>> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (ambient music) >> Lisa: Hey everyone, welcome back to Barcelona, Spain. It's theCUBE Live at MWC 23. Lisa Martin with Dave Vellante. This is day two of four days of cube coverage but you know that, because you've already been watching yesterday and today. We're going to have a great conversation next with EnterpriseWeb and Red Hat. We've had great conversations the last day and a half about the Telco industry, the challenges, the opportunities. We're going to unpack that from this lens. Please welcome Dave Duggal, founder and CEO of EnterpriseWeb and Azhar Sayeed is here, Senior Director Solution Architecture at Red Hat. >> Guys, it's great to have you on the program. >> Yes. >> Thank you Lisa, >> Great being here with you. >> Dave let's go ahead and start with you. Give the audience an overview of EnterpriseWeb. What kind of business is it? What's the business model? What do you guys do? >> Okay so, EnterpriseWeb is reinventing middleware, right? So the historic middleware was to build vertically integrated stacks, right? And those stacks are now such becoming the rate limiters for interoperability for so the end-to-end solutions that everybody's looking for, right? Red Hat's talking about the unified platform. You guys are talking about Supercloud, EnterpriseWeb addresses that we've built middleware based on serverless architecture, so lightweight, low latency, high performance middleware. And we're working with the world's biggest, we sell through channels and we work through partners like Red Hat Intel, Fortnet, Keysight, Tech Mahindra. So working with some of the biggest players that have recognized the value of our innovation, to deliver transformation to the Telecom industry. >> So what are you guys doing together? Is this, is this an OpenShift play? >> Is it? >> Yeah. >> Yeah, so we've got two projects right her on the floor at MWC throughout the various partners, where EnterpriseWeb is actually providing an application layer, sorry application middleware over Red Hat's, OpenShift and we're essentially generating operators so Red Hat operators, so that all our vendors, and, sorry vendors that we onboard into our catalog can be deployed easily through the OpenShift platform. And we allow those, those vendors to be flexibly composed into network services. So the real challenge for operators historically is that they, they have challenges onboarding the vendors. It takes a long time. Each one of them is a snowflake. They, you know, even though there's standards they don't all observe or follow the same standards. So we make it easier using models, right? For, in a model driven process to on boards or streamline that onboarding process, compose functions into services deploy those services seamlessly through Red Hat's OpenShift, and then manage the, the lifecycle, like the quality of service and the SLAs for those services. >> So Red Hat obviously has pretty prominent Telco business has for a while. Red Hat OpenStack actually is is pretty popular within the Telco business. People thought, "Oh, OpenStack, that's dead." Actually, no, it's actually doing quite well. We see it all over the place where for whatever reason people want to build their own cloud. And, and so, so what's happening in the industry because you have the traditional Telcos we heard in the keynotes that kind of typical narrative about, you know, we can't let the over the top vendors do this again. We're, we're going to be Apifi everything, we're going to monetize this time around, not just with connectivity but the, but the fact is they really don't have a developer community. >> Yes. >> Yet anyway. >> Then you have these disruptors over here that are saying "Yeah, we're going to enable ISVs." How do you see it? What's the landscape look like? Help us understand, you know, what the horses on the track are doing. >> Sure. I think what has happened, Dave, is that the conversation has moved a little bit from where they were just looking at IS infrastructure service with virtual machines and OpenStack, as you mentioned, to how do we move up the value chain and look at different applications. And therein comes the rub, right? You have applications with different requirements, IT network that have various different requirements that are there. So as you start to build those cloud platform, as you start to modernize those set of applications, you then start to look at microservices and how you build them. You need the ability to orchestrate them. So some of those problem statements have moved from not just refactoring those applications, but actually now to how do you reliably deploy, manage in a multicloud multi cluster way. So this conversation around Supercloud or this conversation around multicloud is very >> You could say Supercloud. That's okay >> (Dave Duggal and Azhar laughs) >> It's absolutely very real though. The reason why it's very real is, if you look at transformations around Telco, there are two things that are happening. One, Telco IT, they're looking at partnerships with hybrid cloud, I mean with public cloud players to build a hybrid environment. They're also building their own Telco Cloud environment for their network functions. Now, in both of those spaces, they end up operating two to three different environments themselves. Now how do you create a level of abstraction across those? How do you manage that particular infrastructure? And then how do you orchestrate all of those different workloads? Those are the type of problems that they're actually beginning to solve. So they've moved on from really just putting that virtualizing their application, putting it on OpenStack to now really seriously looking at "How do I build a service?" "How do I leverage the catalog that's available both in my private and public and build an overall service process?" >> And by the way what you just described as hybrid cloud and multicloud is, you know Supercloud is what multicloud should have been. And what, what it originally became is "I run on this cloud and I run on this cloud" and "I run on this cloud and I have a hybrid." And, and Supercloud is meant to create a common experience across those clouds. >> Dave Duggal: Right? >> Thanks to, you know, Supercloud middleware. >> Yeah. >> Right? And, and so that's what you guys do. >> Yeah, exactly. Exactly. Dave, I mean, even the name EnterpriseWeb, you know we started from looking from the application layer down. If you look at it, the last 10 years we've looked from the infrastructure up, right? And now everybody's looking northbound saying "You know what, actually, if I look from the infrastructure up the only thing I'll ever build is silos, right?" And those silos get in the way of the interoperability and the agility the businesses want. So we take the perspective as high level abstractions, common tools, so that if I'm a CXO, I can look down on my environments, right? When I'm really not, I honestly, if I'm an, if I'm a CEO I don't really care or CXO, I don't really care so much about my infrastructure to be honest. I care about my applications and their behavior. I care about my SLAs and my quality of service, right? Those are the things I care about. So I really want an EnterpriseWeb, right? Something that helps me connect all my distributed applications all across all of the environments. So I can have one place a consistency layer that speaks a common language. We know that there's a lot of heterogeneity down all those layers and a lot of complexity down those layers. But the business doesn't care. They don't want to care, right? They want to actually take their applications deploy them where they're the most performant where they're getting the best cost, right? The lowest and maybe sustainability concerns, all those. They want to address those problems, meet their SLAs meet their quality service. And you know what, if it's running on Amazon, great. If it's running on Google Cloud platform, great. If it, you know, we're doing one project right here that we're demonstrating here is with with Amazon Tech Mahindra and OpenShift, where we took a disaggregated 5G core, right? So this is like sort of latest telecom, you know net networking software, right? We're deploying pulling elements of that network across core, across Amazon EKS, OpenShift on Red Hat ROSA, as well as just OpenShift for cloud. And we, through a single pane of deployment and management, we deployed the elements of the 5G core across them and then connected them in an end-to-end process. That's Telco Supercloud. >> Dave Vellante: So that's an O-RAN deployment. >> Yeah that's >> So, the big advantage of that, pardon me, Dave but the big advantage of that is the customer really doesn't care where the components are being served from for them. It's a 5G capability. It happens to sit in different locations. And that's, it's, it's about how do you abstract and how do you manage all those different workloads in a cohesive way? And that's exactly what EnterpriseWeb is bringing to the table. And what we do is we abstract the underlying infrastructure which is the cloud layer. So if, because AWS operating environment is different then private cloud operating environment then Azure environment, you have the networking is set up is different in each one of them. If there is a way you can abstract all of that and present it in a common operating model it becomes a lot easier than for anybody to be able to consume. >> And what a lot of customers tell me is the way they deal with multicloud complexity is they go with mono cloud, right? And so they'll lose out on some of the best services >> Absolutely >> If best of, so that's not >> that's not ideal, but at the end of the day, agree, developers don't want to muck with all the plumbing >> Dave Duggal: Yep. >> They want to write code. >> Azhar: Correct. >> So like I come back to are the traditional Telcos leaning in on a way that they're going to enable ISVs and developers to write on top of those platforms? Or are there sort of new entrance and disruptors? And I know, I know the answer is both >> Dave Duggal: Yep. >> but I feel as though the Telcos still haven't, traditional Telcos haven't tuned in to that developer affinity, but you guys sell to them. >> What, what are you seeing? >> Yeah, so >> What we have seen is there are Telcos fall into several categories there. If you look at the most mature ones, you know they are very eager to move up the value chain. There are some smaller very nimble ones that have actually doing, they're actually doing something really interesting. For example, they've provided sandbox environments to developers to say "Go develop your applications to the sandbox environment." We'll use that to build an net service with you. I can give you some interesting examples across the globe that, where that is happening, right? In AsiaPac, particularly in Australia, ANZ region. There are a couple of providers who have who have done this, but in, in, in a very interesting way. But the challenges to them, why it's not completely open or public yet is primarily because they haven't figured out how to exactly monetize that. And, and that's the reason why. So in the absence of that, what will happen is they they have to rely on the ISV ecosystem to be able to build those capabilities which they can then bring it on as part of the catalog. But in Latin America, I was talking to one of the providers and they said, "Well look we have a public cloud, we have our own public cloud, right?" What we want do is use that to offer localized services not just bring everything in from the top >> But, but we heard from Ericson's CEO they're basically going to monetize it by what I call "gouge", the developers >> (Azhar laughs) >> access to the network telemetry as opposed to saying, "Hey, here's an open platform development on top of it and it will maybe create something like an app store and we'll take a piece of the action." >> So ours, >> to be is a better model. >> Yeah. So that's perfect. Our second project that we're showing here is with Intel, right? So Intel came to us cause they are a reputation for doing advanced automation solutions. They gave us carte blanche in their labs. So this is Intel Network Builders they said pick your partners. And we went with the Red Hat, Fort Net, Keysite this company KX doing AIML. But to address your DevX, here's Intel explicitly wants to get closer to the developers by exposing their APIs, open APIs over their infrastructure. Just like Red Hat has APIs, right? And so they can expose them northbound to developers so developers can leverage and tune their applications, right? But the challenge there is what Intel is doing at the low level network infrastructure, right? Is fundamentally complex, right? What you want is an abstraction layer where develop and this gets to, to your point Dave where you just said like "The developers just want to get their job done." or really they want to focus on the business logic and accelerate that service delivery, right? So the idea here is an EnterpriseWeb they can literally declaratively compose their services, express their intent. "I want this to run optimized for low latency. I want this to run optimized for energy consumption." Right? And that's all they say, right? That's a very high level statement. And then the run time translates it between all the elements that are participating in that service to realize the developer's intent, right? No hands, right? Zero touch, right? So that's now a movement in telecom. So you're right, it's taking a while because these are pretty fundamental shifts, right? But it's intent based networking, right? So it's almost two parts, right? One is you have to have the open APIs, right? So that the infrastructure has to expose its capabilities. Then you need abstractions over the top that make it simple for developers to take, you know, make use of them. >> See, one of the demonstrations we are doing is around AIOps. And I've had literally here on this floor, two conversations around what I call as network as a platform. Although it sounds like a cliche term, that's exactly what Dave was describing in terms of exposing APIs from the