>> Announcer: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2017. Presented by AWS, Intel, and our ecosystem of partners. >> Well we are back live here at the Sands Expo Center. We're of course in Las Vegas live at re:Invent. AWS putting on quite a show here. Day one of three days of coverage you'll be seeing right here on theCUBE. I'm John Walls along with Justin Warren. And we're now joined by a couple folks from Datameer. Justin Rodatus who's the CEO of that company, and Pooja Palan who's the Senior Product Manager. And Christian and Pusha thanks for being with us. Good to have you here on theCUBE. >> Thanks for having us. >> So you were cube-ing at just recently up at New York, Christian. >> Yeah absolutely we were seeing your guys in New York and we had actually, we've done some work with a couple of customers probably two weeks ago in Palo Alto I believe. >> I don't know how we can afford you. I mean I'm gonna have to look into our budget. >> Christian: Happy to be here again. >> Okay no it is great, thank for taking the time here. I know this is a busy week for you all. First off let's talk about Datameer in general just to let the audience at home known in case they're not familiar with what you're doing from a core competency standpoint. And let's talk about what you're doing here. >> Absolutely, I mean Datameer was founded eight years ago and Datameer was only an onset of the big data wave that started in the 2009 and 2010 time frame. And Datameer was actually the first commercial platform that provided a tool set to enable our customers to consume enterprise scale Hadoop solutions for their enterprise analytics. So we do everything from ingesting the data into the data lake or we're preparing the data for a consumption by analytics tools throughout the enterprise. And we just recently also launched our own visualization capabilities for sophisticated analysis against very large data sets. We also are capable of integrating machine learning solutions and preparing data for machine learning throughout the organization. And probably the biggest push is into the cloud. And we've been in the cloud for couple of years now, but we see increased momentum from our customers in the market place for about 15 months now I would say. >> So before we dive a little deeper here I'm just kind of curious about your work in general. It's kind of chicken and the egg right? You're trying to come up with new products to meet customer demand. So are you producing to give them what you think they need or are you producing on what they're telling you that they need? How does that work as far as trying to keep up with-- >> You know I can kick this off. So it's actually interesting that you ask this because the customers that did interviews with you guys two weeks ago were part of our customer advisory council. So we get direct feedback from leading customers that do really sophisticated things with Datameer. They are at the forefront of developing really mind blowing analytical applications for high value use cases throughout their organizations. And they help us understanding where theses trends go. And to give you an example. So I was recently in a meeting with a Chief Data Officer of a large global bank in London. And they have kicked off 32 Hadoop projects throughout the organization. And what he told me is just these projects will lead to an expansion of the physical footprint of the data centers in the UK by 30%. So in (mumbles) we are not in the data center business, we don't want this, we need other people to take care of this. And they've launched a massive initiative with Amazon to bring a big chunk of their enterprise analytics into AWS. >> It sounds like you're actually really ahead of the curve in many ways 'cause of the explosion in machine learning and AI, that data analytics side of things. Yeah we had big data for a little while, but it's really hitting now where people are starting to really show some of the amazing things that you can do with data and analysis. So what are you seeing from these customers? What are some of the things that they're saying, actually this thing here, this is what we really love about Datameer, and this is something that we can do here that we wouldn't be able to do in any other way. >> Shall I take that? So when it comes to heart of the matter, there's like you know three things that Datameer hits on really well. So in terms of our user personas, we look at all of our users, our analysts, and data engineers. So what we provide them with that ease of use, being able to take data from anywhere, and be able to use any multiple analytic capabilities within one tool without having to jump around in all different UI's. So it's like ease of use single interface. The second one that they really like about us is being able to not have to, whatever being able to not have to switch between interfaces to be able to get something done. So if they want to ingest data from different sources, it's one place to go to. If they want to access their data, all of it is in the single file browser. They want to munch their data, prepare data, analyze data, it's all within the same interface. And they don't have to use 10 different tools to be able to do that. It's a very seamless workflow. And the same token, the third thing which comes up is that collaboration. It enables collaboration across different user groups within the same organization. Which means that we are totally enabling the data democratization which all of the self service tools are trying to promote here. Making the IT's job easier. And that's what Datameer enables. So it's kind of like a win-win situation between our users and the IT. And the third thing that I want to talk about, which is the IT, making their lives easier, but at the same time not letting them go off, leaving the leash alone. Enabling governance, and that's a key challenge, which is where Datameer comes in the picture to be able to provide enterprise ready governance to be able to deploy it across the board in the organization. >> Yeah, that's something that AWS is certainly lead in, is that democratization of access to things so that you can as individual developers, or individual users go and make use of some of these cloud resources. And seeing here at the show, and we've been talking about that today, about this is becoming a much more enterprise type issue. So being able to do that, have that self service, but also have some of those enterprise level controls. We're starting to see a lot of focus on that from enterprises who want to use cloud, but they really want to make sure that they do it properly, and they do it securely. So what are some of the things that Datameer is doing that helps customers keep that kind of enterprise level control, but without getting in the way of people being able to just use the cloud services to do what they want to do? So could you give us some examples of that maybe? >> I let Puja comment on the specifics on how we deploy in AWS and other cloud solutions for that matter. But what you see with on premise data lakes, customers are struggling with it. So the stack has become outrageously complicated. So they try to stitch all these various solutions together. The open source community I believe now supports 27 different technology platforms. And then there's dozens over dozens of commercial tools that play into that. And what they want, they actually just want this thing to work. They want to deploy what they used from the enterprise IT. Scalability, security, seamlessness across the platforms, appropriate service level agreements with the end user communities and so on and so forth. So they really struggle to make this happen on premise. The cloud address a lot of these issues and takes a lot of the burden away, and it becomes way more flexible, scalable, and adjustable to whatever they need. And when it comes to the specific deployments and how we do this, and we give them enterprise grade solutions that make sense for them, Puja maybe you can comment on that. >> Sure absolutely, and more specific to cloud I would love to talk about this. So in the recent times one of our very first financial services customers went on cloud, and that pretty much brings us over here being even more excited about it. And trust me, even before elasticity, their number one requirement is security. And as part of security, it's not just like, one two three Amazon takes care of it, it's sorted, we have security as part of Datameer, it's been deployed before it's sorted. It's not enough. So when it comes to security it's security at multiple levels, it's security about data in motion, it's security about data at rest. So encryption across the board. And then specifically right now while we're at the Amazon conference, we're talking about enabling key management services, being able to have server-side encryption that Amazon enables. Being able to support that, and then besides that, there's a lot of other custom requirements specifically around how do you, because it's more of hybrid architecture. They do have applications on-prem, they do have like a deployed cloud infrastructure to do compute in the cloud as it may needed for any kind of worst workloads. So as part of that, when data moves between, within their land to the cloud, within that VPC, that itself, those connectivity has to be secured and they want to make sure that all of those user passwords, all of that authentication is also kind of secure. So we've enabled a bunch of capabilities around that, specifically for customers who are like super keen on having security, taking care of rule number one, even before they go. >> So financial services, I mean you mentioned that and both of you are talking about it. That's a pretty big target market for you right? I mean you've really made it a point of emphasis. Are there concerns, or I get it (mumbles) so we understand how treasured that data can be. But do you provide anything different for them? I