face, but bring us home, please. >> Yeah, I got to tell ya, having, you know, 20,000 or so of your closest friends get together to talk about automation for a couple of days is just amazing. That just shows you sort of the power of it. You know, we have a lot of customers this week at AnsibleFest telling you their story, you know, CarMax and ExxonMobil, you know, BlueCross BlueShield. I mean, there's a number across all different verticals, globally, Cepsa from Europe. I mean, just an incredibly, you know, diverse array of customers and use cases. I would encourage people to look at some of the customer presentations that were on at AnsibleFest, listen to the customer telling you what they're doing with Ansible, deploying their networks, deploying their apps, managing their infrastructure, container apps, traditional apps, connecting it, moving faster. They have amazing stories. I encourage people to go look. >> Well, guys, thanks so much for helping us wrap up AnsibleFest 2020. It was really a great discussion. You guys have always been awesome CUBE guests. Really appreciate the partnership and so thank you. >> Thanks a lot, Dave. Appreciate it. >> Yeah, thanks, Dave. >> Thanks for having us. >> All right, and thank you for watching, everybody. This is Dave Vellante for theCUBE and we'll see you next time. (calm music)

>> Hello and welcome to the session featuring CarMax, driving efficiency and innovation with Ansible. I'm your host Christian Emery. I've been at CarMax for over 18 years in several roles ranging from operations to engineering. And in my current role, I'm responsible for CarMax's private cloud and continuous integration, continuous delivery pipelines. Now, my journey with automation started many years ago when I was a Unix and a Linux admin. Day after day, there was always that routine of manual tasks and processes like backups and routine maintenance. Each tasks had a lot of value to the business, but also required consistency, reliability and completion, and demanded quality for system stability. However, it was really boring to carry out the same thing every day. And personally I had a hunger to do more, bring greater value to the business, and need to realize greater satisfaction through my contributions in my career. And this is where automation came into my life. But before we jump into the presentation, I do want to share a little bit about CarMax. For those who may not know, CarMax has been a unique force in the used car industry since 1993. Through innovation and integrity, we've revolutionized the way people buy and sell used cars. We pride ourselves on the experience we provide our customers and our associates to make it possible. And by changing the way we assist our customers, we've also changed the journey of our associates, providing careers in exciting collaborative work environments. In today's presentation, I'm going to cover the early chapters of the CarMax Ansible story. Topics discussed will highlight business need, why we selected Ansible, rapid adoption and our results. And throughout the presentation, I'm also going to share a lot of thoughts and lessons learned to help you with your automation journey. And while listening to the story, I'd like to challenge you to think about your own business needs, technology challenges, and how your team organizes or organization improves approaches automation. Now in our first year, I was challenged to achieve 5,000 hours in efficiency using Ansible. That was a really intimidating number. But we met the challenge and exceeded it. And since then, we've continued to expand our automation through incremental improvements in everyday work to tackling larger operational challenges like regular changes to the environment, routine upgrades and improved infrastructure delivery. Additionally, we expanded automation adoption across multiple teams. We increased our user and contributor base by over five times. And some of that growth was through organic cross team collaboration. However, the greatest growth we had seen was through hackathons, innovation days where we're able to actively collaborate with other teams using Ansible to solve a business problem. And across all those users, we crossed over 15,000 hours of efficiency gain. And I use that term efficiency gained as a measurement to show not only just labor savings, but also tell the story behind other work we accomplished. And keep in mind, this is work that we wouldn't have been able to achieve without automation. And through that user base and hours of efficiency realized, we implemented over 150,000 successful changes. So how do we get there? Earlier I told you about my personal interest in automation and how I've carried that into my current role. And as a leader, I challenge my team to standardize processes and automate as much as possible. We started initially with really repetitive tasks, much like a game of whack-a-mole, but more importantly, through our experimentation, we quickly found we could get better and more consistent results. We soon applied the same approach to our automation for even greater success. But before Ansible, we started to run into issues where team members were taking a more siloed approach to the work. And in an early retrospective, we came to realize that there is a need for a bigger picture mindset. And from that point on, we agreed to standards to increase quality in our code. However, we still occasionally ran into quality issues. Some of these challenges were from homegrown technology, lack of integration and general infrastructure. Now, this is all compounded by the fact that we were using different scripting and programming languages, and not everyone on the team was familiar with Python when compared to say Bash or PowerShell. And while our homegrown solutions made a difference, we thought there could be better ways to meet that demand from the business to do more, better and faster. But like most things in technology, there's always a different tool and approach to get something done. However, some of these other tools required agents on servers making a deployment, a major effort on its own. And additionally, the learning curve was steeper for systems admins and engineers that don't have as much development experience. But this is where Ansible came into the picture. It was easy to use with human readable code. It was an agentless solution allowing us to get started without as much ramp up time. We also liked the fact that it was built on an open standard and a growing user community with an increasing engagement base from partner in vendor integrators. Even better, it had an API we could use to integrate our other platforms as needed. Most recently with the introduction of Ansible collections, we can use community content with greater focus on our automation while worrying less about building new tools. Now, once we select an Ansible as our automation platform, we took a three part approach to implementation and building a foundation for its use. And as I discuss each of these areas, I just like you to consider how to best prepare your teams or organizations for using Ansible. And while planning the transformation, be sure to identify any sort of constraints, roadblocks, and how you plan to measure those results. People, arguably people are the most important part of the equation. You can have all the processes and ways to measure return, but at the end of the day, you need your teams to make that work happen. Start by asking yourself, how well does the team handle change? Are there resource challenges with aligning people and work? Do the people have the right level of knowledge? Do they need training? And how do you start with one team to quickly begin or expand automation? Processes, documentation, standards. Processes are those great ingredients for success in any technology