 from the MGM Grand Hotel in Las Vegas, extracting the signal from the noise. It's theCUBE, covering Splunk.com 2015, brought to you by Splunk. Now, here are your hosts, John Furrier and George Gilbert. And welcome back to another CUBE Live presentation, special event here in Las Vegas, the MGM Grand Source Pavilion, theCUBE is live for two days of wall to wall coverage of Splunk.com 2015. I'm John Furrier with Jeff Frick and George Gilbert from Wikibon. We've got the analysts, we've got everyone to think covered. Keynotes are done. Again, Splunk.com 2015. Go to crowdchat.net slash Splunk conference. We're going to join the conversation. Kicking off the day here, we've got a huge amount of coverage. We have cloud, we've got security, we've got public sector, we've got top customers. You are going to hear from Splunk executives, but more importantly, you're going to hear from their customers on why the company's doing so well. This company has continually growing. Two years ago, new competitors started coming out of the woodwork, but yet Splunk continues to grow. Huge recurring client base, new products being announced. Great product company here with Jeff Frick and George Gilbert. Guys, great to see you, Jeff. Good to see you again. And George, welcome to your first dot conference. We are here live and want to get your take. Jeff, just first with you. These are the Splunk last year and the year before. This is our fourth year at Splunk. Again, great to see the people growing, executives having the spring in their step, but the headcount's getting bigger. They've done some acquisitions. What's your take, compare and contrast last year this year? Yeah, it continues to grow. The chatter this morning around breakfast was people lamenting about how many people that there were there trying to meet up with their friends and talking about how much the conference has grown. You know, Splunk continues to move last year. It was a lot of talk about their integration with Hadoop and cloud. Again, really refocusing on security really seems to be the place that they continue to drive and integrating all these new acquisitions in. So it's a company on the move, John, and we talk about this conference as well as ServiceNow. I think it's two of our favorite conferences where we get a ton of great customers who are really passionate about what they can do with this technology. It's really an IT enabling technology as opposed to an IT competing technology. So you find really great support within the IT infrastructure. And this other concept I love, and I tweeted it out and only really responded, which is Splunking, Splunking becoming a verb, to Splunk data, to Splunk this, to Splunk that, really shows you that this is an interesting way to grab a data stream and bring intelligence to it. It was a great demo in the keynote where we all shook our phones to show how easy it was to set up a small test with no pre-done integration. They had it all set up. We all shook our phones. We saw the instant results on the screen and this constant focus of making data easier, data analytics easier to get it out to a broader distribution. Yeah, and the thing that we're going to be looking at heavily this week is the question of, what does machine learning mean to the big data space? Splunk, continuing to be Splunking data has a huge loyalty in their consumer, I mean their enterprise install base. And what that means is they have a recurring business model. Yet, when I spoke with Guido Schroeder yesterday, they're growing their product team. They're still a product company. From the announcements today, you see a slew of new products, but the key will be how fast can they add new customers because they have a really, really strong loyalty and retention of their customers. Low churn, which will drive the value of profits. George, machine learning has played a critical role in big data. Certainly Splunk is betting on machine learning. They bought two machine learning companies this past year. You're seeing that DNA in the big data aspects of Splunk, differentiating themselves. Now in the IT service management kind of space, automation, machine learning, these are the new normals. What's your take on the role of machine learning and what Splunk needs to do to grow their customer base? So just to back up, one of the first things where Splunk made its mark was they made it easy to analyze log data. If you go way back in Unix machines, people had to write scripts on the Unix command shelf to try and figure out sort of what went wrong. And now Splunk was sort of like Hadoop years before Hadoop was ready. It was an application. It wasn't a platform with 27 different parts. So it worked right out of the box and people could get value out of it. And the initial use case was to analyze log data across systems. And one of the most popular applications actually was security to try and find behavior that was not normal. And that's still something about 35 or 40% of the revenue goes towards Splunk being applied towards security use cases. What was interesting about the Caspita purchase and there was another company whose name I don't remember. We were just talking to the lucky entrepreneur who sold the company. It turns out that security attacks are getting so sophisticated that one human cannot look at the sort of console or consoles and figure out what's going on. So the machine learning analysis builds a model and then it can tell what's anomalous. What's not right? If you're watching here here from George Gilbert his Twitter handle is GGilbert41. Follow him on Twitter and get all the insights. George, I got to ask you about your research around systems of intelligence because the big news and the future of Splunk is big data but more specifically a new market they're going after is ITSI, IT service intelligence. You kind of see them telegraphing an area where IT automation has grown. We've seen service now and other companies really dominating in the IT service management piece which is service catalogs, brokering of services. What Splunk's doing is a little bit different. They're going deeper and automating. They're bringing a DevOps approach, a cloud approach to intelligence. That kind of hints of algorithms, machine learning, stream processing. What's your take of ITSI vis-a-vis your research around systems of intelligence? Well, I'm actually really looking forward to drilling down into this with our guests because today the applications that people or enterprises are building are vastly more complex