mean is the data point is a point as opposed to another business. You just protect the same way? Or do you have unique processes and procedures and treatments in place that give them maybe whatever that additional of oomph of comfort is that they need? >> So that's a good question. So in principle we service a couple of industries that are very demanding. So it's financial services, it's telecommunication and media, it's government agencies, insurance companies. And when you look at the complexities of the stack that I've described. It's very challenging to make security, scalability in these things really happen. You can not inherit security protocols throughout the stack. So you stack a data prep piece together with a BI accelerator with an ingest tool. These things don't make sense. So the big advantage of Datameer is it's an end to end tool. We do everything from ingest, data preparation to enterprise scale analytics, and provide this out of the box in a seamless fashion to our customers. >> It is fascinating how the whole ecosystem has sort of changed in what feels like only a couple of years and how much customers are taking some of these things and putting them together to create some amazing new products and new ways of doing things. So can you give us a bit of an idea of, you were saying earlier that cloud was sort of, it was about two years ago, three years ago. What was it that finally tipped you over and said you know what we gotta do this. We're hearing a lot of talk about people wanting hybrid solutions, wanting to be able to do bursting. What was it really that drove you from the customer perspective to say you know what we have to do this, and we have to go into AWS? >> Did you just catch the entire question? Just repeat the last one. What drove it to the cloud? >> Justin: Yeah, what drove you to the cloud? >> John: What puts you over the top? >> I mean, so this is a very interesting question because Datameer was always innovating ahead of the curve. And this is probably a big piece to the story. And if you look back. I think the first cloud solutions with Microsoft Azure. So first I think we did our own cloud solution, and we moved to Microsoft Azure and this was already maybe two and a half years ago, or even longer. So we were ahead of the curve. Then I would say it was even too early. You saw some adoption, so we have a couple of great customers like JC Penny is already operating in the cloud for us, big retail company, they're actually in AWS. National Instruments works in Microsoft Azure. So there's some good adoption, but now you see this accelerating. And it's related to the complexity of the stack, to the multiple points of failure of on premise solutions to the fact that people want, really they want elasticity. They want flexibility in rolling this out. The primary, interestingly enough, the primary motivators actually not cost. It's really a breathable solution that allows them to spin up clusters, to manage certain workloads that come for a compliance report every quarter. They need another 50 notes, spin them up, run them for a week or two and spin them down again. So it's really the customers are buying elasticity, they're buying elasticity from a technology perspective. They're buying elasticity from a commercial perspective. But they want enterprise grade. >> Yeah we certainly hear customers like that flexibility. >> And I think we are now at a tipping point where customers see that they can actually do this in a highly secure and governed way. So especially our demanding customers. And that it really makes sense from a commercial and elasticity perspective. >> So you were saying that's what they're buying, but they're buying what you're selling. So congratulations on that. Obviously it's working. So good luck, continued success down the road, and thanks for the time here today, we appreciate it. >> Absolutely, thanks for having us. >> John: Always good to have you on theCUBE. >> It's cocktail time, thanks for having us. >> It is five o' clock somewhere, here right now. Back with more live coverage from re:Invent. We'll be back here from Las Vegas live in just a bit. (electronic music)

>>Hello and welcome to the AWS partners showcase season one, episode two. I'm your host of the cube John ferry. We're here with two great guests who John Kumar, CEO of and Sabina Joseph, the general manager of AWS. Welcome to the show. Welcome to welcome to the cube, >>John. Good to see you >>Again. Great to see both of you both cube. Alumna's great to see how the businesses is going, going very well. Cloud scale, continuing to dominate Columbia is doing extremely well. Tell us more about what's going on in Columbia. What's your mission? What kinds of use cases are you seeing? Napa John, that's helping you guys keep your growth trajectory and solve your customer problems. >>Yeah. Firstly, thank you, John. Thank you, Sabina. Great to be here is a backup as a service platform. That's built natively on AWS for AWS, and we do support other use cases beyond AWS. But our primary mission is to basically deliver, you know, a ransomware data protection solution, you know, on AWS for AWS customers. Right? So if we think about it, you know, one of the things that's, you know, typically holding back any company to put mission critical workloads on a fantastic platform, a public cloud platform like AWS is to make sure that the data is protected in the event of any attack. And it's also done with extreme amount of simplicity, right? So that nobody is doing the heavy lift of doing backup themselves, right? So that's what really drew me or provides. It's a service. It's a turnkey service that provides, you know, data protection on AWS, whatever. >>Well, you're a frequent cube alumni. We're always talking about the importance of that, but I want to ask you this year more than ever, you're seeing it at the center of the conversation built in from day one, you're seeing a lot more threats, certainly mentioned ransomware and more there's more and more online attacks that's impacting this particular area more than ever before. Can you comment on what your focus has been this year around that? >>Yeah, I see it. If you think about tumor's evolution, our primary mission has been to go and protect every data source, but guess what? Right with more and more move to the public cloud and you look just AWS is journey and that pioneer in public cloud going from, you know, whatever 3 billion in revenues, 10 years ago to north of 70 billion run rate today, there's so much of data that is in the public cloud and the, and the most important thing that customers need is they want to free themselves from going and protecting this data themselves. Right? And, and there's a lot of scale in these environments, right? If you look at customers running hundreds of thousands of AWS accounts across every region on AWS, and if you give them that kind of flexibility and that kind of scale, what they want is give me a turnkey solution that just allows me to go and protect all of these workloads running across all of these regions in a service that takes the data out of my accounts separately in an air gap fashion, right. And that's really what we basically provide. And that's what we focused on over the last 12 months. Right? So if you look at what we have done is we've gone after every important service on AWS TC to EBS RDS, S3, dynamo, sequel databases, and other databases running on top of BC too. So now that becomes the comprehensive set of things that somebody needs to use to really deliver an application on top of the public cloud. And that's where we want for, >>And the growth has been there and the results on Amazon because of the refactoring has been huge. Can you share any examples of some successes that you've had with, with the AWS refactoring and all that good stuff going on? >>Yeah. I mean, I think that what we have seen is, you know, customers that basically told us that before you guys existed, we had to go and build these things ourselves, right. Again, you know, they had all the, the, the blocks to go and do it themselves, but it was so much of a heavy lift to go and do it themselves. And again, they didn't want to be in a, you know, in that business. So, so what we have done essentially for, and we have, you know, we have some joint customers at a pretty massive scale that basically have said that, okay, let me just use your solution to protect my critical assets. Like, you know, things, you know, sitting in S3 and really, you know, we'll use gloomy as a, as a >>Yeah, I think that's a great example of the refactoring Sabina. Gotta, I gotta ask you, you obviously you're at the center of this. You have your hand on the wheel of the partnerships and all the innovators out there. The growth of AWS just has been spectacular because there's value being created. Again, companies are refactoring their business on the cloud and you're at the center of it. So talk about the partnership with Clooney. Can you tell us how it all started and where it's going? >>Yeah, thanks for having me here, John, and good to see you again, Fujian, if I'm not mistaken for John, we met each other at the San Francisco summit, the AWS San Francisco summit, actually I believe it was in 2016 or 2017. You can correct me if I'm wrong here, but yes, I think so. It was, it was in the 8% a month of April. I still remember it. And that's when, you know, you kind of mentioned to me about and this modern backup as a service solution that you were creating, you're still in stealth mode. So you couldn't talk a lot about it. And B started to engage deeply on the partnership, right from 2017. And initially we were kind of focused around helping Colombia build a solution using our well-architected review. And then as soon as we all came out of stealth mode, we started to engage more deeply around deeper integrations and also on go to market activities. >>As you know, AWS has a very prescriptive approach to our partnerships. So we started