. >>Okay, welcome back. This is live in Las Vegas. This is the end of day one. This is our wrap up segment of the cube at Splunk conference dot conference 2013. I'm John furrier with Dave Alante, my cohost and Jeff Kelly making an appearance in this segment has been scouring for stories, talking to all the folks, talking to the CEO, talking to all the people on the team, customers scouring the web. Guys, welcome to the wrap up. Thank you John. John guys, I gotta I gotta say I'm really impressed with what Splunk's done here. Um, and with post IPO you kind of see what people are made of when they have to do transitional things day. We know we do and I've seen companies pivot, turn on a dime. You guys certainly have helped companies, you know, get into that, into the, into the thermal growth and um, but here a companies succeeding, um, they hit a rocket ship growth. >>They go public. A lot of challenges could be distraction, but certainly, uh, my impression is no distraction here. Splunk certainly is hitting cruising altitude only getting better and stronger. Certainly the customer acquisition numbers as strong and their partner ecosystem is great. Their keynote and fan based or customers are loyal. All in all, Dave, I've got to say, you know Splunk's looking really good. Yeah, John. I mean I think you see a lot of different models. This is too broad models. I guess in the, in the it business one is the safe bet. It's, it's IBM, it's, it's HP, it's, it's EMC, it's Oracle, it's Cisco. I mean you're going to do business with those companies because you know they're going to deliver a product and they're going to stand behind it and they're going to service you and then you got the 10 X value proposition companies, that's companies like Tableau service now Workday, Splunk, these are the companies that are really transforming their irreverence. >>Steve Cohen said disruptive, they're disruptive so they got a little mojo going and I'm gone. But at the same time, customers are willing to take a chance because the value proposition is so compelling and so transformative to their business and they can't get that from their traditional it suppliers despite what the traditional it suppliers are telling them. So I love that kind of mojo at a, at a, at an event like this. Jeff Kelly, I want to go to you for a second. Let's talk about what you're finding us. Show us who you are on the, on the, uh, we had a crowd chat today w you know, preparing them for Hadoop world and big data in New York city. A quick programming note. Um, we, the Q will be in New York city for strata conference. Had duper world covering that in con in concert to the big data New York city event going on as well that week. >>Um, but you're out, you did a chat this morning about big data with Hadoop ecosystem. A lot of had doopy we had cloud era MRR Dhalla on, they have a relationship also with Hortonworks. Um, what did you find out there? What stories did you dig in? What observations did you find? Well, very much like a, the last show we were at a Tableau's customer conference. It's a really excited, uh, customer base here. These, these customers, uh, you know, are, are clapping and cheering during the keynote. It's something you don't necessarily see more than excited. They're giddy, right? I mean, right. They're there, they're getting yapping, they're hooting or hollering, right. And, and there's really a sense of community around the, around the customer base. They love to trade stories. They love to trade best practices. The hackathon, last night I was at, uh, you know, just rooms filled off the, off the corridors here at the, uh, the cosmopolitan. >>They were there till 11 o'clock at night. They were in there, you know, they had, uh, some, some, some, some TV going at, I saw a rerun of Alf playing on the big screen for some reason. I guess that's a popular with the group here. But anyways, these guys were up there all night. You know, they're coding the drinking beers, they're having a good time. Uh, they really enjoy this. You didn't, it's not something you see at eight. At one of the, a larger events, some of the mega vendors we see. Um, you know, the other thing, you know, Mike coming into this Splunk I think was really early on, uh, recognizing the, the value that providing applications that allow you to really manipulate and understand data. Really they saw the value of that very early. Obviously that's, they base their whole premise of their organization on that. >>Oh, they have re, you know, kind of written this wave, uh, of big data, all things big data. And they're one of the few companies out there that are actually selling and providing applications that allow people and make sense of, um, in this case, machine generated data, but they're expanding to other data types. Um, the key for them I think going forward is to continue innovating. You know, they've kinda got that lead, uh, I think because they were the, one of the first out of the gate to recognize the value in this. They gotta keep innovating. And I think you saw with the announcements today, clearly they are, uh, the cloud, uh, option that they unveiled today was very popular. Um, and it's going to help them, especially against some of the more nimble startups. It's funny, it's, Splunk is now kind of a kind of a big established company in a sense in this large, in this big data world, there are companies like om Bogley and Sumo logic who are coming at Splunk doing similar things, but doing it from a cloud perspective, well sponsored down. >>Got an answer for that. Why would I want to ask you guys about that? Because you know, John, Jeremy Burton, we, you know, made, we were there when cloud met big data and so people have been putting those two together. But you take a company like Splunk and a couple of like Tableau, not big cloud plays. What about that cloud meets big data? Is that, is that a misconception on the industry's part or not? Or is it a fundamental requirement that cloud meets big data? I think it's a fundamental requirement as you know, we were, you know, close to EMC when they put that together and we had the first cloud mobile social editorial. You guys had the first real research around those three pillars. Um, and big data just became a, came out of social and cloud and since the cloud era, you know, pun intended with Cloudera, the company, um, but you know, Dave, we saw this from day one. >>This is a fundamental economic wealth creating inflection point, meaning new companies, new brands going to emerge that are going to change the game and this is where all the chips are on the table and you're seeing the incumbent vendors like EMC changed their game and go cloud meets big data and go in there. And EMC, I give Ian, Jeremy Burton a lot of credit. He saw the work we were doing. He saw the marketplace, he came fresh into EMC and said cloud and big data. Those are the two pillars. He bet the ranch on that and the beds coming home. Jeremy is making more money than any, even not a CMO anymore. He's the executive vice president doing great just on the stock options. He made a good bet that's playing out who's also a great executive with some product shops. Absolutely. Table stakes in my opinion. >>Um, that the application market is going to be enabled by that. So, Jeff, Kelly, so I've got to ask you, there are forces that you mentioned you've got open source. Uh, you've got some new players that are or have seen the opportunity that Splunk has created, the, they're going to have to Splunk. So, so what's your prediction here? I mean, you've got, you've got a public company now, they've got more resources. They're clearly a leader in the, in the business, but you got other companies coming after him. Not only start us, you know, we were at, um, we were at HP, uh, the, the Vertica user group, they were talking about, you know, their Splunk killer. Uh, you hear it all the time. Oh, we can do that. We can do that. What does that all mean for Splunk? Well, the good news for Splunk is they're, they're, they're ahead of everybody in this game because they've been doing this for longer. >>Uh, you know, they, they, they have a, a more generally accepted among the customers, uh, you know, a better application for VMware, for instance. So they're actually ahead of a lot of these other vendors, VMware itself trying to claim Oh yeah, it'd be where it says, well now we've got a tool for monitoring that's just as good as Splunk. Well, you know, if you talk to some of the people using the Splunk app for VM ware, they'll disagree with that. So bottom line is, you know, this is a little bit simplified, but people really like the Splunk user interface in the application. It's very easy to use and that's something that you can't necessarily replicate. So, you know, it'll take, it'll take some time for some of these players to catch up. But you know, back to the point John was making this whole idea of cloud and big data and you're asking, you know, is that really, is that really the, the, the two mega trends here? >>And I think absolutely when we start talking about, uh, industrial internet, internet of things, whatever term you wanna use, we're, we're years away from that really being a, a reality I think in terms of it's an interconnected world, but clearly the two key enabling technologies are going to be big data, making sense of all those connected devices and cloud being able to connect them in a way that that makes sense. Um, where you can't do that in an on premise situation if you've got isolated data centers. Now the other thing, this company who started in 2005, it's yet another Silicon Valley success story. John, I mean it's just Silicon Valley is just running the table. What's your take on the Valley action going on here? I think Silicon Valley is going to continue to do well and, and um, and rule the road here and on IPOs and success. >>Silicon Valley is the ecosystem that drives a lot of wellness to wall street of startups. However, there are, there are a lot of successes outside of Silicon Valley. This is just another string of, of successes. Um, but Dave, this is an absolute poster child in my opinion, of a venture that could have gone the wrong way. I mean, Splunk was not a shining star when it got funded. It took two visionary venture capitalists, Nick and David Hornick, Nick from, uh, he'd know the ignition and uh, David Hornik from August capital made the bet. They bet on technical founders, they bet on the right product guys. It was in small tools and it was at the time it was, wasn't the trendy thing. This is pre big data. This is log files. They saw a problem, they saw a good team. Now this thing could've gone off the rails, right? >>If you look at today's market, this is what I worry about all this startup environment is that all the different funding dynamics, all of this crowd sourcing this, that you've got to have good investors. This is a great example of great investors back in their guys back on their team because this thing could have been off the rails in the fourth year. Okay. Product strategy, debate, board room dynamics, people not paying attention, uh, asleep at the switch as we say. And this is, this is an example of a company done right. They hit the growth curve, big data swooped in, they had a great product, happy customers and incrementally move the ball down the field. And finally, you know, scored the big long ball with the touchdown with big data. And I think, you know, it's classic. These are football analogies, you know, first down, first down, first down, and then big data comes down. >>They throw the ball in the end zone, touchdown home run. There it is. That's the IPO. That's the success story. There's a fine line between. Good and great here. Isn't there though? I mean, like you say, I mean who even Steven Cohen was saying, uh, uh, uh, not, not Steve Sorkin, sorry. Steven. I was saying that he didn't, could've never predicted, you know, where they'd be today, the IPO, et cetera. So there is a fine line. You could go, well, this is the thing, this is my point. If you look at Splunk, right? Dave, they could have, no one was buying their stuff initially. Right, and so except for some tech geeks, no one was kind of get it, but the recession hit and people weren't spending in 2008 that was a big surge and you saw the spending and Splunk became a great solution because for very little cash you can come in and create business value. >>That was a really, really important moment in the company's history, David, and what's also happened is they believed in their own product. You heard from the people here culture, they're Everett, they're disruptive, they use their own product and they focused on the customer. Those two things, good timing still is, you know, comes to people who are prepared. I mean it's not an, I mean, it's not enough to just have a big market. It's not enough to just have a lot of capital behind you. You need other ingredients obviously to succeed. I'm afraid the younger generation doesn't understand the startup world is you can't just magically put pixie desk and get the home run. You got some times really be in a good position as they say in basketball and be ready for the rebound off the rim. In this case it log file tool with good technology moves into the big data world and hello, they're got an enterprise customers. >>Part of, I think part of it is, look, you've got to admit, part of it is luck and timing. You've got to have that on your side. But they've also got a really good product and they're smart enough when that, when those opportunities present themselves to take them. I think they are. Again, timing is fantastic for them right now. We've been talking about the, uh, the year of the big data application and we're really still waiting for that. They are in a really good position right now to really take advantage of all the interest in, you know, SQL on Hadoop, interactive analytics on Hootsuite. Well guess what, they've got