>> Okay. We're now going to go into the customer panel, and we'd like to welcome Angelo Fausti, who's a software engineer at the Vera C. Rubin Observatory, and Caleb Maclachlan who's senior spacecraft operations software engineer at Loft Orbital. Guys, thanks for joining us. You don't want to miss folks this interview. Caleb, let's start with you. You work for an extremely cool company, you're launching satellites into space. Of course doing that is highly complex and not a cheap endeavor. Tell us about Loft Orbital and what you guys do to attack that problem. >> Yeah, absolutely. And thanks for having me here by the way. So Loft Orbital is a company that's a series B startup now, who, and our mission basically is to provide rapid access to space for all kinds of customers. Historically, if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, have a big software teams, and then eventually worry about, a bunch like, just a lot of very specialized engineering. And what we're trying to do is change that from a super specialized problem that has an extremely high barrier of access, to a infrastructure problem. So that it's almost as simple as deploying a VM in AWS or GCP is getting your programs, your mission deployed on orbit with access to different sensors, cameras, radios, stuff like that. So, that's kind of our mission and just to give a really brief example of the kind of customer that we can serve. There's a really cool company called Totum Labs, who is working on building IoT cons, an IoT constellation for, internet of things, basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor IoT which means you have this little modem inside a container that container that you track from anywhere in the world as it's going across the ocean. So, and it's really little, and they've been able to stay a small startup that's focused on their product, which is the, that super crazy, complicated, cool radio, while we handle the whole space segment for them, which just, you know, before Loft was really impossible. So that's our mission is providing space infrastructure as a service. We are kind of groundbreaking in this area and we're serving a huge variety of customers with all kinds of different missions, and obviously generating a ton of data in space that we've got to handle. >> Yeah. So amazing Caleb, what you guys do. Now, I know you were lured to the skies very early in your career, but how did you kind of land in this business? >> Yeah, so, I guess just a little bit about me. For some people, they don't necessarily know what they want to do like earlier in their life. For me I was five years old and I knew I want to be in the space industry. So, I started in the Air Force, but have stayed in the space industry my whole career and been a part of, this is the fifth space startup that I've been a part of actually. So, I've kind of started out in satellites, spent some time in working in the launch industry on rockets, then, now I'm here back in satellites and honestly, this is the most exciting of the different space startups that I've been a part of. >> Super interesting. Okay. Angelo, let's talk about the Rubin Observatory. Vera C. Rubin, famous woman scientist, galaxy guru. Now you guys, the Observatory, you're up way up high, you get a good look at the Southern sky. And I know COVID slowed you guys down a bit, but no doubt you continued to code away on the software. I know you're getting close, you got to be super excited, give us the update on the Observatory and your role. >> All right. So, yeah. Rubin is a state of the art observatory that is in construction on a remote mountain in Chile. And, with Rubin we'll conduct the large survey of space and time. We're going to observe the sky with eight meter optical telescope and take 1000 pictures every night with 2.2 Gigapixel camera. And we are going to do that for 10 years, which is the duration of the survey. >> Yeah, amazing project. Now, you earned a doctor of philosophy so you probably spent some time thinking about what's out there, and then you went out to earn a PhD in astronomy and astrophysics. So, this is something that you've been working on for the better part of your career, isn't it? >> Yeah, that's right, about 15 years. I studied physics in college. Then I got a PhD in astronomy. And, I worked for about five years in another project, the Dark Energy Survey before joining Rubin in 2015. >> Yeah, impressive. So it seems like both your organizations are looking at space from two different angles. One thing you guys both have in common of course is software, and you both use InfluxDB as part of your data infrastructure. How did you discover InfluxDB, get into it? How do you use the platform? Maybe Caleb you could start. >> Yeah, absolutely. So, the first company that I extensively used InfluxDB in, was a launch startup called Astra. And we were in the process of designing our first generation rocket there, and testing the engines, pumps, everything that goes into a rocket. And, when I joined the company our data story was not very mature. We were collecting a bunch of data in LabVIEW and engineers were taking that over to MATLAB to process it. And at first, there, you know, that's the way that a lot of engineers and scientists are used to working. And at first that was, like people weren't entirely sure that that was, that needed to change. But, it's, something, the nice thing about InfluxDB is that, it's so easy to deploy. So as, our software engineering team was able to get it deployed and, up and running very quickly and then quickly also backport all of the data that we collected this far into Influx. And, what was amazing to see and is kind of the super cool moment with Influx is, when we hooked that up to Grafana, Grafana as the visualization platform we used with Influx, 'cause it works really well with it. There was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data, where they could just almost instantly easily discover data that they hadn't been able to see before, and take the manual processes that they would run after a test and just throw those all in Influx and have live data as tests were coming, and, I saw them implementing like crazy rocket equation type stuff in Influx, and it just was totally game changing for how we tested. >> So Angelo, I was explaining in my open, that you could add a column in a traditional RDBMS and do time series, but with the volume of data that you're talking about in the example that Caleb just gave, you have to have a purpose built time series database. Where did you first learn about InfluxDB? >> Yeah, correct. So, I work with the data management team, and my first project was the record metrics that measured the performance of our software, the software that we used to process the data. So I started implementing that in our relational database. But then I realized that in fact I was dealing with time series data and I should really use a solution built for that. And then I started looking at time series databases and I found InfluxDB, and that was back in 2018. The, another use for InfluxDB that I'm also interested is the visits database. If you think about the observations, we are moving the telescope all the time and pointing to specific directions in the sky and taking pictures every 30 seconds. So that itself is a time series. And every point in that time series, we call a visit. So we want to record the metadata about those visits in InfluxDB. That time series is going to be 10 years long, with about 1000 points every night. It's actually not too much data compared to other problems. It's really just a different time scale. >> The telescope at the Rubin Observatory is like, pun intended, I guess the star of the show. And I believe I read that it's going to be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hubble's widest camera view, which is amazing. Like, that's like 40 moons in an image, amazingly fast as well. What else can you tell us about the telescope? >> This telescope it has to move really fast. And, it also has to carry the primary mirror which is an eight meter piece of glass. It's very heavy. And it has to carry a camera which has about the size of a small car. And this whole structure weighs about 300 tons. For that to work, the telescope needs to be very compact and stiff. And one thing that's amazing about it's design is that, the telescope, this 300 tons structure, it sits on a tiny film of oil, which has the diameter of human hair. And that makes an, almost zero friction interface. In fact, a few people can move this enormous structure with only their hands. As you said, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So, each image has, in diameter the size of about seven full moons. And, with that, we can map the entire sky in only three days. And of course, during operations everything's controlled by software and it is automatic. There's a very complex piece of software called the Scheduler, which is responsible for moving the telescope, and the camera, which is recording 15 terabytes of data every night. >> And Angelo, all this data lands in InfluxDB, correct? And what are you doing with all that data? >> Yeah, actually not. So we use InfluxDB to record engineering data and metadata about the observations. Like telemetry, events, and commands from the telescope. That's a much smaller data set compared to the images. But it is still challenging because you have some high frequency data that the system needs to keep up, and, we need to store this data and have it around for the lifetime of the project. >> Got it. Thank you. Okay, Caleb, let's bring you back in. Tell us more about the, you got these dishwasher size satellites, kind of using a multi-tenant model, I think it's genius. But tell us about the satellites themselves. >> Yeah, absolutely. So, we have in space some satellites already that as you said, are like dishwasher, mini fridge kind of size. And we're working on a bunch more that are a variety of sizes from shoebox to, I guess, a few times larger than what we have today. And it is, we do shoot to have effectively something like a multi-tenant model where we will buy a bus off the shelf. The bus is what you can kind of think of as the core piece of the satellite, almost like a motherboard or something where it's providing the power, it has the solar panels, it has some radios attached to it. It handles the attitude control, basically steers the spacecraft in orbit, and then we build also in-house, what we call our payload hub which is, has all, any customer payloads attached and our own kind of Edge processing sort of capabilities built into it. And, so we integrate that, we launch it, and those things because they're in lower Earth orbit, they're orbiting the earth every 90 minutes. That's, seven kilometers per second which is several times faster than a speeding bullet. So we have one of the unique challenges of operating spacecraft in lower Earth orbit is that generally you can't talk to them all the time. So, we're managing these things through very brief windows of time, where we get to talk to them through our ground sites, either in Antarctica or in the North pole region. >> Talk more about how you use InfluxDB to make sense of this data through all this tech that you're launching into space. >> We basically, previously we started off when I joined the company, storing all of that as Angelo did in a regular relational database. And we found that it was so slow and the size of our data would balloon over the course of a couple days to the point where we weren't able to even store all of the data that we were getting. So we migrated to InfluxDB to store our time series telemetry from the spacecraft. So, that's things like power level, voltage, currents, counts, whatever metadata we need to monitor about the spacecraft, we now store that in InfluxDB. And that has, now we can actually easily store the entire volume of data for the mission life so far without having to worry about the size bloating to an unmanageable amount, and we can also seamlessly query large chunks of data. Like if I need to see, you know, for example, as an operator, I might want to see how my battery state of charge is evolving over the course of the year, I can have, plot in an Influx that loads that in a fraction of a second for a year's worth of data because it does, intelligent, it can intelligently group the data by assigning time interval. So, it's been extremely powerful for us to access the data. And, as time has gone on, we've gradually migrated more and more of our operating data into Influx. >> Yeah. Let's talk a little bit about, we throw this term around a lot of, you know, data driven, a lot of companies say, "Oh yes, we're data driven." But you guys really are, I mean, you got data at the core. Caleb, what does that mean to you? >> Yeah, so, you know, I think the, and the clearest example of when I saw this be like totally game changing is what I mentioned before at Astra where our engineer's feedback loop went from a lot of kind of slow researching, digging into the data to like an instant, instantaneous almost, seeing the data, making decisions based on it immediately rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. But to give another practical example, as I said, we have a huge amount of data that comes down every orbit and we need to be able to ingest all of that data almost instantaneously and provide it to the operator in near real time, about a second worth of latency is all that's acceptable for us to react to see what is coming down from the spacecraft. And building that pipeline is challenging from a software engineering standpoint. My primary language is Python which isn't necessarily that fast. So what we've done is started, and the goal of being data-driven is publish metrics on individual, how individual pieces of our data processing pipeline are performing into Influx as well. And we do that in production as well as in dev. So we have kind of a production monitoring flow. And what that has done is allow us to make intelligent decisions on our software development roadmap where it makes the most sense for us to focus our development efforts in terms of improving our software efficiency, just because we have that visibility into where the real problems are. And sometimes we've found ourselves before we started doing this, kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. But now that we're being a bit more data driven there, we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scale from supporting a couple of satellites to supporting many, many satellites at once. >> Yeah, of course is how you reduced those dead ends. Maybe Angelo you could talk about what sort of data-driven means to you and your teams. >> I would say that, having real time visibility to the telemetry data and metrics is crucial for us. We need to make sure that the images that we collect with the telescope have good quality, and, that they are within the specifications to meet our science goals. And so if they are not, we want to know that as soon as possible and then start fixing problems. >> Caleb, what are your sort of event, you know, intervals like? >> So I would say that, as of today on the spacecraft, the event, the level of timing that we deal with probably tops out at about 20 Hertz, 20 measurements per second on things like our gyroscopes. But, the, I think the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications and I'll give an example from when I worked at, on the rockets at Astra. There, our baseline data rate that we would ingest data during a test is 500 Hertz. So 500 samples per second, and in some cases we would actually need to ingest much higher rate data, even up to like 1.5 kilohertz, so extremely, extremely high precision data there where timing really matters a lot. And, you know, I can, one of the really powerful things about Influx is the fact that it can handle this. That's one of the reasons we chose it, because, there's, times when we're looking at the results of a firing where you're zooming in, you know, I talked earlier about how on my current job we often zoom out to look at a year's worth of data. You're zooming in to where your screen is preoccupied by a tiny fraction of a second, and you need to see same thing as Angelo just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers, so that can be something like, "Hey, I opened this valve at exactly this time," and that goes, we want to have that at, micro, or even nanosecond precision so that we know, okay, we saw a spike in chamber pressure at this exact moment, was that before or after this valve opened? That kind of visibility is critical in these kind of scientific applications, and absolutely game changing to be able to see that in near real time, and with, a really easy way for engineers to be able to visualize this data themselves without having to wait for us software engineers to go build it for them. >> Can the scientists do self-serve or do you have to design and build all the analytics and queries for your scientists? >> Well, I think that's absolutely, from my perspective that's absolutely one of the best things about Influx and what I've seen be game changing is that, generally I'd say anyone can learn to use Influx. And honestly, most of our users might not even know they're using Influx, because, the interface that we expose to them is Grafana, which is a generic graphing, open source graphing library that is very similar to Influx zone Chronograf. >> Sure. >> And what it does is, it provides this almost, it's a very intuitive UI for building your queries. So, you choose a measurement and it shows a dropdown of available measurements. And then you choose the particular fields you want to look at, and again, that's a dropdown. So, it's really easy for our users to discover and there's kind of point and click options for doing math, aggregations. You can even do like perfect kind of predictions all within Grafana, the Grafana user interface, which is really just a wrapper around the APIs and functionality that Influx provides. >> Putting data in the hands of those who have the context, the domain experts is key. Angelo, is it the same situation for you, is it self-serve? >> Yeah, correct. As I mentioned before, we have the astronomers making their own dashboards because they know what exactly what they need to visualize. >> Yeah, I mean, it's all about using the right tool for the job. I think for us, when I joined the company we weren't using InfluxDB and we were dealing with serious issues of the database growing to an incredible size extremely quickly, and being unable to like even querying short periods of data was taking on the order of seconds, which is just not possible for operations. >> Guys, this has been really formative, it's pretty exciting to see how the edge, is mountaintops, lower Earth orbits, I mean space is the ultimate edge, isn't it? I wonder if you could answer two questions to wrap here. You know, what comes next for you guys? And is there something that you're really excited about that you're working on? Caleb maybe you could go first and then Angelo you can bring us home. >> Basically what's next for Loft Orbital is more satellites, a greater push towards infrastructure, and really making, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, making that happen. It's extremely exciting, an extremely exciting time to be in this company and to be in this industry as a whole. Because there are so many interesting applications out there, so many cool ways of leveraging space that people are taking advantage of, and with companies like SpaceX and the, now rapidly lowering cost of launch it's just a really exciting place to be in. We're launching more satellites, we are scaling up for some constellations, and our ground system has to be improved to match. So, there's a lot of improvements that we're working on to really scale up our control software to be best in class and make it capable of handling such a large workload, so. >> Are you guys hiring? >> We are absolutely hiring, so I would, we have positions all over the company, so, we need software engineers, we need people who do more aerospace specific stuff. So absolutely, I'd encourage anyone to check out the Loft Orbital website, if this is at all interesting. >> All right, Angelo, bring us home. >> Yeah. So what's next for us is really getting this telescope working and collecting data. And when that's happened is going to be just a deluge of data coming out of this camera and handling all that data is going to be really challenging. Yeah, I want to be here for that, I'm looking forward. Like for next year we have like an important milestone, which is our commissioning camera, which is a simplified version of the full camera, it's going to be on sky, and so yeah, most of the system has to be working by then. >> Nice. All right guys, with that we're going to end it. Thank you so much, really fascinating, and thanks to InfluxDB for making this possible, really groundbreaking stuff, enabling value creation at the Edge, in the cloud, and of course, beyond at the space. So, really transformational work that you guys are doing, so congratulations and really appreciate the broader community. I can't wait to see what comes next from having this entire ecosystem. Now, in a moment, I'll be back to wrap up. This is Dave Vellante, and you're watching theCUBE, the leader in high tech enterprise coverage. >> Welcome. Telegraf is a popular open source data collection agent. Telegraf collects data from hundreds of systems like IoT sensors, cloud deployments, and enterprise applications. It's used by everyone from individual developers and hobbyists, to large corporate teams. The Telegraf project has a very welcoming and active Open Source community. Learn how to get involved by visiting the Telegraf GitHub page. Whether you want to contribute code, improve documentation, participate in testing, or just show what you're doing with Telegraf. We'd love to hear what you're building. >> Thanks for watching Moving the World with InfluxDB, made possible by Influx Data. I hope you learned some things and are inspired to look deeper into where time series databases might fit into your environment. If you're dealing with large and or fast data volumes, and you want to scale cost effectively with the highest performance, and you're analyzing metrics and data over time, times series databases just might be a great fit for you. Try InfluxDB out. You can start with a free cloud account by clicking on the link in the resources below. Remember, all these recordings are going to be available on demand of thecube.net and influxdata.com, so check those out. And poke around Influx Data. They are the folks behind InfluxDB, and one of the leaders in the space. We hope you enjoyed the program, this is Dave Vellante for theCUBE, we'll see you soon. (upbeat music)

(upbeat tropical music) >> Announcer: Live from San Juan, Puerto Rico. It's The Cube, covering Blockchain Unbound, brought to you be Blockchain Industries. (upbeat tropical music) >> Hello, everyone. Welcome to this special Cube conversation. We are on the ground in Puerto Rico for Blockchain Unbound and Restart Week, a variety of blockchain, cryptocurrency, industry events, a lot of action here. All the thought leaders, the pioneers, a lot of the people making it happen, from entrepreneurs to the investors, and entrepreneurs who made it in bitcoin blockchain, as well as participants in the local community. Our next guest is Michael Angelo, the co-founder of EDU Block, Edublock.io, EDUblock.io. Interesting story here, he's got a school chain, I call it, going around. Michael, welcome to the conversation. >> It's great to be here. >> So talk about what you guys do. And I think it's super fascinating, you guys are creating a value chain with the university system. Obviously, you know, the first thing that jumps to mind is, hey, it's like the internet. Connect the internet with TCP/IP and next thing you know, the internet's born, the web is born. You're doing something really fascinating with your project, connecting the universities here in Puerto Rico. Take a minute to explain what you're working on. >> Okay, so, Edublock is an educational platform based in Puerto Rico. So what we're doing is, we're connecting every single university in the island to work on open-source projects, to make solutions for the private sector. >> And so you're enabling this actual connectedness, so you got the blockchain which can enable that, cryptocurrency in Puerto Rico is certainly hot. A lot of the ecosystem blending in, coming into the country, into the area; people are excited. What's going on in the front lines? As the young kids are looking at this revolution, this is a massive wave, they've got to be inspired. They've got to look at this as an opportunity. What's some of the things that you're seeing on the front-lines, there? >> Okay, well let me tell you. So, people are scared here. So, Edublock wants to create transparency in blockchain and make people trust us and trust the movement. So we see a bunch of people coming here, and we see a tremendous potential for the island. We could become an emerging market through blockchain technology. But people are scared. Most people come here and they talk about the how and the what, so Edublock wants to talk about the why. So, why is... We want to educate, we want to make this transparent. We want to change the lives of a bunch of people, teach them, so they can become the next world leaders. >> And really, enabling them with tools. So Brock Pierce gave the keynote here, to the kickoff of Blockchain Unbound, as part of a kind of a pitch competition with d10e. Great message, power of we, not me, is really what makes it happen. Paying it forward, cultural ethos. It's global, so this whole global economy's shaping. This is an opportunity for a digital nation to emerge. How do you guys talk about that? The young guys going in there, the developers. The trust needs to be there. What are some of the things people are working on? What kind of things do you imagine happening with Edublock? What are some of the things on your mind, there? >> Okay, so basically what we're doing is, anyone who's coming here in the island, we're just asking them, if you want outreach, you have an ICO, you have a big project, so we have this ecosystem that's running. We have software developers, and you want to teach people. So if you have your ICOs, you have a project, you give it to us, we just lay it down in the ecosystem and see how it works, trial and error. And it's a win-win, 'cause it's free. So you win, you win the expansion here in the island, and we win knowledge. >> So basically, you guys are opening up your arms, saying, hey, throw us what you got, we'll kick the tires, we'll give it a dry run, we'll give you feedback, there's some learnings that are shared. Is that kind of the thing you guys are thinking about? Is that what you're referring to? >> Yeah, that's exactly what we're doing as of now. So we have few projects, we're working with ListCoin, and we have a few ICOs of ourselves, that I cannot go into details right now. But some big projects, that I think some software developers in the island that have talent, could work on, and just develop. >> Michael, talk about who's working with you guys. Who's helping you out? Give some shout-outs, who's involved in the project, what kind of momentum do you have? And what are you guys looking for, for continued support? >> So, we're looking for people that come to the island and have big ICOs. We're looking to just speak with them, see if they could give us some feedback on what we have to do to move along this project. So we're working with Link Puerto Rico, it's a software development company here in the island. So they're helping us with the curriculum. So we're working hands-on with ICOs, but we also want to teach. So we have to make a curriculum. So we teach people that have no idea. The other day, we had an event where we taught 50 people how to create a smart contract from scratch. Those are 50 people who are not the same anymore. So we're working with Brock Pierce, he's going to be one of the main speakers at our event. We're going to have an event the 17th. You can register at Edublock.eo, it's totally free. Why did this event come to be? So, we have Blockchain Unbound, right? So it's about $1,000. So most people want to be part of this event that can't be. Most humans, that's too of a hefty pay. >> John: Yeah, it's a lot of cash. >> It's a lot of cash. You know, $1,000 is food; $1,000 is gas, a whole semester is $1,000. So what we did was, we grabbed 14 main speakers from Blockchain Unbound, Enrique Martinez, Brock Pierce, ListCoin, ArtCoin, they're going to be talking about microgrids, about housing. So we got a university, we have the people. It's free, so anyone can come. All you have to do is register at Edublock.io. >> Great stuff, Michael, this is fantastic. I love what you're doing, and I'm really thankful you're doing it. And because, when you get people together, magic happens. And I think what's really exciting is that the market is accepting that now. And Brock talked about that on stage today, here at Blockchain Unbound, announcing his restart venture fund. 100% dedicated to entrepreneurs. And he's structuring it in a way, where... I mean, not a lot of preference here. So he gets a little bit carved out for the managers of the fund, and they got some lot of cash they're managing. But it's all about feeding the entrepreneurial ecosystem for venture development. >> And that's great, that's why Edublock has to be a thing. 'Cause we are the educational system in the island. And so, if this is a movement that's happening here, and this is going to become the epicenter of this multi-billion dollar market, we need to have people prepared for this. We have to create the transparency. So that's why Edublock is such an important thing, here in the island. >> I love what you're doing, the young people. I see it in Silicon Valley, all around the United States and around the world. Trust matters, reputation matters, who you work with matters. And I love your project. It reminds me of when I interviewed Vint Cerf many years ago, father of the internet. TCP/IP connected three universities, four universities, five universities, and then multiple universities. That became the backbone for the internet. I see what you're doing as something as game-changing. You can connect the universities and then the curriculum, and keep it decentralized, no central authority, you have the trust and you have the voices of the people and software and applications. That's super fantastic. >> By the way, I just want to say something right now. You don't have to be a software developer to be in Edublock. So, most people are scared that if they aren't a programmer, they don't have experience, the don't know solidity, they can't be part of Edublock. The thing is, we're teaching from scratch, as well. We're working with software, we're working with hardware, we're working with a team of daily traders. Miners, we're going to teach how to make GPU, how to make an A6 from scratch. So you're going to learn a lot of things, and it's free. >> Great point. That brings up the community question. Because the point is, you don't have to be a coder. You're in the community. So, I want to ask you, what is the community like right now? What's it look like? It sounds like it's robust, it's active. What do you and the guys hope to do with the development of the community? >> Okay so the community, I would say it's divided, as of now. So most people are scared, they don't know what's going on. Most people that come here start off with the what, the how, and people are scared. But the young people, are like, yo, this is happening. This is not a moment, this is a movement. This is a movement and they're just so happy to be part of it. >> Well, I got to tell ya, as an old guy like me, I've seen many waves. When the waves come, you jump on it. And I'm so excited that you're doing what you're doing. Appreciate what you're doing. Michael Angelo, co-founder of EDU block.io, Edublock.io. They have a big event on the 17th, if you want to check it out. We're going to try to do a swing by with The Cube, but congratulations. Bringing the content to the masses, that's our job at The Cube, that's what we do, that's our mission. And thanks for taking this time, appreciate it. >> Of course. >> I'm John Furrier, with The Cube. Thanks for watching. (upbeat electronic music)

>> Announcer: Live from Las Vegas, its theCUBE, covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back the the Aria in Las Vegas, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with Stu Miniman. Angelo Sciascia is here, big Tom Brady fan, Senior Vice President of NetX Information Systems, from Brooklyn, New York, I don't think so. >> Not a Tom Brady fan. >> Thanks for coming on theCUBE do you think it matters, how much it airs at a football. >> No, not at all, Tom Brady doesn't care about that. >> No, well, listen, thanks for coming on. We have a great conversation, we love talking sports on the Cube. So welcome, how's the show going for you? >> Ah, it's fantastic, you know, lots of great material Veritas has been talking about. 360 Data Management, obviously we all know the benefits of that by now. So we have a lot of customers here so I'm glad they they got to see it from a senior leadership perspective, rather than our sales guys and sales engineers going in there and talking to them, and seeing Veritas executives really getting behind what we're talking about. So it backs up our story and, you know, our customers are pretty excited about it, actually. >> What's the nature of your relationship with Veritas. I know you have a relationship, and maybe still do, with Symantec. How's that all, how did it all evolve? >> Yeah, so we are a Veritas Platinum Partner, we would be, what we consider, a solution-provider type partner. A lot of our business today is either directly or indirectly tied to Veritas, which was kind of funny because we started as a security company, so our roots are systems management, you know. That's where we were in 2005 when I joined NetX, that's where we were for many, many years after Symantec acquired a company called Altiris. We just stayed in that vein, you know, managing endpoints, securing endpoints, encrypting data. And then, somewhere in 2013, we said hey, you know, let's try to diversify the portfolio a little bit. And we used to manufacture an endpoint management appliance for Altiris so we said hey, Symantec's got these things called NetBackup Appliances, let's check it out. It's a formed fact that we know how to sell and, shoot, four years later it's been a great partnership for us, great partnership, I'm sure, for Veritas, and for our customers and that's a lot of our business today. >> So, I mean, it's hot market, you know. Data protection is exploding, and security. I mean, you're in two of the sweet spots in the market right now. So how do you approach the business with customers? Do you, are you a specialist around data protection? You deliver services around them. Maybe you can explain it on the model? >> Yeah, you know, that's actually a good question, because it's evolved quite a bit, right? So, you know, when you had a limited portfolio of just one or two products that you can sell to a customer, you're really doing a product sale, right, which, I would say that was probably the most difficult transition from the split from Symantec to Veritas, because at Symantec we had thousands of products in the portfolio, or hundreds of products in the portfolio that we could actually talk to. And for a little while, really we had a handful, you know, we had NetBackup Appliances, Enterprise Vault and ancillary things to bulk on to that, like Clearwell. I think one of the most exciting things for us, as a reseller, is to now be able to go have a discussion with our customers that we were never able to have before. And rather than sit there and try to sell them a backup product or a storage solution, we could sell them a platform that solves many problems for them, right? Rather than sitting there and trying to sell one-off. So, our conversations are significantly more strategic now then they've ever been, and frankly I speak for myself and my whole team, I know everyone enjoys the conversation more now that we have a portfolio to talk about, than just a handful of products. >> Angelo, you've got an interesting viewpoint on this split off of Aritas from Symantec. What have your customers said about it? What's been your interaction with the organization? What can you tell us about kind of the inside going on? >> Yeah, look, I've lived firsthand on a Symantec acquisition of a company, okay. I was, we were not a Symantec partner when they acquired Veritas. Funny enough, I was actually doing Veritas consulting, you know, on my own on the side prior to Symantec purchasing Veritas. So I really, I'd made my career on two products; Veritas for backup and Altiris for systems management. Symantec bought Veritas and I was like okay, you know, I'm just going to stay with Altiris. Symantec bought Altiris and here we are now, so we can talk about all of them. The thing I noticed was Symantec was always going to be a security company, right, and they weren't going to change that no matter how much they try to integrate it. It's two radically different stories. You know, and for many, many years, things that we look at as new products today were kind of already there in the Symantec portfolio, but buried underneath other products that really never saw the light of day because when you have hundreds or thousands of products, like I said earlier, you know, the ones that are going to move the most are the ones that are going to get the attention. So I think the benefit of the split is that it really allowed Veritas to focus on what they do well, which is managing data, and Symantec to do what they do well, which is securing your infrastructure and securing your data. From my perspective, our customers really appreciated that. Sure, a couple of them were a little annoyed that they had to now split contracts and deal with that kind of stuff, but I think that was a momentary blip and for the most part, it's been well-received from everyone we've spoken to. >> Angelo, you said you're having, your conversations are evolving. Who are you talking to? And maybe take us inside some of those conversations. What are the big challenges they're having? >> Yeah, a year ago, a year and a half ago I was talking to either somebody who was on the messaging side and needed to archive emails or IMs, or on the backup side and they just wanted to be able to meet their backup windows and maybe to get some better d dub rates, right. Fun conversation to have, bit mundane. It's not really solving problems as much as backing up data or archiving data. Today, we're having overarching conversations at a C-level, or a senior VP level, or a director level, and talking about dramatic changes to the way they do business, and how we can do business with them. Six months ago, NetX, we weren't doing anything in the Cloud, you know. We were selling to some customers' Vdub space to the Cloud, and that's about it. We weren't talking Cloud strategy with them. Today we're talking to our customers about moving workloads to the Cloud, doing it in a way that's predictable for them, and doing it with Veritas. >> That's a really interesting point. I have to imagine that changed who you're talking with inside the company. Can you walk us through kind of a typical customer's, you know, and how you kind of move up into a more strategic discussion for Cloud strategy? >> You know, so for full transparency, that whole thing's still evolving, right. 