>> from Burlingame, California It's the Cube covering Suma logic Illuminate 2019. Brought to You by Sumer Logic. >> Hey, welcome back, everybody. Jeffrey here with the Cube worth, assume a logic illuminate 2019 of it. It's at the Hyatt Regency San Francisco airport. About 809 100 people are second year. It's a 30 year of the event, excited to be here and watch it grow. We've seen a bunch of these things grow from little to bigger over a number of years, and it's always funded kind of beer for the zenith. We're excited to do it by our next guest. She's an analyst. It's Nancy Goering, senior analyst for 4 51 research. Nancy, great to see you. >> Thank you for having me. >> Absolutely so first off, Just kind of impressions of the event here. >> Yeah, good stuff. You know, like he's definitely trying to, you know, get on top of some of the big trends. You know, The big news here was their new Cooper nineties monitoring, also obviously kind of staying on the the leading edge of the cloud. Native Technologies. >> It's it's amazing how fast it's growing, you know, doing some research for this. Then I found some of your stuff out on the Internet and just one quote. I think it's from years ago, but just for people to kind of understand the scale, I think, he said, Google was launching four billion containers a week. Twitter had 12,000. Service is uber 4000. Micro service is Yelp and Justin 25 million data points per minute. I think this is like a two or three year old presentation. I mean, the scale in which the data is moving is astronomical. >> Yeah, well, I mean, if you think of Google launching four billion containers every week, they're collecting a number of different data points about a container spinning up about the operation of that container while it's alive about the container spinning down. So it's not even just four billion pieces of data. It's, you know, multiply that by 10 20 or many more. So, yeah, So the volume of operations dated that people are faced with is just, you know, out of this world, and some of that is beginning to get abstracted away, terms of what you need to look at. So, you know, Kubernetes is an orchestration engine so that's helping move things around. You still need to collect that data to inform automation tools, right? So even if you was, even if humans aren't really looking at it, it's being used to drive automation, right? It still has to be collected, >> right, And they're still configurations and settings and and dials. And it seems like a lot of the breaches that we hear about today are people just miss configuring something on us. It's human error. And so how do we kind of square the circle? Because the date is only growing. The quantity sources, the complexity, Yeah, the lack of structure. And that's before we had a I ot And now we got edge devices and they're all reporting in from from home. Yeah, crazy problem. It's >> really, I think, driving a lot of the investments in the focus and more sophisticated analytics, right? So that's why you're hearing a lot more about machine learning. And a I in this space is because humans can't just look at that huge volume >> of data and >> figure out what it means. So the development of machine learning tools, for instance, is gonna pull out a piece of data that's important. Here is the anomaly. This is the thing you should be paying attention to. Andi, obviously getting increasingly sophisticated, right? In terms of correlating data from different parts of your infrastructure in order to yet make sense of it, >> right? And then, Oh, by the way, they're all made up of micro service is a literal interconnected in AP eyes. The third party providers. Yeah. I mean, the complexity is ridicu >> and then, you know, and I've been actually thinking and talking a lot recently about organizational issues within companies that exacerbate some of these challenges. So you mentioned Micro Service is so ah, lot of times, you know, you've got Dev ops groups and an individual Dev Ops group is responsible for a or multiple. Micro service is right. They're all running, sort of autonomous. They're doing their own thing, right? So they could move quickly. But is there anybody overseeing the application that's made up of maybe 1000 Micro Service's? And in some cases, the answer is no. And so it may look like all the Micro Service's are operating well, but the user experience actually is not good, and no one really notices until the user starts complaining. So it's like things start. You know, you have to think about organizational things. Who's responsible for that, right? You know, if you're on a Dev ops team and your job has been to support the certain service's and not the whole, like who's responsible for the whole application and that's it's a challenge, it's something. Actually, in our surveys, we're hearing from people that they're looking for people that skill set, someone who understands how to look at Micro Service's as they work together to deliver a service, right? It's it's a It's a pain point. Shouldn't >> the project the product manager for that application would hopefully have some instances abilities to kind of what they're trying to optimize for? >> In some cases, they're not technical enough, right? A product manager doesn't necessarily have the depth to know that, or they're not used to using the types of tools that the Dev Ops team or the operations team would use to track the performance of an application. So sometimes it's just a matter of having the right tooling in front of them, >> and then even the performance I was like What do you optimizing four you optimized for security up the mind thing for speed are optimizing for yeah, you can optimize for everything if you got a stack rank order at some point in time. So that would also then drive in a different prioritization or the way that you look at those doctorsservices performance. Yeah, interesting. It's another big topic that comes up often is the vision of a single pane of glass in You know, I can't help but think is in my work day. You know how often I'm tabbing between, you know, sales force and email and slack and asana and, um, a couple of browsers air open. I mean, it's it's it's bananas, you know, it's no longer just that that email is the only thing that's open on my desk all day and only imagine the Dev Ops world. No, we saw just crazy complexity around again, managing all the micro service's of the AP eyes. So what's kind of the story? What are you seeing in kind of the development of that? And there's so many vendors now, and so many service is yeah, it's not just we're just gonna put in HB open view, and that's the standard, and that's what we're all right on. >> So if you're looking at it from the lens of of monitoring or observe ability or performance. Traditionally, you had different tools that looked at, say, different layers of a service, so you had a tool that was looking at infrastructure. Was your infrastructure monitoring tool. You had an application performance monitoring tool. You might have a network performance monitoring tool. You might have point tools that are looking just at the data base layer. But as things get more complicated, Azadliq ations are getting much more complex. Looking at that data in a silo tool tends to obscure the bigger picture. You don't understand when you're looking at the's separate tools how some piece of infrastructure might be impacting the application, for instance. And so the idea is to bring all of that operations data about the performance of an application in tow. One spot where you can run again, these more sophisticated analytics so that you can understand the relationship between the different layers of the application stack also horizontally, right? So how micro service's that are dependent on each other? How one micro service might be impacting the performance of another. So that's conceptually the idea behind having a single pane of glass. Now the execution can happen in a bunch of different ways, so you can have one vendor. There are vendors that are growing horizontally, so they're collecting data across the stack. And there's other vendors that are positioning themselves as that sort of central data repositories, so they may not directly collect all of that data. But they might in just some data that another monitoring vendor has collected. So there's an end. You know, there's there's always going to be good arguments for best of breed tools, right? So, you know, in most cases, businesses are not going to settle on just one monitoring tool that does it all. But that's conceptually the reason, right, and you want to bring all of this data together. However you get it, however, it's being collected so that you can analyze it and understand that big picture performance of a complicated application, >> right? But then, even then, as you said, you don't even want, you're not really monitoring the application performance per se. You're just waiting for the you're waiting for some of those needles to fall out of the haystack because you just you just can't get that much stuff. And you know, it's where do you focus your priority? You know what's most critical? What needs attention now. And if without a machine to help kind of point you in the right direction, you're gonna have a hard time finding that needle. >> And there's a lot of different approaches that are beginning to develop. So one is this idea of SL owes or service level objectives. And so, for instance, a really common service level objective that teams are looking at is Leighton. See, So this Leighton see of the service should never drop under whatever ah 100 milliseconds. And and if it does, I want to be alerted. And also if it drops below that objective for a certain amount of time, that can actually help you as a team. Allocate, resource is so if you're not living up to that service level objective, maybe you should shift some people's time toe working on improving the application instead of developing a new feature, right? So it can really help you prioritize your time because you know what? There was a time when people in operations teams or Dev. Ops teams had a really hard time, and they still d'oh figuring out which problems are important because you've always people always have a lot of performance problems going on. So which do you focus your time on? And it's been pretty opaque. It's hard to see. Is this performance impacting the bottom line of my business? Is this impacting? You know, my customers? Are we losing business over this? Like that's That's a really common question that people I can't answer, right? So there you people are beginning to develop these approaches to try to figure out how to prioritize work on performance problems. It's >> interesting because the other one that and some of you mentioned before is kind of this post incident review instead of a post boredom. And, you know, you talked about culture and words matter, and I think that's a really interesting take because it's it's it implies we're gonna learn, and we're gonna go forward. It's dead. Um, yeah, you know, we're gonna yell at each other and someone's gonna get blamed. That's exactly it. And we're going to move on. So, you know, how is that kind of evolved in. And how does that really help organizations do a better job? >> There's, I mean, there's there's much more of a focus on setting aside time to do that kind of analysis, right? So look at how we're performing as a team. Look at how we responded to an incident so that you can find ways that you can do better next time and some of that Israel tactical right? It's tweaking alerts. Did we not get an alert? You know, did we not even know this problem was happening? So maybe you build new alerts or sport get rid of a bunch of alerts that did nothing. You know, there's there's a lot you can learn on again to To your point, I think part of the reason people have started calling in a post Incident review instead of a postmortem is because yet you don't want that to be a session where people are feeling like Blaine. You know, this is my fault. I screwed up. I spent way too long on this, so I >> had to >> set things out properly. It's it's meant to be productive. Let's find the weak points and fill them right. Fill those gaps. >> It's funny you had another. There's another thing I found where you were talking about not not necessarily the Post Borden, but you know, people, people being much more proactive, much more, you know, thoughtful as to how they are going to take care of these things. And it is really more of a social cultural change unnecessarily. The technical piece that culture pieces. So so >> it is and especially, you know, right now there's a lot of focus on on tooling and that can cause some, you know, interesting issues. So, you know, especially in an organization that has really adopted Dev ops practices like the idea of a Dev Ops team is that it's very autonomous. They do what they do, what they need to do right to move fast and to get the job done. And that often includes choosing your own tools, but that that has created a number of problems, especially in monitoring. So if you have 100 Dev ops teams and they all have chosen their own, monitoring tools like this is not efficient, so it's not. It's not a good idea because those tools aren't talking to each other, even though they're micro service's that are dependent on each other. It's inefficient. From a business perspective. You've got all these relationships with vendors, and in some cases, with a single vendor, you might have 50 instances of the same monitoring tool that you know you have 50 accounts with them, like that's just totally inefficient. And then you've got people on a Dev ops, an individual, all the all the individual Dev ops teams have a person who's supposed to be the resident expert in these tools, like maybe you should share that knowledge across. But my point is, you get into the situation where you have hundreds of monitoring tools, sometimes 40 50 monitoring tools. You realize that's a problem. How do you address that problem? Because you're gonna have to go out and tell people you can't use this tool that you love. That helps you do your job that you chose. And so again, this whole cultural question comes out like, How do you manage that transition in a way that's gonna be productive? >> Thea other one that you brought up that was interesting is where the the sport team basically tells the business team you only have X number of incidents. We're gonna give you a budget. Yeah, exceed the budget. We're not going to help you. It's a really different way to think about prioritization. I >> don't necessarily think that's a great approach, but I mean, there was somebody who did that, but I think it's kind of it's kind of >> an interesting thing. And you talked about it in that. I think it was one of your presentations or speeches where, you know, it makes you kind of rethink. You know, why do we have so many incidents? Yeah, and there shouldn't be that many incidents, and maybe some of the responsibility should be shifted to think about why in the how and is more of a systemic problem than a feature problem or a bug, right? It's a broken code. So again, I think there's so many kind of cultural opportunities to rethink this. In a world of continuous development, continuous publishing and continuous pushing out of new code. Yeah, yeah, sure. All right. Nancy will. Thanks for taking a few minutes, and it's really great to talk to you. Thanks >> for having me. >> Alright. She's Nancy. I'm Jeff. You're watching the Cube where it's Uma Logic illuminate 2019. Thanks for watching. We'll see next time

>> Announcer: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey, welcome back, everybody. Jeff Frick here, with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency San Francisco Airport. About 800 people, 900 people, packed house in the keynote earlier this afternoon, really interesting space. And we're excited to have our next guest, kind of on the cutting edge of the IoT space on the consumer side. And he's Robert Parker, the CTO of Samsung SmartThings. Robert, great to see you. >> Hi, great to be here. >> Absolutely, so, before we get into the depth of the conversation, a little bit of a background on SmartThings. I was doing some research, getting ready for this, and the fact that it started as a Kickstarter a long time ago, not that long ago, and now is part of Samsung, a global electronics giant, what a fun adventure. >> Absolutely, I think it's been one of these things where it's great to be something where it's community-driven to begin with. So, Kickstarter was a big part of our launch, and we were one of the biggest Kickstarter launches at the time, really powered by our community around the website and early users. We got a lot of interest in IoT, and then moved on to the next stage of the vision, which is sort of encompassing all devices. And so, that meant we have more than 2,000 different Samsung devices on the platform now, which really allowed devices to talk to each other in ways that are really exciting, and that breadth has been a really great thing to be part of. >> Right, it's really funny, we went to the Samsung Developer Conference a couple years ago, and it was funny to see the living room guys fighting with the kitchen guys as to, what was the center? Is it the TV, or is it the refrigerator? Or is the the washing machine, for that bit? And Samsung's really got a foot in all those places. >> Absolutely, this is one of the things that the SmartThing platform has really enabled Samsung to transition across, as then it's no longer a conversation with the washing machine person or the dryer. All the devices are part of the SmartThings cloud. The SmartThings cloud is a one way that you can talk to Samsung devices, and it's an open ecosystem. So, it's not just Samsung devices, we're equally comfortable with manufacturers, any manufacturer, bringing those devices because home is a multi-vendor environment. You are not going to have all of your home from any one vendor. >> Right. >> And that's been one of the exciting parts of the vision, is that's been part, the open ecosystem has been something that's been part of the SmartThings story forever. To really immortalize that in a platform for Samsung has been a great transition. >> Right, so we're here at Sumo Logic Illuminate, and in preparing for this, I saw an interview with you, you made a really interesting comment. You said that we are a pervasive user of Sumo Logic, and then you said 90% of the team are using Sumo Logic. It's fascinating to me, because I think a lot of companies are chasing innovation, and I think one of the ways to get innovation is you enable more people to have more access to more data, and the tools to actually operate that data so that they can do their jobs and find cool ways to make improvements that aren't necessarily coming from the top down. It sounds like you guys have addressed that philosophy wholeheartedly. >> So, we absolutely have addressed it wholeheartedly, I think there was a lot of luck involved, and I wanted to sort of describe it, is that one of the things that worked well for us is people were excited to use Sumo more and more. They were more excited to see what they could do with the tool, what insights they could get, and so, you'd see your neighbor looking at it, and they'd look at a dashboard and they'd say, hey, can I do a little bit of that? And so much so, in the last year, we've seen a lot of unplanned value come out. So, a third of the value we got out of the Sumo in the past year was unplanned. It was things people didn't, processes they didn't know they would improve that really just came from this groundswell, from what I would call the community. And I think that's where you get, that unlocks a lot of the potential, because you really can't do things from sort of the planned high level. You really need people actively engaged and doing stuff you wouldn't expect. >> That's great. So, I want to talk a little bit about security. Security's a big topic here, it's a topic everywhere we go. And now, with connected devices, and connected keys, and connected doorbells, it seems like, oh, here we go again, and there's this constant talk that security's got to be baked in throughout the entire process. How are you guys dealing with security? It's obviously got to be right at the top of mind in terms of priorities while you're still connecting the sprinklers-- >> No, absolutely. >> And the thermostat and everything else. >> Security and privacy are both critical. I link in privacy even though you didn't ask about it, because, as you think about devices like cameras and things like this, privacy is top of mind. Also, in terms of regulation like GDPR. And so, because of that, we're really looking at both cases, the challenge for both security and privacy is, it really cuts through your whole organization and every process, and by the way, every process that every partner at the organization has, because we can have something that could be exploited from an attack through a customer service representative, that could be a person in the customer service organization, it could be how someone social engineered that. And so, what we've really needed is this kind of continuous intelligence that can span all of these processes, because in something like security, you're as good as your weakest process. And that doesn't mean that we don't focus on all the things that you talked about. We're industry-leading from a device perspective to have hardware baked-in keys and do things in the manufacturing process that lead to something that could be as secure as anything, but that's really the secret of using a lot of the continuous intelligence tools like Sumo, is that all of these could-bes aren't enough. You