our Studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hey welcome back here ready Jeff Rick here with the cube we're in our pal 2 studios today for a cube conversation to talk about a pretty interesting topic right which is the security issue that is pervasive and needs to be baked in all over the place and combining that with networking and software to find networking which is often talked about as kind of the last area of really software-defined execution and a lot of activity around SD win so we're happy to have with us today from Fortin at John Madison he's the CMO and EVP of products for fortinet John great to see you you too and also joining us from Atlanta is Hilton styrsky he is the CIO of Crawford & Company Hilton great to see you as well so let's just jump into it big issue right Crawford & Company Hilton give us a little bit of the which you guys are and more importantly kind of what a distributed company that you are y SD win and when particularly is a pretty important piece of the equation absolutely SD wins very important to us as we look at growth so I'm a confident company we are 77 year old you asked in management's claims company we we haven't focus on restoring and enhancing lives businesses in communities in 2018 we processed about one and a half million claims they are translated into north of fifteen billion dollars in payments but more importantly when you think about the insurance space and really any highly transactional organization will go through a digital disruption and korfin and company is no difference and in particular with the culture of innovation that we have a profiling company we looking at all facets of the business to disrupt and that's our basic infrastructure all the way to the business process applications that interact with our customers and when we think about the network that's the lifeblood of our organization span in seven countries with almost 9,000 employees and NATO it touches every facet of our organization and our business and being on an innovative modern technology enables us to support the Scanlan growth that's invariably coming down the pipes in this industry thank you thanks for that summary and John over to you you know we got a lot of conferences as we go to your guys conference we go to RSA and security the topic because all these security needs to bake be baked in throughout the process it can't just be added on at the end and you guys have taken that to heart so tell us a little bit about you know your guys solution in this SD win space and how you're approaching it slightly differently yes he'll concern just about every company's going through this digital disruption and that means they really need to make sure that network is of high quality high speed can access the applications but most importantly is secure so what we do is make sure with all my networking gear and SDRAM being a specific example that security is totally integrated within that solution and you do it in a different way - right you're not just doing it with software but you've actually introduced you know a hardware component into this into this equation as well yeah well now obviously the software is still very important to make sure you can orchestrate and you've got the feature set but earlier this year we announced the the world's first sd1 ASIC which allows us to get that performance of the networking stack and security stack on a single appliance we're talking about five to 10 X performance and again allows the customer such as Crawford to run and networking and their security in that single appliance so help I'm curious from your perspective I have to say I feel sorry for CIOs cuz that you know as again we go to all these shows we walk around there's so much technology and in security specifically when you walk around RSA as the the granddaddy of all those conferences you know there's hundreds and hundreds and hundreds of vendors and I think my goodness how do you go through how do you evaluate so you know what do you do when you're looking for technology partners among this giant sea of potential opportunities and people telling you to do this that and the other you got to find a partner that's going to help you absolutely so I mean they're number of facets that come to that but first and foremost we take security and privacy not just security extremely or seriously hope it ends because of that we rely on our cyber team to help us make decisions and drive those discussion so these relationships are not just you know come about because of benefits that we see on white papers or interactions with the PIO they really are driven from our cyber organization in the indian research that they do envy attend products we're not just looking for a sexy brands name to put in our our branches in our data centers but we're really looking for a tried and tested product and it wasn't a network that really came down to our cyber team because of the integrated nature of the ESD way and the security applies it to em i'm curious in terms of the changing kind of government regulations you know ii had gdpr we've got the California Privacy Act has that impacted your you know kind of prioritization of security and privacy or has that always just been a top priority and that's just you know kind of another box to check yeah man it's always been there we haven't seen it impacted from a sigh from a networking perspective tea to date but as we think about applications we're looking for the flexibility in the application stack to adhere to GT bernini quite frankly any other regulatory control been in the insurance industry we are highly regulated and that type of scale and flexibility is something that we look to as we build new products more modern future and John to you I'm just curious you know some of the advantages of bringing these two things together to really bake the security and the SD win appliance what is that enable you to do that you couldn't do so much before well it's all about supporting the business and the applications so corporate for example you know obviously voice is very important to me they speak to a lot of people and branch offices video training their applications in the cloud and so bringing mass security and that networking together and accelerating it means they get a high quality of service to all the applications which are important to their business so what's next John what are some of the the things as you look forward and you see this this market to continuing to evolve you guys are really starting to take a real leadership position what are some of your priorities as you as you look forward and we're gonna flip the calendar here in just a few short months you know and definitely you know sd-1 an application on our appliance has exploded we just announced we're actually in the top three in terms of sd-1 benders globally what's coming next well I think what we call cloud on-ramp isn't very important where we provide specific routes and information to make sure we have even higher QoS of devices and users getting to the applications and I knew that on the land side of it was