360 Data Management is still fairly new. So what we're seeing, the conversations turned, it would start, again we're talking to somebody that we've been talking to historically in the backup side or architecture side, and we talk to them about wanting to do better things than what their backup is, and start to talk about, hey this is what 360 Data Management is. What's relevant to that person he's going to want to talk about but then there's going to be things in there that are not relevant to him. So he'll make that introduction and he'll get other stakeholders in the boat with him. And that's something we've really appreciated because the people you used to talk to are now bringing in stakeholders to offset their own desires and their own budgets, so want to bring in other technology. And typically, when we get to that point when we're starting to talk about strategic pricing, is when you're getting that C-level person to really have that aha moment, and say wow, we're offsetting costs here, we're doing things like truly getting rid of tape, or moving to the Cloud and things like that, and it's a conversation that really evolves and it's still starts at the bottom. But we're figuring out ways to start it at a higher point. >> Well, those strategies are still evolving for most customers; the roles of those people that might have had one role definitely are changing. I'm curious, one of the big transition points, especially for a company like Veritas, is going from licenses to some kind of more of a subscription model. Any commentary you have on your customers; their embrace, or like, dislike of some of those transitions? >> I think the one thing the Cloud has done is it's opened up a different avenue of how people consume IT, right. Cloud is very much consumption-based billing, and while that can complicate our lives from a reseller perspective in terms of how to collect and track monthly billing and things like that, they like it because they feel like, and it's the truth, they're only paying for what they're truly using, rather than paying for products or infrastructure that they're only using part of the day, or software that they're only using for a particular project. A lot of our healthcare systems might have a research project that their going on, and they might like to scale up for some backup licensing and scale back down once that project is done. Consumption licensing allows that, versus having to go to them and saying, hey, well now you got to buy 200 terabytes of perpetual licensing, and justify that capital expense, rather than having an operational expense on just that one particular workload that you have to back up for that one period of time. >> Angelo, Stu and I are always interested in the human capital management aspects of things, and you talked about, you went from sort of talking about having a conversation around email archiving or backup, to one about the Cloud, Cloud strategies. From your internal organization perspective, how did you manage that? Are you rescaling, are you retraining? Is it just you got really supersmart people that can adapt? >> We definitely have supersmart people, because they're all over there, that's right. But I definitely have supersmart people. But, you know, it's a little bit of both. It's a little bit of, you know, you take one of our data protection projects; see Christian Muma, you know, he's been in the data center for god knows how many years, he has seen technology evolve. It was a natural fit to look at Cloud infrastructure. Started taking some classes, consumed it, all the information he could, and now we're out there actively selling it. In some other respects, we had to hire from outside and bring in some services ourselves to actually use, maybe some third party partnerships to help us better understand how we price out Cloud for our customers. So it's a little bit of everything, and I think that that's what's exciting about it, because I think for the first time in a long time, everyone's learning something new at the same time, because, I don't care what anyone said about the Cloud years ago; it's different today, it's going to be different in six months, it's going to be different in nine months. And I think that that's exciting, and I've been in this industry since 1996. I've seen a lot of really cool things come and go. I just think that there's still infancy in the Cloud and I think it's exciting because everyone's still learning. And any time you can still learn, I think that's, I think an important part of your job. >> So when you think about your, sort of, near-term and midterm and long-term plan for the company, how do you sort of describe that? Where do you want to take this thing? >> Near-term, I want to have a solid end of the quarter. >> Business is good, right, I mean market's booming right now. >> Business is very good. Veritas will tell me it's not good enough but they're just never happy. No, business is, business is very good. I think, near-term for us, you said hey, how do we get our head around it? Near-term for us is, as we're absorbing all this information, is start to really figure out what our path is going to be. So near-term, I think we still have to identify other ancillary partners that we need to bring to the table. We've got our partnerships with Azure, Microsoft Azure, and our partnerships with AWS. We'll probably have to look at Google and IBM and see what they're doing, and then we have to look at other partnerships that are not related to Veritas but still drive that home. We maybe look at a different colo partnership or partnerships around outsourcing billing, things like that, that we can make where it's easier for our customers to consume the technology. So I think six to nine months from now if we were to have the same conversation, everything that we're doing today is probably going to be somewhat different. But I just think that there's still a lot of planning to do. >> Angelo, any feedback from your customers on what there's still on the to-do list from the vendors? We talked, you know, the strategy, Cloud's changing a lot, you know. What are some of the pinpoints that they said hey, if we could get this into the offering from Veritas or some of the others it would make our lives a lot easier. >> I mean, that's a tough question, because we're going to them now and changing the conversation already. You know, obviously they're always asking for different features, but I don't like to get into a feature conversation with the customers. I try to solve the problem. >> Dave: You're leading that conversation, is what you're saying. >> Yeah, I don't want to get into the weeds of talking about well, this widget does it at 50% and you do it at 48%. You know, I try to sit a little bit more macro. I think that one of the things our customers have asked us to do a better job at is figure out better ways to make it easier to consume the technology from budget perspective. So we're trying to figure that out now; 360 Data Management is a subscription, Veritas would like them sold in three years, we're trying to figure out ways to get creative with our customers on that. What's the right bundle, what's not the right bundle. One thing that I've noticed, and Veritas have been great at it, is we have to have some flexibility in terms of adding things in and make it seem like it's all part of that bundle. There's been some flexibility and I think that, because of that, we haven't hit that roadblock yet where, well, we really want this product in the bundle. Reality is that we'll work through that and try to add it in there, some way, shape or form, even if behind the scenes. >> The customers see you as the experts, and what we often see is that technology is the technology; it's pretty much understood. What's not understood by the customers is how to apply it to their business, and their business is changing so fast that it seems like they're looking to organizations like yours saying okay, here's our business challenge. How can you help me? You tell me, and then the best answer is somebody he'll be able to work with. Is that a valid, sort of, premise? >> Yeah, it is, it certainly is and I think we're really uniquely positioned in the fact that, here we've got, we've got our partnership with Veritas and we're 100% focused to everything in the Veritas portfolio so we don't compete from within. That's the same thing that we could say, basically, on Symantec and some of our traditional storage partners as well. That'll change most likely, on our storage partners, especially because of what Veritas have been releasing with Access and some of the other software providing storage technology. When we're brought in, we're brought in as the experts in that finite area, so we're not brought in as a generalist-type of reseller. We're brought in as, hey, I've got a data management problem, I've got a data security problem, or I'm trying to do some high-performance workloads on storage. So yeah, we are the experts, but at the same time we're being brought in for those handfuls of things, so we're not having these, hey, can you maximize my span on anti-virus software because I want to sell you commoditized software. It's just not us, it's not our thing. We're not adding any value to the customers, or the poor owners for that matter. >> Angelo, curious that there's a lot of startups in the data protection space. What do you here, your customers asking you about them? You know, what's your thoughts there? >> I guess I got to be nice, right? Because I'm being streamed everywhere. >> Stu: They're not listening, go ahead, be a New Yorker. >> Listen, I challenge Rubrik at any point of time, you know, those guys, Rubrik, Cohesity, those guys, they're new, they're the shiny new toy. The problem, the problem is they have their messaging out there, and the problem we have is that they're the shiny new toy. But when the rubber hits the road and when it's time to actually go and prove out what the technology can do, we'll win all the time. We will win ten out of ten times if we get the seat at the table, right. The problem is is because we were a limited portfolio, a limited product, limited integration type of company before, we weren't getting that seat at the table. I think they see it now, I think they're starting to get a little concerned about, hey, you know what, if this 360 Data Management is what it's going to be, and we all know it is, I think they're going to be concerned. They're new, and they're going to get attention. My honest opinion: I'm glad they came out, I'm glad that Rubrik and Cohesity and all these guys came out and did all this different ways to go to market, because I think it really forced all of us to say hey, we got some real tough decisions to make here, the competition has caught up, in certain ways. Let's change the game, and 360 Data Management does that. I think they should take as much business as they can right now, because it's going to be short-lived. >> You said it makes you rethink your strengths, and like you said, change the game. >> Yeah, it changes the game. >> Yeah. Uh, okay, predictions on the MLB? Yankees won their getaway game today to put the pressure on the Red Sox, two and a half to two and a half games back. You know, the Indians are looking good, my man, Terry Francona. What's your prediction for it? >> The Sox fan's outnumbered two to one here, so go ahead. >> You know, so I shouldn't say that the Yankees are going to win the World Series? >> No, he's a Yankees fan. >> I'm a Yankee fan, too. >> Honestly, as a Yankee fan, I think we all know that they weren't supposed to be this team, so I think this is, that's the team to look out for. >> Dave: Maybe this is their year. >> I think this is the year that they're going to challenge people, I mean, are they going to win? It's Cleveland, do you really think Cleveland's going to win anything? They won one thing in the last, what, 30 years. >> That's what they used to say about us in Boston. Angelo, thanks so much coming on, really appreciate it. Keep right there, buddy, we'll be back with our next guest right after this short break. We're live from-- (electronic music)

>>Time series data is any data that's stamped in time in some way that could be every second, every minute, every five minutes, every hour, every nanosecond, whatever it might be. And typically that data comes from sources in the physical world like devices or sensors, temperature, gauges, batteries, any device really, or things in the virtual world could be software, maybe it's software in the cloud or data and containers or microservices or virtual machines. So all of these items, whether in the physical or virtual world, they're generating a lot of time series data. Now time series data has been around for a long time, and there are many examples in our everyday lives. All you gotta do is punch up any stock, ticker and look at its price over time and graphical form. And that's a simple use case that anyone can relate to and you can build timestamps into a traditional relational database. >>You just add a column to capture time and as well, there are examples of log data being dumped into a data store that can be searched and captured and ingested and visualized. Now, the problem with the latter example that I just gave you is that you gotta hunt and Peck and search and extract what you're looking for. And the problem with the former is that traditional general purpose databases they're designed as sort of a Swiss army knife for any workload. And there are a lot of functions that get in the way and make them inefficient for time series analysis, especially at scale. Like when you think about O T and edge scale, where things are happening super fast, ingestion is coming from many different sources and analysis often needs to be done in real time or near real time. And that's where time series databases come in. >>They're purpose built and can much more efficiently support ingesting metrics at scale, and then comparing data points over time, time series databases can write and read at significantly higher speeds and deal with far more data than traditional database methods. And they're more cost effective instead of throwing processing power at the problem. For example, the underlying architecture and algorithms of time series databases can optimize queries and they can reclaim wasted storage space and reuse it. At scale time, series databases are simply a better fit for the job. Welcome to moving the world with influx DB made possible by influx data. My name is Dave Valante and I'll be your host today. Influx data is the company behind InfluxDB. The open source time series database InfluxDB is designed specifically to handle time series data. As I just explained, we have an exciting program for you today, and we're gonna showcase some really interesting use cases. >>First, we'll kick it off in our Palo Alto studios where my colleague, John furrier will interview Evan Kaplan. Who's the CEO of influx data after John and Evan set the table. John's gonna sit down with Brian Gilmore. He's the director of IOT and emerging tech at influx data. And they're gonna dig into where influx data is gaining traction and why adoption is occurring and, and why it's so robust. And they're gonna have tons of examples and double click into the technology. And then we bring it back here to our east coast studios, where I get to talk to two practitioners, doing amazing things in space with satellites and modern telescopes. These use cases will blow your mind. You don't want to miss it. So thanks for being here today. And with that, let's get started. Take it away. Palo Alto. >>Okay. Today we welcome Evan Kaplan, CEO of influx data, the company behind influx DB. Welcome Evan. Thanks for coming on. >>Hey John, thanks for having me >>Great segment here on the influx DB story. What is the story? Take us through the history. Why time series? What's the story >><laugh> so the history history is actually actually pretty interesting. Um, Paul dicks, my partner in this and our founder, um, super passionate about developers and developer experience. And, um, he had worked on wall street building a number of time series kind of platform trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave, which means you had to do a ton of work just to start doing work, which means you had to write a bunch of extrinsic routines. You had to write a bunch of application handling on existing relational databases in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view is this is not how developers should work. And so in 2013, he went through why Combinator and he built something for, he made his first commit to open source in flu DB at the end of 2013. And, and he basically, you know, from my point of view, he invented modern time series, which is you start with a purpose-built time series platform to do these kind of workloads. And you get all the benefits of having something right outta the box. So a developer can be totally productive right away. >>And how many people in the company what's the history of employees and stuff? >>Yeah, I think we're, I, you know, I always forget the number, but it's something like 230 or 240 people now. Um, the company, I joined the company in 2016 and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. Cuz if you think about it, what sensors do is they speak time, series, pressure, temperature, volume, humidity, light, they're measuring they're instrumenting something over time. And so I thought that would be super relevant over long term and I've not regretted it. >>Oh no. And it's interesting at that time, go back in the history, you know, the role of databases, well, relational database is the one database to rule the world. And then as clouds started coming in, you starting to see more databases, proliferate types of databases and time series in particular is interesting. Cuz real time has become super valuable from an application standpoint, O T which speaks time series means something it's like time matters >>Time. >>Yeah. And sometimes data's not worth it after the time, sometimes it worth it. And then you get the data lake. So you have this whole new evolution. Is this the momentum? What's the momentum, I guess the question is what's the momentum behind >>You mean what's causing us to grow. So >>Yeah, the time series, why is time series >>And the >>Category momentum? What's the bottom line? >>Well, think about it. You think about it from a broad, broad sort of frame, which is where, what everybody's trying to do is build increasingly intelligent systems, whether it's a self-driving car or a robotic system that does what you want to do or a self-healing software system, everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well, and you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened what's gonna happen? And so you get to these applications like predictive maintenance or smarter systems. And increasingly you want to do that stuff, not just intelligently, but fast in real time. So millisecond response so that when you're driving a self-driving car and the system realizes that you're about to do something, essentially you wanna be able to act in something that looks like real time, all systems want to do that, want to be more intelligent and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a >>Market. It's interesting near real time. Isn't good enough when you need real time. >><laugh> yeah, it's not, it's not. And it's like, and it's like, everybody wants, even when you don't need it, ironically, you want it. It's like having the feature for, you know, you buy a new television, you want that one feature, even though you're not gonna use it, you decide that your buying criteria real time is a buying criteria >>For, so you, I mean, what you're saying then is near real time is getting closer to real time as possible, as fast as possible. Right. Okay. So talk about the aspect of data, cuz we're hearing a lot of conversations on the cube in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get, know how to fix it. So this is a big part of how we're seeing with people saying, Hey, you know, I wanna make my machine learning algorithms better after the fact I wanna learn from the data. Um, how does that, how do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data knowing when it happened? >>Well, for sure. So, so for sure, what you're saying is, is, is none of this is non-linear, it's all incremental. And so if you take something, you know, just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop, which is I instrumented, I watch what happens, oh, that's wrong? Oh, I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car, but every system moves along that evolution. And so you get the dynamic of, you know, of constantly instrumenting watching the system behave and do it. And this and sets up driving car is one thing. But even in the human genome, if you look at some of our customers, you know, people like, you know, people doing solar arrays, people doing power walls, like all of these systems are getting smarter. >>Well, let's get into that. What are the top applications? What are you seeing for your, with in, with influx DB, the time series, what's the sweet spot for the application use case and some customers give some >>Examples. Yeah. So it's, it's pretty easy to understand on one side of the equation that's the physical side is sensors are sensors are getting cheap. Obviously we know that and they're getting the whole physical world is getting instrumented, your home, your car, the factory floor, your wrist, watch your healthcare, you name it. It's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but, but they're all on that side. They're all about IOT. So they're think about consumer IOT projects like Google's nest todo, um, particle sensors, um, even delivery engines like rapid who deliver the Instacart of south America, like anywhere there's a physical location do and that's on the consumer side. And then another exciting space is the industrial side factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational because what, what has to get smarter when you're building, when you're building a factory is systems all have to get smarter. And then, um, lastly, a lot in the renewables sustainability. So a lot, you know, Tesla, lucid, motors, Cola, motors, um, you know, lots to do with electric cars, solar arrays, windmills, arrays, just anything that's gonna get instrumented that where that instrumentation becomes part of what the purpose >>Is. It's interesting. The convergence of physical and digital is happening with the data IOT. You mentioned, you know, you think of IOT, look at the use cases there, it was proprietary OT systems. Now becoming more IP enabled internet protocol and now edge compute, getting smaller, faster, cheaper AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? What was the, what's the IOT where's the IOT dots connecting to because you know, as these two cultures merge yeah. Operations, basically industrial factory car, they gotta get smarter, intelligent edge is a buzzword, but I mean, it has to be more intelligent. Where's the, where's the action in all this. So the >>Action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the actions really happen at the developer. And so what you're seeing is a movement in the world that, that maybe you and I grew up in with it or OT moving increasingly that developer driven capability. And so all of these IOT systems they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business. What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express theself or am I trying to figure out when the next heart rate monitor's gonna show up on my apple watch, right? What am I trying to do? What's the system I need to build. And so starting with the developers where all of the good stuff happens here, which is different than it used to be, right. Used to be you'd buy an application or a service or a SA thing for, but with this dynamic, with this integration of systems, it's all about bespoke. It's all about building >>Something. So let's get to the developer real quick, real highlight point here is the data. I mean, I could see a developer saying, okay, I need to have an application for the edge IOT edge or car. I mean, we're gonna have, I mean, Tesla's got applications of the car it's right there. I mean, yes, there's the modern application life cycle now. So take us through how this impacts the developer. Does it impact their C I C D pipeline? Is it cloud native? I mean, where does this all, where does this go to? >>Well, so first of all, you're talking about, there was an internal journey that we had to go through as a company, which, which I think is fascinating for anybody who's interested is we went from primarily a monolithic software that was open sourced to building a cloud native platform, which means we had to move from an agile development environment to a C I C D environment. So to a degree that you are moving your service, whether it's, you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right. To degree that that service is cloud. Then increasingly remove from an agile development to a C I C D environment, which you're shipping code to production every day. And so it's not just the developers, all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also gonna happen in a big way >>When your customer base that you have now, and as you see, evolving with infl DB, is it that they're gonna be writing more of the application or relying more on others? I mean, obviously there's an open source component here. So when you bring in kind of old way, new way old way was I got a proprietary, a platform running all this O T stuff and I gotta write, here's an application. That's general purpose. Yeah. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does its job >>A good way to think about this is versus a new way >>Is >>What so yeah, good way to think about this is what, what's the role of the developer slash architect CTO that chain within a large, within an enterprise or a company. And so, um, the way to think about it is I started my career in the aerospace industry <laugh> and so when you look at what Boeing does to assemble a plane, they build very, very few of the parts. Instead, what they do is they assemble, they buy the wings, they buy the engines, they assemble, actually, they don't buy the wings. It's the one thing they buy the, the material for the w they build the wings, cuz there's a lot of tech in the wings and they end up being assemblers smart assemblers of what ends up being a flying airplane, which is pretty big deal even now. And so what, what happens with software people is they have the ability to pull from, you know, the best of the open source world. So they would pull a time series capability from us. Then they would assemble that with, with potentially some ETL logic from somebody else, or they'd assemble it with, um, a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers, but they become masters of that bespoke application. And I think that's where it goes, cuz you're not writing native code for everything. >>So they're more flexible. They have faster time to market cuz they're assembling way faster and they get to still maintain their core competency. Okay. Their wings in this case, >>They become increasingly not just coders, but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff by the way, this is not different than the people just up the road Google have been doing for years or the tier one, Amazon building all their own. >>Well, I think one of the things that's interesting is is that this idea of a systems developing a system architecture, I mean systems, uh, uh, systems have consequences when you make changes. So when you have now cloud data center on premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >>That's exactly. But that's where the that's where the, you know, that that Boeing or that airplane building analogy comes in for us. We've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on pre edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that you wanna make sure, at least that base layer, that database layer, that those components talk to each other. >>So I'll have to ask you if I'm the customer. I put my customer hat on. Okay. Hey, I'm dealing with a lot. >>That mean you have a PO for <laugh> >>A big check. I blank check. If you can answer this question only if the tech, if, if you get the question right, I got all this important operation stuff. I got my factory, I got my self-driving cars. This isn't like trivial stuff. This is my business. How should I be thinking about time series? Because now I have to make these architectural decisions, as you mentioned, and it's gonna impact my application development. So huge decision point for your customers. What should I care about the most? So what's in it for me. Why is time series >>Important? Yeah, that's a great question. So chances are, if you've got a business that was, you know, 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that you built something on a Oracle or you built something on IBM's DB two, right. And you made it work within your system. Right? And so that's what you started building. So it's already out there. There are, you know, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time. I hate the word, but digital transformation. Then you start with time series. It's a foundational base layer for any system that you're gonna build. There's no system I can think of where time series, shouldn't be the foundational base layer. If you just wanna store your data and just leave it there and then maybe look it up every five years. That's fine. That's not time. Series time series is when you're building a smarter, more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems, the more obvious it becomes. >>And since I have a PO for you and a big check, yeah. What is, what's the value to me as I, when I implement this, what's the end state, what's it look like when it's up and running? What's the value proposition for me. What's an >>So, so when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, they're transforming it in near real time. So that the other dependencies that a system that gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's, you know, it's not like it's doing every action that's above, but it's foundational to build a really compelling, intelligent system. I think that's what developers and archs are seeing now. >>Bottom line, final word. What's in it for the customer. What's what, what's your, um, what's your statement to the customer? What would you say to someone looking to do something in time series on edge? >>Yeah. So, so it's pretty clear to clear to us that if you're building, if you view yourself as being in the build business of building systems that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time that you start from time series. But I also wanna say what's in it for us influx what's in it for us is people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare it's hard not to be proud or feel like, wow. Yeah. Somehow I've been lucky. I've arrived at the right time, in the right place with the right people to be able to deliver on that. That's that's also exciting on our side of the equation. >>Yeah. It's critical infrastructure, critical, critical operations. >>Yeah. >>Yeah. Great stuff, Evan. Thanks for coming on. Appreciate this segment. All right. In a moment, Brian Gilmore director of IOT and emerging technology that influx day will join me. You're watching the cube leader in tech coverage. Thanks for watching >>Time series data from sensors systems and applications is a key source in driving automation and prediction in technologies around the world. But managing the massive amount of timestamp data generated these days is overwhelming, especially at scale. That's why influx data developed influx DB, a time series data platform that collects stores and analyzes data influx DB empowers developers to extract valuable insights and turn them into action by building transformative IOT analytics and cloud native applications, purpose built and optimized to handle the scale and velocity of timestamped data. InfluxDB puts the power in your hands with developer tools that make it easy to get started quickly with less code InfluxDB is more than a database. It's a robust developer platform with integrated tooling. That's written in the languages you love. So you can innovate faster, run in flex DB anywhere you want by choosing the provider and region that best fits your needs across AWS, Microsoft Azure and Google cloud flex DB is fast and automatically scalable. So you can spend time delivering value to customers, not managing clusters, take control of your time series data. So you can focus on the features and functionalities that give your applications a competitive edge. Get started for free with influx DB, visit influx data.com/cloud to learn more. >>Okay. Now we're joined by Brian Gilmore director of IOT and emerging technologies at influx data. Welcome to the show. >>Thank you, John. Great to be here. >>We just spent some time with Evan going through the company and the value proposition, um, with influx DV, what's the momentum, where do you see this coming from? What's the value coming out of this? >>Well, I think it, we're sort of hitting a point where the technology is, is like the adoption of it is becoming mainstream. We're seeing it in all sorts of organizations, everybody from like the most well funded sort of advanced big technology companies to the smaller academics, the startups and the managing of that sort of data that emits from that technology is time series and us being able to give them a, a platform, a tool that's super easy to use, easy to start. And then of course will grow with them is, is been key to us. Sort of, you know, riding along with them is they're successful. >>Evan was mentioning that time series has been on everyone's radar and that's in the OT business for years. Now, you go back since 20 13, 14, even like five years ago that convergence of physical and digital coming together, IP enabled edge. Yeah. Edge has always been kind of hyped up, but why now? Why, why is the edge so hot right now from an adoption standpoint? Is it because it's just evolution, the tech getting better? >>I think it's, it's, it's twofold. I think that, you know, there was, I would think for some people, everybody was so focused on cloud over the last probably 10 years. Mm-hmm <affirmative> that they forgot about the compute that was available at the edge. And I think, you know, those, especially in the OT and on the factory floor who weren't able to take Avan full advantage of cloud through their applications, you know, still needed to be able to leverage that compute at the edge. I think the big thing that we're seeing now, which is interesting is, is that there's like a hybrid nature to all of these applications where there's definitely some data that's generated on the edge. There's definitely done some data that's generated in the cloud. And it's the ability for a developer to sort of like tie those two systems together and work with that data in a very unified uniform way. Um, that's giving them the opportunity to build solutions that, you know, really deliver value to whatever it is they're trying to do, whether it's, you know, the, the out reaches of outer space or whether it's optimizing the factory floor. >>Yeah. I think, I think one of the things you also mentions genome too, dig big data is coming to the real world. And I think I, OT has been kind of like this thing for OT and, and in some use case, but now with the, with the cloud, all companies have an edge strategy now. So yeah, what's the secret sauce because now this is hot, hot product for the whole world and not just industrial, but all businesses. What's the secret sauce. >>Well, I mean, I think part of it is just that the technology is becoming more capable and that's especially on the hardware side, right? I mean, like technology compute is getting smaller and smaller and smaller. And we find that by supporting all the way down to the edge, even to the micro controller layer with our, um, you know, our client libraries and then working hard to make our applications, especially the database as small as possible so that it can be located as close to sort of the point of origin of that data in the edge as possible is, is, is fantastic. Now you can take that. You can run that locally. You can do your local decision making. You can use influx DB as sort of an input to automation control the autonomy that people are trying to drive at the edge. But when you link it up with everything that's in the cloud, that's when you get all of the sort of cloud scale capabilities of parallelized, AI and machine learning and all of that. >>So what's interesting is the open source success has been something that we've talked about a lot in the cube about how people are leveraging that you guys have users in the enterprise users that IOT market mm-hmm <affirmative>, but you got developers now. Yeah. Kind of together brought that up. How do you see that emerging? How do developers engage? What are some of the things you're seeing that developers are really getting into with InfluxDB >>What's? Yeah. Well, I mean, I think there are the developers who are building companies, right? And these are the startups and the folks that we love to work with who are building new, you know, new services, new products, things like that. And, you know, especially on the consumer side of IOT, there's a lot of that, just those developers. But I think we, you gotta pay attention to those enterprise developers as well, right? There are tons of people with the, the title of engineer in, in your regular enterprise organizations. And they're there for systems integration. They're there for, you know, looking at what they would build versus what they would buy. And a lot of them come from, you know, a strong, open source background and they, they know the communities, they know the top platforms in those spaces and, and, you know, they're excited to be able to adopt and use, you know, to optimize inside the business as compared to just building a brand new one. >>You know, it's interesting too, when Evan and I were talking about open source versus closed OT systems, mm-hmm <affirmative> so how do you support the backwards compatibility of older systems while maintaining open dozens of data formats out there? Bunch of standards, protocols, new things are emerging. Everyone wants to have a control plane. Everyone wants to leverage the value of data. How do you guys keep track of it all? What do you guys support? >>Yeah, well, I mean, I think either through direct connection, like we have a product called Telegraph, it's unbelievable. It's open source, it's an edge agent. You can run it as close to the edge as you'd like, it speaks dozens of different protocols in its own, right? A couple of which MQTT B, C U a are very, very, um, applicable to these T use cases. But then we also, because we are sort of not only open source, but open in terms of our ability to collect data, we have a lot of partners who have built really