>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by >>Welcome to the cubes coverage of UI path forward for live from Las Vegas. We're here at the Bellagio. Lisa Martin, with Dave a long time, very excited to have in-person events back ish. I'll say we're going to be talking about automation as a boardroom imperative. We have two guests joining us here, James Matras here consulting principal. America's intelligent automation leader at UI and Irv. Dennis retired EA partner, and former CFO of HUD gentlemen. Welcome to the program. Exciting topic automation as a boardroom imperative, James says COO and start with you. How do you discuss the value of automation as being a key component and driver of transformation? >>That's a great question. I think what we've seen in the last couple of years is the evolution of what automation used to be. Two is going nine. And we've seen the shift from what we call generation one, which is very RPA centric type automation to more generation two, which is the combined integration of multiple technologies. It can target an intern process and it's quite important that you understand the pivotal shift because it's not enabling us to move from a task micro top agenda to a macro agenda actually impacts an organization at a strategic level. The ability to be able to look at processes more deeply to automate them in an end to end process collectively and use these different technologies in a synergistic manner truly becomes powerful because it shifts the narrative from a micro process agenda into more systemic area. >>So gen zero is an Emmanuel gen one is RPA point tools that individual maybe getting their personal productivity out. And then now you're saying gen three is across the enterprise. Where are we in terms of, you know, take your experience from your practical experience? Where do you think the world is? It's like probably between zero and one still. Right. But the advanced folks of thinking about gen three, w what's your, >>Yeah, it's a great question. And, um, when you and I, I can do the comparison being private and public sector on this because I was 37 years with E Y then went into retirement and CFL at HUD CFO. Ed was, was a HUD was nowhere. They had to just do all the intelligence digitalization, um, throughout, uh, from scratch. The private sector is probably five or six years ahead of them. But when you think about James talks about the gen one, two and three, the private sector is probably somewhere between two and three. And I know we're talking about the board in this conversation. Um, boards probably have one and two on their radar. Some boards may have three, some may not, but that's where the real strategic focus for boards needs to be is looking forward and, and getting ahead. But I think from a public sector standpoint, lot to go private sector, more to go as well. But, uh, there's a, there's a bit of a gap, but the public sector is probably only about three or four years behind the private sector >>To be okay. Let's look at the numbers, look at, look at the progress for the quarter. And now it's like discussion on cyber discussion on digital discussion on automated issue. It really changed the narrative over the last decade. >>Yeah, I think when you think of boards today, the lots of conversation on cyber that that conversation has been around for a while. A lot of conversation on ESG today, that conversation is getting, getting very popular. But I think when you think of next three, a Jen talks that bear James talks about, um, that's got to start elevating itself if it's not within the boardroom right now, because that will be the future of the company. And the way I think of it from a board's conversation is if a company doesn't think of themselves as a technology company in all aspects, no matter what you do, you are a technology company or you need to be. And if you're not thinking along that way, you're gonna, you're gonna lose market share and you're going to start falling behind your competitors. >>Well, and how much acceleration did the pandemic bring to just that organizations that weren't digital forward last year are probably gone? >>I think it certainly has shifted quite a lot. There's been a drive, the relevance of technology and hard plays for us in the modern workforce in the modern workplace has fundamentally changed the pandemic. We reimagine how we do things. Technology has progressed in itself significantly, and that made a big difference for, for all the environments as a result of that. So certainly is one of the byproducts of the pandemic has been certainly a good thing for everybody. >>Where does automation fit in the board? Virginia? You've got compensation committee. You've probably, I mean, there's somebody in charge of cyber. You got ESG now there's automation part of a broader digital agenda. Where's what's the right word. >>You know, I, I would personally put it in a enterprise risk management from a standpoint that if you're not focused on it, it's going to be a risk to the enterprise. And, um, when you think of automation and intelligent automation and RPA, uh, I think boards have a pretty good sense of how you interface with your customers and your vendors. I think a big push ought to be looking internally at your own infrastructure. You know, what are you, what are you doing in the HR space? What are you doing in a financial statement, close process? What are you doing your procurement process? I suspect there's still a lot of very routine transactions and processing within those, that infrastructure that if you just apply some RPA artificial intelligence, that data extraction techniques, you can probably eliminate a lot of man hours from the routine stuff. And, and the many man hours is probably not the right way to think of it. You could elevate people's work from being pushing numbers around to being data analyzers. And that's where the excitement is for people to see. >>It's not how it's viewed at organizations. We're not eliminating hours. Well focusing folks on much more strategic down at a test. >>Yes. I would say that that's exactly right now in the private sector, you're always going to have the efficiency play and profitability. So there will be an element of that. I know when at HUD we're, we're focused, we were not focused on eliminating hours because we needed people and we focused on creating efficiencies within the space and having people convert from, again, being Trent routine transactions, to being data analyzers and made the jobs, I'm sure. Fund for them as well. I mean, this is a lot of fun stuff. And, and if, uh, uh, companies need to be pushing this down through their entire infrastructure, not just dealing with our customers and the third parties that they deal with >>Catalyst or have been public sector. So you mentioned they may be five or six years behind, but I've seen certain public sector organizations really lean in, they learn from, from the private sector. And then even when you think about some of the military, how advanced they are absolutely. You know, the private could learn from them and if they could open it up. But >>So, yeah, I think that's, that's well said I was in this, you know, the that's the civilian part with, with the housing and urban development. I think the catalyst is, uh, bringing the expertise in, uh, I know when I, when I came, I went to HUD to elevate their financial infrastructure. It was, it was probably the worst of the cabinet agency. The financials were a mess. There was no, there was a, uh, there was not a clean audit opinion for eight years. And I was there to fix that and we fixed it through digitalization and digital transformation, as well as a financial transformation. The catalyst is just creating the education, letting people know what is, what, what technology can do. You don't have to be a programmer, but it's like driving a car. Anybody can drive a car, but we can't mechanic, you know, work as a mechanic on it. >>So I think it's creating education, letting people know what it can do. And at HUD, for example, we did a very simple, I was telling James earlier, we did a very simple RPA project on an, an, a financial statement, close process. It was 2,600 hours, six months. Once we implemented the RPA, brought that down to 70 hours, two weeks, people's eyes exploded with it. And then all of a sudden, I said, I want everyone to go back and come back with, with any manual process, any routine process that can convert to an RPA. And I got a list of a hundred, then it came then became trying to slow everything down. We're not going to do it overnight. Yeah, exactly. >>So, but it was self-funding. It was >>Self-funded. Yes. >>And, and how do you take that message to customers that it could be self-funding how how's that resonating >>Very well. And I think it was important. I always like to say, it's a point of differentiation because you look at, uh, mentioned earlier that organizations are basically technology companies. That's what they are. But now if you look across that we no longer compete at the ERP level without got SAP, Oracle, it's not a point of differentiation. We don't compete the application layer where they've got service. Now, black line, how we use them is helpful. We competed the digital layer and with automation is a major component of that. That's where your differentiation takes place. Now, if you have a point of differentiation, that is self-funding, it fundamentally changes the game. And that's why it's so important for boards to understand this, because that risk management, if you've not doing it, somebody is getting ahead of the game much faster than you are. >>Yeah. Yeah. You mentioned ERP and it, and it triggered something in my mind. Cause I, I said this 10 years ago about data. If in the nineties, you, you couldn't have picked SAP necessarily as the winner of ERP. But if you could have picked the companies that were using ERP could have made a lot of money in the stock market because they outperform their peers. And the same thing was true with data. And I think the same thing is going to be true with automation in the coming decade. >>Couldn't agree more. And I think that's exactly the point that differential acceleration happening this. And it's harder because of the Europeans. Once you knew what it was, you can put the