infrastructure and utilizing them. So once you get that data, then now you can do analytics and do machine learning to be able to build models and figure out how you can orchestrate better how you can monetize better, how can how you can utilize better, right? So all of those things become important. It's just not about internal optimization but it's also about how do you expose it to third party ecosystem to translate that into better delivery mechanisms or IOT capability and so on. >> But if they're going to charge me for every API call in the network I'm going to go broke (team laughs) >> And I'm going to get really pissed. I mean, I feel like, I'm just running down, Oracle. IBM tried it. Oracle, okay, they got Java, but they don't they don't have developer jobs. VMware, okay? They got Aria. EMC used to have a thing called code. IBM had to buy Red Hat to get to the developer community. (Lisa laughs) >> So I feel like the telcos don't today have those developer shops. So, so they have to partner. [Azhar] Yes. >> With guys like you and then be more open and and let a zillion flowers bloom or else they're going to get disrupted in a big way and they're going to it's going to be a repeat of the over, over the top in, in in a different model that I can't predict. >> Yeah. >> Absolutely true. I mean, look, they cannot be in the connectivity business. Telcos cannot be just in the connectivity business. It's, I think so, you know, >> Dave Vellante: You had a fry a frozen hand (Dave Daggul laughs) >> off that, you know. >> Well, you know, think about they almost have to go become over the top on themselves, right? That's what the cloud guys are doing, right? >> Yeah. >> They're riding over their backbone that by taking a creating a high level abstraction, they in turn abstract away the infrastructure underneath them, right? And that's really the end game >> Right? >> Dave Vellante: Yeah. >> Is because now, >> they're over the top it's their network, it's their infrastructure, right? They don't want to become bid pipes. >> Yep. >> Now you, they can take OpenShift, run that in any cloud. >> Yep. >> Right? >> You can run that in hybrid cloud, enterprise web can do the application layer configuration and management. And together we're running, you know, OSI layers one through seven, east to west, north to south. We're running across the the RAN, the core and the transport. And that is telco super cloud, my friend. >> Yeah. Well, >> (Dave Duggal laughs) >> I'm dominating the conversation cause I love talking super cloud. >> I knew you would. >> So speaking of super superpowers, when you're in customer or prospective customer conversations with providers and they've got, obviously they're they're in this transformative state right now. How, what do you describe as the superpower between Red Hat and EnterpriseWeb in terms of really helping these Telcos transforms. But at the end of the day, the connectivity's there the end user gets what they want, which is I want this to work wherever I am. >> Yeah, yeah. That's a great question, Lisa. So I think the way you could look at it is most software has, has been evolved to be specialized, right? So in Telcos' no different, right? We have this in the enterprise, right? All these specialized stacks, all these components that they wire together in the, in you think of Telco as a sort of a super set of enterprise problems, right? They have all those problems like magnified manyfold, right? And so you have specialized, let's say orchestrators and other tools for every Telco domain for every Telco layer. Now you have a zoo of orchestrators, right? None of them were designed to work together, right? They all speak a specific language, let's say quote unquote for doing a specific purpose. But everything that's interesting in the 21st century is across layers and across domains, right? If a siloed static application, those are dead, right? Nobody's doing those anymore. Even developers don't do those developers are doing composition today. They're not doing, nobody wants to hear about a 6 million lines of code, right? They want to hear, "How did you take these five things and bring 'em together for productive use?" >> Lisa: Right. How did you deliver faster for my enterprise? How did you save me money? How did you create business value? And that's what we're doing together. >> I mean, just to add on to Dave, I was talking to one of the providers, they have more than 30,000 nodes in their infrastructure. When I say no to your servers running, you know, Kubernetes,running open stack, running different components. If try managing that in one single entity, if you will. Not possible. You got to fragment, you got to segment in some way. Now the question is, if you are not exposing that particular infrastructure and the appropriate KPIs and appropriate things, you will not be able to efficiently utilize that across the board. So you need almost a construct that creates like a manager of managers, a hierarchical structure, which would allow you to be more intelligent in terms of how you place those, how you manage that. And so when you ask the question about what's the secret sauce between the two, well this is exactly where EnterpriseWeb brings in that capability to analyze information, be more intelligent about it. And what we do is provide an abstraction of the cloud layer so that they can, you know, then do the right job in terms of making sure that it's appropriate and it's consistent. >> Consistency is key. Guys, thank you so much. It's been a pleasure really digging through EnterpriseWeb. >> Thank you. >> What you're doing >> with Red Hat. How you're helping the organization transform and Supercloud, we can't forget Supercloud. (Dave Vellante laughs) >> Fight Supercloud. Guys, thank you so much for your time. >> Thank you so much Lisa. >> Thank you. >> Thank you guys. >> Very nice. >> Lisa: We really appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage coming to you live from MWC 23. We'll be back after a short break.

>>Welcome everyone. I'm Dave Nicholson with the cube. This is a special Q conversation. That is part of the AWS startup showcase. Season two. Got a very interesting conversation on deck with Steve Francis who joins us from Instaclustr. Steve is the chief revenue officer and executive vice president for go-to-market operations for Insta cluster. Steve, welcome to the cube. >>Thank you, Dave. Good to be here. >>It looks like you're on a, uh, you're you're you're coming to us from an exotic locale. Or do you just like to have a nautical theme in your office? >>No, I'm actually on my boat. I have lots of kids at home and, uh, it can be very noisy. So, uh, we call this our apartment in the city and sometimes when we need a quiet place, this, this does nicely >>Well, fantastic. Well, let's, let's talk about Instaclustr. Um, first give us, give us a primmer on Instaclustr and, uh, and what you guys do. And then let's double click on that and go into some of the details. >>Sure. So in sip cluster, we offer a SAS platform for data layer, open source technologies. And what those technologies have in common is they scale massively. We re curate technologies that are capable of massive scale. So people use them to solve big problems typically. And so in addition to SAS offerings for those open source projects where people can provision themselves clusters in minutes, um, we also offer support for all of the technologies that we offer on our SAS platform. We offer our customer support contracts as well. And then we have a consulting team, a global consulting team who are expert in all of those open source projects that can help with implementations that can help with design health checks, uh, you name it. So most of what they do is kind of short term expert engagements, but we've also done longer-term projects with them as well. >>So your business model is to be a SAS provider as opposed to an alternative, which would be to, uh, provide what's referred to as, uh, open core software. Is that, is that right? >>Yeah, that's exactly right. So you, so when, when our customers have an interest in using community open source, we're the right partner for them. And so, you know, really what that means is if they, whether it's our SAS platform, if, if they want the flexibility to say, we want to take that workload off of your SAS platform, maybe at some point operated ourselves because we're not throwing a bunch of PROPRICER proprietary stuff in there. They have the flexibility to do that. So they always have an exit ramp without being locked in and with our support customers, of course, it's very easy. What we support is both the open source project. And if there's a gap in that open source project, what we'll do is rather than create a proprietary piece of software to close the gap, we'll source something from the community and we'll support that. Or if it, or if something does not exist in the community, in many cases, we'll write it ourselves and open source it and then, and then support it. >>Yeah, it's interesting. Uh, supposedly Henry Ford made a comment once that if you ask customers what they want, they'll tell you they want a faster horse, uh, but he was inventing the automobile and some people have, have likened open core to sort of the faster mechanical horse version of open source where you're essentially substituting an old school legacy vendor for a new school vendor. That's wrapping their own proprietary stuff around a delicious core of open source, but it sort of diminishes the value proposition of open source. It sounds like that's, that's the philosophy that you have adopted at this point. That's >>I love that story. I haven't heard that before. One that I like, uh, you know, matching metaphor for metaphor, uh, is, uh, the, um, is the Luddites, right? You know, the Luddites didn't want to lose their weaving jobs. And so they would smash weeding looms and, um, you know, to, to protect their reading jobs. And I think it's the same thing with the open core model they're protecting, uh, you know, they're creating fear, uncertainty and doubt about open, open sourcing. Oh, it isn't secure. And, you know, the, those, those arguments have been used for 15 years or 20 years. And, you know, maybe 15 years ago there were some truth to it. But when you look at who is using open source community open source now for huge projects, you know, if you just do a search for Apache coffee users and go to the Apache Apache website, you know, it's kind of the who's who in big business, and these are people using community open source. And so, um, a lot of the fear and uncertainty and doubt is still used, and it's just, you know, it's just kind of hanging on to a business model that isn't really it's for the benefit of the, of the vendor and not the benefit of the customer. >>Well, so I can imagine being a customer and realizing several years into an open core journey that I basically painted myself into a similar corner that I was in before. Um, and so I can see where that, you know, that can be something that is a realization that, that creeps up over time from a customer perspective, but from your business model perspective, um, if I'm understanding correctly, your, when you scale, you're scaling the ability to, um, take over operations for our customer, uh, that, that some level, I'm sure you've got automation involved in this. Uh, but at some level you've got to scale in terms of really smart people, um, has that limited your ability to scale. So first talk about what have the results been. You guys we've been covering you since 2018. What have your results been over time and has that sort of limited that that limit to your scalability, uh, been an issue at all. >>It's hard to find people, uh, it's hard, it's hard for our customers to find people and it's hard for us to find people. So we have an advantage for two reasons. Number one, we have a really good process for hiring people, hiring graduates, recent computer science graduates typically, and then getting them trained up and productive on our platform and within a pretty short timeframe of three or four months. And, um, you know, so we we've, we've, uh, we have a really well-proven process to do that. And then the other thing that you've already alluded to is automation, right? There's a ton of automation built into our platform. So we have a big cost advantage over our customers. So, you know, our, our customers, you know, if they want to go hire a seasoned, you know, Kafka person or PostGrest personal work, a person, these people are incredibly expensive in the market, but for us, we can get those people for relatively less expensive. And then with the automation that we have built into our platform to do all the operational tasks and handle all the operational burdens on those different open source projects, it's a lot of it's automated. And so, uh, you know, where one of our experts can use, you know, the number of workloads that they can operate is usually, you know, many times more than what someone could do without all of the operational capability or all the automated capabilities that we have. >>So what has your, what is your plan for scaling the business look like into the future? Is it a additional investment in those core operators? Uh, are you looking at, uh, uh, expansion, geographically acquisition? What, what can you share with us? >>We've done some acquisition. We added a Postgres capability. We recently added a last, further Alaska search capability and really buttressed our capabilities there. I think we'll do more of that. And, um, we, we will continue to add technologies that we find interesting and, and federal model, usually what we look for technologies that are pretty popular. They're used to solve big problems and they're complicated to manage, right? If something's easy to manage, people are less likely to perceive our value to be that great. So we look for things that, um, you know, are we kind of take the biggest areas, gnarliest, um, open-source projects for people to manage, and we handle the heavy lifting. >>Well, can you give me an example of something like that? You don't have to, you don't have to share a customer name if you don't, if