great integrations from their own middleware, into influx DB. These are companies like ke wear and high bite who are really experts in those downstream industrial protocols. I mean, that's a business, not everybody wants to be in. It requires some very specialized, very hard work and a lot of support, um, you know, and so by making those connections and building those ecosystems, we get the best of both worlds. The customers can use the platforms they need up to the point where they would be putting into our database. >>What's some of customer testimonies that they, that share with you. Can you share some anecdotal kind of like, wow, that's the best thing I've ever used. This really changed my business, or this is a great tech that's helped me in these other areas. What are some of the, um, soundbites you hear from customers when they're successful? >>Yeah. I mean, I think it ranges. You've got customers who are, you know, just finally being able to do the monitoring of assets, you know, sort of at the edge in the field, we have a customer who's who's has these tunnel boring machines that go deep into the earth to like drill tunnels for, for, you know, cars and, and, you know, trains and things like that. You know, they are just excited to be able to stick a database onto those tunnel, boring machines, send them into the depths of the earth and know that when they come out, all of that telemetry at a very high frequency has been like safely stored. And then it can just very quickly and instantly connect up to their, you know, centralized database. So like just having that visibility is brand new to them. And that's super important. On the other hand, we have customers who are way far beyond the monitoring use case, where they're actually using the historical records in the time series database to, um, like I think Evan mentioned like forecast things. So for predictive maintenance, being able to pull in the telemetry from the machines, but then also all of that external enrichment data, the metadata, the temperatures, the pressure is who is operating the machine, those types of things, and being able to easily integrate with platforms like Jupyter notebooks or, you know, all of those scientific computing and machine learning libraries to be able to build the models, train the models, and then they can send that information back down to InfluxDB to apply it and detect those anomalies, which >>Are, I think that's gonna be an, an area. I personally think that's a hot area because I think if you look at AI right now, yeah. It's all about training the machine learning albums after the fact. So time series becomes hugely important. Yeah. Cause now you're thinking, okay, the data matters post time. Yeah. First time. And then it gets updated the new time. Yeah. So it's like constant data cleansing data iteration, data programming. We're starting to see this new use case emerge in the data field. >>Yep. Yeah. I mean, I think you agree. Yeah, of course. Yeah. The, the ability to sort of handle those pipelines of data smartly, um, intelligently, and then to be able to do all of the things you need to do with that data in stream, um, before it hits your sort of central repository. And, and we make that really easy for customers like Telegraph, not only does it have sort of the inputs to connect up to all of those protocols and the ability to capture and connect up to the, to the partner data. But also it has a whole bunch of capabilities around being able to process that data, enrich it, reform at it, route it, do whatever you need. So at that point you're basically able to, you're playing your data in exactly the way you would wanna do it. You're routing it to different, you know, destinations and, and it's, it's, it's not something that really has been in the realm of possibility until this point. Yeah. Yeah. >>And when Evan was on it's great. He was a CEO. So he sees the big picture with customers. He was, he kinda put the package together that said, Hey, we got a system. We got customers, people are wanting to leverage our product. What's your PO they're sell. He's selling too as well. So you have that whole CEO perspective, but he brought up this notion that there's multiple personas involved in kind of the influx DB system architect. You got developers and users. Can you talk about that? Reality as customers start to commercialize and operationalize this from a commercial standpoint, you got a relationship to the cloud. Yep. The edge is there. Yep. The edge is getting super important, but cloud brings a lot of scale to the table. So what is the relationship to the cloud? Can you share your thoughts on edge and its relationship to the cloud? >>Yeah. I mean, I think edge, you know, edges, you can think of it really as like the local information, right? So it's, it's generally like compartmentalized to a point of like, you know, a single asset or a single factory align, whatever. Um, but what people do who wanna pro they wanna be able to make the decisions there at the edge locally, um, quickly minus the latency of sort of taking that large volume of data, shipping it to the cloud and doing something with it there. So we allow them to do exactly that. Then what they can do is they can actually downsample that data or they can, you know, detect like the really important metrics or the anomalies. And then they can ship that to a central database in the cloud where they can do all sorts of really interesting things with it. Like you can get that centralized view of all of your global assets. You can start to compare asset to asset, and then you can do those things like we talked about, whereas you can do predictive types of analytics or, you know, larger scale anomaly detections. >>So in this model you have a lot of commercial operations, industrial equipment. Yep. The physical plant, physical business with virtual data cloud all coming together. What's the future for InfluxDB from a tech standpoint. Cause you got open. Yep. There's an ecosystem there. Yep. You have customers who want operational reliability for sure. I mean, so you got organic <laugh> >>Yeah. Yeah. I mean, I think, you know, again, we got iPhones when everybody's waiting for flying cars. Right. So I don't know. We can like absolutely perfectly predict what's coming, but I think there are some givens and I think those givens are gonna be that the world is only gonna become more hybrid. Right. And then, you know, so we are going to have much more widely distributed, you know, situations where you have data being generated in the cloud, you have data gen being generated at the edge and then there's gonna be data generated sort sort of at all points in between like physical locations as well as things that are, that are very virtual. And I think, you know, we are, we're building some technology right now. That's going to allow, um, the concept of a database to be much more fluid and flexible, sort of more aligned with what a file would be like. >>And so being able to move data to the compute for analysis or move the compute to the data for analysis, those are the types of, of solutions that we'll be bringing to the customers sort of over the next little bit. Um, but I also think we have to start thinking about like what happens when the edge is actually off the planet. Right. I mean, we've got customers, you're gonna talk to two of them, uh, in the panel who are actually working with data that comes from like outside the earth, like, you know, either in low earth orbit or you know, all the way sort of on the other side of the universe. Yeah. And, and to be able to process data like that and to do so in a way it's it's we gotta, we gotta build the fundamentals for that right now on the factory floor and in the mines and in the tunnels. Um, so that we'll be ready for that one. >>I think you bring up a good point there because one of the things that's common in the industry right now, people are talking about, this is kind of new thinking is hyper scale's always been built up full stack developers, even the old OT world, Evan was pointing out that they built everything right. And the world's going to more assembly with core competency and IP and also property being the core of their apple. So faster assembly and building, but also integration. You got all this new stuff happening. Yeah. And that's to separate out the data complexity from the app. Yes. So space genome. Yep. Driving cars throws off massive data. >>It >>Does. So is Tesla, uh, is the car the same as the data layer? >>I mean the, yeah, it's, it's certainly a point of origin. I think the thing that we wanna do is we wanna let the developers work on the world, changing problems, the things that they're trying to solve, whether it's, you know, energy or, you know, any of the other health or, you know, other challenges that these teams are, are building against. And we'll worry about that time series data and the underlying data platform so that they don't have to. Right. I mean, I think you talked about it, uh, you know, for them just to be able to adopt the platform quickly, integrate it with their data sources and the other pieces of their applications. It's going to allow them to bring much faster time to market on these products. It's gonna allow them to be more iterative. They're gonna be able to do more sort of testing and things like that. And ultimately it will, it'll accelerate the adoption and the creation of >>Technology. You mentioned earlier in, in our talk about unification of data. Yeah. How about APIs? Cuz developers love APIs in the cloud unifying APIs. How do you view view that? >>Yeah, I mean, we are APIs, that's the product itself. Like everything, people like to think of it as sort of having this nice front end, but the front end is B built on our public APIs. Um, you know, and it, it allows the developer to build all of those hooks for not only data creation, but then data processing, data analytics, and then, you know, sort of data extraction to bring it to other platforms or other applications, microservices, whatever it might be. So, I mean, it is a world of APIs right now and you know, we, we bring a very sort of useful set of them for managing the time series data. These guys are all challenged with. It's >>Interesting. You and I were talking before we came on camera about how, um, data is, feels gonna have this kind of SRE role that DevOps had site reliability engineers, which manages a bunch of servers. There's so much data out there now. Yeah. >>Yeah. It's like reigning data for sure. And I think like that ability to be like one of the best jobs on the planet is gonna be to be able to like, sort of be that data Wrangler to be able to understand like what the data sources are, what the data formats are, how to be able to efficiently move that data from point a to point B and you know, to process it correctly so that the end users of that data aren't doing any of that sort of hard upfront preparation collection storage's >>Work. Yeah. That's data as code. I mean, data engineering is it is becoming a new discipline for sure. And, and the democratization is the benefit. Yeah. To everyone, data science get easier. I mean data science, but they wanna make it easy. Right. <laugh> yeah. They wanna do the analysis, >>Right? Yeah. I mean, I think, you know, it, it's a really good point. I think like we try to give our users as many ways as there could be possible to get data in and get data out. We sort of think about it as meeting them where they are. Right. So like we build, we have the sort of client libraries that allow them to just port to us, you know, directly from the applications and the languages that they're writing, but then they can also pull it out. And at that point nobody's gonna know the users, the end consumers of that data, better than those people who are building those applications. And so they're building these user interfaces, which are making all of that data accessible for, you know, their end users inside their organization. >>Well, Brian, great segment, great insight. Thanks for sharing all, all the complexities and, and IOT that you guys helped take away with the APIs and, and assembly and, and all the system architectures that are changing edge is real cloud is real. Yeah, absolutely. Mainstream enterprises. And you got developer attraction too, so congratulations. >>Yeah. It's >>Great. Well, thank any, any last word you wanna share >>Deal with? No, just, I mean, please, you know, if you're, if you're gonna, if you're gonna check out influx TV, download it, try out the open source contribute if you can. That's a, that's a huge thing. It's part of being the open source community. Um, you know, but definitely just, just use it. I think when once people use it, they try it out. They'll understand very, >>Very quickly. So open source with developers, enterprise and edge coming together all together. You're gonna hear more about that in the next segment, too. Right. Thanks for coming on. Okay. Thanks. When we return, Dave LAN will lead a panel on edge and data influx DB. You're watching the cube, the leader in high tech enterprise coverage. >>Why the startup, we move really fast. We find that in flex DB can move as fast as us. It's just a great group, very collaborative, very interested in manufacturing. And we see a bright future in working with influence. My name is Aaron Seley. I'm the CTO at HBI. Highlight's one of the first companies to focus on manufacturing data and apply the concepts of data ops, treat that as an asset to deliver to the it system, to enable applications like overall equipment effectiveness that can help the factory produce better, smarter, faster time series data. And manufacturing's really important. If you take a piece of equipment, you have the temperature pressure at the moment that you can look at to kind of see the state of what's going on. So without that context and understanding you can't do what manufacturers ultimately want to do, which is predict the future. >>Influx DB represents kind of a new way to storm time series data with some more advanced technology and more importantly, more open technologies. The other thing that influx does really well is once the data's influx, it's very easy to get out, right? They have a modern rest API and other ways to access the data. That would be much more difficult to do integrations with classic historians highlight can serve to model data, aggregate data on the shop floor from a multitude of sources, whether that be P C U a servers, manufacturing execution systems, E R P et cetera, and then push that seamlessly into influx to then be able to run calculations. Manufacturing is changing this industrial 4.0, and what we're seeing is influx being part of that equation. Being used to store data off the unified name space, we recommend InfluxDB all the time to customers that are exploring a new way to share data manufacturing called the unified name space who have open questions around how do I share this new data that's coming through my UNS or my QTT broker? How do I store this and be able to query it over time? And we often point to influx as a solution for that is a great brand. It's a great group of people and it's a great technology. >>Okay. We're now going to go into the customer panel and we'd like to welcome Angelo Fasi. Who's a software engineer at the Vera C Ruben observatory in Caleb McLaughlin whose senior spacecraft operations software engineer at loft orbital guys. Thanks for joining us. You don't wanna miss folks this interview, Caleb, let's start with you. You work for an extremely cool company. You're launching satellites into space. I mean, there, of course doing that is, is highly complex and not a cheap endeavor. Tell us about loft Orbi and what you guys do to attack that problem. >>Yeah, absolutely. And, uh, thanks for having me here by the way. Uh, so loft orbital is a, uh, company. That's a series B startup now, uh, who and our mission basically is to provide, uh, rapid access to space for all kinds of customers. Uh, historically if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, you know, have a big software teams, uh, and then eventually worry about, you know, a bunch like just a lot of very specialized engineering. And what we're trying to do is change that from a super specialized problem that has an extremely high barrier of access to a infrastructure problem. So that it's almost as simple as, you know, deploying a VM in, uh, AWS or GCP is getting your, uh, programs, your mission deployed on orbit, uh, with access to, you know, different sensors, uh, cameras, radios, stuff like that. >>So that's, that's kind of our mission. And just to give a really brief example of the kind of customer that we can serve. Uh, there's a really cool company called, uh, totem labs who is working on building, uh, IOT cons, an IOT constellation for in of things, basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor T, which means you have this little modem inside a container container that you, that you track from anywhere in the world as it's going across the ocean. Um, so they're, it's really little and they've been able to stay a small startup that's focused on their product, which is the, uh, that super crazy complicated, cool radio while we handle the whole space segment for them, which just, you know, before loft was really impossible. So that's, our mission is, uh, providing space infrastructure as a service. We are kind of groundbreaking in this area and we're serving, you know, a huge variety of customers with all kinds of different missions, um, and obviously generating a ton of data in space, uh, that we've gotta handle. Yeah. >>So amazing Caleb, what you guys do, I, now I know you were lured to the skies very early in your career, but how did you kinda land on this business? >>Yeah, so, you know, I've, I guess just a little bit about me for some people, you know, they don't necessarily know what they wanna do like early in their life. For me, I was five years old and I knew, you know, I want to be in the space industry. So, you know, I started in the air force, but have, uh, stayed in the space industry, my whole career and been a part of, uh, this is the fifth space startup that I've been a part of actually. So, you know, I've, I've, uh, kind of started out in satellites, did spent some time in working in, uh, the launch industry on rockets. Then, uh, now I'm here back in satellites and you know, honestly, this is the most exciting of the difference based startups. That I've been a part of >>Super interesting. Okay. Angelo, let's, let's talk about the Ruben observatory, ver C Ruben, famous woman scientist, you know, galaxy guru. Now you guys the observatory, you're up way up high. You're gonna get a good look at the Southern sky. Now I know COVID slowed you guys down a bit, but no doubt. You continued to code away on the software. I know you're getting close. You gotta be super excited. Give us the update on, on the observatory and your role. >>All right. So yeah, Rubin is a state of the art observatory that, uh, is in construction on a remote mountain in Chile. And, um, with Rubin, we conduct the, uh, large survey of space and time we are going to observe the sky with, uh, eight meter optical telescope and take, uh, a thousand pictures every night with a 3.2 gig up peaks of camera. And we are going to do that for 10 years, which is the duration of the survey. >>Yeah. Amazing project. Now you, you were a doctor of philosophy, so you probably spent some time thinking about what's out there and then you went out to earn a PhD in astronomy, in astrophysics. So this is something that you've been working on for the better part of your career, isn't it? >>Yeah, that's that's right. Uh, about 15 years, um, I studied physics in college, then I, um, got a PhD in astronomy and, uh, I worked for about five years in another project. Um, the dark energy survey before joining rubing in 2015. >>Yeah. Impressive. So it seems like you both, you know, your organizations are looking at space from two different angles. One thing you guys both have in common of course is, is, is software. And you both use InfluxDB as part of your, your data infrastructure. How did you discover influx DB get into it? How do you use the platform? Maybe Caleb, you could start. >>Uh, yeah, absolutely. So the first company that I extensively used, uh, influx DBN was a launch startup called, uh, Astra. And we were in the process of, uh, designing our, you know, our first generation rocket there and testing the engines, pumps, everything that goes into a rocket. Uh, and when I joined the company, our data story was not, uh, very mature. We were collecting a bunch of data in LabVIEW and engineers were taking that over to MATLAB to process it. Um, and at first there, you know, that's the way that a lot of engineers and scientists are used to working. Um, and at first that was, uh, like people weren't entirely sure that that was a, um, that that needed to change, but it's something the nice thing about InfluxDB is that, you know, it's so easy to deploy. So as the, our software engineering team was able to get it deployed and, you know, up and running very quickly and then quickly also backport all of the data that we collected thus far into influx and what, uh, was amazing to see. >>And as kind of the, the super cool moment with influx is, um, when we hooked that up to Grafana Grafana as the visualization platform we used with influx, cuz it works really well with it. Uh, there was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data where they could just almost instantly easily discover data that they hadn't been able to see before and take the manual processes that they would run after a test and just throw those all in influx and have live data as tests were coming. And, you know, I saw them implementing like crazy rocket equation type stuff in influx, and it just was totally game changing for how we tested. >>So Angelo, I was explaining in my open, you know, you could, you could add a column in a traditional RDBMS and do time series, but with the volume of data that you're talking about, and the example of the Caleb just gave you, I mean, you have to have a purpose built time series database, where did you first learn about influx DB? >>Yeah, correct. So I work with the data management team, uh, and my first project was the record metrics that measured the performance of our software, uh, the software that we used to process the data. So I started implementing that in a relational database. Um, but then I realized that in fact, I was dealing with time series data and I should really use a solution built for that. And then I started looking at time series databases and I found influx B. And that was, uh, back in 2018. The another use for influx DB that I'm also interested is the visits database. Um, if you think about the observations we are moving the telescope all the time in pointing to specific directions, uh, in the Skype and taking pictures every 30 seconds. So that itself is a time series. And every point in that time series, uh, we call a visit. So we want to record the metadata about those visits and flex to, uh, that time here is going to be 10 years long, um, with about, uh, 1000 points every night. It's actually not too much data compared to other, other problems. It's, uh, really just a different, uh, time scale. >>The telescope at the Ruben observatory is like pun intended, I guess the star of the show. And I, I believe I read that it's gonna be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hub's widest camera view, which is amazing, right? That's like 40 moons in, in an image amazingly fast as well. What else can you tell us about the telescope? >>Um, this telescope, it has to move really fast and it also has to carry, uh, the primary mirror, which is an eight meter piece of glass. It's very heavy and it has to carry a camera, which has about the size of a small car. And this whole structure weighs about 300 tons for that to work. Uh, the telescope needs to be, uh, very compact and stiff. Uh, and one thing that's amazing about it's design is that the telescope, um, is 300 tons structure. It sits on a tiny film of oil, which has the diameter of, uh, human hair. And that makes an almost zero friction interface. In fact, a few people can move these enormous structure with only their hands. Uh, as you said, uh, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So each image has, uh, in diameter the size of about seven full moons. And, uh, with that, we can map the entire sky in only, uh, three days. And of course doing operations everything's, uh, controlled by software and it is automatic. Um there's a very complex piece of software, uh, called the scheduler, which is responsible for moving the telescope, um, and the camera, which is, uh, recording 15 terabytes of data every night. >>Hmm. And, and, and Angela, all this data lands in influx DB. Correct. And what are you doing with, with all that data? >>Yeah, actually not. Um, so we are using flex DB to record engineering data and metadata about the observations like telemetry events and commands from the telescope. That's a much smaller data set compared to the images, but it is still challenging because, uh, you, you have some high frequency data, uh, that the system needs to keep up and we need to, to start this data and have it around for the lifetime of the price. Mm, >>Got it. Thank you. Okay, Caleb, let's bring you back in and can tell us more about the, you got these dishwasher size satellites. You're kind of using a multi-tenant model. I think it's genius, but, but tell us about the satellites themselves. >>Yeah, absolutely. So, uh, we have in space, some satellites already that as you said, are like dishwasher, mini fridge kind of size. Um, and we're working on a bunch more that are, you know, a variety of sizes from shoebox to, I guess, a few times larger than what we have today. Uh, and it is, we do shoot to have effectively something like a multi-tenant model where, uh, we will buy a bus off the shelf. The bus is, uh, what you can kind of think of as the core piece of the satellite, almost like a motherboard or something where it's providing the power. It has the solar panels, it has some radios attached to it. Uh, it handles the attitude control, basically steers the spacecraft in orbit. And then we build also in house, what we call our payload hub, which is, has all, any customer payloads attached and our own kind of edge processing sort of capabilities built into it. >>And, uh, so we integrate that. We launch it, uh, and those things, because they're in lower orbit, they're orbiting the earth every 90 minutes. That's, you know, seven kilometers per second, which is several times faster than a speeding bullet. So we've got, we have, uh, one of the unique challenges of operating spacecraft and lower orbit is that generally you can't talk to them all the time. So we're managing these things through very brief windows of time, uh, where we get to talk to them through our ground sites, either in Antarctica or, you know, in the north pole region. >>Talk more about how you use influx DB to make sense of this data through all this tech that you're launching into space. >>We basically previously we started off when I joined the company, storing all of that as Angelo did in a regular relational database. And we found that it was, uh, so slow in the size of our data would balloon over the course of a couple days to the point where we weren't able to even store all of the data that we were getting. Uh, so we migrated to influx DB to store our time series telemetry from the spacecraft. So, you know, that's things like, uh, power level voltage, um, currents counts, whatever, whatever metadata we need to monitor about the spacecraft. We now store that in, uh, in influx DB. Uh, and that has, you know, now we can actually easily store the entire volume of data for the mission life so far without having to worry about, you know, the size bloating to an unmanageable amount. >>And we can also seamlessly query, uh, large chunks of data. Like if I need to see, you know, for example, as an operator, I might wanna see how my, uh, battery state of charge is evolving over the course of the year. I can have a plot and an influx that loads that in a fraction of a second for a year's worth of data, because it does, you know, intelligent, um, I can intelligently group the data by, uh, sliding time interval. Uh, so, you know, it's been extremely powerful for us to access the data and, you know, as time has gone on, we've gradually migrated more and more of our operating data into influx. >>You know, let's, let's talk a little bit, uh, uh, but we throw this term around a lot of, you know, data driven, a lot of companies say, oh, yes, we're data driven, but you guys really are. I mean, you' got data at the core, Caleb, what does that, what does that mean to you? >>Yeah, so, you know, I think the, and the clearest example of when I saw this be like totally game changing is what I mentioned before at Astro where our engineer's feedback loop went from, you know, a lot of kind of slow researching, digging into the data to like an instant instantaneous, almost seeing the data, making decisions based on it immediately, rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. Um, but to give another practical example, uh, as I said, we have a huge amount of data that comes down every orbit, and we need to be able to ingest all of that data almost instantaneously and provide it to the operator. And near real time, you know, about a second worth of latency is all that's acceptable for us to react to, to see what is coming down from the spacecraft and building that pipeline is challenging from a software engineering standpoint. >>Um, our primary language is Python, which isn't necessarily that fast. So what we've done is started, you know, in the, in the goal of being data driven is publish metrics on individual, uh, how individual pieces of our data processing pipeline are performing into influx as well. And we do that in production as well as in dev. Uh, so we have kind of a production monitoring, uh, flow. And what that has done is allow us to make intelligent decisions on our software development roadmap, where it makes the most sense for us to, uh, focus our development efforts in terms of improving our software efficiency. Uh, just because we have that visibility into where the real problems are. Um, it's sometimes we've found ourselves before we started doing this kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. Uh, but now, now that we're being a bit more data driven, there we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scale to, from supporting a couple satellites, to supporting many, many satellites at >>Once. Yeah. Coach. So you reduced those dead ends, maybe Angela, you could talk about what, what sort of data driven means to, to you and your teams? >>I would say that, um, having, uh, real time visibility, uh, to the telemetry data and, and metrics is, is, is crucial for us. We, we need, we need to make sure that the image that we collect with the telescope, uh, have good quality and, um, that they are within the specifications, uh, to meet our science goals. And so if they are not, uh, we want to know that as soon as possible and then, uh, start fixing problems. >>Caleb, what are your sort of event, you know, intervals like? >>So I would say that, you know, as of today on the spacecraft, the event, the, the level of timing that we deal with probably tops out at about, uh, 20 Hertz, 20 measurements per second on, uh, things like our, uh, gyroscopes, but the, you know, I think the, the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications. And I'll give an example, uh, from when I worked at, on the rocket at Astra there, our baseline data rate that we would ingest data during a test is, uh, 500 Hertz. So 500 samples per second. And in some cases we would actually, uh, need to ingest much higher rate data, even up to like 1.5 kilohertz. So, uh, extremely, extremely high precision, uh, data there where timing really matters a lot. And, uh, you know, I can, one of the really powerful things about influx is the fact that it can handle this. >>That's one of the reasons we chose it, uh, because there's times when we're looking at the results of a firing where you're zooming in, you know, I talked earlier about how on my current job, we often zoom out to look, look at a year's worth of data. You're zooming in to where your screen is preoccupied by a tiny fraction of a second. And you need to see same thing as Angela just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers. So that can be something like, Hey, I opened this valve at exactly this time and that goes, we wanna have that at, you know, micro or even nanosecond precision so that we know, okay, we saw a spike in chamber pressure at, you know, at this exact moment, was that before or after this valve open, those kind of, uh, that kind of visibility is critical in these kind of scientific, uh, applications and absolutely game changing to be able to see that in, uh, near real time and, uh, with a really easy way for engineers to be able to visualize this data themselves without having to wait for, uh, software engineers to go build it for them. >>Can the scientists do self-serve or are you, do you have to design and build all the analytics and, and queries for your >>Scientists? Well, I think that's, that's absolutely from, from my perspective, that's absolutely one of the best things about influx and what I've seen be game changing is that, uh, generally I'd say anyone can learn to use influx. Um, and honestly, most of our users might not even know they're using influx, um, because what this, the interface that we expose to them is Grafana, which is, um, a generic graphing, uh, open source graphing library that is very similar to influx own chronograph. Sure. And what it does is, uh, let it provides this, uh, almost it's a very intuitive UI for building your queries. So you choose a measurement and it shows a dropdown of available measurements. And then you choose a particular, the particular field you wanna look at. And again, that's a dropdown, so it's really easy for our users to discover. And there's kind of point and click options for doing math aggregations. You can even do like perfect kind of predictions all within Grafana, the Grafana user interface, which is really just a wrapper around the APIs and functionality of the influx provides putting >>Data in the hands of those, you know, who have the context of domain experts is, is key. Angela, is it the same situation for you? Is it self serve? >>Yeah, correct. Uh, as I mentioned before, um, we have the astronomers making their own dashboards because they know what exactly what they, they need to, to visualize. Yeah. I mean, it's all about using the right tool for the job. I think, uh, for us, when I joined the company, we weren't using influx DB and we, we were dealing with serious issues of the database growing to an incredible size extremely quickly, and being unable to like even querying short periods of data was taking on the order of seconds, which is just not possible for operations >>Guys. This has been really formative it's, it's pretty exciting to see how the edge is mountaintops, lower orbits to be space is the ultimate edge. Isn't it. I wonder if you could answer two questions to, to wrap here, you know, what comes next for you guys? Uh, and is there something that you're really excited about that, that you're working on Caleb, maybe you could go first and an Angela, you can bring us home. >>Uh, basically what's next for loft. Orbital is more, more satellites, a greater push towards infrastructure and really making, you know, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, uh, making that happen, it's extremely exciting and extremely exciting time to be in this company and to be in this industry as a whole, because there are so many interesting applications out there. So many cool ways of leveraging space that, uh, people are taking advantage of. And with, uh, companies like SpaceX and the now rapidly lowering cost, cost of launch, it's just a really exciting place to be. And we're launching more satellites. We are scaling up for some constellations and our ground system has to be improved to match. So there's a lot of, uh, improvements that we're working on to really scale up our control software, to be best in class and, uh, make it capable of handling such a large workload. So >>You guys hiring >><laugh>, we are absolutely hiring. So, uh, I would in we're we need, we have PE positions all over the company. So, uh, we need software engineers. We need people who do more aerospace, specific stuff. So, uh, absolutely. I'd encourage anyone to check out the loft orbital website, if there's, if this is at all interesting. >>All right. Angela, bring us home. >>Yeah. So what's next for us is really, uh, getting this, um, telescope working and collecting data. And when that's happen is going to be just, um, the Lu of data coming out of this camera and handling all, uh, that data is going to be really challenging. Uh, yeah. I wanna wanna be here for that. <laugh> I'm looking forward, uh, like for next year we have like an important milestone, which is our, um, commissioning camera, which is a simplified version of the, of the full camera it's going to be on sky. And so yeah, most of the system has to be working by them. >>Nice. All right, guys, you know, with that, we're gonna end it. Thank you so much, really fascinating, and thanks to influx DB for making this possible, really groundbreaking stuff, enabling value creation at the edge, you know, in the cloud and of course, beyond at the space. So really transformational work that you guys are doing. So congratulations and really appreciate the broader community. I can't wait to see what comes next from having this entire ecosystem. Now, in a moment, I'll be back to wrap up. This is Dave ante, and you're watching the cube, the leader in high tech enterprise coverage. >>Welcome Telegraph is a popular open source data collection. Agent Telegraph collects data from hundreds of systems like IOT sensors, cloud deployments, and enterprise applications. It's used by everyone from individual developers and hobbyists to large corporate teams. The Telegraph project has a very welcoming and active open source community. Learn how to get involved by visiting the Telegraph GitHub page, whether you want to contribute code, improve documentation, participate in testing, or just show what you're doing with Telegraph. We'd love to hear what you're building. >>Thanks for watching. Moving the world with influx DB made possible by influx data. I hope you learn some things and are inspired to look deeper into where time series databases might fit into your environment. If you're dealing with large and or fast data volumes, and you wanna scale cost effectively with the highest performance and you're analyzing metrics and data over time times, series databases just might be a great fit for you. Try InfluxDB out. You can start with a free cloud account by clicking on the link and the resources below. Remember all these recordings are gonna be available on demand of the cube.net and influx data.com. So check those out and poke around influx data. They are the folks behind InfluxDB and one of the leaders in the space, we hope you enjoyed the program. This is Dave Valante for the cube. We'll see you soon.