boundaries on it. Digital, the options are infinite. It's just continuous progress as are from there. >>I've got a question for you. You talked about some great stats about how dramatically faster things were took far less time. How does that help from an adoption perspective? I know how much cultural change is very difficult for folks in any organization, but that sort of self-serving how does that help fuel adoption? >>Well, it's interesting. Um, it's, it is a, we're actually going to talk about this tomorrow. It is a framework and it's got to start at the leadership has got to start with governance. It's got to start with a detailed plan. That's executable. And it's got to start with getting buy-in from not only your, the, the organization, but the people you're dealing with outside the organization. Um, it's, it's, uh, I think that's absolutely critical. And when you bring this back to the boardroom, they are the leaders of the companies. And, and I, James, I talked about this as we're getting ready for tomorrow's session. I think the number one thing a board can do today is an own personal self assessment. Do they understand automation? Do they understand what next generation three is? Do they understand what the different components can do? And do they understand how the companies are implementing it? And if I was a board member, uh, on our boards, I say, we need to understand that or else this is nothing's going to happen. We're going to be here at the reliance of the CEO and the CFO strategy, which may or may not include or be thinking about this next three. So leadership at the top is going to drive this. And it's so critical. >>We were talking about catalyst before. And you mentioned education and expertise. I'm always curious as to what drew you to public sector because it's, yeah, I mean, very successful, you know, you're, you're with one of the global SIS directly, you can make a lot more money and that side. So what was it did, was it a desire to it's a great country? Was it >>Take one for the team and I'm going to do a selfish plug here. I just actually wrote a book in this whole thing called transforming a federal agency. What's the name of the book transforming and federal agency. And it's, uh, I spent my time at E Y for 37 years, fully retired. I wanted to give back and do meaningful work. And we lived in Columbus, Ohio, as I was talking about earlier, I was going to go teach and I got a call from the president's personnel office to see if I wanted to come. And these, the CFO at HUD with secretary Carson and change turn the agency around, uh, that took me a little while to say yes, because I wasn't sure I wanted something full time. It was a, it was in DC. So I'd be in a commuting role back and forth. My family's in Columbus. >>Um, but it was, uh, I did it and I loved it. It was, uh, I would pray, I would ask anyone that's has the ability to go into public service at any point in their career to do it. It's it was very rewarding. It was one of my favorite three years of life. And to your point, I didn't have to do it, but, uh, if I wanted to do something and give back and that met the criteria and we were very successful in turning it around with the digital transformation and a lot of stuff that we're talking about today gave me the ability to talk about it because I helped lead it >>For sharing that and did it. So did it start with the CFO's office? Because the first time I ever even heard about our RPO RPA was at a CFO conference and I started talking to him like, oh, this is going to be game changing. Is that where it started? Is that where it lands today? >>From an infrastructure standpoint, the CFO has the wonderful ability to see most processes within a company and its entire lifestyle from beginning to end. So CFO has that visibility to understand where efficiencies can happen in the process. And so the CFO plays a dramatically important role in this. And you think about a CFO's role today versus 20 years ago, it's no longer this, the bean counter rolling up numbers that become a business advisors to the board, to the CEO and to the executive suite. Um, so the CFO, I think has probably the best visibility of all the processes on a global basis. And they can see where the, the efficiencies and the implementation of automation can happen. >>So they can be catalysts and really fueling the actual >>Redesign of work. Yes, they, they, they probably need to be the catalyst. And as a board member, you want to be asking what is the CFO's strategic imperative for the next year? And if it doesn't include this, it's just got to get on the agenda. >>Well, curve ball here is his CFO question and you know, three years or two years ago, you wouldn't have even thought, I mean, let me set it up better. One of the industries that is highly automated is crypto. Yeah. You wouldn't even thought about crypto in your balance sheet a couple of years ago, but I'm not sure it's a widespread board level discussion, but as a CFO, what do you make of the trend to put Bitcoin on balance sheets? >>Yeah, I'm probably not the right person to ask because I'm a conservative guy. >>If somebody supported me and he said, Hey, why don't we put crypto on the balance sheet? >>I would get much more educated. I wouldn't shut it down. I would put it into, let's get more educated. Let's get the experts in here. Let's understand what's really happening with it. Let's understand what the risks are, what the rewards are. And can we absorb any sort of risk or reward with it? And when you say put it on the balance sheet, you can put it on in a small way to test it out. I wouldn't put the whole, I wouldn't make the whole balance sheet for Dell on day one. So that's why I would think about it. Just tell, tell me more, get me educated. How did you think about it? How can it help our business? How can I help our shareholders? How does it grow the bottom line? And then, then you start making decisions. >>Cause CFOs, let me find nature often conservative and most CFOs that I talked to just say no way, not a chance, but you're, maybe you're not as conservative as you think. Well, >>No, but I will never say go away on anything. I mean, cause I want to learn. I want to know. I mean, um, if you like all this stuff, that's new, it's easy to say go away, right? Yeah. But all of a sudden, three years later, the go away, all your competitors are doing it at a competitive advantage. So never say go away, get yourself educated before you jump into it. >>That's good advice. Yeah. In any walk of life question for you, or have you talked about the education aspect there? I'm curious from a risk mitigation perspective, especially given the last 18, 19 months, so tumultuous, so scary for all those organizations that were very digital, they're either gone or they accelerated very quickly. How much of an education do you have to provide certain industries? And are you seeing certain industries? I think healthcare manufacturing, financial services as being leaders in the uptake? >>Well, I think the financial service industries, for sure, they, they, they get this and then they need to, uh, cause they, you know, they're, they're a transaction and based, uh, industry. Uh, so they get it completely. Um, you know, I think maybe some manufacturing distribution, some of the old line businesses are, you know, they may not be thinking of this as progressively as they should. Um, but they'll get there. They're going to have to get there eventually. Um, you know, when you think about the education, my, I thought you were gonna ask a question about the education of the workforce. And I think as a board member, I would be really focused on, uh, how am I educating my workforce of the future? And do I have the workforce of the future today? Do I have to educate them to have to bring in hiring for it? Do I have to bring third-party service providers to get us there? So as a board member really focus on, do I have the right workforce to get us to this next stage? And if not, what do I need to do to get there? Because >>We'll allocate a percentage of their budgets to training and education. And the question is where do they put it >>In? Is it the right training and education, right? >>Where do they focus though? Right now we hear you iPad talking about they're a horizontal play, but James, when you and Lisa, we were asking about industry, when you go to market, are you, are you more focused on verticals? Are you thinking, >>No, it's on two things. So which often find is regardless of the sector with some nuanced variation, the back office functions are regionally the procure to pay process as the same fundamentals, regardless of the sector where the differentiation comes in at a sector of service is when you start going to the middle of the front office, I mean a mining has only one customer. They sold their product to image the retailer has an endless number of them. So when you get to the middle and front office and really start engaging with a customer and external vendors, then a differentiation is very unique and you'd have a lot of sort of customers having sector specific nuances and variations in how you use the platform. And that's where the shift now is happening as well is the back office functions that are largely driven by the CFO. If now getting good, robust value out of it, there's pivot to make it a differentiator in the market, comes in the front and middle office. And that's where we starting to say, sector specific genres solutions, nuances really come to the fall >>Deep industry expertise. Do you think digital at all changes that the reason I ask it because I see Amazon as a retail and then they're in cloud and they're in grocery other in content Apple's in, in financial services and you're seeing these internet giants with a dual agenda, they're disrupting horizontal technology and then there's disruptive industries. And my premise is it's because of data and digital. Do you ever see that industry specialization changing that value chain >>Without a doubt? And I think it's happens initially. It starts off. When people have started looking at the process, they realize there's such key dependencies on the upstream and downstream components of the value chain that they want to control it. So they actually start bridging out of what the core practices or the core business to own a broader agenda. And with digital, you can do it. You can actively interact more systemically that installs triggering, well, maybe I have a different product offering. Maybe I can own this. Could I monetize the information I had at my disposal today in a completely new line. And that really what gets truly innovative and starts creating a revenue increase as opposed as the cost saving. And that's what they're really going after. It's how do I, >>The vertical integration is not new. The plenty of ended up Koch industries, Tyson foods, but now it's digital. So presumably you can do it faster with greater greater scale >>Without a doubt. And you don't have to move your big ERP and things like that. Cause that's the only way it takes five years to move my technology backbone with digital. I can do the interaction tomorrow and we can build up enough to be able to sustain that in the short term. >>Right. And speaking of speed, unfortunately, guys, we are out of time, but thank you. Fantastic conversation automation as a board imperative guys, that's been great James or >>Thank you for your time. Thank you so much >>For Dave a long day. I'm Lisa Martin. You're watching the queue. We are live in Las Vegas at the Bellagio at UI path forward for stick around Dave and I will be right back. Okay.

