 Live from Washington D.C., it's theCUBE, covering .conf 2017, brought to you by Splunk. And welcome back to the nation's capital, theCUBE continuing our coverage here of .conf 2017. It's Splunk's annual get-together and coming to Washington D.C. For the first time, huge success, 7,000 plus attendees, 65 countries, I forget the millions of miles, the three million miles. Let's see, was it three million? I thought it was 30 million. Maybe 30 million. It's a big number. Dave Vellante, John Walls here on theCUBE, but I'd say off to a roaring start here, to say the least. Josh Rogers joins us. He's the CEO of Syncsort. And Josh, good to have you here on theCUBE. Good to see you, sir. Thanks for having me. Good week for you, big week for you. A couple of announcements that you made here recently. Go ahead and share with us a little bit about those. Sure, so we made two announcements yesterday. The first is a new product. It's called Transaction Tracing. It's an add-on to our IronStream product. IronStream is a solution that delivers mainframe machine data to Splunk Enterprise and has integration points on the security and on the IT service intelligence components within Splunk. What Transaction Tracing does, the new product introduction, is it adds additional capabilities to understand and trace a transaction that could begin on a mobile device and follow it all the way through the multiple hops it will take to ultimately transact against a mainframe. And when that transaction hits the mainframe, there's several things that you want to understand. One is you want to understand how is it performing? How is it affecting my mainframe environment? Is it causing problems in other places? And you want to be able to look at that transaction as or that application as a service. And so you want to be able to track that whole service end to end. So what we've done with Transaction Tracing is created an ability for Splunk customers to be able to service all of that data, collate it together and get a unified view of both how the service is behaving, the performance that, characteristics it's delivering to the customers that are utilizing the service, and then the impacts that it's having on the mainframe. All of which are core components of understanding how your IT operations are performing and kind of all about what Splunk is supporting. We're just adding on additional capabilities for Splunk customers. So I wonder if I could follow up on Transaction Tracing. So I remember about 20 years ago, David Floyer did a piece of research when we were working together at a former company. And I was struck at the time by the number of subsequent transactions that had to occur just to get an outcome of a check process. I mean it was like some orders of magnitude greater. Add to that mobile transactions. I can't imagine with all the internet traffic and other activities going on. Now add to that big data and security and fraud detection and all the other things that were doing the data. The number of ancillary transactions has got to be enormous. Hence the need presumably for Transaction Tracing. So maybe talk about the market need and why Syncsort, you would think doesn't the mainframe have all this stuff integrated into it? Maybe talk about that. Yeah, sure. So I think one of the things to understand is that the mainframe compute volumes continue to go up. I think people tend to think about mainframes as an environment that perhaps isn't growing, but in fact it is growing. And one of the key drivers is this new transactional workload that is driven in part by mobile and other devices. And so what you have if you're running a mainframe is I'm experiencing increase in my transactional workloads. I need to figure out how to kind of support that. But I also have a lot more characteristics I care about, security, performance, et cetera. And so I need deeper analytics. And of course, they are difficult systems. You need to understand the mainframe. You need to understand how kicks and DB2 interact to support a transaction. But you also need to understand kind of this next generation analytic environment and how can I leverage that to actually get the insight I want. And that's really what we call as an example of a big iron to big data challenge. And so what Syncsort's been incredibly focused on is helping customers understand the very specific use cases that are included in that big iron to big data space and providing very differentiated solutions with very deep differentiation to solve those specific use cases. And transaction tracing is a good example of that. It sounds fairly narrow, but it's incredibly important if you're a bank and you want to give your customers an ability to kind of check account balances and interact with you in a way that they haven't in the past. Well, it's one of those things that we talk about, you know, breadth apps and depth apps. This is a depth app, right? Okay, and then in terms of the Splunk relationship, where does that fit in? And what are the swim lanes between you and Splunk? We view Splunk as a key platform in the world today for kind of understanding IT operations and security. We view them as incredibly powerful from a platform perspective, and we also view them as a partner that we can add value to, that we can provide access to data that enriches their platform and allows their customers to get more value out of it, and that we can do that in a unique way. And so we have a very close relationship with Splunk, and that's not just at a go-to-market level, it's also at a product management and engineering level. We work very