it's not appropriate, but give us a, give us an example of, of Instaclustr inaction pretend I'm the customer. And, uh, and, uh, you know, you mentioned elastic search. Let's say that, let's say that that is absolutely something that's involved. And I have a choice between some open, open core solution and throwing my people at it to manage it, uh, and, and, and operate at the data layer, uh, versus what you would do. What does that interaction look like? How do, how does the process, >>Um, so one thing that we hear from elastic search customers a lot is, uh, their customers, some of them are unhappy. And what they'll tell us is look, when we get an operational problem with Alaska search, we go to Alaska search. And the answer we get from them is we gotta buy, you know, you gotta buy more stuff, you got to add more nodes, and they're in the business of, uh, you know, that's, that's our business. And, uh, you know, they do have a SAS offering, but, um, you know, they're, they're also in the business of selling software. And so when those customers, those same customers come to us, our answer is often, well, Hey, we can help you optimize your environment. And, you know, a lot of times when we onboard people into our platform, they'll achieve cost savings because maybe they weren't on the cloud. Maybe they weren't completely optimized there. And, um, you know, we want to make sure that they get a good operational experience and that's how we felt lock customers in, right. We don't lock them in with code. We make sure that they have a positive experience that we take a lot of that operational stuff off their hands. And so there's just a good natural alignment between what we want to provide that customer and what they ultimately want to consume. Uh, you know, that, that alignment I think is, is uniquely high within our business. >>Well, so how, how have things changed just in the last several years? Obviously, I mean, you know, the, the pandemic has, has affected everything in, in one way or another, but, but in terms of things that live at the data layer being important, um, I mean, just in the last three or four years, the talk of various messaging interfaces and databases has shifted to a degree. Um, what do you see on the horizon? What's, what's, what's, what's getting buzz that maybe didn't get buzz a year ago. What, what, what are you looking for as well? If you're out looking for people with skill sets right now, what are those skill sets you're hiring to? >>I don't hire engineers, right. I run the go to market organization. I hire marketers, salespeople, consultants, but, uh, so it's probably different. I'm maybe not the best person to ask from an engineering standpoint, but, uh, your question about the data layer, um, and how, you know, that's evolving trends that we see it's becoming increasingly strategic. You know, every, there's a couple of buzzwords out there that, you know, for years now, people have been talking about, um, modernization, digital transformation, stuff like that, but, you know, there's, there's a lot to it like digital, you know, every business kind of needs to become a digital business. And as that happens, the amount of data that's produced is, is just as mushrooming, right. You know, the amount of data on the planet doubles about every two years. And so for a lot of applications for a lot of enterprise mission-critical applications, data is the most expensive layer of the application. >>You know, much more expensive than delivering a front end, much more expensive than delivering a military when you just, when you factor in storage, um, uh, just the kind of moving data in and out, you know, data transfer fees, the cost of engineering resources that it's, it's incredibly expensive. So data layers are becoming strategic because organizations are looking at it and realizing, you know, the amount that they're spending on this is eye-popping. And so that's why it's becoming strategic. It's on the radar, just due to the, uh, the size of bills that organizations are looking at. Um, and we could drive those bills down. You know, our value proposition is really simpler. It's a better, faster, cheaper, and we eliminate the license fees. We can, you know, we are operational experts, so we can get people architected in the cloud more efficiently, and probably about a third of the time we save our customers cloud fees. Um, so it's, you know, it's a pretty simple model that some of those things that are strategically more, or are there, sorry, traditionally more tactical or becoming strategic, just because of the scope and scale of them. >>We, uh, we're having this conversation as part of the AWS startup showcase, which basically means that AWS said, Hey, Silicon angle, have your cube guys go talk to these people because we think they're cool. So, um, so why, why, why do they think you're cool? Are you a wholly owned subsidiary of AWS? Did you, did you and your family, uh, uh, exceed the 300 order, uh, Amazon threshold last year? Y what's your relationship with Amazon? >>I bought an elf on the shelf from, I don't know, I don't know why. Um, you know, we're, we're growing fast and we're, we're growing north of 50% last year in 21 and closer to 60%. Um, you know, we certainly, I think, uh, when our customers sign up for our services, you know, Amazon gets more workloads. That's, that's probably a positive thing for Amazon. Um, we're certainly not, you know, there's much, much, much bigger vendors and partners than us that they have, but, uh, but you know, they're, I think they're aware that there's, there's some, some of the smaller vendors like us will grow up to be, you know, the, you know, the bigger vendors of tomorrow. Um, but they've kind of, they've been a great partner. You know, we, we support multiple, we do support multiple clouds, and Amazon's cool with that. You know, we support GCP, we support Azure and kind of give our customers the choice of what clouds they want to run on. Uh, most of our customers do run an Amazon that seems to be sort of a defacto standard, but, um, they haven't been a great partner, >>But, but AWS, it's not a dependency. Uh, if you're, if you're working within the cluster, it doesn't mean that you must be in AWS. >>Nope. We can support customers. Uh, that's a great question. So we can support customers and multiple clouds, and we even support them on prem, right? If they, if organizations that have their own data center, we actually have an on-premise managed service offering. And if that's not a fit, we even have, um, we can offer support contracts, like if they want to do it themselves and do a lot of the heavy lifting and just need sort of a red phone for emergency situations. Uh, we offer 24 by 7, 365 support with 20 minutes service levels for urgent issues. >>So your chief revenue officer, that means that you write the code that runs operations in your system. I'm not smiling, but I'm at, but I'm, but I am actually joking. So that's what the dry sense of humor. Uh, but, but, but seriously, let's talk about the business end of this, right? We have, uh, we have a lot of folks who, uh, who tuned into the queue because of the technology aspect of it, but let's talk about your, your growth trajectory over time. Um, uh, this isn't a drill down. I'm not asking for your, your pipeline, Steve, but, uh, but, but, you know, give us an idea of what that trajectory has looked like. Um, what's going on. >>Yeah. I mean the most recent year, you know, we're, we're getting, uh, to be, um, I, I don't know what I'm permitted to share expect, but I, you know, we've, we've had a lot of growth, you know, if we've won a couple, a couple of hundred percent, our revenue has in the amount of time that I've been here, which is three years, and we're the point now, or pretty good size. Uh, and that gives us, uh, it's cool. It's exciting. You know, we're, we're noticing in the market is people who traded two years ago. People, no one knew who we were. And now we're beginning to talk to some partners, some resellers, some customers, and they will say things like, oh yeah, we've heard of you. We didn't know what you did, but we've heard of you. And, you know, that's, that's fun. That's a great place to be. Uh, you know, it becomes a little bit self-sustaining at that point. And, um, we, you know, we are about to launch, I, it's not a secret because this isn't public preview. So I think >>Was there, I noticed the pause where you're like, can I say this or not? Go ahead and say, go ahead and say, >>Really we, uh, I was trying to think, wait, am I revealing anything here? I shouldn't. But, uh, we did just go public preview, uh, probably a month ago with a project called Aiden's, uh, cadence workflow. Uh, you can actually, um, go to the Instaclustr website and look up cadence. Um, it's run their homepage, or you can, if you want to go to the open source project itself, you can go to cadence, workflow.io. Uh, this is a project that's trending pretty highly on Google. It's got a lot of important movers in the technology business that are using it and having a lot of success with it. Uh, and we're going to be first to market globally with a SAS offering for cadence, port flop. And, um, it's an incredibly exciting project. And it's exciting for us to specifically, because it's a little different, right? It's not, it's a middle tier project that is targeted at developers to increase developer productivity and developer velocity. >>Um, you joked about my being a CRO writing code, but I actually used to be a coder long time ago. I was not very good at it, but what I did enough of it to remember that a lot of what I did as a coder was right. Plumbing code, you know, rather than writing that code that makes the business application function a huge amount of my time as a developer was spent writing, you know, just the plumbing code to make things work and to make it secure and to make a transactional and just all that, you know, kind of nitty gritty code that you gotta do in a nutshell, cadence makes writing that code way easier. So especially for distributed applications that have workflow like capabilities requirements, uh, it's a massive productivity and PR increaser. So it's cool. Exciting for us is now we can, rather than just target data operators, we can actually target developers and engage, not just at the data layer, but kind of at that middle tier as well, and begin to, uh, identify and, um, uh, synergies between the different services that we have and, and our customers will obviously benefit from that. >>So that's a big part of our growth strategy. >>Yeah. So more, more on from a business perspective and a go to market perspective. Um, what is your, what is your go to market strategy or, uh, do you have, do you have a channel strategy? Are you working with partners? >>He is pretty nascent. You know, our go to market strategy for the most part has been, you know, we, uh, pay the Google gods and, and lots of people come to our website and say, they want to talk to us. You know, we talked to them and we get them signed up with, uh, uh, on our, our, our SAS platform or with a support contract or with our consulting team. Um, we also do outbound, you know, we do, we have an inside sales team that does outbound prospecting and we have, um, and we also have some self-service. We have some, some self service customers as well that just, you know, anyone can go to our website, swipe a credit card, sign up for one of our SAS offering and begin, literally get fired up in minutes and PR and using the platform. Uh, so, you know, it's a bit of a mix of high touch, low touch, I think are, you know, we have tons of big logos. >>We know lots and lots of our customers are household name, really big organizations solving big problems. And, um, that's kind of where the bulk of our businesses. And so I think we've been a little more focused there and go to market than we have sort of a know startup selling to startups and the people that just from super developer focused, wanting low touch. So, but I think we need to do better at that part of the market. And we are investing some resources there so that, you know, we're not so lopsided at the high end of the market. We want kind of a, more of a balanced approach because, you know, some of those, some of those, um, younger companies are going to grow up to be big massively successful companies. We've had that, you know, door dash is a tough class, has been a customer of ours for years, and they were not nearly, you know, we, there were a prepayment, there were custom bars, pre pandemic, and we all know what happened to them, uh, during the pandemic. And so, you know, we know there's other door dashes out there. >>Yeah. Yeah. Uh, uh, final question, geography, uh, you guys global. I, uh, I know you're in north America, but, um, what, what, what does that look like for you? Where are you at? >>We're super global. So, you know, in my go-to-market organization, we have sellers in, um, uh, AsiaPac and Europe, you know, multiple in Asia, multiple in Europe, uh, you know, lots of lots in the, in the states, uh, same with marketing, uh, same with engineering, same with our tech ops delivery team. We have most of them, uh, in Australia, which is where we were founded. Uh, but we also have a pretty good sized team, uh, out of Boston and, um, kind of a nascent team, uh, in India as well, to help to tell it, to help them out. So yeah, very much global and, um, you know, getting close to 300 employees, um, you know, when I started, I think we're about 85 to 90, >>That's it, that's an exciting growth trajectory. And, uh, I'm just going to assume, because it just feels awesome to assume it that since you're on a boat and since you were founded in Australia, that that's how you go back and forth to, uh, to visit the most. >>Yeah. Yeah. It takes a while. It takes a while. >>So with that, Steve, I want to say a smooth sailing and, uh, and, uh, thanks for joining us here on the cube. I'm Dave Nicholson. Uh, this has been part of the AWS startup showcase my conversation with Steve Francis of Instaclustr again. Thanks Steve. Stay tuned. >>Thanks very much to you, >>Your source for hybrid tech coverage.