(upbeat music) >> Narrator: Live from Las Vegas, it's theCube. Covering AWS re:Invent 2019 brought to you by Amazon Web Services and Intel, along with it's ecosystem partners. >> Hello there and welcome back to theCube's live coverage here in Las Vegas for AWS re:Invent 2019. This is theCube's seventh year covering re:Invent. They've been doing this show for eight years, we missed the first year, I'm John Furr, and my co-host David Vellante. We're here extracting the signal from the noise, and we're here with an amazing guest, our friend, she's been here with us from the beginning of theCube, since inception. Always great to get to comment with her. Sandy Carter Vice President with Amazon Web Services. >> Thank you. >> Now in the public sector handling partners. Great to see you, thanks for coming on again and sharing your content. >> So great to see you guys, so dressed up and looking good guys, I have to say. (laughs) >> You're looking good to, but I can't help but stare at our other guest here, the IoT suitcase. >> First, tell us-- >> Yes. >> About the IoT suitcase. >> Well we, in public sector we have a partner program, and that program helps entrepreneurs. And we're really keen on especially helping female entrepreneurs. So one of our entrepreneurs created this suitcase, that's an IoT based suitcase, you can put your logo's and that sort of thing on it, but more importantly for public sectors, she created this safety ring, John. And so, if I touch it I've de-activated it, but if I touch it, it will call the police for me, if I'm being assaulted. Or if I'm having an emergency, I can touch it and have an ambulance come for me as well. And the really cool thing about it is she worked backwards from the customer, figuring out like how are most people assaulted, and if you have an emergency and you fall, what's the best way to get ahold of someone. It's not your phone, because you don't always carry it, it's for a device like this. >> Or a bigger device that you can't, or you leave on the table somewhere, but that's you know it's attractive. >> It's awesome. >> And it's boom, simple. >> And it's pink. (laughs) >> What I love fast about re:Invent as an event is that there's so much innovation going on, but one of the areas that's become modernized very rapidly is the public sector. Your now in this area, there's a lot of partners, a huge ecosystem going, and the modernization effort is real. >> It is. >> Could you share some commentary on what's going on. Give people a feel for the pace of change, what's accelerating? What are people doubling down on, what are some of the dynamics in public sector? >> Yeah, so if you know public sector, public sector actually has a lot of Windows or Microsoft workloads in it. And so we're seeing a lot of public sector customers looking to modernize their Windows workloads, in fact we made several announcements just yesterday around helping more public sector customers modernize. For example, one is Windows Servers 2003, and 2008 will go out of support, and so we have a great new offering, with technology, that can help them to not re-factor, but actually abstract those layers and move quickly to 2016 and 2019, because both of those will go out of support in January. >> A lot of people don't know, and I've learned this from talking with Andy Jassy in the keynote, as well as hearing from some other folks, is that you got, Amazon runs a lot of Windows. >> Oh, we have 57% Windows workloads on AWS in terms of market segment share. Which is 2x the next nearest cloud provider, 2x. And most customers choose to run their Windows workloads on us, because we are so innovative, we move really fast. We're more reliable. The latest public data from 2018 shows that the nearest cloud provider had seven times more downtime. So if your in public sector or even commercial, who can afford to be down that long, and then finally, we have better security. So one of the things we've been focused on for public sector is FedRamp solutions. We know have over 90 solutions that are FedRamp ready. Which is four times more than the next two cloud providers. Four times more than the two combined. >> That's interesting, so I got to ask the question that's popping up in my mind, I'm sure people are curious about. >> Yeah. >> I get the Windows working on Amazon, and that makes a lot of sense, why wouldn't you want to run on the best cloud. The question I would have is, how would the licensing work, because, that's seems to be lock-in spec, Oracle does it, Microsoft does it, does license become the lock-in. So, when something expires, what happens on the licensing side. Licensing is really tricky, and in fact, October 1st, Microsoft made some new licensing changes. And so, we have some announcement to help our customers still bring their own licenses, or what we call fondly, BYOL over to AWS, so they don't have to double invest on the license. >> So you can honor that license on AWS. >> Yeah, and you have to do it on a dedicated host. Which at midnight madness, we announced new dedicated host solution, that's very cloud-like. Makes it as easy to run a dedicated host instance as it is an EC2 instance. So, wicked easy, very cost effective if your moving those on-premises workloads over. >> I just want to point out John, something that's really important here is a lot of times, software companies will use scare tactics, to your point. They'll jack up the cost of the license, to say, ah you got to stay with us, if you run on our hardware or our platform, you pay half. And then they'll put out, "Oh, Amazon's twice as expensive." But these are all negotiable. I've talked to a number of customers, particularly on the Oracle side, and said, no, no, we just went to Oracle and said look, you got a choice, I either give us the same license price or we're migrating off your database. Okay, all right. But some of it is scare tactics, and I think you know increasingly, that's not working in the marketplace. So I just wanted to point that out. >> So what's the strategy for customers to take, I guess that's the question. Because, certainly the licensing becomes again like they get squeezed, I can see that. But what do customers do, is there a playbook? >> Well there is, and so the best one is you buy your license from Microsoft, and then using BYOL, you can bring that over to AWS. It's faster, more performance, more reliable, that sort of thing. If you do get restricted though John, like they are doing for instance with their end of support, you could run that on Azure, and get all the security fixes. We are trying to provide technical solutions, like the ability to abstract Windows Server 2003 and Server 2008 as it goes out of support. >> I mean certainly in the case of Oracle, it used to be you know 10-15 years ago, you didn't have a choice. Instead of one RDBMS, and now it's so much optionality in databases. >> And I will also tell you that we have a lot of customers today, who are migrating from SQL server, or Oracle over to Aurora. Aurora, is equally as performant, and a tenth of the cost. So we actually have this team called the database freedom team that will help you do that migration. In fact I was talking to a very large customer last night, and I was explaining some of the options. And their like, "Let's do the Aurora thing." Let's do it two-step. Let's start by migrating the database over, Oracle and SQL and then I want to go to Aurora. It's like database built for the cloud, it's faster and its cheaper. So why wouldn't you do that? >> Yeah, and I think the key is, to my question about a friction. What's frictionless? How can they get it done quickly without going through the trip-wires of the licensing. >> Certain workloads are tough, right. You know if you're running your business on high transaction volume. But a lot of the analytics stuff, the data warehouse, you know look at Amazon's own experiences. You guys are just ticking it off, moving over from Oracle to Aurora, it's been fun to watch. >> I want to get you guy's perspective Dave, you and Sandy, because I think you guys might have good insight on this, because everyone knows that I'm really passionate about public sector, I've been really enamored with Teresa's business from Day one, but when she won the CIA deal, that really got my attention. As I dug into the Jedi deal, and that all went sideways, it really jumped out at me, that public sector is probably the most transformative market, because they are modernizing at a record pace. I mean this is like a glacier moving market. They don't really have old ways, they got the beltway bandits, they got old procurement, old technology, and like literally in a short period of time, they have to modernize. So they're becoming more enterprise like, can you guys, I mean pros in the enterprise, what's your take? It just seems like a Tsunami of change in the public sector, because the technology is driving it. What do you guys think about this? Am I on or off base? What are some of the trends