(upbeat music) >> Live, from Miami Beach, Florida, it's theCUBE, covering UiPath Forward Americas. Brought to you by UiPath. >> Welcome back to the former home of Lebron James, I'm Dave Vellante, this is two minimum, we are here at South Beach at the hotel Fontainebleau. This is UiPath Forward Americas, and this is theCUBE, the leader in live tech coverage Leo Da Silva is here, he is the process excellent leader for Best Day Travel and Arnold Schiemann who's Vice President of Latin America and Spain. You get to go to all the fun places for Symphony. Welcome to theCUBE >> Thank you, thank you guys for your invitation >> You're very welcome, Leo let's start with you Best Day Travel, travel site, specializing in Mexico and other parts of the region tell us about the company >> Well, we have a leadership in Mexico we are, the last year we have five point four million travelers, okay? And there's a lot of people, okay? We've been in the business for 35 years, 34 years actually, okay? So, we're pretty solid, okay? While 75% of the all the transactions we have online, okay? And 25% we have offline, and that's why we're doing, all the transformation that we're doing is under this 25%, alright? Like, just to get the additional transformation and everything. >> So 35 years, so you started before the internet (Leo laughing) >> So I guess you should be 100% offline you obviously successfully made that transition. >> That's correct, that's correct. >> Okay, and Arnold, Symphony is the solution provider right? the implementation partner in this case, right? tell us about symphony and your role. >> Well, Symphony is probably the is particularly, suddenly concentrated on our PA management and our PA design, and our PA process rewardization. We were invited by Best Day Travel Group to look at the process, to look at the project and we embark in a very interesting transformation for them, so that they could move into their PA arena with a clear road map. >> So you guys are both process experts I mean that's, >> Yes >> You've got process in your title talk more about your role, if you would. >> Yeah, well, I'm a green belt, okay? And at least six sigma, and we use this methodology actually, and we are like, two years ago we implemented like a BPM, the department, you know inside the company, just to lead this transformation, okay? So that's what we're seeking right now to lead this transformation and, it's a very good challenge, you know? It's not easy, but we are trying to do our best. >> With your six sigma background, I think it would really tie right into what RPA is, 'cause you can really understand what has variance, and what is pretty standardized and that would seem is that the direct correlation with thing that you can have, the robot and the automation based on, really, the variance piece? >> Yes, totally, you know, well, when you start, all the implementation was right before where start you like to do a benchmark and you're able to see which technology we wanted to use and well, we found UiPath, alright? In which we found Symphony, and but it's not exactly, I think the technology is the last thing, right? So, the technology is the enabling alright? To do all those thing happening but if you don't have, like process management, you know, if you don't have that, it's kind of difficult to reach the target, okay? So, yeah, it's pretty much, I think it's when you, I think the most challenging is let people know what they're doing wrong you know, what they're doing repeating tasks, right so, when you do, like, the process walk through, people just get amazed, you know, like, what? Are you serious, we're doing that? >> When did you start? >> We started in February >> This year? >> Yeah >> Okay, so, take us back to February or January whatever, December, when you were maybe even before that, thinking about the business case. How did it come about, and how'd you guys meet? Take us through the sort of initiative. >> Yeah, well, right before, it was six months before I think it was, on July of last year, we started a conversation, right? And when I found that, within like six months of benchmarking and, we reached that like UiPath, and we start to ... trying to get something different, you know? To do something different enterprise and we had this need, okay? From inside, you know, from back office to tranformate because it's operation sometimes it costs a lot, alright? The first step that we did was like a future of work accelerator, okay? Which is, it's this scan, it's a total scan of the area, okay? And to see how how big are the opportunities, okay? To transformate things, right, so was the first step and after we had the pilot, we have three or four projects ongoing. >> And you were involved from the beginning Arnold, last July? >> Yes, yes >> One thing which was really very interesting about the project is that the client was the C.E.O and the C.F.O was totally the C-suite involvement So, and we believe that our PA is about the business, is about the process, it was ideal. So, we had really I believe it was really not work but, really a good time that we spent together integrating very closely with the team from Best Day Travel Group, to the point that you couldn't tell who was from Best Day and who was from Symphony, and then we were able to present to the C-suite, the result of the road map to move forward with a very clear business case, the process that was going to be robotized. Simultaneously, Best Day wanted approved inside, saying lets develop robotized version of one of the processes, and we did one which had been quite successful, we were just talking that the amount of work that that robot is handling today life, is such that either robot doesn't operate, he wouldn't know what to do because there is so much work to do behind in the past, and he doesn't know what he did, but today, it is almost impossible to recreate that. >> Yeah, that's correct, singularity is here >> One of the things that maybe you can help me understand, 'cause I'm a little bit new to this technology, how do you figure out, how do you size this, like how do you know how many things a robot can do, we heard one of the customers has a thousand robots, how does this scale, and how does this build out inside of a customer? >> Two thing that we do is that we look at the company, we identify those process, with heavy like, say, head count with lots of repetitive tasks that can be partially or totally robotized, and then we present it as a road map because the first question they have is "how do we start?" I mean, this is a company, 3000 people 4 million passengers, where do we start? How we get good advantage of the robots and that's how we did it, and then it's going on, the project we just did the first part, we continue now with the second part which is going to be even more interesting. >> What'd the business case look like? I mean, was it a saving money, making presumably some of this was cost reduction right off the bat, right? >> Yes, yes >> Lets talk about that business case what's that framework look like? >> Well, the action will have a pilot, that we just did, we launched already, alright? The business case was like, to to reduce cost, alright? The operational cost is very high, okay? So, now, we have like, just to have an idea the situation before would have, like six person working, you know, like the eight hour shift, okay? And doing like issuing tickets and you know and right now we have, like, just one robot and we built a capability of, 126% okay? On this, just with one robot, alright, and yeah, it's amazing, its amazing and 24/7, you know, right now it working pretty fine. >> Specifically, where do the cost savings come from? >> Well, the cost savings is not exactly that ease, but it's a customer's experience, okay? And also the capability that you can build alright? To get more sales, okay? And there's another project that, before that we had the first one, we have to to reduce the cost of the operation you, know, for 65 people, alright? And ... the transactions cost a lot of money for us, okay? So that's how we're trying to we're trying to understand that and we're trying to eliminate those costs or reduce, you know like, as much as we can. >> Its a part of that, you redeploy people, you put 'em on other tasks, is that what you're doing? >> Yes, yes, we free them up, you put another, you add value task, right? >> So the C.F.O is one of the stakeholders here, >> It was >> So many C.F.Os might say "okay, well, we're "not going to cut head count, so where do I "get my savings?" so the answer, if I'm hearing it is well we're going to increase revenue because these people are going to be on other tasks, and >> That's it, yes >> And, do you have visibility in line of sight as to how fast that can happen, whether, is it already starting to happen? >> Yeah, it already start to happen, already start to happen, like in, you know, this project was we have the roll back in 15 days >> I was going to ask you what the break even was it was inside of a month? >> You know, its already paid, it all 15 days, it's already paid, right so, yeah, the C.F.O is pretty happy with that. >> The first project was relatively small right? >> Yeah, yeah yeah. >> You proved it out and now you're going to throw gasoline on the fire >> That's it, that's it. >> That's great, so what's next for you guys? >> Well, next, we are go to the customer service you know, like ano-traceability, there's a traceability project that we have to do, alright? Just to ... To have the client in front of everything, you know? So that's our strategy right now and we're going to do, well Symphony is going to help us out with our PA and with implementation and the process, because its going to be a new process, it doesn't exist, alright? So there's going to be a brand new one so we have to create from scratch. >> Arnold, I wonder if you can go a little broader for us on this, it sounds like you've got a perfect partner inside the company with, you know, process in his title you've got the C-suite engaged, is that a typical deployment, what are you finding? >> Is not typical but it is, that is something that we look for all the time. 'cause it's, if the client is not engaged, we can do nothing, if the C-suite is not engaged, there is very little process people can do and by being engaged the C-suite, we're driving the cost reductions, but there is another point besides cost, consistency, and also we are eliminating side loss that had existed for long time, 'cause the companies are starting with one organization then another one, another one and all of them touch the customer what the probably will be doing to them hopefully before the end of the year, early next year, to be able to see the transverse of the customer, one and a half million passengers arriving to Cancún and they are passengers. But you don't know how many people will come back so you better know that these guys came here they like to go to the scuba diving next time he's around, we can offer him a scuba diving, we can pick him up from the airport, we can offer other services and then, the company is structured to be exponentially, so that you can grow from 4 million to 8 million passengers without adding head count, adding, that is the future of Best Day Travel Group and that's why we have engaged the management. >> Okay, so you're looking at the moon shot double the number of passengers served with the same head count, that's a huge productivity boost, so I'm hearing 15 day break even, some of that was hard cost reduction, its revenue increased, its proven, now you're going to invest more consistency, better customer service, cross selling, hey they like to scuba dive, maybe we can make an offer here, and better data allows you to do that that's going to summarizes the the business case and we're talking I mean, I don't want to, you know, squeeze the M.P.V at it, but we're talking millions? Hundreds of thousands? >> Millions >> Hundreds of millions? >> Millions right? >> Yeah, yeah, pretty much, it's a huge number you, know, its a huge number and, we have a lot of opportunities and, I think it's going to be a success, you know? >> And presumably the employees want to be part of this ride, right? They want to get, whether it's re-trained, or become R.P.A experts, deploy this technology, drive their digital automation and service those 8 million customers with the same resources you know, or invest in other resources. >> yes >> New growth areas. >> Yes, yes. >> Great story >> Yeah, it is, it is, >> we're working hard >> (laughs) figuring it out >> We're privileged to have been work with them because they are, I say unique but it was done for us from day one everything was put in place, engagement, people, and then the company itself is very easy to manipulate and transform because of the way that it was structured 30 years ago. >> And why UiPath? I mean, you said I chose them last summer why, why'd they win? >> Well, because of, well during a benchmarking, I can see a lot of difference between them, you know? And we have concluded that, well they actually Symphony recommend us, alright? So, you want this, you want that for this situation, it's going to be the best solution, right? And after that, we're pretty sure that it's it's the best it's the best choice, right? Because of the personalities, because a lot of stuffs that they have they can bring to us, you know? >> Do you worry about, do you worry about shadow R.P.A, like (laughter) >> The divisions going off and doing their own robots, or have you guys got a handle on that? >> Yeah, you know (laughing) no, not worried about that, you know, but yeah it's going to happen. >> It's a good thing. >> Alright, gentlemen, thanks so much for coming on theCUBE it was great to have you. >> Thank you for inviting us >> Alright keep it right there everybody, Stu and I will be back at UiPath Forward Americas right after this short break, you're watching theCube, we'll be right back. (closing music)

>>Really excited about this year's data, citizens with so many of you together. Uh, I'm going to talk today about accessible data, because what good is the data. If you can get it into your hands and shop for it, but you can't understand it. Uh, and I'm here today with, uh, bald, really thrilled to be here with Paul. Paul is an award-winning author on all topics data. I think 20 books with 21st on the way over 300 articles, he's been a frequent speaker. He's an expert in future trends. Uh, he's a VP at cognitive systems, uh, over at IBM teachers' data also, um, at the business school and as a champion of diversity initiatives. Paul, thank you for being here, really the conformance, uh, to the session with you. >>Oh, thanks for having me. It's a privilege. >>So let's get started with, uh, our origins and data poll. Um, and I'll start with a little story of my own. So, uh, I trained as an engineer way back when, uh, and, um, in one of the courses we got as an engineer, it was about databases. So we got the stick thick book of CQL and me being in it for the programming. I was like, well, who needs this stuff? And, uh, I wanted to do my part in terms of making data accessible. So essentially I, I was the only book that I sold on. Uh, obviously I learned some hard lessons, uh, later on, as I did a master's in AI after that, and then joined the database research lab at the university that Libra spun off from. Uh, but Hey, we all learned along the way. And, uh, Paula, I'm really curious. Um, when did you awaken first to data? If you will? >>You know, it's really interesting Stan, because I come from the opposite side, an undergrad in economics, uh, with some, uh, information systems research at the higher level. And so I think I was always attuned to what data could do, but I didn't understand how to get at it and the kinds of nuances around it. So then I started this job, a database company, like 27 years ago, and it started there, but I would say the awakening has never stopped because the data game is always changing. Like I look at these epochs that I've been through data. I was a real relational databases thinking third normal form, and then no SQL databases. And then I watch no SQL be about no don't use SQL, then wait a minute. Not only sequel. And today it's really for the data citizens about wait, no, I need SQL. So, um, I think I'm always waking up in data, so I'll call it a continuum if you will. But that was it. It was trying to figure out the technology behind driving analytics in which I took in school. >>Excellent. And I fully agree with you there. Uh, every couple of years they seem to reinvent new stuff and they want to be able to know SQL models. Let me see. I saw those come and go. Uh, obviously, and I think that's, that's a challenge for most people because in a way, data is a very abstract concepts, um, until you get down in the weeds and then it starts to become really, really messy, uh, until you, you know, from that end button extract a certain insights. Um, and as the next thing I want to talk about with you is that challenging organizations, we're hearing a lot about data, being valuable data, being the new oil data, being the new soil, the new gold, uh, data as an asset is being used as a slogan all over. Uh, people are investing a lot in data over multiple decades. Now there's a lot of new data technologies, always, but still, it seems that organizations fundamentally struggle