 Live from the MGM Grand Convention Center in Las Vegas, Nevada, it's theCUBE at Splunk.conf 2014. Brought to you by headline sponsor, Splunk. Here are your hosts, Jeff Kelly and Jeff Frick. Hi, welcome back. We're at the MGM Grand in Las Vegas, Nevada. This is theCUBE. We go out to the events. We extract the signal from the noise. We're at Splunk.conf 2014, the fifth year of Splunk's easier conference over 4,000 people here. Splunkers, customers, partners, prospects, press, analysts, everyone that wants to learn more about what's going on with the latest releases for Splunk. They've outgrown the prior venue and had to move over here to the MGM Grand. So we're theCUBE. This is our third year here. We're excited to be here because it's got great insight and it's an exciting growing company. We're joining this segment by my co-host, Jeff Kelly. Yeah, I'm Jeff Kelly from Wikibon and we are joined by Lena Joshi, who's the Senior Director of Infrastructure and Operations and Marketing at Splunk. Welcome back to theCUBE. Thanks, Jeff, and Jeff. Hi, Cube alumni. Absolutely. One of our women in tech, which we've always loved to get. So Lena, tell us about your impressions of the show. This is by far the biggest.conf we've seen. A lot of energy. How's the show going for you? The show has been simply fantastic. The amount of excitement around, you know, just people increasing their usage of Splunk, trying out different new things, exchanging ideas has been fantastic. So far, I would say the highlights of the show have been, you know, our keynotes, the security keynote that put the fear of God in everyone. Yes, it did. The customers that spoke at our main keynote, especially Snehal Antani from GE and the Coca-Cola platform architect and the Red Hat CIO. They were just amazing, phenomenal stories and they made quite the impact with the audience. Absolutely. So we want to get into some of the announcements, Splunk, as babe, but why don't you remind our audience of your role as senior director of infrastructure and operations marketing? So I run solutions marketing at Splunk, for Splunk and IT operations, applications management and application development. So generally, I just shorten it to solutions marketing. So a lot of announcements, one of them, of course, being Splunk 6.2, the core enterprise platform. And we've talked to a lot of customers here in theCUBE and one of the things they pointed out and that they really like about the new release is the addition of some of the more self-service style tools. Talk a little bit about the kind of philosophy behind 6.2 and maybe detail some of those features. Absolutely. So we started on this journey at least a few months ago or a year ago when we introduced Pivot and data models. And the whole idea, the philosophy behind that was to make the data that in Splunk more accessible to a broader number of users. And with this release, 6.2, we're fundamentally just amazingly increasing the number of users that can interact with machine data that's sitting in Splunk. You can type in any search, it can be simply star search, star error, anything. And on the results, you can instantly pivot. So now you get like an Excel-like interface on just plain old machine data. What this does, it takes the work that somebody has to do to put the machine data in a usable form for a business, non-technical person to understand it and just present it to them in a much more easier interface. In a way that they understand, everyone understands Excel. It's interesting, Excel has been one of those things where it's been, people have a love-hate relationship with it. It's everyone's favorite BI tool. Whether they love it or they hate it, that's what they use for BI. It's the most widely deployed BI tool on the planet. All its flaws and all, but it gets the job done. It's not always the prettiest, but it gets the job done. So talk about why it was important for you to extend Splunk to more users. I mean, obviously from a business perspective, more users equals more revenue. That's great, but at a more philosophical level, what was the thinking behind extending Splunk to that more non-technical person? The great, great question, because this is so ingrained in Splunk that the machine data that you're indexing within Splunk is not just relevant for one particular use case. It is relevant for a wide variety of use cases. It's relevant for operations, troubleshooting, security, and it is also an important indicator of what exactly is going on in the environment. How are users behaving? How are systems behaving? Once you're able to harness the power of this data, you're able to extract insights like XYZ features that I'm offering to my users are more popular than those other ABC features that I was spending a lot of time working on. You get product analytics, you get user analytics, usage analytics, and that's really what makes the data more powerful. It really delivers value to our customers. So it's all this time, it's been about making sure you extract all the value that you can out of machine data. And we've talked about that with a number of guests that basically the same data, depending on the context, can provide insight into lots of different processes. We talked a little bit about off camera, and I want to kind of revisit it. You talked about really enabling the technical folks to really get more involved in business cases and to show and demonstrate what's in the data to