that are going on? >> I mean I have a perspective, but please. >> No, okay. So I'll start. So I see so much transformation regardless of what industry your looking at. If you're looking at Government for example working with SAP NS2, we just actually took 26 different flavors of SAP ERP for the Navy, and helped them to migrate to the cloud. For the US Navy, which is awesome. Arkis Global, did the same thing for the UK. We actually have Amazon Connect in there, so that's like a cool call center driven by Machine Learning, and the health care system for the UK. Or you can even look at things, like here in the U.S. there's a company that really looks at how you do monitoring for the children to keep them safe. They've partnered up with a National Police Association, and they are bringing that to the cloud. So regardless of education, non-profits, government, and it's around the world, it's not just the US. We are seeing these governments education, start-ups, non-profits, all moving to the cloud, and taking their own legacy systems to Linux, to Aurora, and moving very rapidly. >> And I think Andy hit on it yesterday, it's got to start with top-down leadership. And in the government, if you can get somebody whose a leading thinker, CIO, we're going cloud first. Mandate cloud, you know you saw that years ago, but today, I think it's becoming more mainstream. I think the one big challenge is obviously the disruption in defense and that's why you talked about Jedi, in defense it's very high risk, and it needs disruption, it's like healthcare its like certain parts of financial services are very high risk industries, so they need leadership, and they need the best platform underneath in a long term strategy. >> Well Jedi actually went different. It was actually the right call, but I reported on that. But I think that what gets me is that Cerner on stage yesterday, on Yaney's keynote highlights that it's just not inefficiencies that you can solve, there's multiple win-win-win benefits so in that health care example, lower the costs, better care, better, the providers are in better shape, so in government in public sector, there's really no excuse to take the slack out of the system. >> Yeah. >> Well, there's regulation though. >> Yeah, and Dave mentioned cloud first strategies, we're also seeing a lot of movement around data. You know data is really powerful. Andy mentioned this as well yesterday, but for example in our partner keynote where I just came from. We had on stage Avis. Now, Avis, not public sector customer, but what they're doing is, the gentleman said, was that your car can now talk to you, and that data is now being given to local state officials, local city officials, they can use it for emergency response systems. So that public and private use of data, coming together, is also a big trend that we're seeing. >> I think that's a great example, because Avis I think what he said is a 70 year old company, I think the fleet was 18 billion dollar fleet. >> 600,000 vehicles. >> 600,000 vehicles, 18 billion dollars worth of assets, this is not a born in the cloud start-up, right. That's essentially transformed the entire fleet and made it intelligent. >> Right, and using data to drive a lot of their changes. Like the way they manage fuel for 600,000 cars, and the way they exchange that with local officials is helping them to you know not just be number two, but to start to take over number one. >> But to your point, data is at the core, right. >> Yeah. >> If you are the incumbent and you want to transform, you got to start with the data. >> Sandy, I want to get your reaction to two memes that have been developing on theCube this week. One is, if you take the T out of Cloud Native, and it's Cloud Naive. (Sandy laughs) The other one is, if your born in the cloud, that's great, your winning, but at the price of becoming re-born in the cloud. This is the transformation. Some are, and they're going to not have a long shelf life. So there's a real enterprise and now public sector re-birth, re-borning in the cloud, the new awakening. This is something that is happening. You're an industry veteran, you've seen a lot of waves, what's the re-born, what's this getting back on the cloud, really happening. What is going on? >> It's really interesting, because now I'm in the partner business, and one of our most successful programs is called our partner transformation program. And what that does, is it's a hundred day transformation program to get our partners drinking our own champagne, which is to be on the cloud. And one of the things, we know we first started testing it out, we didn't have a lot of takers, but now, those partners who have gone through that transformation, they're seeing 70% year to year growth, versus other apion partners, even though they're at an advanced layer, they're only seeing 34% growth. So its 2x of revenue growth having transformed to the cloud. So I think, you know back to your question, I think some of this showing the power. Like, why do you go to the cloud, it's not just about cost, it's about agility, it's about innovation, it's about that revenue growth, right. I mean 2x, 70% growth, you can't sneeze at that. That's pretty impactful. >> And you know this really hits, something of passion for me and Dave and our team is the impact on a society. This is a real focus across all generations now, not just millennials, and born in the web, into older folks like us, who have seen before the web. There's real impact, mission driven things. This is a check for good, shaping technology for good. Educate you guys have. This is a big part of what you guys are doing. >> Absolutely, this is one of the reasons why I really wanted to come work in the public sector, because it's fun helping customers make money, and we still do that. But it's really better, when you can help them make money and do great things. So you know, making with the Mayo clinic, for example, and some of these non-profit hospitals, so they can get better data. The GE example that Andy used yesterday, that data is used in public sector. Doing things, like, I know that you guys are part of re-powered tech. You know we brought a 112 unrepresented minorities and women to the conference. And I have to tell you I got goosebumps when one person came up to me and he said, it's the first time he stayed in a hotel, and he's coming here to enhance his coding. You don't realize when I go back to my country, you will have changed my life. And that's just like, don't you get goosebumps from that, versus it's great to change a company, and we want to do that, but it's really great when you can impact people, and that form or fashion. >> And the agility makes that happen faster, its a communal activity, tech for good is here. >> Absolutely, and we just announced today, right before this in the partner's session, that we now have the public safety and disaster response competency for our partners. Because when a customer is dealing with some sort of disaster or emergency they need a disconnected environment for a long periods of time. They need a cloud solution to rally the troops. So we announced that, and we had 17 partners step up immediately to sign up for that. And again, that's all about, giving back, helping in emergency situations, whether it's Ebola in Africa or Hurricane Dorene, right. >> Well, Sandy congratulations, not only have you a senior leader for AWS doing a great job. >> Thank you. >> Just a great passion, and Women in Tech, Underabridged Minorities, you do an amazing job on Tech for Good. >> Thank you. Well it's such an honor to always be on the show. I love what you guys do. I love the memes, I'm going to steal them, okay. >> Can I ask you another question? >> Absolutely. >> Before you wrap. You've had an opportunity to work with developers, you've experienced other clouds. Now you're with AWS and a couple of different roles. Can you describe, what's different about AWS, is it cultural, is it the innovation, I mean what's tangible that you can share with our audience in terms of the difference. >> I think it's a couple of things, the first one the way they we hire. So we hire builders, and you know what it really starts from that hiring. I actually interviewed Vernor the other day, and he and I had a debate about can you transform a company where you have all the same people, or do you need to bring in some new talent as well. So I think it's the way we hire. We search for people that not only meet the leadership criteria, but also are builders, are innovators. And the second one is, you know when Andy says we're customer obsessed, we're partnered obsessed. We really are. We have the mechanisms in place, we have the product management discipline. We have the process to learn from customers. So my first service I launched at AWS, I personally talked to 141 customers and another 100 partners. So think about that, that's almost two hundred almost fifty customers and partners. And at most large companies, as a senior executive you only spend about 20% of your time with customers, I spent about 80% of my time here with customers and partners. And that's a big difference. >> Well we look forward to covering the partner network this year. >> Awesome >> Your amazing, we'll see Teresa Carson on theCube here at 3:30. We are going to ask her some tough questions. What should we ask Teresa? >> What to jest Teresa? Where did you get those red pants? (everyone laughs) >> She's amazing, and again. >> She is amazing. >> We totally believe in what you're doing, and we love the impact, not only the technology advancement for modernizing the public sector across the board. But there's real opportunity for the industry to make, shape technology for betterment. >> Yeah. >> You're doing a great job. Thank you so much. >> Thank you. I think we should start another hashtag for theCube too, is #technologyforgood. >> Awesome. >> What do you think? >> Let's do it. >> I love that. >> But Jonathan been doing a lot of work in that area. >> I know he has. >> We love that. #technologyforgood, #techforgood. This is theCube here live in Las Vegas for re:Invent. I want to thank Intel and AWS, this is the big stage. We had two stages, without sponsoring our mission we wouldn't be here. Thank you AWS and Intel. More coverage after this short break. (dramatic music)