have to bring it together by having the intelligence that spans those processes to make sure that all of them are elevated, because at the end of the day, a security attack is going to attack your weakest thing, not your strongest thing. >> Right, so one of the other topics here that's talked about is this exponential growth of data, and you guys are part of the problem, 'cause now we got sensors, and light switches, and all these other things that are kickin' off data that, before, we weren't monitoring. And so, from an execution point of view at the company, when you've got so much data that you need to turn into information, and then actionable insight, you said Sumo's got some unique characteristics that allow you guys to get more leverage out of that platform. I wonder if you could dig into that a little bit more. >> And I'd like to reframe the data discussion a little bit, because a lot of people look at it as a problem, and I want to really talk about the opportunity side. So, part of that goes to our story, where we started off at Kickstarter with a few thousand users. We have over 50 million active users now. >> Jeff: 50 million? >> 50 million, our Android application in the Google Play Store had been been downloaded around 200 million times, so it gives you some idea of that size and scope. So, the data is an opportunity. There's an opportunity to build a customer base, to excite people, and to manage the processes that do that. And what's great now is that the availability of this data means that you can do it in more ways than you ever could before. The problem is, you need a tool that brings this together to be able to do that, and doing that well is difficult. Difficult both on the teams, and difficult because of the size, scope, and complexity of the systems because of the data that you mentioned. But the reason you want to do it is so that you can cross the chasm in terms of this opportunity. And more and more companies have this opportunity out in front of them. One of the things that's been really exciting about the cloud is it sort of democratized the entry point, but that wasn't good enough. Just because you could get in the game with three people, it's like making a, you can make a application in a mobile application store, either on Google's or on Apple's, really easily, that gets you in there. What you really need to do is manage the intelligence that goes from that, and for us, it's been really exciting to be able to take our decisions and make them data-driven. And we can do that by this explosion of data because it is there. >> Right, and the data is good, and I think we see data as an asset, it hasn't really hit balance sheets officially yet, but I think you see it in the valuations of companies like Google, and Facebook, and Amazon, right, who obviously have these crazy, giant multiples of their revenue, one, because they're growing, but two, because they have so much data. So, the market's kind of valuing that data without explicitly calling it out as a line item on the balance sheet. That said, not all data has the same value, not all data needs to be treated the same. And so, it really opens up an opportunity to say how do you tier it? So, you don't want to get, y'know, spend a ton of money on a piece of data and a big, fat stream that somebody leaves open on Amazon accidentally, suddenly have a big bill, and that maybe wasn't the most valuable, so. >> I'd actually double down on what you said, because for a typical company, one of the things that's also been true of the mega-scale companies that you pointed out with, is there's a lot of uniformity in their data. So, a company like Amazon, they have customer orders and they've got orders at this massive scale. A typical company doesn't look like that. Their data spread is more fragmented, smaller scale, and so, because of that, they want to make different decisions. And this is the same thing that has already happened in the storage area. People are really comfortable with storage that they're going to have in either disaster recovery, or long-term storage, and they want a very low-cost footprint around that. They've got their hot data, and they're much more willing to have that data managed differently, and at a higher cost rate, because it's much more valuable. We're looking for tools that span that, not just in storage, but in the ingestion, and the management, and the querying of that data, because, like you said, for most businesses, a lot of data is infrequently looked at, or looked at in response to a situation, so I'll never know which 10% of the data will be looked at. It'll be based on, oh, I got audited, or some other business event that happens. And so, this is one of the keys things that businesses are now struggling with. One of them is that, hey, they want to adopt these practices to become modern, or more modernized, but the second one is, to really be able to tier the data because they couldn't treat all the data as if it's hot data, just like they already figured that out for storage. >> Right, it's pretty interesting, 'cause it's been going on for storage forever, and we really saw it, I think, with the rise of Flash, which was super-high quality but super-expensive in the early days, that's coming down. And then, at the other end, we have the Glacier Storage and the cold storage just put it away. I want to get your last thoughts, last answer, Robert. As you look forward, I can't believe we're already in middle of September of 2019, it's fascinating to me that time flies so fast, but as you look forward, what are some of your priorities over the next year or so? How are you guys moving the ball down the field? >> One of the things that we're looking at was the data problem that you were talking about, if, really looking at our infrequent data, and being able to manage that effectively, both from the types of insights that we can get from that, so a lot of this starts to be better usage of machine learning, pattern recognition, AI, and so that we can, the ideal situation for us in that type of data is it got touched once, it got looked at once, and then we could understand how to action it later, that deferred action. And then, how to trigger that deferred action, as well as the tiering that we sort of talked about, that all data's not-- >> Created equal. >> Created equally, and so both those things are happening. Just to put some numbers on this, as why, is that we have 150 terabytes or so of data that is somewhat interesting to our business generated on a daily basis. >> 150 terabytes a day? >> 150 terabytes a day. >> That's interesting, that's the good stuff. >> And out of that, I'd say 10 terabytes is really actionable. And so, that gives you an idea. The other part is how that's growing, where a year ago, we would've been at maybe 60 terabytes of what I would've called this interesting data, and maybe five terabytes of immediately actionable. And so, this is following that, where that's exponentially growing, and it's a big number, so that's what we really think about. >> So, you scared? Because those curves, those curves get steep. >> It's the same way, we look at it as a huge opportunity, so what will happen is, either people will create value out of that for customers, in which case, actually, the opportunity, because it's at such a scale, it will be great for everyone, or, number two, it just becomes noise. And so, it isn't really something to get scared of, because worst case is, it became noise to you. We really want to be one of those people who are getting value out of it, and see the business growth and the consumer value growth out of that. I'm pretty optimistic that we'll be able to do it, because we really, if I look back three, four, years, we've just been able to figure out a way, and I think it will continue to do that. >> All right, well, Robert, thanks for taking a few minutes of your time and sharing the story, it's a great story. >> Thank you, appreciate being here. >> All right, he's Robert, I'm Jeff, you're watching theCUBE. We're at Sumo Logic Illuminate 2019. Thanks for watching, we'll see you next time.

>> Narrator: From Burlingame, California, it's theCUBE. Covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate 2019. It's at the Hyatt Regency San Francisco Airport. We're excited to be back. It's our second year, so third year of the show, and really, one of the key tenants of this whole event is the report. It's the fourth year of the report. It's The Continuous Intelligence Report, and here to tell us all about it is the VP of Product Marketing, Kalyan Ramanathan. He's, like I said, VP, Product Management of Sumo Logic. Great to see you again. >> All right, thank you, Jeff. >> What a beautiful report. >> Absolutely, I love the cover and I love the data in the report even more. >> Yeah, but you cheat, you cheat. >> How come? >> 'Cause it's not a survey. You guys actually take real data. >> Ah, that's exactly right, exactly right. >> No, I love them, let's jump into it. No, it's a pretty interesting fact, though, and it came out in the keynote that this is not a survey. Tell us how you get the data. >> Yeah, I mean, so as you already know, Sumo Logic is a continuous intelligence platform. And what we do is to help our customers manage the operations and security of the mission critical application. And the way we do that is by collecting machine data from our customers, and many of our customers, we have two thousand, our customers, they're all running modern applications in the cloud, and when we collect this machine data, we can grade insights into how are these customers building their applications, how are these customers running and securing their application, and that insight is what is reflected in this report. And so, you're exactly right, this is not a survey. This is data from our customers that we bring into our system and then what we do is really treat things once we get this data into our system. First and foremost, we completely anonymize this data. So, we don't-- >> I was going to say Let's make sure we have to get that out. >> Yes, absolutely, so we don't have any customer references in this data. Two, we genericize this data. So, we're not looking for anomalies. We are looking for broad patterns, broad trends that we can apply across all of our customers and all of these enterprises that are running modern mission critical applications in the cloud. And then three, we analyze ten weeks to Sunday. We look at these datas, we look at what stands out in terms of good sample sizes, and that's what we reflect in this report. >> Okay, and just to close a loop on that, are there some applications that you don't include? 'Cause they're just legacy applications that're running on the cloud that doesn't give you good information, or you're basically taking them all in? >> Yeah, it's a good point, I mean we collect all data and we collect all applications, so we don't opt-in applications or out applications for that matter because we don't care about it. But what we do look for is significant sample size because we want to make sure that we're not talking about onesie-twosie applications here or there. We're looking for applications that have significant eruption in the cloud and that's what gets reflected in this report. >> Okay, well, let's jump into it. We don't have time to go through the whole thing here now, but people can get it online. They can download their own version and go through it at their leisure. Biggest change from last year as the fourth year of the report. >> Yeah, I mean, look, there are three big insights that we see in this report. The first one is, while we continue to see AWS rule in the cloud and that's not surprising at all, we're starting to see pretty dramatic adoption of multi-cloud technologies. So, two years ago, we saw a smidgen of multi-cloud in this report. Now, we have seen almost a 50% growth year over year in terms of multi-cloud adoption amongst enterprises who are in the cloud, and that's a substantial jump albeit from a smaller baseline. >> Do you have visibility if those are new applications or are those existing ones that are migrating to different platforms? Are they splitting? Do you have any kind of visibility into that? >> Yeah, I mean, it's an interesting point, and part of this is very related to the growth of Kubernetes that we also see in this report. What ypu've seen is that, in AWS itself, Kubernetes adoption has gone up significantly, what's even more interesting is that, as you think about multi-cloud adoption, we see a lot of Kubernetes, Kubernetes as the platform that is driving this multi-cloud adoption. There is a very interesting chart in this report on page nine. Obviously, I think you guys can see this if they want to download the report. If you're looking at AWS only, we see one in five customers are adopting Kubernetes. If you're looking at AWS and GCP, Google Cloud Platform, we see almost 60% of our customers are adopting Kubernetes. Now, when you put in AWS-- >> One in five at AWS, 60% we got Google, so that means four out of five at GCP are using Kubernetes and bring that average up. >> And then, if you look at AWS, Azure, and GCP, now you're talking about the creme de la creme customers who want to adopt all three clouds, it's almost 80% adoption of Kubernetes, so what it tells you is that Kubernetes has almost become this new Linux in the cloud world. If I want to deploy my application across multiple clouds, guess what, Kubernetes is that platform that enables me to deploy my application and then port it and re-target it to any other cloud or, for that matter, even an on-prem environment. >> Now, I mean, you don't see motivation behind action, but I'm just curious how much of it is now that I have Kubernetes. I can do multi-cloud or I've been wanting to do multi-cloud, and now that I have Kubernetes, I have an avenue. >> Yeah, it started another question. What's the chicken and what's the egg right here? My general sense, and we've debated this endlessly in our company, our general sense has been that the initiative to go multi-cloud typically comes top down in an organization. It's usually the CIO or the CSO who says, you know what, we need to go multi-cloud. And there are various reasons to go multi-cloud, some of which you heard in our keynote today. It could be for more reliability, it could be for more choice that you may want, it could be because you don't want to get logged into any one cloud render, so that decision usually comes top down. But then, now, the engineering teams, the ops teams have to support that decision, and what these engineering teams and these ops teams have realized is that, if they deploy Kubernetes, they have a very good option available now to port their applications very easily across these various cloud platforms. So, Kubernetes, in some sense, is supporting the top down decision to go multi-cloud which is something that is shown in spades as a result of this report. >> So, another thing that jumped out at me, or is there another top trend you want to make sure we cover before we get in some of those specifics? >> I mean we can talk to-- >> Yeah, one of them, one of them that jumped out at me was Docker. The Docker adoption. So, Docker was the hottest thing since sliced bread about four years ago, and is the shade of Kubernetes, not that they're replacements for one another specifically, but it definitely put a little bit of appall in the buzz that was the Docker, yet here, the Docker utilization, Docker use is growing year over year. 30%! >> I'll be the first one to tell you that Docker adoption has not stalled at all. This is shown in the report. It's shown in customers that we talk to. I mean, everyone is down the path of containerizing their application. The value of Docker is indisputable. That I get better agility, that I get better portability with Docker cannot be questioned. Now, what is indeed happening is that everyone who is deploying Docker today is choosing a orchestration technology and that orchestration technology happens to be Kubernetes. Again, Kubernetes is the king of the hill. If I'm deploying Docker, I'm deploying Kubernetes along with it. >> Okay, another one that jumped out at me, which shouldn't be a big surprise, but I'm a huge fan of Andy Jassy, we do all the AWS shows, and one of always the shining moments is he throws up the slide, he's got the Customer slide. >> There you go. >> It's the Services slide which is, in like, 2.6 font across a 100-foot screen that fills Las Vegas, and yet, your guys' findings is that it's really: the top ten applications are the vast majority of the AWS offerings that are being consumed. >> Yep, not just that. It's that the top services in AWS are the infrastructure-as-a-service services. These are the core services that you need if you have to build an application in AWS. You need ECDO, I need Esri, I need identity access management. Otherwise, I can't even log into AWS. So, this again goes back to that first point that I was making was that multi-cloud adoption is top of mind for many, many customers right now. It's something that many enterprises think of, and so, if I want to indeed be able to port my application from AWS to any other environment, guess what I should be doing? I shouldn't be adopting every AWS service out there because if I frankly adopted all these AWS services, the tentacles of the cloud render are just so that I will not be able to port away from my cloud render to any other cloud service out there. So, to a certain extent, many of the data points that we have in this report support the story that enterprises are becoming more conscious of the cloud platform choices that they are making. They want to at least keep an option of adopting the second or the third cloud out there, and they're consciously, therefore choosing the services that they are building their applications with. >> So, another hot topic, right? Computer 101 is databases. We're just up the road from Oracle. Oracle OpenWorld's next week. A lot of verbal jabs between Oracle and some of the cloud providers on the databases, et cetera. So, what do the database findings come back as? >> I mean, look at the top four databases: Redis, MySQL, Postgres, Mongo. You know what's common across them? They're all open-source. They're all open-source database, so if you're building your application, find standard components that you can then build your application on, whether it's a community that you can then take and move to any other cloud that you want to. That's takeaway number one. Takeaway number two, look at where Oracle is in this report. I think they're the eighth database in the cloud. I actually talked to a few customers of ours today. >> Now, are you sampling from Oracle's cloud? Is that a dataset? >> No, this is-- >> Yes, right, okay. So, I thought I want to make sure. >> And, if AWS is almost the universe of cloud today, we can debate at some bids, but it is close enough, I'd say, it tells you where Oracle is in this cloud universe, so our friends at Redwood City may talk about cloud day in and day out, but it's very clear that they're not making much of intent in the cloud at this point. >> And then, is this the first year the rollup of the type of database that NoSQL exceeded relational database? >> No, I mean, we've been doing this for the last two years, and it's very clear that NoSQL is ahead of SQL in the cloud, and I think the way we think about it is primarily because, when you are re-architecting your applications in the cloud, the cloud gives you a timeline, it gives you an opportunity to reconsider how you build out your data layer, and many of our customers are saying NoSQL is the way to go. The scalability demands, the reliability demands, so if my application was such that I now have the opportunity to rethink and redo my data layer, and frankly, NoSQL is winning the game. >> Right, it's winning big time. Another big one: serverless, Lambda. Actually, I'm kind of surprised it took so long to get to Lambda 'cause we've been going to smaller atomic units of compute, store, and networking for so, so long, but it sounds like, looks like we're starting to hit some critical mass here. >> Yeah, I mean, look, Lambda's ready for primetime. I mean we have seen that tipping point out here. Almost one in three customers of ours are using Lambda in production environments. And then, if you cast a wider net, go beyond production and even look at dev tests, what we see is that almost 60% of Sumo Logic's customers, and if you look at 2,000 customers, that's a pretty big sample size. Almost 60% of enterprises are using Lambda in some way, shape, or form. So, I think it's not surprising that Lambda is getting used quite well in the enterprise. The question really is: what are these people doing with Lambda? What's the intent behind the use of Lambda? And that's where I think we have to do some more research. My general sense, and I think it's shared widely within Sumo Logic, is that Lambda's still at the edges of the application. It's not at the core of the application. People are not building your mission critical application on Lambda yet because I think that that paradigm of thinking about event-driven application is still a little foreign to many organizations, so I think it'll take a few more years for an entire application to be built on Lambda. >> But you would think, if it's variable demand applications, whether that's a marketing promotion around the Super Bowl or running the books at the end of the month, I guess it's easy enough to just fire up the servers versus doing a pure Lambda at this point in time, but it seems like a natural fit. >> If you're doing the utility type application and you want to start it and you want to kill it and not use it after an event has come and gone, absolutely, Lambda's the way to go. The economics of Lambda. Lambda absolutely makes sense. Having said that, I mean, if you're to build a true mission critical application that you're going to be keeping on for a while to come, I'm not seeing a lot of that in Lambda yet, but it's definitely getting there. I mean we have lots of customers who are building some serious stuff on Lambda. >> Well, a lot of great information. It's nice to have the longitudinal aspect as you do this year over year, and again, we're glad you're cheating 'cause you're getting good data. >> (chuckles) >> (laughs) You're not asking people questions. >> Yeah, I mean, I'd like to finish out by saying this is a report that Sumo Logic builds every year, not because we want to sell Sumo Logic. It's because we want to give back to our community. We want our community to build great apps. We want them to understand how their peers are building some amazing mission critical apps in the cloud and so, please download this report, learn from how your peers are doing things, and that's our only intent and goal from this report. >> Great, well, thanks for sharing the information and a great catch-up, nice event. >> All right, thank you very much, Jeff. >> All right, he's Kalyan, I'm Jeff. You're watching theCUBE. We're at Sumo Logic Illuminate 2019. Thanks for watching, we'll see you next time. (upbeat electronic music)