starting to roll out something called ST branch which gives you the same kind of fabric topology view control and workflow of access from Wi-Fi from Ethernet switching and we've also integrated nak network access control which gives you that visibility control of IOT devices great so I want it I want to give you the last word you know to share with your peers as they're going through this journey a lot of talk about digital transformation but when the rubber hits the road right you actually got to do do the things and do the small things that make a difference as you've gone through this and you've dealt the security you got a lot of remote branches this continuation around hybrid cloud and and distributed infrastructure what are some of the things on your top of mind and what would you share with some of your peers as they you know start to look at some of these technologies well you've got to have an open mindset and obviously like anything it's okay to fail as long as you learn from your mistakes but as we think specifically about our network and coordinate in particular I think trying to reference some of the technologies and that that requires a lot of data so you need to understand what the future looks like and provide a scale and flexible solution for our customers and John also reference Borden ACK we are in the process of deploy in that and it's all about having that single pane of glass in an integrated solution and makes it easier for a smaller supports team to manage and ultimately Triberr you and Ally investments and other parts of their company well Hilton I know we're up against it on the time I want to thank you for for taking some time out of your busy day and lovely Atlanta and sharing your story and John you know nothing but continued success to you and fortunate we've really been happy to be part of the story and share it and come to the conference's and just another step on that on that journey to success thank you thanks a lot all right thanks gentlemen all right you've been watching the cube from our Palo Alto studios thanks for watching we'll see you next time [Music]

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

>> fly from San Francisco. It's the Cube covering Google Cloud. Next nineteen, right Tio by Google Cloud and its ecosystem partners. >> Welcome back to the cues live coverage Here in San Francisco, this is day two of Google Cloud. Next twenty nineteen cubes. Exclusive coverage. We're in the middle of the show floor. All the action Aquino's are still going on a little bit over. I'm John for David Law student and kicking off, breaking down the keynote analysis. Also breaking down Post Day one. All the action in the evening, where all the parties are all the action on alway conversations. Dave's to picking off day to day one was setting the table. New CEO on stage Date date. You gets into the into the products really about data data. I machine learning's all aboutthe data cloud data, and we're seeing a machine learning data management. Smart analytics say Aye and machine learning and collaborations. The four themes of Today Google. Clearly using data has a key value proposition. Big table, Big Queary machine learning the G A support for auto ml for tables, big announcements, your thoughts >> Yes. Oh, John, I think answering some of the things that we brought up yesterday is when When Google puts out their vision of why they should be your partner of choice, like customers choose way thought that data and I and M l would be let read upfront. So they kind of buried the lead a little bit. And, you know, question we had coming this week is and they reclaim that really thought leadership that, you know, a couple years ago, You know, data. You know, they really that G technical science stuff is what Google was really good at. So I thought they laid out some really good things. I think everybody was, you know, impressed. To see there was good diversity of customers as well as all the Google me. There were a lot of the women of Google that you've written about John here showing their sewing their chops here. So a lot of pieces to go through and everything from the G sweetened the chromebooks and sick security and privacy is something I like to talk a little bit about when we get into it here. But quite quite a lot of use that day. Today I at the center of it >> and one of the power Women dipped to use the big table you see and think we're all that stuff, Dave with >> big steam Us on the Kino also was B I with a II B. I think we've covered that do space going back to our ten years of doing the tube. It's the promise of Do Remember those days. Do came from Google about Eric. The emergent Borden works and do this kind of small little sliver of the ecosystem into Google's now showing what was once the promise. Big data. They're giving demos democratizing. Bring in for the masses. Wait stories on silicon engels dot com outlining this, But the reality is there. Now remember hitting the road with promise of big data? Now, with Cloud really changed the game? Your bosses, you've been covering this from Day one? >> Well, I think that there's no question that this is a date, a game, WeII said early on John on the Cube. That big data war was going to be one in the cloud. Data was going to reside in the cloud. And having now machine intelligence applied >> to that data is what's giving companies competitive >> advantage at scale and economics I was struck by the stats that Google gave >> at the beginning of the Kino today. Google in the last three years has spent forty seven billion dollars >> capital expenditures. This year to date alone, they've spent thirteen billion dollars in Cap Xidan Data Centers. Thirteen billion. It would take IBM three and a half years to spend that much in cap back there would take Oracle six years. So from an economic standpoint, in the scale standpoint, Google, Microsoft, Amazon are gonna win that game. There's no question in my mind. So, John, you know it is a game of scale and data and I What do you think? First >> of all, Google, they got the Cuban aunties two of the white paper. They wrote that they did commercialized communities in a way that I thought was really excellent, well executed. I like a Jew where they left out on the side of the road. You got picked up by a Cloudera Michaels and memorable Jeff. I'm a Wagner. We saw what happened do communities. It is true that up. They basically put it out there in the open source system, the way they get behind Ciencia really positive there. On the data front, Google's got so much in the tool shed all across Google from day one. Their legacy is data data driven, large scale. They built software and systems to manage data at scale at a hole on president. Well, I think that they have their well ahead of the marketplace on the technology that our inside Google proper Google Cloud will be proper alphabet, whatever you wanna call it. Self driving cars question for Google is, Can they bring it to get there? They >> need to hire a team of people, just >> go out and just get it all >> together, pull the jewels together and put it into