live from New York it's the cube covering the cube New York City 2018 brought to you by silicon angle media and its ecosystem partners i'm jeff workday Villante we're here nine years our nine years of coverage two days live in New York City and our next two guests shot Mrazek CEO amana stayed at fiendish males CMO mystic good to see you again welcome back thank you bad to be here guys so obviously this show we've been here nine years we were the first original Hadoop world we've seen a change Hadoop was gonna change the world it kind of didn't but we get the idea of it did not it did didn't but it would change our world it brought open source and the notion of low-cost Hardware into the big data game and then the big data became so much more powerful around these new tools but then the cloud comes in full throttles and while they can get horsepower that compute you can stand up infrastructure for analytics all this data goodness starts to change machine learning then becomes the the real utility that's showing this demand for using data right now not the set up using data this is a fundamental big trend so I don't get you guys reaction what do you see this evolving more cloud like how do you guys see the trend in this as data science certainly becoming more mainstream and productivity users to hardcore users and then you got cloud native developers doing things like kubernetes we've heard kubernetes here it's like a cloud is a data science what's going on what's your view of the market so I came from a company that was in an tech and we were built on big data and in looking at how big data is evolved and the movement towards analytics and machine learning it really being enabled by Big Data people have rushed to build these solutions and they've done a great job but it was always about what's the solution to my problem how do i leverage this data and they built out these platforms and in our context what we've seen is that enterprises get to a certain point where they say okay i've got all these different stacks that have been built these apps that have been built to solve my bi and analytics problems but what do I do about how do I manage all these and that's what I encounter my last company where we built everything ourselves and then so wait a minute but what we see at an enterprise level is fascinating because when I go to a large company I go you know we work with no sequel databases and Hadoop and you know how much Couchbase do you have how much Mongo etc the inevitable answer is yes and five of each right and they're cutting to this point where I've got all this distributed data distributed across my organization how am I going to actually manage it and make sure that that data is protected that I can migrate to the cloud or in a hybrid cloud environment and all these questions start to come up at an enterprise level we actually have had some very high-level discussions at a large financial institution here in New York where they literally brought 26 people to the meeting the initial meeting this was literally a second call where we were presenting our capability because they're they're now at the point where it's like this is mission-critical data this is not just some cool stuff somebody built off in one of our divisions it matters to the whole enterprise how do we make sure that data is protected backed up how do we move data around and that's really the the trend that we're tapping into and that the founders of our company saw many years ago and said I need to I need to we need to build a solution around this it's interesting you know you think about network data as a concept or data in general it's kind of got the same concepts we've seen in networking and/or cloud a control plane of some sorts out there and you know we're networking kind of went wrong as the management plane was different than the control plane so management and control or huge issues I mean you bring up this sprawl of data these companies are data full it's not like hey we might have data in the future right they got data now they're like bursting with data one what's the control plane look like what's the management plane look like these are all there's a technical concepts but with that with that in mind this is a big problem what our company is doing right now what are what are some of the steps that are taking now to get a handle on the management the data management it's not just your grandfather's data management so we anymore it's different it looks different your thoughts on on this chain of management so they're approaching the problem now and that's our sweet spot but I don't think they have in their minds yet come to exactly how to solve it it's there's this realization about we need to do this at this point and and and in fact doing it right is something that our founders when they built Lee said look if this problem of data management across big data needs to be solved by a data we're platform built on big data so let's use big data techniques to solve the problem all right so let's before getting some of the solution you guys are doing take a minute to explain what you guys are doing for the company the mission you know the value proposition status what do you guys do how are people gonna consume your product I mean take a particular type gen simple elevator pitch and we were enterprise data management focused specific than had you been no sequel so everyone's familiar with the traditional space of data management in the relational space relational world very large market very mature market well we're tapping into is what John was just saying which is you've got this proliferation but Dupin no sequel and people are hitting the wall they're hitting the ceiling because they don't have the same level of operational tools that they need to be able to mainstream these deployments whether it's data protection whether it's orchestration whether it's migration whatever the case may be so what we do that's essentially our value prophecy at a management for a Dupin no sequel we help organizations essentially drive that control plane really around three buckets data protection if it's business critical I got to protect it okay disaster recovery falls into protection bucket good old stuff everyone's familiar with but not in Hadoop in no single space orchestrations the second big bucket for us which is I'm moving to an agile development model how do i do things like automated test dev how do i do things like GD are the compliance management how do i do things like cloud migration you tut you know john touched on this one before a really interesting trend that we're seeing is you said what are customers doing they're trying to create a unified taxonomy they're trying to create a unified data strategy which is why 26 people end up in the but in lieu of that there's this huge opportunity because of what they need they know that it's got to be protected and they have 12 different platforms and they also want to be able to do things like one Cosmo I'm on go today but I'll be cosmos tomorrow I'm a dupe today but I might be HD inside tomorrow I want to just move from one to the other I want to be able to do intelligence so essentially the problem that we solve is we give them that agility and we give them that protection as they're sort of figuring this all out so we have this right you basically come in and say look it you can have whatever platform you want for your day there whether it's Hadoop and with most equals get unstructured and structured data together which makes sense but protections specifically does it have to morph and get swapped out based upon a decision correct make well now we're focused specifically Hadoop and no sequel so we would not be playing like if you we're not the 21st vendor to be helping s AP and Oracle you know customers backup their data it's basically if your Hadoop renewal sequel that's the platform regardless of what Hadoop distribution you're doing or where it's no see you know change out your piece what they do as they evolve and are correct I feel exactly right you're filling white space right because when this whole movement started it was like you were saying commodity Hardware yeah and you had this this idea of pushing code to data and oh hey his life is so easy and all of a sudden there's no governance there's no data protection no business continuity is all his enterprise stuff I didn't you heard for a long time people were gonna bring enterprise grade to Hadoop but they really didn't focus on the data protection space correct or the orchestra either was in those buckets and you touch them just the last piece of that puzzle value wise is on the machine learning piece yeah we do protection we do orchestration and we're bringing machine learning to bear to automate protection what amazing we hear a lot and that's a huge concern because the HDFS clusters need to talk speech out there right so there's a lot of nuances and Hadoop that are great but also can create headache from a user human standpoint because you need exact errors can get folded I gotta write scripts it creates a huge problem on multiple fronts the whole notion of being eventually being clustered in the first base being eventually consistent in the second place it creates a huge opportunity for us because this notion of being a legs we get the question asked the question why well you know there are a lot of traditional vendors they're just getting into the space and then what do that that's actually good because it rises you know rises all boats if you will because we think we've got a pretty significant technology mode around our ability to provide protection orchestration for eventually consistent clustered environments which is radically different than the traditional I love the story about the 26 people showing them me take me through what happened because that's kind of like what your jonquil fishbowl what do they do it they sit in their auditing they take a node so they really raising their hand they peppering you with questions what what happened in that meeting tell us so so it's an interesting microcosm what's happening in these organizations because as the various divisions and kind of like the federated IT structure started building their own stuff and I think the cloud enabled that it's like