their business leaders. At the same time, there's a move to getting the business people that are not the technical folks the ability for them to have access to the data and for them to massage the data. So it's kind of two different paths to the same journey. Or if you can speak a little bit about your philosophy in terms of the solution design. That's a great question. I mean, if you've downloaded Splunk or if you've played with it on your own, you know that it's a very, very easy tool once you get what you want to do it. But really, behind the scenes, once organizations start adding more and more data to Splunk, it really becomes a platform. And the value is extracted from all this data by being able to make correlations across different types of data. And once you have all those correlations in one place, you're not only solving your IT operations problems, you're solving application management problems, you're solving business decision-making type of problems. With the introduction of these new features in 6.2, we are, as you said, making it fundamental, taking two different paths, two different approaches to making that machine data more usable. The technical people, the people who are Splunk experts, they can now work on more advanced problems and leave the self-service, like here's a set of analytics. If you want to change it or do anything else with it, feel free to do it. So they can empower more users within the organization so that they're not the bottleneck. And on the other side, the users that are typically wanting, okay, I need this report to look like this and I want to run this other query and slice this data this way now, because I think that's more relevant. They can do more with that data. Yeah, and then the other challenge that you guys are giving yourselves is really the delivery across a number of different platforms, right? So you can get the Enterprise Edition and install it on Prim. You've got a cloud solution, you partner with AWS. So in terms of a solution set, you're supporting kind of a number of different flavors of the same application. Talk about kind of those challenges and really philosophically why you guys are supporting that type of delivery model. That one is easy. The easy answer is we want our users to be able to consume our product however they want, wherever they want in whatever model that's very, very convenient for them to use. And that's the reasoning behind Splunk Enterprise, Splunk Cloud, our integration with Amazon web services, where the users are, that's where we want to be. That's also the motivation behind Splunk Mint, our mobile intelligence product, if you want to talk about that. Yeah, that was another announcement here at the show. I think a big announcement and plans right into, to some extent to the whole DevOps conversation we've been having about using data coming from your applications to continually improve those applications. And this Splunk Mint comes from the BugSense acquisition. Talk a little bit about, maybe a little bit about that acquisition and the role Splunk Mint plays with your customers. Absolutely. So yes, for our viewers, if you remember, we acquired a company called BugSense last year. And what we released this year is our first set of products based on that acquisition. So we released Splunk Mint Express, which is a major upgrade from what BugSense was. And what it does is, as you can see, everybody has hundreds of, well, not hundreds, but I sometimes feel like I have a hundred mobile devices. Certainly a hundred passive messages, right? And you're like, what, did I text my Twitter, my Facebook, my email, my LinkedIn? That's right. Yes, so yes. I might have a hundred mobile applications just running on my variety of mobile devices. And the key thing about the applications is you never know, and one airline that shall not be named, but you never know when that application is going to hang right when you press the book it now button. Right? Like, did my credit card get charged? Did my flight get changed? Like, anyway, so it is meant as more and more people move towards using applications on mobile devices, we want to be right there with them. The providers of these applications need visibility into when the applications are crashing, which versions are crashing, when is the user not able to complete a transaction like I wasn't? And when did the network get in the way? When was it the applications fall? Like, this type of visibility is really critical. And particularly in a world like this where if all your users are on mobile devices and you're not answering the question or not finishing the transaction, they might move on to executing it somewhere else, right? Customer lost is revenue lost. Right. And it's the, talk about the real time component because it's one thing to get a report a month later that you had all these issues with customers not being able to complete their transaction. It's another thing to get that in real time and say, okay, how can we respond to that person or at least fix the application so when they try again in an hour it works. That's a fantastic question. Also, so with something like Splunkment Express, you instrument your mobile application with something like one line of code, very, very easy, not a lot of overhead at all. And so for the developers of mobile applications, once users are using these applications, they can just log into a cloud service which is the Splunkment