a product and hunk a cute name, but a good product that allows you to get right in there as a business user and start analyzing, searching data using a circular base. I gotta tell you it's a very good looking product and people are looking for this. >>People are like, well, how am I going to get all that value product? I'm going to get all that value out of Hadoop sense bugs in answer hunk. You got the naming convention, interesting names, but nevertheless they've got a, they've got a play right now in an area that's got a lot of interest and they've got, they've got the track record in the log data to actually show they've got, they know how to, they know what they're doing. I don't remember Mike Olson to cloud Hadoop worlds ago, announced the the application tsunami. That kind of never came the way they said. We said the analytics was a killer app. In the meantime, as the market kind of catches up, we still haven't seen that application framework, but yet still analytics is the killer app, right? It's definitely the killer app. I think. Well, the analytics for the masses is the, is the killer app and that's the Holy grail that everybody's going after. >>And I'm not, I'm not declaring Splunk is there. I don't think Splunk is there. I don't think anybody's there yet. You talk to a Tableau customers, you talk to Splunk customers, they're not there yet, but they're closer than the BI crowd ever was. They're certainly closer than the traditional BI players. And they, and then that's because they don't have that legacy architecture to deal with. But there's also a cultural issue. It's not just the technology of the products, it's getting business users to understand how to look at data and look at it as, as an asset and something that you can actually drive. Timing's right for that. Absolutely. So I want to wrap up and ask you guys some follow up questions at the close, the segment out, first impressions of day one and what are you looking for for day two? Jeff, we'll start with you. >>I am first impressions. You know, like I said, very excited, uh, base of customers here and you know, 18,000, 1800, excuse me. Plus customers, 18,000. That'll be a few years. But, uh, nevertheless a good showing here. Uh, I think tomorrow, you know, on the cube, we're going to look for certainly some more customer stories. Um, you know, it's always interesting to hear from customers because they are on the front lines. They're using the product every day. So I expect to see a lot more of that. Um, and really tomorrow I think is going to be a lot about, a lot about uh, these customers networking with one another and I'm hoping to get out there. Let's add on the question to, uh, to you then, then to Dave. Same thing. What's the challenges for Splunk as well? I think the challenge for me is from, from my perspective is to continue and make the, make the cloud play real, continuing to invest in that, uh, and that product and that approach. >>Um, as we met, as I mentioned a minute ago, I think cloud and big data are critical to really leveraging industrial internet, the internet of things. And if Splunk wants to be a key player there, they've got to really fill out that portfolio of cloud based capabilities. I know you said David, go first. Sorry for me. For me, John, we heard from the executives today, very strong story. We heard very solid product lineup. It's very clear in talking to customers that there's, there's passion here, there's real traction. Um, it's substantive. To me. The big thing is ecosystem. I feel as though the ecosystem here at Splunk is, is, is good, but I feel like it's not been as deliberate as it can be. I think Splunk has a ways to go there. I think that is one of the leverage points that this company really has to focus on. >>Because like today we talked about earlier, 45% of Splunk sales goes through the channel. I think it's gotta be way, way, way higher than that. Now they're making great progress, but I think that they've got to have a goal of getting to 70% and that comes through the ecosystem. It's gonna take some time. It's going to take some investment. That's really where, to me, the big upside is for this company and my impression is I'm very impressed with Splunk. I'm very impressed with the ecosystem. I'm impressed by the rabid fan base of their customers who are proud of the private name getting exemplifies my point about startups having a great product focus products will win. Again, you know, the four P's of marketing, they teach you in marketing one Oh one one of those products. Um, but the challenge is, Dave, I would, I would agree with you. >>The ecosystem is a challenge. Good news is they have a great turnout here. Um, you're not, there's no lightweights out there, all heavyweights in terms of what they're doing with tech and their value proposition. So, you know, gray star for the ecosystem. So I think it's looking good off the tee to use the golf analogy, um, landing in the fairway. So, so that's one. My big, my big thing on the challenges for Splunk and that I'm watching is the cloud. I think moving to the cloud is not as easy as it appears, although that's the value proposition. So to move the DNA of the company with the pressure to drive revenue, luckily the market's kind of moving to them right now. So it might be a, a rising tide floats all boats. Moving to the cloud is very, very difficult. And I think that's gonna be a key challenge. >>We're going to keep watching them look at what SAP has challenged the cloud. They've had multiple restarts and misfires. Now they've seen them get their groove back with HANA. I think this could be a big challenge for Splunk and we're going to, I'm going to watch their cloud and that's going to be my focus then tomorrow. I would agree with that. I would just say on the ecosystem point, um, I, I think they would actually, I think they do have more work to do Dave, but I think they're in a really good position because some of the Hudu players, for instance, knees, Splunk, I think more than Splunk means to them right now. Okay. We're going to close down what the government is closing down right now. So, you know, that's, uh, that's, uh, we'll be back tomorrow because we work for free open source content, um, programming node. >>Next weekday we're gonna talk about big data and internet of things. I'll be interviewing the CEO of GE. Um, I'm really proud of you, John, for, uh, being selected out of the zillion people that they could choose. They chose you to, to host this panel. Yeah, that's fantastic. It might be my last, but we'll see. Moving some Q mojo to the GE event, industrial internet next week in Chicago. Minds and machines, another player to watch. Guys. Great day and great wrap up here. And that's day one. Wrap in the books tomorrow here when we go to the party tonight, find out what's going on here at, at, uh, inside the cube, inside a Splunk conference. Dot conference. 2013. I'm John furrier with Dave Alante and Jeff Kelly Wiki bond with back tomorrow. Goodnight. And, and join us tomorrow.

(Upbeat music) >> Hi everyone and welcome back to the Cube's coverage of Splunk.conf 2021, virtual. We are here, live in the Splunk studios here in Silicon valley. I'm John Furrier, host of the Cube. Spiros Xanthos VP of product management of observability with Splunk is here inside the cube, Spiros, thanks for coming on. Great to see you. [Spiros Xanthos]- John, thanks for having me glad to be here. >> We love observability. Of course we love Kubernetes, but that was before observability became popular. We've been covering cube-con since it was invented even before, during the OpenStack days, a lot of open source momentum with you guys with observability and also in the customer base. So I want to thank you for coming on. Give us the update. What is the observability story its clearly in the headlines of all the stories SiliconANGLE's headline is multi-cloud observability security Splunk doubling down on all three. >> Correct. >> Big part of the story is observability. >> Correct. And you mentioned CubeCon. I was there last week as well. It seems that those observability and security are the two most common buzzwords you hear these days different from how it was when we started it. But yeah, Splank actually has made the huge investment in observability, starting with the acquisition of Victor ops three years ago, and then with Omnition and Signalfx. And last year with Plumbr synthetics company called Rigor and Flowmill and a network monitoring company. And plus a lot of organic investment we've made over the last two years to essentially build an end-to-end observability platform that brings together metrics, traces, and logs, or otherwise infrastructure monitoring, log analytics, application monitoring. Visual experience monitoring all in one platform to monitor let's say traditional legacy and modern cloud native apps. >> For the folks that know SiliconANGLE, the Cube know we've been really following this from the beginning for signal effects, remember when they started they never changed their course. they've had the right They have the right history and from spot by spot, you guys, same way open source and cloud was poo-pooed upon, people went like, oh, it's not secure, they never were. Now it's the center of all the action. [Spiros Xanthos]- Yes >> And so that's really cool. And thanks for doing that. The other thing I want to get your point on is what does end-to-end observability mean? Because there's a lot of observability companies out there right now saying, Hey, we're the solution We're the utility, we're the tool, but I haven't seen a platform. So what's your answer to that? >> Yes. So observability, in my opinion, in the context of what you're describing means two things. One is that when, when we say internal durability, it means that instead of having, let's say multiple monitoring tools that are silent, let's say one for monitoring network, one for monitoring infrastructure, a separate one for monitoring APM that do not work with each other. We bring all of these telemetry in one place we connect it and exactly because actually applications and infrastructure themselves are becoming one. You have a way to monitor all of it from one place. So that's observability. But the other thing that observability also is because these environments tend to be a lot more complex. It's not just about connecting them, right? It's also about having enough data and enough analytics to be able to make sense out of those environments and solve problems faster than you could do in the past with traditional monitoring. >> That's a great definition. I've got to then ask you one of the things coming up that came out of CoopCon was clear, is that the personnel to hire, to run this stuff, it's not everyone can get the skills gap problem. At the same time, automation is at an all time high people are automating and doing AI ops, get outs. What do you want to call this a buzz word for that basically automating the data observability into the CICB pipeline, huge trend right now. And the speed of developers is fast now. They're coding fast. They don't want to wait. >> I agree. So, and that's exactly what's happening, right? We want essentially from traditional IT where developers would develop something a little bit deployed months later by some IT professional, of course, all of this coming together, But we're not stopping that as you say, right, that the shifting left is going earlier into the pipeline. Everyone expect, essentially let's say monitoring to happen at the speed of deployment. And I guess observability again, is this not, as a requirement. Observability is this idea. Let's say that I should be able to monitor my applications in real time and, you know, get information as soon as something happens. >> With the evolution of the shift left trend. I would say for the people don't know what shift left is you put security the beginning, not bolted on at the end and developers can do it with automation, all that good stuff that they have. But how, how real is that right now in terms of it happening? Can you, can you share some vision and ideas and anecdotal data on how, how fast shift left is, or is there still bottlenecks and security groups and IT groups? >> So there are bottlenecks for sure. In my opinion, we are aware with, let's say the shift left or the dev sec ops trend, whether IT and devs maybe a few years ago. And this is both a cultural evolution that has to happen. So security teams and developers have to come closer together, understand like, say the consensus of the requirements of each other so they can work better together the way it happened with DevOps and all sorts of tooling problem, right? Like still observability or monitoring solutions are not working very well with security yet. We at Splunk of course, make this a priority. And we have the platform to integrate all the data in one place. But I don't think is generally something that we'll have achieved as well as an industry yet. And including the cultural aspects of it. >> Is that why you think end to end is important to hit that piece there so that people feel like it's all working together >> I think end to end is important for two reasons. actually one is that essentially, as you say, you hit all the pieces from the point of deployment, let's say all the way to production, but it's also because I think applications and infrastructure, FMLA infrastructure with Kubernetes, microservices are in traditional so much more complexity that you need to step function improvement in the tooling as well. Right? So that you need keep up with the complexity. So bringing everything together and applying analytics on top is the way essentially to have this step function improvement in how your monitoring solution works so that it can keep up with the complexity of the underlying infrastructure and application. >> That is a huge, huge points Spiros. I got to double down on that with you and say, let's expand