to work with around the five pillars of security, reliability, cost optimization, performance, and operational excellence to really help them tune the solution on AWS. And we also started to engage with our service teams and I have to thank Paul John and his team here. They really embraced those deeper and broader integrations, many services that Pooja mentioned, but also specifically want to mention S3 EBS. And our Columbia was also a launch partner for AWS outpost when AWS in fact, launched outpost. So I want to kind of commend CLU, CLU MEO, and the entire team kind of embracing this technology and innovation and this modern backup as a service approach. And also also embracing how we want to focus on the five key pillars that I mentioned. >>And that's a great example of success when you ride the wave, which I talk about the ACLU, Colombia trends in the data protection, because one of the things that you pointed out earlier is the ransomware. Okay. That's a big one, right? That's a big, hot area. How, how is the cloud, first of all, how is that going? And then how has the cloud equation changed the ransomware defense and protection piece of it? >>Yeah. Now I just, I wonder I had a little bit on what Sabina mentioned before I answered the question, John, if you don't mind. Sure. I think that collaboration is where is the reason why we are here today, right? Like if you think about it, like we were the first design partners to go and build, you know, the EBS direct API, right. And we work closely with the EBS teams, not just for the API, but the cost structure of it. How would somebody like us use it? So we are at the bleeding edge of some of these services that we are using and that has enabled us, you know, to be where we are today. So again, thank you very much to be enough for this fantastic partnership. And again, there's so much to go and do to really go and nail this in a, in a, in a, in a great way on, on the public cloud. >>So now coming back to your question, John, you know, fundamentally, if you see right, you know, what happened is when, when, when customers move to the public cloud, you know, right there, you know, the ease of use with which, you know, AWS provides these services, right? And the consumption of these services actually drives some amazing behavior, right? Where people actually want to go and build, build, build, and build. But then it comes a time where somebody comes in and says, okay, you know, are you compliant? Right. You know, do you have the right compliance in place? You have all these accounts that you have, but what is running in each of these accounts, you have visibility in those accounts. And are these accounts that the data in these accounts is this gap, right? This is getting air gap in the same region, or does it need to be across regions? >>Right. You know, I'm in the east, do I need to, you know, have an air gap in the west and so on and so forth. Right? So all of these, you know, confluence of all these things come in and by the, all these problems existed in on-premise world, they get translated in, in the public cloud, where do I need to replicate my data, doing it to back it up? Do I need air gapped in a, like an on-prem world? You had a data domain of plans, which was separate from your primary storage for a reason, same similar something similar now needs to happen here for compliance reasons and for ransomware reason. So a lot of parallels here is just that here we are, it almost feels like, you know, as they say, right, the more things changed. The more they remain the same. That's what it is in the public cloud again. >>Well, that's a good point. I mean, let's take that example of on premises versus the cloud. Also, the clouds got more scale too, by the way. So now you've got regions, this is a common problem that customers are having, you can build your own and, or use solutions, but if you don't get ahead of it, the compliance question can bite you in the, you know what, because you then got to go back and retrofit everything. So, so that's kind of what I hear a lot on my end is like, okay, I want to be compliant from day one. I want to have an answer when asked, I don't want to have to go to old techniques that don't fit the cloud. That comes up a lot. What's your answer to that? >>Yeah, no, no. We were pretty much right. I think it's like, you know, when it, when it comes to compliance and all of these things, you know, people at the end of the day are looking for that same foundation of, of things. The same questions are asked for an encryption. You know, you know, I is my data where it needs to be when it needs to be right. What is my recovery point? Objective? What is my recovery time objective? All of these things basically come together. And now, as you said, it's just the scale that you're dealing is, is extremely different in the cloud and the, and the services, right? The easier it is that, you know, it is to use these services. And especially what AWS does, it makes it so easy. So compelling that same ease of use needs to get translated with a SAS service, like what we are doing with data protection, right? That that ease of use is very important. You have to preserve that sanctity >>Sabina. Let's get back to you. You mentioned earlier about the design partner, that benefits for Colombia. Now let's take it to the next level. As customers really realize they have a problem, they need solutions and you're on the AWS side. So you gotta have the answers for the customers. You've got to put people together, make things work. There's a variety of things that you guys offer. What are some of the different facets of the ISV or the partner programs that you offer to partners like Clooney, you know, that they can benefit from? >>Absolutely John, we believe in a win-win approach to the partnerships because that's what makes partnerships durable over time. We're always striving to do better here. And we continue to broaden our investments. As you know, John, the AWS management team, right from Adam Phillipsky, our CEO down firmly believe that partners are critical to our success, our longterm success, and as partners like CLU MEO work to lean in with us with more investment resources, our technology innovation. We also ensure that we are doing our part by providing value back to Cleo about a few years ago, as you might recall, right. We really did a lot of investment in our sales team on the AWS side. Well, one of the tanks me and also our partners observed is while we were making investments in the AWS sales team, I don't think we were doing a great job at helping our partners with reaching out to those customers. >>What we call as co-sale and partners gave us feedback on this. We are very partner and customer feedback driven, and we introduced in fact, a new role called the ISP success manager, ISS, who are basically embedded in our field. And they work with partners to help them close opportunities. And also net new opportunities are we've also in 2020. I believe that re-invent, we launched the ISB accelerate program whereby we offer incentives to the AWS field team to work with our partners to close existing opportunities and also bring in net new opportunities. So all of this has led to closer collaboration in the field between both our field teams, Muir's field team and our field team, but also accelerated mutual customer wins. I'm not saying that we are doing everything great. We still have a long ways to go. And we are constantly getting feedback from cluneal and also some of our other key partners, and we'll continue to get better at it. But I think the role of the ISV success manager and also the ISP accelerate program has been key to bringing in cold cell success. >>Well, John, what's your take on, is this a good partnership for you? I mean, see, the wave of Vegas has got the growth numbers. You mentioned that, but from a partnership standpoint, you're closing business, they got scale. Is it working? How do you organize your company to take advantage of these benefits? Can you share your thoughts? >>Absolutely not. We have embraced the ecosystem wholeheartedly 100%, but if you think about it, what we have done is look at our offering on AWS marketplace. There's an example, right? We are the only company I would say in our domain, obviously that routes our entire business through AWS marketplace. Whether obviously we get a lot of organic benefit from AWS marketplace, people go and search for a solution and from your shows up, and obviously they go and onboard self onboard themselves, and guess what? We let them self onboard themselves. And we rely on AWS's billing automatically. So you don't need to talk to us. You can just get billed automatically in your AWS bill and you get your data protection solution. Or if you directly reached out to us, guess what we do. We actually route you through AWS marketplace. All the onboarding is just to one place and it's a fantastic experience. >>So we have gone like all in, on that experience and completely like, you know, internalized that that's the right way to do things. And of course, thanks to, you know, Sabina's team and the marketplace team to create that platform so that we could actually plug it into it. But that's the kind of benefits that we have that we have, you know, taken advantage of a DWI. That's one example, another example that Sabina mentioned, right, which is the whole ACE program. We put a ton of registrations on AIS and with all the wins that we get on AWS, they could broadcast it to the sellers. So that creates its own vicious cycle in terms of more coming into the pipeline and more closing in. So, so these are just two small examples, but there's other examples that we look at our recent press release, where AWS, you know, when we, when we launched yesterday data protection and backup, the GM of AWSs three supported us in the press release. So there's things like that, that it's a, it's a fantastic collaboration. That's working really well for our