with getting people access to data. What do you think are some of the key challenges that are underlying the struggles that mud, that organizations seem to face when it comes to data? >>Yeah. Listen, Stan, I'll tell you a lot of people I think are stuck on what I call their data, acumen curves, and you know, data is like a gym membership. If you don't use it, you're not going to get any value on it. And that's what I mean by accurate. And so I like to think that you use the analogy of some mud. There's like three layers that are holding a lot of organizations back at first is just the amount of data. Now, I'm not going to give you some stat about how many times I can go to the moon and back with the data regenerate, but I will give you one. I found interesting stat. The average human being in their lifetime will generate a petabyte of data. How much data is that? If that was my apple music playlist, it would be about 2000 years of nonstop music. >>So that's some kind of playlist. And I think what's happening for the first layer of mud is when I first started writing about data warehousing and analytics, I would be like, go find a needle in the haystack. But now it's really finding a needle in a stack of needles. So much data. So little time that's level one of mine. I think the second thing is people are looking for some kind of magic solution, like Cinderella's glass slipper, and you put it on her. She turns into a princess that's for Disney movies, right? And there's nothing magical about it. It is about skill and acumen and up-skilling. And I think if you're familiar with the duper, you recall the Hadoop craze, that's exactly what happened, right? Like people brought all their data together and everyone was going to be able to access it and give insights. >>And it teams said it was pretty successful, but every line of business I ever talked to said it was a complete failure. And the third layer is governance. That's actually where you're going to find some magic. And the problem in governance is every client I talked to is all about least effort to comply. They don't want to violate GDPR or California consumer protection act or whatever governance overlooks, where they do business and governance. When you don't lead me separate to comply and try not to get fine, but as an accelerant to your analytics, and that gets you out of that third layer of mud. So you start to invoke what I call the wisdom of the crowd. Now imagine taking all these different people with intelligence about the business and giving them access and acumen to hypothesize on thousands of ideas that turn into hundreds, we test and maybe dozens that go to production. So those are three layers that I think every organization is facing. >>Well. Um, I definitely follow on all the days, especially the one where people see governance as a, oh, I have to comply to this, which always hurts me a little bit, honestly, because all good governance is about making things easier while also making sure that they're less riskier. Um, but I do want to touch on that Hadoop thing a little bit, uh, because for me in my a decade or more over at Libra, we saw it come as well as go, let's say around 2015 to 2020 issue. So, and it's still around. Obviously once you put your data in something, it's very hard to make it go away, but I've always felt that had do, you know, it seemed like, oh, now we have a bunch of clusters and a bunch of network engineers. So what, >>Yeah. You know, Stan, I fell for, I wrote the book to do for dummies and it had such great promise. I think the problem is there wasn't enough education on how to extract value out of it. And that's why I say it thinks it's great. They liked clusters and engineers that you just said, but it didn't drive lineup >>Business. Got it. So do you think that the whole paradigm with the clouds that we're now on is going to fundamentally change that or is just an architectural change? >>Yeah. You know, it's, it's a great comment. What you're seeing today now is the movement for the data lake. Maybe a way from repositories, like Hadoop into cloud object stores, right? And then you look at CQL or other interfaces over that not allows me to really scale compute and storage separately, but that's all the technical stuff at the end of the day, whether you're on premise hybrid cloud, into cloud software, as a service, if you don't have the acumen for your entire organization to know how to work with data, get value from data, this whole data citizen thing. Um, you're not going to get the kind of value that goes into your investment, right? And I think that's the key thing that business leaders need to understand is it's not about analytics for kind of science project sakes. It's about analytics to drive. >>Absolutely. We fully agree with that. And I want to touch on that point. You mentioned about the wisdom of the crowds, the concept that I love about, right, and your organization is a big grout full of what we call data citizens. Now, if I remember correctly from the book of the wisdom of the crowds, there's, there's two points that really, you have to take Canada. What is, uh, for the wisdom of the grounds to work, you have to have all the individuals enabled, uh, for them to have access to the right information and to be able to share that information safely kept from the bias from others. Otherwise you're just biasing the outcome. And second, you need to be able to somehow aggregate that wisdom up to a certain decision. Uh, so as Felix mentioned earlier, we all are United by data and it's a data citizen topic. >>I want to touch on with you a little bit, because at Collibra we look at it as anyone who uses data to do their job, right. And 2020 has sort of accelerated digitization. Uh, but apart from that, I've always believed that, uh, you don't have to have data in your title, like a data analyst or a data scientist to be a data citizen. If I take a look at the example inside of Libra, we have product managers and they're trying to figure out which features are most important and how are they used and what patterns of behavior is there. You have a gal managers, and they're always trying to know the most they can about their specific accounts, uh, to be able to serve as them best. So for me, the data citizen is really in its broadest sense. Uh, anyone who uses data to do their job, does that, does that resonate with you? >>Yeah, absolutely. It reminds me of myself. And to be honest in my eyes where I got started from, and I agree, you don't need the word data in your title. What you need to have is curiosity, and that is in your culture and in your being. And, and I think as we look at organizations to transform and take full advantage of their, their data investments, they're going to need great governance. I guarantee you that, but then you're going to have to invest in this data citizen concept. And the first thing I'll tell you is, you know, that kind of acumen, if you will, as a team sport, it's not a departmental sport. So you need to think about what are the upskilling programs of where we can reach across to the technical and the non-technical, you know, lots and lots of businesses rely on Microsoft Excel. >>You have data citizens right there, but then there's other folks who are just flat out curious about stuff. And so now you have to open this up and invest in those people. Like, why are you paying people to think about your business without giving the data? It would be like hiring Tom Brady as a quarterback and telling him not to throw a pass. Right. And I see it all the time. So we kind of limit what we define as data citizen. And that's why I love what you said. You don't need the word data in your title and more so if you don't build the acumen, you don't know how to bring the data together, maybe how to wrangle it, but where did it come from? And where can you fixings? One company I worked with had 17 definitions for a sales individual, 17 definitions, and the talent team and HR couldn't drive to a single definition because they didn't have the data accurate. So when you start thinking of the data citizen, concept it about enabling everybody to shop for data much. Like I would look for a USB cable on Amazon, but also to attach to a business glossary for definition. So we have a common version of what a word means, the lineage of the data who owns it, who did it come from? What did it do? So bring that all together. And, uh, I will tell you companies that invest in the data, citizen concept, outperform companies that don't >>For all of that, I definitely fully agree that there's enough research out there that shows that the ones who are data-driven are capturing the most markets, but also capturing the most growth. So they're capturing the market even faster. And I love what you said, Paul, about, um, uh, the brains, right? You've already paid for the brains you've already invested in. So you may as well leverage them. Um, you may as well recognize and, and enable the data citizens, uh, to get access to the assets that they need to really do their job properly. That's what I want to touch on just a little bit, if, if you're capable, because for me, okay. Getting access to data is one thing, right? And I think you already touched on a few items there, but I'm shopping for data. Now I have it. I have a cul results set in my hands. Let's say, but I'm unable to read and write data. Right? I don't know how to analyze it. I don't know maybe about bias. Uh, maybe I, I, I don't know how to best visualize it. And maybe if I do, maybe I don't know how to craft a compelling persuasion narrative around it to change my bosses decisions. So from your viewpoint, do you think that it's wise for companies to continuously invest in data literacy to continuously upgrade that data citizens? If you will. >>Yeah, absolutely. Forest. I'm going to tell you right now, data literacy years are like dog years stage. So fast, new data types, new sources of data, new ways to get data like API APIs and microservices. But let me take it away from the technical concept for a bit. I want to talk to you about the movie. A star is born. I'm sure most of you have seen it or heard it Bradley Cooper, lady Gaga. So everyone knows the movie. What most people probably don't know is when lady Gaga teamed up with Bradley Cooper to do this movie, she demanded that he sing everything like nothing could be auto-tuned everything line. This is one of the leading actors of Hollywood. They filmed this remake in 42 days and Bradley Cooper spent 18 months on singing lessons. 18 months on a guitar lessons had a voice coach and it's so much and so forth. >>And so I think here's the point. If one of the best actors in the world has to invest three and a half years for 42 days to hit a movie out of the park. Why do we think we don't need a continuous investment in data literacy? Even once you've done your initial training, if you will, over the data, citizen, things are going to change. I don't, you don't. If I, you Stan, if you go to the gym and workout every day for three months, you'll never have to work out for the rest of your life. You would tell me I was ridiculous. So your data literacy is no different. And I will tell you, I have managed thousands of individuals, some of the most technical people around distinguished engineers, fellows, and data literacy comes from curiosity and a culture of never ending learning. That is the number one thing to success. >>And that curiosity, I hire people who are curious, I'll give you one more story. It's about Mozart. And this 21 year old comes to Mozart and he says, Mozart, can you teach me how to compose a symphony? And Mozart looks at this person that says, no, no, you're too young, too young. You compose your fourth symphony when you were 12 and Mozart looks at him and says, yeah, but I didn't go around asking people how to compose a symphony. Right? And so the notion of that story is curiosity. And those people who show up in always want to learn, they're your home run individuals. And they will bring data literacy across the organization. >>I love it. And I'm not going to try and be Mozart, but you know, three and a half years, I think you said two times, 18 months, uh, maybe there's hope for me yet in a singing, you'll be a good singer. Um, Duchy on the, on the, some of the sports references you've made, uh, Paul McGuire, we first connected, uh, I'm not gonna like disclose where you're from, but, uh, I saw he did come up and I know it all sorts of sports that drive to measure everything they can right on the field of the field. So let's imagine that you've done the best analysis, right? You're the most advanced data scientists schooled in the classics, as well as the modernist methods, the best tools you've made a beautiful analysis, beautiful dashboards. And now your coach just wants to put their favorite player on the game, despite what you're building to them. How do you deal with that kind of coaches? >>Yeah. Listen, this is a great question. I think for your data analytics strategy, but also for anyone listening and watching, who wants to just figure out how to drive a career forward? I would give the same advice. So the story you're talking about, indeed hockey, you can figure out where I'm from, but it's around the Ottawa senators, general manager. And he made a quote in an interview and he said, sometimes I want to punch my analytics, people in the head. Now I'm going to tell you, that's not a good culture for analytics. And he goes on to say, they tell me not to play this one player. This one player is very tough. You know, throws four or five hits a game. And he goes, I'd love my analytics people to get hit by bore a wacky and tell me how it feels. That's the player. >>Sure. I'm sure he hits hard, but here's the deal. When he's on the ice, the opposing team gets more shots on goal than the senators do on the opposing team. They score more goals, they lose. And so I think whenever you're trying to convince a movement forward, be it management, be it a project you're trying to fund. I always try to teach something that someone didn't previously know before and make them think, well, I never thought of it that way before. And I think the great opportunity right now, if you're trying to get moving in a data analytics strategy is around this post COVID era. You know, we've seen post COVID now really accelerate, or at least post COVID in certain parts of the world, but accelerate the appetite for digital transformation by about half a decade. Okay. And getting the data within your systems, as you digitize will give you all kinds of types of projects to make people think differently than the way they thought before. >>About data. I call this data exhaust. I'll give you a great example, Uber. I think we're all familiar with Uber. If we all remember back in the days when Uber would offer you search pricing. Okay? So basically you put Uber on your phone, they know everything about you, right? Who are your friends, where you going, uh, even how much batteries on your phone? Well, in a data science paper, I read a long time ago. They recognize that there was a 70% chance that you would accept a surge price. If you had less than 10% of your battery. So 10% of battery on your phone is an example of data exhaust all the lawns that you generate on your digital front end properties. Those are logs. You can take those together and maybe show executive management with data. We can understand why people abandoned their cart at the shipping phase, or what is the amount of shipping, which they abandoned it. When is the signal when our systems are about to go to go down. So, uh, I think that's a tremendous way. And if you look back to the sports, I mean the Atlanta Falcons NFL team, and they monitor their athletes, sleep performance, the Toronto Raptors basketball, they're running AI analytics on people's personalities and everything they tweet and every interview to see if the personality fits. So in sports, I think athletes are the most important commodity, if you will, or asset a yet all these teams are investing in analytics. So I think that's pretty telling, >>Okay, Paul, it looks like we're almost out of time. So in 30 seconds or less, what would you recommend to the data citizens out there? >>Okay. I'm going to give you a four tips in 30 seconds. Number one, remember learning never ends be curious forever. You'll drive your career. Number two, remember companies that invest in analytics and data, citizens outperform those that don't McKinsey says it's about 1.4 times across many KPIs. Number three, stop just collecting the dots and start connecting them with that. You need a strong governance strategy and that's going to help you for the future because the biggest thing in the future is not going to be about analytics, accuracy. It's going to be about analytics, explainability. So accuracy is no longer going to be enough. You're going to have to explain your decisions and finally stay positive and forever test negative. >>Love it. Thank you very much fall. Um, and for all the data seasons is out there. Um, when it comes down to access to data, it's more than just getting your hands on the data. It's also knowing what you can do with it, how you can do that and what you definitely shouldn't be doing with it. Uh, thank you everyone out there and enjoy your learning and interaction with the community. Stay healthy. Bye-bye.