(upbeat music) >> Okay, we're now going to go into the customer panel. And we'd like to welcome Angelo Fausti, who's software engineer at the Vera C Rubin Observatory, and Caleb Maclachlan, who's senior spacecraft operations software engineer at Loft Orbital. Guys, thanks for joining us. You don't want to miss folks, this interview. Caleb, let's start with you. You work for an extremely cool company. You're launching satellites into space. Cause doing that is highly complex and not a cheap endeavor. Tell us about Loft Orbital and what you guys do to attack that problem? >> Yeah, absolutely. And thanks for having me here, by the way. So Loft Orbital is a company that's a series B startup now. And our mission basically is to provide rapid access to space for all kinds of customers. Historically, if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, have big software teams, and then eventually worry about a lot of very specialized engineering. And what we're trying to do is, change that from a super specialized problem that has an extremely high barrier of access to a infrastructure problem. So that it's almost as simple as deploying a VM in AWS or GCP, as getting your programs, your mission deployed on orbit, with access to different sensors, cameras, radios, stuff like that. So that's kind of our mission. And just to give a really brief example of the kind of customer that we can serve. There's a really cool company called Totum labs, who is working on building an IoT constellation, for Internet of Things. Basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor IoT, which means you have this little modem inside a container. A container that you track from anywhere on the world as it's going across the ocean. So it's really little. And they've been able to stay small startup that's focused on their product, which is that super crazy, complicated, cool radio, while we handle the whole space segment for them, which just, before Loft was really impossible. So that's our mission is, providing space infrastructure as a service. We are kind of groundbreaking in this area, and we're serving a huge variety of customers with all kinds of different missions, and obviously, generating a ton of data in space that we've got to handle. >> Yeah, so amazing, Caleb, what you guys do. I know you were lured to the skies very early in your career, but how did you kind of land in this business? >> Yeah, so I guess just a little bit about me. For some people, they don't necessarily know what they want to do, early in their life. For me, I was five years old and I knew, I want to be in the space industry. So I started in the Air Force, but have stayed in the space industry my whole career and been a part of, this is the fifth space startup that I've been a part of, actually. So I've kind of started out in satellites, did spend some time in working in the launch industry on rockets. Now I'm here back in satellites. And honestly, this is the most exciting of the different space startups that I've been a part of. So, always been passionate about space and basically writing software for operating in space for basically extending how we write software into orbit. >> Super interesting. Okay, Angelo. Let's talk about the Rubin Observatory Vera C. Rubin, famous woman scientists, Galaxy guru, Now you guys, the observatory are up, way up high, you're going to get a good look at the southern sky. I know COVID slowed you guys down a bit. But no doubt you continue to code away on the software. I know you're getting close. You got to be super excited. Give us the update on the observatory and your role. >> All right. So yeah, Rubin is state of the art observatory that is in construction on a remote mountain in Chile. And with Rubin we'll conduct the large survey of space and time. We are going to observe the sky with eight meter optical telescope and take 1000 pictures every night with 3.2 gigapixel camera. And we're going to do that for 10 years, which is the duration of the survey. The goal is to produce an unprecedented data set. Which is going to be about .5 exabytes of image data. And from these images will detect and measure the properties of billions of astronomical objects. We are also building a science platform that's hosted on Google Cloud, so that the scientists and the public can explore this data to make discoveries. >> Yeah, amazing project. Now, you aren't a Doctor of Philosophy. So you probably spent some time thinking about what's out there. And then you went on to earn a PhD in astronomy and astrophysics. So this is something that you've been working on for the better part of your career, isn't it? >> Yeah, that's right. About 15 years. I studied physics in college, then I got a PhD in astronomy. And I worked for about five years in another project, the Dark Energy survey before joining Rubin in 2015. >> Yeah, impressive. So it seems like both your organizations are looking at space from two different angles. One thing you guys both have in common, of course, is software. And you both use InfluxDB as part of your data infrastructure. How did you discover InfluxDB, get into it? How do you use the platform? Maybe Caleb, you can start. >> Yeah, absolutely. So the first company that I extensively used InfluxDB in was a launch startup called Astra. And we were in the process of designing our first generation rocket there and testing the engines, pumps. Everything that goes into a rocket. And when I joined the company, our data story was not very mature. We were collecting a bunch of data in LabVIEW. And engineers were taking that over to MATLAB to process it. And at first, that's the way that a lot of engineers and scientists are used to working. And at first that was, like, people weren't entirely sure that, that needed to change. But it's something, the nice thing about InfluxDB is that, it's so easy to deploy. So our software engineering team was able to get it deployed and up and running very quickly and then quickly also backport all of the data that we've collected thus far into Influx. And what was amazing to see and it's kind of the super cool moment with Influx is, when we hooked that up to Grafana, Grafana, is the visualization platform we use with influx, because it works really well with it. There was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data, where they could just almost instantly, easily discover data that they hadn't been able to see before. And take the manual processes that they would run after a test and just throw those all in Influx and have live data as tests were coming. And I saw them implementing crazy rocket equation type stuff in Influx and it just was totally game changing for how we tested. And things that previously it would be like run a test, then wait an hour for the engineers to crunch the data and then we run another test with some changed parameters or a changed startup sequence or something like that, became, by the time the test is over, the engineers know what the next step is, because they have this just like instant game changing access to data. So since that experience, basically everywhere I've gone, every company since then, I've been promoting InfluxDB and using it and spinning it up and quickly showing people how simple and easy it is. >> Yeah, thank you. So Angelo, I was explaining in my open that, you know you could add a column in a traditional RDBMS and do time series. But with the volume of data that you're talking about in the example that Caleb just gave, you have to have a purpose built time series database. Where did you first learn about InfluxDB? >> Yeah, correct. So I worked with the data management team and my first project was the record metrics that measure the performance of our software. The software that we use to process the data. So I started implementing that in our relational database. But then I realized that in fact, I was dealing with time series data. And I should really use a solution built for that. And then I started looking at time series databases and I found InfluxDB, that was back in 2018. Then I got involved in another project. To record telemetry data from the telescope itself. It's very challenging because you have so many subsystems and sensors, producing data. And with that data, the goal is to look at the telescope harder in real time so we can make decisions and make sure that everything's doing the right thing. And another use for InfluxDB that I'm also interested, is the visits database. If you think about the observations, we are moving the telescope all the time and pointing to specific directions in the sky and taking pictures every 30 seconds. So that itself is a time series. And every point in the time series, we call that visit. So we want to record the metadata about those visits in InfluxDB. That time series is going to be 10 years long, with about 1000 points every night. It's actually not too much data compared to the other problems. It's really just the different time scale. So yeah, we have plans on continuing using InfluxDB and finding new applications in the project. >> Yeah and the speed with which you can actually get high quality images. Angelo, my understanding is, you use InfluxDB, as you said, you're monitoring the telescope hardware and the software. And just say, some of the scientific data as well. The telescope at the Rubin Observatory is like, no pun intended, I guess, the star of the show. And I believe, I read that it's going to be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hubble's widest camera view, which is amazing. That's like 40 moons in an image, and amazingly fast as well. What else can you tell us about the telescope? >> Yeah, so it's really a challenging project, from the point of view of engineering. This telescope, it has to move really fast. And it also has to carry the primary mirror, which is an eight meter piece of glass, it's very heavy. And it has to carry a camera, which is about the size of a small car. And this whole structure weighs about 300 pounds. For that to work, the telescope needs to be very compact and stiff. And one thing that's amazing about its design is that the telescope, this 300 tons structure, it sits on a tiny film of oil, which has the diameter of human hair, in that brings an almost zero friction interface. In fact, a few people can move this enormous structure with only their hands. As you said, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So each image has, in diameter, the size of about seven full moons. And with that we can map the entire sky in only three days. And of course, during operations, everything's controlled by software, and it's automatic. There's a very complex piece of software called the scheduler, which is responsible for moving the telescope and the camera. Which will record the 15 terabytes of data every night. >> And Angelo, all this data lands in InfluxDB, correct? And what are you doing with all that data? >> Yeah, actually not. So we're using InfluxDB to record engineering data and metadata about the observations, like telemetry events and the commands from the telescope. That's a much smaller data set compared to the images. But it is still challenging because you have some high frequency data that the system needs to keep up and we need to store this data and have it around for the lifetime of the project. >> Hm. So at the mountain, we keep the data for 30 days. So the observers, they use Influx and InfluxDB instance, running there to analyze the data. But we also replicate the data to another instance running at the US data facility, where we have more computational resources and so more people can look at the data without interfering with the observations. Yeah, I have to say that InfluxDB has been really instrumental for us, and especially at this phase of the project where we are testing and integrating the different pieces of hardware. And it's not just the database, right. It's the whole platform. So I like to give this example, when we are doing this kind of task, it's hard to know in advance which dashboards and visualizations you're going to need, right. So what you really need is a data exploration tool. And with tools like chronograph, for example, having the ability to query and create dashboards on the fly was really a game changer for us. So astronomers, they typically are not software engineers, but they are the ones that know better than anyone, what needs to be monitored. And so they use chronograph and they can create the dashboards and the visualizations that they need. >> Got it. Thank you. Okay, Caleb, let's bring you back in. Tell us more about, you got these dishwasher size satellites are kind of using a multi tenant model. I think it's genius. But tell us about the satellites themselves. >> Yeah, absolutely. So we have in space, some satellites already. That, as you said, are like dishwasher, mini fridge kind of size. And we're working on a bunch more that are a variety of sizes from shoe box to I guess, a few times larger than what we have today. And it is, we do shoot to have, effectively something like a multi tenant model where we will buy a bus off the shelf, the bus is, what you can kind of think of as the core piece of the satellite, almost like a motherboard or something. Where it's providing the power, it has the solar panels, it has some radios attached to it, it handles the altitude control, basically steers the spacecraft in orbit. And then we build, also in house, what we call our payload hub, which is has all any customer payloads attached, and our own kind of edge processing sort of capabilities built into it. And so we integrate that, we launch it, and those things, because they're in low Earth orbit, they're orbiting the Earth every 90 minutes. That's seven kilometers per second, which is several times faster than a speeding bullet. So we've got, we have one of the unique challenges of operating spacecraft in lower Earth orbit is that generally you can't talk to them all the time. So we're managing these things through very brief windows of time. Where we get to talk to them through our ground sites, either in Antarctica or in the North Pole region. So we'll see them for 10 minutes, and then we won't see them for the next 90 minutes as they zip around the Earth collecting data. So one of the challenges that exists for a company like ours is, that's a lot of, you have to be able to make real time decisions operationally, in those short windows that can sometimes be critical to the health and safety of the spacecraft. And it could be possible that we put ourselves into a low power state in the previous orbit or something potentially dangerous to the satellite can occur. And so as an operator, you need to very quickly process that data coming in. And not just the the live data, but also the massive amounts of data that were collected in, what we call the back orbit, which is the time that we couldn't see the spacecraft. >> We got it. So talk more about how you use InfluxDB to make sense of this data from all those tech that you're launching into space. >> Yeah, so we basically, previously we started off, when I joined the company, storing all of that, as Angelo did, in a regular relational database. And we found that it was so slow, and the size of our data would balloon over the course of a couple of days to the point where we weren't able to even store all of the data that we were getting. So we migrated to InfluxDB to store our time series telemetry from the spacecraft. So that thing's like power level voltage, currents counts, whatever metadata we need to monitor about the spacecraft, we now store that in InfluxDB. And that has, you know, now we can actually easily store the entire volume of data for the mission life so far, without having to worry about the size bloating to an unmanageable amount. And we can also seamlessly query large chunks of data, like if I need to see, for example, as an operator, I might want to see how my battery state of charge is evolving over the course of the year, I can have a plot in an Influx that loads that in a fraction of a second for a year's worth of data, because it does, you know, intelligent. I can intelligently group the data by citing time interval. So it's been extremely powerful for us to access the data. And as time has gone on, we've gradually migrated more and more of our operating data into Influx. So not only do we store the basic telemetry about the bus and our payload hub, but we're also storing data for our customers, that our customers are generating on board about things like you know, one example of a customer that's doing something pretty cool. They have a computer on our satellite, which they can reprogram themselves to do some AI enabled edge compute type capability in space. And so they're sending us some metrics about the status of their workloads, in addition to the basics, like the temperature of their payload, their computer or whatever else. And we're delivering that data to them through Influx in a Grafana dashboard that they can plot where they can see, not only has this pipeline succeeded or failed, but also where was the spacecraft when this occurred? What was the voltage being supplied to their payload? Whatever they need to see, it's all right there for them. Because we're aggregating all that data in InfluxDB. >> That's awesome. You're measuring everything. Let's talk a little bit about, we throw this term around a lot, data driven. A lot of companies say, Oh, yes, we're data driven. But you guys really are. I mean, you got data at the core. Caleb, what does that what does that mean to you? >> Yeah, so you know, I think, the clearest example of when I saw this, be like totally game changing is, what I mentioned before it, at Astra, were our engineers feedback loop went from a lot of, kind of slow researching, digging into the data to like an instant, instantaneous, almost, Seeing the data, making decisions based on it immediately, rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. But to give another practical example, as I said, we have a huge amount of data that comes down every orbit, and we need to be able to ingest all that data almost instantaneously and provide it to the operator in near real time. About a second worth of latency is all that's acceptable for us to react to. To see what is coming down from the spacecraft and building that pipeline is challenging, from a software engineering standpoint. Our primary language is Python, which isn't necessarily that fast. So what we've done is started, in the in the goal being data driven, is publish metrics on individual, how individual pieces of our data processing pipeline, are performing into Influx as well. And we do that in production as well as in dev. So we have kind of a production monitoring flow. And what that has done is, allow us to make intelligent decisions on our software development roadmap. Where it makes the most sense for us to focus our development efforts in terms of improving our software efficiency, just because we have that visibility into where the real problems are. At sometimes we've found ourselves, before we started doing this, kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. But now, that we're being a bit more data driven, there, we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scaled from supporting a couple of satellites to supporting many, many satellites at once. >> So you reduce those dead ends. Maybe Angela, you could talk about what sort of data driven means to you and your team? >> Yeah, I would say that having real time visibility, to the telemetry data and metrics is crucial for us. We need to make sure that the images that we collect, with the telescope have good quality and that they are within the specifications to meet our science goals. And so if they are not, we want to know that as soon as possible, and then start fixing problems. >> Yeah, so I mean, you think about these big science use cases, Angelo. They are extremely high precision, you have to have a lot of granularity, very tight tolerances. How does that play into your time series data strategy? >> Yeah, so one of the subsystems that produce the high volume and high rates is the structure that supports the telescope's primary mirror. So on that structure, we have hundreds of actuators that compensate the shape of the mirror for the formations. That's part of our active updated system. So that's really real time. And we have to record this high data rates, and we have requirements to handle data that are a few 100 hertz. So we can easily configure our database with milliseconds precision, that's for telemetry data. But for events, sometimes we have events that are very close to each other and then we need to configure database with higher precision. >> um hm For example, micro seconds. >> Yeah, so Caleb, what are your event intervals like? >> So I would say that, as of today on the spacecraft, the event, the level of timing that we deal with probably tops out at about 20 hertz, 20 measurements per second on things like our gyroscopes. But I think the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications. And I'll give you an example, from when I worked on the rockets at Astra. There, our baseline data rate that we would ingest data during a test is 500 hertz, so 500 samples per second. And in some cases, we would actually need to ingest much higher rate data. Even up to like 1.5 kilohertz. So extremely, extremely high precision data there, where timing really matters a lot. And, I can, one of the really powerful things about Influx is the fact that it can handle this, that's one of the reasons we chose it. Because there's times when we're looking at the results of firing, where you're zooming in. I've talked earlier about how on my current job, we often zoom out to look at a year's worth of data. You're zooming in, to where your screen is preoccupied by a tiny fraction of a second. And you need to see, same thing, as Angelo just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers. So that can be something like, hey, I opened this valve at exactly this time. And that goes, we want to have that at micro or even nanosecond precision, so that we know, okay, we saw a spike in chamber pressure at this exact moment, was that before or after this valve open? That kind of visibility is critical in these kinds of scientific applications and absolutely game changing, to be able to see that in near real time. And with a really easy way for engineers to be able to visualize this data themselves without having to wait for us software engineers to go build it for them. >> Can the scientists do self serve? Or do you have to design and build all the analytics and queries for scientists? >> I think that's absolutely from my perspective, that's absolutely one of the best things about Influx, and what I've seen be game changing is that, generally, I'd say anyone can learn to use Influx. And honestly, most of our users might not even know they're using Influx. Because the interface that we expose to them is Grafana, which is generic graphing, open source graphing library that is very similar to Influx zone chronograph. >> Sure. >> And what it does is, it provides this, almost, it's a very intuitive UI for building your query. So you choose a measurement, and it shows a drop down of available measurements, and then you choose the particular field you want to look at. And again, that's a drop down. So it's really easy for our users to discover it. And there's kind of point and click options for doing math, aggregations. You can even do like, perfect kind of predictions all within Grafana. The Grafana user interface, which is really just a wrapper around the API's and functionality that Influx provides. So yes, absolutely, that's been the most powerful thing about it, is that it gets us out of the way, us software engineers, who may not know quite as much as the scientists and engineers that are closer to the interesting math. And they build these crazy dashboards that I'm just like, wow, I had no idea you could do that. I had no idea that, that is something that you would want to see. And absolutely, that's the most empowering piece. >> Yeah, putting data in the hands of those who have the context, the domain experts is key. Angelo is it the same situation for you? Is it self serve? >> Yeah, correct. As I mentioned before, we have the astronomers making their own dashboards, because they know exactly what they need to visualize. And I have an example just from last week. We had an engineer at the observatory that was building a dashboard to monitor the cooling system of the entire building. And he was familiar with InfluxQL, which was the primarily query language in version one of InfluxDB. And he had, that was really a challenge because he had all the data spread at multiple InfluxDB measurements. And he was like doing one query for each measurement and was not able to produce what he needed. And then, but that's the perfect use case for Flux, which is the new data scripting language that Influx data developed and introduced as the main language in version two. And so with Flux, he was able to combine data from multiple measurements and summarize this data in a nice table. So yeah, having more flexible and powerful language, also allows you to make better a visualization. >> So Angelo, where would you be without time series database, that technology generally, may be specifically InfluxDB, as one of the leading platforms. Would you be able to do this? >> Yeah, it's hard to imagine, doing what we are doing without InfluxDB. And I don't know, perhaps it would be just a matter of time to rediscover InfluxDB. >> Yeah. How about you Caleb? >> Yeah, I mean, it's all about using the right tool for the job. I think for us, when I joined the company, we weren't using InfluxDB and we were dealing with serious issues of the database growing to a an incredible size, extremely quickly. And being unable to, like even querying short periods of data, was taking on the order of seconds, which is just not possible for operations. So time series database is, if you're dealing with large volumes of time series data, Time series database is the right tool for the job and Influx is a great one for it. So, yeah, it's absolutely required to use for this kind of data, there is not really any other option. >> Guys, this has been really informative. It's pretty exciting to see, how the edge is mountain tops, lower Earth orbits. Space is the ultimate edge. Isn't it. I wonder if you could two questions to wrap here. What comes next for you guys? And is there something that you're really excited about? That you're working on. Caleb, may be you could go first and than Angelo you could bring us home. >> Yeah absolutely, So basically, what's next for Loft Orbital is more, more satellites a greater push towards infrastructure and really making, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, making that happen. It's extremely exciting and extremely exciting time to be in this company and to be in this industry as a whole. Because there are so many interesting applications out there. So many cool ways of leveraging space that people are taking advantage of and with companies like SpaceX, now rapidly lowering cost of launch. It's just a really exciting place to be in. And we're launching more satellites. We're scaling up for some constellations and our ground system has to be improved to match. So there is a lot of improvements that we are working on to really scale up our control systems to be best in class and make it capable of handling such large workloads. So, yeah. What's next for us is just really 10X ing what we are doing. And that's extremely exciting. >> And anything else you are excited about? Maybe something personal? Maybe, you know, the titbit you want to share. Are you guys hiring? >> We're absolutely hiring. So, we've positions all over the company. So we need software engineers. We need people who do more aerospace specific stuff. So absolutely, I'd encourage anyone to check out the Loft Orbital website, if this is at all interesting. Personal wise, I don't have any interesting personal things that are data related. But my current hobby is sea kayaking, so I'm working on becoming a sea kayaking instructor. So if anyone likes to go sea kayaking out in the San Francisco Bay area, hopefully I'll see you out there. >> Love it. All right, Angelo, bring us home. >> Yeah. So what's next for us is, we're getting this telescope working and collecting data and when that's happened, it's going to be just a delish of data coming out of this camera. And handling all that data, is going to be a really challenging. Yeah, I wonder I might not be here for that I'm looking for it, like for next year we have an important milestone, which is our commissioning camera, which is a simplified version of the full camera, is going to be on sky and so most of the system has to be working by then. >> Any cool hobbies that you are working on or any side project? >> Yeah, actually, during the pandemic I started gardening. And I live here in Two Sun, Arizona. It gets really challenging during the summer because of the lack of water, right. And so, we have an automatic irrigation system at the farm and I'm trying to develop a small system to monitor the irrigation and make sure that our plants have enough water to survive. >> Nice. All right guys, with that we're going to end it. Thank you so much. Really fascinating and thanks to InfluxDB for making this possible. Really ground breaking stuff, enabling value at the edge, in the cloud and of course beyond, at the space. Really transformational work, that you guys are doing. So congratulations and I really appreciate the broader community. I can't wait to see what comes next from this entire eco system. Now in the moment, I'll be back to wrap up. This is Dave Vallante. And you are watching The cube, the leader in high tech enterprise coverage. (upbeat music)

(upbeat music) >> Hello, and welcome to The Great Cloud Debate. I'm your moderator Rachel Dines. I'm joined by two debaters today Corey Quinn, Cloud Economist at the Duckbill Group and Stu Miniman, Senior Analyst and Host of theCube. Welcome Corey and Stu, this when you can say hello. >> Hey Rachel, great to talk to you. >> And it's better to talk to me. It's always a pleasure to talk to the fine folks over at CloudHealth at by VMware and less of the pleasure to talk to Stu. >> Smack talk is scheduled for later in the agenda gentlemen, so please keep it to a minimum now to keep us on schedule. So here's how today is going to work. I'm going to introduce a debate topic and assign Corey and Stu each to a side. Remember, their assignments are what I decide and they might not actually match their true feelings about a topic, and it definitely does not represent the feelings of their employer or my employer, importantly. Each debater is going to have two minutes to state their opening arguments, then we'll have rebuttals. And each round you the audience gets to vote of who you think is winning. And at the end of the debate, I'll announce the winner. The prize is bragging rights of course, but then also we're having each debater play to win lunch for their local hospital, which is really exciting. So Stu, which hospital are you playing for? >> Yeah, so Rachel, I'm choosing Brigham Women's Hospital. I get a little bit of a home vote for the Boston audience here and was actually my wife's first job out of school. >> Great hospital. Very, very good. All right, Corey, what about you? >> My neighbor winds up being as specialist in infectious diseases as a doctor, and that was always one of those weird things you learn over a cocktail party until this year became incredibly relevant. So I will absolutely be sending the lunch to his department. >> Wonderful! All right. Well, is everyone ready? Any last words? This is your moment for smack talk. >> I think I'll say that for once we can apply it to a specific technology area. Otherwise, it was insulting his appearance and that's too easy. >> All right, let's get going. The first topic is multicloud. Corey, you'll be arguing that companies are better off standardizing on a single cloud. While Stu, you're going to argue the companies are better off with a multicloud strategy. Corey, you're up first, two minutes on the clock and go. >> All right. As a general rule, picking a single provider and going all in leads to the better outcome. Otherwise, you're trying to build every workload to run seamlessly on other providers on a moment's notice. You don't ever actually do it and all you're giving up in return is the ability to leverage whatever your primary cloud provider is letting you build. Now you're suddenly trying to make two differently behaving load balancers work together in the same way, you're using terraform or as I like to call it multicloud formation in the worst of all possible ways. Because now you're having to only really build on one provider, but all the work you're putting in to make that scale to other providers, you might theoretically want to go to at some point, it slows you down, you're never going to be able to move as quickly trying to build for everyone as you are for one particular provider. And I don't care which provider you pick, you probably care which one you pick, I don't care which one. The point is, you've got to pick what's right for your business. And in almost every case, that means start on a single platform. And if you need to migrate down the road years from now, great, that means A you've survived that long, and B you now have the longevity as a business to understand what migrating looks like. Otherwise you're not able to take care of any of the higher level offerings these providers offer that are even slightly differentiated from each other. And even managed database services behave differently. You've got to become a master of all the different ways these things can fail and unfortunate and displeasing ways. It just leaves you in a position where you're not able to specialize, and of course, makes hiring that much harder. Stu, fight me! >> Tough words there. All right, Stu, your turn. Why are companies better off if they go with a multicloud strategy? Got two minutes? >> Yeah, well first of all Corey, I'm really glad that I didn't have to whip out the AWS guidelines, you were not sticking strictly to it and saying that you could not use the words multicloud, cross-cloud, any cloud or every cloud so thank you for saving me that argument. But I want you to kind of come into the real world a little bit. We want access to innovation, we want flexibility, and well, we used to say I would have loved to have a single provider, in the real world we understand that people end up using multiple solutions. If you look at the AI world today, there's not a provider that is a clear leader in every environment that I have. So there's a reason why I might want to use a lot of clouds. Most companies I talked to, Corey, they still have some of their own servers. They're working in a data center, we've seen huge explosion in the service provider world connecting to multiple clouds. So well, a couple of years ago, multicloud was a complete mess. Now, it's only a little bit of a mess, Corey. So absolutely, there's work that we need to do as an industry to make these solutions better. I've been pining for a couple years to say that multicloud needs to be stronger than the sum of its pieces. And we might not yet be there but limiting yourself to a single cloud is reducing your access to innovation, it's reducing your flexibility. And when you start looking at things like edge computing and AI, I'm going to need to access services from multiple providers. So single cloud is a lovely ideal, but in the real world, we understand that teams come with certain skill sets. We end up in many industries, we have mergers and acquisitions. And it's not as easy to just rip out all of your cloud, like you would have 20 years ago, if you said, "Oh, well, they have a phone system or a router "that didn't match what our corporate guidelines is." Cloud is what we're doing. There's lots of solutions out there. And therefore, multicloud is the reality today, and will be the reality going forward for many years to come. >> Strong words from you, Stu. Corey, you've got 60 seconds for rebuttal. I mostly agree with what you just said. I think that having different workloads in different clouds makes an awful lot of sense. Data gravity becomes a bit of a bear. But if you acquire a company that's running on a different cloud than the one that you've picked, you'd be ridiculous to view migrating as anything approaching a strategic priority. Now, this also gets into the question of what is cloud? Our G Suite stuff counts as cloud, but no one really views it in that way. Similarly, when you have an AI specific workload, that's great. As long as it isn't you seriously expensive to move data between providers. That workload doesn't need to live in the same place as your marketing website does. I think that the idea of having a specific cloud provider that you go all in on for every use case, well, at some point that leads to ridiculous things like pretending that Amazon WorkDocs has customers, it does not. But for things that matter to your business and looking at specific workloads, I think that you're going to find a primary provider with secondary workloads here and they're scattered elsewhere to be the strategy that people are getting at when they use the word multicloud badly. >> Time's up for you Corey, Stu we've got time for rebuttal and remember, for those of you in the audience, you can vote at any time and who you think is winning this round. Stu, 60 seconds for a rebuttal. >> Yeah, absolutely Corey. Look, you just gave the Andy Jassy of what multicloud should be 70 to 80% goes to a single provider. And it does make sense we know nobody ever said multicloud equals the same amount in multiple environments but you made a clear case as to why multicloud leveraging multi providers is likely what most companies are going to do. So thank you so much for making a clear case as to why multicloud not equal cloud, across multiple providers is the way to go. So thank you for conceding the victory. >> Last Words, Corey. >> If that's what you took from it Stu, I can't get any closer to it than you have. >> All right, let's move on to the next topic then. The next topic is serverless versus containers which technology is going to be used in, let's say, five to 10 years time? And as a reminder, I'm going to assign each of the debaters these topics, their assignments may or may not match their true feelings about this topic, and they definitely don't represent the topics of my employer, CloudHealth by VMware. Stu, you're going to argue for containers. Corey you're going to argue for start serverless. Stu, you're up first. Two minutes on the clock and go. >> All right, so with all respect to my friends in the serverless community, We need to have a reality check as to how things work. We all know that serverless is a ridiculous name because underneath we do need to worry about all of the infrastructure underneath. So containers today are the de facto building block for cloud native architectures, just as the VM defined the ecosystem for an entire generation of solutions. Containers are the way we build things today. It is the way Google has architected their entire solution and underneath it is often something that's used with serverless. So yes, if you're, building an Alexa service, serverless make what's good for you. But for the vast majority of solutions, I need to have flexibility, I need to understand how things work underneath it. We know in IT that it's great when things work, but we need to understand how to fix them when they break. So containerization gets us to that atomic level, really close to having the same thing as the application. And therefore, we saw the millions of users that deploy Docker, we saw the huge wave of container orchestration led by Kubernetes. And the entire ecosystem and millions of customers are now on board with this way of designing and architecting and breaking down the silos between the infrastructure world and the application developer world. So containers, here to stay growing fast. >> All right, Corey, what do you think? Why is serverless the future? >> I think that you're right in that containers are the way you get from where you were to something that runs effectively in a cloud environment. That is why Google is so strongly behind Kubernetes it helps get the entire industry to write code the way that Google might write code. And that's great. But if you're looking at effectively rewriting something from scratch, or building something that new, the idea of not having to think about infrastructure in the traditional sense of being able to just here, take this code and run it in a given provider that takes whatever it is that you need to do and could loose all these other services together, saves an awful lot of time. As that continues to move up the stack towards the idea of no code or low code. And suddenly, you're now able to build these applications in ways that require just a little bit of code that tie together everything else. We're closer than ever to that old trope of the only code you write is business logic. Serverless gives a much clearer shot of getting there, if you can divorce yourself from the past of legacy workloads. Legacy, of course meaning older than 18 months and makes money. >> Stu, do you have a rebuttal, 60 seconds? >> Yeah. So Corey, we've been talking about this Nirvana in many ways. It's the discussion that we had for paths for over a decade now. I want to be able to write my code once not worry about where it lives, and do all this. But sometimes, there's a reason why we keep trying the same thing over and over again, but never reaching it. So serverless is great for some application If you talked about, okay, if you're some brand new webby thing there and I don't want to have to do this team, that's awesome. I've talked to some wonderful people that don't know anything about coding that have built some cool stuff with serverless. But cool stuff isn't what most business runs on, and therefore containerization is, as you said, it's a bridge to where I need to go, it lives in these cloud environments, and it is the present and it is the future. >> Corey, your response. >> I agree that it's the present, I doubt that it's the future in quite the same way. Right now Kubernetes is really scratching a major itch, which is how all of these companies who are moving to public cloud still I can have their infrastructure teams be able to cosplay as cloud providers themselves. And over time, that becomes simpler and I think on some level, you might even see a convergence of things that are container workloads begin to look a lot more like serverless workloads. Remember, we're aiming at something that is five years away in the context of this question. I think that the serverless and container landscape will look very different. The serverless landscape will be bright and exciting and new, whereas unfortunately the container landscape is going to be represented by people like you Stu. >> Hoarse words from Corey. Stu, any last words or rebuttals? >> Yeah, and look Corey absolutely just like we don't really think about the underlying server or VM, we won't think about the containers you won't think about Kubernetes in the future, but, the question is, which technology will be used in five to 10 years, it'll still be there. It will be the fabric of our lives underneath there for containerization. So, that is what we were talking about. Serverless I think will be useful in pockets of places but will not be the predominant technology, five years from now. >> All right, tough to say who won that one? I'm glad I don't have to decide. I hope everyone out there is voting, last chance to vote on this question before we move on to the next. Next topic is cloud wars. I'm going to give a statement and then I'm going to assign each of you a pro or a con, Google will never be an actual contender in the cloud wars always a far third, we're going to have Corey arguing that Google is never going to be an actual contender. And Stu, you're going to argue that Google is eventually going to overtake the top two AWS and Azure. As a constant reminder, I'm assigning these topics, it's my decision and also they don't match the opinions of me, my employer, or likely Stu or Corey. This is all just for fun and games. But I really want to hear what everyone has to say. So Corey, you're up first two minutes. Why is Google never going to be an actual contender and go. >> The biggest problem Google has in the time of cloud is their ability to forecast longer term on anything that isn't their advertising business, and their ability to talk to human beings long enough to meet people where they are. We're replacing their entire culture is what it's going to take to succeed in the time of cloud and with respect, Thomas Kurian is a spectacular leader internally but look at where he's come from. He spent 22 years at Oracle and now has been transplanted into Google. If we take a look at Satya Nadella's cloud transformation at Microsoft, he was able to pull that off as an insider, after having known intimately every aspect of that company, and he grew organically with it and was perfectly positioned to make that change. You can't instill that kind of culture change by dropping someone externally, on top of an organization and expecting anything to go with this magic one day wake up and everything's going to work out super well. Google has a tremendous amount of strengths, and I don't see that providing common denominator cloud computing services to a number of workloads that from a Google perspective are horrifying, is necessarily in their wheelhouse. It feels like their entire focus on this is well, there's money over there. We should go get some of that too. It comes down to the traditional Google lack of focus. >> Stu, rebuttal? Why do you think Google has a shaft? >> Yeah, so first of all, Corey, I think we'd agree Google is a powerhouse in the world today. My background is networking, when they first came out with with Google Cloud, I said, Google has the best network, second to none in the world. They are ubiquitous today. If you talk about the impact they have on the world, Android phones, you mentioned Kubernetes, everybody uses G Suite maps, YouTube, and the like. That does not mean that they are necessarily going to become the clear leader in cloud but, Corey, they've got really, really smart people. If you're not familiar with that talk to them. They'll tell you how smart they are. And they have built phenomenal solutions, who's going to be able to solve, the challenge every day of, true distributed systems, that a global database that can handle the clock down to the atomic level, Google's the one that does that we've all read the white papers on that. They've set the tone for Hadoop, and various solutions that are all over the place, and their secret weapon is not the advertising, of course, that is a big concern for them, but is that if you talk about, the consumer adoption, everyone uses Google. My kids have all had Chromebooks growing up. It isn't their favorite thing, but they get, indoctrinated with Google technology. And as they go out and leverage technologies in the world, Google is one that is known. Google has the strength of technology and a lot of positioning and partnerships to move them forward. Everybody wants a strong ecosystem in cloud, we don't want a single provider. We already discussed this before, but just from a competitive nature standpoint, if there is a clear counterbalance to AWS, I would say that it is Google, not Microsoft, that is positioned to be that clear and opportune. >> Interesting, very interesting Stu. So your argument is the Gen Zers will of ultimately when they come of age become the big Google proponents. Some strong words that as well but they're the better foil to AWS, Corey rebuttal? >> I think that Stu is one t-shirt change away from a pitch perfect reenactment of Charlie Brown. In this case with Google playing the part of Lucy yanking the football away every time. We've seen it with inbox, Google Reader, Google Maps, API pricing, GKE's pricing for control plane. And when your argument comes down to a suddenly Google is going to change their entire nature and become something that it is as proven as constitutionally incapable of being, namely supporting something that its customers want that it doesn't itself enjoy working on. And to the exclusion of being able to get distracted and focused on other things. Even their own conferences called Next because Google is more interested in what they're shipping than what they're building, than what they're currently shipping. I think that it is a fantasy to pretend that that is somehow going to change without a complete cultural transformation, which again, I don't see the seeds being planted for. >> Some sick burns in there Stu, rebuttal? >> Yeah. So the final word that I'll give you on this is, one of the most important pieces of what we need today. And we need to tomorrow is our data. Now, there are some concerns when we talk about Google and data, but Google also has strong strength in data, understanding data, helping customers leverage data. So while I agree to your points about the cultural shift, they have the opportunity to