that because that's the number one problem, taming the complexity without slowing down. Right? So what is the best practice for that? What do people do? Cause, I mean, I know it's evolving, it's going faster than that, but it's still getting better, but not always there, but what can people do to go faster? >> So, and I will add that it's even more complex than just what the cloud, let's say, native applications introduced because especially large enterprises have to maintain their routine, that on-prem footprint legacy applications that are still in production and then still expand. So it's additive to what they have today, right? If somebody was to start from a clean slate, let's say started with Kubernetes today, maybe yes, we have the cloud native tooling to monitor that, but that's not the reality of most, most enterprises out there. Right? So I think our goal at Splunk at least is to be able to essentially work with our customers through their digital, digital transformation and cloud journey. So to be able to support all their existing applications, but also help them bring those to the cloud and develop new applications in a cloud native fashion, let's say, and we have the tooling, I think, to support all of that, right between let's say our original data platform and our metrics and traces platform that we develop further. >> That's awesome. And then one quick question on the customer side, if I'm a customer, I want observability, I want this, I want everything you just said. How do I tell the difference between a pretender and a player, the good solution and a bad solution? What are the signals that this is the real deal, that's a fake product >> Agreed. So, I mean, everyone obviously believes that original (laughing) I'm not sure if I will. >> You don't want to name names? Here's my, my perspective on what truly is a requirement for absorb-ability right? First of all, I think we have moved past the time where let's say proprietary instrumentation and data collection was a differentiator. In fact, it actually is a problem today, if you are deploying that because it creates silos, right? If I have a proprietary instrumentation approach for my application, that data cannot be connected to my infrastructure or my logs, let's say, right. So that's why we believe open telemetry is the future. And we start there in terms of data collection. Once we standardize, let's say data collection, then the problem moves to analytics. And that's, I think where the future is, right? So observability is not just about collecting a bunch of data and that bring it back to the user. It's about making sense out of this data, right? So the name of the game is analytics and machine learning on top of the data. And of course the more data you can collect, the better it is from that perspective. And of course, then when we're talking about enterprises, scale controls, compliance all of these matter. And I think real time matters a lot as well, right? We cannot be alerting people after minutes of a problem that has happened, but within a few seconds, if we wanted to really be pro-active. >> I think one thing I like to throw out there, maybe get your reaction to it, I think maybe one other thing might be enabling the customer to code on top of it, because I think trying to own the vertical stack as well as is also risky as a vendor to sell to a company, having the ability to add programming ability on top of it. >> I completely agree actually, You do? In general giving more control to the users and how, what do they do with their data, let's say, right? And even allowing them to use open source, whatever is appropriate for them, right? In combination, maybe with a vendor solution when they don't want to invest themselves. >> Build their own apps, build your own experience. That's the way the world works. That's software. >> I agree. And again, Splunk from the beginning was about that, right? Like we'll have thousands of apps built ontop of our platform >> Awesome. Well, I want to talk about open source and the work you're doing with open telemetry. I think that's super important. Again, go back even five, 10 years ago. Oh my God. The cloud's not secure. Oh my God, open source has got security holes. It turns out it's actually the opposite now. So, you know finally through the people woke up. No, but it's gotten better. So take us through the open telemetry and what you guys are doing with that. >> Yes. So first of all, my belief, my personal belief is that if there is no future where infrastructure is anything about open source, right? Because people do not trust actually close our solutions in terms of security. They prefer open source at this point. So I think that's the future. And in that sense, a few years ago, I guess our belief was that all data collection instrumentations with standards based first of all, so that the users have control and second should be open source. That's why we, at Omnition the company I co-founded that was acquired by Splunk. We we're one of the main tenders of open sensors and that we brought together open sensors and OpenTracing in creating open telemetry. And now , Open telemetry is pretty much the de facto. Every vendor supports it, its the second most active project in CNCF. And I think it's the future, right? Both because it frees up the data and breaks up the silos, but also because, has support from all the vendors. It's impossible for any single vendor to keep up with all this complexity and compete with the entire industry when we all come together. So I think it's a great success it's I guess, kudos to everybody, kudos to CNCF as well, that was able to actually create and some others. >> And props to CNCF. Yeah. CNC has done an amazing job and been going to all those events all the years and all the innovations has been phenomenal. I got to ask what the silos, since you brought it up, come multiple times. And again, I think this is important just to kind of put an exclamation point on, machine learning is based upon data. Okay. If you have silos, you have the high risk of having bad machine learning. >> Yes. >> Okay. That's you agree with that? >> Completely. >> So customers, they kind of understand this, right. If you have silos that equals bad future >> Correct >> because machine learning is baked into everything now. >> And I will add to that. So silos is the one problem, and then not being able to have all the data is another problem, right? When it comes to being able to make sense out of it. So we're big believers in what we call full fidelity. So being able to connect every byte of data and do it in a way that makes sense, obviously economically for the customer, but also have, let's say high signal to noise ratio, right? By structuring the data at the source. Overt telemetry is another contributor to that. And by collecting all the data and by having an ability, let's say to connect the data together, metrics, traces, logs, events, incidents, then we can actually build a little more effective tooling on top to provide answers back to the user with high confidence. So then users can start trusting the answers as opposed to they themselves, always having to figure out what the problem is. And I think that's the future. And we're just starting. >> Spiros I want to ask you now, my final question is about culture And you know, when you have scale with the cloud and data, goodness, where you have people actually know the value of data and they incorporate into their application, you have advantages. You have competitive advantages in some cases, but developers were just coding love dev ops because it's infrastructure as code. They don't have to get into the weeds and do the under the hood, datas have that same phenomenon right now where people want access to data. But there's certain departments like security departments and IT groups holding back and slowing down the developers who are waiting days and weeks when they want it in minutes and seconds for have these kinds of things. So the trend is, well there's, first of all, there's the culture of people aren't getting along and they're hating each other or they're not liking each other. >> Yes >> There's a little conflict, always kind of been there, but now more than ever, because why wait? >> I agree. >> How can companies shorten that cycle? Make it more cohesive, still decouple the groups because you've got, you got compliance. How do you maximize the best of a good security group, a good IT group and enables as fast as possible developers. >> I agree with you, by the way, this is primarily cultural. And then of course there is a tooling gap as well. Right. But I think we have to understand, let's say as a security group, instead of developers, what are the needs of each other, right. Why we're doing the things we're doing because everybody has the right intentions to some extent, right? But the truth is there is pain. We are me and myself. Like as we develop our own solutions in a cloud native fashion, we see that right. We want to move as fast as possible, but at the same time, want to be compliant and secure, right. And we cannot compromise actually on security or compliance. I mean, that's really the wrong solution here. So I think we need to come together, understand what each other is trying to do and provide. And actually we need to build better tooling that doesn't get into the way. Today, oftentimes it's painful to have, let's say a compliance solution or a secure solution because it slows down development. I think we need to actually, again, maybe a step function improvement in the type of tooling we'll have in this space. So it doesn't get into the way Right? It does the work it provides. Let's say the security, the security team requires, it provides the guarantees there, but doesn't get in the way of developers. And today it doesn't happen like this most of the time. So we have some ways to go. >> And Garth has mentioning how you guys got some machine learning around different products is one policy kind of give some, you know, open, you know, guardrails for the developers to bounce around and do things until they, until they have to put a new policy in place. Is that an answer automated with automation? >> Big time. Automation is a big part of the answer, right? I think we need to have tooling that first of all works quickly and provides the answers we need. And we'll have to have a way to verify that the answer are in place without slowing down developers.Splunk is, I mean, out of a utility of DevSecOps in particular is around that, right? That we need to do it in a way that doesn't get in the way of, of let's say the developer and the velocity at which they're trying to move, but also at the same time, collect all the data and make sure, you know, we know what's going on in the environment. >> Is AI ops and dev sec ops and GET ops all the same thing in your mind, or is it all just labels >> It's not necessarily the same thing because I think AI ops, in my opinion applies, let's say to even more traditional environments, what are you going to automate? Let's say IT workflows in like legacy applications and infrastructure. Getops in my mind is maybe the equivalent when you're talking about like cloud native solutions, but as a concept, potentially they are very close I guess. >> Well, great stuff. Great insight. Thanks for coming on the Cube. Final point is what's your take this year of the live we're in person, but it's virtual, we're streaming out. It's kind of a hybrid media environment. Splunk's now in the media business with the studios, everything great announcements. What's your takeaway from the keynote this week? What's your, you got to share to the audience, this week's summary. >> First of all, I really hope next year, we're all going to be in one place, but still given the limitations we had I think it was a great production and thanks to everybody who was involved. So my key takeaway is that we truly actually have moved to the data age and data is at the heart of everything we do. Right? And I think Splunk has always been that as a company, but I think we ourselves really embraced that and everything we do is everything. Most of the problems we solve are data problems, whether it's security, observability, DevSecOps, et cetera. So. >> Yeah, and I would say, I would add to that by saying that my observations during the pandemic now we're coming, hopefully to the end of it, you guys have been continuing to ship code and with real, not vaporware real product, the demos were real. And then the success on the open source. Congratulations. >> Thank you. >> All right. Thanks for coming on and we appreciate it >> Thanks alot _Cube coverage here at dot com Splunk annual conference. Virtual is the Cube. We're here live at the studios here at Splunk studios for their event. I'm John Farrow with the Cube. Thanks for watching. (joyful tune)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering Splunk.conf19, brought to you by Splunk. >> Okay, welcome back everyone. We are here inside for Splunk.conf, their 10th-year conference. We've been here seven years. I'm John Furrier, the host. Our next guest is Sherrie Caltagirone, founder and executive director of the Global Emancipation Network, a cutting-edge company and organization connecting different groups together to fight that battle combating human trafficking with the power of data analytics. We're in a digital world. Sherrie, thanks for coming in. >> Thank you so much for having me. >> So love your mission. This is really close to my heart in terms of what you're doing because with digital technologies, there's a unification theme here at Splunk, unifying data sets, you hear on the keynotes. You guys got a shout-out on the keynote, congratulations. >> Sherrie: We did, thank you. >> So unifying data can help fight cybersecurity, fight the bad guys, but also there's other areas where unification comes in. This is what you're doing. Take a minute to explain the Global