>>mhm Yes, everyone, welcome back to the cubes coverage of dr khan 2021. I'm john for your host of the cube. Got a great segment here. One of the big supporters and open source amazon web services returning back second year. Dr khan virtual Deepak Singh, vice president of the compute services at AWS Deepak, Great to see you. Thanks for coming back on remotely again soon. We'll be in real life. Reinvent is going to be in person, we'll be there. Good to see you. >>Good to see you too, john it's always good to do these. I don't know how how often I've been at the cube now, but it's great every single time your >>legend and getting on there, a lot of important things to discuss your in one of the most important areas in the technology industry right now and that is at the confluence of cloud scale and modern development applications as they shift towards as Andy Jassy says, the new guard, right. It's been happening. You guys have been a big proponent of open source and enabling open source is a service creating business models for companies. But more importantly, you guys are powering, making it easier for folks to use software. And doctor has been a big relationship for you. Could you take a minute to first talk about the doctor, a W S relationship and your involvement and what you're doing? >>Yeah, actually it goes back a long way. Uh you know, Justin, we announced PCS had reinvented 2014 and PCS at that time was very much managed orchestration service on top of DACA at that time. I think it was the first really big one out there from a cloud provider. And since then, of course, the world has evolved quite a bit and relationship with DR has evolved a lot. The thing I'd like to talk to is something that we announced that Dr last year, I don't remember if I talked about it on the cube at that time. But last year we started working with DR on how can we go from doctor Run, which customers love or DR desktop, which customers love and make it easy for people to run containers on pcs and Fergie. Uh so most new customers running containers and AWS today start with this Yes and party or half of them and we wanted to make it very easy for them to start with where they are on the laptop which is often bucket to stop and have running services the native US. So we started working with DR and that that collaboration has been very successful. We want to keep you look forward to continuing to work on evolving that where you can use Docker compose doctor, desktop, doctor run the fuel that darker customers used and the labour grand production services on the end of your side, which is the part that we've got that on. So I think that's one area where we work really well together. Uh, the other area where I think the two companies continue to work well together. It's open source in general as some of, you know, AWS has a very strong commitment to contain a. D uh, EKS our community service is moving towards community. Forget it actually runs all on community today and uh, we collaborate dr Rhonda on the Ocr specification because, you know, the Oc I am expect is becoming the de facto packaging format idea. W S. This morning we launched yesterday, we launched a service called Opera. And the main expected input for opera is an Ocr image are being in this Atlanta as well, where those ci images now a way of packaging for lambda. And I think the last one I like to call out and it has been an amazing partnership and it's an area where most people don't pay attention is amid signing. Uh, there's a project called Notary. We do the second version of the Notary Spec for remit signing and AWS Docker and a couple of other companies have been working very closely together on bringing that uh, you know, finalizing no tv too, so that at least in our case we can start building services for our customers on top of that. You know, it's it's a great relationship and I expect to see it continue. >>Well, I think one of the themes this year is developer experience. So good. Good call out there in the new announcements on the tools you have and software because that seems to be a great developer integration with Docker question I have for you is how should the customers think about things like E C. S and versus E K. S. App, Runner lambda uh for kind of running their containers. How do they understand the difference is, what's there? What's the, what's the thought process there? What's >>that? It's a good question actually been announced after. And I think there was one of the questions I started getting on twitter. You know, let's start at the very beginning. Anyone can pick up a Docker container and run it on easy to today. You can run it on easy to, we can run a light sail, but doc around works just fine. It's the limits machine. Then people want to do more complex things. They want to run large scale orchestrated services. They won't run their entire business and containers. We have customers will do that today. Uh, you know, you have people like Vanguard who runs a significant portion of the infrastructure on pcs frg or you have to elope with the heavy user of chaos, our community service. So in general, if you're running large scale systems, you're building your platforms, you're most likely to use the csny Chaos. Um, if you come from a community's background, you're, you're running communities on prem or you want the flexibility and control the communities gives you, you're gonna end up with the chaos. That's what we see our customers doing. If you just want to run containers, you want to use AWS to its fullest extent where you want the continue a P I to be part of the W A S A P. I said then you pick is yes. And I think one of the reasons you see so many customers start with the CSN, Forget is with forget to get the significant ease of use from an operational standpoint. And we see many start ups and you know, enterprises, especially security focus enterprises leaning towards farming. But there's a class of customers that doesn't want to think about orchestration that just wants. Here's my code, here's my container image just run my service for me and that's when things like happen, I can come and that's one of the reasons we launched it. Land is a little bit different. Lambda is a unique service. You buy into an event driven architecture. If you do that, then you can figure our application into this. That's they should start its magic. Uh, the container part, there is what land announced agreement where they now support containers, packaging. So instead of zip files, you can package up your functions as containers. Then lambda will run them for you. The advantage it gives you with all the tooling that you built, that you have to build your containers now works the land as well. So I won't call and a container orchestration service in the same sense of the CSC cso Afrin are but it definitely allows the container image format as a standard packaging format. I think that's the sort of universal common theme that you find across AWS at this point of time. >>You know, one of the things that we're observing at this at this event here is a lot of developers Coop con and Lennox foundations. A lot of operators to kubernetes hits that. But here's developers. And the thing is I want to ease of use, simplicity experience, but also I want the innovation. Yeah, I want all of it. When I ask you what is amazon bring to the table for the new equation, what would you say? >>Yeah, I mean for me it's always you've probably heard me say this 100 times. Many 1000 times. It's foggy fog. It's unique to us. It takes a lot of what we have learned about operating infrastructure scale. The question we asked ourselves, you know, in many ways we talk about forget even before belong pcs but we have to learn on what it meant and what customers really wanted. But the idea was when you are running clusters of instances of machines to run containers on, you have to start thinking about a lot of things that in some ways VMS but BMS in the car were taken away capacity. What kind of infrastructure to run it on? Should have been touched. Should have not been back. You know, where is my container running? Those are things. They suddenly started having to think about those kind of backwards almost. So the idea was how can we make your containerized bundles? So TCS task or community is part of the thing that you talk to and that is the main unit that you operate on. That is the unit that you get built on and meet it on. That's where Forget comes in and it allows us to do many interesting things. We've effectively changed the engine of forget since we've launched it. Uh, we run it on ec two instances and we run it on fire cracker. Uh, we have changed the forget agent architecture. We've made a lot of underneath the hood, uh, changes that even take the take advantage of the broader innovation, the rate of us, We did a whole bunch more to launch acronym trans on top of family customers don't have to think about it. They don't have to worry about it. It happens underneath the hood. It's always your engine as as you go along and it takes away all the operational pain of managing clusters of running into picking which instances to use to getting out, trying to figure out how to bend back and get efficiency. That becomes our problem. So, you know, that is an area where you should expect to see a Stuart done more. It's becoming the fabric of so many things that eight of us now. Uh, it's, you know, in some ways we're just talking a lot more to do. >>Yeah. And it's a really good time. A lot more wave of developers coming in. One of the things that we've been reporting on on Silicon England cube with our cute videos is more developers keep on coming on, more people coming in and contributing to the open source community. Even end users, not just the normal awesome hyper scholars you're talking about like classic, I call main street enterprises. So two things I want to ask you on the customer side because you have kind of to customers, you have the community that open source community and you have enterprise customers that want to make it easier. What are you seeing and hearing from customers? I know you guys work backwards from the customer. So I got to ask you work backwards from the community and work backwards from the enterprise customer. What's going on in their environment? What's the key trends that they're riding? What's the big challenges? What's the big opportunities that they're facing and saying for the community? >>Yeah, I start with the enterprise. That's almost an easier answer. Which is, you know, we're seeing increasingly enterprises moving into the cloud wholesale. Like in some ways you could argue that the pandemic has just accelerated it, but we have started seeing that before. Uh they want to move to the cloud and adult modern best practices. Uh If you see my talk agreement last few years, I've talked about modernization and all the aspects of modernization, and that's 90% of our conversation with enterprises, I've walked into a meeting supposedly to talk about containers, whatever half a conversation is spent on. How does an organization modernize? What does an organization need to do to modernize and containers and serverless play a pretty important part in it, because it gives them an opportunity to step away from the shackles of sort of fixed infrastructure and the methods and approaches that built in. But equally, we are talking about C I C. D, you know, fully automated deployments. What does it mean for developers to run their own services? What are the child, how do you monitor and uh, instrument uh, your services? How do you do observe ability in the modern world? So those are the challenges that enterprises are going towards, and you're spending a ton of time helping them there. But many of them are still running infrastructure on premises. So, you know, we have outpost for them. Uh, you know, just last week, you're talking to a bunch of our customers and they have lots of interesting ideas and things that they want to do without both, but many of them also have their own infrastructure and that's where something like UCS anywhere came from, which is hey, you like using Pcs in the cloud, You like having the safety i that just orchestrates containers for you. It does it on on his in an AWS region. It will do it in an outpost. It'll do it on wavelength, it'll do it on local zone. How about we allow you to do it on whatever infrastructure you bring to us. Uh you want to bring a raspberry pi, you can do that. You want to bring your on premises data center infrastructure, we can do that or a point of sale device, as long as you can get the agent running and you can connect to an AWS region, even though it's okay to lose connectivity every now and then. We can orchestrate a container for you over there and, you know, the same customer that likes the ease of use of Vcs. And the simplicity really resonated with that message really resonates with them. So I think where we are today with the enterprise is we've got some really good solutions for you in eight of us and we are now allowing you to take those a. P. I. S and then launch containers wherever you want to run them, whether it's the edge or whether it's your own data center. I think that's a big part of where the enterprise is going. But by and large, I think yes, a lot of them are still making that change from running infrastructure and applications the way they used to do a modern sort of, if you want to use the word cloud native way and we're helping them a lot. We've done, the community is interesting. They want to be more participatory. Uh that's where things like co pilot comes from. God, honestly, the best thing we've ever done in my order is probably are open road maps where the community can go into the road map and engage with us over there, whether it's an open source project or just trying to tell us what the feature is and how they would like to see it. It's a great engagement and you know, it's not us a lot. It's helped us prioritize correctly and think about what we want to do next. So yeah, I think that's, that >>must be very hard to do for opening up the kimono on the road map because normally that's the crown jewels and its secretive and you know, and um, now it's all out in the open. I think that is a really interesting, um, experiment and what's your reaction to that? What's been the feedback on the road map peace? Because I mean, I definitely want to see, uh, >>we do it pretty much for every service in my organization and we've been doing it now for three years. So years forget, I think about three years and it's been great. Now we are very we are very upfront, which is security and availability. Our job 000 and you know, 100 times out of 100 at altitudes between a new feature and helping our customers be available and safe. We'll do that. And this is why we don't put dates in that we just tell you directionally where we are and what we are prioritizing Uh, there every now and then we'll put something in there that, you know, well not choose not to put a feature in there because we want to keep it secret until it launches. But for the most part, 99% of our own myself there and people engaged with it. And it's not proven to be a problem because you've also been very responsible with how we manage and be very transparent on whether we can commit to something or not. And I think that's not. >>I gotta ask you on as a leader uh threaded leader on this group. Open source is super important, as you know, and you continue to do it from under years. How are you investing in the future? What's your plan? Uh plans for your team, the industry actually very inclusive, Which is very cool. It's gonna resonate well, what's the plans? Give us some details on what you're investing in, what your priorities? What's your first principles? >>Yeah, So it goes in many ways, one when I I also have the luxury also on the amazon open source program office. So, you know, I get the chance to my team, rather not me help amazon engineers participate in open source. That that's the team that helps create the tools for them, makes it easy for them to contribute, creates, you know, manages all the licenses, etcetera. I'll give you a simple example, you know, in there, just think of the cr credential helper that was written by one of our engineers and he kind of distorted because he felt it was something that we needed to do. And we made it open source in general, in in many of our teams. The first question we asked is should something the open why is this thing not open source, especially if it's a utility or some piece of software that runs along with services. So they'll step one. But we've done some big things also, I, you know, a couple of years ago we launched Lennox operating system called bottle Rocket. And right from the beginning it was very clear to us that bottle Rocket was two things. It was both in AWS product. But first it was an open source project. We've already learned a little bit from what we've done at Firecracker. But making bottle rocket and open source operating system is very important. Anyone can take part of Rocket the open source to build tooling. You can run it whatever you want. If you want to take part of Rocket and build a version and manage it for another provider. For another provider wants to do it, go for it. There's nothing stopping you from doing that. So you'll see us do a lot there. Obviously there's multiple areas. You've seen WS investing on the open source side. But to me, the winds come from when engineers can participate in small things, released little helpers or get contributions from outside. I think that's where we're still, we can always have that. We're going to continue to strive to make it better and easier. And uh, you know, I said, I have, you know, me and my team, we have an opportunity to help their inside the company and we continue to do so. But that's what gets me excited. >>Yeah, that's great stuff. And congratulations on investing in the community, really enjoys it and I know it moves the needle for the industry. Deepak, I gotta ask you why I got you here. Dr khan obviously, developers, what's the most important story that they should be paying attention to as a developer because of what's going on shift left for security day two operations also known as a I ops getups, whatever you wanna call it, you know, ongoing, you get server lists, you got land. I mean, all kinds of great things are going on. You mentioned Fargate, >>um >>what should they be paying attention to that's going to really help their life, both innovation wise and just the quality of life. >>Yeah, I would say look at, you know, in the end it is very easy developers in particular, I want to build the buildings and it's very easy to get tempted to try and get learn everything about something. You have access to all the bells and whistles and knobs, but in reality, if you want to run things you want to, you want to focus on what's important, the business application, that and you the application. And I think a lot of what I'll tell developers and I think it's a lot of where the industry is going is we have built a really solid foundation, whether it's humanity, so you CSN forget or you know, continue industries out there. We have very solid foundation that, you know, our customers and develop a goal of the world can use to build upon. But increasingly, and you know, they are going to provide tools that sort of take that wrap them up and providing a nice package solution After another