closely to make sure that our products integrate well with Splunk, so we've got deep integration with IT service intelligence, we've got deep integration with enterprise security, and we'll continue to drive deeper integration into the Splunk platform. So when a customer comes across a scenario where they want to ingest mainframe data, they can be assured that they will get no better product in the marketplace than sync source, IronStream, and associated modules in terms of both how it will perform on its own, but also how it will integrate with Splunk. So that deep integration is something that's always interesting to us on theCUBE. A lot of times you see Barney deals, Barney, I love you, you love me, let's do a press release. And so one of the ways in which we measure or try to measure the intensity of the integration is the engineering that's involved. So I wonder if you could sort of double-click on that. Is it kind of just making sure that you're familiar with the APIs? Are you actually doing integration and engineering on both sides? Maybe you could talk about that. Well, so I'll talk about our integration with enterprise security and IT service intelligence. And those are, you can think of those as specific applications to support deep analytics, and these are Splunk offerings, deep analytics around those two areas of competence, such that a user can rapidly build a set of dashboards that allow them to answer the questions you want to answer if you're focused on IT service intelligence or understanding security. Fundamentally, they're data models. They've gone out and mapped what are all the data elements that you need, what's the structure that you need to that data model to be able to answer the questions that a security-minded kind of analyst would want to answer. That allows you to, if you map the data sources into those data models, that would allow you to rapidly build those dashboards that support those types of roles in the enterprise. What we've done is taken the very large amount of mainframe machine data that gets produced. Generally, it's an SMF record, so there's 260 types of SMF records. Each one has a subtype. We've mapped it into those two data models that Splunk has created. Nobody else has done that. And what that does is it allows those customers to get a complete end in view of how can I rapidly enhance my IT service intelligence application or my enterprise security application with mainframe data, which just happens to run my most sensitive applications and most voluminous applications from a transaction perspective in my enterprise. So we think that that deep integration is a really powerful capability, and it's just an example of where we like to go deeper with our partners than what we see other companies doing. You know, when, I mean, you talked about the mobile environment a little while ago and complexities and that. I'm always just kind of curious, I don't really talk about what that does in terms of when you're harvesting data, and now you're in a non-stationary environment, and that comes with it a whole different set of characteristics and challenges. I mean, what layer of complexity do you take on when you all of a sudden you can be anywhere and feeding data at any time from any machine? Sure, well, I mean, what it creates is a lot more interaction points, right? So I probably interact with my bank a lot more today than I did 10 years ago, because I don't have to find an ATM or go buy a branch. You never walk into a branch, right? And I did this over the weekend. I had to kind of transfer some money, right? So I just transferred it, and I was in Colorado hiking, and I transferred funds between accounts. And then later on the golf course, I did a wire, literally. You didn't have to transfer money on the golf course for a reason, did you? No, no, no, those were unrelated events. Just making sure. Lost a few dots. But that type of interaction, so you get more frequent interactions, which creates an operational challenge, particularly when you think about the mainframe and how customers pay for that, right? They pay for it based on how much CPU they use on a monthly basis. And so what we want to do is help customers run that system as efficiently as possible. It also creates a massive analytic opportunity, because now I have a lot more data that I can start to analyze to understand trends, because I have more touch points. But the trick is I've got to get that data into a repository and into an analytic environment that can handle that data. And that's where I think Splunk creates such an interesting opportunity, and what we're trying to do is just add value to that and make it easy for customers to leverage all their data. Does that make sense? Yeah, it does. How about the government marketplace? We're here in the district. You guys have an announcement around new partners. Maybe talk about the importance of government and what you're doing there. Sure, so we signed a distribution relationship with Karasoft, also a big Splunk partner, and that is going to allow government customers to more easily take advantage of Iron Stream and Transaction Tracing in these use cases. The federal government is an enormous market opportunity. It's also a big mainframe environment. There's a lot of government, core government applications that still run on mainframe environments. In fact, I would tell you most do. IRS, Social Security, CIA, and other agencies. And so we think giving ourselves an easy route to market for these customers is a great opportunity for us. It's also a good opportunity for Splunk's customers who