>> Narrator: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019! Brought to you by Sumo Logic. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Sumo Logic Illuminate 2019 event. It's at the Hyatt Regency San Francisco Airport, about eight hundred, nine hundred people, our second year. It's the third year of the event. Excited to be here and watch it grow. We've seen a bunch of these things grow from little to big over a number of years and it's always fun to kind of be here for the zenith. We're excited to be joined by our next guest, she's an analyst. It's Nancy Gohring, Senior Analyst for 451 Research. Nancy, great to see you. >> Thank you, thanks for having me. >> Absolutely. So first off, just kind of impressions of the event here. >> Yeah, good stuff, you know? Definitely trying to, you know, get on top of some of the big trends, you know, the big news here was their new Kubernetes monitoring tool. So obviously kind of staying on the leading edge of the cloud-native technologies. >> It's amazing how fast it's growing, you know. Doing some research for this event, I found some of your stuff out on the internet, and just one quote, I think it's from years ago, but just for people to kind of understand the scale, I think you said Google was launching four billion containers a week, Twitter had twelve thousand services, Uber four thousand microservices, Yelp ingesting twenty-five million data points per minute, and I think this is a two or three year old presentation, I mean, the scale in which the data is moving is astronomical. >> Yeah, well if you think of Google launching four billion containers every week, they're collecting a number of different data points about a container spinning up, about the operation of that container while it's alive, about the container spinning down. So it's not even just four billion pieces of data, it's, you know, multiply that by ten or twenty or many more. So yeah, so the volume of operations data that people are faced with, is just, you know out of this world. And some of that is beginning to get abstracted away in terms of what you need to look at so you know Kubernetes is an orchestration engine so that's helping move thing around. You still need to collect that data to inform automation tools, right, so even humans aren't really looking at it, it's being used to drive automation. >> Right. >> It still has to be collected. >> Right. And there's still configurations and settings and dials and it seems like a lot of the breaches that we hear about today are just people misconfiguring something on AWS >> Yeah, it's human error. >> It's human error. And so how do we kind of square the circle cause the data's only growing the quantity, the sources, the complexity, the lack of structure and that's before we add IOT and now we have edge devices and they're all reporting in from home. >> Yeah >> Crazy problems. >> It's really, I think, driving a lot of the investments and the focus in more sophisticated analytics, right, so that's why you're hearing a lot more about machine learning and AI in this space. It's because humans can't just look at that huge volume of data and figure out what it means. So, the development of machine learning tools, for instance, is going to pull out a piece of data that's important. Like, here's the anomaly, this is the thing you should be paying attention to. And then obviously getting increasingly sophisticated, right, in terms of correlating data from different parts of your infrastructure in order to make sense of it. >> Right. And then, oh, by the way, they're all made up of microservices that are all interconnected and API is the third party providers >> Yeah. >> I mean the complexity is ridiculous. >> Yeah, and then, you know, and I've been actually thinking and talking a lot recently about organizational issues within companies that exacerbates some of these challenges. So you mentioned microservices. So, a lot of times, you know, you've got DevOps groups and an individual DevOps group is responsible for a, or multiple, microservices, right. They're all running sort of autonomous. They're doing their own thing, right, so that they can move quickly. But is there anybody overseeing the application that's made up of maybe a thousand microservices? And in some cases the answer is "no". And so it may look like all the microservices are operating well, but the user experience actually is not good. And no one really notices until the user starts complaining. So, it's like things start, you know you have to think about organizational things. Who's responsible for that, right? If you're on a DevOps team and your job as been to support these certain services and not the whole, like, who's responsible for the whole application? >> Right. >> And that's, it's a challenge. It's something, actually, in our surveys, we're hearing from people that they're looking for people, that skill set, someone who understands how to look at microservices as they work together to deliver a service, right, it's a pain point. >> Shouldn't the project, or the product manager for that application would hopefully have some visibilities to kind of what they're trying to optimize for. >> In some cases they're not technical enough, right, a product manager doesn't necessarily have the depth to know that. Or they're not used to using tools that the DevOps team or the operations team would use to track the performance of an application. >> Right. >> So sometimes it's just a matter of having the right tooling in front of them >> And then even the performance. It's like, what are you optimizing for? Are you optimizing for security? Are you optimizing for speed? Are you optimizing for... >> Experience... >> You can't optimize for everything. You've got to stack rank order at some point in time, so that would also then drive in a different prioritization or the way that you look at those microservices' performance. >> Yeah, yeah. >> Interesting. So another big topic that comes up often is the vision of a single pane of glass. And, you know, I can't help but think as in my work day how often I'm tabbing between you know, sales force, and email, and slack, and Asana, and a couple of browsers are open. I mean, it's bananas, you know. It's no longer just that email is the only thing that's open on my desk all day. >> Yeah. >> And then you can only imagine the DevOps world that we saw just crazy complexity around, again, managing all the microservices, the APIs, so what kinds of, sort of, what are you seeing in kind of the development of that? And there's so many vendors now, and so many services. >> Yeah. >> It's not just, we're just going to put in HP open view and that's the standard and that's what we're all on. >> So if you're looking at it from the lens of monitoring or observability or performance, traditionally you had different tools that looked at, say, different layers of a service. So you had a tool that was looking at infrastructure - it was your infrastructure monitoring tool. You had an application performance monitoring tool. You might have a network performance monitoring tool. You might have point tools that are looking just at the data base layer. But as things get more complicated, as applications are getting much more complex, looking at that data in a silo tool tends to obscure the bigger picture. You don't understand when you're looking at the separate tools how some piece of infrastructure might be impacting the application, for instance. And so, the idea is to bring all of that operations data about the performance of an application into one spot where you can run, again, these more sophisticated analytics so that you can understand the relationship between the different layers of the application stack, also horizontally, right, so, how microservices that are dependent on eachother how one microservice might be impacting the performance of another, so that's conceptually the idea behind having a single pane of glass. Now the execution can happen in a bunch of different ways. So you can have one vendor, there are vendors that are growing horizontally, so they're collecting data across the stack. There's other vendors that are positioning themselves as that sort of central data repository. So they may not directly collect all of that data, but they might ingest some data that another monitoring vendor has collected. So, there's, and, you know, there's always going to be good arguments for best of breed tools right, so, you know, in most cases, businesses are not going to settle on just one monitoring tool that does it all. But that's conceptually the reason, right, is you want to bring all of this data together however you get it, however it's being collected, so that you can analyze it and understand that "big picture" performance of a complicated application. >> Right. But then, even then, as you said, you don't even want to, you're not really monitoring the application performance per se, you're just waiting for the, you're waiting for some of those needles to fall out of the haystack, cause you just, you just can. There's so much stuff. And you know, it's where do you focus your priority. You know, what's most critical, what needs attention now. >> (Nancy) Yeah. >> And if, without a machine to help kind of, point you in the right direction, you're going to have a hard time finding that needle. >> Yeah, and there's a lot of different approaches that are beginning to develop. And one is this idea of SLO's, or Service Level Objectives. And so, for instance a really common Service Level Objective that teams are looking at is latency. So, the latency of the service should never drop under whatever- a hundred milliseconds, and if it does, I want to be alerted. And also, if it drops below that objective for a certain amount of time that can actually help you as a team allocate resources. So, if you're not living up to that Service Level Objective, maybe you should shift some people's time to working on improving the application instead of developing a new feature. Right? >> (Jeff) Right. >> So it can really help you prioritize your time because you know what? There was a time, people in operations teams, or DevOps teams, had a really hard time, and they still do, figuring out which problems are important. 'Cause you've always, people always have a lot of performance problems going on. So which do you focus your time on? And it's been pretty opaque. It's hard to see, is this performance impacting the bottom line in my business? Is this impacting, you know, my customers? Are we losing business over this? Like, that's, that's a really common question that people can't answer. >> Right. >> So, yeah, people are beginning to develop these approaches to try to figure out how to prioritize work on performance problems. >> It's interesting 'cause the other one that you've mentioned before, kind of this post incident review instead of a post mortem and you know, you talked about culture, and "words matter" >> (Nancy) Yeah. >> And I think that's a really interesting take because it's, it implies, we're going to learn, and we're going to go forward as opposed to "it's dead". >> (Linda) Yeah. >> And, you know, we're going to yell at eachother, and someone's going to get blamed... >> (Linda) That's exactly it... >> And we're going to move on. So, you know, how has that kind of evolved and how does that really help organizations do a better job? >> There's, I mean, there's much more of a focus on setting aside time to do that kind of analysis, right? So look at how we're performing as a team. Look at how we responded to an incident so that you can find ways that you can do better next time. And some of that is real tactical, right, it's tweaking alerts. Did we not get an alert? You know, did we not even know this problem was happening? So maybe you build new alerts or get rid of a bunch of alerts that did nothing. You know, there's a lot you can learn and again, to your point, I think part of the reason people have started calling it a post incident review instead of a post mortem is because, yeah, you don't want that to be as session where people are feeling like blame, you know, this is my fault, I screwed up, I spent way too long on this, or I hadn't set things up properly. It's meant to be productive. >> Right. >> Let's find the weak points and fill them. Right? Fill those gaps. >> It's funny you had another, there was another thing I found, you were talking about not, not necessarily the post mortem but, you know, people being much more pro-active, much more, you know, thoughtful as to how they are going to take care of these things. And it is really more of a social, cultural change than necessarily the technical piece. That culture piece is so, so important. >> It is, and especially, you know, right now there's a lot of focus on tooling and that can cause some, you know, interesting issues. So you know, especially in an organization that has really adopted DevOps practices like, the idea of a DevOps team is that it's very autonomous. They do what they need to do, right, to move fast and to get the job done and that often includes choosing your own tools. But that has created a number of problems especially in monitoring. So if you have a hundred DevOps teams and they all have chosen their own monitoring tools, like, this is not efficient. So it's not a good idea because those tools aren't talking to each other, even though they're microservices that are dependent on each other. It's inefficient from a business perspective. You've got all these relationships with vendors and in some cases with a single vendor. You might have fifty instances of the same monitoring tool that, you know, you have fifty accounts with them. Like that's just totally inefficient. And then you've got people on a DevOps and individual, all the individual DevOps teams have a person who's supposed to be the resident expert in these tools, like, maybe you should share that knowledge across... But my point is you get into this situation where you have hundreds of monitoring tools. Sometimes forty, fifty monitoring tools. You realize that's a problem. How do you address that problem? 'Cause you're going to have to go out and tell people you can't use this tool that you love, that helps you do your job, that you chose. So again this whole cultural question comes up. Like, how do you manage that transition in a way that's going to be productive? >> The other one that you brought up that was interesting was where the support team basically tells the business team you only have X-number of incidents, we're going to give you a budget. (laughs) >> Yeah. >> If you exceed the budget we're not going to help you. It's a really different way to think about prioritization... >> Yeah, I don't necessarily think that's a great approach. I mean there was somebody who did that but like... >> But I think its kind of, it's kind of an interesting thing. And you talked about it in that I think it was one of your presentations or speeches where, you know, it makes you kind of re-think, you know, why do we have so many incidents? >> Yeah. >> And there shouldn't be that many incidents. And maybe some of the responsibility should be shifted to think about why, and the how, and is it more of a systemic problem than a feature problem, or a bug, or... >> Right >> A piece of broken code, so again I think there's so many, kind of, cultural opportunities to re-think this, in this world of continuous development, continuous publishing, continuous pushing out of new code. >> Yeah, yeah. For sure. (laughs) >> Alright Nancy, well thanks for taking a few minutes and it was really great to talk to you. >> Thanks for having me. >> Alright, she's Nancy, I'm Jeff. You're watching theCUBE, where it's Sumo Logic Illuminate 2019. Thanks for watching We'll see you next time (electonic music)

>> from Burlingame, California It's the Cube covering Suma logic Illuminate 2019. Brought to You by Sumer Logic >> Hey, welcome back, everybody. Jeffrey here with the Cube were at the higher Regency San Francisco Airport at Suma Logic, Illuminate, 2019 were here last year for our first time. It's a 30 year the show. It's probably 809 100 people around. 1000 packed house just had the finish. The keynote. And we're really excited to have our first guest of the day. Who's been here since the very beginning is Bruno Critic, the founding VP of product and strategy for Suma Logic, you know, great to see you. Likewise. Thank you. So I did a little homework and you're actually on the cube aws reinvent, I think 2013. Wow. How far has the cloud journey progressed? Since efforts? I think it was our first year at reinvented as well. >> That's the second year agreement, >> right? So what? What an adventure. You guys made a good bet six years ago. Seems to be paying off pretty well. >> It really has been re kind of slipped out that the cloud is gonna be a real thing. Put all of our bats into it and have been executing ever since. And I think we were right. They think it is no longer a question. Is this cloud thing gonna be re alarm enterprise gonna adopt it? It's just how quickly and how much. >> Right? Right. But we've seen kind of this continual evolution, right? Was this jump into public cloud? Everybody jumped in with both feet, and now they're pulling back a little bit. But now really seen this growth of the hybrid cloud Big announcement here with Antos and Google Cloud Platform and in containers. And, you know, the rise of doctor and the rise of kubernetes. So I don't know, a CZ. You look a kind of the evolution. A lot of positive things kind of being added to the ecosystem that have helped you guys in your core mission. >> That's right. Look, you know, five years ago, which is such a short time, But yet instead of the speed of the technology adoption and change, you know it's in It's in millennia. What's happened over the last few years is technology stocks have changed dramatically. We've gone from okay, we can host some v ems in the cloud and put some databases in the cloud. So we're now building micro service's architecture, leveraging new technologies like Kubernetes like Serverless Technologies and all the stuff And, you know, some one of the fastest growing technologies that's being adopted by some village custom base, actually the fastest kubernetes and also the fastest customer segment growing customer segments. ImmuLogic is multi clog customers, basically that sort of desire by enterprise to build choice into their offerings. Being able to have leverage over the providers is really coming to fruition right now, >> right? But the multi cloud almost it makes a lot of sense, right, because we're over and over. You want to put your workload in the environment that supposed appropriate for the workload. It kind of. It kind of flipped the bid. It was no longer. Here's your infrastructure. What kind of APs can you build on it? Now here's my app. Where should it run that maybe on Prem it may be in a public cloud. It may be in a data center, so it's kind of logical that we've come into this this hybrid cloud world that said, Now you've got a whole another layer of complexity that that's been added on. And that's really been a big part of the rise of kubernetes. >> That's right. And so, as you're adopting service's that are not equal, right, you have to create a layer that insulate you from those. Service is if you look a tw r continues intelligence report that we just announced today. You will also see that how customers and enterprise are adopting cloud service is is they're essentially adopting the basic and core compute storage network, and database service is there's a long, long tail of service that are very infrequently adopted. And that is because enterprise they're looking for a way to not get to lock Tintin into anyone. Service provider kubernetes Give them Give them that layer of insulation with in thoughts and other technologies like that, you are now able to seamlessly manage all those workloads rather there on your on premise in AWS in G C. P. In azure or anywhere else, >> right? So there's so much we can unpack. You're one of the things I want to touch on which you talked about six years ago, but it's even more thing appropriate. Today is kind of this scale this exponential growth of data on this exponential scale of complexity. And we, as people, has been written about by a lot of smart people, and I, we have a real hard