take the services that they have, and enable customers to be able to take their data to move forward to the wonderful world of AI, cloud, edge computing, and all of those pieces and solve the solution with data. >> Strong words there. All right, that's a tough one. Again, I hope you're all out there voting for who you think won that round. Let's move on to the last round before we start hitting the lightning questions. I put a call out on several channels and social media for people to have questions that they want you to debate. And this one comes from Og-AWS Slack member, Angelo. Angelo asks, "What about IBM Cloud?" Stu you're pro, Corey you're con. Let's have Stu you're up first. The question is, what about IBM Cloud? >> All right, so great question, Angelo. I think when you look at the cloud providers, first of all, you have to understand that they're not all playing the same game. We talked about AWS and they are the elephant in the room that moves nimbly as a cheetah. Every other provider plays a little bit of a different game. Google has strength in data. Microsoft, of course, has their, business productivity applications. IBM has a strong legacy. Now, Corey is going to say that they are just legacy and you need to think about them but IBM has strong innovation. They are a player in really what we call chapter two of the cloud. So when we start talking about multicloud, when we start talking about living in many environments, IBM was the first one to partner with VMware for VMware cloud before the mega VMware AWS announcement, there was IBM up on stage and if I remember right, they actually have more VMware customers on IBM Cloud than they do in the AWS cloud. So over my shoulder here, there's of course, the Red Hat $34 billion to bet on that multicloud solution. So as we talk about containerization, and Kubernetes, Red Hat is strongly positioned in open-source, and flexibility. So you really need a company that understands both the infrastructure side and the application side. IBM has database, IBM has infrastructure, IBM has long been the leader in middleware, and therefore IBM has a real chance to be a strong player in this next generation of platforms. Doesn't mean that they're necessarily going to go attack Amazon, they're partnering across the board. So I think you will see a kinder, gentler IBM and they are leveraging open source and Red Hat and I think we've let the dogs out on the IBM solution. >> Indeed. >> So before Corey goes, I feel the need to remind everyone that the views expressed here are not the views of my employer nor myself, nor necessarily of Corey or Stu. I have Corey. >> I haven't even said anything yet. And you're disclaiming what I'm about to say. >> I'm just warning the audience, 'cause I can't wait to hear what you're going to say next. >> Sounds like I have to go for the high score. All right. IBM's best days are behind it. And that is pretty clear. They like to get angry when people talk about how making the jokes about a homogenous looking group of guys in blue suits as being all IBM has to offer. They say that hasn't been true since the '80s. But that was the last time people cared about IBM in any meaningful sense and no one has bothered to update the relevance since then. Now, credit where due, I am seeing an awful lot of promoted tweets from IBM into my timeline, all talking about how amazing their IBM blockchain technology is. And yes, that is absolutely the phrasing of someone who's about to turn it all around and win the game. I don't see it happening. >> Stu, rebuttal? >> Look, Corey, IBM was the company that brought us the UPC code. They understand Mac manufacturing and blockchain actually shows strong presence in supply chain management. So maybe you're not quite aware of some of the industries that IBM is an expert in. So that is one of the big strengths of IBM, they really understand verticals quite well. And, at the IBM things show, I saw a lot in the healthcare world, had very large customers that were leveraging those solutions. So while you might dismiss things when they say, Oh, well, one of the largest telecom providers in India are leveraging OpenStack and you kind of go with them, well, they've got 300 million customers, and they're thrilled with the solution that they're doing with IBM, so it is easy to scoff at them, but IBM is a reliable, trusted provider out there and still very strong financially and by the way, really excited with the new leadership in place there, Arvind Krishna knows product, Jim Whitehurst came from the Red Hat side. So don't be sleeping on IBM. >> Corey, any last words? >> I think that they're subject to massive disruption as soon as they release the AWS 400 mainframe in the cloud. And I think that before we, it's easy to forget this, but before Google was turning off Reader, IBM stopped making the model M buckling spring keyboards. Those things were masterpieces and that was one of the original disappointments that we learned that we can't fall in love with companies, because companies in turn will not love us back. IBM has demonstrated that. Lastly, I think I'm thrilled to be working with IBM is exactly the kind of statement one makes only at gunpoint. >> Hey, Corey, by the way, I think you're spending too much time looking at all titles of AWS services, 'cause you don't know the difference between your mainframe Z series and the AS/400 which of course is heavily pending. >> Also the i series. Oh yes. >> The i series. So you're conflating your system, which still do billions of dollars a year, by the way. >> Oh, absolutely. But that's not we're not seeing new banks launching and then building on top of IBM mainframe technology. I'm not disputing that mainframes were phenomenal. They were, I just don't see them as the future and I don't see a cloud story. >> Only a cloud live your mainframe related smack talk. That's the important thing that we're getting to here. All right, we move-- >> I'm hoping there's an announcement from CloudHealth by VMware that they also will now support mainframe analytics as well as traditional cloud. >> I'll look into that. >> Excellent. >> We're moving on to the lightning rounds. Each debater in this round is only going to get 60 seconds for their opening argument and then 30 seconds for a rebuttal. We're going to hit some really, really big important questions here like this first one, which is who deserves to sit on the Iron Throne at the end of "Game of Thrones?" I've been told that Corey has never seen this TV show so I'm very interested to hear him argue for Sansa. But let's Sansa Stark, let's hear Stu go first with his argument for Jon Snow. Stu one minute on the clock, go. >> All right audience let's hear it from the king of the north first of all. Nothing better than Jon Snow. He made the ultimate sacrifice. He killed his love to save Westeros from clear destruction because Khaleesi had gone mad. So Corey is going to say something like it's time for the women to do this but it was a woman she went mad. She started burning the place down and Jon Snow saved it so it only makes sense that he should have done it. Everyone knows it was a travesty that he was sent back to the Wall, and to just wander the wild. So absolutely Jon Snow vote for King of the North. >> Compelling arguments. Corey, why should Sansa Stark sit on the throne? Never having seen the show I've just heard bits and pieces about it and all involves things like bloody slaughters, for example, the AWS partner Expo right before the keynote is best known as AWS red wedding. We take a look at that across the board and not having seen it, I don't know the answer to this question, but how many of the folks who are in positions of power we're in fact mediocre white dudes and here we have Stu advocating for yet another one. Sure, this is a lightning round of a fun event but yes, we should continue to wind up selecting this mediocre white person has many parallels in terms of power, et cetera, politics, current tech industry as a whole. I think she's right we absolutely should give someone with a look like this a potential opportunity to see what they can do instead. >> Ouch, Stu 30 seconds rebuttal. >> Look, I would just give a call out to the women in the audience and say, don't you want Jon Snow to be king? >> I also think it's quite bold of Corey to say that he looks like Kit Harington. Corey, any last words? >> I think that it sad you think Stu was running for office at this point because he's become everyone's least favorite animal, a panda bear. >> Fire. All right, so on to the next question. This one also very important near and dear to my heart personally, is a hot dog a sandwich. Corey you'll be arguing no, Stu will be arguing yes. I must also add this important disclaimer that these assignments are made by me and might not reflect the actual views of the debaters here so Corey, you're up first. Why is a hot dog not a sandwich? >> Because you'll get punched in the face if you go to a deli of any renown and order a hot dog. That is not what they serve there. They wind up having these famous delicatessen in New York they have different sandwiches named after different celebrities. I shudder to think of the deadly insult that naming a hot dog after a celebrity would be to that not only celebrity in some cases also the hot dog too. If you take a look and you want to get sandwiches for lunch? Sure. What are we having catered for this event? Sandwiches. You show up and you see a hot dog, you're looking around the hot dog to find the rest of the sandwich. Now while it may check all of the boxes for a technical definition of what a sandwich is, as I'm sure Stu will boringly get into, it's not what people expect, there's a matter of checking the actual boxes, and then delivering what customers actually want. It's why you can let your product roadmap be guided by cart by customers or by Gartner but rarely both. >> Wow, that one hurts. Stu, why is the hot dog a sandwich? >> Yeah so like Corey, I'm sorry that you must not have done some decent traveling 'cause I'm glad you brought up the definition because I'm not going to bore you with yes, there's bread and there's meat and there's toppings and everything else like that but there are some phenomenal hot dogs out there. I traveled to Iceland a few years ago, and there's a little hot dog stand out there that's been there for over 40 or 50 years. And it's one of the top 10 culinary experience I put in. And I've been to Michelin star restaurants. You go to Chicago and any local will be absolutely have to try our creation. There are regional hot dogs. There are lots of solutions there and so yeah, of course you don't go to a deli. Of course if you're going to the deli for takeout and you're buying meats, they do sell hot dogs, Corey, it's just not the first thing that you're going to order on the menu. So I think you're underselling the hot dog. Whether you are a child and grew up and like eating nothing more than the mustard or ketchup, wherever you ate on it, or if you're a world traveler, and have tried some of the worst options out there. There are a lot of options for hot dogs so hot dog, sandwich, culinary delight. >> Stu, don't think we didn't hear that pun. I'm not sure if that counts for or against you, but Corey 30 seconds rebuttal. >> In the last question, you were agitating for putting a white guy back in power. Now you're sitting here arguing that, "Oh some of my best friend slash meals or hot dogs." Yeah, I think we see what you're putting down Stu and it's not pretty, it's really not pretty and I think people are just going to start having to ask some very pointed, delicate questions. >> Tough words to hear Stu. Close this out or rebuttal. >> I'm going to take the high road, Rachel and leave that where it stands. >> I think that is smart. All right, next question. Tabs versus spaces. Stu, you're going to argue for tabs, Corey, you're going to argue for spaces just to make this fun. Stu, 60 seconds on the clock, you're up first. Why are tabs the correct approach? >> First of all, my competitor here really isn't into pop culture. So he's probably not familiar with the epic Silicon Valley argument over this discussion. So, Corey, if you could explain the middle of algorithm, we will be quite impressed but since you don't, we'll just have to go with some of the technology first. Looks, developers, we want to make things simple on you. Tabs, they're faster to do they take up less memory. Yes, they aren't quite as particular as using spaces but absolutely, they get the job done and it is important to just, focus on productivity, I believe that the conversation as always, the less code you can write, the better and therefore, if you don't have to focus on exactly how many spaces and you can just simplify with the tabs, you're gona get close enough for most of the job. And it is easier to move forward and focus on the real work rather than some pedantic discussion as to whether one thing is slightly more efficient than the other. >> Great points Stu. Corey, why is your pedantic approach better? >> No one is suggesting you sit there and whack the spacebar four times or eight times you hit the Tab key, but your editor should be reasonably intelligent enough to expand that. At that point, you have now set up a precedent where in other cases, other parts of your codebase you're using spaces because everyone always does. And that winds up in turn, causing a weird dissonance you'll see a bunch of linters throwing issues if you use tabs as a direct result. Now the wrong answer is, of course, and I think Steve will agree with me both in the same line. No one is ever in favor of that. But I also want to argue with Stu over his argument about "Oh, it saves a little bit of space "is the reason one should go with tabs instead." Sorry, that argument said bye bye a long time ago, and that time was the introduction of JavaScript, where it takes many hundreds of Meg's of data to wind up building hello world. Yeah, at that point optimization around small character changes are completely irrelevant. >> Stu, rebuttal? >> Yeah, I didn't know that Corey did not try to defend that he had any idea what Silicon Valley was, or any of the references in there. So Rachel, we might have to avoid any other pop culture references. We know Corey just looks at very specific cloud services and can't have fun with some of the broader themes there. >> You're right my mistake Stu. Corey, any last words? >> It's been suggested that whole middle out seen on the whiteboard was came from a number of conversations I used to have with my co-workers as in people who were sitting in the room with me watching that episode said, Oh my God, I've been in the room while you had this debate with your friend and I will not name here because they at least still strive to remain employable. Yeah, it's, I understand the value in the picking these fights, we could have gone just as easily with vi versus Emacs, AWS versus Azure, or anything else that you really care to pick a fight with. But yeah, this is exactly the kind of pedantic fight that everyone loves to get involved with, which is why I walked a different path and pick other ridiculous arguments. >> Speaking of those ridiculous arguments that brings us to our last debate topic of the day, Corey you are probably best known for your strong feelings about the pronunciation of the acronym for Amazon Machine Image. I will not be saying how I think it is pronounced. We're going to have you argue each. Stu, you're going to argue that the acronym Amazon Machine Image should be pronounced to rhyme with butterfly. Corey, you'll be arguing that it rhymes with mommy. Stu, rhymes with butterfly. Let's hear it, 60 seconds on the clock. >> All right, well, Rachel, first of all, I wish I could go to the videotape because I have clear video evidence from a certain Corey Quinn many times arguing why AMI is the proper way to pronounce this, but it is one of these pedantic arguments, is it GIF or GIF? Sometimes you go back and you say, Okay, well, there's the way that the community did it. And the way that oh wait, the founder said it was a certain way. So the only argument against AMI, Jeff Barr, when he wrote about the history of all of the blogging that he's done from AWS said, I wish when I had launched the service that I pointed out the correct pronunciation, which I won't even deem to talk it because the community has agreed by and large that AMI is the proper way to pronounce it. And boy, the tech industry is rific on this kind of thing. Is it SQL and no SQL and you there's various ways that we butcher these constantly. So AMI, almost everyone agrees and the lead champion for this argument, of course is none other than Corey Quinn. >> Well, unfortunately today Corey needs to argue the opposite. So Corey, why does Amazon Machine Image when pronounce as an acronym rhyme with mommy? >> Because the people who built it at Amazon say that it is and an appeal to authorities generally correct when the folks built this. AWS has said repeatedly that they're willing to be misunderstood for long periods of time. And this is one of those areas in which they have been misunderstood by virtually the entire industry, but they are sticking to their guns and continuing to wind up advocating for AMI as the correct pronunciation. But I'll take it a step further. Let's take a look at the ecosystem companies. Whenever Erica Brescia, who is now the COO and GitHub, but before she wound up there, she was the founder of Bitnami. And whenever I call it Bitn AMI she looks like she is barely successfully restraining herself from punching me right in the mouth for that pronunciation of the company. Clearly, it's Bitnami named after the original source AMI, which is what the proper term pronunciation of the three letter acronym becomes. Fight me Stu. >> Interesting. Interesting argument, Stu 30 seconds, rebuttal. >> Oh, the only thing he can come up with is that, you take the word Bitnami and because it has that we know that things sound very different if you put a prefix or a suffix, if you talk to the Kubernetes founders, Kubernetes should be coop con but the people that run the conference, say it cube con so there are lots of debates between the people that create it and the community. I in general, I'm going to vote with the community most of the time. Corey, last words on this topic 'cause I know you have very strong feelings about it. >> I'm sorry, did Stu just say Kubernetes and its community as bastions of truth when it comes to pronouncing anything correctly? Half of that entire conference is correcting people's pronunciation of Kubernetes, Kubernetes, Kubernetes, Kubernetes and 15 other mispronunciations that they will of course yell at you for but somehow they're right on this one. All right. >> All right, everyone, I hope you've been voting all along for who you think is winning each round, 'cause this has been a tough call. But I would like to say that's a wrap for today. big thank you to our debaters. You've been very good sports, even when I've made you argue for against things that clearly are hurting you deep down inside, we're going to take a quick break and tally all the votes. And we're going to announce a winner up on the Zoom Q and A. So go to the top of your screen, Click on Zoom Q and A to join us and hear the winner announced and also get a couple minutes to chat live with Corey and Stu. Thanks again for attending this session. And thank you again, Corey and Stu. It's been The Great Cloud Debate. All right, so each round I will announce the winner and then we're going to announce the overall winner. Remember that Corey and Stu are playing not just for bragging rights and ownership of all of the internet for the next 24 hours, but also for lunch to be donated to their local hospital. Corey is having lunch donated to the California Pacific Medical Centre. And Stu is having lunch donated to Boston Medical Centre. All right, first up round one multicloud versus monocloud. Stu, you were arguing for multicloud, Corey, you were arguing for one cloud. Stu won that one by 64% of the vote. >> The vendor fix was in. >> Yeah, well, look, CloudHealth started all in AWS by supporting customers across those environments. So and Corey you basically conceded it because we said multicloud does not mean we evenly split things up. So you got to work on those two skills, buddy, 'cause, absolutely you just handed the victory my way. So thank you so much and thank you to the audience for understanding multicloud is where we are today, and unfortunately, it's where we're gonnao be in the future. So as a whole, we're going to try to make it better 'cause it is, as Corey and I both agree, a bit of a mess right now. >> Don't get too cocky. >> One of those days the world is going to catch up with me and realize that ad hominem is not a logical fallacy so much as it is an excellent debating skill. >> Well, yeah, I was going to say, Stu, don't get too cocky because round two serverless versus containers. Stu you argued for containers, Corey you argued for serverless. Corey you won that one with 65, 66 or most percent of the vote. >> You can't fight the future. >> Yeah, and as you know Rachel I'm a big fan of serverless. I've been to the serverless comp, I actually just published an excellent interview with Liberty Mutual and what they're doing with serverless. So love the future, it's got a lot of maturity to deliver on the promise that it has today but containers isn't going anyway or either so. >> So, you're not sad that you lost that one. Got it, good concession speech. Next one up was cloud wars specifically Google. is Google a real contender in the clouds? Stu, you were arguing yes they are. Corey, you were arguing no they aren't. Corey also won this round was 72% of the votes. >> Yeah, it's one of those things where at some point, it's sort of embarrassing if you miss a six inch pot. So it's nice that that didn't happen in this case. >> Yeah, so Corey, is this the last week that we have any competitors to AWS? Is that what we're saying? And we all accept our new overlords. Thank you so much, Corey. >> Well I hope not, my God, I don't know what to be an Amazonian monoculture anymore than I do anyone else. Competition makes all of us better. But again, we're seeing a lot of anti competitive behaviour. For example, took until this year for Microsoft to finally make calculator uninstallable and I trust concerned took a long time to work its way of course. >> Yeah, and Corey, I think everyone is listening to what you've been saying about what Google's doing with Google Meet and forcing that us when we make our pieces there. So definitely there's some things that Google culture, we'd love them to clean up. And that's one of the things that's really held back Google's enterprise budget is that advertised advertising driven culture. So we will see. We are working hand-- >> That was already opted out of Hangouts, how do we fix it? We call it something else that they haven't opted out of yet. >> Hey, but Corey, I know you're looking forward to at least two months of weekly Google live stuff starting this summer. So we'll have a lot of time to talk about google. >> Let's not kid ourselves they're going to cancel it halfway through. (Stu laughs) >> Boys, I thought we didn't have any more smack talk left in you but clearly you do. So, all right, moving on. Next slide. This is the last question that we did in the main part of the debate. IBM Cloud. What about IBM Cloud was the question, Stu, you were pro, Corey you were con. Corey, you won this one again with 62% of the vote and for the main. >> It wasn't just me, IBM Cloud also won. The problem is that competition was oxymoron of the day. >> I don't know Rachel, I thought this one had a real shot as to putting where IBM fits. I thought we had a good discussion there. It seemed like some of the early voting was going my way but it just went otherwise. >> It did. We had some last minute swings in these polls. They were going one direction they rapidly swung another it's a fickle crowd today. So right now we've got Corey with three points Stu with one but really the lightning round anyone's game. They got very close here. The next question, lightning round question one, was "Game of Thrones" who deserves to sit on the Iron Throne? Stu was arguing for Jon Snow, Corey was arguing for Sansa Stark also Corey has never seen Game of Thrones. This was shockingly close with Stu at 51.5% of the vote took the crown on this King of the North Stu. >> Well, I'm thrilled and excited that King of the North pulled things out because it would have been just a complete embarrassment if I lost to Corey on this question. >> It would. >> It was the right answer, and as you said, he had no idea what he's talking about, which, unfortunately is how he is on most of the rest of it. You just don't realize that he doesn't know what he's talking about. 'Cause he uses all those fast words and discussion points. >> Well, thank you for saying the quiet part out loud. Now, I am completely crestfallen as to the results of this question about a thing I've never seen and could not possibly care less about not going in my favor. I will someday managed to get over this. >> I'm glad you can really pull yourself together and keep on going with life, Corey it's inspiring. All right, next question. Was the lightning round question two is a hot dog a sandwich? Stu, you were arguing yes. Corey, you were arguing no. Corey landslide, you won this 75% of the vote. >> It all comes down to customer expectations. >> Yeah. >> Just disappointment. Disappointment. >> All right, next question tabs versus spaces. Another very close one. Stu, what were you arguing for Stu? >> I was voting tabs. >> Tabs, yeah. And Corey, you were arguing spaces. This did not turn out the way I expected. So Stu you lost this by slim margin Corey 53% of the vote. You won with spaces. >> Yep. And I use spaces in my day to day life. So that's a position I can actually believe in. >> See, I thought I was giving you the opposite point of view there. I mistook you for the correct answer, in my opinion, which is tabs. >> Well, it is funnier to stalk me on Twitter and look what I have to there than on GitHub where I just completely commit different kinds of atrocities. So I don't blame you. >> Caught that pun there. All right, the last rounds. Speaking of atrocities, AMI, Amazon Machine Image is it pronounced AMI or AMI? >> I better not have won this one. >> So Stu you were arguing that this is pronounced AMI rhymes with butterfly. Corey, you were arguing that it's pronounced AMI like mommy. Any guesses under who won this? >> It better be Stu. >> It was a 50, 50 split complete tie. So no points to anyone. >> For your complete and utterly failed on this because I should have won in a landslide. My entire argument was based on every discussion you've had on this. So, Corey I think they're just voting for you. So I'm really surprised-- >> I think at this point it shows I'm such a skilled debater that I could have also probably brought you to a standstill taking the position that gravity doesn't exist. >> You're a master of few things, Corey. Usually it's when you were dressed up nicely and I think they like the t-shirt. It's a nice t-shirt but not how we're usually hiding behind the attire. >> Truly >> Well. >> Clothes don't always make a demand. >> Gentlemen, I would like to say overall our winner today with five points is Corey. Congratulations, Corey. >> Thank you very much. It's always a pleasure to mop the floor with you Stu. >> Actually I was going to ask Stu to give the acceptance speech for you, Corey and, Corey, if you could give a few words of concession, >> Oh, that's a different direction. Stu, we'll start with you, I suppose. >> Yeah, well, thank you to the audience. Obviously, you voted for me without really understanding that I don't know what I'm talking about. I'm a loudmouth on Twitter. I just create a bunch of arguments out there. I'm influential for reasons I don't really understand. But once again, thank you for your votes so much. >> Yeah, it's always unfortunate to wind up losing a discussion with someone and you wouldn't consider it losing 'cause most of the time, my entire shtick is that I sit around and talk to people who know what they're talking about. And I look smart just by osmosis sitting next to them. Video has been rough on me. So I was sort of hoping that I'd be able to parlay that into something approaching a victory. But sadly, that hasn't worked out quite so well. This is just yet another production brought to you by theCube which shut down my original idea of calling it a bunch of squares. (Rachael laughs) >> All right, well, on that note, I would like to say thank you both Stu and Corey. I think we can close out officially the debate, but we can all stick around for a couple more minutes in case any fans have questions for either of them or want to get them-- >> Find us a real life? Yeah. >> Yeah, have a quick Zoom fight. So thanks, everyone, for attending. And thank you Stu, thank you Corey. This has been The Great Cloud Debate.

>> from the Silicon Angle Media Office in Boston, Massachusetts. It's the queue. Now here's your host. Still minimum. >> I'm stupid, Aman and this is a cube conversation from our Boston area studio. We spent a lot of time talking about digital transformation. Of course, At the center of that digital transformations data this segment We're going to be talking about the data integration platform. Joining me for that segment is Itamar on Cory on Who's the senior vice president of enterprise data Integration with Click. Thanks so much for joining me. >> Thanks to left me here. >> All right, so a zay just said, you know the customers, you know, digital information when you talked to any user, you know, there there's some that might say, Oh, there's a little bit of hyper I don't understand it, but really leveraging that data, you know, there are very few places that that is not core toe what they need to do, and if they're not doing it, they're competition will do it. So can you bring us inside a little bit? That customers you're talking to that, that you know where that fits into their business needs and you know how the data integration platform, you know, helps them solve that issue. >> Absolutely so, As you mentioned, the diesel transformation is driving a lot ofthe innovation, a lot off efforts by corporations and virtually any organization that we're talking. Toa seize data is a core component off, enabling the little transformation. The data creates new analytics, and there was toe power, the digital transformation, whether it's in making better decisions, whether it's embedding the analytics and the intelligence into business processes and custom applications to ever to reach the experience and make it better. So data becomes key, and the more data you can make available through the process, the faster you can make a development in the process. The faster you can adapt your process to accommodate the changes, the better it will be. So we're saying organization, virtually all of them looking to modernize their day, the strategy and the day, the platforms in order to accommodate these needs. >> Yeah, it's such a complex issue. We've we've been at, you know, chief data officer events way, talk about data initiatives. You know, we worry a little bit that the sea seats sometimes here it's like up. They heard data is the new oil and they came and they said, You know, according to the magazine I read, you need we need to have a date, a strategy, and give me the value of data. But, you know, where is the rubber hitting the road? You know what? What are some of those steps that they're taking? You know, how do I help, you know, get my arms around the data and that help make sure it can move along that spectrum from kind of the raw or two, you know, real value. >> I think you made a great point. Talking about the or to value our as we refer to it is a road to ready. And part of the whole innovation that we're seeing is the modernization of the platform where organizations are looking to tap into the tremendous amount of data that is available today. So a couple of things have happened first in the last decade. First of all, we have significantly more data. It is available and and then ever before, because of digitization, off data and new sources become available. But beyond that, we have the technology is the platforms that can both store in process large amounts of data. So we have foundations. But in the end, to make it happen, we need to get all the data to where we want to analyze it and find a way to put it together and turning from more row material into ready, material ready products that can be consumed. And that's really where the challenges and we're seeing. A lot of organizations, especially the CEO Seo the animals, architecture and First data architecture, teams on a journey to understand how to put together these kind of architectures and data systems. And that's where without data integration platform, we focused on accommodating the new challenges they have encountered in trying to make that happen. >> Yeah, help us unpack a little bit, You know, a here today. You know, it's the economy. Everything should work together when I rolled out. You know, in our company, you know, the industries leading serum, it's like, Oh, I've got hundreds of data sources and hundreds of tools I could put together, and it should be really easy for me to just, you know, allow my data to flow and get to the right place. But I always always find a lot a lot of times that that easy. But I've been having a hard time finding that so so >> that that's a good point. And if you cannot takes the bag, understand water, this side of the court challenges or the new needs that we're seeing because we talk about the transformation and more than analytics field by data being part of it. More analytics created a new type of challenges that didn't exist before and therefore kind of traditional data integration tools didn't do the job they didn't meet. Those model needs me very touched on a few of those. So, first of all, and people, when customers are implementing more than analytics many times where they refer to escape well they're trying to do is to do a I machine learning. We'LL use those terms and we talk about him but machine learning and I get smarter, the more data you give them. So it's all about the scale of data, and what we're seeing with customers is where if in the past data warehouse system, but if typically had five ten twenty, they the source is going into it. When I was saying one hundred X uh, times that number of sources. So we have customers that worked with five hundred six hundred, some over two thousand source of data feeding the data analytics system. So scale becomes a critical need and we talk about scale. You need the ability to bring data from hundreds or thousands of sources so systems efficiently with very low impact and ideally, do it also with less resources. Because again, you need to scale the second second chair and you ran in tow s to do with the fact that more than analytics for many organizations means real Time analytics or streaming analytics. So they wantto be ableto process data in real time. In response for that, to do that, you need away toe move data, capture it in real time and be able to make it available and do that in a very economic fashion. And then the third one is in order to deal with the scare in order to deal with the agility that the customers want. The question is, well, are they doing the analytics? And many of them are adopting the cloud, and we've been seeing multicoloured adoption. So in order to get data to the cloud. Now you're dealing with the challenge of efficiency. I have limited network band with. I have a lot of data that I need to move around. How can I move all of that and do that more efficiently? And, uh, the only thing that would add to that is that beyond that, the mechanics of how you move the data with scale, with efficiency even in real time there's also how you approach the process where the whole solution is to beware. What a join those the operations you can implement and accommodate any type of architecture. I need to have a platform that you may choose and we sink us was changed those overtime. So I need a breather to be agile and flexible. >> Yeah, well, ah, Lotto unpack there because, you know, I just made the comment. You know, if you talk about us humans, the more data we give them doesn't mean I'm actually going to get better. It's I need to We need to be able to have those tool ings in there to be able to have that data and help give me the insights, which then I could do on otherwise, you know, we understand most people. It's like if I have to make decisions or choices and I get more thrown at me, there's less and less likelihood that I can do on that on boy the Data Lakes. Yeah, I I remember the first time I heard Data Lakes. It was, you know, we talked about what infrastructure rebuilding, and now the last couple of years, the cloud public cloud tends to be a big piece of it. Even though we know data is goingto live everywhere, you know everything, not just public private ground. But EJ gets into a piece of it so that you know that the data integration platform, you know how easy it for customers get started on that We'LL talk about that diversity of everything else, you know, Where do they start? Give me a little bit of kind of customer journey, if you would. And maybe even if you have a customer example that that would be a great way to go illustrated. >> Absolutely so First of all, it's a journey, and I think that journey started quite a few years ago. I mean, do it is now over ten years old, and they were actually seeing a big change in shifting the market from what was initially the Duke ecosystem into a much brother sort of technology's, especially with the cloud in order to store and process large scales of data. So the journey customs we're going through with a few years, which were very experimental customers were trying trying it on for size. They were trying to understand how Toby the process around it, the solutions of them ivory batch oriented with may produce back in the early days off. But when you look at it today, it's a very it's already evolved significantly, and you're saying this big data systems needing to support different and diverse type off workloads. Some of them are michelle machine learning and sign. Some of them are streaming in the Olympics. Some of them are serving data for micro services toe parad, Egil applications. So there's a lot of need for the data in the journey, and what we're seeing is that customers as they move through this journey, they sometimes need to people and they need if they find you technology that come out and they had the ability to be able to accommodate, to adapt and adopt new technologies as they go through. It s so that's kind of the journey we have worked with our customers through. And as they evolved, once they figured it out, this scale came along. So it's very common to see a customer start with a smaller project and then scale it up. So for many of the cost me worked with, that's how it worked out. And you ask for an example. So one of her customers this month, the world's largest automotive companies, and they decided to have a strategy to turn what they believe is a huge asset they have, which is data. But the data is in a lot of silos across manufacturing facility supply facilities and others inventory and bring it all together into one place. Combined data with data to bring from the car itself and by having all the data in one place, be able to derive new insights into information that they they can use as well as potentially sale or monetizing other other ways. So as they got started, they initially start by running it out to set a number off their data data centers and their source of information manufacturing facilities. So they started small. But then very quickly, once they figured out they can do it fast and figure out the process to scale it. Today, there are over five hundred systems they have. Martha is over two hundred billion changes in data being fed daily. Okay, enter their Data lake. So it's a very, very large scale system. I feel we can talk about what it takes to put together something so big. >> Yeah. Don't pleaded. Please take the next step. That would that would be perfect. >> Okay, so I think whether the key things customers have to understand, uh, you were saying that the enterprise architecture teams is that when you need to scale, you need to change the way you think about things. And in the end of the day, there are two fundamental differences in the approach and the other light technology that enabled that. So we talked earlier about the little things help for the mind to understand. Now I'm going to focus on and hide it. Only two that should be easy to take away. First is that they're the move from bench to real time or from batch tow. The Delta to the changes. Traditionally, data integration was done in the best process. You reload the data today if you want to scale. If you want to work in a real time, you need to work based on the Delta on the change, the fundamental technology behind it. It's called change data capture, and it's like technology and approach. It allows you to find and identify only the changes on the enterprise data systems and imagine all the innovation you can get by capturing, imposing or the change is. First of all, you have a significant impact on the systems. Okay, so we can scale because you were moving less data. It's very efficient as you move the data around because it's only a fraction off the data, and it could be real time because again, you capturing the data as it changes. So they move from bitch to real time or to streaming data based on changes. The capture is fundamental, fundamental in creating a more than their integration environment. >> I'm assuming there's an initial load that has to go in something like that, >> correct. But he did that once and then for the rest of the time you're really moving onto the deltas. The second difference, toe one was get moving from batch toe streaming based on change. The capture and the second eyes how you approach building it, which is moving from a development. Let platform to automation. So through automation, you could take workloads that have traditionally being in the realm ofthe the developer and allow people with out development skills to be able to implement such solutions very quickly. So again, the move from developer toe toe configuration based automation based products or what we've done opportunity is First, we have been one of the pioneers in the innovators in change that I capture technology. So the platform that now it's part of the clique that integration plan from brings with it okay over fifteen years off innovation and optimization change their capture with the broader set of data sources that our support there, with lots of optimization ranging from data sources like sickle server and Oracle, the mainstream toe mainframes and to escape system. And then one of the key focus with the head is how do we take complex processes and ultimatum. So from a user perspective, you can click a few buttons, then few knobs, and you have the optimize solution available for making data moving data across that they're very sets off systems. So through moving on to the Delta and the automation, you allow this cape. >> So a lot of the systems I'm familiar with it's the metadata you know, comes in the system. I don't have to as an admin or somebody's setting that up. I don't have to do all of this or even if you think about you know, the way I think of photos these days. It used to be. I took photos and trying to sort them was, you know, ridiculous. Now, my, you know, my apple or Google, you know, normally facial recognition, but timestamp location, all those things I can sort it and find it. You know, it's built into the system >> absolutely in the metadata is critical to us to the whole process. First of all, because when you bring data from one system to another system, somebody's to understand their data. And the process of getting data into a lake and into a data warehouse is becoming a multi step day the pipeline, and in order to trust the data and understanding that you need to understand all the steps that they went through. And we also see different teams taking part in this process. So for it seemed to be able to pick up the data and work on it, it needs to understand its meta data. By the way, this is also where the click their integration platform bring together the unity software. Together with Click the catalyst, we'LL provide unique value proposition for you that because you have the ability to capture changed data as it changes, deliver that data virtually anywhere. Any data lake, any cloud platform, any analytic platform. And then we find the data to generate analytic ready data sets and together with the click data Catalyst, create derivative data sets and publish all of their for a catalogue that makes it really easy to understand which data exists and how to use it. So we have an end to end solution for streaming data pipelines that generate analytic data that data sets for the end of the day, wrote to ready an accelerated fashion. >> So, Itamar, your customers of the world that out, How did they measures Casesa? Their critical KP eyes is there You know some, you know, journey, you know, math that they help go along. You know what? What? What are some commonalities? >> So it's a great question. And naturally, for many organizations, it's about an arrow. I It's about total cost of ownership. It seeing result, as I mentioned earlier, agility and the timeto value is really changing. Customers are looking to get results within a matter of, if very few month and even sometimes weeks versus what it used to be, which is many months and sometimes even years. So again, the whole point is to do with much, much faster. So from a metric for success, what we're seeing his customers that buy our solution toe enable again large scale strategic initiatives where they have dozens to hundreds of data sources. One of the key metrics is how many data sources heavy onboard that heavy, made available. How many in the end of the data sets that already analytic ready have we published or made available Torrey Tor users and I'LL give you an example. Another example from one of for customers, very large corporation in the United States in the opportunity of after trying to move to the cloud and build a cloud Data Lake and analytic platform. In the two years they're able to move to two three data sets to the cloud after they try, they knew they'd integration platform okay, there. But they moved thirty day The sits within three months, so completely different result. And the other thing that they pointed out and actually talk about their solution is that unlike traditional data integration software, and they took an example of one of those traditional PTL platforms and they pointed out it takes seven months to get a new person skilled on that platform. Okay, with our data integration platform, they could do that in a matter of hours to a few days. So again, the ability to get results much faster is completely different. When you have that kind of software that goes back to a dimension about automation versus development based mouth now, >> it really seems like the industry's going through another step function, just as we saw from traditional data warehouses. Tto win. Who? Duke rolled out that just the order of magnitude, how long it took and the business value return Seems like we're we're going through yet another step function there. So final thing. Yeah, You know what? Some of the first things that people usually get started with any final takeaways you want to share? >> Sure. First, for what people are starting to work with. Is there usually selecting a platform of choice where they're gonna get started in respect of whether Iran analytics and the one take a way I'LL give customers is don't assume that the platform you chose is we're going to end up because new technologies come to market, a new options come. Customers are having mergers, acquisitions, so things change all the time. And as you plan, make sure you have the right infrastructure toe allow you two kind of people support and make changes as you move through the throw. These are innovation. So they may be key key takeaway. And the other one is make sure that you're feeling the right infrastructure that can accommodate speed in terms of real time accomodate scale. Okay, in terms of both enabling data legs, letting cloud data stores having the right efficiency to scale, and then anything agility in respect to being able to deploy solution much, much faster. Yeah, >> well, tomorrow I think that. That's some real important things to say. Well, we know that the only constant Internet industry is change on DH. Therefore, we need to have solutions that can help keep up with that on and be able to manage those environments. And, you know, the the role of is to be able to respond to those needs of the business fast. Because if I don't choose the right thing, the business will go elsewhere. Tara trying to fuck with Angelo. Thank you so much for sharing all the latest on the immigration data platforms. Thank you. Alright, Uh, always lots more on the cube dot Net comes to minimum is always thanks for watching.