Emancipation Network. >> Yeah, thank you. So what we do is we are a data analytics and intelligence nonprofit, dedicated to countering all forms of human trafficking, whether it's labor trafficking, sex trafficking, or any of the sub types, men, women, and children all over the world. So when you think about that, what that really means is that we interact with thousands of stakeholders across law enforcement, governments, nonprofits, academia, and then private sector as well. And all of those essentially act as data silos for human trafficking data. And when you think about that as trafficking as a data problem or you tackle it as a data problem, what that really means is that you have to have a technology and data-led solution in order to solve the problem. So that's really our mission here is to bring together all of those stakeholders, give them easy access to tools that can help improve their counter posture. >> And where are you guys based and how big is the organization? What's the status? Give a quick plug for where you guys are at and what the current focus is. >> Yeah, perfect, so I am based in San Luis Obispo, California. We have just started a brand new trafficking investigations hub out at Cal Poly there. They're a fantastic organization whose motto is learn by doing, and so we are taking the trafficking problem and the tangential other issues, so like we mentioned, cyber crime, wildlife trafficking, drugs trafficking, all of this sort of has a criminal convergence around it and applying technology, and particularly Splunk, to that. >> Yeah, and I just want to make a note 'cause I think it's important to mention. Cal Poly's doing some cutting-edge work. Alison Robinson, Bill Britton, who runs the program over there, they got a great organization. They're doing a lot of data-oriented from media analysis, data, big focus there. Cal Poly quite a big organization. >> They are, and they're doing some wonderful things. AWS just started an innovation hub called the DX Hub there that we are a part of, really trying to tackle these really meaty problems here that are very data-centric and technology-centric. And Cal Poly's the best place to do that. >> Great, let's get into some of the details. One of the things around the news, obviously seeing Mark Zuckerberg doing the tour, Capitol Hill, DC, Georgetown, free speech, data. Facebook has been kind of blamed for breaking democracy. At the same time, it's a platform. They don't consider themselves as an editorial outlet. My personal opinion, they are, but they hide behind that platform. So bad things have happened, good things can happen. So you're seeing technology kind of being pigeonholed as bad. Tech for bad, there's also a tech for good. Pat Gelsinger, the CEO of VMware, publicly said technology's neutral. We humans can shape it. So you guys are looking at it from shaping it for good. How are you doing it? What are some of the things that are going on technically from a business standpoint that is shaping and unifying the data? >> Yeah, I mean, it's absolutely certain that technology has facilitated human trafficking and other ills throughout the world. It's a way that people bring their product, in this case, sadly, human beings, to the market to reach buyers, right? And technology absolutely facilitates that. But, as you mentioned, we can use that against them. So actually here at Conf we are bringing together for a first time the partnership that we did with Splunk for Good, Accenture, and Global Emancipation Network to help automatically classify and score risky businesses, content, ads, and individuals there to help not only with mitigating risk and liability for the private sector, whether it's social media giants or if it's transportation, hospitality, you name it, but also help ease the burden of content moderators. And that's the other side of it. So when you live in this space day in and day out, you really exact a mental toll here. It's really damaging to the individual who sits and reads this material and views photos over and over again. So using technology is a way to automate some of those investigations, and the identification of that content could be helpful in a variety of ways. >> In a way, it's a whole other adversary formula to try to identify. One of the things that Splunk, as we've been here at Splunk Conference, they've been about data from day one. A lot of data and then grew from there, and they have this platform. It's a data problem, and so one of the things that we're seeing here is diverse data, getting at more data makes AI smarter, makes things smarter. But that's hard. Diverse data might be in different data sets or silos, different groups. Sharing data's important, so getting that diverse data, how difficult is it for you guys? Because the bad guys can hide. They're hiding in from Craigslist to social platforms. You name it, they're everywhere. How do you get the data? What's the cutting-edge ingestion? Where are the shadows? Where are the blind spots? How do you guys look at that? Because it's only getting bigger. >> Absolutely, so we do it through a variety of different ways. We absolutely see gathering and aggregating and machining data the most central thing to what we do at Global Emancipation Network. So we have a coalition, really, of organizations that we host their scrapers and crawlers on and we run it through our ingestion pipeline. And we are partnered with Microsoft and AWS to store that data, but everything goes through Splunk as well. So what is that data, really? It's data on the open web, it's on the deep web. We have partners as well who look at the dark web, too, so Recorded Future, who's here at Conf, DeepL as well. So there's lots of different things on that. Now, honestly, the data that's available on the internet is easy for us to get to. It's easy enough to create a scraper and crawler, to even create an authenticated scraper behind a paywall, right? The harder thing is those privately held data sets that are in all of those silos that are in a million different data formats with all kinds of different fields and whatnot. So that is where it's a little bit more of a manual lift. We're always looking at new technologies to machine PDFs and that sort of thing as well. >> One of the things that I love about this business we're on, the wave we're on, we're in a digital media business, is that we're in pursuit of the truth. Trust, truth is a big part of what we do. We talk to people, get the data. You guys are doing something really compelling. You're classifying evil. Okay, this is a topic of your talk track here. Classifying evil, combating human trafficking with the power of data analytics. This is actually super important. Could you share why, for people that aren't following inside the ropes of this problem, why is it such a big problem to classify evil? Why isn't it so easy to do? What's the big story? What should people know about this challenge? >> Yeah, well, human trafficking is actually the second-most profitable crime in the world. It's the fastest-growing crime. So our best estimates are that there's somewhere between 20 million and 45 million people currently enslaved around the world. That's a population the size of Spain. That's nothing that an individual, or even a small army of investigators can handle. And when you think about the content that each of those produce or the traffickers are producing in order to advertise the services of those, it's way beyond the ability of any one organization or even, like I said, an army of them, to manage. And so what we need to do then is to be able to find the signal in the noise here. And there is a lot of noise. Even if you're looking at sex trafficking, particularly, there's consensual sex work or there's other things that are a little bit more in that arena, but we want to find that that is actually engaging in human trafficking. The talk that you mentioned that we're doing is actually a fantastic use case. This is what we did with Splunk for Good and Accenture. We were actually looking at doing a deep dive into the illicit massage industry in the US, and there are likely over 10,000 illicit massage businesses in the US. And those businesses, massages and spas, that are actually just a front for being a brothel, essentially. And it generates $2 billion a year. We're talking about a major industry here, and in that is a very large component of human trafficking. There's a very clear pipeline between Korea, China, down to New York and then being placed there. So what we ended up needing to do then, and again, we were going across data silos here, looking at state-owned data, whether it was license applications, arrest filings, legal cases, that sort of thing, down into the textual advertisements, so doing NLP work with weighted lexicons and really assigning a risk score to individual massage businesses to massage therapist business owners and then, again, to that content. So looking, again, how can we create a classifier to identify evil? >> It's interesting, I think about when you're talking about this is a business. This is a business model, this business continuity. There's a supply chain. This is a bona fide, underground, or overt business process. >> Yeah, absolutely, and you're right on that too that it is actually overt because at this point, traffickers actually operate with impunity for the most part. So actually framing it that way, as a market economy, whether it's shadowy and a little bit more in the black market or completely out in the open, it really helps us frame our identification, how we can manage disruptions, who need to be the stakeholders at the table for us in order to have a wider impact rather than just whack-a-mole. >> I was just talking with Sonia, one of our producers, around inclusiveness and this is so obviously a human passion issue. Why don't we just solve it? I mean, why doesn't someone like the elite class or world organization, just Davos, and people just say they're staring at this problem. Why don't they just say, "Hey, this is evil. "Let's just get rid of it." What's the-- >> Well, we're working on it, John, but the good thing is, and you're absolutely right, that there are a number of organizations who are actually working on it. So not just us, there's some other amazing nonprofits. But the tech sector's actually starting to come to the table as well, whether it's Splunk, it's Microsoft, it's AWS, it's Intel, IBM, Accenture. People are really waking up to how damaging this actually is, the impact that it has on GDP, the way that we're particularly needing to protect vulnerable populations, LGBTQ youth, children in foster care, indigenous populations, refugees, conflict zones. So you're absolutely right. I think, given the right tools and technology, and the awareness that needs to happen on the global stage, we will be able to significantly shrink this problem. >> It's classic arbitrage. If I'm a bad guy, you take advantage of the systematic problems of what's in place, so the current situation. Sounds like siloed groups somewhat funded, not mega-funded. This group over here, disconnect between communications. So you guys are, from what I could tell, pulling everyone together to kind of create a control plane of data to share information to kind of get a more holistic view of everything. >> Yeah, that's exactly it. Trying to do it at scale, at that. So I mentioned that at first we were looking at the illicit massage sector. We're moving over to the social media to look again at the recruitment side and content. And the financial sector is really the common thread that runs through all of it. So being able to identify, taking it back to a general use case here from cyber security, just indicators as well, indicators of compromise, but in our case, these are just words and lexicons, dollar values, things like that, down to behavioral analytics and patterns of behavior, whether people are moving, operating as call centers, network-like behavior, things that are really indicative of trafficking. And making sure that all of those silos understand that, are sharing the data they can, that's not overly sensitive, and making sure that we work together. >> Sherrie, you mentioned AWS. Teresa Carlson, I know she's super passionate about this. She's a leader. Cal Poly, we mentioned that. Splunk, you mentioned, how is Splunk involved? Are they the core technology behind this? Are they powering the-- >> They are, yeah, Splunk was actually with us from day one. We sat at a meeting, actually, at Microsoft and we were really just white boarding. What does this look like? How can we bring Splunk to bear on this problem? And so Splunk for Good, we're part of their pledge, the $10 million pledge over 10 years, and it's been amazing. So after we ingest all of our data, no matter what the data source is, whatever it looks like, and we deal with the ugliest and most unstructured data ever, and Splunk is really the only tool that we looked at that was able to deal with that. So everything goes through Splunk. From there, we're doing a series of external API calls that can really help us enrich that data, add correlations, whether it's spatial data, network analysis, cryptocurrency analysis, public records look-ups, a variety of things. But Splunk is at the heart. >> So I got to ask you, honestly, as this new architecture comes into play for attacking this big problem that you guys are doing, as someone who's not involved in that area, I get wow, spooked out by that. I'm like, "Wow, this is really bad." How can people help? What can people do either in their daily lives, whether it's how they handle their data, observations, donations, involvement? How do people get involved? What do you guys see as some areas that could be collaborating with? What do you guys need? How do people get involved? >> Yeah, one that's big for me is I would love to be able to sit in an interview like this, or go about my daily life, and know that what I am wearing or the things that I'm interacting with, my phone, my computer, weren't built from the hands of slave labor. And at this point, I really can't. So one thing that everybody can do is demand of the people that they are purchasing from that they're doing so in a socially viable and responsible way. So looking at supply chain management as well, and auditing specifically for human trafficking. We have sort of the certified, fair-trade certified organic seals. We need something like that for human trafficking. And that's something that we, the people, can demand. >> I think you're on the right track with that. I see a big business model wave where consumer purchasing power can be shifted to people who make the investments in those areas. So I think it's a big opportunity. It's kind of a new e-commerce, data-driven, social-impact-oriented economy. >> Yep, and you can see more and more, investment firms are becoming more interested in making socially responsible investments. And we just heard Splunk announce their $100 million social innovation fund as well. And I'm sure that human trafficking is going to be part of that awareness. >> Well, I'll tell you one of the things that's inspirational to me personally is that you're starting to see power and money come into helping these causes. My friend, Scott Tierney, just started a venture capital firm called Valo Ventures in Palo Alto. And they're for-profit, social impact investors. So they see a business model shift where people are getting behind these new things. I think your work is awesome, thank you. >> Yeah, thank you so much, I appreciate it. >> Thanks for coming on. Congratulations on the shout-out on the keynote. Appreciate it. The Global Emancipation Network, check them out. They're in San Luis Obispo, California. Get involved. This is theCUBE with bringing you the signal from the noise here at .conf. I'm John Furrier, back with more after this short break. (upbeat music)

