>> 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.

>> 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.