[Music] [Music] [Music] [Music] [Music] [Music] that will be successful in the 21st century [Music] being open is really important because it comes with a lot of trust the open-source community now has matured so much and that contribution from the community is really driving innovation [Music] but what's really exciting is the change that we've seen in our teams not only the way they collaborate but the way they operate in the way they work [Music] I think idea is everything ideas can change the way you see things open-source is more than a license it's actually a way of operating [Music] ladies and gentlemen please welcome Red Hat president and chief executive officer Jim Whitehurst [Music] all right well welcome to day two at the Red Hat summit I'm amazed to see this many people here at 8:30 in the morning given the number of people I saw pretty late last night out and about so thank you for being here and have to give a shout out speaking of power participation that DJ is was Mike Walker who is our global director of open innovation labs so really enjoyed that this morning was great to have him doing that so hey so day one yesterday we had some phenomenal announcements both around Red Hat products and things that we're doing as well as some great partner announcements which we found exciting I hope they were interesting to you and I hope you had a chance to learn a little more about that and enjoy the breakout sessions that we had yesterday so yesterday was a lot about the what with these announcements and partnerships today I wanted to spin this morning talking a little bit more about the how right how do we actually survive and thrive in this digitally transformed world and to some extent the easy parts identifying the problem we all know that we have to be able to move more quickly we all know that we have to be able to react to change faster and we all know that we need to innovate more effectively all right so the problem is easy but how do you actually go about solving that right the problem is that's not a product that you can buy off the shelf right it is a capability that you have to build and certainly it's technology enabled but it's also depends on process culture a whole bunch of things to figure out how we actually do that and the answer is likely to be different in different organizations with different objective functions and different starting points right so this is a challenge that we all need to feel our way to an answer on and so I want to spend some time today talking about what we've seen in the market and how people are working to address that and it's one of the reasons that the summit this year the theme is ideas worth it lorring to take us back on a little history lesson so two years ago here at Moscone the theme of the summit was the power of participation and then I talked a lot about the power of groups of people working together and participating are able to solve problems much more quickly and much more effectively than individuals or even individual organizations working by themselves and some of the largest problems that we face in technology but more broadly in the world will ultimately only be solved if we effectively participate and work together then last year the theme of the summit was the impact of the individual and we took this concept of participation a bit further and we talked about how participation has to be active right it's a this isn't something where you can be passive that you can sit back you have to be involved because the problem in a more participative type community is that there is no road map right you can't sit back and wait for an edict on high or some central planning or some central authority to tell you what to do you have to take initiative you have to get involved right this is a active participation sport now one of the things that I talked about as part of that was that planning was dead and it was kind of a key my I think my keynote was actually titled planning is dead and the concept was that in a world that's less knowable when we're solving problems in a more organic bottom-up way our ability to effectively plan into the future it's much less than it was in the past and this idea that you're gonna be able to plan for success and then build to it it really is being replaced by a more bottom-up participative approach now aside from my whole strategic planning team kind of being up in arms saying what are you saying planning is dead I have multiple times had people say to me well I get that point but I still need to prepare for the future how do I prepare my organization for the future isn't that planning and so I wanted to spend a couple minutes talk a little more detail about what I meant by that but importantly taking our own advice we spent a lot of time this past year looking around at what our customers are doing because what a better place to learn then from large companies and small companies around the world information technology organizations having to work to solve these problems for their organizations and so our ability to learn from each other take the power of participation an individual initiative that people and organizations have taken there are just so many great learnings this year that I want to get a chance to share I also thought rather than listening to me do that that we could actually highlight some of the people who are doing this and so I do want to spend about five minutes kind of contextualizing what we're going to go through over the next hour or so and some of the lessons learned but then we want to share some real-world stories of how organizations are attacking some of these problems under this how do we be successful in a world of constant change in uncertainty so just going back a little bit more to last year talking about planning was dead when I said planning it's kind of a planning writ large and so that's if you think about the way traditional organizations work to solve problems and ultimately execute you start off planning so what's a position you want to get to in X years and whether that's a competitive strategy in a position of competitive advantage or a certain position you want an organizational function to reach you kind of lay out a plan to get there you then typically a senior leaders or a planning team prescribes the sets of activities and the organization structure and the other components required to get there and then ultimately execution is about driving compliance against that plan and you look at you say well that's all logical right we plan for something we then figure out how we're gonna get there we go execute to get there and you know in a traditional world that was easy and still some of this makes sense I don't say throw out all of this but you have to recognize in a more uncertain volatile world where you can be blindsided by orthogonal competitors coming in and you the term uber eyes you have to recognize that you can't always plan or know what the future is and so if you don't well then what replaces the traditional model or certainly how do you augment the traditional model to be successful in a world that you knows ambiguous well what we've heard from customers and what you'll see examples of this through the course of this morning planning is can be replaced by configuring so you can configure for a constant rate of change without necessarily having to know what that change is this idea of prescription of here's the activities people need to perform and let's lay these out very very crisply job descriptions what organizations are going to do can be replaced by a greater degree of enablement right so this idea of how do you enable people with the knowledge and things that they need to be able to make the right decisions and then ultimately this idea of execution as compliance can be replaced by a greater level of engagement of people across the organization to ultimately be able to react at a faster speed to the changes that happen so just double clicking in each of those for a couple minutes so what I mean by configure for constant change so again we don't know exactly what the change is going to be but we know it's going to happen and last year I talked a little bit about a process solution to that problem I called it that you have to try learn modify and what that model try learn modify was for anybody in the app dev space it was basically taking the principles of agile and DevOps and applying those more broadly to business processes in technology organizations and ultimately organizations broadly this idea of you don't have to know what your ultimate destination is but you can try and experiment you can learn from those things and you can move forward and so that I do think in technology organizations we've seen tremendous progress even over the last year as organizations are adopting agile endeavor and so that still continues to be I think a great way for people to to configure their processes for change but this year we've seen some great examples of organizations taking a different tack to that problem and that's literally building modularity into their structures themselves right actually building the idea that change is going to happen into how you're laying out your technology architectures right we've all seen the reverse of that when you build these optimized systems for you know kind of one environment you kind of flip over two years later what was the optimized system it's now called a legacy system that needs to be migrated that's an optimized system that now has to be moved to a new environment because the world has changed so again you'll see a great example of that in a few minutes here on stage next this concept of enabled double-clicking on that a little bit so much of what we've done in technology over the past few years has been around automation how do we actually replace things that people were doing with technology or augmenting what people are doing with technology and that's incredibly important and that's work that can continue to go forward it needs to happen it's not really what I'm talking about here though enablement in this case it's much more around how do you make sure individuals are getting the context they need how are you making sure that they're getting the information they need how are you making sure they're getting the tools they need to make decisions on the spot so it's less about automating what people are doing and more about how can you better enable people with tools and technology now from a leadership perspective that's around making sure people understand the strategy of the company the context in which they're working in making sure you've set the appropriate values etc etc from a technology perspective that's ensuring that you're building the right systems that allow the right information the right tools at the right time to the right people now to some extent even that might not be hard but when the world is constantly changing that gets to be even harder and I think that's one of the reasons we see a lot of traction and open source to solve these problems to use flexible systems to help enterprises be able to enable their people not just in it today but to be flexible going forward and again we'll see some great examples of that and finally engagement so again if execution can't be around driving compliance to a plan because you no longer have this kind of Cris plan well what do leaders do how do organizations operate and so you know I'll broadly use the term engagement several of our customers have used this term and this is really saying well how do you engage your people in real-time to make the right decisions how do you accelerate a pace of cadence how do you operate at a different speed so you can react to change and take advantage of opportunities as they arise and everywhere we look IT is a key enabler of this right in the past IT was often seen as an inhibitor to this because the IT systems move slower than the business might want to move but we are seeing with some of these new technologies that literally IT is becoming the enabler and driving the pace of change back on to the business and you'll again see some great examples of that as well so again rather than listen to me sit here and theoretically talk about these things or refer to what we've seen others doing I thought it'd be much more interesting to bring some of our partners and our customers up here to specifically talk about what they're doing so I'm really excited to have a great group of customers who have agreed to stand in front of 7,500 people or however many here this morning and talk a little bit more about what they're doing so really excited to have them here and really appreciate all them agreeing to be a part of this and so to start I want to start with tee systems we have the CEO of tee systems here and I think this is a great story because they're really two parts to it right because he has two perspectives one is as the CEO of a global company itself having to navigate its way through digital disruption and as a global cloud service provider obviously helping its customers through this same type of change so I'm really thrilled to have a del hasta li join me on stage to talk a little bit about T systems and what they're doing and what we're doing jointly together so Adelle [Music] Jim took to see you Adele thank you for being here you for having me please join me I love to DJ when that fantastic we may have to hire him no more events for events where's well employed he's well employed though here that team do not give him mics activation it's great to have you here really do appreciate it well you're the CEO of a large organization that's going through this disruption in the same way we are I'd love to hear a little bit how for your company you're thinking about you know navigating this change that we're going through great well you know key systems as an ICT service provider we've been around for decades I'm not different to many of our clients we had to change the whole disruption of the cloud and digitization and new skills and new capability and agility it's something we had to face as well so over the last five years and especially in the last three years we invested heavily invested over a billion euros in building new capabilities building new offerings new infrastructures to support our clients so to be very disruptive for us as well and so and then with your customers themselves they're going through this set of change and you're working to help them how are you working to help enable your your customers as they're going through this change well you know all of them you know in this journey of changing the way they run their business leveraging IT much more to drive business results digitization and they're all looking for new skills new ideas they're looking for platforms that take them away from traditional waterfall development that takes a year or a year and a half before they see any results to processes and ways of bringing applications in a week in a month etcetera so it's it's we are part of that journey with them helping them for that and speaking of that I know we're working together and to help our joint customers with that can you talk a little bit more about what we're doing together sure well you know our relationship goes back years and years with with the Enterprise Linux but over the last few years we've invested heavily in OpenShift and OpenStack to build peope as layers to build you know flexible infrastructure for our clients and we've been working with you we tested many different technology in the marketplace and been more successful with Red Hat and the stack there and I'll give you an applique an example several large European car manufacturers who have connected cars now as a given have been accelerating the applications that needed to be in the car and in the past it took them years if not you know scores to get an application into the car and today we're using open shift as the past layer to develop to enable these DevOps for these companies and they bring applications in less than a month and it's a huge change in the dynamics of the competitiveness in the marketplace and we rely on your team and in helping us drive that capability to our clients yeah do you find it fascinating so many of the stories that you hear and that we've talked about with with our customers is this need for speed and this ability to accelerate and enable a greater degree of innovation by simply accelerating what what we're seeing with our customers absolutely with that plus you know the speed is important agility is really critical but doing it securely doing it doing it in a way that is not gonna destabilize the you know the broader ecosystem is really critical and things like GDP are which is a new security standard in Europe is something that a lot of our customers worry about they need help with and we're one of the partners that know what that really is all about and how to navigate within that and use not prevent them from using the new technologies yeah I will say it isn't just the speed of the external but the security and the regulation especially GDR we have spent an hour on that with our board this week there you go he said well thank you so much for being here really to appreciate the work that we're doing together and look forward to continued same here thank you thank you [Applause] we've had a great partnership with tea systems over the years and we've really taken it to the next level and what's really exciting about that is you know we've moved beyond just helping kind of host systems for our customers we really are jointly enabling their success and it's really exciting and we're really excited about what we're able to to jointly accomplish so next i'm really excited that we have our innovation award winners here and we'll have on stage with us our innovation award winners this year our BBVA dnm IAG lasat Lufthansa Technik and UPS and yet they're all working in one for specific technology initiatives that they're doing that really really stand out and are really really exciting you'll have a chance to learn a lot more about those through the course of the event over the next couple of days but in this context what I found fascinating is they were each addressing a different point of this configure enable engage and I thought it would be really great for you all to hear about how they're experimenting and working to solve these problems you know real-time large organizations you know happening now let's start with the video to see what they think about when they think about innovation I define innovation is something that's changing the model changing the way of thinking not just a step change improvement not just making something better but actually taking a look at what already exists and then putting them together in new and exciting lives innovation is about to build something nobody has done before historically we had a statement that business drives technology we flip that equation around an IT is now demonstrating to the business at power of technology innovation desde el punto de vista de la tecnología supone salir de plataform as proprietary as ADA Madero cloud basado an open source it's a possibility the open source que no parameter no sir Kamala and I think way that for me open-source stands for flexibility speed security the community and that contribution from the community is really driving innovation innovation at a pace that I don't think our one individual organization could actually do ourselves right so first I'd like to talk with BBVA I love this story because as you know Financial Services is going through a massive set of transformations and BBVA really is at the leading edge of thinking about how to deploy a hybrid cloud strategy and kind of modular layered architecture to be successful regardless of what happens in the future so with that I'd like to welcome on stage Jose Maria Rosetta from BBVA [Music] thank you for being here and congratulations on your innovation award it's been a pleasure to be here with you it's great to have you hi everybody so Josemaria for those who might not be familiar with BBVA can you give us a little bit of background on your company yeah a brief description BBVA is is a bank as a financial institution with diversified business model and that provides well financial services to more than 73 million of customers in more than 20 countries great and I know we've worked with you for a long time so we appreciate that the partnership with you so I thought I'd start with a really easy question for you how will blockchain you know impact financial services in the next five years I've gotten no idea but if someone knows the answer I've got a job for him for him up a pretty good job indeed you know oh all right well let me go a little easier then so how will the global payments industry change in the next you know four or five years five years well I think you need a a Weezer well I tried to make my best prediction means that in five years just probably will be five years older good answer I like that I always abstract up I hope so I hope so yah-yah-yah hope so good point so you know immediately that's the obvious question you have a massive technology infrastructure is a global bank how do you prepare yourself to enable the organization to be successful when you really don't know what the future is gonna be well global banks and wealth BBBS a global gam Bank a certain component foundations you know today I would like to talk about risk and efficiency so World Bank's deal with risk with the market great the operational reputational risk and so on so risk control is part of all or DNA you know and when you've got millions of customers you know efficiency efficiency is a must so I think there's no problem with all these foundations they problem the problem analyze the problems appears when when banks translate these foundations is valued into technology so risk control or risk management avoid risk usually means by the most expensive proprietary technology in the market you know from one of the biggest software companies in the world you know so probably all of you there are so those people in the room were glad to hear you say that yeah probably my guess the name of those companies around San Francisco most of them and efficiency usually means a savory business unit as every department or country has his own specific needs by a specific solution for them so imagine yourself working in a data center full of silos with many different Hardware operating systems different languages and complex interfaces to communicate among them you know not always documented what really never documented so your life your life in is not easy you know in this scenario are well there's no room for innovation so what's been or or strategy be BES ready to move forward in this new digital world well we've chosen a different approach which is quite simple is to replace all local proprietary system by a global platform based on on open source with three main goals you know the first one is reduce the average transaction cost to one-third the second one is increase or developers productivity five times you know and the third is enable or delete the business be able to deliver solutions of three times faster so you're not quite easy Wow and everything with the same reliability as on security standards as we've got today Wow that is an extraordinary set of objectives and I will say their world on the path of making that successful which is just amazing yeah okay this is a long journey sometimes a tough journey you know to be honest so we decided to partnership with the with the best companies in there in the world and world record we think rate cut is one of these companies so we think or your values and your knowledge is critical for BBVA and well as I mentioned before our collaboration started some time ago you know and just an example in today in BBVA a Spain being one of the biggest banks in in the country you know and using red hat technology of course our firm and fronting architecture you know for mobile and internet channels runs the ninety five percent of our customers request this is approximately 3,000 requests per second and our back in architecture execute 70 millions of business transactions a day this is almost a 50% of total online transactions executed in the country so it's all running yes running I hope so you check for you came on stage it's I'll be flying you know okay good there's no wood up here to knock on it's been a really great partnership it's been a pleasure yeah thank you so much for being here thank you thank you [Applause] I do love that story because again so much of what we talk about when we when we talk about preparing for digital is a processed solution and again things like agile and DevOps and modular izing components of work but this idea of thinking about platforms broadly and how they can run anywhere and actually delivering it delivering at a scale it's just a phenomenal project and experience and in the progress they've made it's a great team so next up we have two organizations that have done an exceptional job of enabling their people with the right information and the tools they need to be successful you know in both of these cases these are organizations who are under constant change and so leveraging the power of open-source to help them build these tools to enable and you'll see it the size and the scale of these in two very very different contexts it's great to see and so I'd like to welcome on stage Oh smart alza' with dnm and David Abraham's with IAG [Music] Oh smart welcome thank you so much for being here Dave great to see you thank you appreciate you being here and congratulations to you both on winning the Innovation Awards thank you so Omar I really found your story fascinating and how you're able to enable your people with data which is just significantly accelerated the pace with which they can make decisions and accelerate your ability to to act could you tell us a little more about the project and then what you're doing Jim and Tina when the muchisimas gracias por ever say interesado pono true projecto [Music] encargado registry controller las entradas a leda's persona por la Frontera argentina yo sé de dos siento treinta siete puestos de contrôle tienen lo largo de la Frontera tanto area the restreamer it EEMA e if looool in dilute ammonia shame or cinta me Jonas the tránsito sacra he trod on in another Fronteras dingus idea idea de la Magneto la cual estamos hablando la Frontera cantina tienen extension the kin same in kilo metros esto es el gada mint a maje or allege Estancia kaeun a poor carretera a la co de mexico con el akka a direction emulation s 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calidad de vida de atras de mettre personas SI y meet our que el delito perform a trois Natura from Dana's Argentine sigue siendo en favor de esto SI temes uno de los países mess Alberto's Allah immigration en Latin America yah hora con una plataforma mas segunda first of all I want to thank you for the interest is played for our project the National migration administration or diem records the entry and exit of people on the Argentine territory it grants residents permits to foreigners who wish to live in our country through 237 entry points land air border sea and river ways Jim dnm registered over 80 million transits throughout last year Argentine borders cover about 15,000 kilometers just our just to give you an idea of the magnitude of our borders this is greater than the distance on a highway between Mexico City and Alaska our department applies the mechanisms that prevent the entry and residents of people involved in crimes like terrorism trafficking of persons weapons drugs and others in 2016 we shifted to a more preventive and predictive paradigm that is how Sam's the system for migration analysis was created with red hats great assistance and support this allowed us to tackle the challenge of integrating multiple and varied issues legal issues police databases national and international security organizations like Interpol API advanced passenger information and PNR passenger name record this involved starting private cloud with OpenShift Rev data virtualization cloud forms and fuse that were the basis to develop Sam and implementing machine learning models and artificial intelligence our analysts consulted a number of systems and other manual files before 2016 4 days for each person entering or leaving the country so this has allowed us to optimize our decisions making them in real time each time Sam is consulted it processes patterns of over two billion data entries Sam's aim is to improve the quality of life of our citizens and visitors making sure that crime doesn't pierce our borders in an environment of analytic evolution and constant improvement in essence Sam contributes toward Argentina being one of the leaders in Latin America in terms of immigration with our new system great thank you and and so Dave tell us a little more about the insurance industry and the challenges in the EU face yeah sure so you know in the insurance industry it's a it's been a bit sort of insulated from a lot of major change in disruption just purely from the fact that it's highly regulated and the cost of so that the barrier to entry is quite high in fact if you think about insurance you know you have to have capital reserves to protect against those major events like floods bush fires and so on but the whole thing is a lot of change there's come in a really rapid pace I'm also in the areas of customer expectations you know customers and now looking and expecting for the same levels of flexibility and convenience that they would experience with more modern and new startups they're expecting out of the older institutions like banks and insurance companies like us so definitely expecting the industry to to be a lot more adaptable and to better meet their needs I think the other aspect of it really is in the data the data area where I think that the donor is now creating a much more significant connection between organizations in a car summers especially when you think about the level of devices that are now enabled and the sheer growth of data that's that that's growing at exponential rates so so that the impact then is that the systems that we used to rely on are the technology we used to rely on to be able to handle that kind of growth no longer keeps up and is able to to you know build for the future so we need to sort of change that so what I G's really doing is transform transforming the organization to become a lot more efficient focus more on customers and and really set ourselves up to be agile and adaptive and so ya know as part of your Innovation Award that the specific set of projects you tied a huge amount of different disparate systems together and with M&A and other you have a lot to do there to you tell us a little more about kind of how you're able to better respond to customer needs by being able to do that yeah no you're right so we've we've we're nearly a hundred year old company that's grown from lots of merger and acquisition and just as a result of that that means that data's been sort of spread out and fragmented across multiple brands and multiple products and so the number one sort of issue and problem that we were hearing was that it was too hard to get access to data and it's highly complicated which is not great from a company from our perspective really because because we are a data company right that's what we do we we collect data about people what they what's important to them what they value and the environment in which they live so that we can understand that risk and better manage and protect those people so what we're doing is we're trying to make and what we have been doing is making data more open and accessible and and by that I mean making data more of easily available for people to use it to make decisions in their day-to-day activity and to do that what we've done is built a single data platform across the group that unifies the data into a single source of truth that we can then build on top of that single views of customers for example that puts the right information into the into the hands of the people that need it the most and so now why does open source play such a big part in doing that I know there are a lot of different solutions that could get you there sure well firstly I think I've been sauce has been k2 these and really it's been key because we've basically started started from scratch to build this this new next-generation data platform based on entirely open-source you know using great components like Kafka and Postgres and airflow and and and and and then fundamentally building on top of red Red Hat OpenStack right to power all that and they give us the flexibility that we need to be able to make things happen much faster for example we were just talking to the pivotal guys earlier this week here and some of the stuff that we're doing they're they're things quite interesting innovative writes even sort of maybe first in the world where we've taken the older sort of appliance and dedicated sort of massive parallel processing unit and ported that over onto red Red Hat OpenStack right which is now giving us a lot more flexibility for scale in a much more efficient way but you're right though that we've come from in the past a more traditional approach to to using vendor based technology right which was good back then when you know technology solutions could last for around 10 years or so on and and that was fine but now that we need to move much faster we've had to rethink that and and so our focus has been on using you know more commoditized open source technology built by communities to give us that adaptability and sort of remove the locking in there any entrenchment of technology so that's really helped us but but I think that the last point that's been really critical to us is is answering that that concern and question about ongoing support and maintenance right so you know in a regular environment the regulator is really concerned about anything that could fundamentally impact business operation and and so the question is always about what happens when something goes wrong who's going to be there to support you which is where the value of the the partnership we have with Red Hat has really come into its own right and what what it's done is is it's actually giving us the best of both worlds a means that we can we can leverage and use and and and you know take some of the technology that's being developed by great communities in the open source way but also partner with a trusted partner in red had to say you know they're going to stand behind that community and provide that support when we needed the most so that's been the kind of the real value out of that partnership okay well I appreciate I love the story it's how do you move quickly leverage the power community but do it in a safe secure way and I love the idea of your literally empowering people with machine learning and AI at the moment when they need it it's just an incredible story so thank you so much for being here appreciate it thank you [Applause] you know again you see in these the the importance of enabling people with data and in an old-world was so much data was created with a system in mind versus data is a separate asset that needs to be available real time to anyone is a theme we hear over and over and over again and so you know really looking at open source solutions that allow that flexibility and keep data from getting locked into proprietary silos you know is a theme that we've I've heard over and over over the past year with many of our customers so I love logistics I'm a geek that way I come from that background in the past and I know that running large complex operations requires flawless execution and that requires great data and we have two great examples today around how to engage own organizations in new and more effective ways in the case of lufthansa technik literally IT became the business so it wasn't enabling the business it became the business offering and importantly went from idea to delivery to customers in a hundred days and so this theme of speed and the importance of speed it's a it's a great story you'll hear more about and then also at UPS UPS again I talked a little earlier about IT used to be kind of the long pole in the tent the thing that was slow moving because of the technology but UPS is showing that IT can actually drive the business and the cadence of business even faster by demonstrating the power and potential of technology to engage in this case hundreds of thousands of people to make decisions real-time in the face of obviously constant change around weather mechanicals and all the different things that can happen in a large logistics operation like that so I'd like to welcome on stage to be us more from Lufthansa Technik and Nick Castillo from ups to be us welcome thank you for being here Nick thank you thank you Jim and congratulations on your Innovation Awards oh thank you it's a great honor so to be us let's start with you can you tell us a little bit more about what a viet are is yeah avatars are a digital platform offering features like aircraft condition analytics reliability management and predictive maintenance and it helps airlines worldwide to digitize and improve their operations so all of the features work and can be used separately or generate even more where you burn combined and finally we decided to set up a viet as an open platform that means that we avoid the whole aviation industry to join the community and develop ideas on our platform and to be as one of things i found really fascinating about this is that you had a mandate to do this at a hundred days and you ultimately delivered on it you tell us a little bit about that i mean nothing in aviation moves that fast yeah that's been a big challenge so in the beginning of our story the Lufthansa bot asked us to develop somehow digital to win of an aircraft within just hundred days and to deliver something of value within 100 days means you cannot spend much time and producing specifications in terms of paper etc so for us it was pretty clear that we should go for an angel approach and immediately start and developing ideas so we put the best experts we know just in one room and let them start to work and on day 2 I think we already had the first scribbles for the UI on day 5 we wrote the first lines of code and we were able to do that because it has been a major advantage for us to already have four technologies taken place it's based on open source and especially rated solutions because we did not have to waste any time setting up the infrastructure and since we wanted to get feedback very fast we were certainly visited an airline from the Lufthansa group already on day 30 and showed them the first results and got a lot of feedback and because from the very beginning customer centricity has been an important aspect for us and changing the direction based on customer feedback has become quite normal for us over time yeah it's an interesting story not only engaging the people internally but be able to engage with a with that with a launch customer like that and get feedback along the way as it's great thing how is it going overall since launch yeah since the launch last year in April we generated much interest in the industry as well from Airlines as from competitors and in the following month we focused on a few Airlines which had been open minded and already advanced in digital activities and we've got a lot of feedback by working with them and we're able to improve our products by developing new features for example we learned that data integration can become quite complex in the industry and therefore we developed a new feature called quick boarding allowing Airlines to integrate into the via table platform within one day using a self-service so and currently we're heading for the next steps beyond predictive maintenance working on process automation and prescriptive prescriptive maintenance because we believe prediction without fulfillment still isn't enough it really is a great example of even once you're out there quickly continuing to innovate change react it's great to see so Nick I mean we all know ups I'm still always blown away by the size and scale of the company and the logistics operations that you run you tell us a little more about the project and what we're doing together yeah sure Jim and you know first of all I think I didn't get the sportcoat memo I think I'm the first one up here today with a sport coat but you know first on you know on behalf of the 430,000 ups was around the world and our just world-class talented team of 5,000 IT professionals I have to tell you we're humbled to be one of this year's red hat Innovation Award recipients so we really appreciate that you know as a global logistics provider we deliver about 20 million packages each day and we've got a portfolio of technologies both operational and customer tech and another customer facing side the power what we call the UPS smart logistics network and I gotta tell you innovations in our DNA technology is at the core of everything we do you know from the ever familiar first and industry mobile platform that a lot of you see when you get delivered a package which we call the diad which believe it or not we delivered in 1992 my choice a data-driven solution that drives over 40 million of our my choice customers I'm whatever you know what this is great he loves logistics he's a my choice customer you could be one too by the way there's a free app in the App Store but it provides unmatched visibility and really controls that last mile delivery experience so now today we're gonna talk about the solution that we're recognized for which is called site which is part of a much greater platform that we call edge which is transforming how our package delivery teams operate providing them real-time insights into our operations you know this allows them to make decisions based on data from 32 disparate data sources and these insights help us to optimize our operations but more importantly they help us improve the delivery experience for our customers just like you Jim you know on the on the back end is Big Data and it's on a large scale our systems are crunching billions of events to render those insights on an easy-to-use mobile platform in real time I got to tell you placing that information in our operators hands makes ups agile and being agile being able to react to changing conditions as you know is the name of the game in logistics now we built edge in our private cloud where Red Hat technologies play a very important role as part of our overage overarching cloud strategy and our migration to agile and DevOps so it's it's amazing it's amazing the size and scale so so you have this technology vision around engaging people in a more effect way those are my word not yours but but I'd be at that's how it certainly feels and so tell us a little more about how that enables the hundreds of thousands people to make better decisions every day yep so you know we're a people company and the edge platform is really the latest in a series of solutions to really empower our people and really power that smart logistics network you know we've been deploying technology believe it or not since we founded the company in 1907 we'll be a hundred and eleven years old this August it's just a phenomenal story now prior to edge and specifically the syphon ishutin firm ation from a number of disparate systems and reports they