time. Is humans with exponential growth. Everything's linear. Tow us. So as you look at this exponential growth and now we're trying to get insights. Now we've got a I ot and this machine a machine data, which is a whole another multiple orders of magnitude. You can't work in that world with a single painted glass with somebody looking at a dashboard that's trying to find a yellow light that's earned it. I'm going to go read. You don't have analytics. Your hose. >> That's right. This is no longer world of Ding dong lights, right? You can just like to say, Okay, red, green, yellow. The as sort of companies go digital right? Which is driving this growth in data, you know? Ultimately, that data is governed by Moore's law. Moore's law says machines are gonna be able to do twice as much every 18 to 24 months. Well, that guess what? They're gonna tell you what they're doing twice as much. Every 18 to 24 months, and that is an exponential growth rate, right? The challenge that is, budgets don't grow at that rate, either, right? So budgets are not exponentially growing. So how do you cope with the onslaught of this data? And if you're running a digital service, right, if you're serving your customers digital generating revenue through digital means, which is just about every industry. At this point in time, you must get that data because if you don't get the data, you can't run your business. This data is useful not just in operations and security. It's useful for general business abuse, useful in marketing and product management in sales and their complexity. And the analytics required to actually make sense of that data and serve it to the right constituency in the business is really hard. And that has been whatever we have been trying to solve, including this economics of machine. Dad and me talked about it today. Keynote. We're trying t bend the cost curve >> Moore's law >> yet delivered analytics that the enterprise can leverage to really not just operate an application but run their business >> right. So let's talk about this concept of observe ability. You've written box about it. When you talk to people about observe ability, what should they be thinking about? How are you defining it? Why is it important? >> It's great question, So observe ability right now is being defined as a technique right. The simplest way to think about it is people think, observe a witty I need to have these three data sets and I have observed ability. And then you have to ask yourself a question. First of all, what is Observe ability and why does it matter? I think there's a a big misconception in the market how people adopt this is that they think, observe abilities the end. But it isn't observe. Ability is the means of achieving a goal. And what we like to talk about is what is the goal? Observe, observe ability right now. Observe abilities talked about strictly in the devil up space, right? Basically, how am I going to get obs Erv City into an application? And it's maybe runtime how it's running, whether it's up and performance. The challenge with that is that is a pigeon pigeon hole view off, observe ability, observe ability. If you think about it, we talk about objectives during observe ability. Operability tau sa two ns Sorry could be up time in performance. Well, guess what a different group like security observe. Ability is not getting breached. Understanding your compliance posture. Making sure that you are compliant with with regular to re rules and things like that observe ability to a business person to a product manager who's who owns a P N. L. On some product is how are my users using this product powers my application being adopted where users having trouble. What are they and where's the user experience? Poor right? So all of this data is multifaceted and multi useful as multi uses and observing Tow us. Is his objectives driven? If you don't know what your object it is, observe. Ability is just a tool. >> I love that, you know, because it falls under this thing We talked about off the two, which is, you know, there's data, right, and then there's information in the data and then, but it is a useful information because it has to be applied to something that's right in and of itself. It has no value, and what you're talking about really is getting the right data to the right person at the right time, which kind of stumbled into another area, which is how do you drive innovation in an organization? In one of the simple concepts is democratization. Get more people more than data more than tools to manipulate the data. Then piano manager is gonna make a different decision based on different visibility than Security Person or the Dev Ops person. So how is how is that evolving? Where do you see it going? Where was it in the past? And you know, I think he made it interesting or remain made. Interesting thing in the keynote where you guys let your software be available to everyone. And there was a lot of people talking about giving Maur. People Maur access to the tools and more of the data so that they can start to drive this innovation >> abuse of an example of one of the one of the sort of aspects of when we talk about continued continues intelligence. What do we mean? So this concept of agile development didn't evolve because people somehow thought, Hey, why don't we just try to push court production all the time? Break stuff all the time. What's the What's the reason why that came about? It did not come about because somehow somebody decided so better. Software development model It's because cos try to innovate faster, so they they wanted Toa accelerate. How they deliver digital product and service is to their customers. And what's facilitates that delivery cycle is the feedback loop. They get out of their data. They push code early. They observed the data. They understand what it's telling them about how their customers are using their products, and service is what products are working with or not. And they're quickly baking that feedback back into their development cycles into the business business cycles. To make better Prada effectively, it evolved as a as a tool to differentiate and out innovate the competition. And that's to a large degree one of the ways that you deliver the right inside to the right group to improve your business right. And so this is applicable across all use cases in order pot. All departments are on the company, but that's just one example of how you think of this continuous innovation, continuous data from to use analytics and don't >> spend two years doing an M r d and another two years doing a P R d and then another to your shift >> When you when you actually ship it. Half of the assumptions that you made two years ago already all the main along, right? So now you've gotta go. You've wasted half of your development time, and you've only released half of the value that you could have other, >> right? Right. And your assumptions are not gonna be correct, right? You just don't know until you get that >> you think over time, like two years of kubernetes with a single digits percentage adoption technology and soon was customer base. Now it's 1/3 right? Right? Which means no things have changed. If I had made an assumption as of two years ago on communities, I would have no way wouldn't have done this announcement, >> right? Right. >> But we did it in an interactive mode and re benefit from that continuous information continues intelligence that we do in our own >> right, right? We fed Joe and the boys on lots of times so that it's a pretty interesting how fast that came and how it really kind of over took. Doctor has informed they contain it. Even the doctor, according to reporters. Still getting a Tana Tana traction >> and it's >> working in conjunction with communities. Communities allows you to manage those containers right, And Dr Containers are always part of the ecosystem. And so it's, you know, you know, it's like the management layer and the actual container layer, >> right? So as you look forward to give you the last word, you know, as we're really kind of getting into the SIA Teague World and five G's coming just around around the corner, which is gonna have a giant impact on an industrial I ity and this machine a machine communications, what are some of your priorities? What are you looking, you know, kind of a little bit down the road and keeping an eye on >> interesting question. You know, we used to think about I ot as is the new domain. We should think about I or tea. And maybe we need to build a solution for right. It turns out our biggest customers, customers and the way that I have personally reframed my thinking about Iris is the following Computational capacity is ubiquitous. Now, what used to be a modern application 345 years ago was something that your access to your laptop or three or mobile app, and maybe you're a smart watch Now the computation that you interface with runs in your doorbell, you know, in a light switch in your light bulbs and how's it runs everywhere runs in your shoe because when you're around, it talks to your phone to tell you how many steps you've taken, all the stuff right? Essentially, enterprises building application to serve their customers are simply pushing computation farther and farther into our being, like everywhere. There's now I, P Networks, CP use memory and all of those distributed computers are now running the applications that are serving us in our lives, right? And to me, that's what I ot is. It's just an extension off what the digital service is our and we interface with does, and it so happens that when you push computation farther and farther into our lives, you get more and more computers participating. You get more data, and many of our largest customers are essentially ingesting their full stack of iron devices to serve their customers >> right crazy future and you know, it just kind of this continual Adam ization to of computer store and memory. Well, Bruno, hopefully it will not be six years before we see you again. Congrats on the conference. And thanks for taking a few minutes. Absolutely. All right. He's Bruno. I'm Jeff. You're watching the Cube where? It's suma logic illuminate at the Hyatt Regency seven square port. Thanks for watching. We'll see you next time.

>> from Burlingame, California It's the Cube covering Suma logic illuminate 2019. Brought to you by Sumer Logic >> Hey, welcome back there. Ready Geoffrey here with the Cube where it's suma logic illuminate 2019. We're here >> at the Hyatt Regency San Francisco Airport is about 809 100 people packed house in the keynote earlier this afternoon. Really excited tohave. The guy that was >> running the whole show was running the whole show here for this company. He's remain Sayer, >> the president and CEO of To Malachi Remain great to see you again. You too. Thanks. Absolutely. So 30 year. The show Second year of us being here. Wonder if you could just kind of reflect on how this thing is growing. >> Yeah. I mean, I think it's really a testament to the community more so than sumo, and we've seen a lot of growth naturally, because of where customers are with their own adoption of technologies such as cloud, but also transformations that they're going through like digital transformation, cloud transformation so naturally that allows for more audience of people to attend conference like this. Because this is not a sales marketing conference. This is a user conference. And as evidenced by the fact that 60 plus percent of the content is users themselves in the community present. >> Right? And you talked about the theme is really this intelligence gap, which, which was really a key piece of the key note. And it's interesting because talking about data in huge amounts of data flow, exponential growth and types of data, flow of data, sources of data and your data is just data until it turns into information. And then if it turns into good information, that actually could maybe turn into some intelligence and some action that you can do something with. But there's no person that has the ability to manage the data flows now that we're starting to see. So you guys are really coming at that at the core? You've been at it for a long time. You made some great early on bets being cloud native and now really starting to see the benefits as this exponential growth of data just hits everybody >> you're spot on, I think, um, you know, maybe to add to that, I think the challenge that we see despite the tsunami of data growth, is that a lot of organizations still struggle because the lacked ability to be able to share the insights and intelligence they glean from this data. So a lot of things we spoke about the key note today was the whole notion of the intelligence gap that exists. And that's predicated on the fact that you know, we're all going through some sort of transformation or migration or business model change. And with that comes five challenges that we talked about with respect to continues intelligence we internally has actually referred to as a challenge of minding the gap of intelligence trap because we need to help our customers become intelligent and collaborate, communicate much more effectively by virtue of what we've become that what we've become is that trusted partner, that data steward that is sitting on all this valuable insights that we need to be able provide continuously to our community of users. >> Right, if you talked about it really out along three different metrics, right, the operations metrics, which is probably what people think of top of mine security metric on then, as well as the business metric. And, you know, we had a Robert Parker on earlier from smart thing Samsung Smart Things, and he made an interesting comment that they are pervasive users of Suma logic within the company, which I thought was really interesting because everyone's chasing innovation. How do you get innovative? I think one of the core ways, as you give more people more access to more data and the tools to actually do something with it. That seems to be a big piece of the of the smart thing story. And that's really a big part of your guys. Messaging. >> Yeah, I mean, I think unlike other vendors who have restrictions on adoption and usage on or charging by user model, you know, we're trying to make sure we tear those silos down on one of the nature's by nature. One of things you have to do is provide ubiquitous access, and second thing you have to do is built to dress all different types of data so you can get value for all those users and ubiquitous access. And so you hear about that through not just smart things, but a lot of other customers and partners that are here today because that's unlike the old models, >> right? Right. It's interesting, right? Minds, we backed you know, 97 97 98 99 when first started seeing people build Web applications. And they had all these pricing models based on, you know, cores and CP use because it was based on how many employees were inside the inside the walls and would have access to the applications. And they try to apply this to to a public Web page. It doesn't work. Still see some of that nasty legacy stuff, though, >> right? And would now it was 20 years later. So you made >> a big announcement today about really changing your pricing model. Two more fit the realities of the world in which we live. >> Yeah, look on the surface. Why it seems revolutionary. It's not. It's evolutionary for sumo. It's something we've been doing since we first started. For example, we always provided a service that charges an average for the month, not for the penalty. You're going over a day we didn't charge for user's because that's antiquated model. More importantly, we actually provide in an economic model all along the mere the business model of all these companies. So the more you ingest and use the lower your cost become not more right. And so the things we announced today is a further commitment that we have been making to the community and effectively taken the headache away from them because he looked at these other tools, for example, that provide observe ability for monitoring or for security. You have to go calculate, count the licenses. You have to go look at the number data point for a minute. You have to look at the number nodes and who wants to manage software you want to manage Service's. And so what we've done has really taken the next license taken existing licensing mall that we have to the next level and providing a credit based system so that you can flex and choose what you want to use in a given day and give a month and given Pierre recycle across a new suite of packing ages or a suite of products that we brought to market >> right or whatever, whatever you are optimizing for that particular day. That particular moment, that particular business >> but also ties or something you mentioned earlier it it actually helps tear down those silos that other vendors air creating because it provides ubiquitous access to all users for all different types of data, right? And instead of trying to keep those silos and separation that exists, that further challenges intelligence gap that we're seeing in intelligence. Economy, >> right, Right. What? Another great slide. I thought earlier in the keynote was given by Anheuser Busch, and he talked about his security infrastructure and all different layers of security in the solution that he has for, you know, front kind of front door and fishing, etcetera, etcetera. But the great thing is, you basically crossed all those applications stack and and it's a pretty interesting position for you guys to be in to be able to integrate with all these other kind of point solutions that make up parts of the puzzle and to bring it all back and to still have kind of this one ubiquitous Data Analytics platform to go on and do stuff with that. >> Yeah, I mean, I think it's truth be told, something we've been doing for a long time. I think the visual that you saw there is the challenged a lot of our customers have, and specifically they have these silos >> of >> endpoint or firewall or email or whatever else, and it could only make sense of it by leveraging the monitoring of those silos to an intelligence platform like sumo. And so the same thing that you saw in security with Anheuser Busch being able to leverage the silos into intelligence platform for security. We see in the monitoring space for developers and operations team so they'll have silo tools. But observe ability, is not it. You need continuous reliability, and therefore you need to be able to take all those different types of dead and signals, just like you saw on security for the different types of infrastructure and applications that your manager aging and provide an intelligence based system and service, not a monitoring based on the system of service. >> Right? Another big trend that's happening. You guys were riding this wave and you're Jennifer up from from Google Cloud and she she had the same presentation on Antos. I think at the Google Cloud platform, someone earlier today, you know the Mo Mentum behind Hybrid Cloud as kind of the whipsaw. You know, it's all jump into public and then let's not jump in and its hybrid and its multi. The fact of the matter is, everything's going to work supposed to be, which is its workloads Pacific and the works load should run where the workload should run Really a great moment, um, for you guys to be ableto leverage because regardless of where the work flows running based on where it should run, I need to see it in a unified front. Back at the back of the ranch. >> Have a Jeff. I think this is what we saw even last year when we put the continuous intelligence report out, then let alone the changes we saw this year. For example, we saw Container Technologies moved from development to production last year in north of two ex growth. Now we're seeing orchestration technologies like Kubernetes more than two Ex Growth. And what's driving the multi cloud common that you made is because the customers want flexibility and choice of where those work clothes run. Historically, they have been able to do that until now. Leveraging contain orchestration, technology that builds an abstraction layer from the eye. Astor infrastructure is a service later, and obviously a testament to what Google's been doing with an throws in the partnership we have with them. Tow develop and integrate things for anthros. Ston service mesh. >> Yeah. So what's next? What do you looking for? I can't believe we're almost done with 2019. It still shocks me every time I flipped a calendar. >> What? Your priorities going forward? >> Another great event. 2020 year of insight and all knowledge. What we're saying we're gonna be, >> uh >> you >> know, we started down this journey before the market was there, and I think the unique position and fortunate position that we're in right now is Maura, Maura, that market opportunities to us and the community's getting more powerful and stronger day by day and year by year. So we're very early innings of this honestly. And so what do we see? Going forward to your question is a lot of the execution of our strategy that we set out a while ago to build the only continuous intelligence platform. And more importantly, the new category of software called into continues intelligence. That's really mirroring the OMB operating model and economic model of every single digital business that needs to thrive, not just survive >> right in an era of exponential growth data, complexity, sources, types, which is ah, good place to be all right. Well, we're mean. I know you're super busy. Thanks for taking a few minutes. And congratulations on a great show for sure. All right, >> ease remain. I'm Jeff. You're watching the Q word. Suma logic illuminate 2019. >> Thanks for watching. We'll see you next time.