great example, our collaboration, the doctor around Dr desktop are a great example where we get all the mark focus on the application and build on top of that and you can get so much done. I think that's one trend. You'll see more and more. Those things are no longer toys, their production grade systems that you can build real world applications on, even though they're so easy to use. The second thing I would add to that is uh, get uh, it is, you know, you can give it whatever name you want. There's uh, there's nuances there, but I actually think get up is the way people should be running the infrastructure, my virus in my personal, you know, it's something that we believe a lot in homicide as hard as you go towards immutable infrastructure, infrastructure, automation, we can get off plays a significant role. I think developers naturally gravitate towards it. And if you want to live in a world where development and operations are tightly linked, I think it after the huge role to play in that it's actually a big part of how we're planning to do things like yes, anywhere, for example, a significant player and that it would be a proton. I think get up will be a significant in the future of proton as well. So I think that's the other trend. If you wanted to pick a trend that people should pay attention. That's what I believe in a lot. >>Well you're an expert. So I want to get you a quick definition. What is get Ops, how would you define it? Because that's a big trend. What does it, what does that mean? >>Electricity will probably shoot me for getting this wrong. I tell you how I think about it. Which is, you know, in many cases, um, you when you're doing deployments are pushing a deployment getups is more of a full deployment. When you are pushing code to get depository, you have a system that knows that the event has happened and then pulls from there and triggers the thing as opposed to you telling it take I have this new piece of code now go deployed everywhere. So to me, the biggest changes that Two parts one is it's more for full mechanism where you're pulling because something has changed. So it needs systems like container orchestrators to keep them, you know, to keep them in sync. And the second part of the natural natural evolution of infrastructure score, which is basically everything is called the figures code. Infrastructure as code, code is code and everything is getting stored in that software repo and the software repo becomes your store of record and drives everything. Uh So for a glass of customers, that's going to be a pretty big deal. >>Yeah, when you're checking in code, that's again, it's like a compiler for the compiler, a container for the container, you've got things for each other. Automation is ultimately what we're talking about here. And that's to me where machine learning kicks in. So again, having this open source foundational fabric, as you said, forget out the muck or the undifferentiated heavy lifting. This is what we're talking about automation, isn't it? Deepak? >>Yes. I mean I said uh one thing where we hang our hat on is there's such good stuff out there in the world which we like to contribute to, but the thing we like to hang our hat on is how do you run this? How do you do it this in ways that you can uniquely bring capabilities to customers where there's things like nitro or things are nitro open stuff. Well, the fact that we have built up this operational infrastructure over the last in a decade plus or in the container space over the last seven years where we really really know how to run these things at scale and have made all the investments to make it easy to do. So that's that's where we have hanger hard keeping people safe, helping them only available applications, their new startup, that just completely takes off in over the weekend. For whatever reason, because, you know, you're the next hot thing on twitter and our goal is to support you whether you are, you know, uh enterprise that's moving from the main train or you are the next hot startup, that's you know, growing virally and uh, you know, we've done a lot to build systems help both sides and yeah, it's >>interesting if you sing about open source where it's come from, I mean I remember that base wouldn't open source wasn't open, I would be peddling software, there's a free copy of Linux, UNIX um in college and now it's all free. But I mean just what's changed now. It used to be just free software, download software. You got it now, it's a service. Service now can be monetized quickly. And what you guys are offering with AWS and cloud scale is you've done all these things as I don't have to have a developer. I get the benefits of the scale, I can bring my open source code to the table, make it a service integrated in with other services and be the next snowflake, be the next, you know, a company that could scale. And that is that's the that's the innovation, right? That's the this is a new phenomenon. So it also changes the business model. >>Yeah, actually you're you're quite right. Actually, I I like one more thing to it. But you look at how a lot of enterprises use containers today. Most of them are using something like this year, Symphony or GS to build an internal developer platform and internal developer portal. And then the question then becomes this hard to scale this modern and development practices to an entire organization. What is your big bank that's been around as thousands and thousands of ID stuff That may not all be experts are running communities running container is when you scale it out different systems that proton come into play. That was actually the inspiration is how do you help an organization where they're building these developer Portholes and developer infrastructure, developer platforms, How do you make it easy for them to build it? Be almost use it as a way to get these modern practices into the hands of all the business units, where they may not have the time to become experts at the modern ways of running infrastructure because they're busy doing other things. And I think you'll see the a lot more happening that space that's not happening in the open source community. There's proton, there's a bunch of interesting things happening here and be interesting to see how that evolves. >>And also, you know, the communal, communal aspect of not just writing code together, but succeeding, right, building something. I mean, that's when you start to see the commercial meets open kind of ethos of communal activity of working together and sharing a big part of this year's. Dakar Con is sharing not just running and shipping code but sharing. >>Yeah, I mean if you think about it uh Dockers original value was you build run and shit right? You use the same code to build it, you use the same code to ship it, the same sort of infrastructure interface and then you run it and that, you know, the fact that the doctor images such a wonderfully shareable entity uh that can run every girl is such a powerful and it's called the Ci Image. Now I still call him Dr images because it's just easier. But that to me like that is a big deal and I think it's becoming and become an even bigger deal over the years. I came from something before, Amazon has to work in The sciences and bioinformatics and you know, the ability to share codeshare dependencies, package all of that up in a container image is a big deal. It's what got me one of the reasons I got fascinated with container 78 years ago. So it will be interesting to see where all of systems. >>It's great, great stuff. Great success. And congratulations. Deepak, Great to always talk to you got a great finger on the pulse. You lead a really important organizations at AWS and you know, doctor has such a huge success with developers, even though the company has gone through kind of a uh change over and a pivot to what they're doing now. They're back to their open source roots, but they have millions and millions of developers use Docker and new developers are coming in dot net developers are coming in. Windows developers are coming in and and so it's no longer about Lennox anymore. It's about just coding. >>Yeah. And it's it's part of this big trend towards infrastructure, automation and and you know development and deployment practices that I think everyone is going to adopt faster than we think they will. But you know, companies like Doctor and opens those projects that they involved are critical in making that a lot easier for them. And then you know, folks like us get to build on top of that orbit them and make it even easier. >>Well, great testimony the doctor that you guys based your E C. S on Docker Doctor has a critical role in developing community. I run composed in their hub with dr desktop and we'll be watching amazon and and the community activity and see what kind of experiences you guys can bring to the table and continue that momentum. Thank you Deepak for coming on the >>cube. Thank you, john. That's always a pleasure. >>Okay. Mr cubes. Dr khan 2021 virtual coverage. I'm john for your host of the cube. Thanks for watching.

(upbeat music) >> Hello, welcome to theCUBE studios of Palo Alto California for RSA conference keynote coverage and conference coverage. I'm Sean for your host of theCUBE. We're breaking down the keynote of RSA day one kickoff. We had Mark Nunnikhoven, who's the distinguished cloud strategist at Lacework. Mark former cube alumni and expert and security has been on many times before, Mark great to see you. Thanks for coming on and helping me break down RSA conference 2021 virtual this year. Thanks for joining. >> Happy to be here. Thanks for having me John. >> You know, one of the things Mark about these security conferences is that interesting, RSA was the last conference we actually did interviews physically face to face and then the pandemic went down and it was a huge shutdown. So we're still virtual coming back to real life. So and they're virtual this year, so kind of a turn of events, but that was kind of the theme this year in the keynote. Changing the game on security, the script has been flipped, connectivity everywhere, security from day one being reinvented. Some people were holding onto the old way some people trying to get on there, on the future wave. Clearly you got the laggards and you've got the innovators all trying to kind of, you know, find their position. This has been obvious in this keynote. What's your take? >> Yeah and that was exactly it. They use that situation of being that last physical security conference, somewhat to their advantage to weave this theme of resiliency. And it's a message that we heard throughout the keynote. It's a message we're going to hear throughout the week. There's a number of talks that are tying back to this and it really hits at the core of what security aims to do. And I think aims is really the right word for it because we're not quite there yet. But it's about making sure that our technology is flexible that it expands and adapts to the situations because as we all know this year, you know basically upended everything we assumed about how our businesses were running, how our communities and society was running and we've all had to adapt. And that's what we saw at the keynote today was they acknowledged that and then woven into the message to drive that home for security providers. >> Yeah and to me one of the most notable backdrops to the entire thing was the fact that the RSA continues to operate from the sell out when Dell sold them for alright $2 billion to a consortium, private privately private equity company, Symphony Technology Group. So there they're operating now on their own. They're out in the wild, as you said, cybersecurity threats are ever increasing, the surface area has changed with cloud native. Basically RSA is a 3000 person startup basically now. So they've got secure ID, the old token business we all have anyone's had those IDs you know it's pretty solid, but now they've got to kind of put this event back together and mobile world Congress is right around the corner. They're going to try to actually have a physical event. So you have this pandemic problem of trying to get the word out and it's weird. It's kind of, I found it. It's hard to get your hands around all the news. >> It is. And it's, you know, we're definitely missing that element. You know, we've seen that throughout the year people have tried to adapt these events into a virtual format. We're missing those elements of those sorts of happenstance run-ins I know we've run into each other at a number of events just sort of in the hall, you get to catch up, but you know as part of those interactions, they're not just social but you also get a little more insight into the conference. Hey, you know, did you catch this great talk or are you going to go catch this thing later? And we're definitely missing that. And I don't think anyone's really nailed this virtual format yet. It's very difficult to wrap your head around like you said, I saw a tweet online from one InfoSec analyst today. It was pointed out, you know, there were 17 talks happening at the same time, which you know, in a physical thing you'd pick one and go to it in a virtual there's that temptation to kind of click across the channels. So even if you know what's going on it's hard to focus in these events. >> Yeah the one conference has got a really good I think virtual platform is Docker con, they have 48 panels, a lot of great stuff there. So that's one of more watching closest coming up on May 27. Check that one out. Let's get into this, let's get into the analysis. I really want to get your thoughts on this because you know, I thought the keynote was very upbeat. Clearly the realities are presenting it. Chuck Robbins, the CEO of Cisco there and you had a bunch of industry legends in there. So let's start with, let's start with what you thought of Rowan's keynote and then we'll jump into what Chuck Robbins was saying. >> Sure yeah. And I thought, Rohit, you know, at first I questioned cause he brought up and he said, I'm going to talk about tigers, airplanes and sewing machines. And you know, as a speaker myself, I said, okay, this is either really going to work out well or it's not going to work out at all. Unfortunately, you know, Rohit head is a professional he's a great speaker and it worked out. And so he tied these three examples. So it was tiger king for Netflix, at World War II, analyzing airplane damage and a great organization in India that pivoted from sewing into creating masks and other supplies for the pandemic. He wove those three examples through with resiliency and showed adaptation. And I thought it was really really well done first of all. But as a cloud guy, I was really excited as well that that first example was Netflix. And he was referencing a chaos monkey, which is a chaos engineering tool, which I don't think a lot of security people are exposed to. So we use it very often in cloud building where essentially this tool will purposely blow up things in your environment. So it will down services. It will cut your communications off because the idea is you need to figure out how to react to these things before they happen for real. And so getting keynote time for a tool like that a very modern cloud tool, I thought was absolutely fantastic. Even if that's, you know, not so well known or not a secret in the cloud world anymore, it's very commonly understood, but getting a security audience exposure to that was great. And so you know, Rohit is a pro and it was a good kickoff and yeah, very upbeat, a lot of high energy which was great for virtual keynote. Cause sometimes that's what's really missing is that energy. >> Yeah, we like Rohit too. He's got some, he's got charisma. He also has his hand on the pulse. I think the chaos monkey point you're making is as a great call out because it's been around the DevOps community. But what that really shows I think and puts an exclamation point around this industry right now is that DevSecOps is here and it's never going away and cloud native and certainly the pandemic has shown that cloud scale speed data and now distributed computing with the edge, 5G has been mentioned, as you said, this is a real deal. So this is DevOps. This is infrastructure as code and security is being reinvented in it. This is a killer theme and it's kind of a wake-up call. What's your reaction to that? what's your take? >> Yeah, it absolutely is a wake-up call and it actually blended really well into a Rohit second point, which was around using data. And I think, you know, having these messages put out to the, you know, what is the security conference for the year always, is really important because the rest of the business has moved forward and security teams have been a little hesitant there, we're a little behind the times compared to the rest of the business who are taking advantage of these cloud services, taking advantage of data being everywhere. So for security professionals to realize like hey there are tools that can make us better at our jobs and make us, you know, keep or help us keep pace with the business is absolutely critical because like you said, as much as you know I always cringe when I hear the term DevSecOps, it's important because security needs to be there. The reason I cringe is because I think security should be built into everything. But the challenge we have is that security teams are still a lot of us are still stuck in the past to sort of put our arms around something. And you know, if it's in that box, I'm good with it. And that just doesn't work in the cloud. We have better tools, we have better data. And that was really Rohit's key message was those tools and that data can help you be resilient, can help your organization be resilient and whether that's the situation like a pandemic or a major cyber attack, you need to be flexible. You need to be able to bounce back. >> You know, when we actually have infrastructure as code and no one ever talks about DevOps or DevSecOps you know, we've, it's over, it's in the right place, but I want to get your thoughts and seeing if you heard anything about automation because one of the things that you bring up about not liking the word DevSecOps is really around, having this new team formation, how people are organizing their developers and their operations teams. And it really is becoming programmable and that's kind of the word, but automation scales it. So that's been a big theme this year. What are you hearing? What did you hear on the keynote? Any signs of reality around automation, machine learning you mentioned data, did they dig into automation? >> Automation was on the periphery. So a lot of what they're talking about only works with automation. So, you know, the Netflix shout out for chaos monkey absolutely as an automated tool to take advantage of this data, you absolutely need to be automated but the keynote mainly focused on sort of the connectivity and the differences in how we view an organization over the last year versus moving forward. And I think that was actually a bit of a miss because as you rightfully point out, John, you need automation. The thing that baffles me as a builder, as a security guy, is that cyber criminals have been automated for years. That's how they scale. That's how they make their money. Yet we still primarily defend manually. And I don't know if you've ever tried to beat, you know the robots that are everything or really complicated video games. We don't tend