Express service and immediately see where which applications are experiencing what errors, what crashes, by which version, by which device, which transactions are not getting executed, when is the network the problem, all of that good stuff. Now Mint Express is a cloud service and can be accessed very easily. We think there's more value to this mobile application data. And the extra value, the extra step that we're introducing here is we introduce Splunkment Enterprise as a beta version, basically, we introduce the beta Splunkment Enterprise where you can connect this mobile application data now to all the other data in Splunk. So it includes an integration with Splunk. What is the value of this? Well, your mobile application data is it does not exist in a silo by itself. Yes, you can get user analytics about what people are doing with your mobile application with Mint Express, but really what we want to enable with Splunkment Enterprise is the cross-tier correlation. So from an operations perspective, if you want to see my mobile application is not performing well because I didn't provision enough capacity or my web servers weren't responding or my backend system crashed, you want to see all that data in one place so that you can figure out which thing is causing problems or not living up to its SLA. The second really, it's almost like the cherry on top is the omnichannel analytics piece. You're getting user and user analytics from the mobile application so you can see what users are doing. But you can now correlate with Splunk Enterprise. Let's say you have data from your web servers also, let's say you have data from other channels in Splunk Enterprise, you can correlate all these pieces together. What do you get from this? You can see, oh, my user started to do this on the desktop and then they stopped and then they moved to the mobile application to complete this transaction. Like, why is that? And one of our customers actually started doing this. Customer called ADP, I think you interviewed them last year. They were the ones who were really pioneering this use case even without Mint Express or Mint Enterprise being there, is they were collecting information from all channels and looking across the board and seeing, well, how can I optimize this? This feature is popular on the desktop, that feature is popular on the mobile. How do I optimize? And it can be invaluable, especially when you're running promotions, running deals and so on. Well, we talk about the consumerization of IT all the time on theCUBE. And really what that means is people's expectation of the way applications are supposed to act. If I'm on Chrome, if I go from my home computer, I walk out the door, I open it up on my tablet, I expect it all basically to be the same, to have all the same access. I think of the old Sunray systems back in the day where you stuck your card in wherever you were in the world that it lit up the desktop right from where you were. So people expect that behavior. They want it all to be the same and don't really think through what the potential technical challenges are of trying to deliver the same experience on this little thing versus a big screen or a tablet, a hard list of networks and everything else. So talk about your guys' approach to that. And then the other piece of that is really this expanding population of data sets that you guys can now leverage and pull in. And that just continues to grow and add more flavor, more color, hopefully more relevance, accuracy, higher confidence levels in those correlations that you guys are able to find. Absolutely. And just along those lines about last month or so we announced this Splunk app for Stream, which collects wire data. And the wire data is the information that applications transmit over the network. And it can be an extremely important indicator of response times, business activity, how long is something taking to complete its action. All of those, how long are transactions taking as an example? All of those things can be extracted from your wire data. And with the additional Splunk app for Stream, we are now in a position to collect tons and tons of this wire data, not just from infrastructure that is under your control, but you may have virtual machines running in the cloud somewhere, you can drop the Stream modular input onto this virtual machines. And now you can collect data even without access to network tabs and span ports. You can do both. You can do the span port network tab thing, but you can also do it the agent way where you're dropping an agent onto virtual machines that are running in a cloud and simply collecting data about what's being transmitted over the wire. Yeah, and you even do mainframes too, right? So you get, you go from the Twitter Stream to the mainframe Stream and everything in between. That's right, that's right. So talk a little bit about, from a marketing perspective, one of the things that struck us as we've had conversations over the last few days is a potential challenge for Splunk is that because of your approach, it could be a marketing challenge or you're an application company or you're a platform company, and we're hearing the word platform much more. How do you approach that from a marketing perspective? Telling the story of Splunk in a way that both your customers understand, partners that understand, what's your approach to messaging around Splunk? I think the main message around Splunk