then need to manually look across these various data sources and and frankly it was inefficient and prone to inaccuracy and it wasn't really real-time at all now edge consumes data as I mentioned earlier from 32 disparate systems it allows our operators to make decisions on staffing equipment the flow of packages through the buildings in real time the ability to give our people on the ground the most up-to-date data allows them to make informed decisions now that's incredibly empowering because not only are they influencing their local operations but frankly they're influencing the entire global network it's truly extraordinary and so why open source and open shift in particular as part of that solution yeah you know so as I mentioned Red Hat and Red Hat technology you know specifically open shift there's really core to our cloud strategy and to our DevOps strategy the tools and environments that we've partnered with Red Hat to put in place truly are foundational and they've fundamentally changed the way we develop and deploy our systems you know I heard Jose talk earlier you know we had complex solutions that used to take 12 to 18 months to develop and deliver to market today we deliver those same solutions same level of complexity in months and even weeks now openshift enables us to container raise our workloads that run in our private cloud during normal operating periods but as we scale our business during our holiday peak season which is a very sure window about five weeks during the year last year as a matter of fact we delivered seven hundred and sixty-two million packages in that small window and our transactions our systems they just spiked dramatically during that period we think that having open shift will allow us in those peak periods to seamlessly move workloads to the public cloud so we can take advantage of burst capacity economically when needed and I have to tell you having this flexibility I think is key because you know ultimately it's going to allow us to react quickly to customer demands when needed dial back capacity when we don't need that capacity and I have to say it's a really great story of UPS and red hat working you together it really is a great story is just amazing again the size and scope but both stories here a lot speed speed speed getting to market quickly being able to try things it's great lessons learned for all of us the importance of being able to operate at a fundamentally different clock speed so thank you all for being here very much appreciated congratulate thank you [Applause] [Music] alright so while it's great to hear from our Innovation Award winners and it should be no surprise that they're leading and experimenting in some really interesting areas its scale so I hope that you got a chance to learn something from these interviews you'll have an opportunity to learn more about them you'll also have an opportunity to vote on the innovator of the year you can do that on the Red Hat summit mobile app or on the Red Hat Innovation Awards homepage you can learn even more about their stories and you'll have a chance to vote and I'll be back tomorrow to announce the the summit winner so next I like to spend a few minutes on talking about how Red Hat is working to catalyze our customers efforts Marko bill Peter our senior vice president of customer experience and engagement and John Alessio our vice president of global services will both describe areas in how we are working to configure our own organization to effectively engage with our customers to use open source to help drive their success so with that I'd like to welcome marquel on stage [Music] good morning good morning thank you Jim so I want to spend a few minutes to talk about how we are configured how we are configured towards your success how we enable internally as well to work towards your success and actually engage as well you know Paul yesterday talked about the open source culture and our open source development net model you know there's a lot of attributes that we have like transparency meritocracy collaboration those are the key of our culture they made RedHat what it is today and what it will be in the future but we also added our passion for customer success to that let me tell you this is kind of the configuration from a cultural perspective let me tell you a little bit on what that means so if you heard the name my organization is customer experience and engagement right in the past we talked a lot about support it's an important part of the Red Hat right and how we are configured we are configured probably very uniquely in the industry we put support together we have product security in there we add a documentation we add a quality engineering into an organization you think there's like wow why are they doing it we're also running actually the IT team for actually the product teams why are we doing that now you can imagine right we want to go through what you see as well right and I'll give you a few examples on how what's coming out of this configuration we invest more and more in testing integration and use cases which you are applying so you can see it between the support team experiencing a lot what you do and actually changing our test structure that makes a lot of sense we are investing more and more testing outside the boundaries so not exactly how things must fall by product management or engineering but also how does it really run in an environment that you operate we run complex setups internally right taking openshift putting in OpenStack using software-defined storage underneath managing it with cloud forms managing it if inside we do that we want to see how that works right we are reshaping documentation console to kind of help you better instead of just documenting features and knobs as in how can how do you want to achieve things now part of this is the configuration that are the big part of the configuration is the voice of the customer to listen to what you say I've been here at Red Hat a few years and one of my passion has always been really hearing from customers how they do it I travel constantly in the world and meet with customers because I want to know what is really going on we use channels like support we use channels like getting from salespeople the interaction from customers we do surveys we do you know we interact with our people to really hear what you do what we also do what maybe not many know and it's also very unique in the industry we have a webpage called you asked reacted we show very transparently you told us this is an area for improvement and it's not just in support it's across the company right build us a better web store build us this we're very transparent about Hades improvements we want to do with you now if you want to be part of the process today go to the feedback zone on the next floor down and talk to my team I might be there as well hit me up we want to hear the feedback this is how we talk about configuration of the organization how we are configured let me go to let me go to another part which is innovation innovation every day and that in my opinion the enable section right we gotta constantly innovate ourselves how do we work with you how do we actually provide better value how do we provide faster responses in support this is what we would I say is is our you know commitment to innovation which is the enabling that Jim talked about and I give you a few examples which I'm really happy and it kind of shows the open source culture at Red Hat our commitment is for innovation I'll give you good example right if you have a few thousand engineers and you empower them you kind of set the business framework as hey this is an area we got to do something you get a lot of good IDs you get a lot of IDs and you got a shape an inter an area that hey this is really something that brings now a few years ago we kind of said or I say is like based on a lot of feedback is we got to get more and more proactive if you customers and so I shaped my team and and I shaped it around how can we be more proactive it started very simple as in like from kbase articles or knowledgebase articles in getting started guys then we started a a tool that we put out called labs you've probably seen them if you're on the technical side really taking small applications out for you to kind of validate is this configured correctly stat configure there was the start then out of that the ideas came and they took different turns and one of the turns that we came out was right at insights that we launched a few years ago and did you see the demo yesterday that in Paul's keynote that they showed how something was broken with one the data centers how it was applied to fix and how has changed this is how innovation really came from the ground up from the support side and turned into something really a being a cornerstone of our strategy and we're keeping it married from the day to day work right you don't want to separate this you want to actually keep that the data that's coming from the support goes in that because that's the power that we saw yesterday in the demo now innovation doesn't stop when you set the challenge so we did the labs we did the insights we just launched a solution engine called solution engine another thing that came out of that challenge is in how do we break complex issues down that it's easier for you to find a solution quicker it's one example but we're also experimenting with AI so insights uses AI as you probably heard yesterday we also use it internally to actually drive faster resolution we did in one case with a a our I bought basically that we get to 25% faster resolution on challenges that you have the beauty for you obviously it's well this is much faster 10% of all our support cases today are supported and assisted by an AI now I'll give you another example of just trying to tell you the innovation that comes out if you configure and enable the team correctly kbase articles are knowledgebase articles we q8 thousands and thousands every year and then I get feedback as and while they're good but they're in English as you can tell my English is perfect so it's not no issue for that but for many of you is maybe like even here even I read it in Japanese so we actually did machine translation because it's too many that we can do manually the using machine translation I can tell it's a funny example two weeks ago I tried it I tried something from English to German I looked at it the German looked really bad I went back but the English was bad so it really translates one to one actually what it does but it's really cool this is innovation that you can apply and the team actually worked on this and really proud on that now the real innovation there is not these tools the real innovation is that you can actually shape it in a way that the innovation comes that you empower the people that's the configure and enable and what I think is all it's important this don't reinvent the plumbing don't start from scratch use systems like containers on open shift to actually build the innovation in a smaller way without reinventing the plumbing you save a lot of issues on security a lot of issues on reinventing the wheel focus on that that's what we do as well if you want to hear more details again go in the second floor now let's talk about the engage that Jim mentioned before what I translate that engage is actually engaging you as a customer towards your success now what does commitment to success really mean and I want to reflect on that on a traditional IT company shows up with you talk the salesperson solution architect works with you consulting implements solution it comes over to support and trust me in a very traditional way the support guy has no clue what actually was sold early on it's what happens right and this is actually I think that red had better that we're not so silent we don't show our internal silos or internal organization that much today we engage in a way it doesn't matter from which team it comes we have a better flow than that you deserve how the sausage is made but we can never forget what was your business objective early on now how is Red Hat different in this and we are very strong in my opinion you might disagree but we are very strong in a virtual accounting right really putting you in the middle and actually having a solution architect work directly with support or consulting involved and driving that together you can also help us in actually really embracing that model if that's also other partners or system integrators integrate put yourself in the middle be around that's how we want to make sure that we don't lose sight of the original business problem trust me reducing the hierarchy or getting rid of hierarchy and bureaucracy goes a long way now this is how we configured this is how we engage and this is how we are committed to your success with that I'm going to introduce you to John Alessio that talks more about some of the innovation done with customers thank you [Music] good morning I'm John Alessio I'm the vice president of Global Services and I'm delighted to be with you here today I'd like to talk to you about a couple of things as it relates to what we've been doing since the last summit in the services organization at the core of everything we did it's very similar to what Marco talked to you about our number one priority is driving our customer success with red hat technology and as you see here on the screen we have a number of different offerings and capabilities all the way from training certification open innovation labs consulting really pairing those capabilities together with what you just heard from Marco in the support or cee organization really that's the journey you all go through from the beginning of discovering what your business challenge is all the way through designing those solutions and deploying them with red hat now the highlight like to highlight a few things of what we've been up to over the last year so if I start with the training and certification team they've been very busy over the last year really updating enhancing our curriculum if you haven't stopped by the booth there's a preview for new capability around our learning community which is a new way of learning and really driving that enable meant in the community because 70% of what you need to know you learned from your peers and so it's a very key part of our learning strategy and in fact we take customer satisfaction with our training and certification business very seriously we survey all of our students coming out of training 93% of our students tell us they're better prepared because of red hat training and certification after Weeds they've completed the course we've updated the courses and we've trained well over a hundred and fifty thousand people over the last two years so it's a very very key part of our strategy and that combined with innovation labs and the consulting operation really drive that overall journey now we've been equally busy in enhancing the system of enablement and support for our business partners another very very key initiative is building out the ecosystem we've enhanced our open platform which is online partner enablement network we've added new capability and in fact much of the training and enablement that we do for our internal consultants our deal is delivered through the open platform now what I'm really impressed with and thankful for our partners is how they are consuming and leveraging this material we train and enable for sales for pre-sales and for delivery and we're up over 70% year in year in our partners that are enabled on RedHat technology let's give our business partners a round of applause now one of our offerings Red Hat open innovation labs I'd like to talk a bit more about and take you through a case study open innovation labs was created two years ago it's really there to help you on your journey in adopting open source technology it's an immersive experience where your team will work side-by-side with Red Hatters to really propel your journey forward in adopting open source technology and in fact we've been very busy since the summit in Boston as you'll see coming up on the screen we've completed dozens of engagements leveraging our methods tools and processes for open innovation labs as you can see we've worked with large and small accounts in fact if you remember summit last year we had a European customer easier AG on stage which was a startup and we worked with them at the very beginning of their business to create capabilities in a very short four-week engagement but over the last year we've also worked with very large customers such as Optim and Delta Airlines here in North America as well as Motability operations in the European arena one of the accounts I want to spend a little bit more time on is Heritage Bank heritage Bank is a community owned bank in Toowoomba Australia their challenge was not just on creating new innovative technology but their challenge was also around cultural transformation how to get people to work together across the silos within their organization we worked with them at all levels of the organization to create a new capability the first engagement went so well that they asked us to come in into a second engagement so I'd like to do now is run a video with Peter lock the chief executive officer of Heritage Bank so he can take you through their experience Heritage Bank is one of the country's oldest financial institutions we have to be smarter we have to be more innovative we have to be more agile we had to change we had to find people to help us make that change the Red Hat lab is the only one that truly helps drive that change with a business problem the change within the team is very visible from the start to now we've gone from being separated to very single goal minded seeing people that I only ever seen before in their cubicles in the room made me smile programmers in their thinking I'm now understanding how the whole process fits together the productivity of IT will change and that is good for our business that's really the value that were looking for the Red Hat innovation labs for us were a really great experience I'm not interested in running an organization I'm interested in making a great organization to say I was pleasantly surprised by it is an understatement I was delighted I love the quote I was delighted makes my heart warm every time I see that video you know since we were at summit for those of you who are with us in Boston some of you went on our hardhat tours we've opened three physical facilities here at Red Hat where we can conduct red head open Innovation Lab engagements Singapore London and Boston were all opened within the last physical year and in fact our site in Boston is paired with our world-class executive briefing center as well so if you haven't been there please do check it out I'd like to now talk to you a bit about a very special engagement that we just recently completed we just recently completed an engagement with UNICEF the United Nations Children's Fund and the the purpose behind this engagement was really to help UNICEF create an open-source platform that marries big data with social good the idea is UNICEF needs to be better prepared to respond to emergency situations and as you can imagine emergency situations are by nature unpredictable you can't really plan for them they can happen anytime anywhere and so we worked with them on a project that we called school mapping and the idea was to provide more insights so that when emergency situations arise UNICEF could do a much better job in helping the children in the region and so we leveraged our Red Hat open innovation lab methods tools processes that you've heard about just like we did at Heritage Bank and the other accounts I mentioned but then we also leveraged Red Hat software technologies so we leveraged OpenShift container platform we leveraged ansible automation we helped the client with a more agile development approach so they could have releases much more frequently and continue to update this over time we created a continuous integration continuous deployment pipeline we worked on containers and container in the application etc with that we've been able to provide a platform that is going to allow for their growth to better respond to these emergency situations let's watch a short video on UNICEF mission of UNICEF innovation is to apply technology to the world's most pressing problems facing children data is changing the landscape of what we do at UNICEF this means that we can figure out what's happening now on the ground who it's happening to and actually respond to it in much more of a real-time manner than we used to be able to do we love working with open source communities because of their commitment that we should be doing good for the world we're actually with red hat building a sandbox where universities or other researchers or data scientists can connect and help us with our work if you want to use data for social good there's so many groups out there that really need your help and there's so many ways to get involved [Music] so let's give a very very warm red hat summit welcome to Erica kochi co-founder of unicef innovation well Erica first of all welcome to Red Hat summit thanks for having me here it's our pleasure and thank you for joining us so Erica I've just talked a bit about kind of what we've been up to and Red Hat services over the last year we talked a bit about our open innovation labs and we did this project the school mapping project together our two teams and I thought the audience might find it interesting from your point of view on why the approach we use in innovation labs was such a good fit for the school mapping project yeah it was a great fit for for two reasons the first is values everything that we do at UNICEF innovation we use open source technology and that's for a couple of reasons because we can take it from one place and very easily move it to other countries around the world we work in 190 countries so that's really important for us not to be able to scale things also because it makes sense we can get we can get more communities involved in this and look not just try to do everything by ourselves but look much open much more openly towards the open source communities out there to help us with our work we can't do it alone yeah and then the second thing is methodology you know the labs are really looking at taking this agile approach to prototyping things trying things failing trying again and that's really necessary when you're developing something new and trying to do something new like mapping every school in the world yeah very challenging work think about it 190 countries Wow and so the open source platform really works well and then the the rapid prototyping was really a good fit so I think the audience might find it interesting on how this application and this platform will help children in Latin America so in a lot of countries in Latin America and many countries throughout the world that UNICEF works in are coming out of either decades of conflict or are are subject to natural disasters and not great infrastructure so it's really important to a for us to know where schools are where communities are well where help is needed what's connected what's not and using a overlay of various sources of data from poverty mapping to satellite imagery to other sources we can really figure out what's happening where resources are where they aren't and so we can plan better to respond to emergencies and to and to really invest in areas that are needed that need that investment excellent excellent it's quite powerful what we were able to do in a relatively short eight or nine week engagement that our two teams did together now many of your colleagues in the audience are using open source today looking to expand their use of open source and I thought you might have some recommendations for them on how they kind of go through that journey and expanding their use of open source since your experience at that yeah for us it was it was very much based on what's this gonna cost we have limited resources and what's how is this gonna spread as quickly as possible mm-hmm and so we really asked ourselves those two questions you know about 10 years ago and what we realized is if we are going to be recommending technologies that governments are going to be using it really needs to be open source they need to have control over it yeah and they need to be working with communities not developing it themselves yeah excellent excellent so I got really inspired with what we were doing here in this project it's one of those you know every customer project is really interesting to me this one kind of pulls a little bit at your heartstrings on what the real impact could be here and so I know some of our colleagues here in the audience may want to get involved how can they get involved well there's many ways to get involved with the other UNICEF or other groups out there you can search for our work on github and there are tasks that you can do right now if and if you're looking for to do she's got work for you and if you want sort of a more a longer engagement or a bigger engagement you can check out our website UNICEF stories org and you can look at the areas you might be interested in and contact us we're always open to collaboration excellent well Erica thank you for being with us here today thank you for the great project we worked on together and have a great summer thank you for being give her a round of applause all right well I hope that's been helpful to you to give you a bit of an update on what we've been focused on in global services the message I'll leave with you is our top priority is customer success as you heard through the story from UNICEF from Heritage Bank and others we can help you innovate where you are today I hope you have a great summit and I'll call out Jim Whitehurst thank you John and thank you Erica that's really an inspiring story we have so many great examples of how individuals and organizations are stepping up to transform in the face of digital disruption I'd like to spend my last few minutes with one real-world example that brings a lot of this together and truly with life-saving impact how many times do you think you can solve a problem which is going to allow a clinician to now save the life I think the challenge all of his physicians are dealing with is data overload I probably look at over 100,000 images in a day and that's just gonna get worse what if it was possible for some computer program to look at these images with them and automatically flag images that might deserve better attention Chris on the surface seems pretty simple but underneath Chris has a lot going on in the past year I've seen Chris Foreman community and a space usually dominated by proprietary software I think Chris can change medicine as we know it today [Music] all right with that I'd like to invite on stage dr. Ellen grant from Boston Children's Hospital dr. grant welcome thank you for being here so dr. grant tell me who is Chris Chris does a lot of work for us and I think Chris is making me or has definitely the potential to make me a better doctor Chris helps us take data from our archives in the hospital and port it to wrap the fastback ends like the mass up and cloud to do rapid data processing and provide it back to me in any format on a desktop an iPad or an iPhone so it it basically brings high-end data analysis right to me at the bedside and that's been a barrier that I struggled with years ago to try to break down so that's where we started with Chris is to to break that barrier between research that occurred on a timeline of days to weeks to months to clinical practice which occurs in the timeline of seconds to minutes well one of things I found really fascinating about this story RedHat in case you can't tell we're really passionate about user driven innovation is this is an example of user driven innovation not directly at a technology company but in medicine excuse me can you tell us just a little bit about the genesis of Chris and how I got started yeah Chris got started when I was running a clinical division and I was very frustrated with not having the latest image analysis tools at my fingertips while I was on clinical practice and I would have to on the research so I could go over and you know do line code and do the data analysis but if I'm always over in clinical I kept forgetting how to do those things and I wanted to have all those innovations that my fingertips and not have to remember all the computer science because I'm a physician not like a better scientist so I wanted to build a platform that gave me easy access to that back-end without having to remember all the details and so that's what Chris does for us is brings allowed me to go into the PAC's grab a dataset send it to a computer and back in to do the analysis and bring it back to me without having to worry about where it was or how it got there that's all involved in the in the platform Chris and why not just go to a vendor and ask them to write a piece of software for you to do that yeah we thought about that and we do a lot of technical innovations and we always work with the experts so we wanted to work with if I'm going to be able to say an optical device I'm going to work with the optical engineers or an EM our system I'm going to work with em our engineers so we wanted to work with people who really knew or the plumbers so to speak of the software in industry so we ended up working with the massive point cloud for the platform and the distributed systems in Red Hat as the infrastructure that's starting to support Chris and that's been actually a really incredible journey for us because medical ready medical softwares not typically been a community process and that's something that working with dan from Red Hat we learned a lot about how to participate in an open community and I think our team has grown a lot as a result of that collaboration and I know you we've talked about in the past that getting this data locked into a proprietary system you may not be able to get out there's a real issue can you talk about the importance of open and how that's worked in the process yeah and I think for the medical community and I find this resonates with other physicians as well too is that it's medical data we want to continue to own and we feel very awkward about giving it to industry so we would rather have our data sitting in an open cloud like the mass open cloud where we can have a data consortium that oversees the data governance so that we're not giving our data way to somebody else but have a platform that we can still keep a control of our own data and I think it's going to be the future because we're running of a space in the hospital we generate so much data and it's just going to get worse as I was mentioning and all the systems run faster we get new devices so the amount of data that we have to filter through is just astronomically increasing so we need to have resources to store and compute on such large databases and so thinking about where this could go I mean this is a classic feels like an open-source project it started really really small with a originally modest set of goals and it's just kind of continue to grow and grow and grow it's a lot like if yes leanest torval Linux would be in 1995 you probably wouldn't think it would be where it is now so if you dream with me a little bit where do you think this could possibly go in the next five years ten years what I hope it'll do is allow us to break down the silos within the hospital because to do the best job at what we physicians do not only do we have to talk and collaborate together as individuals we have to take the data each each community develops and be able to bring it together so in other words I need to be able to bring in information from vital monitors from mr scans from optical devices from genetic tests electronic health record and be able to analyze on all that data combined so ideally this would be a platform that breaks down those information barriers in a hospital and also allows us to collaborate across multiple institutions because many disorders you only see a few in each hospital so we really have to work as teams in the medical community to combine our data together and also I'm hoping that and we even have discussions with people in the developing world because they have systems to generate or to got to create data or say for example an M R system they can't create data but they don't have the resources to analyze on it so this would be a portable for them to participate in this growing data analysis world without having to have the infrastructure there and be a portal into our back-end and we could provide the infrastructure to do the data analysis it really is truly amazing to see how it's just continued to grow and grow and expand it really is it's a phenomenal story thank you so much for being here appreciate it thank you [Applause] I really do love that story it's a great example of user driven innovation you know in a different industry than in technology and you know recognizing that a clinicians need for real-time information is very different than a researchers need you know in projects that can last weeks and months and so rather than trying to get an industry to pivot and change it's a great opportunity to use a user driven approach to directly meet those needs so we still have a long way to go we have two more days of the summit and as I said yesterday you know we're not here to give you all the answers we're here to convene the conversation so I hope you will have an opportunity today and tomorrow to meet some new people to share some ideas we're really really excited about what we can all do when we work together so I hope you found today valuable we still have a lot more happening on the main stage as well this afternoon please join us back for the general session it's a really amazing lineup you'll hear from the women and opensource Award winners you'll also hear more about our collab program which is really cool it's getting middle school girls interested in open sourcing coding and so you'll have an opportunity to see some people involved in that you'll also hear from the open source Story speakers and you'll including in that you will see a demo done by a technologist who happens to be 11 years old so really cool you don't want to miss that so I look forward to seeing you then this afternoon thank you [Applause]

(upbeat music) >> Narrator: Live from New Orleans, Louisiana, it's theCUBE! Covering .NEXT Conference 2018. Brought to you by Nutanix. >> Welcome back to theCUBE's coverage here from Nutanix .Next 2018. I'm Stu Miniman, with my cohost, Keith Townsend. Happy to welcome back to the program, Ben Gibson, who's the Chief Marketing Officer at Nutanix. Ben, nice to have you on your third time now on theCUBE. Couple more, you got one of those VIP badges on our website. (Ben laughs) >> It's getting to be a really good habit. I'm really enjoying it. Thanks for having me here. >> Well, thank you. And You and Keith share something in common. This is the first time you've been to a .NEXT conference. >> Indeed. >> So, I've had the pleasure of actually being at every single one of the US and Europeans. Haven't done the .NEXT On Tours. But give us your impression so far as to, you're heavily involved, but of the show. >> You know, I have to say it's lived up to all my expectations and more. I talked about this, this morning. The first .NEXT back in 2015. You were there, it was in Miami. We had a little over 800 people. Today, we had 5,500 registered to be here. And it's a thrill to see that many of our best customers and partners come together. And for me too being new to this company, I've been here almost six months now. It really brings home the level of energy, and loyalty in excitement that we've engendered within our customer base. It's palpable. And what better way to experience that live than here in New Orleans? >> Yeah, as we say, a lot of shows like this, there sometimes it's like well, I've got all the true believers here. But, you know, there's good customers here. They're poking, they're prodding, they're trying. But they are big fans of the product. Any kind of key things, interactions, you've had so far? >> Yeah, I've had a lot of conversations with customers here. And I am picking up on some common themes. One of them is moving more and more of tier-one applications onto Nutanix. And that's very exciting for us. You know, in our early days, it was all about VDI and that was the sweet spot workload. And now, we're starting to see more and more Oracle and SAP, and other major tier-one applications, being deployed over Nutanix. And customers are excited to do that because we've made things so much radically simple for them in terms of the infrastructure that is being run upon, (laughs), so to speak right? And so that's certainly a key theme that we're hearing. >> Yeah, one of the things that I took out of your opening at the keynote is that we talk about how much change there is in the industry, but in some ways it's a challenge, but another way it's really an opportunity for customers to go through their transformations, change their businesses, and prove their careers. What's Nutanix's positioning? >> Yeah, first of all, my first and Nutanix's first position on this is .NEXT. We see as a place where IT professionals can come, they can learn, they can share, get certified; but also help them position themselves for all this change that's happening in the industry. Public cloud, right? If you're managing and building infrastructure or you're renting it. And we think there's a really interesting opportunity for those who have built, to become those who have advise and lead. As everything moves to be a more hybrid cloud scenario out there. And so, I think that's the opportunity that we have and this show is about how do we empower our attendees to go back out and be that strategic counselor. To build the right type of data center the way they've always wanted to do. And, be that broker almost, between different clouds. And that's a lot about, what you heard Sunil talk about today. >> So Ben, one of the things that I've heard consistently from customers over the past couple of days: Nutanix, humble. Nutanix, not entitled. You're the chief storyteller at Nutanix. How did you get that message out, without eliminating the core of that message? I mean, that's great to hear when I'm here at the show. But how do you expand that message out to the greater audience and future customers? >> That's a great question. It's something I think about every day and every night (chuckles). And for us, you know, we talk about our core values, about being hungry, humble, and honest. And I really think we live up to that. I think, how do we get out that persona of who we are as a company out to the broader marketplace? We have a lot of great early adoptive customers. And now as we move and as hyperconvergence and everything we're doing moves more into mainstream with candidly more conservative customers that may not be ready to try the brand new, then we do have to get that story out there more. So one big way we do it, just this week we've launched our new brand campaign around freedom: Freedom to build. Freedom to run the applications where you want to run them. Freedom to choose the right cloud platform that suit your needs. And so, a big thing we're doing this week is we're rolling out this campaign. And who better to unveil that to you first, than our best and brightest and most loyal customers here at .NEXT? >> Yeah, expand on that, that freedom campaign. It definitely, it struck me when I landed in the airport, here in New Orleans. And I believe it's: "Build, run, cloud, invent, and play." >> Ben: Yeah. >> Some of those themes, I've heard in the past. I remember the first .NEXT conference, it was, "Nutanix gave me my weekends back." And then, you know went a little bit, "Nutanix enabled me to go to "that security project that I couldn't do before." So, why the freedom brand? what have you heard from customers that resonated with that? >> We chose to go down this path, because we wanted to make sure we connected, everything that's wonderful about Nutanix. And, I'm going to brag about my marketing team. What I inherited here is an amazing marketing team. And, we've all recognized that what this team has built in terms of the voice of the company, in terms of the story that we created. A category how, maybe not quite so humbly, say we created with hyperconvergence. We want to connect the past to the present and into the future. And so, yes, give us your weekends back. That's something in common, we have heard from customers. Freedom to play is about building all for that. Freedom to build, is about building on the early success we've had. Now it's freedom to run, Freedom to cloud. As we've moved into multi-cloud and hybrid-cloud management automation and control. These are new elements to our portfolio. So these are new storylines that we need to open up. So, the way I like to think about it, this campaign is connecting everything that's been great about Nutanix to today and then also taking us into a new direction. >> So, Nuich talked earlier about the importance of being able to just go to that website, download Nutanix CE version, kick the tires; A promise Angelo Luciani, who runs the community program-- >> They did a wonderful job. >> Wonderful program, tie that together to their freedom program. How important is your community program? Which gave some big numbers today on stage. How important is that in helping customers discover Nutanix and move their careers in help digital transformation? >> Keith I'm glad you brought this up. Our next community, yeah, so the number I gave today was close to 70,000 active members. And we've drawn almost 20,000 to all of our .NEXT conferences over the past year. The online community to me is fundamental to how we continue to grow and deepen the connection and affinity we have with our customers. And what you going to see us do is really bet on driving more curriculum that's easy to consume, that helps our community members expand their knowledge base in the areas like multi-cloud, hybrid-cloud management. We introduced Nutanix Era today bringing new database services to the floor starting with copy data management. That community needs to be step number one for where our best customers go and learn more about the roadmap. Learn about best tips in trades to be able to embrace this new capabilities and then weed down into the fabric of they are doing with their data center builds. So community, I'm a big believer in it. We are lucky enough to have a vibrant and strong community already. So, now it's like how do we add more to that experience. This place, is kind of like coming to Mecca, it's like coming to-- (laughing) For us, right? It's coming to the event to have a touchstone. But then for the other 51 weeks to the year, that's what NEXT community is all about. >> Yeah, Ben, what type of roles are you trying to reach with your message? We've talked traditionally. We're talking kind of the infrastructure, getting out of the silos, going to the architect, But then we have a product like Beam which doesn't even. It started in the public clouds and working there. Who are you trying to reach with your freedom messaging and as you expand the portfolio to SaaS and beyond. >> You know it's interesting. Our business is diversifying and the audience and the personas that we have reach is definitely diversifying. So, obviously we have great affinity with servers, store admins, infrastructure managers. We are increasingly engaging up the IT stacks so to speak. Application owners and developers, is a significant audience for us. In fact yesterday for the first time in .NEXT, we had our inaugural Hackathon. And we had lot of folks that come from DevOps practices, within their organization, and this is a huge growth area within enterprises, and they came yesterday, they sat down, they had six hours, we fed them cookies, we gave them drink. All sorts of drink, and they came up with some really cool new apps where they developed to our APIs. And that's just one representation of a new audience and building that bridge between whose building an architect in the infrastructure And who's developing these new apps, which by the way need to get to market immediately. Which is why you need such radically simplified infrastructure to make that happen. App developers move up the stack. Before I came here to join you, I was with a room full of CIOs, and we talked a lot about some of the business pressures they're feeling. We talked a lot about governance and cloud. So there's a lot of new topics there, that under the freedom campaign, we talk about freedom to cloud. But then the meat underneath that is really around some of these topics we covered earlier today. >> So, still we've been at other infrastructure shows that have tried to do DevOps and Hackathons and they haven't been successful or they've been successful for a limited amount, you guys actually, quote unquote, sold out the space. What is the message that's resonating with that crowd that's bringing them to a DevOps Hackathon at what is essentially still, an infrastructure-focused audience? >> You know, the way I'll answer that question, one of my favorite early stories since I've joined Nutanix; major retail or customer. The infrastructure team without telling the app dev folks, moved some of their early apps onto Nutanix and didn't tell them. All the sudden, they started getting all these phone calls, and it's like, "what did you do?" "My apps are performing beautifully. "Oh, my Gosh it's so simple." Then they provided them with the portal that we offer through our software, So they could see how everything is moving. Are the SLAs there? Are these Apps humming? And they said, "what did you do?" "Well, we moved it onto Nutanix." And so then all of a sudden this new audience for us started saying we want the Nutanix. (Keith laughs) Which I think is a brilliant tagline, I love it. >> Keith: The Nutanix. We're trying to capture that spirit. So to me it's about. In the past there's been a lot of frustration, candidly, between these app developers who are under extreme pressure to get their new app to market. Customer facing, business facing, or what have you. And it's been so slow to get it done and so then often a crazy CMO of an organization, may work around IT and go throw something out in the public cloud. Well that could still be the model, but with the tools and HCI as a simplified infrastructure. Now there's a big answer, hey, we can move, we can sprint at your speed. And I think that's the key message. And so we're starting to attract that self-fulfilling prophecy to help make that possible. >> All right so, Ben, you are talking about your teams built a really impressive show here. Got the Hackathon as a new thing, one of the things I noticed here in the Expo Hall, there's now a whole area with some of the channel providers. There's always been channel providers here but they've got booths and speaking gigs. What other aspects for those people that didn't attend, in person here would you want to call out, give a little bit of color to what's happening? >> Yeah, Stu thanks for pointing out channel partners. This year over 1,200 representatives from Nutanix's channel are here. And Lou Attanasio, my esteemed colleague and global head of sales, and Rodney Foreman, our head of channels, they are both with me very focused on how do we go bigger and deeper with our channel community. If you think about it, we've moved to a software choice strategy. You can consume Nutanix on our own appliance, you can consume it on our OEM, great OEM partner Dell, but we also have ways that you consume our software with Cisco infrastructure, with HPE servers and the like. Channels is a wonderful way for us to be able to gage and find that new elasticity, candidly, in the market where they have customer relationships we may not have yet, but we have to invest in that, we have to invest in technical enablement, we have to invest in co-marketing with them, and I'd say we've done some on this front in the past. The time is now for us to really go deeper on that front. And that one's a big message we delivered during our partner exchange event just yesterday here in beautiful New Orleans. >> All right, so Ben do we have to wait to the closing keynote till we know where Nutanix .NEXT US is next year? >> Yes, you cannot get it out of me. The announcement will come tomorrow end of day. >> Camera's will lie for their all asking. >> No, I'm not going to betray any body language or anything, but we're looking forward to seeing you there next year. >> All right, well, Ben Gibson, pleasure to catch up with you again. For Keith Townsend, I'm Stu Miniman. Lots more coverage here from Nutanix .NEXT in New Orleans. You're watching theCUBE. (upbeat music)