to win well when we're fighting automation. So security absolutely needs to step up. The good news is looking at the agenda for the week, taking in some talks today, while it was a bit of a miss and the keynote, there is a good theme of automation throughout some of the deeper dive sessions. So it is a topic that people are aware of and moving forward. But again, I always want to see us move fast. >> Was there a reason Chuck Robbins headlines or is that simply because there are a big 800 pound gorilla in the networking space? You know, why Cisco? Are they relevant security? Is that signaling that networking is more important? As of 5G at the edge, but is Cisco the player? >> Obviously Cisco has a massive business and they are a huge player in the security industry but I think they're also representative of, you know and this was definitely Chuck's message. They were representative of this idea that security needs to be built in at every layer. So even though, you know I live on primarily the cloud technologies dealing with organizations that are built in the cloud, there is, you know, the reality of that we are all connected through a multitude of networks. And we've seen that with work from home which is a huge theme this year at the conference and the improvements in mobility with 5G and other connectivity areas like Edge and WiFi six. So having a big network player and security player like Cisco in the keynote I think is important just because their message was not just about inclusion and diversity for skills which was a theme we saw repeated in the keynote actually but it was about building security in from the start to the finish throughout. And I think that's a really important message. We can't just pick one place and say this is where we're going to build security. It needs to be built throughout all of our systems. >> If you were a Cicso listening today what was your take on that? Were you impressed? Were you blown away? Did you fall out of your chair or was it just right down the middle? >> I mean, you might fall out of your chair just cause you're sitting in it for so long taken in a virtual event. And I mean, I know that's the big downside of virtual is that your step counter is way down compared to where it should be for these conferences but there was nothing revolutionary in the opening parts of the keynote. It was just, you know sort of beating the drum that has been talked about, has been simmering in the background from sort of the more progressive side of security. So if you've been focusing on primarily traditional techniques and the on-premise world, then perhaps this was a little a bit of an eye-opener and something where you go, wow, there's, you know there's something else out here and we can move things forward. For people who are, you know, more cloud native or more into that automation space, that data space this is really just sort of a head nodding going, yeap, I agree with this. This makes sense. This is where we all should be at this point. But as we know, you know there's a very long tail insecurity and insecurity organizations. So to have that message, you know repeated from a large stage like the keynote I think was very important. >> Well you know, we're going to be, theCUBE will be onsite and virtual with our virtual platform for Amazon web services reinforced coming up in Houston. So that's going to be interesting to see and you compare contrast like an AWS reinforce which is kind of the I there I think they had the first conference two years ago so it's kind of a new conference. And then you got the old kind of RSA conference. The question I have for you, is it a just a position of almost two conferences, right? You got the cloud native AWS, which is really about, oh shared responsibility, et cetera, et cetera a lot more action happening there. And you got this conference here seem come the old school legacy players. So I want to get your thoughts on that. And I want to get your take on just just the cryptographers panel, because, you know, as I'm not saying this as a state-of-the-art that the old guys saying get off my lawn, you know crypto, we're the crypto purists, they were trashing NFTs which as you know, is all the rage. So I, and Ron rivers who wrote new co-create RSA public key technology, which is isn't everything these days. Is this a sign of just get off my lawn? Or is it a sign of the times trashing the NFTs? What's your take? >> Yeah, well, so let's tackle the NFTs then we'll do the contrast between the two conferences. But I thought the NFT, you know Ron and Addie both had really interesting ways of explaining what an NFT was, because that's most of the discussion around the NFT is exactly what are we buying or what are we investing in? And so I think it was Addie who said, you know it was basically you have a tulip then you could have a picture of a tulip and then you could have something explaining the picture of the tulip and that's what an NFT is. So I think, you know, but at the same time he recognized the value of potential for artists. So I think there was some definitely, you know get off my lawn, but also sort of the the cryptographer panels is always sort of very pragmatic, very evidence-based as shown today when they actually were talking about a paper by Schnorr who debates, whether RSA or if he has new math that he thinks can debunk RSA or at least break the algorithm. And so they had a very logical and intelligent discussion about that. But the cryptographers panel in contrast to the rest of the keynote, it's not about the hype. It's not about what's going on in the industry. It's really is truly a cryptographers panel talking about the math, talking about the fundamental underpinnings of our security things as a big nerd, I'm a huge fan but a lot of people watch that and just kind of go, okay now's a great time to grab a snack and maybe move those legs a little bit. But if you're interested in the more technical deeper dive side, it's definitely worth taking in. >> Super fascinating and I think, you know, it's funny, they said it's not even a picture of a tulip it's s pointer to a picture of a tulip. Which is technically it. >> That was it. >> It's interesting how, again, this is all fun. NFTs are, I mean, you can't help, but get an Amber by decentralization. And that, that wave is coming. It's very interesting how you got a decentralization wave coming, yet a lot of people want to hang on to the centralized view. Okay, this is an architectural conflict. Is there a balance in your mind as a techie, we look at security, certainly as the perimeter is gone that's not even debate anymore, but as we have much more of a distributed computing environment, is there a need for some sensuality and or is it going to be all decentralized in your opinion? >> Yeah that's actually a really interesting question. It's a great set up to connect both of these points of sort of the cryptographers panel and that contrast between newer conferences and RSA because the cryptographers panel brought up the fact that you can't have resilient systems unless you're going for a distributed systems, unless you're spreading things out because otherwise you're creating a central point of failure, even if it's at hyper-scale which is not resilient by definition. So that was a very interesting and very valid point. I think the reality is it's a combination of the two is that we want resilient systems that are distributed that scale up independently of other factors. You know, so if you're sitting in the cloud you're going multi-region or maybe even multicloud, you know you want this distributed area just for that as Verner from AWS calls it, you know, the reduced blast radius. So if something breaks, not everything does but then the challenge from a security and from an operational point of view, is you need that central visibility. And I think this is where automation, where machine learning and really viewing security as a data problem, comes into play. If you have the systems distributed but you can provide visibility centrally which is something we can achieve with modern cloud technologies, you kind of hit that sweet spot. You've got resilient underpinnings in your systems but you as a team can actually understand what's going on because that was a, yet another point from Carmela and from Ross on the cryptographers panel when it comes to AI and machine learning, we're at the point where we don't really understand a lot of what's going on in the algorithm we kind of understand the output and the input. So again, it tied back to that resiliency. So I think that key is distributed systems are great but you need that central visibility and you only get there through viewing things as a data problem, heavy automation and modern tooling. >> Great great insight, Mark. Great, great call out there. And great point tied in there. Let me ask you a question on your take on the keynote in the conference in general as first day gets going. Do you see this evolving from the classic enterprise kind of buyer supplier relationship to much more of a CSO driven or CXO driven? I need to start building about my teams. I got to start hiring developers, not so much in operation side. I mean, I see InfoSec is these industries are not going away. People are still buying tools and stacking up the tool shed but there's been a big trend towards platforms and shifting left from a developer CICB pipeline standpoint which speaks to scale on the cloud native side and that distributed side. So is this conference hitting that Mark, or you still think there are more hardware and service systems people? What's the makeup? What's the take? >> I think we're definitely starting to a shift. So a great example of that is the CSA. The Cloud Security Alliance always runs a day one or day zero summit at RSA. And this year it was a CSO executive summit. And whereas in previous years it's been practitioners. So that is a good sign I think, that's a positive sign to start to look at a long ignored area of security, which is how do we train the next generation of security professionals. We've always taken this traditional view. We've, you know, people go through the standard you get your CISSP, you hold onto it forever. You know, you do your time on the firewall, you go through the standard thing but I think we really need to adjust and look for people with that automation capability, with development, with better business skills and definitely better communication skills, because really as we integrate as we leave our sort of protected little cave of security, we need to be better business people and better team players. >> Well Mark, I really appreciate you coming on here. A cube alumni and a trusted resource and verified, trusted contributor. Thank you for coming on and sharing your thoughts on the RSA conference and breaking down the keynote analysis, the RSA conference. Thanks for coming on. >> Thank you. >> Well, what we got you here to take a minute to plug what you're doing at Lacework, what you're excited about. What's going on over there? >> Sure, I appreciate that. So I just joined Lacework, I'm a weekend. So I'm drinking from the fire hose of knowledge and what I've found so far, fantastic platform, fantastic teams. It's got me wrapped up and excited again because we're approaching, you know security from the data point of view. We're really, we're born in the cloud, built for the cloud and we're trying to help teams really gather context. And the thing that appealed to me about that was that it's not just targeting the security team. It's targeting builders, it's targeting the business, it's giving them that visibility into what's going on so that they can make informed decision. And for me, that's really what security is all about. >> Well, I appreciate you coming on. Thanks so much for sharing. >> Thank you. >> Okay CUBE coverage of RSA conference here with Lacework, I'm John Furrier. Thanks for watching. (upbeat music)

>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

>> Narrator: Live from San Francisco it's theCUBE covering RSA Conference 2020 San Francisco brought to you by SiliconANGLE media. >> Welcome back, everybody. Jeff Frick here with theCUBE. We are at the RSA 2020, a really special segment. As you can tell it's really quiet here, it's not like normal CUBE action, we are here before the expo hall even opens on Thursday morning with a very special guest, we pulled them away from a crazy busy week if not more, it's Rohit Ghai the president of RSA, Rohit great to see you again. >> Always a pleasure, thanks Jeff. >> Absolutely, so I was really looking forward to this, I was really impressed by the opening keynotes, first it rolled out George Takei, that's a pretty bold move even more bold is to try to follow him up. >> Totally (laughing) >> So congratulations, and you know, that was pretty brave. >> I appreciate it, thank you. That was quite a, you know, quite a hurdle to got to follow George Takei. >> Right, and I just want to get kind of these other things that were kind of bubbling above the surface out of the way you know, a big piece of news, I think a week it came out before the show is that RSA was sold to Symphony I believe? >> Rohit: Symphony Technology Group. >> Right, so give us a little bit of the story there. >> Absolutely, so you know we entered into a definitive agreement, Symphony Technology Group acquiring RSA from Dell Technologies. What this does is this it basically clarifies the swim lanes for Dell Technologies to focus on intrinsic security and RSA can focus on managing digital and cyber risk, and you know, we are excited about the opportunity to become agile and independent and you know, kind of play in a smaller company setting to pursue our future, so we are super excited to be part of Symphony. >> Yeah, that's great, and the other thing that's kind of a pall, I mean just to put it out there is the corona virus thing. And you know, Mobile World Congress, a completely different show but a big show, probably the first big show of our industry this year was canceled. A hundred thousand plus people, so I just am just wondering if you can share kind of what were some of your thoughts and the team's thoughts 'cause we were all curious to see well how is this going to happen, there was a couple of drop outs but I think it's been a very good week. >> It has been a great week, you know what I'll say is it was a demonstration of resilience on part of the attendees, you know when we analyzed the situation what we noted was about 82 plus percent of our attendees are from the Americas right, so there was a core set of attendees that were perhaps not as impacted in terms of travel, et cetera, so we decided to move forward, we've been in close collaboration with the CDC and the mayor's office right here, Major London Breed's office right here is SF to make sure it's going to be a safe event for everyone and you know, the team put together a great kind of set of measures to make sure everyone has hand sanitizer. >> Great, great. >> And you know, we made sure we did what was needed to manage the risk and ensure resilience through this sort of you know very global risk that is playing out, so very proud of the team, and we garnered 40 thousand plus attendees despite you know, despite the coronavirus issue. >> You know, good job I am sure it was touch and go and a real sensitive situation and I can tell you a lot of other people and event organizers you know, were getting ready to head into a very busy event season, it's what we do and so, you know nice kind of lead indicator from you to execute with caution. >> I appreciate it, thank you. >> So let's jump into the fun stuff. So your key note was not really talking that much about bad guys and technology and this and that, you talked about story telling and you got very much into kind of the human element, which is the theme this year, but really the role of stories, the importance of stories, and most importantly for the security industry to take back their story and not let it get away from them. >> You summed it up really well Jeff, and you know what I said is hey if the theme of the conference is the human element, let's explore what intrinsically makes us human and the point, you know you've all know that it is stories that makes us human and I feel we've lost control of the narrative as an industry and as such we need to take that back and make sure we clarify the role of all the human characters in our story because until we do that, until we change our story we have no shot at changing our reality. >> Right, but you're kind of in a weird spot right, it's the classic spy dilemma. You can't necessarily tell people what you know because then they'll know that you know it and you might not be able to get more or better information down the road, so as you said in you keynote you don't necessarily have the ability to celebrate your wins, and a DDoS attack thwarted doesn't make the news. I keep thinking it's like ref in a game or like a offensive lineman in football you only hear about them on that one play when they get the holding call, not the 70 other plays were they did their job. >> Rohit: Totally, totally. >> So it's a unique challenge though >> It is, it is a challenge, it is not an easy problem and you know, there is a couple of recipes that I put out there for us to consider as an industry is you know, recipe one is we can celebrate our successes at a collective level right so, just like we put out breach reports, et cetera, in terms of what the statistics are, where the breaches are animating from we can talk about defensive strategies that are working at a collective level as an industry and share that sort of best practices recipes to win, that would be a fine start. I think another area, another point that I made was that we don't have to win for the hacker to lose. 71% of the breaches were motivated by financial gains, right, and as such if we, despite breaches, which is not a win for us, if we deny financial gain to the hackers we make them lose and they are subject to the same laws of economics, they have a profit and loss statement, they are spending resources for gain and when we deny them gain we make them lose, so those are a couple of ideas on how we can begin to change the narrative. >> Right. So the other piece of the human part is the rise of the bots, right, and the raise of AI and the rise of these increasingly smart and sophisticated machines. I think I saw one of those reports that we talk about on air was you know that people are an increasingly targeted group we hear it all the time, we hear about social engineering. As that gets more complicated, how does the role of people change? 