>> Narrator: From Burlingame, California, it's the Cube, covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey welcome back everybody! Jeff Frick here with the Cube, we're at the Sumo Logic Illuminate conference, it's at the Hyatt San Francisco Airport. About 700, 800 people, full house in the keynote earlier today, all about operational process monitoring, all this crazy data is being kicked out of the Cloud and IoT and all these crazy next-gen applications. We're excited to have a very close friend of mine, CEO of a very hot company, Kamal Shah, the CEO of StackRox. Kamal, great to see you! >> Thank you, and great to be here, Jeff! >> Absolutely! So for folks that aren't familiar with StackRox, give us the overview. >> Sure, so in a nutshell, we do Kubernetes Security, and so as we've heard all day today, enterprises are deploying microservices, containers, Kubernetes, and we do security for your cloud data infrastructure. >> So how does security work for Kubernetes versus security for other things? >> Yeah, so the use cases for security, or the mission for the security team is the same, right? You got to harden your environment to prevent the bad guys from getting in. >> And, you have to make sure, despite your best efforts, if somebody does break in, then you catch them before they do any damage, right? But the how you do security has to evolve for the cloud data stack, right? It has to understand the containers are immutable affirm all infrastructure, you have to understand that it's not just about the container, but it's also about the orchestrator, and specifically Kubernetes, and it's also about making sure that you seamlessly integrate with dev ops processes, automation and workflow. So it requires a fundamentally different approach to security than traditional security tools. >> So you know, we talk a lot about the increasing attack area that's offered by IoT, right? And increasing attack area that's offered by all those API's and all these interconnected applications, but I've never heard anyone really talk about containers or orchestration as kind of a new attack surface. Did we just stop paying attention? Is that something you're seeing happen? >> Yeah it's something that is starting to emerge, and we've seen some high-profile breachers at a large next generation electric car company, and a large shopping site where misconfigurations led to security breaches in the Kubernetes' environment, and Kubernetes' ecosystem also did a Cube security audit, and so I think we're going to start to hear a lot more, because there's more and more applications are being deployed in production. It's creating a new attack area, and as the old saying goes, the predators go where there's food in the system. >> And so if you're not proactive about it, I think it's going to really hurt as you deploy containers in Kubernetes. >> Right, so we hear over and over and over again about breaches because people misconfigure stuff. That just seems to happen, whether it's a database or this, that, and the other. And I think we can pretty much safely assume everyone's going to get breached if they haven't got breached already, 'cause we hear about it all the time. How do you catch them fast, limit the damage and try not to have too much vulnerabilities? >> Exactly, so the use cases for what we do at Kubernetes are the same. Right? Its vulnerability management, it's configuration management, and we just did a study around the state of container in Kubernetes security and misconfigeration was the number one concern. Because the reality is that Kubernetes, there are a lot of knobs. And each knob has multiple options, so if you're not careful you can really misconfigure your environment and make it so much easier for attackers. >> Right, right. >> And it's precisely what happened at the two examples I sighted earlier. So a misconfigerations is important, runtime security is important, and also compliance. Let's not forget about compliance, right. You have to make sure that you meet your PCI, HIPAA, NIST, and CIS benchmark standards for this cloud native stock. >> So what we're seeing is that these are all becoming very, very important and as a result, it's increasing awareness as Kubernetes gets more prominent. >> Right, and then they are creating and tearing down hundreds, thousands, millions of these things at a nidicolous pace. >> I mean exactly. Kubernetes came out of Google, they open sourced it, and it's really what allows you to deploy, manage, containers at scale. Apparently, they manage hundreds of millions of container a day using Kubernetes, it's incredible. >> Jeff: Oh yeah, I saw a statistic that Google launches 4 billion containers per week. That was from a presentation, actually from a 451 analyst from like 2 years ago. So one can only imagine the scale. >> We are also seeing not quite 4 billion containers per week, but we are seeing thousands, and tens of thousands of containers at scale at companies everywhere. They are all deployed in production, and now they are waking up to security. The good news here is that they are waiting for breaches to happen before they solve the problem. There's still a lack of awareness, and what Sumo Logic has done today with the announcement around continued intelligence for Kubernetes just increases the awareness around, hey we have to solve observability, which is logs, metrics, and tracing, which is what Sumo does, and security for your cloud native infrastructures. >> Yeah, I mean the automation is so important, right? You can't do any of this stuff with this exponential growth of data, exponential growth of pushes, of new code releases. There's so many pieces in this, so automation is a huge piece of the puzzle. >> Automation is paramount and with this new infrastructure there aren't enough security people to solve this. So security has to become everybody's responsibility. And the only way we are going to solve this is to automate it. It also has to integrate with your DebOps processes and automation and work flows. If you don't, then the DebOps body is going to reject the security organ, right? So it has to be seamless in the way you deploy it. >> It's interesting you say that because we go to RSA, forty thousand people, more vendor than you can count, it bulges Moscone to the absolute edges. Everyone says over and over that security has to be baked in the entire process from beginning to end, it's not a bolt on and can never be successful as a bolt on. So it surprises me to hear you say that still a lot of people are kind of behind the curve. >> Well I mean if you think about I, even though they say that, right? In a traditional model of the application you go to spend 6 months building it and then you can go spend a couple of weeks or month hardening and putting security around it. But when you are launching applications every 6 hours, you can spend 6 days addressing security, so it has to be built in. And speaking of RSA, if you recall, last year the big talk at RSA was around AI, right. Everything was AI driven security. My prediction, my bold prediction for this RSA is it's going to be all around Kubernetes security. >> Yeah, well it's applied AI. Applied AI for Kubernetes. >> Exactly. >> And that's what you need. I always feel for the SISO just walking the floor at RSA going, "Where do I begin? I mean where do I spend my money, how do I prioritize?" It's kind of like an insurance problem. You can't insure to the nth degree. You got to have a budget, but how do you deploy your assets? It's got to be super, super confusing. >> It really is. I think what your seeing is that SISO's are relying on their DEV and IT ops teams, right? They are partnering with the VP of platform, the VP of infrastructure, the VP engineering, because when you think about this new world security is really, the ownership of security is now shifting from the information's security teams to DevOps teams. So security teams still drive policy, and they still want to make sure they do the trust and verify, but the implementation of the security is now being owned by DevOps teams. So its a big cultural shift that's going on in organizations today. SISO's have to realize that it's no longer just them, but they have to partner with their DevOps counterparts to effectively address security for this cloud native stock. >> Right, so tell us a little bit about the relationship with Sumo. How do the applications work together? What's the solution look like when the 2 solutions are brought together. >> So Sumo has been a great partner. We have several joint customers. The simplest way to think about this is that Sumo does observability for Kubernetes, so that's logs, metrics, and tracing, and we do security from Kubernetes. We are the yin to their yang. What we do is we have taken all the intelligence we get from security and we feed it into the Sumo dashboard. Sumo customers get a single pane of glass, not just for the observability data, but also for their security violations, weather its for vulnerability, weathers it's for configuration or if it's for runtime threats, right? You get it all in one single place. >> Right. So I just want to get your take on kind of this rise of the momentum behind Hybrid Cloud that we've seen recently. Big announcement at Google Cloud show, with Anthos. Big announcement between VMware and Amazon. It always kind of swings back and forth. It was all in to public cloud and now there's a little bit of a pullback in Hybrid, but that's terrific for you. The fact of the matter is workload should run where they should run, they don't really care it's what's appropriate. Horses for courses, right? >> Precisely so, we see the shift from public cloud to Multi-cloud, and then from Multi-cloud to Hybrid cloud. The underlying infrastructure that makes that a reality are containers and Kubernetes, right? And that's why we've seen this tremendous momentum on Kubernetes. What we are seeing is customers that want to give their Dev teams that flexibility to pick their favorite cloud, or to do it on premises, their private clouds. But they want to make it in a single security solution that gets integrated no matter where you run your infrastructure and that's integrated back to your Sumo dashboard. So you have visibility across all Dev teams, all your application infrastructure, regardless of where they are running. There is one security standard that gets implemented. That is really, that's the future. You don't want to be beholden to a one claw provider, you want flexibility, you want choice. Kubernetes allows you to do that. >> Well and the whole thing becomes more autotomized, right, with autonomic memory, autonomic compute, autonomic store, throw that on an IoT and Edges and now you're starting to distribute all those pieces all over the place, which is going to happen. >> Kamal: It is going to happen for sure. >> All right, looking forward I can't believe we're almost through 2019, it still shocks me everyday I look at the calendar, but what are some of your priorities looking forward? What are you guys working on? What do you see coming down the pipe? >> Yes, so you touches on a couple of these. So today, is a lot of talk around Kubernete. We are seeing Kubernetes also get deployed in IoT and edge devices, we are also seeing they are being used to manage serve-less infrastructure. So we are going to continue to evolve as Kubernetes evolves. The other big trend that we are seeing in the market today is around service mesh. People talk a lot about Istio and Linkerd and using service mesh as your policy framework to drive consistent policies across applications, so that's another area where we are innovating very rapidly and that will become, I think, more and more real in enterprise deployments over 2020. >> Well, congratulations Kamal to you and the team. I think you picked a good horse to ride on, I should say ship, right, with Kubernetes. Thanks for taking a few minutes. >> No, thank you for having me. I can officially say now that I've checked off one of my professional bucket-list items, which is to be on the Cube with an old friend. So thank you for having me. >> Check that box man. All right, he's Kamal, I'm Jeff, you're watching the Cube. Were at Sumo Logic Illuminate from the Hyatt San Francisco Airport. Thanks for watching, see you next time.

>> from Burlingame, California It's the Cube covering Suma logic Illuminate 2019. Brought to you by Sumer Logic >> Hey, welcome back already, Jeffrey Here with the Cube Worth Suma >> logic illuminated the higher Regency San Francisco airport. About 800 people, 900 people packed house in the keynote earlier this afternoon. Really interesting space, and we're excited to have our next guest >> kind of on the cutting edge >> of the I o T space on the consumer side. And he's Robert Parker, the CTO of Sand Samsung. Smart things, Robert. Great to see you. >> Great to be here. >> Absolutely so before we get into >> the kind of the depth of the conversation, a little bit of a background on smart things. I was doing some research getting ready for this and the fact that it started as a kickstarter a long time ago, not that long ago, and now is part of Samsung, a global electronics giants. What a fun adventure. >> Absolutely. I think it's been one of these things where it's great to be something where it's community driven to begin with, so kick start. It was a big part of our launch, and we were one of the biggest kicks are launches at the time. Uh, really powered by our community around the website and early users. We got a lot of interest in I O. T. And then moved on to the next stage of the vision, which is sort of encompassing all devices. And so that meant we have more than 2000 different Samsung devices on the platform now, which really allow devices to talk to each other in ways that are really exciting. And that breath has been really great thing to be part of >> right. It's really funny. We went to the Samsung Developer conference a couple of years ago. It was funny to see the the living room guys fighting with the kitchen guys, you know, What was >> the centers that the TV or is it >> the fridge aerator? Or is it the washing machine for that bit? And Samsung's got really got a foot in all those places? >> Absolutely. This is one of the things that the smart thing platform is really enabled Samsung to transition across is then it's no longer a conversation with the washing machine person or the dryer. All the devices are part of the smart things. Cloud. Martin Claude is a one way that you could talk to Samsung Devices, and it's an open ecosystem. So it's not just Samsung. Devices were equally comfortable with manufacturers. Any manufacturer bringing those devices because home is a multi vendor environment you are not. We're gonna have all of your home from anyone, vendor, right? And that's been one of the exciting parts of visions that's been part The open ecosystem is something that's been part of smart things. Story forever to really immortalize that in a platform for Samsung has been great transit, >> right? So we're here. It's Uma Logic, eliminate and preparing for this. I saw an interview with you. You made a really interesting comment. >> You said that we are a pervasive >> user of suma logic, and he said 90% of the team are using similar logic. It's fascinating to me because I think a lot of companies air chasing innovation. I think one of the ways to get innovation is you enable more people to have more access to more data and the tools to actually operate that data so that they can do their jobs and find cool ways to make improvements that aren't necessarily coming from the top down. It sounds like you guys have addressed that philosophy wholeheartedly, >> so we absolutely have addressed it wholeheartedly. I think there's a lot of luck involved, and I want to sort of describe it Is that one of the things that worked well for us is people were excited to use sumo more and more. They're more excited to see what they could do with the tool, what insights they could get. And so you see your neighbor looking at it and they look a dashboard and they say, Can I do a little bit of that? And so much So you know, in the last year we've seen ah lot of unplanned value come out. So 1/3 of the value we gotta assume of, um, um in the past year was unplanned. These things people didn't process, they didn't know they would improve. That really just came from this groundswell from what I would call the community. And I think that's where you get that. That unlocks a lot of the potential because you really can't do things from sort of the planned high level. You really need. People actively engaged right and doing stuff you wouldn't expect. >> That's great. So I >> want to talk about >> a little bit about security. Security is a big topic here. It's topic everywhere we go on and now, with connected devices and connected keys and connect doorbells, it seems like, Oh, here we go again And there's this constant talk that security's got to be baked in throughout the entire process. How are you guys dealing with security? Obviously got to be right at the top of mind in terms of priorities. While you're still connecting the sprinklers in the thermostat and everything else. Security >> and privacy are both critical link in privacy, even though you didn't ask about it. Because as you think about devices like cameras and things like this, privacy is top of mind. Also, in terms of regulation like GDP, are so because of that, we're really looking at both cases that the challenge for both security and privacy is it really cuts through your whole organization and every process, and by the way, every process that every partner, if the organization has because we can have something that could be exploited from sort of a an attack through a customer service representative. That could be a person in the customer service organization. It could be how some of social engineered that. And so what we've really needed is this kind of continuous intelligence that can span all of these processes because in something I security, you're as good as your weakest process. And that doesn't mean that we don't focus on all things that you talked about. Were industry leading from device perspective tohave hardware baked in keys and, you know, do things the manufacturing process that lead to something that could be as secure as anything. But that's really that the secret of using a lot of the continuous intelligence tools like sumo is that all of these could bees aren't enough. You have to bring it together by having the intelligence that spans those processes to make sure that all of them are elevated. Because at the end of the day, a security attack is gonna attack your weakest thing, not your strongest right. >> So one of the other >> topics here that talked about is this exponential growth of data, and you guys were part of the problem because now we got sensors and light switches and all these other things that are kicking off data that before we weren't monitoring. And so from from an execution point of view at the company, when you've got so much data that you need to turn into information and then actionable insight, you said Sumo's got some unique characteristics that allow you guys to get more leverage of that platform. I wonder if you could dig into that little bit more >> and I'd like to reframe the data discussion a little bit. A lot of people look at it. It's a problem. I want to really talk about the opportunity side. So part of that goes to our story where we started off at KICKSTARTER with a few 1000 users, we have over 50 million active users now. >> 50 million >> 50 million. Our Android application, the Google Play store, had been downloaded around 200 million times, so it gives you some idea of that size and scope. So the data is an opportunity. There's an opportunity to build a customer base, too, excite people and to manage the processes that do that. And you know what's great now is that the availability of this data means that you can do it in more ways than you ever could before. The problem is, you need a tool that brings us together. To be able to do that in doing that well is difficult, difficult both on the teams and difficult because the size, scope and complexity of the systems because of the data that you mentioned. But the >> reason you want to >> do it is so that you can cross the chasm in terms of this opportunity, and more and more companies are enough. You have this opportunity on the front of them. One of the things that's been really exciting, but the cloud is a sort of democratized the entry point. But that wasn't good enough just because you could get in the game with three people. It's like making a you can make us application in Mobile Applications store, either on Google's on Apple's really easily that gets you in there. What you really need to do is manage the intelligence that goes from that, and for us, it's been really exciting to be able to take our decisions and make them data driven, and we can do that by this explosion of data because it is their >> right in the date is good. And I think we see, you know, kind of date of it as an asset. It hasn't really hit balance sheets officially yet, but I think you see it in the valuations of of companies like Google and Facebook and Amazon, right, who obviously have these crazy giant multiples of the revenue one because they're growing but too because they have so much data. So the markets kind of valuing that data without explicitly calling it out as a line on the balance sheet. That said, not all data has the same value, not all day. Not all data needs to be treated the same and so really opens up an opportunity. How do you tear it so you don't want to get? You know, it's been a ton of money on a piece of data and a big fat stream that somebody leaves open and accidentally suddenly have a big building that maybe wasn't the most valuable. So >> it actually double down on what you said because for a typical company, one of things has also been true. Of the mega scale companies that you pointed out with is there's a lot of uniformity in their data coming the cost of the Amazon. They have customer orders, and they've got orders at this massive scale. A typical company doesn't look like that. They have their data spread is more fragmented, smaller scale on so >> because they want to make different decisions. And this is the >> same thing that has already happened in the storage area. People are really comfortable with storage that they're gonna have in either just disaster recovery or long term storage. And they want a very low cost footprint around that they've got their hot data and they're much more willing, tohave that data managed differently and at a higher cost rate because it's it's much more valuable. We're looking for tools that span that not just in storage, but in the ingestion in the management in the querying of that data. Because, like you said for most businesses, a lot of data's infrequently looked at or looked at in response to a situation, so I'll never know which 10% of the data will be looked at. It will be based on Oh, I got audited or, you know, some other business event that happened on, so this is one of the key things that business is struggling with. One of them is that they they want to adopt these practices to become modern or boring, modernized. But the 2nd 1 is to really be able to tear the data because they couldn't treat all the data's if it's hot data, just like they already figured that out for storage, >> right? It's pretty interesting. It's been going on for storage forever. We really saw it, I think, with the rise of Flash, which was super high quality but super expensive in the early days that's coming down and then at the other. And we have the end of the glacier storage in the cold, cold, cold store. Just put it away by what your last thought's that last. Answer, Robert. As you look forward, I can't believe you're already in middle of September of 2019. It's fascinating to me that time flies so fast. But as >> you look >> forward, what are some of your priorities over the next year or so? How are you guys kind of moving the ball down the field? >> So we're one of the things that we're looking at? Was the data problem that you were talking about, if really looking at are infrequent data and be able to manage that effectively both from the types of insights that we can get from that. So a lot of this starts to be better usage of machine learning pattern recognition a eye on so that we can, you know, the ideal situation for us and not type of data is it got touched once it got looked at once, and then we could understand how to action it later that deferred action. And then how do you know trigger that deferred action as well as the tearing that we sort of talked about that all day? It is not created, equal, created equally, and so both those things are happening just to put some numbers on this. And why is that? We have 150 terabytes or so of data that is somewhat interesting to our business generated on a daily basis. 150. Terrible, terrible. That's interesting. And then on that's out of that, I'd say 10 terabytes is kind of really actionable. It's that gives you an idea. The other part is how that's growing. Where a year ago, we would have been at maybe 60 terabytes of what I would have called this interesting data and maybe five terabytes of, of of, you know, immediately actionable. And And so that's where you know this is following that where that's exponentially growing and it's a big number. So that's what we really think about. >> So you scared those curves. Curves get state, we look. It >> is a huge opportunity. What will happen is either people will create value out of that for customers, in which case, actually the opportunity, because is that such a scale? It will be great for everyone or number two, you know, it just becomes noise, right? And so it isn't really something that scared of, because worst case is it became noise to you. We really want to be one of those people were getting value out of it and see sort of the business growth and the consumer value growth. Out of that, I I'm pretty optimistic that we'll be able to do it because we really if I look back 34 years, we've just been able to figure out a way, and I think it will continue to do that >> All right. Well, Robert, thanks for taking a few minutes of your time and ensuring the story. It's a great story. Thank you. Appreciate being here. All right. >> He's Robert. I'm Jeff. You're watching the Q word. Suma logic illuminate 2019. >> Thanks for watching. We'll see you next time.