>> Narrator: Live from San Juan, Puerto Rico, it's theCube, covering CoinAgenda, brought to you by SiliconANGLE. (salsa music) >> Hello everyone, welcome to our special CUBE exclusive coverage in Puerto Rico. I've been here on the island all week, talking to the most important people, entrepreneurs, citizens of Puerto Rico, the entrepreneur, the students, connecting with Blockchain, investors, thought leaders, and the pioneers. I'm John Furrier, the cohost of theCUBE, co-founder of SiliconANGLE Media, and we're here with Crystal Rose, who is the CEO and co-founder of Sensay, doing something really cutting edge, really relevant, and kind of ahead of its time, but I think it's time to get it out there and get that token program. Crystal Rose, thanks for joining me and spending time with me. >> Thank you for having me. >> So one of the things I think that you're doing, and I want you to explain this because it's nuanced, and a lot of the super geeks get it and alpha geeks will get it, but the mainstream people are used to dealing in their silos. I use Facebook, I use LinkedIn, I use Twitter, I use chat, I use Telegram, I use these apps. The world's kind of horizontally being disrupted because of the network affect that Blockchain and Crypto is now the underpinnings of, and there's ICOs out there and other things happening, but it's a disruption at the technology stack with software. You guys are doing something with Sensay in the SENSE token that is changing the equation of how people come together, how people grow and learn, whether it's a nonlinear path of some proficiency or connecting with folks or just learning, whatever it is, it's a discovery mechanism. Take a minute to explain what you guys are doing and why it's so important. >> Well we built Sensay to connect everyone together without any borders or intermediaries, and so really it's as simple as every phone has the capability to have a messenger. We have five billion phones that have SMS on them, and so we wanted to take the most basic messaging system, which is the most important thing that people do, and connect it to any other messenger, so Facebook Messenger, Telegram, Slack, anywhere where people are chatting, we wanted to create a system that is interoperable and can decentralize your contact list, essentially. >> Yeah, so this is important, so like most people when they go to social networks you got to find a friend, you get connected. In some cases I don't want to have to friend someone just to have a chat, I mean I may not want to friend them, or I might want to or it's a hassle, I don't know who to friend. Is that kind of where you guys come in? >> Yeah, that's one really great use case, because things like Facebook max you at five thousand friends, so if you friended everybody that you had a conversation with, if you needed to know something. Let's say that every Google search that you did was actually a conversation, you would cap the number of potential contacts. We have a circle of people around us that extends out with different tiers. But I think some of the most important people in our lives are actually strangers. So instead of building the social graph we wanted to build the stranger graph. Sensay cares more about what you know than who you know. Because if we can connect people together around similar interests and like-mindedness, we're connecting tribes, and that's really the innate human connection that we're all looking for. And it's also when you extend yourself outside of your social graph, you're most likely to educate yourself or to uplift yourself more. So the way to level up is to get somebody who's an eight or a 10 if you're a five or a two, and find someone outside of your current circle. >> And that also eliminates all this group think we've seen on some of these hate threads that have been on, whether it's Facebook or some IRC backchannel or Slack channel, you see the hate just comes in because everyone's just talking to themselves. This is the new way, right? Connecting out? Through the metadata of the chat. >> Exactly, we want people to seek out good connections, helpful connections, and so if you can both contribute what you know you get rewarded. And if you can ask people on the network you also get rewarded. So by asking something, you're receiving a reward. It's a two-way system. So it's not just the person who is helping, so we don't really encourage an economy of experts. We think that everyone is a sensei. A sensei literally means a person who's been there before. So we think of that as somebody who has had that life experience. And I think if we look at the internet, the internet democratized expertise. It gave us the ability for every single person to write what they were thinking, or contribute some kind of content in some way. But for 20 years the internet has been free. It's a really beautiful thing for consumption, and open source is the absolute right methodology for software. When it comes to your own content a reward makes sense, and so we wanted to create SENSE on top of the platform as a value exchange. It was a point system, so kind of like Reddit Karma. And we wanted to let people exchange it out for some value that they could transact in the world. >> So basically you're going to reward folks with a system that says, okay, first ante up some content, that's your SENSE token, and then based upon how you want to work with people in the network, there's a token transaction that could come out of it. Did I get that right? >> Exactly. So the person who contributes on the network gets rewarded for that data, and it can be anything that you've done in the past, too. So if you have a lot historical data on Facebook or on GitHub for instance. Let's say you're a developer and you have a bunch of repos out there that could be analyzed to see what kind of developer you are, or if you've contributed a lot to Reddit, all of that data is out there, and it's been something that defines you and your personality and your skills and who you are, so you can leverage that, and you can get a reward for it just by letting Sensay understand more about you, so the AI runs through it. You get more rewards, though, if you have real conversations. So it's almost like a bounty program on conversation. >> So we have the same mission. We love what you're doing. I'm really so glad you're doing it. I want to get to an example in Puerto Rico where you've reached out with strangers, I know you have. And get that, I want to get to that in a minute, but I want to continue on the Sensay for a second and the SENSE token. As you guys do this, what is the token going to be looking like to the user? Because you have a user who's contributing content and data, and then you have people who are going to transact with the token, it could be a bounty, it could be someone trying to connect. How is the token economics, just so I can get that out there, how does that work? >> Well right now in Sensay the transaction is peer to peer, so both users who are chatting have the ability to tip each other, essentially. They can give each other some coins within the chat. We have the concept that when you're having a conversation it's always a buyer and a seller. It's always a merchant and a consumer, and sometimes those roles flip, too. I'll be selling you something and eventually you're selling me something. But it's a natural way that we chat to transact. So that was the first way that the token could be used. We then realized that the powerful part of the platform is actually everything underlying the application. So the layer underneath really was the most powerful thing. And so SENSE network evolved as a way for developers who are creating apps or bots to be able to build on top of the network and leverage the access to the humans or to their data, and so now the token can be used to access the network. You get paid if you contribute data or users and vice versa, you can pay to access them. What that's doing is it's taking away the advertising model from being the only entity that's earning a profit on the data. So you, the user, when you're giving your data to Facebook, Facebook earns a lot of money on it, selling it over and over repeatedly to advertisers, and while it's technically yours in the terms you own it, you don't actually have any upside of that profit, and so what we're doing is saying, well why don't we just let a potential business talk to you directly on your consent and give you the money directly for that? So that two or five dollars for one connection would go straight to you. >> This is the new business model. I mean, this is something that, I mean first of all, don't get me started on my ad and tech rant because advertising creates a bad behavior. Okay? You're chasing a business model that's failing, attention and page views, so the content is not optimized the proper way. And you mentioned the Facebook example. Facebook's not optimizing their data for a user experience, they're optimizing for their monetization, which is counter to what users want to do. So I think you kind of are taking it in another direction, which we love 'cause that's what we do, we are open source content, but the role of the data is critical so I got to ask you the hard question. I'm a user, it's my data, how do the developers get access to it? Do they pay me coins or... You want developers because that's going to be a nice piece of the growth so what's the relationship between the developer, who's trying to add value, but also respecting the user's data? >> Exactly, so the developer pays the network and as a user you're a token holder, you own the network, essentially. So there is really no real middle layer since the token will take a small amount out for continuing to power the network, but a nominal amount. Right now the most expensive thing that happens is the gas that's on top of Ethereum because we're an ERC20 token. So we're looking to be polychain. We want to move onto other types of blockchains that have better, faster transactions with no fees and be able to pass that through as well. So we really want to just do a peer-to-peer connection. There's no interest in owning that connection or owning the repository of data. That's why the blockchain's important. We want the data to be distributed, we want it to be owned by the user, and we want it to be accessible by anyone that they want to give access to. So if it's a developer, they're building a bot maybe, or if it's a brand, they're using a developer on their behalf they have to pay the user for that data. So the developer's incentives are completely aligned with the peer-to-peer architecture that you have, users interests, and the technical underpinnings of the plumbing. Is that right? >> Exactly. >> Okay, good, so check. Now I got that. All right, now let's talk about my favorite topic, since we're on this kind of data topic. Who's influential? I mean, what does an influencer mean to you? Is it the most followers (mumbles) it's kind of a canned question, you can hear it coming. I'll just say it. I don't like the influencer model right now because it's all about followers. It's the wrong signal. 'Cause you can have a zillion followers and not be influential. And we know people are buying followers. So there's kind of been that gamification. What should influence really be like in this network? Because sometimes you can be really influential and then discover and go outside your comfort zone into a new area for some reason, whether it's a discovery or progression to some proficiency or connection, you're not an influencer, you're a newbie. So, context is very important. How do you guys look at, how do you look at influencers and how influence is measured? >> I think at the bare bones an influencer is someone who drives action. So it's a person who can elicit an action in another person. And if you can do that at scale, so one to many, then you have more power as an influencer. So that's sort of the traditional thinking. But I think we're missing something there, which is good action. So an influencer to me, a good influencer, is somebody who can encourage positive action. And so if it's one to one and you get one person to do one positive thing, versus one to a thousand and you get a thousand people to do something not so great, like buy a product that's crap because it was advertised to them for the purpose of that influencer making profit, that metric doesn't add up. So I think we live in a world of vanity metrics, where we have tons of numbers all over the place, we have hearts and likes and stars and followers and all of these things that keep adding up, but they have no real value. And so I think it's a really, like you said before, the behavior is being trained in the wrong way. We're encouraged to just get numbers rather than quality, and so what I think a really good influencer is is somebody who has a small group of people who will always take action. It can be any number of people. But let's say a group of followers who will take action based on that person's movements and will follow them in a positive direction. >> And guess what, its a network graph so you can actually measure it. That's interesting... >> Exactly, exactly. >> I can see where you're going with this. Okay, so I got to talk about your role here in Puerto Rico. You mentioned earlier about reaching out to strangers, the stranger graph, which is a way, people's outside of their comfort zones sometimes, reaching out to strangers. You came here in the analog sense, you're in person, but on the digital side as well, kind of blends together. Give an example where you reached out to strangers and how that's impacted your life and their life, because this is the heart of your system, if I can get that right. You're connecting people and creating value, I mean sometimes there might not be value, but you're creating connections, which have the potential for more value. What have you done here in Puerto Rico that's been a stranger outreach that turned into a wow moment. >> Our outreach has been so far an invitation. So we bought a space here that's turned into a community center. Even at the very beginning we had no power as most of the places around that have been sitting for a year or two or since the hurricane, and so we put a call out and said we'd like to get to know the community. We're doing something called Let There Be Light, which is turn the power on, and you know, we put it out to a public group and saw who would show up. So basically it's a community, central building, it's a historical building, so a lot of people know it. There's a lot of curiosity, so it was just a call, it was a call for help. It was really, I think the biggest thing people love is when you're asking them for help, and then you give gratitude in return for that help and you create a connection around it. So that's why we built Sensay the way that we did, and I think there's a lot of possibilities for how it could be used, but having that encouragement of the community to come and share, we've done that now this whole week, so this is restart week, and one of the other things that we've done is help all of the conferences come together, collaborate rather than compete, so go into the same week, and put all of these satellite groups around it. And then we blanketed a week around it so that we had one place for people to go and look for all of the events, and also for them to understand a movement. So we since then have done a dinner every single night, and it's been an open invitation. It's basically whoever comes in first, and we've had drinks every night as well, open. So it's really been an invitation. It's been an open invitation. >> Well congratulations. I really love what you're doing. You guys are doing great work down here. The event this week has been great. We've got great content. We have some amazing people and it's working, so congratulations on that. As you guys look forward, one of the things I've observed in my many years of history, is that there are a lot of waves, I've seen all the waves, this wave's the biggest. But what jumps out at me is the mission-driven aspect of it. So I mean I can geek out on what's the decentralize and the stacks and all the tech stuff happening, but what's most impressive is the mission oriented, the impact kind of thinking. This is now, society is now software driven. This is a new major thinking. Used to be philanthropy was a waterfall model. Yeah, donate, it either goes or doesn't go. Go to the next one, go to the next one. Now you have this integrated model where it's not just philanthropy, it's action, there's money behind it, there's coding, there's community. This is now a new era of societal entrepreneurship, societal missions. Let's talk about your vision on this mission and impact culture that's part of this ethos. >> I think impact is the important word there. So we think about, we think about bringing capital, like you said with normal philanthropy, you can bring capital and you can continuously pump capital into something, but if the model is wrong it's just going to drain, and it's going to go to inefficient systems, and in the end maybe do some help, but a very small percentage of the capacity of what it could do. So what we have the concept of is bringing funds here. We have a fund that was just launched called Restart Ventures, and the idea is instead of compounding interests, we want to make compounding impact, and so it's a social good focused fund, but at the same time all of the proceeds generated from the fund recycle back into other things that are making more impact. So we're measuring based on how much impact can be created with different projects. It could be a charity or it could be an entrepreneur. And if we're getting a multiple, most of that money is going back. So a very small percentage goes to the actual fund and to the fund managers, and the lion's share of the fund is going back into Puerto Rico. So I think if we look at how we can help in a way that is constantly regenerative, sustainable is good, regenerative is better. We want to at least elevate ourselves and get to the point of sustainability, but we're not improving at that point. We're still just fixing problems. We want regenerative. So if we can keep planting things that regrow themselves, if we can make it so that we're setting up the ecosystem to constantly mend itself, it's like a self-healing system of software, this is the right way to do it. So I think that's the new model. >> You built in some nurturing into the algorithm, I like that. 'Cause you're not going to do the classic venture capital carry, you're going to rotate in, but still pay some operators to run it, so they got to get paid. So I noticed in the announcement there was some money for managing directors to do it. So they get paid, and the rest goes into the compounding impact. >> Right. >> Okay, so I got to ask you what your view is these days on something that's really been important in open source software, which again, when I started it was a tier 2 citizen, at best, now it's running the world, tier 1. Open source ethoses are sprinkled throughout these new, awesome opportunities, but community made it happen. What is your current view on the role of the community, communities in general, to make this new compounding impact, whether it's software development, innovation, impact giving, regenerative growth. What's your view on community? >> If community operates with a mentality of giving or contribution over consumption we do a lot better. So when you have an open source network, if a community comes and they contribute to it more, that's something that regenerates. It keeps adding value. But if a community comes and they just keep consuming, then you have to continue to have more and more people giving. I think a really good example of this is Wikipedia. Wikipedia has hundreds of thousands of people who constantly contribute, and the only reward that they've ever gotten for that is a banner ad that says please donate because we don't do ads. So it's a broken model, because you want it to be free and you want it to continue to have the same ethos and you want it to have no advertising, yet the people who contribute most of the time also contribute most of the funding to keep it alive because they love it and care about it so much. So how could we change that model so that the community could give contributions while also receiving a way to make sure that they're able to keep doing that. And a reward system works, and maybe that's not the only solution, but we have to think about how we can keep creating more and more. >> Well I think transparency is one thing I've always loved. The thing that I always hear, especially with women in tech and these new important areas like underserved minorities, and also the bad behavior that goes on in other groups, is to shine the light on things. Having the data being open, changes everything. That is a huge thing. So community and open data. Your thoughts? I'm sure you agree? Open data and the importance of having the data exposed. >> One hundred percent. So our platform also has a layer of anonymity on the user by default, and part of the idea of being able to understand whether or not data is good. Because think of human data, we have to figure out quality. In the past there would be a validation system that is actually other humans telling you whether or not you're good and giving you some accreditation, some verification. This is our concept of experts on things. Now we would rather take consensus. So let's just crowdsource this validation and use a consensus mechanism that would see whether or not other humans think the data is good. If we're using a system like that, we have to have open data, it has to be transparent and it has to be able to be viewed in order to be voted on. So on our platform on just the first application on Sensay, we expose this consensus mechanism in a feature called Peek. So Peek basically lets you peek inside of conversations happening on the network. You can watch all the conversations that happen, the AI pulls out the good ones, and then you vote on them. >> It's kind of like when you walk into a nightclub, do I want to kind of hang out here? >> Yeah, you're kind of a voyeur but you get rewarded for doing it. It's a way for us to help classify, it's a way for us to help train the AI, and also it's a way for people to have passive ability to interact without having to have a conversation with an actual human. >> Well you're exposing the conversation to folks, but also you get signaling data. Who jumps in, who kind of walks away. I mean it's a gesture data, but it's a data point. >> Right, and it's completely private. So the beauty of the transparency is there's actually privacy baked in. And that's what I love about blockchain is it has all of the good things. >> Crystal, I got to ask you a final question. I know you're very busy, and thank you for taking the time to share your thoughts with me today here on theCUBE here in Puerto Rico. This week you've been super busy, you look great. I'm sure you've been up, burning the midnight oil, as they say. What is the, I won't say craziest thing because I've seen a lot of cool, crazy things going on here, it's been fun, what is some highlights for you? Conversations, meeting new people, can you just share a couple anecdotal highlights from restart week that have moved you or surprised you or just in general might be worth noting. >> I've been overall extremely surprised but the sheer number of people who showed up. I feel like a few months ago there was a small group of us sitting around wondering what it would be like if we could encourage our friends to come here and share the space. So just to see the thousands of people who have come here to support these several conferences has been amazing. My most surprising thing, though, is the amount of people that have told me that they bought a one-way ticket and have no intention of going home. So to make Puerto Rico your home I think is a really amazing first step, and I just did a panel earlier today with the person in government who had instituted Act 20 and 22, and that was the initial incentive-- >> Just take a minute to explain what that is for the folks that don't know what it is. >> Sure. So Act 20 and 22 are for the company and the individual respectively. They are a way for you to get a tax incentive for moving here as a resident or domiciling your company here. So you get 0% taxes. I think companies range up to 4% or something like that, and that incentive was created to bring more brilliant minds and entrepreneurs and different types of people with different vocations to the island. So basically, give them a tax incentive and encourage the stimulation of economy. So that has brought this wave of people in who have an idea that no taxes are great. At the same time they fall in love with the island. It's amazing because to me Puerto Rico is a combination of LA's weather, San Francisco's open-mindedness, and Barcelona's deep European history. It's just a really beautiful place. >> And it's US territory, so it's a short hop and a jump to the States if you need to, or Europe. >> Yeah exactly. And no customs and you have your driver's license to get here. Also it's a US dollar. And I say that because most people in America mainland don't realize that Puerto Rico is an American territory, and so they sort of think they're going to a foreign country because it's treated that way by our government. But what I've been really shocked about, though, is the sheer amount of innovation already here. The forward thinking ways of people and the embracing of things like open source and blockchain technology, because their minds are already in a mode of community, a mode of sharing, a mode of giving. >> We interviewed Michael Angelo from Edublock.ido, Edublock, they're connecting all the universities with blockchain. We also interviewed Damaris Rivera, with Puerto Rico Advantage. They'll move you down here. You can press a button, it's instant move. So folks in Silicon Valley who are watching who know us and around the world know theCUBE, there's a group of like-minded people here that have tech chops, there's capital flowing. There's capital people I know have moved here, setting up shop, as well as the Caymans and everywhere else, but it's nice. So it's kind of like LA. >> There is a lot of capital. I have just witnessed a couple hundred million dollars of funds that were established in the last couple of months. And this is around all different types of technology sectors. You don't have to be a blockchain company. You can be innovating in any way possible. One of my favorite projects is a machine that turns plastic bottles into diesel fuel. So one of the problems here is that the generators on the island, when we were here last time we met a guy that was working at a bar in a restaurant, and he was like, "Hey I saw you guys in New York Times "and I think you're like the Crypto people." And he had a conversation, and he said, "I was wondering if you could help my grandmother "who is stuck with no power, and it's been months, "and she's in her 90s, and she needs a generator to run "a machine that keeps her life supported." and so a couple of people went out to bring more fuel, bring a generator to donate. They started understanding that there are so many areas that still need this level of help, that there's a lot that we can do. So when I see projects like that, that's something I want to back. >> Yeah, it's entrepreneurial action taking impact. Crystal, thanks so much for coming out. Crystal Rose, CEO, co-founder of Sensay, real innovative company, pioneer here in the Puerto Rico movement. It's a movement, a lot of tech, entrepreneurs, capital, investors, and the pioneers in the blockchain, decentralized internet are all here. This is like the Silicon Valley of Crypto, right? >> I think they're calling it Crypto Island. >> Crypto Island, yes. It sounds like a TV show. We should be on it. It's not lost, it's Crypto Island. >> Exactly. >> Thanks so much for spending the time on theCUBE. >> Thanks John. >> John: I appreciate it. >> I appreciate it so much. Thanks for making sense of me. >> I'm John Furrier here on theCUBE here in Puerto Rico. Our coverage continues after this short break.

(lively music) >> Narrator: Live from San Juan, Puerto Rico. It's The Cube! Covering Blockchain Unbound. Brought to you by Blockchain Industries. (lively island music) >> Hey, hello everyone. I'm John Furrier. We are reporting on the ground here in Puerto Rico for Blockchain Unbound, a global conference of leaders from around the world who are coming into Puerto Rico with the local entrepreneurs, with the local ecosystem, to talk about the future of the digital nations in the world, digital transformation, also cryptocurrency, Blockchain...all the people are here, The Cube is here, as part of our 2018 kickoff of all the crypto Blockchain shows. My next guest here on The Cube is Gustavo Diaz Skoff, who is the founder and president of the Young Entrepreneurs in Puerto Rico's society, also heavily involved in the ecosystem. Thanks for speaking with me. >> Thank you. >> John: So, what's going on here in Puerto Rico? Also, we just talked with Michael Angelo, who is the co-founder of Edublock, but we're talking about a whole transformation going on in Puerto Rico. What's the young culture like? What's the old guard say? I mean, are people... What's going on? What's the mindset? What's going on in Puerto Rico? We know the hurricane that hit, but, again, looking past that, what's the cultural vibe right now in Puerto Rico? I think the cultural vibe right now is that there's a little bit of a hesitation, but, at the same time, there's a lot of excitement. Events that, like, for example, the one that were hosted yesterday, Law 23, that brought the local and the vicinity communities together to actually clear up and like lowered those stations and actually bonded and brought more energy into the whole push. I think that is the overarching vibe here in the island, it's just like awesome. There's...something's happening. We don't know quite yet what it is, but there is a historical narrative of the island, and there is definitely a very bullish view of the island. So what's really going on here is that the people are excited, but you got the whole world descending upon Puerto Rico. We grabbed a lot last night with the party. >> Yeah. >> We put out a nice sizzle reel this morning, but the vibe was awesome. People were dancing, a lot of people smiling. >> You were there? >> We were there! We just put some up on our telegram channel. >> I was the organizer of it. >> Congratulations, really awesome. >> Thank you. >> John: Outside, nice weather, things were great, but it really is about the cross-pollination. It's about the culture of Puerto Rico, maintaining the culture in Puerto Rico, seems to be the top story that we hear from folks here. Yes, we like to bring in the industry, but don't tell us what to do. We're Puerto Rico (laughing) you know, don't stomp on our land! I'm not being...but I mean there's kind of a vibe like 'look it, Puerto Rico's proud.' But that's got to translate into execution... what's the young guns doing? >> So, this is the reality in terms of what the young guns are doing, and, sadly, sometimes they're a very sad story, and the reality is like when you look at the world economic forums competitive reports, we have the sixth-largest conglomeration of trained scientists and engineers in the world. Holy shit! That's insane. But, at the same time, we have 90 percent of them being unemployed or underemployed, because we don't have like technology companies that are actually requesting and demanding that type of knowledge. And so, that's where we're actually failing in terms of execution, because we're going to end up working for a bank or for a government agency, and so there's not that many opportunities to actually go and build that. And now, just looking at the whole shift and how the world has basically come into our shores, it's like, wow. There is an opportunity to actually use this human capital and work together and just start developing and challenging ourselves locally to keep building, either as an entrepreneur or as an intrapreneur. >> John: You know, Brock Pierce, I thought, said it great today on the keynote he gave here at the Blockchain Unbound Conference, "It's a global 'we' going on; it's a 'we,' not a 'me.'" >> And I think, you know, someone who's seen many waves in my life, this is the biggest wave ever, because it's creating essentially a flat world, it's global, so it's not like the old guard, gatekeeper, migration paths up, so the migration for up the ladder, if you will, in society for a young individual was kind of structured in the past. >> Now the ladder has fallen. It's flat. (chuckling) >> Peter Thiel, who at one point was looking at paying people not to go to school, literally the world is your oyster with this new technology, because now it's a global fabric. There's no central authority. You have access to open source software. It's fully connected. So now's the time to make it translate. What do you hope for for the community in Puerto Rico to make that connection in the actual property flow, the relationships. What are you guys looking for to have happen? >> Yeah. So the answer is going to be a little bit historical, and that goes back to the question I asked off of the camera, was like, "Do you know where the first special economic zone was built, the first SEZ was built?" It was here in Puerto Rico. And for those that don't know, that was the economic model that we used as a human race in 130 nations in 4300 zones around the world to transition our economy from agriculture to manufacturing. And I believe that, right now, we're building that fabric. We're starting to reconstruct the second generation of an SEZ, and, whatever is happening here, to either build better cities, where people are able to access their food, are able to access capital, are able to access opportunities in a way that it's de-risked. I believe it's being built right now. And I think that is where we're heading. Because we already did it 71 years ago, and this is just the perfect concoction to re-do it. >> John: You know, I talk with a lot of leaders. One of them, in particular, Teresa Carlson, runs Amazon Web Services' global public sector, which is government, schools, and whatever. We're seeing for the first time, and this is what, I think, Amazon sees, and they're the leader in cloud computing, which is phenomenal, which, again, levels a lot of gatekeepers, if you think about it that way. She talks about digital nations, that we are now at the front end of the beginning of a wave where sovereignty, at a national level, with this no-border, kind of digital culture, is a huge opportunity. >> Yeah. >> How are you guys recruiting? How are you spreading the love? How are you spreading the word? Because it's not just developers, it's about the communities. >> Well, first of all, I think it's important to actually say that it's better, I think, Puerto Rico being a free associated states of the United States of America, it's like the best place to actually test this philosophy and push for that. I think that the way that we're actually starting to recruit that is by spreading out into the world and saying, "Hey, this is happening, come back." As I was mentioning, in May, we're going to Washington DC to present over 23 organizations that are working on basically all that's happening, and be able to bring more consciousness, bring more tools into the island and be able to build, essentially, the future of it. >> Tell me about the things that you're working on right now. You mentioned before we came on camera some of the things you were doing in Washington DC. What are some of the things you're hoping to accomplish over the next year in your role, inside the community here in Puerto Rico? >> I hope to, with Edublock, be able to help more students get into this space, be able to leverage better connections and relationships with these corporations that are in need now of Blockchain developers, and be able to have that circle of flow of the people here in the island and the people internationally that are looking for talent. That's my main goal. And if I could put a number of it, it would be amazing to have 500 students recruited, or with an internship, within corporations by the next 365 days. >> As you guys at Edublock are creating a separate event forum for what's happening at Blockchain Unbound to the education community, because it's pretty pricey to come to this conference, it's an investor's conference, it's an industry conference. You're seeing a world coming together, a lot of people coming in from the crypto blockchain community. What are people talking about in Puerto Rico about this migration and this intersection of the two worlds? Is it good, bad, confusing? Are people trying to figure it out? What's the vibe? >> They need more information. They need more data. (laughing) We only have a few articles, and that's it. >> John: Yeah. >> My father, for example... >> John: Articles from centralized news organizations, not trusted news organizations. >> Yes, yes. >> What does the decentralized data say? >> The decentralized data say is that this is a good technology, and we need to be careful, like we need to understand it correctly. And we need to raise awareness around the community, because it can either go really, really, really, really, really well, or we can repeat the past couple of years in the island. >> It could fail miserably or be a home run. >> Great stuff. We certainly want to expose the information and share what the stories of the key things that we're...you're doing a great job. You guys are doing great work. We support you from Silicon Valley with The Cube. >> Our job is open, free content, which we're doing here in Puerto Rico. We're with Gustavo Diaz Skoff, who is the founder and president of the Young Entrepreneur's Club here, Entrepreneurial Society, in Puerto Rico. We're on the ground, getting all the top stories and sharing the data with you. I'm John Furrier. Thanks for watching. (digital music)