joint customers. Sorry. >>And tell us something about the partnership between 80 of us, including, you know, that people might not be aware of some of the things that Poojan said that they're different out there that, that are, co-selling go marketing, that you guys offer people you guys work together on. >>Yeah. The, the ISV accelerate program that was created, it was really created with partners like Klunier in mind, our SAS partners. I think that that is something very, very unique between our partnership and, you know, I, I want to double click on what Poojan said, which is riding their opportunities through marketplace, right? All of their opportunities. That is something pretty unique. They understand the richness of the platform and also how customers are procuring software today in this world. And they've embraced that. And we really appreciate that. And I want to say, you know, another thing about Qumulo is they're all in on AWS, which is another unique thing. There are not a lot of, I would say all in partnerships in my world and I manage infrastructure, business apps, applications, and industry partnerships from the Americas globally. And all of those things are very, very unique in our partnership, which has led to success. Right. We started very, very early stage when Columbia was in stealth mode in 2017 and look where we've come today. And it's really kudos to Paul, John and his entire team for believing in the partnership for leaning in with us and for placing that trust with us. >>Awesome. Pooja, any final words you'd like to share for folks out there about the conversation and what's going on in Columbia? >>Yeah, no, absolutely. You know, as I said, I think we have been fortunate to be very early adopters of all these technologies and go and really build what a true cloud native solution has to be. Right. And, and again, right, you know, this is what customers are really looking for. And people are looking for, you know, at least on the data protection side, you know, ransomware air gap solution, people are looking for a solution natively built on the cloud because that's the only way a solution can deliver something at the scale and the cost structure that is needed to have, you know, a data protection solution in the public cloud. So, so this has been just a fantastic thing end to end, you know, for us overall. And we really look forward to, you know, going, you know, doing much more with AWS as we essentially go and scale, >>I have to ask, but before we, before we go, cause you're the CEO of the company and founder having all that backend infrastructure from Amazon, just on the resources, great. It creates a market for your product, but also the sales piece, you know, they got the marketplace, you mentioned, that's a big expense that you don't have to carry, you know, and you get revenue and top line. I mean, that's an impact for startups out there and growing companies. That's a pretty big deal. What's your, what's your advice to folks out there who are trying to think about the buy versus use the leverage of the, of the marketplace, which is, which is at large scale, because as a CEO, you're, you've got to make these decisions. What's your opinion on that? >>It's not, it's not as, as easy as I make it sound to do your own part. You know, AWS is, is, is, is huge, right? It's huge. And so we have to do our part to educate everybody within the, you know, even the AWS seller base to make sure that they internalize the fact that this is the right solution for the customers, for our joint customers, right? So we have to do that all day long. So there's no running away the no shortcut to everything, but obviously AWS does its part to make it very, as easy as possible, but there's a lot of heavy lifting we still have to do. And I think that'll only become easier and easier over the next few years >>And Sabina your takeout at AVS. You've got a great job. You were with all the hot growth companies. This is the big wave we're on right now with the cloud next generation clouds here, a lot of opportunities. >>Absolutely. And it's, and it's thanks to Pooja and, and partners like Lumeo that really understand what it takes to build a cloud native solution because it's part of it is building. And part of it is the co-selling go-to-market engine and embracing both of that is critical to success. >>Well, thank you both for coming on this journey here on the cube, as part of the showcase, push on. Great to see you to being a great to see you as well. And thanks for sharing that insight. Appreciate it. >>Thank you very much. >>Okay. AWS partners showcase speeding innovation with AWS. I'm John Ford, your host of the cube. Thanks for watching.

>>Hey, we're here in the second manufacturing drill down session with Michael Gerber. He was the managing director for automotive and manufacturing solutions at Cloudera. And we're going to continue the discussion with a look at how to lower costs and drive quality in IOT analytics with better uptime and hook. When you do the math, it's really quite obvious when the system is down, productivity is lost and it hits revenue and the bottom line improve quality drives, better service levels and reduces lost opportunities. Michael. Great >>To see you take it away. >>All right, guys. Thank you so much. So I'd say we're going to talk a little bit about connected manufacturing, right? And how those IOT IOT around connected manufacturing can do as Dave talked about improved quality outcomes for manufacturing and flute and improve your plant uptime. So just a little bit quick, quick, little indulgent, quick history lesson. I promise to be quick. We've all heard about industry 4.0, right? That is the fourth industrial revolution. And that's really what we're here to talk about today. First industrial revolution, real simple, right? You had steam power, right? You would reduce backbreaking work. Second industrial revolution, mass assembly line. Right. So think about Henry Ford and motorized conveyor belts, mass automation, third industrial revolution, things got interesting, right? You started to see automation, but that automation was done essentially programmed your robot to do something and did the same thing over and over and over irrespective about of how your outside operations, your outside conditions change fourth industrial revolution, very different, right? >>Cause now we're connecting, um, equipment and processes and getting feedback from it. And through machine learning, we can make those, um, those processes adapted right through machine learning. That's really what we're talking about in the fourth industrial revolution. And it is intrinsically connected to data and a data life cycle. And by the way, it's important, not just for a little bit of a slight issue, there we'll issue that, but it's important. Not for technology's sake, right? It's important because it actually drives very important business outcomes. First of all, quality, right? If you look at the cost of quality, even despite decades of, of, of, uh, companies and manufacturers moving to improve while its quality prompts still accounts for 20% of sales, right? So every fifth of what you meant are manufactured from a revenue perspective, do back quality issues that are costing you a lot planned downtime, cost companies, $50 billion a year. >>So when we're talking about using data and these industry 4.0 types of use cases, connected data types of new spaces, we're not doing it just merely to implement technology. We're doing it to move these from members, improving quality, reducing downtime. So let's talk about how a connected manufacturing data life with what like, right, but this is actually the business. The cloud area is, is in. Let's talk a little bit about that. So we call this manufacturing edge to AI. This is analytics life cycle, and it starts with having your plants, right? Those plants are increasingly connected. As I say, sensor prices have come down two thirds over the last decade, right? And those sensors are connected over the internet. So suddenly we can collect all this data from your, um, manufacturing plants, and what do we want to be able to do? You know, we want to be able to collect it. >>We want to be able to analyze that data as it's coming across. Right? So, uh, in scream, right, we want to be able to analyze it and take intelligent time actions. Right? We might do some simple processing and filtering at the edge, but we really want to take real-time actions on that data. But, and this is the inference part of things are taking about time, but this, the ability to take these real-time actions or, um, is actually the result of a machine learning life cycle. I want to walk you through this, right? And it starts with, um, ingesting this data for the first time, putting it into an enterprise data lake, right in that data lake enterprise data lake can be either within your data center or it could be in the cloud. You're going to, you're going to ingest that data. You're going to store it. >>You're going to enrich it with enterprise data sources. So now you'll have say sensor data and you'll have maintenance repair orders from your maintenance management systems. Right now you could start to think about, you're getting really nice data sets. You can start to say, Hey, which sensor values correlate to the need for machine maintenance, right? You start to see the data sets. They're becoming very compatible with machine learning, but so you, you bring these data sets together. You process that you align your time series data from your sensors to your timestamp data from your, um, you know, from your enterprise systems that your maintenance management system, as I mentioned, you know, once you've done that, we can put a query layer on top. So now we can start to do advanced analytics query across all these different types of data sets. But as I mentioned to you, and what's really important here is the fact that once you've stored one history sets data, you