>>Welcome back to the cubes cover dot com. Splunk annual conference >>Virtual this year. I'm john for >>your host of the cube as always we're being the best stories. The best guest to you and the best guest today is the ceo Doug merit of course, Top Dog. It's great to see you. Thanks for coming on to be seen. >>So nice. I can't believe it. We had a whole year without seeing each other. >>I love this conference because it's kind of like a studio taking over a full virtual studio multiple sets, cubes here. You have the main stage, you've got rooms upstairs, tons of virtual interactions. Great numbers. Congratulations. >>Thank you. Thank you. We were, we wanted this to be primarily live where we are live, primarily on site. Um, and we pivoted some private marketing team. How quickly they pivoted and I love the environment they've created as I know next year we will be always have virtual now we've all learned but will be on site, which is great. >>It's good to see kind of you guys telling the story a lot, a lot more stories happening and You know, we've been covering splint since 2012 on the Cube. I think longer than aws there was 2013 our first cube seeing Splunk emerge is the trend has been, it's new, it's got value and you operationalize it for customers. Something new happens. You operationalized for customers and it just keeps on the Splunk way, the culture of innovation. It just seems now more than ever. You guys were involved in security early 2015 I think that was the year we started kind of talking about it your first year and now it just feels like something bigger is right here in front of us. It's and people are trying to figure out multi cloud observe ability. We see that what that's a big growth wave coming. What's the wave that's happening? >>So uh the beauty of Splunk and the kind of culture and how we were born was we have this non structured backbone um what I would call the investigative lake where you just dump garbage into it and then get value out of it through the question asking which means you can traverse anywhere because you're not taking a point of view on the data it's usable all over the place. And that's how we went up in security. As we had the I. T. Systems administrators pinging that thing with with questions. And at that point in time the separate teams were almost always part of the I. T. Teams like hey can we ask questions that thing. It's like yeah go ahead. And also they got value. And then the product managers and the app dev guys started asking questions. And so a lot of our proliferation has been because of the underlying back bonus blank the ability for new people to come to the data and find value in the data. Um as you know and as our users know we have tried to stay very focused on the go to market basis on serving the technical triumphant the cyber teams, the infrastructure management, 90 ops teams and the abdomen devoPS teams and on the go to market basis and the solutions we package that is, we're trying to stay super pure to that. That's $90 billion of total addressable market. We're super excited will be well over three billion an error this year, which is amazing is 300 million when I started seven years ago so that 10 x and seven years is great. But three billion and 90 billion like we're all just getting going right now with those Corbyn centers. The were on top of what sean bison as we tell you about, hey, we've got to continue to focus on multi cloud and edge is really important. Machine learning is important. That the lever that we've been focused on for a long time that we'll continue to gain better traction on is making sure that we've got the right data plane and application platform layer so that the rest of the world can participate in building high quality reusable and recyclable applications so that operate operationalization that we have done officially around cyber it and devops and unofficially on a one off basis for marketing and supply chain and logistics and manufacturing that those other use cases can be packaged repeated, sold and supported by the people that really know those domains because we're not manufacturing experts. It's we're honored that portion BMW are using us to get operational insight into the manufacturing floor. But they lead that we just were there is the technical Splunk people to help bring that to life. But there are lots of firms out there, no manufacturing cold process versus the screed and they can create with these packages. They're appropriate for automotive, automotive versus paint versus wineries versus having that. I think the big Accelerant over the next 10 years response, we gotta keep penetrating our core use cases but it would be allowing our ecosystem and so happy Teresa Karlsson's here is just pounding the table and partners to take the other probably 90% of the market that is not covered by by our core market. >>Yeah, I think that's awesome. And the first time we get to the partner 1st and 2nd the rebranding of the ecosystem as it's growing. But you mentioned you didn't know manufacturing as an example where the value is being created. That's interesting because you guys are enabling that value, their adding that because they know their apps then they're experts. That's where the ecosystem is really gonna shine because if you can provide that enablement this control plane as you mentioned, that's going to feed the ecosystem. So the question I have for you is as you guys have become essentially the de facto control playing for most companies because they were using spring for a lot of other great reasons now you have set them up that way is the pattern to just keep building machine learning apps on top of it or more querying what's the what's the customer next level trends that you're seeing. >>So the two core focus areas that we will stay on top of is enriching that data platform and ensure that we continue to provide better at peace and better interfaces so that when people want to build a really interesting automotive parts, supply chain optimization app that they're able to do that, we've got the right A. P. S. We've got the right services, we've got the right separation between the application of platforms so they can get that done, we'll continue to advance that platform so that there's modernization capabilities and there's