a coherent platform. That's kind of the tea leaves that I see that we're reading here. Is that Curry and pointed down the keynote. We got tons of technology. The question is, can they pull it together in a package and make a consumable addressable programmable programing, FBI's? We've seen that movie that's happening right now. The next level of innovation for Google is, can they make data programmable? This is going to be a ten year opportunity. If they get that right, they will win. Big move the ball down the field to see Amazon going big on stage maker. It's all about data data, analytics at scale, auto machine learning. These are the tell signs do data program ability. They got all the things. Can >> they bring it to bear? >> Yeah, Well, John, one of the things I saw it got a lot of people excited is if I have, You know, I'm a G sweet. Customers were geese sweet customers, and I'm using spreadsheets. Now I can use Big Query with that. So the power of analytics and big data be able to plug that right in, make it really easy. And what's interesting is trying to squint through. You know what was kind of the Google consumer side of the house that many of us know. And if used for for lots of years versus the Enterprise G sweet chromebooks and mobile? Well, you know, under Diane Green, it was Google Enterprise, and now it's all part of Google Cloud. Just when we talk about Microsoft, it's like, Well, is it azure or is it au three sixty five? Well, it was a G sweet words. Is it Google and one that I want to, you know, get get your guys comment on is they talk about privacy way. No, Google as a whole alphabet is You know what, ninety five percent plus ad revenue and they were very strong out here is that we do not own your data. We will not sell it to a third party. Privacy, privacy, privacy. And it's great to hear them say that. But way all interacted work with Google. We know all the cloud providers. The data is an important thing. When I do Aye aye and ml type activities. I need to be able to anonymous isat and leverage it train on it. So data privacy issue is still something that, you know, I heard what they said, but you know, there's got to be some concerns. >> There is another angle here that I'd like to talk about, and that's the database. Google, Amazon, Microsoft, Oracle, IBM, Mike Attention, Alibaba. All the big cloud guys. They want your data. That's why Amazon spending so much effort on the database market. That's why you don't see Oracle having such a dominant position in database. You like Google's announcement yesterday they were basically doing a backhanded slap but Amazon, saying, We're more open. They didn't deal with Mongo. There's a lot of discussion in the community of software community about how how Amazon, obviously Bogart's open source. But But if you if you look, it's something that's true if you look at Amazon, they basically taken a lot of open source products. It built their own databases. But if you look at Google, Google's got relational databases. They got non relational databases. They got operational databases. So I wonder out loud, Is this a Trojan horse strategy? Because they need to own your data that databases so important now that I think that is I talked to one noise that yesterday was a executive VP at Oracle, and he said to me that the cloud providers basically looked at the data base as another application to run on top of servers in virtual machines, >> he said, Were Oracle we integrate, you know, they do all the exit data stuff, etcetera. So my point is, database is the war to be won. That's where it starts. And if you're going to go away, I you want to have the data proximate to the application. Well, >> I mean there's two ways to look at that day. I would say that what might take on >> the database war or a position in the stack is you look out from the old way the new way the old way would be an oracle. Well, we got to preserve the database. We license that we have the license agreements. The new way is to change the game with automation. Like what? Google showing where all this stuff is gonna be done on behalf of the customer. So the business model of how database and the impact of data is being used well dictated my opinion, the monetization. And that's the question that everyone that I've talked to on the show floor offline on email, on direct messages, how we're gonna make money with containers, how we're gonna make money with Cooper Netease. How am I going to make money with data? This is the fundamental question. Now, if you look at the success pattern of the partner ecosystem, moneymaking is about new economics, new price points and new services. So if you're Deloitte or you're a censure, you're saying wow of goo could automate all the stuff that used to be really hard to do, like data migration, moving application were close around. That was once a high profit yield activity for this system integrators or selling databases like Oracle. That's the old way. The smart partners are essential, saying, OK, I'LL take the new economics where all that cost is distracted away by the automation. And I'll lower my price point but still capture the margin margin. Opportunity for cloud is significant, and this is where the smart money is going. The smart monetization schemes are around leveraging what Google and Amazon are doing at scale and shifting their business model. Take advantage of the lower cost but then lowering the price not as much, so they still capture the margin. So this's the immigration, and these are things that were like months and months project going. Data migrations to Melrose projects are like could be months. So smart money is saying Okay, how dowe I make money on this. It's not the old way. So this classic you know what side his treaty on old way or new way that's going to define who wins and who loses >> weight. By the way, I mean it. Sue Ellen >> license selling database license, for instance, is an old way. Well, essentially, it was Ramadan. Amazon does databases of service. What is the license by as you go? But you don't have, You >> know, the Oracle sells a zit buys you go to mean they play that same game. To me, it's more about when it comes to database. It's more about workloads. How much of the world needs acid property databases? Because that's oracles game versus how much of the world needs you no less database data store for for Lex structure data. And that's really I think, what Google and to a certain extent, Amazon are betting on. Although both companies, especially Amazon, is making a bet on both transactional data bases and non relationship, I >> mean in the ideal world database would be free from the margin get shifted to another spot. That's not clear yet, but still it can make money on database but lower caught in lower price. So Google makes money at scale, so with clouds scale, they can lower the price of the database like this, whether it's it's a service or some fee. But it's the people implementing, like the integrators and the people that are building applications as they build that agility. And how are they going to monetize? How does a