'Cause clearly they can't monitor tens and tens and hundreds of thousands of concurrent attacks all the time. >> Absolutely, so you know the bad guys are using AI you know I cited the example of a deep fake audio clip that actually duped the CEO into initiating a wire transfer so they are using all these sophisticated attacks so to your point, we cannot rely on the end user to discern through these very sophisticates. It's unfair for us to think of them as the first line of defense, we have to on the IT side, we have to bring in technology, make the technology more usable, so you don't have to pay attention to this one millimeter by one millimeter lock at the corner of the browser to realize whether a web interaction is safe or not. We need to make more usable software, we need to do a better job of managing and reducing vulnerabilities to reduce the attack surface so IT has to step up in that regard, and then on the security teams I think they have to step up to use AI to detect bot initiated attacks so we are not leaning on the human to discern what is an anomalous interaction and what could be a phishing or a smishing attack, et cetera, you know we need to bring AI to fight the good fight on our behalf. >> Right. So the other kind of angle on that I thought was really interesting, Wendy's keynote, a couple of keynotes after yours from Cisco talked about, you know, a theme we see over and over in tech which is really kind of the democratization of security and get it out of just the hallowed halls of the super billion CSOCs and technologists that are just security and open it up to everybody so make them part of the solution and not those pesky people that keep clicking on links that they are not supposed to. >> Absolutely. She did a great job of kind of making that point and you know the way I think about it is again we need to move from a culture of elitism to a culture of inclusion. Until we really get the steaming going, not just within the security professionals which we are doing a better job of certainly in the industry, but we have to team with the user, the IT and the business teams in order to have a shot at tipping the balance in our favor. >> Yeah, it's really funny 'cause that kind of democratization theme is something that we see kind of across many levels of technology, whether it's in big data, can get away from the data scientists, in doing your own reports, in having access to your own marketing material and you know, so it's kind of funny that now we are just hearing it here I guess the last bastion of we're the smartest people in the room, no no, you need to use all the brain power. >> All the brain power. I use the phrase let's stop being STEM snobs and let's be more inclusive, and you know garner the entire spectrum of the diverse talent pool that we have available and you know making the point, perhaps a provocative point, that the cyber talent gap, a bit of it might be actually self-inflicted because we have been in this sort of elitism mindset. >> Right, and I think one of the themes that you talked about in you keynote was because of kind of the elite mindset we only want to focus on the elite challenges and in fact it's not the hardest challenges that are necessarily the most dangerous or the ones that are more frequently used, it doesn't have to be the craziest hardest way in. >> It absolutely does not. The point I made was preparing for the worse does not prepare you for the likely and the statistics are overwhelming. 60% of the breaches were on the back of six stolen credentials. That's a pretty table stakes basic issue that ought to be just taken off the table, and if we take care of the basics then we can focus our energy on the corner cases but let's first prepare for the likely before we get to the worst situations. >> Right. So Rohit I'm just curious to get your take as you have been here for the last couple of days, you know you did a whole lot of work getting into that keynote and getting this thing up and off the ground but you've had a couple of days to be here walked around, talked to a lot of customers and clients, partners, I wonder if there is anything that's kind of come up as a theme that you either didn't expect or kind of reinforced some of thoughts that you had coming into this week. >> Absolutely. I think if I would've net it out Jeff what I'm sensing is there is a whole movement to shift security left, which is this whole idea of IT stepping up as the first line of defense, reduce cyber exposure, take care of patching, multi-factor authentication, reduce the attack surface intrinsic security right so DevOps and SecDevOps take care of it right up front before the apps even get built right, then there is another movement to shift things right which is take care of the new aspects of the attack surface right, what the hacker always take advantage of are the areas where they sense we are unprepared and for a long time they've seen us being unprepared in terms of reducing the attack surface and then they go after the new aspects of the attack surface and what are those? IT, IoT, OT, data as an attack surface and the Edge right, so these are areas were there is a lot of activity, a lot of innovation, you know, on the floor here if you walk the corners shifting left shifting right as in all the new aspects of the attack surface. I am seeing a lot of conversations, a lot of innovation is that area. >> Yeah. Well, there's certainly no shortage of innovation in the companies here and in fact I think it's probably one of the biggest challenges that I think of from a virus perspective is to walk this floor and to figure it all out 'cause I don't know how many thousand of vendors there are but there's really big ones and there is lot's of little ones like you said tucked in the corner in kind of the cutting edge of the innovation. What advice do you give to people who is their first time coming to RSA? >> Yes, I think you know, it's a huge challenge for customers, there's 14 of every category. I think the customers what they have to see is they have to think about the recipe rather they have to focus not on the tool but the concept behind the tool, and think about the architecture right and they should seek out vendors that take this platform approach. It is, you know, the market hasn't consolidated that much where they can just go to a few vendors but when they build that architecture they should choose vendors that behave well as a puzzle piece in the jigsaw puzzle that our customers are having to assemble together right, that they are investing in the API integrations on the edges so they can slot in and be part of a broader solution. That's a key, key criteria that customers should utilize in their selection of the vendors. >> Yes, that's good. That's good advice, and they should be listening. So Rohit, thanks again for your time. Congratulations on a week and I hope you get that weekend of absolutely nothing coming up in just a couple of days that you talked about. >> I absolutely do. The joke I made was, you know, the only time I'm okay being labeled as useless is the weekend after RSA conference. So, I fully look forward to being useless over this weekend, it's been a great week and thank you again for having me. >> All right, two more days, 48 hours. All right, thanks again. He's Rohit, I'm Jeff, you're watching theCUBE. We're at RSA 2020, the year we're going to know everything with the benefit of hindsight. We're not quite there yet but we're trying yo get a little closer. Thanks for watching, we'll see you next time. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering UiPath Forward Americas, 2019. Brought to you by UiPath. >> Welcome back everyone to theCUBE's live coverage of UiPath Forward here at the Bellagio in Las Vegas, Nevada. I'm your host, Rebecca Knight, co-hosting alongside of Dave Vellante. We're joined by Cathy Tornbohm, she is the distinguished VP Analyst at Gartner. Thank you so much for coming on theCUBE. >> Very welcome, nice to be here. >> And Guy Kirkwood, he is the Chief Evangelist at UiPath. Thank you so much. >> Thanks Rebecca. >> So, we're hearing so much of these mantras, these catchphrases of UiPath. "automation first", "a robot for every person", "we're re-booting work", these are the theme's that Guy was touting up on the main stage, Cathy. Beyond that, I'd like to hear from you a little bit about what you're seeing in the RPA space at the moment. What are the trends and the themes that you think are most salient? >> I think the most fascinating thing about RPA right now is that it's really highlighting the problems the organizations have. All their accidents of history are really being brought up by RPA. And then you've got these digital darlings that they're trying to compete with, the Greenfield site kind of people. And some of those don't have beautiful back offices, but let's not go there for a minute. So, it, RPA is an opportunity for companies to link their digital dreams with their existing legacy nightmares. >> And those legacy nightmares include all of the things that Guy was talking about today: the drudgery, the dreariness, those mundane tasks that take up so much of our time. >> Absolutely, and really, if you think about it, in organizations, typically less than 15% of the applications that they're using have got some sort of application programming interface. So if you don't have a way of linking them, you end up with this long turn of applications that aren't linked together, with people literally being swivel-chair integration between the applications. >> Well, why can't you just string a bunch of API's together and automate that way? >> Well, in fact, there's a guy called Ian Barkin who works for Symphony, one of their organizations, it was set up to create automations for organizations. So one of the services businesses since been acquired by Sykes. And he describes it as process sediment, and it builds up in businesses in the same way that sedimentary rock builds up over millions of years. And digging through that, so that you can actually become more efficient is very difficult to do. So doing it on API level means you got to join up all those things individually. Whereas, using RPA, if system 'A' has a user interface, and system 'B' has a user interface, you can just use RPA. >> So, Cathy, you've been following process automation as a category for a number of years. Why RPA, why is it so hot, and why now? We've heard that it's the number one software category... >> Cathy: Fastest growing, yeah. Fastest growing, from Gartner. We've seen spending data that confirms that. Why now? (sighing) >> It's the digital competition that companies are facing, and the recognition that they cannot continue to be quite as bad at some of the things that they are bad at. So it's really that business transformation story back again, business process re-engineering, the same story that we had with BPO like ten years ago, but now, with robots instead. >> Yeah, it's interesting, I was at a, we had a show last weekend, it was the CEO of Suze, Suze... How do ya say it? Anyway, Suze, she said to me, "Well, you know, digital transformation's really about business transformation." And you kind of said the same thing. I mean, thoughts on that? >> I mean, you look at the start of the outsourcing market, the BPA market, twenty years ago. The very first deals were actually IT outsourcing deals that then transformed the business using IT as the enabler. So the first deal that I got involved with ever, in the outsourcing market, was Perot Systems with a British and Asian company. And we were putting in business process re-engineering consultants who actually transformed the business using IT as the enabler for that. There is no difference now, in fact one of the, one of the partners here, one of our original customers, actually put together a plan where we did the implementation, you know, soup to nuts, so that we could find out how we fit in to that whole transformation piece. And our team put together a whole package on all the learnings that we got out of that. And I had to laugh, because they're exactly the same things that every transformation program has had for the last thirty years. >> You know, if you look at kind of the history of certain segments, and I wonder if, Cathy, if you see RPA as one of them, like if you could've figured out who was implementing ERP the best, you didn't know SAP was going to become the leader, but if you could've figured out who was adopting ERP, you could've made a lot of money in the stock market, 'cause those companies had a huge productivity boost. Kind of same thing with Big Data, nobody really made any money in Big Data, so-called 'Big Data', a dupe. But the guys who applied it probably did pretty well. Do you see RPA as similar where the practitioners are going to actually be the ones that add more value to the industry than the new, the newly minted billionaires? >> It's almost the opposite. So the more RPA a company needs, it means the worse they did at managing their ERP in the first place. >> So they're kind of a mess? >> Yeah, yes. That need to be cleaned up, yeah. >> Yes, if you've got a hundred and twenty four ERP's that don't talk to each other, and you want to close your books in any kind of reasonable time frame, you're going to be a massive adopter of RPA, which basically means the more rubbish you are and activity, the more opportunity there is to automate more of it. >> So, what are the metrics that matter when you talk to your clients? >> Well, what I try and encourage clients to do is to really focus on business outcomes. So, much as Guy probably doesn't want me to say this, I don't really care how many 'scripts', aka robots, you've built, or how many run times you've deployed. What I care about is the business impact that you've managed to achieve. So, whatever KPI's are important to you, so are you managing to collect more revenue? Are you managing to make your customers happier because you're managing to decrease average handle times? or increase right first time activities. So anything that you're doing that actually improves the good old business metrics, is just going to be fantastic. So those are the sort of metrics that, really, companies should be focusing on. Not how many scripts they've built, that's absolutely pointless. >> I mean, are they focusing on that? I mean, when you... >> Yeah, lots of people are. >> Yeah? >> Yeah. >> In terms of ROI, we hear from customers that it has had them more accurate, they're more efficient, they're cost saving on human hours of the mundane tasks. But, when you were up on the main stage talking about how we're rebooting work, we're changing this moment, is it sparking the creativity, the imagination, the time spent on strategy in the more higher-level things? Is that, I mean that seems like that's the goal of return on investment. >> It is, within those organizations that are the most mature. So, what we're seeing, is the bifurcation, really, of the market between those organizations that are just starting and scaling up what they can, internal senses of excellence. Those organizations that are using the partners behind us. Those organizations that are using external parties to help them develop that. So Delight, for instance, they are sort of a managed service business. And instead of using people, they're using automation. So, Delight, by accident, has a BPA business in Spain, but then they'll turn that into an automation-heavy business and then providing that managed service. And then, the smartest customers, including SNBC, who we heard from yesterday, are actually turning their back office cost operations into a front office of revenue generator. Now, that is radically different from what we've seen prior. >> So Cathy, I got to ask you, when I was on a plane out here, somebody texted me a picture of the latest hype cycle. And they said, they knew I was going to UiPath, they said, "RPA has entered the trough of disillusionment." I said, "Oh, awesome, Gartner's, Cathy's coming on, and I can ask her about that." Well, what's your take on that? >> I think as Guy says, some people have already sailed through the trough, they've already gone through the challenges, or some of the challenges, and they've already found these fantastic productive things. I mean, we're estimating that people will save close to a million dollars for a large company, and just not having to do re-work of getting it wrong first time with re-keying that data. So, where there's some fantastic savings available, that you know, some of the ones have gone through the trough and done that, a lot of the other ones, they kind of, they don't understand the limitations of RPA and all those other partner tools that they need to put with it. So, don't understand it, can't handle unstructured data by itself. It needs a sister tool, so, what Gartner's talking about right now is this concept of hyper automation where you look across all the different activities that you would need to, sort of replace a person. So the people that are heading into the trough as sort of this second wave of adopters that Guy talked about, that will really struggle because they didn't understand the limitations in the first place. >> Well then, you know the, sometimes, things like the Magic Quadrant, and the trough of disillusionment, they're somewhat misunderstood sometimes, people, you know they see 'em, Gartner's very clever with the way it works things, but, so how should we think about that hype cycle? It's actually, in a way it's progress, isn't it? For an industry where they start... Entering that trough. >> Its, what Gartner says, is all industries have to go through that type of growing pains. And I think that we're seeing that, UiPath's expanded massively, and that's always a challenge for companies as they grow very rapidly. And as companies try and, as they say, take these wrong metrics. So I think things like UiPath buying ProcessGold is fantastic, it's a really, really good move for them. And I expect to see a lot of other process mining companies acquired, brought in to the RPA fold, because, there's four reasons why companies are going to go into this disillusionment, right? These are the main challenges with companies trying to use RPA properly. One is, they don't know what the processes are. So ProcessGold will give you a really good indication, they don't know about the microscopic level, and they don't know about the macro level. So things like digital twins will be something else that we would expect to see very closely partnered with companies like UiPath. And they don't know how to orchestrate their resources. So, other companies, like Innate, that can help you figure out how to do that will become... So its kind of like we're sort of breaking down a lot of what happened in other software categories and re-building them all up, in the way that the business can actually adopt them, hence, the AI Fabric sort of idea. So they don't know the processes, politics, people will lie to you about what they do all day, so they can sabotage your process, and there's a lot of silos within organizations that hate each other and throw things over the wall. So that all needs streamlining, and the more you can do across silos, the more successful any automation project would be. Then you've got, when you take a person out of a process, you take their eyes, their ears, the mouth, the nose. How are you going to replace that when you're trying to take them out, because you've got the keyboard fingers thing with the RPA tool? You need all these other activities replaced, replicated, supported. And then you've got the economics of production, so actually making sure that the scripts that you've built are actually worthwhile and are going to be cost-effective. It's something that we're studying at the moment. So you've got all these, all these different barriers, from all these different angles that are really going to push this thing into the trough for a little bit. And that's why it's great that RPA companies are looking at ways to mitigate that for their customers. >> Now, remember we said, as the understandings. So RPA is really good at dealing with structured data. Rule-spaced activities, deterministic things. That's why in regulatory, highly regulated