advertising capabilities and other pieces that they can make their business. The other piece that will stay very focused on is within the cyber realm within I. T. Ops within devops, ensuring that we're leveraging that platform, but baking ml and baking all the advanced edge and other capabilities into those solutions because the cyber teams as where you started with a You know, we really started reporting on cyber 2015, those guys have got such a hard job and while there's lots of people pretending like they're going to come in and serve them, it's the difficulty is there are hundreds of tools and technologies that the average C so deals with and the rate of innovation is not slowing down and those vendors that have a vested interest and I want to maintain my footprint and firewalls, I want to maintain an implant, I want to maintain. It's really hard for them to say, you know what? There are 25 other categories of tools and there's 500 vendors. You gotta play nicely with your competitors and know all those folks if you really want to provide the ml the detection, the remediation, The investigation capabilities. And that's where I'm really excited about the competition. The fake competition in many cases because like, yeah, bring it on. Like I've got 2000 engineers, all they do all day long is focused on the data layer and making sure that we're effective there and I'm not diverting my engineers with any other tasks that I've got a it's hard enough to do what we do in the day layers. Well, >>it's interesting. I just had some notes here, I had one data driven innovation you've been talking about since you've been here. We've been talking about data driven innovation, cybersecurity mentioned for many years, it's almost like the balance of you gotta have tools, but you gotta have the platform. If you have too many tools and no platform, then there's a mix match here and you get hung up with tools and these blind spots. You can't have blind spots, you can't have silos. This is what kind of everyone's pretty much agreeing on right now. It's not a debate. It's more like, okay, I got silos and I got blind spots. Well how do I solve >>the difficulty? And I touched a little bit of the sun my keynote of There are well over 60 and I was using 16 because DB engines categorizes 16 different database tools. But there's actually more if you go deeper. So there's different 16 different categories of database tools. Think relational database, data warehouse, ledger databases, graph database, et cetera over 16 categories those 350 vendors. That's not because we're all stupid in tech like a graph DB is different than a relational database, which is different than what we do with our stimulus index. So there's those categories that many vendors because they're trying to solve different problems within the swim lane that you are in which for us is this non structured, high volume difficult data to manage Now. The problem is how do you create that non broken that end to end view. So you can handle your use cases effectively. Um and then the customer is still going to do with the fact that we're not a relational database engine company. We're not a data warehousing company where we were beginning to use graph DB capabilities within our our solution sets. We're gonna lean on open source other vendors use the tool for the job >>you need. But I think that what you're thinking hitting on my like is this control plane idea. I want to get back to that because if you think about what the modern application developers want is they want devops and deVOps kind of one infrastructures codes there. But if I'm a modern developer, I just want to code, >>I don't want to configure >>the data or the infrastructure. So the data value now is so much more important for the developer, whether that's policy based innovation, get options, some people call it A I ops, these are big trends. This is fairly new in the sense of being mainstream. It's been around for a couple of years, but this time, how do you see the data being much more of a developer input. >>People talk about deVOps is a new thing when I was running on the HR products at Peoplesoft in 2000 and four, we had a deVOPS teams. So that is, you know, there's always been a group of people whether Disney or not that are kind of managing the manufacturing floor for your developers, making sure they got the right tools and databases and what's new is because the ephemeral nature of cloud, that app dev work and devops and everyone that surrounds those or is now 100% data driven because you have ephemeral services, they're popping up and popping down. And if you're not able to trap the data that are each one of those services are admitting and do it on a real time basis and a thorough, complete basis, you can't sample then you are flying blind and that's not gonna work when you've got a critical code push for a feature your customers demanding and if you don't get it out, your competitors are, you need to have assurance that you've done the right things and that the quality and and the actual deployment actually works And that's where what lettuce tubes or ability Three years ago as we roughly started doing our string of acquisitions is we saw that transition from a state full world where it was all transaction engine driven. I've got to insert transaction and engines in a code. Very different engineering problem to I've got to grab data and it's convoluted data. It's chaotic data. It's changing all the time. Well, jeez that sounds and latency >>issues to they're gonna be doing fast. >>I've got to do it. You literally millisecond by millisecond. You've got are are bigger customers were honored because of how we operate. Splunk to serve some of the biggest web properties in the in the globe and they're dealing with hundreds of terabytes to petabytes of data per day that are traversing these pipes and you've got to be able to extract metrics that entire multi petabyte or traces that entire multi pedal extreme and you can't hope you're guessing right by only extracting from portions of it because again, if you missed that data you've missed it forever. So for us that was a data problem, which is why we stepped in and >>other things That data problem these days, it's almost it's the most fun to talk about if you love the