you know basically giving a the middle finger to central IT and so I can do all this stuff myself and then the organization gets to this realization of like no we need a central way to approach data management so in this meeting basically so we had an initial meeting with a couple of senior people and said we are we are going about consolidating how we manage all this data across all these platforms we want you to come in and present so when we presented there was a lot of engagement a lot of questions you could also see people still though there's an element of I want to protect my world and so this organizational dynamic plays out but you know when you're at a fortune 50 company and data is everything there's the central control starts to assert itself again and that's what we saw in this because the consequences of not addressing it is what is potentially massive data you know data loss loss of millions hundreds of millions of dollars you know data is the gold now right is the new oil so the central organizations are starting to assert that so we say that see that playing out and that's why all these people were in this meeting which is good in a way because then we're not like okay we got to sell ten different groups or ten different organizations it's actually being so there's there's kind of this pull back to the center it's happened in the no sequel world of your perspectives on this I mean early on you had guys like Mongo took off because it was so simple to use and capture unstructured data and now you're hearing everybody's talking about you know acid compliance and enterprise you know great capabilities that's got to be a tailwind for you guys could you bring it in the data protection and orchestration component but yeah what do you see it in that world what do you guys support today and maybe give us a glimpse of the future sure so that what we see as well a couple different things we are we are agnostic to the databases in the sense that we are definitely in Switzerland we were we you know we support all commerce so it's you know it's follow the follow the follow of the market share if you will Cassandra Mongo couch data stacks right on down the line on the no sequel side and what's interesting so they have very there have all varying degrees of maturity in terms of what their enterprise capabilities are some of them offer sort of rudimentary backup type stuff some fancy they have more backup versus others but at the end of the day you know their core differentiation they each it's fascinating to each have sort of a unique value prop in terms of what they're good at so it's a very fragmented market so that's a challenge that's an opportunity for us but it's a challenge from a marketplace networkers they've got to carve out there they all want the biggest slice of the pie but it's very fragmented because each of them is good at doing something slightly different yeah okay and so that like the the situation described before is they've got yes so you got one of everything yeah so they've got 19 different backup and recovery right coordinate processes approach or the or nothing or scripting law so that they do have to they've got a zillion steps associated with that and they're all scripted and so their probability of a failure you know very you drop a mirror that's a human error to is another problem and you use the word tailwind and I think that's very appropriate because with most of these vendors they're there they've got their hands full just moving their database features forward right you know where the engagement so when we can come in and actually help them with a customer who's now like okay great thank you database platform what do you do for backup well we have a rudimentary thing we should belong with it but there is one of our partners a manas who can provide these like robust enterprise it really helps them so with some of those vendors were actually a lot of partner traction because they see it's like that's not what their their strength is and they got to focus on moving their database so I'll give you some stats I'm writing a piece right now a traditional enterprise back in recovery but I wonder if you could comment on how it applies to your world so these are these are research that David flora did and some survey work that we've done on average of global 2000 organizations will have 50 to 80 steps associated with its backup and recovery processes and they're generally automated with scripts which of course a fragile yeah right and their prefer own to era and it's basically because of all this complexity there's a 1 in 4 chance of encountering an error on recovery which is obviously going to lead to longer outages and you know if you look at I mean the average cost the downtime for a typical global global 2000 companies between 75 thousand and two hundred fifteen thousand dollars an hour right now I don't know is your world because it's data it's all digitally the worst built as a source is it probably higher end of the spectrum all those numbers go AHA all those numbers go up and here's why all those metrics tie back to a monolithic architecture the world is now micro services based apps and you're running these applications in clusters and distributor architectures drop a note which is common I mean think you know you're talking about you're talking about commodity hardware to come out of the infrastructure it's completely normal to drop notes drops off you just add one back in everything keeps going on if your script expects five nodes and now there's four everything goes sideways so the probability I would I don't have the same stats back but it's worse because the the likelihood of error based upon configuration changes something as simple as that and you said micro-services was interesting to is is that now is it just a data lake kind of idea of storing data and a new cluster with microservices now you're having data that's an input to another app check so now so that the level of outage 7so mole severity is multiple because there could be a revenue-generating app at good young some sort of recommendation engine for e-commerce or something yeah something that's important like sorry you can't get your bank balance right now can't you any transfers because the hadoo closes down okay this is pretty big yes so it's a little bit different than say oh well to have a guy go out there and add a new server maybe a little bit different yeah and this is the you know this is the type of those are the types of stats that organizations that we're talking to now are caring a lot more it speaks to the market maturity do you run into the problem of you know it's insurance yeah and so they don't want to pay for insurance but a big theme in that you know the traditional enterprises how do we get more out of this data whether it's helping manage you know this I guess where that that's where your orchestration comes in cloud management maybe cloud migration maybe talk about some of the non insurance value add to our components and how that's resonating with with cost yeah yeah I so I'll jump in but the yeah the non protection stuff the orchestration bucket we're actually seeing it comes back to the to the problem sting we just said before which is they don't have it's not a monolithic stack it's a micro services based stack they've got multiple data sources they've got multiple data types it's sort of a it's the it's the byproduct of essentially putting power into into divisions hands to drive these different data strategies so you know the whole cloud let me double click on cloud migrations is a is a huge value problem that we have we talked about this notion of being data where so the ability to I'm here today but I want to be somewhere else tomorrow is a very strong operational argument that we hear from customers that we also also hear from the SI community because they hear it from the other community the other piece of that puzzle is you also hear that from the cloud folks because you've got multiple data for platforms that you're dealing with that you need agility to move around and the second piece is you've got the cloud obviously there's a massive migration to the cloud particularly with the dubidouxs sequel workloads so how do I streamline that process how do I provide the agility to be able to go from point A to point B just from of migration standpoint so that's a very very important use case for us has a lot of strategic value like it's coming it's sort of the markets talking to us like no no no we have this is him but we have to be able to do this and then simple things like not simple but you know automated test step is a big deal for us everybody's moved agile development so they want to spin up you know I don't want it I don't want to basically I want 10% of my data set I want to mask out my PII data I want to spin it up on Azure and I want to do that automatically every hour because I'm gonna run 16 I'm gonna run six builds today clouds certainly accelerates your opportunity big-time it forces everything to the table right yeah everybody's you can't hide anymore right what are you gonna do right you gotta answer the questions these are the questions so okay my final question I want to get on the table is for you in the segment is the product strategy how you guys looking at as an assassin gonna be software on premise cloud how's that look at how people consume the OP the offering and to opportunities because you guys are a young growing company you're kind of good good time you don't have the dog'll or the bagging it's Hadoop has changed a lot certainly there's a use case that neurons getting behind but clouds now a factor that product strategy and then when you're in deal why are you being called in why would someone want to call you rotor signs that would say you know call you guys up when with it when would a customer see signals and what signals would that be and to give you guys a ring or a digital connection product so the primary use cases are talking about recovery there's also data migration and the test step we have a big account right now that we're in final negotiations with where their primary use case is they're they're in health care and it's all about privacy and they need to securely mask and subset the data to your specific question around how are we