>> Narrator: Live, from Washington, D.C. It's theCube! Covering Boomi World 19. Brought to you by Boomi. >> Welcome back to the Cube's coverage of Boomi World 2019, from D.C. I'm Lisa Martin. John Furrier is my cohost, and we're pleased to be welcome a couple of guests from Accenture, Boomi partner. To my right, we've got Pete Yao, Global Managing Director of Integration, and Laetitia Cailleteau, Accenture's Global Lead for Conversational AI. Welcome, both of you. >> Thank you. It's great to be here. >> Thank you so much. So, big news. You can't go anywhere these days without talking about AI. I mean, there's even commercials on TV, that, you know, any generation knows something about AI. But, Laetitia, let's start with you. Some big news coming out this morning, with what Boomi and Accenture are doing for conversational AI. Give our audience, kind of an overview of what you guys announced this morning. >> So, thank you very much. So, conversational AI is booming in the market. It's at the top of the agenda for a number of our C-Suites. It's a new way to make system more human. So, instead of having to learn the system you can actually speak. Ask them direct question. Have a conversation. And actually, what we are doing, what we announced this morning, is Accenture and Boomi are going to partner together to deliver that kind of services for our client. Much faster. Cause we have the expertise and the know how, of designing those conversational experience, and Boomi, obviously, integrates really fast with Beacon system. And the two, together, can really be accelerating, you know, the value delivered to our client. >> And the technology piece, I just want to sure of something. Cause, you guys are providing a front end, so, real technology, with Boomi. So, it's a together story? >> Yeah, it's definitely a together story. And as you say, we are quite expert in designing those experience on the front end. And Boomi, obviously, kind of powers up the integration in the background. >> So, this is going to be enabler of, something you said a minute ago, is, instead of us humans having to learn the tech the tech's going to learn us. Is that fair to say? >> Very fair to say. That's exactly how we want to see it. And I think we call that trend, radically human systems. So, systems are going to become more radically human as we go on. And conversational AI is one enabler of that. >> Is it going to be empathetic? Like, when, you were saying this morning something I loved, on stage. We've all had these interactions with AI, with bots, whether we're on a dot com site, trying to fix something for our cable provider. Or we're calling into a call center. You're starting to get, your voice changes, your agent! And you want that. Is it going to be able to understand, oh, all right, this person, maybe we need to escalate this. There's anger coming through the voice. Is it going to be able to detect that? >> On voice, you can definitely start detecting tone much better than on text. Cause on texts it's very small snippets. And it's quite difficult to define somebody's mood by one small interaction. Typically, you need a number of interactions to kind of see the build up of the person's emotion. But, on voice, definitely. You know, your intonation definitely defines your state of communication. >> You can tell someone's happy, sad, and then use the text meta data to add to it. This is fascinating, cause we all see Apple with Siri front end. That's a different system. They have a back end to Apple. This is a similar thing. You guys have a solution at Accenture. Can you explain how people engage with Accenture? Cause, the Boomi story is a great announcement, congratulations on that. But still, you can deploy this technology to any back end. Is that right? >> Yeah, to any back end. We have a number of live deployment running at the moment. I think the key thing is, you know, especially in the call center. Call center is an area that has not been invested in for, like decades, yeah. And, very often, the scripts are very inward driven. So they would describe the company's processes rather than think about the end user. So, what we do in Accenture, is we try to reinvent the experience, be much more user driven. And then we have a low code, no code, kind of interface, to be able to craft some of those conversation on all the variation. But, more importantly, we actually store all those conversation and can learn. And so we have assisted learning module to make a natural language processor cleverer and cleverer. And as you were saying, before we started to be on air, the user is contributing training data. Yeah, I was just sharing one of recent stories, of an ISP that I was trying to interact with, and frustrated that I couldn't just solve this problem on my own. And then after I was doing some work for theCube, a few months ago I realized, oh, actually I have to be calm here. I have an opportunity, as does everybody, to help train the models. Because that's what they need, right? It takes a tremendous amount of training data before our voices can become like fingerprints. So, I think, if more of us just kind of flip that, maybe our tone will get better, and obviously the machines will detect that, right? >> Yeah, no definitely. I think they key with conversational AI is not to see it as just plain tech, but really an opportunity to be more human centered. And, you know, obviously knowing who peoples are and how they interact in different kind of problems and scenario is absolutely critical. >> Pete, I want to get your thoughts on digital transformation, because we've done, I've done thousands of interviews on theCube, and many, many shows. Digital transformation has been around for awhile It all stops in one area. Okay, process technology, great areas, we've got visibility on that. Automation's excellent for processes. Technology, a plethora of activity. The people equations always broken down. Culture, has stopped dev ops. Maybe not enough data scientists or linguistic engineers to do conversational AI. You guys fill that void. Great technology. The people equation changes when there's successes. It all comes down to integration. Because that's where, either I don't believe in it, I don't want to do it, the culture doesn't want it. Time to value. The integration piece is critical. Can you guys explain how the Boomi Accenture integration works? And what should enterprises take away from this? >> Well, yeah, one of the key things when we started our relationship with Boomi more than five years ago now, really, Boomi was the leader, kind of the ones who invented iPad, right, the integration platform as a service. So, in the small and medium business, a lot of those companies had already moved a lot of the critical apps to the cloud. But, in the enterprise we see that it's taken a lot longer, right, so, certain departments may move certain pieces, but it's still very much a hybrid, right, between a cloud and on-prem based. So, taking a platform like Boomi, and being able to use that with the atomsphere platform has really allowed us to move forward. We've done quite a bit of work in Europe. And, now, in the last year, we've been focusing on North America, along with Europe. So, really, the platform has allowed us to focus on the integration. >> It's interesting, you bring up, you guys have been at Accenture for a long time, you've seen the waves. Oh, big 18 month deployment, eight years. Sometimes years, going back to the 80s and 90s. But now, the large enterprise kind of looks like SMB's because the projects all look, they're different now. You could have a plethora of projects out there, hundreds of projects, not one monolith. So, this seems to be a trend. Do you guys see it that away? Do you agree? Could you, like, share some insight as to what's going on in these large companies. Is it still the same game of a lot of big projects? Or, are things being broken down into smaller chunks with cloud platform? Can you guys just share your insights on this? >> Do you want to take that one first? >> You can do first, yeah. >> Okay. So the days of the big bang, big transformation, multi year programs, we don't see very many of those. A lot of our clients have moved away, towards lean, agile delivery. So, it's really being able to deliver value in shorter periods of time. And in that sense, you do see these big companies acting more like SMBs. Cause you really have to deliver that value. And, with Boomi's platform it's not just the integration aspect, and though our relationship started there, it's with some of the other pieces of technology, like flow and low code or no code as well, which has allowed Boomi customers and our clients and our teams to be able to get those applications out to production much quicker. >> Lisa: A big enabler, sorry, of the citizen developer. >> Yeah, absolutely. >> John: Thoughts on this trend. >> Yeah, so I guess my thought I will come with the innovation angle. So, obviously, we are in a very turbulent time, where company, you know, like a number of the Fortune 500 of 20 years ago, they're not there any longer. And there's quite a heavy rotation on some of the big corporation. And, what's really important is to size the market, and innovate all the time. And I think that's one of the reason why we have much smaller project. Because if you want to innovate you need to go to market really fast, try things up, and pivot ideas really fast, to try to see if people like it and want it. And, I think, that's also one of the key driver of smaller, kind of projects, that would just go much faster to like... >> We had a guy on theCube say, data is the new software. Kind of provocative, bringing a provocative statement around data's now part of the programatic element. And integration speaks volumes. I want to get your reaction to the idea of glue layers. I mean, people kick that term around. That's a glue layer. Basically integration layer with data. Control plane. This isn't really a big part of the integration story for Boomi but for other customers. What's your guys thoughts on this data layer, glue layer, that software and data come together? You're showing it with the conversational AI. It's voice, in terms of software, connects to another system. There's glue. >> Yeah, so, that's a very interesting angle. Cause I think, you know, in the old integration world people would just build an interface, and then it would go live, and they wouldn't necessarily know exactly what's going on the bonnet. And I think, adding that insight, of what you flow, or how often they use, when they're kicked off, is something that becomes quite important when you have a lot of integration to manage. I would remember, I was working for a bank, a major bank in the UK, where we trying to make a mainframe system go real time. But we had all those batch schedule, kind of running, and nobody really knew when, what, and the dependency in between each other. So, I think it definitely helps a lot. You know, bubbling up that level of visibility you need to transform truly. >> Yeah, and you're seeing lot of companies now have Chief Data Officers. Right, but data really is important. And with big data data links, unstructured data, structured data, tradional RDMS databases, being able to access that information. Is it just read only? Is it read and write? You're really seeing, kind of, how all of it has to come together. >> So, if we look at the go-to-market for Boomi and Accenture. Pete, talk to us about how that go-to-market strategy has evolved during the partnership. And where you see it going with respect to emerging technologies like conversational AI. >> Oh, yeah, we've got great opportunities. So, we've started off, really just, hey, there was integration opportunity. Are we doing much work with Boomi and the enterprise. Five years ago, we hadn't. And we started doing more work, kind of in AsiaPac, and then in Europe. Three years ago we entered a formal relationship to accelerate the growth. It was accelerated growth platform which started at Amia. And this last year we formally signed one in North America as well. And in the last three years we've done four times the amount of work. The number of customers, we've got more than 40 joint customers together. The number of trained professionals within Accenture. We have more than 400 people certified, with more than 600 certifications. Some of them may be a developer as well as an architect. And so, a lot of that is really that awareness and the education, training and enablement, as well as some joint go-to-market activities. >> Any of those in a specific, I was reading some US cases in healthcare and utilities? >> Yeah, we're definitely, we've seen quite a bit in utilities and our energy practice. We've seen it in transportation. Because Accenture covers all the different industry groups we're really seeing it in all of them. >> You know, I'm fascinated by the announcement you guys had with Boomi. The big news. Conversational AI. Because it just makes so much sense. But I worry people will pigeon hole this into, you know, voice, like telephone call centers only. Cause the US cases you guys were showing on stage was essentially like, almost like a query engine, and using voices. Versus like an agent call center work flow, which is an actual work flow. Big market there, I have no doubt about it. But, there's other US cases. I mean, this is a big, wide topic. Can you just share the vision of conversational AI a little further? >> So, meaning, I think the capability we have is to kind of go on any channel. Voice is an interesting one, cause it's, I think, it's very common still, you know, to have a call center, when you dip into challenges. And this is kind of the most emerging and challenging from a technology perspective. So, that's the one that was showcased. But there's a number of chat channels that are also very important. On the web, or a synchronous channel, like Whatsapp and Facebook and all of that kind of thing. So, it's really kind of, really offering a broad choice to the end consumer. So they can pick and choose what they want at the moment they want. I think what we see in the market is a big shift from synchronous kind of interaction, like on the web. You go on the web, you chat with something, and you just need to be there to finish it. To actually text. Because you can just send a text, get a response, go to a meeting, and on the back of the meeting, when you have five minutes, you just kind of do the reply. And you actually solve your problem on your own terms. But really when you have the time. So, there is a lot coming there. And, you know, with Apple Business Chat, you know, there's a number of mechanisms that are coming up, and new channels. Before company tended to be, you know, we do digital, we do call center, and maybe we have chat, but actually all of that is broadening up. You know, people want multi channel experts. >> So, synchronous is key. Synchronous and synchronous communication. So, is there a tell sign for a client that says I'm ready for conversational AI? Would I have to have a certain data set? I mean, is it interface? What are some of the requirements, someone says, hey, I really want this. I want to do this. >> Yeah, so, the way we deal with all of that, very often, is if you have call center recording or chat recording, we have a set of routines that we pass through. So, we transcribe everything and we do what we'd call intend discovery. And from that we can know, you know, what are the most, kind of critical, kind of processes kicked off. And from that, we know if it's transactional, or if it's an interaction, or an attendant's emotionally loaded, like people not happy with their bill. And then we have different techniques to address all of those different, kind of processes, if you want, and transform them into new experiences. And we can very easily, kind of look at the potential value we can get out of it. So, for instance, with one of our client, we identify, you know, if you do that kind of transformation you can get 25 million off your call center. You know, like, which is very sizeable. And it's very precise cause it's data driven. So, it's based on kind of, real calls, recordings and data. >> Can't hide from data. I mean, it's either successful or not. You can't hide anymore. >> Yeah, and I think one of the extra value add is very often call center agent or chat agent, they're not really paid to classify properly, so they would just pick up the most easy one all time. So, they will misclassify some of those recordings. Choose what's easiest for them. But when you actually go into what was said it's a very different story. >> John: Well, great insight. >> So, AI becoming, not just IQ, but EQ, in the future? >> Yes, definitely. That's the whole idea. That why we need our users to emrace it. (laughing) >> Exactly. And turn those frustrating experiences into I have the opportunity to influence the model. >> Last question, Pete, for you. In terms of conversational AI, and the business opportunities that this partnership with Boomi is going to give to you guys, at Accenture. >> Oh, definitely looking forward to joint go-to-market, taking this globally. We were named, earlier this week, yesterday, the worldwide partner of the year. Second time that Accenture's been awarded that. Which we appreciate. And that we look forward to working with Boomi and taking conversational AI to our joint clients. >> Awesome. Laetitia, Pete, thank you so much for joining John and me. Really interesting conversation. Can't wait to see where it goes. >> Great. Thank you very much. >> Our pleasure. >> Great conversational. >> Very conversational. >> Got some AI here, come on. >> Next time we give you a bot to sit in our seat. (all laughing) >> Cube conversations. >> Exactly. For our guests, and for John Furrier, I'm Lisa Martin. You're watching theCube, from Boomi World 19. Thanks for watching. (upbeat music)