can build out those machine learning models. >>I talked to you about earlier. So like I said, you can start to say, which sensor values drove the need of correlated to the need for equipment maintenance for my maintenance management systems, right? And you can build out those models and say, Hey, here are the sensor values of the conditions that predict the need for maintenance. Once you understand that you can actually then build out the smiles, you could deploy the models after the edge where they will then work in that inference mode, that photographer, I will continuously sniff that data as it's coming and say, Hey, which are the, are we experiencing those conditions that, that predicted the need for maintenance? If so, let's take real-time action, but schedule a work order and equipment maintenance work order in the past, let's in the future, let's order the parts ahead of time before that piece of equipment fails and allows us to be very, very proactive. >>So, >>You know, we have, this is a, one of the Mo the most popular use cases we're seeing in terms of connected, connected manufacturing. And we're working with many different manufacturers around the world. I want to just highlight. One of them is I thought it's really interesting. This company is for SIA for ECA is the, um, is the, was, is the, um, the, uh, a supplier associated with Pooja central line out of France. They are huge, right? This is a multinational automotive, um, parts and systems supplier. And as you can see, they operate in 300 sites in 35 countries. So very global, um, they connected 2000 machines, right. Um, and they once be able to take data from that. They started off with learning how to ingest the data. They started off very well with, um, you know, with, uh, manufacturing control towers, right? To be able to just monitor the data firms coming in, you know, monitor the process. >>That was the first step, right. Uh, and you know, 2000 machines, 300 different variables, things like, um, fibrations pressure temperature, right? So first let's do performance monitoring. Then they said, okay, let's start doing machine learning on some of these things to start to build out things like equipment, um, predictive maintenance models, or compute. What they really focused on is computer vision, wilding inspection. So let's take pictures of parts as they go through a process and then classify what that was this picture associated with the good or bad quality outcome. Then you teach the machine to make that decision on its own. So now, now the machine, the camera is doing the inspections beer. And so they both have those machine learning models. So they took that data. All this data was on-prem, but they pushed that data up to the cloud to do the machine learning models, develop those machine learning models. >>Then they push the machine learning models back into the plants where they, where they could take real-time actions through these computer vision, quality inspections. So great use case, a great example of how you can start with monitoring, move to machine learning, but at the end of the day, or improving quality and improving, um, uh, equipment uptime. And that is the goal of most manufacturers. So with that being said, um, I would like to say, if you want to learn some more, um, we've got a wealth of information on our website. You see the URL in front of you, please go there and you'll learn. There's a lot of information there in terms of the use cases that we're seeing in manufacturing and a lot more detail and a lot more talk about a lot more customers we'll work with. If you need that information, please do find it. Um, with that, I'm going to turn it over to Dave, to Steve. I think you had some questions you wanted to run by. >>I do, Michael, thank you very much for that. And before I get into the questions, I just wanted to sort of make some observations that was, you know, struck by what you're saying about the phases of industry. We talk about industry 4.0, and my observation is that, you know, traditionally, you know, machines have always replaced humans, but it's been around labor and, and the difference with 4.0, and what you talked about with connecting equipment is you're injecting machine intelligence. Now the camera inspection example, and then the machines are taking action, right? That's, that's different and, and is a really new kind of paradigm here. I think the, the second thing that struck me is, you know, the costs, you know, 20% of sales and plant downtime costing, you know, many tens of billions of dollars a year. Um, so that was huge. I mean, the business case for this is I'm going to reduce my expected loss quite dramatically. >>And then I think the third point, which we turn in the morning sessions and the main stage is really this, the world is hybrid. Everybody's trying to figure out hybrid, get hybrid, right. And it certainly applies here. Uh, this is, this is a hybrid world you've got to accommodate, you know, regardless of, of where the data is. You've gotta be able to get to it, blend it, enrich it, and then act on it. So anyway, those are my big, big takeaways. Um, so first question. So in thinking about implementing connected manufacturing initiatives, what are people going to run into? What are the big challenges that they're gonna, they're gonna hit? >>You know, there's, there's there, there's a few of the, but I think, you know, one of the, uh, one of the key ones is bridging what we'll call the it and OT data divide, right. And what we mean by the it, you know, your, it systems are the ones, your ERP systems, your MES systems, right? Those are your transactional systems that run on relational databases and your it departments are brilliant at running on that, right? The difficulty becomes an implementing these use cases that you also have to deal with operational technology, right? And those are, um, all of the, that's all the equipment in your manufacturing plant that runs on its proprietary network with proprietary pro protocols. That information can be very, very difficult to get to. Right. So, and it's unsafe, it's a much more unstructured than from your OT. So the key challenge is being able to bring these data sets together in a single place where you can start to do advanced analytics and leverage that diverse data to do machine learning. >>Right? So that is one of the, if I had to boil it down to the single hardest thing in this, uh, in this, in this type of environment, nectar manufacturing is that that operational technology has kind of run on its own in its own world for a long time, the silos, um, uh, you know, the silos, uh, bound, but at the end of the day, this is incredibly valuable data that now can be tapped, um, um, to, to, to, to move those, those metrics we talked about right around quality and uptime. So a huge opportunity. >>Well, and again, this is a hybrid theme and you've kind of got this world, that's going toward an equilibrium. You've got the OT side, you know, pretty hardcore engineers. And we know, we know it. Uh, a lot of that data historically has been analog data. Now it's getting, you know, instrumented and captured. Uh, so you've got that, that cultural challenge. And, you know, you got to blend those two worlds. That's critical. Okay. So Michael, let's talk about some of the use cases you touched on, on some, but let's peel the onion a bit when you're thinking about this world of connected manufacturing and analytics in that space. And when you talk to customers, you know, what are the most common use cases that you see? >>Yeah, that's a good, that's a great question. And you're right. I did allude to it earlier, but there really is. I want people to think about, there's a spectrum of use cases ranging from simple to complex, but you can get value even in the simple phases. And when I talk about the simple use cases, the simplest use cases really is really around monitoring, right? So in this, you monitor your equipment or monitor your processes, right? And you just make sure that you're staying within the bounds of your control plan, right? And this is much easier to do now. Right? Cause some of these sensors are a more sensors and those sensors are moving more and more towards internet types of technology. So, Hey, you've got the opportunity now to be able to do some monitoring. Okay. No machine learning, we're just talking about simple monitoring next level down. >>And we're seeing is something we would call quality event forensic announces. And now on this one, you say, imagine I've got warranty plans in the, in the field, right? So I'm starting to see warranty claims, kick kickoff. And what you simply want to be able to do is do the forensic analysis back to what was the root cause of within the manufacturing process that caused it. So this is about connecting the dots by about warranty issues. What were the manufacturing conditions of the day that caused it? Then you could also say which other tech, which other products were impacted by those same conditions. And we call those proactively rather than, and, and selectively rather than say, um, recalling an entire year's fleet of the car. So, and that, again, also not machine learning where simply connecting the dots from a warranty claims in the field to the manufacturing conditions of the day, so that you could take corrective actions, but then you get into a whole of machine learning use case, you know, and, and that ranges from things like quality or say yield optimization, where you start to collect sensor values and, um, manufacturing yield, uh, values from your ERP system. >>And you're certain start to say, which, um, you know, which map a sensor values or factors drove good or bad yield outcomes. And you can identify those factors that are the most important. So you, um, you, you measure those, you monitor those and you optimize those, right. That's how you optimize your, and then you go down to the more traditional machine learning use cases around predictive