(funky music) >> Live from San Francisco, it's theCube, covering RSA Conference 2019 brought to you by Forescout. >> Hey welcome back everybody Jeff Frick here with theCUBE. We're at the RSA Conference at downtown San Francisco Moscone Center, they finally finished the remodel. We're excited to be in the Forescout booth, we've never been in the Forescout booth before, psyched that they invited us in. But we've got an old time CUBE alumni and a special company in my heart, was my very first CUBE event ever was Splunk.conf 2012. >> I did not know that Jeff. >> Yeah so we're live. We have Doug Merritt on he's a CEO of Splunk. Doug great to see you. >> Thanks Jeff, good to see you again also. >> Yeah so we've been doing Splunk.conf since 2012. >> The early days. The Cosmo Hotel and it was pouring rain that week. >> That was the third year. >> Probably the third year? >> Second year, yeah long time ago, it's grown. >> 2012 wasn't that big but this is a crazy show. You've been coming here for a while. Security is such an important part of the Splunk value proposition, just general impressions of RSA as you've been here for a couple of days. >> Yeah, it's amazing to see how the show has grown over the years, security's gone from this, kind of backwater thing that a few weird people did in the corner, that only understood the cyber landscape, to something that boards care about now. And that, obviously has helped with this show, I don't know what the attendee numbers are like, but tens of thousands of people. >> Oh yeah. >> You can't walk down a hallway without bumping into 10 brand new companies that were launched in the past year, and the security space and make the biggest challenge people that I have, and I think that other people have is, how do you tell different, where's the wheat from the chaff? What is really important in security and how do you tell different companies and different trends apart, so you can actually focus on what matters? >> Right, I just feel for the seed-sows, right, I mean, you guys have a big ecosystem at .conf, but those are all kind of complimentary things around the core Splunk solution. This is, you've got co-opetition, competition, how does somebody navigate so many options? 'Cause at the end of the day you don't have unlimited resources, you don't have unlimited people to try to figure all these pieces of the puzzle out. >> Yeah, and the CSOs have got a really tough job, the average CSO has got well over a hundred different vendors you're dealing with, and with Splunk what we're very focused on, and where I think we add value is that we become, if done right, we become the abstraction layer that creates a brain and nervous system that allows all those different products, and all of them have got unique capabilities. When you think about the complexity of all the networking, all the compute, all the storage, all the end point landscapes that's only getting worse for the cloud, because now there's more services with more varieties across more cloud vendors. How do you get visibility on that? >> Right, right. >> And you need products at those different junctures, 'cause protect and prevent and defend is still an important function for CSOs, but when we know that you can't prevent everything. >> Right. >> And things will go wrong, how do you know that, that is actually occurring? And what the splunk value prop is, we are the, we don't have as much of a point of view on any one product, we aggregate data from all the products, which is why so many people are partners, and then help companies with both raw investigations, given that if something goes wrong with our schema less data structure, but then also with effective monitoring and analytics that's correlating data across those tens, hundreds or thousands of different technologies. So you can get a better feel for what are the patterns that make sense to pay attention to. >> I think you just gave me like 10 questions to ask just in that answer, you covered it all. 'Cause the other thing, you know, there's also IoT now and OT and all these connected devices so, you know the end points, the surface area, the throughput is only going up by orders of magnitude. >> Without a doubt. >> It's crazy. >> I saw some stats the other day that, globally at this point there's, I may get these off by one digit, but lets say there's 80,000 servers that are the backbone of the entire internet. There's already over 11 billion connected devices, going back to that IoT theme. So the ramifications at the edge and what that means are so profound and companies like Forescout, as a key partner of Splunk's, help make sure that you're aware of; what are all the different elements that are ever hitting my network in a way. And what do they look like and what, what should I be doing, as different things pop on and pop off and, again, we're trying to be the interpretation and brain layer for that, so that they are more and more intelligent to the actions they're taking, given their depth of domain, their deep knowledge of what a camera should look like, or what a windows PC should look like or what a firewall should look like given the configurations that are important to that company. >> Before we turned on the cameras you made an interesting comment. We used to talk about schema on read versus schema on write, that was the big, kind of big data theme, and you guys are sitting on a huge data flow, but you had a really kind of different take, because you never really know, even with schema on read it seems you know what the schema is but in today's changing environment you're not really sure what it is you're going to be looking for next right? And that can evolve and change over time, so you guys have kind of modified that approach a little bit. >> Yeah, I think we are this year you'll see us really reemphasizing that core of Splunk. That the reason you'd have an investigative lake, and I don't think most people know what a schema is period, much less read or write so my new terminology is hey you need a very thorough investigative lake. Going back to the discussion we were having, with so much surface area, so many network devices, so many servers, so many end points, what tool do you have that's reading in data from all of those, and they all are going to have crazy formats. The logs around those are not manageable. To say you can manage logs and centralize. Centralized logs I get, manage those words don't work together. >> Right. Logs are chaotic by nature, you're not going to manage them, you're not going to force every developer and every device to adhere to a certain data structure so it can neatly fit into your structured database. >> Right. >> It is too chaotic, but more importantly, even if you could you're going to miss a point, which is, once you structure data, you're limited with the types of questions you can ask, which means you had to visualize what the questions would be in the first place. In this chaotic environment you don't know what the questions going to be. The dynamics are changing way to quickly, so the investigative lake is truly, our index is not schematized in any way, so you can ask a million questions once versus a schematized data store where it is; I ask one question >> A million times. a million times. And that's super efficient for that, but, the uniqueness of Splunk is, the investigative lake is the fabric of what we do, and where I think our customers, almost have forgotten about Splunk is, read all that data in. I know we've got a volume based licensing model that we're working on customers, were working to solve that for you, that's not the, I'm not trying to get data in so that we can charge more, I'm trying to get data in so that everybody has got the capacity to investigate, 'cause we cannot fail in answering what, why, when, where, how, and stuff'll go wrong, if you can't answer that, man you're in big trouble. And then on top of that let's make sure you've got right monitoring capability, the right predictive analytics capability; and now with tools like Phantom, and we bought a company called victorOps, which is a beautiful collaboration tool, let's make sure you've got the right automation and action frameworks so that you can actually leverage peoples skills across the investigative, monitoring and analytical data stores that at Splunk we help with all four of those. >> Right, right, again, you touch on a lot of good stuff. We could go for hours but we don't have you all day. But I want to follow up on a couple of things, because one of the things that we hear over and over and over is the time to even know that you've been breached. The time to know that you have a problem, and again, by having all that data there you can now start adjusting your questions based on that way you now know. But I think what's even more kind of intriguing to me is, as nation states have become more active, as we've seen the politicalization of a lot of things, you know, what is valuable today is a much varied, much more varied answer than just tapping into a bank account or trying to steal credit card numbers. So it really supports, kind of this notion that you're saying, which you don't have a clue what the question is that you're going to need to ask tomorrow. So how do you make sure you're in a position, when you find out what the question is, that you can ask it? >> And that's the design architecture I like about splunk as a company is that our orientation is, if you're dealing with a world of chaos, allow that chaos to exist and then find the needles in the haystack, the meaning from that chaos, and then when you find the meaning, now you know that a monitor is worthwhile, because you've validated root cause and it exists. And when your monitor is kicked a few times, and you know it's legit, build a predictive routine, because you now know it's worth trying to predict, because you've seen this thing trip a number of times, which inverts the way that most people, that all of us were taught. Which is start with the end in mind, because garbage in equals garbage out, so be really thoughtful in what you want and then you can structure everything, it's like well, that's not the way the world works. What if the question we asked 15 years ago was, what if you couldn't start with the end in mind, what would you have to do? Well you'd have to have a schema less storage vehicle and a language that allows you to ask any question you want and get structure on the question, but then you still need a structure. So you're going to structure them one way or the other, how do you make sure you've got high quality structure, and in our dynamic landscape that's always going to change. >> Right, well the good news is 2020 next year so we'll all know everything right? >> Yeah, exactly. >> We'll have the hindsight. So the last thing before I let you go is really to talk about automation, and just the quantity and volume and throughput of these systems. Again, one, escalating, just 'cause it's always escalating, but two, now adding this whole connected devices and IoT, and this whole world of operational technology devices, you just, you can't buy your way out of it, you can't hire your way out of it, you have to have an increasing level of automation. So how are you kind of seeing that future evolve over the next couple of years? >> I've been meeting with a lot of customers obviously this week, and one of them said, the interesting part about where we are now is, you can't unsee what you've seen. And where we were five years ago, as most people in security and IT; which are natively digitized, they still didn't know how to wrap there arms around the data. So they just didn't see it, they were like the ostrich. Now with tools like Splunk they can actually see the data, but now, what do I do with it? When I've got a billion potential events per day, how do I deal with that? And even if I could find enough manpower, the skills are going to be changing at such a constant basis, so I think this security, orchestration, automation, response; SOAR, area