company out in this floor make money? >> I just remember data stacks and probably like twenty twelve. I was talking to Billy Bob's worth the CEO about the merits of being in the US marketplace, and he said, You know, I'm a little nervous about that. What do you think, Dave? Do you think? Do you think they're gonna like, own me at some point in time and compete with me? So And that's what Google's announcement yesterday said is, You know, you're our friends, we're not going. They don't really come out and say, We're not going to compete with you They just basically said We are more open than aided us without mentioning a W S >> s. So it's interesting, you know, I've only had a little bit of a chance to walk around, but it's a different ecosystem, then Amazon. I remember six years ago, when we first went to Amazon. It was like game developers and all these weird start ups that I couldn't understand what they do. And now it's like, you know, like VM world, but bigger with just that. A broad ecosystem here, you know, there's a big section on collaboration. I went toe Enterprise connect a couple of weeks ago, talking about contact centers and see a lot of the same companies here heard five nines mentioned on stage zooms. Here, you know howto they plug into Google Cloud hurt sales force talking very devout Contact center. So it's a diverse ecosystem, but it's different than than Amazon, and there's not and Amazon. There's always that underlying, you know thing. Oh, is Amazon going to take over this business here? You know, I haven't heard that concern at this show. Well, >> I mean, the bottom line is that there's a shift in the economics and his model technology back in the database. Question. The fact that Mongo D. B. Was once forecast to go out of business. Oh, Amazon's going kill Mongo Devi that dynamo d B. Google's got databases. The fact the matter is, there's no one database anymore. Every application at some level has a database. So if you think about that, then you're gonna have a a new model where everything's has a database and the database is going be characterises on the workload in application. So I do agree with that point. Question is, it's not mutually exclusive one database license for all versus databases everywhere. So if databases air everywhere, then the connective tissue becomes the opportunity. That's where I think you see somebody's data playing technologies with Cloud very compelling, because I can move data very quickly around, and that's where the machine learning really shines. That's going to be a latent see question that's going to be a data integrity question. This is the new model. This is what horizontal scale ability means in the cloud, not by Oracle database. And we're good. This is It's kind of that game is that game is slowly moving into the oblivion. >> Well, I think you know, I think Amazon would say, Hey, if you're a database vendor, you gotta innovate or because we're not going to stop innovating. Whereas I think Google's message to the database vendors is somewhat different is, you know we want to partner with you, and maybe that's because they're not coming from a position of enterprise strength. But that ice I'm sensing, too, apparently different strategies. I just don't know what the end game is. And I believe the endgame is on the data. >> The tell sign on the databases of the developer, right? If I want to run a document store because that's best for my Jason or my my feeds from using Sage, eh, John? A lot of drama script. I'LL use document store. I want to use a relational database. I'll use a relational David So the ideal world does not have to develop are forced into a tooling and database decision that data >> mongo changed its licensing policy as a direct result of what Amazon was doing. So they made their community edition Ah, licence terms more restrictive if you follow that. So what? They said anybody, any cloud service provider that distributes the our community edition has to open source their entire software stack associated with distributing that, or they got to pay us. So basically saying you have to pay an open source tax or you gonna pay us we'LL be looking very interesting change in their database. One of >> the one the announcements here on the day two was the data fusion thing, which essentially means tell sign as well that fusion data moving data integrating Data's a critical thing. Pray ay, ay, ay and machine machine learning in a eyes only as good as the data that it's working with. So the data is, if his missing data saying a retail transaction, you potentially missing out on an opportunity to better user experience. So address ability of data. Having that accessible is a critical feature for machine learning, an a I and again, it's garbage in garbage out relatives of the data equation. High quality data gets high quality machine learning. High quality machine learning is high quality. I. So let's do that's that's kind of cloud offers with large compute large horizontal scale ability. >> Well, I said yes, and I said yesterday was kind of disappointed. It wasn't of talk about a I will. Google certainly made up for that today, didn't they? Still, >> Yeah, sorry was their questions >> were what was your favorite keynote moment today? >> Look, it was it was good when they actually let a couple of customers go up there and talk was that was a little bit disappointed that, you know, some of the sessions field a little bit too scripted for my take, but they laid out a lot of pieces there It takes a little wild, uh, you know, squint through all of the adjustment, you know, and all the changes that they have their I'm still digging through, like on the Antos. We talked about it quite a bit yesterday, but, you know, had some good conversations afterwards. They've got the cloud run announcement that's coming out this afternoon. But But, you know, digging into that open source discussion that you were just talking about from the database is something that I have a lot of interested. I'm glad we're actually right had on today will get their opinion as to, you know, they know a thing or two about open source and communities. And how does something like open shift fit with aunt those? They can work together, but it's not a owe it. Everything works back and forth If I'm p k s if I'm open shift or from you know, the geek based Antos, it's not seamless, and it sure ain't free you >> for not customers so weird from UPS. Scotiabank Baker Hughes McCasland heard from Cole's yesterday. So it's pretty high level senior people from the customer side speaking on stage, which is progress in the C e >> o of ups. I thought was great. He really laid out, You know, the scale of their business and how they grow. >> All right, guys, we got dates. You were kicking off here on the show floor here in San Francisco for Google Cloud next twenty nineteen. They never got it all day. And every day, two of three days, a live coverage. Stay with us as we kick off a full day of great interviews. Executives, entrepreneurs and ecosystem parties here at Google next stay with us for more after this short break.