maintenance. So the key point here, Dave is, look, there's a huge, you know, depending on a customer's maturity around big data, you could start something with monitoring, get a lot of value, start, then bring together more diverse data sets to do things like connect the.analytics then and all the way then to, to, to the more advanced machine learning use cases there's value to be had throughout. I >>Remember when the, you know, the it industry really started to think about, or in the early days, you know, IOT and IOT. Um, it reminds me of when, you know, there was the, the old days of football field, we were grass and, and a new player would come in and he'd be perfectly white uniform and you had it. We had to get dirty as an industry, you know, it'll learn. And so, so my question relates to other technology partners that you might be working with that are maybe new in this space that, that to accelerate some of these solutions that we've been talking about. >>Yeah. That's a great question that it kind of, um, goes back to one of the things I alluded earlier, we've got some great partners, a partner, for example, litmus automation, whose whole world is the OT world. And what they've done is for example, they've built some adapters to be able to catch it practically every industrial protocol. And they've said, Hey, we can do that. And then give a single interface of that data to the Patera data platform. So now, you know, we're really good at ingesting it data and things like that. We can leverage say a company like litmus that can open the flood gates of that OT data, making it much easier to get that data into our platform. And suddenly you've got all the data you need to, to, to implement those types of industry 4.0, our analytics use cases. And it really boils down to, can I get to that? Can I break down that it OT, um, you know, uh, a barrier that we've always had and bring together those data sets that we can really move the needle in terms of improving manufacturing performance. >>Okay. Thank you for that last question. Speaking to moving the needle, I want to lead this discussion on the technology advances. I'd love to talk tech here, uh, are the key technology enablers, and advancers, if you will, that are going to move connected manufacturing and machine learning forward in this transportation space, sorry, manufacturing in >>A factory space. Yeah. I knew what you meant in know in the manufacturing space. There's a few things, first of all, I think the fact that obviously I know we touched upon this, the fact that sensor prices have come down and have become ubiquitous that number one, we can w we're finally being able to get to the OT data, right? That's that's number one, number, number two, I think, you know, um, we, we have the ability that now to be able to store that data a whole lot more efficiently, you know, we've got back way capabilities to be able to do that, to put it over into the cloud, to do the machine learning types of workloads. You've got things like if you're doing computer vision, while in analyst respect GPU's to make those machine learning models much more, uh, much more effective, if that 5g technology that starts to blur at least from a latency perspective where you do your computer, whether it be on the edge or in the cloud, you've, you've got more, you know, super business critical stuff. >>You probably don't want to rely on, uh, any type of network connection, but from a latency perspective, you're starting to see, uh, you know, the ability to do compute where it's the most effective now. And that's really important. And again, the machine learning capabilities, and they believed the book to build a GP, you know, GPU level machine learning, build out those models and then deployed by over the air updates to your equipment. All of those things are making this, um, there's, you know, there's the advanced analytics machine learning, uh, data life cycle just faster and better. And at the end of the day, to your point, Dave, that equipment and processor getting much smarter, very much more quickly. Yep. We got >>A lot of data and we have way lower cost, uh, processing platforms I'll throw in NP use as well. Watch that space neural processing units. Okay. Michael, we're going to leave it there. Thank you so much. Really appreciate your time, >>Dave. I really appreciate it. And thanks. Thanks for, for everybody who joined us. Thanks. Thanks for joining.

and II just think about how data could be customer experience value propositions operations that improve profitability and strategic options for the business as it moves forward but that means openly either we're thinking about how we embed data more deeply into our operations that means we must also think about how we're going to protect that data so the business does not suffer because someone got a hold of our data or corrupted our data or that a system just failed and we needed to restore that data very quickly now what we want to be able to do is we want to do that in a way that's natural and looks a lot like a cloud because we want that cloud experience in our data protection as well so that's we're going to talk about with Klum you know today a lot of folks think in terms of moving all the data into the cloud we think increasingly we have to recognize a cloud is not a strategy for centralizing data but rather distributing data and being able to protect that data where it is utilizing a simple common cloud like experience it's becoming an increasingly central competitive need for a lot of digital enterprises the first conversation we had was with pooja Kumar who John is a CEO and co-founder of Kaleo let's hear a pooja I had to say about data value data services and Kumi Oh poo John welcome to the show thank you Peter nice to be here so give us the update in clue so comeö is a two year old company right we just recently launched out of stealth so so far you know we we came out with innovative offering which is a SAS solution to go and protect on premises you know VMware and BMC environments that's what we launched out of style two months ago we won our best of show when we came out of stealth in in VMware 2019 but ultimately we started with a vision about you know protecting data irrespective of where it resides so it was all about you know you know on-premises on cloud and other SAS services so one single service that protects data irrespective of where it resides so far we executed on on-premises VMware and BMC today what we are announcing for the first time is our protection to go and protect applications natively built on AWS so these are applications that are natively built on AWS that loomio as a service will protect irrespective of you know them running you know in one region or cross region cross accounts and a single service that will allow our customers to protect native AWS applications the other big announcement we are making is a new round of financing and that is testament to the interest in the space and the innovative nature of the platform that we have built so when we came out of stealth we announced we had raised two rounds of financing 51 million dollars in series a and Series B rounds of financing today what we are announcing is a Series C round of financing of 135 million dollars the largest I would say Series C financing for a SAS enterprise company especially a company that's a little over two years old Oh congratulations that's gonna buy a lot of new technology and a lot of customer engagement but what customers as I said up from what customers are really looking for is they're looking for tooling and methods and capabilities that allow them to treat their data differently talk a bit about the central importance of data and how it's driving decisions of Cluny oh yes so fundamentally you know when we built out the the data platform it was about going after the data protection as the first use case on the platform longer term the journey really is to go from a data protection company to a data management company and this is possible for the first time because you have the public cloud on your side if you truly built a platform for the cloud on the public cloud you have this distinct advantage of now taking the data that you're protecting and really leveraging it for other services that you can enable the enterprise for and this is exactly what enterprises are asking for especially as they you know you know make a transition from on-premises to the public cloud where they're powering on more and more applications in the public cloud and they really you know sometimes have no idea in terms of where the data is sitting and how they can take advantage of all these data sources that ultimately protecting well no idea where the data is sitting take advantage of these data sources presumably facilitate new classes of integration because that's how you generate value out of data that suggests that we're not just looking at protection as crucial and important as it is we're looking at new classes of services they're going to make it possible to alter the way you think about data management if I got that right and what are those new services yes it's it's a journey as I said right so starting with you know again data protection it's also about doing data protection across multiple clouds right so ultimately we are a platform even though we are announcing you know AWS you know application support today we've already done VMware and BMC as we go along you'll see us kind of doing this across multiple clouds so an application that's built on the cloud running across multiple clouds AWS ashore and GCP or whatever it might be you see as kind of doing data protection across in applications in multiple clouds and then it's about going and saying you know can we take advantage of the data that we are protecting and really power on adjacent use cases you know there could be security use cases because we know exactly what's changing when it's changing there could be infrastructure analytics