 Okay, welcome back everybody, Jeff Frick here with theCUBE. We're in the Palo Alto studios having a CUBE conversation. You know, we go out to all the events, we talk to a lot of executives and engineers and developers, et cetera. But what we really like to do when the opportunity is here, is talk to practitioners. People are actually implementing the technology, putting it in play, trying to get a competitive advantage and we're really excited to have our next guest, he's Stephen McKay, he is the senior director in user services and support at the Lending Club. Stephen, great to see you. Thank you. So for people that aren't familiar with the Lending Club, just give us kind of the basic overview. Sure, we've got sort of two halves of the business. One is perhaps you'd like a loan, restructure your debt or do some life changes like a wedding or something like that. So you could come to us for a personal loan. The other half of our business is for people who have money that they wish to invest in a different kind of vehicle. And so they invest in other people's debt and it gives them a steady cash flow because when the loans get paid back, they get paid. And so we provide a marketplace for those two halves to me. So that's really what makes you different. It's clear there's lots of places that people can go get a loan, but I've never heard kind of that second half of the equation. So what percentage of your capital comes from people participating on the supply side? So almost, well, all of our debt is designed to be sold on the marketplace. We invest almost, well, we invest a little bit of money just mainly as a float, but almost everything is for our investor. That's so cool. And is it done in like a fund or how's it kind of structured or you're kind of buying into a portfolio of loans? When you go on to our platform, you go in and you can see the type of customer that you wish to invest in, certain FICO score, certain geography, certain background in jobs, the reason why they're wanting a loan. And then you select some loans individually, but you're not buying the entire loan. Let's say someone wants $5,000. You're going to invest $25, $50 in that person and you're going to find 100 people like that to invest your money. So that way, if someone does default, that does happen. You're not out your entire... Right, right. And does the transaction happen on demand or I put in whatever my amount is I want to put in your platform, I put my profile in and then you basically parse it out as those customers come in. Yeah, so basically what's happening is when you go on the platform you're seeing people that have already applied and we have basically approved and you are funding their loan. So you have a few days to decide which loans you're going to fund before they disappear because we are going to have to give the people money. How cool, and how can you share the scale of kind of the size of your operation or I don't know what's public or private so you don't say anything. So we actually are the nation's largest personal loan lender in this market space. Wow. So yeah, several billion dollars a year. Very cool. So presumably you have an advantage because you're a modern company, you're looking at different types of data, more data, cutting it different ways than maybe a traditional bank that's just using your FICO score, some of the kind of more traditional scoring methods. Exactly. So big data and data in general, tremendous piece of your guys core business. So what are some of the things, maybe I don't know if you could share that that you look at that maybe people would never think that's a valuable, not the whole portfolio, but are there some funny ones? I can't get into too much details because it is somewhat, you know, so probably it's the secret sauce. Don't tell me any secrets. But we do use a wide variety of the traditional sorts of things that people are familiar with, but we look at things that are a little bit outside the box too, that have a lot more to do with who you are as a person and the type of credit that you've had in the past and things like that. Very cool. All right, and then what do you do? Obviously, Ridge, you're title, but what do you keep busy with all day long? Besides coming to visit us here and follow all the tests? Yeah, I keep busy with making our internal employees happy. So I'm on the corporate technology side of Lending Club and I make sure that our employees have the tools that they need to be able to do their jobs on a daily basis. So I'm running back-end infrastructure or things like our email services and stuff like that, but also just the day-to-day grind of laptops and things like that. Right, keeping the lights on. It's a classic kind of IT. So you're here on behalf of Cohesity. So where does Cohesity play in your world now and then we'll get into it a little bit deeper as to why and how. Sure, so Cohesity is basically our new backup platform. We were a very traditional backup environment, standard software, back-end virtual disk system, very traditional type shop. Honestly, I've been in IT for over 20 years and I put in a system like this, one of my first gigs as a consultant over 20 years ago. So it was time to look outside the box and maybe shake things up a little bit and look at something that's been developed in the last decade. And so that's how we kind of landed at Cohesity. So what appealed to you? What were the kind of top two or three things you were looking for? Well, our huge, our biggest challenge was, I mean, back in when I started in IT I was backing up four gig hard drives and four gigs was awesome, you know. And