problem statement that we're trying to solve. I want to get your reaction something if you don't mind. I was talking to a C. So in the C. I. O. We have a conversation kind of off camera at an event recently and I said what's the biggest challenge that you have? Just curious? I asked him, it's actually it's personnel people are mad at each other. Developers want to go faster because there are ci cd pipeline is devops their coding. They're having to wait for the security groups in some cases weeks and days when they could do it in minutes they want to do it on the in the pipelines, shifting left as some call it and it's kind of getting in the way. So it's kind of like it's not they're not getting along very well uh meaning they're slowing things down. I can say something what they really said, but they weren't getting along. What's your reaction? Because that seems to be a speed scale problem. That's developer centric, not organizational, you've got organizational challenges and being slowed down. >>So uh while we all talk about this converted landscape and how exciting is going to be. You do have diametrically opposed metrics and you're never going to have, it's very difficult to get a single person to have the same allegiance to those diametrically a virgin metrics as you want. So you've got checks and balances and the reality of what the cyber teams need to be doing to ensure that you aren't just coding effective functions with the right delivery timeframe. But that's also secure is I think going to make the security team is important forever and the same thing. You can't just write sloppy code that consumes, that blows your AWS budget or G. C. P budget within the first week of deploying it because you've still got to run a responsible business. So there are different dimensions that we all have to deal with quality time and feature functionality that different groups represent. So we, I believe a converged landscape is important. It's not that we're gonna blow it up and one person is going to do it all if you've got to get those groups talking better and you've got to reduce cycle times now we believe it's plunk is with a common data plane, which is the backbone and then solutions built from that common data plane to serve those groups. You're lessening the lack of understanding and you're reducing the cycle time. So now I can look when I'm publishing the code. If it's done properly, is it also secure And the cyber teams can kind of be flying in saying, hey, wait, wait, wait, we just saw something in the data says we're not quite ready. I'm sorry. I know you want to push, you can't push now, but there'll be a data driven conversation and not this, you shouldn't be waiting a week or two weeks, like we can't operate that scale and you've got to address people with facts and data and logic and that's what we're trying to get done. And you >>guys have a good policy engine, you can put up that up into the pipeline. So awesome. That's great, great insight there. Thanks for sharing. Final question. Um looking back in your time since you've been Ceo the culture kind of hasn't changed at Splunk, it's still they have fun, hard charging laid back a little bit and public company now, he's still got to meet the numbers, but your growing business is good, but there's a lot more coming as a big wave coming talk about the Splunk culture. >>So the core elements of culture that I love that. I think all of us agree you don't want to change one where curiosity driven culture, our tool is an investigative tool, so I never want to lose. I think that threat of grit, determination, tenacity and curiosity is paramount in life and I think literally what we push out represents that and I want our people represent that and I think the fun element is really the quirkiness of the fund, like that is one of the things I love about Splunk but we are a serious company, we are in the data plane of tens of thousands of organizations globally and what we do literally makes a difference on whether they're successful or not. As organizations, we're talking about walmart is example And how one second latency can have a, have a 10% drop off in fulfillment of transaction for wal mart that's like a billion dollars a week if you cannot get their system to perform at the level it needs to so what we do matters and the change that we've been driving that I think is a great enhancement to the culture is as we are now tip into the 50% cloud company, you have the opportunity to measure millisecond by millisecond, second by second, minute by minute, hour by hour and that's a different level of help that you get. You can literally see patterns happening over the course of minutes within customers and that's not something we were born with. We were an on premise solution, we had beautiful tools and it was the C E O. S problem, the CSS problem um and their opportunity to get that feedback. Now we get that feedback so we're trying to measure that crunchiness, the fun, the cool part about Splunk with. We also have got to be very operationally disciplined because we carry a heavy responsibility set from our customers and we're in the middle of that as well as the world knows, we're halfway through our transition to be a cloud first company but I'm excited with the results I'm seeing, so I think curiosity and tenacity go with that operational rigor. Like we should all be growth mindset oriented and very excited about, Hey, can I improve? I guess there's some information that I need that I'm not getting that will make me serve my customers better and that is the tone and tenor. I want to cross all the Splunk of whether in HR legal or engineering or sales or we serve customers and we've got to be so excited every day about getting better feedback and how to serve them better. >>Doug. Thanks for coming on the Cuban, sharing that inside. I know you had to cancel your physical event, pulled off an exceptionally strong virtual event here in person. Thanks for having the Cuban. Thanks for coming on. >>Thank you for being here and I can't wait to do this in person. Next >>to mary the ceo of Splunk here inside the cube cube coverage continues stay with us for more. We've got more interviews all the rest of the day, Stay with us. I'm john for your host. Thanks for watching. Mm >>mm mhm >>mhm >>Yeah