organization. How well are your existing processes documented? Are there any sort of defined standards methods to approaching work? What about your environments? How well does your organization handle executing processes or changes? And lastly, technology. We always need to show results for our investments and technology can help us show that math. Does your organization use metrics and measurements to track progress and results? How do you define or measure success for a project? How should return on investment be measured or quantified? Like I mentioned before, I can't stress it enough, your people, your teams are the most important part of implementing Ansible. They'll be responsible for implementing and developing, maintaining the platform as well as following standards to execute that transformation. And to be successful, they need to have tools, environments, and knowledge. But one of the great things about Ansible is its comparatively easy learning curve. Ansible playbooks are written in a human readable markup language. And I found that most systems admins and engineers are able to pick up Ansible relatively quickly. And for our adoption, some folks were able to pick it up and begin development, while others were a little bit more comfortable and confident with just a little bit of training. Now, Ansible also democratizes technology, freeing up admins and engineers from traditional OS defined silos. Additionally, Ansible playbooks can be consumed by teams without explicit knowledge of the systems or the underlying technology. That's only if a playbook is well written and returns consistent results each time. For us, we first used Ansible to improve our delivery and reduce repeatable manual tasks. Then we turned our attention to shifting left self-service and we're now focused on enabling developers by getting out of the way. These improvements afforded our teams more time to deliver new capabilities to the business. But another benefit to that is teams were able to devote more time to learning and experimenting. When teams first started automating, there's always that impulse or need to go after that biggest win. I would always caution folks to start simple, find small wins to build that experience. These incremental gains are going to feel small, but they quickly add up over time. And as you're going to see, the work should always be done in those smaller increments to return value faster while allowing the ability to quickly make corrections or change course all together. Now, another huge benefit of using that smaller code increment is reuse. These smaller building blocks can and will be used time and time again, reducing future development efforts. And as we quickly learned, one of the best places to start with automation are documented processes. Each step in a process is already documented, it's a huge opportunity to convert it to code and step through those manual processes. And at CarMax, one of the first places we started out was our server checklist process. The process was really thorough, had over a hundred steps to validate systems, make sure they have the right configuration security and specs for each build. And while that process really gave us good consistent results, it was time consuming. It was also prone to human error. But once we automated each of those steps in validations, we were able to turn our focus to the next bottleneck in the process to speed up delivery. And this is why it's always important to strive for quality through consistent predictable results. Automation is just another tool to help make that vision a reality. And when working with teams, it's also important to understand development best practices, keep it simple, and always use version control with code. Better yet, if you're from an ops background, I'd say partner with your development teams to help with this part of the journey. And lastly, when it comes to integrations between platforms and systems, use a modular design, be flexible because technology changes, and over time, so are your integrations. And when it comes to Ansible or just automation in general, there's always that need for efficiency, consistency, reliability, and flexible integrations. And to make this become a reality, you really need to take both a low tech and a high tech approach. If you recall earlier, I mentioned starting with documented processes. That low tech road involves using process mapping value stream analysis tools where you lay out processes end to end to determine the amount of time it takes to execute a process. These processes can be mapped out using whiteboard, sticky notes or by software tools. And from there, more importantly, you can visualize the process bottlenecks and the areas of improvement should be pretty visible. So for CarMax, what we did was we mapped out our infrastructure delivery. We found it was a huge opportunity. But it was also an area we were more comfortable automating given our deep knowledge of the process. So years ago, when we started the process, our time to deliver virtual environments was about two days. Fast forward to now, we can consistently deliver the same infrastructure in just minutes. And in turn, we reuse portions of that process and code for OS refreshes, virtual machine rehydration, system recovery and hypervisor upgrades, just to name a few. And by freeing up team members to do more knowledge work and spend less time on operations, we're able to pivot more resources on the team to align with the business on strategic initiatives. Team members also had more time to do training, research and development for new capabilities, and other areas for future innovation. Now, Ansible gave us a tool where we need to think more like a DevOps organization. And admittedly, a lot of what I've talked about so far has been very operation centric, but systems engineers were all of a sudden writing a testing code, building tools, delivering infrastructure via code, pipelines and API integrations. And as a result, we instantly had to build and strengthen the collaborative relationship between traditional development and operations teams, we had to break down those silos. But the developers appreciate it because they can focus on developing code and not necessarily worry about environments being ready in time or configured correctly. Conversely, operations teams can be focused more on improvements, new capabilities, and spending less time on firefighting. But regardless of the outcomes, you need data to tell that story. And these data elements can start with the hard numbers from reduced cycle times when we were mapping out processes, you can use delivery and SLA metrics. Those were some easy go to numbers. But also consider how you tell that efficiency story. And remember, ROI isn't always about money or the time savings. So as an example, metrics we used included the number of teams using the platform, active contributors, workflows, processes run, and efficiency gain calculations. And as we evolve our journey, the metrics may change along with that story that we need to tell. So to recap, at CarMax, we put people first and you should too. Think about the resources and knowledge your teams are going to need to be successful. And like I said earlier, remember to start small, reuse code as much as possible. This is going to help teams realize faster return on their efforts and start that snowball effect where gains quickly compound over time. Have a vision and decide on targeted outcomes for your team or organization. Then build ROI metrics to help tell that story. But a big part of innovation is experimenting and learning from mistakes. So take a chance, try something new. And in closing, I'd like to thank you for your time. I sincerely hope our results and lessons learned will help you on your automation journey wherever it takes you.