>> Live from Las Vegas, it's theCUBE, covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World 2019. I'm your host Rebecca Knight, along with my co-host John Furrier. We're joined by Ali Ghodsi, he is the CEO of Databricks, thank you so much for coming on, for returning to theCUBE. You're a CUBE veteran. >> Yes, thank you for having me. >> So I want to pick up on something that you said up on the main stage, and that is that every enterprise on the planet wants to add AI capabilities, but the hardest part of AI is not AI, it's the data. >> Yeah. >> Can you riff on that a little bit for our viewers? Elaborate? >> Yeah, actually, the interesting part is that, if you look at the company that succeeded with AI, the actual AI algorithms they're using, are actually algorithms from the 70s, you know, they're actually developed in the 70s, that's 50 years ago. So then how come they're succeeding now? When actually the same algorithms weren't working in the 70s, so people gave up on them. Like, these things called neural nets, right? Now they're en vogue and they're, you know, super successful. The reason is you have to apply orders of magnitude more data. If you feed those algorithms that we thought were broken orders of magnitude more data, you actually get great results, but that's actually hard. You know, dealing with petabyte scale data and cleaning it, making sure that it's actually the right data for the task at hand is not easy. So that's the part that people are struggling with. >> I saw you up on stage, I'm like ah, Ali's here, Databricks is here, that's awesome. Psyched that you stopped by theCUBE. Been a while. I wanted to get a quick update, 'cause you guys have been on a tear, doing some great work at Cal, we were just told before we came on camera. But what are you doing here? What's the, is there any announcements or news with Informatica? What's the story? >> Yeah, it's, we're doing partnership around Delta Lake, which is our next generation engine that we built, so we're super excited about that. It integrates with all of the Informatica platform. So their ingestion tools, their transformation tools, and the catalog that they also have. So we think together, this can actually really help enterprises make that transition into the AI era. >> So you know, we've been followers, our 10th year, so remember when we were in the cloud era office of Mike Olsen and Amr Awadallah when we first started and now, Hadoop movement started, and then the cloud came along. Right when you guys started your company, the cloud growth took off. You guys were instrumental in changing the equation in dealing with data, data lakes, whatever they're calling it back then. So now, data, holistically, is a systems architecture. On premise it's a huge challenge, cloud native, well no real challenge, people love that. Data feeds AI, lot of risk taking, lot of reward. We're seeing the SaaS business explode, Zoom communications. The list goes on and on. Do you know, enterprise that's trying to be SAS is hard. So you can't just take data from an enterprise and make it SaaS-ified. You really got to think differently. What are you guys doing? How have you guys evolved and vectored into that challenge, because this is where your core value proposition initially started change. Take us through that Databricks story and how you're solving that problem today. >> Yeah, it's a great question. Really what happened is that people started collecting a lot of our data about a decade ago. And the promise was, you can do great things with this. There are all these aspirational use cases around machine learning, real time, it's going to be amazing. Right? So people started collecting it. They started storing one petabytes, two petabytes, and they kept going back to their boss and saying this project is real successful I now have five petabytes in it. But at some point the business said, okay that's great but what can you do with it? What business problems are you actually addressing? What are you solving? And so, in the last couple years there's been a push towards let's prove the value of these data lakes. And actually, many of these projects are falling short. Many are failing. And the reason is, people have just been dumping this data into data lakes without thinking about, the structure, the quality, how it's going to be used. The use cases have been an afterthought. So the number one thing in the top of mind for everyone right now is how do we make these data lakes that we have successful so we can prove some business value to our management? Towards this, this is the main problem that we're focusing on. Towards this, we built something called Delta Lake. It's something you situate on top of your data lake. And what it does is it increases the quality, the reliability, the performance, and the scale of your data lake. >> (John) So it's like a filter. >> Yeah. >> The cream rises to the top. >> (Ari) Exactly. >> Let's the sludge, the data swamp stay below the clean water, if you will. >> Exactly actually you nailed it. So basically, we look at the data as it comes in, filter as you said, and then look at, if there's any quality issues we then put it back in the data lake. It's fine, it can stay there. We'll figure out how to get value out of it later. But if it makes it into the Delta Lake, it will have high quality. Right? So that's great. And since we're anyway already looking at all the data as it's coming in, we might as well also store a lot of inducees and a lot of things that let us performance optimize it later on. So that, later, when people are actually trying to use that data they get really high performance, they get really good quality. And we also added asset transactions to it so that now you're also getting all those transactional use cases working on your existing data lake. >> I saw, at my daughter's graduation in Cal Berkley this weekend and yesterday, people around with Databricks backpacks. Very popular in academic. You guys got the young generation coming in. What's the update on the company? How many employees? What's the traction? Give us a quick business update. >> Yeah we're about 800 employees now. About 100 people in Europe, I would say, and maybe 40-50 people in Asiapac. We're expanding the ME and the Asia business. >> (John) Growth mode. >> Yeah, growth mode. So it's expanding as fast as possible. I mean, I actually, as a CEO, I try to always, slow the hiring down to make sure that we keep the quality bars. So that's actually top of mind for me. But yeah we're-- >> (John) You did Delta Lake on that one. >> Yeah (laughing) >> Exactly. Yeah and we're super excited about working with these universities. We get a lot of graduate students from top universities-- >> And Cal had the first ever class in college of data analytics, what was that? Data analytics are the first inagaural class graduated. Shows how early it is. >> Yeah, yeah, yeah. And actually used Databricks, the community edition, for a class of over a thousand students at Cal used the platform. So they're going to be trained in data science as they come out. >> So I want to ask about that because as you said you're trying to slow down the hiring to make sure that you are maintaining a high bar for your new hires. But yet, I'm sure there's a huge demand because you are in growth mode. So what are you doing? You said you're working with universities to make sure that the next generation is trained up and is capable of performing at Databricks. So tell us more about those efforts. >> Yeah I mean, so, obviously university recruiting is big for us. Cal, I think Databricks has the longest line of all the companies that come there on the career fair day. So, we work very closely with these universities. I think, next generation, as they come out, this generation that's coming out today actually is data science trained. So it's a big difference. There is a huge skills gap out there. Every big enterprise you talk tells you my biggest problem is actually, I don't have skilled people. Can you help me hire people? I say, hey we're not in the recruiting business. But, the good news is, if you look at the universities, they're all training thousands and thousands of data scientists every year now. I can tell you just at Cal, because, I happpen to be on the faculty there, is, almost every applicant now, to grad school, wants to do something AI related. Which has actually led to, if you look at all the programs in universities today, people used to do networking, professors used to do networking, say we do intelligent networks. People who do databases say, we do intelligent databases. People who do systems research say, hey we do intelligent systems, right? So what that means is, in a couple years you'll have lots of students coming out and these companies, that are now struggling hiring, then will be able to hire this talent and will actually succeed better with these AI projects. >> As they say in Berkley, nothing like a good revolution once in a while. AI is kind of changing everyone over. I got to ask you for the young kids out there, and parents who have kids either in elementary school or high school, everyone is trying to figure out, and there's no yet clear playbook, we're starting to see first generation training, but is there a skill set, because there's a range in surface area, you got hardcore coding to ethics, and everything in between from visualization, multiple dimensions of opportunities. What skills do you that people could hone or tweak that may not be on a curriculum that they could get, or pieces of different curriculums in school that would be a good foundation for folks learning and wanting to jump in to data and data value, whether it's coding to ethics? >> Yeah, just looking at my own background and seeing how, what I got to learn in school, the thing that was lacking, compared to what's needed today, is statistics. Understanding of statistics, statistical knowledge, That I think, it's going to be pervasive. So I think, 10, 15 years from now, no matter which field you're in, actually whatever job you have, you have to have some basic level of statistical understanding 'cause the systems you're working with will be, they'll be spitting out statistics and numbers and you need to understand what is false positives, what is this, what is the sample, what is that? What do these things mean? So that's one thing that's definitely missing and actually it's coming, that's one. The second is computing will continue being important. So, in the intersection of those two is, I think a lot of those jobs. >> In all fields, we were talking about earlier, biology, everything's intersecting, biochemistry to whatever right? >> (Ali) Yeah. >> I got to ask you about, well I'm a little old school, I'm 53 years old but I remember when I broke into the business coding, I used to walk into departments, they were called DP, data processing. So we're getting into the data processing world now, you've got statistics, you've got pipeline, these are data concepts. So I got to ask you as companies that are in the enterprise may be slower to move to the cutting edge like you guys are, they got to figure out where to store the data. So can you share your opinion or view on how customers are thinking and how they maybe should be architecting data on premise, in the cloud. Certainly cloud's great, if you're getting cloud native for pure SAS, and born in the cloud like a start-up. But if you're a large enterprise, and you want to be SAS-like, to have all that benefit, take the risk with the reward of being agile, you got to have data because if you don't the data into the machine learning or AI, you're not going to have good AI. So you need to get that data feeding in fast. And if it's constrained with regulation compliance you're screwed. So what's your view on this? Where should it be stored? What's your opinion? >> Yeah, we've had the same opinion for five, six years, right? Which is the data belongs in the cloud. Don't try to do this yourself. Don't try to do this on prem. Don't store it in, at Duke, it's not built for this. Store it in the cloud. In the cloud, first of all, you get a lot of security benefits that the cloud vendors are already working on. So that's one good thing about it. Second, you get it, it's realiable. You get the 10, 11 lines of availability, so that's great, you get that. Start collecting data there. Another reason you want to do it in the cloud is that a lot of the data sets that you need to actually get good quality results, are available in the cloud. Often times what happens with AI is, you build a predictive model, but actually, it's terrible. It didn't work well. So you go back, and then the main trick, the first tricks you use to increase the quality is actually augmenting that data with other data sets. You might purchase those data sets from other vendors. You don't want to be shipping hard drives around or, you know, getting that into your data center. Those will be available in the cloud, so you can augment that data. So we're big fans of storing your data in data lakes, in the cloud. We obviously believe that you need to make that data high quality and reliable. With that we believe the Delta Lake platform, open-source project that we created is a great vehicle for that. But I think moving to the cloud is the number one thing. >> (John) And hybrid works with that if you need to have something on premise? >> In my opinion the two worlds are so different, that it's hard. You hear a lot of vendors that say we're the hybrid solution that works on both and so on. But the two models are so different, fundamentally, that it's hard to actually make them work well. I have not yet seen a customer yet or enterprise. You see a lot of offerings, where people say hybrid is the way. Of course, a lot of on prem vendors are now saying, hey, we're the hybrid solution. I haven't actually seen that be successful to be frank. Maybe someone will crack that nut but-- >> I think it's an operational question to see who can make it work. Ali, congratulations on all your success. Great to see you. >> Yeah it's been great having you on the show. >> Thank you so much for having me. >> You are watching theCUBE, Informatica 2019. I'm Rebecca Knight, for John Furrier, stay tuned.