>> Narrator: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019! Brought to you by Sumo Logic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency, San Francisco Airport. Our second year here, about a thousand people, third year of the conference, a really good vibe. You know I think some of these cases where the marketers really come to Sumo Logic in terms of data and data monitoring, and there's so many applications that are business and security, and operations. We're excited to have our next guest. He is Lior Mechlovich. He's an architect at Informatica. Lior, great to see you. >> Great to see you, too. >> Absolutely, so you said you've been coming to this for a couple years, just kind of general impressions as it's grown. >> Sure, it's my third year, it's grown very nicely. Always exciting. I think there's a very nice vibe to this conference. I always learn new things so we've been with Sumo for more than four years now for Informatica. And excited as always. >> Yeah, and we've been covering the Informatica show. I think we've looked it up, since 2015 so, we've been doing a lot of work and you guys are right in the heart of this whole data thing, >> Right. >> And you been part of the kind of migration from pretty much pure on-prem, to Cloud. There's rush to public Cloud, and then now kind of this Hybrid model. So you kind of look at the data perspective you know, what's kind of your take as this thing has evolved over the last several years? >> Sure, so we have been around for 26 years. I think building a lot of on-pram, data platforms for being the enterprise Cloud data management that Informatica sells with basically getting your data inside our outside the organization from Clouds, on-pram, or whatever integration pattern you have and we decided four or five years ago to be a Cloud-first company and migrated most of our products to be on Cloud to provide them as a service. And for us, it was a huge journey, we needed to take some offering that we had in the Cloud, some products, and really revamp and building a new microscopic architecture and then slowly migrate all the customers. It took us over a year to make that. We currently run on all three Cloud providers. And really using Sumo mentoring tools to really understand the impact that we have on our customers during this migration. It was a very successful. They hardly noticed that-- >> Oh good. >> Only the nice UI, but they hardly noticed the problems. I mean we really changed a lot of things. >> What is some of the things you learned in that process that you can apply now with just some of your customers in terms of data migration and operating in a Cloud situation versus a traditional data center? >> Sure, so I would definitely highlight the need to be able to roll back and the need to always keep really good money to working it and understanding how the end user getting impacted. And so we really kept that in mind. Everything we do try do always do it side by side, and then when we migrate we're really sure that it is successful and there's no impact on the customer. So I think that's definitely too, harshly monitored everything and be able to roll back when you need to, because you will need to at some point. >> But the rollback is funny, because it use to be you had you know the release cadence was significantly slower than now. And now you've got all these kind of micro pushes that are going on multiple times a day. >> Yeah. >> So how does that impact kind of keeping that safety net? That rollback safety net? >> So it's interesting. So we actually don't deploy that many times a day. Where we can really impact the customer so we deploy the things that are not customer urgent impacting production more, but still the really heavy productions of the thrilling part of the customer; we try to minimize that and make it very customer aware okay. >> So basically they choose their own windows of maintenance and all that. But our customers again hospitals, all kinds of very important, then we are in charge of the data byte in those places. So we don't want to just push whatever we can. We really cannot take that, even a rollback of 1%, it can be very bad so we're a bit more conservative models of deployments, but actually that means we put a lot of effort in our monitoring. What is going on doing those deployments. >> Right. All right, so what are the big trends that happen? I mean containers have been around for awhile, but we really saw kind of the rise of containers in terms of the popular consciousness with Docker couple three or four years ago, and then a couple years ago the Cooper 90's coming in for the orchestration. From your point of view how had those things impacted your world, and how you do your job, and take care of your customers? >> Sure, so for us Cubernetics is really a great opportunity to standardize the way that we deploy across different products. So we have our platform, but we have also different products; different people across the globe. We're a very multi-globe organization, and to get a standard like Cubernetics to help us standardize to get more releases, more stable environments that really solves a lot of problems, because we had this migration that I talked about really left us with a lot of clusters across the globe, different time zones. It was really hard to standardize on the pipelines, and to deploy to really minimize the problems that we give to the end user at the end. >> So we really took that opportunity to use Cubernetics, to use containers to minimize the difference it has from the developer machine all the way to production. To automate the most we can so when it's really is excelling in this. Yeah, so that's where we really... took those containers apart. Today we are in migrating, so not all of that, but we truly see the benefits of standardization, of immutable infrastructure as that key component for us. >> This is just so great, because you have such a longitudinal point of view having been in. The company's been at it for awhile, and you've been at the company for awhile. So another topic I'd love to get your thought is just kind of this exponential explosion of data. I mean it would be curious not to know the numbers, but kind of the scale of data in which you guys are dealing with for you customers, and how that has changed over the last several years before you even really factor in IOT, and this next kind of machine to machine explosion? >> So we definitely see that explosion of data. It's not just the explosion. It's also the different types, and where data has been on-prem, now moving to Cloud. Where do people want to run off all those work loads? As of course a lot of feedback for us as well need to support all the Cloud providers when we use to do a lot of Hadoop on-prem, right? It's all changed now too. >> All the Cloud providers, the data it's theirs. So the data move, data locality is a big thing, Now we need to run all those things on the Cloud. So, I don't remember the exact numbers. I guess we're doing something of 2.5 billion transactions a month for like number of records that we serve. That being we usually just see more work loads, more people, more use cases for onboarding more data from Cloud applications. The data became more dispersed not just more data, but the sources has become like everybody needs to integrate Salesforce or Workday with their on-prem that gives unique opportunities for this kind of data. >> Well, it's funny when you talk about the workloads, because it always use to be, do you bring the workload to the data or the data to the workload, and a knock on the Cloud is that you got to get all the data into the Cloud, and pay for the transport of the data. And there's data gravity that said once you have it in a central location like that the opportunity to put applications against that data is much much higher than if you're bringing the data to the application. You see and how are customers taking advantage of that opportunity? >> So for sure we saw they did that move to the Cloud. When we started from on naked Cloud 10 years ago our entire model was hybrid, so we can stick around on-prem, because the data was on-prem, and since then our hybrid model that you still run both on-prem and on Cloud, you can see the change right? You can see more of our agents. We have an agent based architecture to really being deployed much more on easy 2's, on AKS or whatever to run those workloads in the Cloud. >> Right, but I would imagine the number of workloads applied to each data set now have increased significantly, because now it's in that central repository. >> Yes, and definitely you can see those data legs being built, and mostly in the Cloud. That gives unique opportunity. >> So just get your perspective after a couple days here. I know you haven't been here for a couple of days. We're just getting started at this show. What does Sumo Logic bring to you and your team? What does it enable you to do that you couldn't otherwise do? Why are you happy to be a customer of Sumo? >> Sure, so four and foremost it's the democratization of data. I really like to say that internally. In an organization that's spread across the globe, really sharing insides based on data, it's very important. When you have many R&D centers that can just send this summary; send the data and show people what they mean saves so much time, and so we use it across. We use the customer success, product management to understand feature being used, SRE's, developers. All of those really can communicate based on data. In this Microsoft Office tool you cannot do it without that. You cannot do it without linking, because the different products that we onboard on the platform will not be able to communicate effectively without that. So that's very important, and giving that landing pages dashboard templates for onboarded services to have this kind of standard to follow to monitor how to operate that's very important for us. >> That's great. Go ahead. I'm sorry I interrupted you. >> Sorry, and the key place that we brought Sumo in is basically for instant management. So how to understand when something doesn't work just to try to understand the blast radius, which products are impacted. We have a variety of products, so just in minutes we minimize that in four hours to minutes trying to understand what exactly is going on. Who's impacted to update the customer  and all that. >> I love the part you talked about the democratization, because again I talk about it all the time, and I'll talk about it again, but to drive innovation in a company I think such a key piece of it is to enable more people to have more information, and the tools to manipulate that information, so they see opportunities to make improvements here, there, and otherwise and it sounds like you guys are really using it for that. >> Definitely. Definitely. >> In this case. >> You know when you get some people that you never knew that even though we have a customer support guys that did some crazy dash wars that we had no idea it's possible even, and they really getting chance to work with customers better to really tell the customer, "Oh, you just did that and that. "Maybe you'll try this option." And we found that even communicating, and really minimize the time it takes for them to figure out what's going on that it's been really impactful. >> With no call to It to help (laughs). >> And it was never the intent, so we wanted to allow dev's and off's to operate, and all of a sudden you're getting customer support without even telling them. >> Good, well Lior thanks for sharing your story and really appreciate you taking the time. >> Thank you. >> All right, he's Lior. I'm Jeff. You're watching theCube. We are at Sumo Logic Illuminate 2019. Thanks for watching. We'll see you next time. (upbeat techno music)

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hey welcome back everybody Jeffrey here with the cube we're in our Palo Alto Studios here today for a cute conversation it's a little bit of a dog days of summer conference seasons a little bit slow so we're excited we can kind of take a step back and we're gonna look back actually in time we're excited to have a very special guest rich Kolbert he is the field CTO at Dell EMC but really what we're talking about today is this data domain is 10-year anniversary of the date domain acquisition so rich first off welcome to the to the cube thanks Jeff excited to be here thanks for the invitation appreciate it I can't believe we're talking before we turned the cameras on that you join in 2006 and yet it's been 10 years I'm like wait 2006 was more than 10 can that be we're just getting old I don't know things are changing too fast no it's like a trip down memory lane and it just seems so long ago and yes in a way it also seems like yesterday I think things have gone so quickly so we're also joined in this segment by our top data analyst also the founder of wiki bond and co-ceo of Silicon angle media and founder of that as well so Dave Villante is joining us all the way from Boston Dave good to see ya hey Jeff hi rich to talk to you guys hey Dave so let's take a quick trip back 10 years ago actually maybe 11 years ago things were starting to heat up there was a lot of different vendors out there a lot of different players and things started to consolidate so I wonder if you can give us a little bit of your perspective what what's going on rich and then we'll get Dave's perspective yeah it was an interesting time right before the data domain acquisition we actually went through some economic times in 2008 and the markets are changing and and and some companies are becoming more successful some companies were struggling through that time customers were also looking for ways to to you know save money and do some interesting things there so it was a mixed feeling set of you know through that times data domain had IPO in 2007 and we were kind of going through this this explosive period of growth but you know across the board we just saw so many things change all at once and we really were surprised I think when initially was NetApp that an that they had intentions to bias and I think that was due to some of the economic factors of play and then of course EMC stepped in and and started a bidding contest with NetApp for for the company right so I Dave wonder if you could share your perspective you're sitting as an analyst you got Jo TG The Godfather of storage back in Boston what were you seeing in terms of the kind of the market dynamics and was it a surprise wouldn't that app decided to make a move well if you know first first of all I had left the storage industry for quite some time and when I started wiki bond we looked at storage and nothing had changed except one thing which was David deduplication that was new until a new tape was finally I always hated the tape the tape was finally being attacked so it was it was amazing time and EMC at the time we had some obviously great management yet Frank Sluman running data domain yo Joe Tucci who always balanced out acquisitions with organic you know in how to R&D and when Tom Georgians and NetApp said they were gonna go by David domain emt's walk right in and said no way so it was somewhat of a defensive move but at the same time when you talk to the M&A guys they said no no it's not just defense we can actually make this a growth play and that's exactly what happened Dayna domain I think at the time rich was probably a couple of hundred million dollar company and then they they popped that at the EMC and scaled that to you know well over a billion dollars and it'll maintain the the franchise and then grew it quite dramatically beyond where all the expectations were for the market the market team at the time was probably around a billion and I think ID seen rich as a over three billion today yeah one of the things that's so don't quote me on all the numbers because I'm not like you know watching the market caps and stocks but I think we'd gotten up to about a 500 million dollar run rate in terms of sales and prior to the crash I think our market cap was actually significantly higher so so our price came down you know which is one of the things I think that attracted NetApp to the game so the interesting dynamic inside the company was that the NetApp offer was was kind of the first one so they were working with the data domain leadership and they were speaking with us EMC was more of a kind of unsolicited offer so there was less communication and I remember there was a morning I was at San Francisco Airport going out to meet a customer and Joe to Chi put out a full-page ad in a local newspaper and we were reading that and that was his way of communicating to the to the people a data domain saying he wants to welcome us into the family it was quite a moment well it sure was and of course you guys were fierce competitors data domain was fierce competitors with with EMC you know fighting for for the install base and then all of a sudden you know the cultures it's somehow work EMC was was very good at acquisitions and he made it work and they not active it was an outside observer but you were there you know Frank Sluman came in did it's kind of running the the data protection organization but a lot has changed since then hasn't it I mean back then you stored you know a little bit of data I think accounting of terabytes today we live in a petabyte scale world I could talk about what's changed well you know the scales and performance certainly has changed I think the data domain platform today is about a thousand times larger than it was when it first came to market and in fact when we were being bid on by NetApp and EMC we had a flagship product is the DD 690 you know behind the scenes we had a system that was coming out that was double that size and EMC nor Netta knew about that so once the deal closed they got to find out that our size had just doubled in our performance and doubled at the same time but you're right you kind of talked about the dynamics inside of EMC EMC had a very large data protection you know division they had avemar networker santaros v TLS they also had an OEM arrangement for a competing product with the data domain platform so it was really like you know I compared to going to Hogwarts right where you have all of these different houses and we came in with with data domain and and I think the thing that really the glue that really helped it come to get was Joe Tucci you know tapping Frank's Luqman on the shoulder as the leader to bring this together and taking what was the borough division and and reforming it as the BRS division and I think we came together very quickly as a team even though people came from all of these different backgrounds you know standing for these different products rich let me follow up on that because there's a lot of M&A activity going on right now and and not very many big M&A deals are ultimately successful it turns out so what you said a little bit about you know Joe and Frank you know coming together but what are some of the other attributes that you would say that made it work it actually did what everybody hopes on an acquisition which is take great technology put it into a big sales machine and watch it grow and grow I think part of it you know quite frankly just comes down to the product and being differentiated because there are a lot of products out there and and if you take a step back they have good things that they're doing but it's very hard to find a product that says hey you're doing something that even if you put the blueprints out there it's very hard for other people to follow in those footsteps and create a similar value proposition and I think I think in this case it was a differentiated product and it had a lot of energy of its own and and I think from an EMC perspective they just stood back and said let's take this momentum and and play it out and see how how far it can take itself unfortunately I think a lot of times they don't do that right a lot of times acquiring companies don't just take this great thing and kind of get out of the way and add the juice where they can but you try to to try to change it so that's a really nice statement on Joe to G and what he was able to accomplish yeah no he was fantastic for us and and his support was tremendous but also his you know delegation and and kind of seeing how this but you know kind of having a vision of how this business unit should be formed right I think what was was very prison and then now you're part of Dell so obviously Michael Dell big personality as well the Dell technology stories he's doing a great job of pulling all these pieces together and you know kind of reinvigorating the brand coming back out of the little little side bar you know make it private for a while and come back so I wonder if you can talk about that integration how's that going as you've gone now a couple of times well I think it's been very exciting for us because the one piece that EMC had always been lacking had been the the compute part of the picture and now we have really the ability to go in and talk about the entire stack with our customers and that's that's a lot more powerful than saying here is an element of it and then if you want to go and add compute to that perhaps you know put in your virtual or physical servers then you're gonna we're going to need to partner with somebody and you know it's it's just a much cleaner story from end to end right right so the big big change obviously that wasn't around ten years ago that is around today is public cloud right huge impact not only directly in in taking workloads to the public cloud but also I think much more importantly changing the way people think about provisioning thinking about the way people think about elastic capacity so as as the market has evolved the rise of AWS and any other public clouds how has that changed what you guys are doing how are you reacting to that house at a new opportunity you know to kind of grow the maturity of the core product yeah well the thing is we have taken a lot of approach you know that's been learning and evolving as well right so so you know developers and applications really figured out AWS and the public cloud early I think data protection has has followed along with a couple years of lag in terms of doing that so you know our perspective is we learned as well right so so 2015 2016 I think there was some resistance and I think ultimately when we started to follow those workloads into the cloud there