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation >> universe. And welcome to another cube conversation from our wonderful Palo Alta Studios in beautiful Palo Alto, California. As we do with every cute conversation, we're gonna talk about an important topic with smart people that can provide some good clues and guidance as to how the industry's gonna be forward. We're gonna do that today, too. Specifically, what we're gonna talk about is that there has been an enormous amount of interest in kubernetes is a technology for making possible the whole micro service's approached application development. But one of the challenges that kubernetes has been specifically built to be stateless, which means that it's not necessarily aware of its underlying data. Now that is okay for certain classes of application. But the typical enterprise does want to ensure that its data can remain state full. That does have a level of protection required, et cetera, which creates a new need within the industry for how do we marry state full capabilities, staple storage capabilities with kubernetes and have that conversation? We've got great guests here. Part of Ayatollah is a co founder and C t o of robin dot io and radish men on is the CMO Robin. I owe partner Radish. Welcome to the Cube. >> Great to be here. >> All right, so, reddish one, we start with you. Why don't you give us a quick update on Robin Donna? >> Sure. Robin. Daughter, You, as you were alluding to, is addressing super important problem that is in front of us, which is that you've got cloud. Native technologies, especially containers. And community is becoming the default way in which enterprises are choosing to innovate. But at the same time, there's a >> whole swath >> of applications which were architected just five years ago, which all need to get the same benefits off agility, portability and efficiency of cloud native technologies. Robin helps bridge that, and I hope to talk more about that. >> Excellent. So part of let's start with you and talk about this problem this impedance mismatch between applications that require some state full assurance about the data and kubernetes, which tends to be stateless. How does that How does that impact the way applications get built and deployed? >> Sure. So if you look at me as you mentioned that communities is a platform that has started our originated for stateless workloads, and people have adopted the fastest growing open source project. We know about that, but when you look at a stateless work lord, it actually depends on state from somewhere. It's basically computing something right. It's computing state that's coming either, for the network ordered. Is computing on state that store brother inside, big data data, data leak or inside a database? Now, if you look at the problem itself, developers have gotten used to the agility benefits that communities has to offer the mostly infrastructure as a court kind of construct centered offers, however, the agility is not complete if you do not bring the state full workload workloads also into the communities for so as an example, think about somebody who's trying to build on entire pipeline right across the in. Just process so visualized by plane. If you're saying that you know what, in order to put this entire stock together, our entire pipeline together are to still do something that is non agile by going out sorry communities and then marry that with something inside communities. That's not true, actually. So more and more we're seeing developers and the develops teams basically saying that. Okay, I want to have the entire stock developed on deployed on a child platform, like open these. And of course, that comes with a bunch of challenges that need to be addressed and hoping you talk about that today. >> Well, if we have a zoo said the state has to be maintained somewhere, state may be maintained somewhere up in the cloud, But there are gonna be circumstances where because of data locality issues on, you know you want local control. You have ah, Leighton. See, considerations a number of other issues that you want to be ableto locate state in the closer close to the kubernetes. Is that really what we're talking about here? >> That's one aspect of it which is essentially around the performance and maybe you in governance reasons why you want to call a Kate State and stateless, Right? But the other reason I was saying is, if you want to deploy a stack, stack is comprised of many too many competent, stateless as well estate full. And you're talking about the birth of an entire application that the developer is gonna push under this platform right, so there. It's not about just the data locality and all that. It's also that just enabling the entire stock to be deployed in one shot. >> So you just you just you want a simpler, more manageable stats at all, right? So what's the solution? What people, what people have to do to get access to both those performance more more performance state Full application. Cubans clusters that record, have some degree of day locality concerns or to sustain that dream of increasingly simple stacks. What has to happen differently? >> Sure, and there are two aspects to this. The 1st 1 I would say, is that a the platform that is going to offer this on top of communities has to guarantee the persistency needs, whether it is in terms of reliability, dumps of performances. Selous, it has to guarantee does so you have to get those onto the platform first. But beyond that, if you look at other issues talking about many, there are many, many data platforms or data applications of workloads that predict board docker and communities. Now, if you don't really bring them into the Ford, you really are not solving the real business challenges that people have today, right? So beyond just providing persistency layer to communities pods, you need to have a way in which you can take complex platforms such as Mongol, Cassandra Elastic, such article rack. Cloudera these kind of workload and bring them onto a platform that has architected for Microsoft. Just communities, right? Because these platforms are not. These workers are not designed for micro service's workloads. So how do you marry them onto a platform such as communities that is designed as a micro service's platform? So you go to solve that, and that is exactly what Robin has done. So we have taken this approach where you can take complex workloads, rear platforms and then make them run on on a Microsoft this platform like abilities, starting with the storage subsystem, which is where one of our course fences. >> So I could conceivably imagine an Oracle database being rendered as a container with inside a cougar and he's cluster and position as a service have been orchestrated by by that kubernetes instance. What >> if I could jump in? You don't have to imagine we have customers in production there. They have Oracle Rack as a service offered on robin right now. One thing I want to contextualize is that our roots are in problem solving this hard problem off applications that I haven't been designed for containers contain arising them and being able