use cases because people are running tens of thousands of instances and containers and VMs in the public cloud and if a problem happens nobody really knows what caused it and we have all the data and we can kind of you know index it in the backend analyze in the backend without the customer needing to lift a finger and really show them what happened in their environment that they didn't know about right so there's a lot of interesting use cases that get powered on because you have the ability to index all the data here you have the ability to essentially look at all the changes that are happening and really give that visibility to the end customer and all of this one-click and automating it without the customer needing to do much I will tell you this that we've talked to a number of customers of Cuneo and the fundamental choice the clue Meo choice was simplicity how are you going to sustain that even as you add these new classes of services that is the key right and that is about the foundation we have built at the end of the day right so if you look at all of our customers that have you know on boarded today it's really the experience we're in less than you know 15 minutes they can we start enjoying the power of the platform and the backend that we have built and the focus on design that we have is ultimately why we are able to do this with simplicity so so when we when we think about you know all the things we do in the back end there's obviously a lot of complexity in the back end because it is a complex platform but every time we ask ourselves the question that okay from a customer perspective how do we make sure that it is one click and easy for them so that focus and that attention to detail that we have behind the scenes to make sure that the customer ultimately should just consume the service and should not need to do anything more than what they absolutely need to do so that they can essentially focus on what adds value to their business takes a lot of technology a lot of dedication to make complex things really simple absolutely whoo John Kumar CEO and co-founder of coolio thanks very much for being on the cube Thank You bigger great conversation with poo John data value leading to data services now let's think a little bit more about how enterprises ultimately need to start thinking about how to manifest that in a cloud rich world Chad Kenney is the vice president and chief acknowledges of Cuneo and Chad and I had an opportunity to sit down and talk about some of the interesting approaches that are possible because of cloud and very importantly to talk about a new announcement that clue miios making as they expand their support of different cloud types let's see what Chad had to say the notion of data services has been around for a long time but it's being upended recast reformed as a consequence of what cloud can do but that also means that cloud is creating new ways of thinking about data services new opportunities to introduce and drive this powerful approach of thinking about digital businesses centralized assets and to have that conversation about what that means we've got Chad Kenny who's a VP and chief technologists of comeö with us today Chad welcome to the cube thanks so much for having me okay so let's start with that notion of data services and the role the clouds going to play Kumi always looked at this problem this challenge from the ground up what does that mean so if you look at the the cloud as a whole customers have gone through a significant journey we've seen you know that the first shadow IT kind of play out where people decided to go to the cloud IT was too slow it moved into kind of a cloud first movement where people realize the power of cloud services that then got them to understand a little bit of interesting things that played out one moving applications as they exist were not very efficient and so they needed to react attack certain applications second SAS was a core way of getting to the cloud in a very simplistic fashion without having to do much of whatsoever and so for applications that were not core competencies they realized they should go SACEM for anything that was a core competency they needed to really reaaargh attack to be able to take advantage of those you know very powerful cloud services and so when you look at it if people were to develop applications today cloud is the default that you'd go towards and so for us we had the luxury of building from the cloud up on these very powerful cloud services to enable a much more simple model for our customers to consume but even more so to be able to actually leverage the agility and elasticity of the cloud think about this for a quick second we can take facilities break them up expand them across many different compute resources within the cloud versus having to take kind of what you did on prim in a single server or multitudes of servers and try to plant that in the cloud from a customer's experience perspective it's vastly different you get a world where you don't think about how you manage the infrastructure how you manage the service you just consume it and the value that customers get out of that is not only getting their data there which is the on-ramp around our data protection mechanisms but also being able to leverage cloud native services on top of that data in the longer term as we have this one common global index and platform what we're super excited today to announce is that we're adding in AWS native capabilities to be able to date and protect that data in the public cloud and this is kind of the default place where most people go to from a cloud perspective to really get their applications up and running and take advantage a lot of those cloud native services well if you're gonna be cloud native and promise to customers as you're going to support their workloads you got to be obviously on AWS so congratulations on that but let's go back to this notion of user word powerful mm-hmm AWS is a mature platform GCPs coming along very rapidly asher is you know also very very good and there are others as well but sometimes enterprises discover that they have to make some trade-offs to get the simplicity they have to get less function to get the reliability they have to get rid of simplicity how does qu mio think through those trade-offs to deliver that simple that powerful that reliable platform for something as important as data protection and data services in general so we wanted to create an experience that was single click discover everything and be able to help people consume that service quickly and if you look at the problem that people are dealing with a customer's talked to us about this all the time is the power of the cloud resulted in hundreds if not thousands of accounts within AWS and now you get into a world where you're having to try to figure out how do I manage all of these for one discover all of it and consistently make sure that my data which as you've mentioned is incredibly important to businesses today as protect it and so having that one common view is incredibly important to start with and the simplicity of that is immensely powerful when you look at what we do as a business to make sure that that continues to occur is first we leverage cloud native services on the back which are complex and and and you know getting those things to run and orchestrate are things that we build on the back end on the front end we take the customer's view and looking at what is the most simple way of getting this experience to occur for both discovery as well as you know backup for recovery and even being able to search in a global fashion and so really taking their seats to figure out what would be the easiest way to both consume the service and then also be able to get value from it by running that service AWS has been around well AWS in many respects founded the cloud industry it's it's you know certainly Salesforce and the south side but AWS is that first company to make the promise that it was going to provide this very flexible very powerful very a a July infrastructure as a service and they've done an absolutely marvelous job about it and they've also advanced the state of your technology dramatically and in many respects are in the driver's seat what trade offs what limits does your new platform face as it goes to AWS or is it the same Coolio experience adding now all of the capabilities of AWS it's a great question because I think a lot of solutions out there today are different parts and pieces kind of clump together well we built is a platform that these new services just get instantly added next time you log into that service you'll see that that available to you and you can just go ahead and log in to your accounts and be able to discover directly and I think that the vow the power of SAS is really that not only have we made it immensely secure which is something that people think about quite a bit with having you know not only data in flight but data at rest encryption and and leveraging really the cloud capabilities of security but we've made it incredibly simple for them to be able to consume that easily literally not lift a finger to get anything done it's available for you when you log into that system and so having more and more data sources in one single pane of glass and being able to see all the accounts especially in AWS where you have quite a few of those accounts and to be able to apply policies in a consistent fashion to ensure that you're you know compliant within the environment for whatever business requirements that you have around data protection is immensely powerful to our customers Chad Denny Chief Technologist plumie oh thanks very much for being on the tube thank you great conversation Chad especially interested in hearing about how klum EO is being extended to include AWS services within its overall data protection approach and obviously into Data Services but let's take a little bit more into that Columbia was actually generated