was a little bit of a lift and shift what we've learned is that the architecture really matters when you get to the cloud so the efficient use of resources the ability to do things in a cloud like way to use for example object storage instead of block storage when when the case presents itself so we took our products and virtualize them and followed them into the cloud but we realized that just taking the on-premise version of the product and putting it in the cloud itself isn't enough right because at the end of the day the customer is paying for all the underlying resources and so if your architecture is an efficient from a cost perspective as well as a performance perspective it's not going to be a viable solution and so 2017-2018 we've really seen a big acceleration in our adoption in the cloud because we have adapted our architecture to be more cloud friendly and more cost-effective for our customers to deploy but it was a learning experience for sure you know and and I think we're continuing to learn and continue to develop in that space and there's a lot of opportunity ahead of us the other big change I think that's come that we see over and over and over is really data as an asset only as an asset but as a huge valuable asset that drives your business drives real lytx but then becomes actually something that drives your company value and I think we see that and the Facebook's of the world and the googles of the world of why they have these crazy high valuations relative to here to their revenue and their profits because they're getting value for the data alright great news for you right it used to be a sample the day of the day was a pain it was expensive to store I didn't want to keep it all now everyone wants all the data they want to analyze it in real time and they want to put it in a place where they can actually put multiple applications across that same data set to do all kinds of new analytics so again super opportunity for you guys people aren't storing any less data no absolutely yeah no the data amount being stored is definitely growing one of the things that we're seeing that that's this kind of pervasive is this idea of of really using the right data the right place the right time so accessibility to whether it is a data Lake or it is your protection copies or you know an instant access of your protection copies there's a lot of different thing customers are doing with data but it's no longer a one-size-fits-all proposition like it was back in the tape automation days where I'm just throwing all of this stuff into a box and and never accessing it again right so the dynamics are changing and continue to evolve I expect that if we have this conversation two or three years down the road we're going to see some amazing things happen in the next couple of years that and some of it we were not predicting now we're gonna find out as customer demand and as innovation guides us along right because then the other big piece is the media right we've talked about tapes and the original data domain was was in response to some issues with tape and we get spinning rust as everybody likes to call it and now of course flash so yeah again see change in terms of capability the cost is coming down it's no longer the super high-end thing just for super high value applications so very transfer transformative opportunity on the on the media side as well on the flashlight as well you hit on a couple of really key things data domain was very successful because it became viable and practical to displace tape automation and nobody was a fan of their tape automation environments and now I think we're gonna see that's that same shift you know spinning disk is right now being relegated to archival and backup purposes but we're gonna hit an inflection point very soon I think we're where every instance of spinning disk probably can be questioned and so we are actually doing the you know kind of getting ahead of that curve and coming out with all flash products as a choice for a customer so we'll still have spinning disk for some backup use cases but we'll also have you know be able to offer customers a choice of the data domain technology on an all flash set of platforms and that will give customers a chance to get out of the yeah that spinning disk business as well right good I wonder if I get what if I get chime in here I you guys were talking about the the technologies and the cloud and the architecture it's interesting it David the main really started out don't hate me for saying this but as a feature product and the key feature was data deduplication data domain had the best you had a lot of guys doing post process you had you know some guys trying to do server-side avemar itself for example but they domain really killed it with regard to data David II do and if this feature product became a platform and had an architecture people became as you know unicorn times 2 plus plus and so I wanted to ask you rich about that architecture and aware it can go you're talking about different media now beyond spinning disk you know it used to be just a kind of a dumb target you've now got integrated appliances you've got software that's integrated there so it's you know you talked about the scale and the capacity where do you see this architecture going I wonder if you could comment on yeah well I think a lot of that belongs in in the realm of the data management software that speaks to it and and by having a distributed ecosystem and having things like you know distributed segment processing so we can take data domains technology and extend it out into those data management activities because a lot of the what's happening in the market is as new workloads are coming into the market they're having their own methods and native tools built-in for data protection and to be able to leverage those and have a highly consolidated affect on the backend is still extremely valuable to our customers and you're right it was a differentiated product from a deduplication standpoint but really the feature was that I can keep my 30 60 or 90 days worth of copies that are separate from my primary copies so I putting them somewhere safe I can even put them under different governance from my primary storage or my primary application owners right and it's practical and feasible and and prior to that the only real way to do that was with tape automation deduplication has become more of a broader word itself and it goes beyond what data domain does so there's deduplication and primary storage but if you look at primary storage deduplication it's good but it's designed to help you reduce the use of primary storage by 2 or 3 times it doesn't touch on the 30 60 90 days of retention that data domain does so there the similar technologies and a common use of the word but but they're two different use cases that the the remains separate I think yeah and you know as a former practitioner the other you are I think a former customer the genius part of the genius of data domain was its ability to just plug in to existing processes yes you didn't have to change things up and so it was an easy in but but it's impressive that you've been able to keep that that architecture going I wanted to ask you about market share you aided them in has always had a sixty plus percent market share I think it's at sixty now but it's it's like the Cisco of purpose-built backhaul appliances you're able to sort of dominate that little segment of the market which keeps getting bigger what but now you've got a lot of new entrants you know on VC money pouring in a lot of noise in the marketplace I feel like you guys maybe a couple years ago took your eye off the wall and now you've got this renewed sense of a vigor you know maybe it was parked partly the acquisition but you know we've talked to Beth Phelan about this a number of times you've really refreshed the portfolio so so wonder if you can talk about that and my question is what gives you confidence that you can continue to maintain your dominance yeah that's a great question and things have really changed I think starting around 2014 we were having some internal conversations about things like simplification the consumerization of IT and and all of those those dollars that you're talking about are really being poured into companies that are trying to take a different approach they're going into the white space that we had kind of left open which was simplicity right if you if you look back 10 or 15 years and you look at the the data management and enterprise backup software space enterprise backup software has been complicated and as you add more use cases it has become even more complicated and the customer base is no longer tolerant of that that's something that that maybe 10 or 15 years ago that was kind of a badge of honor to be working with complex and people just don't have the time for that there's a lot of IT generalists and folks that are out there that don't want to go to training class you know you know five days or ten days out of the year to learn how to use a product so that was a really good thing that we're seeing in the marketplace in terms of making products simpler easier to use and more approachable with things like discoverable functionality we certainly have the you know put a lot of effort into going in that direction because we think that's the right direction but what gives me confidence is the underlying storage value proposition about efficiency and performance and scale is something that we've still think that we have a strong upper hand on and when it comes down to that you know we take cloud as an example our data reduction in the cloud we think allows a much lower cost to serve and you know the customer is going to pay for that cloud storage or that cloud compute regardless of which vendor they're trusting in terms of their their solutions so simple only goes so far we think we can get there with simple but we don't necessarily see our competition having the efficiencies scalability and and so forth that we've already had so that that's good that gives me a lot of confidence so when you talk to customers what's the big problem the big hairy problem that they're trying to solve in your space and how are you guys helping so I one of the two big problems I see is is really a lot of IT teams are confronted with they've got a digital transformation going on they've got a cloud strategy going on an IT isn't necessarily being invited to the table early enough or often enough to go ahead and help with that process so what you have is you a cloud team building applications bringing things online and then the data protection the backups the snapshots whatever they're doing to make sure that that data is safe is is a bit of an afterthought and it you know I think of DevOps and I think about the ops part and I've never really come across an application team that wanted to own the business responsibility for the risk of you know backups recovery replication and all of that and I think IT has a lot of established practices that would be good to inform how those things should be built so the number one thing that I'm talking to with my customers when we're talking about this whole you know tectonic shift and in the way things are being done is that IT and the digital transformation or the cloud team do need to speak early and often and proactively about how they approach data protection because they continue to need to have a strategy that evolves and make sure they keep themselves protected as they start moving these critical workloads into the cloud it's an age-old problem with backup and data protection people think of it as a back as a bolt-on is an afterthought and your point is right on it's got to be a fundamental part of any transformation it's just like security you can't bolt it on earth just doesn't scale yeah and it's very much like you know back in the day when open systems was just coming of age there was a lot of operational discipline that the mainframe teams had and the mid-range teams had but the open systems was the Wild West and eventually open systems learned and and and a lot of that you know was knowledge sharing about best practices and you know Mis became IT now IT is becoming you know DevOps and digital transformation we're seeing a lot of that same dynamic happening again and and you know my main point is just you know start those conversations and if you're on the IT side start those conversations proactively you might not be getting invited to the digital transformation party invite yourself rich has been quite a 10 years and and as I was just watching an Andy Jazzy interview if you think the last 10 years have been crazy you ain't seen nothing yet so you guys are in a great position to stay agile and I'm gonna steal your line that it's no longer an honor to work on complicated systems that's great yeah it's been great being here thanks for having me and looking forward to maybe coming back in ten years and seeing what changed so hopefully we won't wait 10 years so rich thanks for stopping by Dave thanks for checking in from Boston and it's great to see you as well thanks you guys thanks Dave thanks Jeff [Music]

>> From San Francisco, It's theCUBE. Covering Sumo Logic Illuminate 2018. Now here's Jeff Frick. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We are at Sumo Logic Illuminate 2018: about 600 people. I think its three times as big as it was last year here at the Hyatt San Francisco Airport in Burlingame, and on of the big topics of today is the release of this new report. It's called The State of Modern Applications in DevOps Security, and to talk all about it and the results and kind of the process we are excited to have Kalyan Ramanathan, excuse me, VP of Product Marketing at Sumo Logic. Welcome. >> Thank you, Jeff. >> So you've been doing this report for a while, correct? >> Yeah, exactly, I think this is the third version of this report, and from what we know the first and only report that looks at how, you know, leading edge customers actually build, run, manage, and secure their applications in public cloud environments. >> Right, so just a little history for people that aren't familiar: Sumo launched in the cloud natively, right, and I think you guys launched on AWS. >> Absolutely. >> Way back when, I think, one of our very first AWS shows we went to in 2013, Summit San Francisco, I remember it well, we had you guys on, and so you guys have really grown along with AWS, but obviously you have expanded well beyond just simply inside of AWS. >> That's right. So, the company was founded in 2010, and we were one of the first big data services to run on AWS. I think our founders, you know, ran into one of the AWS architects who describe this new thing called a cloud, and they were completely smitten by it. They thought that this was the next new wave of how services are going to be delivered, so it just made a lot of sense to build this machine data analytics platform, that we were building, or that we were planning to build on AWS. >> Right. >> The scalability, the agility, the, ya know, the flexibility that AWS offered was exactly what our platform needed, and so this was a marriage made in heaven. But we can support applications that run just about anywhere. We obviously support applications running on AWS extremely well; that's our DNA. We get those applications, because we build and run those applications ourselves, but we also support Azure. We support GCP. We support hybrid environments. Many of our customers, ya know, are either, ya know, built in the cloud, and they know only cloud, but a few of them are also making the transition to the cloud, are migrating their applications to the cloud, and you know, we believe that we live in an age where flexibility is extremely important, and we support our customers where ever their applications are today. >> Right, so let's look at some of the findings, so. >> Absolutely. >> Just from a process point of view, you interviewed your customer data base, right? Your, your numbers here? >> Yeah, yeah, I think, yeah. We looked at our 16 hundred customers. >> Sixteen hundred customers, okay. >> And an important point to make out here is that we don't interview our customers. What we do is to, essentially, collect data from our customers, which is what we do when we are doing machine data analytics, we anonymize those data, and we represent as to what is happening in terms of these applications. How do our customers build these applications, you know, manage them, and secure them? >> Right. >> So this is not a >> It's the real data, though. >> It's real data. >> This is not, this is not what they think they know, and they're going to answer the survey. >> Absolutely. Exactly. Right. >> And all the survey biases that can come up. >> You are very right, I mean, you know, that's what makes this report unique, right? >> Right, right. >> It's the first report where we're actually reflecting what customers actually do. It's not a survey. It's not an aggregation of, you know, data from ten other sources. This is as close to truth as you can get in terms of running and building and securing applications. >> Right. >> In the cloud environment. >> So, I was happy to see that the data supports a number of the hypotheses that we derive at a lot of the shows. >> Absolutely. >> That we go through. You know, right of the top: Docker and the adoption of Kubernetes in orchestration is growing rapidly. >> Absolutely, I mean, ya know, everywhere you go you hear containers: container this, container that, so, ya know, we see a similar adoption. Docker has grown from 14 percent to about 28 percent in this, as we see in this report, but what's interesting is also the growth of Kubernetes and orchestration, right? If you were to ask anyone, even in this conference, you know, about orchestration, let's say two or three years ago, and even the word Kubernetes, ya know, I'm sure you'd have gotten blank stares. >> Right, right. >> Here we are, two years into Kubernetes becoming, you know, somewhat mainstream, and we are already starting to see 30 per cent adoption of orchestration within AWS, and out of that 30 per cent, we almost see fifteen per cent of those folks using Kubernetes as a native technology. AWS has just announced their own Kubernetes service. I am sure if, when we have this conversation next year, >> Right. >> Kubernetes, you know, will become a household name. You will see 30 per cent adoption of Kubernetes alone, >> Right. >> Ya know, in a report of this kind. >> Well it's funny: when we were at VMworld a couple weeks ago, and Kubernetes was both in Pat's, Pat Gelsinger's keynote. >> Uh-huh. >> As well as Sonjay's, you know, so it's just, it really shows how fast in this type of a world a new technology adoption can just be put into place. >> Yeah, I mean, if you bring the right capabilities, if you have the right support, which is what Kubernetes does, and, obviously, if you have the right backing, you know, in the form of Google, obviously, incubating this project and then, you know, promoting it as an open source standard, and everybody is now falling behind it. Ya know, we support it. We hear it from our customers, and, you know, the data also bears this out. >> Right, so what about on the database side? What did you find on the database side? >> Yeah, I mean, the database results are always interesting for us, right? You know, I think the most important thing that we learned is that, you know, as customers are building apps in their public cloud environments, they really have a choice, ya know? If you were to build an on-prem, you know, application, once upon a time, I mean, you are usually stuck with Oracle or, ya know, MySQL or SQL Silver or some of those standard database fares everyone has heard about. >> Right. >> But when you, now, go to the cloud, when you migrate to the cloud, or when you are, you know, incubating your applications in the cloud to begin with, you want to re-think your database layer. This is the core layer that powers your application, and there are lots more, ya know, opportunities to, and options out there. >> Right. >> So, what we are seeing is, one, the growth of no-SQL databases: they are way more scalable, ya know, they handle big data way better that, ya know, traditional SQL databases, so we're definitely seeing a growth of that, of no-SQL databases. >> Right. >> What's also interesting is that, ya know, is customers have the choice. They are looking at other forms of databases. Ya know, I could look at Redis, I could look at MongoDB, I could look at Posgres, and, right, I'm not stuck going back to, ya know, our favorite Oracle or SQL Silver anymore. >> Right. What strikes me is that the definition of the requirement has been flipped upside-down. Before it was, "What infrastructure do we have? What's available that IT can deliver to me? What do we have licenses for, and what can I build on top of?" Now the application has taken center stage, so now it's "This is what I want to do with my application. What is it that I need underneath the covers to deliver that capability?" So it really flipped the whole thing on its head. >> Ya know, this also goes back to that, you know, sort of the democratization of decisions where, you know, developers, now, can make these choices. You know, once upon a time, right, I mean, someone, a muckity-muck in your organization says Oracle is the way to go, and everybody follows suite, follows suit. That's not the case any more, right? >> Right. >> I mean, the engineer, they're a developer who is building their application, especially in the microservices world, they can make choices in terms of what is a data server that they may choose to build into that microservcie? And that doesn't have to be Oracle every time. It doesn't have to be SQL Silver every time. You know, if Redis makes sense, if MongoDB makes sense, let's go build that into our into our platform. >> Right, so, another one, you know, serverless is all the hot buzz, and clearly that is supported here with some of the data around Lambda adoption. >> Yeah, I mean, Lambda growth, you know, continues to astound us. We are seeing Lambda grow from twelve per cent two years ago, which is when we did our first report, to now, you know, almost 30 per cent, you know? So, imagine that, right: one in three enterprises today are using Lambda, and this is a technology that is very easy to use, but architecture-wise, you need to re-think how you are putting your applications