to manage that gracefully in carbonated right. It just gave the example off Oracle Rack as a service. Or we also have customers with, let's say, multiple petabytes of data with her new bastard service, um, covering big large enterprises as well. Now from that lineage. Now, what've you also offering is that there is a set of customers who, already picked, Committed is already right might be open shift. It might be P K, as it might be g k to do its customers. We also have an offering called Robbins Storage, which brings powerful data management capabilities right. So to offering the platform offering, which is communities plus storage plus networking. Bless application bundles for some of the demanding workloads. But we just talked about, and then Robin Storage is a new offering which can add the magic of data management and advanced data management capabilities to any community. Is that you? >> Well, let's talk about that just for one second the uh, when I think of data management capabilities, I'm thinking not just a Iot being written back and forth between some media and some application. I'm thinking in terms of, oh, data protection and security. So are there Give us a sense of the scope of the service? Is that our part off this solution that you're talking? >> Yeah, I'll start in part like and chime in as well. So the first context you need to have is that all these data management capabilities are in the context of a hybrid being the normed implementation, right? Nine or 10 customers are looking at implementing on Prem with Public Cloud, right? So in that context, any of the cable release that we're talking about being being able to take snapshots or being able to take, you know, move that snap short to be offer as a back up in the cloud or ability, the clone and rehydrate applications, these air own capabilities that need to operate in a hybrid cloud context, that's number one. The second thing is, rather than just solve the storage level problem off taking snapshots, being able to bring application and data together is a big game changer in partner. Can you add a little bit more on the apple is data? >> Absolutely. Because, I mean, if you look at the the dinner service is the radish doctor board snapshots and clones and things living backups. Those constructs have existed in the storage industries for almost three decades. So there's nothing new about dark, right? But if you look at applying them for work Lord that are running in communities, you gotta uplevel that, because when you look at a story little snapshot, it is still a volume orelon level snapshot. But what a developer develops team needs is the ability to take an entire workload. That's a Mongo TB cluster and the only snap, short and dark cluster. I want to keep different states, even if the topology of the application is changing. Correct. And that is something that Robin has innovated on because we recognized. And I come from a storage bag when I was a distinguishing. Jenna very does have Bean fortunate to be building many data platforms there on be recognized that just leaving that storage does not deliver the promise of agility that communities offers. They were uplevel it into applications and for the very first time. In fact, we're introducing concepts such as you go to a Mongo classroom. You say I want to go snapshot this cluster. We understand the apology that this cluster has. How many shards depositor for offering these things. The service is under Langston the volumes and we dark forms a snapshot. That's an application. Little snapshot of the benefit of application will snap Shirt is that if another developer wants to go clone and run queries on that, you don't have to go Dr Storage Admin inside. Just give me clones of these large volumes. They'll say, Just clone this Mongol Devi cluster on. Then within minutes, you have an up and running long body be cluster fully functional. You can start readies life. Exactly. Other thing would be draw the stock double portability. So you have this snapshot taken periodic snapshots. So let's say that you run out of capacity nor deer center, and you would like to go bust into a different cloud. That's your on premises, and you want to go and run a clone in geeky because that's where the capacities, our snapshots and the baby, a implemented and architect of this allow you to port an entire application along with topology? Medea on data so that he can go and stand up Fully functional, ready to use. That's among Would he be cluster and geeky in the club? >> Now you talk about UK a Google kubernetes engine on G C P Google Cloud Platform. Obviously, that's when you think about kubernetes. That's kind of the mother ship. When you come right down to it. How does your platform and G K E G. C P work together? >> So the first thing is >> that we have, ah, partnership, which is led by engineering to engineering engagement, that >> part eyes front, ending around a standard set of AP eyes whereby the advanced data management capabilities that we're talking about can be brought into communities world itself and, of course, geeky as the implementation footprint. Right? So that's one area that we've been collaborating on. The second is from, ah, Google perspective. The preferred storage for running enterprise workloads or state full workloads or the data intensive work clothes that be talking about is Robin Storage and that's ah that we definitely are pretty excited by the fact that through rigorous technical evaluation, after rigorous technical evaluation, Google is chosen Robyn stories as the preferred storage for these demanding workloads. So from both these standpoints off moving the state of the art of what does it mean to provide data management capabilities to communities, to providing a solution that works today for customers who are embracing G K both on Prem in in the cloud to be able to bring state full workloads? We're working with Google and pretty excited about that part. Anyone add further color on the engineering partnership? >> He absolutely, I think, as a radish mentioned. So Google perform. We are the purport storage solution for that. Now can we just rewind back a little bit there? About 25 30 different stories? When does providing stories for communities? Right. So what is this? I think that this move is something special that let us tow this thing at this point, right. We took a very fundamentally different approach when we when we saw this problem for G k r for communities you could have started with several open source story solutions, are there and build on top of that. When their companies that take barter effects, for example, pity orifice and build on that. The companies that takes seven belong there, right? Be formally said that. Listen, if you want to elevate the experience from storage onto applications, that the example that I took earlier off taking a snatcher, a mongo migrating and if your story, it's stackers underwear off the application, which means that the stories track is unaware of the topology of the application. Can you really do application consistent snapshots? You can't. All he can do is begin to snapshot individual