(upbeat inspirational music) >> Hello everyone, I'm John Furrier in the Palo Alto Studios for Cube Conversation. I'm here with David Link who's the CEO of ScienceLogic. David, thanks for coming in. Good to see you. >> Great to be here, John. >> So, thanks for coming in. You came in from D.C., that's where your headquarters and ScienceLogic, you guys are having good business run right now. You're self-funded early on, now you get to venture back. Take a minute to explain how you guys got started, what does the company do? >> So, this is the classic story of entrepreneurship. We started in the garage. Myself and a couple of co-founders believed that IT management operations was broken and it was broken because a lot of the industry had really focused on having silos of data, the silos of data, the network, the application, the security, the storage, now cloud, containers and every technology had its own data silo of manageability. We believe that that was intrinsically wrong to understand how the service that combined all these different applications and technologies was behaving. We wanted a service view, so we brought it all together, kicked off, really the first seven years we boot strapped the company, the first year and a half we coded, got the product to market, it grew very quickly, got to the Inc. 500 a couple times, and then we attracted a lot of financing options. We had about 250 companies approach us. We never made one outbound call and fortunately, we had some really great and strong investors in EA, then Intel Capital, and three and a half years ago, our last round of financing was with Goldman Sachs and they've really been a great catalyst to help us continue our growth over the last five years. I think we've grown about 540% on the revenue side, so it's been an exciting time. >> Well congratulations. It's always a good success story to be a hot deal when you don't have to make any calls, they come to you. >> Yes. >> And that's good, that's part of growth, but I got to ask you what year did you start the company up? >> 2003. >> So, it's not obvious then, it's obvious to you as a visionary, but now people now know IT operations is broken. Cloud highlights it in a big way. The lights get turned on, the cockroaches are running around, but web services were still booming at that time. You start to see the beginning of the whole web services movement, you guys saw this early. Now, it's well recognized that IT operations can be automated away and Cloud certainly has an automations vibe to it. AI has been a big part of the AI operations. Is this kind of where you guys started with that vision? Was the original vision kind of where it is today? Take us through kind of what you saw and what's happening today. >> So, thematically we have this next wave of the computer architecture, Cloud computer architecture, edge computing where the way you manage that kind of infrastructure is different than the classic client server. There are different needs, different requirements, and that thematically has led with the change of infrastructure. Applications are changing and applications are now more infrastructure-aware. When we started the company, usually applications sat on one system or a cluster of systems and they weren't widely distributed. So now that the applications profile is changing, the architects are changing to microservices, that really puts huge strain on our industry. The industry, the total adjustable market, is about 25 billion dollars a year annual spent on tools. John, if you can imagine that. 25 billion a year is spent. It's going through an amazing, I would say, tectonic shift because why? Infrastructure's shifting and as more people move workloads to the Cloud into what I would call ephemeral workloads where they're moving around, that causes all kinds of pressure on the systems and record to manage that so that you understand what is happening at this moment in time. Where is it? What Cloud is it running on? How's the application performing? And you really need to tie the application to the infrastructure real-time. >> I want to get your thoughts on this. I interviewed a CIO this past week for a big company. I won't say the name 'cause we haven't published the video yet, but he told me candidly, he said that, look it, we outsourced everything and we outsourced our way into oblivion and what he meant by that was is that the core competency of IT, and he reference the book, Nick Carr, IT Doesn't Matter, which kind of was true, but wasn't true. Now, IT has a competitive advantage and essentially, they had this anemic IT department that was outsourced and they lost their competitive advantage, so he's like the reinvestment in IT is more than ever now because of Cloud, because of these new environments. So, I kind of believe that to be true. I'm sure you do too, but the reaction really is is you've got a lot of Legacy vendors that were dictating how to do things. >> Yes. >> I'm IBM, I'm Oracle, you got to do it this way and you were kind of constrained, IT was constrained by that. Now, you got to be much more agile, you have workloads that are dynamic, provisioning, orchestration, this is a whole new dynamic. What's the impact to the IT buyer, the IT environment with this new model, this new modern dynamic, new modern era? >> When you think about CIOs and CEOs, the pressure that they have to be Cloud first. Cloud first is such a strong... At the Board level, there's pressure. The adoption of Cloud now is happening faster and more rapidly than the adoption of virtualization, maybe it's doubling in the speed in the time warp, but what that means is that most CIOs are dealing with as many as nine to 11 Clouds, not one. You have a federation of Clouds: Private Clouds, public Clouds, software as a service Clouds, and that's your IT landscape, so it's changing so quickly that you have to think of it in a more federated approach. That means that the way you used to manage your private systems, and now your public systems, are really different and you've got to look at them more holistically because often they're communicating with one another in hybrid architectures. So, that's really the heart at our mission, to provide the context of how all the services you're trying to deliver as a CIO are behaving. What's their availability? What's the risk of the service having a problem? And knowing that real-time is ultimately what you want to do with your Cloud first strategy, but you need the right tooling operationally to affect that kind of outcome for your team. >> So, what's the core problem that you guys are solving? 'Cause obviously, there's a lot of complexity now, it's a new environment, so I still got the baggage of some Legacy environments. Is it monitoring you're solving? I guess, what's the core problem is my question that you guys are solving? If you had to kind of finish that, the core problem is blank. >> The core problem is visibility. The Holy Grail is application to infrastructure and the problem is that's becoming so complicated because everything is moving around. The more abstraction layers where it's a container, which is abstracted on top of a virtual machine, which is on top of bare-metal server. SD-WAN is an abstraction on top of an MPLS network. So, you have all of these layers that get from a software-defined perspective, they get abstracted away from the actual equipment that it's running on. Well, when that happens, where is the problem? Because it's moving around. The problem isn't in one place. So, that application to infrastructure awareness, it's almost like one of the things that we've looked at in the world of Facebook. You've got a lot of relationships, you've got videos, you've got friends, you've got all these different connections that are constantly moving around with data streams. What we do as a company is pull all these different data streams from the technologies themselves, from the Cloud providers, from the application layer, pull it together in a data hub that we can then understand how they all relate to one another so you can really, truly understand service impact and that is the crux of the problem most companies are dealing with now. You've got to fight with your Legacy, 'cause you still have that and it's not going away tomorrow, so you've got to make sure you're good at that, you've also got Cloud, the Cloud first initiative, and then you've got in between systems that are using both. That's really where we play. We're really good at the Legacy, we're good at Cloud, and connecting the two together and that is a really tough space because most Legacy providers really didn't get good with managing hyperactive ephemeral Cloud estates. The guys who started over the last five years building tools to manage the Cloud are really good at Cloud, but they don't cover Legacy. They're not going to cover a net app or hyper-converge, typically. So, we combine the both, Legacy and Cloud together in one management system, monitoring management paradigm, and then there's an automation engine where we actually proactively remediate problems real-time. So, the three together is where algorithmic operations, AI Ops, comes together. >> David, I want to dig into the offering, but before we get there, I want to get your thoughts on two trends: one is multi-Cloud. Recently, we've seen a lot of hybrid Cloud discussion, but now the big hubbub is multi-Cloud and the other one is AI Operations. So, I've been saying on The Cube, everyone who's in IT Operations is screwed, going to get automated away by AI. It's kind of tongue in cheek, but it's kind of a reality is that those old business models that were based upon certain service levels are going to be done in software. Now, you've got multi-Cloud. So, first question is what is multi-Cloud definition that you have for that? What does it mean? What is multi-Cloud? >> In our world, multi-Cloud is... Most large organizations use more than one Cloud and half of that is driven by what Cloud is best to operate a particular application profile? Amazon's really good at a lot of application profiles, but Azure might be better at certain Microsoft profiles, and then Google has profiles, and IBM Watson has profiles. Depending upon what you're trying to do with the application, where it was born, how it's living, how it's been re-factored, you're going to use one Cloud or the other, but most customers that we see have many Clouds. There really isn't one Cloud management scape when you're using... Vendors are still reasonably proprietary in the public hyper-scales. >> Some are better than others. >> And some are better. It depends on the use case. So, we try to bring all that together so that you're not looking at four panels, you're looking at one. >> So, you make it easy with one dash port. Okay, AI Operations. This is a hot trend, a lot of venture capitals are funding companies that have AI Ops in it, machine-learning obviously booming, no doubt software automation is coming. I'm seeing it everywhere. What does that mean? What is the definition of AI Operations? I mean, I'm bombastic at saying the industry sectors is going to crumble. I kind of think it will, but it will shift, but what is the impact to IT Operations with AI and what is AI Ops? >> We like to think of it as a life cycle. So, when you look at the life cycle of operations you have at the beginning of the life cycle, provisioning, so when we think about algorithmic, there's many different layers of automation: machine learning, cognitive learning, and you're going to use different parts of algorithmic operations for different parts of the life cycle. So at the very beginning, you're going to connect generally to a provisioning system so you know what's been provisioned or de-provisioned so we can automatically align a manageability template because nobody can be on a keyboard now, John. This has to be all machine to machine. So, once then it gets provisioned, then there's the run operate part and how do you learn from the normal operating conditions that you're looking for? The anomalies that you would look for to detect things aren't behaving appropriately? And then, once you understand those anomalies and the patterns, you can remediate them proactively, adding resources, decreasing resources, changing configurations, those are the things that kind of that last tier, and then that final tier, when there is a problem, if there is a problem, you've got to then raise a ticket, you've got to then work through the incident management of that ticket so there's another multi-step layers of automation to the incident management orchestration layer of solving problems, closing out a ticket. So, we have so many different layers across that life cycle that we plug into, most of which are native to our core platform. >> And your secret sauce is managing all the workloads that are moving around really fast, so to complicate that even further, you've got a lot of stuff moving around to track it all. I love what you said about not typing on the keyboard anymore, but essentially I'll translate that from what I heard was command line interface of CLIs has been the primary mechanism for dealing with either network and or storage, which is moving packets from here to there and moving storage from now to then, storing stuff. So, CLI is moving to a