and we were fortunate enough to form a great relationship with phantom a couple of years ago and add them to the Splunk fold, exactly a year ago, as, I think, the best of the SOAR vendors, but it's a brand new category. Because companies have not yet had that unseeing moment of, holy cow, what do I do, how do I even deal with this amount of information? And adding in automation, intelligent automation, dynamic automation, with the right orchestration layer is an absolute imperative for these shops going forward, and when I look at a combination of phantom and their competitors there's still less then a thousand companies in a sea of a million plus corporate entities, globally, that have licensed these products. So we're at the very beginning of this portion of the wave. But there's no way that companies will be able to be successful without beginning to understand what that means, and wrapping their minds around how to use it. What we're so excited about with Splunk, is traversing investigate, monitor, analyze and automate up and down continuously, we think is the key to getting the best value from this really, really diverse and chaotic landscape and then having phantom as part of the fold helps a lot, because you can get signal on, did I do the right automation? Did It actually achieve the goal that my brain told me to do, or not? And if not, what do I adjust in the brain? Do I go after different data, do I structure the data a different way? But that up and down the chain of check and balance, am I doing the right stuff is something that-- >> And do it continuously. >> It's got to be continuous. >> It's got to be continuous. So we're sitting in the Forescout booth, so talk about how Forescout plays. I mean you guys have been sitting on those (mumbles), really fundamental core date, they're really kind of been opening up a whole different set of data, so how is that kind of working out? >> Yeah, so I'm really thankful for the relationship, mostly because they're a great company and I love their CEO, but mostly, if you go customer back, it's a very important relationship. Which is the proliferation of devices, developments continues to grow, and most companies aren't even aware of the number of devices that exist in their sphere, much less how they should look, and then what vulnerabilities might exist because of changes in those devices. So the information flow of, here's what's in the eco-sphere of a customer into Splunk is really helpful, and then the correlation that Splunk drives, so that Forescout gets even more intelligent on what corrective actions to what type of actions period do I take across this sea of devices is a really important and beneficial relationship for our customers. >> Excellent, so I'll give you the last word, little plug for Splunk.conf coming up in October. >> Yeah, I'm really excited about conf, excited to have you guys there again. We've been on a really intense innovation march for the past few years. This last conf we introduced 20 products at conf, which was a record. We're trying to keep the same pace for conf 2019 and I hope that everyone gets a chance to come, because we're going to both be, moving forward those products that we talked about, but, I think really surprising people, with some of the directions that were taking, the investigate, monitor, analyze and act capabilities both as a platform and for security IT and our other key buy-in centers. >> Alright, well we'll see you there Doug, thanks for stopping by. >> Thank you, Jeff. >> Great seeing you. >> He's Doug, I'm Jeff, you're watching theCUBE, we're in the Forescout booth at RSA Conference 2019, thanks for watching we'll see ya next time. >> Thank you. (electronic music)

(upbeat music) >> Live from Orlando, Florida, it's theCUBE covering .conf18. Brought to you by Splunk. >> Hello everybody, welcome to Orlando. This is theCUBE, the leader in live tech coverage, and we're here at Splunk conf .conf 2018. The hashtag is #splunkconf18. My name is Dave Vellante, I'm here with my co-host Stu Miniman. Stu it's great to be in Orlando again. Last year we were in D.C. This is our seventh year covering Splunk.conf and we've seen the company really move from essentially analyzing log files on PRAM in a perpetual license model, to now a company that is permeating all of IT into the lines of business. Security, IT performance, application performance, moving into IOT. Really becoming a mature company. It's a company with $1.7 billion in revenue forecasted for this year. They were talking about a $17 billion market cap, they're growing at 36%, and they're a company Stu, that is in the process of successfully going from a perpetual license model to a renewable model. Splunk set the goal of being 75% renewable by 2020. Sounds like renewable energy, but repeatable renewable from a subscription standpoint, they're already there. So you're seeing that in the execution. This is your first .conf, or conf as they like to say. We were at the ESPN Wide World of Sports Center, you saw what, what's the number, 8,000 people? >> Yeah I think 8,000 at the show this year, it's strong growth, and Dave I've been hearing from the team for years the excitement of the show, the passion of the show, saw like, right over near where we were sitting there's the whole group of that was the Splunk trust. They've got the fezzes on, a lot of them have superhero capes on, and it's what you'd expect from a passionate, technical maybe even geeky audience. Things like, we're announcing the S3 API-compatible storage. Everybody's like, yay we're so excited for this. It's hardcore techies. >> What was the other big clap? Screen? >> Yeah, that's right dark mode. We're going to go to dark mode, I don't have to play with the CSS. Anybody that's played with a website, changing these things is not trivial. I click a little button and the joke was this was the bright one for the executives, but when I'm down in the gamer center I don't want this glaring screen here, so I can switch it over to dark mode. And people were pretty excited about that. >> So again the roots of Splunk, they took log data and analyzed it. Doug Merritt the CEO, talked today talked about, making things happen with data. I thought he did a really good job of laying out the past, putting the past behind us in terms of he said, "I've been to I can't tell you "how many Master Data management classes "trying to optimize the database, "trying to codify business processes "and harden those business processes." The problem is data is messy. Data is growing so fast, business processes are changing so fast, the competition is moving so fast, customers are changing. So you have to be able to organize your data in the moment. So, the whole idea that, even go back to the early big data days and Hadoop, the whole idea was to bring five megabytes of compute to a petabyte of data. And no schema on write, or what some call schema on read. Splunk was really a part of that. Put the data, get the data organized in a way that you can look at in in a moment, but then let the data flow. So that has definite implications in terms of how you think about data. It's not trying to get the data all perfect so you can use it, it's trying to get the data into your data ocean, as we like to say, and then have the tooling to be able to analyze it very, very quickly. They announced Splunk 7.2 today which is a big deal. Some things, we'll talk about a few of the features, obviously focused on performance, but one of the things they talked about was basically being able to split storage and compute. So previously you had to add essentially a brick of storage and compute simultaneously. We've heard about these complaints for years in the conversion infrastructure space, it's obviously a problem in the software space as well. Now customers are able to add storage or compute in a granular fashion, and they're cozying up to Amazon doing S3 compatible store. >> Dave, I love that message that he put out there you said, "life is messy. "You can't try to control the chaos, "you want to be able to ride those waves of data "take advantage of them and not overly "make things rigid with structure." Because once you put things in place you're going to get new data or something else that's going to come along and your structure is going to be blown away. So when you need to search things you want to be able to look at them in that point in time but be able to ride those waves, flow with the data, live the way your data lives. That's definitely something that resonates in this community. Dave, something I've watching this space, as an infrastructure guy and watching the Cloud movement, there were a lot of reasons why traditional big data failed. I kind of never looked at Splunk like most of those other big data companies. Yes they had data, yes they're part of the movement of taking advantage of data, but they weren't, oh well we have this one tool that we're going to create to do it all, like some of the new players. They're playing with all the latest things. You want tentraflow, you want to do the A.I, the ML. Splunk is ready to take advantage of all of these new waves of technologies, and they've done a couple of acquisitions like VictorOps in the space that they keep growing and the goal is, you mentioned the revenue, but Splunk today has I think it's 16,000 customers. They have a short term goal of getting to 20,000 but with what they started talking about in the keynote today, Splunk Next, they really want to be able to do an order of magnitude of more customers and when you get great customer examples like Carnival Cruises. The CEO I thought, talked about the sea of data. Lots of good puns in the keynote there but mobile cities floating around and lots of data that they want to be able to get the customer experience and make sure the customer gets what they need and make sure that Carnival knows what they have to make sure that they're running better and optimizing their business too, so great example. Looking forward to talking to them on theCUBE. >> Well and they have many dozens, I think it's in last quarter, it was like 60 plus deals over a million dollars. They have many $10 million plus deals. That's an outcome of happy customers, it's not like they're trying to engineer those deals. I'm sure some of the sales guys would love to do that. But that's a metric that I think was popularized by the likes of Aneel Bhusri at Workday, certainly Frank Slootman at ServiceNow. It's one that Wall Street watches and Splunk it's an indicator. Splunk is doing some very very large deals that underscores the commitment that many customers are making to Splunk. Having said that, there are many more that are still smaller users of Splunk. There's a lot of upside here. And they're going into a serious TAM expansion that's something we're going to talk to Doug Merritt about. Making acquisitions of a company, VictorOps was their most recent acquisition sort of security orchestration and management. They're doing, the ecosystem is growing, they're doing bigger deals or partnerships with the likes of Accenture, Deloitte is here, EY. Accenture actually has a huge space at this event, and those are indicators. I want to go back to something you said earlier about the failure of big data. Certainly big data failed to live up to the hype in many ways. You didn't see a lot of wholesale replacement of traditional databases and EDWs. You did see a reduction in cost, that was the big deal. But clearly enterprise data warehouses and ETL, they're still a fundamental part of people's data strategies despite what Doug Merritt saying, hey, the data is messy and you've just got to let it flow, essentially what he's saying. There is still a need for structured data and mixing, sort of, interacting of structured and unstructured data. Bringing transaction data and systems of intelligence together, analytic data. But the one thing that big data did do and the Hadoop movement, it did a couple things: one is, architecturally it pushed data out and back in the day you had to get a big Unix box and stuff everything in there. It was your god box of data. And you had Oracle licenses and Sun Microsystems boxes and it was very expensive. And you had a couple of people who knew how to get the data out. So the goal of democratizing data, what it did is, it is messy. Data went out to the distributed nodes and now the edge. But it brought attention to the importance of data and the whole bromide of data driven companies. And so now we're in a position to make a new promise and that promise is A.I, machine learning, machine intelligence, which seems to be substantive. We talk a lot on theCUBE is this old wine, new bottle? And we had an event in New York last month and the consensus from a lot of practitioners and others in the room was: no there's something substantive, the data substrate is now in place. Now it's all about taking advantage of it. Tooling is still complex but emerging or evolving. And I think the cloud, to your point, is a huge part of that. By integrating data pipelines in the cloud it dramatically simplifies the deployment model and the complexity of managing big data. >> Yeah, Dave, as you said, there used to be these giant boxes and some of these initiatives I needed 18 months, you know, millions of dollars and a large time you either need to be a country or a multi-national company to be able to put this thing together. I remember one of the earliest case studies that David Floyer did when we were looking at big data it was how do I take that 18 month deployment and drive it down to more like a six week deployment, and when you talk about A.I, ML, and deep learning, the promise is that a business user should be able to get answers in a much much shorter window. So actionable on that data, being able to do things with it not just looking backwards but hear the team. So I want to be able to be proactive, I want to be able to be responsive. I want to even predict what my client is going to need and be ready for it. >> So as Doug Merritt said that digital and physical worlds they're coming together. They don't stop evolving. They're organic. Your data model has to be flexible. It's a sea of data. It's an ocean of data. It's not a confined data lake, as John Furrier and others like to say. And so I was happy to hear Doug Merritt talking about a sea. We use the term oceans because that's really what it is. And oceans are unpredictable, they're sometimes really harsh, they can sometimes be messy. But they're constantly evolving and so I think that kind of metaphor works in this world of Splunk. We've got two days here of coverage. A lot of customers coming on today, in fact, Splunk is one of those companies that puts many customers on theCUBE, which we love. We love to dig in to the case studies. We've got some ecosystem partners. Some of the big SIs are coming on and of course, we're going to hear from some of the product people at Splunk that go to market people. Doug Merritt will be on tomorrow. And a number of folks. I'm Dave Vellante, @DVellante on Twitter. He's @Stu. Stu Miniman. Keep it right there, buddy. We'll be back with our next guest right after this short break. You're watching day one from Splunk conf18 in Orlando. Be right back. (soft bouncy music)