Williams. Correct. Now, if the stories stock is not a rare off the application to polish, can you actually the application level quality? Also, this. If you can't do that, can you really guarantee noisy neighbor elimination? You had to >> do all >> those things right? If you really wanna run data platforms, those are the core things that you need to do right and Soviet took an approach is that it doesn't know it will not cut it if you build a story. Stack on top of border defense, for example, are on set, so we do a ground up approach and he said, Look, if you wanna build a story, started this cloud native communities native. How would that look like? And how would the perimeters exposed so that it can deliver the entire experienced applications? So architectural leave yard very superior compared to the other players out there, it's proof is that we've got picked. Now that's one aspect. The other aspect is the approach that were taken to expose these primitives, their own snapshots and backup on a portability and all that was very clean. Right on. Very pragmatic how it works with both the born in the cloud as well as the the prior boatloads right on. Because of that, we're also collaborating with the Google engineers is to come up with a set off a P eyes that were planning to standardize right around community so that you could have a very standard set off a p I through which you can trigger these data management calls. Right? So that's that's other like no other stock Borden engineering to engineering collaboration. So that's the other thing that we're collaborating on to create the stana riser of FBI's based on the knowledge that we have had, because we have have we have feel deployments off like rubbish. Talked about right article rack. We have field the Prime Minster. People are deploying multiple petabytes off starting in the single communities. Robin, cluster. Right? So all that learning all the experience that we have had its contributed towards this joint Engineering to engineering. Afford that you're going to create the standardized data management. >> So we've got Robin. I owe has delivered a piece of technology for handling state full kubernetes clusters that has been validated by Google I o. Today or you know, so that can be used now. And is the basis for further engineering work to move this Maur into the mainstream for the future? That's good. Very exciting stuff, Partha. Right, Dash. Thanks very much for being here in the Cube. Thank you. Thank you. And once again, I want to thank part uh Chautala, Who is the co founder and CEO of Robin I owe and radish men on Who's the CMO Robin don I owe once again. I'm Peter Bursts. Thanks very much for watching this cube conversation until next time

>>Live from Las Vegas, Nevada. Extracting the signal from the noise. It's the queue covering IBM edge 2015 brought to you by IBM. >>Hello everyone. Welcome to the cube. I'm John furrier. We are here in Las Vegas for a special presentation inside the cube. A special announcement. We have mayor AC Borden, mayor of Memphis and Jen Crozer who's the vice president at IBM alliances and Alliance. Welcome to the cube. So mayor Memphis, I'll see renounced city, great culture. Um, smarter cities is a big thing right now. So talk about why Memphis, why IBM, why are you here? What's the big announcement? What's happening in Memphis? >>Well, it's a great day for Memphis in addition to the Grizzlies had slipped that in there, but uh, one, uh, of, of, of just the handful of cities that are receiving what are known as IBM smart cities challenge grants, we pick a challenge. We have, uh, they help us come up with a solution to it. And it's not some abstract idea. In our case, it's how do we weed out the non-emergency calls from the true emergency calls and our EMS service? 120,000, over 120,000 calls a year, about 25,000 of them are not truly emergency calls. So what that does is it takes valuable time and resources away from those true emergency, a true emergency calls. It should be attended to on a priority basis. >>So I know that you have a Twitter handle and you've got a lot of followers. Is the tech culture in Memphis emerging describes the folks that they, what's it like in Memphis from a tech perspective? Are there people who have moved over or there's rabbit. I know there's a lot of folks in town really talk about the tech community. >>Even in my generation, I'm on there just to do a little quality checking. Also on a double analysis. I'm still in this from Zinn. Uh, we're one of the three cities that will received the, uh, Twitter grants, which will allow us to access us and get that data there and use it as we make decisions. So that's really going to be unique for Memphis. So yes, Memphis is a up to date. >>Jen, I gotta ask you because one of the things that's near and dear to our heart in the cube is technology for the advancement of better signal, not noise, whether that's society, education, the Twitter data, and we've talked to in heat you saw about this is that it's the signal of the humans. Um, and this notion of smarter cities is bringing technology to impact the human lives, not just making people get an iWatch or what are, there's some real benefits. Talk about the grants, talk about what IBM is doing because this is real important stuff. I mean, smarter planets to marketing slogan, but the end of the day technology can help people and talk about how that's part of the grant and, and why Memphis and what are these guys doing that's unique. That could be a great case study for others. We started building a smarter planet at one of the things we had to think about was what was the acupressure >>points that would have the biggest ripple effects. And it's cities, right? More than half of the world's population lives in cities. And that's growing by a multiplier every day. And so that's where we wanted to start and we've been really gratified when we started smarter cities challenge, which is a pro bono program. Give us your toughest problem. We will send you a team of six IBM executives for three weeks to help you solve it for free. We've had over 600 mayors apply and we've delivered more than 115 teens >>and in Memphis. I got to ask the question about how you look at the, the governing process now with mobile computing, you can hear everything. They're talking back in real time and it might not be as organized. Certainly tweeting all over the place and kind of getting that data is really key. What's your vision >>that that's the key. We know Memphis, we know what information we have with that. We have what in the world do you do with it? So what better partner than IBM? We know Memphis, but IBM knows the world. We're not the only one who's faced this challenge. So with this team of experts, the IBM professionals who will be owned the ground there, they will then say, here's what you have. Here's the best way to use it. Here's what they did in Rome. Here's what they did in Berlin, London, New York or wherever. So the key is not how much information do you have but what in the world can you do with it in real day to day solutions to those everyday problems. And