are in the government, because they can go and buy additional capabilities that are relevant to their environment through the same partners that they've been working with. Is there a difference in how you deal public and private sector then? I mean, governance and compliance and all those things, I would assume you have different hurdles. They're different contract vehicles which have different kind of requirements in them, and that's one of the values that we get with the Karasoft relationship is just giving us access to those various contract vehicles. Talk a little bit about life. I mean, you've always been a private company, but you don't have the 90 day shot clock. You got new owners. What's the objective? Maybe talk about that sort of the patience of the capital, what your priorities are with regard to these owners? Maybe discuss that a little bit. Yeah, sure. So just to give a little background, in early July, we announced, and in mid-August, we closed a transaction whereby Cinerbridge partners acquired SyncSort and another company vision solutions from our previous owner, ClearLake Capital, and we've combined the two companies under the SyncSort umbrella, and myself and our leadership team is going to take the company forward. So the 90 day shot clock, I would say definitely we still care about the 90 day shot clock. We are very focused on growing this business and doing that in a consistent way on a quarterly basis. I guess the difference is I get to talk to my investors every day rather than once a quarter, but they've been great partners. The Cinerbridge guys have a lot of resources. They've been incredibly helpful in helping us start to think through kind of the strategy, some of the integration work we're doing with vision, but we think there's an opportunity to build a big business. We've employed a dual strategy of organic growth focused largely in the big iron to big data spaces, as described earlier, combined with M&A, and over the last 24 months, we've tripled the size of SyncSort. So it's grown 3X in revenue. We've doubled in employees. So you say that again. We've tripled revenue, doubled headcount. Okay, so you've increased profitability in theory then. Yeah, and we will continue to run this same play. We're seeing acceleration in our organic plays focused on the big iron to big data market, and we also believe there are additional data management capabilities that are relevant to our customers that we can acquire and help point towards that big iron to big data play. And so we'll continue to look at various spaces that are interesting adjacencies that are relevant to our customers. And some of that revenue growth, obviously, is through acquisition, right? And so when you think about, it used to be the classic private equity play was to suck all the money out of the company, leave the carcass for somebody else to deal with. It seems like there's a new thinking, not seems like there is a new thinking here. Invest, acquire, increase the value. I think the money guys are realizing, wow, there's a lot more money to be invested in the technology business. We have an eye towards profitable growth, but we are absolutely making investments. And as you get larger scale, you can make meaningful investments in these specific areas that can help deliver really great innovation to customers. And transaction tracing is an example of that. And certainly I can give you others. But for sure, we are trying to build value. This is not a traditional kind of private equity play. And I also think that private equity is generally understanding that there's an opportunity to create value after the catch, if you will, in the tech industry. And I was looking at an analysis last week that financial investors, private equity, for the first time ever, will do more deals in technology than strategics in 2017. And so I think that's a statement that says that there's certainly an opportunity to create long-term sustained value in a private equity-backed kind of model. And I think to some extent, SyncSort's been pioneering that with a dual approach on organic growth and on additional acquisitions. Well, I mean, and you've seen it, coming out of the downturn, or maybe sort of into downturn, a lot of these public companies were struggling. I mean, you certainly saw it with Dell, BMC, Riverbed, in for all examples of private equity where there's investment going on and I think a longer-term vision with some, as I call it, patient capital. SyncSort is obviously part of that. And SyncSort, actually interesting when it spun out its storage business, as a successful company, CataLogic is doing its thing, so SyncSort was able to monetize that and then really focus on the core knitting. And then figure out where in the big data space that you can make money, which not a lot of people were making money in the big data space. So that's good. Congratulations on that. It's been, I like to tell folks that we've had a really good run, but it's really the first couple of innings. The Cinterbridge team is going to be incredibly supportive and I can't wait to get started on the next leg of the journey. I think there's going to be a lot more innovation to come and I'm looking forward to it. Sir, you're in the middle of the game. Yeah, we appreciate the time here. Good luck with that. The long-term plan down the road. I hope the show's going well for you. It's going great. And it's good seeing you. Great, thanks Josh. Josh Rogers from SyncSort with us today here, SyncSort rather here on theCUBE. Back with more Washington DC, theCUBE live at dot com 2017, right after this.