now my phone is- Four terabytes, four gigs. Yeah, and now my phone is bigger than four gigs, a lot bigger than four gigs. And that backup system couldn't back up my phone. And so we have terabyte file systems and things. And with the traditional backup system that was, if it was successful, it took days, four days or so to actually do a backup. And so that's not tenable. And so going to something that rather than copying every file every single time does it on a block level and is a little more integrated directly into our virtualization layer was the right way to go. Well, I love how you said before we turn on the cameras that when you make a decision to replace something you try very, very hard to actually replace something and not just add something new. Yeah, so I drive my staff a little nuts because they know that when they come to me and say, we're going to do this new exciting thing and we're going to stop doing this over here. I'm like, you're going to stop. That means I'm going to walk in the data center, flip that thing off, right? And they're like, well, but there's that old stuff. I'm like, yeah, well we got to get the old stuff out. And so that was really one of the competitive advantages that Cohesity had for us is because they're not just a backup appliance or whatnot. They do have a file system in there. We could basically replicate all our old backup jobs into the Cohesity. And that way we have to keep the software around, you know, and being able to restore an old job if we had reason to do so, we'd be able to. But at least we can go into the data center and shut that old device off. So were there any particular features that jumped out at the top of the list that, or was it just, you know, you're looking for really a modern architecture with a whole bunch of features? Yeah, it was, it's really, it's a very modern architecture. It has some great capabilities to move data into the cloud and into A to S space to actually use this sort of same technology and the same policies to backup devices in the cloud that you would use on-prem. And so, you know, it has a lot of great features, but to us really the competitive differentiator was that file system. Being able to move our old backups directly into the system and be able to use our old backup software. We didn't have to do, you know, restore and re-back up or anything crazy like that. Right. So all your peers are all probably wondering how hard was it, you know, what was kind of the scope of the effort? What was the scope of moving the old stuff over? Well, so, what would you tell to somebody making, you know, considering this move? Have a good partner. I hired our integrator to do the actual migration. And one of the reasons I chose the integrator I chose is because they were willing to bid on this, knowing that what they're really gonna do is dial into my system for four hours a week for a very long period of time and just scheduling backup jobs to keep the engine humming. And there wasn't a lot of like sit there and there was no value of having one of my people sit there and watch stuff because it's just backup restores. It's not rocket science, but it does take a little bit of hand-holding. So I outsourced the actual migration of all the jobs. The actual setting up of Cohesity is like, you know, a couple of hours. Once it's racked, it's, you know, actually setting it up in the migration of, you know, turning it on, making it active, doing some test restores, doing some test backups, test restores of systems, and then just, you know, opening the floodgates. That was relatively simple. And you mentioned that one of the things that appealed to you was an integration to public cloud environments beyond just the on-prem. Are you using that? And if so, how are you divvying up what goes where? Yeah, so most of our services are on-prem or cloud services. You know, no infrastructure. We're just, you know, the sales forces that workdays, those sorts of services. And so we don't have a ton of stuff in AWS based on the corporate side. My peers in the product side would be very different answer there. But what we're doing is we're doing migration so that we can do our DR in the cloud. So that we can keep stuff on-prem, but if we needed, you know, if we had a problem on-prem, we can do DR. We're also doing replications between our colos, but that's our primary use case. Is to get it off, so it's cool. So do you consider that kind of secondary storage or it's really more just pure backup there if you had a problem? Yeah, so I mean, so we are looking for secondary storage and things, you know, our file servers and things like that. We've had such good performance with the backup migration. And so we're looking at getting off of our file server so we don't even have to back it up so it's just native objects inside. So I'm just curious in terms of kind of the data growth that you have to deal with on a day-to-day basis. Your data growth in terms of the IT shop is probably, your explosive stuff's probably happening more, I would imagine, on the core product or you're smiling and making it a funny face. Well actually, yeah, so it's something we didn't talk about earlier. So one of the things that was very interesting to me, we put in the Cohesity system and we sized it all out and based on our data volumes and things like that. But what we didn't realize is that we had a system that is part of our statistical analysis for our loan modeling, okay? And what we didn't understand is we couldn't back that up. It was too large and we couldn't back it up with our old backup system. And what the statistic guys are doing is