let me point this out. This is much more than just technology with the process we're going to employ in Memphis using nurses perhaps as dispatchers so that they can ask a few more questions when the call comes in are perhaps helping us set up a system in which nurses will go to the homes of the individuals who we call frequent flyers who often call when, it's not true any emergency but this is because life is on the line here and you really have to have the ability to analyze in real time and apply the right solution. >>And this is why IBM's expertise on a worldwide basis is so critical. >>We always talk about, we always talk about two aspects of real time near real time, which is people get today it's close enough, but when you're in a self driving car maybe or an emergency situation, you want real time. So that's really the key here. Yeah, >>that's the gay real time information being employed in a real real life situation. And that's what any emergency call that's. >>So I've got to get under the hood a little bit cause we like to go a little bit into the engine of, of the, of the local environment. I mean it, people who know life today, they got their cell phones, they think it's easy to call nine one one. It's not that easy. You have these old systems and the cell towers are connected to the municipal networks and you've got a lot of volume of calls coming in. That's a challenge for the local, the technology team and with this new system that's going to clear it up. So, so talk how you guys go from this clogged, you know, traffic calls to really segmenting the emergencies from the nonverbal. >>Again, that's another critical point. We're confident this is going to work and it will somewhat declaw if that's a word unclog because I experienced just without the grant shows us that we could weed out so many of the other calls. They will not be coming in to your nine one one. So that's, that's a big, big help right there is to make sure if we could weed out 25,000 calls, which is what we had last year. We're not truly emergency calls, you wouldn't speak in terms of a Claude nine one one system. >>I was talking to a friend, they're like, give me an example of some of this clog networks that I go, well imagine your phone going off a million times a night. The notifications, cause we're in a notification economy that you have to kind of weed through that. So how are you guys using the data? What's the technology? Can you give some specifics to what's being implemented, the team and how the local resources inter interact with IBM? >>Well I think, you know, the mayor's called out this one source of data that he's getting and mayors we know are getting multiple strings. So we have our intelligent operations center that IBM uses to create dashboards for mayors to see real time data about several different industries or sources or areas that are important to them. But I think that your point about the humans talking is a really critical one. And I want to come back to that because it's easy for us to fixate on the technology. And I think one of the things we've seen in this program is the technology enabling city leaders to hear their constituents in new ways, what they're saying and what they're not saying. And also for them to communicate back with them and close the loop on feedback as policies and programs are inactive. And the thing about the presence of IBM is kind of like a good housekeeping. It will open up Memphis to resources from other national groups. As a matter of fact, we're already using funds from another entity to set up our dashboards for performance in all areas, including of the nine one one calls. So IBM is like this huge magnet. But once folks see, Hey, IBM is in there, others who come in and say, we're going to help Memphis as it develops this system. So >>may I have to ask you a question. If as automation and technology helps abstract away a lot of the manual clogged data and understanding the signal from the noise, what's relevant, what's real time, you have a lot more contextual visibility into your environment and the people. How would you envision the future organization of the government and education and, and uh, police, fire, et cetera, working together? What's the preferred future in your mind's eye? As technology rolls out? The preferred future will be >>the, that when we come up with an innovation like this will be a non event. It would just be, it ought to be the order of the day. Uh, government sometimes kind of lags behind. No, we want to get to the point where we're leading. Uh, quite frankly, my vision is that this soon will become a non event. It will become the order of the day. Uh, humans are citizens will not be afraid of, Oh, I bet not call. I'm going to get a computer on the end of the line or they got a gadget down. They're just going to try to innovate me and see if I'm going to say it would be the order of the day. That's, that's what we're working forward and what we are emphasizing here is not what we are taking away but what we are bringing in. Additionally for this technology, we will actually be able to have a good diagnosis, a good case record built on what we call the frequent flyers. We know the people who call every two weeks, but they will feel so much better when two days before they usually call. A nurse will show up and say, came to check on you and that's what's coming out of this will be customers. This will be the new norm >>because is work. This is already that they're happy people, happy customers, happy voters. Hey, you nailed it. Barack Obama had put in for the first time a data scientist on the white house, DJ Patel, a former entrepreneur, former venture capitalist. Data science is a big deal. Now. Um, are you guys seeing that role coming into the local presence as well? Yes, >>and it's so critical to government and the private sector. If you come up with an item that's not reducing the profit margin, you just shut it down. We can't do that in government that week. Every service we provide, we're locked into that. I cannot say, well the police department where we are, we're not breaking even on that. Let's just shut that down. We won't run three shifts. We'll cut out that third shift. So we have a mandate. It's an imperative. What we're doing here is not an option. This is an absolutely essential. >>So you're excited for the grant. What's next after the announcement? What do you guys be doing together? We've got 16 cities around the world who will be getting these teams. So it's time to schedule them and get started and have the grant now, how many mayors applied and what was the numbers again? Over the life of the program, over 600 mayors have applied for this. This year it was just over a hundred and we are sending teams to 16 cities this year. Well, you guys can get that technology go and get some more music pumping through the world. That's a great place and I'll see the technology, help them. This is a citizen. Thanks for, for sharing the great story. Congratulations, mr mayor. Thanks for joining us on the cube. We right back here in Las Vegas. You watching the cube? I'm John. We'll be right back.