is always start with the data. Data is our big differentiator, our ability to ingest data from any source in any format, be able to correlate things across different types of data, and we're not restricted to machine data. It's kind of fantastic that we can combine machine data with structured data for those very high level insights, and when you use data to tell the story, I think the answer becomes very, very simple. It's, if you have data about solving a problem, Splunk can solve it. We should have had you on the analyst's call. The analysts were confused, right? They're saying now you're going from kind of a single app or single solution company, now you're spreading your portfolio broadly. Obviously that adds execution difficulty, adds resource complexity. So how are you guys sorting all that out as you continue to grow your portfolio? I mean this is great, I always start with the data, so that's a nice kind of foundation. If you start with the data, then actually the story for the customer becomes very easy. You're indexing your data once, the same data is being used for your security use case, the same data is being used for your operations use case, the same data is supporting business decision making. At this point you're extracting as much value from the data as you possibly can with Splunk. So it makes Splunk adoption easy, it makes, you know, for us it makes business easy really when customers can see that much value coming out of their data with the help of Splunk. So that's another big one, right? As we talk about solutions and technology and blah, blah, blah. But really what's most important is what value is being unleashed with the customer, right? We had the guys on earlier talking about the trains and small increases in efficiency have huge impacts on their maintenance bills, their fuel bills, et cetera. So I know you get to talk to a lot of customers here at the show and otherwise. One of you can share some fun examples of just ridiculous amounts of value extracted with small deltas that they're able to execute with Splunk. Well, I don't know if you've had, if you've had Mackenzie from Oscar Insurance talk here. No, I don't think so. Well, Oscar Insurance is this very small startup. It's a very well-funded startup, but they're fundamentally, you know, changing the approach to insurance. I think they're going to be a really disruptive startup. They have a, they have a small Splunk license, I would say. But every single person at Oscar Insurance uses Splunk. I think they're the biggest user of DB Connect, one of our free apps. And they have just even the reports that get mailed to their customers about which doctors are in your area are powered by Splunk. So I would say they're using Splunk for operations. They're using Splunk for security. They're using Splunk for compliance. They're using Splunk for reporting. They're doing good with that. Yeah, that's your kind of customer, right? I think it speaks to the work you're doing to make it more accessible to non-technical users. The biggest illustration that to me today was, I forget the guess, but they were talking about their biggest user of Splunk and their company and the person's background was, you know, he was a non-technical person and he had a liberal arts degree. And I'm thinking now, if you can get somebody with, Jim from In-N-Out. Yeah, if you get somebody with like, I don't know, an English or literature degree from some liberal arts college can use Splunk. I think you've got the market pretty much covered. But, you know, in just my two cents, in terms of the marketing message, I love talking about, you're talking about data first. I wonder, it'll be interesting, Jeff, to watch Splunk's marketing and how it may evolve over the next several years, because clearly you have big ambitions beyond, you know, the IT shop, just security. You're looking for much wider use cases and, you know, the term machine data, I think, is a good one. But it could be limiting in that, as you illustrate, you're dealing with customer data as well and customer analytics. You're touching the customer. You're driving business outcomes. So I'll be interested to see if the marketing shifts a little bit over the next few years as your footprint expands and as you take on more and more use cases. So just my two cents. I'll be back next year, so. All right, we'll talk about it. All right, good. Well, I'll give you the one last exit before we cut out. You already gave me the bumper sticker. I'll always start with the data. But what are you most excited about? What are you waking up every morning just really rare to go? Well, there's so many, I mean, now this is the real difficult question because there are so many things to be excited about with Splunk. I would say all of our announcements, version 6.2, mobile intelligence, all of those have been really fun announcements and really fun projects to work on. Okay, good. Well, we'll look for some of the secret ones I know you have under the covers for next year. So, Lena, thanks for stopping by. Thank you, Jeff. Jeff Rick here with Jeff Kelly. We're on theCUBE. We're at thesplunk.conf 2014, their fifth annual user conference. Third time we've had theCUBE here. Go out to the events, extract the signal from the noise, look at the smartest people we can find like Lena, share her insight and knowledge with you. We'd love to do it. We'll be back with our next segment after this short break.