together with Lambda, and we are starting to see, you know, some wide-spread Lambda adoption, you know, within enterprises. >> Right, but isn't that the ultimate goal, I mean, as we get closer and closer to, you know, atomic versions of store, compute, & networking, I mean, shouldn't it all, ultimately, get there. >> Yeah. >> I mean, there's requirements, and, you know, there's reality I don't deal, you know, luckily I don't have to go turn the stuff on and run it, but, you know, that is the vision, right? Atomic units of compute, atomic units of store, atomic units of network. >> Yeah, I mean, look, serverless is the ultimate Nirvana when it comes to the cloud, right? I mean, the notion of the cloud is that, you know, I have an application. It needs to run. I don't worry about the infrastructure, and to a certain extent, I don't even worry about the management. So, serverless and Lambda is the manifestation of that. >> Right. >> Right, and what we are starting to see is that many customers are, at least dabbling with Lambda. Now, I won't say that customers are building their core application with Lambda yet, because that requires a re-think of their application itself, but what we are starting to see is that Lambda is used in DevOps, Lambda is used in integration, Lambda is a glue-ware that sort of ties all of these applications together. >> Right. >> In fact, you know, this report that we put together, a lot of it has actually been put together on the back of Lambda. We use Lambda extensively to collect this kind of data, and create a report of this kind. >> (chuckles) That's great! Another piece I wanted to make sure that we talked about is really, kind of, the break-down of the clouds. >> Uh-huh. >> Obviously you guys have a huge percentage of your business is, you know, you ask customers, you guys were born in AWS. >> That's right. >> That seems pretty logical, but what's interesting is a lot of multi-cloud, so, you know, I don't know if you distinguish between multi-cloud, hyper-cloud, but at the end of the day, as I think Ramin talked about in the keynote, right, there's going to be different places for different workloads. >> Absolutely. You know, look, as you rightfully pointed out, we are born in AWS, so we have an affinity to AWS, and so AWS customers also have an affinity to Sumo Logic, so it's not wonder that a big swath of our customers are built in AWS. Now, having said that, what we are also seeing is actually an acceleration of our customers, you know, adopting more and more AWS. I mean, they are the leaders in the space. I mean, I think nobody can, nobody can question that statistics. What is interesting, though, is that we are starting to see increased adoption of multi-cloud. We saw about five per cent of our customers dabble in multi-cloud last year. We are at close to ten per cent this year. We are also seeing increased adoption of Azure. We had a, you know, about five per cent of our customers use Azure last year. We are starting to see almost, I should say about eight per cent of our customers used Azure last year. We saw, we're seeing about fifteen per cent of our customers use Azure this year. >> Right, right. >> Right, so Azure is a, you know, has definitely become a very credible second cloud alternative for many of our customers. >> Sure. >> Now, we do see interest in GCP. It's not translated into lots of GCP adoption in production environments yet, but we're definitely seeing that increased interest, and I'm sure, you know, when we put this report together next year, you'll see some very credible and statistically relevant GCP data in this report. >> Right, right, so, Kalyan, there's a lot here, and we could go on for (chuckles) and on and on. So, people can go to the website. They can download the report, but... It's so great, but what I like most about this report is you lay out the facts, right, you lay out your findings, people can question your data source or this or that, but you lay out your methodology, but then you have very specific instructions for the IT buyer about what they should consider, and I think that is so powerful, because I think from the position of an IT purchaser today, >> Right. >> They've got to just be getting creamed with, you know, like, with things we're talkin' about, like, with serverless and Lambda and security and DevOps and >> Right. >> And the pace of change for them keeps going faster, so where do they even begin when they're doin' this kind of analysis? It's not just putting it out for an RFP anymore, right? >> Yeah, I mean, that was the intent of this report, right? I mean, at the, you know, when we started this report our goal was to provide accurate, real-time information about, you know, where are these modern apps in the public cloud going? You know, our leading-edge customers, like Airbnb and the Twitters and the Salesforce and the Adobes, know how to do this well, but there is a huge swath of our community that is, in some sense, perplexed, right? I mean, they see this cloud adoption happening. They see this cloud wave coming. They have cut their teeth on, you know, data centers and applications in the data center. How do I make that transition to the cloud? How do I, you know, follow these cloud-first companies and learn from these companies? And, so, what we wanted to do was to collect this data, anonymously surface this data, and provide, you know, this insight to this community so that they can, you know, in some sense emulate, you know, these leading-edge companies and learn how to architect, build, run and secure their apps. >> Right, right, and I love this little, you know, kind of, the new stack, if you will, the architecture set-up. >> Right. >> Cake chart that you've done in the past. All right, great! So, a lot of, ton of information. I'll give you the last word as we're here at Illuminate, triple last year's numbers. A little bit about where you guys are goin' next. What's, kind of, top of your mind? >> You know, look, you know, Sumo Logic, as a company, you know, we are doing exceptionally well in this machine data analytics space. We are the only cloud-native machine data analytics vendor. We are where the market is going, right? We understand cloud; the apps are going to the cloud. We know how to manage these apps exceptionally well, but more importantly, you know, we think that it's also important and it behooves us to make sure that we take our developer community, our ops community, our security community along with us, and that's the intent of this report. >> Right. >> It's to not sell product, though we do want to sell it eventually. >> Yeah. >> But it's to provide you guys, actually I should say, provide the community with the right kinds of information so that, you know, they can do their jobs better. >> Right, right. >> That's the goal of Sumo Logic. It's all about, you know, empowering the people who power these modern apps, which is actually the theme of this event itself. >> Well, very good. Well, we'll leave it there, and thanks for taking a few minutes of your time. >> Thank you very much, Jeff. >> All right, he's Kalyan. I'm Jeff. You're watchin' theCUBE. We're at Sumo Logic Illuminate at San Francisco Hyatt Regency by the airport. See ya next time. (hip music)

>> (Narrator) From San Francisco, it's theCUBE. Covering Sumo Logic Illuminate 2018. Now, here's Jeff Frick. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency at San Francisco airport in Burlingame, about 600 people. The second year this conference, about triple the amount of people that they had last year. A lot of buzz, a lot of activities, some really creative things that I've never seen in the conference world with the silent disco kind of treatment for the training is pretty cool. Everyone's in the same room listening to their own, in training, I've never seen that before. We're excited to have, fresh off the keynote, the leader of this party, President and CEO of Sumo Logic, Ramin Sayar. Ramin, great job on the keynote today. >> Great, thank you for having me today. >> Absolutely. >> Thanks for being here. >> So, a lot of passion really came through. It struck me and it was palatable in your keynote, really reaching out to the community and talking about being on this mission together. I wonder if you can speak a little bit to how important community is to you, to the company, and what you guys are trying to accomplish. >> Well the interesting thing about that, Jeff, is that that's really innate in our culture and that's part of, one of the reasons why I actually joined Sumo. Specifically, one of our core values is we're in it with our customers. And that permeates all the way through to every action that every employee takes every single day, and ultimately, is seen and felt here at an event like Illuminate. So when we talked about community, is we're living and breathing the same thing that a lot of our customers are every single day. All the challenges that they're dealing with, the cloud, the cost, the migrations, the training. And so the more we get intelligent in terms of using our own service, the better it is for the rest of the users in our community, so that was a big theme for not just what we wanted people to take away, but also naturally as part of the announcements we made around some of the new intelligence. >> Right, right. I think it's an under-reported kind of attribute of SaaS-based business models, in that you are in bed with your customer because you're taking money from them every month, or whatever the frequency is, so you've got to have this ongoing relationship and continue to deliver value. And we've heard that time and time again, we heard it from the MLB guy on stage, we had another partner on-- >> Samsung, the smart things. >> The smartphone, but we had another one here. But just talking about working together with your teams collaboratively to execute on the objectives at hand. Not just here's some stuff, I'll take the money, good luck, we'll see you next year. >> Yeah, interesting enough you point out something that's a precursor to being successful in the SaaS business, and that is, you're having to get reelected every single year. But we don't wait 'til every single year, we try to make sure from the moment we land a new customer that we help them understand what it's going to take for them to get, not just instant value, but ongoing value out of our service. And we often times make sure they also understand they we're actually living and breathing the same experience they are, so there's that trusted advisor relationship, not just a vendor relationship. >> Right. The other great thing I'd love to see, and I think we first interviewed Sumo at our first AWS San Francisco 2013, You guys definitely picked the right rocket ship to strap onto. But one of the things that we love to watch is kind of the change of a company from an application space to a platform space. 'Cause nobody has a line item for new platform, nobody wants to buy a new platform. I tried to launch a platform company as a platform, it doesn't work, you got to have an app. So that's what you guys did, but you've got the infrastructure and the architecture in place that's now allowing you to get into the platform play and the slide that really jumped out to me, and I took a picture of it on my camera, was the diversity of roles in organizations that have Sumo Logic. After, I think they've had 60 months, you start seeing customer success people, design people, quality assurance people, these are not engineers. This is not reliability, this is a whole separate set of people that are using this great tool that you guys have built to solve some different business objectives, and maybe the ones when they started the company. >> Well, that's predicated on how we started the company. We never started the company to be a silo tool use for one part of the organization. It was always meant for how do we take what was typically in the back room only to select few of folks in security or operations to other parts of the organization, thereby democratizing like we've been talking about. And so, over the last few years, since you mentioned AWS and the reinvent show, we spent an enormous amount of energy and investment in terms of making sure that we're constantly listening to our users, we're constantly redesigning and iterating on a user experience, so that we can actually extend from the power users that might be in development or operations or security, into these other teams that you've been mentioning. And now we're seeing evidence of that, which is phenomenal. >> So it's, you know, we go to so many shows, we talk to a lot of smart people, it's really fun. And one of the things that I've come to believe in terms of how do you drive innovation... Some really simple things, you give more people access to more data with the tools to manipulate it and then the ability to make decisions based on that data. And that was really a big part of your theme, in terms of, you know, some of the new product releases that you announced and also again what we just talked about in terms of the use cases, is giving more people the tools and the data so they can actually make innovative steps instead of just funneling it through you know, asking somebody to run a BI report for me or this or that. That's not the way anymore. >> You're spot on. And I think we're still earning that right, to be honest with you. And while we've seen massive adoption in terms of various profiles of users and the types of data, I think we're honestly just scratching the surface here. And specifically what I mean by that is, we've announced some interesting things around industry benchmarks and community insights and obviously the modern app report that you talked about and covered before, but there's also a different subset of users that are now embarking on and leveraging a platform like this, and those are the data engineers, and those are the data scientists, because they don't want to be left on the back room. They also want, just like security operations or analysts or development teams, to be able to collaborate, be able to iterate, be able to share their own experience with not just the service, but how they're to getting value out of this. And so what's most refreshing, and honestly something that we pay very close attention to, is the types of roles and users that are here. And you see people from interesting enough product or finance or success report to your comment, but that's innate in the value of something like this that we're referring to in terms of machine data analytics platform. >> Right. So you guys are in such a good spot with the machine data. The MLB guy was interesting. He just threw up a slide with a whole bunch of really big numbers. But even more than that, we were at an AT&T show on Monday that the conversation's all about 5G, and the big thing about 5G 100X, 100X more throughput than 4G, designed for machine-to-machine interaction. I mean, the tsunami of data that we've been living through up 'til now is going to be dwarfed by this continuing tsunami when we get 5G internet of things, industrial internet of things. You guys are pretty well positioned to take advantage of this big, giant trend. >> We are. But we're also being very conscious and prescriptive how we approach it. So we've been maniacally focused first on the new applications, and therefore the new architectures associated with these applications that are being built and born and bred in the cloud. Then we extended it to those that are being lifted and shifted, because we had to earn the trust and the right there, particularly those that were running traditionally on-prem, we want to rewrite the front end, and in doing so, we had to often times interface and interact and get sign-off by security. And so that naturally led us into the CISO, in the security operations analyst teams starting to understand, "What's going on over there? "Why are those guys using that service, and why aren't we?" So then we extended our opportunity to security analytics play, and you naturally pointed out there's other opportunities into connected devices, industrial IOT, and what we heard from some of our customers today, in consumer IOT. But we're going to go to it gradually. We're also going to go to it through partners, and really extend the platform as customers use it for those use cases, not necessarily how we see fit always. >> I wonder if you can dig a little deeper into how security has changed. You've been in the industry for a long time, go Gauchos, I saw you went to Santa Barbara, my daughter's at Santa Barbara now, so we're all about the Gauchos. But you've seen how security has changed from this walled garden or moat around the castle, however you wanted to describe it, into being baked everywhere, up and down the stack, throughout the applications, throughout the infrastructure, and how that's really changed everyone being involved in security, regardless of what your day job is or what your title is. >> See that's what's the interesting thing. You heard it from MLB and Neil. There's a shortage of security professionals that are out there, so it's no longer just a duty and a responsibility of security operations or analysts; it's everyone upstream. And that's the power of what Sumo provides. It can't be an afterthought. And so what we're helping understand for our customers to understand is, as you architect these new workloads, specifically looking at micro services or containers or cloud, put some forethought and insight into what does that mean from not just an operational perspective, how do you instrument, collect, and log and events and metrics, but also from a security perspective. And so when you're able to leverage one platform to do so, it actually is a connecting mechanism, meaning that it's bringing these teams together versus isolating and siloing them like in the past. >> Right, right. I'd love to jump... You did a little bit in your report and now you announced some of the benchmarks and stuff about how you're able to aggregate, anonymize and aggregate back end data from a lot of different customers to start to share that information. To use BI and machine intelligence to optimize. To use benchmarks and to help your customers do a better job. And you're sitting on a boatload of data. And it's really a great way to provide another layer of value, beyond just the core functions of the products. >> I totally agree. And we are still early in that journey, though. And as I mentioned earlier in the announcements today, one of the ways that we're fixated on making sure we continue to get more data is constantly look for ways that we can bend that cost curve down for our customers. So that they can start to ingest more their tier-two, tier-three data or their lower-performing data so we can get more intelligent, more smart, and also provide that value, add back into the community and the service. So we felt that we weren't ready before because we needed to see multiple sets of years across multiple different types of data sets to be able to launch and release something like global insights. We started actually three years ago with a modern app report, because that was usage-based, not survey-based. And it's really interesting-- >> Real data. >> Because it's real data, right? But we were contemplating, even three years ago when we did the report, do we start to put out some of these benchmarks? And we felt that we were too early, because we needed more data, we needed different types of data from across different geographies, different types of usage, different technologies, and so we held off. And so that was one of the things that we've been paying very close attention to, and what the announcement today was all centered on is, yes, we've been talking about some insights around the industry, but you as the community of users here are helping us get smart and helping each other get smarter, and we're going to start to allow you guys to compare yourselves, back to your question, around, "Am I best in class from an operational KPI perspective?" And what does that mean? From utilization versus cost. And, "Am I best in class from a key risk perspective?" From a security perspective, for example. And how does that compare to others? And when you're staring the reality of that type of data in your face, it forces you to do something, take action. And the whole premise here is insights and intelligence. And so the more forthcoming, transparent we are with our customers in terms of these types of insights and intelligence, the more they're going to be using and adopting the platform, and hopefully, together as a community, getting smarter, more efficient. >> The graphic you showed, you get a whole bunch of green lights and one yellow light, all the eyes go right to... "What the heck, what's my yellow light?" Alright, I give you the last word on a word that you used again a number of times in your keynote, and that's trust. >> Yes. >> At the end of the day, that is such an important word in all types of relationships, but certainly in business relationships. Why're you putting the focus on that? Clearly it's important, you're highlighting trust. In fact I think you said, "We are your trusted steward for your data." Really important attribute for this company. >> Well that's been something early on, Jeff, in our architecture and things we did in terms of guaranteeing data sovereignty, privacy, encryption. We took no short change or shortcuts in terms of how we architect the service, eight-plus years ago. And we don't take any of those now. And the trust comment is because we have to trust, we have to build the trust and relationship, not just in terms of the value they're getting out of using the service, but that we're going to make sure that we keep their data safe and secure. Because we are PCI certified. We are also HIPAA certified, SOC type one, type two, we're doing GPR, all these other attestations and stuff that our customers have to face, we're also facing. So together, we're actually creating a trusted network, and that's the strategy here, is to create that trusted network. To share the insights. >> Well the passion comes through. And again, congratulations on the show, and the success, and we continue to enjoy watching the ride. >> Thank you very much for being part of it. It's great to be here with you. >> He's Ramin, I'm Jeff, you're watching theCUBE. We're at Sumo Logic Illuminate 2018. Thanks for watching. (inquisitive electronic music)