environments, it's very effective, and the regulators love this sort of stuff. Because it's deterministic. When you look at AI, then we look at it in four ways. So you've got process understanding, which is the ProcessGold acquisition, you look at conversational understanding, 'cause ultimately robots are going to be controlled by voice. So you have to understand, the system has to understand that, let's say you're sitting in a bank, and the robot doesn't understand something, you say, "Okay, robot, stick that in the Well's account." It has to understand that Well's, in this case, means Well's Fargo. It does not mean a hole in the ground, water at the bottom, or a town in Somerset, in the UK, 'cause they're well's. So getting those ontologies correct is so important. So, that's conversational understanding. Document understanding. Because, as Cathy said, companies are still wading around in paper. So, understanding what those different documents are and how to action them is going to be really important. And finally, you're looking at visual understanding. So understanding and viewing things on the screen exactly the same way that humans do. So it's getting that combination right. >> So for RPA to live up to the hype, and there's a lot of hype, and it's a good thing, it's fun to track. It's got to go presumably beyond cleaning up the crime scene, if you will, to this new vision that you and Guy just laid out. What is the distance between, I dunno, sometimes I say 'paving the cow path', which gives you a nice hit, but as you say, it's 'cause companies... Ya know, they're messed up, to this vision of this, actually the guy from Pepsi today talked about it, this fabric of automation across the organization. How big of a gap is that? >> It's very different by every different company on the planet, really, in terms of their accidents of history, what their IT application landscape looks like, and what their business landscape looks like. And when you try and put the two things together, that's where you find the opportunities for any type of automation. >> Well come on, that's such an 'it depends' answer. (laughing) At the macro, will... In your expert opinion, will RPA live up to the hype? So many trends haven't, enterprise data warehousing, Big Data, Doob, all that stuff. You think RPA has the potential to crack through that. >> You mentioned a very good point. I think the most successful companies are the ones that actually will take the person that's managing the data and analytics of how their process is performing, and doing that with their automation strategy. And there are very few companies that've actually worked that out. They've still got totally two walls and they just meet up here at the CEO. So, unless companies actually take a more active business outcomes approach, and look at their end-to-end processes of order to cash and source to pay, these problems will carry on for some time. >> Well that's a great point, I mean, so it's data, it's machine intelligence, I guess Cloud for scale, you guys made a SAS announcement today, it's "automation first", to use your buzz word. >> Cathy: You need it all to come together. >> And it's really developing those best practices in your role as Chief Evangelist in helping understand what the most successful companies do, and then making sure that's implemented. >> Well that's why I spend more of my time listening than I do talking. Because the very nature of being a Chief Evangelist is the best job and the worst job title in the world. It's the best job because I spend my entire time talking to people like Cathy who know about what's happening within the market, and then feeding it back into our organization so we can make the right bets, so we can make the right acquisitions, but develop the right things. The bad thing about the job, is that I keep getting an inordinate number of people on LinkedIn saying, "So pleased that Jesus has entered your life." And I'm not that type of evangelist. (laughing) >> It's in the title. >> You know there's always this age-old debate in the industry of best of breed versus kind of a sweet approach. You see in SAP, for instance, acquired an RPA company, In Four talks about it. And then you get the specialist, UiPath. How do you see that shaking out, as the industry gets kind of more consolidated, how do you see a company like UiPath thriving, continuing to thrive? >> Gartner's going to predict coming in our new prediction series, but... Roughly 20 to 30% of enterprise adoption of AI, machine learning activities for process-based activities, will go through the RPA market. So, and with the IBPMS market, sort of combined together, that process management, because RPA has managed, cleverly, to capture the imagination of the business person. So, actually, there's a lot of IT departments that are talking to us about, how do we, how do we enshrine this activity, foreshadow IT, that's happening in the business, and make it successful, put governance plans in place so it will actually be successful in the way that it's actually now dealing with its own crime scene... (laughing) (mumbling) Its own rubbish, in a much better way. And I think that responsibility of business to understand how it can automate things and how it can manage things will really help a lot. So, I think the RPA players are well-placed to either be acquired into that bigger set of the established, large... Software providers, all to kind of keep blazing a trail for independence of the business. I'm not so sure about this idea that everybody should be programming their own scripts, I think that's a challenge. And I think the new interfaces will help mitigate some of the problems that we've seen with that approach, that hasn't been, haven't been very well done historically, so that's another area that will probably be a bit trough of disillusionment, but, actually, well-managed RPA projects have actually got a really good chance of delivering back very interesting benefits for businesses. >> Yeah, as a discreet innovation category, it does kind of feel that way, and often times, those markets are winner take most, the winner makes a ton of dough, number two makes a little bit of money, number three kind of breaks even, and everybody else gets consolidated or goes out of business, so, you guys go big or go home. That's kind of... Your posture. >> Tomorrow morning I'm doing, I'm doing my predictions for next year, and one of them is that the challenger RPA vendors, and indeed the service organizations that are small, are going to continue to consolidate and get acquired next year. So that's the 2020 prediction for us. >> Great. Well, Guy and Cathy, thank you both so much for coming on theCUBE. It was a great conversation. >> Oh, good, thank you. >> Thank you very much, indeed. Thanks Rebecca. >> Dave: Thanks you guys. >> I'm Rebecca Knight for Dave Vellante, stay tuned for more of theCUBES live coverage of UiPath. (techno music)

>> Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> And welcome back, here on theCUBE, along with Justin Warren, I'm John Walls and now we're joined by Peter Nichol, who's the CEO of Instaclustr. Peter, good to see you this morning sir. >> Thank you very much John. Nice to meet you. >> and Todd Greene, CEO of PubNub. >> Good to see ya. >> Good morning Todd. >> Good morning. >> First off, let's just talk about what the two of you guys do or specifically what Instaclustr does and PubNub. Peter, if you would. >> Basically at a high level, what Instaclustr does is, we help customers to build applications that have to scale massively in a reliable way. Massive scale means terabytes or petabytes of data or even more. Reliability means the application has got to be up and running all of the time. The way we do that is, we focus on technologies in the data layer and we allow companies to essentially outsource the management of those technologies to us. So they can focus on building their application, which is what they do best, and we focus on taking a lot of the complexity away, which is helping to manage the technologies in the data layer. And the technologies that we focus on are basically in the area of storage, search, messaging, and analytics. Those technologies are Cassandra, for storage, Kafka, for messaging, Spark, for analytics, and Elasticsearch for search. We can manage all of those technologies, in any of the cloud providers, including AWS, and essentially this allows customers to outsource that and focus on their core business. We've got some great customers, PubNub being one of our best customers, a hot startup in Silicon Valley, and we're really proud to have them here with us today. >> So Todd, >> Thanks Peter. >> if you will, give us the PubNub story. >> PubNub is a company that provides a global network, which is infrastructure for real-time applications. What's a real-time application? When we started the company six, seven years ago, we made this realization that, the world was moving from applications that sort of requested data when they needed to, you know, you pull up social information, you wanted to see where something was, you ask a question, to ones where things were constantly moving and changing. So devices were emitting data and consuming data all the time. Uber was launching and everyone wanted to see where their taxi was now. Chat applications were getting big inside, dating apps and B to B apps, and B to C apps, and on top of that IoT was exploding and people needed a way to control devices and turn lights on and off. And all the infrastructure that existed at the time, didn't really address these real-time use cases. So these companies were building that stuff themselves. So PubNub launched this thing we call a Data Stream Network, but it effectively does three things. It allows you to connect to devices and leave an always-on connection over the internet, to deliver data bidirectionally to those devices. Real-time message signaling in under a quarter of a second, and then control that data going back and forth, so being able to provide logic. That core infrastructure, that sort of connect, deliver, control, powers everything from Peloton exercise bikes to Symphony Investor chat applications, athenahealth doctor, patient, nurse, kinds of collaboration and lots of IoT companies, from Logitech Harmony to Samsung smart refrigerators. Across the board, it turns out, our infrastructure has been the key to making these real-time experiences come alive. >> So you had this moment, and startups usually do, they have, you hope you do, they reach a tipping point, right, of success And things work great and you hit a boiling point (laughs) in a way, a few years back, to where things were working almost too well, and that's how you got in to Instaclustr. Tell us, give me that story if you would, or share that with our folks watching. >> Yeah absolutely, you know, it's funny, I was talking to someone recently at Amazon, at AWS, who said we rarely talk to a company your size that actually is doing more traffic than AWS is and we discovered we were doing more than twice as many messages, these control signals we talked about, around our network, more than twice as many as the world's global SMS traffic. We were doing close to 50 billion of these messages per day. So as you can imagine, that's not a simple infrastructure. We store that data, we process it, we route it, we do all these things and in one of our storage layers, built on Cassandra, we were really struggling with the expertise needed to scale this thing at the size that we needed to scale it. And we hit a tipping point about two years ago, when we realized we really needed help and we needed help immediately. We had a lot of outreach to a lot of companies, including the company themselves that had created Cassandra. But once we stumbled on Instaclustr, it was like, you know, the clouds parting, right? All of the sudden we had folks from Instaclustr on with us 24 by 7, helping us migrate, helping us move to a more stable and scaled infrastructure and we've had this ongoing relationship ever since. We now have them managing a lot of different uses of Cassandra within PubNub. >> Yeah, so, infrastructure is, (stammers) sorry, Instaclustr is built on all these open-source technologies you mentioned, like Cassandra and Spark and Kafka, but what made you choose those technologies? What was it that was attractive about them that said, you know what, this is what we want to base our company on? >> Customers are always basically looking for three things, and I think Todd summed it up very well in his business, it's basically all about scalability. If your business is successful, you want to be able to scale massively as you get more and more customers. The second thing is reliability, which means the applications have got to be always on, always up and running. The third thing is performance, which is all about latency and speed and feed and all that type of thing. We chose Cassandra because it is one of the most popular, highly scalable data bases. It's used by Apple and Netflix and big companies that have got millions of customers. We generally pick technologies, based on those three criteria, but we also focus on open-source only, for two reasons. Number one, open-source doesn't involve expensive license fees, so customers don't get locked in with expensive license fees and number two, open-source provides a degree of flexibility, cloud independence, so if you don't want to be locked in to a specific cloud provider, and you want to keep your options in the future, choose open-source. >> Okay, that's a pretty compelling sort of argument there and certainly I think the world has discovered that open-source is totally a thing that we should all be using. I'm old enough to remember when open-source was verboten and you shouldn't be using it and now it just seems to be everywhere. What is it about Instaclustr that makes you special though, because open-source, anyone could use it. I could go and download it >> Yep, yep. >> for free tomorrow, so maybe I could attempt to steal PubNub's customers, steal your customers away. So clearly that's not going to be possible for me to be able to do tomorrow. What is it about Instaclustr that you've invested in this company that makes you so special, that means that PubNub was able to rely on you? >> Right, so I think the main thing is, we have 100% of our focus on operations, not on developing proprietary IP, which we sell, which is the typical software model, we take the open-source software and we actually manage it for our customers. Basically what that means is, if they want to use Cassandra, they go to our website, they go to the customer portal, they choose the cloud provider they want to use, they choose the technology they want to use, what regions do they want to run in, what size is their cluster? They press a button and everything else is done behind the scenes by us. We do the provisioning, we install the software, and from that point on, we're managing it 24 by 7. So instead of, for example, PubNub having to build their own team for each one of these technologies, they can outsource it to us, we can do it much cheaper and we can get them to market much faster, if we're doing our job right. It's all about the operations. We can do it much cheaper and faster and that's our main advantage. The other advantage is we manage all of these different technologies in the data layer, which means that customers have one vendor they can go to, to manage several different technologies. It's all heavily, highly, integrated from one vendor. That's a big, rather than having five different vendors to manage five different technologies, we provide the complete platform. >> So Todd, what does this mean for you, now that you have this partner that you can rely on and that you can trust? What does that change for the business? What has that enabled you to be able to do now that you can look forward to saying, you know what, we can do this to grow our business. >> Well that's a good question. Like Instaclustr, we operate PubNub. Customers pay us, not for our technology, but for our ability to operate our technology at massive scale. And we provide five nines SLA, which is a fancy way for saying, if we have an outage for more than 26 seconds in a month, we provide credits back to our customers. That's a really hard, high bar to fill. And so philosophically, we see ourselves as an operations company ourselves, right? And so we're very careful about who we would bring in to the fold as part of operations, right? And so it has to be an organization that has the same security levels that we do, SOC 2 Type II Compliance, has the same understandings and philosophy around operating things at high availability, and can do it in a way that we feel like, you know, in many ways is a part of our team and not some vendor that we don't know how to get on the phone. Not some vendor that we don't really trust, right? It has to feel like it's part of our company. So really it's only been Instaclustr that we've been able to develop that trust around. And so it is actually in all of us to sort of focus on areas where we can do more innovation while keeping the five nines SLAs at 26 seconds minimum, you know, maximum, of issues any month, but allow us to focus a lot more on innovation and not on the things that, frankly, Instaclustr, as far as we can tell, is best in the world at, which is really operating this infrastructure, the Cassandra piece. >> And what do you want to take on then? You told about innovation. If there's an area of your business, you say alright, this is where 2019, where I want it to take us, what would that be? >> It's a great question. One of the big changes for PubNub, was that we built our initial business on the backs of other startups and it was great. We got to some level of scale by powering a lot of innovative interesting applications that were themselves trying to be the first real-time this and the first real-time that and the first real-time the other thing. And then about two years ago something happened, a year and a half ago, that need for real-time, for having things update in real time, inventory, prices, chat applications, moving things on a map, seeing where your trucks were, that went mainstream, and now even the largest app companies in the world, if they release any kind of application, whether it's a business application or a consumer app, if it doesn't have that same real-time experience like an Uber or like a Snapchat, people kind of look at it and say, well this feels like it was built 20 years ago, right? And so what's happened to our industry, has been the moving of the need for this real-time experience, into the mainstream. Now that's been great for us, but it also means as we are selling to a larger and larger group of, we call mainstream larger enterprise customers, the way we package our product, the way we make it consumable by larger companies, make it easier to deploy our product, make it easier to understand and adding features that round that out, is really the core of our focus right now. Is really being able to appeal to those larger companies. We already have the scale, in fact, we recently participated in an event which was the Guinness Book of World (stammers) Record's largest online event in history. And we powered the source in India for Cricket, we powered the largest social interaction, over 10 million people synchronously going through our network, all in one virtual environment. So we know we can scale this thing beyond any existing human need and now it's really about making sure it's accessible to the world's largest companies. >> So it was cricket in India? >> Yes, yes. >> I would've thought it was the Justin Warren fan club, but I guess not, I (stammers) second online, right? >> Yeah, probably. >> There's a lot of people in India who love cricket, and they all have mobile phones. >> Yes, well gentlemen, thanks for being with us, Peter, Todd, continued success and then thanks for being here on theCUBE. >> Okay, thank you very much. >> Thank you so much, it's been a pleasure, thank you. >> We continue live coverage here from Las Vegas. We're in the Sands. We're here all week at AWS re-Invent. (calm digital music)