getting called in basically you've got two things you've got the the administrators either the database architect or the IT or infrastructure people who are saying okay I need a backup solution I'm at a point now where I really need to protect my data as one and then there's this other track which is these higher-level strategic discussions where we're called in like the twenty six person meeting it's like okay we need an enterprise-wide data strategy so we're kind of attacking it both at the use case and at the higher level strategic and and and obviously the more we can drive that strategic discussion and get more of people wanting to talk to us about that that's gonna be better for our business and the stakeholders in that strategic discussion or whomever CIT is involved CIO maybe use their chief data officer and yeah database architect enterprise architecture head of enterprise architecture you know various flavors but you basically it kind of ways comes down to like two polls there's somebody who's kind of owns infrastructure and then there's somebody who kind of owns the data so it could be a chief data officer data architect or whatever depending on the scale of your and they're calling you because they're full they had to move the production workloads or they have production workloads that are from a bond from what uncared-for undershirt or is that the main reason they're in pain or you're the aspirin are you more others like we had a day loss and we didn't have any point in time recovery and that's what you guys provide so we don't want to go through this again so that's that's a huge impetus for us it is all about to your point it is mature its production workloads I mean the simple qualifying are you are you running a duper no sequel yes are you running in production yes you have a backup strategy sort of tip of the spear now to just briefly answer your question before we before we run out of time so it's an it's it's not a SAS basement we're software-defined solution will run in bare mantle running VMs will run in the cloud as your Google whatever you want to run on so we run anywhere you want we're sorry for be fine we use any storage that you want and basically it's an annual subscription base so it's not a SAS consumption model that may come down the road but it's basically in a license that you buy deploy it wherever you want customers choose what to do basically customers can do you know it's complete flexible flexible but back to you so let's go back to something you said you said they didn't have a point in time recovery what their point in time recovery was their last full backup or they just didn't have one or they just didn't have one all of the above you know see we've seen both yeah there's a market maturity issues so it's represented yeah you know that a lot its clustered I you know I just replicate my data and replication is not earth and truth be told my old company that was our approach we had a script but still it was like and the key thing is even if you write that script as you point out before the whole recovery thing so you know having a recovery sandbox is really in thing about this we designed everything exactly extract the value and show the use case prove it out yeah dupes real the history is repeating itself in that regard if you refuel a tional space there's a very in correlation to the Delton between the database platforms of the data mention logical hence they are involved coming in okay let's look at this in the big picture let's dad what's the recovery strategy how we gonna scale this exactly it's just a product Carson so your granularity for a point in time is you offer any point in time any point in time is varying and we'll have more news on that in the next couple weeks okay mantas data here inside the cube hot new startup growing companies really solving a real need need in the marketplace you're kind of an aspirant today but you know growth opportunity for as they scale up so congratulations good luck with the opportunity to secure bringing you live coverage here is part of Cuban YC our ninth year covering the big data ecosystem starting originally 2010 with a dupe world now it's a machine learning Hadoop clusters going at the production guys thanks for coming I really appreciate it this is the cube thanks for watching day one we'll be here all day tomorrow stay with us for more tomorrow be right back tomorrow I'll see you tomorrow

(upbeat music) >> Announcer: Live from San Francisco, it's theCUBE, covering Spark Summit 2017, brought to you by Databricks. >> Welcome back to theCUBE, it's day two at the Spark Summit 2017. I'm David Goad and here with George Gilbert from Wikibon, George. >> George: Good to be here. >> Alright and the guest of honor of course, is Ash Munshi, who is the CEO of Pepperdata. Ash, welcome to the show. >> Thank you very much, thank you. >> Well you have an interesting background, I want you to just tell us real quick here, not give the whole bio, but you got a great background in machine learning, you were an early user of Spark, tell us a little bit about your experience. >> So I'm actually a mathematician originally, a theoretician who worked for IBM Research, and then subsequently Larry Ellison at Oracle, and a number of other places. But most recently I was CTO at Yahoo, and then subsequent to that I did a bunch of startups, that involved different types of machine learning, and also just in general, sort of a lot of big data infrastructure stuff. >> And go back to 2012 with Spark right? You had an interesting development. Right, so 2011, 2012, when Spark was still early, we were actually building a recommendation system, based on user-generated reviews. That was a project that was done with Nando de Freitas, who is now at DeepMind, and Peter Cnudde, who's one of the key guys that runs infrastructure at Yahoo. We started that company, and we were one of the early users of Spark, and what we found was, that we were analyzing all the reviews at Amazon. So Amazon allows you to crawl all of their reviews, and we basically had natural language processing, that would allow us to analyze all those reviews. When we were doing sort of MapReduce stuff, it was taking us a huge number of nodes, and 24 hours to actually go do analysis. And then we had this little project called Spark, out of AMPlab, and we decided spin it up, and see what we could do. It had lots of issues at that time, but we were able to actually spin it up on to, I think it was in the order of 100,000 nodes, and we were able take our times for running our algorithms from you know, sort of tens of hours, down to sort of an hour or two, so it was a significant improvement in performance. And that's when we realized that, you know, this is going to be something that's going to be really important once this set of issues, where it, once it was going to get mature enough to make happen, and I'm glad to see that that it's actually happened now, and it's actually taken over the world. >> Yeah that little project became a big deal, didn't it? >> It became a big deal, and now everybody's taking advantage of the same thing. >> Well bring us to the present here. We'll talk about Pepperdata and what you do, and then George is going to ask a little bit more about some of the solutions that you have. >> Perfect, so Pepperdata was a company founded by two gentlemen, Sean Suchter and Chad Carson. Sean used to run Yahoo Search, and one of the first guys who actually helped develop Hadoop next to Eric14 and that team. And then Chad was one of the first guys who actually figured out how to monetize clicks, and was the data science guy around the whole thing. So those are the two guys that actually started the company. I joined the company last July as CEO, and you know, what we've done recently, is we've sort of expanded our focus of the company to addressing DevOps for big data. And the reason why DevOps for big data is important, is because what's happened in the last few years, is people have gone from experimenting with big data, to taking big data into production, and now they're actually starting to figure out how to actually make it so that it actually runs properly, and scales, and does all the other kinds of things that are there, right? So, it's that transition that's actually happened, so, "Hey, we ran it in production, "and it didn't quite work the way we wanted to, "now we actually have to make it work correctly." That's where we sort of fit in, and that's where DevOps comes in, right? DevOps comes in when you're actually trying to make production systems that are going to perform in the right way. And the reason for DevOps is it shortens the cycle between developers and operators, right? So the tighter the loop, the faster you can get solutions out, because business users are actually wanting that to happen. That's where we're squarely focused, is how do we make that work? How do we make that work correctly for big data? And the difference between, sort of classic DevOps and DevOps for big data, is that you're now dealing with not just, you know, a set of computers solving an isolated sort of problem. You're dealing with thousands of machines that are solving one problem, and the amount of data is significantly larger. So the classical methodologies that you have, while, you know, agile and all that still works, the tools don't work to actually figure out what you can do with DevOps, and that's where we come in. We've got a set of tools that are focused on performance effectively, 'cause that's the big difference between distributed systems performance I should say, that's the big difference between that, and sort of classic even scaled out computing, right? So if you've got web servers, yes performance is important, and you need data for those, but that can actually be sharded nicely. This is one system working on one problem, right? Or a set of systems working on one problem. That's much harder, it's a different set of problems, and we help solve those problems. >> Yeah, and George you look like you're itching to dig into this, feel free. (exclaims loudly) >> Well so, it was, so one of the big announcements at the show, and the sort of the headline announcement today, was Spark server lists, like so it's not just someone running Spark in the cloud sort of as a manage