>> Narrator: Live from San Francisco, it's the Cube, covering AWS Summit 2017. Brought to you by Amazon Web Services. (upbeat music) >> Hi, welcome back to the Cube, live from the AWS Summit San Francisco. Jeff Frick, and I are here with the CMO of Splunk, Brian Goldfarb. Hey Brian, welcome to the Cube. >> Thanks, thanks for having us, we're really glad to be here. >> You've been the CMO at the Cube, the Cube, congratulations! >> Brian: Promotion, this is amazing. (laughs) >> You've been promoted. Let me start again, you've been the CMO with Splunk, am I red yet, for about six months. Talk to us about the new role that you have there, what do you, what's exciting, what's happening? >> Yeah, it has been almost six months now. It's been an amazing experience. Splunk was super attractive to me as I was looking at opportunities, because it has both an amazing product and customers who love it. And that combination, particularly in technology, is that rare first place. That's a marketer's dream. You're not creating champions, you're not convincing anyone that it's great. And so I've been coming in focusing on how do take that incredible asset, our community, and our users and really expand it. And that's been a big focus for me over the last five months. It's an amazing company. I'm very honored and lucky to be working with such a great place. And in fact, we won, "Best Places to Work." >> Lisa: Congratulations. >> For the tenth year in a row. >> The Santana row office are pretty nice. I was lucky enough to go down there and check those out when you opened them. >> Oh yeah, that's awesome. Our headquarters is in San Francisco, but as you think about the expansion of the area having facilities down in San Jose is super great for as we grow our company. >> So I guess, it's a match made in heaven, but the word on the street is you're a data guy. You want data to support everything. Data driven solutions. Data backed decision making. What a perfect fit because the essence of Splunk is basically sitting on that machine data that's flowing through the system. >> That's right. You think about where our roots are, is really how do take big data and make it useful for people. Like machine data is often forgotten. All the information flowing from sensors and hardware and servers. And as we sit here, at the Amazon Web Services show in San Francisco, all of that infrastructure is core to creating machine data. And we want to make it accessible and usable for everyone to get insights. And what we see is that manifest itself in a lot of interesting ways. I'll give you an example, Yelp. Think about food, think about reviews, but they're using Splunk for a couple things. One, make sure that their core infrastructure is up and running, obviously important. Because we need that restaurant review, you need it now. That's a very San Francisco thing. But more importantly as they've rolled out their new food delivery capabilities, all of the business analytics required to make sure that operations business runs tip top is critical. So they're using Splunk for all those pieces. >> So I wonder if you can speak a little bit about the relationship with AWS? I know you're relatively new, but Doug Merritt is relatively new. And of all of the logos that Verner went which were numerous and hard to see, (Brian laughs) he picked Doug to come up and really help out with the keynote. Obviously, Cloud, big deal, AWS, big deal. What is the relationship, how has it evolved over time, and how is this cloud-enabled delivery impacting the way Splunk does business? >> Yeah, we're very fortunate to have a wonderful partnership with Amazon Web Services. We've been a strategic partner of them for almost five years. And we made a big bet of our business on using their product to deliver our product in the cloud. Our business started 14 years ago with Splunk Enterprise, an on-premises based software solutions that's been adopted by over 13,000 customers around the globe. And we heard time and time again, as the cloud became more important in the decisions people were making, how do we get the visibility that we need both across our on-premises assets and our cloud assets? And so the relationship with Amazon has been predicated on how do we deliver Splunk in the cloud and more importantly, how do we give everyone who's now adopting Amazon at this amazing clip the visibility into all the components that they're using, so they can maintain their solutions, they can make sure things are running, they can optimize their span, et cetera. >> And it's even a building partner, right? So it's an infrastructure partner, it's a delivery slash sales channel partner, and there you can even build directly through Amazon, if I heard right today. >> That's right. So we're both a customer and a partner is one way to think about it. And today in the keynote, we announced with their new AWS marketplace, SaaS Contracts API release, that we're one of their first partners delivering our product through that new delivery model. And what's really interesting about it is today enterprises are trying to innovate faster. They get stuck sometimes through things that shouldn't matter. Procurement, legal, how do you actually get the assets that you need in order to do the things they need to do? Speed is such an important part of being successful. And now that we can deliver Splunk through the AWS marketplace, customers can easily find it. They can now easily buy it using their existing building relationship with Amazon. They can use friendly terms that are defined there. And they can buy on one year, two year or three year contracts with the appropriate term-based discount. So the longer you buy, the cheaper it is. So, procurement's happy, legal's happy, the technical user's happy 'cause they can move faster than they ever have before. >> One of things that we're hearing in a lot of enterprises is that directives coming down from the board to the CIO. You've got to move more legacy applications to the hub, but you've also got to try to find more value from digital assets. With that respect, what are some of the core functions that Splunk Enterprise on AWS is delivering to customers from a value out of our assets perspective? >> There's assets across so many different categories, so we look at, what are we doing across the infrastructure side of the business? What are we doing across the security side of the business and now this emerging category of IOT, how do we get all of the assets working together? And one of the things that we think about a lot with our customers is we have all this data. How do you apply different lenses so that different people can ask different questions of this same data and get the key insights back. So if I'm a security investigatory trying to prevent fraud, that's something that we can do, but that's also helping the people in IT maintain systems faster and it's also doing business, process management, working with supply chain and we see that happening everywhere. We were talking just before we started about this mental model that enterprises have where they're stuck in this reactive place. Something breaks, then you fix it. Or a customer complains and you deal with it and everyone's on this journey to being more proactive. How do I get notified that something broke so that I can fix it, or better yet, predictive? So we're taking machine learning and artificial intelligence concepts, baking them in directly into the Splunk platform and using that to help people go from that reactive state that they're in to this forward state of predictive intelligence and being able to fix things before they even become a problem. >> I would love to dig in a little bit deeper on IOT, 'cause you guys are into IOT when it was called machines. Machines are just a subset of the things and now, the IOT thing is really taking off. Obviously, we to the GE shows and also people are things, too, which sometimes gets forgotten in the conversations, and we all throw off a ton of digitals off, so you guys are pretty well positioned to apply your technology techniques, processes now to a whole giant new set of data flows coming off all these things. >> You put the words in my mouth. People forget about people being things. We talk about machine data, the word machine can mean anything, really. It's how do you take all of this data, correlate it together in interesting ways, then do something with it. Thing about the retail use case. Customers now have an expectation of the experience that they're going to have, higher than ever before. You just expect more, you know they have the information, so you want it. You think about beacons and knowing your preferences, so retailers need to take advantage of that and they can use technology like Splunk to really get there. Another example around customer expectation, think about travel. We all travel here, you guys probably flew in or drove in, and we have mediocre experiences at the airport in particular. We have a customer Gatwick Airports in the UK who's completely Splunked everything they're doing at the airport with a goal of reducing the amount of time that it takes to go from the front desk to your gate to less than five minutes. So on a dashboard, they can see wait times at any particular security terminal, they can redeploy assets, they get alerts, and they can monitor all the different data streams, whether it's weather data, air traffic control data, airline data, sensors from all the different parts of the airport, and pull all that together into a people-based experience to drive up that engagement. >> Gatwick, great example, and your CEO was also talking about Coca Cola on stage, for example. You've got over 13,000 customers, so as we look at where we are today with cloud users maturing, cloud providers maturing, looking at what Amazon has to date, over 90 services. As customers look at getting more legacy applications out of operations, how is Splunk helping customers on this journey to hybrid, or is hybrid a destination? What's the conversation there like with the senior leaders that you talk to down to the IT folks? >> In my job, I get the luxury of talking to hundreds of CIOs and I'll tell you, all of them see hybrid as the destination. Most of the enterprises that exist in the world have investments in things from mainframes to existing infrastructure and data centers and even as they consolidate more and more into the cloud, we're going to be in a world where people have assets in many different places. What we've seen with Amazon and why I think our partnership has been so successful is we're helping a lot of these enterprises justify and control how they're able to get to the cloud faster. We talked about innovation and speed. Being able to adopt services in the cloud in addition to what we're doing on premise is critical. And with Splunk, they get insight across all their different components. They feel that they can manage the security across both on premises and the cloud and they get the peace of mind that they have that operational visibility because they're going to be hybrid, they're going to be running in the cloud, they're always going to have their existing investments. That's kind of the state of the world for the foreseeable future. >> So, looking forward, you've been in the job about six months or so, what are your priorities for the next six months? Doug says, "alright, warm up time's over, "get to work, Brian." >> He said that on the third day. >> (laughs) On the third day. So what are some of your priorities? >> As a business, we have a collection of priorities. One is the cloud, full stop. We know that the journey to the cloud is coming full speed and what we can do around Splunk cloud and being able to fulfill and delivers services for our customers there is absolutely critical and continuing to grow that capability. And second for us is customer success. How we get people beyond single use case to multi use case. Using it in IT, how to take advantage of it in security. How do you take advantage of it in supply chain? Because that magic moment that customers have is really when they have the same data in and they get value across their entire business. For me, as the CMO, my priority is piggy back on that. First and foremost is digital. It's kind of trite, everyone's talking about it but I came from Google and sales force. I'm a performance guy and so I'm looking at how we can reconstitute the entire buyer journey from the moment someone says, "I'm interested "in a topic that's relevant to our product" to "I transact online" and that's a big initiative for what we're doing across web and sales team to work