>> Announcer: Live, from Washington DC, it's the CUBE. Covering .conf2017. Brought to you by Splunk. >> And welcome back here on theCUBE. John Walls and Dave Vellante, we're in Washington DC for .conf2017, Splunk's annual get together coming up to the nation's capital for the first time. This is the eighth year for the show, and 7,000 plus attendees, 65 countries, quite a wide menu of activities going on here. We'll get into that a little bit later on. We're joined now by a couple of gentlemen, Michael Arahuleta who is the Vice President of Engineering at Atlassian, Michael, thank you for being with us. >> Thank you, actually it's Director of Business Development. >> John: Oh, Director of Business Development, my apologies >> He's doin' a great job >> My apologies. >> I don't need that. >> Oh very good. And Brooke Gravitt, who I believe is the VP of Engineering, >> There ya go. >> And the Chief Software Architect at Forty8Fifty. >> Yep, how ya doin'? >> No promotions or job assignments, I've gotcha on the right path there? >> Yeah, yeah. >> Good deal, alright. Thank you for joining us, both of you. First off, let's just set the stage a little bit for the folks watching at home, tell us a little bit about your company, descriptions, core competencies, and your responsibilities, and then we'll get into the intersection, of why the two of you are here. So Michael, why don't you lead off. >> So Atlassian, we, in our simplest form, right, we make team collaboration software. So our goal as a company is to really help make the tools that companies use to collaborate and communicate internally. Our primary focus, and kind of our bread and butter has always been making the tools that software companies use to turn around and make their software. Which is a great position to be in, and an increasingly we're seeing ourselves expand into providing that team collaboration software products like Jira, Confluence, BitBucket, and now, the new introduction of a product called Stride, which is a real time team collaboration product, not just for technical teams, but we're really seeing a great opportunity to empower all teams 'cause every team in every organization needs a better way to communicate and get things done. That's really what Atlassian core focus is all about. >> John: Gotcha. Brooke, if you would. >> Yeah, so Forty8Fifty Labs, we're the software development and DevOps focused subsidiary of Veristor Systems based out of Atlanta. We focus primarily on four key partners, which would be Atlassian, Splunk, QA Symphony, and Red Hat, and primarily, we do integrations and extensibility around products that these guys provide as well as hosting, training, and consulting on DevOps and Atlassian products. >> So the ideal state in your worlds is you've got -- true DevOps, Agile, infrastructure as code, I'll throw all the buzzwords out at ya, but essentially you're not tossing code from the development team into the operations team who them hacks the code, messes it up, points fingers, all that stuff is in part anyway what you're about eliminating, >> Right. >> And getting to value sooner. Okay, so that's the sort of end state Nirvana. Many companies struggle with that obviously, You got, what, Gartner has this term, bimodal IT, which everybody, you know, everybody criticizes but it's sort of true. You've got hybrid clouds, you've got, you know, different skillsets, what is the state of, Agile development, DevOps, where are we in terms of organizational maturity? Wonder if you guys could comment. >> I'll start with that right, I think -- Even though we've been talking about DevOps for a while and companies like Atlassian and Splunk, we live and breathe it. I still think when you look at the vast majority of enterprises, we're still at the early stages of effectively implementing this. I think we're still really bringing the right definition to what DevOps is, we're kind of go through those cycles where either a buzzword gets hot, everybody glams onto it, but no one really knows what it means. I think we're really getting into that truly understanding what DevOps means. I know we've been working hard at Atlassian to really define that strong ecosystem of partners. We really see ourselves as kind of in the middle of that DevOps lifecycle, and we integrate with so many great solutions around monitoring and logging, testing, other operational softwares, and things of that nature to really complete that DevOps lifecycle. I think we're really just now finally seeing it come together and finally starting to see even larger organizations, very large Fortune 100 companies talk about how they know they've got to get away from Waterfall, they've got to embrace Agile, and they've got to get to a true DevOps culture, and I think that's where Atlassian is very strong, devs have loved us for a long time. Operations teams are really learning to embrace Atlassian as well. I think we're really going to great position to be at that mesh of what truly is DevOps as it really emerges in the next couple years. >> Brooke, people come to Forty8Fifty, and they say, alright, teach me how to fish in the DevOps world, is that right? >> Yeah, absolutely. I mean, one of the challenges that you have in large enterprises is bringing these two groups of people together, and one of the easy ways is to go out and buy a tool, I think the harder and more difficult challenge that they face is the culture change that's required to really have a successful DevOps transformation. So we do a little bit of consulting in that area with workshops with folks like Gene Kim, Gary Gruver, Jez Humble that we bring in who are sort of industry icons for that sort of DevOps transformation. To assist, based on our experiences ourselves in previous companies or engagements with customers where we've been successful. >> So the cloud native guys, people who are doing predominantly cloud, or smaller companies, tech companies presumably, have glommed onto this, what about the sort of the Fortune 1000, the Global 2000, what are we seeing in terms of their adoption, I mean, you mentioned Waterfall before, you talk to some application development heads will say, well listen, we got to protect some of our Waterfall, because it's appropriate. What are you seeing in the sort of traditional enterprise? >> We see the traditional enterprise really embracing Agile in a very aggressive way. Obviously they wouldn't be working with Atlassian if they weren't, so our view is probably a little bit tilted. Companies that engage with us are the more open to that. But we're definitely seeing that the far and away the vast majority in the reports that we get from our partners like Forty8Fifty Labs is that increasingly larger and larger companies are really aggressively looking to embrace Agile, bring these methodologies in, and the other simple truth is with the way Atlassian sells -- the way we sell our products online, we have always sort of grown kind of bottoms up inside a lot of these large organizations, so where officially IT may still be doing something else, they're always countless smaller teams within the organization that have embraced Atlassian, are using Atlassian products, and then, a year down the road, or two years down the road, we tend to then emerge as the defacto solution for the organization after we kind of spread through all these different groups within the company. It's a great growth strategy, a lot are trying to replicate it. >> Okay, what's the Splunk angle? What do you guys do with Splunk, and how does it affect your business? >> Mike: Do you want to start? >> Sure, so, we're both a partner of Splunk, a customer of Splunk, and we use it in our own products in terms of our hosting, and support methodologies that we leverage at Forty8Fifty. We use the product day in and day out, and so with Atlassian, we have pulled together a connector that is -- one half of it is a Splunk app, it's available on Splunk base, and the other part is in the Atlassian marketplace, which allows us to send events from Juris Service Desk, ticketing events, over to Splunk to be indexed. You have a data model that ties in and allows you to get some metrics out of those events, and then the return trip is to -- based on real time searches, or alerts, or things that you have -- you're very interested in reports, you can trigger issues to be created inside of Jira. >> I think the only thing to add to that, so definitely, that's been a great relationship and partnership, and we're seeing an increasing number of our partners also become partners with Splunk and vice versa, which is great. The other strong side to this as well, is our own internal use of Splunk. So, we as a company, we always like to empower our different teams to pick whatever solution they want to use, and embrace that, and really give that authority to the individual teams. However, with logging, we were having a huge problem where all of our different teams were using over a whole host variety of different logging solutions, and frankly not to go into all the details, it was a mess. Our security team decided to embrace Splunk and start using Splunk, and really got a lot of value out of the solution and fell in love with the solution. Which says a lot, because our security team doesn't normally like much of anything, especially if it's not homegrown. That was a huge statement there, and then quickly Splunk now has spread to our cloud team which is growing rapidly as our cloud scales dramatically. Our developers are using it for troubleshooting, our SREs and our support team for incident management, and it's even spread to our marketplace, which is one of the larger marketplaces out there today for third party apps. Then the new product, Stride, for team collaboration is going to be very dependent on Splunk for logging as well. It's become that uniform fabric. I even heard a dev use a term which I've never heard a dev talk about logs and talk about log love, which is no PR, that is the direct statement from a developer, which I thought was amazing to hear. 'cause you know, they just want to code and make stuff, they don't want to deal when it actually breaks and have to fix it. But with Splunk they've actually -- They're telling me they actually enjoy that. So that's a great -- >> That's more than the answer is in the logs, that's there's value in our logs, right? >> Yeah, a ton of value, right? Because at the end of the day, these alerts are coming in and then we use tools like the Forty8Fifty Labs tool to get those tickets into Jira. Those logs and things are coming in, that means there's an issue and there's something to be resolved and there's customer pain. So the quicker we can resolve that, that log is that first indicator of what's going on in the cloud and in our platforms to help us figure out how do we keep that customer happy? This isn't just work, and just a task, this is about delivering customer value and that log can be that first indicator. The sooner you can get something resolved, the sooner the customer's back to getting stuff done and that's really our focus as a company, right? How do we enable people to get things done? >> Excuse me, when you are talking about your customers, what are their pain points? Today? I mean, big data's getting bigger and more capabilities, you've got all kinds of transport problems and storage problems, and security problems, so what are the pain points for the people who are just trying to get up to speed, trying to get into the game, and that the kind of services you're trying to bring to them to open their eyes. >> I think if you look at the value stream mapping and time to market for most businesses, where Splunk and Atlassian play in is getting that fast feedback. The closer in to the development side, the left hand side of value stream that you can pull in, key metrics, and get an understanding of where issues are, that actually -- it's much less expensive to fix problems in development than when they're in production, obviously. Rolling things like Splunk that can be used as a SIM to do some security analysis on, whether it be product code or business process early, rather than end up with a data breach or finding something after it's already in production. That kind of stuff, those are the challenges that a lot of the companies are facing is -- especially when the news, if you look at all the things that are goin on from a security perspective, taking these two products and being able to detect things that are going on, trends, any sort of unusual activity, and immediately having that come back for somebody in a service desk to work on either as a security incident or if it's a developer finding a bug early in the lifecycle, and augmenting your sort of infrastructure as code, the build out of the infrastructure itself. Being able to log all that data, and look at the metrics around that to help you build more robust enterprise class platforms for your teams. >> We've been sort of joking earlier about how the big data, nobody really talks about big data anymore, interestingly, Splunk who used to never talk about big data is now talking about big data, cause they're kind of living it. It's almost like same wine, new bottle with machine learning and AI and deep learning are all kind of the new big data buzzwords, but my question is, as practitioners, you were describing a situation where you can sort of identify a problem, maybe get an alert, and then manually I guess remediate that problem, how far away are we from -- so the machines automating that remediation? Thoughts on that? >> Am I first up? >> You guys kind of -- >> We've done a lot of automated remdediation. Close with remediation is what you call it. The big challenge is, it's a multi-disciplinary effort, so you might have folks that need to have expertise between network and systems and the application stack, maybe load balancing. There's a lot of different pieces there, so step one is you got to have folks that have the capacity to actually create the automation for their domain of expertise, and then you need to have sort of that cross platform DevOps mindset of being able to pull that together and the coordinator role of let's orchastrate all of the automations, and then hopefully out of that, combined with machine learning, some of the stuff that you can do in AWS, or with IBM's got out. You can take some of that analysis and be a little bit smarter about running the automation. In terms of whether that's scaling things up, or when -- For example, if you're in a financial industry and you've got a webpage that people are doing bill pay for, if you have a single website down, a web server down, out of a farm of 1000, in a traditional NOC, that would be kind of red on a dashboard. It's high, it's low priority, but it's high visibility and it's just noise, and so leveraging machine learning, people do that in Splunk to really refine what actually shows up in the NOC, that's something I think is compelling to customers. >> How are devs dealing with complexity, obviously, collaboration tools help, but I mean, the level of complexity today, versus when you think back to client server, is orders of magnitude greater for admins and developers, now you got to throw in containers and microservices, and the amount of data, is the industry keeping pace with the pace of escalation of complexity, and if so, how? >> I think we're trying. I think that's where we come into play. As this complexity increases really the only way you can solve it is through better communication and better tools to make sure that teams have the right information at their fingertips. The other challenge too is now in the world of the cloud, these teams need to be on 24/7. But you've got to kind of roll across the globe, and have your support teams in different time zones. You don't always have the right people online at the same time to be able to address, and you can't always talk directly, so that's where having the right tools and processes in place are extremely important so that team can know and know what did the team earlier do, how did they resolve this, where's the run book for this issue, and if this happens, how do we resolve it? How do we do so quickly? I think that tooling is key, and also too, this complexity is also as you guys were talking about before, being solved through some automation as well, and we're increasingly seeing that to where if this occurs and a certain thing occurs, then Jira can now automatically start to trigger some things for you, and then report back as to what it did. You're going to see more and more of that going forward as these models become more intelligent and we can redeploy, or if capacity is low, let's pull back resources, and let's not spend all this money on cloud computing platforms that we may not need because utilization is low. You're seeing all of those things start to happen and Jira as that workflow engine is that engine that's making those things happen in either an automated way at times, or just enabling people to communicate and do things in a very logical fashion. >> As ecosystem partners, how do you view the evolution of Splunk, is it becoming a application platform for you? Are you concerned about swim lanes? I wonder if you could talk about that? >> I personally, I don't see any real concerns of overlap between Splunk and Atlassian. In our view at Atlassian is, we tend to work very closely with people kind of fit into that frenemy category, and they're definitely a partner that we overlap with I think in very very few ways. If and when we ever do, I mean in a way, that's kind of something we always embrace as a company. I mean one thing we'll say a lot is overlap is better than a gap. Because if there's a gap between us and a partner, then that's going to result in customer pain. That means there's nothing that's filling that void. I'd rather have some overlap, and then give the customer the power to choose how do they want to do it. I mean, Splunk says you can probably do it this way, Atlassian says you could do it this way, as long as they can get stuff done, and that's always -- it's not a cliche from us, I mean that's a core message from Atlassian, then we're happy. Regardless if they completely embrace it our way, a little bit, a little deviation, that's not what really matters. >> Too much better than too little. >> Exactly. >> Is what it comes down to. Gentlemen, thanks for being with us. >> Thank you. >> We appreciate the time today and look forward to seeing you down the road and looking as your relationship continues. Not only between the two companies, but with Splunk as well. Thanks for being here. >> Mike: Thank you guys. >> We continue theCUBE does, live from Washington DC here at .conf2017, back with more in just a bit.