they're building a model and going, does this work? And they'll run a ton of data through there and they'll create a model and it'll be two terabytes in size and they'll take one look at it and go, nope, that doesn't work, they'll throw it away, okay? And then a week later they go, well, you know, maybe, let me look at that again. And they call us up and say, I need to restore that two terabytes. Well in the past, they couldn't do that because we couldn't back it up, all right? And so all of a sudden, we can back this stuff up. And so it's getting backed up when we're just starting to do these restores. And so they only had a working size of 20, 30 terabytes or something like that. But what we found out was they generate like 10 terabytes a day and they throw it away. And so our backup volume had nothing to do with the size of the volume that we were giving them. It had to do with how much data they generate. So they generate a ton of data. We had to- So they want to back up Mondays, Tuesdays, Wednesdays, and Thursdays, even though the sum of that is five X, you know, what is their working amount. But they still want it backed up and they still make the call. Well in the past, they wouldn't be able to call us. So they would rerun the job, it would take them a day or two and then they'd have their answer. Now we can expose that old backup job directly to them. It's maybe not high performance because it is secondary storage, but at least they can take a look at it and kind of go, yeah, okay, let's bring that back into our primary storage and continue working with it. And that recreation is not so much a Monday, Tuesday, it's really like a 10 a.m., noon, two, four kind of thing. So has that changed the behavior in kind of the frequency or it's their work environment or now they feel more comfortable having a lot more of those models, a lot more simulations, and ultimately should help their business? Yeah, well and the thing is, is that it gives them the ability to quickly play with the model, throw it away and they can throw it away knowing we can give it back to them quickly rather than having them to completely regenerate the data. So they are able to churn through a lot more models. How many weeks do you keep that stuff? Or how many versions? Well, yeah, there's a lot of debate around that. It's zero to infinite, but there's a lot of debate about that. There's some negotiation around that. I mean, we have multiple different working areas and some of it's like, okay, if you think you might need it and you want to keep it around for a while and we actually may use it, then it goes into one storage area and we keep that for a lot longer. That's funny. That's a really elegant example of something we talk about all the time in theCUBE, which is at what point in time will the value of the data become a balance sheet asset? Whether that's your core data in your product set or I'm sure there's a whole lot of value in all these models that they're building. And before data wasn't necessarily considered an asset. It was a liability because I had to buy all this stuff to store it and keep it in. Like you said, some stuff I couldn't even store. Now people recognize it's a huge value. It's not necessarily in the balance sheet yet. I think it will be at some point down the road, but this is a terrific example of how you can explode the value by exploding the access, the reuse, the capability, without necessarily exploding the budget that you got to take back up to your boss. Yep. Yeah, very much so. And then to be able to drive all these different models, tweak them, customize them, standardize them, target them. Really, they must be loving that. They're very happy. Yeah, yeah. Okay, so as you look down the road, like you said, you've been in the business a long time. The data explosions go and bananas. You're in a pretty cool, unique little marketplace. What are some of your priorities? What's next for you? Well, okay, so this is nothing to do with what we've been talking about. But a month ago, I turned my laptop into my desktop support team. And I now run everything off my phone. Oh, you turned your physical laptop. My physical, that thing, I don't carry that thing. That's too big, big. So we have a VDI implementation. And I have a Samsung phone that has a dock. So I dock it and I have my monitor and I go in to do VDI. And but I don't have a laptop anymore. I can do everything I can do for my phone. And so I think that is like how to make that something that the business users can do rather than just us techie guys who want to push the boundary and push the envelope. I think that really is the future. And the whole idea of mobile first, it's kind of like mobile only. We really shouldn't be doing mobile first. It's mobile only and how can you make it work? And I like your style. You're just extreme. Like you said, you just turn off the old light switch. If you're going to make the move, make the move. Just rip the Band-Aid off and get on with it. They've got the laptop. I told them to redeploy it. It's a nice laptop. Give it to somebody else. If there's something I can't do, I'll go get one alone. Don't say that too loud. Chuck's looking for a few laptops. All right, Steven. Well, thank you for coming by and sharing the story. I got to dig more into the company. I didn't know that whole kind of backside in terms of the investor opportunity. That looks pretty cool. And again, thanks for stopping by. All right, thanks for having me. All right, he's Steven. I'm Jeff. You're watching theCUBE from the Palo Alto Studios. Keep conversation. Thanks for watching. We'll see you next time.