through all those pieces, and then second, I now am the chief t-shirt officer. >> Jeff: That's not an easy job. >> It's the hardest job I've ever had, 'cause I'm not in my strength and always innovating on what's next. I hear I was trending on Twitter, Doug's t-shirt versus Werner's t-shirt today. >> Jeff: That's right. >> I think we were winning. >> And you guys have the biggest t-shirt booth installation, device at trade shows than anyone rather than just giving away, in the back, the entire booth is basically built around the t-shirts. >> Oh, and we're Splunking everything, too. >> Impressive. >> And we saw a spike in traffic, too. Our store this morning after we went on stage. >> I put the picture up, so I sent the link, hopefully it will get me some Amazon affiliate money back. I don't know. >> The t-shirts match the buyer's journey. >> Of course. >> Of course, as a marketer, of course. >> Stop chasing your tail dash f. You got to connect to your logs and always keep watching. >> Before we let you go, let's get a plug in for splunk.conf. The Cube has been going, I think this will be our fifth or sixth year, I can't count that high, I'm out of fingers and toes. >> Eighth. >> Your eighth, our sixth there, I think. >> There you go, you're a regular. >> So where is it, what's the highlights this year? It's always a great event. >> Much like AWS, we're doing events all across the world all the time. We have a series called Splunk live, we just did one in San Francisco last week which are super great ways to come and learn about the product and get hands-on keyboard to improve your skills, but it all culminates in .conf which is our leading event in the category. It's going to be in D.C. this year, September 25th to 28th and that's the best place to come, learn about Splunk, get hands-on with the product, meet the product team, learn from your peers, which to me, is the thing that matters the most. To see all the innovative ideas that everyone is doing, 'cause one of the great things about Splunk is the use cases for the product are basically infinite, and so you hear more and more stories, whether it's the city of San Francisco or shazaam or Yelp or Gatwick or thousands of others and .conf is the place, so you guys are going to be there, I'm going to be there, which is the reason everyone should come, obviously. >> Exactly, t-shirts for all. >> Brian: T-shirts for everybody. >> Well, Brian Goldfarb, CMO of Splunk, I got that right this time, thank you so much. >> Brian: And the Cube. >> And the Cube, apparently. (laughs) >> Jeff: Watch out, John, we've got a new CMO. >> Lisa: Thank you so much for joining us. Great, your passion is evident, we wish you the best of luck and continued success in your role. For my co-host Jeff Frick, I'm Lisa Martin. We are live at the AWS Summit San Francisco. Stick around, we'll be right back. (upbeat music) Is changing and this entire process, you started to mention a little bit, how is-- (upbeat music)

(upbeat music) >> Hi, I'm Lauren Cooney, and welcome back to theCUBE. Today we have Jeff Frick with us, who is the general manager of theCUBE, and we're here to learn about what goes on at theCUBE, what the business is like, some of the most fun aspects of what he does, and go from there. >> Jeff: Great to be here. >> Thank you so much. So, Jeff, starting out, really, when did you join theCUBE, and really what are your goals and aspirations for theCUBE as you look to business going forward now? >> My first CUBE gig was, I've known John for a long, long time, reached out. It was actually Splunk.conf 2012 in the Cosmo, I'll never forget, and they needed an extra host, we were over-subscribed, and I went and did that show. I did it with Jeff Kelley, and was really touched by this format where you've got kind of this professional looking, newsy, opportunity for people to tell their story, most people don't ever get to tell their story in that context, which I thought was pretty cool. And then also just to personalize the people behind the tech because since Steve Jobs, and that genre of people, people want to know who the people are behind the technology. So not only the people that run the companies, but who creates it. I think Open-source had a lot to do with that where people are interested in other people, not just the tech for itself. And that's what I really like. >> You bring up a great point with stories, and luminaries, and visionaries. Can you talk about some of those folks that you've had on theCUBE, some of the best guests you've ever had? >> Oh my gosh, we've had so much. People ask me this all the time, I need to prepare my answer better. But like Scott Cook, from Intuit, was just phenomenal. Tremendously successful, still focused on the same core vision that he came up with when his wife was filling out her checkbook, writing checks, about just a better way to organize and manage cash. And that show is so inspirational because it's really a small business show pretending to be an accounting show. We've had Robert Gates on, I didn't get to interview Robert Gates, but served with many, many President's. We're really fortunate, we often get the keynotes. Fred Luddy, from ServiceNow, phenomenal founder, goofy, quirky. Maria Klawe who runs Harvey Mudd College, goofy, quirky, great personality. So there's just so many great individuals and then some that you don't know. We had, an original ServiceNow we had this little older lady who had got a ServiceNow POC through, it's some ancient company, I don't even remember what company it was, and it was just fascinating to me how this, you know, she wasn't young and hip and new and on top of things, was able to kind of see the vision, get it funded, get a project underway, and then eventually build into being a customer for them. And how she was able to do that, and what was the story, and how many peers out there are curious to know how they could do that for their company. And those, I love those stories. >> Those are great. And I think one of the things that we want to look at too is that we want to understand for the most part what are some of the bloopers that you've seen out there? What are some of the things that you've noticed that are funny or were oh my gosh, you know, while you were on air, while you were thinking about different things. Can you tell me a little bit about that? >> Well, of course, the classic one that we've referenced over and over and over, and if you've seen any of our promos you see, it was John Cleese. Ironically again, at another ServiceNow keynote he was doing their CIO Summit or something, and he came on and he basically decided he wanted to rewrite the end of the, it became a sketch, not an interview. And just stood up and threw his water all over John and Dave, fried Dave's laptop, and marched off the stage. Half the people there, we had a huge live audience, were laughing hysterically. The other half were petrified. Unfortunately, a number of those were the client senior executives who didn't really know, and we had to go out and do some investigation and find out he actually does it a lot to people. And in fact the guys ran into him later that night and he said, "Wasn't that fun, wasn't that fun?" So that's one that just jumps right off the page. Another great one was Michael North from the NFL was at an IBM event talking about how they build the schedule. And while the analytics are fine, and you run an algorithm and it can plug a bunch of numbers, it's really the softer side. You know, how do you leverage at that point a Peyton Manning versus a Tom Brady match up? Do you use it to leverage an existing relationship? Do you use it to build a new network? Do you use it in your feature presentation to get the most leverage from that asset? So a whole lot of kind of soft, softer sided things in terms of the decision making. Which I think is what's really interesting. >> Yeah, I think that's great. And I want to take it a little bit further into what are the business aspects of theCUBE? What do you do on a day to day basis? What are the things that matter the most for running this business? >> Big question. So most important area is our customers. So what customer, what value does theCUBE bring to people when they take us to their conference? >> Lauren: And who are the key customers? >> Well key customers, right. IBM, and we've mentioned ServiceNow, Splunk, EMC, Dell EMC now, Vmware and their ecosystem partners. So a lot of enterprise infrastructure, a lot of opensource, and a lot of applications. But really there's three key components to why people bring theCUBE and what we deliver when we're there. One of them is just great content. The format that we have, the conversational tone, the way that it all works, we just get people to say stuff that you wouldn't ever ask them to say, especially on the customer reference ones. So the content is great and, you know, conferences are looking for more great content. The second really is our community and our distribution. You know we are a media company, we're super active in the community, we leverage a lot of social tools. We try to ask interviews and get information that's topical and evergreen and can be used often and over and over, and really run that out through a number of different channels and different formats. And then the third thing, which we didn't use to talk about as much, but we really do now, it's really the theater of our presence. There's something to bright lights and cameras when theCUBE is at an event. It's like, oh, theCUBE guys are here. And we hear it all the time, theCUBE guys are here. >> Everyone likes to be a star. >> Everybody wants to be a star. And it does a little bit of, I won't say validates for the greater good, but certainly within our community when we're at an event it's a signal that something's going on, something's exciting here, theCUBE guys are here, and we're covering it. And we hear that over and over. We have people stop us literally in an elevator to say, I look at your guys' upcoming sheet to make some decisions as to where I should plan my schedule time. And, or we've also heard, you know, I just wait and watch theCUBE all day, I can't go, I just have theCUBE running in the background. And get a taste of not necessarily what happened in all the breakouts and all the keynotes and all the other stuff, but we generally get all the same people who run all the keynotes. You're getting those same folks, but you're getting them in a conversational tone, talking often about many of the similar topics, it's just a different way to get that message across. >> So how do you grow the community further? So you talk about the community you have, you talk about the community that's at large right now. How are you looking to grow your user base and your community further? >> Right, so it's really kind of along two angles. One is kind of this natural bundling of subsets within our existing community. And that's like our Women in Tech coverage that we started years ago. Honestly, you know things were kind of slowing again in November, so we're like, you know, there's some great women, they're not getting highlighted, let's go out and do some Women in Tech interviews and integrate that. So that's kind of more of a horizontal play if you will. In terms of more vertical plays, we're trying to get a little bit out of the application infrastructure space and more into the app space. So autonomous vehicles, autonomous drones, commercial drones, we've done a lot of just app shows as companies do their own shows versus more of an industry show. So like I said, I mentioned QuickBooks Connect was fun. So really getting into some of these other areas that are more application specific and not just kind of infrastructure, per se which is the roots. >> So when you so application specific, are you looking at for example, you know Microsoft for example is a very large company. They have application space. Is that what you're looking for? >> Love to do some Microsoft shows, yeah, we have a Microsoft build and Ignite, they have a number of shows. >> What about Salesforce? Salesforce is doing some really interesting stuff around applications and community and the whole nine yards. >> Right, so before we didn't really go after Salesforce per se, 'cause it was just really big and we were just really small, we were trying to get a lot of our processes and structure in place. Since then we actually covered one Salesforce lightly a couple years back. A friend of mine, Lynn Voinovich, was a CMO and we covered the kick off. >> I love Lynn. >> You know Lynn? But we need to get back to Salesforce, that's one that we should be at, it's an important show, we should be there. >> Great, so let's have, let's kind of end here with a fun fact. So tell me a fun fact about your job or something that you do that perhaps people don't know about. >> A fun fact about my job. Just, it's just a lot. >> Lauren: Let's make it fun, not a lot of work. >> Basically our job is kind of like the proverbial duck, right? When we run production, we do about a hundred shows a year. There is, I always tell people it's like catering. There's about a thousand details that you kind of have some idea about, and there's a thousand ideas, there's a thousand issues that you have just no control. So being able to dance, being able to be like that proverbial duck that looks smooth, and cool, calm, and collected on top, but it's really pumping pretty hard underneath, you know we've got a lot of people, we've got a lot of back end processes, we have a lot of dancing that happens to try to make it really smooth for the guests, really smooth for the consumer. And we screw up and things happen. But I think we're pretty good, and we're constantly trying to improve our process. >> Great, thank you so much, and thank you for being here again. >> Thank you. >> I really appreciate your time. And we'll be back shortly on theCUBE with something that is coming up in about 15 minutes. (techno music)