programmable model? This is the big takeaway. So, I totally think this is the mega trend. The command line interface mode of operation is moving to programmable, which hits your run and operate. >> Correct. >> This is the mega trend. Your thoughts? >> It is and that's one of the layers of complication because instead of a CLI, it's an API, and it's usually a restful API or a graph API. Those APIs are very different in construct and instead of talking to one device, that one device is virtualized into a hundred or a thousand and so with one API call, you actually create a thousand devices versus one device and understanding how one system is behaving, like a CLI would be to one system, right? So, that is a layer of complication where when we make an API call, we break it up into hundreds of things that then we track and understand the tenancy of what is a multi-tenant nature of that? What is the organization? What is the service view for all these little components that are part of one API call? And that abstraction layer makes it really difficult for the enterprise because the one thing about our API economy right now, there is no standard. Every vendor chooses their own formats for their products and in some cases, many formats for products in a product family. So, that layer of complexity, John, is what we're really solving for. The customer doesn't have to worry about that. We take care of that for them, but you're right, the API has become the CLI and it's just a level of complexity beyond what most enterprises are wanting to deal with themselves. That's why they bring us in to help. >> That is so important too that the data's in the API. >> That's right. >> That's key and Cloud's got orchestration challenges, state and state-less applications. All right, let's get into ScienceLogic's offering. So, what do you guys provide to customers? Talk about the product. How do you guys deliver it? Is it software, is it Cloud, is it service, is it appliance? Take us through the offering. What's the key secret sauce? How do people buy and use your product? >> So, our product's delivered as a service. You can use it in the Cloud. We deliver it as a service in our Cloud, but we also provide it if customers are using Amazon or IBM or Google or Microsoft. They can put our product, same code-base, same product, they subscribe to it, it's a subscription license model, so it's a pay-as-you-go and you pay for the number of devices that are under management. Typically, there are some customers, whether it's in the government, financial services, or international locations where they might want to deploy our product on premise, so we offer the same mode, either in the Cloud or on premise, but most customers now are choosing to deploy the product in the Cloud and that is a really easy... It's easy to get >> That's good for you guys. >> It's great for us because there's consistency of operations, we can keep everything up to date, and most customers want technology delivered as a service. They just want it to work. They want it to solve the business problem and do it easily, efficiently, even better, solve complex problems in an easy format. >> Give some customer examples or benefits or anecdotal stories around customers that have used your service that extracted benefits and value out of it, and second part of that question is when does someone know they need your product? What are the smoke signals? Is something breaking or is it just pain? When do they know to call you guys? So first one is customer examples or stories and then how does someone know who's watching this, hey I might need these guys? >> There are four segments that we cover. We have customers all over the world. There's enterprise customers. This is really a product for large enterprise, Fortune 1000 companies, so Clorox would be a customer, Hughes Satellite would be a customer, Cisco Systems out here in the valley is a customer, Dell, EMC, so it depends on what problem we're trying to solve for the customer. >> So large IT deployments basically? >> Very large, multinational, big networks, hundreds of thousands of devices, tens of thousands of devices is where those companies have immense complexity, lots of heterogeneous technology that comes together to deliver a service. They need a really robust solution to manage that proactively. So, enterprise customers, service providers, so a lot of managed service providers, infrastructure service providers, Telcos, they all use it, so I think we have about 60% of the infrastructure as a service providers use our product to deliver managed services to their customers and then the federal government all over the world, we have government customers around the world. I think right now about 70,000 organizations use our product every day and it's fairly evenly split, AMIA and AsiaPac, and then the US is our biggest market. >> You know, it's interesting you mention heterogeneous. I always kind of smile because you mentioned client server earlier. Every wave has their reflection point and I think what's going on with Cloud and I'd love to get your reaction is that Cloud, where it's winning, is it's a scale out, large scale, pool of resources. We look at what's going on with Amazon, all this, is that you don't need to know what service they have, just get more servers, so you're scaling out. >> Yes. >> But now, you need to have heterogeneous components. It's not just X-86. You could have a GPU, you have other stuff, AI going on, so heterogeneous is different now, but it's still the same came, it's still complex, it needs to be abstracted away. Is this kind of the key area that you're riding on? Is that right? What's your thoughts about that concept? >> Well to a large degree, John, the Cloud providers have really provided a layer for you to not have to worry about that, but we've seen customers actually with hyper-converged environments that they build in-house and or systems that they built because of geo-fencing in different countries that need the data kept in the country. There are requirements that drive people to build their own system, so the real thing that we're seeing a tremendous struggle with right now is that context, understanding what connects to what. All the different technologies that come together, all the heterogeneity that comes together to deliver a service, and whether you buy best in class technologies to solve one part of the stack, the landscape of whether it's your load balancer or a caching server or the database or the server, the network, all those different components, the security layer, those components that come together, often people have chosen specific technologies to solve those problems. The Cloud kind of abstracts that away with they hyper-scalers, but often you're putting infrastructure that you have on prem combined with infrastructure in the Cloud to deliver an aggregate solution so that multi-tiered architecture, just like back in the day, a three-tiered architecture, we're seeing those emerging again with public Cloud because you might want the data that actually generates the information on the web client's side to be in your data center, but you still have to understand how the service is behaving. So, we really look at all layers of the stack to solve the problem and that's really hard to do. >> Well David, great to have this conversation. Before we end, I want you to get a quick plug in for the company. How many employees, offices? What's the revenue like? What's your goals? You don't have to share the revenue if you don't want to, but if you want to, you can. Give a plug for the company. What's happening? >> Well, I'm really proud of what the team's done. We've got a great team of employees, about 370 employees today, full-time, they're spread all over the world, probably 80% are here in the Americas and the vision for the company, we think that this is a big opportunity. We are far from done. We really started the company to disrupt the industry 'cause the industry, as I said, was a silo industry and it really is, 20 years later, it's still that way. It's not really converged into a unified solution. We have great aspirations. Every year we've been growing the business 40, 50% a year for the last several years, and this year, we'll round over 100 million within the next 12 months of our run rate, so it's an exciting time for the company. >> Well, you've got a great model, SAS, in a massively growing and changing market, complex market, heterogeneous networks, apps are all being abstracted away and automation's driving this, so I think it's a perfect storm of innovation. Congratulations and thanks for chatting on The Cube here in Palo Alto. >> Love to be here, John. Thanks for having me. >> John Ferrier here, Cube Conversation, and we're here with David Link, CEO of ScienceLogic, and also the founder. Self-funded, big venture rounds, growing like a weed, based in D.C. This is the Cube Conversation. I'm John Furrier. Thanks for watching. (dramatic inspirational music)

(upbeat music) >> This is theCUBE from Silicon ANGLE Media. I'm Paul Gillin. The cloud is all the rage these days, but as companies move to the cloud, and some of them seeking simplicity, what they find is they actually get complexity. Because they want to balance their resources, they want to hedge their bets, they don't want to get locked in, so they end up doing business with multiple cloud providers, and often with an on premise cloud as well. That creates cost complexity, and that's what Cloud Health Technologies is addressing. My guest is Tom Axbey, he's the new CEO of Cloud Health Technologies, a Boston based company, recently raised $46 million, they have software that helps companies understand their cloud costs and of course, to reduce them as well. So, Tom, just a couple weeks on the job, welcome to theCUBE. >> Right, thank you Paul, nice to be here. >> I'm sure you could tell better what Cloud Health does, than I can, so why don't you give your description. >> Actually, I mean you just did a very good set up for me. I mean Cloud Health is the de facto standard, cloud service management software. And as you quite rightly pointed out, One of the complexities now, is have a multi-cloud or hybrid cloud environment. So people aren't making a single vendor bet. That of course, increases, as you mentioned, the complexity and the costs controls, the governance, security, even more, and that's what we do. We manage all that complexity and give our customers a single pane of glass to help manage and optimize their cloud experience. >> When do customers typically come to you? Are they in a crisis, or are they coming to you earlier in the process, to avoid that crisis? >> You know, it's all over the map. It depends on their cloud maturity. So, customers, we've got, who are early customers, who were literally born in the cloud. So you think of services such as AirBnB and Pinterest, and Yelp!, you know, those services are cloud based right from the get go. What they've done is experienced tremendous growth, on global basis by offering these services, managing huge data sets, in the public cloud. But, they also had the expertise, because they were going through that right from the beginning. As soon as that scale becomes unmanageable, as it does, and that complexity becomes greater in a multi-cloud environment, they bring us in. It's just that their technical acumen was a little bit more advanced than say someone in the enterprise, who's been managing data centers and they want to migrate to the cloud. But they find that their expertise is in the data center world, and their expectations are, I want the same governance and management that I had in my data center, as I move to the cloud. So you're really embarking on the beginning of their cloud journey. Then sort of the third set of our customers are MSPs. So these are actually cloud service providers, who are basically offering their customers, and they're the trusted source for their customers, all the aggregated services that are available for them, and their experience. Mainly small-medium businesses and mid-market businesses will go through the MSPs, but they're customers for us too. >> Talk about complexity, what are some of the unique characteristics of the cloud environment that create complexity that perhaps customers don't always anticipate? >> Well the first thing is, is the pace of innovation in the cloud is at light speed. You've got these cloud vendors, Amazon, Microsoft, Google, and now you got IBM, you got Oracle, and many other ones, Alibaba, and AsiaPac, they're all increasing their service offerings at a rapid pace of innovation. Just keeping up to speed with the domain expertise is very very complex. Then, when you migrate to the cloud, you're migrating services, critical business services, and just like any other environment, computing environment, whether it's distributed computing or client server, you got to manage those complexities, so your business services and applications can run smoothly. As you know from certainly your experience, there's an inordinate amount of moving parts, and even more so in the cloud. Now, you multiply that by a multi-cloud or a cloud, or a hybrid cloud experience, and certainly, being able to aggregate that data, becomes a business critical task. >> We hear a lot about