service, it's up there as a, you know, sort of SaaS application. And you could call it platform of the service, but it's basically a service where, you know, the infrastructure is invisible. Now, for all those customers who are running their own clusters, which is pretty much everyone I would imagine at this point, how far can you take them in hiding much of the overhead of running those clusters? And by the overhead I mean, you know, the primarily performance and maximizing, you know, sort of maximizing resource efficiency. >> So, you have to actually sort of double-click on to the kind of resources that we're talking about here, right? So there's the number of nodes that you're going to need to actually do the computation. There is, you know, the amount of disc storage and stuff that you're going to need, what type of CPUs you're going to need. All of that stuff is sort of part of the costing if you will, of running an infrastructure. If somebody hides all that stuff, and makes it so that it's economical, then you know, that's a great thing, right? And if it can actually be made so that it's works for huge installations, and hides it appropriately so I don't pay too much of a tax, that's a wonderful thing to do. But we have, our customers are enterprises, typically Fortune 200 enterprises, and they have both a mixture of cloud-based stuff, where they actually want to control everything about what's going on, and then they have infrastructure internally, which by definition they control everything that's going on, and for them we're very, very applicable. I don't know how we'd applicable in this, sort of new world as a service that grows and shrinks. I can certainly imagine that whoever provides that service would embed us, to be able to use the stuff more efficiently. >> No, you answered my question, which is, for the people who aren't getting the turnkey you know, sort of SaaS solution, and they need help managing, you know, what's a fairly involved stack, they would turn to you? >> Ash: Yes. >> Okay. >> Can I ask you about the specific products? >> George: Oh yes. >> I saw you at the booth, and I saw you were announcing a couple of things. Well what is new-- >> Ash: Correct. >> With the show? >> Correct, so at the show we announced Code Analyzer for Apache Spark, and what that allows people to do, is really understand where performance issues are actually happening in their code. So, one of the wonderful things about Spark, compared to MapReduce, is that it abstracts the paradigm that you actually write against, right? So that's a wonderful thing, 'cause it makes it easier to write code. The problem when we abstract, is what does that abstraction do down in the hardware, and where am I losing performance? And being able to give that information back to the user. So you know, in Spark, you have jobs that can run in parallel. So an apps consists of jobs, jobs can run in parallel, and each one of these things can consume resources, CPU, memory, and you see that through sort of garbage collection, or a disc or a network, and what you want to find out, is which one these parallel tasks was dominating the CPU? Why was it dominating the CPU? Which one actually caused the garbage collector actually go crazy at some point? While the Spark UI provides some of that information, what it doesn't do, is gives you a time series view of what's going on. So it's sort of a blow-by-blow view of what's going on. By imposing the time series view on sort of an enhanced version of the Spark UI, you now have much better visibility about which offending stages are causing the issue. And the nice thing about that is, once you know that, you know exactly which piece of code that you actually want to go and look at. So classic example would be, you might have two stages that are running in parallel. The Spark UI will tell you that it's stage three that's causing the problem, but if you look at the time series, you'll find out that stage two actually runs longer, and that's the one that's pegging the CPU. And you can see that because we have the time series, but you couldn't see that any other way. >> So you have a code analyzer and also the app profiler. >> So the app profiler is the other product that we announced a few months ago. We announced that I guess about three months ago or so. And the app profiler, what it does, is it actually looks after the run is done, it actually looks at all the data that the run produces, so the Spark history server produces, and then it actually goes back and analyzes that and says, "Well you know what? "You're executors here, are not working as efficiently, "these are the executors "that aren't working as efficiently." It might be using too much memory or whatever, and then it allows the developer to basically be able to click on it and say, "Explain to me why that's happening?" And then it gives you a little, you know, a little fix-it if you will. It's like, if this is happening, you probably want to do these things, in order to improve performance. So, what's happening with our customers, is our customers are asking developers to run the application profiler first, before they actually put stuff on production. Because if the application profiler comes back and says, "Everything is green." That there's no critical issues there. Then they're saying, "Okay fine, put it on my cluster, "on the production cluster, "but don't do it ahead of time." The application profiler, to be clear, is actually based on some work that, on open source project called Dr. Elephant, which comes out of LinkedIn. And now we're working very closely together to make sure that we actually can advance the set of heuristics that we have, that will allow developers to understand and diagnose more and more complex problems. >> The Spark community has the best code names ever. Dr. Elephant, I've never heard of that one before. (laughter) >> Well Dr. Elephant, actually, is not just the Spark community, it's actually also part of the MapReduce community, right? >> David: Ah, okay. >> So yeah, I mean remember Hadoop? >> David: Yes. >> The elephant thing, so Dr. Elephant, and you know. >> Well let's talk about where things are going next, George? >> So, you know, one of the things we hear all the time from customers and vendors, is, "How are we going to deal with this new era "of distributed computing?" You know, where we've got the cloud, on-prem, edge, and like so, for the first question, let's leave out the edge and say, you've got your Fortune 200 client, they have, you know, production clusters or even if it's just one on-prem, but they also want to work in the cloud, whether it's for elastics stuff, or just for, they're gathering a lot of data there. How can you help them manage both, you know, environments? >> Right, so I think there's a bunch of times still, before we get into most customers actually facing that problem. What we see today is, that a lot of the Fortune 200, or our customers, I shouldn't say a lot of the Fortune 200, a lot of our customers have significant, you know, deployments internally on-prem. They do experimentation on the cloud, right? The current infrastructure for managing all these, and sort of orchestrating all this stuff, is typically YARN. What we're seeing, is that more than likely they're going to wind up, or at least our intelligence tells us that it's going to wind up being Kubernetes that's actually going to wind up managing that. So, what will happen is-- >> George: Both on-prem and-- >> Well let me get to that, alright? >> George: Okay. >> So, I think YARN will be replaced certainly on-prem with Kupernetes, because then you can do multi data center, and things of that sort. The nice thing about Kupernetes, is it in fact can span the cloud as well. So, Kupernetes as an infrastructure, is certainly capable of being able to both handle a multi data center deployment on-prem, along with whatever actually happens on the cloud. There is infrastructure available to do that. It's very immature, most of the customers aren't anywhere close to being able to do that, and I would say even before Kupernetes gets accepted within the environment, it's probably 18 months, and there's probably another 18 months to two years, before we start facing this hybrid cloud, on-prem kind of problem. So we're a few years out I think. >> So, would, for those of us including our viewers, you know, who know the acronym, and know that it's a, you know, scheduler slash cluster manager, resource manager, would that give you enough of a control plane and knowledge of sort of the resources out there, for you to be able to either instrument or deploy an instrument to all the clusters (mumbles). >> So we are actually leading the effort right now for big data on Kupernetes. So there is a group of, there's a small group working. It's Google, us, Red Hat, Palantir, Bloomberg now has joined the group as well. We are actually today talking about our effort on getting HDFS working on Kupernetes, so we see the writing on the wall. We clearly are positioning ourselves to be a player in that particular space, so we think we'll be ready and able to take that challenge on. >> Ash this is great stuff, we've just got about a minute before the break, so I wanted to ask you just a final question. You've been in the Spark community for a while, so what of their open source tools should we be keeping our eyes out for? >> Kupernetes. >> David: That's the one? >> To me that is the killer that's coming next. >> David: Alright. >> I think that's going to make life, it's going to unify the microservices architecture, plus the sort of multi data center and everything else. I think it's really, really good. Board works, it's been working for a long time. >> David: Alright, and I want to thank you for that little Pepper pen that I got over at your booth, as the coolest-- >> Come and get more. >> Gadget here. >> We also have Pepper sauce. >> Oh, of course. (laughter) Well there sir-- >> It's our sauce. >> There's the hot news from-- >> Ash: There you go. >> Pepperdata Ash Munshi. Thank you so much for being on the show, we appreciate it. >> Ash: My pleasure, thank you very much. >> And thank you for watching theCUBE. We're going to be back with more guests, including Ali Ghodsi, CEO of Databricks, coming up next. (upbeat music) (ocean roaring)