than what they were not that long ago. In the client server era, you had sort of a web server. You had an app server that ran all the business logic for the application and you had a database and maybe you had multiple copies or instances of the app server. Now you have like hundreds, if not thousands of microservices spinning up, spinning down, disappearing. And the idea of analyzing that and keeping track of that is incredibly difficult and needs a completely new technology and we're seeing tons of startups in this space. Splunk has a head start in the sense that it has very strong relationships with customers and it has good technology for analyzing the logs. The IT service intelligence opportunity is for them to be able to look across all the machine data that's being spit out by all these different elements, the hardware, the infrastructure, all these application services. And so if you were to boil it down, it's like if something goes wrong here and you get all sorts of error conditions downstream, you need to know that all that is irrelevant and the original thing is the one thing you have to fix. And what we need to find out this week is Splunk doing that. Or how soon? We talked about last year, the notion of security, kind of the perfect storm. Jeff, I want to get your take on this. Last year, all the keynotes had a security flair to it. This is still what's happening today. What's your take on that? Because intelligence obviously is important for identifying rogue packets, rogue data. I mean, ultimately, security is a big data problem. What's your take? Yeah, I mean, I tweeted earlier tonight for people to go back and look at the Splunk keynote from last year. It was very, very powerful talking about, we will all have our time and the sophistication and the frequency of these attacks is huge. And George, I like your comment that there's just no way that a person can analyze the vast amounts of data. I think what's interesting about Splunk, and you talk about it too, John, is this perimeterless security, right? The walled castles no longer the strategy. There's just too many bits and pieces flying about from too many devices and too many integrated devices at Internet of Things. You've got a whole another layer of complexity. So to be able to put a monitor, and it really, I'd like to get your take, George, seems like Splunk's ahead of the game. Because they did it with logs and servers, they're kind of used to working with live active data that's flowing in a massive stream and going and finding those anomalies. Lo and behold, here comes the Internet of Things. The other interesting twist is people are things too. So this whole user behavioral analysis to look for anomalies within the machine data reminds us that it's people too, and how do you find the anomalies between the way people typically act and the way that you're now sensing that the machines are acting to find those outlier use cases so you can quickly react. And we've had people on many times in theCUBE saying how many days and months it takes for people to generally find out they've already been attacked. So much time has gone by. That has to shrink. How could they shrink that down and react to it? You know, when you say that, it does resonate with the whole systems of intelligence theme, which is we have to shrink the time between where we analyze something and we can take action on it. And this issue of going long after the fact to find out something went wrong, that means you've been exposed that whole time. So we are here live at the Splunk conference. We're going to hear a great programming set, day one, two days of programming, but day one can be about kicking off, talking to their top customers. We're going to jump into IT operations and the systems of intelligence concepts, ITSI, service intelligence. This is their big announcement in my opinion. Watch this trend, it's going to be disruptive but also it's going to disrupt the status quo as Carly Friarina would say in the Republican debate. This is going to be a disruptor. And the question is how much of a disruption we're going to analyze that. And of course the partner ecosystem is a huge thing for them. Day two, global reach, cloud plus security is going to be a big focus. Join us on day two for all the cloud and security. So Wednesday, mark on your calendar, afternoon is going to be security, the morning's going to be cloud. It's going to be great. George, your take on that real quick in our last minute, what's your take on the ability to get new customers? What's the economics like for Splunk in the marketplace? Well, enterprise software has always been much, much easier to acquire, or I should say, grow a greater footprint with existing customers because you have a relationship with them, there's trust, you know the opportunities in the account. So Splunk has now a broadening footprint, so that means more opportunities to land and expand. But let's explore that further. The product line is growing very rapidly. Yeah. And where do you think, John, where's the land and expand? So they've got their core business monitoring logs, they've brought in cloud, they've brought in hunk with Hadoop, we've brought in this behavior analysis of people. Where do you think they go next? I think Splunk is still a product company. I think what they have done is, they've done things extremely well by building a foundation, as George said, from log data, expanding into cloud. And what they've done is they've got a great recurring set of revenue, they're going to build on that and launch new products. The new products are going to be easy to get into with cloud and continue to grow with differentiation. Machine learning and all the stuff going on in big data from stream processing to other stuff will be a key element of Splunk's growth and more importantly, global reach. The security equation will be instrumental for Splunk growth to maintain their customer base. So I see Splunk continue to do well on the product side and really using the security headwinds, I mean tailwinds that they have to grow that market and then get into the clouds. I think Splunk's really in a good spot to add new customers and we're going to talk with those customers to find out what's going on. So guys, let's get this going. Two days of coverage, this is theCUBE live at dot conference 2015, hashtag Splunk conference. Go on Twitter, join the conversation or join us on crowdchat.net slash Splunk.com. C-O-N-F. This is theCUBE, we'll be right back after this short break.