multi-cloud and customers trying to hedge their bets, is that a major force in the industry right now? Do you see companies actively trying to diversify the number of providers that they work with? >> We do, yeah, absolutely, and obviously, the larger the company, and the larger their cloud spend, the more likely they are to do that. So their not reliant on one cloud provider, and also they're experiencing different paces of innovation from the cloud providers, who are jockeying for that innovation right now. We're really focused on as well is the hybrid cloud. It could be a multi-cloud environment, but it also could be their private data center they're managing, or both. So yeah, we do see a huge trend in that. >> When customers come to you for the first time, and you do an initial analysis, what are typically some of the areas where you find the greatest inefficiencies, the greatest opportunities to save costs? >> Sure, I think it depends again on where they are in their cloud journey. They may be moving to the cloud, or thinking about it, and they want is some kind of visibility because they're so used to having tight controls, visibility, and budgets within their data center, because that environment is so mature to them, and the cloud is like the wild west to them. They're going to get these monthly bills, or they got to commit to certain workloads, or resources, without really understanding what their usage patterns are going to be. So we may come in and help with the migration, capacity planning, and certainly their forecasting abilities. The more mature they are, they want to start allocating costs, maybe by department, or by geographic regions, so they're getting more and more sophisticated in terms of their cost breakdown and their usage patterns and when those usage patterns happen. But also, as they control their costs, one of the ways they can do that is to buy future visibility, if you will, into those resources or compute power from the cloud providers. Being able to figure that out from a histotical and perspective billing standpoint, can be incredibly valuable to the customers. >> So what kinds of data do you provide for them? >> Well we provide essentially a window of aggregated roll-up of any particular service that they could have. So it could be their financial data in terms of their usage information, which resources or compute loads are working, also as they've deployed stovepipe data vendors for performance management or configuration management, security management, all of that comes into play as well, so we can roll up that aggregated data source. So they got a single pane of glass into sort of their entire environment. That could be at the VP level, who's running a multi-cloud environment, it could be at the financial level, where they're looking for cost controls, or could be the DevOps level where they're looking for anomalies or performance issues, or bottlenecks, or capacity planning, so at every level, we're trying to provide visibility into sort of the function and task that our customers have. >> Of course cloud vendors aren't interested in having their customers be multi-cloud, they want them to be single cloud, how cooperative do you find the vendors are in working with you to enable your customers to hedge their bets? >> I mean I think that they're very helpful, I mean number one, we've got deep relationships with all the cloud providers because we've been doing this a long time. Also, what we're doing is, we're hastening and accelerating our customers movement to the cloud by offering them the same visibility and governance and tools that they had in their data, or private data center world. So they actually embrace it, and they know it's going to be a multi-cloud environment, especially for the larger customers, and so, absolutely, we're helping that. >> Are customers beginning to look to broker their experiences, their costs, to move workloads sort of flexibly between different cloud providers, based, perhaps on even short term savings? >> They can do, yeah, absolutely. But again, short term savings are a trade off between long term savings, in terms of how much capacity you're buying, how much visibility you've got into your usage patterns as well. Certainly, that's the world that we're getting into these days, I mean, Amazon does per second billing now. When you think about all that data, it's absolutely, the complexity of it is absolutely mind boggling. >> The cloud world as Forester pointed out in a recent report, is consolidating into basically three big players, and then sort of everybody else. Do you think that's a good trend as far as customers are concerned? >> I think we've seen it over and over again, you see the dominant providers come forth and start taking over a marketplace, but there's always going to be room for other vendors. Now IBM and Oracle certainly are not just going to lay down. People like VMware are getting into the cloud business as well. They're the dominate ones right now, absolutely. I think what's good for the business is the trend itself of people moving all these workloads to the cloud and having more control over it, so that it'd actually be transparent as to who the cloud provider is. >> You certainly had the opportunity to take executive positions in a number of companies, what was it about this opportunity that appealed to you? >> Well, that's a very good question, I'd been at Rave for quite some time, especially in the high tech world, and we had a very successful run there, and we were acquired by a private equity firm. I was looking around and perhaps making a move, and I'd been fascinated by the cloud, and what it was doing, and how transformative it was to business. It was very akin to experiences I've had in my career, selling infrastructure software. I was at IBM, Tivoli for example, I was at MicroMUSE, and they were basically undergoing exactly the same transformation, in client server and distributed computing days. I was also aware of the investors and a couple of board members of Cloud Health, and I recall their very first investment, and it was explained to me by one their investors, this is Tivoli for the cloud. And of course, that resonated with me. I thought, that's brilliant, that's so simple, 'cause you've got exactly the same complexities, and then I tracked the company, had the opportunity to meet the founders, and I saw how they had executed against their vision, I saw the caliber of the team there. So, when an opportunity came up because the CEO and co-founder Dan Phillips was moving into the Chairman role, as my partner now, I jumped at it. >> You say Tivoli for the cloud, is an interesting analogy, of course the difference with Tivoli and cloud, is that Tivoli is on premise. You control the infrastructure, you have access to all the interfaces you need, not necessarily the case with the cloud. What are some of the difficulties that you encounter with getting customers the information that they need from their cloud providers? >> Well certainly the cloud, like I said, the pace of innovation is huge. So you've really got to be up to speed with the latest offerings, and if you look at all those APIs and how they could be changing, new services that they could be coming out with, literally on week by week basis, you've got to keep track of all of those. Then you've got to have a flexible architecture so you can actually easily integrate with those data sources and also understand the necessary workflows to present all that data in a consumable way. So it really is a very fast pace of innovation right now, and I think that's why the analogy of Tivoli for the cloud was a good one because you are aggregating all that data, you're given critical insight into, certainly back then, their network and infrastructure, business services, so the analogy holds true, but I think you're right, the pace of innovation is much quicker. >> Now, talk about how you justify your cost, what kind of deliverables do you promise customers in exchange for what you charge them? >> Fortunately, the deliverables are born out of history. We've got incredible ROIs. As you know, the monthly spend as it increases, as people's cloud experience grows, those costs can spiral quickly. I think that when people talk about the cost, we always talk about the value. What value are you looking for? How are you going to optimize your environment? So the savings we can save just on their billing or utilization, and then there's the governance, and then people want to do departmental charge backs or geo charge backs, and we can help them with that cost allocation. So we tend to talk about value more than cost. >> Where do customers leave money on the table though? Where do you find some of the greatest disconnects between what they could be spending and what they really are spending? >> It all comes down to consumption. If you, just like if you're deciding which mobile phone bill you want to get based on what your projected consumption is going to be, you know, they want to lock you into the biggest one, they're going to show you lots of different values for signing you up for a three year contract. It's the same for a cloud provider. The more you're willing to prepare, the more you can lock in your costs, and of course, as you do that, the risk is, you don't fulfill all of those costs and realize those savings. On the other hand, you maybe growing so exponentially quickly, that you're actually paying more than you would be, than if you just basically consumed a different pricing model. >> In general though, do you find that customers, if they manage their cloud costs wisely, do they, in the final analysis, save money by moving to the cloud versus an on premises architecture? >> Without a doubt. The time to deploy services is so quick. The time to integrate different facets of your business services is so quick. When you think about unlimited throughput, and speed, and storage, on a global basis for your services, it's unprecedented. >> Does your service cover software as a service as well? We do, I mean, we're a SAS company ourselves. So, as you know, many SAS companies are now providing services into the cloud. We could be collecting data from those services too. >> What's the future hold then for Cloud Health? Where do you want to take this company? >> I think that in beginning, I said we're the de facto standard for cloud service management. It's hard to claim you're really the de facto standard. Especially when we're a private company. I think what we want to do is continue to provide value, continue to innovate, continue to have that domain expertise, and when you look across the whole governance spectrum, about all these different systems, all these cloud providers, all these different data sources, it's absolutely immense. I think that always having that single pane of glass so that people can really get the visibility they need to optimize their services, we're going to be a very large company just doing that. >> I understand you have some ambitious growth plans this year in terms of the number of employees and also moving your headquarters. >> We do, I mean, I've only been on board for what, two and a half weeks, and there's already been 10 people hired since I've been there, so that's the pace of hiring right now. I think we'll end the year at about 240 employees, so probably hired about 80 employees, and then we are moving early next year, we're moving Fort Point to Downtown Crossing. So we got to accommodate them all. >> For those of you who are not familiar with Boston, Downtown Crossing is the center of town, and Four Point is the hot new area where GE is building it's new headquarters. In terms of how your business category develops, do you see this as a continuing to be a major independent category, type of services you provide, or do you think cloud vendors will ultimately acquire companies like yours and offer these services on their own? >> I think both is going to happen. I think cloud vendors will acquire companies who do stovepipe, perhaps functionality, for a certain area, but no cloud vendor's going to be able to offer the cross multi-cloud or hybrid cloud experience that we do. I think you're going to see both, but absolutely, the ability to manage multi and hybrid cloud environments is the key. >> It's something I always ask our Boston based guests, what are the advantages of being based in Boston? >> Well the advantage is absolutely huge, especially in this day and age. Boston has got an immense talent pool coming out every single year from universities, and that talent pool now wants to stay in Boston as opposed to move to other places. Because the city has gone through rejuvenation, it's a vibrant city, it's an invested in city, you mentioned GE, there's other companies moving here, it's a great time to be here, you've got many success points in the high tech arena such as HubSpot and Wayfair, and LogMeIn, publicly traded companies offering great opportunities, so I think the pace of innovation here is happening at a tremendous clip, so Boston's a great place to be. >> Glad to hear it, welcome to town. Congratulations on your growth, and much success to you. >> Tom: Great, well thank you very much for having me. >> Cloud complexity, simplified. I'm Pual Gillin, this is theCUBE. (upbeat music)