and prepared a short video that we could take a look at that goes a little bit more deeply into how this is all going to work enterprises are moving rapidly to the cloud embracing sass for simplified delivery of key services in this cloud centric world IT teams can focus on more strategic work accelerating digital transformation initiatives for when it comes to backup IT is stuck designing patching and capacity planning for on-premise systems snapshots alone for data protection in the public cloud is risky and there are hundreds of unprotected SAS applications in the typical enterprise the move to cloud should make backup simpler but it can quickly become exponentially worse it's time to rethink the backup experience what if there were no hardware software or virtual appliances to size configure manage or even buy it all and by adding Enterprise backup public cloud workloads are no longer exposed to accidental data deletion and ransomware and Clube o we deliver secure data backup and recovery without any of that complexity or risk we provide all of the critical functions of enterprise backup d dupe and scheduling user and key management and cataloging because we're built in the public cloud we can rapidly deliver new innovations and take advantage of inherent data security controls our mission is to protect your data wherever it's stored the clew mio authentic SAS backup experience scales on demand to manage and protect your data more easily and efficiently and without things like cloud bills or egress charges luenell gives you predictable costs monitoring global backup compliance is far simpler and the built-in always-on security of Clue mio means that your data is safe take advantage of the cloud for backup with no constraints clew mio authentic SAS for the enterprise great video as we think about moving forward in the future and what customers are trying to do we have to think more in terms of the native services that cloud can provide and how to fully exploit them to increase the aggregate flexible both within our enterprises but also based on what our supplies have to offer we had a great conversation with wounds Young who is the CTO and co-founder of Clue mio about just that let's hear it wound had to say everybody's talking about the cloud and what the cloud might be able to do for their business the challenges there are a limited number of people in the world who really understands what it means to build for the cloud utilizing the cloud it's a lot of approximations out there but not a lot of folks are deeply involved in actually doing it right we've got one here with us today woo Jung is the CTO and co-founder of Cluny Oh woo and welcome to the cube how they theny here so let's start with this issue of what it means to build for the cloud now loomio has made the decision to have everything fit into that as a service model what is that practically mean so from the engineering point of view building our SAS application is fundamentally different so the way that I'll go and say is that at Combe you know we actually don't build software and ship software what we actually do it will service and service is what we actually ship to our customers let me give you an example in the case of Kumu they say backups fail like software sometimes fails and we get that failures >> the difference in between chromeo and traditional solutions is that if something were to fail we are the one detecting that failure before our customers - not only that when something fails we actually know exactly why you fail therefore we can actually troubleshoot it and we can actually fix it and operate the service without the customer intervention so it's not about the bugs also or about the troubleshooting aspect but it's also about new features if you were to introduce our new features we can actually do this without having customers upgraded code we will actually do it ourselves so essentially it frees the customers from actually doing all these actions because we will do them on behalf of them at scale and I think that's the second thing I want to talk about quickly is that the ability to use the cloud to do many of the things that you're talking about at scale creates incredible ranges of options that customers have at their disposal so for example AWS customers have historically used things like snapshots to provide it a modicum of data protection to their AWS workloads but there are other new options that could be applied if the systems are built to supply them give us a sense of how kkumeul is looking at this question of no snapshots versus something else yeah so basically traditionally even on the on print side of the things you have something called the snapshots and you had your backups right and there they're fundamentally different but if you actually shift your gears and you look at what they Wis offers today they actually offers the ability for you to take snapshots but actually that's not a backup right and they're fundamentally different so let's talk about it a little bit more what it means to be snapshots and a backup right so let's say there's a bad actor and your account gets compromised like your AWS account gets compromised so then the bad actor has access not only to the EBS volumes but also to the EBS snapshots what that means is that that person can actually go ahead and delete the EBS volume as well as the EBS snapshots now if you had a backup let's say you actually take a backup of that EBS volume to Kumu that bad actor will have access to the EBS volumes however they won't be able to delete the backup that we actually have in Kumu so in the whole thing the idea of Kumi on is that you should be able to protect all of your assets that being either a non-prime or AWS by setting up a single policies and these are true backups and not just snapshots and that leads to the last question I have which is ultimately the ability to introduce these capabilities at scale creates a lot of new opportunities that customers can utilize to do a better job of building applications but also I presume managing how they use AWS because snapshots and other types of servers can expand dramatically which can increase your cost how is doing it better with things like native backup services improve a customer's ability to administer their AWS spend and accounts so great question so essentially if you look at the enterprise's today obviously they have multiple you know on-premise data centers and also a different card provide that they use like AWS and Azure and also a few SAS applications right so then the idea is for cumin is to create this single platform where all of these things can actually be backed up in a uniform way where you can actually manage all of them and then the other thing is all doing it in the cloud so if you think about it if you don't solve the poem fundamentally in the cloud there's things that you end up paying later on so let's take an example right moving bytes moving bytes in between one server to the other traditionally basically moving bytes from one rack to the other it was always free you never had to pay anything for that certainly in the data center all right but if you actually go to the public cloud you cannot say the same thing right basically moving by it across aw s recent regions is not free anymore moving data from AWS to the on premises that's not fair either so these are all the things that any you know car provider service provider like ours has to consider and actually solve so that the customers can only back it up into Kumu but then they actually can leverage different cloud providers you know in a seamless way without having to worry all of this costs associated with it so kkumeul we should be able to back it up but we should be able to also offer mobility in between either AWS back at VMware or VNC so if I can kind of summarize what you just said that you want to be able to provide to an account to an enterprise the ability to not have to worry about the back-end infrastructure from a technical and process standpoint but not also have to worry so much about the back-end infrastructure from a cost and financial standpoint that by providing a service and then administering how that service is optimally handled the customer doesn't have to think about some of those financial considerations of moving data around in the same way that they used to I got that right I absolutely yes basically multiple accounts multiple regions multiple providers it is extremely hard to manage what Cuneo does it will actually provide you a single pane of glass where you can actually manage them all but then if you actually think about just and manageability it's actually you can actually do that by just building a management layer on top of it but more importantly you and we need to have a single data you know repository for you for us to be able to provide a true mobility between them one is about managing but the other thing is about if you're done if you're done it the real the right way it provides you the ability to move them and it leverages the cloud power so that you don't have to worry about the cloud expenses but kkumeul internally is the one are actually optimizing all of this for our customers wound jeong CTO and co-founder of columbia thanks very much for being on the cube thank you thanks very much moon I want to thank chromeo for providing this important content about the increasingly important evolution of data protection and cloud now here's your opportunity to weigh in on this crucially important arena what do you think about this evolving relationship how do you foresee it operating in your enterprise what comments do you have what questions do you have of the thought leaders from clew mio and elsewhere that's what we're going to do now we're gonna go into the crowd chat and we're gonna hear from each other about this really important topic and what you foresee in your enterprise as your digital business transforms let's crouch at you [Music] [Music] [Music]